Sample records for causal variants underlying
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Identifying Causal Variants at Loci with Multiple Signals of Association
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-01-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20–50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515
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Identifying causal variants at loci with multiple signals of association.
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-10-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. Copyright © 2014 by the Genetics Society of America.
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Temporal Expression Profiling Identifies Pathways Mediating Effect of Causal Variant on Phenotype
Gupta, Saumya; Radhakrishnan, Aparna; Raharja-Liu, Pandu; Lin, Gen; Steinmetz, Lars M.; Gagneur, Julien; Sinha, Himanshu
2015-01-01
Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants’ effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage of analyzing allele-specific transcriptional dynamics of mediating genes. Applications in higher eukaryotes can be valuable for inferring causal molecular pathways underlying complex dynamic processes, such as development, physiology and disease progression. PMID:26039065
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Meng, Xiang-He; Shen, Hui; Chen, Xiang-Ding; Xiao, Hong-Mei; Deng, Hong-Wen
2018-03-01
Genome-wide association studies (GWAS) have successfully identified numerous genetic variants associated with diverse complex phenotypes and diseases, and provided tremendous opportunities for further analyses using summary association statistics. Recently, Pickrell et al. developed a robust method for causal inference using independent putative causal SNPs. However, this method may fail to infer the causal relationship between two phenotypes when only a limited number of independent putative causal SNPs identified. Here, we extended Pickrell's method to make it more applicable for the general situations. We extended the causal inference method by replacing the putative causal SNPs with the lead SNPs (the set of the most significant SNPs in each independent locus) and tested the performance of our extended method using both simulation and empirical data. Simulations suggested that when the same number of genetic variants is used, our extended method had similar distribution of test statistic under the null model as well as comparable power under the causal model compared with the original method by Pickrell et al. But in practice, our extended method would generally be more powerful because the number of independent lead SNPs was often larger than the number of independent putative causal SNPs. And including more SNPs, on the other hand, would not cause more false positives. By applying our extended method to summary statistics from GWAS for blood metabolites and femoral neck bone mineral density (FN-BMD), we successfully identified ten blood metabolites that may causally influence FN-BMD. We extended a causal inference method for inferring putative causal relationship between two phenotypes using summary statistics from GWAS, and identified a number of potential causal metabolites for FN-BMD, which may provide novel insights into the pathophysiological mechanisms underlying osteoporosis.
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Huang, Dandan; Yi, Xianfu; Zhang, Shijie; Zheng, Zhanye; Wang, Panwen; Xuan, Chenghao; Sham, Pak Chung; Wang, Junwen; Li, Mulin Jun
2018-05-16
Genome-wide association studies have generated over thousands of susceptibility loci for many human complex traits, and yet for most of these associations the true causal variants remain unknown. Tissue/cell type-specific prediction and prioritization of non-coding regulatory variants will facilitate the identification of causal variants and underlying pathogenic mechanisms for particular complex diseases and traits. By leveraging recent large-scale functional genomics/epigenomics data, we develop an intuitive web server, GWAS4D (http://mulinlab.tmu.edu.cn/gwas4d or http://mulinlab.org/gwas4d), that systematically evaluates GWAS signals and identifies context-specific regulatory variants. The updated web server includes six major features: (i) updates the regulatory variant prioritization method with our new algorithm; (ii) incorporates 127 tissue/cell type-specific epigenomes data; (iii) integrates motifs of 1480 transcriptional regulators from 13 public resources; (iv) uniformly processes Hi-C data and generates significant interactions at 5 kb resolution across 60 tissues/cell types; (v) adds comprehensive non-coding variant functional annotations; (vi) equips a highly interactive visualization function for SNP-target interaction. Using a GWAS fine-mapped set for 161 coronary artery disease risk loci, we demonstrate that GWAS4D is able to efficiently prioritize disease-causal regulatory variants.
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Establishing the role of rare coding variants in known Parkinson's disease risk loci.
Jansen, Iris E; Gibbs, J Raphael; Nalls, Mike A; Price, T Ryan; Lubbe, Steven; van Rooij, Jeroen; Uitterlinden, André G; Kraaij, Robert; Williams, Nigel M; Brice, Alexis; Hardy, John; Wood, Nicholas W; Morris, Huw R; Gasser, Thomas; Singleton, Andrew B; Heutink, Peter; Sharma, Manu
2017-11-01
Many common genetic factors have been identified to contribute to Parkinson's disease (PD) susceptibility, improving our understanding of the related underlying biological mechanisms. The involvement of rarer variants in these loci has been poorly studied. Using International Parkinson's Disease Genomics Consortium data sets, we performed a comprehensive study to determine the impact of rare variants in 23 previously published genome-wide association studies (GWAS) loci in PD. We applied Prix fixe to select the putative causal genes underneath the GWAS peaks, which was based on underlying functional similarities. The Sequence Kernel Association Test was used to analyze the joint effect of rare, common, or both types of variants on PD susceptibility. All genes were tested simultaneously as a gene set and each gene individually. We observed a moderate association of common variants, confirming the involvement of the known PD risk loci within our genetic data sets. Focusing on rare variants, we identified additional association signals for LRRK2, STBD1, and SPATA19. Our study suggests an involvement of rare variants within several putatively causal genes underneath previously identified PD GWAS peaks. Copyright © 2017 Elsevier Inc. All rights reserved.
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Overexpression of the Cytokine BAFF and Autoimmunity Risk.
Steri, Maristella; Orrù, Valeria; Idda, M Laura; Pitzalis, Maristella; Pala, Mauro; Zara, Ilenia; Sidore, Carlo; Faà, Valeria; Floris, Matteo; Deiana, Manila; Asunis, Isadora; Porcu, Eleonora; Mulas, Antonella; Piras, Maria G; Lobina, Monia; Lai, Sandra; Marongiu, Mara; Serra, Valentina; Marongiu, Michele; Sole, Gabriella; Busonero, Fabio; Maschio, Andrea; Cusano, Roberto; Cuccuru, Gianmauro; Deidda, Francesca; Poddie, Fausto; Farina, Gabriele; Dei, Mariano; Virdis, Francesca; Olla, Stefania; Satta, Maria A; Pani, Mario; Delitala, Alessandro; Cocco, Eleonora; Frau, Jessica; Coghe, Giancarlo; Lorefice, Lorena; Fenu, Giuseppe; Ferrigno, Paola; Ban, Maria; Barizzone, Nadia; Leone, Maurizio; Guerini, Franca R; Piga, Matteo; Firinu, Davide; Kockum, Ingrid; Lima Bomfim, Izaura; Olsson, Tomas; Alfredsson, Lars; Suarez, Ana; Carreira, Patricia E; Castillo-Palma, Maria J; Marcus, Joseph H; Congia, Mauro; Angius, Andrea; Melis, Maurizio; Gonzalez, Antonio; Alarcón Riquelme, Marta E; da Silva, Berta M; Marchini, Maurizio; Danieli, Maria G; Del Giacco, Stefano; Mathieu, Alessandro; Pani, Antonello; Montgomery, Stephen B; Rosati, Giulio; Hillert, Jan; Sawcer, Stephen; D'Alfonso, Sandra; Todd, John A; Novembre, John; Abecasis, Gonçalo R; Whalen, Michael B; Marrosu, Maria G; Meloni, Alessandra; Sanna, Serena; Gorospe, Myriam; Schlessinger, David; Fiorillo, Edoardo; Zoledziewska, Magdalena; Cucca, Francesco
2017-04-27
Genomewide association studies of autoimmune diseases have mapped hundreds of susceptibility regions in the genome. However, only for a few association signals has the causal gene been identified, and for even fewer have the causal variant and underlying mechanism been defined. Coincident associations of DNA variants affecting both the risk of autoimmune disease and quantitative immune variables provide an informative route to explore disease mechanisms and drug-targetable pathways. Using case-control samples from Sardinia, Italy, we performed a genomewide association study in multiple sclerosis followed by TNFSF13B locus-specific association testing in systemic lupus erythematosus (SLE). Extensive phenotyping of quantitative immune variables, sequence-based fine mapping, cross-population and cross-phenotype analyses, and gene-expression studies were used to identify the causal variant and elucidate its mechanism of action. Signatures of positive selection were also investigated. A variant in TNFSF13B, encoding the cytokine and drug target B-cell activating factor (BAFF), was associated with multiple sclerosis as well as SLE. The disease-risk allele was also associated with up-regulated humoral immunity through increased levels of soluble BAFF, B lymphocytes, and immunoglobulins. The causal variant was identified: an insertion-deletion variant, GCTGT→A (in which A is the risk allele), yielded a shorter transcript that escaped microRNA inhibition and increased production of soluble BAFF, which in turn up-regulated humoral immunity. Population genetic signatures indicated that this autoimmunity variant has been evolutionarily advantageous, most likely by augmenting resistance to malaria. A TNFSF13B variant was associated with multiple sclerosis and SLE, and its effects were clarified at the population, cellular, and molecular levels. (Funded by the Italian Foundation for Multiple Sclerosis and others.).
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Kant on causal laws and powers.
Henschen, Tobias
2014-12-01
The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.
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Assessing the Power of Exome Chips.
Page, Christian Magnus; Baranzini, Sergio E; Mevik, Bjørn-Helge; Bos, Steffan Daniel; Harbo, Hanne F; Andreassen, Bettina Kulle
2015-01-01
Genotyping chips for rare and low-frequent variants have recently gained popularity with the introduction of exome chips, but the utility of these chips remains unclear. These chips were designed using exome sequencing data from mainly American-European individuals, enriched for a narrow set of common diseases. In addition, it is well-known that the statistical power of detecting associations with rare and low-frequent variants is much lower compared to studies exclusively involving common variants. We developed a simulation program adaptable to any exome chip design to empirically evaluate the power of the exome chips. We implemented the main properties of the Illumina HumanExome BeadChip array. The simulated data sets were used to assess the power of exome chip based studies for varying effect sizes and causal variant scenarios. We applied two widely-used statistical approaches for rare and low-frequency variants, which collapse the variants into genetic regions or genes. Under optimal conditions, we found that a sample size between 20,000 to 30,000 individuals were needed in order to detect modest effect sizes (0.5% < PAR > 1%) with 80% power. For small effect sizes (PAR <0.5%), 60,000-100,000 individuals were needed in the presence of non-causal variants. In conclusion, we found that at least tens of thousands of individuals are necessary to detect modest effects under optimal conditions. In addition, when using rare variant chips on cohorts or diseases they were not originally designed for, the identification of associated variants or genes will be even more challenging.
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Guidelines for investigating causality of sequence variants in human disease
MacArthur, D. G.; Manolio, T. A.; Dimmock, D. P.; Rehm, H. L.; Shendure, J.; Abecasis, G. R.; Adams, D. R.; Altman, R. B.; Antonarakis, S. E.; Ashley, E. A.; Barrett, J. C.; Biesecker, L. G.; Conrad, D. F.; Cooper, G. M.; Cox, N. J.; Daly, M. J.; Gerstein, M. B.; Goldstein, D. B.; Hirschhorn, J. N.; Leal, S. M.; Pennacchio, L. A.; Stamatoyannopoulos, J. A.; Sunyaev, S. R.; Valle, D.; Voight, B. F.; Winckler, W.; Gunter, C.
2014-01-01
The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development. PMID:24759409
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Guidelines for investigating causality of sequence variants in human disease.
MacArthur, D G; Manolio, T A; Dimmock, D P; Rehm, H L; Shendure, J; Abecasis, G R; Adams, D R; Altman, R B; Antonarakis, S E; Ashley, E A; Barrett, J C; Biesecker, L G; Conrad, D F; Cooper, G M; Cox, N J; Daly, M J; Gerstein, M B; Goldstein, D B; Hirschhorn, J N; Leal, S M; Pennacchio, L A; Stamatoyannopoulos, J A; Sunyaev, S R; Valle, D; Voight, B F; Winckler, W; Gunter, C
2014-04-24
The discovery of rare genetic variants is accelerating, and clear guidelines for distinguishing disease-causing sequence variants from the many potentially functional variants present in any human genome are urgently needed. Without rigorous standards we risk an acceleration of false-positive reports of causality, which would impede the translation of genomic research findings into the clinical diagnostic setting and hinder biological understanding of disease. Here we discuss the key challenges of assessing sequence variants in human disease, integrating both gene-level and variant-level support for causality. We propose guidelines for summarizing confidence in variant pathogenicity and highlight several areas that require further resource development.
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Identification of causal genes for complex traits.
Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar
2015-06-15
Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider 'causal variants' as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Software is freely available for download at genetics.cs.ucla.edu/caviar. © The Author 2015. Published by Oxford University Press.
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Use of allele scores as instrumental variables for Mendelian randomization
Burgess, Stephen; Thompson, Simon G
2013-01-01
Background An allele score is a single variable summarizing multiple genetic variants associated with a risk factor. It is calculated as the total number of risk factor-increasing alleles for an individual (unweighted score), or the sum of weights for each allele corresponding to estimated genetic effect sizes (weighted score). An allele score can be used in a Mendelian randomization analysis to estimate the causal effect of the risk factor on an outcome. Methods Data were simulated to investigate the use of allele scores in Mendelian randomization where conventional instrumental variable techniques using multiple genetic variants demonstrate ‘weak instrument’ bias. The robustness of estimates using the allele score to misspecification (for example non-linearity, effect modification) and to violations of the instrumental variable assumptions was assessed. Results Causal estimates using a correctly specified allele score were unbiased with appropriate coverage levels. The estimates were generally robust to misspecification of the allele score, but not to instrumental variable violations, even if the majority of variants in the allele score were valid instruments. Using a weighted rather than an unweighted allele score increased power, but the increase was small when genetic variants had similar effect sizes. Naive use of the data under analysis to choose which variants to include in an allele score, or for deriving weights, resulted in substantial biases. Conclusions Allele scores enable valid causal estimates with large numbers of genetic variants. The stringency of criteria for genetic variants in Mendelian randomization should be maintained for all variants in an allele score. PMID:24062299
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Identification of causal genes for complex traits
Hormozdiari, Farhad; Kichaev, Gleb; Yang, Wen-Yun; Pasaniuc, Bogdan; Eskin, Eleazar
2015-01-01
Motivation: Although genome-wide association studies (GWAS) have identified thousands of variants associated with common diseases and complex traits, only a handful of these variants are validated to be causal. We consider ‘causal variants’ as variants which are responsible for the association signal at a locus. As opposed to association studies that benefit from linkage disequilibrium (LD), the main challenge in identifying causal variants at associated loci lies in distinguishing among the many closely correlated variants due to LD. This is particularly important for model organisms such as inbred mice, where LD extends much further than in human populations, resulting in large stretches of the genome with significantly associated variants. Furthermore, these model organisms are highly structured and require correction for population structure to remove potential spurious associations. Results: In this work, we propose CAVIAR-Gene (CAusal Variants Identification in Associated Regions), a novel method that is able to operate across large LD regions of the genome while also correcting for population structure. A key feature of our approach is that it provides as output a minimally sized set of genes that captures the genes which harbor causal variants with probability ρ. Through extensive simulations, we demonstrate that our method not only speeds up computation, but also have an average of 10% higher recall rate compared with the existing approaches. We validate our method using a real mouse high-density lipoprotein data (HDL) and show that CAVIAR-Gene is able to identify Apoa2 (a gene known to harbor causal variants for HDL), while reducing the number of genes that need to be tested for functionality by a factor of 2. Availability and implementation: Software is freely available for download at genetics.cs.ucla.edu/caviar. Contact: eeskin@cs.ucla.edu PMID:26072484
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An Evolutionary Perspective on Epistasis and the Missing Heritability
Hemani, Gibran; Knott, Sara; Haley, Chris
2013-01-01
The relative importance between additive and non-additive genetic variance has been widely argued in quantitative genetics. By approaching this question from an evolutionary perspective we show that, while additive variance can be maintained under selection at a low level for some patterns of epistasis, the majority of the genetic variance that will persist is actually non-additive. We propose that one reason that the problem of the “missing heritability” arises is because the additive genetic variation that is estimated to be contributing to the variance of a trait will most likely be an artefact of the non-additive variance that can be maintained over evolutionary time. In addition, it can be shown that even a small reduction in linkage disequilibrium between causal variants and observed SNPs rapidly erodes estimates of epistatic variance, leading to an inflation in the perceived importance of additive effects. We demonstrate that the perception of independent additive effects comprising the majority of the genetic architecture of complex traits is biased upwards and that the search for causal variants in complex traits under selection is potentially underpowered by parameterising for additive effects alone. Given dense SNP panels the detection of causal variants through genome-wide association studies may be improved by searching for epistatic effects explicitly. PMID:23509438
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Whole exome sequencing for familial bicuspid aortic valve identifies putative variants.
Martin, Lisa J; Pilipenko, Valentina; Kaufman, Kenneth M; Cripe, Linda; Kottyan, Leah C; Keddache, Mehdi; Dexheimer, Phillip; Weirauch, Matthew T; Benson, D Woodrow
2014-10-01
Bicuspid aortic valve (BAV) is the most common congenital cardiovascular malformation. Although highly heritable, few causal variants have been identified. The purpose of this study was to identify genetic variants underlying BAV by whole exome sequencing a multiplex BAV kindred. Whole exome sequencing was performed on 17 individuals from a single family (BAV=3; other cardiovascular malformation, 3). Postvariant calling error control metrics were established after examining the relationship between Mendelian inheritance error rate and coverage, quality score, and call rate. To determine the most effective approach to identifying susceptibility variants from among 54 674 variants passing error control metrics, we evaluated 3 variant selection strategies frequently used in whole exome sequencing studies plus extended family linkage. No putative rare, high-effect variants were identified in all affected but no unaffected individuals. Eight high-effect variants were identified by ≥2 of the commonly used selection strategies; however, these were either common in the general population (>10%) or present in the majority of the unaffected family members. However, using extended family linkage, 3 synonymous variants were identified; all 3 variants were identified by at least one other strategy. These results suggest that traditional whole exome sequencing approaches, which assume causal variants alter coding sense, may be insufficient for BAV and other complex traits. Identification of disease-associated variants is facilitated by the use of segregation within families. © 2014 American Heart Association, Inc.
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Interpreting findings from Mendelian randomization using the MR-Egger method.
Burgess, Stephen; Thompson, Simon G
2017-05-01
Mendelian randomization-Egger (MR-Egger) is an analysis method for Mendelian randomization using summarized genetic data. MR-Egger consists of three parts: (1) a test for directional pleiotropy, (2) a test for a causal effect, and (3) an estimate of the causal effect. While conventional analysis methods for Mendelian randomization assume that all genetic variants satisfy the instrumental variable assumptions, the MR-Egger method is able to assess whether genetic variants have pleiotropic effects on the outcome that differ on average from zero (directional pleiotropy), as well as to provide a consistent estimate of the causal effect, under a weaker assumption-the InSIDE (INstrument Strength Independent of Direct Effect) assumption. In this paper, we provide a critical assessment of the MR-Egger method with regard to its implementation and interpretation. While the MR-Egger method is a worthwhile sensitivity analysis for detecting violations of the instrumental variable assumptions, there are several reasons why causal estimates from the MR-Egger method may be biased and have inflated Type 1 error rates in practice, including violations of the InSIDE assumption and the influence of outlying variants. The issues raised in this paper have potentially serious consequences for causal inferences from the MR-Egger approach. We give examples of scenarios in which the estimates from conventional Mendelian randomization methods and MR-Egger differ, and discuss how to interpret findings in such cases.
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Hitomi, Yuki; Tokunaga, Katsushi
2017-01-01
Human genome variation may cause differences in traits and disease risks. Disease-causal/susceptible genes and variants for both common and rare diseases can be detected by comprehensive whole-genome analyses, such as whole-genome sequencing (WGS), using next-generation sequencing (NGS) technology and genome-wide association studies (GWAS). Here, in addition to the application of an NGS as a whole-genome analysis method, we summarize approaches for the identification of functional disease-causal/susceptible variants from abundant genetic variants in the human genome and methods for evaluating their functional effects in human diseases, using an NGS and in silico and in vitro functional analyses. We also discuss the clinical applications of the functional disease causal/susceptible variants to personalized medicine.
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CRISPR-directed mitotic recombination enables genetic mapping without crosses.
Sadhu, Meru J; Bloom, Joshua S; Day, Laura; Kruglyak, Leonid
2016-05-27
Linkage and association studies have mapped thousands of genomic regions that contribute to phenotypic variation, but narrowing these regions to the underlying causal genes and variants has proven much more challenging. Resolution of genetic mapping is limited by the recombination rate. We developed a method that uses CRISPR (clustered, regularly interspaced, short palindromic repeats) to build mapping panels with targeted recombination events. We tested the method by generating a panel with recombination events spaced along a yeast chromosome arm, mapping trait variation, and then targeting a high density of recombination events to the region of interest. Using this approach, we fine-mapped manganese sensitivity to a single polymorphism in the transporter Pmr1. Targeting recombination events to regions of interest allows us to rapidly and systematically identify causal variants underlying trait differences. Copyright © 2016, American Association for the Advancement of Science.
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Mendelian randomization analyses in cardiometabolic disease: challenges in evaluating causality
Holmes, Michael V; Ala-Korpela, Mika; Davey Smith, George
2017-01-01
Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings. PMID:28569269
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Linkage disequilibrium among commonly genotyped SNP and variants detected from bull sequence
USDA-ARS?s Scientific Manuscript database
Genomic prediction utilizing causal variants could increase selection accuracy above that achieved with SNP genotyped by commercial assays. A number of variants detected from sequencing influential sires are likely to be causal, but noticable improvements in prediction accuracy using imputed sequen...
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Smith, Andrew J P; Deloukas, Panos; Munroe, Patricia B
2018-04-13
Over the last decade, genome-wide association studies (GWAS) have propelled the discovery of thousands of loci associated with complex diseases. The focus is now turning towards the function of these association signals, determining the causal variant(s) amongst those in strong linkage disequilibrium, and identifying their underlying mechanisms, such as long-range gene regulation. Genome-editing techniques utilising zinc-finger nucleases (ZFN), transcription activator-like effector nucleases (TALENs) and clustered regularly-interspaced short palindromic repeats with Cas9 nuclease (CRISPR-Cas9), are becoming the tools of choice to establish functionality for these variants, due to the ability to assess effects of single variants in vivo. This review will discuss examples of how these technologies have begun to aid functional analysis of GWAS loci for complex traits such as cardiovascular disease, type 2 diabetes, cancer, obesity and autoimmune disease. We focus on analysis of variants occurring within non-coding genomic regions, as these comprise the majority of GWAS variants, providing the greatest challenges to determining functionality, and compare editing strategies that provide different levels of evidence for variant functionality. The review describes molecular insights into some of these potentially causal variants, and how these may relate to the pathology of the trait, and look towards future directions for these technologies in post-GWAS analysis, such as base-editing.
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Zhu, Qianqian; Shepherd, Lori; Lunetta, Kathryn L.; Yao, Song; Liu, Qian; Hu, Qiang; Haddad, Stephen A.; Sucheston-Campbell, Lara; Bensen, Jeannette T.; Bandera, Elisa V.; Rosenberg, Lynn; Liu, Song; Haiman, Christopher A.; Olshan, Andrew F.; Palmer, Julie R.; Ambrosone, Christine B.
2016-01-01
Leveraging population-distinct linkage equilibrium (LD) patterns, trans-ethnic follow-up of variants discovered from genome-wide association studies (GWAS) has proved to be useful in facilitating the identification of bona fide causal variants. We previously developed the preferential LD approach, a novel method that successfully identified causal variants driving the GWAS signals within European-descent populations even when the causal variants were only weakly linked with the GWAS-discovered variants. To evaluate the performance of our approach in a trans-ethnic setting, we applied it to follow up breast cancer GWAS hits identified mostly from populations of European ancestry in African Americans (AA). We evaluated 74 breast cancer GWAS variants in 8,315 AA women from the African American Breast Cancer Epidemiology and Risk (AMBER) consortium. Only 27% of them were associated with breast cancer risk at significance level α=0.05, suggesting race-specificity of the identified breast cancer risk loci. We followed up on those replicated GWAS hits in the AMBER consortium utilizing the preferential LD approach, to search for causal variants or better breast cancer markers from the 1000 Genomes variant catalog. Our approach identified stronger breast cancer markers for 80% of the GWAS hits with at least nominal breast cancer association, and in 81% of these cases, the marker identified was among the top 10 of all 1000 Genomes variants in the corresponding locus. The results support trans-ethnic application of the preferential LD approach in search for candidate causal variants, and may have implications for future genetic research of breast cancer in AA women. PMID:27825120
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Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification
Faye, Laura L.; Machiela, Mitchell J.; Kraft, Peter; Bull, Shelley B.; Sun, Lei
2013-01-01
Next generation sequencing has dramatically increased our ability to localize disease-causing variants by providing base-pair level information at costs increasingly feasible for the large sample sizes required to detect complex-trait associations. Yet, identification of causal variants within an established region of association remains a challenge. Counter-intuitively, certain factors that increase power to detect an associated region can decrease power to localize the causal variant. First, combining GWAS with imputation or low coverage sequencing to achieve the large sample sizes required for high power can have the unintended effect of producing differential genotyping error among SNPs. This tends to bias the relative evidence for association toward better genotyped SNPs. Second, re-use of GWAS data for fine-mapping exploits previous findings to ensure genome-wide significance in GWAS-associated regions. However, using GWAS findings to inform fine-mapping analysis can bias evidence away from the causal SNP toward the tag SNP and SNPs in high LD with the tag. Together these factors can reduce power to localize the causal SNP by more than half. Other strategies commonly employed to increase power to detect association, namely increasing sample size and using higher density genotyping arrays, can, in certain common scenarios, actually exacerbate these effects and further decrease power to localize causal variants. We develop a re-ranking procedure that accounts for these adverse effects and substantially improves the accuracy of causal SNP identification, often doubling the probability that the causal SNP is top-ranked. Application to the NCI BPC3 aggressive prostate cancer GWAS with imputation meta-analysis identified a new top SNP at 2 of 3 associated loci and several additional possible causal SNPs at these loci that may have otherwise been overlooked. This method is simple to implement using R scripts provided on the author's website. PMID:23950724
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Dunning, Alison M; Michailidou, Kyriaki; Kuchenbaecker, Karoline B; Thompson, Deborah; French, Juliet D; Beesley, Jonathan; Healey, Catherine S; Kar, Siddhartha; Pooley, Karen A; Lopez-Knowles, Elena; Dicks, Ed; Barrowdale, Daniel; Sinnott-Armstrong, Nicholas A; Sallari, Richard C; Hillman, Kristine M; Kaufmann, Susanne; Sivakumaran, Haran; Moradi Marjaneh, Mahdi; Lee, Jason S; Hills, Margaret; Jarosz, Monika; Drury, Suzie; Canisius, Sander; Bolla, Manjeet K; Dennis, Joe; Wang, Qin; Hopper, John L; Southey, Melissa C; Broeks, Annegien; Schmidt, Marjanka K; Lophatananon, Artitaya; Muir, Kenneth; Beckmann, Matthias W; Fasching, Peter A; Dos-Santos-Silva, Isabel; Peto, Julian; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; González-Neira, Anna; Perez, Jose I A; Anton-Culver, Hoda; Eunjung, Lee; Arndt, Volker; Brenner, Hermann; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Aittomäki, Kristiina; Blomqvist, Carl; Ito, Hidemi; Matsuo, Keitaro; Bogdanova, Natasha; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Kosma, Veli-Matti; Mannermaa, Arto; Tseng, Chiu-Chen; Wu, Anna H; Lambrechts, Diether; Wildiers, Hans; Chang-Claude, Jenny; Rudolph, Anja; Peterlongo, Paolo; Radice, Paolo; Olson, Janet E; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Henderson, Brian E; Goldberg, Mark S; Teo, Soo H; Yip, Cheng Har; Nord, Silje; Borresen-Dale, Anne-Lise; Kristensen, Vessela; Long, Jirong; Zheng, Wei; Pylkäs, Katri; Winqvist, Robert; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; Figueroa, Jonine; Sherman, Mark E; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; van den Ouweland, Ans M W; Humphreys, Keith; Gao, Yu-Tang; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Ghoussaini, Maya; Perkins, Barbara J; Shah, Mitul; Choi, Ji-Yeob; Kang, Daehee; Lee, Soo Chin; Hartman, Mikael; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Brennan, Paul; Sangrajrang, Suleeporn; Ambrosone, Christine B; Toland, Amanda E; Shen, Chen-Yang; Wu, Pei-Ei; Orr, Nick; Swerdlow, Anthony; McGuffog, Lesley; Healey, Sue; Lee, Andrew; Kapuscinski, Miroslav; John, Esther M; Terry, Mary Beth; Daly, Mary B; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Tihomirova, Laima; Tung, Nadine; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Neuhausen, Susan L; Ejlertsen, Bent; Hansen, Thomas V O; Osorio, Ana; Benitez, Javier; Rando, Rachel; Weitzel, Jeffrey N; Bonanni, Bernardo; Peissel, Bernard; Manoukian, Siranoush; Papi, Laura; Ottini, Laura; Konstantopoulou, Irene; Apostolou, Paraskevi; Garber, Judy; Rashid, Muhammad Usman; Frost, Debra; Izatt, Louise; Ellis, Steve; Godwin, Andrew K; Arnold, Norbert; Niederacher, Dieter; Rhiem, Kerstin; Bogdanova-Markov, Nadja; Sagne, Charlotte; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Sinilnikova, Olga M; Mazoyer, Sylvie; Isaacs, Claudine; Claes, Kathleen B M; De Leeneer, Kim; de la Hoya, Miguel; Caldes, Trinidad; Nevanlinna, Heli; Khan, Sofia; Mensenkamp, Arjen R; Hooning, Maartje J; Rookus, Matti A; Kwong, Ava; Olah, Edith; Diez, Orland; Brunet, Joan; Pujana, Miquel Angel; Gronwald, Jacek; Huzarski, Tomasz; Barkardottir, Rosa B; Laframboise, Rachel; Soucy, Penny; Montagna, Marco; Agata, Simona; Teixeira, Manuel R; Park, Sue Kyung; Lindor, Noralane; Couch, Fergus J; Tischkowitz, Marc; Foretova, Lenka; Vijai, Joseph; Offit, Kenneth; Singer, Christian F; Rappaport, Christine; Phelan, Catherine M; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Imyanitov, Evgeny N; Hulick, Peter J; Phillips, Kelly-Anne; Piedmonte, Marion; Mulligan, Anna Marie; Glendon, Gord; Bojesen, Anders; Thomassen, Mads; Caligo, Maria A; Yoon, Sook-Yee; Friedman, Eitan; Laitman, Yael; Borg, Ake; von Wachenfeldt, Anna; Ehrencrona, Hans; Rantala, Johanna; Olopade, Olufunmilayo I; Ganz, Patricia A; Nussbaum, Robert L; Gayther, Simon A; Nathanson, Katherine L; Domchek, Susan M; Arun, Banu K; Mitchell, Gillian; Karlan, Beth Y; Lester, Jenny; Maskarinec, Gertraud; Woolcott, Christy; Scott, Christopher; Stone, Jennifer; Apicella, Carmel; Tamimi, Rulla; Luben, Robert; Khaw, Kay-Tee; Helland, Åslaug; Haakensen, Vilde; Dowsett, Mitch; Pharoah, Paul D P; Simard, Jacques; Hall, Per; García-Closas, Montserrat; Vachon, Celine; Chenevix-Trench, Georgia; Antoniou, Antonis C; Easton, Douglas F; Edwards, Stacey L
2016-04-01
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER(+) or ER(-)) and human ERBB2 (HER2(+) or HER2(-)) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER(-) tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression.
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Dunning, Alison M; Michailidou, Kyriaki; Kuchenbaecker, Karoline B; Thompson, Deborah; French, Juliet D; Beesley, Jonathan; Healey, Catherine S; Kar, Siddhartha; Pooley, Karen A; Lopez-Knowles, Elena; Dicks, Ed; Barrowdale, Daniel; Sinnott-Armstrong, Nicholas A; Sallari, Richard C; Hillman, Kristine M; Kaufmann, Susanne; Sivakumaran, Haran; Marjaneh, Mahdi Moradi; Lee, Jason S; Hills, Margaret; Jarosz, Monika; Drury, Suzie; Canisius, Sander; Bolla, Manjeet K; Dennis, Joe; Wang, Qin; Hopper, John L; Southey, Melissa C; Broeks, Annegien; Schmidt, Marjanka K; Lophatananon, Artitaya; Muir, Kenneth; Beckmann, Matthias W; Fasching, Peter A; dos-Santos-Silva, Isabel; Peto, Julian; Sawyer, Elinor J; Tomlinson, Ian; Burwinkel, Barbara; Marme, Frederik; Guénel, Pascal; Truong, Thérèse; Bojesen, Stig E; Flyger, Henrik; González-Neira, Anna; Perez, Jose I A; Anton-Culver, Hoda; Eunjung, Lee; Arndt, Volker; Brenner, Hermann; Meindl, Alfons; Schmutzler, Rita K; Brauch, Hiltrud; Hamann, Ute; Aittomäki, Kristiina; Blomqvist, Carl; Ito, Hidemi; Matsuo, Keitaro; Bogdanova, Natasha; Dörk, Thilo; Lindblom, Annika; Margolin, Sara; Kosma, Veli-Matti; Mannermaa, Arto; Tseng, Chiu-chen; Wu, Anna H; Lambrechts, Diether; Wildiers, Hans; Chang-Claude, Jenny; Rudolph, Anja; Peterlongo, Paolo; Radice, Paolo; Olson, Janet E; Giles, Graham G; Milne, Roger L; Haiman, Christopher A; Henderson, Brian E; Goldberg, Mark S; Teo, Soo H; Yip, Cheng Har; Nord, Silje; Borresen-Dale, Anne-Lise; Kristensen, Vessela; Long, Jirong; Zheng, Wei; Pylkäs, Katri; Winqvist, Robert; Andrulis, Irene L; Knight, Julia A; Devilee, Peter; Seynaeve, Caroline; Figueroa, Jonine; Sherman, Mark E; Czene, Kamila; Darabi, Hatef; Hollestelle, Antoinette; van den Ouweland, Ans M W; Humphreys, Keith; Gao, Yu-Tang; Shu, Xiao-Ou; Cox, Angela; Cross, Simon S; Blot, William; Cai, Qiuyin; Ghoussaini, Maya; Perkins, Barbara J; Shah, Mitul; Choi, Ji-Yeob; Kang, Daehee; Lee, Soo Chin; Hartman, Mikael; Kabisch, Maria; Torres, Diana; Jakubowska, Anna; Lubinski, Jan; Brennan, Paul; Sangrajrang, Suleeporn; Ambrosone, Christine B; Toland, Amanda E; Shen, Chen-Yang; Wu, Pei-Ei; Orr, Nick; Swerdlow, Anthony; McGuffog, Lesley; Healey, Sue; Lee, Andrew; Kapuscinski, Miroslav; John, Esther M; Terry, Mary Beth; Daly, Mary B; Goldgar, David E; Buys, Saundra S; Janavicius, Ramunas; Tihomirova, Laima; Tung, Nadine; Dorfling, Cecilia M; van Rensburg, Elizabeth J; Neuhausen, Susan L; Ejlertsen, Bent; Hansen, Thomas V O; Osorio, Ana; Benitez, Javier; Rando, Rachel; Weitzel, Jeffrey N; Bonanni, Bernardo; Peissel, Bernard; Manoukian, Siranoush; Papi, Laura; Ottini, Laura; Konstantopoulou, Irene; Apostolou, Paraskevi; Garber, Judy; Rashid, Muhammad Usman; Frost, Debra; Izatt, Louise; Ellis, Steve; Godwin, Andrew K; Arnold, Norbert; Niederacher, Dieter; Rhiem, Kerstin; Bogdanova-Markov, Nadja; Sagne, Charlotte; Stoppa-Lyonnet, Dominique; Damiola, Francesca; Sinilnikova, Olga M; Mazoyer, Sylvie; Isaacs, Claudine; Claes, Kathleen B M; De Leeneer, Kim; de la Hoya, Miguel; Caldes, Trinidad; Nevanlinna, Heli; Khan, Sofia; Mensenkamp, Arjen R; Hooning, Maartje J; Rookus, Matti A; Kwong, Ava; Olah, Edith; Diez, Orland; Brunet, Joan; Pujana, Miquel Angel; Gronwald, Jacek; Huzarski, Tomasz; Barkardottir, Rosa B; Laframboise, Rachel; Soucy, Penny; Montagna, Marco; Agata, Simona; Teixeira, Manuel R; Park, Sue Kyung; Lindor, Noralane; Couch, Fergus J; Tischkowitz, Marc; Foretova, Lenka; Vijai, Joseph; Offit, Kenneth; Singer, Christian F; Rappaport, Christine; Phelan, Catherine M; Greene, Mark H; Mai, Phuong L; Rennert, Gad; Imyanitov, Evgeny N; Hulick, Peter J; Phillips, Kelly-Anne; Piedmonte, Marion; Mulligan, Anna Marie; Glendon, Gord; Bojesen, Anders; Thomassen, Mads; Caligo, Maria A; Yoon, Sook-Yee; Friedman, Eitan; Laitman, Yael; Borg, Ake; von Wachenfeldt, Anna; Ehrencrona, Hans; Rantala, Johanna; Olopade, Olufunmilayo I; Ganz, Patricia A; Nussbaum, Robert L; Gayther, Simon A; Nathanson, Katherine L; Domchek, Susan M; Arun, Banu K; Mitchell, Gillian; Karlan, Beth Y; Lester, Jenny; Maskarinec, Gertraud; Woolcott, Christy; Scott, Christopher; Stone, Jennifer; Apicella, Carmel; Tamimi, Rulla; Luben, Robert; Khaw, Kay-Tee; Helland, Åslaug; Haakensen, Vilde; Dowsett, Mitch; Pharoah, Paul D P; Simard, Jacques; Hall, Per; García-Closas, Montserrat; Vachon, Celine; Chenevix-Trench, Georgia; Antoniou, Antonis C; Easton, Douglas F; Edwards, Stacey L
2016-01-01
We analyzed 3,872 common genetic variants across the ESR1 locus (encoding estrogen receptor α) in 118,816 subjects from three international consortia. We found evidence for at least five independent causal variants, each associated with different phenotype sets, including estrogen receptor (ER+ or ER−) and human ERBB2 (HER2+ or HER2−) tumor subtypes, mammographic density and tumor grade. The best candidate causal variants for ER− tumors lie in four separate enhancer elements, and their risk alleles reduce expression of ESR1, RMND1 and CCDC170, whereas the risk alleles of the strongest candidates for the remaining independent causal variant disrupt a silencer element and putatively increase ESR1 and RMND1 expression. PMID:26928228
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Kaufman, Kenneth M; Zhao, Jian; Kelly, Jennifer A; Hughes, Travis; Adler, Adam; Sanchez, Elena; Ojwang, Joshua O; Langefeld, Carl D; Ziegler, Julie T; Williams, Adrienne H; Comeau, Mary E; Marion, Miranda C; Glenn, Stuart B; Cantor, Rita M; Grossman, Jennifer M; Hahn, Bevra H; Song, Yeong Wook; Yu, Chack-Yung; James, Judith A; Guthridge, Joel M; Brown, Elizabeth E; Alarcón, Graciela S; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Petri, Michelle A; Reveille, John D; Vilá, Luis M; Anaya, Juan-Manuel; Boackle, Susan A; Stevens, Anne M; Freedman, Barry I; Criswell, Lindsey A; Pons Estel, Bernardo A; Lee, Joo-Hyun; Lee, Ji-Seon; Chang, Deh-Ming; Scofield, R Hal A; Gilkeson, Gary S; Merrill, Joan T; Niewold, Timothy B; Vyse, Timothy James; Bae, Sang-Cheol; Alarcón-Riquelme, Marta E; Jacob, Chaim O; Moser Sivils, Kathy; Gaffney, Patrick M; Harley, John B; Sawalha, Amr H; Tsao, Betty P
2013-03-01
The Xq28 region containing IRAK1 and MECP2 has been identified as a risk locus for systemic lupus erythematosus (SLE) in previous genetic association studies. However, due to the strong linkage disequilibrium between IRAK1 and MECP2, it remains unclear which gene is affected by the underlying causal variant(s) conferring risk of SLE. We fine-mapped ≥136 SNPs in a ∼227 kb region on Xq28, containing IRAK1, MECP2 and seven adjacent genes (L1CAM, AVPR2, ARHGAP4, NAA10, RENBP, HCFC1 and TMEM187), for association with SLE in 15 783 case-control subjects derived from four different ancestral groups. Multiple SNPs showed strong association with SLE in European Americans, Asians and Hispanics at p<5×10(-8) with consistent association in subjects with African ancestry. Of these, six SNPs located in the TMEM187-IRAK1-MECP2 region captured the underlying causal variant(s) residing in a common risk haplotype shared by all four ancestral groups. Among them, rs1059702 best explained the Xq28 association signals in conditional testings and exhibited the strongest p value in transancestral meta-analysis (p(meta )= 1.3×10(-27), OR=1.43), and thus was considered to be the most likely causal variant. The risk allele of rs1059702 results in the amino acid substitution S196F in IRAK1 and had previously been shown to increase NF-κB activity in vitro. We also found that the homozygous risk genotype of rs1059702 was associated with lower mRNA levels of MECP2, but not IRAK1, in SLE patients (p=0.0012) and healthy controls (p=0.0064). These data suggest contributions of both IRAK1 and MECP2 to SLE susceptibility.
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Grinde, Kelsey E.; Arbet, Jaron; Green, Alden; O'Connell, Michael; Valcarcel, Alessandra; Westra, Jason; Tintle, Nathan
2017-01-01
To date, gene-based rare variant testing approaches have focused on aggregating information across sets of variants to maximize statistical power in identifying genes showing significant association with diseases. Beyond identifying genes that are associated with diseases, the identification of causal variant(s) in those genes and estimation of their effect is crucial for planning replication studies and characterizing the genetic architecture of the locus. However, we illustrate that straightforward single-marker association statistics can suffer from substantial bias introduced by conditioning on gene-based test significance, due to the phenomenon often referred to as “winner's curse.” We illustrate the ramifications of this bias on variant effect size estimation and variant prioritization/ranking approaches, outline parameters of genetic architecture that affect this bias, and propose a bootstrap resampling method to correct for this bias. We find that our correction method significantly reduces the bias due to winner's curse (average two-fold decrease in bias, p < 2.2 × 10−6) and, consequently, substantially improves mean squared error and variant prioritization/ranking. The method is particularly helpful in adjustment for winner's curse effects when the initial gene-based test has low power and for relatively more common, non-causal variants. Adjustment for winner's curse is recommended for all post-hoc estimation and ranking of variants after a gene-based test. Further work is necessary to continue seeking ways to reduce bias and improve inference in post-hoc analysis of gene-based tests under a wide variety of genetic architectures. PMID:28959274
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Partial Granger causality--eliminating exogenous inputs and latent variables.
Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng
2008-07-15
Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.
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Strategic approaches to unraveling genetic causes of cardiovascular diseases
USDA-ARS?s Scientific Manuscript database
DNA sequence variants are major components of the "causal field" for virtually all medical phenotypes, whether single gene familial disorders or complex traits without a clear familial aggregation. The causal variants in single gene disorders are necessary and sufficient to impart large effects. In ...
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Vigorito, Elena; Kuchenbaecker, Karoline B.; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A.; Andrulis, Irene L.; Arun, Banu K.; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A.; Campbell, Ian; Chan, Salina B.; Claes, Kathleen B. M.; Cohn, David E.; Cook, Jackie; Daly, Mary B.; Damiola, Francesca; Davidson, Rosemarie; de Pauw, Antoine; Delnatte, Capucine; Diez, Orland; Domchek, Susan M.; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F.; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D. Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D.; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A.; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K.; Goldgar, David E.; Hake, Christopher R.; Hansen, Thomas V. O.; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B. L.; Houdayer, Claude; Hulick, Peter J.; Imyanitov, Evgeny N.; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M.; Vijai, Joseph; Karlan, Beth Y.; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L.; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R.; Montagna, Marco; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I.; Ong, Kai-ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M.; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C.; Rookus, Matti A.; Ross, Eric A.; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F.; Slavin, Thomas P.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I.; Tea, Muy-Kheng; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J.; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N.; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J.; Greene, Mark H.; Couch, Fergus J.; Offit, Kenneth; Pharoah, Paul D. P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10−16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10−6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population. PMID:27463617
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Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A; Andrulis, Irene L; Arun, Banu K; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A; Campbell, Ian; Chan, Salina B; Claes, Kathleen B M; Cohn, David E; Cook, Jackie; Daly, Mary B; Damiola, Francesca; Davidson, Rosemarie; Pauw, Antoine de; Delnatte, Capucine; Diez, Orland; Domchek, Susan M; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K; Goldgar, David E; Hake, Christopher R; Hansen, Thomas V O; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B L; Houdayer, Claude; Hulick, Peter J; Imyanitov, Evgeny N; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M; Vijai, Joseph; Karlan, Beth Y; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R; Montagna, Marco; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I; Ong, Kai-Ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C; Rookus, Matti A; Ross, Eric A; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F; Slavin, Thomas P; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I; Tea, Muy-Kheng; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J; Greene, Mark H; Couch, Fergus J; Offit, Kenneth; Pharoah, Paul D P; Chenevix-Trench, Georgia; Antoniou, Antonis C
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.
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Mapping rare and common causal alleles for complex human diseases
Raychaudhuri, Soumya
2011-01-01
Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual’s risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on this data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes. PMID:21962507
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Utilizing population controls in rare-variant case-parent association tests.
Jiang, Yu; Satten, Glen A; Han, Yujun; Epstein, Michael P; Heinzen, Erin L; Goldstein, David B; Allen, Andrew S
2014-06-05
There is great interest in detecting associations between human traits and rare genetic variation. To address the low power implicit in single-locus tests of rare genetic variants, many rare-variant association approaches attempt to accumulate information across a gene, often by taking linear combinations of single-locus contributions to a statistic. Using the right linear combination is key-an optimal test will up-weight true causal variants, down-weight neutral variants, and correctly assign the direction of effect for causal variants. Here, we propose a procedure that exploits data from population controls to estimate the linear combination to be used in an case-parent trio rare-variant association test. Specifically, we estimate the linear combination by comparing population control allele frequencies with allele frequencies in the parents of affected offspring. These estimates are then used to construct a rare-variant transmission disequilibrium test (rvTDT) in the case-parent data. Because the rvTDT is conditional on the parents' data, using parental data in estimating the linear combination does not affect the validity or asymptotic distribution of the rvTDT. By using simulation, we show that our new population-control-based rvTDT can dramatically improve power over rvTDTs that do not use population control information across a wide variety of genetic architectures. It also remains valid under population stratification. We apply the approach to a cohort of epileptic encephalopathy (EE) trios and find that dominant (or additive) inherited rare variants are unlikely to play a substantial role within EE genes previously identified through de novo mutation studies. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Krämer, Andreas; Shah, Sohela; Rebres, Robert Anthony; Tang, Susan; Richards, Daniel Rene
2017-08-11
Next-generation sequencing is widely used to identify disease-causing variants in patients with rare genetic disorders. Identifying those variants from whole-genome or exome data can be both scientifically challenging and time consuming. A significant amount of time is spent on variant annotation, and interpretation. Fully or partly automated solutions are therefore needed to streamline and scale this process. We describe Phenotype Driven Ranking (PDR), an algorithm integrated into Ingenuity Variant Analysis, that uses observed patient phenotypes to prioritize diseases and genes in order to expedite causal-variant discovery. Our method is based on a network of phenotype-disease-gene relationships derived from the QIAGEN Knowledge Base, which allows for efficient computational association of phenotypes to implicated diseases, and also enables scoring and ranking. We have demonstrated the utility and performance of PDR by applying it to a number of clinical rare-disease cases, where the true causal gene was known beforehand. It is also shown that PDR compares favorably to a representative alternative tool.
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Zaitlen, Noah A.; Ye, Chun Jimmie; Witte, John S.
2016-01-01
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. PMID:27197206
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Burgess, Stephen; Scott, Robert A; Timpson, Nicholas J; Davey Smith, George; Thompson, Simon G
2015-07-01
Finding individual-level data for adequately-powered Mendelian randomization analyses may be problematic. As publicly-available summarized data on genetic associations with disease outcomes from large consortia are becoming more abundant, use of published data is an attractive analysis strategy for obtaining precise estimates of the causal effects of risk factors on outcomes. We detail the necessary steps for conducting Mendelian randomization investigations using published data, and present novel statistical methods for combining data on the associations of multiple (correlated or uncorrelated) genetic variants with the risk factor and outcome into a single causal effect estimate. A two-sample analysis strategy may be employed, in which evidence on the gene-risk factor and gene-outcome associations are taken from different data sources. These approaches allow the efficient identification of risk factors that are suitable targets for clinical intervention from published data, although the ability to assess the assumptions necessary for causal inference is diminished. Methods and guidance are illustrated using the example of the causal effect of serum calcium levels on fasting glucose concentrations. The estimated causal effect of a 1 standard deviation (0.13 mmol/L) increase in calcium levels on fasting glucose (mM) using a single lead variant from the CASR gene region is 0.044 (95 % credible interval -0.002, 0.100). In contrast, using our method to account for the correlation between variants, the corresponding estimate using 17 genetic variants is 0.022 (95 % credible interval 0.009, 0.035), a more clearly positive causal effect.
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The salience network causally influences default mode network activity during moral reasoning
Wilson, Stephen M.; D’Esposito, Mark; Kayser, Andrew S.; Grossman, Scott N.; Poorzand, Pardis; Seeley, William W.; Miller, Bruce L.; Rankin, Katherine P.
2013-01-01
Large-scale brain networks are integral to the coordination of human behaviour, and their anatomy provides insights into the clinical presentation and progression of neurodegenerative illnesses such as Alzheimer’s disease, which targets the default mode network, and behavioural variant frontotemporal dementia, which targets a more anterior salience network. Although the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, patients with Alzheimer’s disease give normal responses to these dilemmas whereas patients with behavioural variant frontotemporal dementia give abnormal responses to these dilemmas. We hypothesized that this apparent discrepancy between activation- and patient-based studies of moral reasoning might reflect a modulatory role for the salience network in regulating default mode network activation. Using functional magnetic resonance imaging to characterize network activity of patients with behavioural variant frontotemporal dementia and healthy control subjects, we present four converging lines of evidence supporting a causal influence from the salience network to the default mode network during moral reasoning. First, as previously reported, the default mode network is recruited when healthy subjects deliberate about ‘personal’ moral dilemmas, but patients with behavioural variant frontotemporal dementia producing atrophy in the salience network give abnormally utilitarian responses to these dilemmas. Second, patients with behavioural variant frontotemporal dementia have reduced recruitment of the default mode network compared with healthy control subjects when deliberating about these dilemmas. Third, a Granger causality analysis of functional neuroimaging data from healthy control subjects demonstrates directed functional connectivity from nodes of the salience network to nodes of the default mode network during moral reasoning. Fourth, this Granger causal influence is diminished in patients with behavioural variant frontotemporal dementia. These findings are consistent with a broader model in which the salience network modulates the activity of other large-scale networks, and suggest a revision to a previously proposed ‘dual-process’ account of moral reasoning. These findings also characterize network interactions underlying abnormal moral reasoning in frontotemporal dementia, which may serve as a model for the aberrant judgement and interpersonal behaviour observed in this disease and in other disorders of social function. More broadly, these findings link recent work on the dynamic interrelationships between large-scale brain networks to observable impairments in dementia syndromes, which may shed light on how diseases that target one network also alter the function of interrelated networks. PMID:23576128
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2012-01-01
The increasing size and complexity of exome/genome sequencing data requires new tools for clinical geneticists to discover disease-causing variants. Bottlenecks in identifying the causative variation include poor cross-sample querying, constantly changing functional annotation and not considering existing knowledge concerning the phenotype. We describe a methodology that facilitates exploration of patient sequencing data towards identification of causal variants under different genetic hypotheses. Annotate-it facilitates handling, analysis and interpretation of high-throughput single nucleotide variant data. We demonstrate our strategy using three case studies. Annotate-it is freely available and test data are accessible to all users at http://www.annotate-it.org. PMID:23013645
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Molecular Diagnosis of Cystic Fibrosis.
Deignan, Joshua L; Grody, Wayne W
2016-01-01
This unit describes a recommended approach to identifying causal genetic variants in an individual suspected of having cystic fibrosis. An introduction to the genetics and clinical presentation of cystic fibrosis is initially presented, followed by a description of the two main strategies used in the molecular diagnosis of cystic fibrosis: (1) an initial targeted variant panel used to detect only the most common cystic fibrosis-causing variants in the CFTR gene, and (2) sequencing of the entire coding region of the CFTR gene to detect additional rare causal CFTR variants. Finally, the unit concludes with a discussion regarding the analytic and clinical validity of these approaches. Copyright © 2016 John Wiley & Sons, Inc.
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Uricchio, Lawrence H; Zaitlen, Noah A; Ye, Chun Jimmie; Witte, John S; Hernandez, Ryan D
2016-07-01
The role of rare alleles in complex phenotypes has been hotly debated, but most rare variant association tests (RVATs) do not account for the evolutionary forces that affect genetic architecture. Here, we use simulation and numerical algorithms to show that explosive population growth, as experienced by human populations, can dramatically increase the impact of very rare alleles on trait variance. We then assess the ability of RVATs to detect causal loci using simulations and human RNA-seq data. Surprisingly, we find that statistical performance is worst for phenotypes in which genetic variance is due mainly to rare alleles, and explosive population growth decreases power. Although many studies have attempted to identify causal rare variants, few have reported novel associations. This has sometimes been interpreted to mean that rare variants make negligible contributions to complex trait heritability. Our work shows that RVATs are not robust to realistic human evolutionary forces, so general conclusions about the impact of rare variants on complex traits may be premature. © 2016 Uricchio et al.; Published by Cold Spring Harbor Laboratory Press.
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Kill or Die: Moral Judgment Alters Linguistic Coding of Causality
ERIC Educational Resources Information Center
De Freitas, Julian; DeScioli, Peter; Nemirow, Jason; Massenkoff, Maxim; Pinker, Steven
2017-01-01
What is the relationship between the language people use to describe an event and their moral judgments? We test the hypothesis that moral judgment and causative verbs rely on the same underlying mental model of people's actions. Experiment 1a finds that participants choose different verbs to describe the major variants of a moral dilemma, the…
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Gat-Viks, Irit; Chevrier, Nicolas; Wilentzik, Roni; Eisenhaure, Thomas; Raychowdhury, Raktima; Steuerman, Yael; Shalek, Alex; Hacohen, Nir; Amit, Ido; Regev, Aviv
2013-01-01
Individual genetic variation affects gene expression in response to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness QTLs; reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant acts as an activator of the antiviral response; using RNAi, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli. PMID:23503680
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Gat-Viks, Irit; Chevrier, Nicolas; Wilentzik, Roni; Eisenhaure, Thomas; Raychowdhury, Raktima; Steuerman, Yael; Shalek, Alex K; Hacohen, Nir; Amit, Ido; Regev, Aviv
2013-04-01
Individual genetic variation affects gene responsiveness to stimuli, often by influencing complex molecular circuits. Here we combine genomic and intermediate-scale transcriptional profiling with computational methods to identify variants that affect the responsiveness of genes to stimuli (responsiveness quantitative trait loci or reQTLs) and to position these variants in molecular circuit diagrams. We apply this approach to study variation in transcriptional responsiveness to pathogen components in dendritic cells from recombinant inbred mouse strains. We identify reQTLs that correlate with particular stimuli and position them in known pathways. For example, in response to a virus-like stimulus, a trans-acting variant responds as an activator of the antiviral response; using RNA interference, we identify Rgs16 as the likely causal gene. Our approach charts an experimental and analytic path to decipher the mechanisms underlying genetic variation in circuits that control responses to stimuli.
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Genetics of Triglycerides and the Risk of Atherosclerosis.
Dron, Jacqueline S; Hegele, Robert A
2017-07-01
Plasma triglycerides are routinely measured with a lipid profile, and elevated plasma triglycerides are commonly encountered in the clinic. The confounded nature of this trait, which is correlated with numerous other metabolic perturbations, including depressed high-density lipoprotein cholesterol (HDL-C), has thwarted efforts to directly implicate triglycerides as causal in atherogenesis. Human genetic approaches involving large-scale populations and high-throughput genomic assessment under a Mendelian randomization framework have undertaken to sort out questions of causality. We review recent large-scale meta-analyses of cohorts and population-based sequencing studies designed to address whether common and rare variants in genes whose products are determinants of plasma triglycerides are also associated with clinical cardiovascular endpoints. The studied loci include genes encoding lipoprotein lipase and proteins that interact with it, such as apolipoprotein (apo) A-V, apo C-III and angiopoietin-like proteins 3 and 4, and common polymorphisms identified in genome-wide association studies. Triglyceride-raising variant alleles of these genes showed generally strong associations with clinical cardiovascular endpoints. However, in most cases, a second lipid disturbance-usually depressed HDL-C-was concurrently associated. While the findings collectively shift our understanding towards a potential causal role for triglycerides, we still cannot rule out the possibilities that triglycerides are a component of a joint phenotype with low HDL-C or that they are but markers of deeper causal metabolic disturbances that are not routinely measured in epidemiological-scale genetic studies.
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Time, frequency, and time-varying Granger-causality measures in neuroscience.
Cekic, Sezen; Grandjean, Didier; Renaud, Olivier
2018-05-20
This article proposes a systematic methodological review and an objective criticism of existing methods enabling the derivation of time, frequency, and time-varying Granger-causality statistics in neuroscience. The capacity to describe the causal links between signals recorded at different brain locations during a neuroscience experiment is indeed of primary interest for neuroscientists, who often have very precise prior hypotheses about the relationships between recorded brain signals. The increasing interest and the huge number of publications related to this topic calls for this systematic review, which describes the very complex methodological aspects underlying the derivation of these statistics. In this article, we first present a general framework that allows us to review and compare Granger-causality statistics in the time domain, and the link with transfer entropy. Then, the spectral and the time-varying extensions are exposed and discussed together with their estimation and distributional properties. Although not the focus of this article, partial and conditional Granger causality, dynamical causal modelling, directed transfer function, directed coherence, partial directed coherence, and their variant are also mentioned. Copyright © 2018 John Wiley & Sons, Ltd.
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Improved methods for multi-trait fine mapping of pleiotropic risk loci.
Kichaev, Gleb; Roytman, Megan; Johnson, Ruth; Eskin, Eleazar; Lindström, Sara; Kraft, Peter; Pasaniuc, Bogdan
2017-01-15
Genome-wide association studies (GWAS) have identified thousands of regions in the genome that contain genetic variants that increase risk for complex traits and diseases. However, the variants uncovered in GWAS are typically not biologically causal, but rather, correlated to the true causal variant through linkage disequilibrium (LD). To discern the true causal variant(s), a variety of statistical fine-mapping methods have been proposed to prioritize variants for functional validation. In this work we introduce a new approach, fastPAINTOR, that leverages evidence across correlated traits, as well as functional annotation data, to improve fine-mapping accuracy at pleiotropic risk loci. To improve computational efficiency, we describe an new importance sampling scheme to perform model inference. First, we demonstrate in simulations that by leveraging functional annotation data, fastPAINTOR increases fine-mapping resolution relative to existing methods. Next, we show that jointly modeling pleiotropic risk regions improves fine-mapping resolution compared to standard single trait and pleiotropic fine mapping strategies. We report a reduction in the number of SNPs required for follow-up in order to capture 90% of the causal variants from 23 SNPs per locus using a single trait to 12 SNPs when fine-mapping two traits simultaneously. Finally, we analyze summary association data from a large-scale GWAS of lipids and show that these improvements are largely sustained in real data. The fastPAINTOR framework is implemented in the PAINTOR v3.0 package which is publicly available to the research community http://bogdan.bioinformatics.ucla.edu/software/paintor CONTACT: gkichaev@ucla.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Mahajan, Anubha; Wessel, Jennifer; Willems, Sara M; Zhao, Wei; Robertson, Neil R; Chu, Audrey Y; Gan, Wei; Kitajima, Hidetoshi; Taliun, Daniel; Rayner, N William; Guo, Xiuqing; Lu, Yingchang; Li, Man; Jensen, Richard A; Hu, Yao; Huo, Shaofeng; Lohman, Kurt K; Zhang, Weihua; Cook, James P; Prins, Bram Peter; Flannick, Jason; Grarup, Niels; Trubetskoy, Vassily Vladimirovich; Kravic, Jasmina; Kim, Young Jin; Rybin, Denis V; Yaghootkar, Hanieh; Müller-Nurasyid, Martina; Meidtner, Karina; Li-Gao, Ruifang; Varga, Tibor V; Marten, Jonathan; Li, Jin; Smith, Albert Vernon; An, Ping; Ligthart, Symen; Gustafsson, Stefan; Malerba, Giovanni; Demirkan, Ayse; Tajes, Juan Fernandez; Steinthorsdottir, Valgerdur; Wuttke, Matthias; Lecoeur, Cécile; Preuss, Michael; Bielak, Lawrence F; Graff, Marielisa; Highland, Heather M; Justice, Anne E; Liu, Dajiang J; Marouli, Eirini; Peloso, Gina Marie; Warren, Helen R; Afaq, Saima; Afzal, Shoaib; Ahlqvist, Emma; Almgren, Peter; Amin, Najaf; Bang, Lia B; Bertoni, Alain G; Bombieri, Cristina; Bork-Jensen, Jette; Brandslund, Ivan; Brody, Jennifer A; Burtt, Noël P; Canouil, Mickaël; Chen, Yii-Der Ida; Cho, Yoon Shin; Christensen, Cramer; Eastwood, Sophie V; Eckardt, Kai-Uwe; Fischer, Krista; Gambaro, Giovanni; Giedraitis, Vilmantas; Grove, Megan L; de Haan, Hugoline G; Hackinger, Sophie; Hai, Yang; Han, Sohee; Tybjærg-Hansen, Anne; Hivert, Marie-France; Isomaa, Bo; Jäger, Susanne; Jørgensen, Marit E; Jørgensen, Torben; Käräjämäki, Annemari; Kim, Bong-Jo; Kim, Sung Soo; Koistinen, Heikki A; Kovacs, Peter; Kriebel, Jennifer; Kronenberg, Florian; Läll, Kristi; Lange, Leslie A; Lee, Jung-Jin; Lehne, Benjamin; Li, Huaixing; Lin, Keng-Hung; Linneberg, Allan; Liu, Ching-Ti; Liu, Jun; Loh, Marie; Mägi, Reedik; Mamakou, Vasiliki; McKean-Cowdin, Roberta; Nadkarni, Girish; Neville, Matt; Nielsen, Sune F; Ntalla, Ioanna; Peyser, Patricia A; Rathmann, Wolfgang; Rice, Kenneth; Rich, Stephen S; Rode, Line; Rolandsson, Olov; Schönherr, Sebastian; Selvin, Elizabeth; Small, Kerrin S; Stančáková, Alena; Surendran, Praveen; Taylor, Kent D; Teslovich, Tanya M; Thorand, Barbara; Thorleifsson, Gudmar; Tin, Adrienne; Tönjes, Anke; Varbo, Anette; Witte, Daniel R; Wood, Andrew R; Yajnik, Pranav; Yao, Jie; Yengo, Loïc; Young, Robin; Amouyel, Philippe; Boeing, Heiner; Boerwinkle, Eric; Bottinger, Erwin P; Chowdhury, Rajiv; Collins, Francis S; Dedoussis, George; Dehghan, Abbas; Deloukas, Panos; Ferrario, Marco M; Ferrières, Jean; Florez, Jose C; Frossard, Philippe; Gudnason, Vilmundur; Harris, Tamara B; Heckbert, Susan R; Howson, Joanna M M; Ingelsson, Martin; Kathiresan, Sekar; Kee, Frank; Kuusisto, Johanna; Langenberg, Claudia; Launer, Lenore J; Lindgren, Cecilia M; Männistö, Satu; Meitinger, Thomas; Melander, Olle; Mohlke, Karen L; Moitry, Marie; Morris, Andrew D; Murray, Alison D; de Mutsert, Renée; Orho-Melander, Marju; Owen, Katharine R; Perola, Markus; Peters, Annette; Province, Michael A; Rasheed, Asif; Ridker, Paul M; Rivadineira, Fernando; Rosendaal, Frits R; Rosengren, Anders H; Salomaa, Veikko; Sheu, Wayne H-H; Sladek, Rob; Smith, Blair H; Strauch, Konstantin; Uitterlinden, André G; Varma, Rohit; Willer, Cristen J; Blüher, Matthias; Butterworth, Adam S; Chambers, John Campbell; Chasman, Daniel I; Danesh, John; van Duijn, Cornelia; Dupuis, Josée; Franco, Oscar H; Franks, Paul W; Froguel, Philippe; Grallert, Harald; Groop, Leif; Han, Bok-Ghee; Hansen, Torben; Hattersley, Andrew T; Hayward, Caroline; Ingelsson, Erik; Kardia, Sharon L R; Karpe, Fredrik; Kooner, Jaspal Singh; Köttgen, Anna; Kuulasmaa, Kari; Laakso, Markku; Lin, Xu; Lind, Lars; Liu, Yongmei; Loos, Ruth J F; Marchini, Jonathan; Metspalu, Andres; Mook-Kanamori, Dennis; Nordestgaard, Børge G; Palmer, Colin N A; Pankow, James S; Pedersen, Oluf; Psaty, Bruce M; Rauramaa, Rainer; Sattar, Naveed; Schulze, Matthias B; Soranzo, Nicole; Spector, Timothy D; Stefansson, Kari; Stumvoll, Michael; Thorsteinsdottir, Unnur; Tuomi, Tiinamaija; Tuomilehto, Jaakko; Wareham, Nicholas J; Wilson, James G; Zeggini, Eleftheria; Scott, Robert A; Barroso, Inês; Frayling, Timothy M; Goodarzi, Mark O; Meigs, James B; Boehnke, Michael; Saleheen, Danish; Morris, Andrew P; Rotter, Jerome I; McCarthy, Mark I
2018-04-01
We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10 -7 ); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.
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Fritsche, Lars G.; Igl, Wilmar; Cooke Bailey, Jessica N.; Grassmann, Felix; Sengupta, Sebanti; Bragg-Gresham, Jennifer L.; Burdon, Kathryn P.; Hebbring, Scott J.; Wen, Cindy; Gorski, Mathias; Kim, Ivana K.; Cho, David; Zack, Donald; Souied, Eric; Scholl, Hendrik P. N.; Bala, Elisa; Lee, Kristine E.; Hunter, David J.; Sardell, Rebecca J.; Mitchell, Paul; Merriam, Joanna E.; Cipriani, Valentina; Hoffman, Joshua D.; Schick, Tina; Lechanteur, Yara T. E.; Guymer, Robyn H.; Johnson, Matthew P.; Jiang, Yingda; Stanton, Chloe M.; Buitendijk, Gabriëlle H. S.; Zhan, Xiaowei; Kwong, Alan M.; Boleda, Alexis; Brooks, Matthew; Gieser, Linn; Ratnapriya, Rinki; Branham, Kari E.; Foerster, Johanna R.; Heckenlively, John R.; Othman, Mohammad I.; Vote, Brendan J.; Liang, Helena Hai; Souzeau, Emmanuelle; McAllister, Ian L.; Isaacs, Timothy; Hall, Janette; Lake, Stewart; Mackey, David A.; Constable, Ian J.; Craig, Jamie E.; Kitchner, Terrie E.; Yang, Zhenglin; Su, Zhiguang; Luo, Hongrong; Chen, Daniel; Ouyang, Hong; Flagg, Ken; Lin, Danni; Mao, Guanping; Ferreyra, Henry; Stark, Klaus; von Strachwitz, Claudia N.; Wolf, Armin; Brandl, Caroline; Rudolph, Guenther; Olden, Matthias; Morrison, Margaux A.; Morgan, Denise J.; Schu, Matthew; Ahn, Jeeyun; Silvestri, Giuliana; Tsironi, Evangelia E.; Park, Kyu Hyung; Farrer, Lindsay A.; Orlin, Anton; Brucker, Alexander; Li, Mingyao; Curcio, Christine; Mohand-Saïd, Saddek; Sahel, José-Alain; Audo, Isabelle; Benchaboune, Mustapha; Cree, Angela J.; Rennie, Christina A.; Goverdhan, Srinivas V.; Grunin, Michelle; Hagbi-Levi, Shira; Campochiaro, Peter; Katsanis, Nicholas; Holz, Frank G.; Blond, Frédéric; Blanché, Hélène; Deleuze, Jean-François; Igo, Robert P.; Truitt, Barbara; Peachey, Neal S.; Meuer, Stacy M.; Myers, Chelsea E.; Moore, Emily L.; Klein, Ronald; Hauser, Michael A.; Postel, Eric A.; Courtenay, Monique D.; Schwartz, Stephen G.; Kovach, Jaclyn L.; Scott, William K.; Liew, Gerald; Tƒan, Ava G.; Gopinath, Bamini; Merriam, John C.; Smith, R. Theodore; Khan, Jane C.; Shahid, Humma; Moore, Anthony T.; McGrath, J. Allie; Laux, Reneé; Brantley, Milam A.; Agarwal, Anita; Ersoy, Lebriz; Caramoy, Albert; Langmann, Thomas; Saksens, Nicole T. M.; de Jong, Eiko K.; Hoyng, Carel B.; Cain, Melinda S.; Richardson, Andrea J.; Martin, Tammy M.; Blangero, John; Weeks, Daniel E.; Dhillon, Bal; van Duijn, Cornelia M.; Doheny, Kimberly F.; Romm, Jane; Klaver, Caroline C. W.; Hayward, Caroline; Gorin, Michael B.; Klein, Michael L.; Baird, Paul N.; den Hollander, Anneke I.; Fauser, Sascha; Yates, John R. W.; Allikmets, Rando; Wang, Jie Jin; Schaumberg, Debra A.; Klein, Barbara E. K.; Hagstrom, Stephanie A.; Chowers, Itay; Lotery, Andrew J.; Léveillard, Thierry; Zhang, Kang; Brilliant, Murray H.; Hewitt, Alex W.; Swaroop, Anand; Chew, Emily Y.; Pericak-Vance, Margaret A.; DeAngelis, Margaret; Stambolian, Dwight; Haines, Jonathan L.; Iyengar, Sudha K.; Weber, Bernhard H. F.; Abecasis, Gonçalo R.; Heid, Iris M.
2016-01-01
Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly with limited therapeutic options. Here, we report on a study of >12 million variants including 163,714 directly genotyped, most rare, protein-altering variant. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5×10–8) distributed across 34 loci. While wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first signal specific to wet AMD, near MMP9 (difference-P = 4.1×10–10). Very rare coding variants (frequency < 0.1%) in CFH, CFI, and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes. PMID:26691988
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Association analysis of multiple traits by an approach of combining P values.
Chen, Lili; Wang, Yong; Zhou, Yajing
2018-03-01
Increasing evidence shows that one variant can affect multiple traits, which is a widespread phenomenon in complex diseases. Joint analysis of multiple traits can increase statistical power of association analysis and uncover the underlying genetic mechanism. Although there are many statistical methods to analyse multiple traits, most of these methods are usually suitable for detecting common variants associated with multiple traits. However, because of low minor allele frequency of rare variant, these methods are not optimal for rare variant association analysis. In this paper, we extend an adaptive combination of P values method (termed ADA) for single trait to test association between multiple traits and rare variants in the given region. For a given region, we use reverse regression model to test each rare variant associated with multiple traits and obtain the P value of single-variant test. Further, we take the weighted combination of these P values as the test statistic. Extensive simulation studies show that our approach is more powerful than several other comparison methods in most cases and is robust to the inclusion of a high proportion of neutral variants and the different directions of effects of causal variants.
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TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies
van der Sluis, Sophie; Posthuma, Danielle; Dolan, Conor V.
2013-01-01
To date, the genome-wide association study (GWAS) is the primary tool to identify genetic variants that cause phenotypic variation. As GWAS analyses are generally univariate in nature, multivariate phenotypic information is usually reduced to a single composite score. This practice often results in loss of statistical power to detect causal variants. Multivariate genotype–phenotype methods do exist but attain maximal power only in special circumstances. Here, we present a new multivariate method that we refer to as TATES (Trait-based Association Test that uses Extended Simes procedure), inspired by the GATES procedure proposed by Li et al (2011). For each component of a multivariate trait, TATES combines p-values obtained in standard univariate GWAS to acquire one trait-based p-value, while correcting for correlations between components. Extensive simulations, probing a wide variety of genotype–phenotype models, show that TATES's false positive rate is correct, and that TATES's statistical power to detect causal variants explaining 0.5% of the variance can be 2.5–9 times higher than the power of univariate tests based on composite scores and 1.5–2 times higher than the power of the standard MANOVA. Unlike other multivariate methods, TATES detects both genetic variants that are common to multiple phenotypes and genetic variants that are specific to a single phenotype, i.e. TATES provides a more complete view of the genetic architecture of complex traits. As the actual causal genotype–phenotype model is usually unknown and probably phenotypically and genetically complex, TATES, available as an open source program, constitutes a powerful new multivariate strategy that allows researchers to identify novel causal variants, while the complexity of traits is no longer a limiting factor. PMID:23359524
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Exome Sequencing in Suspected Monogenic Dyslipidemias
Stitziel, Nathan O.; Peloso, Gina M.; Abifadel, Marianne; Cefalu, Angelo B.; Fouchier, Sigrid; Motazacker, M. Mahdi; Tada, Hayato; Larach, Daniel B.; Awan, Zuhier; Haller, Jorge F.; Pullinger, Clive R.; Varret, Mathilde; Rabès, Jean-Pierre; Noto, Davide; Tarugi, Patrizia; Kawashiri, Masa-aki; Nohara, Atsushi; Yamagishi, Masakazu; Risman, Marjorie; Deo, Rahul; Ruel, Isabelle; Shendure, Jay; Nickerson, Deborah A.; Wilson, James G.; Rich, Stephen S.; Gupta, Namrata; Farlow, Deborah N.; Neale, Benjamin M.; Daly, Mark J.; Kane, John P.; Freeman, Mason W.; Genest, Jacques; Rader, Daniel J.; Mabuchi, Hiroshi; Kastelein, John J.P.; Hovingh, G. Kees; Averna, Maurizio R.; Gabriel, Stacey; Boileau, Catherine; Kathiresan, Sekar
2015-01-01
Background Exome sequencing is a promising tool for gene mapping in Mendelian disorders. We utilized this technique in an attempt to identify novel genes underlying monogenic dyslipidemias. Methods and Results We performed exome sequencing on 213 selected family members from 41 kindreds with suspected Mendelian inheritance of extreme levels of low-density lipoprotein (LDL) cholesterol (after candidate gene sequencing excluded known genetic causes for high LDL cholesterol families) or high-density lipoprotein (HDL) cholesterol. We used standard analytic approaches to identify candidate variants and also assigned a polygenic score to each individual in order to account for their burden of common genetic variants known to influence lipid levels. In nine families, we identified likely pathogenic variants in known lipid genes (ABCA1, APOB, APOE, LDLR, LIPA, and PCSK9); however, we were unable to identify obvious genetic etiologies in the remaining 32 families despite follow-up analyses. We identified three factors that limited novel gene discovery: (1) imperfect sequencing coverage across the exome hid potentially causal variants; (2) large numbers of shared rare alleles within families obfuscated causal variant identification; and (3) individuals from 15% of families carried a significant burden of common lipid-related alleles, suggesting complex inheritance can masquerade as monogenic disease. Conclusions We identified the genetic basis of disease in nine of 41 families; however, none of these represented novel gene discoveries. Our results highlight the promise and limitations of exome sequencing as a discovery technique in suspected monogenic dyslipidemias. Considering the confounders identified may inform the design of future exome sequencing studies. PMID:25632026
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The HABP2 G534E polymorphism does not increase nonmedullary thyroid cancer risk in Hispanics
Bohórquez, Mabel E; Estrada, Ana P; Stultz, Jacob; Sahasrabudhe, Ruta; Williamson, John; Lott, Paul; Duque, Carlos S; Donado, Jorge; Mateus, Gilbert; Bolaños, Fernando; Vélez, Alejandro; Echeverry, Magdalena
2016-01-01
Familial nonmedullary thyroid cancer (NMTC) has not been clearly linked to causal germline variants, despite the large role that genetic factors play in risk. Recently, HABP2 G534E (rs7080536A) has been implicated as a causal variant in NMTC. We have previously shown that the HABP2 G534E variant is not associated with TC risk in patients from the British Isles. Hispanics are the largest and the youngest minority in the United States and NMTC is now the second most common malignancy in women from this population. In order to determine if the HABP2 G534E variant played a role in NMTC risk among Hispanic populations, we analyzed 281 cases and 1105 population-matched controls from a multicenter study in Colombia, evaluating the association through logistic regression. We found that the HABP2 G534E variant was not significantly associated with NMTC risk (P=0.843) in this Hispanic group. We also stratified available clinical data by multiple available clinicopathological variables and further analyzed the effect of HABP2 on NMTC presentation. However, we failed to detect associations between HABP2 G534E and NMTC risk, regardless of disease presentation (P≥0.273 for all cases). Therefore, without any significant associations between the HABP2 G534E variant and NMTC risk, we conclude that the variant is not causal of NMTC in this Hispanic population. PMID:27097599
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Clinical Applications of Molecular Genetic Discoveries
Marian, A.J.
2015-01-01
Genome-wide association studies (GWAS) of complex traits have mapped more than 15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as Next Generation Sequencing, to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population as well as in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: “The good physician treats the disease; the great physician treats the patient who has the disease.” The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease. PMID:26548329
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Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A
2018-03-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.
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Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Kawaji, Hideya; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Hume, David A.
2018-01-01
Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits. PMID:29494619
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Lee, Yujung; Kim, Changshin; Park, YoungJoon; Pyun, Jung-A; Kwack, KyuBum
2016-12-01
Premature ovarian failure (POF) is characterized by heterogeneous genetic causes such as chromosomal abnormalities and variants in causal genes. Recently, development of techniques made next generation sequencing (NGS) possible to detect genome wide variants including chromosomal abnormalities. Among 37 Korean POF patients, XY karyotype with distal part deletions of Y chromosome, Yp11.32-31 and Yp12 end part, was observed in two patients through NGS. Six deleterious variants in POF genes were also detected which might explain the pathogenesis of POF with abnormalities in the sex chromosomes. Additionally, the two POF patients had no mutation in SRY but three non-synonymous variants were detected in genes regarding sex reversal. These findings suggest candidate causes of POF and sex reversal and show the propriety of NGS to approach the heterogeneous pathogenesis of POF. Copyright © 2016 Elsevier Inc. All rights reserved.
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New insights into old methods for identifying causal rare variants.
Wang, Haitian; Huang, Chien-Hsun; Lo, Shaw-Hwa; Zheng, Tian; Hu, Inchi
2011-11-29
The advance of high-throughput next-generation sequencing technology makes possible the analysis of rare variants. However, the investigation of rare variants in unrelated-individuals data sets faces the challenge of low power, and most methods circumvent the difficulty by using various collapsing procedures based on genes, pathways, or gene clusters. We suggest a new way to identify causal rare variants using the F-statistic and sliced inverse regression. The procedure is tested on the data set provided by the Genetic Analysis Workshop 17 (GAW17). After preliminary data reduction, we ranked markers according to their F-statistic values. Top-ranked markers were then subjected to sliced inverse regression, and those with higher absolute coefficients in the most significant sliced inverse regression direction were selected. The procedure yields good false discovery rates for the GAW17 data and thus is a promising method for future study on rare variants.
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Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K.; Thomas, Venetta; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J.; Cheng, Iona; Chu, Lisa; Deming, Sandra L.; Driver, W. Ryan; Goodman, Phyllis; Hayes, Richard B.; Hennis, Anselm J. M.; Hsing, Ann W.; Hu, Jennifer J.; Ingles, Sue A.; John, Esther M.; Kittles, Rick A.; Kolb, Suzanne; Leske, M. Cristina; Monroe, Kristine R.; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F.; Rodriguez-Gil, Jorge L.; Rybicki, Ben A.; Schumacher, Fredrick; Stanford, Janet L.; Signorello, Lisa B.; Strom, Sara S.; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S.; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G.; Stram, Alexander H.; Kolonel, Laurence N.; Marchand, Loïc Le; Henderson, Brian E.; Haiman, Christopher A.; Stram, Daniel O.
2015-01-01
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious. PMID:26125186
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Chen, Fang; He, Jing; Zhang, Jianqi; Chen, Gary K; Thomas, Venetta; Ambrosone, Christine B; Bandera, Elisa V; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Cai, Qiuyin; Carpten, John; Casey, Graham; Chanock, Stephen J; Cheng, Iona; Chu, Lisa; Deming, Sandra L; Driver, W Ryan; Goodman, Phyllis; Hayes, Richard B; Hennis, Anselm J M; Hsing, Ann W; Hu, Jennifer J; Ingles, Sue A; John, Esther M; Kittles, Rick A; Kolb, Suzanne; Leske, M Cristina; Millikan, Robert C; Monroe, Kristine R; Murphy, Adam; Nemesure, Barbara; Neslund-Dudas, Christine; Nyante, Sarah; Ostrander, Elaine A; Press, Michael F; Rodriguez-Gil, Jorge L; Rybicki, Ben A; Schumacher, Fredrick; Stanford, Janet L; Signorello, Lisa B; Strom, Sara S; Stevens, Victoria; Van Den Berg, David; Wang, Zhaoming; Witte, John S; Wu, Suh-Yuh; Yamamura, Yuko; Zheng, Wei; Ziegler, Regina G; Stram, Alexander H; Kolonel, Laurence N; Le Marchand, Loïc; Henderson, Brian E; Haiman, Christopher A; Stram, Daniel O
2015-01-01
Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.
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Lozano, Reymundo; Vino, Arianna; Lozano, Cristina; Fisher, Simon E; Deriziotis, Pelagia
2015-12-01
FOXP1 (forkhead box protein P1) is a transcription factor involved in the development of several tissues, including the brain. An emerging phenotype of patients with protein-disrupting FOXP1 variants includes global developmental delay, intellectual disability and mild to severe speech/language deficits. We report on a female child with a history of severe hypotonia, autism spectrum disorder and mild intellectual disability with severe speech/language impairment. Clinical exome sequencing identified a heterozygous de novo FOXP1 variant c.1267_1268delGT (p.V423Hfs*37). Functional analyses using cellular models show that the variant disrupts multiple aspects of FOXP1 activity, including subcellular localization and transcriptional repression properties. Our findings highlight the importance of performing functional characterization to help uncover the biological significance of variants identified by genomics approaches, thereby providing insight into pathways underlying complex neurodevelopmental disorders. Moreover, our data support the hypothesis that de novo variants represent significant causal factors in severe sporadic disorders and extend the phenotype seen in individuals with FOXP1 haploinsufficiency.
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Wang, Nan; Zhang, Yeting; Gedvilaite, Erika; Loh, Jui Wan; Lin, Timothy; Liu, Xiuping; Liu, Chang-Gong; Kumar, Dibyendu; Donnelly, Robert; Raymond, Kimiyo; Schuchman, Edward H; Sleat, David E; Lobel, Peter; Xing, Jinchuan
2017-11-01
Lysosomes are membrane-bound, acidic eukaryotic cellular organelles that play important roles in the degradation of macromolecules. Mutations that cause the loss of lysosomal protein function can lead to a group of disorders categorized as the lysosomal storage diseases (LSDs). Suspicion of LSD is frequently based on clinical and pathologic findings, but in some cases, the underlying genetic and biochemical defects remain unknown. Here, we performed whole-exome sequencing (WES) on 14 suspected LSD cases to evaluate the feasibility of using WES for identifying causal mutations. By examining 2,157 candidate genes potentially associated with lysosomal function, we identified eight variants in five genes as candidate disease-causing variants in four individuals. These included both known and novel mutations. Variants were corroborated by targeted sequencing and, when possible, functional assays. In addition, we identified nonsense mutations in two individuals in genes that are not known to have lysosomal function. However, mutations in these genes could have resulted in phenotypes that were diagnosed as LSDs. This study demonstrates that WES can be used to identify causal mutations in suspected LSD cases. We also demonstrate cases where a confounding clinical phenotype may potentially reflect more than one lysosomal protein defect. © 2017 Wiley Periodicals, Inc.
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Edwards, Stefan M.; Sørensen, Izel F.; Sarup, Pernille; Mackay, Trudy F. C.; Sørensen, Peter
2016-01-01
Predicting individual quantitative trait phenotypes from high-resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding, and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorphisms and causal variants individually have small effects on the traits. We hypothesized that mapping molecular polymorphisms to genomic features such as genes and their gene ontology categories could increase the accuracy of genomic prediction models. We developed a genomic feature best linear unbiased prediction (GFBLUP) model that implements this strategy and applied it to three quantitative traits (startle response, starvation resistance, and chill coma recovery) in the unrelated, sequenced inbred lines of the Drosophila melanogaster Genetic Reference Panel. Our results indicate that subsetting markers based on genomic features increases the predictive ability relative to the standard genomic best linear unbiased prediction (GBLUP) model. Both models use all markers, but GFBLUP allows differential weighting of the individual genetic marker relationships, whereas GBLUP weighs the genetic marker relationships equally. Simulation studies show that it is possible to further increase the accuracy of genomic prediction for complex traits using this model, provided the genomic features are enriched for causal variants. Our GFBLUP model using prior information on genomic features enriched for causal variants can increase the accuracy of genomic predictions in populations of unrelated individuals and provides a formal statistical framework for leveraging and evaluating information across multiple experimental studies to provide novel insights into the genetic architecture of complex traits. PMID:27235308
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Fine-mapping inflammatory bowel disease loci to single variant resolution
Huang, Hailiang; Fang, Ming; Jostins, Luke; Mirkov, Maša Umićević; Boucher, Gabrielle; Anderson, Carl A; Andersen, Vibeke; Cleynen, Isabelle; Cortes, Adrian; Crins, François; D'Amato, Mauro; Deffontaine, Valérie; Dimitrieva, Julia; Docampo, Elisa; Elansary, Mahmoud; Farh, Kyle Kai-How; Franke, Andre; Gori, Ann-Stephan; Goyette, Philippe; Halfvarson, Jonas; Haritunians, Talin; Knight, Jo; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mariman, Rob; Meuwissen, Theo; Mni, Myriam; Momozawa, Yukihide; Parkes, Miles; Spain, Sarah L; Théâtre, Emilie; Trynka, Gosia; Satsangi, Jack; van Sommeren, Suzanne; Vermeire, Severine; Xavier, Ramnik J; Weersma, Rinse K; Duerr, Richard H; Mathew, Christopher G; Rioux, John D; McGovern, Dermot PB; Cho, Judy H; Georges, Michel; Daly, Mark J; Barrett, Jeffrey C
2017-01-01
Summary The inflammatory bowel diseases (IBD) are chronic gastrointestinal inflammatory disorders that affect millions worldwide. Genome-wide association studies have identified 200 IBD-associated loci, but few have been conclusively resolved to specific functional variants. Here we report fine-mapping of 94 IBD loci using high-density genotyping in 67,852 individuals. We pinpointed 18 associations to a single causal variant with >95% certainty, and an additional 27 associations to a single variant with >50% certainty. These 45 variants are significantly enriched for protein-coding changes (n=13), direct disruption of transcription factor binding sites (n=3) and tissue specific epigenetic marks (n=10), with the latter category showing enrichment in specific immune cells among associations stronger in CD and in gut mucosa among associations stronger in UC. The results of this study suggest that high-resolution fine-mapping in large samples can convert many GWAS discoveries into statistically convincing causal variants, providing a powerful substrate for experimental elucidation of disease mechanisms. PMID:28658209
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The Model Analyst’s Toolkit: Scientific Model Development, Analysis, and Validation
2013-11-20
Granger causality F-test validation 3.1.2. Dynamic time warping for uneven temporal relationships Many causal relationships are imperfectly...mapping for dynamic feedback models Granger causality and DTW can identify causal relationships and consider complex temporal factors. However, many ...variant of the tf-idf algorithm (Manning, Raghavan, Schutze et al., 2008), typically used in search engines, to “score” features. The (-log tf) in
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Al Chawa, Taofik; Ludwig, Kerstin U; Fier, Heide; Pötzsch, Bernd; Reich, Rudolf H; Schmidt, Gül; Braumann, Bert; Daratsianos, Nikolaos; Böhmer, Anne C; Schuencke, Hannah; Alblas, Margrieta; Fricker, Nadine; Hoffmann, Per; Knapp, Michael; Lange, Christoph; Nöthen, Markus M; Mangold, Elisabeth
2014-06-01
The genes Gremlin-1 (GREM1) and Noggin (NOG) are components of the bone morphogenetic protein 4 pathway, which has been implicated in craniofacial development. Both genes map to recently identified susceptibility loci (chromosomal region 15q13, 17q22) for nonsyndromic cleft lip with or without cleft palate (nsCL/P). The aim of the present study was to determine whether rare variants in either gene are implicated in nsCL/P etiology. The complete coding regions, untranslated regions, and splice sites of GREM1 and NOG were sequenced in 96 nsCL/P patients and 96 controls of Central European ethnicity. Three burden and four nonburden tests were performed. Statistically significant results were followed up in a second case-control sample (n = 96, respectively). For rare variants observed in cases, segregation analyses were performed. In NOG, four rare sequence variants (minor allele frequency < 1%) were identified. Here, burden and nonburden analyses generated nonsignificant results. In GREM1, 33 variants were identified, 15 of which were rare. Of these, five were novel. Significant p-values were generated in three nonburden analyses. Segregation analyses revealed incomplete penetrance for all variants investigated. Our study did not provide support for NOG being the causal gene at 17q22. However, the observation of a significant excess of rare variants in GREM1 supports the hypothesis that this is the causal gene at chr. 15q13. Because no single causal variant was identified, future sequencing analyses of GREM1 should involve larger samples and the investigation of regulatory elements. © 2014 Wiley Periodicals, Inc.
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Causal Genetic Variation Underlying Metabolome Differences.
Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A
2017-08-01
An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.
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Rodriguez, Gabriela; Ueyama, Tomomi; Ogata, Takehiro; Czernuszewicz', Grazyna; Tan, Yanli; Dorn, Gerald W.; Bogaev, Roberta; Amano, Katsuya; Oh, Hidemasa; Matsubara, Hiroaki; Willerson, James T.; Marian, Ali J.
2011-01-01
Background Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are classic forms of systolic and diastolic heart failure, respectively. Mutations in genes encoding sarcomere and cytoskeletal proteins are major causes of HCM and DCM. MURC, encoding muscle-restricted coiled-coil, a Z line protein, regulates cardiac function in mice. We investigated potential causal role of MURC in human cardiomyopathies. Methods and Results We sequenced MURC in 1,199 individuals including 383 probands with DCM, 307 with HCM and 509 healthy controls. We found six heterozygous DCM-specific missense variants (p.N128K, p.R140W, p.L153P, p.S307T, p.P324L and p.S364L) in eight unrelated probands. Variants p.N128K and p.S307T segregated with inheritance of DCM in small families (χ2=8.5, p=0.003). Variants p.N128K, p.R140W, p.L153P and p.S364L were considered probably or possibly damaging. Variant p.P324L recurred in three independent probands, including one proband with a TPM1 mutation (p.M245T). A deletion variant (p.L232-R238del) was present in three unrelated HCM probands but it did not segregate with HCM in a family who also had a MYH7 mutation (p.L970V). The phenotype in mutation carriers was notable for progressive heart failure leading to heart transplantation in four patients, conduction defects and atrial arrhythmias. Expression of mutant MURC proteins in neonatal rat cardiac myocytes transduced with recombinant adenoviruses was associated with reduced RhoA activity, lower mRNA levels of hypertrophic markers and smaller myocyte size as compared to wild type MURC. Conclusions MURC mutations impart loss-of-function effects on MURC functions and are likely causal variants in human DCM. The causal role of a deletion mutation in HCM is uncertain. PMID:21642240
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Rodriguez, Gabriela; Ueyama, Tomomi; Ogata, Takehiro; Czernuszewicz, Grazyna; Tan, Yanli; Dorn, Gerald W; Bogaev, Roberta; Amano, Katsuya; Oh, Hidemasa; Matsubara, Hiroaki; Willerson, James T; Marian, Ali J
2011-08-01
Dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM) are classic forms of systolic and diastolic heart failure, respectively. Mutations in genes encoding sarcomere and cytoskeletal proteins are major causes of HCM and DCM. MURC, encoding muscle-restricted coiled-coil, a Z-line protein, regulates cardiac function in mice. We investigated potential causal role of MURC in human cardiomyopathies. We sequenced MURC in 1199 individuals, including 383 probands with DCM, 307 with HCM, and 509 healthy control subjects. We found 6 heterozygous DCM-specific missense variants (p.N128K, p.R140W, p.L153P, p.S307T, p.P324L, and p.S364L) in 8 unrelated probands. Variants p.N128K and p.S307T segregated with inheritance of DCM in small families (χ(2)=8.5, P=0.003). Variants p.N128K, p.R140W, p.L153P, and p.S364L were considered probably or possibly damaging. Variant p.P324L recurred in 3 independent probands, including 1 proband with a TPM1 mutation (p.M245T). A deletion variant (p.L232-R238del) was present in 3 unrelated HCM probands, but it did not segregate with HCM in a family who also had a MYH7 mutation (p.L907V). The phenotype in mutation carriers was notable for progressive heart failure leading to heart transplantation in 4 patients, conduction defects, and atrial arrhythmias. Expression of mutant MURC proteins in neonatal rat cardiac myocytes transduced with recombinant adenoviruses was associated with reduced RhoA activity, lower mRNA levels of hypertrophic markers and smaller myocyte size as compared with wild-type MURC. MURC mutations impart loss-of-function effects on MURC functions and probably are causal variants in human DCM. The causal role of a deletion mutation in HCM is uncertain.
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Price, T. Ryan; De Pablo-Fernandez, Eduardo; Haycock, Philip C.; Schrag, Anette; Lees, Andrew J.; Hardy, John; Singleton, Andrew; Nalls, Mike A.; Pearce, Neil; Wood, Nicholas W.
2017-01-01
Background Both positive and negative associations between higher body mass index (BMI) and Parkinson disease (PD) have been reported in observational studies, but it has been difficult to establish causality because of the possibility of residual confounding or reverse causation. To our knowledge, Mendelian randomisation (MR)—the use of genetic instrumental variables (IVs) to explore causal effects—has not previously been used to test the effect of BMI on PD. Methods and findings Two-sample MR was undertaken using genome-wide association (GWA) study data. The associations between the genetic instruments and BMI were obtained from the GIANT consortium and consisted of the per-allele difference in mean BMI for 77 independent variants that reached genome-wide significance. The per-allele difference in log-odds of PD for each of these variants was estimated from a recent meta-analysis, which included 13,708 cases of PD and 95,282 controls. The inverse-variance weighted method was used to estimate a pooled odds ratio (OR) for the effect of a 5-kg/m2 higher BMI on PD. Evidence of directional pleiotropy averaged across all variants was sought using MR–Egger regression. Frailty simulations were used to assess whether causal associations were affected by mortality selection. A combined genetic IV expected to confer a lifetime exposure of 5-kg/m2 higher BMI was associated with a lower risk of PD (OR 0.82, 95% CI 0.69–0.98). MR–Egger regression gave similar results, suggesting that directional pleiotropy was unlikely to be biasing the result (intercept 0.002; p = 0.654). However, the apparent protective influence of higher BMI could be at least partially induced by survival bias in the PD GWA study, as demonstrated by frailty simulations. Other important limitations of this application of MR include the inability to analyse non-linear associations, to undertake subgroup analyses, and to gain mechanistic insights. Conclusions In this large study using two-sample MR, we found that variants known to influence BMI had effects on PD in a manner consistent with higher BMI leading to lower risk of PD. The mechanism underlying this apparent protective effect warrants further study. PMID:28609445
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Yan, Song; Li, Yun
2014-02-15
Despite its great capability to detect rare variant associations, next-generation sequencing is still prohibitively expensive when applied to large samples. In case-control studies, it is thus appealing to sequence only a subset of cases to discover variants and genotype the identified variants in controls and the remaining cases under the reasonable assumption that causal variants are usually enriched among cases. However, this approach leads to inflated type-I error if analyzed naively for rare variant association. Several methods have been proposed in recent literature to control type-I error at the cost of either excluding some sequenced cases or correcting the genotypes of discovered rare variants. All of these approaches thus suffer from certain extent of information loss and thus are underpowered. We propose a novel method (BETASEQ), which corrects inflation of type-I error by supplementing pseudo-variants while keeps the original sequence and genotype data intact. Extensive simulations and real data analysis demonstrate that, in most practical situations, BETASEQ leads to higher testing powers than existing approaches with guaranteed (controlled or conservative) type-I error. BETASEQ and associated R files, including documentation, examples, are available at http://www.unc.edu/~yunmli/betaseq
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Fine-mapping inflammatory bowel disease loci to single-variant resolution.
Huang, Hailiang; Fang, Ming; Jostins, Luke; Umićević Mirkov, Maša; Boucher, Gabrielle; Anderson, Carl A; Andersen, Vibeke; Cleynen, Isabelle; Cortes, Adrian; Crins, François; D'Amato, Mauro; Deffontaine, Valérie; Dmitrieva, Julia; Docampo, Elisa; Elansary, Mahmoud; Farh, Kyle Kai-How; Franke, Andre; Gori, Ann-Stephan; Goyette, Philippe; Halfvarson, Jonas; Haritunians, Talin; Knight, Jo; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mariman, Rob; Meuwissen, Theo; Mni, Myriam; Momozawa, Yukihide; Parkes, Miles; Spain, Sarah L; Théâtre, Emilie; Trynka, Gosia; Satsangi, Jack; van Sommeren, Suzanne; Vermeire, Severine; Xavier, Ramnik J; Weersma, Rinse K; Duerr, Richard H; Mathew, Christopher G; Rioux, John D; McGovern, Dermot P B; Cho, Judy H; Georges, Michel; Daly, Mark J; Barrett, Jeffrey C
2017-07-13
Inflammatory bowel diseases are chronic gastrointestinal inflammatory disorders that affect millions of people worldwide. Genome-wide association studies have identified 200 inflammatory bowel disease-associated loci, but few have been conclusively resolved to specific functional variants. Here we report fine-mapping of 94 inflammatory bowel disease loci using high-density genotyping in 67,852 individuals. We pinpoint 18 associations to a single causal variant with greater than 95% certainty, and an additional 27 associations to a single variant with greater than 50% certainty. These 45 variants are significantly enriched for protein-coding changes (n = 13), direct disruption of transcription-factor binding sites (n = 3), and tissue-specific epigenetic marks (n = 10), with the last category showing enrichment in specific immune cells among associations stronger in Crohn's disease and in gut mucosa among associations stronger in ulcerative colitis. The results of this study suggest that high-resolution fine-mapping in large samples can convert many discoveries from genome-wide association studies into statistically convincing causal variants, providing a powerful substrate for experimental elucidation of disease mechanisms.
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Verweij, Karin J H; Treur, Jorien L; Vink, Jacqueline M
2018-07-01
Epidemiological studies consistently show co-occurrence of use of different addictive substances. Whether these associations are causal or due to overlapping underlying influences remains an important question in addiction research. Methodological advances have made it possible to use published genetic associations to infer causal relationships between phenotypes. In this exploratory study, we used Mendelian randomization (MR) to examine the causality of well-established associations between nicotine, alcohol, caffeine and cannabis use. Two-sample MR was employed to estimate bidirectional causal effects between four addictive substances: nicotine (smoking initiation and cigarettes smoked per day), caffeine (cups of coffee per day), alcohol (units per week) and cannabis (initiation). Based on existing genome-wide association results we selected genetic variants associated with the exposure measure as an instrument to estimate causal effects. Where possible we applied sensitivity analyses (MR-Egger and weighted median) more robust to horizontal pleiotropy. Most MR tests did not reveal causal associations. There was some weak evidence for a causal positive effect of genetically instrumented alcohol use on smoking initiation and of cigarettes per day on caffeine use, but these were not supported by the sensitivity analyses. There was also some suggestive evidence for a positive effect of alcohol use on caffeine use (only with MR-Egger) and smoking initiation on cannabis initiation (only with weighted median). None of the suggestive causal associations survived corrections for multiple testing. Two-sample Mendelian randomization analyses found little evidence for causal relationships between nicotine, alcohol, caffeine and cannabis use. © 2018 Society for the Study of Addiction.
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Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY PERIODICALS, INC.
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Generalized functional linear models for gene-based case-control association studies.
Fan, Ruzong; Wang, Yifan; Mills, James L; Carter, Tonia C; Lobach, Iryna; Wilson, Alexander F; Bailey-Wilson, Joan E; Weeks, Daniel E; Xiong, Momiao
2014-11-01
By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene region are disease related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease datasets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. © 2014 WILEY PERIODICALS, INC.
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Generalized Functional Linear Models for Gene-based Case-Control Association Studies
Mills, James L.; Carter, Tonia C.; Lobach, Iryna; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Weeks, Daniel E.; Xiong, Momiao
2014-01-01
By using functional data analysis techniques, we developed generalized functional linear models for testing association between a dichotomous trait and multiple genetic variants in a genetic region while adjusting for covariates. Both fixed and mixed effect models are developed and compared. Extensive simulations show that Rao's efficient score tests of the fixed effect models are very conservative since they generate lower type I errors than nominal levels, and global tests of the mixed effect models generate accurate type I errors. Furthermore, we found that the Rao's efficient score test statistics of the fixed effect models have higher power than the sequence kernel association test (SKAT) and its optimal unified version (SKAT-O) in most cases when the causal variants are both rare and common. When the causal variants are all rare (i.e., minor allele frequencies less than 0.03), the Rao's efficient score test statistics and the global tests have similar or slightly lower power than SKAT and SKAT-O. In practice, it is not known whether rare variants or common variants in a gene are disease-related. All we can assume is that a combination of rare and common variants influences disease susceptibility. Thus, the improved performance of our models when the causal variants are both rare and common shows that the proposed models can be very useful in dissecting complex traits. We compare the performance of our methods with SKAT and SKAT-O on real neural tube defects and Hirschsprung's disease data sets. The Rao's efficient score test statistics and the global tests are more sensitive than SKAT and SKAT-O in the real data analysis. Our methods can be used in either gene-disease genome-wide/exome-wide association studies or candidate gene analyses. PMID:25203683
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Yavorska, Olena O; Burgess, Stephen
2017-12-01
MendelianRandomization is a software package for the R open-source software environment that performs Mendelian randomization analyses using summarized data. The core functionality is to implement the inverse-variance weighted, MR-Egger and weighted median methods for multiple genetic variants. Several options are available to the user, such as the use of robust regression, fixed- or random-effects models and the penalization of weights for genetic variants with heterogeneous causal estimates. Extensions to these methods, such as allowing for variants to be correlated, can be chosen if appropriate. Graphical commands allow summarized data to be displayed in an interactive graph, or the plotting of causal estimates from multiple methods, for comparison. Although the main method of data entry is directly by the user, there is also an option for allowing summarized data to be incorporated from the PhenoScanner database of genotype-phenotype associations. We hope to develop this feature in future versions of the package. The R software environment is available for download from [https://www.r-project.org/]. The MendelianRandomization package can be downloaded from the Comprehensive R Archive Network (CRAN) within R, or directly from [https://cran.r-project.org/web/packages/MendelianRandomization/]. Both R and the MendelianRandomization package are released under GNU General Public Licenses (GPL-2|GPL-3). © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Serum iron level and kidney function: a Mendelian randomization study.
Del Greco M, Fabiola; Foco, Luisa; Pichler, Irene; Eller, Philipp; Eller, Kathrin; Benyamin, Beben; Whitfield, John B; Pramstaller, Peter P; Thompson, John R; Pattaro, Cristian; Minelli, Cosetta
2017-02-01
Iron depletion is a known consequence of chronic kidney disease (CKD), but there is contradicting epidemiological evidence on whether iron itself affects kidney function and whether its effect is protective or detrimental in the general population. While epidemiological studies tend to be affected by confounding and reverse causation, Mendelian randomization (MR) can provide unconfounded estimates of causal effects by using genes as instruments. We performed an MR study of the effect of serum iron levels on estimated glomerular filtration rate (eGFR), using genetic variants known to be associated with iron. MR estimates of the effect of iron on eGFR were derived based on the association of each variant with iron and eGFR from two large genome-wide meta-analyses on 48 978 and 74 354 individuals. We performed a similar MR analysis for ferritin, which measures iron stored in the body, using variants associated with ferritin. A combined MR estimate across all variants showed a 1.3% increase in eGFR per standard deviation increase in iron (95% confidence interval 0.4–2.1%; P = 0.004). The results for ferritin were consistent with those for iron. Secondary MR analyses of the effects of iron and ferritin on CKD did not show significant associations but had very low statistical power. Our study suggests a protective effect of iron on kidney function in the general population. Further research is required to confirm this causal association, investigate it in study populations at higher risk of CKD and explore its underlying mechanism of action.
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USDA-ARS?s Scientific Manuscript database
Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a mor...
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Coassin, Stefan; Friedel, Salome; Köttgen, Anna; Lamina, Claudia; Kronenberg, Florian
2016-11-01
A recent observational study with almost 2 million men reported an association between low high-density lipoprotein (HDL) cholesterol and worse kidney function. The causality of this association would be strongly supported if genetic variants associated with HDL cholesterol were also associated with kidney function. We used 68 genetic variants (single-nucleotide polymorphisms [SNPs]) associated with HDL cholesterol in genome-wide association studies including >188 000 subjects and tested their association with estimated glomerular filtration rate (eGFR) using summary statistics from another genome-wide association studies meta-analysis of kidney function including ≤133 413 subjects. Fourteen of the 68 SNPs (21%) had a P value <0.05 compared with the 5% expected by chance (Binomial test P=5.8×10 - 6 ). After Bonferroni correction, 6 SNPs were still significantly associated with eGFR. The genetic variants with the strongest associations with HDL cholesterol concentrations were not the same as those with the strongest association with kidney function and vice versa. An evaluation of pleiotropy indicated that the effects of the HDL-associated SNPs on eGFR were not mediated by HDL cholesterol. In addition, we performed a Mendelian randomization analysis. This analysis revealed a positive but nonsignificant causal effect of HDL cholesterol-increasing variants on eGFR. In summary, our findings indicate that HDL cholesterol does not causally influence eGFR and propose pleiotropic effects on eGFR for some HDL cholesterol-associated SNPs. This may cause the observed association by mechanisms other than the mere HDL cholesterol concentration. © 2016 The Authors.
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Pardiñas, Antonio F.; Holmans, Peter; Pocklington, Andrew J.; Escott-Price, Valentina; Ripke, Stephan; Carrera, Noa; Legge, Sophie E.; Bishop, Sophie; Cameron, Darren; Hamshere, Marian L.; Han, Jun; Hubbard, Leon; Lynham, Amy; Mantripragada, Kiran; Rees, Elliott; MacCabe, James H.; McCarroll, Steven A.; Baune, Bernhard T.; Breen, Gerome; Byrne, Enda M.; Dannlowski, Udo; Eley, Thalia C.; Hayward, Caroline; Martin, Nicholas G.; McIntosh, Andrew M.; Plomin, Robert; Porteous, David J.; Wray, Naomi R.; Caballero, Armando; Geschwind, Daniel H.; Huckins, Laura M.; Ruderfer, Douglas M.; Santiago, Enrique; Sklar, Pamela; Stahl, Eli A.; Won, Hyejung; Agerbo, Esben; Als, Thomas D.; Andreassen, Ole A.; Bækvad-Hansen, Marie; Mortensen, Preben Bo; Pedersen, Carsten Bøcker; Børglum, Anders D.; Bybjerg-Grauholm, Jonas; Djurovic, Srdjan; Durmishi, Naser; Pedersen, Marianne Giørtz; Golimbet, Vera; Grove, Jakob; Hougaard, David M.; Mattheisen, Manuel; Molden, Espen; Mors, Ole; Nordentoft, Merete; Pejovic-Milovancevic, Milica; Sigurdsson, Engilbert; Silagadze, Teimuraz; Hansen, Christine Søholm; Stefansson, Kari; Stefansson, Hreinn; Steinberg, Stacy; Tosato, Sarah; Werge, Thomas; Collier, David A.; Rujescu, Dan; Kirov, George; Owen, Michael J.; O’Donovan, Michael C.; Walters, James T. R.
2018-01-01
Schizophrenia is a debilitating psychiatric condition often associated with poor quality of life and decreased life expectancy. Lack of progress in improving treatment outcomes has been attributed to limited knowledge of the underlying biology, although large-scale genomic studies have begun to provide insights. We report a new genome-wide association study of schizophrenia (11,260 cases and 24,542 controls), and through meta-analysis with existing data we identify 50 novel associated loci and 145 loci in total. Through integrating genomic fine-mapping with brain expression and chromosome conformation data, we identify candidate causal genes within 33 loci. We also show for the first time that the common variant association signal is highly enriched among genes that are under strong selective pressures. These findings provide new insights into the biology and genetic architecture of schizophrenia, highlight the importance of mutation-intolerant genes and suggest a mechanism by which common risk variants persist in the population. PMID:29483656
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Genetic architecture for human aggression: A study of gene-phenotype relationship in OMIM.
Zhang-James, Yanli; Faraone, Stephen V
2016-07-01
Genetic studies of human aggression have mainly focused on known candidate genes and pathways regulating serotonin and dopamine signaling and hormonal functions. These studies have taught us much about the genetics of human aggression, but no genetic locus has yet achieved genome-significance. We here present a review based on a paradoxical hypothesis that studies of rare, functional genetic variations can lead to a better understanding of the molecular mechanisms underlying complex multifactorial disorders such as aggression. We examined all aggression phenotypes catalogued in Online Mendelian Inheritance in Man (OMIM), an Online Catalog of Human Genes and Genetic Disorders. We identified 95 human disorders that have documented aggressive symptoms in at least one individual with a well-defined genetic variant. Altogether, we retrieved 86 causal genes. Although most of these genes had not been implicated in human aggression by previous studies, the most significantly enriched canonical pathways had been previously implicated in aggression (e.g., serotonin and dopamine signaling). Our findings provide strong evidence to support the causal role of these pathways in the pathogenesis of aggression. In addition, the novel genes and pathways we identified suggest additional mechanisms underlying the origins of human aggression. Genome-wide association studies with very large samples will be needed to determine if common variants in these genes are risk factors for aggression. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
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Gallo, Eduardo F; Posner, Jonathan
2016-01-01
Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterised by developmentally inappropriate levels of inattention and hyperactivity or impulsivity. The heterogeneity of its clinical manifestations and the differential responses to treatment and varied prognoses have long suggested myriad underlying causes. Over the past decade, clinical and basic research efforts have uncovered many behavioural and neurobiological alterations associated with ADHD, from genes to higher order neural networks. Here, we review the neurobiology of ADHD by focusing on neural circuits implicated in the disorder and discuss how abnormalities in circuitry relate to symptom presentation and treatment. We summarise the literature on genetic variants that are potentially related to the development of ADHD, and how these, in turn, might affect circuit function and relevant behaviours. Whether these underlying neurobiological factors are causally related to symptom presentation remains unresolved. Therefore, we assess efforts aimed at disentangling issues of causality, and showcase the shifting research landscape towards endophenotype refinement in clinical and preclinical settings. Furthermore, we review approaches being developed to understand the neurobiological underpinnings of this complex disorder including the use of animal models, neuromodulation, and pharmaco-imaging studies. PMID:27183902
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Hu, Hao; Wienker, Thomas F; Musante, Luciana; Kalscheuer, Vera M; Kahrizi, Kimia; Najmabadi, Hossein; Ropers, H Hilger
2014-12-01
Next-generation sequencing has greatly accelerated the search for disease-causing defects, but even for experts the data analysis can be a major challenge. To facilitate the data processing in a clinical setting, we have developed a novel medical resequencing analysis pipeline (MERAP). MERAP assesses the quality of sequencing, and has optimized capacity for calling variants, including single-nucleotide variants, insertions and deletions, copy-number variation, and other structural variants. MERAP identifies polymorphic and known causal variants by filtering against public domain databases, and flags nonsynonymous and splice-site changes. MERAP uses a logistic model to estimate the causal likelihood of a given missense variant. MERAP considers the relevant information such as phenotype and interaction with known disease-causing genes. MERAP compares favorably with GATK, one of the widely used tools, because of its higher sensitivity for detecting indels, its easy installation, and its economical use of computational resources. Upon testing more than 1,200 individuals with mutations in known and novel disease genes, MERAP proved highly reliable, as illustrated here for five families with disease-causing variants. We believe that the clinical implementation of MERAP will expedite the diagnostic process of many disease-causing defects. © 2014 WILEY PERIODICALS, INC.
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Bailey-Wilson, Joan E.; Brennan, Jennifer S.; Bull, Shelley B; Culverhouse, Robert; Kim, Yoonhee; Jiang, Yuan; Jung, Jeesun; Li, Qing; Lamina, Claudia; Liu, Ying; Mägi, Reedik; Niu, Yue S.; Simpson, Claire L.; Wang, Libo; Yilmaz, Yildiz E.; Zhang, Heping; Zhang, Zhaogong
2012-01-01
Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors. PMID:22128066
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Causality networks from multivariate time series and application to epilepsy.
Siggiridou, Elsa; Koutlis, Christos; Tsimpiris, Alkiviadis; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris
2015-08-01
Granger causality and variants of this concept allow the study of complex dynamical systems as networks constructed from multivariate time series. In this work, a large number of Granger causality measures used to form causality networks from multivariate time series are assessed. For this, realizations on high dimensional coupled dynamical systems are considered and the performance of the Granger causality measures is evaluated, seeking for the measures that form networks closest to the true network of the dynamical system. In particular, the comparison focuses on Granger causality measures that reduce the state space dimension when many variables are observed. Further, the linear and nonlinear Granger causality measures of dimension reduction are compared to a standard Granger causality measure on electroencephalographic (EEG) recordings containing episodes of epileptiform discharges.
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Kullback-Leibler divergence for detection of rare haplotype common disease association.
Lin, Shili
2015-11-01
Rare haplotypes may tag rare causal variants of common diseases; hence, detection of such rare haplotypes may also contribute to our understanding of complex disease etiology. Because rare haplotypes frequently result from common single-nucleotide polymorphisms (SNPs), focusing on rare haplotypes is much more economical compared with using rare single-nucleotide variants (SNVs) from sequencing, as SNPs are available and 'free' from already amassed genome-wide studies. Further, associated haplotypes may shed light on the underlying disease causal mechanism, a feat unmatched by SNV-based collapsing methods. In recent years, data mining approaches have been adapted to detect rare haplotype association. However, as they rely on an assumed underlying disease model and require the specification of a null haplotype, results can be erroneous if such assumptions are violated. In this paper, we present a haplotype association method based on Kullback-Leibler divergence (hapKL) for case-control samples. The idea is to compare haplotype frequencies for the cases versus the controls by computing symmetrical divergence measures. An important property of such measures is that both the frequencies and logarithms of the frequencies contribute in parallel, thus balancing the contributions from rare and common, and accommodating both deleterious and protective, haplotypes. A simulation study under various scenarios shows that hapKL has well-controlled type I error rates and good power compared with existing data mining methods. Application of hapKL to age-related macular degeneration (AMD) shows a strong association of the complement factor H (CFH) gene with AMD, identifying several individual rare haplotypes with strong signals.
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Torrezan, Giovana T; de Almeida, Fernanda G Dos Santos R; Figueiredo, Márcia C P; Barros, Bruna D de Figueiredo; de Paula, Cláudia A A; Valieris, Renan; de Souza, Jorge E S; Ramalho, Rodrigo F; da Silva, Felipe C C; Ferreira, Elisa N; de Nóbrega, Amanda F; Felicio, Paula S; Achatz, Maria I; de Souza, Sandro J; Palmero, Edenir I; Carraro, Dirce M
2018-01-01
Pathogenic variants in known breast cancer (BC) predisposing genes explain only about 30% of Hereditary Breast Cancer (HBC) cases, whereas the underlying genetic factors for most families remain unknown. Here, we used whole-exome sequencing (WES) to identify genetic variants associated to HBC in 17 patients of Brazil with familial BC and negative for causal variants in major BC risk genes ( BRCA1/2, TP53 , and CHEK2 c.1100delC). First, we searched for rare variants in 27 known HBC genes and identified two patients harboring truncating pathogenic variants in ATM and BARD1 . For the remaining 15 negative patients, we found a substantial vast number of rare genetic variants. Thus, for selecting the most promising variants we used functional-based variant prioritization, followed by NGS validation, analysis in a control group, cosegregation analysis in one family and comparison with previous WES studies, shrinking our list to 23 novel BC candidate genes, which were evaluated in an independent cohort of 42 high-risk BC patients. Rare and possibly damaging variants were identified in 12 candidate genes in this cohort, including variants in DNA repair genes ( ERCC1 and SXL4 ) and other cancer-related genes ( NOTCH2, ERBB2, MST1R , and RAF1 ). Overall, this is the first WES study applied for identifying novel genes associated to HBC in Brazilian patients, in which we provide a set of putative BC predisposing genes. We also underpin the value of using WES for assessing the complex landscape of HBC susceptibility, especially in less characterized populations.
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A splice variant in the ACSL5 gene relates migraine with fatty acid activation in mitochondria
Matesanz, Fuencisla; Fedetz, María; Barrionuevo, Cristina; Karaky, Mohamad; Catalá-Rabasa, Antonio; Potenciano, Victor; Bello-Morales, Raquel; López-Guerrero, Jose-Antonio; Alcina, Antonio
2016-01-01
Genome-wide association studies (GWAS) in migraine are providing the molecular basis of this heterogeneous disease, but the understanding of its aetiology is still incomplete. Although some biomarkers have currently been accepted for migraine, large amount of studies for identifying new ones is needed. The migraine-associated variant rs12355831:A>G (P=2 × 10−6), described in a GWAS of the International Headache Genetic Consortium, is localized in a non-coding sequence with unknown function. We sought to identify the causal variant and the genetic mechanism involved in the migraine risk. To this end, we integrated data of RNA sequences from the Genetic European Variation in Health and Disease (GEUVADIS) and genotypes from 1000 GENOMES of 344 lymphoblastoid cell lines (LCLs), to determine the expression quantitative trait loci (eQTLs) in the region. We found that the migraine-associated variant belongs to a linkage disequilibrium block associated with the expression of an acyl-coenzyme A synthetase 5 (ACSL5) transcript lacking exon 20 (ACSL5-Δ20). We showed by exon-skipping assay a direct causality of rs2256368-G in the exon 20 skipping of approximately 20 to 40% of ACSL5 RNA molecules. In conclusion, we identified the functional variant (rs2256368:A>G) affecting ACSL5 exon 20 skipping, as a causal factor linked to the migraine-associated rs12355831:A>G, suggesting that the activation of long-chain fatty acids by the spliced ACSL5-Δ20 molecules, a mitochondrial located enzyme, is involved in migraine pathology. PMID:27189022
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Role of Adiponectin in Coronary Heart Disease Risk
Lawlor, Debbie A.; de Oliveira, Cesar; White, Jon; Horta, Bernardo Lessa; Barros, Aluísio J.D.
2016-01-01
Rationale: Hypoadiponectinemia correlates with several coronary heart disease (CHD) risk factors. However, it is unknown whether adiponectin is causally implicated in CHD pathogenesis. Objective: We aimed to investigate the causal effect of adiponectin on CHD risk. Methods and Results: We undertook a Mendelian randomization study using data from genome-wide association studies consortia. We used the ADIPOGen consortium to identify genetic variants that could be used as instrumental variables for the effect of adiponectin. Data on the association of these genetic variants with CHD risk were obtained from CARDIoGRAM (22 233 CHD cases and 64 762 controls of European ancestry) and from CARDIoGRAMplusC4D Metabochip (63 746 cases and 130 681 controls; ≈ 91% of European ancestry) consortia. Data on the association of genetic variants with adiponectin levels and with CHD were combined to estimate the influence of blood adiponectin on CHD risk. In the conservative approach (restricted to using variants within the adiponectin gene as instrumental variables), each 1 U increase in log blood adiponectin concentration was associated with an odds ratio for CHD of 0.83 (95% confidence interval, 0.68–1.01) in CARDIoGRAM and 0.97 (95% confidence interval, 0.84–1.12) in CARDIoGRAMplusC4D Metabochip. Findings from the liberal approach (including variants in any locus across the genome) indicated a protective effect of adiponectin that was attenuated to the null after adjustment for known CHD predictors. Conclusions: Overall, our findings do not support a causal role of adiponectin levels in CHD pathogenesis. PMID:27252388
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An update on the genetic architecture of hyperuricemia and gout.
Merriman, Tony R
2015-04-10
Genome-wide association studies that scan the genome for common genetic variants associated with phenotype have greatly advanced medical knowledge. Hyperuricemia is no exception, with 28 loci identified. However, genetic control of pathways determining gout in the presence of hyperuricemia is still poorly understood. Two important pathways determining hyperuricemia have been confirmed (renal and gut excretion of uric acid with glycolysis now firmly implicated). Major urate loci are SLC2A9 and ABCG2. Recent studies show that SLC2A9 is involved in renal and gut excretion of uric acid and is implicated in antioxidant defense. Although etiological variants at SLC2A9 are yet to be identified, it is clear that considerable genetic complexity exists at the SLC2A9 locus, with multiple statistically independent genetic variants and local epistatic interactions. The positions of implicated genetic variants within or near chromatin regions involved in transcriptional control suggest that this mechanism (rather than structural changes in SLC2A9) is important in regulating the activity of SLC2A9. ABCG2 is involved primarily in extra-renal uric acid under-excretion with the etiological variant influencing expression. At the other 26 loci, probable causal genes can be identified at three (PDZK1, SLC22A11, and INHBB) with strong candidates at a further 10 loci. Confirmation of the causal gene will require a combination of re-sequencing, trans-ancestral mapping, and correlation of genetic association data with expression data. As expected, the urate loci associate with gout, although inconsistent effect sizes for gout require investigation. Finally, there has been no genome-wide association study using clinically ascertained cases to investigate the causes of gout in the presence of hyperuricemia. In such a study, use of asymptomatic hyperurcemic controls would be expected to increase the ability to detect genetic associations with gout.
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Corbin, Laura J; Tan, Vanessa Y; Hughes, David A; Wade, Kaitlin H; Paul, Dirk S; Tansey, Katherine E; Butcher, Frances; Dudbridge, Frank; Howson, Joanna M; Jallow, Momodou W; John, Catherine; Kingston, Nathalie; Lindgren, Cecilia M; O'Donavan, Michael; O'Rahilly, Stephen; Owen, Michael J; Palmer, Colin N A; Pearson, Ewan R; Scott, Robert A; van Heel, David A; Whittaker, John; Frayling, Tim; Tobin, Martin D; Wain, Louise V; Smith, George Davey; Evans, David M; Karpe, Fredrik; McCarthy, Mark I; Danesh, John; Franks, Paul W; Timpson, Nicholas J
2018-02-19
Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.
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Education and myopia: assessing the direction of causality by mendelian randomisation.
Mountjoy, Edward; Davies, Neil M; Plotnikov, Denis; Smith, George Davey; Rodriguez, Santiago; Williams, Cathy E; Guggenheim, Jeremy A; Atan, Denize
2018-06-06
To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education. Bidirectional, two sample mendelian randomisation study. Publically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively. 67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error. Mendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error. Conventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of -0.18 dioptres/y (95% confidence interval -0.19 to -0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: -0.27 dioptres/y (-0.37 to -0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error -0.008 y/dioptre, 95% confidence interval -0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least -1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates. This study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Treur, Jorien L; Gibson, Mark; Taylor, Amy E; Rogers, Peter J; Munafò, Marcus R
2018-04-22
Observationally, higher caffeine consumption is associated with poorer sleep and insomnia. We investigated whether these associations are a result of shared genetic risk factors and/or (possibly bidirectional) causal effects. Summary-level data were available from genome-wide association studies on caffeine intake (n = 91 462), plasma caffeine and caffeine metabolic rate (n = 9876), sleep duration and chronotype (being a "morning" versus an "evening" person) (n = 128 266), and insomnia complaints (n = 113 006). First, genetic correlations were calculated, reflecting the extent to which genetic variants influencing caffeine consumption and those influencing sleep overlap. Next, causal effects were estimated with bidirectional, two-sample Mendelian randomization. This approach utilizes the genetic variants most robustly associated with an exposure variable as an "instrument" to test causal effects. Estimates from individual variants were combined using inverse-variance weighted meta-analysis, weighted median regression and MR-Egger regression. We found no clear evidence for a genetic correlation between caffeine intake and sleep duration (rg = 0.000, p = .998), chronotype (rg = 0.086, p = .192) or insomnia complaints (rg = -0.034, p = .700). For plasma caffeine and caffeine metabolic rate, genetic correlations could not be calculated because of the small sample size. Mendelian randomization did not support causal effects of caffeine intake on sleep, or vice versa. There was weak evidence that higher plasma caffeine levels causally decrease the odds of being a morning person. Although caffeine may acutely affect sleep when taken shortly before bedtime, our findings suggest that a sustained pattern of high caffeine consumption is more likely to be associated with poorer sleep through shared environmental factors. Future research should identify such environments, which could aid the development of interventions to improve sleep. © 2018 The Authors. Journal of Sleep Research published by John Wiley & Sons Ltd on behalf of European Sleep Research Society.
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Bowden, Jack; Del Greco M, Fabiola; Minelli, Cosetta; Davey Smith, George; Sheehan, Nuala A; Thompson, John R
2016-12-01
: MR-Egger regression has recently been proposed as a method for Mendelian randomization (MR) analyses incorporating summary data estimates of causal effect from multiple individual variants, which is robust to invalid instruments. It can be used to test for directional pleiotropy and provides an estimate of the causal effect adjusted for its presence. MR-Egger regression provides a useful additional sensitivity analysis to the standard inverse variance weighted (IVW) approach that assumes all variants are valid instruments. Both methods use weights that consider the single nucleotide polymorphism (SNP)-exposure associations to be known, rather than estimated. We call this the `NO Measurement Error' (NOME) assumption. Causal effect estimates from the IVW approach exhibit weak instrument bias whenever the genetic variants utilized violate the NOME assumption, which can be reliably measured using the F-statistic. The effect of NOME violation on MR-Egger regression has yet to be studied. An adaptation of the I2 statistic from the field of meta-analysis is proposed to quantify the strength of NOME violation for MR-Egger. It lies between 0 and 1, and indicates the expected relative bias (or dilution) of the MR-Egger causal estimate in the two-sample MR context. We call it IGX2 . The method of simulation extrapolation is also explored to counteract the dilution. Their joint utility is evaluated using simulated data and applied to a real MR example. In simulated two-sample MR analyses we show that, when a causal effect exists, the MR-Egger estimate of causal effect is biased towards the null when NOME is violated, and the stronger the violation (as indicated by lower values of IGX2 ), the stronger the dilution. When additionally all genetic variants are valid instruments, the type I error rate of the MR-Egger test for pleiotropy is inflated and the causal effect underestimated. Simulation extrapolation is shown to substantially mitigate these adverse effects. We demonstrate our proposed approach for a two-sample summary data MR analysis to estimate the causal effect of low-density lipoprotein on heart disease risk. A high value of IGX2 close to 1 indicates that dilution does not materially affect the standard MR-Egger analyses for these data. : Care must be taken to assess the NOME assumption via the IGX2 statistic before implementing standard MR-Egger regression in the two-sample summary data context. If IGX2 is sufficiently low (less than 90%), inferences from the method should be interpreted with caution and adjustment methods considered. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Chen, Wenan; McDonnell, Shannon K; Thibodeau, Stephen N; Tillmans, Lori S; Schaid, Daniel J
2016-11-01
Functional annotations have been shown to improve both the discovery power and fine-mapping accuracy in genome-wide association studies. However, the optimal strategy to incorporate the large number of existing annotations is still not clear. In this study, we propose a Bayesian framework to incorporate functional annotations in a systematic manner. We compute the maximum a posteriori solution and use cross validation to find the optimal penalty parameters. By extending our previous fine-mapping method CAVIARBF into this framework, we require only summary statistics as input. We also derived an exact calculation of Bayes factors using summary statistics for quantitative traits, which is necessary when a large proportion of trait variance is explained by the variants of interest, such as in fine mapping expression quantitative trait loci (eQTL). We compared the proposed method with PAINTOR using different strategies to combine annotations. Simulation results show that the proposed method achieves the best accuracy in identifying causal variants among the different strategies and methods compared. We also find that for annotations with moderate effects from a large annotation pool, screening annotations individually and then combining the top annotations can produce overly optimistic results. We applied these methods on two real data sets: a meta-analysis result of lipid traits and a cis-eQTL study of normal prostate tissues. For the eQTL data, incorporating annotations significantly increased the number of potential causal variants with high probabilities. Copyright © 2016 by the Genetics Society of America.
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USDA-ARS?s Scientific Manuscript database
Fine-mapping of causal variants is becoming feasible for complex traits in livestock GWAS, as an increasing number of animals are sequenced. Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on small reference populations of sequenced animals. ...
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USDA-ARS?s Scientific Manuscript database
Major whole genome sequencing projects promise to identify rare and causal variants within livestock species; however, the efficient selection of animals for sequencing remains a major problem within these surveys. The goal of this project was to develop a library of high accuracy genetic variants f...
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USDA-ARS?s Scientific Manuscript database
Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on reference populations of sequenced animals. With the implementation of the 1000 Bull Genomes Project and increasing numbers of animals sequenced, fine-mapping of causal variants is becoming f...
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Pausch, Hubert; Wurmser, Christine; Reinhardt, Friedrich; Emmerling, Reiner; Fries, Ruedi
2015-06-01
Most association studies for pinpointing trait-associated variants are performed within breed. The availability of sequence data from key ancestors of several cattle breeds now enables immediate assessment of the frequency of trait-associated variants in populations different from the mapping population and their imputation into large validation populations. The objective of this study was to validate the effects of 4 putatively causative variants on milk production traits, male fertility, and stature in German Fleckvieh and Holstein-Friesian animals using targeted sequence imputation. We used whole-genome sequence data of 456 animals to impute 4 missense mutations in DGAT1, GHR, PRLR, and PROP1 into 10,363 Fleckvieh and 8,812 Holstein animals. The accuracy of the imputed genotypes exceeded 95% for all variants. Association testing with imputed variants revealed consistent antagonistic effects of the DGAT1 p.A232K and GHR p.F279Y variants on milk yield and protein and fat contents, respectively, in both breeds. The allele frequency of both polymorphisms has changed considerably in the past 20 yr, indicating that they were targets of recent selection for milk production traits. The PRLR p.S18N variant was associated with yield traits in Fleckvieh but not in Holstein, suggesting that it may be in linkage disequilibrium with a mutation affecting yield traits rather than being causal. The reported effects of the PROP1 p.H173R variant on milk production, male fertility, and stature could not be confirmed. Our results demonstrate that population-wide imputation of candidate causal variants from sequence data is feasible, enabling their rapid validation in large independent populations. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Genomic selection in domestic animals: Principles, applications and perspectives.
Boichard, Didier; Ducrocq, Vincent; Croiseau, Pascal; Fritz, Sébastien
2016-01-01
The principles of genomic selection are described, with the main factors affecting its efficiency and the assumptions underlying the different models proposed. The reasons of its fast adoption in dairy cattle are explained and the conditions of its application to other species are discussed. Perspectives of development include: selection for new traits and new breeding objectives; adoption of more robust approaches based on information on causal variants; predictions of genotype×environment interactions. Copyright © 2016 Académie des sciences. Published by Elsevier SAS. All rights reserved.
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Entanglement renormalization, quantum error correction, and bulk causality
NASA Astrophysics Data System (ADS)
Kim, Isaac H.; Kastoryano, Michael J.
2017-04-01
Entanglement renormalization can be viewed as an encoding circuit for a family of approximate quantum error correcting codes. The logical information becomes progres-sively more well-protected against erasure errors at larger length scales. In particular, an approximate variant of holographic quantum error correcting code emerges at low energy for critical systems. This implies that two operators that are largely separated in scales behave as if they are spatially separated operators, in the sense that they obey a Lieb-Robinson type locality bound under a time evolution generated by a local Hamiltonian.
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Burgess, Stephen; Zuber, Verena; Valdes-Marquez, Elsa; Sun, Benjamin B; Hopewell, Jemma C
2017-12-01
Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be used to assess this causal relationship. However, using too many genetic variants in the analysis can lead to spurious estimates and inflated Type 1 error rates. But if only a few genetic variants are used, then the majority of the data is ignored and estimates are highly sensitive to the particular choice of variants. We propose an approach based on summarized data only (genetic association and correlation estimates) that uses principal components analysis to form instruments. This approach has desirable theoretical properties: it takes the totality of data into account and does not suffer from numerical instabilities. It also has good properties in simulation studies: it is not particularly sensitive to varying the genetic variants included in the analysis or the genetic correlation matrix, and it does not have greatly inflated Type 1 error rates. Overall, the method gives estimates that are less precise than those from variable selection approaches (such as using a conditional analysis or pruning approach to select variants), but are more robust to seemingly arbitrary choices in the variable selection step. Methods are illustrated by an example using genetic associations with testosterone for 320 genetic variants to assess the effect of sex hormone related pathways on coronary artery disease risk, in which variable selection approaches give inconsistent inferences. © 2017 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.
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Inheritance-mode specific pathogenicity prioritization (ISPP) for human protein coding genes.
Hsu, Jacob Shujui; Kwan, Johnny S H; Pan, Zhicheng; Garcia-Barcelo, Maria-Mercè; Sham, Pak Chung; Li, Miaoxin
2016-10-15
Exome sequencing studies have facilitated the detection of causal genetic variants in yet-unsolved Mendelian diseases. However, the identification of disease causal genes among a list of candidates in an exome sequencing study is still not fully settled, and it is often difficult to prioritize candidate genes for follow-up studies. The inheritance mode provides crucial information for understanding Mendelian diseases, but none of the existing gene prioritization tools fully utilize this information. We examined the characteristics of Mendelian disease genes under different inheritance modes. The results suggest that Mendelian disease genes with autosomal dominant (AD) inheritance mode are more haploinsufficiency and de novo mutation sensitive, whereas those autosomal recessive (AR) genes have significantly more non-synonymous variants and regulatory transcript isoforms. In addition, the X-linked (XL) Mendelian disease genes have fewer non-synonymous and synonymous variants. As a result, we derived a new scoring system for prioritizing candidate genes for Mendelian diseases according to the inheritance mode. Our scoring system assigned to each annotated protein-coding gene (N = 18 859) three pathogenic scores according to the inheritance mode (AD, AR and XL). This inheritance mode-specific framework achieved higher accuracy (area under curve = 0.84) in XL mode. The inheritance-mode specific pathogenicity prioritization (ISPP) outperformed other well-known methods including Haploinsufficiency, Recessive, Network centrality, Genic Intolerance, Gene Damage Index and Gene Constraint scores. This systematic study suggests that genes manifesting disease inheritance modes tend to have unique characteristics. ISPP is included in KGGSeq v1.0 (http://grass.cgs.hku.hk/limx/kggseq/), and source code is available from (https://github.com/jacobhsu35/ISPP.git). mxli@hku.hkSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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van Heemst, Jurgen; Huizinga, Tom J W; van der Woude, Diane; Toes, René E M
2015-05-01
To provide an update on and the context of the recent findings obtained with novel statistical methods on the association of the human leukocyte antigen (HLA) locus with rheumatic diseases. Novel single nucleotide polymorphism fine-mapping data obtained for the HLA locus have indicated the strongest association with amino acid positions 11 and 13 of HLA-DRB1 molecule for several rheumatic diseases. On the basis of these data, a dominant role for position 11/13 in driving the association with these diseases is proposed and the identification of causal variants in the HLA region in relation to disease susceptibility implicated. The HLA class II locus is the most important risk factor for several rheumatic diseases. Recently, new statistical approaches have identified previously unrecognized amino acid positions in the HLA-DR molecule that associate with anticitrullinated protein antibody-negative and anticitrullinated protein antibody-positive rheumatoid arthritis. Likewise, similar findings have been made for other rheumatic conditions such as giant-cell arteritis and systemic lupus erythematosus. Interestingly, all these studies point toward an association with the same amino acid positions: amino acid positions 11 and 13 of the HLA-DR β chain. As both these positions influence peptide binding by HLA-DR and have been implicated in antigen presentation, the novel fine-mapping approach is proposed to map causal variants in the HLA region relevant to rheumatoid arthritis and several rheumatic diseases. If these interpretations are correct, they would direct the biological research aiming to address the explanation for the HLA-disease association. Here, we provide an overview of the recent findings and evidence from literature that, although relevant new insights have been obtained on HLA-disease associations, the interpretation of the biological role of these amino acids as causal variants explaining that such associations should be taken with caution.
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El Malti, Rajae; Liu, Hui; Doray, Bérénice; Thauvin, Christel; Maltret, Alice; Dauphin, Claire; Gonçalves-Rocha, Miguel; Teboul, Michel; Blanchet, Patricia; Roume, Joëlle; Gronier, Céline; Ducreux, Corinne; Veyrier, Magali; Marçon, François; Acar, Philippe; Lusson, Jean-René; Levy, Marilyne; Beyler, Constance; Vigneron, Jacqueline; Cordier-Alex, Marie-Pierre; Heitz, François; Sanlaville, Damien; Bonnet, Damien; Bouvagnet, Patrice
2016-01-01
The etiology of congenital heart defect (CHD) combines environmental and genetic factors. So far, there were studies reporting on the screening of a single gene on unselected CHD or on familial cases selected for specific CHD types. Our goal was to systematically screen a proband of familial cases of CHD on a set of genetic tests to evaluate the prevalence of disease-causing variant identification. A systematic screening of GATA4, NKX2-5, ZIC3 and Multiplex ligation-dependent probe amplification (MLPA) P311 Kit was setup on the proband of 154 families with at least two cases of non-syndromic CHD. Additionally, ELN screening was performed on families with supravalvular arterial stenosis. Twenty-two variants were found, but segregation analysis confirmed unambiguously the causality of 16 variants: GATA4 (1 ×), NKX2-5 (6 ×), ZIC3 (3 ×), MLPA (2 ×) and ELN (4 ×). Therefore, this approach was able to identify the causal variant in 10.4% of familial CHD cases. This study demonstrated the existence of a de novo variant even in familial CHD cases and the impact of CHD variants on adult cardiac condition even in the absence of CHD. This study showed that the systematic screening of genetic factors is useful in familial CHD cases with up to 10.4% elucidated cases. When successful, it drastically improved genetic counseling by discovering unaffected variant carriers who are at risk of transmitting their variant and are also exposed to develop cardiac complications during adulthood thus prompting long-term cardiac follow-up. This study provides an important baseline at dawning of the next-generation sequencing era. PMID:26014430
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Causal Modeling the Delayed-Choice Experiment
NASA Astrophysics Data System (ADS)
Chaves, Rafael; Lemos, Gabriela Barreto; Pienaar, Jacques
2018-05-01
Wave-particle duality has become one of the flagships of quantum mechanics. This counterintuitive concept is highlighted in a delayed-choice experiment, where the experimental setup that reveals either the particle or wave nature of a quantum system is decided after the system has entered the apparatus. Here we consider delayed-choice experiments from the perspective of device-independent causal models and show their equivalence to a prepare-and-measure scenario. Within this framework, we consider Wheeler's original proposal and its variant using a quantum control and show that a simple classical causal model is capable of reproducing the quantum mechanical predictions. Nonetheless, among other results, we show that, in a slight variant of Wheeler's gedanken experiment, a photon in an interferometer can indeed generate statistics incompatible with any nonretrocausal hidden variable model, whose dimensionality is the same as that of the quantum system it is supposed to mimic. Our proposal tolerates arbitrary losses and inefficiencies, making it specially suited to loophole-free experimental implementations.
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A plausibly causal functional lupus-associated risk variant in the STAT1-STAT4 locus.
Patel, Zubin; Lu, Xiaoming; Miller, Daniel; Forney, Carmy R; Lee, Joshua; Lynch, Arthur; Schroeder, Connor; Parks, Lois; Magnusen, Albert F; Chen, Xiaoting; Pujato, Mario; Maddox, Avery; Zoller, Erin E; Namjou, Bahram; Brunner, Hermine I; Henrickson, Michael; Huggins, Jennifer L; Williams, Adrienne H; Ziegler, Julie T; Comeau, Mary E; Marion, Miranda C; Glenn, Stuart B; Adler, Adam; Shen, Nan; Nath, Swapan K; Stevens, Anne M; Freedman, Barry I; Pons-Estel, Bernardo A; Tsao, Betty P; Jacob, Chaim O; Kamen, Diane L; Brown, Elizabeth E; Gilkeson, Gary S; Alarcón, Graciela S; Martin, Javier; Reveille, John D; Anaya, Juan-Manuel; James, Judith A; Sivils, Kathy L; Criswell, Lindsey A; Vilá, Luis M; Petri, Michelle; Scofield, R Hal; Kimberly, Robert P; Edberg, Jeffrey C; Ramsey-Goldman, Rosalind; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol; Boackle, Susan A; Cunninghame Graham, Deborah; Vyse, Timothy J; Merrill, Joan T; Niewold, Timothy B; Ainsworth, Hannah C; Silverman, Earl D; Weisman, Michael H; Wallace, Daniel J; Raj, Prithvi; Guthridge, Joel M; Gaffney, Patrick M; Kelly, Jennifer A; Alarcón-Riquelme, Marta E; Langefeld, Carl D; Wakeland, Edward K; Kaufman, Kenneth M; Weirauch, Matthew T; Harley, John B; Kottyan, Leah C
2018-04-18
Systemic Lupus Erythematosus (SLE or lupus) (OMIM: 152700) is a chronic autoimmune disease with debilitating inflammation that affects multiple organ systems. The STAT1-STAT4 locus is one of the first and most highly-replicated genetic loci associated with lupus risk. We performed a fine-mapping study to identify plausible causal variants within the STAT1-STAT4 locus associated with increased lupus disease risk. Using complementary frequentist and Bayesian approaches in trans-ancestral Discovery and Replication cohorts, we found one variant whose association with lupus risk is supported across ancestries in both the Discovery and Replication cohorts: rs11889341. In B cell lines from patients with lupus and healthy controls, the lupus risk allele of rs11889341 was associated with increased STAT1 expression. We demonstrated that the transcription factor HMGA1, a member of the HMG transcription factor family with an AT-hook DNA-binding domain, has enriched binding to the risk allele compared to the non-risk allele of rs11889341. We identified a genotype-dependent repressive element in the DNA within the intron of STAT4 surrounding rs11889341. Consistent with expression quantitative trait locus (eQTL) analysis, the lupus risk allele of rs11889341 decreased the activity of this putative repressor. Altogether, we present a plausible molecular mechanism for increased lupus risk at the STAT1-STAT4 locus in which the risk allele of rs11889341, the most probable causal variant, leads to elevated STAT1 expression in B cells due to decreased repressor activity mediated by increased binding of HMGA1.
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Guo, Michael; Liu, Zun; Willen, Jessie; Shaw, Cameron P; Richard, Daniel; Jagoda, Evelyn; Doxey, Andrew C; Hirschhorn, Joel; Capellini, Terence D
2017-12-05
GWAS have identified hundreds of height-associated loci. However, determining causal mechanisms is challenging, especially since height-relevant tissues (e.g. growth plates) are difficult to study. To uncover mechanisms by which height GWAS variants function, we performed epigenetic profiling of murine femoral growth plates. The profiled open chromatin regions recapitulate known chondrocyte and skeletal biology, are enriched at height GWAS loci, particularly near differentially expressed growth plate genes, and enriched for binding motifs of transcription factors with roles in chondrocyte biology. At specific loci, our analyses identified compelling mechanisms for GWAS variants. For example, at CHSY1 , we identified a candidate causal variant (rs9920291) overlapping an open chromatin region. Reporter assays demonstrated that rs9920291 shows allelic regulatory activity, and CRISPR/Cas9 targeting of human chondrocytes demonstrates that the region regulates CHSY1 expression. Thus, integrating biologically relevant epigenetic information (here, from growth plates) with genetic association results can identify biological mechanisms important for human growth.
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The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.
Astle, William J; Elding, Heather; Jiang, Tao; Allen, Dave; Ruklisa, Dace; Mann, Alice L; Mead, Daniel; Bouman, Heleen; Riveros-Mckay, Fernando; Kostadima, Myrto A; Lambourne, John J; Sivapalaratnam, Suthesh; Downes, Kate; Kundu, Kousik; Bomba, Lorenzo; Berentsen, Kim; Bradley, John R; Daugherty, Louise C; Delaneau, Olivier; Freson, Kathleen; Garner, Stephen F; Grassi, Luigi; Guerrero, Jose; Haimel, Matthias; Janssen-Megens, Eva M; Kaan, Anita; Kamat, Mihir; Kim, Bowon; Mandoli, Amit; Marchini, Jonathan; Martens, Joost H A; Meacham, Stuart; Megy, Karyn; O'Connell, Jared; Petersen, Romina; Sharifi, Nilofar; Sheard, Simon M; Staley, James R; Tuna, Salih; van der Ent, Martijn; Walter, Klaudia; Wang, Shuang-Yin; Wheeler, Eleanor; Wilder, Steven P; Iotchkova, Valentina; Moore, Carmel; Sambrook, Jennifer; Stunnenberg, Hendrik G; Di Angelantonio, Emanuele; Kaptoge, Stephen; Kuijpers, Taco W; Carrillo-de-Santa-Pau, Enrique; Juan, David; Rico, Daniel; Valencia, Alfonso; Chen, Lu; Ge, Bing; Vasquez, Louella; Kwan, Tony; Garrido-Martín, Diego; Watt, Stephen; Yang, Ying; Guigo, Roderic; Beck, Stephan; Paul, Dirk S; Pastinen, Tomi; Bujold, David; Bourque, Guillaume; Frontini, Mattia; Danesh, John; Roberts, David J; Ouwehand, Willem H; Butterworth, Adam S; Soranzo, Nicole
2016-11-17
Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal. Copyright © 2016 Elsevier Inc. All rights reserved.
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Pharmacogenetic testing through the direct-to-consumer genetic testing company 23andMe.
Lu, Mengfei; Lewis, Cathryn M; Traylor, Matthew
2017-06-19
Rapid advances in scientific research have led to an increase in public awareness of genetic testing and pharmacogenetics. Direct-to-consumer (DTC) genetic testing companies, such as 23andMe, allow consumers to access their genetic information directly through an online service without the involvement of healthcare professionals. Here, we evaluate the clinical relevance of pharmacogenetic tests reported by 23andMe in their UK tests. The research papers listed under each 23andMe report were evaluated, extracting information on effect size, sample size and ethnicity. A wider literature search was performed to provide a fuller assessment of the pharmacogenetic test and variants were matched to FDA recommendations. Additional evidence from CPIC guidelines, PharmGKB, and Dutch Pharmacogenetics Working Group was reviewed to determine current clinical practice. The value of the tests across ethnic groups was determined, including information on linkage disequilibrium between the tested SNP and causal pharmacogenetic variant, where relevant. 23andMe offers 12 pharmacogenetic tests to their UK customers, some of which are in standard clinical practice, and others which are less widely applied. The clinical validity and clinical utility varies extensively between tests. The variants tested are likely to have different degrees of sensitivity due to different risk allele frequencies and linkage disequilibrium patterns across populations. The clinical relevance depends on the ethnicity of the individual and variability of pharmacogenetic markers. Further research is required to determine causal variants and provide more complete assessment of drug response and side effects. 23andMe reports provide some useful pharmacogenetics information, mirroring clinical tests that are in standard use. Other tests are unspecific, providing limited guidance and may not be useful for patients without professional interpretation. Nevertheless, DTC companies like 23andMe act as a powerful intermediate step to integrate pharmacogenetic testing into clinical practice.
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Taylor, Robert W; Pyle, Angela; Griffin, Helen; Blakely, Emma L; Duff, Jennifer; He, Langping; Smertenko, Tania; Alston, Charlotte L; Neeve, Vivienne C; Best, Andrew; Yarham, John W; Kirschner, Janbernd; Schara, Ulrike; Talim, Beril; Topaloglu, Haluk; Baric, Ivo; Holinski-Feder, Elke; Abicht, Angela; Czermin, Birgit; Kleinle, Stephanie; Morris, Andrew A M; Vassallo, Grace; Gorman, Grainne S; Ramesh, Venkateswaran; Turnbull, Douglass M; Santibanez-Koref, Mauro; McFarland, Robert; Horvath, Rita; Chinnery, Patrick F
2014-07-02
Mitochondrial disorders have emerged as a common cause of inherited disease, but their diagnosis remains challenging. Multiple respiratory chain complex defects are particularly difficult to diagnose at the molecular level because of the massive number of nuclear genes potentially involved in intramitochondrial protein synthesis, with many not yet linked to human disease. To determine the molecular basis of multiple respiratory chain complex deficiencies. We studied 53 patients referred to 2 national centers in the United Kingdom and Germany between 2005 and 2012. All had biochemical evidence of multiple respiratory chain complex defects but no primary pathogenic mitochondrial DNA mutation. Whole-exome sequencing was performed using 62-Mb exome enrichment, followed by variant prioritization using bioinformatic prediction tools, variant validation by Sanger sequencing, and segregation of the variant with the disease phenotype in the family. Presumptive causal variants were identified in 28 patients (53%; 95% CI, 39%-67%) and possible causal variants were identified in 4 (8%; 95% CI, 2%-18%). Together these accounted for 32 patients (60% 95% CI, 46%-74%) and involved 18 different genes. These included recurrent mutations in RMND1, AARS2, and MTO1, each on a haplotype background consistent with a shared founder allele, and potential novel mutations in 4 possible mitochondrial disease genes (VARS2, GARS, FLAD1, and PTCD1). Distinguishing clinical features included deafness and renal involvement associated with RMND1 and cardiomyopathy with AARS2 and MTO1. However, atypical clinical features were present in some patients, including normal liver function and Leigh syndrome (subacute necrotizing encephalomyelopathy) seen in association with TRMU mutations and no cardiomyopathy with founder SCO2 mutations. It was not possible to confidently identify the underlying genetic basis in 21 patients (40%; 95% CI, 26%-54%). Exome sequencing enhances the ability to identify potential nuclear gene mutations in patients with biochemically defined defects affecting multiple mitochondrial respiratory chain complexes. Additional study is required in independent patient populations to determine the utility of this approach in comparison with traditional diagnostic methods.
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Duan, Jubao
2015-02-01
Schizophrenia (SZ) is a devastating mental disorder afflicting 1% of the population. Recent genome-wide association studies (GWASs) of SZ have identified >100 risk loci. However, the causal variants/genes and the causal mechanisms remain largely unknown, which hinders the translation of GWAS findings into disease biology and drug targets. Most risk variants are noncoding, thus likely regulate gene expression. A major mechanism of transcriptional regulation is chromatin remodeling, and open chromatin is a versatile predictor of regulatory sequences. MicroRNA-mediated post-transcriptional regulation plays an important role in SZ pathogenesis. Neurons differentiated from patient-specific induced pluripotent stem cells (iPSCs) provide an experimental model to characterize the genetic perturbation of regulatory variants that are often specific to cell type and/or developmental stage. The emerging genome-editing technology enables the creation of isogenic iPSCs and neurons to efficiently characterize the effects of SZ-associated regulatory variants on SZ-relevant molecular and cellular phenotypes involving dopaminergic, glutamatergic, and GABAergic neurotransmissions. SZ GWAS findings equipped with the emerging functional genomics approaches provide an unprecedented opportunity for understanding new disease biology and identifying novel drug targets.
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Genetic Instrumental Variable Studies of Effects of Prenatal Risk Factors
von Hinke Kessler Scholder, Stephanie
2013-01-01
Identifying the effects of maternal risk factors during pregnancy on infant and child health is an area of tremendous research interest. However, of interest to policy makers is unraveling the causal effects of prenatal risk factors, not their associations with child health, which may be confounded by several unobserved factors. In this paper, we evaluate the utility of genetic variants in three genes that have unequivocal evidence of being related to three major risk factors – CHRNA3 for smoking, ADH1B for alcohol use, and FTO for obesity – as instrumental variables for identifying the causal effects of such factors during pregnancy. Using two independent datasets, we find that these variants are overall predictive of the risk factors and are not systematically related to observed confounders, suggesting that they may be useful instruments. We also find some suggestive evidence that genetic effects are stronger during than before pregnancy. We provide an empirical example illustrating the use of these genetic variants as instruments to evaluate the effects of risk factors on birth weight. Finally, we offer suggestions for researchers contemplating the use of these variants as instruments. PMID:23701534
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Mahajan, Anubha; Locke, Adam; Rayner, N William; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Goncalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Borringer, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex SF; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian’an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Perry, John RB; Platou, Carl GP; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth JF; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin NA; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O’Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P
2015-01-01
We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease. PMID:26551672
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Hammer, Christian; Begemann, Martin; McLaren, Paul J.; Bartha, István; Michel, Angelika; Klose, Beate; Schmitt, Corinna; Waterboer, Tim; Pawlita, Michael; Schulz, Thomas F.; Ehrenreich, Hannelore; Fellay, Jacques
2015-01-01
The magnitude of the human antibody response to viral antigens is highly variable. To explore the human genetic contribution to this variability, we performed genome-wide association studies of the immunoglobulin G response to 14 pathogenic viruses in 2,363 immunocompetent adults. Significant associations were observed in the major histocompatibility complex region on chromosome 6 for influenza A virus, Epstein-Barr virus, JC polyomavirus, and Merkel cell polyomavirus. Using local imputation and fine mapping, we identified specific amino acid residues in human leucocyte antigen (HLA) class II proteins as the most probable causal variants underlying these association signals. Common HLA-DRβ1 haplotypes showed virus-specific patterns of humoral-response regulation. We observed an overlap between variants affecting the humoral response to influenza A and EBV and variants previously associated with autoimmune diseases related to these viruses. The results of this study emphasize the central and pathogen-specific role of HLA class II variation in the modulation of humoral immune response to viral antigens in humans. PMID:26456283
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Classification of BRCA1 missense variants of unknown clinical significance
Phelan, C; Dapic, V; Tice, B; Favis, R; Kwan, E; Barany, F; Manoukian, S; Radice, P; van der Luijt, R B; van Nesselrooij, B P M; Chenevix-Trench, G; kConFab; Caldes, T; de La Hoya, M; Lindquist, S; Tavtigian, S; Goldgar, D; Borg, A; Narod, S; Monteiro, A
2005-01-01
Background: BRCA1 is a tumour suppressor with pleiotropic actions. Germline mutations in BRCA1 are responsible for a large proportion of breast–ovarian cancer families. Several missense variants have been identified throughout the gene but because of lack of information about their impact on the function of BRCA1, predictive testing is not always informative. Classification of missense variants into deleterious/high risk or neutral/low clinical significance is essential to identify individuals at risk. Objective: To investigate a panel of missense variants. Methods and results: The panel was investigated in a comprehensive framework that included (1) a functional assay based on transcription activation; (2) segregation analysis and a method of using incomplete pedigree data to calculate the odds of causality; (3) a method based on interspecific sequence variation. It was shown that the transcriptional activation assay could be used as a test to characterise mutations in the carboxy-terminus region of BRCA1 encompassing residues 1396–1863. Thirteen missense variants (H1402Y, L1407P, H1421Y, S1512I, M1628T, M1628V, T1685I, G1706A, T1720A, A1752P, G1788V, V1809F, and W1837R) were specifically investigated. Conclusions: While individual classification schemes for BRCA1 alleles still present limitations, a combination of several methods provides a more powerful way of identifying variants that are causally linked to a high risk of breast and ovarian cancer. The framework presented here brings these variants nearer to clinical applicability. PMID:15689452
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Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer
Lawrenson, Kate; Iversen, Edwin S.; Tyrer, Jonathan; Weber, Rachel Palmieri; Concannon, Patrick; Hazelett, Dennis J.; Li, Qiyuan; Marks, Jeffrey R.; Berchuck, Andrew; Lee, Janet M.; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Plisiecka-Halasa, Joanna; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Gronwald, Jacek; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Jakubowska, Anna; Paul, James; Jensen, Allan; Karlan, Beth Y.; Kjaer, Susanne Kruger; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Cannioto, Rikki; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; Nevanlinna, Heli; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Noor Azmi, Mat Adenan; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Pearce, Celeste L.; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Budzilowska, Agnieszka; Sellers, Thomas A.; Shu, Xiao-Ou; Shvetsov, Yurii B.; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J.; Timorek, Agnieszka; Tworoger, Shelley S.; Nieuwenhuysen, Els Van; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Coetzee, Gerhard A.; Freedman, Matthew L.; Monteiro, Alvaro N.A.; Moes-Sosnowska, Joanna; Kupryjanczyk, Jolanta; Pharoah, Paul D.; Gayther, Simon A.; Schildkraut, Joellen M.
2015-01-01
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10–7). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r 2 with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11–1.24, P = 1.1×10−7). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10−8). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r 2 = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10-8). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene. PMID:26424751
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Mägi, Reedik; Horikoshi, Momoko; Sofer, Tamar; Mahajan, Anubha; Kitajima, Hidetoshi; Franceschini, Nora; McCarthy, Mark I.; Morris, Andrew P.
2017-01-01
Abstract Trans-ethnic meta-analysis of genome-wide association studies (GWAS) across diverse populations can increase power to detect complex trait loci when the underlying causal variants are shared between ancestry groups. However, heterogeneity in allelic effects between GWAS at these loci can occur that is correlated with ancestry. Here, a novel approach is presented to detect SNP association and quantify the extent of heterogeneity in allelic effects that is correlated with ancestry. We employ trans-ethnic meta-regression to model allelic effects as a function of axes of genetic variation, derived from a matrix of mean pairwise allele frequency differences between GWAS, and implemented in the MR-MEGA software. Through detailed simulations, we demonstrate increased power to detect association for MR-MEGA over fixed- and random-effects meta-analysis across a range of scenarios of heterogeneity in allelic effects between ethnic groups. We also demonstrate improved fine-mapping resolution, in loci containing a single causal variant, compared to these meta-analysis approaches and PAINTOR, and equivalent performance to MANTRA at reduced computational cost. Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates stronger signals of association than fixed-effects meta-analysis when heterogeneity in allelic effects is correlated with ancestry. Application of MR-MEGA to fine-mapping four type 2 diabetes susceptibility loci in 22,086 cases and 42,539 controls highlights: (i) strong evidence for heterogeneity in allelic effects that is correlated with ancestry only at the index SNP for the association signal at the CDKAL1 locus; and (ii) 99% credible sets with six or fewer variants for five distinct association signals. PMID:28911207
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Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Alejandro Q; Musolf, Anthony; Matise, Tara C; Finch, Stephen J; Gordon, Derek
2012-01-01
As with any new technology, next-generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to those data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single-variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p value, no matter how many loci. Copyright © 2013 S. Karger AG, Basel.
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Kim, Wonkuk; Londono, Douglas; Zhou, Lisheng; Xing, Jinchuan; Nato, Andrew; Musolf, Anthony; Matise, Tara C.; Finch, Stephen J.; Gordon, Derek
2013-01-01
As with any new technology, next generation sequencing (NGS) has potential advantages and potential challenges. One advantage is the identification of multiple causal variants for disease that might otherwise be missed by SNP-chip technology. One potential challenge is misclassification error (as with any emerging technology) and the issue of power loss due to multiple testing. Here, we develop an extension of the linear trend test for association that incorporates differential misclassification error and may be applied to any number of SNPs. We call the statistic the linear trend test allowing for error, applied to NGS, or LTTae,NGS. This statistic allows for differential misclassification. The observed data are phenotypes for unrelated cases and controls, coverage, and the number of putative causal variants for every individual at all SNPs. We simulate data considering multiple factors (disease mode of inheritance, genotype relative risk, causal variant frequency, sequence error rate in cases, sequence error rate in controls, number of loci, and others) and evaluate type I error rate and power for each vector of factor settings. We compare our results with two recently published NGS statistics. Also, we create a fictitious disease model, based on downloaded 1000 Genomes data for 5 SNPs and 388 individuals, and apply our statistic to that data. We find that the LTTae,NGS maintains the correct type I error rate in all simulations (differential and non-differential error), while the other statistics show large inflation in type I error for lower coverage. Power for all three methods is approximately the same for all three statistics in the presence of non-differential error. Application of our statistic to the 1000 Genomes data suggests that, for the data downloaded, there is a 1.5% sequence misclassification rate over all SNPs. Finally, application of the multi-variant form of LTTae,NGS shows high power for a number of simulation settings, although it can have lower power than the corresponding single variant simulation results, most probably due to our specification of multi-variant SNP correlation values. In conclusion, our LTTae,NGS addresses two key challenges with NGS disease studies; first, it allows for differential misclassification when computing the statistic; and second, it addresses the multiple-testing issue in that there is a multi-variant form of the statistic that has only one degree of freedom, and provides a single p-value, no matter how many loci. PMID:23594495
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A comprehensive global genotype-phenotype database for rare diseases.
Trujillano, Daniel; Oprea, Gabriela-Elena; Schmitz, Yvonne; Bertoli-Avella, Aida M; Abou Jamra, Rami; Rolfs, Arndt
2017-01-01
The ability to discover genetic variants in a patient runs far ahead of the ability to interpret them. Databases with accurate descriptions of the causal relationship between the variants and the phenotype are valuable since these are critical tools in clinical genetic diagnostics. Here, we introduce a comprehensive and global genotype-phenotype database focusing on rare diseases. This database (CentoMD ® ) is a browser-based tool that enables access to a comprehensive, independently curated system utilizing stringent high-quality criteria and a quickly growing repository of genetic and human phenotype ontology (HPO)-based clinical information. Its main goals are to aid the evaluation of genetic variants, to enhance the validity of the genetic analytical workflow, to increase the quality of genetic diagnoses, and to improve evaluation of treatment options for patients with hereditary diseases. The database software correlates clinical information from consented patients and probands of different geographical backgrounds with a large dataset of genetic variants and, when available, biomarker information. An automated follow-up tool is incorporated that informs all users whenever a variant classification has changed. These unique features fully embedded in a CLIA/CAP-accredited quality management system allow appropriate data quality and enhanced patient safety. More than 100,000 genetically screened individuals are documented in the database, resulting in more than 470 million variant detections. Approximately, 57% of the clinically relevant and uncertain variants in the database are novel. Notably, 3% of the genetic variants identified and previously reported in the literature as being associated with a particular rare disease were reclassified, based on internal evidence, as clinically irrelevant. The database offers a comprehensive summary of the clinical validity and causality of detected gene variants with their associated phenotypes, and is a valuable tool for identifying new disease genes through the correlation of novel genetic variants with specific, well-defined phenotypes.
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Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics
Chen, Wenan; Larrabee, Beth R.; Ovsyannikova, Inna G.; Kennedy, Richard B.; Haralambieva, Iana H.; Poland, Gregory A.; Schaid, Daniel J.
2015-01-01
Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. PMID:25948564
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Yamagishi, Kazumasa; Tanigawa, Takeshi; Kitamura, Akihiko; Köttgen, Anna; Folsom, Aaron R; Iso, Hiroyasu
2010-08-01
Recent genome-wide association and functional studies have shown that the ABCG2 gene encodes for a urate transporter, and a common causal ABCG2 variant, rs2231142, leads to elevated uric acid levels and prevalent gout among Whites and Blacks. We examined whether this finding is observed in a Japanese population, since Asians have a high reported prevalence of the T-risk allele. A total of 3923 Japanese people from the Circulatory Risk in Communities Study aged 40-90 years were genotyped for rs2231142. Associations of the rs2231142 variant with serum uric acid levels and prevalence of gout and hyperuricaemia were examined. The frequency of the T-risk allele was 31% in this Japanese sample. Multivariable adjusted mean uric acid levels were 7-9 micromol/l higher for TG and TT than GG carriers (P-additive = 0.0006). The multivariable-adjusted odds ratio (OR) of prevalent gout was 1.37 (95% CI 0.68, 2.76) for TG and 4.37 (95% CI 1.98, 9.62) for TT compared with the GG carriers (P-additive = 0.001). When evaluating the combined outcome of hyperuricaemia and gout, the respective ORs were 1.40 (95% CI 1.04, 1.87) for TG and 1.88 (95% CI 1.23, 2.89) for TT carriers. The population attributable risk was 29% for gout and 19% for gout and/or hyperuricaemia. The association of the causal ABCG2 rs2231142 variant with uric acid levels and gout was confirmed in a sample of Japanese ancestry. Our study emphasizes the importance of this common causal variant in a population with a high risk allele frequency, especially as more Japanese adopt a Western lifestyle with a concomitant increase in mean serum uric acid levels.
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Gene-Based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions.
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y; Chen, Wei
2016-02-01
Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, here we develop Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT), which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. © 2016 WILEY PERIODICALS, INC.
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Gene-based Association Analysis for Censored Traits Via Fixed Effect Functional Regressions
Fan, Ruzong; Wang, Yifan; Yan, Qi; Ding, Ying; Weeks, Daniel E.; Lu, Zhaohui; Ren, Haobo; Cook, Richard J; Xiong, Momiao; Swaroop, Anand; Chew, Emily Y.; Chen, Wei
2015-01-01
Summary Genetic studies of survival outcomes have been proposed and conducted recently, but statistical methods for identifying genetic variants that affect disease progression are rarely developed. Motivated by our ongoing real studies, we develop here Cox proportional hazard models using functional regression (FR) to perform gene-based association analysis of survival traits while adjusting for covariates. The proposed Cox models are fixed effect models where the genetic effects of multiple genetic variants are assumed to be fixed. We introduce likelihood ratio test (LRT) statistics to test for associations between the survival traits and multiple genetic variants in a genetic region. Extensive simulation studies demonstrate that the proposed Cox RF LRT statistics have well-controlled type I error rates. To evaluate power, we compare the Cox FR LRT with the previously developed burden test (BT) in a Cox model and sequence kernel association test (SKAT) which is based on mixed effect Cox models. The Cox FR LRT statistics have higher power than or similar power as Cox SKAT LRT except when 50%/50% causal variants had negative/positive effects and all causal variants are rare. In addition, the Cox FR LRT statistics have higher power than Cox BT LRT. The models and related test statistics can be useful in the whole genome and whole exome association studies. An age-related macular degeneration dataset was analyzed as an example. PMID:26782979
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Gong, Chenrui; Du, Qingzhang; Xie, Jianbo; Quan, Mingyang; Chen, Beibei; Zhang, Deqiang
2018-01-01
Short insertions and deletions (InDels) are one of the major genetic variants and are distributed widely across the genome; however, few investigations of InDels have been conducted in long-lived perennial plants. Here, we employed a combination of RNA-seq and population resequencing to identify InDels within differentially expressed (DE) genes underlying wood formation in a natural population of Populus tomentosa (435 individuals) and utilized InDel-based association mapping to detect the causal variants under additive, dominance, and epistasis underlying growth and wood properties. In the present paper, 5,482 InDels detected from 629 DE genes showed uneven distributions throughout all 19 chromosomes, and 95.9% of these loci were diallelic InDels. Seventy-four InDels (positive false discovery rate q ≤ 0.10) from 68 genes exhibited significant additive/dominant effects on 10 growth and wood-properties, with an average of 14.7% phenotypic variance explained. Potential pleiotropy was observed in one-third of the InDels (representing 24 genes). Seven genes exhibited significantly differential expression among the genotypic classes of associated InDels, indicating possible important roles for these InDels. Epistasis analysis showed that overlapping interacting genes formed unique interconnected networks for each trait, supporting the putative biochemical links that control quantitative traits. Therefore, the identification and utilization of InDels in trees will be recognized as an effective marker system for molecular marker-assisted breeding applications, and further facilitate our understanding of quantitative genomics. PMID:29403506
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Buchmann, Nikolaus; Scholz, Markus; Lill, Christina M; Burkhardt, Ralph; Eckardt, Rahel; Norman, Kristina; Loeffler, Markus; Bertram, Lars; Thiery, Joachim; Steinhagen-Thiessen, Elisabeth; Demuth, Ilja
2017-11-01
Inverse relationships have been described between the largely genetically determined levels of serum/plasma lipoprotein(a) [Lp(a)], type 2 diabetes (T2D) and fasting insulin. Here, we aimed to evaluate the nature of these relationships with respect to causality. We tested whether we could replicate the recent negative findings on causality between Lp(a) and T2D by employing the Mendelian randomization (MR) approach using cross-sectional data from three independent cohorts, Berlin Aging Study II (BASE-II; n = 2012), LIFE-Adult (n = 3281) and LIFE-Heart (n = 2816). Next, we explored another frequently discussed hypothesis in this context: Increasing insulin levels during the course of T2D disease development inhibits hepatic Lp(a) synthesis and thereby might explain the inverse Lp(a)-T2D association. We used two fasting insulin-associated variants, rs780094 and rs10195252, as instrumental variables in MR analysis of n = 4937 individuals from BASE-II and LIFE-Adult. We further investigated causality of the association between fasting insulin and Lp(a) by combined MR analysis of 12 additional SNPs in LIFE-Adult. While an Lp(a)-T2D association was observed in the combined analysis (meta-effect of OR [95% CI] = 0.91 [0.87-0.96] per quintile, p = 1.3x10 -4 ), we found no evidence of causality in the Lp(a)-T2D association (p = 0.29, fixed effect model) when using the variant rs10455872 as the instrumental variable in the MR analyses. Likewise, no evidence of a causal effect of insulin on Lp(a) levels was found. While these results await confirmation in larger cohorts, the nature of the inverse Lp(a)-T2D association remains to be elucidated.
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Comparison of statistical tests for association between rare variants and binary traits.
Bacanu, Silviu-Alin; Nelson, Matthew R; Whittaker, John C
2012-01-01
Genome-wide association studies have found thousands of common genetic variants associated with a wide variety of diseases and other complex traits. However, a large portion of the predicted genetic contribution to many traits remains unknown. One plausible explanation is that some of the missing variation is due to the effects of rare variants. Nonetheless, the statistical analysis of rare variants is challenging. A commonly used method is to contrast, within the same region (gene), the frequency of minor alleles at rare variants between cases and controls. However, this strategy is most useful under the assumption that the tested variants have similar effects. We previously proposed a method that can accommodate heterogeneous effects in the analysis of quantitative traits. Here we extend this method to include binary traits that can accommodate covariates. We use simulations for a variety of causal and covariate impact scenarios to compare the performance of the proposed method to standard logistic regression, C-alpha, SKAT, and EREC. We found that i) logistic regression methods perform well when the heterogeneity of the effects is not extreme and ii) SKAT and EREC have good performance under all tested scenarios but they can be computationally intensive. Consequently, it would be more computationally desirable to use a two-step strategy by (i) selecting promising genes by faster methods and ii) analyzing selected genes using SKAT/EREC. To select promising genes one can use (1) regression methods when effect heterogeneity is assumed to be low and the covariates explain a non-negligible part of trait variability, (2) C-alpha when heterogeneity is assumed to be large and covariates explain a small fraction of trait's variability and (3) the proposed trend and heterogeneity test when the heterogeneity is assumed to be non-trivial and the covariates explain a large fraction of trait variability.
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Dynamical Causal Modeling from a Quantum Dynamical Perspective
DOE Office of Scientific and Technical Information (OSTI.GOV)
Demiralp, Emre; Demiralp, Metin
Recent research suggests that any set of first order linear vector ODEs can be converted to a set of specific vector ODEs adhering to what we have called ''Quantum Harmonical Form (QHF)''. QHF has been developed using a virtual quantum multi harmonic oscillator system where mass and force constants are considered to be time variant and the Hamiltonian is defined as a conic structure over positions and momenta to conserve the Hermiticity. As described in previous works, the conversion to QHF requires the matrix coefficient of the first set of ODEs to be a normal matrix. In this paper, thismore » limitation is circumvented using a space extension approach expanding the potential applicability of this method. Overall, conversion to QHF allows the investigation of a set of ODEs using mathematical tools available to the investigation of the physical concepts underlying quantum harmonic oscillators. The utility of QHF in the context of dynamical systems and dynamical causal modeling in behavioral and cognitive neuroscience is briefly discussed.« less
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Precautionary principles: a jurisdiction-free framework for decision-making under risk.
Ricci, Paolo F; Cox, Louis A; MacDonald, Thomas R
2004-12-01
Fundamental principles of precaution are legal maxims that ask for preventive actions, perhaps as contingent interim measures while relevant information about causality and harm remains unavailable, to minimize the societal impact of potentially severe or irreversible outcomes. Such principles do not explain how to make choices or how to identify what is protective when incomplete and inconsistent scientific evidence of causation characterizes the potential hazards. Rather, they entrust lower jurisdictions, such as agencies or authorities, to make current decisions while recognizing that future information can contradict the scientific basis that supported the initial decision. After reviewing and synthesizing national and international legal aspects of precautionary principles, this paper addresses the key question: How can society manage potentially severe, irreversible or serious environmental outcomes when variability, uncertainty, and limited causal knowledge characterize their decision-making? A decision-analytic solution is outlined that focuses on risky decisions and accounts for prior states of information and scientific beliefs that can be updated as subsequent information becomes available. As a practical and established approach to causal reasoning and decision-making under risk, inherent to precautionary decision-making, these (Bayesian) methods help decision-makers and stakeholders because they formally account for probabilistic outcomes, new information, and are consistent and replicable. Rational choice of an action from among various alternatives--defined as a choice that makes preferred consequences more likely--requires accounting for costs, benefits and the change in risks associated with each candidate action. Decisions under any form of the precautionary principle reviewed must account for the contingent nature of scientific information, creating a link to the decision-analytic principle of expected value of information (VOI), to show the relevance of new information, relative to the initial (and smaller) set of data on which the decision was based. We exemplify this seemingly simple situation using risk management of BSE. As an integral aspect of causal analysis under risk, the methods developed in this paper permit the addition of non-linear, hormetic dose-response models to the current set of regulatory defaults such as the linear, non-threshold models. This increase in the number of defaults is an important improvement because most of the variants of the precautionary principle require cost-benefit balancing. Specifically, increasing the set of causal defaults accounts for beneficial effects at very low doses. We also show and conclude that quantitative risk assessment dominates qualitative risk assessment, supporting the extension of the set of default causal models.
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'Mendelian randomization': an approach for exploring causal relations in epidemiology.
Gupta, V; Walia, G K; Sachdeva, M P
2017-04-01
To assess the current status of Mendelian randomization (MR) approach in effectively influencing the observational epidemiology for examining causal relationships. Narrative review on studies related to principle, strengths, limitations, and achievements of MR approach. Observational epidemiological studies have repeatedly produced several beneficiary associations which were discarded when tested by standard randomized controlled trials (RCTs). The technique which is more feasible, highly similar to RCTs, and has the potential to establish a causal relationship between modifiable exposures and disease outcomes is known as MR. The technique uses genetic variants related to modifiable traits/exposures as instruments for detecting causal and directional associations with outcomes. In the last decade, the approach of MR has methodologically developed and progressed to a stage of high acceptance among the epidemiologists and is gradually expanding the landscape of causal relationships in non-communicable chronic diseases. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
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Pierce, Brandon L; Ahsan, Habibul; Vanderweele, Tyler J
2011-06-01
Mendelian Randomization (MR) studies assess the causality of an exposure-disease association using genetic determinants [i.e. instrumental variables (IVs)] of the exposure. Power and IV strength requirements for MR studies using multiple genetic variants have not been explored. We simulated cohort data sets consisting of a normally distributed disease trait, a normally distributed exposure, which affects this trait and a biallelic genetic variant that affects the exposure. We estimated power to detect an effect of exposure on disease for varying allele frequencies, effect sizes and samples sizes (using two-stage least squares regression on 10,000 data sets-Stage 1 is a regression of exposure on the variant. Stage 2 is a regression of disease on the fitted exposure). Similar analyses were conducted using multiple genetic variants (5, 10, 20) as independent or combined IVs. We assessed IV strength using the first-stage F statistic. Simulations of realistic scenarios indicate that MR studies will require large (n > 1000), often very large (n > 10,000), sample sizes. In many cases, so-called 'weak IV' problems arise when using multiple variants as independent IVs (even with as few as five), resulting in biased effect estimates. Combining genetic factors into fewer IVs results in modest power decreases, but alleviates weak IV problems. Ideal methods for combining genetic factors depend upon knowledge of the genetic architecture underlying the exposure. The feasibility of well-powered, unbiased MR studies will depend upon the amount of variance in the exposure that can be explained by known genetic factors and the 'strength' of the IV set derived from these genetic factors.
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Larson, Nicholas B; McDonnell, Shannon; Cannon Albright, Lisa; Teerlink, Craig; Stanford, Janet; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng; Cooney, Kathleen A; Lange, Ethan; Schleutker, Johanna; Carpten, John D; Powell, Isaac; Bailey-Wilson, Joan E; Cussenot, Olivier; Cancel-Tassin, Geraldine; Giles, Graham G; MacInnis, Robert J; Maier, Christiane; Whittemore, Alice S; Hsieh, Chih-Lin; Wiklund, Fredrik; Catalona, William J; Foulkes, William; Mandal, Diptasri; Eeles, Rosalind; Kote-Jarai, Zsofia; Ackerman, Michael J; Olson, Timothy M; Klein, Christopher J; Thibodeau, Stephen N; Schaid, Daniel J
2017-05-01
Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results. © 2017 WILEY PERIODICALS, INC.
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Genomic Influences on Hyperuricemia and Gout.
Merriman, Tony
2017-08-01
Genome-wide association studies (GWAS) have identified nearly 30 loci associated with urate concentrations that also influence the subsequent risk of gout. The ABCG2 Q141 K variant is highly likely to be causal and results in internalization of ABCG2, which can be rescued by drugs. Three other GWAS loci contain uric acid transporter genes, which are also highly likely to be causal. However identification of causal genes at other urate loci is challenging. Finally, relatively little is known about the genetic control of progression from hyperuricemia to gout. Only 4 small GWAS have been published for gout. Copyright © 2017 Elsevier Inc. All rights reserved.
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Saklatvala, Jake R; Dand, Nick; Simpson, Michael A
2018-05-01
The genetic diagnosis of rare monogenic diseases using exome/genome sequencing requires the true causal variant(s) to be identified from tens of thousands of observed variants. Typically a virtual gene panel approach is taken whereby only variants in genes known to cause phenotypes resembling the patient under investigation are considered. With the number of known monogenic gene-disease pairs exceeding 5,000, manual curation of personalized virtual panels using exhaustive knowledge of the genetic basis of the human monogenic phenotypic spectrum is challenging. We present improved probabilistic methods for estimating phenotypic similarity based on Human Phenotype Ontology annotation. A limitation of existing methods for evaluating a disease's similarity to a reference set is that reference diseases are typically represented as a series of binary (present/absent) observations of phenotypic terms. We evaluate a quantified disease reference set, using term frequency in phenotypic text descriptions to approximate term relevance. We demonstrate an improved ability to identify related diseases through the use of a quantified reference set, and that vector space similarity measures perform better than established information content-based measures. These improvements enable the generation of bespoke virtual gene panels, facilitating more accurate and efficient interpretation of genomic variant profiles from individuals with rare Mendelian disorders. These methods are available online at https://atlas.genetics.kcl.ac.uk/~jake/cgi-bin/patient_sim.py. © 2018 Wiley Periodicals, Inc.
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Hill, W D; Davies, G; Harris, S E; Hagenaars, S P; Liewald, D C; Penke, L; Gale, C R; Deary, I J
2016-12-13
Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.
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Gaulton, Kyle J; Ferreira, Teresa; Lee, Yeji; Raimondo, Anne; Mägi, Reedik; Reschen, Michael E; Mahajan, Anubha; Locke, Adam; Rayner, N William; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Gonçalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Bottinger, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex S F; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kao, Wen-Hong L; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian'an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Peltonen, Leena; Perry, John R B; Platou, Carl G P; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wiltshire, Steven; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth J F; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöcke, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin N A; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O'Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P
2015-12-01
We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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Hill, W D; Davies, G; Harris, S E; Hagenaars, S P; Davies, Gail; Deary, Ian J; Debette, Stephanie; Verbaas, Carla I; Bressler, Jan; Schuur, Maaike; Smith, Albert V; Bis, Joshua C; Bennett, David A; Ikram, M Arfan; Launer, Lenore J; Fitzpatrick, Annette L; Seshadri, Sudha; van Duijn, Cornelia M; Mosley Jr, Thomas H; Liewald, D C; Penke, L; Gale, C R; Deary, I J
2016-01-01
Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions. PMID:27959336
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Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, Amit V.; Kathiresan, Sekar
2018-01-01
Coronary artery disease is the leading global cause of mortality. Long recognized to be heritable, recent advances have started to unravel the genetic architecture of the disease. Common variant association studies have linked about 60 genetic loci to coronary risk. Large-scale gene sequencing efforts and functional studies have facilitated a better understanding of causal risk factors, elucidated underlying biology and informed the development of new therapeutics. Moving forward, genetic testing could enable precision medicine approaches, by identifying subgroups of patients at increased risk of CAD or those with a specific driving pathophysiology in whom a therapeutic or preventive approach is most useful. PMID:28286336
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Wendelsdorf, Katherine; Shah, Sohela
2015-09-01
There is on-going effort in the biomedical research community to leverage Next Generation Sequencing (NGS) technology to identify genetic variants that affect our health. The main challenge facing researchers is getting enough samples from individuals either sick or healthy - to be able to reliably identify the few variants that are causal for a phenotype among all other variants typically seen among individuals. At the same time, more and more individuals are having their genome sequenced either out of curiosity or to identify the cause of an illness. These individuals may benefit from of a way to view and understand their data. QIAGEN's Ingenuity Variant Analysis is an online application that allows users with and without extensive bioinformatics training to incorporate information from published experiments, genetic databases, and a variety of statistical models to identify variants, from a long list of candidates, that are most likely causal for a phenotype as well as annotate variants with what is already known about them in the literature and databases. Ingenuity Variant Analysis is also an information sharing platform where users may exchange samples and analyses. The Empowered Genome Community (EGC) is a new program in which QIAGEN is making this on-line tool freely available to any individual who wishes to analyze their own genetic sequence. EGC members are then able to make their data available to other Ingenuity Variant Analysis users to be used in research. Here we present and describe the Empowered Genome Community in detail. We also present a preliminary, proof-of-concept study that utilizes the 200 genomes currently available through the EGC. The goal of this program is to allow individuals to access and understand their own data as well as facilitate citizen-scientist collaborations that can drive research forward and spur quality scientific dialogue in the general public.
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Common variants at the CHEK2 gene locus and risk of epithelial ovarian cancer.
Lawrenson, Kate; Iversen, Edwin S; Tyrer, Jonathan; Weber, Rachel Palmieri; Concannon, Patrick; Hazelett, Dennis J; Li, Qiyuan; Marks, Jeffrey R; Berchuck, Andrew; Lee, Janet M; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Bandera, Elisa V; Bean, Yukie; Beckmann, Matthias W; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; Plisiecka-Halasa, Joanna; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Eccles, Diana; Easton, Douglas T; Edwards, Robert P; Eilber, Ursula; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Gronwald, Jacek; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Jakubowska, Anna; Paul, James; Jensen, Allan; Karlan, Beth Y; Kjaer, Susanne Kruger; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph L; Kiemeney, Lambertus A; Krakstad, Camilla; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Cannioto, Rikki; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Nevanlinna, Heli; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Noor Azmi, Mat Adenan; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Budzilowska, Agnieszka; Sellers, Thomas A; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston, Lara; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Coetzee, Gerhard A; Freedman, Matthew L; Monteiro, Alvaro N A; Moes-Sosnowska, Joanna; Kupryjanczyk, Jolanta; Pharoah, Paul D; Gayther, Simon A; Schildkraut, Joellen M
2015-11-01
Genome-wide association studies have identified 20 genomic regions associated with risk of epithelial ovarian cancer (EOC), but many additional risk variants may exist. Here, we evaluated associations between common genetic variants [single nucleotide polymorphisms (SNPs) and indels] in DNA repair genes and EOC risk. We genotyped 2896 common variants at 143 gene loci in DNA samples from 15 397 patients with invasive EOC and controls. We found evidence of associations with EOC risk for variants at FANCA, EXO1, E2F4, E2F2, CREB5 and CHEK2 genes (P ≤ 0.001). The strongest risk association was for CHEK2 SNP rs17507066 with serous EOC (P = 4.74 x 10(-7)). Additional genotyping and imputation of genotypes from the 1000 genomes project identified a slightly more significant association for CHEK2 SNP rs6005807 (r (2) with rs17507066 = 0.84, odds ratio (OR) 1.17, 95% CI 1.11-1.24, P = 1.1×10(-7)). We identified 293 variants in the region with likelihood ratios of less than 1:100 for representing the causal variant. Functional annotation identified 25 candidate SNPs that alter transcription factor binding sites within regulatory elements active in EOC precursor tissues. In The Cancer Genome Atlas dataset, CHEK2 gene expression was significantly higher in primary EOCs compared to normal fallopian tube tissues (P = 3.72×10(-8)). We also identified an association between genotypes of the candidate causal SNP rs12166475 (r (2) = 0.99 with rs6005807) and CHEK2 expression (P = 2.70×10(-8)). These data suggest that common variants at 22q12.1 are associated with risk of serous EOC and CHEK2 as a plausible target susceptibility gene. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Clinical analysis of genome next-generation sequencing data using the Omicia platform
Coonrod, Emily M; Margraf, Rebecca L; Russell, Archie; Voelkerding, Karl V; Reese, Martin G
2013-01-01
Aims Next-generation sequencing is being implemented in the clinical laboratory environment for the purposes of candidate causal variant discovery in patients affected with a variety of genetic disorders. The successful implementation of this technology for diagnosing genetic disorders requires a rapid, user-friendly method to annotate variants and generate short lists of clinically relevant variants of interest. This report describes Omicia’s Opal platform, a new software tool designed for variant discovery and interpretation in a clinical laboratory environment. The software allows clinical scientists to process, analyze, interpret and report on personal genome files. Materials & Methods To demonstrate the software, the authors describe the interactive use of the system for the rapid discovery of disease-causing variants using three cases. Results & Conclusion Here, the authors show the features of the Opal system and their use in uncovering variants of clinical significance. PMID:23895124
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Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.
Chen, Wenan; Larrabee, Beth R; Ovsyannikova, Inna G; Kennedy, Richard B; Haralambieva, Iana H; Poland, Gregory A; Schaid, Daniel J
2015-07-01
Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. Copyright © 2015 by the Genetics Society of America.
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Nedeljkovic, Ivana; Terzikhan, Natalie; Vonk, Judith M; van der Plaat, Diana A; Lahousse, Lies; van Diemen, Cleo C; Hobbs, Brian D; Qiao, Dandi; Cho, Michael H; Brusselle, Guy G; Postma, Dirkje S; Boezen, H M; van Duijn, Cornelia M; Amin, Najaf
2018-01-01
Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14-15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4-11q14.1 (LOD = 3.71) and 5q14.3-5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein ( AHNAK ), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 ( PLCB3 ), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 ( SLC22A11 ), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 ( MTL5 ), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.
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Mucopolysaccharidosis VI in cats - clarification regarding genetic testing.
Lyons, Leslie A; Grahn, Robert A; Genova, Francesca; Beccaglia, Michela; Hopwood, John J; Longeri, Maria
2016-07-02
The release of new DNA-based diagnostic tools has increased tremendously in companion animals. Over 70 different DNA variants are now known for the cat, including DNA variants in disease-associated genes and genes causing aesthetically interesting traits. The impact genetic tests have on animal breeding and health management is significant because of the ability to control the breeding of domestic cats, especially breed cats. If used properly, genetic testing can prevent the production of diseased animals, causing the reduction of the frequency of the causal variant in the population, and, potentially, the eventual eradication of the disease. However, testing of some identified DNA variants may be unwarranted and cause undo strife within the cat breeding community and unnecessary reduction of gene pools and availability of breeding animals. Testing for mucopolysaccharidosis Type VI (MPS VI) in cats, specifically the genetic testing of the L476P (c.1427T>C) and the D520N (c.1558G>A) variants in arylsulfatase B (ARSB), has come under scrutiny. No health problems are associated with the D520N (c.1558G>A) variant, however, breeders that obtain positive results for this variant are speculating as to possible correlation with health concerns. Birman cats already have a markedly reduced gene pool and have a high frequency of the MPS VI D520N variant. Further reduction of the gene pool by eliminating cats that are heterozygous or homozygous for only the MPS VI D520N variant could lead to more inbreeding depression effects on the breed population. Herein is debated the genetic testing of the MPS VI D520N variant in cats. Surveys from different laboratories suggest the L476P (c.1427T>C) disease-associated variant should be monitored in the cat breed populations, particularly breeds with Siamese derivations and outcrosses. However, the D520N has no evidence of association with disease in cats and testing is not recommended in the absence of L476P genotyping. Selection against the D520N is not warranted in cat populations. More rigorous guidelines may be required to support the genetic testing of DNA variants in all animal species.
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Felix, Janine F.; Gaillard, Romy; McMahon, George
2017-01-01
Background It has been suggested that greater maternal adiposity during pregnancy affects lifelong risk of offspring fatness via intrauterine mechanisms. Our aim was to use Mendelian randomisation (MR) to investigate the causal effect of intrauterine exposure to greater maternal body mass index (BMI) on offspring BMI and fat mass from childhood to early adulthood. Methods and Findings We used maternal genetic variants as instrumental variables (IVs) to test the causal effect of maternal BMI in pregnancy on offspring fatness (BMI and dual-energy X-ray absorptiometry [DXA] determined fat mass index [FMI]) in a MR approach. This was investigated, with repeat measurements, from ages 7 to 18 in the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 2,521 to 3,720 for different ages). We then sought to replicate findings with results for BMI at age 6 in Generation R (n = 2,337 for replication sample; n = 6,057 for total pooled sample). In confounder-adjusted multivariable regression in ALSPAC, a 1 standard deviation (SD, equivalent of 3.7 kg/m2) increase in maternal BMI was associated with a 0.25 SD (95% CI 0.21–0.29) increase in offspring BMI at age 7, with similar results at later ages and when FMI was used as the outcome. A weighted genetic risk score was generated from 32 genetic variants robustly associated with BMI (minimum F-statistic = 45 in ALSPAC). The MR results using this genetic risk score as an IV in ALSPAC were close to the null at all ages (e.g., 0.04 SD (95% CI -0.21–0.30) at age 7 and 0.03 SD (95% CI -0.26–0.32) at age 18 per SD increase in maternal BMI), which was similar when a 97 variant generic risk score was used in ALSPAC. When findings from age 7 in ALSPAC were meta-analysed with those from age 6 in Generation R, the pooled confounder-adjusted multivariable regression association was 0.22 SD (95% CI 0.19–0.25) per SD increase in maternal BMI and the pooled MR effect (pooling the 97 variant score results from ALSPAC with the 32 variant score results from Generation R) was 0.05 SD (95%CI -0.11–0.21) per SD increase in maternal BMI (p-value for difference between the two results = 0.05). A number of sensitivity analyses exploring violation of the MR results supported our main findings. However, power was limited for some of the sensitivity tests and further studies with relevant data on maternal, offspring, and paternal genotype are required to obtain more precise (and unbiased) causal estimates. Conclusions Our findings provide little evidence to support a strong causal intrauterine effect of incrementally greater maternal BMI resulting in greater offspring adiposity. PMID:28118352
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Preferential Binding to Elk-1 by SLE-Associated IL10 Risk Allele Upregulates IL10 Expression
Kelly, Jennifer A.; Brown, Elizabeth E.; Harley, John B.; Bae, Sang-Cheol; Alarcόn-Riquelme, Marta E.; Edberg, Jeffrey C.; Kimberly, Robert P.; Ramsey-Goldman, Rosalind; Petri, Michelle A.; Reveille, John D.; Vilá, Luis M.; Alarcón, Graciela S.; Kaufman, Kenneth M.; Vyse, Timothy J.; Jacob, Chaim O.; Gaffney, Patrick M.; Sivils, Kathy Moser; James, Judith A.; Kamen, Diane L.; Gilkeson, Gary S.; Niewold, Timothy B.; Merrill, Joan T.; Scofield, R. Hal; Criswell, Lindsey A.; Stevens, Anne M.; Boackle, Susan A.; Kim, Jae-Hoon; Choi, Jiyoung; Pons-Estel, Bernardo A.; Freedman, Barry I.; Anaya, Juan-Manuel; Martin, Javier; Yu, C. Yung; Chang, Deh-Ming; Song, Yeong Wook; Langefeld, Carl D.; Chen, Weiling; Grossman, Jennifer M.; Cantor, Rita M.; Hahn, Bevra H.; Tsao, Betty P.
2013-01-01
Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10−8, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans. PMID:24130510
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Preferential binding to Elk-1 by SLE-associated IL10 risk allele upregulates IL10 expression.
Sakurai, Daisuke; Zhao, Jian; Deng, Yun; Kelly, Jennifer A; Brown, Elizabeth E; Harley, John B; Bae, Sang-Cheol; Alarcόn-Riquelme, Marta E; Edberg, Jeffrey C; Kimberly, Robert P; Ramsey-Goldman, Rosalind; Petri, Michelle A; Reveille, John D; Vilá, Luis M; Alarcón, Graciela S; Kaufman, Kenneth M; Vyse, Timothy J; Jacob, Chaim O; Gaffney, Patrick M; Sivils, Kathy Moser; James, Judith A; Kamen, Diane L; Gilkeson, Gary S; Niewold, Timothy B; Merrill, Joan T; Scofield, R Hal; Criswell, Lindsey A; Stevens, Anne M; Boackle, Susan A; Kim, Jae-Hoon; Choi, Jiyoung; Pons-Estel, Bernardo A; Freedman, Barry I; Anaya, Juan-Manuel; Martin, Javier; Yu, C Yung; Chang, Deh-Ming; Song, Yeong Wook; Langefeld, Carl D; Chen, Weiling; Grossman, Jennifer M; Cantor, Rita M; Hahn, Bevra H; Tsao, Betty P
2013-01-01
Immunoregulatory cytokine interleukin-10 (IL-10) is elevated in sera from patients with systemic lupus erythematosus (SLE) correlating with disease activity. The established association of IL10 with SLE and other autoimmune diseases led us to fine map causal variant(s) and to explore underlying mechanisms. We assessed 19 tag SNPs, covering the IL10 gene cluster including IL19, IL20 and IL24, for association with SLE in 15,533 case and control subjects from four ancestries. The previously reported IL10 variant, rs3024505 located at 1 kb downstream of IL10, exhibited the strongest association signal and was confirmed for association with SLE in European American (EA) (P = 2.7×10⁻⁸, OR = 1.30), but not in non-EA ancestries. SNP imputation conducted in EA dataset identified three additional SLE-associated SNPs tagged by rs3024505 (rs3122605, rs3024493 and rs3024495 located at 9.2 kb upstream, intron 3 and 4 of IL10, respectively), and SLE-risk alleles of these SNPs were dose-dependently associated with elevated levels of IL10 mRNA in PBMCs and circulating IL-10 protein in SLE patients and controls. Using nuclear extracts of peripheral blood cells from SLE patients for electrophoretic mobility shift assays, we identified specific binding of transcription factor Elk-1 to oligodeoxynucleotides containing the risk (G) allele of rs3122605, suggesting rs3122605 as the most likely causal variant regulating IL10 expression. Elk-1 is known to be activated by phosphorylation and nuclear localization to induce transcription. Of interest, phosphorylated Elk-1 (p-Elk-1) detected only in nuclear extracts of SLE PBMCs appeared to increase with disease activity. Co-expression levels of p-Elk-1 and IL-10 were elevated in SLE T, B cells and monocytes, associated with increased disease activity in SLE B cells, and were best downregulated by ERK inhibitor. Taken together, our data suggest that preferential binding of activated Elk-1 to the IL10 rs3122605-G allele upregulates IL10 expression and confers increased risk for SLE in European Americans.
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Transethnic differences in GWAS signals: A simulation study.
Zanetti, Daniela; Weale, Michael E
2018-05-07
Genome-wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes. To determine whether properties (1)-(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case-control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro-centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine-mapping. © 2018 John Wiley & Sons Ltd/University College London.
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Carnitine Palmitoyltransferase 1A P479L and Infant Death: Policy Implications of Emerging Data
Fohner, Alison E.; Garrison, Nanibaa’ A.; Austin, Melissa A.; Burke, Wylie
2017-01-01
Carnitine Palmitoyltransferase 1 Isoform A (CPT1A) is a crucial enzyme for the transport of long chain fatty acids into the mitochondria. The CPT1A P479L variant is found in high frequencies among indigenous populations residing on the west and north coasts of Alaska and Canada and in northeast Siberia and Greenland. Epidemiological studies have reported a statistical association between P479L homozygosity and infant death in Alaska Native and Canadian Inuit populations. Here, we review the available evidence about the P479L variant and apply to these data the epidemiological criteria for assessing causal associations. We find insufficient evidence to support a causal association with infant death and further, that if a causal association is present, the genotype is likely to be only one of a complex set of factors contributing to an increased risk of infant death. We conclude that additional research is needed to clarify the observed association and to inform effective preventative measures for infant death. In light of these findings, we discuss the policy implications for public health efforts, as policies based on the observed association between P479L homozygosity and infant death data are premature. PMID:28125087
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Day, Felix R; Ruth, Katherine S; Thompson, Deborah J; Lunetta, Kathryn L; Pervjakova, Natalia; Chasman, Daniel I; Stolk, Lisette; Finucane, Hilary K; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D; Elks, Cathy E; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A; Franke, Lude L; Huffman, Jennifer E; Keller, Margaux F; McArdle, Patrick F; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M; Schick, Ursula M; Smith, Jennifer A; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L; Anton-Culver, Hoda; Antoniou, Antonis C; Arndt, Volker; Arnold, Alice M; Barbieri, Caterina; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J; Chapman, J Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J; Coviello, Andrea D; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W; Dennis, Joe; Devilee, Peter; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eicher, John D; Fasching, Peter A; Faul, Jessica D; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E; García-Closas, Montserrat; Giles, Graham G; Girotto, Giorgia G; Goldberg, Mark S; González-Neira, Anna; Goodarzi, Mark O; Grove, Megan L; Gudbjartsson, Daniel F; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A; Hall, Per; Hamann, Ute; Henderson, Brian E; Hocking, Lynne J; Hofman, Albert; Homuth, Georg; Hooning, Maartje J; Hopper, John L; Hu, Frank B; Huang, Jinyan; Humphreys, Keith; Hunter, David J; Jakubowska, Anna; Jones, Samuel E; Kabisch, Maria; Karasik, David; Knight, Julia A; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian'an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B; Nordestgaard, Børge G; Olson, Janet E; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D P; Pirastu, Nicola N; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F; Sanna, Serena; Sawyer, Elinor J; Schlessinger, David; Schmidt, Marjanka K; Schmidt, Frank; Schmutzler, Rita K; Schoemaker, Minouk J; Scott, Robert A; Seynaeve, Caroline M; Simard, Jacques; Sorice, Rossella; Southey, Melissa C; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D; Thorsteinsdottir, Unnur; Toland, Amanda E; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F; Winqvist, Robert; Wolffenbuttel, Bruce B H R; Wright, Alan F; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I; Buring, Julie E; Ferrucci, Luigi; Montgomery, Grant W; Gudnason, Vilmundur; Spector, Tim D; van Duijn, Cornelia M; Alizadeh, Behrooz Z; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F; Gasparini, Paolo P; Gieger, Christian; Harris, Tamara B; Hayward, Caroline; Kardia, Sharon L R; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C; Reiner, Alex P; Ridker, Paul M; Rotter, Jerome I; Toniolo, Daniela; Uitterlinden, André G; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J; Weir, David R; Yerges-Armstrong, Laura M; Price, Alkes L; Stefansson, Kari; Visser, Jenny A; Ong, Ken K; Chang-Claude, Jenny; Murabito, Joanne M; Perry, John R B; Murray, Anna
2015-11-01
Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ∼70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two regions harboring additional rare missense alleles of large effect. We found enrichment of signals in or near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses identified major association with DNA damage response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomization analyses supported a causal effect of later ANM on breast cancer risk (∼6% increase in risk per year; P = 3 × 10(-14)), likely mediated by prolonged sex hormone exposure rather than DDR mechanisms.
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Lunetta, Kathryn L.; Pervjakova, Natalia; Chasman, Daniel I.; Stolk, Lisette; Finucane, Hilary K.; Sulem, Patrick; Bulik-Sullivan, Brendan; Esko, Tõnu; Johnson, Andrew D.; Elks, Cathy E.; Franceschini, Nora; He, Chunyan; Altmaier, Elisabeth; Brody, Jennifer A.; Franke, Lude L.; Huffman, Jennifer E.; Keller, Margaux F.; McArdle, Patrick F.; Nutile, Teresa; Porcu, Eleonora; Robino, Antonietta; Rose, Lynda M.; Schick, Ursula M.; Smith, Jennifer A.; Teumer, Alexander; Traglia, Michela; Vuckovic, Dragana; Yao, Jie; Zhao, Wei; Albrecht, Eva; Amin, Najaf; Corre, Tanguy; Hottenga, Jouke-Jan; Mangino, Massimo; Smith, Albert V.; Tanaka, Toshiko; Abecasis, Goncalo; Andrulis, Irene L.; Anton-Culver, Hoda; Antoniou, Antonis C.; Arndt, Volker; Arnold, Alice M.; Barbieri, Caterina; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Bernstein, Leslie; Bielinski, Suzette J.; Blomqvist, Carl; Boerwinkle, Eric; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Borresen-Dale, Anne-Lise; Boutin, Thibaud S; Brauch, Hiltrud; Brenner, Hermann; Brüning, Thomas; Burwinkel, Barbara; Campbell, Archie; Campbell, Harry; Chanock, Stephen J.; Chapman, J. Ross; Chen, Yii-Der Ida; Chenevix-Trench, Georgia; Couch, Fergus J.; Coviello, Andrea D.; Cox, Angela; Czene, Kamila; Darabi, Hatef; De Vivo, Immaculata; Demerath, Ellen W.; Dennis, Joe; Devilee, Peter; Dörk, Thilo; dos-Santos-Silva, Isabel; Dunning, Alison M.; Eicher, John D.; Fasching, Peter A.; Faul, Jessica D.; Figueroa, Jonine; Flesch-Janys, Dieter; Gandin, Ilaria; Garcia, Melissa E.; García-Closas, Montserrat; Giles, Graham G.; Girotto, Giorgia G.; Goldberg, Mark S.; González-Neira, Anna; Goodarzi, Mark O.; Grove, Megan L.; Gudbjartsson, Daniel F.; Guénel, Pascal; Guo, Xiuqing; Haiman, Christopher A.; Hall, Per; Hamann, Ute; Henderson, Brian E.; Hocking, Lynne J.; Hofman, Albert; Homuth, Georg; Hooning, Maartje J.; Hopper, John L.; Hu, Frank B.; Huang, Jinyan; Humphreys, Keith; Hunter, David J.; Jakubowska, Anna; Jones, Samuel E.; Kabisch, Maria; Karasik, David; Knight, Julia A.; Kolcic, Ivana; Kooperberg, Charles; Kosma, Veli-Matti; Kriebel, Jennifer; Kristensen, Vessela; Lambrechts, Diether; Langenberg, Claudia; Li, Jingmei; Li, Xin; Lindström, Sara; Liu, Yongmei; Luan, Jian’an; Lubinski, Jan; Mägi, Reedik; Mannermaa, Arto; Manz, Judith; Margolin, Sara; Marten, Jonathan; Martin, Nicholas G.; Masciullo, Corrado; Meindl, Alfons; Michailidou, Kyriaki; Mihailov, Evelin; Milani, Lili; Milne, Roger L.; Müller-Nurasyid, Martina; Nalls, Michael; Neale, Ben M.; Nevanlinna, Heli; Neven, Patrick; Newman, Anne B.; Nordestgaard, Børge G.; Olson, Janet E.; Padmanabhan, Sandosh; Peterlongo, Paolo; Peters, Ulrike; Petersmann, Astrid; Peto, Julian; Pharoah, Paul D.P.; Pirastu, Nicola N.; Pirie, Ailith; Pistis, Giorgio; Polasek, Ozren; Porteous, David; Psaty, Bruce M.; Pylkäs, Katri; Radice, Paolo; Raffel, Leslie J.; Rivadeneira, Fernando; Rudan, Igor; Rudolph, Anja; Ruggiero, Daniela; Sala, Cinzia F.; Sanna, Serena; Sawyer, Elinor J.; Schlessinger, David; Schmidt, Marjanka K.; Schmidt, Frank; Schmutzler, Rita K.; Schoemaker, Minouk J.; Scott, Robert A.; Seynaeve, Caroline M.; Simard, Jacques; Sorice, Rossella; Southey, Melissa C.; Stöckl, Doris; Strauch, Konstantin; Swerdlow, Anthony; Taylor, Kent D.; Thorsteinsdottir, Unnur; Toland, Amanda E.; Tomlinson, Ian; Truong, Thérèse; Tryggvadottir, Laufey; Turner, Stephen T.; Vozzi, Diego; Wang, Qin; Wellons, Melissa; Willemsen, Gonneke; Wilson, James F.; Winqvist, Robert; Wolffenbuttel, Bruce B.H.R.; Wright, Alan F.; Yannoukakos, Drakoulis; Zemunik, Tatijana; Zheng, Wei; Zygmunt, Marek; Bergmann, Sven; Boomsma, Dorret I.; Buring, Julie E.; Ferrucci, Luigi; Montgomery, Grant W.; Gudnason, Vilmundur; Spector, Tim D.; van Duijn, Cornelia M; Alizadeh, Behrooz Z.; Ciullo, Marina; Crisponi, Laura; Easton, Douglas F.; Gasparini, Paolo P.; Gieger, Christian; Harris, Tamara B.; Hayward, Caroline; Kardia, Sharon L.R.; Kraft, Peter; McKnight, Barbara; Metspalu, Andres; Morrison, Alanna C.; Reiner, Alex P.; Ridker, Paul M.; Rotter, Jerome I.; Toniolo, Daniela; Uitterlinden, André G.; Ulivi, Sheila; Völzke, Henry; Wareham, Nicholas J.; Weir, David R.; Yerges-Armstrong, Laura M.; Price, Alkes L.; Stefansson, Kari; Visser, Jenny A.; Ong, Ken K.; Chang-Claude, Jenny; Murabito, Joanne M.; Perry, John R.B.; Murray, Anna
2015-01-01
Menopause timing has a substantial impact on infertility and risk of disease, including breast cancer, but the underlying mechanisms are poorly understood. We report a dual strategy in ~70,000 women to identify common and low-frequency protein-coding variation associated with age at natural menopause (ANM). We identified 44 regions with common variants, including two harbouring additional rare missense alleles of large effect. We found enrichment of signals in/near genes involved in delayed puberty, highlighting the first molecular links between the onset and end of reproductive lifespan. Pathway analyses revealed a major association with DNA damage-response (DDR) genes, including the first common coding variant in BRCA1 associated with any complex trait. Mendelian randomisation analyses supported a causal effect of later ANM on breast cancer risk (~6% risk increase per-year, P=3×10−14), likely mediated by prolonged sex hormone exposure, rather than DDR mechanisms. PMID:26414677
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Genome-wide association studies and resting heart rate.
Kilpeläinen, Tuomas O
Genome-wide association studies (GWASs) have revolutionized the search for genetic variants regulating resting heart rate. In the last 10years, GWASs have led to the identification of at least 21 novel heart rate loci. These discoveries have provided valuable insights into the mechanisms and pathways that regulate heart rate and link heart rate to cardiovascular morbidity and mortality. GWASs capture majority of genetic variation in a population sample by utilizing high-throughput genotyping chips measuring genotypes for up to several millions of SNPs across the genome in thousands of individuals. This allows the identification of the strongest heart rate associated signals at genome-wide level. While GWASs provide robust statistical evidence of the association of a given genetic locus with heart rate, they are only the starting point for detailed follow-up studies to locate the causal variants and genes and gain further insights into the biological mechanisms underlying the observed associations. Copyright © 2016 Elsevier Inc. All rights reserved.
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Jørgensen, Anders Berg; Frikke-Schmidt, Ruth; West, Anders Sode; Grande, Peer; Nordestgaard, Børge G; Tybjærg-Hansen, Anne
2013-06-01
Elevated non-fasting triglycerides mark elevated levels of remnant cholesterol. Using a Mendelian randomization approach, we tested whether genetically increased remnant cholesterol in hypertriglyceridaemia due to genetic variation in the apolipoprotein A5 gene (APOA5) associates with an increased risk of myocardial infarction (MI). We resequenced the core promoter and coding regions of APOA5 in individuals with the lowest 1% (n = 95) and highest 2% (n = 190) triglyceride levels in the Copenhagen City Heart Study (CCHS, n = 10 391). Genetic variants which differed in frequency between the two extreme triglyceride groups (c.-1131T > C, S19W, and c.*31C > T; P-value: 0.06 to <0.001), thus suggesting an effect on triglyceride levels, were genotyped in the Copenhagen General Population Study (CGPS), the CCHS, and the Copenhagen Ischemic Heart Disease Study (CIHDS), comprising a total of 5705 MI cases and 54 408 controls. Genotype combinations of these common variants associated with increases in non-fasting triglycerides and calculated remnant cholesterol of, respectively, up to 68% (1.10 mmol/L) and 56% (0.40 mmol/L) (P < 0.001), and with a corresponding odds ratio for MI of 1.87 (95% confidence interval: 1.25-2.81). Using APOA5 genotypes in instrumental variable analysis, the observational hazard ratio for a doubling in non-fasting triglycerides was 1.57 (1.32-2.68) compared with a causal genetic odds ratio of 1.94 (1.40-1.85) (P for comparison = 0.28). For calculated remnant cholesterol, the corresponding values were 1.67(1.38-2.02) observational and 2.23(1.48-3.35) causal (P for comparison = 0.21). These data are consistent with a causal association between elevated levels of remnant cholesterol in hypertriglyceridaemia and an increased risk of MI. Limitations include that remnants were not measured directly, and that APOA5 genetic variants may influence other lipoprotein parameters.
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Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander
2016-01-01
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894
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Ward, Lucas D; Kellis, Manolis
2016-01-04
More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
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Marioni, Riccardo E; Deary, Ian J; Murray, Gordon D; Lowe, Gordon D O; Rafnsson, Snorri B; Strachan, Mark W J; Luciano, Michelle; Houlihan, Lorna M; Gow, Alan J; Harris, Sarah E; Stewart, Marlene C; Rumley, Ann; Fowkes, F Gerry R; Price, Jackie F
2010-01-01
It is unknown whether the relationship between raised inflammatory biomarker levels and late-life cognitive ability is causal. We explored this issue by testing the association between genetic regulators of plasma C-reactive protein (CRP) and cognition. Data were analysed from four cohorts based in central Scotland (Total N = 4,782). Associations were tested between variants in the CRP gene and both plasma CRP levels and a battery of neuropsychological tests, including a vocabulary-based estimate of peak prior cognitive ability and a general (summary) cognitive factor score, or 'g'. CRP levels were associated with a number of variants in the CRP gene (SNPs), including rs1205, rs1130864, rs1800947, and rs1417938 (P range 4.2e-06 to 0.041). Higher CRP levels were also associated with vocabulary-adjusted cognitive ability, used here to estimate lifetime cognitive change (P range 1.7e-04 to 0.038). After correction for multiple testing and adjustment for age and sex, no statistically significant associations were found between the SNPs and cognition. CRP is unlikely to be a causal determinant of late-life cognitive ability.
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Boulling, Arnaud; Masson, Emmanuelle; Zou, Wen-Bin; Paliwal, Sumit; Wu, Hao; Issarapu, Prachand; Bhaskar, Seema; Génin, Emmanuelle; Cooper, David N; Li, Zhao-Shen; Chandak, Giriraj R; Liao, Zhuan; Chen, Jian-Min; Férec, Claude
2017-08-01
The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser) variant (also known as rs17107315:T>C) represents the most important heritable risk factor for idiopathic chronic pancreatitis identified to date. The causal variant contained within this risk haplotype has however remained stubbornly elusive. Herein, we set out to resolve this enigma by employing a hypothesis-driven approach. First, we searched for variants in strong linkage disequilibrium (LD) with rs17107315:T>C using HaploReg v4.1. Second, we identified two candidate SNPs by visual inspection of sequences spanning all 25 SNPs found to be in LD with rs17107315:T>C, guided by prior knowledge of pancreas-specific transcription factors and their cognate binding sites. Third, employing a novel cis-regulatory module (CRM)-guided approach to further filter the two candidate SNPs yielded a solitary candidate causal variant. Finally, combining data from phylogenetic conservation and chromatin accessibility, cotransfection transactivation experiments, and population genetic studies, we suggest that rs142703147:C>A, which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L CRM located ∼4 kb upstream of the SPINK1 promoter, contributes to the aforementioned chronic pancreatitis risk haplotype. Further studies are required not only to improve the characterization of this functional SNP but also to identify other functional components that might contribute to this high-risk haplotype. © 2017 Wiley Periodicals, Inc.
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Narrow-sense heritability estimation of complex traits using identity-by-descent information.
Evans, Luke M; Tahmasbi, Rasool; Jones, Matt; Vrieze, Scott I; Abecasis, Gonçalo R; Das, Sayantan; Bjelland, Douglas W; de Candia, Teresa R; Yang, Jian; Goddard, Michael E; Visscher, Peter M; Keller, Matthew C
2018-03-28
Heritability is a fundamental parameter in genetics. Traditional estimates based on family or twin studies can be biased due to shared environmental or non-additive genetic variance. Alternatively, those based on genotyped or imputed variants typically underestimate narrow-sense heritability contributed by rare or otherwise poorly tagged causal variants. Identical-by-descent (IBD) segments of the genome share all variants between pairs of chromosomes except new mutations that have arisen since the last common ancestor. Therefore, relating phenotypic similarity to degree of IBD sharing among classically unrelated individuals is an appealing approach to estimating the near full additive genetic variance while possibly avoiding biases that can occur when modeling close relatives. We applied an IBD-based approach (GREML-IBD) to estimate heritability in unrelated individuals using phenotypic simulation with thousands of whole-genome sequences across a range of stratification, polygenicity levels, and the minor allele frequencies of causal variants (CVs). In simulations, the IBD-based approach produced unbiased heritability estimates, even when CVs were extremely rare, although precision was low. However, population stratification and non-genetic familial environmental effects shared across generations led to strong biases in IBD-based heritability. We used data on two traits in ~120,000 people from the UK Biobank to demonstrate that, depending on the trait and possible confounding environmental effects, GREML-IBD can be applied to very large genetic datasets to infer the contribution of very rare variants lost using other methods. However, we observed apparent biases in these real data, suggesting that more work may be required to understand and mitigate factors that influence IBD-based heritability estimates.
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The genetics of celiac disease: A comprehensive review of clinical implications.
Dieli-Crimi, Romina; Cénit, M Carmen; Núñez, Concepción
2015-11-01
Celiac disease (CD) is a complex immune-related disease with a very strong genetic component. Multiple genetic findings over the last decade have added to the already known MHC influence numerous genetic variants associated to CD susceptibility. Currently, it is well-established that 6 MHC and 39 non-MHC loci, including a higher number of independent genetic variants, are associated to disease risk. Moreover, additional regions have been recently implicated in the disease, which would increase the number of involved loci. Together, the firmly described genetic variants account for roughly 31% of CD heritability, being 25% explained by the MHC influence. These new variants represent markers of disease risk and turn the identification of the causal genes and the causal variants inside the associated loci, as well as their precise biological role on the disease, into a major challenge in CD research. Numerous studies have been developed with this aim showing the high impact of risk variants on gene expression. These studies also indicate a central role of CD4(+) T cells in CD pathogenesis and point to B cells as important players, which is in accordance with the key steps highlighted by the immunological models of pathogenesis. We comprehensively summarize the current knowledge about the genetic architecture of CD, characterized by multiple low-risk variants located within diverse loci which are most likely affecting genes with immune-related functions. These findings are leading to a better understanding of CD pathogenesis and helping in the design of new treatments. The repertoire of potential drug targets for CD has largely broadened last years, bringing us closer to get alternative or complementary treatments to the life-long gluten-free diet, the only effective treatment so far. Epigenetics and microbiota are emerging as potent factors modulating disease risk and putatively affecting disease manifestation, which are also being explored as therapeutic targets. Copyright © 2015 Elsevier Ltd. All rights reserved.
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A variant of special relativity and long-distance astronomy.
Segal, I E
1974-03-01
THE REDSHIFT, MICROWAVE BACKGROUND, AND OTHER OBSERVABLE ASTRONOMICAL FEATURES ARE DEDUCED FROM TWO THEORETICAL ASSUMPTIONS: (1) global space-time is a certain variant of Minkowski space, locally indistinguishable in causality and covariance features but globally admitting the full conformal group as symmetries although having a spherical space component; (2) the true energy operator corresponds to a certain generator of this group which is not globally scale-covariant, whereas laboratory frequency measurements are inevitably such and correspond to the conventional energy operator [unk]/i[unk]/[unk]t.
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Tada, Hayato; Kawashiri, Masa-Aki; Yamagishi, Masakazu
2017-04-01
Dyslipidemias, especially hyper-low-density lipoprotein cholesterolemia and hypertriglyceridemia, are important causal risk factors for coronary artery disease. Comprehensive genotyping using the 'next-generation sequencing' technique has facilitated the investigation of Mendelian dyslipidemias, in addition to Mendelian randomization studies using common genetic variants associated with plasma lipids and coronary artery disease. The beneficial effects of low-density lipoprotein cholesterol-lowering therapies on coronary artery disease have been verified by many randomized controlled trials over the years, and subsequent genetic studies have supported these findings. More recently, Mendelian randomization studies have preceded randomized controlled trials. When the on-target/off-target effects of rare variants and common variants exhibit the same direction, novel drugs targeting molecules identified by investigations of rare Mendelian lipid disorders could be promising. Such a strategy could aid in the search for drug discovery seeds other than those for dyslipidemias.
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Farfan, Ivan D. Barrero; De La Fuente, Gerald N.; Murray, Seth C.; Isakeit, Thomas; Huang, Pei-Cheng; Warburton, Marilyn; Williams, Paul; Windham, Gary L.; Kolomiets, Mike
2015-01-01
The primary maize (Zea mays L.) production areas are in temperate regions throughout the world and this is where most maize breeding is focused. Important but lower yielding maize growing regions such as the sub-tropics experience unique challenges, the greatest of which are drought stress and aflatoxin contamination. Here we used a diversity panel consisting of 346 maize inbred lines originating in temperate, sub-tropical and tropical areas testcrossed to stiff-stalk line Tx714 to investigate these traits. Testcross hybrids were evaluated under irrigated and non-irrigated trials for yield, plant height, ear height, days to anthesis, days to silking and other agronomic traits. Irrigated trials were also inoculated with Aspergillus flavus and evaluated for aflatoxin content. Diverse maize testcrosses out-yielded commercial checks in most trials, which indicated the potential for genetic diversity to improve sub-tropical breeding programs. To identify genomic regions associated with yield, aflatoxin resistance and other important agronomic traits, a genome wide association analysis was performed. Using 60,000 SNPs, this study found 10 quantitative trait variants for grain yield, plant and ear height, and flowering time after stringent multiple test corrections, and after fitting different models. Three of these variants explained 5–10% of the variation in grain yield under both water conditions. Multiple identified SNPs co-localized with previously reported QTL, which narrows the possible location of causal polymorphisms. Novel significant SNPs were also identified. This study demonstrated the potential to use genome wide association studies to identify major variants of quantitative and complex traits such as yield under drought that are still segregating between elite inbred lines. PMID:25714370
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Mancuso, Nicholas; Shi, Huwenbo; Goddard, Pagé; Kichaev, Gleb; Gusev, Alexander; Pasaniuc, Bogdan
2017-03-02
Although genome-wide association studies (GWASs) have identified thousands of risk loci for many complex traits and diseases, the causal variants and genes at these loci remain largely unknown. Here, we introduce a method for estimating the local genetic correlation between gene expression and a complex trait and utilize it to estimate the genetic correlation due to predicted expression between pairs of traits. We integrated gene expression measurements from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide association studies (TWASs). We identified 1,196 genes whose expression is associated with these traits; of these, 168 reside more than 0.5 Mb away from any previously reported GWAS significant variant. We then used our approach to find 43 pairs of traits with significant genetic correlation at the level of predicted expression; of these, eight were not found through genetic correlation at the SNP level. Finally, we used bi-directional regression to find evidence that BMI causally influences triglyceride levels and that triglyceride levels causally influence low-density lipoprotein. Together, our results provide insight into the role of gene expression in the susceptibility of complex traits and diseases. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Kim, Kwangwoo; Bang, So-Young; Ikari, Katsunori; Yoo, Dae Hyun; Cho, Soo-Kyung; Choi, Chan-Bum; Sung, Yoon-Kyoung; Kim, Tae-Hwan; Jun, Jae-Bum; Kang, Young Mo; Suh, Chang-Hee; Shim, Seung-Cheol; Lee, Shin-Seok; Lee, Jisoo; Chung, Won Tae; Kim, Seong-Kyu; Choe, Jung-Yoon; Momohara, Shigeki; Taniguchi, Atsuo; Yamanaka, Hisashi; Nath, Swapan K.; Lee, Hye-Soon; Bae, Sang-Cheol
2016-01-01
Considerable sharing of disease alleles among populations is well-characterized in autoimmune disorders (e.g., rheumatoid arthritis), but there are some exceptional loci showing heterogenic association among populations. Here we investigated genetic variants with distinct effects on the development of rheumatoid arthritis in Asian and European populations. Ancestry-related association heterogeneity was examined using Cochran’s homogeneity tests for the disease association data from large Asian (n = 14,465; 9,299 discovery subjects and 5,166 validation subjects; 4 collections) and European (n = 45,790; 11 collections) rheumatoid arthritis case-control cohorts with Immunochip and genome-wide SNP array data. We identified significant heterogeneity between the two ancestries for the common variants in the GTF2I locus (PHeterogeneity = 9.6 × 10−9 at rs73366469) and showed that this heterogeneity was due to an Asian-specific association effect (ORMeta = 1.37 and PMeta = 4.2 × 10−13 in Asians; ORMeta = 1.00 and PMeta = 1.00 in Europeans). Trans-ancestral comparison and bioinfomatics analysis revealed a plausibly causal or disease-variant-tagging SNP (rs117026326; in linkage disequilibrium with rs73366469), whose minor allele is common in Asians but rare in Europeans. In conclusion, we identified largest-ever effect on Asian rheumatoid arthritis across human non-HLA regions at GTF2I by heterogeneity mapping followed by replication studies, and pinpointed a possible causal variant. PMID:27272985
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Asgari, Samira; McLaren, Paul J; Peake, Jane; Wong, Melanie; Wong, Richard; Bartha, Istvan; Francis, Joshua R; Abarca, Katia; Gelderman, Kyra A; Agyeman, Philipp; Aebi, Christoph; Berger, Christoph; Fellay, Jacques; Schlapbach, Luregn J
2016-01-01
One out of three pediatric sepsis deaths in high income countries occur in previously healthy children. Primary immunodeficiencies (PIDs) have been postulated to underlie fulminant sepsis, but this concept remains to be confirmed in clinical practice. Pseudomonas aeruginosa ( P. aeruginosa ) is a common bacterium mostly associated with health care-related infections in immunocompromised individuals. However, in rare cases, it can cause sepsis in previously healthy children. We used exome sequencing and bioinformatic analysis to systematically search for genetic factors underpinning severe P. aeruginosa infection in the pediatric population. We collected blood samples from 11 previously healthy children, with no family history of immunodeficiency, who presented with severe sepsis due to community-acquired P. aeruginosa bacteremia. Genomic DNA was extracted from blood or tissue samples obtained intravitam or postmortem. We obtained high-coverage exome sequencing data and searched for rare loss-of-function variants. After rigorous filtrations, 12 potentially causal variants were identified. Two out of eight (25%) fatal cases were found to carry novel pathogenic variants in PID genes, including BTK and DNMT3B . This study demonstrates that exome sequencing allows to identify rare, deleterious human genetic variants responsible for fulminant sepsis in apparently healthy children. Diagnosing PIDs in such patients is of high relevance to survivors and affected families. We propose that unusually severe and fatal sepsis cases in previously healthy children should be considered for exome/genome sequencing to search for underlying PIDs.
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Asgari, Samira; McLaren, Paul J.; Peake, Jane; Wong, Melanie; Wong, Richard; Bartha, Istvan; Francis, Joshua R.; Abarca, Katia; Gelderman, Kyra A.; Agyeman, Philipp; Aebi, Christoph; Berger, Christoph; Fellay, Jacques; Schlapbach, Luregn J.; Posfay-Barbe, Klara
2016-01-01
One out of three pediatric sepsis deaths in high income countries occur in previously healthy children. Primary immunodeficiencies (PIDs) have been postulated to underlie fulminant sepsis, but this concept remains to be confirmed in clinical practice. Pseudomonas aeruginosa (P. aeruginosa) is a common bacterium mostly associated with health care-related infections in immunocompromised individuals. However, in rare cases, it can cause sepsis in previously healthy children. We used exome sequencing and bioinformatic analysis to systematically search for genetic factors underpinning severe P. aeruginosa infection in the pediatric population. We collected blood samples from 11 previously healthy children, with no family history of immunodeficiency, who presented with severe sepsis due to community-acquired P. aeruginosa bacteremia. Genomic DNA was extracted from blood or tissue samples obtained intravitam or postmortem. We obtained high-coverage exome sequencing data and searched for rare loss-of-function variants. After rigorous filtrations, 12 potentially causal variants were identified. Two out of eight (25%) fatal cases were found to carry novel pathogenic variants in PID genes, including BTK and DNMT3B. This study demonstrates that exome sequencing allows to identify rare, deleterious human genetic variants responsible for fulminant sepsis in apparently healthy children. Diagnosing PIDs in such patients is of high relevance to survivors and affected families. We propose that unusually severe and fatal sepsis cases in previously healthy children should be considered for exome/genome sequencing to search for underlying PIDs. PMID:27703454
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Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; Karaderi, Tugce; Lempradl, Adelheid; Locke, Adam E; Mahajan, Anubha; Marouli, Eirini; Sivapalaratnam, Suthesh; Young, Kristin L; Alfred, Tamuno; Feitosa, Mary F; Masca, Nicholas GD; Manning, Alisa K; Medina-Gomez, Carolina; Mudgal, Poorva; Ng, Maggie CY; Reiner, Alex P; Vedantam, Sailaja; Willems, Sara M; Winkler, Thomas W; Abecasis, Goncalo; Aben, Katja K; Alam, Dewan S; Alharthi, Sameer E; Allison, Matthew; Amouyel, Philippe; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Bang, Lia E; Barroso, Inês; Bastarache, Lisa; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boehnke, Michael; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Brumat, Marco; Burt, Amber A; Butterworth, Adam S; Campbell, Peter T; Cappellani, Stefania; Carey, David J; Catamo, Eulalia; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der Ida; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Galbany, Jordi Corominas; Cox, Amanda J; Crosslin, David S; Cuellar-Partida, Gabriel; D'Eustacchio, Angela; Danesh, John; Davies, Gail; de Bakker, Paul IW; de Groot, Mark CH; de Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; den Heijer, Martin; den Hollander, Anneke I; den Ruijter, Hester M; Dennis, Joe G; Denny, Josh C; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dubé, Marie-Pierre; Dunning, Alison M; Easton, Douglas F; Edwards, Todd L; Ellinghaus, David; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Farooqi, I. Sadaf; Faul, Jessica D; Fauser, Sascha; Feng, Shuang; Ferrannini, Ele; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franco, Oscar H; Franke, Andre; Franks, Paul W; Friedrich, Nele; Frikke-Schmidt, Ruth; Galesloot, Tessel E.; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Gibson, Jane; Giedraitis, Vilmantas; Gjesing, Anette P; Gordon-Larsen, Penny; Gorski, Mathias; Grabe, Hans-Jörgen; Grant, Struan FA; Grarup, Niels; Griffiths, Helen L; Grove, Megan L; Gudnason, Vilmundur; Gustafsson, Stefan; Haessler, Jeff; Hakonarson, Hakon; Hammerschlag, Anke R; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Have, Christian T; Hayward, Caroline; He, Liang; Heard-Costa, Nancy L; Heath, Andrew C; Heid, Iris M; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Holmen, Oddgeir L; Hovingh, G Kees; Howson, Joanna MM; Hu, Yao; Huang, Paul L; Huffman, Jennifer E; Ikram, M Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jia, Yucheng; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon LR; Karpe, Fredrik; Kathiresan, Sekar; Kee, Frank; Kiemeney, Lambertus A; Kim, Eric; Kitajima, Hidetoshi; Komulainen, Pirjo; Kooner, Jaspal S; Kooperberg, Charles; Korhonen, Tellervo; Kovacs, Peter; Kuivaniemi, Helena; Kutalik, Zoltán; Kuulasmaa, Kari; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A; Lamparter, David; Lange, Ethan M; Lange, Leslie A; Langenberg, Claudia; Larson, Eric B; Lee, Nanette R; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Keng-Hung; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Ching-Ti; Liu, Dajiang J; Liu, Yongmei; Lo, Ken Sin; Lophatananon, Artitaya; Lotery, Andrew J; Loukola, Anu; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Männistö, Satu; Marenne, Gaëlle; Mazul, Angela L; McCarthy, Mark I; McKean-Cowdin, Roberta; Medland, Sarah E; Meidtner, Karina; Milani, Lili; Mistry, Vanisha; Mitchell, Paul; Mohlke, Karen L; Moilanen, Leena; Moitry, Marie; Montgomery, Grant W; Mook-Kanamori, Dennis O; Moore, Carmel; Mori, Trevor A; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Narisu, Narisu; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Nyholt, Dale R; O'Connel, Jeffrey R; O’Donoghue, Michelle L.; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin NA; Palmer, Nicholette D; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John RB; Pers, Tune H; Person, Thomas N; Peters, Annette; Petersen, Eva RB; Peyser, Patricia A; Pirie, Ailith; Polasek, Ozren; Polderman, Tinca J; Puolijoki, Hannu; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Renström, Frida; Rheinberger, Myriam; Ridker, Paul M; Rioux, John D; Rivas, Manuel A; Roberts, David J; Robertson, Neil R; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sapkota, Yadav; Sattar, Naveed; Schoen, Robert E; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati H; Sheu, Wayne H-H; Sim, Xueling; Slater, Andrew J; Small, Kerrin S; Smith, Albert Vernon; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Stefansson, Kari; Steinthorsdottir, Valgerdur; Stirrups, Kathleen E; Strauch, Konstantin; Stringham, Heather M; Stumvoll, Michael; Sun, Liang; Surendran, Praveen; Swift, Amy J; Tada, Hayato; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Uusitupa, Matti; van der Laan, Sander W; van Duijn, Cornelia M; van Leeuwen, Nienke; van Setten, Jessica; Vanhala, Mauno; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Velez Edwards, Digna R; Vermeulen, Sita H; Veronesi, Giovanni; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Völker, Uwe; Vuckovic, Dragana; Wagenknecht, Lynne E; Walker, Mark; Wallentin, Lars; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Ware, Erin B; Wareham, Nicholas J; Warren, Helen R; Waterworth, Dawn M; Wessel, Jennifer; White, Harvey D; Willer, Cristen J; Wilson, James G; Witte, Daniel R; Wood, Andrew R; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zhou, Wei; Zondervan, Krina T; Rotter, Jerome I; Pospisilik, John A; Rivadeneira, Fernando; Borecki, Ingrid B; Deloukas, Panos; Frayling, Timothy M; Lettre, Guillaume; North, Kari E; Lindgren, Cecilia M; Hirschhorn, Joel N; Loos, Ruth JF
2018-01-01
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, non-coding variants from which pinpointing causal genes remains challenging. Here, we combined data from 718,734 individuals to discover rare and low-frequency (MAF<5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which eight in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2, ZNF169) newly implicated in human obesity, two (MC4R, KSR2) previously observed in extreme obesity, and two variants in GIPR. Effect sizes of rare variants are ~10 times larger than of common variants, with the largest effect observed in carriers of an MC4R stop-codon (p.Tyr35Ter, MAF=0.01%), weighing ~7kg more than non-carriers. Pathway analyses confirmed enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically-supported therapeutic targets to treat obesity. PMID:29273807
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C-terminal oligomerization of podocin mediates interallelic interactions.
Stráner, Pál; Balogh, Eszter; Schay, Gusztáv; Arrondel, Christelle; Mikó, Ágnes; L'Auné, Gerda; Benmerah, Alexandre; Perczel, András; K Menyhárd, Dóra; Antignac, Corinne; Mollet, Géraldine; Tory, Kálmán
2018-07-01
Interallelic interactions of membrane proteins are not taken into account while evaluating the pathogenicity of sequence variants in autosomal recessive disorders. Podocin, a membrane-anchored component of the slit diaphragm, is encoded by NPHS2, the major gene mutated in hereditary podocytopathies. We formerly showed that its R229Q variant is only pathogenic when trans-associated to specific 3' mutations and suggested the causal role of an abnormal C-terminal dimerization. Here we show by FRET analysis and size exclusion chromatography that podocin oligomerization occurs exclusively through the C-terminal tail (residues 283-382): principally through the first C-terminal helical region (H1, 283-313), which forms a coiled coil as shown by circular dichroism spectroscopy, and through the 332-348 region. We show the principal role of the oligomerization sites in mediating interallelic interactions: while the monomer-forming R286Tfs*17 podocin remains membranous irrespective of the coexpressed podocin variant identity, podocin variants with an intact H1 significantly influence each other's localization (r 2 = 0.68, P = 9.2 × 10 -32 ). The dominant negative effect resulting in intracellular retention of the pathogenic F344Lfs*4-R229Q heterooligomer occurs in parallel with a reduction in the FRET efficiency, suggesting the causal role of a conformational rearrangement. On the other hand, oligomerization can also promote the membrane localization: it can prevent the endocytosis of F344Lfs*4 or F344* podocin mutants induced by C-terminal truncation. In conclusion, C-terminal oligomerization of podocin can mediate both a dominant negative effect and interallelic complementation. Interallelic interactions of NPHS2 are not restricted to the R229Q variant and have to be considered in compound heterozygous individuals. Copyright © 2018 Elsevier B.V. All rights reserved.
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Common variants associated with plasma triglycerides and risk for coronary artery disease
USDA-ARS?s Scientific Manuscript database
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common va...
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Genotype imputation in a tropical crossbred dairy cattle population
USDA-ARS?s Scientific Manuscript database
The application of new tools, such as genomic selection and genotype imputation, still presents challenges in crossbred populations because relationships of causal variants with markers may vary across breeds. In order to make genomic selection more cost effective, cheap low density chips are often ...
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Common variants associated with plasma triglycerides and risk for coronary artery disease.
Do, Ron; Willer, Cristen J; Schmidt, Ellen M; Sengupta, Sebanti; Gao, Chi; Peloso, Gina M; Gustafsson, Stefan; Kanoni, Stavroula; Ganna, Andrea; Chen, Jin; Buchkovich, Martin L; Mora, Samia; Beckmann, Jacques S; Bragg-Gresham, Jennifer L; Chang, Hsing-Yi; Demirkan, Ayşe; Den Hertog, Heleen M; Donnelly, Louise A; Ehret, Georg B; Esko, Tõnu; Feitosa, Mary F; Ferreira, Teresa; Fischer, Krista; Fontanillas, Pierre; Fraser, Ross M; Freitag, Daniel F; Gurdasani, Deepti; Heikkilä, Kauko; Hyppönen, Elina; Isaacs, Aaron; Jackson, Anne U; Johansson, Asa; Johnson, Toby; Kaakinen, Marika; Kettunen, Johannes; Kleber, Marcus E; Li, Xiaohui; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Magnusson, Patrik K E; Mangino, Massimo; Mihailov, Evelin; Montasser, May E; Müller-Nurasyid, Martina; Nolte, Ilja M; O'Connell, Jeffrey R; Palmer, Cameron D; Perola, Markus; Petersen, Ann-Kristin; Sanna, Serena; Saxena, Richa; Service, Susan K; Shah, Sonia; Shungin, Dmitry; Sidore, Carlo; Song, Ci; Strawbridge, Rona J; Surakka, Ida; Tanaka, Toshiko; Teslovich, Tanya M; Thorleifsson, Gudmar; Van den Herik, Evita G; Voight, Benjamin F; Volcik, Kelly A; Waite, Lindsay L; Wong, Andrew; Wu, Ying; Zhang, Weihua; Absher, Devin; Asiki, Gershim; Barroso, Inês; Been, Latonya F; Bolton, Jennifer L; Bonnycastle, Lori L; Brambilla, Paolo; Burnett, Mary S; Cesana, Giancarlo; Dimitriou, Maria; Doney, Alex S F; Döring, Angela; Elliott, Paul; Epstein, Stephen E; Eyjolfsson, Gudmundur Ingi; Gigante, Bruna; Goodarzi, Mark O; Grallert, Harald; Gravito, Martha L; Groves, Christopher J; Hallmans, Göran; Hartikainen, Anna-Liisa; Hayward, Caroline; Hernandez, Dena; Hicks, Andrew A; Holm, Hilma; Hung, Yi-Jen; Illig, Thomas; Jones, Michelle R; Kaleebu, Pontiano; Kastelein, John J P; Khaw, Kay-Tee; Kim, Eric; Klopp, Norman; Komulainen, Pirjo; Kumari, Meena; Langenberg, Claudia; Lehtimäki, Terho; Lin, Shih-Yi; Lindström, Jaana; Loos, Ruth J F; Mach, François; McArdle, Wendy L; Meisinger, Christa; Mitchell, Braxton D; Müller, Gabrielle; Nagaraja, Ramaiah; Narisu, Narisu; Nieminen, Tuomo V M; Nsubuga, Rebecca N; Olafsson, Isleifur; Ong, Ken K; Palotie, Aarno; Papamarkou, Theodore; Pomilla, Cristina; Pouta, Anneli; Rader, Daniel J; Reilly, Muredach P; Ridker, Paul M; Rivadeneira, Fernando; Rudan, Igor; Ruokonen, Aimo; Samani, Nilesh; Scharnagl, Hubert; Seeley, Janet; Silander, Kaisa; Stančáková, Alena; Stirrups, Kathleen; Swift, Amy J; Tiret, Laurence; Uitterlinden, Andre G; van Pelt, L Joost; Vedantam, Sailaja; Wainwright, Nicholas; Wijmenga, Cisca; Wild, Sarah H; Willemsen, Gonneke; Wilsgaard, Tom; Wilson, James F; Young, Elizabeth H; Zhao, Jing Hua; Adair, Linda S; Arveiler, Dominique; Assimes, Themistocles L; Bandinelli, Stefania; Bennett, Franklyn; Bochud, Murielle; Boehm, Bernhard O; Boomsma, Dorret I; Borecki, Ingrid B; Bornstein, Stefan R; Bovet, Pascal; Burnier, Michel; Campbell, Harry; Chakravarti, Aravinda; Chambers, John C; Chen, Yii-Der Ida; Collins, Francis S; Cooper, Richard S; Danesh, John; Dedoussis, George; de Faire, Ulf; Feranil, Alan B; Ferrières, Jean; Ferrucci, Luigi; Freimer, Nelson B; Gieger, Christian; Groop, Leif C; Gudnason, Vilmundur; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B; Hingorani, Aroon; Hirschhorn, Joel N; Hofman, Albert; Hovingh, G Kees; Hsiung, Chao Agnes; Humphries, Steve E; Hunt, Steven C; Hveem, Kristian; Iribarren, Carlos; Järvelin, Marjo-Riitta; Jula, Antti; Kähönen, Mika; Kaprio, Jaakko; Kesäniemi, Antero; Kivimaki, Mika; Kooner, Jaspal S; Koudstaal, Peter J; Krauss, Ronald M; Kuh, Diana; Kuusisto, Johanna; Kyvik, Kirsten O; Laakso, Markku; Lakka, Timo A; Lind, Lars; Lindgren, Cecilia M; Martin, Nicholas G; März, Winfried; McCarthy, Mark I; McKenzie, Colin A; Meneton, Pierre; Metspalu, Andres; Moilanen, Leena; Morris, Andrew D; Munroe, Patricia B; Njølstad, Inger; Pedersen, Nancy L; Power, Chris; Pramstaller, Peter P; Price, Jackie F; Psaty, Bruce M; Quertermous, Thomas; Rauramaa, Rainer; Saleheen, Danish; Salomaa, Veikko; Sanghera, Dharambir K; Saramies, Jouko; Schwarz, Peter E H; Sheu, Wayne H-H; Shuldiner, Alan R; Siegbahn, Agneta; Spector, Tim D; Stefansson, Kari; Strachan, David P; Tayo, Bamidele O; Tremoli, Elena; Tuomilehto, Jaakko; Uusitupa, Matti; van Duijn, Cornelia M; Vollenweider, Peter; Wallentin, Lars; Wareham, Nicholas J; Whitfield, John B; Wolffenbuttel, Bruce H R; Altshuler, David; Ordovas, Jose M; Boerwinkle, Eric; Palmer, Colin N A; Thorsteinsdottir, Unnur; Chasman, Daniel I; Rotter, Jerome I; Franks, Paul W; Ripatti, Samuli; Cupples, L Adrienne; Sandhu, Manjinder S; Rich, Stephen S; Boehnke, Michael; Deloukas, Panos; Mohlke, Karen L; Ingelsson, Erik; Abecasis, Goncalo R; Daly, Mark J; Neale, Benjamin M; Kathiresan, Sekar
2013-11-01
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
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Common variants associated with plasma triglycerides and risk for coronary artery disease
Do, Ron; Willer, Cristen J.; Schmidt, Ellen M.; Sengupta, Sebanti; Gao, Chi; Peloso, Gina M.; Gustafsson, Stefan; Kanoni, Stavroula; Ganna, Andrea; Chen, Jin; Buchkovich, Martin L.; Mora, Samia; Beckmann, Jacques S.; Bragg-Gresham, Jennifer L.; Chang, Hsing-Yi; Demirkan, Ayşe; Den Hertog, Heleen M.; Donnelly, Louise A.; Ehret, Georg B.; Esko, Tõnu; Feitosa, Mary F.; Ferreira, Teresa; Fischer, Krista; Fontanillas, Pierre; Fraser, Ross M.; Freitag, Daniel F.; Gurdasani, Deepti; Heikkilä, Kauko; Hyppönen, Elina; Isaacs, Aaron; Jackson, Anne U.; Johansson, Åsa; Johnson, Toby; Kaakinen, Marika; Kettunen, Johannes; Kleber, Marcus E.; Li, Xiaohui; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Magnusson, Patrik K.E.; Mangino, Massimo; Mihailov, Evelin; Montasser, May E.; Müller-Nurasyid, Martina; Nolte, Ilja M.; O'Connell, Jeffrey R.; Palmer, Cameron D.; Perola, Markus; Petersen, Ann-Kristin; Sanna, Serena; Saxena, Richa; Service, Susan K.; Shah, Sonia; Shungin, Dmitry; Sidore, Carlo; Song, Ci; Strawbridge, Rona J.; Surakka, Ida; Tanaka, Toshiko; Teslovich, Tanya M.; Thorleifsson, Gudmar; Van den Herik, Evita G.; Voight, Benjamin F.; Volcik, Kelly A.; Waite, Lindsay L.; Wong, Andrew; Wu, Ying; Zhang, Weihua; Absher, Devin; Asiki, Gershim; Barroso, Inês; Been, Latonya F.; Bolton, Jennifer L.; Bonnycastle, Lori L; Brambilla, Paolo; Burnett, Mary S.; Cesana, Giancarlo; Dimitriou, Maria; Doney, Alex S.F.; Döring, Angela; Elliott, Paul; Epstein, Stephen E.; Eyjolfsson, Gudmundur Ingi; Gigante, Bruna; Goodarzi, Mark O.; Grallert, Harald; Gravito, Martha L.; Groves, Christopher J.; Hallmans, Göran; Hartikainen, Anna-Liisa; Hayward, Caroline; Hernandez, Dena; Hicks, Andrew A.; Holm, Hilma; Hung, Yi-Jen; Illig, Thomas; Jones, Michelle R.; Kaleebu, Pontiano; Kastelein, John J.P.; Khaw, Kay-Tee; Kim, Eric; Klopp, Norman; Komulainen, Pirjo; Kumari, Meena; Langenberg, Claudia; Lehtimäki, Terho; Lin, Shih-Yi; Lindström, Jaana; Loos, Ruth J.F.; Mach, François; McArdle, Wendy L; Meisinger, Christa; Mitchell, Braxton D.; Müller, Gabrielle; Nagaraja, Ramaiah; Narisu, Narisu; Nieminen, Tuomo V.M.; Nsubuga, Rebecca N.; Olafsson, Isleifur; Ong, Ken K.; Palotie, Aarno; Papamarkou, Theodore; Pomilla, Cristina; Pouta, Anneli; Rader, Daniel J.; Reilly, Muredach P.; Ridker, Paul M.; Rivadeneira, Fernando; Rudan, Igor; Ruokonen, Aimo; Samani, Nilesh; Scharnagl, Hubert; Seeley, Janet; Silander, Kaisa; Stančáková, Alena; Stirrups, Kathleen; Swift, Amy J.; Tiret, Laurence; Uitterlinden, Andre G.; van Pelt, L. Joost; Vedantam, Sailaja; Wainwright, Nicholas; Wijmenga, Cisca; Wild, Sarah H.; Willemsen, Gonneke; Wilsgaard, Tom; Wilson, James F.; Young, Elizabeth H.; Zhao, Jing Hua; Adair, Linda S.; Arveiler, Dominique; Assimes, Themistocles L.; Bandinelli, Stefania; Bennett, Franklyn; Bochud, Murielle; Boehm, Bernhard O.; Boomsma, Dorret I.; Borecki, Ingrid B.; Bornstein, Stefan R.; Bovet, Pascal; Burnier, Michel; Campbell, Harry; Chakravarti, Aravinda; Chambers, John C.; Chen, Yii-Der Ida; Collins, Francis S.; Cooper, Richard S.; Danesh, John; Dedoussis, George; de Faire, Ulf; Feranil, Alan B.; Ferrières, Jean; Ferrucci, Luigi; Freimer, Nelson B.; Gieger, Christian; Groop, Leif C.; Gudnason, Vilmundur; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B.; Hingorani, Aroon; Hirschhorn, Joel N.; Hofman, Albert; Hovingh, G. Kees; Hsiung, Chao Agnes; Humphries, Steve E.; Hunt, Steven C.; Hveem, Kristian; Iribarren, Carlos; Järvelin, Marjo-Riitta; Jula, Antti; Kähönen, Mika; Kaprio, Jaakko; Kesäniemi, Antero; Kivimaki, Mika; Kooner, Jaspal S.; Koudstaal, Peter J.; Krauss, Ronald M.; Kuh, Diana; Kuusisto, Johanna; Kyvik, Kirsten O.; Laakso, Markku; Lakka, Timo A.; Lind, Lars; Lindgren, Cecilia M.; Martin, Nicholas G.; März, Winfried; McCarthy, Mark I.; McKenzie, Colin A.; Meneton, Pierre; Metspalu, Andres; Moilanen, Leena; Morris, Andrew D.; Munroe, Patricia B.; Njølstad, Inger; Pedersen, Nancy L.; Power, Chris; Pramstaller, Peter P.; Price, Jackie F.; Psaty, Bruce M.; Quertermous, Thomas; Rauramaa, Rainer; Saleheen, Danish; Salomaa, Veikko; Sanghera, Dharambir K.; Saramies, Jouko; Schwarz, Peter E.H.; Sheu, Wayne H-H; Shuldiner, Alan R.; Siegbahn, Agneta; Spector, Tim D.; Stefansson, Kari; Strachan, David P.; Tayo, Bamidele O.; Tremoli, Elena; Tuomilehto, Jaakko; Uusitupa, Matti; van Duijn, Cornelia M.; Vollenweider, Peter; Wallentin, Lars; Wareham, Nicholas J.; Whitfield, John B.; Wolffenbuttel, Bruce H.R.; Altshuler, David; Ordovas, Jose M.; Boerwinkle, Eric; Palmer, Colin N.A.; Thorsteinsdottir, Unnur; Chasman, Daniel I.; Rotter, Jerome I.; Franks, Paul W.; Ripatti, Samuli; Cupples, L. Adrienne; Sandhu, Manjinder S.; Rich, Stephen S.; Boehnke, Michael; Deloukas, Panos; Mohlke, Karen L.; Ingelsson, Erik; Abecasis, Goncalo R.; Daly, Mark J.; Neale, Benjamin M.; Kathiresan, Sekar
2013-01-01
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD. PMID:24097064
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Hu, Zhi-Liang; Ramos, Antonio M.; Humphray, Sean J.; Rogers, Jane; Reecy, James M.; Rothschild, Max F.
2011-01-01
The newly available pig genome sequence has provided new information to fine map quantitative trait loci (QTL) in order to eventually identify causal variants. With targeted genomic sequencing efforts, we were able to obtain high quality BAC sequences that cover a region on pig chromosome 17 where a number of meat quality QTL have been previously discovered. Sequences from 70 BAC clones were assembled to form an 8-Mbp contig. Subsequently, we successfully mapped five previously identified QTL, three for meat color and two for lactate related traits, to the contig. With an additional 25 genetic markers that were identified by sequence comparison, we were able to carry out further linkage disequilibrium analysis to narrow down the genomic locations of these QTL, which allowed identification of the chromosomal regions that likely contain the causative variants. This research has provided one practical approach to combine genetic and molecular information for QTL mining. PMID:22303339
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Genetics: Implications for Prevention and Management of Coronary Artery Disease.
Assimes, Themistocles L; Roberts, Robert
2016-12-27
An exciting new era has dawned for the prevention and management of coronary artery disease (CAD) utilizing genetic risk variants. The recent identification of over 60 susceptibility loci for CAD confirms not only the importance of established risk factors, but also the existence of many novel causal pathways that are expected to improve our understanding of the genetic basis of CAD and facilitate the development of new therapeutic agents over time. Concurrently, Mendelian randomization studies have provided intriguing insights on the causal relationship between CAD-related traits, and highlight the potential benefits of long-term modifications of risk factors. Last, genetic risk scores of CAD may serve not only as prognostic, but also as predictive markers, and carry the potential to considerably improve the delivery of established prevention strategies. This review will summarize the evolution and discovery of genetic risk variants for CAD and their current and future clinical applications. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
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Burgess, Stephen; Daniel, Rhian M; Butterworth, Adam S; Thompson, Simon G
2015-01-01
Background: Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation. Methods: We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid. Results: These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates. Conclusions: These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes. PMID:25150977
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Turcot, Valérie; Lu, Yingchang; Highland, Heather M; Schurmann, Claudia; Justice, Anne E; Fine, Rebecca S; Bradfield, Jonathan P; Esko, Tõnu; Giri, Ayush; Graff, Mariaelisa; Guo, Xiuqing; Hendricks, Audrey E; Karaderi, Tugce; Lempradl, Adelheid; Locke, Adam E; Mahajan, Anubha; Marouli, Eirini; Sivapalaratnam, Suthesh; Young, Kristin L; Alfred, Tamuno; Feitosa, Mary F; Masca, Nicholas G D; Manning, Alisa K; Medina-Gomez, Carolina; Mudgal, Poorva; Ng, Maggie C Y; Reiner, Alex P; Vedantam, Sailaja; Willems, Sara M; Winkler, Thomas W; Abecasis, Gonçalo; Aben, Katja K; Alam, Dewan S; Alharthi, Sameer E; Allison, Matthew; Amouyel, Philippe; Asselbergs, Folkert W; Auer, Paul L; Balkau, Beverley; Bang, Lia E; Barroso, Inês; Bastarache, Lisa; Benn, Marianne; Bergmann, Sven; Bielak, Lawrence F; Blüher, Matthias; Boehnke, Michael; Boeing, Heiner; Boerwinkle, Eric; Böger, Carsten A; Bork-Jensen, Jette; Bots, Michiel L; Bottinger, Erwin P; Bowden, Donald W; Brandslund, Ivan; Breen, Gerome; Brilliant, Murray H; Broer, Linda; Brumat, Marco; Burt, Amber A; Butterworth, Adam S; Campbell, Peter T; Cappellani, Stefania; Carey, David J; Catamo, Eulalia; Caulfield, Mark J; Chambers, John C; Chasman, Daniel I; Chen, Yii-Der I; Chowdhury, Rajiv; Christensen, Cramer; Chu, Audrey Y; Cocca, Massimiliano; Collins, Francis S; Cook, James P; Corley, Janie; Corominas Galbany, Jordi; Cox, Amanda J; Crosslin, David S; Cuellar-Partida, Gabriel; D'Eustacchio, Angela; Danesh, John; Davies, Gail; Bakker, Paul I W; Groot, Mark C H; Mutsert, Renée; Deary, Ian J; Dedoussis, George; Demerath, Ellen W; Heijer, Martin; Hollander, Anneke I; Ruijter, Hester M; Dennis, Joe G; Denny, Josh C; Di Angelantonio, Emanuele; Drenos, Fotios; Du, Mengmeng; Dubé, Marie-Pierre; Dunning, Alison M; Easton, Douglas F; Edwards, Todd L; Ellinghaus, David; Ellinor, Patrick T; Elliott, Paul; Evangelou, Evangelos; Farmaki, Aliki-Eleni; Farooqi, I Sadaf; Faul, Jessica D; Fauser, Sascha; Feng, Shuang; Ferrannini, Ele; Ferrieres, Jean; Florez, Jose C; Ford, Ian; Fornage, Myriam; Franco, Oscar H; Franke, Andre; Franks, Paul W; Friedrich, Nele; Frikke-Schmidt, Ruth; Galesloot, Tessel E; Gan, Wei; Gandin, Ilaria; Gasparini, Paolo; Gibson, Jane; Giedraitis, Vilmantas; Gjesing, Anette P; Gordon-Larsen, Penny; Gorski, Mathias; Grabe, Hans-Jörgen; Grant, Struan F A; Grarup, Niels; Griffiths, Helen L; Grove, Megan L; Gudnason, Vilmundur; Gustafsson, Stefan; Haessler, Jeff; Hakonarson, Hakon; Hammerschlag, Anke R; Hansen, Torben; Harris, Kathleen Mullan; Harris, Tamara B; Hattersley, Andrew T; Have, Christian T; Hayward, Caroline; He, Liang; Heard-Costa, Nancy L; Heath, Andrew C; Heid, Iris M; Helgeland, Øyvind; Hernesniemi, Jussi; Hewitt, Alex W; Holmen, Oddgeir L; Hovingh, G Kees; Howson, Joanna M M; Hu, Yao; Huang, Paul L; Huffman, Jennifer E; Ikram, M Arfan; Ingelsson, Erik; Jackson, Anne U; Jansson, Jan-Håkan; Jarvik, Gail P; Jensen, Gorm B; Jia, Yucheng; Johansson, Stefan; Jørgensen, Marit E; Jørgensen, Torben; Jukema, J Wouter; Kahali, Bratati; Kahn, René S; Kähönen, Mika; Kamstrup, Pia R; Kanoni, Stavroula; Kaprio, Jaakko; Karaleftheri, Maria; Kardia, Sharon L R; Karpe, Fredrik; Kathiresan, Sekar; Kee, Frank; Kiemeney, Lambertus A; Kim, Eric; Kitajima, Hidetoshi; Komulainen, Pirjo; Kooner, Jaspal S; Kooperberg, Charles; Korhonen, Tellervo; Kovacs, Peter; Kuivaniemi, Helena; Kutalik, Zoltán; Kuulasmaa, Kari; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A; Lamparter, David; Lange, Ethan M; Lange, Leslie A; Langenberg, Claudia; Larson, Eric B; Lee, Nanette R; Lehtimäki, Terho; Lewis, Cora E; Li, Huaixing; Li, Jin; Li-Gao, Ruifang; Lin, Honghuang; Lin, Keng-Hung; Lin, Li-An; Lin, Xu; Lind, Lars; Lindström, Jaana; Linneberg, Allan; Liu, Ching-Ti; Liu, Dajiang J; Liu, Yongmei; Lo, Ken S; Lophatananon, Artitaya; Lotery, Andrew J; Loukola, Anu; Luan, Jian'an; Lubitz, Steven A; Lyytikäinen, Leo-Pekka; Männistö, Satu; Marenne, Gaëlle; Mazul, Angela L; McCarthy, Mark I; McKean-Cowdin, Roberta; Medland, Sarah E; Meidtner, Karina; Milani, Lili; Mistry, Vanisha; Mitchell, Paul; Mohlke, Karen L; Moilanen, Leena; Moitry, Marie; Montgomery, Grant W; Mook-Kanamori, Dennis O; Moore, Carmel; Mori, Trevor A; Morris, Andrew D; Morris, Andrew P; Müller-Nurasyid, Martina; Munroe, Patricia B; Nalls, Mike A; Narisu, Narisu; Nelson, Christopher P; Neville, Matt; Nielsen, Sune F; Nikus, Kjell; Njølstad, Pål R; Nordestgaard, Børge G; Nyholt, Dale R; O'Connel, Jeffrey R; O'Donoghue, Michelle L; Olde Loohuis, Loes M; Ophoff, Roel A; Owen, Katharine R; Packard, Chris J; Padmanabhan, Sandosh; Palmer, Colin N A; Palmer, Nicholette D; Pasterkamp, Gerard; Patel, Aniruddh P; Pattie, Alison; Pedersen, Oluf; Peissig, Peggy L; Peloso, Gina M; Pennell, Craig E; Perola, Markus; Perry, James A; Perry, John R B; Pers, Tune H; Person, Thomas N; Peters, Annette; Petersen, Eva R B; Peyser, Patricia A; Pirie, Ailith; Polasek, Ozren; Polderman, Tinca J; Puolijoki, Hannu; Raitakari, Olli T; Rasheed, Asif; Rauramaa, Rainer; Reilly, Dermot F; Renström, Frida; Rheinberger, Myriam; Ridker, Paul M; Rioux, John D; Rivas, Manuel A; Roberts, David J; Robertson, Neil R; Robino, Antonietta; Rolandsson, Olov; Rudan, Igor; Ruth, Katherine S; Saleheen, Danish; Salomaa, Veikko; Samani, Nilesh J; Sapkota, Yadav; Sattar, Naveed; Schoen, Robert E; Schreiner, Pamela J; Schulze, Matthias B; Scott, Robert A; Segura-Lepe, Marcelo P; Shah, Svati H; Sheu, Wayne H-H; Sim, Xueling; Slater, Andrew J; Small, Kerrin S; Smith, Albert V; Southam, Lorraine; Spector, Timothy D; Speliotes, Elizabeth K; Starr, John M; Stefansson, Kari; Steinthorsdottir, Valgerdur; Stirrups, Kathleen E; Strauch, Konstantin; Stringham, Heather M; Stumvoll, Michael; Sun, Liang; Surendran, Praveen; Swift, Amy J; Tada, Hayato; Tansey, Katherine E; Tardif, Jean-Claude; Taylor, Kent D; Teumer, Alexander; Thompson, Deborah J; Thorleifsson, Gudmar; Thorsteinsdottir, Unnur; Thuesen, Betina H; Tönjes, Anke; Tromp, Gerard; Trompet, Stella; Tsafantakis, Emmanouil; Tuomilehto, Jaakko; Tybjaerg-Hansen, Anne; Tyrer, Jonathan P; Uher, Rudolf; Uitterlinden, André G; Uusitupa, Matti; Laan, Sander W; Duijn, Cornelia M; Leeuwen, Nienke; van Setten, Jessica; Vanhala, Mauno; Varbo, Anette; Varga, Tibor V; Varma, Rohit; Velez Edwards, Digna R; Vermeulen, Sita H; Veronesi, Giovanni; Vestergaard, Henrik; Vitart, Veronique; Vogt, Thomas F; Völker, Uwe; Vuckovic, Dragana; Wagenknecht, Lynne E; Walker, Mark; Wallentin, Lars; Wang, Feijie; Wang, Carol A; Wang, Shuai; Wang, Yiqin; Ware, Erin B; Wareham, Nicholas J; Warren, Helen R; Waterworth, Dawn M; Wessel, Jennifer; White, Harvey D; Willer, Cristen J; Wilson, James G; Witte, Daniel R; Wood, Andrew R; Wu, Ying; Yaghootkar, Hanieh; Yao, Jie; Yao, Pang; Yerges-Armstrong, Laura M; Young, Robin; Zeggini, Eleftheria; Zhan, Xiaowei; Zhang, Weihua; Zhao, Jing Hua; Zhao, Wei; Zhao, Wei; Zhou, Wei; Zondervan, Krina T; Rotter, Jerome I; Pospisilik, John A; Rivadeneira, Fernando; Borecki, Ingrid B; Deloukas, Panos; Frayling, Timothy M; Lettre, Guillaume; North, Kari E; Lindgren, Cecilia M; Hirschhorn, Joel N; Loos, Ruth J F
2018-01-01
Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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Zhang, Kunlin; Chang, Suhua; Cui, Sijia; Guo, Liyuan; Zhang, Liuyan; Wang, Jing
2011-07-01
Genome-wide association study (GWAS) is widely utilized to identify genes involved in human complex disease or some other trait. One key challenge for GWAS data interpretation is to identify causal SNPs and provide profound evidence on how they affect the trait. Currently, researches are focusing on identification of candidate causal variants from the most significant SNPs of GWAS, while there is lack of support on biological mechanisms as represented by pathways. Although pathway-based analysis (PBA) has been designed to identify disease-related pathways by analyzing the full list of SNPs from GWAS, it does not emphasize on interpreting causal SNPs. To our knowledge, so far there is no web server available to solve the challenge for GWAS data interpretation within one analytical framework. ICSNPathway is developed to identify candidate causal SNPs and their corresponding candidate causal pathways from GWAS by integrating linkage disequilibrium (LD) analysis, functional SNP annotation and PBA. ICSNPathway provides a feasible solution to bridge the gap between GWAS and disease mechanism study by generating hypothesis of SNP → gene → pathway(s). The ICSNPathway server is freely available at http://icsnpathway.psych.ac.cn/.
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Theodoratou, Evropi; Farrington, Susan M.; Tenesa, Albert; Dunlop, Malcolm G.; McKeigue, Paul; Campbell, Harry
2013-01-01
Introduction Vitamin D deficiency has been associated with increased risk of colorectal cancer (CRC), but causal relationship has not yet been confirmed. We investigate the direction of causation between vitamin D and CRC by extending the conventional approaches to allow pleiotropic relationships and by explicitly modelling unmeasured confounders. Methods Plasma 25-hydroxyvitamin D (25-OHD), genetic variants associated with 25-OHD and CRC, and other relevant information was available for 2645 individuals (1057 CRC cases and 1588 controls) and included in the model. We investigate whether 25-OHD is likely to be causally associated with CRC, or vice versa, by selecting the best modelling hypothesis according to Bayesian predictive scores. We examine consistency for a range of prior assumptions. Results Model comparison showed preference for the causal association between low 25-OHD and CRC over the reverse causal hypothesis. This was confirmed for posterior mean deviances obtained for both models (11.5 natural log units in favour of the causal model), and also for deviance information criteria (DIC) computed for a range of prior distributions. Overall, models ignoring hidden confounding or pleiotropy had significantly poorer DIC scores. Conclusion Results suggest causal association between 25-OHD and colorectal cancer, and support the need for randomised clinical trials for further confirmations. PMID:23717431
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Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li
2014-01-01
Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158
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Negligible impact of rare autoimmune-locus coding-region variants on missing heritability.
Hunt, Karen A; Mistry, Vanisha; Bockett, Nicholas A; Ahmad, Tariq; Ban, Maria; Barker, Jonathan N; Barrett, Jeffrey C; Blackburn, Hannah; Brand, Oliver; Burren, Oliver; Capon, Francesca; Compston, Alastair; Gough, Stephen C L; Jostins, Luke; Kong, Yong; Lee, James C; Lek, Monkol; MacArthur, Daniel G; Mansfield, John C; Mathew, Christopher G; Mein, Charles A; Mirza, Muddassar; Nutland, Sarah; Onengut-Gumuscu, Suna; Papouli, Efterpi; Parkes, Miles; Rich, Stephen S; Sawcer, Steven; Satsangi, Jack; Simmonds, Matthew J; Trembath, Richard C; Walker, Neil M; Wozniak, Eva; Todd, John A; Simpson, Michael A; Plagnol, Vincent; van Heel, David A
2013-06-13
Genome-wide association studies (GWAS) have identified common variants of modest-effect size at hundreds of loci for common autoimmune diseases; however, a substantial fraction of heritability remains unexplained, to which rare variants may contribute. To discover rare variants and test them for association with a phenotype, most studies re-sequence a small initial sample size and then genotype the discovered variants in a larger sample set. This approach fails to analyse a large fraction of the rare variants present in the entire sample set. Here we perform simultaneous amplicon-sequencing-based variant discovery and genotyping for coding exons of 25 GWAS risk genes in 41,911 UK residents of white European origin, comprising 24,892 subjects with six autoimmune disease phenotypes and 17,019 controls, and show that rare coding-region variants at known loci have a negligible role in common autoimmune disease susceptibility. These results do not support the rare-variant synthetic genome-wide-association hypothesis (in which unobserved rare causal variants lead to association detected at common tag variants). Many known autoimmune disease risk loci contain multiple, independently associated, common and low-frequency variants, and so genes at these loci are a priori stronger candidates for harbouring rare coding-region variants than other genes. Our data indicate that the missing heritability for common autoimmune diseases may not be attributable to the rare coding-region variant portion of the allelic spectrum, but perhaps, as others have proposed, may be a result of many common-variant loci of weak effect.
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Diogo, Dorothée; Bastarache, Lisa; Liao, Katherine P.; Graham, Robert R.; Fulton, Robert S.; Greenberg, Jeffrey D.; Eyre, Steve; Bowes, John; Cui, Jing; Lee, Annette; Pappas, Dimitrios A.; Kremer, Joel M.; Barton, Anne; Coenen, Marieke J. H.; Franke, Barbara; Kiemeney, Lambertus A.; Mariette, Xavier; Richard-Miceli, Corrine; Canhão, Helena; Fonseca, João E.; de Vries, Niek; Tak, Paul P.; Crusius, J. Bart A.; Nurmohamed, Michael T.; Kurreeman, Fina; Mikuls, Ted R.; Okada, Yukinori; Stahl, Eli A.; Larson, David E.; Deluca, Tracie L.; O'Laughlin, Michelle; Fronick, Catrina C.; Fulton, Lucinda L.; Kosoy, Roman; Ransom, Michael; Bhangale, Tushar R.; Ortmann, Ward; Cagan, Andrew; Gainer, Vivian; Karlson, Elizabeth W.; Kohane, Isaac; Murphy, Shawn N.; Martin, Javier; Zhernakova, Alexandra; Klareskog, Lars; Padyukov, Leonid; Worthington, Jane; Mardis, Elaine R.; Seldin, Michael F.; Gregersen, Peter K.; Behrens, Timothy; Raychaudhuri, Soumya; Denny, Joshua C.; Plenge, Robert M.
2015-01-01
Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3x10-21), A928V (rs35018800, OR = 0.53, P = 1.2x10-9), and I684S (rs12720356, OR = 0.86, P = 4.6x10-7). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6x10-18), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; Pomnibus = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases. PMID:25849893
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Diogo, Dorothée; Bastarache, Lisa; Liao, Katherine P; Graham, Robert R; Fulton, Robert S; Greenberg, Jeffrey D; Eyre, Steve; Bowes, John; Cui, Jing; Lee, Annette; Pappas, Dimitrios A; Kremer, Joel M; Barton, Anne; Coenen, Marieke J H; Franke, Barbara; Kiemeney, Lambertus A; Mariette, Xavier; Richard-Miceli, Corrine; Canhão, Helena; Fonseca, João E; de Vries, Niek; Tak, Paul P; Crusius, J Bart A; Nurmohamed, Michael T; Kurreeman, Fina; Mikuls, Ted R; Okada, Yukinori; Stahl, Eli A; Larson, David E; Deluca, Tracie L; O'Laughlin, Michelle; Fronick, Catrina C; Fulton, Lucinda L; Kosoy, Roman; Ransom, Michael; Bhangale, Tushar R; Ortmann, Ward; Cagan, Andrew; Gainer, Vivian; Karlson, Elizabeth W; Kohane, Isaac; Murphy, Shawn N; Martin, Javier; Zhernakova, Alexandra; Klareskog, Lars; Padyukov, Leonid; Worthington, Jane; Mardis, Elaine R; Seldin, Michael F; Gregersen, Peter K; Behrens, Timothy; Raychaudhuri, Soumya; Denny, Joshua C; Plenge, Robert M
2015-01-01
Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3 x 10(-21)), A928V (rs35018800, OR = 0.53, P = 1.2 x 10(-9)), and I684S (rs12720356, OR = 0.86, P = 4.6 x 10(-7)). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6 x 10(-18)), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P(omnibus) = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases.
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de Vries, Tamar I; Monroe, Glen R; van Belzen, Martine J; van der Lans, Christian A; Savelberg, Sanne Mc; Newman, William G; van Haaften, Gijs; Nievelstein, Rutger A; van Haelst, Mieke M
2016-08-01
Rubinstein-Taybi syndrome (RTS, OMIM 180849) and Filippi syndrome (FLPIS, OMIM 272440) are both rare syndromes, with multiple congenital anomalies and intellectual deficit (MCA/ID). We present a patient with intellectual deficit, short stature, bilateral syndactyly of hands and feet, broad thumbs, ocular abnormalities, and dysmorphic facial features. These clinical features suggest both RTS and FLPIS. Initial DNA analysis of DNA isolated from blood did not identify variants to confirm either of these syndrome diagnoses. Whole-exome sequencing identified a homozygous variant in C9orf173, which was novel at the time of analysis. Further Sanger sequencing analysis of FLPIS cases tested negative for CKAP2L variants did not, however, reveal any further variants. Subsequent analysis using DNA isolated from buccal mucosa revealed a mosaic variant in CREBBP. This report highlights the importance of excluding mosaic variants in patients with a strong but atypical clinical presentation of a MCA/ID syndrome if no disease-causing variants can be detected in DNA isolated from blood samples. As the striking syndactyly observed in the present case is typical for FLPIS, we suggest CREBBP analysis in saliva samples for FLPIS syndrome cases in which no causal CKAP2L variant is detected.
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Association of SNPs of CD40 Gene with Multiple Sclerosis in Russians
Sokolova, Ekaterina Alekseevna; Malkova, Nadezhda Alekseevna; Korobko, Denis Sergeevich; Rozhdestvenskii, Aleksey Sergeevich; Kakulya, Anastasia Vladimirovna; Khanokh, Elena Vladimirovna; Delov, Roman Andreevich; Platonov, Fedor Alekseevich; Popova, Tatyana Yegorovna; Aref′eva, Elena Gennadievna; Zagorskaya, Natalia Nikolaevna; Alifirova, Valentina Mikhailovna; Titova, Marina Andreevna; Smagina, Inna Vadimovna; El′chaninova, Svetlana Alksandrovna; Popovtseva, Anna Valentinovna; Puzyrev, Valery Pavlovich; Kulakova, Olga Georgievna; Tsareva, Ekaterina Yur'evna; Favorova, Olga Olegovna; Shchur, Sergei Gennadievich; Lashch, Natalia Yurievna; Popova, Natalia Fyodorovna; Popova, Ekaterina Valerievna; Gusev, Evgenii Ivanovich; Boyko, Aleksey Nikolaevich; Aulchenko, Yurii Sergeevich; Filipenko, Maxim Leonidovich
2013-01-01
Multiple sclerosis (MS) is a serious, incurable neurological disease. In 2009, the ANZgene studies detected the suggestive association of located upstream of CD40 gene in chromosome 20q13 (p = 1.3×10−7). Identification of the causal variant(s) in the CD40 locus leads to a better understanding of the mechanism underlying the development of autoimmune pathologies. We determined the genotypes of rs6074022, rs1883832, rs1535045, and rs11086996 in patients with MS (n = 1684) and in the control group (n = 879). Two SNPs were significantly associated with MS: rs6074022 (additive model C allele OR = 1.27, 95% CI = [1.12–1.45], p = 3×10−4) and rs1883832 (additive model T allele OR = 1.20, 95% CI = [1.05–1.38], p = 7×10−3). In the meta-analysis of our results and the results of four previous studies, we obtain the association p-value of 2.34×10−12, which confirmed the association between MS and rs6074022 at a genome-wide significant level. Next, we demonstrated that the model including rs6074022 only sufficiently described the association. From our analysis, we can speculate that the association between rs1883832 and MS was induced by LD, whereas rs6074022 was a marker in stronger LD with the functional variant or was the functional variant itself. Our results indicated that the functional variants were located in the upstream region of the gene CD40 and were in higher LD with rs6074022 than LD with rs1883832. PMID:23613777
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Alcina, Antonio; Fedetz, Maria; Fernández, Óscar; Saiz, Albert; Izquierdo, Guillermo; Lucas, Miguel; Leyva, Laura; García-León, Juan-Antonio; Abad-Grau, María del Mar; Alloza, Iraide; Antigüedad, Alfredo; Garcia-Barcina, María J; Vandenbroeck, Koen; Varadé, Jezabel; de la Hera, Belén; Arroyo, Rafael; Comabella, Manuel; Montalban, Xavier; Petit-Marty, Natalia; Navarro, Arcadi; Otaegui, David; Olascoaga, Javier; Blanco, Yolanda; Urcelay, Elena; Matesanz, Fuencisla
2013-01-01
Background and aim Several studies have highlighted the association of the 12q13.3–12q14.1 region with coeliac disease, type 1 diabetes, rheumatoid arthritis and multiple sclerosis (MS); however, the causal variants underlying diseases are still unclear. The authors sought to identify the functional variant of this region associated with MS. Methods Tag-single nucleotide polymorphism (SNP) analysis of the associated region encoding 15 genes was performed in 2876 MS patients and 2910 healthy Caucasian controls together with expression regulation analyses. Results rs6581155, which tagged 18 variants within a region where 9 genes map, was sufficient to model the association. This SNP was in total linkage disequilibrium (LD) with other polymorphisms that associated with the expression levels of FAM119B, AVIL, TSFM, TSPAN31 and CYP27B1 genes in different expression quantitative trait loci studies. Functional annotations from Encyclopedia of DNA Elements (ENCODE) showed that six out of these rs6581155-tagged-SNPs were located in regions with regulatory potential and only one of them, rs10877013, exhibited allele-dependent (ratio A/G=9.5-fold) and orientation-dependent (forward/reverse=2.7-fold) enhancer activity as determined by luciferase reporter assays. This enhancer is located in a region where a long-range chromatin interaction among the promoters and promoter-enhancer of several genes has been described, possibly affecting their expression simultaneously. Conclusions This study determines a functional variant which alters the enhancer activity of a regulatory element in the locus affecting the expression of several genes and explains the association of the 12q13.3–12q14.1 region with MS. PMID:23160276
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RNA splicing. The human splicing code reveals new insights into the genetic determinants of disease.
Xiong, Hui Y; Alipanahi, Babak; Lee, Leo J; Bretschneider, Hannes; Merico, Daniele; Yuen, Ryan K C; Hua, Yimin; Gueroussov, Serge; Najafabadi, Hamed S; Hughes, Timothy R; Morris, Quaid; Barash, Yoseph; Krainer, Adrian R; Jojic, Nebojsa; Scherer, Stephen W; Blencowe, Benjamin J; Frey, Brendan J
2015-01-09
To facilitate precision medicine and whole-genome annotation, we developed a machine-learning technique that scores how strongly genetic variants affect RNA splicing, whose alteration contributes to many diseases. Analysis of more than 650,000 intronic and exonic variants revealed widespread patterns of mutation-driven aberrant splicing. Intronic disease mutations that are more than 30 nucleotides from any splice site alter splicing nine times as often as common variants, and missense exonic disease mutations that have the least impact on protein function are five times as likely as others to alter splicing. We detected tens of thousands of disease-causing mutations, including those involved in cancers and spinal muscular atrophy. Examination of intronic and exonic variants found using whole-genome sequencing of individuals with autism revealed misspliced genes with neurodevelopmental phenotypes. Our approach provides evidence for causal variants and should enable new discoveries in precision medicine. Copyright © 2015, American Association for the Advancement of Science.
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Wood, Andrew R; Esko, Tonu; Yang, Jian; Vedantam, Sailaja; Pers, Tune H; Gustafsson, Stefan; Chu, Audrey Y; Estrada, Karol; Luan, Jian'an; Kutalik, Zoltán; Amin, Najaf; Buchkovich, Martin L; Croteau-Chonka, Damien C; Day, Felix R; Duan, Yanan; Fall, Tove; Fehrmann, Rudolf; Ferreira, Teresa; Jackson, Anne U; Karjalainen, Juha; Lo, Ken Sin; Locke, Adam E; Mägi, Reedik; Mihailov, Evelin; Porcu, Eleonora; Randall, Joshua C; Scherag, André; Vinkhuyzen, Anna A E; Westra, Harm-Jan; Winkler, Thomas W; Workalemahu, Tsegaselassie; Zhao, Jing Hua; Absher, Devin; Albrecht, Eva; Anderson, Denise; Baron, Jeffrey; Beekman, Marian; Demirkan, Ayse; Ehret, Georg B; Feenstra, Bjarke; Feitosa, Mary F; Fischer, Krista; Fraser, Ross M; Goel, Anuj; Gong, Jian; Justice, Anne E; Kanoni, Stavroula; Kleber, Marcus E; Kristiansson, Kati; Lim, Unhee; Lotay, Vaneet; Lui, Julian C; Mangino, Massimo; Mateo Leach, Irene; Medina-Gomez, Carolina; Nalls, Michael A; Nyholt, Dale R; Palmer, Cameron D; Pasko, Dorota; Pechlivanis, Sonali; Prokopenko, Inga; Ried, Janina S; Ripke, Stephan; Shungin, Dmitry; Stancáková, Alena; Strawbridge, Rona J; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van Setten, Jessica; Van Vliet-Ostaptchouk, Jana V; Wang, Zhaoming; Yengo, Loïc; Zhang, Weihua; Afzal, Uzma; Arnlöv, Johan; Arscott, Gillian M; Bandinelli, Stefania; Barrett, Amy; Bellis, Claire; Bennett, Amanda J; Berne, Christian; Blüher, Matthias; Bolton, Jennifer L; Böttcher, Yvonne; Boyd, Heather A; Bruinenberg, Marcel; Buckley, Brendan M; Buyske, Steven; Caspersen, Ida H; Chines, Peter S; Clarke, Robert; Claudi-Boehm, Simone; Cooper, Matthew; Daw, E Warwick; De Jong, Pim A; Deelen, Joris; Delgado, Graciela; Denny, Josh C; Dhonukshe-Rutten, Rosalie; Dimitriou, Maria; Doney, Alex S F; Dörr, Marcus; Eklund, Niina; Eury, Elodie; Folkersen, Lasse; Garcia, Melissa E; Geller, Frank; Giedraitis, Vilmantas; Go, Alan S; Grallert, Harald; Grammer, Tanja B; Gräßler, Jürgen; Grönberg, Henrik; de Groot, Lisette C P G M; Groves, Christopher J; Haessler, Jeffrey; Hall, Per; Haller, Toomas; Hallmans, Goran; Hannemann, Anke; Hartman, Catharina A; Hassinen, Maija; Hayward, Caroline; Heard-Costa, Nancy L; Helmer, Quinta; Hemani, Gibran; Henders, Anjali K; Hillege, Hans L; Hlatky, Mark A; Hoffmann, Wolfgang; Hoffmann, Per; Holmen, Oddgeir; Houwing-Duistermaat, Jeanine J; Illig, Thomas; Isaacs, Aaron; James, Alan L; Jeff, Janina; Johansen, Berit; Johansson, Åsa; Jolley, Jennifer; Juliusdottir, Thorhildur; Junttila, Juhani; Kho, Abel N; Kinnunen, Leena; Klopp, Norman; Kocher, Thomas; Kratzer, Wolfgang; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lobbens, Stéphane; Lorentzon, Mattias; Lu, Yingchang; Lyssenko, Valeriya; Magnusson, Patrik K E; Mahajan, Anubha; Maillard, Marc; McArdle, Wendy L; McKenzie, Colin A; McLachlan, Stela; McLaren, Paul J; Menni, Cristina; Merger, Sigrun; Milani, Lili; Moayyeri, Alireza; Monda, Keri L; Morken, Mario A; Müller, Gabriele; Müller-Nurasyid, Martina; Musk, Arthur W; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Nöthen, Markus M; Oozageer, Laticia; Pilz, Stefan; Rayner, Nigel W; Renstrom, Frida; Robertson, Neil R; Rose, Lynda M; Roussel, Ronan; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Schumacher, Fredrick R; Schunkert, Heribert; Scott, Robert A; Sehmi, Joban; Seufferlein, Thomas; Shi, Jianxin; Silventoinen, Karri; Smit, Johannes H; Smith, Albert Vernon; Smolonska, Joanna; Stanton, Alice V; Stirrups, Kathleen; Stott, David J; Stringham, Heather M; Sundström, Johan; Swertz, Morris A; Syvänen, Ann-Christine; Tayo, Bamidele O; Thorleifsson, Gudmar; Tyrer, Jonathan P; van Dijk, Suzanne; van Schoor, Natasja M; van der Velde, Nathalie; van Heemst, Diana; van Oort, Floor V A; Vermeulen, Sita H; Verweij, Niek; Vonk, Judith M; Waite, Lindsay L; Waldenberger, Melanie; Wennauer, Roman; Wilkens, Lynne R; Willenborg, Christina; Wilsgaard, Tom; Wojczynski, Mary K; Wong, Andrew; Wright, Alan F; Zhang, Qunyuan; Arveiler, Dominique; Bakker, Stephan J L; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boomsma, Dorret I; Bornstein, Stefan R; Bovet, Pascal; Brambilla, Paolo; Brown, Morris J; Campbell, Harry; Caulfield, Mark J; Chakravarti, Aravinda; Collins, Rory; Collins, Francis S; Crawford, Dana C; Cupples, L Adrienne; Danesh, John; de Faire, Ulf; den Ruijter, Hester M; Erbel, Raimund; Erdmann, Jeanette; Eriksson, Johan G; Farrall, Martin; Ferrannini, Ele; Ferrières, Jean; Ford, Ian; Forouhi, Nita G; Forrester, Terrence; Gansevoort, Ron T; Gejman, Pablo V; Gieger, Christian; Golay, Alain; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Haas, David W; Hall, Alistair S; Harris, Tamara B; Hattersley, Andrew T; Heath, Andrew C; Hengstenberg, Christian; Hicks, Andrew A; Hindorff, Lucia A; Hingorani, Aroon D; Hofman, Albert; Hovingh, G Kees; Humphries, Steve E; Hunt, Steven C; Hypponen, Elina; Jacobs, Kevin B; Jarvelin, Marjo-Riitta; Jousilahti, Pekka; Jula, Antti M; Kaprio, Jaakko; Kastelein, John J P; Kayser, Manfred; Kee, Frank; Keinanen-Kiukaanniemi, Sirkka M; Kiemeney, Lambertus A; Kooner, Jaspal S; Kooperberg, Charles; Koskinen, Seppo; Kovacs, Peter; Kraja, Aldi T; Kumari, Meena; Kuusisto, Johanna; Lakka, Timo A; Langenberg, Claudia; Le Marchand, Loic; Lehtimäki, Terho; Lupoli, Sara; Madden, Pamela A F; Männistö, Satu; Manunta, Paolo; Marette, André; Matise, Tara C; McKnight, Barbara; Meitinger, Thomas; Moll, Frans L; Montgomery, Grant W; Morris, Andrew D; Morris, Andrew P; Murray, Jeffrey C; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J; Ong, Ken K; Ouwehand, Willem H; Pasterkamp, Gerard; Peters, Annette; Pramstaller, Peter P; Price, Jackie F; Qi, Lu; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rice, Treva K; Ritchie, Marylyn; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J; Saramies, Jouko; Sarzynski, Mark A; Schwarz, Peter E H; Sebert, Sylvain; Sever, Peter; Shuldiner, Alan R; Sinisalo, Juha; Steinthorsdottir, Valgerdur; Stolk, Ronald P; Tardif, Jean-Claude; Tönjes, Anke; Tremblay, Angelo; Tremoli, Elena; Virtamo, Jarmo; Vohl, Marie-Claude; Amouyel, Philippe; Asselbergs, Folkert W; Assimes, Themistocles L; Bochud, Murielle; Boehm, Bernhard O; Boerwinkle, Eric; Bottinger, Erwin P; Bouchard, Claude; Cauchi, Stéphane; Chambers, John C; Chanock, Stephen J; Cooper, Richard S; de Bakker, Paul I W; Dedoussis, George; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Groop, Leif C; Haiman, Christopher A; Hamsten, Anders; Hayes, M Geoffrey; Hui, Jennie; Hunter, David J; Hveem, Kristian; Jukema, J Wouter; Kaplan, Robert C; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; Martin, Nicholas G; März, Winfried; Melbye, Mads; Moebus, Susanne; Munroe, Patricia B; Njølstad, Inger; Oostra, Ben A; Palmer, Colin N A; Pedersen, Nancy L; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Powell, Joseph E; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Reinmaa, Eva; Ridker, Paul M; Rivadeneira, Fernando; Rotter, Jerome I; Saaristo, Timo E; Saleheen, Danish; Schlessinger, David; Slagboom, P Eline; Snieder, Harold; Spector, Tim D; Strauch, Konstantin; Stumvoll, Michael; Tuomilehto, Jaakko; Uusitupa, Matti; van der Harst, Pim; Völzke, Henry; Walker, Mark; Wareham, Nicholas J; Watkins, Hugh; Wichmann, H-Erich; Wilson, James F; Zanen, Pieter; Deloukas, Panos; Heid, Iris M; Lindgren, Cecilia M; Mohlke, Karen L; Speliotes, Elizabeth K; Thorsteinsdottir, Unnur; Barroso, Inês; Fox, Caroline S; North, Kari E; Strachan, David P; Beckmann, Jacques S; Berndt, Sonja I; Boehnke, Michael; Borecki, Ingrid B; McCarthy, Mark I; Metspalu, Andres; Stefansson, Kari; Uitterlinden, André G; van Duijn, Cornelia M; Franke, Lude; Willer, Cristen J; Price, Alkes L; Lettre, Guillaume; Loos, Ruth J F; Weedon, Michael N; Ingelsson, Erik; O'Connell, Jeffrey R; Abecasis, Goncalo R; Chasman, Daniel I; Goddard, Michael E; Visscher, Peter M; Hirschhorn, Joel N; Frayling, Timothy M
2014-11-01
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
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Chu, Audrey Y; Estrada, Karol; Luan, Jian’an; Kutalik, Zoltán; Amin, Najaf; Buchkovich, Martin L; Croteau-Chonka, Damien C; Day, Felix R; Duan, Yanan; Fall, Tove; Fehrmann, Rudolf; Ferreira, Teresa; Jackson, Anne U; Karjalainen, Juha; Lo, Ken Sin; Locke, Adam E; Mägi, Reedik; Mihailov, Evelin; Porcu, Eleonora; Randall, Joshua C; Scherag, André; Vinkhuyzen, Anna AE; Westra, Harm-Jan; Winkler, Thomas W; Workalemahu, Tsegaselassie; Zhao, Jing Hua; Absher, Devin; Albrecht, Eva; Anderson, Denise; Baron, Jeffrey; Beekman, Marian; Demirkan, Ayse; Ehret, Georg B; Feenstra, Bjarke; Feitosa, Mary F; Fischer, Krista; Fraser, Ross M; Goel, Anuj; Gong, Jian; Justice, Anne E; Kanoni, Stavroula; Kleber, Marcus E; Kristiansson, Kati; Lim, Unhee; Lotay, Vaneet; Lui, Julian C; Mangino, Massimo; Leach, Irene Mateo; Medina-Gomez, Carolina; Nalls, Michael A; Nyholt, Dale R; Palmer, Cameron D; Pasko, Dorota; Pechlivanis, Sonali; Prokopenko, Inga; Ried, Janina S; Ripke, Stephan; Shungin, Dmitry; Stancáková, Alena; Strawbridge, Rona J; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van Setten, Jessica; Van Vliet-Ostaptchouk, Jana V; Wang, Zhaoming; Yengo, Loïc; Zhang, Weihua; Afzal, Uzma; Ärnlöv, Johan; Arscott, Gillian M; Bandinelli, Stefania; Barrett, Amy; Bellis, Claire; Bennett, Amanda J; Berne, Christian; Blüher, Matthias; Bolton, Jennifer L; Böttcher, Yvonne; Boyd, Heather A; Bruinenberg, Marcel; Buckley, Brendan M; Buyske, Steven; Caspersen, Ida H; Chines, Peter S; Clarke, Robert; Claudi-Boehm, Simone; Cooper, Matthew; Daw, E Warwick; De Jong, Pim A; Deelen, Joris; Delgado, Graciela; Denny, Josh C; Dhonukshe-Rutten, Rosalie; Dimitriou, Maria; Doney, Alex SF; Dörr, Marcus; Eklund, Niina; Eury, Elodie; Folkersen, Lasse; Garcia, Melissa E; Geller, Frank; Giedraitis, Vilmantas; Go, Alan S; Grallert, Harald; Grammer, Tanja B; Gräßler, Jürgen; Grönberg, Henrik; de Groot, Lisette C.P.G.M.; Groves, Christopher J; Haessler, Jeffrey; Hall, Per; Haller, Toomas; Hallmans, Goran; Hannemann, Anke; Hartman, Catharina A; Hassinen, Maija; Hayward, Caroline; Heard-Costa, Nancy L; Helmer, Quinta; Hemani, Gibran; Henders, Anjali K; Hillege, Hans L; Hlatky, Mark A; Hoffmann, Wolfgang; Hoffmann, Per; Holmen, Oddgeir; Houwing-Duistermaat, Jeanine J; Illig, Thomas; Isaacs, Aaron; James, Alan L; Jeff, Janina; Johansen, Berit; Johansson, Åsa; Jolley, Jennifer; Juliusdottir, Thorhildur; Junttila, Juhani; Kho, Abel N; Kinnunen, Leena; Klopp, Norman; Kocher, Thomas; Kratzer, Wolfgang; Lichtner, Peter; Lind, Lars; Lindström, Jaana; Lobbens, Stéphane; Lorentzon, Mattias; Lu, Yingchang; Lyssenko, Valeriya; Magnusson, Patrik KE; Mahajan, Anubha; Maillard, Marc; McArdle, Wendy L; McKenzie, Colin A; McLachlan, Stela; McLaren, Paul J; Menni, Cristina; Merger, Sigrun; Milani, Lili; Moayyeri, Alireza; Monda, Keri L; Morken, Mario A; Müller, Gabriele; Müller-Nurasyid, Martina; Musk, Arthur W; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Nöthen, Markus M; Oozageer, Laticia; Pilz, Stefan; Rayner, Nigel W; Renstrom, Frida; Robertson, Neil R; Rose, Lynda M; Roussel, Ronan; Sanna, Serena; Scharnagl, Hubert; Scholtens, Salome; Schumacher, Fredrick R; Schunkert, Heribert; Scott, Robert A; Sehmi, Joban; Seufferlein, Thomas; Shi, Jianxin; Silventoinen, Karri; Smit, Johannes H; Smith, Albert Vernon; Smolonska, Joanna; Stanton, Alice V; Stirrups, Kathleen; Stott, David J; Stringham, Heather M; Sundström, Johan; Swertz, Morris A; Syvänen, Ann-Christine; Tayo, Bamidele O; Thorleifsson, Gudmar; Tyrer, Jonathan P; van Dijk, Suzanne; van Schoor, Natasja M; van der Velde, Nathalie; van Heemst, Diana; van Oort, Floor VA; Vermeulen, Sita H; Verweij, Niek; Vonk, Judith M; Waite, Lindsay L; Waldenberger, Melanie; Wennauer, Roman; Wilkens, Lynne R; Willenborg, Christina; Wilsgaard, Tom; Wojczynski, Mary K; Wong, Andrew; Wright, Alan F; Zhang, Qunyuan; Arveiler, Dominique; Bakker, Stephan JL; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boomsma, Dorret I; Bornstein, Stefan R; Bovet, Pascal; Brambilla, Paolo; Brown, Morris J; Campbell, Harry; Caulfield, Mark J; Chakravarti, Aravinda; Collins, Rory; Collins, Francis S; Crawford, Dana C; Cupples, L Adrienne; Danesh, John; de Faire, Ulf; den Ruijter, Hester M; Erbel, Raimund; Erdmann, Jeanette; Eriksson, Johan G; Farrall, Martin; Ferrannini, Ele; Ferrières, Jean; Ford, Ian; Forouhi, Nita G; Forrester, Terrence; Gansevoort, Ron T; Gejman, Pablo V; Gieger, Christian; Golay, Alain; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Haas, David W; Hall, Alistair S; Harris, Tamara B; Hattersley, Andrew T; Heath, Andrew C; Hengstenberg, Christian; Hicks, Andrew A; Hindorff, Lucia A; Hingorani, Aroon D; Hofman, Albert; Hovingh, G Kees; Humphries, Steve E; Hunt, Steven C; Hypponen, Elina; Jacobs, Kevin B; Jarvelin, Marjo-Riitta; Jousilahti, Pekka; Jula, Antti M; Kaprio, Jaakko; Kastelein, John JP; Kayser, Manfred; Kee, Frank; Keinanen-Kiukaanniemi, Sirkka M; Kiemeney, Lambertus A; Kooner, Jaspal S; Kooperberg, Charles; Koskinen, Seppo; Kovacs, Peter; Kraja, Aldi T; Kumari, Meena; Kuusisto, Johanna; Lakka, Timo A; Langenberg, Claudia; Le Marchand, Loic; Lehtimäki, Terho; Lupoli, Sara; Madden, Pamela AF; Männistö, Satu; Manunta, Paolo; Marette, André; Matise, Tara C; McKnight, Barbara; Meitinger, Thomas; Moll, Frans L; Montgomery, Grant W; Morris, Andrew D; Morris, Andrew P; Murray, Jeffrey C; Nelis, Mari; Ohlsson, Claes; Oldehinkel, Albertine J; Ong, Ken K; Ouwehand, Willem H; Pasterkamp, Gerard; Peters, Annette; Pramstaller, Peter P; Price, Jackie F; Qi, Lu; Raitakari, Olli T; Rankinen, Tuomo; Rao, DC; Rice, Treva K; Ritchie, Marylyn; Rudan, Igor; Salomaa, Veikko; Samani, Nilesh J; Saramies, Jouko; Sarzynski, Mark A; Schwarz, Peter EH; Sebert, Sylvain; Sever, Peter; Shuldiner, Alan R; Sinisalo, Juha; Steinthorsdottir, Valgerdur; Stolk, Ronald P; Tardif, Jean-Claude; Tönjes, Anke; Tremblay, Angelo; Tremoli, Elena; Virtamo, Jarmo; Vohl, Marie-Claude; Amouyel, Philippe; Asselbergs, Folkert W; Assimes, Themistocles L; Bochud, Murielle; Boehm, Bernhard O; Boerwinkle, Eric; Bottinger, Erwin P; Bouchard, Claude; Cauchi, Stéphane; Chambers, John C; Chanock, Stephen J; Cooper, Richard S; de Bakker, Paul IW; Dedoussis, George; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Groop, Leif C; Haiman, Christopher A; Hamsten, Anders; Hayes, M Geoffrey; Hui, Jennie; Hunter, David J.; Hveem, Kristian; Jukema, J Wouter; Kaplan, Robert C; Kivimaki, Mika; Kuh, Diana; Laakso, Markku; Liu, Yongmei; Martin, Nicholas G; März, Winfried; Melbye, Mads; Moebus, Susanne; Munroe, Patricia B; Njølstad, Inger; Oostra, Ben A; Palmer, Colin NA; Pedersen, Nancy L; Perola, Markus; Pérusse, Louis; Peters, Ulrike; Powell, Joseph E; Power, Chris; Quertermous, Thomas; Rauramaa, Rainer; Reinmaa, Eva; Ridker, Paul M; Rivadeneira, Fernando; Rotter, Jerome I; Saaristo, Timo E; Saleheen, Danish; Schlessinger, David; Slagboom, P Eline; Snieder, Harold; Spector, Tim D; Strauch, Konstantin; Stumvoll, Michael; Tuomilehto, Jaakko; Uusitupa, Matti; van der Harst, Pim; Völzke, Henry; Walker, Mark; Wareham, Nicholas J; Watkins, Hugh; Wichmann, H-Erich; Wilson, James F; Zanen, Pieter; Deloukas, Panos; Heid, Iris M; Lindgren, Cecilia M; Mohlke, Karen L; Speliotes, Elizabeth K; Thorsteinsdottir, Unnur; Barroso, Inês; Fox, Caroline S; North, Kari E; Strachan, David P; Beckmann, Jacques S.; Berndt, Sonja I; Boehnke, Michael; Borecki, Ingrid B; McCarthy, Mark I; Metspalu, Andres; Stefansson, Kari; Uitterlinden, André G; van Duijn, Cornelia M; Franke, Lude; Willer, Cristen J; Price, Alkes L.; Lettre, Guillaume; Loos, Ruth JF; Weedon, Michael N; Ingelsson, Erik; O’Connell, Jeffrey R; Abecasis, Goncalo R; Chasman, Daniel I; Goddard, Michael E
2014-01-01
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explain one-fifth of heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured the majority (60%) of heritability. The 697 variants clustered in 423 loci enriched for genes, pathways, and tissue-types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin, and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants. PMID:25282103
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van Leeuwen, Elisabeth M; Sabo, Aniko; Bis, Joshua C; Huffman, Jennifer E; Manichaikul, Ani; Smith, Albert V; Feitosa, Mary F; Demissie, Serkalem; Joshi, Peter K; Duan, Qing; Marten, Jonathan; van Klinken, Jan B; Surakka, Ida; Nolte, Ilja M; Zhang, Weihua; Mbarek, Hamdi; Li-Gao, Ruifang; Trompet, Stella; Verweij, Niek; Evangelou, Evangelos; Lyytikäinen, Leo-Pekka; Tayo, Bamidele O; Deelen, Joris; van der Most, Peter J; van der Laan, Sander W; Arking, Dan E; Morrison, Alanna; Dehghan, Abbas; Franco, Oscar H; Hofman, Albert; Rivadeneira, Fernando; Sijbrands, Eric J; Uitterlinden, Andre G; Mychaleckyj, Josyf C; Campbell, Archie; Hocking, Lynne J; Padmanabhan, Sandosh; Brody, Jennifer A; Rice, Kenneth M; White, Charles C; Harris, Tamara; Isaacs, Aaron; Campbell, Harry; Lange, Leslie A; Rudan, Igor; Kolcic, Ivana; Navarro, Pau; Zemunik, Tatijana; Salomaa, Veikko; Kooner, Angad S; Kooner, Jaspal S; Lehne, Benjamin; Scott, William R; Tan, Sian-Tsung; de Geus, Eco J; Milaneschi, Yuri; Penninx, Brenda W J H; Willemsen, Gonneke; de Mutsert, Renée; Ford, Ian; Gansevoort, Ron T; Segura-Lepe, Marcelo P; Raitakari, Olli T; Viikari, Jorma S; Nikus, Kjell; Forrester, Terrence; McKenzie, Colin A; de Craen, Anton J M; de Ruijter, Hester M; Pasterkamp, Gerard; Snieder, Harold; Oldehinkel, Albertine J; Slagboom, P Eline; Cooper, Richard S; Kähönen, Mika; Lehtimäki, Terho; Elliott, Paul; van der Harst, Pim; Jukema, J Wouter; Mook-Kanamori, Dennis O; Boomsma, Dorret I; Chambers, John C; Swertz, Morris; Ripatti, Samuli; Willems van Dijk, Ko; Vitart, Veronique; Polasek, Ozren; Hayward, Caroline; Wilson, James G; Wilson, James F; Gudnason, Vilmundur; Rich, Stephen S; Psaty, Bruce M; Borecki, Ingrid B; Boerwinkle, Eric; Rotter, Jerome I; Cupples, L Adrienne; van Duijn, Cornelia M
2016-01-01
Background So far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage. Results Our study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene. Conclusions This study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels. PMID:27036123
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Utilising family-based designs for detecting rare variant disease associations.
Preston, Mark D; Dudbridge, Frank
2014-03-01
Rare genetic variants are thought to be important components in the causality of many diseases but discovering these associations is challenging. We demonstrate how best to use family-based designs to improve the power to detect rare variant disease associations. We show that using genetic data from enriched families (those pedigrees with greater than one affected member) increases the power and sensitivity of existing case-control rare variant tests. However, we show that transmission- (or within-family-) based tests do not benefit from this enrichment. This means that, in studies where a limited amount of genotyping is available, choosing a single case from each of many pedigrees has greater power than selecting multiple cases from fewer pedigrees. Finally, we show how a pseudo-case-control design allows a greater range of statistical tests to be applied to family data. © 2014 The Authors. Annals of Human Genetics published by John Wiley & Sons Ltd/University College London.
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Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.
Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C
2014-03-07
To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.
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USDA-ARS?s Scientific Manuscript database
Many studies leverage targeted whole genome sequencing (WGS) experiments in order to identify rare and causal variants within populations. As a natural consequence of experimental design, many of these surveys tend to sequence redundant haplotype segments due to high frequency in the base population...
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Novel mutation in the CHST6 gene causes macular corneal dystrophy in a black South African family.
Carstens, Nadia; Williams, Susan; Goolam, Saadiah; Carmichael, Trevor; Cheung, Ming Sin; Büchmann-Møller, Stine; Sultan, Marc; Staedtler, Frank; Zou, Chao; Swart, Peter; Rice, Dennis S; Lacoste, Arnaud; Paes, Kim; Ramsay, Michèle
2016-07-20
Macular corneal dystrophy (MCD) is a rare autosomal recessive disorder that is characterized by progressive corneal opacity that starts in early childhood and ultimately progresses to blindness in early adulthood. The aim of this study was to identify the cause of MCD in a black South African family with two affected sisters. A multigenerational South African Sotho-speaking family with type I MCD was studied using whole exome sequencing. Variant filtering to identify the MCD-causal mutation included the disease inheritance pattern, variant minor allele frequency and potential functional impact. Ophthalmologic evaluation of the cases revealed a typical MCD phenotype and none of the other family members were affected. An average of 127 713 variants per individual was identified following exome sequencing and approximately 1.2 % were not present in any of the investigated public databases. Variant filtering identified a homozygous E71Q mutation in CHST6, a known MCD-causing gene encoding corneal N-acetyl glucosamine-6-O-sulfotransferase. This E71Q mutation results in a non-conservative amino acid change in a highly conserved functional domain of the human CHST6 that is essential for enzyme activity. We identified a novel E71Q mutation in CHST6 as the MCD-causal mutation in a black South African family with type I MCD. This is the first description of MCD in a black Sub-Saharan African family and therefore contributes valuable insights into the genetic aetiology of this disease, while improving genetic counselling for this and potentially other MCD families.
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Designs of Empirical Evaluations of Nonexperimental Methods in Field Settings.
Wong, Vivian C; Steiner, Peter M
2018-01-01
Over the last three decades, a research design has emerged to evaluate the performance of nonexperimental (NE) designs and design features in field settings. It is called the within-study comparison (WSC) approach or the design replication study. In the traditional WSC design, treatment effects from a randomized experiment are compared to those produced by an NE approach that shares the same target population. The nonexperiment may be a quasi-experimental design, such as a regression-discontinuity or an interrupted time-series design, or an observational study approach that includes matching methods, standard regression adjustments, and difference-in-differences methods. The goals of the WSC are to determine whether the nonexperiment can replicate results from a randomized experiment (which provides the causal benchmark estimate), and the contexts and conditions under which these methods work in practice. This article presents a coherent theory of the design and implementation of WSCs for evaluating NE methods. It introduces and identifies the multiple purposes of WSCs, required design components, common threats to validity, design variants, and causal estimands of interest in WSCs. It highlights two general approaches for empirical evaluations of methods in field settings, WSC designs with independent and dependent benchmark and NE arms. This article highlights advantages and disadvantages for each approach, and conditions and contexts under which each approach is optimal for addressing methodological questions.
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Grarup, Niels; Rivas, Manuel A; Mahajan, Anubha; Locke, Adam E; Cingolani, Pablo; Pers, Tune H; Viñuela, Ana; Brown, Andrew A; Wu, Ying; Flannick, Jason; Fuchsberger, Christian; Gamazon, Eric R; Gaulton, Kyle J; Im, Hae Kyung; Teslovich, Tanya M; Blackwell, Thomas W; Bork-Jensen, Jette; Burtt, Noël P; Chen, Yuhui; Green, Todd; Hartl, Christopher; Kang, Hyun Min; Kumar, Ashish; Ladenvall, Claes; Ma, Clement; Moutsianas, Loukas; Pearson, Richard D; Perry, John R B; Rayner, N William; Robertson, Neil R; Scott, Laura J; van de Bunt, Martijn; Eriksson, Johan G; Jula, Antti; Koskinen, Seppo; Lehtimäki, Terho; Palotie, Aarno; Raitakari, Olli T; Jacobs, Suzanne BR; Wessel, Jennifer; Chu, Audrey Y; Scott, Robert A; Goodarzi, Mark O; Blancher, Christine; Buck, Gemma; Buck, David; Chines, Peter S; Gabriel, Stacey; Gjesing, Anette P; Groves, Christopher J; Hollensted, Mette; Huyghe, Jeroen R; Jackson, Anne U; Jun, Goo; Justesen, Johanne Marie; Mangino, Massimo; Murphy, Jacquelyn; Neville, Matt; Onofrio, Robert; Small, Kerrin S; Stringham, Heather M; Trakalo, Joseph; Banks, Eric; Carey, Jason; Carneiro, Mauricio O; DePristo, Mark; Farjoun, Yossi; Fennell, Timothy; Goldstein, Jacqueline I; Grant, George; de Angelis, Martin Hrabé; Maguire, Jared; Neale, Benjamin M; Poplin, Ryan; Purcell, Shaun; Schwarzmayr, Thomas; Shakir, Khalid; Smith, Joshua D; Strom, Tim M; Wieland, Thomas; Lindstrom, Jaana; Brandslund, Ivan; Christensen, Cramer; Surdulescu, Gabriela L; Lakka, Timo A; Doney, Alex S F; Nilsson, Peter; Wareham, Nicholas J; Langenberg, Claudia; Varga, Tibor V; Franks, Paul W; Rolandsson, Olov; Rosengren, Anders H; Farook, Vidya S; Thameem, Farook; Puppala, Sobha; Kumar, Satish; Lehman, Donna M; Jenkinson, Christopher P; Curran, Joanne E; Hale, Daniel Esten; Fowler, Sharon P; Arya, Rector; DeFronzo, Ralph A; Abboud, Hanna E; Syvänen, Ann-Christine; Hicks, Pamela J; Palmer, Nicholette D; Ng, Maggie C Y; Bowden, Donald W; Freedman, Barry I; Esko, Tõnu; Mägi, Reedik; Milani, Lili; Mihailov, Evelin; Metspalu, Andres; Narisu, Narisu; Kinnunen, Leena; Bonnycastle, Lori L; Swift, Amy; Pasko, Dorota; Wood, Andrew R; Fadista, João; Pollin, Toni I; Barzilai, Nir; Atzmon, Gil; Glaser, Benjamin; Thorand, Barbara; Strauch, Konstantin; Peters, Annette; Roden, Michael; Müller-Nurasyid, Martina; Liang, Liming; Kriebel, Jennifer; Illig, Thomas; Grallert, Harald; Gieger, Christian; Meisinger, Christa; Lannfelt, Lars; Musani, Solomon K; Griswold, Michael; Taylor, Herman A; Wilson, Gregory; Correa, Adolfo; Oksa, Heikki; Scott, William R; Afzal, Uzma; Tan, Sian-Tsung; Loh, Marie; Chambers, John C; Sehmi, Jobanpreet; Kooner, Jaspal Singh; Lehne, Benjamin; Cho, Yoon Shin; Lee, Jong-Young; Han, Bok-Ghee; Käräjämäki, Annemari; Qi, Qibin; Qi, Lu; Huang, Jinyan; Hu, Frank B; Melander, Olle; Orho-Melander, Marju; Below, Jennifer E; Aguilar, David; Wong, Tien Yin; Liu, Jianjun; Khor, Chiea-Chuen; Chia, Kee Seng; Lim, Wei Yen; Cheng, Ching-Yu; Chan, Edmund; Tai, E Shyong; Aung, Tin; Linneberg, Allan; Isomaa, Bo; Meitinger, Thomas; Tuomi, Tiinamaija; Hakaste, Liisa; Kravic, Jasmina; Jørgensen, Marit E; Lauritzen, Torsten; Deloukas, Panos; Stirrups, Kathleen E; Owen, Katharine R; Farmer, Andrew J; Frayling, Timothy M; O'Rahilly, Stephen P; Walker, Mark; Levy, Jonathan C; Hodgkiss, Dylan; Hattersley, Andrew T; Kuulasmaa, Teemu; Stančáková, Alena; Barroso, Inês; Bharadwaj, Dwaipayan; Chan, Juliana; Chandak, Giriraj R; Daly, Mark J; Donnelly, Peter J; Ebrahim, Shah B; Elliott, Paul; Fingerlin, Tasha; Froguel, Philippe; Hu, Cheng; Jia, Weiping; Ma, Ronald C W; McVean, Gilean; Park, Taesung; Prabhakaran, Dorairaj; Sandhu, Manjinder; Scott, James; Sladek, Rob; Tandon, Nikhil; Teo, Yik Ying; Zeggini, Eleftheria; Watanabe, Richard M; Koistinen, Heikki A; Kesaniemi, Y Antero; Uusitupa, Matti; Spector, Timothy D; Salomaa, Veikko; Rauramaa, Rainer; Palmer, Colin N A; Prokopenko, Inga; Morris, Andrew D; Bergman, Richard N; Collins, Francis S; Lind, Lars; Ingelsson, Erik; Tuomilehto, Jaakko; Karpe, Fredrik; Groop, Leif; Jørgensen, Torben; Hansen, Torben; Pedersen, Oluf; Kuusisto, Johanna; Abecasis, Gonçalo; Bell, Graeme I; Blangero, John; Cox, Nancy J; Duggirala, Ravindranath; Seielstad, Mark; Wilson, James G; Dupuis, Josee; Ripatti, Samuli; Hanis, Craig L; Florez, Jose C; Mohlke, Karen L; Meigs, James B; Laakso, Markku; Morris, Andrew P; Boehnke, Michael; Altshuler, David; McCarthy, Mark I; Gloyn, Anna L; Lindgren, Cecilia M
2017-01-01
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting insulin, a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in fasting plasma insulin (FI) levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-hour insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio=1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2. PMID:28341696
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Genetic evidence of a causal effect of insulin resistance on branched-chain amino acid levels.
Mahendran, Yuvaraj; Jonsson, Anna; Have, Christian T; Allin, Kristine H; Witte, Daniel R; Jørgensen, Marit E; Grarup, Niels; Pedersen, Oluf; Kilpeläinen, Tuomas O; Hansen, Torben
2017-05-01
Fasting plasma levels of branched-chain amino acids (BCAAs) are associated with insulin resistance, but it remains unclear whether there is a causal relation between the two. We aimed to disentangle the causal relations by performing a Mendelian randomisation study using genetic variants associated with circulating BCAA levels and insulin resistance as instrumental variables. We measured circulating BCAA levels in blood plasma by NMR spectroscopy in 1,321 individuals from the ADDITION-PRO cohort. We complemented our analyses by using previously published genome-wide association study (GWAS) results from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) (n = 46,186) and from a GWAS of serum BCAA levels (n = 24,925). We used a genetic risk score (GRS), calculated using ten established fasting serum insulin associated variants, as an instrumental variable for insulin resistance. A GRS of three variants increasing circulating BCAA levels was used as an instrumental variable for circulating BCAA levels. Fasting plasma BCAA levels were associated with higher HOMA-IR in ADDITION-PRO (β 0.137 [95% CI 0.08, 0.19] p = 6 × 10 -7 ). However, the GRS for circulating BCAA levels was not associated with fasting insulin levels or HOMA-IR in ADDITION-PRO (β -0.011 [95% CI -0.053, 0.032] p = 0.6 and β -0.011 [95% CI -0.054, 0.031] p = 0.6, respectively) or in GWAS results for HOMA-IR from MAGIC (β for valine-increasing GRS -0.012 [95% CI -0.069, 0.045] p = 0.7). By contrast, the insulin-resistance-increasing GRS was significantly associated with increased BCAA levels in ADDITION-PRO (β 0.027 [95% CI 0.005, 0.048] p = 0.01) and in GWAS results for serum BCAA levels (β 1.22 [95% CI 0.71, 1.73] p = 4 × 10 -6 , β 0.96 [95% CI 0.45, 1.47] p = 3 × 10 -4 , and β 0.67 [95% CI 0.16, 1.18] p = 0.01 for isoleucine, leucine and valine levels, respectively) and instrumental variable analyses in ADDITION-PRO indicated that HOMA-IR is causally related to higher circulating fasting BCAA levels (β 0.73 [95% CI 0.26, 1.19] p = 0.002). Our results suggest that higher BCAA levels do not have a causal effect on insulin resistance while increased insulin resistance drives higher circulating fasting BCAA levels.
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Education and myopia: assessing the direction of causality by mendelian randomisation
Mountjoy, Edward; Davies, Neil M; Plotnikov, Denis; Smith, George Davey; Rodriguez, Santiago; Williams, Cathy E; Guggenheim, Jeremy A
2018-01-01
Abstract Objectives To determine whether more years spent in education is a causal risk factor for myopia, or whether myopia is a causal risk factor for more years in education. Design Bidirectional, two sample mendelian randomisation study. Setting Publically available genetic data from two consortiums applied to a large, independent population cohort. Genetic variants used as proxies for myopia and years of education were derived from two large genome wide association studies: 23andMe and Social Science Genetic Association Consortium (SSGAC), respectively. Participants 67 798 men and women from England, Scotland, and Wales in the UK Biobank cohort with available information for years of completed education and refractive error. Main outcome measures Mendelian randomisation analyses were performed in two directions: the first exposure was the genetic predisposition to myopia, measured with 44 genetic variants strongly associated with myopia in 23andMe, and the outcome was years in education; and the second exposure was the genetic predisposition to higher levels of education, measured with 69 genetic variants from SSGAC, and the outcome was refractive error. Results Conventional regression analyses of the observational data suggested that every additional year of education was associated with a more myopic refractive error of −0.18 dioptres/y (95% confidence interval −0.19 to −0.17; P<2e-16). Mendelian randomisation analyses suggested the true causal effect was even stronger: −0.27 dioptres/y (−0.37 to −0.17; P=4e-8). By contrast, there was little evidence to suggest myopia affected education (years in education per dioptre of refractive error −0.008 y/dioptre, 95% confidence interval −0.041 to 0.025, P=0.6). Thus, the cumulative effect of more years in education on refractive error means that a university graduate from the United Kingdom with 17 years of education would, on average, be at least −1 dioptre more myopic than someone who left school at age 16 (with 12 years of education). Myopia of this magnitude would be sufficient to necessitate the use of glasses for driving. Sensitivity analyses showed minimal evidence for genetic confounding that could have biased the causal effect estimates. Conclusions This study shows that exposure to more years in education contributes to the rising prevalence of myopia. Increasing the length of time spent in education may inadvertently increase the prevalence of myopia and potential future visual disability. PMID:29875094
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Inherited platelet disorders: toward DNA-based diagnosis
Lentaigne, Claire; Freson, Kathleen; Laffan, Michael A.; Turro, Ernest
2016-01-01
Variations in platelet number, volume, and function are largely genetically controlled, and many loci associated with platelet traits have been identified by genome-wide association studies (GWASs).1 The genome also contains a large number of rare variants, of which a tiny fraction underlies the inherited diseases of humans. Research over the last 3 decades has led to the discovery of 51 genes harboring variants responsible for inherited platelet disorders (IPDs). However, the majority of patients with an IPD still do not receive a molecular diagnosis. Alongside the scientific interest, molecular or genetic diagnosis is important for patients. There is increasing recognition that a number of IPDs are associated with severe pathologies, including an increased risk of malignancy, and a definitive diagnosis can inform prognosis and care. In this review, we give an overview of these disorders grouped according to their effect on platelet biology and their clinical characteristics. We also discuss the challenge of identifying candidate genes and causal variants therein, how IPDs have been historically diagnosed, and how this is changing with the introduction of high-throughput sequencing. Finally, we describe how integration of large genomic, epigenomic, and phenotypic datasets, including whole genome sequencing data, GWASs, epigenomic profiling, protein–protein interaction networks, and standardized clinical phenotype coding, will drive the discovery of novel mechanisms of disease in the near future to improve patient diagnosis and management. PMID:27095789
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Implication of Genes for the N-Methyl-D-Aspartate (NMDA) Receptor in Substance Addictions.
Chen, Jiali; Ma, Yunlong; Fan, Rongli; Yang, Zhongli; Li, Ming D
2018-02-10
Drug dependence is a chronic brain disease with harmful consequences for both individual users and society. Glutamate is a primary excitatory neurotransmitter in the brain, and both in vivo and in vitro experiments have implicated N-methyl-D-aspartate (NMDA) receptor, a glutamate receptor, as an element in various types of addiction. Recent findings from genetics-based approaches such as genome-wide linkage, candidate gene association, genome-wide association (GWA), and next-generation sequencing have demonstrated the significant association of NMDA receptor subunit genes such as GluN3A, GluN2B, and GluN2A with various addiction-related phenotypes. Of these genes, GluN3A has been the most studied, and it has been revealed to play crucial roles in the etiology of addictions. In this communication, we provide an updated view of the genetic effects of NMDA receptor subunit genes and their functions in the etiology of addictions based on the findings from investigation of both common and rare variants as well as SNP-SNP interactions. To better understand the molecular mechanisms underlying addiction-related behaviors and to promote the development of specific medicines for the prevention and treatment of addictions, current efforts aim not only to identify more causal variants in NMDA receptor subunits by using large independent samples but also to reveal the molecular functions of these variants in addictions.
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Bonilla, Carolina; Lewis, Sarah J; Rowlands, Mari-Anne; Gaunt, Tom R; Davey Smith, George; Gunnell, David; Palmer, Tom; Donovan, Jenny L; Hamdy, Freddie C; Neal, David E; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Al Olama, Ali Amin; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Grönberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Blot, William J; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Lathrop, Mark; Martin, Richard M; Holly, Jeff M P
2016-10-01
Circulating insulin-like growth factors (IGFs) and their binding proteins (IGFBPs) are associated with prostate cancer. Using genetic variants as instruments for IGF peptides, we investigated whether these associations are likely to be causal. We identified from the literature 56 single nucleotide polymorphisms (SNPs) in the IGF axis previously associated with biomarker levels (8 from a genome-wide association study [GWAS] and 48 in reported candidate genes). In ∼700 men without prostate cancer and two replication cohorts (N ∼ 900 and ∼9,000), we examined the properties of these SNPS as instrumental variables (IVs) for IGF-I, IGF-II, IGFBP-2 and IGFBP-3. Those confirmed as strong IVs were tested for association with prostate cancer risk, low (< 7) vs. high (≥ 7) Gleason grade, localised vs. advanced stage, and mortality, in 22,936 controls and 22,992 cases. IV analysis was used in an attempt to estimate the causal effect of circulating IGF peptides on prostate cancer. Published SNPs in the IGFBP1/IGFBP3 gene region, particularly rs11977526, were strong instruments for IGF-II and IGFBP-3, less so for IGF-I. Rs11977526 was associated with high (vs. low) Gleason grade (OR per IGF-II/IGFBP-3 level-raising allele 1.05; 95% CI: 1.00, 1.10). Using rs11977526 as an IV we estimated the causal effect of a one SD increase in IGF-II (∼265 ng/mL) on risk of high vs. low grade disease as 1.14 (95% CI: 1.00, 1.31). Because of the potential for pleiotropy of the genetic instruments, these findings can only causally implicate the IGF pathway in general, not any one specific biomarker. © 2016 UICC.
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Martin, Richard M.; Geybels, Milan S.; Stanford, Janet L.; Shui, Irene; Eeles, Rosalind; Easton, Doug; Kote‐Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G.; Travis, Ruth C; Neal, David; Pashayan, Nora; Khaw, Kay‐Tee; Blot, William; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon‐Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Donovan, Jenny; Munafò, Marcus R.
2016-01-01
Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all‐cause and prostate cancer‐specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high‐grade compared to low‐grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all‐cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer‐specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression. PMID:27741566
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Hemani, Gibran; Yang, Jian; Vinkhuyzen, Anna; Powell, Joseph E; Willemsen, Gonneke; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Mangino, Massimo; Valdes, Ana M; Medland, Sarah E; Madden, Pamela A; Heath, Andrew C; Henders, Anjali K; Nyholt, Dale R; de Geus, Eco J C; Magnusson, Patrik K E; Ingelsson, Erik; Montgomery, Grant W; Spector, Timothy D; Boomsma, Dorret I; Pedersen, Nancy L; Martin, Nicholas G; Visscher, Peter M
2013-11-07
Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 × 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 × 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Exome Sequence Analysis of 14 Families With High Myopia.
Kloss, Bethany A; Tompson, Stuart W; Whisenhunt, Kristina N; Quow, Krystina L; Huang, Samuel J; Pavelec, Derek M; Rosenberg, Thomas; Young, Terri L
2017-04-01
To identify causal gene mutations in 14 families with autosomal dominant (AD) high myopia using exome sequencing. Select individuals from 14 large Caucasian families with high myopia were exome sequenced. Gene variants were filtered to identify potential pathogenic changes. Sanger sequencing was used to confirm variants in original DNA, and to test for disease cosegregation in additional family members. Candidate genes and chromosomal loci previously associated with myopic refractive error and its endophenotypes were comprehensively screened. In 14 high myopia families, we identified 73 rare and 31 novel gene variants as candidates for pathogenicity. In seven of these families, two of the novel and eight of the rare variants were within known myopia loci. A total of 104 heterozygous nonsynonymous rare variants in 104 genes were identified in 10 out of 14 probands. Each variant cosegregated with affection status. No rare variants were identified in genes known to cause myopia or in genes closest to published genome-wide association study association signals for refractive error or its endophenotypes. Whole exome sequencing was performed to determine gene variants implicated in the pathogenesis of AD high myopia. This study provides new genes for consideration in the pathogenesis of high myopia, and may aid in the development of genetic profiling of those at greatest risk for attendant ocular morbidities of this disorder.
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de Vries, Tamar I; R Monroe, Glen; van Belzen, Martine J; van der Lans, Christian A; Savelberg, Sanne MC; Newman, William G; van Haaften, Gijs; Nievelstein, Rutger A; van Haelst, Mieke M
2016-01-01
Rubinstein–Taybi syndrome (RTS, OMIM 180849) and Filippi syndrome (FLPIS, OMIM 272440) are both rare syndromes, with multiple congenital anomalies and intellectual deficit (MCA/ID). We present a patient with intellectual deficit, short stature, bilateral syndactyly of hands and feet, broad thumbs, ocular abnormalities, and dysmorphic facial features. These clinical features suggest both RTS and FLPIS. Initial DNA analysis of DNA isolated from blood did not identify variants to confirm either of these syndrome diagnoses. Whole-exome sequencing identified a homozygous variant in C9orf173, which was novel at the time of analysis. Further Sanger sequencing analysis of FLPIS cases tested negative for CKAP2L variants did not, however, reveal any further variants. Subsequent analysis using DNA isolated from buccal mucosa revealed a mosaic variant in CREBBP. This report highlights the importance of excluding mosaic variants in patients with a strong but atypical clinical presentation of a MCA/ID syndrome if no disease-causing variants can be detected in DNA isolated from blood samples. As the striking syndactyly observed in the present case is typical for FLPIS, we suggest CREBBP analysis in saliva samples for FLPIS syndrome cases in which no causal CKAP2L variant is detected. PMID:26956253
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GM2 Gangliosidosis in Shiba Inu Dogs with an In-Frame Deletion in HEXB.
Kolicheski, A; Johnson, G S; Villani, N A; O'Brien, D P; Mhlanga-Mutangadura, T; Wenger, D A; Mikoloski, K; Eagleson, J S; Taylor, J F; Schnabel, R D; Katz, M L
2017-09-01
Consistent with a tentative diagnosis of neuronal ceroid lipofuscinosis (NCL), autofluorescent cytoplasmic storage bodies were found in neurons from the brains of 2 related Shiba Inu dogs with a young-adult onset, progressive neurodegenerative disease. Unexpectedly, no potentially causal NCL-related variants were identified in a whole-genome sequence generated with DNA from 1 of the affected dogs. Instead, the whole-genome sequence contained a homozygous 3 base pair (bp) deletion in a coding region of HEXB. The other affected dog also was homozygous for this 3-bp deletion. Mutations in the human HEXB ortholog cause Sandhoff disease, a type of GM2 gangliosidosis. Thin-layer chromatography confirmed that GM2 ganglioside had accumulated in an affected Shiba Inu brain. Enzymatic analysis confirmed that the GM2 gangliosidosis resulted from a deficiency in the HEXB encoded protein and not from a deficiency in products from HEXA or GM2A, which are known alternative causes of GM2 gangliosidosis. We conclude that the homozygous 3-bp deletion in HEXB is the likely cause of the Shiba Inu neurodegenerative disease and that whole-genome sequencing can lead to the early identification of potentially disease-causing DNA variants thereby refocusing subsequent diagnostic analyses toward confirming or refuting candidate variant causality. Copyright © 2017 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.
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Convergence between biological, behavioural and genetic determinants of obesity.
Ghosh, Sujoy; Bouchard, Claude
2017-12-01
Multiple biological, behavioural and genetic determinants or correlates of obesity have been identified to date. Genome-wide association studies (GWAS) have contributed to the identification of more than 100 obesity-associated genetic variants, but their roles in causal processes leading to obesity remain largely unknown. Most variants are likely to have tissue-specific regulatory roles through joint contributions to biological pathways and networks, through changes in gene expression that influence quantitative traits, or through the regulation of the epigenome. The recent availability of large-scale functional genomics resources provides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic variants. Interrogation of knockout mouse phenotype resources provides a further avenue to test for evidence of convergence between genetic variation and biological or behavioural determinants of obesity.
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Comparison of six methods for the detection of causality in a bivariate time series
NASA Astrophysics Data System (ADS)
Krakovská, Anna; Jakubík, Jozef; Chvosteková, Martina; Coufal, David; Jajcay, Nikola; Paluš, Milan
2018-04-01
In this comparative study, six causality detection methods were compared, namely, the Granger vector autoregressive test, the extended Granger test, the kernel version of the Granger test, the conditional mutual information (transfer entropy), the evaluation of cross mappings between state spaces, and an assessment of predictability improvement due to the use of mixed predictions. Seven test data sets were analyzed: linear coupling of autoregressive models, a unidirectional connection of two Hénon systems, a unidirectional connection of chaotic systems of Rössler and Lorenz type and of two different Rössler systems, an example of bidirectionally connected two-species systems, a fishery model as an example of two correlated observables without a causal relationship, and an example of mediated causality. We tested not only 20 000 points long clean time series but also noisy and short variants of the data. The standard and the extended Granger tests worked only for the autoregressive models. The remaining methods were more successful with the more complex test examples, although they differed considerably in their capability to reveal the presence and the direction of coupling and to distinguish causality from mere correlation.
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C-reactive protein and genetic variants and cognitive decline in old age: The PROSPER Study
USDA-ARS?s Scientific Manuscript database
Plasma concentrations of C-reactive protein (CRP), a marker of chronic inflammation, have been associated with cognitive impairment in old age. However, it is unknown whether CRP is causally linked to cognitive decline. Within the Prospective Study of Pravastatin in the Elderly at Risk (PROSPER) tri...
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USDA-ARS?s Scientific Manuscript database
Initial genomic test results for US Ayrshire dairy cattle became available in January of 2013. Several haplotypes that showed a deficiency of homozygotes were investigated to determine if they had an effect on fertility. A haplotype on chromosome 17 was determined to affect fertility, indicating tha...
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Genome-wide and fine-resolution association analysis of malaria in West Africa.
Jallow, Muminatou; Teo, Yik Ying; Small, Kerrin S; Rockett, Kirk A; Deloukas, Panos; Clark, Taane G; Kivinen, Katja; Bojang, Kalifa A; Conway, David J; Pinder, Margaret; Sirugo, Giorgio; Sisay-Joof, Fatou; Usen, Stanley; Auburn, Sarah; Bumpstead, Suzannah J; Campino, Susana; Coffey, Alison; Dunham, Andrew; Fry, Andrew E; Green, Angela; Gwilliam, Rhian; Hunt, Sarah E; Inouye, Michael; Jeffreys, Anna E; Mendy, Alieu; Palotie, Aarno; Potter, Simon; Ragoussis, Jiannis; Rogers, Jane; Rowlands, Kate; Somaskantharajah, Elilan; Whittaker, Pamela; Widden, Claire; Donnelly, Peter; Howie, Bryan; Marchini, Jonathan; Morris, Andrew; SanJoaquin, Miguel; Achidi, Eric Akum; Agbenyega, Tsiri; Allen, Angela; Amodu, Olukemi; Corran, Patrick; Djimde, Abdoulaye; Dolo, Amagana; Doumbo, Ogobara K; Drakeley, Chris; Dunstan, Sarah; Evans, Jennifer; Farrar, Jeremy; Fernando, Deepika; Hien, Tran Tinh; Horstmann, Rolf D; Ibrahim, Muntaser; Karunaweera, Nadira; Kokwaro, Gilbert; Koram, Kwadwo A; Lemnge, Martha; Makani, Julie; Marsh, Kevin; Michon, Pascal; Modiano, David; Molyneux, Malcolm E; Mueller, Ivo; Parker, Michael; Peshu, Norbert; Plowe, Christopher V; Puijalon, Odile; Reeder, John; Reyburn, Hugh; Riley, Eleanor M; Sakuntabhai, Anavaj; Singhasivanon, Pratap; Sirima, Sodiomon; Tall, Adama; Taylor, Terrie E; Thera, Mahamadou; Troye-Blomberg, Marita; Williams, Thomas N; Wilson, Michael; Kwiatkowski, Dominic P
2009-06-01
We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10(-7) to P = 4 × 10(-14), with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations.
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Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B
2017-06-01
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
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Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Smith, George Davey; de Geus, Eco JCN; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian’an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O’Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Velez Edwards, Digna R; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B
2018-01-01
The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project–imputed genotype data in up to ~370,000 women, we identify 389 independent signals (P < 5 × 10−8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ~7.4% of the population variance in age at menarche, corresponding to ~25% of the estimated heritability. We implicate ~250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility. PMID:28436984
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The multifaceted interplay between lipids and epigenetics.
Dekkers, Koen F; Slagboom, P Eline; Jukema, J Wouter; Heijmans, Bastiaan T
2016-06-01
The interplay between lipids and epigenetic mechanisms has recently gained increased interest because of its relevance for common diseases and most notably atherosclerosis. This review discusses recent advances in unravelling this interplay with a particular focus on promising approaches and methods that will be able to establish causal relationships. Complementary approaches uncovered close links between circulating lipids and epigenetic mechanisms at multiple levels. A characterization of lipid-associated genetic variants suggests that these variants exert their influence on lipid levels through epigenetic changes in the liver. Moreover, exposure of monocytes to lipids persistently alters their epigenetic makeup resulting in more proinflammatory cells. Hence, epigenetic changes can both impact on and be induced by lipids. It is the combined application of technological advances to probe epigenetic modifications at a genome-wide scale and methodological advances aimed at causal inference (including Mendelian randomization and integrative genomics) that will elucidate the interplay between circulating lipids and epigenetics. Understanding its role in the development of atherosclerosis holds the promise of identifying a new category of therapeutic targets, since epigenetic changes are amenable to reversal.
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Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R.; Mahajan, Anubha; Asimit, Jennifer L.; Ferreira, Teresa; Locke, Adam E.; Robertson, Neil R.; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E.; Tam, Claudia H.T.; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I.; Blangero, John; Burtt, Noél P.; Duggirala, Ravindranath; Florez, Jose C.; Hanis, Craig L.; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C.N.; Ma, Ronald C.W.; Froguel, Philippe; Wilson, James G.; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B.; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S.; Chambers, John C.; Saleheen, Danish; Kadowaki, Takashi; Tai, E. Shyong; Mohlke, Karen L.; Cox, Nancy J.; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I.; Morris, Andrew P.
2016-01-01
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. PMID:26911676
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Decoding the role of regulatory element polymorphisms in complex disease.
Vockley, Christopher M; Barrera, Alejandro; Reddy, Timothy E
2017-04-01
Genetic variation in gene regulatory elements contributes to diverse human diseases, ranging from rare and severe developmental defects to common and complex diseases such as obesity and diabetes. Early examples of regulatory mechanisms of human diseases involve large chromosomal rearrangements that change the regulatory connections within the genome. Single nucleotide variants in regulatory elements can also contribute to disease, potentially via demonstrated associations with changes in transcription factor binding, enhancer activity, post-translational histone modifications, long-range enhancer-promoter interactions, or RNA polymerase recruitment. Establishing causality between non-coding genetic variants, gene regulation, and disease has recently become more feasible with advances in genome-editing and epigenome-editing technologies. As establishing causal regulatory mechanisms of diseases becomes routine, functional annotation of target genes is likely to emerge as a major bottleneck for translation into patient benefits. In this review, we discuss the history and recent advances in understanding the regulatory mechanisms of human disease, and new challenges likely to be encountered once establishing those mechanisms becomes rote. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Davies, Benjamin; Brown, Laurence A; Cais, Ondrej; Clayton, Amber J; Chang, Veronica T; Biggs, Daniel; Preece, Christopher; Hernandez-Pliego, Polinka; Krohn, Jon; Bhomra, Amarjit; Twigg, Stephen R F; Rimmer, Andrew; Kanapin, Alexander; Sen, Arjune; Zaiwalla, Zenobia; McVean, Gil; Foster, Russell; Donnelly, Peter; Taylor, Jenny C; Blair, Edward; Nutt, David; Aricescu, A Radu; Greger, Ingo H; Peirson, Stuart N; Flint, Jonathan
2017-01-01
Abstract The discovery of genetic variants influencing sleep patterns can shed light on the physiological processes underlying sleep. As part of a large clinical sequencing project, WGS500, we sequenced a family in which the two male children had severe developmental delay and a dramatically disturbed sleep-wake cycle, with very long wake and sleep durations, reaching up to 106-h awake and 48-h asleep. The most likely causal variant identified was a novel missense variant in the X-linked GRIA3 gene, which has been implicated in intellectual disability. GRIA3 encodes GluA3, a subunit of AMPA-type ionotropic glutamate receptors (AMPARs). The mutation (A653T) falls within the highly conserved transmembrane domain of the ion channel gate, immediately adjacent to the analogous residue in the Grid2 (glutamate receptor) gene, which is mutated in the mouse neurobehavioral mutant, Lurcher. In vitro, the GRIA3(A653T) mutation stabilizes the channel in a closed conformation, in contrast to Lurcher. We introduced the orthologous mutation into a mouse strain by CRISPR-Cas9 mutagenesis and found that hemizygous mutants displayed significant differences in the structure of their activity and sleep compared to wild-type littermates. Typically, mice are polyphasic, exhibiting multiple sleep bouts of sleep several minutes long within a 24-h period. The Gria3A653T mouse showed significantly fewer brief bouts of activity and sleep than the wild-types. Furthermore, Gria3A653T mice showed enhanced period lengthening under constant light compared to wild-type mice, suggesting an increased sensitivity to light. Our results suggest a role for GluA3 channel activity in the regulation of sleep behavior in both mice and humans. PMID:29016847
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Whole exome sequencing of rare variants in EIF4G1 and VPS35 in Parkinson disease
Nuytemans, Karen; Bademci, Guney; Inchausti, Vanessa; Dressen, Amy; Kinnamon, Daniel D.; Mehta, Arpit; Wang, Liyong; Züchner, Stephan; Beecham, Gary W.; Martin, Eden R.; Scott, William K.
2013-01-01
Objective: Recently, vacuolar protein sorting 35 (VPS35) and eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) have been identified as 2 causal Parkinson disease (PD) genes. We used whole exome sequencing for rapid, parallel analysis of variations in these 2 genes. Methods: We performed whole exome sequencing in 213 patients with PD and 272 control individuals. Those rare variants (RVs) with <5% frequency in the exome variant server database and our own control data were considered for analysis. We performed joint gene-based tests for association using RVASSOC and SKAT (Sequence Kernel Association Test) as well as single-variant test statistics. Results: We identified 3 novel VPS35 variations that changed the coded amino acid (nonsynonymous) in 3 cases. Two variations were in multiplex families and neither segregated with PD. In EIF4G1, we identified 11 (9 nonsynonymous and 2 small indels) RVs including the reported pathogenic mutation p.R1205H, which segregated in all affected members of a large family, but also in 1 unaffected 86-year-old family member. Two additional RVs were found in isolated patients only. Whereas initial association studies suggested an association (p = 0.04) with all RVs in EIF4G1, subsequent testing in a second dataset for the driving variant (p.F1461) suggested no association between RVs in the gene and PD. Conclusions: We confirm that the specific EIF4G1 variation p.R1205H seems to be a strong PD risk factor, but is nonpenetrant in at least one 86-year-old. A few other select RVs in both genes could not be ruled out as causal. However, there was no evidence for an overall contribution of genetic variability in VPS35 or EIF4G1 to PD development in our dataset. PMID:23408866
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Thyroid Signaling, Insulin Resistance, and 2 Diabetes Mellitus: A Mendelian Randomization Study.
Bos, Maxime M; Smit, Roelof A J; Trompet, Stella; van Heemst, Diana; Noordam, Raymond
2017-06-01
Increasing evidence suggests an association between thyroid-stimulating hormone (TSH), free thyroxine (fT4), and deiodinases with insulin resistance and type 2 diabetes mellitus (T2D). We examined whether TSH and fT4 levels and deiodinases are causally associated with insulin resistance and T2D, using Mendelian randomization. We selected 20 genetic variants for TSH level and four for fT4 level (identified in a genome-wide association study (GWAS) meta-analysis of European-ancestry cohorts) as instrumental variables for TSH and fT4 levels, respectively. We used summary data from GWASs on the outcomes T2D [Diabetes, Genetics Replication and Meta-analysis (DIAGRAM), n = 12,171 cases and n = 56,862 control subjects] and glycemic traits in patients without diabetes [Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), n = 46,186 for fasting glucose and insulin and n = 46,368 for hemoglobin A1c]. To examine whether the associations between TSH/fT4 levels and the study outcomes were causal, we combined the effects of the genetic instruments. Furthermore, we examined the associations among 16 variants in DIO1, DIO2, DIO3, and T2D and glycemic traits. We found no evidence for an association between the combined genetic instrumental variables for TSH and fT4 and the study outcomes. For example, we did not observe a genetically determined association between high TSH level and T2D (odds ratio, 0.91 per standard deviation TSH increase; 95% confidence interval, 0.78 to 1.07). Selected genetic variants in DIO1 (e.g., rs7527713) were associated with measures of insulin resistance. We found no evidence for a causal association between circulatory levels of TSH and fT4 with insulin resistance and T2D, but we found suggestive evidence that DIO1 affects glucose metabolism. Copyright © 2017 by the Endocrine Society
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Genetic Candidate Variants in Two Multigenerational Families with Childhood Apraxia of Speech
Wijsman, Ellen M.; Nato, Alejandro Q.; Matsushita, Mark M.; Chapman, Kathy L.; Stanaway, Ian B.; Wolff, John; Oda, Kaori; Gabo, Virginia B.; Raskind, Wendy H.
2016-01-01
Childhood apraxia of speech (CAS) is a severe and socially debilitating form of speech sound disorder with suspected genetic involvement, but the genetic etiology is not yet well understood. Very few known or putative causal genes have been identified to date, e.g., FOXP2 and BCL11A. Building a knowledge base of the genetic etiology of CAS will make it possible to identify infants at genetic risk and motivate the development of effective very early intervention programs. We investigated the genetic etiology of CAS in two large multigenerational families with familial CAS. Complementary genomic methods included Markov chain Monte Carlo linkage analysis, copy-number analysis, identity-by-descent sharing, and exome sequencing with variant filtering. No overlaps in regions with positive evidence of linkage between the two families were found. In one family, linkage analysis detected two chromosomal regions of interest, 5p15.1-p14.1, and 17p13.1-q11.1, inherited separately from the two founders. Single-point linkage analysis of selected variants identified CDH18 as a primary gene of interest and additionally, MYO10, NIPBL, GLP2R, NCOR1, FLCN, SMCR8, NEK8, and ANKRD12, possibly with additive effects. Linkage analysis in the second family detected five regions with LOD scores approaching the highest values possible in the family. A gene of interest was C4orf21 (ZGRF1) on 4q25-q28.2. Evidence for previously described causal copy-number variations and validated or suspected genes was not found. Results are consistent with a heterogeneous CAS etiology, as is expected in many neurogenic disorders. Future studies will investigate genome variants in these and other families with CAS. PMID:27120335
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Tang, Clara S; Zhang, He; Cheung, Chloe Y Y; Xu, Ming; Ho, Jenny C Y; Zhou, Wei; Cherny, Stacey S; Zhang, Yan; Holmen, Oddgeir; Au, Ka-Wing; Yu, Haiyi; Xu, Lin; Jia, Jia; Porsch, Robert M; Sun, Lijie; Xu, Weixian; Zheng, Huiping; Wong, Lai-Yung; Mu, Yiming; Dou, Jingtao; Fong, Carol H Y; Wang, Shuyu; Hong, Xueyu; Dong, Liguang; Liao, Yanhua; Wang, Jiansong; Lam, Levina S M; Su, Xi; Yan, Hua; Yang, Min-Lee; Chen, Jin; Siu, Chung-Wah; Xie, Gaoqiang; Woo, Yu-Cho; Wu, Yangfeng; Tan, Kathryn C B; Hveem, Kristian; Cheung, Bernard M Y; Zöllner, Sebastian; Xu, Aimin; Eugene Chen, Y; Jiang, Chao Qiang; Zhang, Youyi; Lam, Tai-Hing; Ganesh, Santhi K; Huo, Yong; Sham, Pak C; Lam, Karen S L; Willer, Cristen J; Tse, Hung-Fat; Gao, Wei
2015-12-22
Blood lipids are important risk factors for coronary artery disease (CAD). Here we perform an exome-wide association study by genotyping 12,685 Chinese, using a custom Illumina HumanExome BeadChip, to identify additional loci influencing lipid levels. Single-variant association analysis on 65,671 single nucleotide polymorphisms reveals 19 loci associated with lipids at exome-wide significance (P<2.69 × 10(-7)), including three Asian-specific coding variants in known genes (CETP p.Asp459Gly, PCSK9 p.Arg93Cys and LDLR p.Arg257Trp). Furthermore, missense variants at two novel loci-PNPLA3 p.Ile148Met and PKD1L3 p.Thr429Ser-also influence levels of triglycerides and low-density lipoprotein cholesterol, respectively. Another novel gene, TEAD2, is found to be associated with high-density lipoprotein cholesterol through gene-based association analysis. Most of these newly identified coding variants show suggestive association (P<0.05) with CAD. These findings demonstrate that exome-wide genotyping on samples of non-European ancestry can identify additional population-specific possible causal variants, shedding light on novel lipid biology and CAD.
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Rodriguez-Flores, Juan L.; Fakhro, Khalid; Hackett, Neil R.; Salit, Jacqueline; Fuller, Jennifer; Agosto-Perez, Francisco; Gharbiah, Maey; Malek, Joel A.; Zirie, Mahmoud; Jayyousi, Amin; Badii, Ramin; Al-Marri, Ajayeb Al-Nabet; Chouchane, Lotfi; Stadler, Dora J.; Hunter-Zinck, Haley; Mezey, Jason G.; Crystal, Ronald G.
2013-01-01
Exome sequencing of families of related individuals has been highly successful in identifying genetic polymorphisms responsible for Mendelian disorders. Here, we demonstrate the value of the reverse approach, where we use exome sequencing of a sample of unrelated individuals to analyze allele frequencies of known causal mutations for Mendelian diseases. We sequenced the exomes of 100 individuals representing the three major genetic subgroups of the Qatari population (Q1 Bedouin, Q2 Persian-South Asian, Q3 African) and identified 37 variants in 33 genes with effects on 36 clinically significant Mendelian diseases. These include variants not present in 1000 Genomes and variants at high frequency when compared to 1000 Genomes populations. Several of these Mendelian variants were only segregating in one Qatari subpopulation, where the observed subpopulation specificity trends were confirmed in an independent population of 386 Qataris. Pre-marital genetic screening in Qatar tests for only 4 out of the 37, such that this study provides a set of Mendelian disease variants with potential impact on the epidemiological profile of the population that could be incorporated into the testing program if further experimental and clinical characterization confirms high penetrance. PMID:24123366
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A generalized least-squares framework for rare-variant analysis in family data.
Li, Dalin; Rotter, Jerome I; Guo, Xiuqing
2014-01-01
Rare variants may, in part, explain some of the hereditability missing in current genome-wide association studies. Many gene-based rare-variant analysis approaches proposed in recent years are aimed at population-based samples, although analysis strategies for family-based samples are clearly warranted since the family-based design has the potential to enhance our ability to enrich for rare causal variants. We have recently developed the generalized least squares, sequence kernel association test, or GLS-SKAT, approach for the rare-variant analyses in family samples, in which the kinship matrix that was computed from the high dimension genetic data was used to decorrelate the family structure. We then applied the SKAT-O approach for gene-/region-based inference in the decorrelated data. In this study, we applied this GLS-SKAT method to the systolic blood pressure data in the simulated family sample distributed by the Genetic Analysis Workshop 18. We compared the GLS-SKAT approach to the rare-variant analysis approach implemented in family-based association test-v1 and demonstrated that the GLS-SKAT approach provides superior power and good control of type I error rate.
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Bouwman, Aniek C; Veerkamp, Roel F
2014-10-03
The aim of this study was to determine the consequences of splitting sequencing effort over multiple breeds for imputation accuracy from a high-density SNP chip towards whole-genome sequence. Such information would assist for instance numerical smaller cattle breeds, but also pig and chicken breeders, who have to choose wisely how to spend their sequencing efforts over all the breeds or lines they evaluate. Sequence data from cattle breeds was used, because there are currently relatively many individuals from several breeds sequenced within the 1,000 Bull Genomes project. The advantage of whole-genome sequence data is that it carries the causal mutations, but the question is whether it is possible to impute the causal variants accurately. This study therefore focussed on imputation accuracy of variants with low minor allele frequency and breed specific variants. Imputation accuracy was assessed for chromosome 1 and 29 as the correlation between observed and imputed genotypes. For chromosome 1, the average imputation accuracy was 0.70 with a reference population of 20 Holstein, and increased to 0.83 when the reference population was increased by including 3 other dairy breeds with 20 animals each. When the same amount of animals from the Holstein breed were added the accuracy improved to 0.88, while adding the 3 other breeds to the reference population of 80 Holstein improved the average imputation accuracy marginally to 0.89. For chromosome 29, the average imputation accuracy was lower. Some variants benefitted from the inclusion of other breeds in the reference population, initially determined by the MAF of the variant in each breed, but even Holstein specific variants did gain imputation accuracy from the multi-breed reference population. This study shows that splitting sequencing effort over multiple breeds and combining the reference populations is a good strategy for imputation from high-density SNP panels towards whole-genome sequence when reference populations are small and sequencing effort is limiting. When sequencing effort is limiting and interest lays in multiple breeds or lines this provides imputation of each breed.
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Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia
2018-06-11
Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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Mendelian randomization in nutritional epidemiology
Qi, Lu
2013-01-01
Nutritional epidemiology aims to identify dietary and lifestyle causes for human diseases. Causality inference in nutritional epidemiology is largely based on evidence from studies of observational design, and may be distorted by unmeasured or residual confounding and reverse causation. Mendelian randomization is a recently developed methodology that combines genetic and classical epidemiological analysis to infer causality for environmental exposures, based on the principle of Mendel’s law of independent assortment. Mendelian randomization uses genetic variants as proxiesforenvironmentalexposuresofinterest.AssociationsderivedfromMendelian randomization analysis are less likely to be affected by confounding and reverse causation. During the past 5 years, a body of studies examined the causal effects of diet/lifestyle factors and biomarkers on a variety of diseases. The Mendelian randomization approach also holds considerable promise in the study of intrauterine influences on offspring health outcomes. However, the application of Mendelian randomization in nutritional epidemiology has some limitations. PMID:19674341
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Bailey, Julia N; Patterson, Christopher; de Nijs, Laurence; Durón, Reyna M; Nguyen, Viet-Huong; Tanaka, Miyabi; Medina, Marco T; Jara-Prado, Aurelio; Martínez-Juárez, Iris E; Ochoa, Adriana; Molina, Yolli; Suzuki, Toshimitsu; Alonso, María E; Wight, Jenny E; Lin, Yu-Chen; Guilhoto, Laura; Targas Yacubian, Elza Marcia; Machado-Salas, Jesús; Daga, Andrea; Yamakawa, Kazuhiro; Grisar, Thierry M; Lakaye, Bernard; Delgado-Escueta, Antonio V
2017-02-01
EFHC1 variants are the most common mutations in inherited myoclonic and grand mal clonic-tonic-clonic (CTC) convulsions of juvenile myoclonic epilepsy (JME). We reanalyzed 54 EFHC1 variants associated with epilepsy from 17 cohorts based on National Human Genome Research Institute (NHGRI) and American College of Medical Genetics and Genomics (ACMG) guidelines for interpretation of sequence variants. We calculated Bayesian LOD scores for variants in coinheritance, unconditional exact tests and odds ratios (OR) in case-control associations, allele frequencies in genome databases, and predictions for conservation/pathogenicity. We reviewed whether variants damage EFHC1 functions, whether efhc1 -/- KO mice recapitulate CTC convulsions and "microdysgenesis" neuropathology, and whether supernumerary synaptic and dendritic phenotypes can be rescued in the fly model when EFHC1 is overexpressed. We rated strengths of evidence and applied ACMG combinatorial criteria for classifying variants. Nine variants were classified as "pathogenic," 14 as "likely pathogenic," 9 as "benign," and 2 as "likely benign." Twenty variants of unknown significance had an insufficient number of ancestry-matched controls, but ORs exceeded 5 when compared with racial/ethnic-matched Exome Aggregation Consortium (ExAC) controls. NHGRI gene-level evidence and variant-level evidence establish EFHC1 as the first non-ion channel microtubule-associated protein whose mutations disturb R-type VDCC and TRPM2 calcium currents in overgrown synapses and dendrites within abnormally migrated dislocated neurons, thus explaining CTC convulsions and "microdysgenesis" neuropathology of JME.Genet Med 19 2, 144-156.
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Manning, Alisa; Highland, Heather M; Gasser, Jessica; Sim, Xueling; Tukiainen, Taru; Fontanillas, Pierre; Grarup, Niels; Rivas, Manuel A; Mahajan, Anubha; Locke, Adam E; Cingolani, Pablo; Pers, Tune H; Viñuela, Ana; Brown, Andrew A; Wu, Ying; Flannick, Jason; Fuchsberger, Christian; Gamazon, Eric R; Gaulton, Kyle J; Im, Hae Kyung; Teslovich, Tanya M; Blackwell, Thomas W; Bork-Jensen, Jette; Burtt, Noël P; Chen, Yuhui; Green, Todd; Hartl, Christopher; Kang, Hyun Min; Kumar, Ashish; Ladenvall, Claes; Ma, Clement; Moutsianas, Loukas; Pearson, Richard D; Perry, John R B; Rayner, N William; Robertson, Neil R; Scott, Laura J; van de Bunt, Martijn; Eriksson, Johan G; Jula, Antti; Koskinen, Seppo; Lehtimäki, Terho; Palotie, Aarno; Raitakari, Olli T; Jacobs, Suzanne B R; Wessel, Jennifer; Chu, Audrey Y; Scott, Robert A; Goodarzi, Mark O; Blancher, Christine; Buck, Gemma; Buck, David; Chines, Peter S; Gabriel, Stacey; Gjesing, Anette P; Groves, Christopher J; Hollensted, Mette; Huyghe, Jeroen R; Jackson, Anne U; Jun, Goo; Justesen, Johanne Marie; Mangino, Massimo; Murphy, Jacquelyn; Neville, Matt; Onofrio, Robert; Small, Kerrin S; Stringham, Heather M; Trakalo, Joseph; Banks, Eric; Carey, Jason; Carneiro, Mauricio O; DePristo, Mark; Farjoun, Yossi; Fennell, Timothy; Goldstein, Jacqueline I; Grant, George; Hrabé de Angelis, Martin; Maguire, Jared; Neale, Benjamin M; Poplin, Ryan; Purcell, Shaun; Schwarzmayr, Thomas; Shakir, Khalid; Smith, Joshua D; Strom, Tim M; Wieland, Thomas; Lindstrom, Jaana; Brandslund, Ivan; Christensen, Cramer; Surdulescu, Gabriela L; Lakka, Timo A; Doney, Alex S F; Nilsson, Peter; Wareham, Nicholas J; Langenberg, Claudia; Varga, Tibor V; Franks, Paul W; Rolandsson, Olov; Rosengren, Anders H; Farook, Vidya S; Thameem, Farook; Puppala, Sobha; Kumar, Satish; Lehman, Donna M; Jenkinson, Christopher P; Curran, Joanne E; Hale, Daniel Esten; Fowler, Sharon P; Arya, Rector; DeFronzo, Ralph A; Abboud, Hanna E; Syvänen, Ann-Christine; Hicks, Pamela J; Palmer, Nicholette D; Ng, Maggie C Y; Bowden, Donald W; Freedman, Barry I; Esko, Tõnu; Mägi, Reedik; Milani, Lili; Mihailov, Evelin; Metspalu, Andres; Narisu, Narisu; Kinnunen, Leena; Bonnycastle, Lori L; Swift, Amy; Pasko, Dorota; Wood, Andrew R; Fadista, João; Pollin, Toni I; Barzilai, Nir; Atzmon, Gil; Glaser, Benjamin; Thorand, Barbara; Strauch, Konstantin; Peters, Annette; Roden, Michael; Müller-Nurasyid, Martina; Liang, Liming; Kriebel, Jennifer; Illig, Thomas; Grallert, Harald; Gieger, Christian; Meisinger, Christa; Lannfelt, Lars; Musani, Solomon K; Griswold, Michael; Taylor, Herman A; Wilson, Gregory; Correa, Adolfo; Oksa, Heikki; Scott, William R; Afzal, Uzma; Tan, Sian-Tsung; Loh, Marie; Chambers, John C; Sehmi, Jobanpreet; Kooner, Jaspal Singh; Lehne, Benjamin; Cho, Yoon Shin; Lee, Jong-Young; Han, Bok-Ghee; Käräjämäki, Annemari; Qi, Qibin; Qi, Lu; Huang, Jinyan; Hu, Frank B; Melander, Olle; Orho-Melander, Marju; Below, Jennifer E; Aguilar, David; Wong, Tien Yin; Liu, Jianjun; Khor, Chiea-Chuen; Chia, Kee Seng; Lim, Wei Yen; Cheng, Ching-Yu; Chan, Edmund; Tai, E Shyong; Aung, Tin; Linneberg, Allan; Isomaa, Bo; Meitinger, Thomas; Tuomi, Tiinamaija; Hakaste, Liisa; Kravic, Jasmina; Jørgensen, Marit E; Lauritzen, Torsten; Deloukas, Panos; Stirrups, Kathleen E; Owen, Katharine R; Farmer, Andrew J; Frayling, Timothy M; O'Rahilly, Stephen P; Walker, Mark; Levy, Jonathan C; Hodgkiss, Dylan; Hattersley, Andrew T; Kuulasmaa, Teemu; Stančáková, Alena; Barroso, Inês; Bharadwaj, Dwaipayan; Chan, Juliana; Chandak, Giriraj R; Daly, Mark J; Donnelly, Peter J; Ebrahim, Shah B; Elliott, Paul; Fingerlin, Tasha; Froguel, Philippe; Hu, Cheng; Jia, Weiping; Ma, Ronald C W; McVean, Gilean; Park, Taesung; Prabhakaran, Dorairaj; Sandhu, Manjinder; Scott, James; Sladek, Rob; Tandon, Nikhil; Teo, Yik Ying; Zeggini, Eleftheria; Watanabe, Richard M; Koistinen, Heikki A; Kesaniemi, Y Antero; Uusitupa, Matti; Spector, Timothy D; Salomaa, Veikko; Rauramaa, Rainer; Palmer, Colin N A; Prokopenko, Inga; Morris, Andrew D; Bergman, Richard N; Collins, Francis S; Lind, Lars; Ingelsson, Erik; Tuomilehto, Jaakko; Karpe, Fredrik; Groop, Leif; Jørgensen, Torben; Hansen, Torben; Pedersen, Oluf; Kuusisto, Johanna; Abecasis, Gonçalo; Bell, Graeme I; Blangero, John; Cox, Nancy J; Duggirala, Ravindranath; Seielstad, Mark; Wilson, James G; Dupuis, Josee; Ripatti, Samuli; Hanis, Craig L; Florez, Jose C; Mohlke, Karen L; Meigs, James B; Laakso, Markku; Morris, Andrew P; Boehnke, Michael; Altshuler, David; McCarthy, Mark I; Gloyn, Anna L; Lindgren, Cecilia M
2017-07-01
To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2 . © 2017 by the American Diabetes Association.
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Ng, Maggie C Y; Graff, Mariaelisa; Lu, Yingchang; Justice, Anne E; Mudgal, Poorva; Liu, Ching-Ti; Young, Kristin; Yanek, Lisa R; Feitosa, Mary F; Wojczynski, Mary K; Rand, Kristin; Brody, Jennifer A; Cade, Brian E; Dimitrov, Latchezar; Duan, Qing; Guo, Xiuqing; Lange, Leslie A; Nalls, Michael A; Okut, Hayrettin; Tajuddin, Salman M; Tayo, Bamidele O; Vedantam, Sailaja; Bradfield, Jonathan P; Chen, Guanjie; Chen, Wei-Min; Chesi, Alessandra; Irvin, Marguerite R; Padhukasahasram, Badri; Smith, Jennifer A; Zheng, Wei; Allison, Matthew A; Ambrosone, Christine B; Bandera, Elisa V; Bartz, Traci M; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Bottinger, Erwin P; Carpten, John; Chanock, Stephen J; Chen, Yii-Der Ida; Conti, David V; Cooper, Richard S; Fornage, Myriam; Freedman, Barry I; Garcia, Melissa; Goodman, Phyllis J; Hsu, Yu-Han H; Hu, Jennifer; Huff, Chad D; Ingles, Sue A; John, Esther M; Kittles, Rick; Klein, Eric; Li, Jin; McKnight, Barbara; Nayak, Uma; Nemesure, Barbara; Ogunniyi, Adesola; Olshan, Andrew; Press, Michael F; Rohde, Rebecca; Rybicki, Benjamin A; Salako, Babatunde; Sanderson, Maureen; Shao, Yaming; Siscovick, David S; Stanford, Janet L; Stevens, Victoria L; Stram, Alex; Strom, Sara S; Vaidya, Dhananjay; Witte, John S; Yao, Jie; Zhu, Xiaofeng; Ziegler, Regina G; Zonderman, Alan B; Adeyemo, Adebowale; Ambs, Stefan; Cushman, Mary; Faul, Jessica D; Hakonarson, Hakon; Levin, Albert M; Nathanson, Katherine L; Ware, Erin B; Weir, David R; Zhao, Wei; Zhi, Degui; Arnett, Donna K; Grant, Struan F A; Kardia, Sharon L R; Oloapde, Olufunmilayo I; Rao, D C; Rotimi, Charles N; Sale, Michele M; Williams, L Keoki; Zemel, Babette S; Becker, Diane M; Borecki, Ingrid B; Evans, Michele K; Harris, Tamara B; Hirschhorn, Joel N; Li, Yun; Patel, Sanjay R; Psaty, Bruce M; Rotter, Jerome I; Wilson, James G; Bowden, Donald W; Cupples, L Adrienne; Haiman, Christopher A; Loos, Ruth J F; North, Kari E
2017-04-01
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.
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Gorin, Michael B.
2012-01-01
Age-related macular degeneration (AMD) is a common condition among the elderly population that leads to the progressive central vision loss and serious compromise of quality of life for its sufferers. It is also one of the few disorders for whom the investigation of its genetics has yielded rich insights into its diversity and causality and holds the promise of enabling clinicians to provide better risk assessments for individuals as well as to develop and selectively deploy new therapeutics to either prevent or slow the development of disease and lessen the threat of vision loss. The genetics of AMD began initially with the appreciation of familial aggregation and increase risk and expanded with the initial association of APOE variants with the disease. The first major breakthroughs came with family-based linkage studies of affected (and discordant) sibs, which identified a number of genetic loci and led to the targeted search of the 1q31 and 10q26 loci for associated variants. Three of the initial four reports for the CFH variant, Y402H, were based on regional candidate searches, as were the two initial reports of the ARMS2/HTRA1 locus variants. Case-control association studies initially also played a role in discovering the major genetic variants for AMD, and the success of those early studies have been used to fuel enthusiasm for the methodology for a number of diseases. Until 2010, all of the subsequent genetic variants associated with AMD came from candidate gene testing based on the complement factor pathway. In 2010, several large-scale genome-wide association studies (GWAS) identified genes that had not been previously identified. Much of this historical information is available in a number of recent reviews.(Chen et al., 2010b; Deangelis et al., 2011; Fafowora and Gorin, 2012b; Francis and Klein, 2011; Kokotas et al., 2011) Large meta analysis of AMD GWAS has added new loci and variants to this collection.(Chen et al., 2010a; Kopplin et al., 2010; Yu et al., 2011) This paper will focus on the ongoing controversies that are confronting AMD genetics at this time, rather than attempting to summarize this field, which has exploded in the past 5 years. PMID:22561651
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‘US Furr’ and ‘US Furr-ST’ Mandarin
USDA-ARS?s Scientific Manuscript database
This document marks the official release of ‘US Furr’, a hybrid of ‘Clementine’ x ‘Murcott’, and ‘US Furr-ST’, an irradiated variant of ‘US Furr’ with apparent field tolerance to citrus scab (causal agent Elsinoe fawcetti Bitanc. and Jenk.). The hybridization creating ‘US Furr’ and ultimately ‘US Fu...
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Evaluating the quality of Marfan genotype-phenotype correlations in existing FBN1 databases.
Groth, Kristian A; Von Kodolitsch, Yskert; Kutsche, Kerstin; Gaustadnes, Mette; Thorsen, Kasper; Andersen, Niels H; Gravholt, Claus H
2017-07-01
Genetic FBN1 testing is pivotal for confirming the clinical diagnosis of Marfan syndrome. In an effort to evaluate variant causality, FBN1 databases are often used. We evaluated the current databases regarding FBN1 variants and validated associated phenotype records with a new Marfan syndrome geno-phenotyping tool called the Marfan score. We evaluated four databases (UMD-FBN1, ClinVar, the Human Gene Mutation Database (HGMD), and Uniprot) containing 2,250 FBN1 variants supported by 4,904 records presented in 307 references. The Marfan score calculated for phenotype data from the records quantified variant associations with Marfan syndrome phenotype. We calculated a Marfan score for 1,283 variants, of which we confirmed the database diagnosis of Marfan syndrome in 77.1%. This represented only 35.8% of the total registered variants; 18.5-33.3% (UMD-FBN1 versus HGMD) of variants associated with Marfan syndrome in the databases could not be confirmed by the recorded phenotype. FBN1 databases can be imprecise and incomplete. Data should be used with caution when evaluating FBN1 variants. At present, the UMD-FBN1 database seems to be the biggest and best curated; therefore, it is the most comprehensive database. However, the need for better genotype-phenotype curated databases is evident, and we hereby present such a database.Genet Med advance online publication 01 December 2016.
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Bone, William P.; Washington, Nicole L.; Buske, Orion J.; Adams, David R.; Davis, Joie; Draper, David; Flynn, Elise D.; Girdea, Marta; Godfrey, Rena; Golas, Gretchen; Groden, Catherine; Jacobsen, Julius; Köhler, Sebastian; Lee, Elizabeth M. J.; Links, Amanda E.; Markello, Thomas C.; Mungall, Christopher J.; Nehrebecky, Michele; Robinson, Peter N.; Sincan, Murat; Soldatos, Ariane G.; Tifft, Cynthia J.; Toro, Camilo; Trang, Heather; Valkanas, Elise; Vasilevsky, Nicole; Wahl, Colleen; Wolfe, Lynne A.; Boerkoel, Cornelius F.; Brudno, Michael; Haendel, Melissa A.; Gahl, William A.; Smedley, Damian
2016-01-01
Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Genet Med 18 6, 608–617. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein–protein association neighbors. Genet Med 18 6, 608–617. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Genet Med 18 6, 608–617. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders. Genet Med 18 6, 608–617. PMID:26562225
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An expanded genome-wide association study of type 2 diabetes in Europeans
Scott, Robert A; Scott, Laura J; Mägi, Reedik; Marullo, Letizia; Gaulton, Kyle J; Kaakinen, Marika; Pervjakova, Natalia; Pers, Tune H; Johnson, Andrew D; Eicher, John D; Jackson, Anne U; Ferreira, Teresa; Lee, Yeji; Ma, Clement; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Van Zuydam, Natalie R; Mahajan, Anubha; Chen, Han; Almgren, Peter; Voight, Ben F; Grallert, Harald; Müller-Nurasyid, Martina; Ried, Janina S; Rayner, William N; Robertson, Neil; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Fuchsberger, Christian; Kwan, Phoenix; Teslovich, Tanya M; Chanda, Pritam; Li, Man; Lu, Yingchang; Dina, Christian; Thuillier, Dorothee; Yengo, Loic; Jiang, Longda; Sparso, Thomas; Kestler, Hans A; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Frånberg, Mattias; Strawbridge, Rona J; Benediktsson, Rafn; Hreidarsson, Astradur B; Kong, Augustine; Sigurðsson, Gunnar; Kerrison, Nicola D; Luan, Jian'an; Liang, Liming; Meitinger, Thomas; Roden, Michael; Thorand, Barbara; Esko, Tõnu; Mihailov, Evelin; Fox, Caroline; Liu, Ching-Ti; Rybin, Denis; Isomaa, Bo; Lyssenko, Valeriya; Tuomi, Tiinamaija; Couper, David J; Pankow, James S; Grarup, Niels; Have, Christian T; Jørgensen, Marit E; Jørgensen, Torben; Linneberg, Allan; Cornelis, Marilyn C; van Dam, Rob M; Hunter, David J; Kraft, Peter; Sun, Qi; Edkins, Sarah; Owen, Katharine R; Perry, John RB; Wood, Andrew R; Zeggini, Eleftheria; Tajes-Fernandes, Juan; Abecasis, Goncalo R; Bonnycastle, Lori L; Chines, Peter S; Stringham, Heather M; Koistinen, Heikki A; Kinnunen, Leena; Sennblad, Bengt; Mühleisen, Thomas W; Nöthen, Markus M; Pechlivanis, Sonali; Baldassarre, Damiano; Gertow, Karl; Humphries, Steve E; Tremoli, Elena; Klopp, Norman; Meyer, Julia; Steinbach, Gerald; Wennauer, Roman; Eriksson, Johan G; Männistö, Satu; Peltonen, Leena; Tikkanen, Emmi; Charpentier, Guillaume; Eury, Elodie; Lobbens, Stéphane; Gigante, Bruna; Leander, Karin; McLeod, Olga; Bottinger, Erwin P; Gottesman, Omri; Ruderfer, Douglas; Blüher, Matthias; Kovacs, Peter; Tonjes, Anke; Maruthur, Nisa M; Scapoli, Chiara; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; de Faire, Ulf; Hamsten, Anders; Stumvoll, Michael; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; Ripatti, Samuli; Salomaa, Veikko; Pedersen, Nancy L; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Tuomilehto, Jaakko; Hansen, Torben; Pedersen, Oluf; Barroso, Inês; Lannfelt, Lars; Ingelsson, Erik; Lind, Lars; Lindgren, Cecilia M; Cauchi, Stephane; Froguel, Philippe; Loos, Ruth JF; Balkau, Beverley; Boeing, Heiner; Franks, Paul W; Barricarte Gurrea, Aurelio; Palli, Domenico; van der Schouw, Yvonne T; Altshuler, David; Groop, Leif C; Langenberg, Claudia; Wareham, Nicholas J; Sijbrands, Eric; van Duijn, Cornelia M; Florez, Jose C; Meigs, James B; Boerwinkle, Eric; Gieger, Christian; Strauch, Konstantin; Metspalu, Andres; Morris, Andrew D; Palmer, Colin NA; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Dupuis, Josée; Morris, Andrew P; Boehnke, Michael; McCarthy, Mark I; Prokopenko, Inga
2017-01-01
To characterise type 2 diabetes (T2D) associated variation across the allele frequency spectrum, we conducted a meta-analysis of genome-wide association data from 26,676 T2D cases and 132,532 controls of European ancestry after imputation using the 1000 Genomes multi-ethnic reference panel. Promising association signals were followed-up in additional data sets (of 14,545 or 7,397 T2D cases and 38,994 or 71,604 controls). We identified 13 novel T2D-associated loci (p<5×10-8), including variants near the GLP2R, GIP, and HLA-DQA1 genes. Our analysis brought the total number of independent T2D associations to 128 distinct signals at 113 loci. Despite substantially increased sample size and more complete coverage of low-frequency variation, all novel associations were driven by common SNVs. Credible sets of potentially causal variants were generally larger than those based on imputation with earlier reference panels, consistent with resolution of causal signals to common risk haplotypes. Stratification of T2D-associated loci based on T2D-related quantitative trait associations revealed tissue-specific enrichment of regulatory annotations in pancreatic islet enhancers for loci influencing insulin secretion, and in adipocytes, monocytes and hepatocytes for insulin action-associated loci. These findings highlight the predominant role played by common variants of modest effect and the diversity of biological mechanisms influencing T2D pathophysiology. PMID:28566273
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TCF7L2 is a master regulator of insulin production and processing.
Zhou, Yuedan; Park, Soo-Young; Su, Jing; Bailey, Kathleen; Ottosson-Laakso, Emilia; Shcherbina, Liliya; Oskolkov, Nikolay; Zhang, Enming; Thevenin, Thomas; Fadista, João; Bennet, Hedvig; Vikman, Petter; Wierup, Nils; Fex, Malin; Rung, Johan; Wollheim, Claes; Nobrega, Marcelo; Renström, Erik; Groop, Leif; Hansson, Ola
2014-12-15
Genome-wide association studies have revealed >60 loci associated with type 2 diabetes (T2D), but the underlying causal variants and functional mechanisms remain largely elusive. Although variants in TCF7L2 confer the strongest risk of T2D among common variants by presumed effects on islet function, the molecular mechanisms are not yet well understood. Using RNA-sequencing, we have identified a TCF7L2-regulated transcriptional network responsible for its effect on insulin secretion in rodent and human pancreatic islets. ISL1 is a primary target of TCF7L2 and regulates proinsulin production and processing via MAFA, PDX1, NKX6.1, PCSK1, PCSK2 and SLC30A8, thereby providing evidence for a coordinated regulation of insulin production and processing. The risk T-allele of rs7903146 was associated with increased TCF7L2 expression, and decreased insulin content and secretion. Using gene expression profiles of 66 human pancreatic islets donors', we also show that the identified TCF7L2-ISL1 transcriptional network is regulated in a genotype-dependent manner. Taken together, these results demonstrate that not only synthesis of proinsulin is regulated by TCF7L2 but also processing and possibly clearance of proinsulin and insulin. These multiple targets in key pathways may explain why TCF7L2 has emerged as the gene showing one of the strongest associations with T2D. © The Author 2014. Published by Oxford University Press.
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Genetic studies of Crohn's disease: Past, present and future
Liu, Jimmy Z.; Anderson, Carl A.
2014-01-01
The exact aetiology of Crohn's disease is unknown, though it is clear from early epidemiological studies that a combination of genetic and environmental risk factors contributes to an individual's disease susceptibility. Here, we review the history of gene-mapping studies of Crohn's disease, from the linkage-based studies that first implicated the NOD2 locus, through to modern-day genome-wide association studies that have discovered over 140 loci associated with Crohn's disease and yielded novel insights into the biological pathways underlying pathogenesis. We describe on-going and future gene-mapping studies that utilise next generation sequencing technology to pinpoint causal variants and identify rare genetic variation underlying Crohn's disease risk. We comment on the utility of genetic markers for predicting an individual's disease risk and discuss their potential for identifying novel drug targets and influencing disease management. Finally, we describe how these studies have shaped and continue to shape our understanding of the genetic architecture of Crohn's disease. PMID:24913378
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Wright, Caroline F; Fitzgerald, Tomas W; Jones, Wendy D; Clayton, Stephen; McRae, Jeremy F; van Kogelenberg, Margriet; King, Daniel A; Ambridge, Kirsty; Barrett, Daniel M; Bayzetinova, Tanya; Bevan, A Paul; Bragin, Eugene; Chatzimichali, Eleni A; Gribble, Susan; Jones, Philip; Krishnappa, Netravathi; Mason, Laura E; Miller, Ray; Morley, Katherine I; Parthiban, Vijaya; Prigmore, Elena; Rajan, Diana; Sifrim, Alejandro; Swaminathan, G Jawahar; Tivey, Adrian R; Middleton, Anna; Parker, Michael; Carter, Nigel P; Barrett, Jeffrey C; Hurles, Matthew E; FitzPatrick, David R; Firth, Helen V
2015-04-04
Human genome sequencing has transformed our understanding of genomic variation and its relevance to health and disease, and is now starting to enter clinical practice for the diagnosis of rare diseases. The question of whether and how some categories of genomic findings should be shared with individual research participants is currently a topic of international debate, and development of robust analytical workflows to identify and communicate clinically relevant variants is paramount. The Deciphering Developmental Disorders (DDD) study has developed a UK-wide patient recruitment network involving over 180 clinicians across all 24 regional genetics services, and has performed genome-wide microarray and whole exome sequencing on children with undiagnosed developmental disorders and their parents. After data analysis, pertinent genomic variants were returned to individual research participants via their local clinical genetics team. Around 80,000 genomic variants were identified from exome sequencing and microarray analysis in each individual, of which on average 400 were rare and predicted to be protein altering. By focusing only on de novo and segregating variants in known developmental disorder genes, we achieved a diagnostic yield of 27% among 1133 previously investigated yet undiagnosed children with developmental disorders, whilst minimising incidental findings. In families with developmentally normal parents, whole exome sequencing of the child and both parents resulted in a 10-fold reduction in the number of potential causal variants that needed clinical evaluation compared to sequencing only the child. Most diagnostic variants identified in known genes were novel and not present in current databases of known disease variation. Implementation of a robust translational genomics workflow is achievable within a large-scale rare disease research study to allow feedback of potentially diagnostic findings to clinicians and research participants. Systematic recording of relevant clinical data, curation of a gene-phenotype knowledge base, and development of clinical decision support software are needed in addition to automated exclusion of almost all variants, which is crucial for scalable prioritisation and review of possible diagnostic variants. However, the resource requirements of development and maintenance of a clinical reporting system within a research setting are substantial. Health Innovation Challenge Fund, a parallel funding partnership between the Wellcome Trust and the UK Department of Health. Copyright © 2015 Wright et al. Open Access article distributed under the terms of CC BY. Published by Elsevier Ltd. All rights reserved.
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Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter
2017-08-10
A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of independent biological knowledge.
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Lintas, Carla; Picinelli, Chiara; Piras, Ignazio Stefano; Sacco, Roberto; Brogna, Claudia; Persico, Antonio M
2017-03-17
Autism Spectrum Disorder (ASD) is endowed with impressive heritability estimates and high recurrence rates. Its genetic underpinnings are nonetheless very heterogeneous, with common, and rare contributing variants located in hundreds of different loci, each characterized by variable levels of penetrance. Multiplex families from single ethnic groups represent a useful means to reduce heterogeneity and enhance genetic load. We screened 19 Italian ASD multiplex families (3 triplets and 16 duplets, total N = 41 ASD subjects), using array-CGH (Agilent 180 K). Causal or ASD-relevant CNVs were detected in 36.6% (15/41) of ASD probands, corresponding to 36.8% (7/19) multiplex families with at least one affected sibling genetically positive. However, only in less than half (3/7) of positive families, affected siblings share the same causal or ASD-relevant CNV. Even in these three families, additional potentially relevant CNVs not shared by affected sib pairs were also detected. These results provide further evidence of genetic heterogeneity in ASD even within multiplex families belonging to a single ethnic group. Differences in CNV burden may likely contribute to the substantial clinical heterogeneity observed between affected siblings. In addition, Gene Ontology enrichment analysis indicates that most potentially causal or relevant ASD genes detected in our cohort belong to nervous system-specific categories, especially involved in neurite elongation and synaptic structure/function. These findings point toward the existence of genomic instability in these families, whose underlying genetic and epigenetic mechanisms deserve further scrutiny. © 2017 Wiley Periodicals, Inc.
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A variational Bayes discrete mixture test for rare variant association
Logsdon, Benjamin A.; Dai, James Y.; Auer, Paul L.; Johnsen, Jill M.; Ganesh, Santhi K.; Smith, Nicholas L.; Wilson, James G.; Tracy, Russell P.; Lange, Leslie A.; Jiao, Shuo; Rich, Stephen S.; Lettre, Guillaume; Carlson, Christopher S.; Jackson, Rebecca D.; O’Donnell, Christopher J.; Wurfel, Mark M.; Nickerson, Deborah A.; Tang, Hua; Reiner, Alexander P.; Kooperberg, Charles
2014-01-01
Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that “aggregate” tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute’s Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans. PMID:24482836
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A variational Bayes discrete mixture test for rare variant association.
Logsdon, Benjamin A; Dai, James Y; Auer, Paul L; Johnsen, Jill M; Ganesh, Santhi K; Smith, Nicholas L; Wilson, James G; Tracy, Russell P; Lange, Leslie A; Jiao, Shuo; Rich, Stephen S; Lettre, Guillaume; Carlson, Christopher S; Jackson, Rebecca D; O'Donnell, Christopher J; Wurfel, Mark M; Nickerson, Deborah A; Tang, Hua; Reiner, Alexander P; Kooperberg, Charles
2014-01-01
Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that "aggregate" tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute's Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans.
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USDA-ARS?s Scientific Manuscript database
Barley Mla (Mildew resistance locus a) confers allele-specific interactions with natural variants of the ascomycete fungus, Blumeria graminis f. sp. hordei (Bgh), causal agent of powdery mildew disease. Significant reprogramming of host gene expression occurs upon infection by this obligate biotrop...
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Genetic maps of stem rust resistance gene Sr35 in diploid and hexaploid wheat
USDA-ARS?s Scientific Manuscript database
Puccinia graminis f. sp. tritici is the causal agent of stem rust of wheat. A new race designated TTKSK (also known as Ug99) has recently spread through East Africa, Yemen and on to Iran. TTKSK and its variants (TTKST and TTTSK) are virulent to most of the stem rust resistance genes currently deploy...
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Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R; Mahajan, Anubha; Asimit, Jennifer L; Ferreira, Teresa; Locke, Adam E; Robertson, Neil R; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E; Tam, Claudia H T; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I; Blangero, John; Burtt, Noél P; Duggirala, Ravindranath; Florez, Jose C; Hanis, Craig L; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C N; Ma, Ronald C W; Froguel, Philippe; Wilson, James G; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S; Chambers, John C; Saleheen, Danish; Kadowaki, Takashi; Tai, E Shyong; Mohlke, Karen L; Cox, Nancy J; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I; Morris, Andrew P
2016-05-15
To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. © The Author 2016. Published by Oxford University Press.
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Glubb, Dylan M.; Johnatty, Sharon E.; Quinn, Michael C.J.; O’Mara, Tracy A.; Tyrer, Jonathan P.; Gao, Bo; Fasching, Peter A.; Beckmann, Matthias W.; Lambrechts, Diether; Vergote, Ignace; Velez Edwards, Digna R.; Beeghly-Fadiel, Alicia; Benitez, Javier; Garcia, Maria J.; Goodman, Marc T.; Thompson, Pamela J.; Dörk, Thilo; Dürst, Matthias; Modungo, Francesmary; Moysich, Kirsten; Heitz, Florian; du Bois, Andreas; Pfisterer, Jacobus; Hillemanns, Peter; Karlan, Beth Y.; Lester, Jenny; Goode, Ellen L.; Cunningham, Julie M.; Winham, Stacey J.; Larson, Melissa C.; McCauley, Bryan M.; Kjær, Susanne Krüger; Jensen, Allan; Schildkraut, Joellen M.; Berchuck, Andrew; Cramer, Daniel W.; Terry, Kathryn L.; Salvesen, Helga B.; Bjorge, Line; Webb, Penny M.; Grant, Peter; Pejovic, Tanja; Moffitt, Melissa; Hogdall, Claus K.; Hogdall, Estrid; Paul, James; Glasspool, Rosalind; Bernardini, Marcus; Tone, Alicia; Huntsman, David; Woo, Michelle; Group, AOCS; deFazio, Anna; Kennedy, Catherine J.; Pharoah, Paul D.P.; MacGregor, Stuart; Chenevix-Trench, Georgia
2017-01-01
We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that MEF2D and ZNF100 are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the ZNF100 promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced MEF2D promoter activity and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, MEF2D and ZNF100 expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates at the 1q22 and 19p12 loci, as well as other regional variants, were nominally associated with patient outcome; however, no associations reached our threshold for statistical significance (p<1×10-5). Larger patient numbers will be needed to convincingly identify any true associations at these loci. PMID:29029385
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Heteropolymerization of S, I, and Z α1-antitrypsin and liver cirrhosis
Mahadeva, Ravi; Chang, Wun-Shaing W.; Dafforn, Timothy R.; Oakley, Diana J.; Foreman, Richard C.; Calvin, Jacqueline; Wight, Derek G.D.; Lomas, David A.
1999-01-01
The association between Z α1-antitrypsin deficiency and juvenile cirrhosis is well-recognized, and there is now convincing evidence that the hepatic inclusions are the result of entangled polymers of mutant Z α1-antitrypsin. Four percent of the northern European Caucasian population are heterozygotes for the Z variant, but even more common is S α1-antitrypsin, which is found in up to 28% of southern Europeans. The S variant is known to have an increased susceptibility to polymerization, although this is marginal compared with the more conformationally unstable Z variant. There has been speculation that the two may interact to produce cirrhosis, but this has never been demonstrated experimentally. This hypothesis was raised again by the observation reported here of a mixed heterozygote for Z α1-antitrypsin and another conformationally unstable variant (I α1-antitrypsin; 39Arg→Cys) identified in a 34-year-old man with cirrhosis related to α1-antitrypsin deficiency. The conformational stability of the I variant has been characterized, and we have used fluorescence resonance energy transfer to demonstrate the formation of heteropolymers between S and Z α1-antitrypsin. Taken together, these results indicate that not only may mixed variants form heteropolymers, but that this can causally lead to the development of cirrhosis. PMID:10194472
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Analysis of CHRNA7 rare variants in autism spectrum disorder susceptibility.
Bacchelli, Elena; Battaglia, Agatino; Cameli, Cinzia; Lomartire, Silvia; Tancredi, Raffaella; Thomson, Susanne; Sutcliffe, James S; Maestrini, Elena
2015-04-01
Chromosome 15q13.3 recurrent microdeletions are causally associated with a wide range of phenotypes, including autism spectrum disorder (ASD), seizures, intellectual disability, and other psychiatric conditions. Whether the reciprocal microduplication is pathogenic is less certain. CHRNA7, encoding for the alpha7 subunit of the neuronal nicotinic acetylcholine receptor, is considered the likely culprit gene in mediating neurological phenotypes in 15q13.3 deletion cases. To assess if CHRNA7 rare variants confer risk to ASD, we performed copy number variant analysis and Sanger sequencing of the CHRNA7 coding sequence in a sample of 135 ASD cases. Sequence variation in this gene remains largely unexplored, given the existence of a fusion gene, CHRFAM7A, which includes a nearly identical partial duplication of CHRNA7. Hence, attempts to sequence coding exons must distinguish between CHRNA7 and CHRFAM7A, making next-generation sequencing approaches unreliable for this purpose. A CHRNA7 microduplication was detected in a patient with autism and moderate cognitive impairment; while no rare damaging variants were identified in the coding region, we detected rare variants in the promoter region, previously described to functionally reduce transcription. This study represents the first sequence variant analysis of CHRNA7 in a sample of idiopathic autism. © 2015 Wiley Periodicals, Inc.
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Caputo, Sandrine; Benboudjema, Louisa; Sinilnikova, Olga; Rouleau, Etienne; Béroud, Christophe; Lidereau, Rosette
2012-01-01
BRCA1 and BRCA2 are the two main genes responsible for predisposition to breast and ovarian cancers, as a result of protein-inactivating monoallelic mutations. It remains to be established whether many of the variants identified in these two genes, so-called unclassified/unknown variants (UVs), contribute to the disease phenotype or are simply neutral variants (or polymorphisms). Given the clinical importance of establishing their status, a nationwide effort to annotate these UVs was launched by laboratories belonging to the French GGC consortium (Groupe Génétique et Cancer), leading to the creation of the UMD-BRCA1/BRCA2 databases (http://www.umd.be/BRCA1/ and http://www.umd.be/BRCA2/). These databases have been endorsed by the French National Cancer Institute (INCa) and are designed to collect all variants detected in France, whether causal, neutral or UV. They differ from other BRCA databases in that they contain co-occurrence data for all variants. Using these data, the GGC French consortium has been able to classify certain UVs also contained in other databases. In this article, we report some novel UVs not contained in the BIC database and explore their impact in cancer predisposition based on a structural approach.
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regSNPs: a strategy for prioritizing regulatory single nucleotide substitutions
Teng, Mingxiang; Ichikawa, Shoji; Padgett, Leah R.; Wang, Yadong; Mort, Matthew; Cooper, David N.; Koller, Daniel L.; Foroud, Tatiana; Edenberg, Howard J.; Econs, Michael J.; Liu, Yunlong
2012-01-01
Motivation: One of the fundamental questions in genetics study is to identify functional DNA variants that are responsible to a disease or phenotype of interest. Results from large-scale genetics studies, such as genome-wide association studies (GWAS), and the availability of high-throughput sequencing technologies provide opportunities in identifying causal variants. Despite the technical advances, informatics methodologies need to be developed to prioritize thousands of variants for potential causative effects. Results: We present regSNPs, an informatics strategy that integrates several established bioinformatics tools, for prioritizing regulatory SNPs, i.e. the SNPs in the promoter regions that potentially affect phenotype through changing transcription of downstream genes. Comparing to existing tools, regSNPs has two distinct features. It considers degenerative features of binding motifs by calculating the differences on the binding affinity caused by the candidate variants and integrates potential phenotypic effects of various transcription factors. When tested by using the disease-causing variants documented in the Human Gene Mutation Database, regSNPs showed mixed performance on various diseases. regSNPs predicted three SNPs that can potentially affect bone density in a region detected in an earlier linkage study. Potential effects of one of the variants were validated using luciferase reporter assay. Contact: yunliu@iupui.edu Supplementary information: Supplementary data are available at Bioinformatics online PMID:22611130
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Taylor, Amy E; Martin, Richard M; Geybels, Milan S; Stanford, Janet L; Shui, Irene; Eeles, Rosalind; Easton, Doug; Kote-Jarai, Zsofia; Amin Al Olama, Ali; Benlloch, Sara; Muir, Kenneth; Giles, Graham G; Wiklund, Fredrik; Gronberg, Henrik; Haiman, Christopher A; Schleutker, Johanna; Nordestgaard, Børge G; Travis, Ruth C; Neal, David; Pashayan, Nora; Khaw, Kay-Tee; Blot, William; Thibodeau, Stephen; Maier, Christiane; Kibel, Adam S; Cybulski, Cezary; Cannon-Albright, Lisa; Brenner, Hermann; Park, Jong; Kaneva, Radka; Batra, Jyotsna; Teixeira, Manuel R; Pandha, Hardev; Donovan, Jenny; Munafò, Marcus R
2017-01-15
Coffee consumption has been shown in some studies to be associated with lower risk of prostate cancer. However, it is unclear if this association is causal or due to confounding or reverse causality. We conducted a Mendelian randomisation analysis to investigate the causal effects of coffee consumption on prostate cancer risk and progression. We used two genetic variants robustly associated with caffeine intake (rs4410790 and rs2472297) as proxies for coffee consumption in a sample of 46,687 men of European ancestry from 25 studies in the PRACTICAL consortium. Associations between genetic variants and prostate cancer case status, stage and grade were assessed by logistic regression and with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression. There was no clear evidence that a genetic risk score combining rs4410790 and rs2472297 was associated with prostate cancer risk (OR per additional coffee increasing allele: 1.01, 95% CI: 0.98,1.03) or having high-grade compared to low-grade disease (OR: 1.01, 95% CI: 0.97,1.04). There was some evidence that the genetic risk score was associated with higher odds of having nonlocalised compared to localised stage disease (OR: 1.03, 95% CI: 1.01, 1.06). Amongst men with prostate cancer, there was no clear association between the genetic risk score and all-cause mortality (HR: 1.00, 95% CI: 0.97,1.04) or prostate cancer-specific mortality (HR: 1.03, 95% CI: 0.98,1.08). These results, which should have less bias from confounding than observational estimates, are not consistent with a substantial effect of coffee consumption on reducing prostate cancer incidence or progression. © 2016 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.
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Non-Gaussian Methods for Causal Structure Learning.
Shimizu, Shohei
2018-05-22
Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.
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Liao, Hsiao-Mei; Liu, Hebing; Lei, Heiyan; Li, Bingjie; Chin, Pei-Ju; Tsai, Shien; Bhatia, Kishor; Gutierrez, Marina; Epelman, Sidnei; Biggar, Robert J; Nkrumah, Francis; Neequaye, Janet; Ogwang, Martin D; Reynolds, Steven J; Lo, Shyh-Ching; Mbulaiteye, Sam M
2018-06-02
Epstein-Barr virus (EBV) is linked to several cancers, including endemic Burkitt lymphoma (eBL), but causal variants are unknown. We recently reported novel sequence variants in the LMP-1 gene and promoter in EBV genomes sequenced from 13 of 14 BL biopsies. Alignments of the novel sequence variants for 114 published EBV genomes, including 27 from BL cases, revealed four LMP-1 variant patterns, designated A to D. Pattern A variant was found in 48% of BL EBV genomes. Here, we used PCR-Sanger sequencing to evaluate 50 additional BL biopsies from Ghana, Brazil, and Argentina, and peripheral blood samples from 113 eBL cases and 115 controls in Uganda. Pattern A was found in 60.9% of 64 BL biopsies evaluated. Compared to PCR-negative subjects in Uganda, detection of Pattern A in peripheral blood was associated with eBL case status (odds ratio [OR] 31.7, 95% confidence interval: 6.8⁻149), controlling for relevant confounders. Variant Pattern A and Pattern D were associated with eBL case status, but with lower ORs (9.7 and 13.6, respectively). Our results support the hypothesis that EBV LMP-1 Pattern A may be associated with eBL, but it is not the sole associated variant. Further research is needed to replicate and elucidate our findings.
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Gonzaga-Jauregui, Claudia; Harel, Tamar; Gambin, Tomasz; Kousi, Maria; Griffin, Laurie B.; Francescatto, Ludmila; Ozes, Burcak; Karaca, Ender; Jhangiani, Shalini; Bainbridge, Matthew N.; Lawson, Kim S.; Pehlivan, Davut; Okamoto, Yuji; Withers, Marjorie; Mancias, Pedro; Slavotinek, Anne; Reitnauer, Pamela J; Goksungur, Meryem T.; Shy, Michael; Crawford, Thomas O.; Koenig, Michel; Willer, Jason; Flores, Brittany N.; Pediaditrakis, Igor; Us, Onder; Wiszniewski, Wojciech; Parman, Yesim; Antonellis, Anthony; Muzny, Donna M.; Katsanis, Nicholas; Battaloglu, Esra; Boerwinkle, Eric; Gibbs, Richard A.; Lupski, James R.
2015-01-01
Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous distal symmetric polyneuropathy. Whole-exome sequencing (WES) of 40 individuals from 37 unrelated families with CMT-like peripheral neuropathy refractory to molecular diagnosis identified apparent causal mutations in ~45% (17/37) of families. Three candidate disease genes are proposed, supported by a combination of genetic and in vivo studies. Aggregate analysis of mutation data revealed a significantly increased number of rare variants across 58 neuropathy associated genes in subjects versus controls; confirmed in a second ethnically discrete neuropathy cohort, suggesting mutation burden potentially contributes to phenotypic variability. Neuropathy genes shown to have highly penetrant Mendelizing variants (HMPVs) and implicated by burden in families were shown to interact genetically in a zebrafish assay exacerbating the phenotype established by the suppression of single genes. Our findings suggest that the combinatorial effect of rare variants contributes to disease burden and variable expressivity. PMID:26257172
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Meta-analysis of gene-level associations for rare variants based on single-variant statistics.
Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu
2013-08-08
Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.
Astuti, Galuh D N; van den Born, L Ingeborgh; Khan, M Imran; Hamel, Christian P; Bocquet, Béatrice; Manes, Gaël; Quinodoz, Mathieu; Ali, Manir; Toomes, Carmel; McKibbin, Martin; El-Asrag, Mohammed E; Haer-Wigman, Lonneke; Inglehearn, Chris F; Black, Graeme C M; Hoyng, Carel B; Cremers, Frans P M; Roosing, Susanne
2018-01-10
Inherited retinal diseases (IRDs) display an enormous genetic heterogeneity. Whole exome sequencing (WES) recently identified genes that were mutated in a small proportion of IRD cases. Consequently, finding a second case or family carrying pathogenic variants in the same candidate gene often is challenging. In this study, we searched for novel candidate IRD gene-associated variants in isolated IRD families, assessed their causality, and searched for novel genotype-phenotype correlations. Whole exome sequencing was performed in 11 probands affected with IRDs. Homozygosity mapping data was available for five cases. Variants with minor allele frequencies ≤ 0.5% in public databases were selected as candidate disease-causing variants. These variants were ranked based on their: (a) presence in a gene that was previously implicated in IRD; (b) minor allele frequency in the Exome Aggregation Consortium database (ExAC); (c) in silico pathogenicity assessment using the combined annotation dependent depletion (CADD) score; and (d) interaction of the corresponding protein with known IRD-associated proteins. Twelve unique variants were found in 11 different genes in 11 IRD probands. Novel autosomal recessive and dominant inheritance patterns were found for variants in Small Nuclear Ribonucleoprotein U5 Subunit 200 ( SNRNP200 ) and Zinc Finger Protein 513 ( ZNF513 ), respectively. Using our pathogenicity assessment, a variant in DEAH-Box Helicase 32 ( DHX32 ) was the top ranked novel candidate gene to be associated with IRDs, followed by eight medium and lower ranked candidate genes. The identification of candidate disease-associated sequence variants in 11 single families underscores the notion that the previously identified IRD-associated genes collectively carry > 90% of the defects implicated in IRDs. To identify multiple patients or families with variants in the same gene and thereby provide extra proof for pathogenicity, worldwide data sharing is needed.
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Measuring missing heritability: Inferring the contribution of common variants
Golan, David; Lander, Eric S.; Rosset, Saharon
2014-01-01
Genome-wide association studies (GWASs), also called common variant association studies (CVASs), have uncovered thousands of genetic variants associated with hundreds of diseases. However, the variants that reach statistical significance typically explain only a small fraction of the heritability. One explanation for the “missing heritability” is that there are many additional disease-associated common variants whose effects are too small to detect with current sample sizes. It therefore is useful to have methods to quantify the heritability due to common variation, without having to identify all causal variants. Recent studies applied restricted maximum likelihood (REML) estimation to case–control studies for diseases. Here, we show that REML considerably underestimates the fraction of heritability due to common variation in this setting. The degree of underestimation increases with the rarity of disease, the heritability of the disease, and the size of the sample. Instead, we develop a general framework for heritability estimation, called phenotype correlation–genotype correlation (PCGC) regression, which generalizes the well-known Haseman–Elston regression method. We show that PCGC regression yields unbiased estimates. Applying PCGC regression to six diseases, we estimate the proportion of the phenotypic variance due to common variants to range from 25% to 56% and the proportion of heritability due to common variants from 41% to 68% (mean 60%). These results suggest that common variants may explain at least half the heritability for many diseases. PCGC regression also is readily applicable to other settings, including analyzing extreme-phenotype studies and adjusting for covariates such as sex, age, and population structure. PMID:25422463
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GWASeq: targeted re-sequencing follow up to GWAS.
Salomon, Matthew P; Li, Wai Lok Sibon; Edlund, Christopher K; Morrison, John; Fortini, Barbara K; Win, Aung Ko; Conti, David V; Thomas, Duncan C; Duggan, David; Buchanan, Daniel D; Jenkins, Mark A; Hopper, John L; Gallinger, Steven; Le Marchand, Loïc; Newcomb, Polly A; Casey, Graham; Marjoram, Paul
2016-03-03
For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS. We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer. Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.
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Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E; Aberg, Karolina A; Kumar, Gaurav; Nerella, Sri; Xie, Linying; Collins, Ann L; Crowley, James J; Quakenbush, Corey R; Hillard, Christopher E; Gao, Guimin; Shabalin, Andrey A; Peterson, Roseann E; Copeland, William E; Silberg, Judy L; Maes, Hermine; Sullivan, Patrick F; Costello, Elizabeth J; van den Oord, Edwin J
2016-05-01
Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\\CHRNA3\\CHRNB4, CHRNB3\\CHRNA6 and EGLN2\\CYP2A6. Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations. We employed targeted capture of the CHRNA5\\CHRNA3\\CHRNB4, CHRNB3\\CHRNA6, and EGLN2\\CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations. In total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3\\CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6. Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2. We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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McClay, Joseph L.; Adkins, Daniel E.; Aberg, Karolina A.; Kumar, Gaurav; Nerella, Sri; Xie, Linying; Collins, Ann L.; Crowley, James J.; Quakenbush, Corey R.; Hillard, Christopher E.; Gao, Guimin; Shabalin, Andrey A.; Peterson, Roseann E.; Copeland, William E.; Silberg, Judy L.; Maes, Hermine; Sullivan, Patrick F.; Costello, Elizabeth J.; van den Oord, Edwin J.
2016-01-01
Abstract Introduction: Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\\CHRNA3\\CHRNB4 , CHRNB3\\CHRNA6 and EGLN2\\CYP2A6 . Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations. Methods: We employed targeted capture of the CHRNA5\\CHRNA3\\CHRNB4 , CHRNB3\\CHRNA6 , and EGLN2\\CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations. Results: In total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3\\CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6 . Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2 . Conclusions: We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up. PMID:26283763
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Hibbeln, Joseph R; SanGiovanni, John Paul; Golding, Jean; Emmett, Pauline M; Northstone, Kate; Davis, John M; Schuckit, Marc; Heron, Jon
2017-11-01
Reducing meat consumption is often advised; however, inadvertent nutritional deficiencies during pregnancy may result in residual neurodevelopmental harms to offspring. This study assessed possible effects of maternal diets in pregnancy on adverse substance use among adolescent offspring. Pregnant women and their 13-year-old offspring taking part in a prospective birth cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC), provided Food Frequency Questionnaire data from which dietary patterns were derived using principal components analysis. Multivariable logistic regression models including potential confounders evaluated adverse alcohol, cannabis, and tobacco use of the children at 15 years of age. Lower maternal meat consumption was associated with greater problematic substance use among 15-year-old offspring in dose-response patterns. Comparing never to daily meat consumption after adjustment, risks were greater for all categories of problem substance use: alcohol, odds ratio OR = 1.75, 95% CI = (1.23, 2.56), p < 0.001; tobacco use OR = 1.85, 95% CI = (1.28, 2.63), p < 0.001; and cannabis OR = 2.70, 95% CI = (1.89, 4.00), p < 0.001. Given the likelihood of residual confounding, potential causality was evaluated using stratification for maternal allelic variants that impact biological activity of cobalamin (vitamin B12) and iron. Lower meat consumption disproportionally increased the risks of offspring substance misuse among mothers with optimally functional (homozygous) variants (rs1801198) of the gene transcobalamin 2 gene (TCN2) which encodes the vitamin B12 transport protein transcobalamin 2 implicating a causal role for cobalamin deficits. Functional maternal variants in iron metabolism were unrelated to the adverse substance use. Risks potentially attributable to cobalamin deficits during pregnancy include adverse adolescent alcohol, cannabis, and tobacco use (14, 37, and 23, respectively). Lower prenatal meat consumption was associated with increased risks of adolescent substance misuse. Interactions between TCN2 variant status and meat intake implicate cobalamin deficiencies. Copyright © 2017 by the Research Society on Alcoholism.
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The HABP2 G534E Variant Is an Unlikely Cause of Familial Nonmedullary Thyroid Cancer
Sahasrabudhe, Ruta; Stultz, Jacob; Williamson, John; Lott, Paul; Estrada, Ana; Bohorquez, Mabel; Palles, Claire; Polanco-Echeverry, Guadalupe; Jaeger, Emma; Martin, Lynn; Echeverry, Maria Magdalena; Tomlinson, Ian
2016-01-01
Context: A recent study reported the nonsynonymous G534E (rs7080536, allele A) variant in the HABP2 gene as causal in familial nonmedullary thyroid cancer (NMTC). Objective: The objective of this study was to evaluate the causality of HABP2 G534E in the TCUKIN study, a multicenter population-based study of NMTC cases from the British Isles. Design and Setting: A case-control analysis of rs7080536 genotypes was performed using 2105 TCUKIN cases and 5172 UK controls. Participants: Cases comprised 2105 NMTC cases. Patient subgroups with papillary (n = 1056), follicular (n = 691), and Hürthle cell (n = 86) thyroid cancer cases were studied separately. Controls comprised 5172 individuals from the 1958 Birth Cohort and the National Blood Donor Service study. The controls had previously been genotyped using genome-wide single nucleotide polymorphism arrays by the Wellcome Trust Case Control Consortium study. Outcome Measures: Association between HABP2 G534E (rs7080536A) and NMTC risk was evaluated using logistic regression. Results: The frequency of the HABP2 G534E was 4.2% in cases and 4.6% in controls. We did not detect an association between this variant and NMTC risk (odds ratio [OR] = 0.896; 95% confidence interval, 0.746–1.071; P = .233). We also failed to detect an association between the HABP2 G534E and cases with papillary (1056 cases; G534E frequency = 3.5%; OR = 0.74; P = .017), follicular (691 cases; G534E frequency = 4.7%; OR = 1.00; P = 1.000), or Hürthle cell (86 cases; G534E frequency = 6.3%; OR = 1.40; P = .279) histology. Conclusions: We found that HABP2 G534E is a low-to-moderate frequency variant in the British Isles and failed to detect an association with NMTC risk, independent of histological type. Hence, our study does not implicate HABP2 G534E or a correlated polymorphism in familial NMTC, and additional data are required before using this variant in NMTC risk assessment. PMID:26691890
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The HABP2 G534E variant is an unlikely cause of familial non-medullary thyroid cancer.
Sahasrabudhe, Ruta; Stultz, Jacob; Williamson, John; Lott, Paul; Estrada, Ana; Bohorquez, Mabel; Palles, Claire; Polanco-Echeverry, Guadalupe; Jaeger, Emma; Martin, Lynn; Magdalena Echeverry, Maria; Tomlinson, Ian; Carvajal-Carmona, Luis G
2016-03-01
A recent study reported the non-synonymous G534E (rs7080536, allele A) variant in the HABP2 gene as causal in familial non-medullary thyroid cancer (NMTC). The objective of this study was to evaluate the causality of HABP2 G534E in the TCUKIN study, a multi-center population based study of NMTC cases from the British Isles. A case-control analysis of rs7080536 genotypes was performed using 2,105 TCUKIN cases and 5,172 UK controls. Cases comprised 2,105 NMTC cases. Patients sub-groups with papillary (N=1,056), follicular (N=691) and Hurthle cell (N=86) TC cases were studied separately. Controls comprised 5,172 individuals from the 1958 Birth Cohort (58C) and the National Blood Donor Service (NBS) study. The controls had previously been genotyped using genome-wide SNP arrays by the Wellcome Trust Case Control Consortium study. Measures: Association between HABP2 G534E (rs7080536A) and NMTC risk was evaluated using logistic regression. The frequency of HABP2 G534E was 4.2% in cases and 4.6% in controls. We did not detect an association between this variant and NMTC risk (OR=0.896, 95% CI: 0.746-1.071, P=0.233). We also failed to detect an association between HABP2 G534E and cases with papillary (1056 cases, G534E frequency= 3.5%, OR=0.74, P=0.017), follicular (691 cases, G534E frequency= 4.7%, OR=1.00, P=1.000) or Hurthle cell (86 cases, G534E frequency= 6.3%, OR=1.40, P=0.279) histology. We found that HABP2 G534E is a low-to-moderate frequency variant in the British Isles and failed to detect an association with NMTC risk, independent of histological type. Hence, our study does not implicate HABP2 G534E or a correlated polymorphism in familial NMTC and additional data are required before using this variant in NMTC risk assessment.
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Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Alonso, M. Rosario; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Benitez, Javier; Bogdanova, Natalia V.; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M.; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F.; Fasching, Peter A.; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G.; Goldberg, Mark S.; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A.; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L.; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L.; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C.; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H.; Tessier, Daniel C.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M.; Vincent, Daniel; Winqvist, Robert; Wu, Anna H.; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D. P.; Hall, Per; Edwards, Stacey L.; Simard, Jacques; French, Juliet D.; Chenevix-Trench, Georgia; Dunning, Alison M.
2016-01-01
Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90–0.94; P = 8.96 × 10−15)) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10−09, r2 = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10−11, r2 = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus. PMID:27600471
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Differential control of ageing and lifespan by isoforms and splice variants across the mTOR network.
Razquin Navas, Patricia; Thedieck, Kathrin
2017-07-15
Ageing can be defined as the gradual deterioration of physiological functions, increasing the incidence of age-related disorders and the probability of death. Therefore, the term ageing not only reflects the lifespan of an organism but also refers to progressive functional impairment and disease. The nutrient-sensing kinase mTOR (mammalian target of rapamycin) is a major determinant of ageing. mTOR promotes cell growth and controls central metabolic pathways including protein biosynthesis, autophagy and glucose and lipid homoeostasis. The concept that mTOR has a crucial role in ageing is supported by numerous reports on the lifespan-prolonging effects of the mTOR inhibitor rapamycin in invertebrate and vertebrate model organisms. Dietary restriction increases lifespan and delays ageing phenotypes as well and mTOR has been assigned a major role in this process. This may suggest a causal relationship between the lifespan of an organism and its metabolic phenotype. More than 25 years after mTOR's discovery, a wealth of metabolic and ageing-related effects have been reported. In this review, we cover the current view on the contribution of the different elements of the mTOR signalling network to lifespan and age-related metabolic impairment. We specifically focus on distinct roles of isoforms and splice variants across the mTOR network. The comprehensive analysis of mouse knockout studies targeting these variants does not support a tight correlation between lifespan prolongation and improved metabolic phenotypes and questions the strict causal relationship between them. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.
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2012-01-01
Background In observational epidemiological studies type 2 diabetes (T2D) and both low and high plasma concentrations of fasting glucose have been found to be associated with lower cognitive performance. These associations could be explained by confounding. Methods In this study we looked at the association between genetic variants, known to be robustly associated with fasting glucose and T2D risk, in the mother and her offspring to determine whether there is likely to be a causal link between early life exposure to glucose and child’s intelligence quotient (IQ) scores in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. We generated a fasting glucose (FGGRS) and a T2D (T2DGRS) genetic risk score and used them in a Mendelian randomization approach. Results We found a strong correlation between the FGGRS and fasting glucose plasma measurements that were available for a subset of children, but no association of either the maternal or the offspring FGGRS with child’s IQ was observed. In contrast, the maternal T2DGRS was positively associated with offspring IQ. Conclusions Maternal and offspring genetic variants which are associated with glucose levels are not associated with offspring IQ, suggesting that there is unlikely to be a causal link between glucose exposure in utero and IQ in childhood. Further exploration in even larger cohorts is required to exclude the possibility that our null findings were due to a lack of statistical power. PMID:23013243
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Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Alonso, M Rosario; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Benitez, Javier; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G; Goldberg, Mark S; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H; Tessier, Daniel C; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M; Vincent, Daniel; Winqvist, Robert; Wu, Anna H; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D P; Hall, Per; Edwards, Stacey L; Simard, Jacques; French, Juliet D; Chenevix-Trench, Georgia; Dunning, Alison M
2016-09-07
Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.
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Welderufael, B G; Løvendahl, Peter; de Koning, Dirk-Jan; Janss, Lucas L G; Fikse, W F
2018-01-01
Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to - but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t -test and a genome-wide significance level of P -value < 10 -4 was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to - or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2 ) and genes involved in macrophage recruitment and regulation of inflammations ( PDGFD and PTX3 ) were suggested as possible causal genes for susceptibility to - and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to - and recoverability from mastitis.
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USDA-ARS?s Scientific Manuscript database
A new race of Puccinia graminis f. sp. tritici, the causal pathogen of stem rust of wheat, designated TTKSK (also known as Ug99) and its variants are virulent to most of the stem rust resistance genes currently deployed in wheat cultivars worldwide. Therefore, identification, mapping and deployment ...
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van der Harst, Pim; Verweij, Niek
2018-02-02
Coronary artery disease (CAD) is a complex phenotype driven by genetic and environmental factors. Ninety-seven genetic risk loci have been identified to date, but the identification of additional susceptibility loci might be important to enhance our understanding of the genetic architecture of CAD. To expand the number of genome-wide significant loci, catalog functional insights, and enhance our understanding of the genetic architecture of CAD. We performed a genome-wide association study in 34 541 CAD cases and 261 984 controls of UK Biobank resource followed by replication in 88 192 cases and 162 544 controls from CARDIoGRAMplusC4D. We identified 75 loci that replicated and were genome-wide significant ( P <5×10 -8 ) in meta-analysis, 13 of which had not been reported previously. Next, to further identify novel loci, we identified all promising ( P <0.0001) loci in the CARDIoGRAMplusC4D data and performed reciprocal replication and meta-analyses with UK Biobank. This led to the identification of 21 additional novel loci reaching genome-wide significance ( P <5×10 -8 ) in meta-analysis. Finally, we performed a genome-wide meta-analysis of all available data revealing 30 additional novel loci ( P <5×10 -8 ) without further replication. The increase in sample size by UK Biobank raised the number of reconstituted gene sets from 4.2% to 13.9% of all gene sets to be involved in CAD. For the 64 novel loci, 155 candidate causal genes were prioritized, many without an obvious connection to CAD. Fine mapping of the 161 CAD loci generated lists of credible sets of single causal variants and genes for functional follow-up. Genetic risk variants of CAD were linked to development of atrial fibrillation, heart failure, and death. We identified 64 novel genetic risk loci for CAD and performed fine mapping of all 161 risk loci to obtain a credible set of causal variants. The large expansion of reconstituted gene sets argues in favor of an expanded omnigenic model view on the genetic architecture of CAD. © 2017 The Authors.
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Auer, Paul L.; Johnsen, Jill M.; Johnson, Andrew D.; Logsdon, Benjamin A.; Lange, Leslie A.; Nalls, Michael A.; Zhang, Guosheng; Franceschini, Nora; Fox, Keolu; Lange, Ethan M.; Rich, Stephen S.; O’Donnell, Christopher J.; Jackson, Rebecca D.; Wallace, Robert B.; Chen, Zhao; Graubert, Timothy A.; Wilson, James G.; Tang, Hua; Lettre, Guillaume; Reiner, Alex P.; Ganesh, Santhi K.; Li, Yun
2012-01-01
Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombpoietin receptor gene (p = 1.5 × 10−11). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10−13). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325∗) was associated with lower platelet count; and several missense variants at the α-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies. PMID:23103231
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Lu, Yingchang; Justice, Anne E.; Mudgal, Poorva; Liu, Ching-Ti; Young, Kristin; Feitosa, Mary F.; Rand, Kristin; Dimitrov, Latchezar; Duan, Qing; Guo, Xiuqing; Lange, Leslie A.; Nalls, Michael A.; Okut, Hayrettin; Tayo, Bamidele O.; Vedantam, Sailaja; Bradfield, Jonathan P.; Chen, Guanjie; Chesi, Alessandra; Irvin, Marguerite R.; Padhukasahasram, Badri; Zheng, Wei; Allison, Matthew A.; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Blot, William J.; Bottinger, Erwin P.; Carpten, John; Chanock, Stephen J.; Chen, Yii-Der Ida; Conti, David V.; Cooper, Richard S.; Fornage, Myriam; Freedman, Barry I.; Garcia, Melissa; Goodman, Phyllis J.; Hsu, Yu-Han H.; Hu, Jennifer; Huff, Chad D.; Ingles, Sue A.; John, Esther M.; Kittles, Rick; Klein, Eric; Li, Jin; McKnight, Barbara; Nayak, Uma; Nemesure, Barbara; Olshan, Andrew; Salako, Babatunde; Sanderson, Maureen; Shao, Yaming; Siscovick, David S.; Stanford, Janet L.; Strom, Sara S.; Witte, John S.; Yao, Jie; Zhu, Xiaofeng; Ziegler, Regina G.; Zonderman, Alan B.; Ambs, Stefan; Cushman, Mary; Faul, Jessica D.; Hakonarson, Hakon; Levin, Albert M.; Nathanson, Katherine L.; Weir, David R.; Zhi, Degui; Arnett, Donna K.; Kardia, Sharon L. R.; Oloapde, Olufunmilayo I.; Rao, D. C.; Williams, L. Keoki; Becker, Diane M.; Borecki, Ingrid B.; Evans, Michele K.; Harris, Tamara B.; Hirschhorn, Joel N.; Psaty, Bruce M.; Wilson, James G.; Bowden, Donald W.; Cupples, L. Adrienne; Haiman, Christopher A.; Loos, Ruth J. F.; North, Kari E.
2017-01-01
Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations. PMID:28430825
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Causal discovery and inference: concepts and recent methodological advances.
Spirtes, Peter; Zhang, Kun
This paper aims to give a broad coverage of central concepts and principles involved in automated causal inference and emerging approaches to causal discovery from i.i.d data and from time series. After reviewing concepts including manipulations, causal models, sample predictive modeling, causal predictive modeling, and structural equation models, we present the constraint-based approach to causal discovery, which relies on the conditional independence relationships in the data, and discuss the assumptions underlying its validity. We then focus on causal discovery based on structural equations models, in which a key issue is the identifiability of the causal structure implied by appropriately defined structural equation models: in the two-variable case, under what conditions (and why) is the causal direction between the two variables identifiable? We show that the independence between the error term and causes, together with appropriate structural constraints on the structural equation, makes it possible. Next, we report some recent advances in causal discovery from time series. Assuming that the causal relations are linear with nonGaussian noise, we mention two problems which are traditionally difficult to solve, namely causal discovery from subsampled data and that in the presence of confounding time series. Finally, we list a number of open questions in the field of causal discovery and inference.
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Dorshorst, Ben; Molin, Anna-Maja; Rubin, Carl-Johan; Johansson, Anna M.; Strömstedt, Lina; Pham, Manh-Hung; Chen, Chih-Feng; Hallböök, Finn; Ashwell, Chris; Andersson, Leif
2011-01-01
Dermal hyperpigmentation or Fibromelanosis (FM) is one of the few examples of skin pigmentation phenotypes in the chicken, where most other pigmentation variants influence feather color and patterning. The Silkie chicken is the most widespread and well-studied breed displaying this phenotype. The presence of the dominant FM allele results in extensive pigmentation of the dermal layer of skin and the majority of internal connective tissue. Here we identify the causal mutation of FM as an inverted duplication and junction of two genomic regions separated by more than 400 kb in wild-type individuals. One of these duplicated regions contains endothelin 3 (EDN3), a gene with a known role in promoting melanoblast proliferation. We show that EDN3 expression is increased in the developing Silkie embryo during the time in which melanoblasts are migrating, and elevated levels of expression are maintained in the adult skin tissue. We have examined four different chicken breeds from both Asia and Europe displaying dermal hyperpigmentation and conclude that the same structural variant underlies this phenotype in all chicken breeds. This complex genomic rearrangement causing a specific monogenic trait in the chicken illustrates how novel mutations with major phenotypic effects have been reused during breed formation in domestic animals. PMID:22216010
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Hypervirulence and hypermucoviscosity: Two different but complementary Klebsiella spp. phenotypes?
Catalán-Nájera, Juan Carlos; Garza-Ramos, Ulises; Barrios-Camacho, Humberto
2017-01-01
ABSTRACT Since the hypermucoviscous variants of Klebsiella pneumoniae were first reported, many cases of primary liver abscesses and other invasive infections caused by this pathogen have been described worldwide. Hypermucoviscosity is a phenotypic feature characterized by the formation of a viscous filament ≥5 mm when a bacterial colony is stretched by a bacteriological loop; this is the so-called positive string test. Hypermucoviscosity appears to be associated with this unusual and aggressive type of infection, and therefore, the causal strains are considered hypervirulent. Since these first reports, the terms hypermucoviscosity and hypervirulence have often been used synonymously. However, new evidence has suggested that hypermucoviscosity and hypervirulence are 2 different phenotypes that should not be used synonymously. Moreover, it is important to establish that a negative string test is insufficient in determining whether a strain is or is not hypervirulent. On the other hand, hypervirulence- and hypermucoviscosity-associated genes must be identified, considering that these phenotypes correspond to 2 different phenomena, regardless of whether they can act in synergy under certain circumstances. Therefore, it is essential to quickly identify the genetic determinants behind the hypervirulent phenotype to develop effective methodologies that can diagnose in a prompt and effective way these hypervirulent variants of K. pneumoniae. PMID:28402698
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Fry, Andrew E.; Ghansa, Anita; Small, Kerrin S.; Palma, Alejandro; Auburn, Sarah; Diakite, Mahamadou; Green, Angela; Campino, Susana; Teo, Yik Y.; Clark, Taane G.; Jeffreys, Anna E.; Wilson, Jonathan; Jallow, Muminatou; Sisay-Joof, Fatou; Pinder, Margaret; Griffiths, Michael J.; Peshu, Norbert; Williams, Thomas N.; Newton, Charles R.; Marsh, Kevin; Molyneux, Malcolm E.; Taylor, Terrie E.; Koram, Kwadwo A.; Oduro, Abraham R.; Rogers, William O.; Rockett, Kirk A.; Sabeti, Pardis C.; Kwiatkowski, Dominic P.
2009-01-01
The prevalence of CD36 deficiency in East Asian and African populations suggests that the causal variants are under selection by severe malaria. Previous analysis of data from the International HapMap Project indicated that a CD36 haplotype bearing a nonsense mutation (T1264G; rs3211938) had undergone recent positive selection in the Yoruba of Nigeria. To investigate the global distribution of this putative selection event, we genotyped T1264G in 3420 individuals from 66 populations. We confirmed the high frequency of 1264G in the Yoruba (26%). However, the 1264G allele is less common in other African populations and absent from all non-African populations without recent African admixture. Using long-range linkage disequilibrium, we studied two West African groups in depth. Evidence for recent positive selection at the locus was demonstrable in the Yoruba, although not in Gambians. We screened 70 variants from across CD36 for an association with severe malaria phenotypes, employing a case–control study of 1350 subjects and a family study of 1288 parent–offspring trios. No marker was significantly associated with severe malaria. We focused on T1264G, genotyping 10 922 samples from four African populations. The nonsense allele was not associated with severe malaria (pooled allelic odds ratio 1.0; 95% confidence interval 0.89–1.12; P = 0.98). These results suggest a range of possible explanations including the existence of alternative selection pressures on CD36, co-evolution between host and parasite or confounding caused by allelic heterogeneity of CD36 deficiency. PMID:19403559
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Fry, Andrew E; Ghansa, Anita; Small, Kerrin S; Palma, Alejandro; Auburn, Sarah; Diakite, Mahamadou; Green, Angela; Campino, Susana; Teo, Yik Y; Clark, Taane G; Jeffreys, Anna E; Wilson, Jonathan; Jallow, Muminatou; Sisay-Joof, Fatou; Pinder, Margaret; Griffiths, Michael J; Peshu, Norbert; Williams, Thomas N; Newton, Charles R; Marsh, Kevin; Molyneux, Malcolm E; Taylor, Terrie E; Koram, Kwadwo A; Oduro, Abraham R; Rogers, William O; Rockett, Kirk A; Sabeti, Pardis C; Kwiatkowski, Dominic P
2009-07-15
The prevalence of CD36 deficiency in East Asian and African populations suggests that the causal variants are under selection by severe malaria. Previous analysis of data from the International HapMap Project indicated that a CD36 haplotype bearing a nonsense mutation (T1264G; rs3211938) had undergone recent positive selection in the Yoruba of Nigeria. To investigate the global distribution of this putative selection event, we genotyped T1264G in 3420 individuals from 66 populations. We confirmed the high frequency of 1264G in the Yoruba (26%). However, the 1264G allele is less common in other African populations and absent from all non-African populations without recent African admixture. Using long-range linkage disequilibrium, we studied two West African groups in depth. Evidence for recent positive selection at the locus was demonstrable in the Yoruba, although not in Gambians. We screened 70 variants from across CD36 for an association with severe malaria phenotypes, employing a case-control study of 1350 subjects and a family study of 1288 parent-offspring trios. No marker was significantly associated with severe malaria. We focused on T1264G, genotyping 10,922 samples from four African populations. The nonsense allele was not associated with severe malaria (pooled allelic odds ratio 1.0; 95% confidence interval 0.89-1.12; P = 0.98). These results suggest a range of possible explanations including the existence of alternative selection pressures on CD36, co-evolution between host and parasite or confounding caused by allelic heterogeneity of CD36 deficiency.
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Saleheen, Danish; Haycock, Philip C; Zhao, Wei; Rasheed, Asif; Taleb, Adam; Imran, Atif; Abbas, Shahid; Majeed, Faisal; Akhtar, Saba; Qamar, Nadeem; Zaman, Khan Shah; Yaqoob, Zia; Saghir, Tahir; Rizvi, Syed Nadeem Hasan; Memon, Anis; Mallick, Nadeem Hayyat; Ishaq, Mohammad; Rasheed, Syed Zahed; Memon, Fazal-Ur-Rehman; Mahmood, Khalid; Ahmed, Naveeduddin; Frossard, Philippe; Tsimikas, Sotirios; Witztum, Joseph L; Marcovina, Santica; Sandhu, Manjinder; Rader, Daniel J; Danesh, John
2017-07-01
The lipoprotein(a) pathway is a causal factor in coronary heart disease. We used a genetic approach to distinguish the relevance of two distinct components of this pathway, apolipoprotein(a) isoform size and circulating lipoprotein(a) concentration, to coronary heart disease. In this mendelian randomisation study, we measured lipoprotein(a) concentration and determined apolipoprotein(a) isoform size with a genetic method (kringle IV type 2 [KIV2] repeats in the LPA gene) and a serum-based electrophoretic assay in patients and controls (frequency matched for age and sex) from the Pakistan Risk of Myocardial Infarction Study (PROMIS). We calculated odds ratios (ORs) for myocardial infarction per 1-SD difference in either LPA KIV2 repeats or lipoprotein(a) concentration. In a genome-wide analysis of up to 17 503 participants in PROMIS, we identified genetic variants associated with either apolipoprotein(a) isoform size or lipoprotein(a) concentration. Using a mendelian randomisation study design and genetic data on 60 801 patients with coronary heart disease and 123 504 controls from the CARDIoGRAMplusC4D consortium, we calculated ORs for myocardial infarction with variants that produced similar differences in either apolipoprotein(a) isoform size in serum or lipoprotein(a) concentration. Finally, we compared phenotypic versus genotypic ORs to estimate whether apolipoprotein(a) isoform size, lipoprotein(a) concentration, or both were causally associated with coronary heart disease. The PROMIS cohort included 9015 patients with acute myocardial infarction and 8629 matched controls. In participants for whom KIV2 repeat and lipoprotein(a) data were available, the OR for myocardial infarction was 0·93 (95% CI 0·90-0·97; p<0·0001) per 1-SD increment in LPA KIV2 repeats after adjustment for lipoprotein(a) concentration and conventional lipid concentrations. The OR for myocardial infarction was 1·10 (1·05-1·14; p<0·0001) per 1-SD increment in lipoprotein(a) concentration, after adjustment for LPA KIV2 repeats and conventional lipids. Genome-wide analysis identified rs2457564 as a variant associated with smaller apolipoprotein(a) isoform size, but not lipoprotein(a) concentration, and rs3777392 as a variant associated with lipoprotein(a) concentration, but not apolipoprotein(a) isoform size. In 60 801 patients with coronary heart disease and 123 504 controls, OR for myocardial infarction was 0·96 (0·94-0·98; p<0·0001) per 1-SD increment in apolipoprotein(a) protein isoform size in serum due to rs2457564, which was directionally concordant with the OR observed in PROMIS for a similar change. The OR for myocardial infarction was 1·27 (1·07-1·50; p=0·007) per 1-SD increment in lipoprotein(a) concentration due to rs3777392, which was directionally concordant with the OR observed for a similar change in PROMIS. Human genetic data suggest that both smaller apolipoprotein(a) isoform size and increased lipoprotein(a) concentration are independent and causal risk factors for coronary heart disease. Lipoprotein(a)-lowering interventions could be preferentially effective in reducing the risk of coronary heart disease in individuals with smaller apolipoprotein(a) isoforms. British Heart Foundation, US National Institutes of Health, Fogarty International Center, Wellcome Trust, UK Medical Research Council, UK National Institute for Health Research, and Pfizer. Copyright © 2017 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND license. Published by Elsevier Ltd.. All rights reserved.
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Royo, Carolina; Torres-Pérez, Rafael; Mauri, Nuria; Diestro, Nieves; Cabezas, José Antonio; Marchal, Cécile; Lacombe, Thierry; Ibáñez, Javier; Tornel, Manuel; Carreño, Juan; Martínez-Zapater, José M; Carbonell-Bejerano, Pablo
2018-05-31
Seedlessness is greatly prized by consumers of fresh grapes. While stenospermocarpic seed abortion determined by the SEED DEVELOPMENT INHIBITOR (SDI) locus is the usual source of seedlessness in commercial grapevine (Vitis vinifera) cultivars, the underlying sdi mutation remains unknown. Here, we undertook an integrative approach to identify the causal mutation. Quantitative genetics and fine mapping in two 'Crimson Seedless' (CS)-derived F1 mapping populations confirmed the major effect of the SDI locus and delimited the sdi mutation to a 323-kb region on chromosome 18. RNA-seq comparing seed traces of seedless and seeds of seeded F1 individuals identified processes triggered during sdi-determined seed abortion, including activation of salicylic acid-dependent defenses. The RNA-seq dataset was investigated for candidate genes and, while no evidence for causal cis-acting regulatory mutations was detected, deleterious nucleotide changes in coding sequences of the seedless haplotype were predicted in two genes within the sdi fine mapping interval. Targeted re-sequencing of the two genes in a collection of 124 grapevine cultivars showed that only the point variation causing the Arg197Leu substitution in the seed morphogenesis regulator gene AGAMOUS-LIKE 11 (VviAGL11) was fully linked with stenospermocarpy. The concurrent post-zygotic variation identified for this missense polymorphism and seedlessness phenotype in seeded somatic variants of the original stenospermocarpic cultivar supports a causal effect. We postulate that seed abortion caused by this amino acid substitution in VviAGL11 is the major cause of seedlessness in cultivated grapevine. This information can be exploited to boost seedless grape breeding. {copyright, serif} 2018 American Society of Plant Biologists. All rights reserved.
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Davies, Benjamin; Brown, Laurence A; Cais, Ondrej; Watson, Jake; Clayton, Amber J; Chang, Veronica T; Biggs, Daniel; Preece, Christopher; Hernandez-Pliego, Polinka; Krohn, Jon; Bhomra, Amarjit; Twigg, Stephen R F; Rimmer, Andrew; Kanapin, Alexander; Sen, Arjune; Zaiwalla, Zenobia; McVean, Gil; Foster, Russell; Donnelly, Peter; Taylor, Jenny C; Blair, Edward; Nutt, David; Aricescu, A Radu; Greger, Ingo H; Peirson, Stuart N; Flint, Jonathan; Martin, Hilary C
2017-10-15
The discovery of genetic variants influencing sleep patterns can shed light on the physiological processes underlying sleep. As part of a large clinical sequencing project, WGS500, we sequenced a family in which the two male children had severe developmental delay and a dramatically disturbed sleep-wake cycle, with very long wake and sleep durations, reaching up to 106-h awake and 48-h asleep. The most likely causal variant identified was a novel missense variant in the X-linked GRIA3 gene, which has been implicated in intellectual disability. GRIA3 encodes GluA3, a subunit of AMPA-type ionotropic glutamate receptors (AMPARs). The mutation (A653T) falls within the highly conserved transmembrane domain of the ion channel gate, immediately adjacent to the analogous residue in the Grid2 (glutamate receptor) gene, which is mutated in the mouse neurobehavioral mutant, Lurcher. In vitro, the GRIA3(A653T) mutation stabilizes the channel in a closed conformation, in contrast to Lurcher. We introduced the orthologous mutation into a mouse strain by CRISPR-Cas9 mutagenesis and found that hemizygous mutants displayed significant differences in the structure of their activity and sleep compared to wild-type littermates. Typically, mice are polyphasic, exhibiting multiple sleep bouts of sleep several minutes long within a 24-h period. The Gria3A653T mouse showed significantly fewer brief bouts of activity and sleep than the wild-types. Furthermore, Gria3A653T mice showed enhanced period lengthening under constant light compared to wild-type mice, suggesting an increased sensitivity to light. Our results suggest a role for GluA3 channel activity in the regulation of sleep behavior in both mice and humans. © The Author 2017. Published by Oxford University Press.
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Ahsan, Muhammad; Ek, Weronica E.; Karlsson, Torgny; Gyllensten, Ulf
2017-01-01
Associations between epigenetic alterations and disease status have been identified for many diseases. However, there is no strong evidence that epigenetic alterations are directly causal for disease pathogenesis. In this study, we combined SNP and DNA methylation data with measurements of protein biomarkers for cancer, inflammation or cardiovascular disease, to investigate the relative contribution of genetic and epigenetic variation on biomarker levels. A total of 121 protein biomarkers were measured and analyzed in relation to DNA methylation at 470,000 genomic positions and to over 10 million SNPs. We performed epigenome-wide association study (EWAS) and genome-wide association study (GWAS) analyses, and integrated biomarker, DNA methylation and SNP data using between 698 and 1033 samples depending on data availability for the different analyses. We identified 124 and 45 loci (Bonferroni adjusted P < 0.05) with effect sizes up to 0.22 standard units’ change per 1% change in DNA methylation levels and up to four standard units’ change per copy of the effective allele in the EWAS and GWAS respectively. Most GWAS loci were cis-regulatory whereas most EWAS loci were located in trans. Eleven EWAS loci were associated with multiple biomarkers, including one in NLRC5 associated with CXCL11, CXCL9, IL-12, and IL-18 levels. All EWAS signals that overlapped with a GWAS locus were driven by underlying genetic variants and three EWAS signals were confounded by smoking. While some cis-regulatory SNPs for biomarkers appeared to have an effect also on DNA methylation levels, cis-regulatory SNPs for DNA methylation were not observed to affect biomarker levels. We present associations between protein biomarker and DNA methylation levels at numerous loci in the genome. The associations are likely to reflect the underlying pattern of genetic variants, specific environmental exposures, or represent secondary effects to the pathogenesis of disease. PMID:28915241
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Defining the consequences of genetic variation on a proteome–wide scale
Chick, Joel M.; Munger, Steven C.; Simecek, Petr; Huttlin, Edward L.; Choi, Kwangbom; Gatti, Daniel M.; Raghupathy, Narayanan; Svenson, Karen L.; Churchill, Gary A.; Gygi, Steven P.
2016-01-01
Genetic variation modulates protein expression through both transcriptional and post-transcriptional mechanisms. To characterize the consequences of natural genetic diversity on the proteome, here we combine a multiplexed, mass spectrometry-based method for protein quantification with an emerging outbred mouse model containing extensive genetic variation from eight inbred founder strains. By measuring genome-wide transcript and protein expression in livers from 192 Diversity outbred mice, we identify 2,866 protein quantitative trait loci (pQTL) with twice as many local as distant genetic variants. These data support distinct transcriptional and post-transcriptional models underlying the observed pQTL effects. Using a sensitive approach to mediation analysis, we often identified a second protein or transcript as the causal mediator of distant pQTL. Our analysis reveals an extensive network of direct protein–protein interactions. Finally, we show that local genotype can provide accurate predictions of protein abundance in an independent cohort of collaborative cross mice. PMID:27309819
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Bao, Riyue; Hernandez, Kyle; Huang, Lei; Kang, Wenjun; Bartom, Elizabeth; Onel, Kenan; Volchenboum, Samuel; Andrade, Jorge
2015-01-01
Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud.
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The genomic landscape shaped by selection on transposable elements across 18 mouse strains.
Nellåker, Christoffer; Keane, Thomas M; Yalcin, Binnaz; Wong, Kim; Agam, Avigail; Belgard, T Grant; Flint, Jonathan; Adams, David J; Frankel, Wayne N; Ponting, Chris P
2012-06-15
Transposable element (TE)-derived sequence dominates the landscape of mammalian genomes and can modulate gene function by dysregulating transcription and translation. Our current knowledge of TEs in laboratory mouse strains is limited primarily to those present in the C57BL/6J reference genome, with most mouse TEs being drawn from three distinct classes, namely short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs) and the endogenous retrovirus (ERV) superfamily. Despite their high prevalence, the different genomic and gene properties controlling whether TEs are preferentially purged from, or are retained by, genetic drift or positive selection in mammalian genomes remain poorly defined. Using whole genome sequencing data from 13 classical laboratory and 4 wild-derived mouse inbred strains, we developed a comprehensive catalogue of 103,798 polymorphic TE variants. We employ this extensive data set to characterize TE variants across the Mus lineage, and to infer neutral and selective processes that have acted over 2 million years. Our results indicate that the majority of TE variants are introduced though the male germline and that only a minority of TE variants exert detectable changes in gene expression. However, among genes with differential expression across the strains there are twice as many TE variants identified as being putative causal variants as expected. Most TE variants that cause gene expression changes appear to be purged rapidly by purifying selection. Our findings demonstrate that past TE insertions have often been highly deleterious, and help to prioritize TE variants according to their likely contribution to gene expression or phenotype variation.
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Colombo, Mara; Lòpez-Perolio, Irene; Meeks, Huong D; Caleca, Laura; Parsons, Michael T; Li, Hongyan; De Vecchi, Giovanna; Tudini, Emma; Foglia, Claudia; Mondini, Patrizia; Manoukian, Siranoush; Behar, Raquel; Garcia, Encarna B Gómez; Meindl, Alfons; Montagna, Marco; Niederacher, Dieter; Schmidt, Ane Y; Varesco, Liliana; Wappenschmidt, Barbara; Bolla, Manjeet K; Dennis, Joe; Michailidou, Kyriaki; Wang, Qin; Aittomäki, Kristiina; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Beeghly-Fadel, Alicia; Benitez, Javier; Boeckx, Bram; Bogdanova, Natalia V; Bojesen, Stig E; Bonanni, Bernardo; Brauch, Hiltrud; Brenner, Hermann; Burwinkel, Barbara; Chang-Claude, Jenny; Conroy, Don M; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Gabrielson, Marike; García-Closas, Montserrat; Giles, Graham G; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A; Hall, Per; Hamann, Ute; Hartman, Mikael; Hauke, Jan; Hollestelle, Antoinette; Hopper, John L; Jakubowska, Anna; Jung, Audrey; Kosma, Veli-Matti; Lambrechts, Diether; Le Marchand, Loid; Lindblom, Annika; Lubinski, Jan; Mannermaa, Arto; Margolin, Sara; Miao, Hui; Milne, Roger L; Neuhausen, Susan L; Nevanlinna, Heli; Olson, Janet E; Peterlongo, Paolo; Peto, Julian; Pylkäs, Katri; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Schneeweiss, Andreas; Schoemaker, Minouk J; See, Mee Hoong; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo H; Toland, Amanda E; Tomlinson, Ian; Truong, Thérèse; van Asperen, Christi J; van den Ouweland, Ans M W; van der Kolk, Lizet E; Winqvist, Robert; Yannoukakos, Drakoulis; Zheng, Wei; Dunning, Alison M; Easton, Douglas F; Henderson, Alex; Hogervorst, Frans B L; Izatt, Louise; Offitt, Kenneth; Side, Lucy E; van Rensburg, Elizabeth J; Embrace, Study; Hebon, Study; McGuffog, Lesley; Antoniou, Antonis C; Chenevix-Trench, Georgia; Spurdle, Amanda B; Goldgar, David E; Hoya, Miguel de la; Radice, Paolo
2018-05-01
Although the spliceogenic nature of the BRCA2 c.68-7T > A variant has been demonstrated, its association with cancer risk remains controversial. In this study, we accurately quantified by real-time PCR and digital PCR (dPCR), the BRCA2 isoforms retaining or missing exon 3. In addition, the combined odds ratio for causality of the variant was estimated using genetic and clinical data, and its associated cancer risk was estimated by case-control analysis in 83,636 individuals. Co-occurrence in trans with pathogenic BRCA2 variants was assessed in 5,382 families. Exon 3 exclusion rate was 4.5-fold higher in variant carriers (13%) than controls (3%), indicating an exclusion rate for the c.68-7T > A allele of approximately 20%. The posterior probability of pathogenicity was 7.44 × 10 -115 . There was neither evidence for increased risk of breast cancer (OR 1.03; 95% CI 0.86-1.24) nor for a deleterious effect of the variant when co-occurring with pathogenic variants. Our data provide for the first time robust evidence of the nonpathogenicity of the BRCA2 c.68-7T > A. Genetic and quantitative transcript analyses together inform the threshold for the ratio between functional and altered BRCA2 isoforms compatible with normal cell function. These findings might be exploited to assess the relevance for cancer risk of other BRCA2 spliceogenic variants. © 2018 The Authors. Human Mutation published by Wiley Periodicals, Inc.
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The role of counterfactual theory in causal reasoning.
Maldonado, George
2016-10-01
In this commentary I review the fundamentals of counterfactual theory and its role in causal reasoning in epidemiology. I consider if counterfactual theory dictates that causal questions must be framed in terms of well-defined interventions. I conclude that it does not. I hypothesize that the interventionist approach to causal inference in epidemiology stems from elevating the randomized trial design to the gold standard for thinking about causal inference. I suggest that instead the gold standard we should use for thinking about causal inference in epidemiology is the thought experiment that, for example, compares an actual disease frequency under one exposure level with a counterfactual disease frequency under a different exposure level (as discussed in Greenland and Robins (1986) and Maldonado and Greenland (2002)). I also remind us that no method should be termed "causal" unless it addresses the effect of other biases in addition to the problem of confounding. Copyright © 2016 Elsevier Inc. All rights reserved.
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Cho, Eun Young; Jang, Yangsoo; Shin, Eun Soon; Jang, Hye Yoon; Yoo, Yeon-Kyeong; Kim, Sook; Jang, Ji Hyun; Lee, Ji Yeon; Yun, Min Hye; Park, Min Young; Chae, Jey Sook; Lim, Jin Woo; Shin, Dong Jik; Park, Sungha; Lee, Jong Ho; Han, Bok Ghee; Rae, Kim Hyung; Cardon, Lon R; Morris, Andrew P; Lee, Jong Eun; Clarke, Geraldine M
2010-01-01
Background Recent genome-wide association (GWA) studies have identified and replicated several genetic loci associated with the risk of development of coronary artery disease (CAD) in samples from populations of Caucasian and Asian descent. However, only chromosome 9p21 has been confirmed as a major susceptibility locus conferring risk for development of CAD across multiple ethnic groups. The authors aimed to find evidence of further similarities and differences in genetic risk of CAD between Korean and other populations. Methods The authors performed a GWA study comprising 230 cases and 290 controls from a Korean population typed on 490 032 single nucleotide polymorphisms (SNPs). A total of 3148 SNPs were taken forward for genotyping in a subsequent replication study using an independent sample of 1172 cases and 1087 controls from the same population. Results The association previously observed on chromosome 9p21 was independently replicated (p=3.08e–07). Within this region, the same risk haplotype was observed in samples from both Korea and of Western European descent, suggesting that the causal mutation carried on this background occurred on a single ancestral allele. Other than 9p21, the authors were unable to replicate any of the previously reported signals for association with CAD. Furthermore, no evidence of association was found at chromosome 1q41 for risk of myocardial infarction, previously identified as conferring risk in a Japanese population. Conclusion A common causal variant is likely to be responsible for risk of CAD in Korean and Western European populations at chromosome 9p21.3. Further investigations are required to confirm non-replication of any other cross-race genetic risk factors. PMID:27325954
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Screening for rare variants in the PNPLA3 gene in obese liver biopsy patients.
Zegers, Doreen; Verrijken, An; Francque, Sven; de Freitas, Fenna; Beckers, Sigri; Aerts, Evi; Ruppert, Martin; Hubens, Guy; Michielsen, Peter; Van Hul, Wim; Van Gaal, Luc F
2016-12-01
Previous research has clearly implicated the PNPLA3 gene in the etiology of nonalcoholic fatty liver disease as a polymorphism in the gene was found to be robustly associated to the disease. However, data on the involvement of rare PNPLA3 variants in the development of nonalcoholic fatty liver disease (NAFLD) is currently limited. Therefore, we performed an extensive mutation analysis study on a cohort of obese liver biopsy patients to determine PNPLA3 variation and its correlation with fatty liver disease. We screened the entire coding region of the PNPLA3 gene in DNA samples of 393 obese liver biopsy patients with varying degrees of fatty liver disease. Mutation analysis was performed by high-resolution melting curve analysis in combination with direct sequencing. We identified several common polymorphisms as well as one rare synonymous variant (c.867G>A rs139896256), one rare intronic variant (c.979+13C>T) and 3 nonsynonymous coding variants (p.A76T, p.A104V and p.T200M) in the PNPLA3 gene. In silico analysis indicated that the p.A104V variant will probably have no functional effect, whereas for the p.A76T and p.T200M variant a possible pathogenic effect is suggested. Overall, we showed that novel variants in PNPLA3 are very rare in our liver biopsy cohort, thereby indicating that their impact on the etiology of NAFLD is probably limited. Nevertheless, for the three rare coding variants that were identified in patients with advanced liver disease, further functional characterization will be essential to verify their potential disease causality. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
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Genetic Misdiagnoses and the Potential for Health Disparities.
Manrai, Arjun K; Funke, Birgit H; Rehm, Heidi L; Olesen, Morten S; Maron, Bradley A; Szolovits, Peter; Margulies, David M; Loscalzo, Joseph; Kohane, Isaac S
2016-08-18
For more than a decade, risk stratification for hypertrophic cardiomyopathy has been enhanced by targeted genetic testing. Using sequencing results, clinicians routinely assess the risk of hypertrophic cardiomyopathy in a patient's relatives and diagnose the condition in patients who have ambiguous clinical presentations. However, the benefits of genetic testing come with the risk that variants may be misclassified. Using publicly accessible exome data, we identified variants that have previously been considered causal in hypertrophic cardiomyopathy and that are overrepresented in the general population. We studied these variants in diverse populations and reevaluated their initial ascertainments in the medical literature. We reviewed patient records at a leading genetic-testing laboratory for occurrences of these variants during the near-decade-long history of the laboratory. Multiple patients, all of whom were of African or unspecified ancestry, received positive reports, with variants misclassified as pathogenic on the basis of the understanding at the time of testing. Subsequently, all reported variants were recategorized as benign. The mutations that were most common in the general population were significantly more common among black Americans than among white Americans (P<0.001). Simulations showed that the inclusion of even small numbers of black Americans in control cohorts probably would have prevented these misclassifications. We identified methodologic shortcomings that contributed to these errors in the medical literature. The misclassification of benign variants as pathogenic that we found in our study shows the need for sequencing the genomes of diverse populations, both in asymptomatic controls and the tested patient population. These results expand on current guidelines, which recommend the use of ancestry-matched controls to interpret variants. As additional populations of different ancestry backgrounds are sequenced, we expect variant reclassifications to increase, particularly for ancestry groups that have historically been less well studied. (Funded by the National Institutes of Health.).
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Demiralp, Metin
This work focuses on the dynamics of a system of quantum multi harmonic oscillators whose Hamiltonian is conic in positions and momenta with time variant coefficients. While it is simple, this system is useful for modeling the dynamics of a number of systems in contemporary sciences where the equations governing spatial or temporal changes are described by sets of ODEs. The dynamical causal models used readily in neuroscience can be indirectly described by these systems. In this work, we want to show that it is possible to describe these systems using quantum wave function type entities and expectations if themore » dynamic of the system is related to a set of ODEs.« less
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DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis.
Kular, Lara; Liu, Yun; Ruhrmann, Sabrina; Zheleznyakova, Galina; Marabita, Francesco; Gomez-Cabrero, David; James, Tojo; Ewing, Ewoud; Lindén, Magdalena; Górnikiewicz, Bartosz; Aeinehband, Shahin; Stridh, Pernilla; Link, Jenny; Andlauer, Till F M; Gasperi, Christiane; Wiendl, Heinz; Zipp, Frauke; Gold, Ralf; Tackenberg, Björn; Weber, Frank; Hemmer, Bernhard; Strauch, Konstantin; Heilmann-Heimbach, Stefanie; Rawal, Rajesh; Schminke, Ulf; Schmidt, Carsten O; Kacprowski, Tim; Franke, Andre; Laudes, Matthias; Dilthey, Alexander T; Celius, Elisabeth G; Søndergaard, Helle B; Tegnér, Jesper; Harbo, Hanne F; Oturai, Annette B; Olafsson, Sigurgeir; Eggertsson, Hannes P; Halldorsson, Bjarni V; Hjaltason, Haukur; Olafsson, Elias; Jonsdottir, Ingileif; Stefansson, Kari; Olsson, Tomas; Piehl, Fredrik; Ekström, Tomas J; Kockum, Ingrid; Feinberg, Andrew P; Jagodic, Maja
2018-06-19
The human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization provide evidence that HLA variants mediate risk for MS via changes in the HLA-DRB1 DMR that modify HLA-DRB1 expression. Meta-analysis of 14,259 cases and 171,347 controls confirms that these variants confer risk from DRB1*15:01 and also identifies a protective variant (rs9267649, p < 3.32 × 10 -8 , odds ratio = 0.86) after conditioning for all MS-associated variants in the region. rs9267649 is associated with increased DNA methylation at the HLA-DRB1 DMR and reduced expression of HLA-DRB1, suggesting a modulation of the DRB1*15:01 effect. Our integrative approach provides insights into the molecular mechanisms of MS susceptibility and suggests putative therapeutic strategies targeting a methylation-mediated regulation of the major risk gene.
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The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis
Ploner, Alexander; Fischer, Krista; Horikoshi, Momoko; Sarin, Antti-Pekka; Thorleifsson, Gudmar; Ladenvall, Claes; Kals, Mart; Kuningas, Maris; Draisma, Harmen H. M.; Ried, Janina S.; van Zuydam, Natalie R.; Huikari, Ville; Mangino, Massimo; Sonestedt, Emily; Benyamin, Beben; Nelson, Christopher P.; Rivera, Natalia V.; Kristiansson, Kati; Shen, Huei-yi; Havulinna, Aki S.; Dehghan, Abbas; Donnelly, Louise A.; Kaakinen, Marika; Nuotio, Marja-Liisa; Robertson, Neil; de Bruijn, Renée F. A. G.; Ikram, M. Arfan; Amin, Najaf; Balmforth, Anthony J.; Braund, Peter S.; Doney, Alexander S. F.; Döring, Angela; Elliott, Paul; Esko, Tõnu; Franco, Oscar H.; Gretarsdottir, Solveig; Hartikainen, Anna-Liisa; Heikkilä, Kauko; Herzig, Karl-Heinz; Holm, Hilma; Hottenga, Jouke Jan; Hyppönen, Elina; Illig, Thomas; Isaacs, Aaron; Isomaa, Bo; Karssen, Lennart C.; Kettunen, Johannes; Koenig, Wolfgang; Kuulasmaa, Kari; Laatikainen, Tiina; Laitinen, Jaana; Lindgren, Cecilia; Lyssenko, Valeriya; Läärä, Esa; Rayner, Nigel W.; Männistö, Satu; Pouta, Anneli; Rathmann, Wolfgang; Rivadeneira, Fernando; Ruokonen, Aimo; Savolainen, Markku J.; Sijbrands, Eric J. G.; Small, Kerrin S.; Smit, Jan H.; Steinthorsdottir, Valgerdur; Syvänen, Ann-Christine; Taanila, Anja; Tobin, Martin D.; Uitterlinden, Andre G.; Willems, Sara M.; Willemsen, Gonneke; Witteman, Jacqueline; Perola, Markus; Evans, Alun; Ferrières, Jean; Virtamo, Jarmo; Kee, Frank; Tregouet, David-Alexandre; Arveiler, Dominique; Amouyel, Philippe; Ferrario, Marco M.; Brambilla, Paolo; Hall, Alistair S.; Heath, Andrew C.; Madden, Pamela A. F.; Martin, Nicholas G.; Montgomery, Grant W.; Whitfield, John B.; Jula, Antti; Knekt, Paul; Oostra, Ben; van Duijn, Cornelia M.; Penninx, Brenda W. J. H.; Davey Smith, George; Kaprio, Jaakko; Samani, Nilesh J.; Gieger, Christian; Peters, Annette; Wichmann, H.-Erich; Boomsma, Dorret I.; de Geus, Eco J. C.; Tuomi, TiinaMaija; Power, Chris; Hammond, Christopher J.; Spector, Tim D.; Lind, Lars; Orho-Melander, Marju; Palmer, Colin Neil Alexander; Morris, Andrew D.; Groop, Leif; Järvelin, Marjo-Riitta; Salomaa, Veikko; Vartiainen, Erkki; Hofman, Albert; Ripatti, Samuli; Metspalu, Andres; Thorsteinsdottir, Unnur; Stefansson, Kari; Pedersen, Nancy L.; McCarthy, Mark I.; Ingelsson, Erik; Prokopenko, Inga
2013-01-01
Background The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach. Methods and Findings We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses. Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001). Conclusions We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes. Please see later in the article for the Editors' Summary PMID:23824655
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ERIC Educational Resources Information Center
Jeong, Allan; Lee, Woon Jee
2012-01-01
This study examined some of the methodological approaches used by students to construct causal maps in order to determine which approaches help students understand the underlying causes and causal mechanisms in a complex system. This study tested the relationship between causal understanding (ratio of root causes correctly/incorrectly identified,…
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A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease
Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel
2013-01-01
Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213
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Learning by Self-Explaining Causal Diagrams in High-School Biology
ERIC Educational Resources Information Center
Cho, Young Hoan; Jonassen, David H.
2012-01-01
Understanding scientific phenomena requires comprehension and application of the underlying causal relationships that describe those phenomena (Carey 2002). The current study examined the roles of self-explanation and meta-level feedback for understanding causal relationships described in a causal diagram. In this study, 63 Korean high-school…
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Nikpay, Majid; Goel, Anuj; Won, Hong-Hee; Hall, Leanne M; Willenborg, Christina; Kanoni, Stavroula; Saleheen, Danish; Kyriakou, Theodosios; Nelson, Christopher P; Hopewell, Jemma C; Webb, Thomas R; Zeng, Lingyao; Dehghan, Abbas; Alver, Maris; Armasu, Sebastian M; Auro, Kirsi; Bjonnes, Andrew; Chasman, Daniel I; Chen, Shufeng; Ford, Ian; Franceschini, Nora; Gieger, Christian; Grace, Christopher; Gustafsson, Stefan; Huang, Jie; Hwang, Shih-Jen; Kim, Yun Kyoung; Kleber, Marcus E; Lau, King Wai; Lu, Xiangfeng; Lu, Yingchang; Lyytikäinen, Leo-Pekka; Mihailov, Evelin; Morrison, Alanna C; Pervjakova, Natalia; Qu, Liming; Rose, Lynda M; Salfati, Elias; Saxena, Richa; Scholz, Markus; Smith, Albert V; Tikkanen, Emmi; Uitterlinden, Andre; Yang, Xueli; Zhang, Weihua; Zhao, Wei; de Andrade, Mariza; de Vries, Paul S; van Zuydam, Natalie R; Anand, Sonia S; Bertram, Lars; Beutner, Frank; Dedoussis, George; Frossard, Philippe; Gauguier, Dominique; Goodall, Alison H; Gottesman, Omri; Haber, Marc; Han, Bok-Ghee; Huang, Jianfeng; Jalilzadeh, Shapour; Kessler, Thorsten; König, Inke R; Lannfelt, Lars; Lieb, Wolfgang; Lind, Lars; Lindgren, Cecilia M; Lokki, Marja-Liisa; Magnusson, Patrik K; Mallick, Nadeem H; Mehra, Narinder; Meitinger, Thomas; Memon, Fazal-Ur-Rehman; Morris, Andrew P; Nieminen, Markku S; Pedersen, Nancy L; Peters, Annette; Rallidis, Loukianos S; Rasheed, Asif; Samuel, Maria; Shah, Svati H; Sinisalo, Juha; Stirrups, Kathleen E; Trompet, Stella; Wang, Laiyuan; Zaman, Khan S; Ardissino, Diego; Boerwinkle, Eric; Borecki, Ingrid B; Bottinger, Erwin P; Buring, Julie E; Chambers, John C; Collins, Rory; Cupples, L Adrienne; Danesh, John; Demuth, Ilja; Elosua, Roberto; Epstein, Stephen E; Esko, Tõnu; Feitosa, Mary F; Franco, Oscar H; Franzosi, Maria Grazia; Granger, Christopher B; Gu, Dongfeng; Gudnason, Vilmundur; Hall, Alistair S; Hamsten, Anders; Harris, Tamara B; Hazen, Stanley L; Hengstenberg, Christian; Hofman, Albert; Ingelsson, Erik; Iribarren, Carlos; Jukema, J Wouter; Karhunen, Pekka J; Kim, Bong-Jo; Kooner, Jaspal S; Kullo, Iftikhar J; Lehtimäki, Terho; Loos, Ruth J F; Melander, Olle; Metspalu, Andres; März, Winfried; Palmer, Colin N; Perola, Markus; Quertermous, Thomas; Rader, Daniel J; Ridker, Paul M; Ripatti, Samuli; Roberts, Robert; Salomaa, Veikko; Sanghera, Dharambir K; Schwartz, Stephen M; Seedorf, Udo; Stewart, Alexandre F; Stott, David J; Thiery, Joachim; Zalloua, Pierre A; O'Donnell, Christopher J; Reilly, Muredach P; Assimes, Themistocles L; Thompson, John R; Erdmann, Jeanette; Clarke, Robert; Watkins, Hugh; Kathiresan, Sekar; McPherson, Ruth; Deloukas, Panos; Schunkert, Heribert; Samani, Nilesh J; Farrall, Martin
2015-10-01
Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
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van Rheenen, Wouter; Shatunov, Aleksey; Dekker, Annelot M; McLaughlin, Russell L; Diekstra, Frank P; Pulit, Sara L; van der Spek, Rick A A; Võsa, Urmo; de Jong, Simone; Robinson, Matthew R; Yang, Jian; Fogh, Isabella; van Doormaal, Perry TC; Tazelaar, Gijs H P; Koppers, Max; Blokhuis, Anna M; Sproviero, William; Jones, Ashley R; Kenna, Kevin P; van Eijk, Kristel R; Harschnitz, Oliver; Schellevis, Raymond D; Brands, William J; Medic, Jelena; Menelaou, Androniki; Vajda, Alice; Ticozzi, Nicola; Lin, Kuang; Rogelj, Boris; Vrabec, Katarina; Ravnik-Glavač, Metka; Koritnik, Blaž; Zidar, Janez; Leonardis, Lea; Grošelj, Leja Dolenc; Millecamps, Stéphanie; Salachas, François; Meininger, Vincent; de Carvalho, Mamede; Pinto, Susana; Mora, Jesus S; Rojas-García, Ricardo; Polak, Meraida; Chandran, Siddharthan; Colville, Shuna; Swingler, Robert; Morrison, Karen E; Shaw, Pamela J; Hardy, John; Orrell, Richard W; Pittman, Alan; Sidle, Katie; Fratta, Pietro; Malaspina, Andrea; Topp, Simon; Petri, Susanne; Abdulla, Susanne; Drepper, Carsten; Sendtner, Michael; Meyer, Thomas; Ophoff, Roel A; Staats, Kim A; Wiedau-Pazos, Martina; Lomen-Hoerth, Catherine; Van Deerlin, Vivianna M; Trojanowski, John Q; Elman, Lauren; McCluskey, Leo; Basak, A Nazli; Tunca, Ceren; Hamzeiy, Hamid; Parman, Yesim; Meitinger, Thomas; Lichtner, Peter; Radivojkov-Blagojevic, Milena; Andres, Christian R; Maurel, Cindy; Bensimon, Gilbert; Landwehrmeyer, Bernhard; Brice, Alexis; Payan, Christine A M; Saker-Delye, Safaa; Dürr, Alexandra; Wood, Nicholas W; Tittmann, Lukas; Lieb, Wolfgang; Franke, Andre; Rietschel, Marcella; Cichon, Sven; Nöthen, Markus M; Amouyel, Philippe; Tzourio, Christophe; Dartigues, Jean-François; Uitterlinden, Andre G; Rivadeneira, Fernando; Estrada, Karol; Hofman, Albert; Curtis, Charles; Blauw, Hylke M; van der Kooi, Anneke J; de Visser, Marianne; Goris, An; Weber, Markus; Shaw, Christopher E; Smith, Bradley N; Pansarasa, Orietta; Cereda, Cristina; Bo, Roberto Del; Comi, Giacomo P; D’Alfonso, Sandra; Bertolin, Cinzia; Sorarù, Gianni; Mazzini, Letizia; Pensato, Viviana; Gellera, Cinzia; Tiloca, Cinzia; Ratti, Antonia; Calvo, Andrea; Moglia, Cristina; Brunetti, Maura; Arcuti, Simona; Capozzo, Rosa; Zecca, Chiara; Lunetta, Christian; Penco, Silvana; Riva, Nilo; Padovani, Alessandro; Filosto, Massimiliano; Muller, Bernard; Stuit, Robbert Jan; Blair, Ian; Zhang, Katharine; McCann, Emily P; Fifita, Jennifer A; Nicholson, Garth A; Rowe, Dominic B; Pamphlett, Roger; Kiernan, Matthew C; Grosskreutz, Julian; Witte, Otto W; Ringer, Thomas; Prell, Tino; Stubendorff, Beatrice; Kurth, Ingo; Hübner, Christian A; Leigh, P Nigel; Casale, Federico; Chio, Adriano; Beghi, Ettore; Pupillo, Elisabetta; Tortelli, Rosanna; Logroscino, Giancarlo; Powell, John; Ludolph, Albert C; Weishaupt, Jochen H; Robberecht, Wim; Van Damme, Philip; Franke, Lude; Pers, Tune H; Brown, Robert H; Glass, Jonathan D; Landers, John E; Hardiman, Orla; Andersen, Peter M; Corcia, Philippe; Vourc’h, Patrick; Silani, Vincenzo; Wray, Naomi R; Visscher, Peter M; de Bakker, Paul I W; van Es, Michael A; Pasterkamp, R Jeroen; Lewis, Cathryn M; Breen, Gerome; Al-Chalabi, Ammar; van den Berg, Leonard H; Veldink, Jan H
2017-01-01
To elucidate the genetic architecture of amyotrophic lateral sclerosis (ALS) and find associated loci, we assembled a custom imputation reference panel from whole-genome-sequenced patients with ALS and matched controls (n = 1,861). Through imputation and mixed-model association analysis in 12,577 cases and 23,475 controls, combined with 2,579 cases and 2,767 controls in an independent replication cohort, we fine-mapped a new risk locus on chromosome 21 and identified C21orf2 as a gene associated with ALS risk. In addition, we identified MOBP and SCFD1 as new associated risk loci. We established evidence of ALS being a complex genetic trait with a polygenic architecture. Furthermore, we estimated the SNP-based heritability at 8.5%, with a distinct and important role for low-frequency variants (frequency 1–10%). This study motivates the interrogation of larger samples with full genome coverage to identify rare causal variants that underpin ALS risk. PMID:27455348
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Hundreds of variants clustered in genomic loci and biological pathways affect human height
Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segrè, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Mägi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Åsa; Zillikens, M.Carola; Feitosa, Mary F.; Esko, Tõnu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Glazer, Nicole L.; Hayward, Caroline; Hottenga, Jouke-Jan; Jacobs, Kevin B.; Knowles, Joshua W.; Kutalik, Zoltán; Monda, Keri L.; Polasek, Ozren; Preuss, Michael; Rayner, Nigel W.; Robertson, Neil R.; Steinthorsdottir, Valgerdur; Tyrer, Jonathan P.; Voight, Benjamin F.; Wiklund, Fredrik; Xu, Jianfeng; Zhao, Jing Hua; Nyholt, Dale R.; Pellikka, Niina; Perola, Markus; Perry, John R.B.; Surakka, Ida; Tammesoo, Mari-Liis; Altmaier, Elizabeth L.; Amin, Najaf; Aspelund, Thor; Bhangale, Tushar; Boucher, Gabrielle; Chasman, Daniel I.; Chen, Constance; Coin, Lachlan; Cooper, Matthew N.; Dixon, Anna L.; Gibson, Quince; Grundberg, Elin; Hao, Ke; Junttila, M. Juhani; Kaplan, Lee M.; Kettunen, Johannes; König, Inke R.; Kwan, Tony; Lawrence, Robert W.; Levinson, Douglas F.; Lorentzon, Mattias; McKnight, Barbara; Morris, Andrew P.; Müller, Martina; Ngwa, Julius Suh; Purcell, Shaun; Rafelt, Suzanne; Salem, Rany M.; Salvi, Erika; Sanna, Serena; Shi, Jianxin; Sovio, Ulla; Thompson, John R.; Turchin, Michael C.; Vandenput, Liesbeth; Verlaan, Dominique J.; Vitart, Veronique; White, Charles C.; Ziegler, Andreas; Almgren, Peter; Balmforth, Anthony J.; Campbell, Harry; Citterio, Lorena; De Grandi, Alessandro; Dominiczak, Anna; Duan, Jubao; Elliott, Paul; Elosua, Roberto; Eriksson, Johan G.; Freimer, Nelson B.; Geus, Eco J.C.; Glorioso, Nicola; Haiqing, Shen; Hartikainen, Anna-Liisa; Havulinna, Aki S.; Hicks, Andrew A.; Hui, Jennie; Igl, Wilmar; Illig, Thomas; Jula, Antti; Kajantie, Eero; Kilpeläinen, Tuomas O.; Koiranen, Markku; Kolcic, Ivana; Koskinen, Seppo; Kovacs, Peter; Laitinen, Jaana; Liu, Jianjun; Lokki, Marja-Liisa; Marusic, Ana; Maschio, Andrea; Meitinger, Thomas; Mulas, Antonella; Paré, Guillaume; Parker, Alex N.; Peden, John F.; Petersmann, Astrid; Pichler, Irene; Pietiläinen, Kirsi H.; Pouta, Anneli; Ridderstråle, Martin; Rotter, Jerome I.; Sambrook, Jennifer G.; Sanders, Alan R.; Schmidt, Carsten Oliver; Sinisalo, Juha; Smit, Jan H.; Stringham, Heather M.; Walters, G.Bragi; Widen, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Zagato, Laura; Zgaga, Lina; Zitting, Paavo; Alavere, Helene; Farrall, Martin; McArdle, Wendy L.; Nelis, Mari; Peters, Marjolein J.; Ripatti, Samuli; van Meurs, Joyce B.J.; Aben, Katja K.; Ardlie, Kristin G; Beckmann, Jacques S.; Beilby, John P.; Bergman, Richard N.; Bergmann, Sven; Collins, Francis S.; Cusi, Daniele; den Heijer, Martin; Eiriksdottir, Gudny; Gejman, Pablo V.; Hall, Alistair S.; Hamsten, Anders; Huikuri, Heikki V.; Iribarren, Carlos; Kähönen, Mika; Kaprio, Jaakko; Kathiresan, Sekar; Kiemeney, Lambertus; Kocher, Thomas; Launer, Lenore J.; Lehtimäki, Terho; Melander, Olle; Mosley, Tom H.; Musk, Arthur W.; Nieminen, Markku S.; O'Donnell, Christopher J.; Ohlsson, Claes; Oostra, Ben; Palmer, Lyle J.; Raitakari, Olli; Ridker, Paul M.; Rioux, John D.; Rissanen, Aila; Rivolta, Carlo; Schunkert, Heribert; Shuldiner, Alan R.; Siscovick, David S.; Stumvoll, Michael; Tönjes, Anke; Tuomilehto, Jaakko; van Ommen, Gert-Jan; Viikari, Jorma; Heath, Andrew C.; Martin, Nicholas G.; Montgomery, Grant W.; Province, Michael A.; Kayser, Manfred; Arnold, Alice M.; Atwood, Larry D.; Boerwinkle, Eric; Chanock, Stephen J.; Deloukas, Panos; Gieger, Christian; Grönberg, Henrik; Hall, Per; Hattersley, Andrew T.; Hengstenberg, Christian; Hoffman, Wolfgang; Lathrop, G.Mark; Salomaa, Veikko; Schreiber, Stefan; Uda, Manuela; Waterworth, Dawn; Wright, Alan F.; Assimes, Themistocles L.; Barroso, Inês; Hofman, Albert; Mohlke, Karen L.; Boomsma, Dorret I.; Caulfield, Mark J.; Cupples, L.Adrienne; Erdmann, Jeanette; Fox, Caroline S.; Gudnason, Vilmundur; Gyllensten, Ulf; Harris, Tamara B.; Hayes, Richard B.; Jarvelin, Marjo-Riitta; Mooser, Vincent; Munroe, Patricia B.; Ouwehand, Willem H.; Penninx, Brenda W.; Pramstaller, Peter P.; Quertermous, Thomas; Rudan, Igor; Samani, Nilesh J.; Spector, Timothy D.; Völzke, Henry; Watkins, Hugh; Wilson, James F.; Groop, Leif C.; Haritunians, Talin; Hu, Frank B.; Kaplan, Robert C.; Metspalu, Andres; North, Kari E.; Schlessinger, David; Wareham, Nicholas J.; Hunter, David J.; O'Connell, Jeffrey R.; Strachan, David P.; Wichmann, H.-Erich; Borecki, Ingrid B.; van Duijn, Cornelia M.; Schadt, Eric E.; Thorsteinsdottir, Unnur; Peltonen, Leena; Uitterlinden, André; Visscher, Peter M.; Chatterjee, Nilanjan; Loos, Ruth J.F.; Boehnke, Michael; McCarthy, Mark I.; Ingelsson, Erik; Lindgren, Cecilia M.; Abecasis, Gonçalo R.; Stefansson, Kari; Frayling, Timothy M.; Hirschhorn, Joel N
2010-01-01
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P=0.016), and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants, and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. PMID:20881960
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Brezovský, Jan
2016-01-01
An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools’ predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2. PMID:27224906
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Bendl, Jaroslav; Musil, Miloš; Štourač, Jan; Zendulka, Jaroslav; Damborský, Jiří; Brezovský, Jan
2016-05-01
An important message taken from human genome sequencing projects is that the human population exhibits approximately 99.9% genetic similarity. Variations in the remaining parts of the genome determine our identity, trace our history and reveal our heritage. The precise delineation of phenotypically causal variants plays a key role in providing accurate personalized diagnosis, prognosis, and treatment of inherited diseases. Several computational methods for achieving such delineation have been reported recently. However, their ability to pinpoint potentially deleterious variants is limited by the fact that their mechanisms of prediction do not account for the existence of different categories of variants. Consequently, their output is biased towards the variant categories that are most strongly represented in the variant databases. Moreover, most such methods provide numeric scores but not binary predictions of the deleteriousness of variants or confidence scores that would be more easily understood by users. We have constructed three datasets covering different types of disease-related variants, which were divided across five categories: (i) regulatory, (ii) splicing, (iii) missense, (iv) synonymous, and (v) nonsense variants. These datasets were used to develop category-optimal decision thresholds and to evaluate six tools for variant prioritization: CADD, DANN, FATHMM, FitCons, FunSeq2 and GWAVA. This evaluation revealed some important advantages of the category-based approach. The results obtained with the five best-performing tools were then combined into a consensus score. Additional comparative analyses showed that in the case of missense variations, protein-based predictors perform better than DNA sequence-based predictors. A user-friendly web interface was developed that provides easy access to the five tools' predictions, and their consensus scores, in a user-understandable format tailored to the specific features of different categories of variations. To enable comprehensive evaluation of variants, the predictions are complemented with annotations from eight databases. The web server is freely available to the community at http://loschmidt.chemi.muni.cz/predictsnp2.
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Sivley, R Michael; Sheehan, Jonathan H; Kropski, Jonathan A; Cogan, Joy; Blackwell, Timothy S; Phillips, John A; Bush, William S; Meiler, Jens; Capra, John A
2018-01-23
Next-generation sequencing of individuals with genetic diseases often detects candidate rare variants in numerous genes, but determining which are causal remains challenging. We hypothesized that the spatial distribution of missense variants in protein structures contains information about function and pathogenicity that can help prioritize variants of unknown significance (VUS) and elucidate the structural mechanisms leading to disease. To illustrate this approach in a clinical application, we analyzed 13 candidate missense variants in regulator of telomere elongation helicase 1 (RTEL1) identified in patients with Familial Interstitial Pneumonia (FIP). We curated pathogenic and neutral RTEL1 variants from the literature and public databases. We then used homology modeling to construct a 3D structural model of RTEL1 and mapped known variants into this structure. We next developed a pathogenicity prediction algorithm based on proximity to known disease causing and neutral variants and evaluated its performance with leave-one-out cross-validation. We further validated our predictions with segregation analyses, telomere lengths, and mutagenesis data from the homologous XPD protein. Our algorithm for classifying RTEL1 VUS based on spatial proximity to pathogenic and neutral variation accurately distinguished 7 known pathogenic from 29 neutral variants (ROC AUC = 0.85) in the N-terminal domains of RTEL1. Pathogenic proximity scores were also significantly correlated with effects on ATPase activity (Pearson r = -0.65, p = 0.0004) in XPD, a related helicase. Applying the algorithm to 13 VUS identified from sequencing of RTEL1 from patients predicted five out of six disease-segregating VUS to be pathogenic. We provide structural hypotheses regarding how these mutations may disrupt RTEL1 ATPase and helicase function. Spatial analysis of missense variation accurately classified candidate VUS in RTEL1 and suggests how such variants cause disease. Incorporating spatial proximity analyses into other pathogenicity prediction tools may improve accuracy for other genes and genetic diseases.
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Power, Robert A; Kyaga, Simon; Uher, Rudolf; MacCabe, James H; Långström, Niklas; Landen, Mikael; McGuffin, Peter; Lewis, Cathryn M; Lichtenstein, Paul; Svensson, Anna C
2013-01-01
It is unknown how genetic variants conferring liability to psychiatric disorders survive in the population despite strong negative selection. However, this is key to understanding their etiology and designing studies to identify risk variants. To examine the reproductive fitness of patients with schizophrenia and other psychiatric disorders vs their unaffected siblings and to evaluate the level of selection on causal genetic variants. We measured the fecundity of patients with schizophrenia, autism, bipolar disorder, depression, anorexia nervosa, or substance abuse and their unaffected siblings compared with the general population. Population databases in Sweden, including the Multi-Generation Register and the Swedish Hospital Discharge Register. In total, 2.3 million individuals among the 1950 to 1970 birth cohort in Sweden. Fertility ratio (FR), reflecting the mean number of children compared with that of the general population, accounting for age, sex, family size, and affected status. Except for women with depression, affected patients had significantly fewer children (FR range for those with psychiatric disorder, 0.23-0.93; P < 10-10). This reduction was consistently greater among men than women, suggesting that male fitness was particularly sensitive. Although sisters of patients with schizophrenia and bipolar disorder had increased fecundity (FR range, 1.02-1.03; P < .01), this was too small on its own to counterbalance the reduced fitness of affected patients. Brothers of patients with schizophrenia and autism showed reduced fecundity (FR range, 0.94-0.97; P < .001). Siblings of patients with depression and substance abuse had significantly increased fecundity (FR range, 1.01-1.05; P < 10-10). In the case of depression, this more than compensated for the lower fecundity of affected individuals. Our results suggest that strong selection exists against schizophrenia, autism, and anorexia nervosa and that these variants may be maintained by new mutations or an as-yet unknown mechanism. Bipolar disorder did not seem to be under strong negative selection. Vulnerability to depression, and perhaps substance abuse, may be preserved by balancing selection, suggesting the involvement of common genetic variants in ways that depend on other genes and on environment.
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In search of causal variants: refining disease association signals using cross-population contrasts.
Saccone, Nancy L; Saccone, Scott F; Goate, Alison M; Grucza, Richard A; Hinrichs, Anthony L; Rice, John P; Bierut, Laura J
2008-08-29
Genome-wide association (GWA) using large numbers of single nucleotide polymorphisms (SNPs) is now a powerful, state-of-the-art approach to mapping human disease genes. When a GWA study detects association between a SNP and the disease, this signal usually represents association with a set of several highly correlated SNPs in strong linkage disequilibrium. The challenge we address is to distinguish among these correlated loci to highlight potential functional variants and prioritize them for follow-up. We implemented a systematic method for testing association across diverse population samples having differing histories and LD patterns, using a logistic regression framework. The hypothesis is that important underlying biological mechanisms are shared across human populations, and we can filter correlated variants by testing for heterogeneity of genetic effects in different population samples. This approach formalizes the descriptive comparison of p-values that has typified similar cross-population fine-mapping studies to date. We applied this method to correlated SNPs in the cholinergic nicotinic receptor gene cluster CHRNA5-CHRNA3-CHRNB4, in a case-control study of cocaine dependence composed of 504 European-American and 583 African-American samples. Of the 10 SNPs genotyped in the r2 > or = 0.8 bin for rs16969968, three demonstrated significant cross-population heterogeneity and are filtered from priority follow-up; the remaining SNPs include rs16969968 (heterogeneity p = 0.75). Though the power to filter out rs16969968 is reduced due to the difference in allele frequency in the two groups, the results nevertheless focus attention on a smaller group of SNPs that includes the non-synonymous SNP rs16969968, which retains a similar effect size (odds ratio) across both population samples. Filtering out SNPs that demonstrate cross-population heterogeneity enriches for variants more likely to be important and causative. Our approach provides an important and effective tool to help interpret results from the many GWA studies now underway.
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Jensen, Majken K; Bartz, Traci M; Djoussé, Luc; Kizer, Jorge R; Zieman, Susan J; Rimm, Eric B; Siscovick, David S; Psaty, Bruce M; Ix, Joachim H; Mukamal, Kenneth J
2013-10-01
Fetuin-A levels are associated with higher risk of type 2 diabetes, but it is unknown if the association is causal. We investigated common (>5%) genetic variants in the fetuin-A gene (AHSG) fetuin-A levels, fasting glucose, and risk of type 2 diabetes. Genetic variation, fetuin-A levels, and fasting glucose were assessed in 2,893 Caucasian and 542 African American community-living individuals 65 years of age or older in 1992-1993. Common AHSG variants (rs4917 and rs2248690) were strongly associated with fetuin-A concentrations (P<0.0001). In analyses of 259 incident cases of type 2 diabetes, the single nucleotide polymorphisms (SNPs) were not associated with diabetes risk during follow-up and similar null associations were observed when 579 prevalent cases were included. As expected, higher fetuin-A levels were associated with higher fasting glucose concentrations (1.9 mg/dL [95% CI, 1.2-2.7] higher per SD in Caucasians), but Mendelian randomization analyses using both SNPs as unbiased proxies for measured fetuin-A did not support an association between genetically predicted fetuin-A levels and fasting glucose (-0.3 mg/dL [95% CI, -1.9 to 1.3] lower per SD in Caucasians). The difference between the associations of fasting glucose with actual and genetically predicted fetuin-A level was statistically significant (P=0.001). Results among the smaller sample of African Americans trended in similar directions but were statistically insignificant. Common variants in the AHSG gene are strongly associated with plasma fetuin-A concentrations, but not with risk of type 2 diabetes or glucose concentrations, raising the possibility that the association between fetuin-A and type 2 diabetes may not be causal.
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Welderufael, B. G.; Løvendahl, Peter; de Koning, Dirk-Jan; Janss, Lucas L. G.; Fikse, W. F.
2018-01-01
Because mastitis is very frequent and unavoidable, adding recovery information into the analysis for genetic evaluation of mastitis is of great interest from economical and animal welfare point of view. Here we have performed genome-wide association studies (GWAS) to identify associated single nucleotide polymorphisms (SNPs) and investigate the genetic background not only for susceptibility to – but also for recoverability from mastitis. Somatic cell count records from 993 Danish Holstein cows genotyped for a total of 39378 autosomal SNP markers were used for the association analysis. Single SNP regression analysis was performed using the statistical software package DMU. Substitution effect of each SNP was tested with a t-test and a genome-wide significance level of P-value < 10-4 was used to declare significant SNP-trait association. A number of significant SNP variants were identified for both traits. Many of the SNP variants associated either with susceptibility to – or recoverability from mastitis were located in or very near to genes that have been reported for their role in the immune system. Genes involved in lymphocyte developments (e.g., MAST3 and STAB2) and genes involved in macrophage recruitment and regulation of inflammations (PDGFD and PTX3) were suggested as possible causal genes for susceptibility to – and recoverability from mastitis, respectively. However, this is the first GWAS study for recoverability from mastitis and our results need to be validated. The findings in the current study are, therefore, a starting point for further investigations in identifying causal genetic variants or chromosomal regions for both susceptibility to – and recoverability from mastitis. PMID:29755506
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Rametta, Raffaela; Ruscica, Massimiliano; Dongiovanni, Paola; Macchi, Chiara; Fracanzani, Anna L; Steffani, Liliana; Fargion, Silvia; Magni, Paolo; Valenti, Luca
2014-07-01
Fetuin-A is a liver-derived peptide associated with insulin resistance. Aim of this cross-sectional study was to evaluate whether Fetuin-A is increased in patients with nonalcoholic fatty liver disease (NAFLD) vs. healthy subjects without metabolic abnormalities and the association with insulin resistance and liver damage. To investigate the causal relationship between fatty liver and Fetuin-A, we also analysed whether the inherited I148M PNPLA3 variant modulates Fetuin-A. In 137 patients with histological NAFLD, complete metabolic characterization, PNPLA3 genotype, and in 260 healthy subjects without metabolic alterations, Fetuin-A was measured by enzyme-linked immunoabsorbent assay. Serum Fetuin-A was higher in NAFLD patients than in controls (P < 0·0001), independently of age, sex, BMI, insulin resistance, dyslipidemia, adiponectin, PNPLA3 I148M and ALT levels (OR 1·006 95% CI 1·003-1·11; P = 0·003). In NAFLD patients, Fetuin-A was associated with steatosis severity (P = 0·03) and metabolic syndrome features, but not with hepatic inflammation. At multivariate analysis, Fetuin-A levels were associated with BMI, triglycerides, hyperglycemia and PNPLA3 I148M (P = 0·034) independently also of age, sex and ALT levels. As PNPLA3 I148M is a strong and inherited determinant of liver fat without affecting insulin resistance and lipid levels, these data suggest that steatosis has a causal role in determining serum Fetuin-A levels. Liver fat accumulation and the I148M variant of PNPLA3 are associated with serum Fetuin-A levels independently of insulin resistance. Fetuin-A may be implicated in the pathogenesis of metabolic complications associated with NAFLD. © 2014 Stichting European Society for Clinical Investigation Journal Foundation.
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Goharian, T S; Andersen, L B; Franks, P W; Wareham, N J; Brage, S; Veidebaum, T; Ekelund, U; Lawlor, D A; Loos, R J F; Grøntved, A
2015-03-01
The aim of the study was to determine whether genetically raised fasting glucose (FG) levels are associated with blood pressure (BP) in healthy children and adolescents. We used 11 common genetic variants of FG discovered in genome-wide association studies (GWAS), including the rs560887 single-nucleotide polymorphism (SNP) located in the G6PC2 locus found to be robustly associated with FG in children and adolescents, as an instrument to associate FG with resting BP in 1506 children and adolescents from the European Youth Heart Study (EYHS). Rs560887 was associated with increased FG levels corresponding to an increase of 0.08 mmol l(-1) (P=2.4 × 10(-8)). FG was associated with BP, independent of other important determinants of BP in conventional multivariable analysis (systolic BP z-score: 0.32 s.d. per increase in mmol l(-1) (95% confidence interval (CI) 0.20-0.44, P=1.9 × 10(-7)), diastolic BP z-score: 0.13 s.d. per increase in mmol l(-1) (95% CI 0.04-0.21, P=3.2 × 10(-3)). This association was not supported by the Mendelian randomization approach, neither from instrumenting FG from all 11 variants nor from the rs560887, where non-significant associations of glucose with BP were observed. The results of this study could not support a causal association between FG and BP in healthy children and adolescents; however, it is possible that rs560887 has pleiotropic effects on unknown factors with a BP lowering effect or that these results were due to a lack of statistical power.
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Lewis, Sarah J; Araya, Ricardo; Smith, George Davey; Freathy, Rachel; Gunnell, David; Palmer, Tom; Munafò, Marcus
2011-01-01
Smokers have a higher prevalence of major depressive episodes and depressive symptoms than the general population, but whether this association is causal, or is due to confounding or reverse causation is uncertain because of the problems inherent in some epidemiological studies. Mendelian randomization, in which a genetic variant is used as a surrogate for measuring exposure, is an approach which may be used to better understand this association. We investigated the rs1051730 single nucleotide polymorphism in the nicotine acetylcholine receptor gene cluster (CHRNA5-CHRNA3-CHRNB4), associated with smoking phenotypes, to determine whether women who continued to smoke were also more likely to report a low mood during pregnancy. We found among women who smoked pre-pregnancy, those with the 1051730 T allele smoked more and were less likely to quit smoking during pregnancy, but were also less likely to report high levels of depressed mood at 18 weeks of pregnancy (per allele OR = 0.84, 95%CI 0.72 to 0.99, p = 0.034). The association between genotype and depressed mood was limited to women who were smokers prior to pregnancy, with weak evidence of an interaction between smoking status and genotype (p = 0.07). Our results do not support a causal role of smoking on depressed mood, but are consistent with a self-medication hypothesis, whereby smoking is used to alleviate symptoms of depression. A replication study using multiple genetic variants which influence smoking via different pathways is required to confirm these findings and provide evidence that the genetic variant is reflecting the effect of quitting smoking on depressed mood, and is not directly affecting mood.
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Ricaño-Ponce, Isis; Zhernakova, Daria V; Deelen, Patrick; Luo, Oscar; Li, Xingwang; Isaacs, Aaron; Karjalainen, Juha; Di Tommaso, Jennifer; Borek, Zuzanna Agnieszka; Zorro, Maria M; Gutierrez-Achury, Javier; Uitterlinden, Andre G; Hofman, Albert; van Meurs, Joyce; Netea, Mihai G; Jonkers, Iris H; Withoff, Sebo; van Duijn, Cornelia M; Li, Yang; Ruan, Yijun; Franke, Lude; Wijmenga, Cisca; Kumar, Vinod
2016-04-01
Genome-wide association and fine-mapping studies in 14 autoimmune diseases (AID) have implicated more than 250 loci in one or more of these diseases. As more than 90% of AID-associated SNPs are intergenic or intronic, pinpointing the causal genes is challenging. We performed a systematic analysis to link 460 SNPs that are associated with 14 AID to causal genes using transcriptomic data from 629 blood samples. We were able to link 71 (39%) of the AID-SNPs to two or more nearby genes, providing evidence that for part of the AID loci multiple causal genes exist. While 54 of the AID loci are shared by one or more AID, 17% of them do not share candidate causal genes. In addition to finding novel genes such as ULK3, we also implicate novel disease mechanisms and pathways like autophagy in celiac disease pathogenesis. Furthermore, 42 of the AID SNPs specifically affected the expression of 53 non-coding RNA genes. To further understand how the non-coding genome contributes to AID, the SNPs were linked to functional regulatory elements, which suggest a model where AID genes are regulated by network of chromatin looping/non-coding RNAs interactions. The looping model also explains how a causal candidate gene is not necessarily the gene closest to the AID SNP, which was the case in nearly 50% of cases. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Mendelian randomisation in type 2 diabetes and coronary artery disease.
Frayling, Timothy M; Stoneman, Charli E
2018-06-20
Type 2 diabetes, coronary artery disease and hypertension are associated with anthropometric and biomarker traits, including waist-to-hip-ratio, body mass index and altered glucose and insulin levels. Clinical trials, for example of weight-loss interventions, show these factors are causal, but lifelong impact of subtle changes in body mass index and body fat distribution are less clear. The use of human genetics can quantify the causal effects of long-term exposure to subtle changes of modifiable risk factors. Mendelian randomisation (MR) uses human genetic variants associated with the risk factor to quantify the relationship between risk factor and disease outcome. The last two years have seen an increase in the number of MR studies investigating the relationship between anthropometric traits and metabolic diseases. This review provides an overview of these recent MR studies in relation to type 2 diabetes, coronary artery disease and hypertension. MR provides evidence for causal associations of waist-to-hip-ratio, body mass index and altered glucose levels with type 2 diabetes, coronary artery disease and hypertension. Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.
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Guillen-Ahlers, Hector; Erbe, Christy B; Chevalier, Frédéric D; Montoya, Maria J; Zimmerman, Kip D; Langefeld, Carl D; Olivier, Michael; Runge, Christina L
2018-04-19
Sensorineural hearing loss (SNHL) is a common form of hearing loss that can be inherited or triggered by environmental insults; auditory neuropathy spectrum disorder (ANSD) is a SNHL subtype with unique diagnostic criteria. The genetic factors associated with these impairments are vast and diverse, but causal genetic factors are rarely characterized. A family dyad, both cochlear implant recipients, presented with a hearing history of bilateral, progressive SNHL, and ANSD. Whole-exome sequencing was performed to identify coding sequence variants shared by both family members, and screened against genes relevant to hearing loss and variants known to be associated with SNHL and ANSD. Both family members are successful cochlear implant users, demonstrating effective auditory nerve stimulation with their devices. Genetic analyses revealed a mutation (rs35725509) in the TMTC2 gene, which has been reported previously as a likely genetic cause of SNHL in another family of Northern European descent. This study represents the first confirmation of the rs35725509 variant in an independent family as a likely cause for the complex hearing loss phenotype (SNHL and ANSD) observed in this family dyad. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.
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Verweij, Karin J.H.; Yang, Jian; Lahti, Jari; Veijola, Juha; Hintsanen, Mirka; Pulkki-Råback, Laura; Heinonen, Kati; Pouta, Anneli; Pesonen, Anu-Katriina; Widen, Elisabeth; Taanila, Anja; Isohanni, Matti; Miettunen, Jouko; Palotie, Aarno; Penke, Lars; Service, Susan K.; Heath, Andrew C.; Montgomery, Grant W.; Raitakari, Olli; Kähönen, Mika; Viikari, Jorma; Räikkönen, Katri; Eriksson, Johan G; Keltikangas-Järvinen, Liisa; Lehtimäki, Terho; Martin, Nicholas G.; Järvelin, Marjo-Riitta; Visscher, Peter M.; Keller, Matthew C.; Zietsch, Brendan P.
2012-01-01
Personality traits are basic dimensions of behavioural variation, and twin, family, and adoption studies show that around 30% of the between-individual variation is due to genetic variation. There is rapidly-growing interest in understanding the evolutionary basis of this genetic variation. Several evolutionary mechanisms could explain how genetic variation is maintained in traits, and each of these makes predictions in terms of the relative contribution of rare and common genetic variants to personality variation, the magnitude of nonadditive genetic influences, and whether personality is affected by inbreeding. Using genome-wide SNP data from >8,000 individuals, we estimated that little variation in the Cloninger personality dimensions (7.2% on average) is due to the combined effect of common, additive genetic variants across the genome, suggesting that most heritable variation in personality is due to rare variant effects and/or a combination of dominance and epistasis. Furthermore, higher levels of inbreeding were associated with less socially-desirable personality trait levels in three of the four personality dimensions. These findings are consistent with genetic variation in personality traits having been maintained by mutation-selection balance. PMID:23025612
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Volaki, Konstantina; Pampanos, Andreas; Kitsiou-Tzeli, Sophia; Vrettou, Christina; Oikonomakis, Vasilis; Sofocleous, Christalena; Kanavakis, Emmanuel
2013-10-01
Molecular and neurobiological evidence for the involvement of neuroligins (particularly NLGN3 and NLGN4X genes) in autistic disorder is accumulating. However, previous mutation screening studies on these two genes have yielded controversial results. The present study explores, for the first time, the contribution of NLGN3 and NLGN4X genetic variants in Greek patients with autistic disorder. We analyzed the full exonic sequence of NLGN3 and NLGN4X genes in 40 patients strictly fulfilling the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. criteria for autistic disorder. We identified nine nucleotide changes in NLGN4X--one probable causative mutation (p.K378R) previously reported by our research group, one novel variant (c.-206G>C), one nonvalidated single nucleotide polymorphism (SNP, rs111953947), and six known human SNPs reported in the SNP database--and one known human SNP in NLGN3 also reported in the SNP database. The variants identified are expected to be benign. However, they should be investigated in the context of variants in interacting cellular pathways to assess their contribution to the etiology of autism.
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Cortical Hierarchies Perform Bayesian Causal Inference in Multisensory Perception
Rohe, Tim; Noppeney, Uta
2015-01-01
To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the “causal inference problem.” Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI), and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation). At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion). Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world. PMID:25710328
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Dynamics of Quantum Causal Structures
NASA Astrophysics Data System (ADS)
Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav
2018-01-01
It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
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Large-scale sequencing efforts are uncovering the complexity of cancer genomes, which are composed of causal "driver" mutations that promote tumor progression along with many more pathologically neutral "passenger" events. The majority of mutations, both in known cancer drivers and uncharacterized genes, are generally of low occurrence, highlighting the need to functionally annotate the long tail of infrequent mutations present in heterogeneous cancers.
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Anand, Deepti; Agrawal, Smriti A; Slavotinek, Anne; Lachke, Salil A
2018-04-01
Mutations in the transcription factor genes FOXE3, HSF4, MAF, and PITX3 cause congenital lens defects including cataracts that may be accompanied by defects in other components of the eye or in nonocular tissues. We comprehensively describe here all the variants in FOXE3, HSF4, MAF, and PITX3 genes linked to human developmental defects. A total of 52 variants for FOXE3, 18 variants for HSF4, 20 variants for MAF, and 19 variants for PITX3 identified so far in isolated cases or within families are documented. This effort reveals FOXE3, HSF4, MAF, and PITX3 to have 33, 16, 18, and 7 unique causal mutations, respectively. Loss-of-function mutant animals for these genes have served to model the pathobiology of the associated human defects, and we discuss the currently known molecular function of these genes, particularly with emphasis on their role in ocular development. Finally, we make the detailed FOXE3, HSF4, MAF, and PITX3 variant information available in the Leiden Online Variation Database (LOVD) platform at https://www.LOVD.nl/FOXE3, https://www.LOVD.nl/HSF4, https://www.LOVD.nl/MAF, and https://www.LOVD.nl/PITX3. Thus, this article informs on key variants in transcription factor genes linked to cataract, aphakia, corneal opacity, glaucoma, microcornea, microphthalmia, anterior segment mesenchymal dysgenesis, and Ayme-Gripp syndrome, and facilitates their access through Web-based databases. © 2018 Wiley Periodicals, Inc.
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Dissociation Between APOC3 Variants, Hepatic Triglyceride Content and Insulin Resistance
Kozlitina, Julia; Boerwinkle, Eric; Cohen, Jonathan C; Hobbs, Helen H
2011-01-01
Nonalcoholic fatty liver disease (NAFLD) is an escalating health problem that is frequently associated with obesity and insulin resistance. The mechanistic relationship between NAFLD, obesity, and insulin resistance is not well understood. A nonsynonymous variant in patatin-like phospholipase domain containing 3 (rs738409, I148M) has been reproducibly associated with increased hepatic triglyceride content (HTGC) but has not been associated with either the body mass index (BMI) or indices of insulin resistance. Conversely, two sequence variants in apolipoprotein C3 (APOC3) that have been linked to hypertriglyceridemia (rs2854117 C > T and rs2854116 T > C) have recently been reported to be associated with both hepatic fat content and insulin resistance. Here we genotyped two APOC3 variants in 1228 African Americans, 843 European Americans and 426 Hispanics from a multiethnic population based study, the Dallas Heart Study and test for association with HTGC and homeostatic model of insulin resistance (HOMA-IR). We also examined the relationship between these two variants and HOMA-IR in the Atherosclerosis Risk in Communities (ARIC) study. No significant difference in hepatic fat content was found between carriers and noncarriers in the Dallas Heart Study. Neither APOC3 variant was associated with HOMA-IR in the Dallas Heart Study; this lack of association was confirmed in the ARIC study, even after the analysis was restricted to lean (BMI < 25 kg/m2) individuals (n = 4399). Conclusion: Our data do not support a causal relationship between these two variants in APOC3 and either HTGC or insulin resistance in middle-aged men and women. (Hepatology 2011;53:467-474) PMID:21274868
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Huang, Lei; Kang, Wenjun; Bartom, Elizabeth; Onel, Kenan; Volchenboum, Samuel; Andrade, Jorge
2015-01-01
Whole exome sequencing has facilitated the discovery of causal genetic variants associated with human diseases at deep coverage and low cost. In particular, the detection of somatic mutations from tumor/normal pairs has provided insights into the cancer genome. Although there is an abundance of publicly-available software for the detection of germline and somatic variants, concordance is generally limited among variant callers and alignment algorithms. Successful integration of variants detected by multiple methods requires in-depth knowledge of the software, access to high-performance computing resources, and advanced programming techniques. We present ExScalibur, a set of fully automated, highly scalable and modulated pipelines for whole exome data analysis. The suite integrates multiple alignment and variant calling algorithms for the accurate detection of germline and somatic mutations with close to 99% sensitivity and specificity. ExScalibur implements streamlined execution of analytical modules, real-time monitoring of pipeline progress, robust handling of errors and intuitive documentation that allows for increased reproducibility and sharing of results and workflows. It runs on local computers, high-performance computing clusters and cloud environments. In addition, we provide a data analysis report utility to facilitate visualization of the results that offers interactive exploration of quality control files, read alignment and variant calls, assisting downstream customization of potential disease-causing mutations. ExScalibur is open-source and is also available as a public image on Amazon cloud. PMID:26271043
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
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TCIRG1-associated congenital neutropenia.
Makaryan, Vahagn; Rosenthal, Elisabeth A; Bolyard, Audrey Anna; Kelley, Merideth L; Below, Jennifer E; Bamshad, Michael J; Bofferding, Kathryn M; Smith, Joshua D; Buckingham, Kati; Boxer, Laurence A; Skokowa, Julia; Welte, Karl; Nickerson, Deborah A; Jarvik, Gail P; Dale, David C
2014-07-01
Severe congenital neutropenia (SCN) is a rare hematopoietic disorder, with estimated incidence of 1 in 200,000 individuals of European descent, many cases of which are inherited in an autosomal dominant pattern. Despite the fact that several causal genes have been identified, the genetic basis for >30% of cases remains unknown. We report a five-generation family segregating a novel single nucleotide variant (SNV) in TCIRG1. There is perfect cosegregation of the SNV with congenital neutropenia in this family; all 11 affected, but none of the unaffected, individuals carry this novel SNV. Western blot analysis show reduced levels of TCIRG1 protein in affected individuals, compared to healthy controls. Two unrelated patients with SCN, identified by independent investigators, are heterozygous for different, rare, highly conserved, coding variants in TCIRG1. © 2014 WILEY PERIODICALS, INC.
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Imm, Jennifer; Kerrigan, Talitha L; Jeffries, Aaron; Lunnon, Katie
2017-11-01
It is thought that both genetic and epigenetic variation play a role in Alzheimer's disease initiation and progression. With the advent of somatic cell reprogramming into induced pluripotent stem cells it is now possible to generate patient-derived cells that are able to more accurately model and recapitulate disease. Furthermore, by combining this with recent advances in (epi)genome editing technologies, it is possible to begin to examine the functional consequence of previously nominated genetic variants and infer epigenetic causality from recently identified epigenetic variants. In this review, we explore the role of genetic and epigenetic variation in Alzheimer's disease and how the functional relevance of nominated loci can be investigated using induced pluripotent stem cells and (epi)genome editing techniques.
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TCIRG1 associated Congenital Neutropenia
Makaryan, Vahagn; Rosenthal, Elisabeth A.; Bolyard, Audrey Anna; Kelley, Merideth L.; Below, Jennifer E.; Bamshad, Michael J.; Bofferding, Kathryn M.; Smith, Joshua D.; Buckingham, Kati; Boxer, Laurence A.; Skokowa, Julia; Welte, Karl; Nickerson, Deborah A.; Jarvik, Gail P.; Dale, David C.
2014-01-01
Severe congenital neutropenia (SCN) is a rare hematopoietic disorder, with estimated incidence of 1 in 200,000 individuals of European descent, many cases of which are inherited in an autosomal dominant pattern. Despite the fact that several causal genes have been identified, the genetic basis for >30% of cases remains unknown. We report a five generation family segregating a novel single nucleotide variant (SNV) in TCIRG1. There is perfect co-segregation of the SNV with congenital neutropenia in this family; all 11 affected, but none of the unaffected, individuals carry this novel SNV. Western blot analysis show reduced levels of TCIRG1 protein in affected individuals, compared to healthy controls. Two unrelated patients with SCN, identified by independent investigators, are heterozygous for different, rare, highly conserved, coding variants in TCIRG1. PMID:24753205
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Kos, M Z; Yan, J; Dick, D M; Agrawal, A; Bucholz, K K; Rice, J P; Johnson, E O; Schuckit, M; Kuperman, S; Kramer, J; Goate, A M; Tischfield, J A; Foroud, T; Nurnberger, J; Hesselbrock, V; Porjesz, B; Bierut, L J; Edenberg, H J; Almasy, L
2013-07-01
Alcohol dependence (AD) is a heritable substance addiction with adverse physical and psychological consequences, representing a major health and economic burden on societies worldwide. Genes thus far implicated via linkage, candidate gene and genome-wide association studies (GWAS) account for only a small fraction of its overall risk, with effects varying across ethnic groups. Here we investigate the genetic architecture of alcoholism and report on the extent to which common, genome-wide SNPs collectively account for risk of AD in two US populations, African-Americans (AAs) and European-Americans (EAs). Analyzing GWAS data for two independent case-control sample sets, we compute polymarker scores that are significantly associated with alcoholism (P = 1.64 × 10(-3) and 2.08 × 10(-4) for EAs and AAs, respectively), reflecting the small individual effects of thousands of variants derived from patterns of allelic architecture that are population specific. Simulations show that disease models based on rare and uncommon causal variants (MAF < 0.05) best fit the observed distribution of polymarker signals. When scoring bins were annotated for gene location and examined for constituent biological networks, gene enrichment is observed for several cellular processes and functions in both EA and AA populations, transcending their underlying allelic differences. Our results reveal key insights into the complex etiology of AD, raising the possibility of an important role for rare and uncommon variants, and identify polygenic mechanisms that encompass a spectrum of disease liability, with some, such as chloride transporters and glycine metabolism genes, displaying subtle, modifying effects that are likely to escape detection in most GWAS designs. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
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Exome sequencing in Thai patients with familial obesity.
Kaewsutthi, S; Santiprabhob, J; Phonrat, B; Tungtrongchitr, A; Lertrit, P; Tungtrongchitr, R
2016-07-14
Obesity is a major worldwide health issue, with increasing prevalence in adults and children from developed and developing countries. Obesity causes several chronic diseases, including cardiovascular and respiratory diseases, osteoarthritis, hypertension, stroke, type II diabetes, obstructive sleep apnea, and several types of cancer. Previous genome-wide association studies have identified several genes associated with obesity, including LEP, LEPR, POMC, PCSK1, FTO, MC3R, MC4R, GNPDA2, TMEM18, QPCTL/GIPR, BDNF, ETV5, MAP2K5/SKOR1, SEC16B, SIM1, and TNKS/MSRA. However, most of these variants are found in the intronic or intergenic regions, making it difficult to elucidate the underlying mechanisms. Therefore, in this study, we performed a whole exome sequencing of the protein-coding regions in the total genome (exome) of two obese and one normal subject belonging to the same Thai family to identify the genes responsible for obesity. We identified 709 functional variants that were differentially expressed between obese and normal subjects; of these, 65 were predicted to be deleterious to protein structure or function. The minor allele frequency of 14 of these genes (ALOX5AP, COL9A2, DEFB126, GDPD4, HCRTR1, MLL3, OPLAH, OR4C45, PRIM2, RXFP2, TIGD6, TRPM8, USP49, and ZNF596) was low, indicating causal variants that could be associated with complex traits or diseases. Genotyping revealed HCRTR1, COL9A2, and TRPM8 to be associated with the regulation of feeding behavior and energy expenditure. These genes constituted a network of pathways, including lipid metabolism, signaling transduction, immune, membrane transport, and gene regulation pathways, and seemed to play important roles in obesity.
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Brenner, Darren R.; Amos, Christopher I.; Brhane, Yonathan; Timofeeva, Maria N.; Caporaso, Neil; Wang, Yufei; Christiani, David C.; Bickeböller, Heike; Yang, Ping; Albanes, Demetrius; Stevens, Victoria L.; Gapstur, Susan; McKay, James; Boffetta, Paolo; Zaridze, David; Szeszenia-Dabrowska, Neonilia; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Krokan, Hans E.; Skorpen, Frank; Gabrielsen, Maiken E.; Vatten, Lars; Njølstad, Inger; Chen, Chu; Goodman, Gary; Lathrop, Mark; Vooder, Tõnu; Välk, Kristjan; Nelis, Mari; Metspalu, Andres; Broderick, Peter; Eisen, Timothy; Wu, Xifeng; Zhang, Di; Chen, Wei; Spitz, Margaret R.; Wei, Yongyue; Su, Li; Xie, Dong; She, Jun; Matsuo, Keitaro; Matsuda, Fumihiko; Ito, Hidemi; Risch, Angela; Heinrich, Joachim; Rosenberger, Albert; Muley, Thomas; Dienemann, Hendrik; Field, John K.; Raji, Olaide; Chen, Ying; Gosney, John; Liloglou, Triantafillos; Davies, Michael P.A.; Marcus, Michael; McLaughlin, John; Orlow, Irene; Han, Younghun; Li, Yafang; Zong, Xuchen; Johansson, Mattias; Liu, Geoffrey; Tworoger, Shelley S.; Le Marchand, Loic; Henderson, Brian E.; Wilkens, Lynne R.; Dai, Juncheng; Shen, Hongbing; Houlston, Richard S.; Landi, Maria T.; Brennan, Paul; Hung, Rayjean J.
2015-01-01
Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10−8) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10−7) and MTMR2 at 11q21 (rs10501831, P = 3.1×10−6) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10−7) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10−4 for KCNIP4, represented by rs9799795) and AC (P = 2.16×10−4 for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range. PMID:26363033
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Brenner, Darren R; Amos, Christopher I; Brhane, Yonathan; Timofeeva, Maria N; Caporaso, Neil; Wang, Yufei; Christiani, David C; Bickeböller, Heike; Yang, Ping; Albanes, Demetrius; Stevens, Victoria L; Gapstur, Susan; McKay, James; Boffetta, Paolo; Zaridze, David; Szeszenia-Dabrowska, Neonilia; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Mates, Dana; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Krokan, Hans E; Skorpen, Frank; Gabrielsen, Maiken E; Vatten, Lars; Njølstad, Inger; Chen, Chu; Goodman, Gary; Lathrop, Mark; Vooder, Tõnu; Välk, Kristjan; Nelis, Mari; Metspalu, Andres; Broderick, Peter; Eisen, Timothy; Wu, Xifeng; Zhang, Di; Chen, Wei; Spitz, Margaret R; Wei, Yongyue; Su, Li; Xie, Dong; She, Jun; Matsuo, Keitaro; Matsuda, Fumihiko; Ito, Hidemi; Risch, Angela; Heinrich, Joachim; Rosenberger, Albert; Muley, Thomas; Dienemann, Hendrik; Field, John K; Raji, Olaide; Chen, Ying; Gosney, John; Liloglou, Triantafillos; Davies, Michael P A; Marcus, Michael; McLaughlin, John; Orlow, Irene; Han, Younghun; Li, Yafang; Zong, Xuchen; Johansson, Mattias; Liu, Geoffrey; Tworoger, Shelley S; Le Marchand, Loic; Henderson, Brian E; Wilkens, Lynne R; Dai, Juncheng; Shen, Hongbing; Houlston, Richard S; Landi, Maria T; Brennan, Paul; Hung, Rayjean J
2015-11-01
Large-scale genome-wide association studies (GWAS) have likely uncovered all common variants at the GWAS significance level. Additional variants within the suggestive range (0.0001> P > 5×10(-8)) are, however, still of interest for identifying causal associations. This analysis aimed to apply novel variant prioritization approaches to identify additional lung cancer variants that may not reach the GWAS level. Effects were combined across studies with a total of 33456 controls and 6756 adenocarcinoma (AC; 13 studies), 5061 squamous cell carcinoma (SCC; 12 studies) and 2216 small cell lung cancer cases (9 studies). Based on prior information such as variant physical properties and functional significance, we applied stratified false discovery rates, hierarchical modeling and Bayesian false discovery probabilities for variant prioritization. We conducted a fine mapping analysis as validation of our methods by examining top-ranking novel variants in six independent populations with a total of 3128 cases and 2966 controls. Three novel loci in the suggestive range were identified based on our Bayesian framework analyses: KCNIP4 at 4p15.2 (rs6448050, P = 4.6×10(-7)) and MTMR2 at 11q21 (rs10501831, P = 3.1×10(-6)) with SCC, as well as GAREM at 18q12.1 (rs11662168, P = 3.4×10(-7)) with AC. Use of our prioritization methods validated two of the top three loci associated with SCC (P = 1.05×10(-4) for KCNIP4, represented by rs9799795) and AC (P = 2.16×10(-4) for GAREM, represented by rs3786309) in the independent fine mapping populations. This study highlights the utility of using prior functional data for sequence variants in prioritization analyses to search for robust signals in the suggestive range. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Deep Sequencing of 71 Candidate Genes to Characterize Variation Associated with Alcohol Dependence.
Clark, Shaunna L; McClay, Joseph L; Adkins, Daniel E; Kumar, Gaurav; Aberg, Karolina A; Nerella, Srilaxmi; Xie, Linying; Collins, Ann L; Crowley, James J; Quackenbush, Corey R; Hilliard, Christopher E; Shabalin, Andrey A; Vrieze, Scott I; Peterson, Roseann E; Copeland, William E; Silberg, Judy L; McGue, Matt; Maes, Hermine; Iacono, William G; Sullivan, Patrick F; Costello, Elizabeth J; van den Oord, Edwin J
2017-04-01
Previous genomewide association studies (GWASs) have identified a number of putative risk loci for alcohol dependence (AD). However, only a few loci have replicated and these replicated variants only explain a small proportion of AD risk. Using an innovative approach, the goal of this study was to generate hypotheses about potentially causal variants for AD that can be explored further through functional studies. We employed targeted capture of 71 candidate loci and flanking regions followed by next-generation deep sequencing (mean coverage 78X) in 806 European Americans. Regions included in our targeted capture library were genes identified through published GWAS of alcohol, all human alcohol and aldehyde dehydrogenases, reward system genes including dopaminergic and opioid receptors, prioritized candidate genes based on previous associations, and genes involved in the absorption, distribution, metabolism, and excretion of drugs. We performed single-locus tests to determine if any single variant was associated with AD symptom count. Sets of variants that overlapped with biologically meaningful annotations were tested for association in aggregate. No single, common variant was significantly associated with AD in our study. We did, however, find evidence for association with several variant sets. Two variant sets were significant at the q-value <0.10 level: a genic enhancer for ADHFE1 (p = 1.47 × 10 -5 ; q = 0.019), an alcohol dehydrogenase, and ADORA1 (p = 5.29 × 10 -5 ; q = 0.035), an adenosine receptor that belongs to a G-protein-coupled receptor gene family. To our knowledge, this is the first sequencing study of AD to examine variants in entire genes, including flanking and regulatory regions. We found that in addition to protein coding variant sets, regulatory variant sets may play a role in AD. From these findings, we have generated initial functional hypotheses about how these sets may influence AD. Copyright © 2017 by the Research Society on Alcoholism.
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Rare ADH Variant Constellations are Specific for Alcohol Dependence
Zuo, Lingjun; Zhang, Heping; Malison, Robert T.; Li, Chiang-Shan R.; Zhang, Xiang-Yang; Wang, Fei; Lu, Lingeng; Lu, Lin; Wang, Xiaoping; Krystal, John H.; Zhang, Fengyu; Deng, Hong-Wen; Luo, Xingguang
2013-01-01
Aims: Some of the well-known functional alcohol dehydrogenase (ADH) gene variants (e.g. ADH1B*2, ADH1B*3 and ADH1C*2) that significantly affect the risk of alcohol dependence are rare variants in most populations. In the present study, we comprehensively examined the associations between rare ADH variants [minor allele frequency (MAF) <0.05] and alcohol dependence, with several other neuropsychiatric and neurological disorders as reference. Methods: A total of 49,358 subjects in 22 independent cohorts with 11 different neuropsychiatric and neurological disorders were analyzed, including 3 cohorts with alcohol dependence. The entire ADH gene cluster (ADH7–ADH1C–ADH1B–ADH1A–ADH6–ADH4–ADH5 at Chr4) was imputed in all samples using the same reference panels that included whole-genome sequencing data. We stringently cleaned the phenotype and genotype data to obtain a total of 870 single nucleotide polymorphisms with 0< MAF <0.05 for association analysis. Results: We found that a rare variant constellation across the entire ADH gene cluster was significantly associated with alcohol dependence in European-Americans (Fp1: simulated global P = 0.045), European-Australians (Fp5: global P = 0.027; collapsing: P = 0.038) and African-Americans (Fp5: global P = 0.050; collapsing: P = 0.038), but not with any other neuropsychiatric disease. Association signals in this region came principally from ADH6, ADH7, ADH1B and ADH1C. In particular, a rare ADH6 variant constellation showed a replicable association with alcohol dependence across these three independent cohorts. No individual rare variants were statistically significantly associated with any disease examined after group- and region-wide correction for multiple comparisons. Conclusion: We conclude that rare ADH variants are specific for alcohol dependence. The ADH gene cluster may harbor a causal variant(s) for alcohol dependence. PMID:23019235
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Dobbyn, Amanda; Huckins, Laura M; Boocock, James; Sloofman, Laura G; Glicksberg, Benjamin S; Giambartolomei, Claudia; Hoffman, Gabriel E; Perumal, Thanneer M; Girdhar, Kiran; Jiang, Yan; Raj, Towfique; Ruderfer, Douglas M; Kramer, Robin S; Pinto, Dalila; Akbarian, Schahram; Roussos, Panos; Domenici, Enrico; Devlin, Bernie; Sklar, Pamela; Stahl, Eli A; Sieberts, Solveig K
2018-06-07
Causal genes and variants within genome-wide association study (GWAS) loci can be identified by integrating GWAS statistics with expression quantitative trait loci (eQTL) and determining which variants underlie both GWAS and eQTL signals. Most analyses, however, consider only the marginal eQTL signal, rather than dissect this signal into multiple conditionally independent signals for each gene. Here we show that analyzing conditional eQTL signatures, which could be important under specific cellular or temporal contexts, leads to improved fine mapping of GWAS associations. Using genotypes and gene expression levels from post-mortem human brain samples (n = 467) reported by the CommonMind Consortium (CMC), we find that conditional eQTL are widespread; 63% of genes with primary eQTL also have conditional eQTL. In addition, genomic features associated with conditional eQTL are consistent with context-specific (e.g., tissue-, cell type-, or developmental time point-specific) regulation of gene expression. Integrating the 2014 Psychiatric Genomics Consortium schizophrenia (SCZ) GWAS and CMC primary and conditional eQTL data reveals 40 loci with strong evidence for co-localization (posterior probability > 0.8), including six loci with co-localization of conditional eQTL. Our co-localization analyses support previously reported genes, identify novel genes associated with schizophrenia risk, and provide specific hypotheses for their functional follow-up. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
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Detectability of Granger causality for subsampled continuous-time neurophysiological processes.
Barnett, Lionel; Seth, Anil K
2017-01-01
Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity from neurophysiological recordings. Copyright © 2016 Elsevier B.V. All rights reserved.
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Xie, Weijia; Wood, Andrew R; Lyssenko, Valeriya; Weedon, Michael N; Knowles, Joshua W; Alkayyali, Sami; Assimes, Themistocles L; Quertermous, Thomas; Abbasi, Fahim; Paananen, Jussi; Häring, Hans; Hansen, Torben; Pedersen, Oluf; Smith, Ulf; Laakso, Markku; Dekker, Jacqueline M; Nolan, John J; Groop, Leif; Ferrannini, Ele; Adam, Klaus-Peter; Gall, Walter E; Frayling, Timothy M; Walker, Mark
2013-06-01
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity-related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites-glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)-and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits.
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Xie, Weijia; Wood, Andrew R.; Lyssenko, Valeriya; Weedon, Michael N.; Knowles, Joshua W.; Alkayyali, Sami; Assimes, Themistocles L.; Quertermous, Thomas; Abbasi, Fahim; Paananen, Jussi; Häring, Hans; Hansen, Torben; Pedersen, Oluf; Smith, Ulf; Laakso, Markku; Dekker, Jacqueline M.; Nolan, John J.; Groop, Leif; Ferrannini, Ele; Adam, Klaus-Peter; Gall, Walter E.; Frayling, Timothy M.; Walker, Mark
2013-01-01
Circulating metabolites associated with insulin sensitivity may represent useful biomarkers, but their causal role in insulin sensitivity and diabetes is less certain. We previously identified novel metabolites correlated with insulin sensitivity measured by the hyperinsulinemic-euglycemic clamp. The top-ranking metabolites were in the glutathione and glycine biosynthesis pathways. We aimed to identify common genetic variants associated with metabolites in these pathways and test their role in insulin sensitivity and type 2 diabetes. With 1,004 nondiabetic individuals from the RISC study, we performed a genome-wide association study (GWAS) of 14 insulin sensitivity–related metabolites and one metabolite ratio. We replicated our results in the Botnia study (n = 342). We assessed the association of these variants with diabetes-related traits in GWAS meta-analyses (GENESIS [including RISC, EUGENE2, and Stanford], MAGIC, and DIAGRAM). We identified four associations with three metabolites—glycine (rs715 at CPS1), serine (rs478093 at PHGDH), and betaine (rs499368 at SLC6A12; rs17823642 at BHMT)—and one association signal with glycine-to-serine ratio (rs1107366 at ALDH1L1). There was no robust evidence for association between these variants and insulin resistance or diabetes. Genetic variants associated with genes in the glycine biosynthesis pathways do not provide consistent evidence for a role of glycine in diabetes-related traits. PMID:23378610
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Wium-Andersen, Marie Kim; Ørsted, David Dynnes; Tolstrup, Janne Schurmann; Nordestgaard, Børge Grønne
2015-04-01
Increased alcohol consumption has been associated with depression and alcoholism, but whether these associations are causal remains unclear. We tested whether alcohol consumption is causally associated with depression and alcoholism. We included 78,154 men and women aged 20-100 years randomly selected in 1991-2010 from the general population of Copenhagen, Denmark, and genotyped 68,486 participants for two genetic variants in two alcohol dehydrogenase (ADH) genes, ADH-1B (rs1229984) and ADH-1C (rs698). We performed observational and causal analyses using a Mendelian randomization design with antidepressant medication use and hospitalization/death, with depression and alcoholism as outcomes. In prospective analyses, the multifactorially adjusted hazard ratio for participants reporting >6 drinks/day vs participants reporting 0.1-1 drinks/day was 1.28 (95% confidence interval, 1.00-1.65) for prescription antidepressant use, with a corresponding hazard ratio of 0.80 (0.45-1.45) for hospitalization/death with depression and of 11.7 (8.77-15.6) for hospitalization/death with alcoholism. For hospitalization/death with alcoholism, instrumental variable analysis yielded a causal odds ratio of 28.6 (95 % confidence interval 6.47-126) for an increase of 1 drink/day estimated from the combined genotype combination, whereas the corresponding multifactorially adjusted observational odds ratio was 1.28 (1.25-1.31). Corresponding odds ratios were 1.11 (0.67-1.83) causal and 1.04 (1.03-1.06) observational for prescription antidepressant use, and 4.52 (0.99-20.5) causal and 0.98 (0.94-1.03) observational for hospitalization/death with depression. These data indicate that the association between increased alcohol consumption and alcoholism is causal, without similar strong evidence for depression. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Shift-Variant Multidimensional Systems.
1985-05-29
i=0,1,** *N-1 in (3.1), one will get 0() i_0,1,* ,N-1 which is nonnegative due to the Perron - Frobenius Theorem [24]. That is, the A nonnegativity ...and the current input. The state-space model was extended in order to model 2-D discrete LSV systems with support on a causality cone . Subsequently...formulated as a special system of linear equations with nonnegative coefficients whose solution is required to satisfy con- straints like nonnegativity in
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FamLBL: detecting rare haplotype disease association based on common SNPs using case-parent triads.
Wang, Meng; Lin, Shili
2014-09-15
In recent years, there has been an increasing interest in using common single-nucleotide polymorphisms (SNPs) amassed in genome-wide association studies to investigate rare haplotype effects on complex diseases. Evidence has suggested that rare haplotypes may tag rare causal single-nucleotide variants, making SNP-based rare haplotype analysis not only cost effective, but also more valuable for detecting causal variants. Although a number of methods for detecting rare haplotype association have been proposed in recent years, they are population based and thus susceptible to population stratification. We propose family-triad-based logistic Bayesian Lasso (famLBL) for estimating effects of haplotypes on complex diseases using SNP data. By choosing appropriate prior distribution, effect sizes of unassociated haplotypes can be shrunk toward zero, allowing for more precise estimation of associated haplotypes, especially those that are rare, thereby achieving greater detection power. We evaluate famLBL using simulation to gauge its type I error and power. Compared with its population counterpart, LBL, highlights famLBL's robustness property in the presence of population substructure. Further investigation by comparing famLBL with Family-Based Association Test (FBAT) reveals its advantage for detecting rare haplotype association. famLBL is implemented as an R-package available at http://www.stat.osu.edu/∼statgen/SOFTWARE/LBL/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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Exploring the Epileptic Brain Network Using Time-Variant Effective Connectivity and Graph Theory.
Storti, Silvia Francesca; Galazzo, Ilaria Boscolo; Khan, Sehresh; Manganotti, Paolo; Menegaz, Gloria
2017-09-01
The application of time-varying measures of causality between source time series can be very informative to elucidate the direction of communication among the regions of an epileptic brain. The aim of the study was to identify the dynamic patterns of epileptic networks in focal epilepsy by applying multivariate adaptive directed transfer function (ADTF) analysis and graph theory to high-density electroencephalographic recordings. The cortical network was modeled after source reconstruction and topology modulations were detected during interictal spikes. First a distributed linear inverse solution, constrained to the individual grey matter, was applied to the averaged spikes and the mean source activity over 112 regions, as identified by the Harvard-Oxford Atlas, was calculated. Then, the ADTF, a dynamic measure of causality, was used to quantify the connectivity strength between pairs of regions acting as nodes in the graph, and the measure of node centrality was derived. The proposed analysis was effective in detecting the focal regions as well as in characterizing the dynamics of the spike propagation, providing evidence of the fact that the node centrality is a reliable feature for the identification of the epileptogenic zones. Validation was performed by multimodal analysis as well as from surgical outcomes. In conclusion, the time-variant connectivity analysis applied to the epileptic patients can distinguish the generator of the abnormal activity from the propagation spread and identify the connectivity pattern over time.
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Analysis of MSH3 in endometrial cancers with defective DNA mismatch repair.
Swisher, E M; Mutch, D G; Herzog, T J; Rader, J S; Kowalski, L D; Elbendary, A; Goodfellow, P J
1998-01-01
To clarify the origin of defective mismatch repair (MMR) in sporadic endometrial cancers with microsatellite instability (MSI), a thorough mutation analysis was performed on the human mismatch repair gene MSH3. Twenty-eight MSI-positive endometrial cancers were investigated for mutations in the human mismatch repair gene MSH3 using single-strand conformation variant (SSCV) analysis of all 24 exons. All variants were sequenced. Loss of heterozygosity was investigated at all MSH3 polymorphisms discovered. A subset of tumors were investigated for methylation of the 5' promoter region of MSH3 using Southern blot hybridization. An identical single-base deletion (delta A) predicted to result in a truncated proteins was discovered in six tumors (21.4%). This deletion occurs in a string of eight consecutive adenosine residues (A8). Because simple repeat sequences are unstable in cells with defective MMR, the observed mutation may be an effect, rather than a cause, of MSI. Evidence of inactivation of the second MSH3 allele in tumors with the delta A mutation would strongly support a causal role for these MSH3 mutations. However, there was no evidence of a second mutation, loss of sequences, or methylation of the promoter region in any of the tumors with the delta A mutation. Although the delta A mutation is a frequent event in sporadic MSI-positive endometrial cancers, it may not be causally associated with defective DNA MMR.
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Kwok, Chun T; Morris, Alex; de Belleroche, Jacqueline S
2014-04-01
Mutations in the SQSTM1 gene have been reported to be associated with amyotrophic lateral sclerosis (ALS). We sought to determine the frequency of these mutations in a UK familial ALS (FALS) cohort. Sequences of all eight exons of the SQSTM1 gene were analysed in index cases from 61 different FALS kindred lacking known FALS mutations. Six exonic variants c.463G>A, p.(Glu155Lys), c.822G>C, p.(Glu274Asp), c.888G>T, p.(=), c.954C>T, p.(=), c.1038G>A, p.(=) and c.1175C>T, p.(Pro392Leu) were identified in five FALS index cases, three of which were non-synonymous and three were synonymous. One index case harboured three variants (c.822G>C, c.888G>T and c.954C>T), and a second index case harboured two variants (c.822G>C and c.954C>T). Only the p.(Pro392Leu) and p.(Glu155Lys) mutations were predicted to be pathogenic. In one p.(Pro392Leu) kindred, the carrier developed both ALS and Paget's disease of bone (PDB), and, in the p.(Glu155Lys) kindred, the father of the proband developed PDB. All p.(Pro392Leu) carriers were heterozygous for a previously reported founder haplotype for PDB, where this mutation has an established causal effect. The frequency of the p.(Pro392Leu) mutation in this UK FALS cohort was 2.3% and 0.97% overall including three previously screened FALS cohorts. Our results confirm the presence of the p.(Pro392Leu) SQSTM1 mutation in FALS. This mutation is the most common SQSTM1 mutation found in ALS to date, and a likely pathogenicity is supported by having an established causal role in PDB. The occurrence of the same mutation in ALS and PDB is indicative of a common pathogenic pathway that converges on protein homeostasis.
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A quantum causal discovery algorithm
NASA Astrophysics Data System (ADS)
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
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Instrumental Variable Analysis with a Nonlinear Exposure–Outcome Relationship
Davies, Neil M.; Thompson, Simon G.
2014-01-01
Background: Instrumental variable methods can estimate the causal effect of an exposure on an outcome using observational data. Many instrumental variable methods assume that the exposure–outcome relation is linear, but in practice this assumption is often in doubt, or perhaps the shape of the relation is a target for investigation. We investigate this issue in the context of Mendelian randomization, the use of genetic variants as instrumental variables. Methods: Using simulations, we demonstrate the performance of a simple linear instrumental variable method when the true shape of the exposure–outcome relation is not linear. We also present a novel method for estimating the effect of the exposure on the outcome within strata of the exposure distribution. This enables the estimation of localized average causal effects within quantile groups of the exposure or as a continuous function of the exposure using a sliding window approach. Results: Our simulations suggest that linear instrumental variable estimates approximate a population-averaged causal effect. This is the average difference in the outcome if the exposure for every individual in the population is increased by a fixed amount. Estimates of localized average causal effects reveal the shape of the exposure–outcome relation for a variety of models. These methods are used to investigate the relations between body mass index and a range of cardiovascular risk factors. Conclusions: Nonlinear exposure–outcome relations should not be a barrier to instrumental variable analyses. When the exposure–outcome relation is not linear, either a population-averaged causal effect or the shape of the exposure–outcome relation can be estimated. PMID:25166881
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Rare Coding Variants in ANGPTL6 Are Associated with Familial Forms of Intracranial Aneurysm.
Bourcier, Romain; Le Scouarnec, Solena; Bonnaud, Stéphanie; Karakachoff, Matilde; Bourcereau, Emmanuelle; Heurtebise-Chrétien, Sandrine; Menguy, Céline; Dina, Christian; Simonet, Floriane; Moles, Alexis; Lenoble, Cédric; Lindenbaum, Pierre; Chatel, Stéphanie; Isidor, Bertrand; Génin, Emmanuelle; Deleuze, Jean-François; Schott, Jean-Jacques; Le Marec, Hervé; Loirand, Gervaise; Desal, Hubert; Redon, Richard
2018-01-04
Intracranial aneurysms (IAs) are acquired cerebrovascular abnormalities characterized by localized dilation and wall thinning in intracranial arteries, possibly leading to subarachnoid hemorrhage and severe outcome in case of rupture. Here, we identified one rare nonsense variant (c.1378A>T) in the last exon of ANGPTL6 (Angiopoietin-Like 6)-which encodes a circulating pro-angiogenic factor mainly secreted from the liver-shared by the four tested affected members of a large pedigree with multiple IA-affected case subjects. We showed a 50% reduction of ANGPTL6 serum concentration in individuals heterozygous for the c.1378A>T allele (p.Lys460Ter) compared to relatives homozygous for the normal allele, probably due to the non-secretion of the truncated protein produced by the c.1378A>T transcripts. Sequencing ANGPTL6 in a series of 94 additional index case subjects with familial IA identified three other rare coding variants in five case subjects. Overall, we detected a significant enrichment (p = 0.023) in rare coding variants within this gene among the 95 index case subjects with familial IA, compared to a reference population of 404 individuals with French ancestry. Among the 6 recruited families, 12 out of 13 (92%) individuals carrying IA also carry such variants in ANGPTL6, versus 15 out of 41 (37%) unaffected ones. We observed a higher rate of individuals with a history of high blood pressure among affected versus healthy individuals carrying ANGPTL6 variants, suggesting that ANGPTL6 could trigger cerebrovascular lesions when combined with other risk factors such as hypertension. Altogether, our results indicate that rare coding variants in ANGPTL6 are causally related to familial forms of IA. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Liu, Dajiang J; Leal, Suzanne M
2012-10-05
Next-generation sequencing has led to many complex-trait rare-variant (RV) association studies. Although single-variant association analysis can be performed, it is grossly underpowered. Therefore, researchers have developed many RV association tests that aggregate multiple variant sites across a genetic region (e.g., gene), and test for the association between the trait and the aggregated genotype. After these aggregate tests detect an association, it is only possible to estimate the average genetic effect for a group of RVs. As a result of the "winner's curse," such an estimate can be biased. Although for common variants one can obtain unbiased estimates of genetic parameters by analyzing a replication sample, for RVs it is desirable to obtain unbiased genetic estimates for the study where the association is identified. This is because there can be substantial heterogeneity of RV sites and frequencies even among closely related populations. In order to obtain an unbiased estimate for aggregated RV analysis, we developed bootstrap-sample-split algorithms to reduce the bias of the winner's curse. The unbiased estimates are greatly important for understanding the population-specific contribution of RVs to the heritability of complex traits. We also demonstrate both theoretically and via simulations that for aggregate RV analysis the genetic variance for a gene or region will always be underestimated, sometimes substantially, because of the presence of noncausal variants or because of the presence of causal variants with effects of different magnitudes or directions. Therefore, even if RVs play a major role in the complex-trait etiologies, a portion of the heritability will remain missing, and the contribution of RVs to the complex-trait etiologies will be underestimated. Copyright © 2012 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Dissociation between APOC3 variants, hepatic triglyceride content and insulin resistance.
Kozlitina, Julia; Boerwinkle, Eric; Cohen, Jonathan C; Hobbs, Helen H
2011-02-01
Nonalcoholic fatty liver disease (NAFLD) is an escalating health problem that is frequently associated with obesity and insulin resistance. The mechanistic relationship between NAFLD, obesity, and insulin resistance is not well understood. A nonsynonymous variant in patatin-like phospholipase domain containing 3 (rs738409, I148M) has been reproducibly associated with increased hepatic triglyceride content (HTGC) but has not been associated with either the body mass index (BMI) or indices of insulin resistance. Conversely, two sequence variants in apolipoprotein C3 (APOC3) that have been linked to hypertriglyceridemia (rs2854117 C > T and rs2854116 T > C) have recently been reported to be associated with both hepatic fat content and insulin resistance. Here we genotyped two APOC3 variants in 1228 African Americans, 843 European Americans and 426 Hispanics from a multiethnic population based study, the Dallas Heart Study and test for association with HTGC and homeostatic model of insulin resistance (HOMA-IR). We also examined the relationship between these two variants and HOMA-IR in the Atherosclerosis Risk in Communities (ARIC) study. No significant difference in hepatic fat content was found between carriers and noncarriers in the Dallas Heart Study. Neither APOC3 variant was associated with HOMA-IR in the Dallas Heart Study; this lack of association was confirmed in the ARIC study, even after the analysis was restricted to lean (BMI < 25 kg/m(2) ) individuals (n = 4399). Our data do not support a causal relationship between these two variants in APOC3 and either HTGC or insulin resistance in middle-aged men and women. Copyright © 2010 American Association for the Study of Liver Diseases.
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Lupus Risk Variant Increases pSTAT1 Binding and Decreases ETS1 Expression
Lu, Xiaoming; Zoller, Erin E.; Weirauch, Matthew T.; Wu, Zhiguo; Namjou, Bahram; Williams, Adrienne H.; Ziegler, Julie T.; Comeau, Mary E.; Marion, Miranda C.; Glenn, Stuart B.; Adler, Adam; Shen, Nan; Nath, Swapan K.; Stevens, Anne M.; Freedman, Barry I.; Tsao, Betty P.; Jacob, Chaim O.; Kamen, Diane L.; Brown, Elizabeth E.; Gilkeson, Gary S.; Alarcón, Graciela S.; Reveille, John D.; Anaya, Juan-Manuel; James, Judith A.; Sivils, Kathy L.; Criswell, Lindsey A.; Vilá, Luis M.; Alarcón-Riquelme, Marta E.; Petri, Michelle; Scofield, R. Hal; Kimberly, Robert P.; Ramsey-Goldman, Rosalind; Joo, Young Bin; Choi, Jeongim; Bae, Sang-Cheol; Boackle, Susan A.; Graham, Deborah Cunninghame; Vyse, Timothy J.; Guthridge, Joel M.; Gaffney, Patrick M.; Langefeld, Carl D.; Kelly, Jennifer A.; Greis, Kenneth D.; Kaufman, Kenneth M.; Harley, John B.; Kottyan, Leah C.
2015-01-01
Genetic variants at chromosomal region 11q23.3, near the gene ETS1, have been associated with systemic lupus erythematosus (SLE), or lupus, in independent cohorts of Asian ancestry. Several recent studies have implicated ETS1 as a critical driver of immune cell function and differentiation, and mice deficient in ETS1 develop an SLE-like autoimmunity. We performed a fine-mapping study of 14,551 subjects from multi-ancestral cohorts by starting with genotyped variants and imputing to all common variants spanning ETS1. By constructing genetic models via frequentist and Bayesian association methods, we identified 16 variants that are statistically likely to be causal. We functionally assessed each of these variants on the basis of their likelihood of affecting transcription factor binding, miRNA binding, or chromatin state. Of the four variants that we experimentally examined, only rs6590330 differentially binds lysate from B cells. Using mass spectrometry, we found more binding of the transcription factor signal transducer and activator of transcription 1 (STAT1) to DNA near the risk allele of rs6590330 than near the non-risk allele. Immunoblot analysis and chromatin immunoprecipitation of pSTAT1 in B cells heterozygous for rs6590330 confirmed that the risk allele increased binding to the active form of STAT1. Analysis with expression quantitative trait loci indicated that the risk allele of rs6590330 is associated with decreased ETS1 expression in Han Chinese, but not other ancestral cohorts. We propose a model in which the risk allele of rs6590330 is associated with decreased ETS1 expression and increases SLE risk by enhancing the binding of pSTAT1. PMID:25865496
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Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J; Murcray, Cassandra Elizabeth; Conti, David
2011-12-01
Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. © 2011 Wiley Periodicals, Inc.
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Li, Dalin; Lewinger, Juan Pablo; Gauderman, William J.; Murcray, Cassandra Elizabeth; Conti, David
2014-01-01
Variants identified in recent genome-wide association studies based on the common-disease common-variant hypothesis are far from fully explaining the hereditability of complex traits. Rare variants may, in part, explain some of the missing hereditability. Here, we explored the advantage of the extreme phenotype sampling in rare-variant analysis and refined this design framework for future large-scale association studies on quantitative traits. We first proposed a power calculation approach for a likelihood-based analysis method. We then used this approach to demonstrate the potential advantages of extreme phenotype sampling for rare variants. Next, we discussed how this design can influence future sequencing-based association studies from a cost-efficiency (with the phenotyping cost included) perspective. Moreover, we discussed the potential of a two-stage design with the extreme sample as the first stage and the remaining nonextreme subjects as the second stage. We demonstrated that this two-stage design is a cost-efficient alternative to the one-stage cross-sectional design or traditional two-stage design. We then discussed the analysis strategies for this extreme two-stage design and proposed a corresponding design optimization procedure. To address many practical concerns, for example measurement error or phenotypic heterogeneity at the very extremes, we examined an approach in which individuals with very extreme phenotypes are discarded. We demonstrated that even with a substantial proportion of these extreme individuals discarded, an extreme-based sampling can still be more efficient. Finally, we expanded the current analysis and design framework to accommodate the CMC approach where multiple rare-variants in the same gene region are analyzed jointly. PMID:21922541
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Zhang, G
1997-12-01
This article presents high, medium, and low variants of projections for China's population aged 0-14 years, 15-59 years, over 60 years, over 65 years, and over 80 years. Projections are based on data from the 1990 Census and the 1995 1% sample survey. China's population is expected to reach 1.281 billion in 2000, and 1.666 billion in 2050, under the high variant; 1.271 billion in 2000, and 1.535 billion in 2040, under the medium variant; and 1.261 billion in 2000, 1.442 billion in 2030, and declining to 1.346 billion by 2050, under the low variant. Decreases will not occur under the medium variant until 2050, to 1.507 billion. The total fertility rate is expected to decline from 2.3 in 2000, to 2.0 before 2050, under the high variant; from 2.0 in 2000, to 1.8 before 2050, under the medium variant; and 1.8 in 2000, to 1.6 before 2050, under the low variant. By 2050, the average life expectancy is expected to increase to 75 years for males and 79 years for females. The death rate will decline from 7% at present to 6.8% in 2000, and then increase to 14% by 2050. The total dependency ratio will decrease from 56.92% in 2000, to 53.53% in 2010, and then increase to 72.46% in 2050, under the high variant. The child dependency ratio will decline from 41.13% in 2000, to 32.19% in 2050. The aged dependency ratio will rise from 15.79% in 2000, to 40.27% in 2050. The aged-child ratio will increase from 38.39% in 2000, to 125.08% in 2050.
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White, Peter A
2009-09-01
Many kinds of common and easily observed causal relations exhibit property transmission, which is a tendency for the causal object to impose its own properties on the effect object. It is proposed that property transmission becomes a general and readily available hypothesis used to make interpretations and judgments about causal questions under conditions of uncertainty, in which property transmission functions as a heuristic. The property transmission hypothesis explains why and when similarity information is used in causal inference. It can account for magical contagion beliefs, some cases of illusory correlation, the correspondence bias, overestimation of cross-situational consistency in behavior, nonregressive tendencies in prediction, the belief that acts of will are causes of behavior, and a range of other phenomena. People learn that property transmission is often moderated by other factors, but under conditions of uncertainty in which the operation of relevant other factors is unknown, it tends to exhibit a pervasive influence on thinking about causality. (c) 2009 APA, all rights reserved.
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Morris, Richard W; Taylor, Amy E; Fluharty, Meg E; Bjørngaard, Johan H; Åsvold, Bjørn Olav; Elvestad Gabrielsen, Maiken; Campbell, Archie; Marioni, Riccardo; Kumari, Meena; Korhonen, Tellervo; Männistö, Satu; Marques-Vidal, Pedro; Kaakinen, Marika; Cavadino, Alana; Postmus, Iris; Husemoen, Lise Lotte N; Skaaby, Tea; Ahluwalia, Tarun Veer Singh; Treur, Jorien L; Willemsen, Gonneke; Dale, Caroline; Wannamethee, S Goya; Lahti, Jari; Palotie, Aarno; Räikkönen, Katri; McConnachie, Alex; Padmanabhan, Sandosh; Wong, Andrew; Dalgård, Christine; Paternoster, Lavinia; Ben-Shlomo, Yoav; Tyrrell, Jessica; Horwood, John; Fergusson, David M; Kennedy, Martin A; Nohr, Ellen A; Christiansen, Lene; Kyvik, Kirsten Ohm; Kuh, Diana; Watt, Graham; Eriksson, Johan G; Whincup, Peter H; Vink, Jacqueline M; Boomsma, Dorret I; Davey Smith, George; Lawlor, Debbie; Linneberg, Allan; Ford, Ian; Jukema, J Wouter; Power, Chris; Hyppönen, Elina; Jarvelin, Marjo-Riitta; Preisig, Martin; Borodulin, Katja; Kaprio, Jaakko; Kivimaki, Mika; Smith, Blair H; Hayward, Caroline; Romundstad, Pål R; Sørensen, Thorkild I A; Munafò, Marcus R; Sattar, Naveed
2015-08-11
To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity. Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes. 148,731 current, former and never-smokers of European ancestry aged ≥ 16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). Waist and hip circumferences, and waist-hip ratio. The data included up to 66,809 never-smokers, 43,009 former smokers and 38,913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele. For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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2014-01-01
Background Genome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers. Results By using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions. Conclusion Where QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle. PMID:24456127
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Experimental verification of an indefinite causal order
Rubino, Giulia; Rozema, Lee A.; Feix, Adrien; Araújo, Mateus; Zeuner, Jonas M.; Procopio, Lorenzo M.; Brukner, Časlav; Walther, Philip
2017-01-01
Investigating the role of causal order in quantum mechanics has recently revealed that the causal relations of events may not be a priori well defined in quantum theory. Although this has triggered a growing interest on the theoretical side, creating processes without a causal order is an experimental task. We report the first decisive demonstration of a process with an indefinite causal order. To do this, we quantify how incompatible our setup is with a definite causal order by measuring a “causal witness.” This mathematical object incorporates a series of measurements that are designed to yield a certain outcome only if the process under examination is not consistent with any well-defined causal order. In our experiment, we perform a measurement in a superposition of causal orders—without destroying the coherence—to acquire information both inside and outside of a “causally nonordered process.” Using this information, we experimentally determine a causal witness, demonstrating by almost 7 SDs that the experimentally implemented process does not have a definite causal order. PMID:28378018
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Myles-Worsley, Marina; Tiobech, Josepha; Browning, Sharon R; Korn, Jeremy; Goodman, Sarah; Gentile, Karen; Melhem, Nadine; Byerley, William; Faraone, Stephen V; Middleton, Frank A
2013-03-01
Growing evidence for genetic overlap between schizophrenia (SCZ) and bipolar disorder (BPD) suggests that causal variants of large effect on disease risk may cross traditional diagnostic boundaries. Extended multigenerational families with both SCZ and BPD cases can be a valuable resource for discovery of shared biological pathways because they can reveal the natural evolution of the underlying genetic disruptions and their phenotypic expression. We investigated a deletion at the SLC1A1 glutamate transporter gene originally identified as a copy number variant exclusively carried by members of a 5-generation Palauan family. Using an expanded sample of 21 family members, quantitative PCR confirmed the deletion in all seven individuals with psychosis, three "obligate-carrier" parents and one unaffected sibling, while four marry-in parents were non-carriers. Linkage analysis under an autosomal dominant model generated a LOD-score of 3.64, confirming co-segregation of the deletion with psychosis. For more precise localization, we determined the approximate deletion end points using alignment of next-generation sequencing data for one affected deletion-carrier and then designed PCR amplicons to span the entire deletion locus. These probes established that the deletion spans 84,298 bp, thus eliminating the entire promoter, the transcription start site, and the first 59 amino acids of the protein, including the first transmembrane Na(2+)/dicarboxylate symporter domain, one of the domains that perform the glutamate transport action. Discovery of this functionally relevant SLC1A1 mutation and its co-segregation with psychosis in an extended multigenerational pedigree provides further support for the important role played by glutamatergic transmission in the pathophysiology of psychotic disorders. Copyright © 2013 Wiley Periodicals, Inc.
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Identifying Mendelian disease genes with the Variant Effect Scoring Tool
2013-01-01
Background Whole exome sequencing studies identify hundreds to thousands of rare protein coding variants of ambiguous significance for human health. Computational tools are needed to accelerate the identification of specific variants and genes that contribute to human disease. Results We have developed the Variant Effect Scoring Tool (VEST), a supervised machine learning-based classifier, to prioritize rare missense variants with likely involvement in human disease. The VEST classifier training set comprised ~ 45,000 disease mutations from the latest Human Gene Mutation Database release and another ~45,000 high frequency (allele frequency >1%) putatively neutral missense variants from the Exome Sequencing Project. VEST outperforms some of the most popular methods for prioritizing missense variants in carefully designed holdout benchmarking experiments (VEST ROC AUC = 0.91, PolyPhen2 ROC AUC = 0.86, SIFT4.0 ROC AUC = 0.84). VEST estimates variant score p-values against a null distribution of VEST scores for neutral variants not included in the VEST training set. These p-values can be aggregated at the gene level across multiple disease exomes to rank genes for probable disease involvement. We tested the ability of an aggregate VEST gene score to identify candidate Mendelian disease genes, based on whole-exome sequencing of a small number of disease cases. We used whole-exome data for two Mendelian disorders for which the causal gene is known. Considering only genes that contained variants in all cases, the VEST gene score ranked dihydroorotate dehydrogenase (DHODH) number 2 of 2253 genes in four cases of Miller syndrome, and myosin-3 (MYH3) number 2 of 2313 genes in three cases of Freeman Sheldon syndrome. Conclusions Our results demonstrate the potential power gain of aggregating bioinformatics variant scores into gene-level scores and the general utility of bioinformatics in assisting the search for disease genes in large-scale exome sequencing studies. VEST is available as a stand-alone software package at http://wiki.chasmsoftware.org and is hosted by the CRAVAT web server at http://www.cravat.us PMID:23819870
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Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy
Golbus, Jessica R.; Puckelwartz, Megan J.; Dellefave-Castillo, Lisa; ...
2014-09-01
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused onmore » 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.« less
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Using volcano plots and regularized-chi statistics in genetic association studies.
Li, Wentian; Freudenberg, Jan; Suh, Young Ju; Yang, Yaning
2014-02-01
Labor intensive experiments are typically required to identify the causal disease variants from a list of disease associated variants in the genome. For designing such experiments, candidate variants are ranked by their strength of genetic association with the disease. However, the two commonly used measures of genetic association, the odds-ratio (OR) and p-value may rank variants in different order. To integrate these two measures into a single analysis, here we transfer the volcano plot methodology from gene expression analysis to genetic association studies. In its original setting, volcano plots are scatter plots of fold-change and t-test statistic (or -log of the p-value), with the latter being more sensitive to sample size. In genetic association studies, the OR and Pearson's chi-square statistic (or equivalently its square root, chi; or the standardized log(OR)) can be analogously used in a volcano plot, allowing for their visual inspection. Moreover, the geometric interpretation of these plots leads to an intuitive method for filtering results by a combination of both OR and chi-square statistic, which we term "regularized-chi". This method selects associated markers by a smooth curve in the volcano plot instead of the right-angled lines which corresponds to independent cutoffs for OR and chi-square statistic. The regularized-chi incorporates relatively more signals from variants with lower minor-allele-frequencies than chi-square test statistic. As rare variants tend to have stronger functional effects, regularized-chi is better suited to the task of prioritization of candidate genes. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Identification of rare paired box 3 variant in strabismus by whole exome sequencing
Gong, Hui-Min; Wang, Jing; Xu, Jing; Zhou, Zhan-Yu; Li, Jing-Wen; Chen, Shu-Fang
2017-01-01
AIM To identify the potentially pathogenic gene variants that contributes to the etiology of strabismus. METHODS A Chinese pedigree with strabismus was collected and the exomes of two affected individuals were sequenced using the next-generation sequencing technology. The resulting variants from exome sequencing were filtered by subsequent bioinformatics methods and the candidate mutation was verified as heterozygous in the affected proposita and her mother by sanger sequencing. RESULTS Whole exome sequencing and filtering identified a nonsynonymous mutation c.434G-T transition in paired box 3 (PAX3) in the two affected individuals, which were predicted to be deleterious by more than 4 bioinformatics programs. This altered amino acid residue was located in the conserved PAX domain of PAX3. This gene encodes a member of the PAX family of transcription factors, which play critical roles during fetal development. Mutations in PAX3 were associated with Waardenburg syndrome with strabismus. CONCLUSION Our results report that the c.434G-T mutation (p.R145L) in PAX3 may contribute to strabismus, expanding our understanding of the causally relevant genes for this disorder. PMID:28861346
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Zhuravlyova, L V; Shekhovtsova, Y O
2015-01-01
The purpose of the present study was to determine the causal factors of the progression of metabolic disorders in pancreatic tissue and their relationships in patients with assotiated clinical variants of chronic pancreatitis (CP) and type 2 diabetes mellitus (T2DM). The study involved of 76 patients with CP and T2DM. The causes of progression of metabolic disorders in the pancreas in patients with associated clinical variants of CP and T2DM has been analyzed. The most significant of them were insulin resistance and abdominal obesity, which promotes early formation of the metabolic syndrome and the activation of fibrogenesis and steatosis in the pancreas and is caused by dyslipidemia, impaired glucose metabolism and the development of systemic inflammation and imbalance of adipocytokines. The relationships between adipocytokines, body weight and individual components of the metabolic syndrome in patients with CP and T2DM suggests the involvement of these hormones of adipose tissue in the formation of the metabolic syndrome and its components.
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Identification of rare paired box 3 variant in strabismus by whole exome sequencing.
Gong, Hui-Min; Wang, Jing; Xu, Jing; Zhou, Zhan-Yu; Li, Jing-Wen; Chen, Shu-Fang
2017-01-01
To identify the potentially pathogenic gene variants that contributes to the etiology of strabismus. A Chinese pedigree with strabismus was collected and the exomes of two affected individuals were sequenced using the next-generation sequencing technology. The resulting variants from exome sequencing were filtered by subsequent bioinformatics methods and the candidate mutation was verified as heterozygous in the affected proposita and her mother by sanger sequencing. Whole exome sequencing and filtering identified a nonsynonymous mutation c.434G-T transition in paired box 3 (PAX3) in the two affected individuals, which were predicted to be deleterious by more than 4 bioinformatics programs. This altered amino acid residue was located in the conserved PAX domain of PAX3. This gene encodes a member of the PAX family of transcription factors, which play critical roles during fetal development. Mutations in PAX3 were associated with Waardenburg syndrome with strabismus. Our results report that the c.434G-T mutation (p.R145L) in PAX3 may contribute to strabismus, expanding our understanding of the causally relevant genes for this disorder.
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Pathomechanisms of polycystic ovary syndrome: Multidimensional approaches.
Sagvekar, Pooja; Dadachanji, Roshan; Patil, Krutika; Mukherjee, Srabani
2018-03-01
Polycystic ovary syndrome is a complex endocrine disorder affecting numerous women of reproductive age across the globe. Characterized mainly by irregular menses, hirsutism, skewed LH: FSH ratios and bulky polycystic ovaries, this multifactorial endocrinopathy results in unfavorable reproductive and metabolic sequelae, including anovulatory infertility, type 2 diabetes, metabolic syndrome and cardiovascular disease in later years. Increasing evidence has shown that the manifestation of polycystic ovary syndrome (PCOS) is attributable to a cumulative impact of altered genetic, epigenetic and protein profiles which bring about a systemic dysfunction. While genetic approaches help ascertain role of causal variants in its etiology, tissue-specific epigenetic patterns help in deciphering the auxiliary role of environmental, nutritional and behavioral factors. Proteomics is advantageous, linking both genotype and phenotype and contributing to biomarker discovery. Investigating molecular mechanism underlying PCOS is imperative in order to gain insight into the pathophysiology of PCOS and formulate novel diagnostic and treatment strategies. In this review we have summarized these three aspects, which have been successfully utilized to delineate the pathomechanisms of PCOS.
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Wray, Naomi R; Ripke, Stephan; Mattheisen, Manuel; Trzaskowski, Maciej; Byrne, Enda M; Abdellaoui, Abdel; Adams, Mark J; Agerbo, Esben; Air, Tracy M; Andlauer, Till M F; Bacanu, Silviu-Alin; Bækvad-Hansen, Marie; Beekman, Aartjan F T; Bigdeli, Tim B; Binder, Elisabeth B; Blackwood, Douglas R H; Bryois, Julien; Buttenschøn, Henriette N; Bybjerg-Grauholm, Jonas; Cai, Na; Castelao, Enrique; Christensen, Jane Hvarregaard; Clarke, Toni-Kim; Coleman, Jonathan I R; Colodro-Conde, Lucía; Couvy-Duchesne, Baptiste; Craddock, Nick; Crawford, Gregory E; Crowley, Cheynna A; Dashti, Hassan S; Davies, Gail; Deary, Ian J; Degenhardt, Franziska; Derks, Eske M; Direk, Nese; Dolan, Conor V; Dunn, Erin C; Eley, Thalia C; Eriksson, Nicholas; Escott-Price, Valentina; Kiadeh, Farnush Hassan Farhadi; Finucane, Hilary K; Forstner, Andreas J; Frank, Josef; Gaspar, Héléna A; Gill, Michael; Giusti-Rodríguez, Paola; Goes, Fernando S; Gordon, Scott D; Grove, Jakob; Hall, Lynsey S; Hannon, Eilis; Hansen, Christine Søholm; Hansen, Thomas F; Herms, Stefan; Hickie, Ian B; Hoffmann, Per; Homuth, Georg; Horn, Carsten; Hottenga, Jouke-Jan; Hougaard, David M; Hu, Ming; Hyde, Craig L; Ising, Marcus; Jansen, Rick; Jin, Fulai; Jorgenson, Eric; Knowles, James A; Kohane, Isaac S; Kraft, Julia; Kretzschmar, Warren W; Krogh, Jesper; Kutalik, Zoltán; Lane, Jacqueline M; Li, Yihan; Li, Yun; Lind, Penelope A; Liu, Xiaoxiao; Lu, Leina; MacIntyre, Donald J; MacKinnon, Dean F; Maier, Robert M; Maier, Wolfgang; Marchini, Jonathan; Mbarek, Hamdi; McGrath, Patrick; McGuffin, Peter; Medland, Sarah E; Mehta, Divya; Middeldorp, Christel M; Mihailov, Evelin; Milaneschi, Yuri; Milani, Lili; Mill, Jonathan; Mondimore, Francis M; Montgomery, Grant W; Mostafavi, Sara; Mullins, Niamh; Nauck, Matthias; Ng, Bernard; Nivard, Michel G; Nyholt, Dale R; O'Reilly, Paul F; Oskarsson, Hogni; Owen, Michael J; Painter, Jodie N; Pedersen, Carsten Bøcker; Pedersen, Marianne Giørtz; Peterson, Roseann E; Pettersson, Erik; Peyrot, Wouter J; Pistis, Giorgio; Posthuma, Danielle; Purcell, Shaun M; Quiroz, Jorge A; Qvist, Per; Rice, John P; Riley, Brien P; Rivera, Margarita; Saeed Mirza, Saira; Saxena, Richa; Schoevers, Robert; Schulte, Eva C; Shen, Ling; Shi, Jianxin; Shyn, Stanley I; Sigurdsson, Engilbert; Sinnamon, Grant B C; Smit, Johannes H; Smith, Daniel J; Stefansson, Hreinn; Steinberg, Stacy; Stockmeier, Craig A; Streit, Fabian; Strohmaier, Jana; Tansey, Katherine E; Teismann, Henning; Teumer, Alexander; Thompson, Wesley; Thomson, Pippa A; Thorgeirsson, Thorgeir E; Tian, Chao; Traylor, Matthew; Treutlein, Jens; Trubetskoy, Vassily; Uitterlinden, André G; Umbricht, Daniel; Van der Auwera, Sandra; van Hemert, Albert M; Viktorin, Alexander; Visscher, Peter M; Wang, Yunpeng; Webb, Bradley T; Weinsheimer, Shantel Marie; Wellmann, Jürgen; Willemsen, Gonneke; Witt, Stephanie H; Wu, Yang; Xi, Hualin S; Yang, Jian; Zhang, Futao; Arolt, Volker; Baune, Bernhard T; Berger, Klaus; Boomsma, Dorret I; Cichon, Sven; Dannlowski, Udo; de Geus, E C J; DePaulo, J Raymond; Domenici, Enrico; Domschke, Katharina; Esko, Tõnu; Grabe, Hans J; Hamilton, Steven P; Hayward, Caroline; Heath, Andrew C; Hinds, David A; Kendler, Kenneth S; Kloiber, Stefan; Lewis, Glyn; Li, Qingqin S; Lucae, Susanne; Madden, Pamela F A; Magnusson, Patrik K; Martin, Nicholas G; McIntosh, Andrew M; Metspalu, Andres; Mors, Ole; Mortensen, Preben Bo; Müller-Myhsok, Bertram; Nordentoft, Merete; Nöthen, Markus M; O'Donovan, Michael C; Paciga, Sara A; Pedersen, Nancy L; Penninx, Brenda W J H; Perlis, Roy H; Porteous, David J; Potash, James B; Preisig, Martin; Rietschel, Marcella; Schaefer, Catherine; Schulze, Thomas G; Smoller, Jordan W; Stefansson, Kari; Tiemeier, Henning; Uher, Rudolf; Völzke, Henry; Weissman, Myrna M; Werge, Thomas; Winslow, Ashley R; Lewis, Cathryn M; Levinson, Douglas F; Breen, Gerome; Børglum, Anders D; Sullivan, Patrick F
2018-05-01
Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.
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Histone modification: cause or cog?
Henikoff, Steven; Shilatifard, Ali
2011-10-01
Histone modifications are key components of chromatin packaging but whether they constitute a 'code' has been contested. We believe that the central issue is causality: are histone modifications responsible for differences between chromatin states, or are differences in modifications mostly consequences of dynamic processes, such as transcription and nucleosome remodeling? We find that inferences of causality are often based on correlation and that patterns of some key histone modifications are more easily explained as consequences of nucleosome disruption in the presence of histone modifying enzymes. We suggest that the 35-year-old DNA accessibility paradigm provides a mechanistically sound basis for understanding the role of nucleosomes in gene regulation and epigenetic inheritance. Based on this view, histone modifications and variants contribute to diversification of a chromatin landscape shaped by dynamic processes that are driven primarily by transcription and nucleosome remodeling. Copyright © 2011 Elsevier Ltd. All rights reserved.
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The causal structure of utility conditionals.
Bonnefon, Jean-François; Sloman, Steven A
2013-01-01
The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ''if p then q'' statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility-informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility-informed inferences conditional reasoning requires three components: utility, probability, and causal structure. Copyright © 2012 Cognitive Science Society, Inc.
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Formalizing Neurath's ship: Approximate algorithms for online causal learning.
Bramley, Neil R; Dayan, Peter; Griffiths, Thomas L; Lagnado, David A
2017-04-01
Higher-level cognition depends on the ability to learn models of the world. We can characterize this at the computational level as a structure-learning problem with the goal of best identifying the prevailing causal relationships among a set of relata. However, the computational cost of performing exact Bayesian inference over causal models grows rapidly as the number of relata increases. This implies that the cognitive processes underlying causal learning must be substantially approximate. A powerful class of approximations that focuses on the sequential absorption of successive inputs is captured by the Neurath's ship metaphor in philosophy of science, where theory change is cast as a stochastic and gradual process shaped as much by people's limited willingness to abandon their current theory when considering alternatives as by the ground truth they hope to approach. Inspired by this metaphor and by algorithms for approximating Bayesian inference in machine learning, we propose an algorithmic-level model of causal structure learning under which learners represent only a single global hypothesis that they update locally as they gather evidence. We propose a related scheme for understanding how, under these limitations, learners choose informative interventions that manipulate the causal system to help elucidate its workings. We find support for our approach in the analysis of 3 experiments. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Functional brain networks and white matter underlying theory-of-mind in autism.
Kana, Rajesh K; Libero, Lauren E; Hu, Christi P; Deshpande, Hrishikesh D; Colburn, Jeffrey S
2014-01-01
Human beings constantly engage in attributing causal explanations to one's own and to others' actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism.
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Sahana, G; Guldbrandtsen, B; Thomsen, B; Holm, L-E; Panitz, F; Brøndum, R F; Bendixen, C; Lund, M S
2014-11-01
Mastitis is a mammary disease that frequently affects dairy cattle. Despite considerable research on the development of effective prevention and treatment strategies, mastitis continues to be a significant issue in bovine veterinary medicine. To identify major genes that affect mastitis in dairy cattle, 6 chromosomal regions on Bos taurus autosome (BTA) 6, 13, 16, 19, and 20 were selected from a genome scan for 9 mastitis phenotypes using imputed high-density single nucleotide polymorphism arrays. Association analyses using sequence-level variants for the 6 targeted regions were carried out to map causal variants using whole-genome sequence data from 3 breeds. The quantitative trait loci (QTL) discovery population comprised 4,992 progeny-tested Holstein bulls, and QTL were confirmed in 4,442 Nordic Red and 1,126 Jersey cattle. The targeted regions were imputed to the sequence level. The highest association signal for clinical mastitis was observed on BTA 6 at 88.97 Mb in Holstein cattle and was confirmed in Nordic Red cattle. The peak association region on BTA 6 contained 2 genes: vitamin D-binding protein precursor (GC) and neuropeptide FF receptor 2 (NPFFR2), which, based on known biological functions, are good candidates for affecting mastitis. However, strong linkage disequilibrium in this region prevented conclusive determination of the causal gene. A different QTL on BTA 6 located at 88.32 Mb in Holstein cattle affected mastitis. In addition, QTL on BTA 13 and 19 were confirmed to segregate in Nordic Red cattle and QTL on BTA 16 and 20 were confirmed in Jersey cattle. Although several candidate genes were identified in these targeted regions, it was not possible to identify a gene or polymorphism as the causal factor for any of these regions. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Benavides, Julio; Perez, Valentín; Tosser-Klopp, Gwenola; Klopp, Christophe; Keennel, Stephen J.; Arranz, Juan José
2015-01-01
In this study, we demonstrate the use of a genome-wide association mapping together with RNA-seq in a reduced number of samples, as an efficient approach to detect the causal mutation for a Mendelian disease. Junctional epidermolysis bullosa is a recessive genodermatosis that manifests with neonatal mechanical fragility of the skin, blistering confined to the lamina lucida of the basement membrane and severe alteration of the hemidesmosomal junctions. In Spanish Churra sheep, junctional epidermolysis bullosa (JEB) has been detected in two commercial flocks. The JEB locus was mapped to Ovis aries chromosome 11 by GWAS and subsequently fine-mapped to an 868-kb homozygous segment using the identical-by-descent method. The ITGB4, which is located within this region, was identified as the best positional and functional candidate gene. The RNA-seq variant analysis enabled us to discover a 4-bp deletion within exon 33 of the ITGB4 gene (c.4412_4415del). The c.4412_4415del mutation causes a frameshift resulting in a premature stop codon at position 1472 of the integrin β4 protein. A functional analysis of this deletion revealed decreased levels of mRNA in JEB skin samples and the absence of integrin β4 labeling in immunohistochemical assays. Genotyping of c.4412_4415del showed perfect concordance with the recessive mode of the disease phenotype. Selection against this causal mutation will now be used to solve the problem of JEB in flocks of Churra sheep. Furthermore, the identification of the ITGB4 mutation means that affected sheep can be used as a large mammal animal model for the human form of epidermolysis bullosa with aplasia cutis. Our approach evidences that RNA-seq offers cost-effective alternative to identify variants in the species in which high resolution exome-sequencing is not straightforward. PMID:25955497
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2014-01-01
Background The absence of horns, called polled phenotype, is the favored trait in modern cattle husbandry. To date, polled cattle are obtained primarily by dehorning calves. Dehorning is a practice that raises animal welfare issues, which can be addressed by selecting for genetically hornless cattle. In the past 20 years, there have been many studies worldwide to identify unique genetic markers in complete association with the polled trait in cattle and recently, two different alleles at the POLLED locus, both resulting in the absence of horns, were reported: (1) the Celtic allele, which is responsible for the polled phenotype in most breeds and for which a single candidate mutation was detected and (2) the Friesian allele, which is responsible for the polled phenotype predominantly in the Holstein-Friesian breed and in a few other breeds, but for which five candidate mutations were identified in a 260-kb haplotype. Further studies based on genome-wide sequencing and high-density SNP (single nucleotide polymorphism) genotyping confirmed the existence of the Celtic and Friesian variants and narrowed down the causal Friesian haplotype to an interval of 145 kb. Results Almost 6000 animals were genetically tested for the polled trait and we detected a recombinant animal which enabled us to reduce the Friesian POLLED haplotype to a single causal mutation, namely a 80-kb duplication. Moreover, our results clearly disagree with the recently reported perfect co-segregation of the POLLED mutation and a SNP at position 1 390 292 bp on bovine chromosome 1 in the Holstein-Friesian population. Conclusion We conclude that the 80-kb duplication, as the only remaining variant within the shortened Friesian haplotype, represents the most likely causal mutation for the polled phenotype of Friesian origin. PMID:24993890
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Suárez-Vega, Aroa; Gutiérrez-Gil, Beatriz; Benavides, Julio; Perez, Valentín; Tosser-Klopp, Gwenola; Klopp, Christophe; Keennel, Stephen J; Arranz, Juan José
2015-01-01
In this study, we demonstrate the use of a genome-wide association mapping together with RNA-seq in a reduced number of samples, as an efficient approach to detect the causal mutation for a Mendelian disease. Junctional epidermolysis bullosa is a recessive genodermatosis that manifests with neonatal mechanical fragility of the skin, blistering confined to the lamina lucida of the basement membrane and severe alteration of the hemidesmosomal junctions. In Spanish Churra sheep, junctional epidermolysis bullosa (JEB) has been detected in two commercial flocks. The JEB locus was mapped to Ovis aries chromosome 11 by GWAS and subsequently fine-mapped to an 868-kb homozygous segment using the identical-by-descent method. The ITGB4, which is located within this region, was identified as the best positional and functional candidate gene. The RNA-seq variant analysis enabled us to discover a 4-bp deletion within exon 33 of the ITGB4 gene (c.4412_4415del). The c.4412_4415del mutation causes a frameshift resulting in a premature stop codon at position 1472 of the integrin β4 protein. A functional analysis of this deletion revealed decreased levels of mRNA in JEB skin samples and the absence of integrin β4 labeling in immunohistochemical assays. Genotyping of c.4412_4415del showed perfect concordance with the recessive mode of the disease phenotype. Selection against this causal mutation will now be used to solve the problem of JEB in flocks of Churra sheep. Furthermore, the identification of the ITGB4 mutation means that affected sheep can be used as a large mammal animal model for the human form of epidermolysis bullosa with aplasia cutis. Our approach evidences that RNA-seq offers cost-effective alternative to identify variants in the species in which high resolution exome-sequencing is not straightforward.
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Nemati, Shahram; Teimourian, Shahram
2017-01-01
Inflammatory bowel disease (IBD) is the consequence of an aberrant hemostasis of the immune cells at the gut mucosal border. Based on clinical manifestation, laboratory tests, radiological studies, endoscopic and histological features, this disease is divided into three main types including Crohn’s disease (CD), Ulcerative colitis (UC), and IBDunclassified (IBD-U). IBD is frequently presented in adults, but about 20% of IBD cases are diagnosed during childhood called pediatric IBD (PIBD). Some patients in the latter group emerge the first symptoms during infancy or under 5 years of age named infantile and very early onset IBD (VEO-IBD), respectively. These subtypes make a small fraction of PIBD, but they have exclusive phenotypic and genetic characteristics such that they are accompanied by severe disease course and resistance to conventional therapy. In this context, understanding the underlying molecular pathology opens a promising field for individualized and effective treatment. Here, we describe current hypotheses on IBD pathophysiology then explain the new idea about genetic screening technology as a good potential approach to identify the causal variants early in the disease manifestation, which is especially important for the fast and accurate treatment of VEO-IBD. PMID:28638582
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Nonparametric Identification of Causal Effects under Temporal Dependence
ERIC Educational Resources Information Center
Dafoe, Allan
2018-01-01
Social scientists routinely address temporal dependence by adopting a simple technical fix. However, the correct identification strategy for a causal effect depends on causal assumptions. These need to be explicated and justified; almost no studies do so. This article addresses this shortcoming by offering a precise general statement of the…
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White, Peter A
2009-06-01
Contingency information is information about empirical associations between possible causes and outcomes. In the present research, it is shown that, under some circumstances, there is a tendency for negative contingencies to lead to positive causal judgments and for positive contingencies to lead to negative causal judgments. If there is a high proportion of instances in which a candidate cause (CC) being judged is present, these tendencies are predicted by weighted averaging models of causal judgment. If the proportion of such instances is low, the predictions of weighted averaging models break down. It is argued that one of the main aims of causal judgment is to account for occurrences of the outcome. Thus, a CC is not given a high causal judgment if there are few or no occurrences of it, regardless of the objective contingency. This argument predicts that, if there is a low proportion of instances in which a CC is present, causal judgments are determined mainly by the number of Cell A instances (i.e., CC present, outcome occurs), and that this explains why weighted averaging models fail to predict judgmental tendencies under these circumstances. Experimental results support this argument.
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Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred
2014-01-01
Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield. PMID:25333064
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Krawitz, Peter M; Schiska, Daniela; Krüger, Ulrike; Appelt, Sandra; Heinrich, Verena; Parkhomchuk, Dmitri; Timmermann, Bernd; Millan, Jose M; Robinson, Peter N; Mundlos, Stefan; Hecht, Jochen; Gross, Manfred
2014-09-01
Usher syndrome is an autosomal recessive disorder characterized both by deafness and blindness. For the three clinical subtypes of Usher syndrome causal mutations in altogether 12 genes and a modifier gene have been identified. Due to the genetic heterogeneity of Usher syndrome, the molecular analysis is predestined for a comprehensive and parallelized analysis of all known genes by next-generation sequencing (NGS) approaches. We describe here the targeted enrichment and deep sequencing for exons of Usher genes and compare the costs and workload of this approach compared to Sanger sequencing. We also present a bioinformatics analysis pipeline that allows us to detect single-nucleotide variants, short insertions and deletions, as well as copy number variations of one or more exons on the same sequence data. Additionally, we present a flexible in silico gene panel for the analysis of sequence variants, in which newly identified genes can easily be included. We applied this approach to a cohort of 44 Usher patients and detected biallelic pathogenic mutations in 35 individuals and monoallelic mutations in eight individuals of our cohort. Thirty-nine of the sequence variants, including two heterozygous deletions comprising several exons of USH2A, have not been reported so far. Our NGS-based approach allowed us to assess single-nucleotide variants, small indels, and whole exon deletions in a single test. The described diagnostic approach is fast and cost-effective with a high molecular diagnostic yield.
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Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk
Curtin, Karen; Rajamanickam, Venkatesh; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S. Vincent; Kumar, Shaji; Slager, Susan; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; Lipkin, Steven M.; Dumontet, Charles; Vachon, Celine M.
2018-01-01
The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance–a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits. PMID:29389935
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Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk.
Waller, Rosalie G; Darlington, Todd M; Wei, Xiaomu; Madsen, Michael J; Thomas, Alun; Curtin, Karen; Coon, Hilary; Rajamanickam, Venkatesh; Musinsky, Justin; Jayabalan, David; Atanackovic, Djordje; Rajkumar, S Vincent; Kumar, Shaji; Slager, Susan; Middha, Mridu; Galia, Perrine; Demangel, Delphine; Salama, Mohamed; Joseph, Vijai; McKay, James; Offit, Kenneth; Klein, Robert J; Lipkin, Steven M; Dumontet, Charles; Vachon, Celine M; Camp, Nicola J
2018-02-01
The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance-a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.
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Optimal causal inference: estimating stored information and approximating causal architecture.
Still, Susanne; Crutchfield, James P; Ellison, Christopher J
2010-09-01
We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.
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CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS
Shpitser, Ilya; Tchetgen, Eric Tchetgen
2017-01-01
Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl’s front-door criterion. PMID:28919652
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Splenomegaly - Diagnostic validity, work-up, and underlying causes.
Curovic Rotbain, Emelie; Lund Hansen, Dennis; Schaffalitzky de Muckadell, Ove; Wibrand, Flemming; Meldgaard Lund, Allan; Frederiksen, Henrik
2017-01-01
Our aim was to assess the validity of the ICD-10 code for splenomegaly in the Danish National Registry of Patients (DNRP), as well as to investigate which underlying diseases explained the observed splenomegaly. Splenomegaly is a common finding in patients referred to an internal medical department and can be caused by a large spectrum of diseases, including haematological diseases and liver cirrhosis. However, some patients remain without a causal diagnosis, despite extensive medical work-up. We identified 129 patients through the DNRP, that had been given the ICD-10 splenomegaly diagnosis code in 1994-2013 at Odense University Hospital, Denmark, excluding patients with prior splenomegaly, malignant haematological neoplasia or liver cirrhosis. Medical records were reviewed for validity of the splenomegaly diagnosis, diagnostic work-up, and the underlying disease was determined. The positive predictive value (PPV) with 95% confidence interval (CI) was calculated for the splenomegaly diagnosis code. Patients with idiopathic splenomegaly in on-going follow-up were also invited to be investigated for Gaucher disease. The overall PPV was 92% (95% CI: 85, 96). Haematological diseases were the underlying causal diagnosis in 39%; hepatic diseases in 18%, infectious disease in 10% and other diseases in 8%. 25% of patients with splenomegaly remained without a causal diagnosis. Lymphoma was the most common haematological causal diagnosis and liver cirrhosis the most common hepatic causal diagnosis. None of the investigated patients with idiopathic splenomegaly had Gaucher disease. Our findings show that the splenomegaly diagnosis in the DNRP is valid and can be used in registry-based studies. However, because of suspected significant under-coding, it should be considered if supplementary data sources should be used in addition, in order to attain a more representative population. Haematological diseases were the most common cause, however in a large fraction of patients no causal diagnosis was found.
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CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS.
Shpitser, Ilya; Tchetgen, Eric Tchetgen
2016-12-01
Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl's front-door criterion.
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Milne, Roger L; Burwinkel, Barbara; Michailidou, Kyriaki; Arias-Perez, Jose-Ignacio; Zamora, M Pilar; Menéndez-Rodríguez, Primitiva; Hardisson, David; Mendiola, Marta; González-Neira, Anna; Pita, Guillermo; Alonso, M Rosario; Dennis, Joe; Wang, Qin; Bolla, Manjeet K; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk; Ko, Yon-Dschun; Brauch, Hiltrud; Hamann, Ute; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Tchatchou, Sandrine; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Li, Jingmei; Brand, Judith S; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Lambrechts, Diether; Peuteman, Gilian; Christiaens, Marie-Rose; Smeets, Ann; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katazyna; Hartman, Mikael; Hui, Miao; Yen Lim, Wei; Wan Chan, Ching; Marme, Federick; Yang, Rongxi; Bugert, Peter; Lindblom, Annika; Margolin, Sara; García-Closas, Montserrat; Chanock, Stephen J; Lissowska, Jolanta; Figueroa, Jonine D; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Hooning, Maartje J; Kriege, Mieke; van den Ouweland, Ans M W; Koppert, Linetta B; Fletcher, Olivia; Johnson, Nichola; dos-Santos-Silva, Isabel; Peto, Julian; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha J; Long, Jirong; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Schmidt, Marjanka K; Broeks, Annegien; Cornelissen, Sten; Braaf, Linde; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Noh, Dong-Young; Simard, Jacques; Dumont, Martine; Goldberg, Mark S; Labrèche, France; Fasching, Peter A; Hein, Alexander; Ekici, Arif B; Beckmann, Matthias W; Radice, Paolo; Peterlongo, Paolo; Azzollini, Jacopo; Barile, Monica; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Hopper, John L; Schmidt, Daniel F; Makalic, Enes; Southey, Melissa C; Hwang Teo, Soo; Har Yip, Cheng; Sivanandan, Kavitta; Tay, Wan-Ting; Shen, Chen-Yang; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Guénel, Pascal; Truong, Therese; Sanchez, Marie; Mulot, Claire; Blot, William; Cai, Qiuyin; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Bogdanova, Natalia; Dörk, Thilo; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Zhang, Ben; Couch, Fergus J; Toland, Amanda E; Yannoukakos, Drakoulis; Sangrajrang, Suleeporn; McKay, James; Wang, Xianshu; Olson, Janet E; Vachon, Celine; Purrington, Kristen; Severi, Gianluca; Baglietto, Laura; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Czene, Kamila; Eriksson, Mikael; Humphreys, Keith; Darabi, Hatef; Ahmed, Shahana; Shah, Mitul; Pharoah, Paul D P; Hall, Per; Giles, Graham G; Benítez, Javier; Dunning, Alison M; Chenevix-Trench, Georgia; Easton, Douglas F
2014-11-15
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04-1.10, P = 2.9 × 10(-6)], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03-1.07, P = 1.7 × 10(-6)) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07-1.12, P = 5.1 × 10(-17)). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05-1.10, P = 1.0 × 10(-8)); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04-1.07, P = 2.0 × 10(-10)). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act. © The Author 2014. Published by Oxford University Press.
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Milne, Roger L.; Burwinkel, Barbara; Michailidou, Kyriaki; Arias-Perez, Jose-Ignacio; Zamora, M. Pilar; Menéndez-Rodríguez, Primitiva; Hardisson, David; Mendiola, Marta; González-Neira, Anna; Pita, Guillermo; Alonso, M. Rosario; Dennis, Joe; Wang, Qin; Bolla, Manjeet K.; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk; Ko, Yon-Dschun; Brauch, Hiltrud; Hamann, Ute; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Li, Jingmei; Brand, Judith S.; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Lambrechts, Diether; Peuteman, Gilian; Christiaens, Marie-Rose; Smeets, Ann; Jakubowska, Anna; Lubinski, Jan; Jaworska-Bieniek, Katarzyna; Durda, Katazyna; Hartman, Mikael; Hui, Miao; Yen Lim, Wei; Wan Chan, Ching; Marme, Federick; Yang, Rongxi; Bugert, Peter; Lindblom, Annika; Margolin, Sara; García-Closas, Montserrat; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Bojesen, Stig E.; Nordestgaard, Børge G.; Flyger, Henrik; Hooning, Maartje J.; Kriege, Mieke; van den Ouweland, Ans M.W.; Koppert, Linetta B.; Fletcher, Olivia; Johnson, Nichola; dos-Santos-Silva, Isabel; Peto, Julian; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha J.; Long, Jirong; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Cox, Angela; Cross, Simon S.; Reed, Malcolm W.R.; Schmidt, Marjanka K.; Broeks, Annegien; Cornelissen, Sten; Braaf, Linde; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Noh, Dong-Young; Simard, Jacques; Dumont, Martine; Goldberg, Mark S.; Labrèche, France; Fasching, Peter A.; Hein, Alexander; Ekici, Arif B.; Beckmann, Matthias W.; Radice, Paolo; Peterlongo, Paolo; Azzollini, Jacopo; Barile, Monica; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Miller, Nicola; Hopper, John L.; Schmidt, Daniel F.; Makalic, Enes; Southey, Melissa C.; Hwang Teo, Soo; Har Yip, Cheng; Sivanandan, Kavitta; Tay, Wan-Ting; Shen, Chen-Yang; Hsiung, Chia-Ni; Yu, Jyh-Cherng; Hou, Ming-Feng; Guénel, Pascal; Truong, Therese; Sanchez, Marie; Mulot, Claire; Blot, William; Cai, Qiuyin; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Wu, Anna H.; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O.; Bogdanova, Natalia; Dörk, Thilo; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Zhang, Ben; Couch, Fergus J.; Toland, Amanda E.; Yannoukakos, Drakoulis; Sangrajrang, Suleeporn; McKay, James; Wang, Xianshu; Olson, Janet E.; Vachon, Celine; Purrington, Kristen; Severi, Gianluca; Baglietto, Laura; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Devilee, Peter; Tollenaar, Robert A.E.M.; Seynaeve, Caroline; Czene, Kamila; Eriksson, Mikael; Humphreys, Keith; Darabi, Hatef; Ahmed, Shahana; Shah, Mitul; Pharoah, Paul D.P.; Hall, Per; Giles, Graham G.; Benítez, Javier; Dunning, Alison M.; Chenevix-Trench, Georgia; Easton, Douglas F.; Berchuck, Andrew; Eeles, Rosalind A.; Olama, Ali Amin Al; Kote-Jarai, Zsofia; Benlloch, Sara; Antoniou, Antonis; McGuffog, Lesley; Offit, Ken; Lee, Andrew; Dicks, Ed; Luccarini, Craig; Tessier, Daniel C.; Bacot, Francois; Vincent, Daniel; LaBoissière, Sylvie; Robidoux, Frederic; Nielsen, Sune F.; Cunningham, Julie M.; Windebank, Sharon A.; Hilker, Christopher A.; Meyer, Jeffrey; Angelakos, Maggie; Maskiell, Judi; van der Schoot, Ellen; Rutgers, Emiel; Verhoef, Senno; Hogervorst, Frans; Boonyawongviroj, Prat; Siriwanarungsan, Pornthep; Schrauder, Michael; Rübner, Matthias; Oeser, Sonja; Landrith, Silke; Williams, Eileen; Ryder-Mills, Elaine; Sargus, Kara; McInerney, Niall; Colleran, Gabrielle; Rowan, Andrew; Jones, Angela; Sohn, Christof; Schneeweiß, Andeas; Bugert, Peter; Álvarez, Núria; Lacey, James; Wang, Sophia; Ma, Huiyan; Lu, Yani; Deapen, Dennis; Pinder, Rich; Lee, Eunjung; Schumacher, Fred; Horn-Ross, Pam; Reynolds, Peggy; Nelson, David; Ziegler, Hartwig; Wolf, Sonja; Hermann, Volker; Lo, Wing-Yee; Justenhoven, Christina; Baisch, Christian; Fischer, Hans-Peter; Brüning, Thomas; Pesch, Beate; Rabstein, Sylvia; Lotz, Anne; Harth, Volker; Heikkinen, Tuomas; Erkkilä, Irja; Aaltonen, Kirsimari; von Smitten, Karl; Antonenkova, Natalia; Hillemanns, Peter; Christiansen, Hans; Myöhänen, Eija; Kemiläinen, Helena; Thorne, Heather; Niedermayr, Eveline; Bowtell, D; Chenevix-Trench, G; deFazio, A; Gertig, D; Green, A; Webb, P; Green, A.; Parsons, P.; Hayward, N.; Webb, P.; Whiteman, D.; Fung, Annie; Yashiki, June; Peuteman, Gilian; Smeets, Dominiek; Brussel, Thomas Van; Corthouts, Kathleen; Obi, Nadia; Heinz, Judith; Behrens, Sabine; Eilber, Ursula; Celik, Muhabbet; Olchers, Til; Manoukian, Siranoush; Peissel, Bernard; Scuvera, Giulietta; Zaffaroni, Daniela; Bonanni, Bernardo; Feroce, Irene; Maniscalco, Angela; Rossi, Alessandra; Bernard, Loris; Tranchant, Martine; Valois, Marie-France; Turgeon, Annie; Heguy, Lea; Sze Yee, Phuah; Kang, Peter; Nee, Kang In; Mariapun, Shivaani; Sook-Yee, Yoon; Lee, Daphne; Ching, Teh Yew; Taib, Nur Aishah Mohd; Otsukka, Meeri; Mononen, Kari; Selander, Teresa; Weerasooriya, Nayana; staff, OFBCR; Krol-Warmerdam, E.; Molenaar, J.; Blom, J.; Brinton, Louise; Szeszenia-Dabrowska, Neonila; Peplonska, Beata; Zatonski, Witold; Chao, Pei; Stagner, Michael; Bos, Petra; Blom, Jannet; Crepin, Ellen; Nieuwlaat, Anja; Heemskerk, Annette; Higham, Sue; Cross, Simon; Cramp, Helen; Connley, Dan; Balasubramanian, Sabapathy; Brock, Ian; Luccarini, Craig; Conroy, Don; Baynes, Caroline; Chua, Kimberley
2014-01-01
Candidate variant association studies have been largely unsuccessful in identifying common breast cancer susceptibility variants, although most studies have been underpowered to detect associations of a realistic magnitude. We assessed 41 common non-synonymous single-nucleotide polymorphisms (nsSNPs) for which evidence of association with breast cancer risk had been previously reported. Case-control data were combined from 38 studies of white European women (46 450 cases and 42 600 controls) and analyzed using unconditional logistic regression. Strong evidence of association was observed for three nsSNPs: ATXN7-K264R at 3p21 [rs1053338, per allele OR = 1.07, 95% confidence interval (CI) = 1.04–1.10, P = 2.9 × 10−6], AKAP9-M463I at 7q21 (rs6964587, OR = 1.05, 95% CI = 1.03–1.07, P = 1.7 × 10−6) and NEK10-L513S at 3p24 (rs10510592, OR = 1.10, 95% CI = 1.07–1.12, P = 5.1 × 10−17). The first two associations reached genome-wide statistical significance in a combined analysis of available data, including independent data from nine genome-wide association studies (GWASs): for ATXN7-K264R, OR = 1.07 (95% CI = 1.05–1.10, P = 1.0 × 10−8); for AKAP9-M463I, OR = 1.05 (95% CI = 1.04–1.07, P = 2.0 × 10−10). Further analysis of other common variants in these two regions suggested that intronic SNPs nearby are more strongly associated with disease risk. We have thus identified a novel susceptibility locus at 3p21, and confirmed previous suggestive evidence that rs6964587 at 7q21 is associated with risk. The third locus, rs10510592, is located in an established breast cancer susceptibility region; the association was substantially attenuated after adjustment for the known GWAS hit. Thus, each of the associated nsSNPs is likely to be a marker for another, non-coding, variant causally related to breast cancer risk. Further fine-mapping and functional studies are required to identify the underlying risk-modifying variants and the genes through which they act. PMID:24943594
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Keel, B N; Nonneman, D J; Rohrer, G A
2017-08-01
Genetic variants detected from sequence have been used to successfully identify causal variants and map complex traits in several organisms. High and moderate impact variants, those expected to alter or disrupt the protein coded by a gene and those that regulate protein production, likely have a more significant effect on phenotypic variation than do other types of genetic variants. Hence, a comprehensive list of these functional variants would be of considerable interest in swine genomic studies, particularly those targeting fertility and production traits. Whole-genome sequence was obtained from 72 of the founders of an intensely phenotyped experimental swine herd at the U.S. Meat Animal Research Center (USMARC). These animals included all 24 of the founding boars (12 Duroc and 12 Landrace) and 48 Yorkshire-Landrace composite sows. Sequence reads were mapped to the Sscrofa10.2 genome build, resulting in a mean of 6.1 fold (×) coverage per genome. A total of 22 342 915 high confidence SNPs were identified from the sequenced genomes. These included 21 million previously reported SNPs and 79% of the 62 163 SNPs on the PorcineSNP60 BeadChip assay. Variation was detected in the coding sequence or untranslated regions (UTRs) of 87.8% of the genes in the porcine genome: loss-of-function variants were predicted in 504 genes, 10 202 genes contained nonsynonymous variants, 10 773 had variation in UTRs and 13 010 genes contained synonymous variants. Approximately 139 000 SNPs were classified as loss-of-function, nonsynonymous or regulatory, which suggests that over 99% of the variation detected in our pigs could potentially be ignored, allowing us to focus on a much smaller number of functional SNPs during future analyses. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
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Pellegrino, Renata; Kavakli, Ibrahim Halil; Goel, Namni; Cardinale, Christopher J; Dinges, David F; Kuna, Samuel T; Maislin, Greg; Van Dongen, Hans P A; Tufik, Sergio; Hogenesch, John B; Hakonarson, Hakon; Pack, Allan I
2014-08-01
Earlier work described a mutation in DEC2 also known as BHLHE41 (basic helix-loophelix family member e41) as causal in a family of short sleepers, who needed just 6 h sleep per night. We evaluated whether there were other variants of this gene in two well-phenotyped cohorts. Sequencing of the BHLHE41 gene, electroencephalographic data, and delta power analysis and functional studies using cell-based luciferase. We identified new variants of the BHLHE41 gene in two cohorts who had either acute sleep deprivation (n = 200) or chronic partial sleep deprivation (n = 217). One variant, Y362H, at another location in the same exon occurred in one twin in a dizygotic twin pair and was associated with reduced sleep duration, less recovery sleep following sleep deprivation, and fewer performance lapses during sleep deprivation than the homozygous twin. Both twins had almost identical amounts of non rapid eye movement (NREM) sleep. This variant reduced the ability of BHLHE41 to suppress CLOCK/BMAL1 and NPAS2/BMAL1 transactivation in vitro. Another variant in the same exome had no effect on sleep or response to sleep deprivation and no effect on CLOCK/BMAL1 transactivation. Random mutagenesis identified a number of other variants of BHLHE41 that affect its function. There are a number of mutations of BHLHE41. Mutations reduce total sleep while maintaining NREM sleep and provide resistance to the effects of sleep loss. Mutations that affect sleep also modify the normal inhibition of BHLHE41 of CLOCK/BMAL1 transactivation. Thus, clock mechanisms are likely involved in setting sleep length and the magnitude of sleep homeostasis. Pellegrino R, Kavakli IH, Goel N, Cardinale CJ, Dinges DF, Kuna ST, Maislin G, Van Dongen HP, Tufik S, Hogenesch JB, Hakonarson H, Pack AI. A novel BHLHE41 variant is associated with short sleep and resistance to sleep deprivation in humans. SLEEP 2014;37(8):1327-1336.
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Estimators for Clustered Education RCTs Using the Neyman Model for Causal Inference
ERIC Educational Resources Information Center
Schochet, Peter Z.
2013-01-01
This article examines the estimation of two-stage clustered designs for education randomized control trials (RCTs) using the nonparametric Neyman causal inference framework that underlies experiments. The key distinction between the considered causal models is whether potential treatment and control group outcomes are considered to be fixed for…
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Child Care Subsidy Use and Child Development: Potential Causal Mechanisms
ERIC Educational Resources Information Center
Hawkinson, Laura E.
2011-01-01
Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…
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Dongiovanni, P; Stender, S; Pietrelli, A; Mancina, R M; Cespiati, A; Petta, S; Pelusi, S; Pingitore, P; Badiali, S; Maggioni, M; Mannisto, V; Grimaudo, S; Pipitone, R M; Pihlajamaki, J; Craxi, A; Taube, M; Carlsson, L M S; Fargion, S; Romeo, S; Kozlitina, J; Valenti, L
2018-04-01
Nonalcoholic fatty liver disease is epidemiologically associated with hepatic and metabolic disorders. The aim of this study was to examine whether hepatic fat accumulation has a causal role in determining liver damage and insulin resistance. We performed a Mendelian randomization analysis using risk alleles in PNPLA3, TM6SF2, GCKR and MBOAT7, and a polygenic risk score for hepatic fat, as instruments. We evaluated complementary cohorts of at-risk individuals and individuals from the general population: 1515 from the liver biopsy cohort (LBC), 3329 from the Swedish Obese Subjects Study (SOS) and 4570 from the population-based Dallas Heart Study (DHS). Hepatic fat was epidemiologically associated with liver damage, insulin resistance, dyslipidemia and hypertension. The impact of genetic variants on liver damage was proportional to their effect on hepatic fat accumulation. Genetically determined hepatic fat was associated with aminotransferases, and with inflammation, ballooning and fibrosis in the LBC. Furthermore, in the LBC, the causal association between hepatic fat and fibrosis was independent of disease activity, suggesting that a causal effect of long-term liver fat accumulation on liver disease is independent of inflammation. Genetically determined hepatic steatosis was associated with insulin resistance in the LBC and SOS. However, this association was dependent on liver damage severity. Genetically determined hepatic steatosis was associated with liver fibrosis/cirrhosis and with a small increase in risk of type 2 diabetes in publicly available databases. These data suggest that long-term hepatic fat accumulation plays a causal role in the development of chronic liver disease. © 2017 The Authors Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.
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Pierce, Brandon L; Tong, Lin; Argos, Maria; Gao, Jianjun; Farzana, Jasmine; Roy, Shantanu; Paul-Brutus, Rachelle; Rahaman, Ronald; Rakibuz-Zaman, Muhammad; Parvez, Faruque; Ahmed, Alauddin; Quasem, Iftekhar; Hore, Samar K; Alam, Shafiul; Islam, Tariqul; Harjes, Judith; Sarwar, Golam; Slavkovich, Vesna; Gamble, Mary V; Chen, Yu; Yunus, Mohammad; Rahman, Mahfuzar; Baron, John A; Graziano, Joseph H; Ahsan, Habibul
2013-12-01
Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal. Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls. Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62). We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.
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Gomes, Clarissa P C; Nagata, Tatsuya; de Jesus, Waldir C; Neto, Carlos R Borges; Pappas, Georgios J; Martin, Darren P
2008-01-16
Citrus sudden death (CSD), a disease that rapidly kills orange trees, is an emerging threat to the Brazilian citrus industry. Although the causal agent of CSD has not been definitively determined, based on the disease's distribution and symptomatology it is suspected that the agent may be a new strain of Citrus tristeza virus (CTV). CTV genetic variation was therefore assessed in two Brazilian orange trees displaying CSD symptoms and a third with more conventional CTV symptoms. A total of 286 RNA-dependent-RNA polymerase (RdRp) and 284 heat shock protein 70 homolog (HSP70h) gene fragments were determined for CTV variants infecting the three trees. It was discovered that, despite differences in symptomatology, the trees were all apparently coinfected with similar populations of divergent CTV variants. While mixed CTV infections are common, the genetic distance between the most divergent population members observed (24.1% for RdRp and 11.0% for HSP70h) was far greater than that in previously described mixed infections. Recombinants of five distinct RdRp lineages and three distinct HSP70h lineages were easily detectable but respectively accounted for only 5.9 and 11.9% of the RdRp and HSP70h gene fragments analysed and there was no evidence of an association between particular recombinant mosaics and CSD. Also, comparisons of CTV population structures indicated that the two most similar CTV populations were those of one of the trees with CSD and the tree without CSD. We suggest that if CTV is the causal agent of CSD, it is most likely a subtle feature of population structures within mixed infections and not merely the presence (or absence) of a single CTV variant within these populations that triggers the disease.
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Xie, Jingyuan; Kiryluk, Krzysztof; Li, Yifu; Mladkova, Nikol; Zhu, Li; Hou, Ping; Ren, Hong; Wang, Weiming; Zhang, Hong; Chen, Nan
2016-01-01
An intronic variant at the complement factor H (CFH) gene on chromosome 1q32 (rs6677604) associates with risk of IgA nephropathy (IgAN), but the association signal has not been uniformly replicated in Han Chinese populations. We investigated whether the causal sequence variant resides in the CFH gene or the neighboring complement factor H–related 1 (CFHR1) gene and CFHR3, which harbor an 84-kb combined deletion (CFHR3,1Δ) in linkage disequilibrium with rs6677604. Imputation of 1000 Genomes Project data did not suggest new causal single–nucleotide variants within the CFH cluster. We next performed copy number analysis across the CFH locus in two independent Han Chinese case-control cohorts (combined n=3581). The CFHR3,1Δ and rs6677604-A alleles were rare (4.4% in patients and 7.1% in controls) and in strong linkage disequilibrium with each other (r2=0.95); of these alleles, CFHR3,1Δ associated more significantly with decreased risk of IgAN (odds ratio [OR], 0.56; 95% confidence interval [95% CI], 0.46 to 0.70; P=8.5 × 10−8 versus OR, 0.61; 95% CI, 0.50 to 0.75; P=1.6 × 10−6 for rs6677604-A). Moreover, CFHR3,1Δ explained all of the association signal at rs6677604 and remained significant after conditioning on rs6677604 genotype (P=0.01). Exploratory analyses of clinical and histopathologic parameters using the Oxford classification criteria revealed a suggestive association of CFHR3,1Δ with reduced tubulointerstitial injury (OR, 0.46; 95% CI, 0.25 to 0.79). These data indicate that dysregulated activity of the alternative complement pathway contributes to IgAN pathogenesis in both Asians and Europeans and implicate CFHR3,1Δ as the functional allele at this locus. PMID:26940089
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Koenighofer, M; Hung, C Y; McCauley, J L; Dallman, J; Back, E J; Mihalek, I; Gripp, K W; Sol-Church, K; Rusconi, P; Zhang, Z; Shi, G-X; Andres, D A; Bodamer, O A
2016-03-01
RASopathies are a clinically heterogeneous group of conditions caused by mutations in 1 of 16 proteins in the RAS-mitogen activated protein kinase (RAS-MAPK) pathway. Recently, mutations in RIT1 were identified as a novel cause for Noonan syndrome. Here we provide additional functional evidence for a causal role of RIT1 mutations and expand the associated phenotypic spectrum. We identified two de novo missense variants p.Met90Ile and p.Ala57Gly. Both variants resulted in increased MEK-ERK signaling compared to wild-type, underscoring gain-of-function as the primary functional mechanism. Introduction of p.Met90Ile and p.Ala57Gly into zebrafish embryos reproduced not only aspects of the human phenotype but also revealed abnormalities of eye development, emphasizing the importance of RIT1 for spatial and temporal organization of the growing organism. In addition, we observed severe lymphedema of the lower extremity and genitalia in one patient. We provide additional evidence for a causal relationship between pathogenic mutations in RIT1, increased RAS-MAPK/MEK-ERK signaling and the clinical phenotype. The mutant RIT1 protein may possess reduced GTPase activity or a diminished ability to interact with cellular GTPase activating proteins; however the precise mechanism remains unknown. The phenotypic spectrum is likely to expand and includes lymphedema of the lower extremities in addition to nuchal hygroma. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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New insights into susceptibility to glioma.
Liu, Yanhong; Shete, Sanjay; Hosking, Fay J; Robertson, Lindsay B; Bondy, Melissa L; Houlston, Richard S
2010-03-01
The study of inherited susceptibility to cancer has been one of the most informative areas of research in the past decade. Most of the cancer genetics studies have been focused on the common tumors such as breast and colorectal cancers. As the allelic architecture of these tumors is unraveled, research attention is turning to other rare cancers such as glioma, which are also likely to have a major genetic component as the basis of their development. In this brief review we discuss emerging data on glioma whole genome-association searches to identify risk loci. Two glioma genome-wide association studies have so far been reported. Our group identified 5 risk loci for glioma susceptibility (TERT rs2736100, CCDC26 rs4295627, CDKN2A/CDKN2B rs4977756, RTEL1 rs6010620, and PHLDB1 rs498872). Wrensch and colleagues provided further evidence to 2 risk loci (CDKN2B rs1412829 and RTEL1 rs6010620) for GBM and anaplastic astrocytoma. Although these data provide the strongest evidence to date for the role of common low-risk variants in the etiology of glioma, the single-nucleotide polymorphisms identified alone are unlikely to be candidates for causality. Identifying the causal variant at each specific locus and its biological impact now poses a significant challenge, contingent on a combination of fine mapping and functional analyses. Finally, we hope that a greater understanding of the biological basis of the disease will lead to the development of novel therapeutic interventions.
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Jansen, Henning; Loley, Christina; Lieb, Wolfgang; Pencina, Michael J; Nelson, Christopher P; Kathiresan, Sekar; Peloso, Gina M; Voight, Benjamin F; Reilly, Muredach P; Assimes, Themistocles L; Boerwinkle, Eric; Hengstenberg, Christian; Laaksonen, Reijo; McPherson, Ruth; Roberts, Robert; Thorsteinsdottir, Unnur; Peters, Annette; Gieger, Christian; Rawal, Rajesh; Thompson, John R; König, Inke R; Vasan, Ramachandran S; Erdmann, Jeanette; Samani, Nilesh J; Schunkert, Heribert
2015-01-01
Background The mechanisms underlying the association between diabetes and coronary artery disease (CAD) risk are unclear. We aimed to assess this association by studying genetic variants that have been shown to associate with type 2 diabetes (T2DM). If the association between diabetes and CAD is causal, we expected to observe an association of these variants with CAD as well. Methods and Results We studied all genetic variants currently known to be associated with T2DM at a genome-wide significant level (p<5*10−8) in CARDIoGRAM, a genome-wide data-set of CAD including 22,233 CAD cases and 64,762 controls. Out of the 44 published T2DM SNPs 10 were significantly associated with CAD in CARDIoGRAM (OR>1, p<0.05), more than expected by chance (p=5.0*10−5). Considering all 44 SNPs, the average CAD risk observed per individual T2DM risk allele was 1.0076 (95% confidence interval (CI), 0.9973–1.0180). Such average risk increase was significantly lower than the increase expected based on i) the published effects of the SNPs on T2DM risk and ii) the effect of T2DM on CAD risk as observed in the Framingham Heart Study, which suggested a risk of 1.067 per allele (p=7.2*10−10 vs. the observed effect). Studying two risk scores based on risk alleles of the diabetes SNPs, one score using individual level data in 9856 subjects, and the second score on average effects of reported beta-coefficients from the entire CARDIoGRAM data-set, we again observed a significant - yet smaller than expected - association with CAD. Conclusions Our data indicate that an association between type 2 diabetes related SNPs and CAD exists. However, the effects on CAD risk appear to be by far lower than what would be expected based on the effects of risk alleles on T2DM and the effect of T2DM on CAD in the epidemiological setting. PMID:26074316
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[Burns in childhood. Social implications in the eve of the year 2000].
Abad, P; Acosta, D; Martínez Ibáñez, V; Lloret, J; Patiño, B; Gubern, L; Carol, J; Boix Ochoa, J
2000-07-01
The thermic wounds in childhood are the third cause of morbility at hospital in our ambiance. The knowledge about incidence, the causal agents more frequent, and the detailed analysis of different variants about the subject are the unique manner to try to establish precautions against. The aim of this project is to analyse the factors and situations associated with thermic wound, through the retrospective study about the patients admitted. During three years, 362 patients were admitted at hospital, between 0 and 14 years old, following the criterion: barge burn size more than 10%, critical location (hands, face, neck), causal agent (electricity, chemical) or social situation. Different facts were analyzed about provenance, place, causal agent, burned part of the body, degree of lesion and the average stay at hospital. There were 59.6% males, and 40.3% females. Children between 1 and 5 years old, represented the largest group of patients, 205 cases. The 66% were from other hospital were they receive the first aid. The 98.7% were burned at home, and the place more frequent was kitchen, 51%. The causal agent was liquid in 65.4%, specially scald with water about 104 cases. The zones more affected were the face (39.2%), and the superior extremities, about 81% second degree superficial or deep. The size was 10 to 20% in 19% of patients, and more than 40% in 0.2% of children. The average stay was 17.47 days at hospital.
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Age at Menarche and Time Spent in Education: A Mendelian Randomization Study.
Gill, D; Del Greco M, F; Rawson, T M; Sivakumaran, P; Brown, A; Sheehan, N A; Minelli, C
2017-09-01
Menarche signifies the primary event in female puberty and is associated with changes in self-identity. It is not clear whether earlier puberty causes girls to spend less time in education. Observational studies on this topic are likely to be affected by confounding environmental factors. The Mendelian randomization (MR) approach addresses these issues by using genetic variants (such as single nucleotide polymorphisms, SNPs) as proxies for the risk factor of interest. We use this technique to explore whether there is a causal effect of age at menarche on time spent in education. Instruments and SNP-age at menarche estimates are identified from a Genome Wide Association Study (GWAS) meta-analysis of 182,416 women of European descent. The effects of instruments on time spent in education are estimated using a GWAS meta-analysis of 118,443 women performed by the Social Science Genetic Association Consortium (SSGAC). In our main analysis, we demonstrate a small but statistically significant causal effect of age at menarche on time spent in education: a 1 year increase in age at menarche is associated with 0.14 years (53 days) increase in time spent in education (95% CI 0.10-0.21 years, p = 3.5 × 10 -8 ). The causal effect is confirmed in sensitivity analyses. In identifying this positive causal effect of age at menarche on time spent in education, we offer further insight into the social effects of puberty in girls.
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A Mouse Model for the Metabolic Effects of the Human Fat Mass and Obesity Associated FTO Gene
Church, Chris; Deacon, Robert; Gerken, Thomas; Lee, Angela; Moir, Lee; Mecinović, Jasmin; Quwailid, Mohamed M.; Schofield, Christopher J.; Ashcroft, Frances M.; Cox, Roger D.
2009-01-01
Human FTO gene variants are associated with body mass index and type 2 diabetes. Because the obesity-associated SNPs are intronic, it is unclear whether changes in FTO expression or splicing are the cause of obesity or if regulatory elements within intron 1 influence upstream or downstream genes. We tested the idea that FTO itself is involved in obesity. We show that a dominant point mutation in the mouse Fto gene results in reduced fat mass, increased energy expenditure, and unchanged physical activity. Exposure to a high-fat diet enhances lean mass and lowers fat mass relative to control mice. Biochemical studies suggest the mutation occurs in a structurally novel domain and modifies FTO function, possibly by altering its dimerisation state. Gene expression profiling revealed increased expression of some fat and carbohydrate metabolism genes and an improved inflammatory profile in white adipose tissue of mutant mice. These data provide direct functional evidence that FTO is a causal gene underlying obesity. Compared to the reported mouse FTO knockout, our model more accurately reflects the effect of human FTO variants; we observe a heterozygous as well as homozygous phenotype, a smaller difference in weight and adiposity, and our mice do not show perinatal lethality or an age-related reduction in size and length. Our model suggests that a search for human coding mutations in FTO may be informative and that inhibition of FTO activity is a possible target for the treatment of morbid obesity. PMID:19680540
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de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.
2012-01-01
Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806
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Functional Brain Networks and White Matter Underlying Theory-of-Mind in Autism
Kana, Rajesh K.; Libero, Lauren E.; Hu, Christi P.; Deshpande, Hrishikesh D.; Colburn, Jeffrey S.
2014-01-01
Human beings constantly engage in attributing causal explanations to one’s own and to others’ actions, and theory-of-mind (ToM) is critical in making such inferences. Although children learn causal attribution early in development, children with autism spectrum disorders (ASDs) are known to have impairments in the development of intentional causality. This functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) study investigated the neural correlates of physical and intentional causal attribution in people with ASDs. In the fMRI scanner, 15 adolescents and adults with ASDs and 15 age- and IQ-matched typically developing peers made causal judgments about comic strips presented randomly in an event-related design. All participants showed robust activation in bilateral posterior superior temporal sulcus at the temporo-parietal junction (TPJ) in response to intentional causality. Participants with ASDs showed lower activation in TPJ, right inferior frontal gyrus and left premotor cortex. Significantly weaker functional connectivity was also found in the ASD group between TPJ and motor areas during intentional causality. DTI data revealed significantly reduced fractional anisotropy in ASD participants in white matter underlying the temporal lobe. In addition to underscoring the role of TPJ in ToM, this study found an interaction between motor simulation and mentalizing systems in intentional causal attribution and its possible discord in autism. PMID:22977198
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Using genetic data to strengthen causal inference in observational research.
Pingault, Jean-Baptiste; O'Reilly, Paul F; Schoeler, Tabea; Ploubidis, George B; Rijsdijk, Frühling; Dudbridge, Frank
2018-06-05
Causal inference is essential across the biomedical, behavioural and social sciences.By progressing from confounded statistical associations to evidence of causal relationships, causal inference can reveal complex pathways underlying traits and diseases and help to prioritize targets for intervention. Recent progress in genetic epidemiology - including statistical innovation, massive genotyped data sets and novel computational tools for deep data mining - has fostered the intense development of methods exploiting genetic data and relatedness to strengthen causal inference in observational research. In this Review, we describe how such genetically informed methods differ in their rationale, applicability and inherent limitations and outline how they should be integrated in the future to offer a rich causal inference toolbox.
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Redundant variables and Granger causality
NASA Astrophysics Data System (ADS)
Angelini, L.; de Tommaso, M.; Marinazzo, D.; Nitti, L.; Pellicoro, M.; Stramaglia, S.
2010-03-01
We discuss the use of multivariate Granger causality in presence of redundant variables: the application of the standard analysis, in this case, leads to under estimation of causalities. Using the un-normalized version of the causality index, we quantitatively develop the notions of redundancy and synergy in the frame of causality and propose two approaches to group redundant variables: (i) for a given target, the remaining variables are grouped so as to maximize the total causality and (ii) the whole set of variables is partitioned to maximize the sum of the causalities between subsets. We show the application to a real neurological experiment, aiming to a deeper understanding of the physiological basis of abnormal neuronal oscillations in the migraine brain. The outcome by our approach reveals the change in the informational pattern due to repetitive transcranial magnetic stimulations.
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Camps, Carme; Petousi, Nayia; Bento, Celeste; Cario, Holger; Copley, Richard R.; McMullin, Mary Frances; van Wijk, Richard; Ratcliffe, Peter J.; Robbins, Peter A.; Taylor, Jenny C.
2016-01-01
Erythrocytosis is a rare disorder characterized by increased red cell mass and elevated hemoglobin concentration and hematocrit. Several genetic variants have been identified as causes for erythrocytosis in genes belonging to different pathways including oxygen sensing, erythropoiesis and oxygen transport. However, despite clinical investigation and screening for these mutations, the cause of disease cannot be found in a considerable number of patients, who are classified as having idiopathic erythrocytosis. In this study, we developed a targeted next-generation sequencing panel encompassing the exonic regions of 21 genes from relevant pathways (~79 Kb) and sequenced 125 patients with idiopathic erythrocytosis. The panel effectively screened 97% of coding regions of these genes, with an average coverage of 450×. It identified 51 different rare variants, all leading to alterations of protein sequence, with 57 out of 125 cases (45.6%) having at least one of these variants. Ten of these were known erythrocytosis-causing variants, which had been missed following existing diagnostic algorithms. Twenty-two were novel variants in erythrocytosis-associated genes (EGLN1, EPAS1, VHL, BPGM, JAK2, SH2B3) and in novel genes included in the panel (e.g. EPO, EGLN2, HIF3A, OS9), some with a high likelihood of functionality, for which future segregation, functional and replication studies will be useful to provide further evidence for causality. The rest were classified as polymorphisms. Overall, these results demonstrate the benefits of using a gene panel rather than existing methods in which focused genetic screening is performed depending on biochemical measurements: the gene panel improves diagnostic accuracy and provides the opportunity for discovery of novel variants. PMID:27651169
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Camps, Carme; Petousi, Nayia; Bento, Celeste; Cario, Holger; Copley, Richard R; McMullin, Mary Frances; van Wijk, Richard; Ratcliffe, Peter J; Robbins, Peter A; Taylor, Jenny C
2016-11-01
Erythrocytosis is a rare disorder characterized by increased red cell mass and elevated hemoglobin concentration and hematocrit. Several genetic variants have been identified as causes for erythrocytosis in genes belonging to different pathways including oxygen sensing, erythropoiesis and oxygen transport. However, despite clinical investigation and screening for these mutations, the cause of disease cannot be found in a considerable number of patients, who are classified as having idiopathic erythrocytosis. In this study, we developed a targeted next-generation sequencing panel encompassing the exonic regions of 21 genes from relevant pathways (~79 Kb) and sequenced 125 patients with idiopathic erythrocytosis. The panel effectively screened 97% of coding regions of these genes, with an average coverage of 450×. It identified 51 different rare variants, all leading to alterations of protein sequence, with 57 out of 125 cases (45.6%) having at least one of these variants. Ten of these were known erythrocytosis-causing variants, which had been missed following existing diagnostic algorithms. Twenty-two were novel variants in erythrocytosis-associated genes (EGLN1, EPAS1, VHL, BPGM, JAK2, SH2B3) and in novel genes included in the panel (e.g. EPO, EGLN2, HIF3A, OS9), some with a high likelihood of functionality, for which future segregation, functional and replication studies will be useful to provide further evidence for causality. The rest were classified as polymorphisms. Overall, these results demonstrate the benefits of using a gene panel rather than existing methods in which focused genetic screening is performed depending on biochemical measurements: the gene panel improves diagnostic accuracy and provides the opportunity for discovery of novel variants. Copyright© Ferrata Storti Foundation.
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Howard, Sasha R; Guasti, Leonardo; Poliandri, Ariel; David, Alessia; Cabrera, Claudia P; Barnes, Michael R; Wehkalampi, Karoliina; O'Rahilly, Stephen; Aiken, Catherine E; Coll, Anthony P; Ma, Marcella; Rimmington, Debra; Yeo, Giles S H; Dunkel, Leo
2018-02-01
Self-limited delayed puberty (DP) is often associated with a delay in physical maturation, but although highly heritable the causal genetic factors remain elusive. Genome-wide association studies of the timing of puberty have identified multiple loci for age at menarche in females and voice break in males, particularly in pathways controlling energy balance. We sought to assess the contribution of rare variants in such genes to the phenotype of familial DP. We performed whole-exome sequencing in 67 pedigrees (125 individuals with DP and 35 unaffected controls) from our unique cohort of familial self-limited DP. Using a whole-exome sequencing filtering pipeline one candidate gene [fat mass and obesity-associated gene (FTO)] was identified. In silico, in vitro, and mouse model studies were performed to investigate the pathogenicity of FTO variants and timing of puberty in FTO+/- mice. We identified potentially pathogenic, rare variants in genes in linkage disequilibrium with genome-wide association studies of age at menarche loci in 283 genes. Of these, five genes were implicated in the control of body mass. After filtering for segregation with trait, one candidate, FTO, was retained. Two FTO variants, found in 14 affected individuals from three families, were also associated with leanness in these patients with DP. One variant (p.Leu44Val) demonstrated altered demethylation activity of the mutant protein in vitro. Fto+/- mice displayed a significantly delayed timing of pubertal onset (P < 0.05). Mutations in genes implicated in body mass and timing of puberty in the general population may contribute to the pathogenesis of self-limited DP. Copyright © 2017 Endocrine Society
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Morrison, Jean V.; Brown, Lisa; Schurmann, Claudia; Chen, Diane D.; Liu, Yong Mei; Auer, Paul L.; Taylor, Kent D.; Papanicolaou, George; Kurita, Ryo; Nakamura, Yukio; Loos, Ruth J. F.; North, Kari E.; Thornton, Timothy A.; Pankratz, Nathan; Bauer, Daniel E.
2017-01-01
Prior GWAS have identified loci associated with red blood cell (RBC) traits in populations of European, African, and Asian ancestry. These studies have not included individuals with an Amerindian ancestral background, such as Hispanics/Latinos, nor evaluated the full spectrum of genomic variation beyond single nucleotide variants. Using a custom genotyping array enriched for Amerindian ancestral content and 1000 Genomes imputation, we performed GWAS in 12,502 participants of Hispanic Community Health Study and Study of Latinos (HCHS/SOL) for hematocrit, hemoglobin, RBC count, RBC distribution width (RDW), and RBC indices. Approximately 60% of previously reported RBC trait loci generalized to HCHS/SOL Hispanics/Latinos, including African ancestral alpha- and beta-globin gene variants. In addition to the known 3.8kb alpha-globin copy number variant, we identified an Amerindian ancestral association in an alpha-globin regulatory region on chromosome 16p13.3 for mean corpuscular volume and mean corpuscular hemoglobin. We also discovered and replicated three genome-wide significant variants in previously unreported loci for RDW (SLC12A2 rs17764730, PSMB5 rs941718), and hematocrit (PROX1 rs3754140). Among the proxy variants at the SLC12A2 locus we identified rs3812049, located in a bi-directional promoter between SLC12A2 (which encodes a red cell membrane ion-transport protein) and an upstream anti-sense long-noncoding RNA, LINC01184, as the likely causal variant. We further demonstrate that disruption of the regulatory element harboring rs3812049 affects transcription of SLC12A2 and LINC01184 in human erythroid progenitor cells. Together, these results reinforce the importance of genetic study of diverse ancestral populations, in particular Hispanics/Latinos. PMID:28453575
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Olson, Heather E; Jean-Marçais, Nolwenn; Yang, Edward; Heron, Delphine; Tatton-Brown, Katrina; van der Zwaag, Paul A; Bijlsma, Emilia K; Krock, Bryan L; Backer, E; Kamsteeg, Erik-Jan; Sinnema, Margje; Reijnders, Margot R F; Bearden, David; Begtrup, Amber; Telegrafi, Aida; Lunsing, Roelineke J; Burglen, Lydie; Lesca, Gaetan; Cho, Megan T; Smith, Lacey A; Sheidley, Beth R; Moufawad El Achkar, Christelle; Pearl, Phillip L; Poduri, Annapurna; Skraban, Cara M; Tarpinian, Jennifer; Nesbitt, Addie I; Fransen van de Putte, Dietje E; Ruivenkamp, Claudia A L; Rump, Patrick; Chatron, Nicolas; Sabatier, Isabelle; De Bellescize, Julitta; Guibaud, Laurent; Sweetser, David A; Waxler, Jessica L; Wierenga, Klaas J; Donadieu, Jean; Narayanan, Vinodh; Ramsey, Keri M; Nava, Caroline; Rivière, Jean-Baptiste; Vitobello, Antonio; Tran Mau-Them, Frédéric; Philippe, Christophe; Bruel, Ange-Line; Duffourd, Yannis; Thomas, Laurel; Lelieveld, Stefan H; Schuurs-Hoeijmakers, Janneke; Brunner, Han G; Keren, Boris; Thevenon, Julien; Faivre, Laurence; Thomas, Gary; Thauvin-Robinet, Christel
2018-05-03
Developmental and epileptic encephalopathies (DEEs) represent a large clinical and genetic heterogeneous group of neurodevelopmental diseases. The identification of pathogenic genetic variants in DEEs remains crucial for deciphering this complex group and for accurately caring for affected individuals (clinical diagnosis, genetic counseling, impacting medical, precision therapy, clinical trials, etc.). Whole-exome sequencing and intensive data sharing identified a recurrent de novo PACS2 heterozygous missense variant in 14 unrelated individuals. Their phenotype was characterized by epilepsy, global developmental delay with or without autism, common cerebellar dysgenesis, and facial dysmorphism. Mixed focal and generalized epilepsy occurred in the neonatal period, controlled with difficulty in the first year, but many improved in early childhood. PACS2 is an important PACS1 paralog and encodes a multifunctional sorting protein involved in nuclear gene expression and pathway traffic regulation. Both proteins harbor cargo(furin)-binding regions (FBRs) that bind cargo proteins, sorting adaptors, and cellular kinase. Compared to the defined PACS1 recurrent variant series, individuals with PACS2 variant have more consistently neonatal/early-infantile-onset epilepsy that can be challenging to control. Cerebellar abnormalities may be similar but PACS2 individuals exhibit a pattern of clear dysgenesis ranging from mild to severe. Functional studies demonstrated that the PACS2 recurrent variant reduces the ability of the predicted autoregulatory domain to modulate the interaction between the PACS2 FBR and client proteins, which may disturb cellular function. These findings support the causality of this recurrent de novo PACS2 heterozygous missense in DEEs with facial dysmorphim and cerebellar dysgenesis. Copyright © 2018 American Society of Human Genetics. All rights reserved.
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Can chance cause cancer? A causal consideration.
Stensrud, Mats Julius; Strohmaier, Susanne; Valberg, Morten; Aalen, Odd Olai
2017-04-01
The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonising views arise due to estimation of substantially different causal effects. These effects may be hard to interpret, and the results cannot be immediately compared. Indeed, it is not clear whether it is possible to define a causal effect of chance at all. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Estimating Causal Effects with Ancestral Graph Markov Models
Malinsky, Daniel; Spirtes, Peter
2017-01-01
We present an algorithm for estimating bounds on causal effects from observational data which combines graphical model search with simple linear regression. We assume that the underlying system can be represented by a linear structural equation model with no feedback, and we allow for the possibility of latent variables. Under assumptions standard in the causal search literature, we use conditional independence constraints to search for an equivalence class of ancestral graphs. Then, for each model in the equivalence class, we perform the appropriate regression (using causal structure information to determine which covariates to include in the regression) to estimate a set of possible causal effects. Our approach is based on the “IDA” procedure of Maathuis et al. (2009), which assumes that all relevant variables have been measured (i.e., no unmeasured confounders). We generalize their work by relaxing this assumption, which is often violated in applied contexts. We validate the performance of our algorithm on simulated data and demonstrate improved precision over IDA when latent variables are present. PMID:28217244
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Taylor, Amy E; Fluharty, Meg E; Bjørngaard, Johan H; Gabrielsen, Maiken Elvestad; Skorpen, Frank; Marioni, Riccardo E; Campbell, Archie; Engmann, Jorgen; Mirza, Saira Saeed; Loukola, Anu; Laatikainen, Tiina; Partonen, Timo; Kaakinen, Marika; Ducci, Francesca; Cavadino, Alana; Husemoen, Lise Lotte N; Ahluwalia, Tarunveer Singh; Jacobsen, Rikke Kart; Skaaby, Tea; Ebstrup, Jeanette Frost; Mortensen, Erik Lykke; Minica, Camelia C; Vink, Jacqueline M; Willemsen, Gonneke; Marques-Vidal, Pedro; Dale, Caroline E; Amuzu, Antoinette; Lennon, Lucy T; Lahti, Jari; Palotie, Aarno; Räikkönen, Katri; Wong, Andrew; Paternoster, Lavinia; Wong, Angelita Pui-Yee; Horwood, L John; Murphy, Michael; Johnstone, Elaine C; Kennedy, Martin A; Pausova, Zdenka; Paus, Tomáš; Ben-Shlomo, Yoav; Nohr, Ellen A; Kuh, Diana; Kivimaki, Mika; Eriksson, Johan G; Morris, Richard W; Casas, Juan P; Preisig, Martin; Boomsma, Dorret I; Linneberg, Allan; Power, Chris; Hyppönen, Elina; Veijola, Juha; Jarvelin, Marjo-Riitta; Korhonen, Tellervo; Tiemeier, Henning; Kumari, Meena; Porteous, David J; Hayward, Caroline; Romundstad, Pål R; Smith, George Davey; Munafò, Marcus R
2014-10-07
To investigate whether associations of smoking with depression and anxiety are likely to be causal, using a Mendelian randomisation approach. Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730) as a proxy for smoking heaviness, and observational meta-analyses of the associations of smoking status and smoking heaviness with depression, anxiety and psychological distress. Current, former and never smokers of European ancestry aged ≥16 years from 25 studies in the Consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). Binary definitions of depression, anxiety and psychological distress assessed by clinical interview, symptom scales or self-reported recall of clinician diagnosis. The analytic sample included up to 58 176 never smokers, 37 428 former smokers and 32 028 current smokers (total N=127 632). In observational analyses, current smokers had 1.85 times greater odds of depression (95% CI 1.65 to 2.07), 1.71 times greater odds of anxiety (95% CI 1.54 to 1.90) and 1.69 times greater odds of psychological distress (95% CI 1.56 to 1.83) than never smokers. Former smokers also had greater odds of depression, anxiety and psychological distress than never smokers. There was evidence for positive associations of smoking heaviness with depression, anxiety and psychological distress (ORs per cigarette per day: 1.03 (95% CI 1.02 to 1.04), 1.03 (95% CI 1.02 to 1.04) and 1.02 (95% CI 1.02 to 1.03) respectively). In Mendelian randomisation analyses, there was no strong evidence that the minor allele of rs16969968/rs1051730 was associated with depression (OR=1.00, 95% CI 0.95 to 1.05), anxiety (OR=1.02, 95% CI 0.97 to 1.07) or psychological distress (OR=1.02, 95% CI 0.98 to 1.06) in current smokers. Results were similar for former smokers. Findings from Mendelian randomisation analyses do not support a causal role of smoking heaviness in the development of depression and anxiety. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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ERIC Educational Resources Information Center
Hayes, Brett K.; Hawkins, Guy E.; Newell, Ben R.
2016-01-01
Four experiments examined the locus of impact of causal knowledge on consideration of alternative hypotheses in judgments under uncertainty. Two possible loci were examined; overcoming neglect of the alternative when developing a representation of a judgment problem and improving utilization of statistics associated with the alternative…
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An update on the genetics of hyperuricaemia and gout.
Major, Tanya J; Dalbeth, Nicola; Stahl, Eli A; Merriman, Tony R
2018-06-01
A central aspect of the pathogenesis of gout is elevated urate concentrations, which lead to the formation of monosodium urate crystals. The clinical features of gout result from an individual's immune response to these deposited crystals. Genome-wide association studies (GWAS) have confirmed the importance of urate excretion in the control of serum urate levels and the risk of gout and have identified the kidneys, the gut and the liver as sites of urate regulation. The genetic contribution to the progression from hyperuricaemia to gout remains relatively poorly understood, although genes encoding proteins that are involved in the NLRP3 (NOD-, LRR- and pyrin domain-containing 3) inflammasome pathway play a part. Genome-wide and targeted sequencing is beginning to identify uncommon population-specific variants that are associated with urate levels and gout. Mendelian randomization studies using urate-associated genetic variants as unconfounded surrogates for lifelong urate exposure have not supported claims that urate is causal for metabolic conditions that are comorbidities of hyperuricaemia and gout. Genetic studies have also identified genetic variants that predict responsiveness to therapies (for example, urate-lowering drugs) for treatment of hyperuricaemia. Future research should focus on large GWAS (that include asymptomatic hyperuricaemic individuals) and on increasing the use of whole-genome sequencing data to identify uncommon genetic variants with increased penetrance that might provide opportunities for clinical translation.
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Coulonges, Cedric; Bartha, István; Lenz, Tobias L.; Deutsch, Aaron J.; Bashirova, Arman; Buchbinder, Susan; Carrington, Mary N.; Cossarizza, Andrea; Dalmau, Judith; De Luca, Andrea; Goedert, James J.; Gurdasani, Deepti; Haas, David W.; Herbeck, Joshua T.; Johnson, Eric O.; Kirk, Gregory D.; Lambotte, Olivier; Luo, Ma; Mallal, Simon; van Manen, Daniëlle; Martinez-Picado, Javier; Meyer, Laurence; Miro, José M.; Mullins, James I.; Obel, Niels; Poli, Guido; Sandhu, Manjinder S.; Schuitemaker, Hanneke; Shea, Patrick R.; Theodorou, Ioannis; Walker, Bruce D.; Weintrob, Amy C.; Winkler, Cheryl A.; Wolinsky, Steven M.; Raychaudhuri, Soumya; Goldstein, David B.; Telenti, Amalio; de Bakker, Paul I. W.; Zagury, Jean-François; Fellay, Jacques
2015-01-01
Previous genome-wide association studies (GWAS) of HIV-1–infected populations have been underpowered to detect common variants with moderate impact on disease outcome and have not assessed the phenotypic variance explained by genome-wide additive effects. By combining the majority of available genome-wide genotyping data in HIV-infected populations, we tested for association between ∼8 million variants and viral load (HIV RNA copies per milliliter of plasma) in 6,315 individuals of European ancestry. The strongest signal of association was observed in the HLA class I region that was fully explained by independent effects mapping to five variable amino acid positions in the peptide binding grooves of the HLA-B and HLA-A proteins. We observed a second genome-wide significant association signal in the chemokine (C-C motif) receptor (CCR) gene cluster on chromosome 3. Conditional analysis showed that this signal could not be fully attributed to the known protective CCR5Δ32 allele and the risk P1 haplotype, suggesting further causal variants in this region. Heritability analysis demonstrated that common human genetic variation—mostly in the HLA and CCR5 regions—explains 25% of the variability in viral load. This study suggests that analyses in non-European populations and of variant classes not assessed by GWAS should be priorities for the field going forward. PMID:26553974
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Danhauser, Katharina; Herebian, Diran; Haack, Tobias B; Rodenburg, Richard J; Strom, Tim M; Meitinger, Thomas; Klee, Dirk; Mayatepek, Ertan; Prokisch, Holger; Distelmaier, Felix
2016-03-01
Coenzyme Q10 (CoQ10) has an important role in mitochondrial energy metabolism by way of its functioning as an electron carrier in the respiratory chain. Genetic defects disrupting the endogenous biosynthesis pathway of CoQ10 may lead to severe metabolic disorders with onset in early childhood. Using exome sequencing in a child with fatal neonatal lactic acidosis and encephalopathy, we identified a homozygous loss-of-function variant in COQ9. Functional studies in patient fibroblasts showed that the absence of the COQ9 protein was concomitant with a strong reduction of COQ7, leading to a significant accumulation of the substrate of COQ7, 6-demethoxy ubiquinone10. At the same time, the total amount of CoQ10 was severely reduced, which was reflected in a significant decrease of mitochondrial respiratory chain succinate-cytochrome c oxidoreductase (complex II/III) activity. Lentiviral expression of COQ9 restored all these parameters, confirming the causal role of the variant. Our report on the second COQ9 patient expands the clinical spectrum associated with COQ9 variants, indicating the importance of COQ9 already during prenatal development. Moreover, the rescue of cellular CoQ10 levels and respiratory chain complex activities by CoQ10 supplementation points to the importance of an early diagnosis and immediate treatment.
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Metzger, Julia; Gast, Alana Christina; Schrimpf, Rahel; Rau, Janina; Eikelberg, Deborah; Beineke, Andreas; Hellige, Maren; Distl, Ottmar
2017-04-01
The Miniature Shetland pony represents a horse breed with an extremely small body size. Clinical examination of a dwarf Miniature Shetland pony revealed a lowered size at the withers, malformed skull and brachygnathia superior. Computed tomography (CT) showed a shortened maxilla and a cleft of the hard and soft palate which protruded into the nasal passage leading to breathing difficulties. Pathological examination confirmed these findings but did not reveal histopathological signs of premature ossification in limbs or cranial sutures. Whole-genome sequencing of this dwarf Miniature Shetland pony and comparative sequence analysis using 26 reference equids from NCBI Sequence Read Archive revealed three probably damaging missense variants which could be exclusively found in the affected foal. Validation of these three missense mutations in 159 control horses from different horse breeds and five donkeys revealed only the aggrecan (ACAN)-associated g.94370258G>C variant as homozygous wild-type in all control samples. The dwarf Miniature Shetland pony had the homozygous mutant genotype C/C of the ACAN:g.94370258G>C variant and the normal parents were heterozygous G/C. An unaffected full sib and 3/5 unaffected half-sibs were heterozygous G/C for the ACAN:g.94370258G>C variant. In summary, we could demonstrate a dwarf phenotype in a miniature pony breed perfectly associated with a missense mutation within the ACAN gene.
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Applications of CRISPR Genome Engineering in Cell Biology
Wang, Fangyuan; Qi, Lei S.
2016-01-01
Recent advances in genome engineering are starting a revolution in biological research and translational applications. The CRISPR-associated RNA-guided endonuclease Cas9 and its variants enable diverse manipulations of genome function. In this review, we describe the development of Cas9 tools for a variety of applications in cell biology research, including the study of functional genomics, the creation of transgenic animal models, and genomic imaging. Novel genome engineering methods offer a new avenue to understand the causality between genome and phenotype, thus promising a fuller understanding of cell biology. PMID:27599850
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Lawrenson, Kate; Li, Qiyuan; Kar, Siddhartha; Seo, Ji-Heui; Tyrer, Jonathan; Spindler, Tassja J; Lee, Janet; Chen, Yibu; Karst, Alison; Drapkin, Ronny; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Baker, Helen; Bandera, Elisa V; Bean, Yukie; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Anne; Chen, Zhihua; Cook, Linda S; Cramer, Daniel W; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T; Edwards, Robert P; Eilber, Ursula; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; James, Paul; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kruger Kjaer, Susanne; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph L; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Nevanlinna, Heli; McNeish, Ian; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste L; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Sellers, Thomas A; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston, Lara; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Monteiro, Alvaro; Pharoah, Paul D; Gayther, Simon A; Freedman, Matthew L
2015-09-22
Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10(-5)). For three cis-eQTL associations (P<1.4 × 10(-3), FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10(-10) for risk variants (P<10(-4)) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC.
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Lawrenson, Kate; Li, Qiyuan; Kar, Siddhartha; Seo, Ji-Heui; Tyrer, Jonathan; Spindler, Tassja J.; Lee, Janet; Chen, Yibu; Karst, Alison; Drapkin, Ronny; Aben, Katja K. H.; Anton-Culver, Hoda; Antonenkova, Natalia; Bowtell, David; Webb, Penelope M.; deFazio, Anna; Baker, Helen; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chen, Anne; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A. T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; James, Paul; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y.; Kruger Kjaer, Susanne; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F. A. G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; Nevanlinna, Heli; McNeish, Ian; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste L.; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Phelan, Catherine M.; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Sellers, Thomas A.; Shu, Xiao-Ou; Shvetsov, Yurii B.; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J.; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Monteiro, Alvaro; Pharoah, Paul D.; Gayther, Simon A.; Freedman, Matthew L.
2015-01-01
Genome-wide association studies have reported 11 regions conferring risk of high-grade serous epithelial ovarian cancer (HGSOC). Expression quantitative trait locus (eQTL) analyses can identify candidate susceptibility genes at risk loci. Here we evaluate cis-eQTL associations at 47 regions associated with HGSOC risk (P≤10−5). For three cis-eQTL associations (P<1.4 × 10−3, FDR<0.05) at 1p36 (CDC42), 1p34 (CDCA8) and 2q31 (HOXD9), we evaluate the functional role of each candidate by perturbing expression of each gene in HGSOC precursor cells. Overexpression of HOXD9 increases anchorage-independent growth, shortens population-doubling time and reduces contact inhibition. Chromosome conformation capture identifies an interaction between rs2857532 and the HOXD9 promoter, suggesting this SNP is a leading causal variant. Transcriptomic profiling after HOXD9 overexpression reveals enrichment of HGSOC risk variants within HOXD9 target genes (P=6 × 10−10 for risk variants (P<10−4) within 10 kb of a HOXD9 target gene in ovarian cells), suggesting a broader role for this network in genetic susceptibility to HGSOC. PMID:26391404
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Case Studies Nested in Fuzzy-Set QCA on Sufficiency: Formalizing Case Selection and Causal Inference
ERIC Educational Resources Information Center
Schneider, Carsten Q.; Rohlfing, Ingo
2016-01-01
Qualitative Comparative Analysis (QCA) is a method for cross-case analyses that works best when complemented with follow-up case studies focusing on the causal quality of the solution and its constitutive terms, the underlying causal mechanisms, and potentially omitted conditions. The anchorage of QCA in set theory demands criteria for follow-up…
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Tools for Detecting Causality in Space Systems
NASA Astrophysics Data System (ADS)
Johnson, J.; Wing, S.
2017-12-01
Complex systems such as the solar and magnetospheric envivonment often exhibit patterns of behavior that suggest underlying organizing principles. Causality is a key organizing principle that is particularly difficult to establish in strongly coupled nonlinear systems, but essential for understanding and modeling the behavior of systems. While traditional methods of time-series analysis can identify linear correlations, they do not adequately quantify the distinction between causal and coincidental dependence. We discuss tools for detecting causality including: granger causality, transfer entropy, conditional redundancy, and convergent cross maps. The tools are illustrated by applications to magnetospheric and solar physics including radiation belt, Dst (a magnetospheric state variable), substorm, and solar cycle dynamics.
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Discovery and refinement of muscle weight QTLs in B6 × D2 advanced intercross mice
Carbonetto, P.; Cheng, R.; Gyekis, J. P.; Parker, C. C.; Blizard, D. A.; Palmer, A. A.
2014-01-01
The genes underlying variation in skeletal muscle mass are poorly understood. Although many quantitative trait loci (QTLs) have been mapped in crosses of mouse strains, the limited resolution inherent in these conventional studies has made it difficult to reliably pinpoint the causal genetic variants. The accumulated recombination events in an advanced intercross line (AIL), in which mice from two inbred strains are mated at random for several generations, can improve mapping resolution. We demonstrate these advancements in mapping QTLs for hindlimb muscle weights in an AIL (n = 832) of the C57BL/6J (B6) and DBA/2J (D2) strains, generations F8–F13. We mapped muscle weight QTLs using the high-density MegaMUGA SNP panel. The QTLs highlight the shared genetic architecture of four hindlimb muscles and suggest that the genetic contributions to muscle variation are substantially different in males and females, at least in the B6D2 lineage. Out of the 15 muscle weight QTLs identified in the AIL, nine overlapped the genomic regions discovered in an earlier B6D2 F2 intercross. Mapping resolution, however, was substantially improved in our study to a median QTL interval of 12.5 Mb. Subsequent sequence analysis of the QTL regions revealed 20 genes with nonsense or potentially damaging missense mutations. Further refinement of the muscle weight QTLs using additional functional information, such as gene expression differences between alleles, will be important for discerning the causal genes. PMID:24963006
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Discovery and refinement of muscle weight QTLs in B6 × D2 advanced intercross mice.
Carbonetto, P; Cheng, R; Gyekis, J P; Parker, C C; Blizard, D A; Palmer, A A; Lionikas, A
2014-08-15
The genes underlying variation in skeletal muscle mass are poorly understood. Although many quantitative trait loci (QTLs) have been mapped in crosses of mouse strains, the limited resolution inherent in these conventional studies has made it difficult to reliably pinpoint the causal genetic variants. The accumulated recombination events in an advanced intercross line (AIL), in which mice from two inbred strains are mated at random for several generations, can improve mapping resolution. We demonstrate these advancements in mapping QTLs for hindlimb muscle weights in an AIL (n = 832) of the C57BL/6J (B6) and DBA/2J (D2) strains, generations F8-F13. We mapped muscle weight QTLs using the high-density MegaMUGA SNP panel. The QTLs highlight the shared genetic architecture of four hindlimb muscles and suggest that the genetic contributions to muscle variation are substantially different in males and females, at least in the B6D2 lineage. Out of the 15 muscle weight QTLs identified in the AIL, nine overlapped the genomic regions discovered in an earlier B6D2 F2 intercross. Mapping resolution, however, was substantially improved in our study to a median QTL interval of 12.5 Mb. Subsequent sequence analysis of the QTL regions revealed 20 genes with nonsense or potentially damaging missense mutations. Further refinement of the muscle weight QTLs using additional functional information, such as gene expression differences between alleles, will be important for discerning the causal genes. Copyright © 2014 the American Physiological Society.
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Tang, Haiming; Thomas, Paul D
2016-07-15
PANTHER-PSEP is a new software tool for predicting non-synonymous genetic variants that may play a causal role in human disease. Several previous variant pathogenicity prediction methods have been proposed that quantify evolutionary conservation among homologous proteins from different organisms. PANTHER-PSEP employs a related but distinct metric based on 'evolutionary preservation': homologous proteins are used to reconstruct the likely sequences of ancestral proteins at nodes in a phylogenetic tree, and the history of each amino acid can be traced back in time from its current state to estimate how long that state has been preserved in its ancestors. Here, we describe the PSEP tool, and assess its performance on standard benchmarks for distinguishing disease-associated from neutral variation in humans. On these benchmarks, PSEP outperforms not only previous tools that utilize evolutionary conservation, but also several highly used tools that include multiple other sources of information as well. For predicting pathogenic human variants, the trace back of course starts with a human 'reference' protein sequence, but the PSEP tool can also be applied to predicting deleterious or pathogenic variants in reference proteins from any of the ∼100 other species in the PANTHER database. PANTHER-PSEP is freely available on the web at http://pantherdb.org/tools/csnpScoreForm.jsp Users can also download the command-line based tool at ftp://ftp.pantherdb.org/cSNP_analysis/PSEP/ CONTACT: pdthomas@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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A novel variant of FGFR3 causes proportionate short stature.
Kant, Sarina G; Cervenkova, Iveta; Balek, Lukas; Trantirek, Lukas; Santen, Gijs W E; de Vries, Martine C; van Duyvenvoorde, Hermine A; van der Wielen, Michiel J R; Verkerk, Annemieke J M H; Uitterlinden, André G; Hannema, Sabine E; Wit, Jan M; Oostdijk, Wilma; Krejci, Pavel; Losekoot, Monique
2015-06-01
Mutations of the fibroblast growth factor receptor 3 (FGFR3) cause various forms of short stature, of which the least severe phenotype is hypochondroplasia, mainly characterized by disproportionate short stature. Testing for an FGFR3 mutation is currently not part of routine diagnostic testing in children with short stature without disproportion. A three-generation family A with dominantly transmitted proportionate short stature was studied by whole-exome sequencing to identify the causal gene mutation. Functional studies and protein modeling studies were performed to confirm the pathogenicity of the mutation found in FGFR3. We performed Sanger sequencing in a second family B with dominant proportionate short stature and identified a rare variant in FGFR3. Exome sequencing and/or Sanger sequencing was performed, followed by functional studies using transfection of the mutant FGFR3 into cultured cells; homology modeling was used to construct a three-dimensional model of the two FGFR3 variants. A novel p.M528I mutation in FGFR3 was detected in family A, which segregates with short stature and proved to be activating in vitro. In family B, a rare variant (p.F384L) was found in FGFR3, which did not segregate with short stature and showed normal functionality in vitro compared with WT. Proportionate short stature can be caused by a mutation in FGFR3. Sequencing of this gene can be considered in patients with short stature, especially when there is an autosomal dominant pattern of inheritance. However, functional studies and segregation studies should be performed before concluding that a variant is pathogenic. © 2015 European Society of Endocrinology.
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Gustafsson, Stefan; Rybin, Denis; Stančáková, Alena; Chen, Han; Liu, Ching-Ti; Hong, Jaeyoung; Jensen, Richard A.; Rice, Ken; Morris, Andrew P.; Mägi, Reedik; Tönjes, Anke; Prokopenko, Inga; Kleber, Marcus E.; Delgado, Graciela; Silbernagel, Günther; Jackson, Anne U.; Appel, Emil V.; Grarup, Niels; Lewis, Joshua P.; Montasser, May E.; Landenvall, Claes; Staiger, Harald; Luan, Jian’an; Frayling, Timothy M.; Weedon, Michael N.; Xie, Weijia; Morcillo, Sonsoles; Martínez-Larrad, María Teresa; Biggs, Mary L.; Chen, Yii-Der Ida; Corbaton-Anchuelo, Arturo; Færch, Kristine; Gómez-Zumaquero, Juan Miguel; Goodarzi, Mark O.; Kizer, Jorge R.; Koistinen, Heikki A.; Leong, Aaron; Lind, Lars; Lindgren, Cecilia; Machicao, Fausto; Manning, Alisa K.; Martín-Núñez, Gracia María; Rojo-Martínez, Gemma; Rotter, Jerome I.; Siscovick, David S.; Zmuda, Joseph M.; Zhang, Zhongyang; Serrano-Rios, Manuel; Smith, Ulf; Soriguer, Federico; Hansen, Torben; Jørgensen, Torben J.; Linnenberg, Allan; Pedersen, Oluf; Walker, Mark; Langenberg, Claudia; Scott, Robert A.; Wareham, Nicholas J.; Fritsche, Andreas; Häring, Hans-Ulrich; Stefan, Norbert; Groop, Leif; O’Connell, Jeff R.; Boehnke, Michael; Bergman, Richard N.; Collins, Francis S.; Mohlke, Karen L.; Tuomilehto, Jaakko; März, Winfried; Kovacs, Peter; Stumvoll, Michael; Psaty, Bruce M.; Kuusisto, Johanna; Laakso, Markku; Meigs, James B.; Dupuis, Josée; Ingelsson, Erik; Florez, Jose C.
2016-01-01
Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10−11), rs12454712 (BCL2; P = 2.7 × 10−8), and rs10506418 (FAM19A2; P = 1.9 × 10−8). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci. PMID:27416945
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Nguyen, Thu T.; Tchetgen Tchetgen, Eric J.; Kawachi, Ichiro; Gilman, Stephen E.; Walter, Stefan; Liu, Sze Y.; Manly, Jennifer; Glymour, M. Maria
2015-01-01
Purpose Education is an established correlate of cognitive status in older adulthood, but whether expanding educational opportunities would improve cognitive functioning remains unclear given limitations of prior studies for causal inference. Therefore, we conducted instrumental variable (IV) analyses of the association between education and dementia risk, using for the first time in this area, genetic variants as instruments as well as state-level school policies. Methods IV analyses in the Health and Retirement Study cohort (1998–2010) used two sets of instruments: 1) a genetic risk score constructed from three single nucleotide polymorphisms (SNPs) (n=8,054); and 2) compulsory schooling laws (CSLs) and state school characteristics (term length, student teacher ratios, and expenditures) (n=13,167). Results Employing the genetic risk score as an IV, there was a 1.1% reduction in dementia risk per year of schooling (95% CI: −2.4, 0.02). Leveraging compulsory schooling laws and state school characteristics as IVs, there was a substantially larger protective effect (−9.5%; 95% CI: −14.8, −4.2). Analyses evaluating the plausibility of the IV assumptions indicated estimates derived from analyses relying on CSLs provide the best estimates of the causal effect of education. Conclusion IV analyses suggest education is protective against risk of dementia in older adulthood. PMID:26633592
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Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo
2016-01-01
Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473
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Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin
2016-12-01
Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.
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Kottyan, Leah C; Zoller, Erin E; Bene, Jessica; Lu, Xiaoming; Kelly, Jennifer A; Rupert, Andrew M; Lessard, Christopher J; Vaughn, Samuel E; Marion, Miranda; Weirauch, Matthew T; Namjou, Bahram; Adler, Adam; Rasmussen, Astrid; Glenn, Stuart; Montgomery, Courtney G; Hirschfield, Gideon M; Xie, Gang; Coltescu, Catalina; Amos, Chris; Li, He; Ice, John A; Nath, Swapan K; Mariette, Xavier; Bowman, Simon; Rischmueller, Maureen; Lester, Sue; Brun, Johan G; Gøransson, Lasse G; Harboe, Erna; Omdal, Roald; Cunninghame-Graham, Deborah S; Vyse, Tim; Miceli-Richard, Corinne; Brennan, Michael T; Lessard, James A; Wahren-Herlenius, Marie; Kvarnström, Marika; Illei, Gabor G; Witte, Torsten; Jonsson, Roland; Eriksson, Per; Nordmark, Gunnel; Ng, Wan-Fai; Anaya, Juan-Manuel; Rhodus, Nelson L; Segal, Barbara M; Merrill, Joan T; James, Judith A; Guthridge, Joel M; Scofield, R Hal; Alarcon-Riquelme, Marta; Bae, Sang-Cheol; Boackle, Susan A; Criswell, Lindsey A; Gilkeson, Gary; Kamen, Diane L; Jacob, Chaim O; Kimberly, Robert; Brown, Elizabeth; Edberg, Jeffrey; Alarcón, Graciela S; Reveille, John D; Vilá, Luis M; Petri, Michelle; Ramsey-Goldman, Rosalind; Freedman, Barry I; Niewold, Timothy; Stevens, Anne M; Tsao, Betty P; Ying, Jun; Mayes, Maureen D; Gorlova, Olga Y; Wakeland, Ward; Radstake, Timothy; Martin, Ezequiel; Martin, Javier; Siminovitch, Katherine; Moser Sivils, Kathy L; Gaffney, Patrick M; Langefeld, Carl D; Harley, John B; Kaufman, Kenneth M
2015-01-15
Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5-TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5-TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10(-49); OR = 1.38-1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10(-27)-10(-32), OR = 1.7-1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis whereas only the IRF5-TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5-TNPO3. Published by Oxford University Press 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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Kottyan, Leah C.; Zoller, Erin E.; Bene, Jessica; Lu, Xiaoming; Kelly, Jennifer A.; Rupert, Andrew M.; Lessard, Christopher J.; Vaughn, Samuel E.; Marion, Miranda; Weirauch, Matthew T.; Namjou, Bahram; Adler, Adam; Rasmussen, Astrid; Glenn, Stuart; Montgomery, Courtney G.; Hirschfield, Gideon M.; Xie, Gang; Coltescu, Catalina; Amos, Chris; Li, He; Ice, John A.; Nath, Swapan K.; Mariette, Xavier; Bowman, Simon; Rischmueller, Maureen; Lester, Sue; Brun, Johan G.; Gøransson, Lasse G.; Harboe, Erna; Omdal, Roald; Cunninghame-Graham, Deborah S.; Vyse, Tim; Miceli-Richard, Corinne; Brennan, Michael T.; Lessard, James A.; Wahren-Herlenius, Marie; Kvarnström, Marika; Illei, Gabor G.; Witte, Torsten; Jonsson, Roland; Eriksson, Per; Nordmark, Gunnel; Ng, Wan-Fai; Anaya, Juan-Manuel; Rhodus, Nelson L.; Segal, Barbara M.; Merrill, Joan T.; James, Judith A.; Guthridge, Joel M.; Hal Scofield, R.; Alarcon-Riquelme, Marta; Bae, Sang-Cheol; Boackle, Susan A.; Criswell, Lindsey A.; Gilkeson, Gary; Kamen, Diane L.; Jacob, Chaim O.; Kimberly, Robert; Brown, Elizabeth; Edberg, Jeffrey; Alarcón, Graciela S.; Reveille, John D.; Vilá, Luis M.; Petri, Michelle; Ramsey-Goldman, Rosalind; Freedman, Barry I.; Niewold, Timothy; Stevens, Anne M.; Tsao, Betty P.; Ying, Jun; Mayes, Maureen D.; Gorlova, Olga Y.; Wakeland, Ward; Radstake, Timothy; Martin, Ezequiel; Martin, Javier; Siminovitch, Katherine; Moser Sivils, Kathy L.; Gaffney, Patrick M.; Langefeld, Carl D.; Harley, John B.; Kaufman, Kenneth M.
2015-01-01
Exploiting genotyping, DNA sequencing, imputation and trans-ancestral mapping, we used Bayesian and frequentist approaches to model the IRF5–TNPO3 locus association, now implicated in two immunotherapies and seven autoimmune diseases. Specifically, in systemic lupus erythematosus (SLE), we resolved separate associations in the IRF5 promoter (all ancestries) and with an extended European haplotype. We captured 3230 IRF5–TNPO3 high-quality, common variants across 5 ethnicities in 8395 SLE cases and 7367 controls. The genetic effect from the IRF5 promoter can be explained by any one of four variants in 5.7 kb (P-valuemeta = 6 × 10−49; OR = 1.38–1.97). The second genetic effect spanned an 85.5-kb, 24-variant haplotype that included the genes IRF5 and TNPO3 (P-valuesEU = 10−27–10−32, OR = 1.7–1.81). Many variants at the IRF5 locus with previously assigned biological function are not members of either final credible set of potential causal variants identified herein. In addition to the known biologically functional variants, we demonstrated that the risk allele of rs4728142, a variant in the promoter among the lowest frequentist probability and highest Bayesian posterior probability, was correlated with IRF5 expression and differentially binds the transcription factor ZBTB3. Our analytical strategy provides a novel framework for future studies aimed at dissecting etiological genetic effects. Finally, both SLE elements of the statistical model appear to operate in Sjögren's syndrome and systemic sclerosis whereas only the IRF5–TNPO3 gene-spanning haplotype is associated with primary biliary cirrhosis, demonstrating the nuance of similarity and difference in autoimmune disease risk mechanisms at IRF5–TNPO3. PMID:25205108
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Boerebach, Benjamin C. M.; Lombarts, Kiki M. J. M. H.; Scherpbier, Albert J. J.; Arah, Onyebuchi A.
2013-01-01
Background In fledgling areas of research, evidence supporting causal assumptions is often scarce due to the small number of empirical studies conducted. In many studies it remains unclear what impact explicit and implicit causal assumptions have on the research findings; only the primary assumptions of the researchers are often presented. This is particularly true for research on the effect of faculty’s teaching performance on their role modeling. Therefore, there is a need for robust frameworks and methods for transparent formal presentation of the underlying causal assumptions used in assessing the causal effects of teaching performance on role modeling. This study explores the effects of different (plausible) causal assumptions on research outcomes. Methods This study revisits a previously published study about the influence of faculty’s teaching performance on their role modeling (as teacher-supervisor, physician and person). We drew eight directed acyclic graphs (DAGs) to visually represent different plausible causal relationships between the variables under study. These DAGs were subsequently translated into corresponding statistical models, and regression analyses were performed to estimate the associations between teaching performance and role modeling. Results The different causal models were compatible with major differences in the magnitude of the relationship between faculty’s teaching performance and their role modeling. Odds ratios for the associations between teaching performance and the three role model types ranged from 31.1 to 73.6 for the teacher-supervisor role, from 3.7 to 15.5 for the physician role, and from 2.8 to 13.8 for the person role. Conclusions Different sets of assumptions about causal relationships in role modeling research can be visually depicted using DAGs, which are then used to guide both statistical analysis and interpretation of results. Since study conclusions can be sensitive to different causal assumptions, results should be interpreted in the light of causal assumptions made in each study. PMID:23936020
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Kelsen, Judith R; Dawany, Noor; Martinez, Alejandro; Martinez, Alejuandro; Grochowski, Christopher M; Maurer, Kelly; Rappaport, Eric; Piccoli, David A; Baldassano, Robert N; Mamula, Petar; Sullivan, Kathleen E; Devoto, Marcella
2015-11-18
Children with very early-onset inflammatory bowel disease (VEO-IBD), those diagnosed at less than 5 years of age, are a unique population. A subset of these patients present with a distinct phenotype and more severe disease than older children and adults. Host genetics is thought to play a more prominent role in this young population, and monogenic defects in genes related to primary immunodeficiencies are responsible for the disease in a small subset of patients with VEO-IBD. We report a child who presented at 3 weeks of life with very early-onset inflammatory bowel disease (VEO-IBD). He had a complicated disease course and remained unresponsive to medical and surgical therapy. The refractory nature of his disease, together with his young age of presentation, prompted utilization of whole exome sequencing (WES) to detect an underlying monogenic primary immunodeficiency and potentially target therapy to the identified defect. Copy number variation analysis (CNV) was performed using the eXome-Hidden Markov Model. Whole exome sequencing revealed 1,380 nonsense and missense variants in the patient. Plausible candidate variants were not detected following analysis of filtered variants, therefore, we performed CNV analysis of the WES data, which led us to identify a de novo whole gene deletion in XIAP. This is the first reported whole gene deletion in XIAP, the causal gene responsible for XLP2 (X-linked lymphoproliferative Disease 2). XLP2 is a syndrome resulting in VEO-IBD and can increase susceptibility to hemophagocytic lymphohistocytosis (HLH). This identification allowed the patient to be referred for bone marrow transplantation, potentially curative for his disease and critical to prevent the catastrophic sequela of HLH. This illustrates the unique etiology of VEO-IBD, and the subsequent effects on therapeutic options. This cohort requires careful and thorough evaluation for monogenic defects and primary immunodeficiencies.
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Hindsight bias doesn't always come easy: causal models, cognitive effort, and creeping determinism.
Nestler, Steffen; Blank, Hartmut; von Collani, Gernot
2008-09-01
Creeping determinism, a form of hindsight bias, refers to people's hindsight perceptions of events as being determined or inevitable. This article proposes, on the basis of a causal-model theory of creeping determinism, that the underlying processes are effortful, and hence creeping determinism should disappear when individuals lack the cognitive resources to make sense of an outcome. In Experiments 1 and 2, participants were asked to read a scenario while they were under either low or high processing load. Participants who had the cognitive resources to make sense of the outcome perceived it as more probable and necessary than did participants under high processing load or participants who did not receive outcome information. Experiment 3 was designed to separate 2 postulated subprocesses and showed that the attenuating effect of processing load on hindsight bias is not due to a disruption of the retrieval of potential causal antecedents but to a disruption of their evaluation. Together the 3 experiments show that the processes underlying creeping determinism are effortful, and they highlight the crucial role of causal reasoning in the perception of past events. (c) 2008 APA, all rights reserved.
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Blieck, Lies; Toye, Geert; Dumortier, Françoise; Verstrepen, Kevin J.; Delvaux, Freddy R.; Thevelein, Johan M.; Van Dijck, Patrick
2007-01-01
To save energy, space, and time, today's breweries make use of high-gravity brewing in which concentrated medium (wort) is fermented, resulting in a product with higher ethanol content. After fermentation, the product is diluted to obtain beer with the desired alcohol content. While economically desirable, the use of wort with an even higher sugar concentration is limited by the inability of brewer's yeast (Saccharomyces pastorianus) to efficiently ferment such concentrated medium. Here, we describe a successful strategy to obtain yeast variants with significantly improved fermentation capacity under high-gravity conditions. We isolated better-performing variants of the industrial lager strain CMBS33 by subjecting a pool of UV-induced variants to consecutive rounds of fermentation in very-high-gravity wort (>22° Plato). Two variants (GT336 and GT344) showing faster fermentation rates and/or more-complete attenuation as well as improved viability under high ethanol conditions were identified. The variants displayed the same advantages in a pilot-scale stirred fermenter under high-gravity conditions at 11°C. Microarray analysis identified several genes whose altered expression may be responsible for the superior performance of the variants. The role of some of these candidate genes was confirmed by genetic transformation. Our study shows that proper selection conditions allow the isolation of variants of commercial brewer's yeast with superior fermentation characteristics. Moreover, it is the first study to identify genes that affect fermentation performance under high-gravity conditions. The results are of interest to the beer and bioethanol industries, where the use of more-concentrated medium is economically advantageous. PMID:17158628
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Financial incentives for kidney donation: A comparative case study using synthetic controls.
Bilgel, Fırat; Galle, Brian
2015-09-01
Although many commentators called for increased efforts to incentivize organ donations, theorists and some evidence suggest these efforts will be ineffective. Studies examining the impact of tax incentives generally report zero/negative coefficients, but these studies incorrectly define their tax variables and rely on difference-in-differences despite likely failures of the parallel trends assumption. We identify the causal effect of tax legislation to serve as an organ donor on living kidney donation rates in the U.S. states using more precise tax data and allowing for heterogeneous time-variant causal effects. Employing a synthetic control method, we find that the passage of tax incentive legislation increased living unrelated kidney donation rates by 52 percent in New York relative to a comparable synthetic New York in the absence of legislation. It is possible that New York is unique, but our methodology does not allow us to measure accurately effects in other states. Copyright © 2015 Elsevier B.V. All rights reserved.
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Hot money and China's stock market volatility: Further evidence using the GARCH-MIDAS model
NASA Astrophysics Data System (ADS)
Wei, Yu; Yu, Qianwen; Liu, Jing; Cao, Yang
2018-02-01
This paper investigates the influence of hot money on the return and volatility of the Chinese stock market using a nonlinear Granger causality test and a new GARCH-class model based on mixed data sampling regression (GARCH-MIDAS). The empirical results suggest that no linear or nonlinear causality exists between the growth rate of hot money and the Chinese stock market return, implying that the Chinese stock market is not driven by hot money and vice versa. However, hot money has a significant positive impact on the long-term volatility of the Chinese stock market. Furthermore, the dependence between the long-term volatility caused by hot money and the total volatility of the Chinese stock market is time-variant, indicating that huge volatilities in the stock market are not always triggered by international speculation capital flow and that Chinese authorities should further focus on more systemic reforms in the trading rules and on effectively regulating the stock market.
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Molecular Characterization of the NLRC4 Expression in Relation to Interleukin-18 Levels
Zeller, Tanja; Haase, Tina; Müller, Christian; Riess, Helene; Lau, Denise; Zeller, Simon; Krause, Jasmin; Baumert, Jens; Pless, Ole; Dupuis, Josée; Wild, Philipp S.; Eleftheriadis, Medea; Waldenberger, Melanie; Zeilinger, Sonja; Ziegler, Andreas; Peters, Annette; Tiret, Laurence; Proust, Carole; Marzi, Carola; Munzel, Thomas; Strauch, Konstantin; Prokisch, Holger; Lackner, Karl J.; Herder, Christian; Thorand, Barbara; Benjamin, Emilia J.; Blankenberg, Stefan; Koenig, Wolfgang; Schnabel, Renate B.
2015-01-01
Background Interleukin-18 (IL-18) is a pleiotropic cytokine centrally involved in the cytokine cascade with complex immunomodulatory functions in innate and acquired immunity. Circulating IL-18 concentrations are associated with type 2 diabetes, cardiovascular events and diverse inflammatory and autoimmune disorders. Methods and Results To identify causal variants affecting circulating IL-18 concentrations, we applied various omics and molecular biology approaches. By GWAS, we confirmed association of IL-18 levels with a SNP in the untranslated exon 2 of the inflammasome component NLRC4 (NLR family, CARD domain containing 4) gene on chromosome 2 (rs385076, P=2.4×10−45). Subsequent molecular analyses by gene expression analysis and reporter gene assays indicated an effect of rs385076 on NLRC4 expression and differential isoform usage by modulating binding of the transcription factor PU.1. Conclusions Our study provides evidence for the functional causality of SNP rs385076 within the NLRC4 gene in relation to IL-18 activation. PMID:26362438
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Gottlieb, Michael M; Arenillas, David J; Maithripala, Savanie; Maurer, Zachary D; Tarailo Graovac, Maja; Armstrong, Linlea; Patel, Millan; van Karnebeek, Clara; Wasserman, Wyeth W
2015-04-01
Advances in next-generation sequencing (NGS) technologies have helped reveal causal variants for genetic diseases. In order to establish causality, it is often necessary to compare genomes of unrelated individuals with similar disease phenotypes to identify common disrupted genes. When working with cases of rare genetic disorders, finding similar individuals can be extremely difficult. We introduce a web tool, GeneYenta, which facilitates the matchmaking process, allowing clinicians to coordinate detailed comparisons for phenotypically similar cases. Importantly, the system is focused on phenotype annotation, with explicit limitations on highly confidential data that create barriers to participation. The procedure for matching of patient phenotypes, inspired by online dating services, uses an ontology-based semantic case matching algorithm with attribute weighting. We evaluate the capacity of the system using a curated reference data set and 19 clinician entered cases comparing four matching algorithms. We find that the inclusion of clinician weights can augment phenotype matching. © 2015 WILEY PERIODICALS, INC.
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Causal networks clarify productivity-richness interrelations, bivariate plots do not
Grace, James B.; Adler, Peter B.; Harpole, W. Stanley; Borer, Elizabeth T.; Seabloom, Eric W.
2014-01-01
We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.
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ERIC Educational Resources Information Center
Melby-Lervag, Monica
2012-01-01
The acknowledgement that educational achievement is highly dependent on successful reading development has led to extensive research on its underlying factors. A strong argument has been made for a causal relationship between reading and phoneme awareness; similarly, causal relations have been suggested for reading with short-term memory and rhyme…
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ERIC Educational Resources Information Center
Morris, Stephen P.; Edovald, Triin; Lloyd, Cheryl; Kiss, Zsolt
2016-01-01
Based on the experience of evaluating 2 cross-age peer-tutoring interventions, we argue that researchers need to pay greater attention to causal mechanisms within the context of school-based randomised controlled trials. Without studying mechanisms, researchers are less able to explain the underlying causal processes that give rise to results from…
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Serum total bilirubin levels and coronary heart disease--Causal association or epiphenomenon?
Kunutsor, Setor K
2015-12-01
Observational epidemiological evidence supports a linear inverse and independent association between serum total bilirubin levels and coronary heart disease (CHD) risk, but whether this association is causal remains to be ascertained. A Mendelian randomization approach was employed to test whether serum total bilirubin is causally linked to CHD. The genetic variant rs6742078--well known to specifically modify levels of serum total bilirubin and accounting for up to 20% of the variance in circulating serum total bilirubin levels--was used as an instrumental variable. In pooled analysis of estimates reported from published genome-wide association studies, every copy of the T allele of rs6742078 was associated with 0.42 standard deviation (SD) higher levels of serum total bilirubin (95% confidence interval, 0.40 to 0.43). Based on combined data from the Coronary Artery Disease Genome wide Replication and Meta-analyses and the Coronary Artery Disease (C4D) Genetics Consortium involving a total of 36,763 CHD cases and 76,997 controls, the odds ratio for CHD per copy of the T allele was 1.01 (95% confidence interval, 0.99 to 1.04). The odds ratio of CHD for a 1 SD genetically elevated serum total bilirubin level was 1.03 (95% confidence interval, 0.98 to 1.09). The current findings casts doubt on a strong causal association of serum total bilirubin levels with CHD. The inverse associations demonstrated in observational studies may be driven by biases such as unmeasured confounding and/or reverse causation. However, further research in large-scale consortia is needed. Copyright © 2015 Elsevier Inc. All rights reserved.
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Friston, Karl J.; Bastos, André M.; Oswal, Ashwini; van Wijk, Bernadette; Richter, Craig; Litvak, Vladimir
2014-01-01
This technical paper offers a critical re-evaluation of (spectral) Granger causality measures in the analysis of biological timeseries. Using realistic (neural mass) models of coupled neuronal dynamics, we evaluate the robustness of parametric and nonparametric Granger causality. Starting from a broad class of generative (state-space) models of neuronal dynamics, we show how their Volterra kernels prescribe the second-order statistics of their response to random fluctuations; characterised in terms of cross-spectral density, cross-covariance, autoregressive coefficients and directed transfer functions. These quantities in turn specify Granger causality — providing a direct (analytic) link between the parameters of a generative model and the expected Granger causality. We use this link to show that Granger causality measures based upon autoregressive models can become unreliable when the underlying dynamics is dominated by slow (unstable) modes — as quantified by the principal Lyapunov exponent. However, nonparametric measures based on causal spectral factors are robust to dynamical instability. We then demonstrate how both parametric and nonparametric spectral causality measures can become unreliable in the presence of measurement noise. Finally, we show that this problem can be finessed by deriving spectral causality measures from Volterra kernels, estimated using dynamic causal modelling. PMID:25003817
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Africa: continent of genome contrasts with implications for biomedical research and health.
Ramsay, Michèle
2012-08-31
The genomic architecture of African populations is poorly understood and there is considerable variation between ethno-linguistic groups. Genome-wide approaches have been extensively applied to search for genetic associations to complex traits in Europeans, but rarely in Africans. This is largely attributed to lower levels of funding, poor infrastructure and public health systems, and to the small pool of trained scientists. High levels of genetic variation and underlying population structure in Africans present significant challenges, but lower levels of linkage disequilibrium provide an opportunity for more effective localisation of causal variants. High throughput technologies, including dense genotyping arrays, genome sequencing and epigenome studies, together with plummeting costs, are making research more affordable, even for African scientists. Understanding the interactions between genome structure and environmental influences is essential to interpreting their contributions to the increase in infectious diseases and non-communicable diseases, exacerbated by adverse environments and lifestyle choices. The unique genome dynamics in African populations have an important role to play in understanding human health and susceptibility to disease. Copyright © 2012. Published by Elsevier B.V.
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Determination of nonlinear genetic architecture using compressed sensing.
Ho, Chiu Man; Hsu, Stephen D H
2015-01-01
One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)∼0.5), can be extracted from data sets comprised of n ⋆∼100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ∼10 k loci, roughly a million individuals would be sufficient for application of the method.
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A Novel BHLHE41 Variant is Associated with Short Sleep and Resistance to Sleep Deprivation in Humans
Pellegrino, Renata; Kavakli, Ibrahim Halil; Goel, Namni; Cardinale, Christopher J.; Dinges, David F.; Kuna, Samuel T.; Maislin, Greg; Van Dongen, Hans P.A.; Tufik, Sergio; Hogenesch, John B.; Hakonarson, Hakon; Pack, Allan I.
2014-01-01
Study Objectives: Earlier work described a mutation in DEC2 also known as BHLHE41 (basic helix-loophelix family member e41) as causal in a family of short sleepers, who needed just 6 h sleep per night. We evaluated whether there were other variants of this gene in two well-phenotyped cohorts. Design: Sequencing of the BHLHE41 gene, electroencephalographic data, and delta power analysis and functional studies using cell-based luciferase. Results: We identified new variants of the BHLHE41 gene in two cohorts who had either acute sleep deprivation (n = 200) or chronic partial sleep deprivation (n = 217). One variant, Y362H, at another location in the same exon occurred in one twin in a dizygotic twin pair and was associated with reduced sleep duration, less recovery sleep following sleep deprivation, and fewer performance lapses during sleep deprivation than the homozygous twin. Both twins had almost identical amounts of non rapid eye movement (NREM) sleep. This variant reduced the ability of BHLHE41 to suppress CLOCK/BMAL1 and NPAS2/BMAL1 transactivation in vitro. Another variant in the same exome had no effect on sleep or response to sleep deprivation and no effect on CLOCK/BMAL1 transactivation. Random mutagenesis identified a number of other variants of BHLHE41 that affect its function. Conclusions: There are a number of mutations of BHLHE41. Mutations reduce total sleep while maintaining NREM sleep and provide resistance to the effects of sleep loss. Mutations that affect sleep also modify the normal inhibition of BHLHE41 of CLOCK/BMAL1 transactivation. Thus, clock mechanisms are likely involved in setting sleep length and the magnitude of sleep homeostasis. Citation: Pellegrino R, Kavakli IH, Goel N, Cardinale CJ, Dinges DF, Kuna ST, Maislin G, Van Dongen HP, Tufik S, Hogenesch JB, Hakonarson H, Pack AI. A novel BHLHE41 variant is associated with short sleep and resistance to sleep deprivation in humans. SLEEP 2014;37(8):1327-1336. PMID:25083013
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Deep whole-genome sequencing of 90 Han Chinese genomes.
Lan, Tianming; Lin, Haoxiang; Zhu, Wenjuan; Laurent, Tellier Christian Asker Melchior; Yang, Mengcheng; Liu, Xin; Wang, Jun; Wang, Jian; Yang, Huanming; Xu, Xun; Guo, Xiaosen
2017-09-01
Next-generation sequencing provides a high-resolution insight into human genetic information. However, the focus of previous studies has primarily been on low-coverage data due to the high cost of sequencing. Although the 1000 Genomes Project and the Haplotype Reference Consortium have both provided powerful reference panels for imputation, low-frequency and novel variants remain difficult to discover and call with accuracy on the basis of low-coverage data. Deep sequencing provides an optimal solution for the problem of these low-frequency and novel variants. Although whole-exome sequencing is also a viable choice for exome regions, it cannot account for noncoding regions, sometimes resulting in the absence of important, causal variants. For Han Chinese populations, the majority of variants have been discovered based upon low-coverage data from the 1000 Genomes Project. However, high-coverage, whole-genome sequencing data are limited for any population, and a large amount of low-frequency, population-specific variants remain uncharacterized. We have performed whole-genome sequencing at a high depth (∼×80) of 90 unrelated individuals of Chinese ancestry, collected from the 1000 Genomes Project samples, including 45 Northern Han Chinese and 45 Southern Han Chinese samples. Eighty-three of these 90 have been sequenced by the 1000 Genomes Project. We have identified 12 568 804 single nucleotide polymorphisms, 2 074 210 short InDels, and 26 142 structural variations from these 90 samples. Compared to the Han Chinese data from the 1000 Genomes Project, we have found 7 000 629 novel variants with low frequency (defined as minor allele frequency < 5%), including 5 813 503 single nucleotide polymorphisms, 1 169 199 InDels, and 17 927 structural variants. Using deep sequencing data, we have built a greatly expanded spectrum of genetic variation for the Han Chinese genome. Compared to the 1000 Genomes Project, these Han Chinese deep sequencing data enhance the characterization of a large number of low-frequency, novel variants. This will be a valuable resource for promoting Chinese genetics research and medical development. Additionally, it will provide a valuable supplement to the 1000 Genomes Project, as well as to other human genome projects. © The Authors 2017. Published by Oxford University Press.
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Schendelaar, Pamela; La Bastide-Van Gemert, Sacha; Heineman, Maas Jan; Middelburg, Karin J; Seggers, Jorien; Van den Heuvel, Edwin R; Hadders-Algra, Mijna
2016-12-01
Research on cognitive and behavioural development of children born after assisted conception is inconsistent. This prospective study aimed to explore underlying causal relationships between ovarian stimulation, in-vitro procedures, subfertility components and child cognition and behaviour. Participants were singletons born to subfertile couples after ovarian stimulation IVF (n = 63), modified natural cycle IVF (n = 53), natural conception (n = 79) and singletons born to fertile couples (reference group) (n = 98). At 4 years, cognition (Kaufmann-ABC-II; total IQ) and behaviour (Child Behavior Checklist; total problem T-score) were assessed. Causal inference search algorithms and structural equation modelling was applied to unravel causal mechanisms. Most children had typical cognitive and behavioural scores. No underlying causal effect was found between ovarian stimulation and the in-vitro procedure and outcome. Direct negative causal effects were found between severity of subfertility (time to pregnancy) and cognition and presence of subfertility and behaviour. Maternal age and maternal education acted as confounders. The study concludes that no causal effects were found between ovarian stimulation or in-vitro procedures and cognition and behaviour in childrenaged 4 years born to subfertile couples. Subfertility, especially severe subfertility, however, was associated with worse cognition and behaviour. Copyright © 2016 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
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The Role of Local Ancestry Adjustment in Association Studies Using Admixed Populations
Zhang, Jianqi; Stram, Daniel O.
2016-01-01
Association analysis using admixed populations imposes challenges and opportunities for disease mapping. By developing some explicit results for the variance of an allele of interest conditional on either local or global ancestry and by simulation of recently admixed genomes we evaluate power and false-positive rates under a variety of scenarios concerning linkage disequilibrium (LD) and the presence of unmeasured variants. Pairwise LD patterns were compared between admixed and nonadmixed populations using the HapMap phase 3 data. Based on the above, we showed that as follows: For causal variants with similar effect size in all populations, power is generally higher in a study using admixed population than using nonadmixed population, especially for highly differentiated SNPs. This gain of power is achieved with adjustment of global ancestry, which completely removes any cross-chromosome inflation of type I error rates, and addresses much of the intrachromosome inflation.If reliably estimated, adjusting for local ancestry precisely recovers the localization that could have been achieved in a stratified analysis of source populations. Improved localization is most evident for highly differentiated SNPs; however, the advantage of higher power is lost on exactly the same differentiated SNPs.In the real admixed populations such as African Americans and Latinos, the expansion of LD is not as dramatic as in our simulation.While adjustment for global ancestry is required prior to announcing a novel association seen in an admixed population, local ancestry adjustment may best be regarded as a localization tool not strictly required for discovery purposes. PMID:25043967
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Power, Robert A; Cohen-Woods, Sarah; Ng, Mandy Y; Butler, Amy W; Craddock, Nick; Korszun, Ania; Jones, Lisa; Jones, Ian; Gill, Michael; Rice, John P; Maier, Wolfgang; Zobel, Astrid; Mors, Ole; Placentino, Anna; Rietschel, Marcella; Aitchison, Katherine J; Tozzi, Federica; Muglia, Pierandrea; Breen, Gerome; Farmer, Anne E; McGuffin, Peter; Lewis, Cathryn M; Uher, Rudolf
2013-09-01
Stressful life events are an established trigger for depression and may contribute to the heterogeneity within genome-wide association analyses. With depression cases showing an excess of exposure to stressful events compared to controls, there is difficulty in distinguishing between "true" cases and a "normal" response to a stressful environment. This potential contamination of cases, and that from genetically at risk controls that have not yet experienced environmental triggers for onset, may reduce the power of studies to detect causal variants. In the RADIANT sample of 3,690 European individuals, we used propensity score matching to pair cases and controls on exposure to stressful life events. In 805 case-control pairs matched on stressful life event, we tested the influence of 457,670 common genetic variants on the propensity to depression under comparable level of adversity with a sign test. While this analysis produced no significant findings after genome-wide correction for multiple testing, we outline a novel methodology and perspective for providing environmental context in genetic studies. We recommend contextualizing depression by incorporating environmental exposure into genome-wide analyses as a complementary approach to testing gene-environment interactions. Possible explanations for negative findings include a lack of statistical power due to small sample size and conditional effects, resulting from the low rate of adequate matching. Our findings underscore the importance of collecting information on environmental risk factors in studies of depression and other complex phenotypes, so that sufficient sample sizes are available to investigate their effect in genome-wide association analysis. Copyright © 2013 Wiley Periodicals, Inc.
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Alonso, Nerea; Estrada, Karol; Albagha, Omar M E; Herrera, Lizbeth; Reppe, Sjur; Olstad, Ole K; Gautvik, Kaare M; Ryan, Niamh M; Evans, Kathryn L; Nielson, Carrie M; Hsu, Yi-Hsiang; Kiel, Douglas P; Markozannes, George; Ntzani, Evangelia E; Evangelou, Evangelos; Feenstra, Bjarke; Liu, Xueping; Melbye, Mads; Masi, Laura; Brandi, Maria Luisa; Riches, Philip; Daroszewska, Anna; Olmos, José Manuel; Valero, Carmen; Castillo, Jesús; Riancho, José A; Husted, Lise B; Langdahl, Bente L; Brown, Matthew A; Duncan, Emma L; Kaptoge, Stephen; Khaw, Kay-Tee; Usategui-Martín, Ricardo; Del Pino-Montes, Javier; González-Sarmiento, Rogelio; Lewis, Joshua R; Prince, Richard L; D'Amelio, Patrizia; García-Giralt, Natalia; Nogués, Xavier; Mencej-Bedrac, Simona; Marc, Janja; Wolstein, Orit; Eisman, John A; Oei, Ling; Medina-Gómez, Carolina; Schraut, Katharina E; Navarro, Pau; Wilson, James F; Davies, Gail; Starr, John; Deary, Ian; Tanaka, Toshiko; Ferrucci, Luigi; Gianfrancesco, Fernando; Gennari, Luigi; Lucas, Gavin; Elosua, Roberto; Uitterlinden, André G; Rivadeneira, Fernando; Ralston, Stuart H
2018-03-01
To identify genetic determinants of susceptibility to clinical vertebral fractures, which is an important complication of osteoporosis. Here we conduct a genome-wide association study in 1553 postmenopausal women with clinical vertebral fractures and 4340 controls, with a two-stage replication involving 1028 cases and 3762 controls. Potentially causal variants were identified using expression quantitative trait loci (eQTL) data from transiliac bone biopsies and bioinformatic studies. A locus tagged by rs10190845 was identified on chromosome 2q13, which was significantly associated with clinical vertebral fracture (P=1.04×10 -9 ) with a large effect size (OR 1.74, 95% CI 1.06 to 2.6). Bioinformatic analysis of this locus identified several potentially functional SNPs that are associated with expression of the positional candidate genes TTL (tubulin tyrosine ligase) and SLC20A1 (solute carrier family 20 member 1). Three other suggestive loci were identified on chromosomes 1p31, 11q12 and 15q11. All these loci were novel and had not previously been associated with bone mineral density or clinical fractures. We have identified a novel genetic variant that is associated with clinical vertebral fractures by mechanisms that are independent of BMD. Further studies are now in progress to validate this association and evaluate the underlying mechanism. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Metselaar, Karin I; Abee, Tjakko; Zwietering, Marcel H; den Besten, Heidy M W
2016-09-01
Listeria monocytogenes exhibits a heterogeneous response upon stress exposure which can be partially attributed to the presence of stable stress-resistant variants. This study aimed to evaluate the impact of the presence of stress-resistant variants of Listeria monocytogenes and their corresponding trade-offs on population composition under different environmental conditions. A set of stress robustness and growth parameters of the wild type (WT) and an rpsU deletion variant was obtained and used to model their growth behavior under combined mild stress conditions and to model their kinetics under single- and mixed-strain conditions in a simulated food chain. Growth predictions for the WT and the rpsU deletion variant matched the experimental data generally well, although some deviations from the predictions were observed. The data highlighted the influence of the environmental conditions on the ratio between the WT and variant. Prediction of performance in the simulated food chain proved to be challenging. The trend of faster growth and lower stress robustness for the WT than for the rpsU variant in the different steps of the chain was confirmed, but especially for the inactivation steps and the time needed to resume growth after an inactivation step, the experimental data deviated from the model predictions. This report provides insights into the conditions which can select for stress-resistant variants in industrial settings and discusses their potential persistence in food processing environments. Listeria monocytogenes exhibits a heterogeneous stress response which can partially be attributed to the presence of genetic variants. These stress-resistant variants survive better under severe conditions but have, on the other hand, a reduced growth rate. To date, the ecological behavior and potential impact of the presence of stress-resistant variants is not fully understood. In this study, we quantitatively assessed growth and inactivation behavior of wild-type L. monocytogenes and its stress-resistant variants. Predictions were validated under different conditions, as well as along a model food chain. This work illustrates the effects of environmental factors on population dynamics of L. monocytogenes and is a first step in evaluating the impact of population diversity on food safety. Copyright © 2016, American Society for Microbiology. All Rights Reserved.
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Direk, Kenan; Lau, Winston; Small, Kerrin S; Maniatis, Nikolas; Andrew, Toby
2014-01-01
Numerous functional studies have implicated PARL in relation to type 2 diabetes (T2D). We hypothesised that conflicting human association studies may be due to neighbouring causal variants being in linkage disequilibrium (LD) with PARL. We conducted a comprehensive candidate gene study of the extended LD genomic region that includes PARL and transporter ABCC5 using three data sets (two European and one African American), in relation to healthy glycaemic variation, visceral fat accumulation and T2D disease. We observed no evidence for previously reported T2D association with Val262Leu or PARL using array and fine-map genomic and expression data. By contrast, we observed strong evidence of T2D association with ABCC5 (intron 26) for European and African American samples (P = 3E−07) and with ABCC5 adipose expression in Europeans [odds ratio (OR) = 3.8, P = 2E−04]. The genomic location estimate for the ABCC5 functional variant, associated with all phenotypes and expression data (P = 1E−11), was identical for all samples (at Chr3q 185,136 kb B36), indicating that the risk variant is an expression quantitative trait locus (eQTL) with increased expression conferring risk of disease. That the association with T2D is observed in populations of disparate ancestry suggests the variant is a ubiquitous risk factor for T2D. PMID:25117150
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Zhao, Wei; Niu, Guannan; Shen, Botao; Zheng, Yang; Gong, Fangchao; Wang, Xianfu; Lee, Jiyun; Mulvihill, John J; Chen, Xiaohui; Li, Shibo
2013-12-01
As patients with congenital heart disease (CHD) increasingly survive to childbearing age, it becomes important to understand the genetic origins of CHD. In children, CHD is frequently caused by chromosomal imbalances. We searched for submicroscopic imbalances in adults with CHD focusing on simple-to-moderate phenotypes, without associated dysmorphic features, a group not previously examined. A total of 100 Han Chinese adults with a diverse range of isolated CHD and 65 ethnically matched controls were screened using whole-genome array comparative genomic hybridization. Forty-five large (>100 kb) rare copy number variants (CNVs) were identified in 36/100 patients. These variants were not listed in the Database of Genomic Variants nor found in controls. In three of these genomic imbalances (22q11.2, 18q23, 3q21.3), genes that play an important role in cardiac development were implicated, including CRKL, NFATC1, PLXNA1, the latter has not been associated with human CHD before. This study detected a 0.7 Mb 22q11.2 deletion, which marginally overlapped the common 3 Mb 22q11.2 deletion, in one patient with a perimembranous ventricular septal defect without any extracardiac manifestation. Furthermore, we detected a novel inherited aberration dup (16q23.1). Although a causal relationship with CHD remains to be established, this CNVs profile provides a spectrum of genomic imbalances in this condition, and improves the CNV-phenotype correlations. © 2013 Wiley Periodicals, Inc.
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Fonseca, Dora Janeth; Ortega-Recalde, Oscar; Esteban-Perez, Clara; Moreno-Ortiz, Harold; Patiño, Liliana Catherine; Bermúdez, Olga María; Ortiz, Angela María; Restrepo, Carlos M; Lucena, Elkin; Laissue, Paul
2014-11-01
BMP15 has drawn particular attention in the pathophysiology of reproduction, as its mutations in mammalian species have been related to different reproductive phenotypes. In humans, BMP15 coding regions have been sequenced in large panels of women with premature ovarian failure (POF), but only some mutations have been definitely validated as causing the phenotype. A functional association between the BMP15 c.-9C>G promoter polymorphism and cause of POF have been reported. The aim of this study was to determine the potential functional effect of this sequence variant on specific BMP15 promoter transactivation disturbances. Bioinformatics was used to identify transcription factor binding sites located on the promoter region of BMP15. Reverse transcription polymerase chain reaction was used to study specific gene expression in ovarian tissue. Luciferase reporter assays were used to establish transactivation disturbances caused by the BMP15 c.-9C>G variant. The c.-9C>G variant was found to modify the PITX1 transcription factor binding site. PITX1 and BMP15 co-expressed in human and mouse ovarian tissue, and PITX1 transactivated both BMP15 promoter versions (-9C and -9G). It was found that the BMP15 c.-9G allele was related to BMP15 increased transcription, supporting c.-9C>G as a causal agent of POF. Copyright © 2014 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.
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Soukarieh, Omar; Gaildrat, Pascaline; Hamieh, Mohamad; Drouet, Aurélie; Baert-Desurmont, Stéphanie; Frébourg, Thierry; Tosi, Mario; Martins, Alexandra
2016-01-01
The identification of a causal mutation is essential for molecular diagnosis and clinical management of many genetic disorders. However, even if next-generation exome sequencing has greatly improved the detection of nucleotide changes, the biological interpretation of most exonic variants remains challenging. Moreover, particular attention is typically given to protein-coding changes often neglecting the potential impact of exonic variants on RNA splicing. Here, we used the exon 10 of MLH1, a gene implicated in hereditary cancer, as a model system to assess the prevalence of RNA splicing mutations among all single-nucleotide variants identified in a given exon. We performed comprehensive minigene assays and analyzed patient’s RNA when available. Our study revealed a staggering number of splicing mutations in MLH1 exon 10 (77% of the 22 analyzed variants), including mutations directly affecting splice sites and, particularly, mutations altering potential splicing regulatory elements (ESRs). We then used this thoroughly characterized dataset, together with experimental data derived from previous studies on BRCA1, BRCA2, CFTR and NF1, to evaluate the predictive power of 3 in silico approaches recently described as promising tools for pinpointing ESR-mutations. Our results indicate that ΔtESRseq and ΔHZEI-based approaches not only discriminate which variants affect splicing, but also predict the direction and severity of the induced splicing defects. In contrast, the ΔΨ-based approach did not show a compelling predictive power. Our data indicates that exonic splicing mutations are more prevalent than currently appreciated and that they can now be predicted by using bioinformatics methods. These findings have implications for all genetically-caused diseases. PMID:26761715
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Prognostic Relevance of Urinary Bladder Cancer Susceptibility Loci
Grotenhuis, Anne J.; Dudek, Aleksandra M.; Verhaegh, Gerald W.; Witjes, J. Alfred; Aben, Katja K.; van der Marel, Saskia L.; Vermeulen, Sita H.; Kiemeney, Lambertus A.
2014-01-01
In the last few years, susceptibility loci have been identified for urinary bladder cancer (UBC) through candidate-gene and genome-wide association studies. Prognostic relevance of most of these loci is yet unknown. In this study, we used data of the Nijmegen Bladder Cancer Study (NBCS) to perform a comprehensive evaluation of the prognostic relevance of all confirmed UBC susceptibility loci. Detailed clinical data concerning diagnosis, stage, treatment, and disease course of a population-based series of 1,602 UBC patients were collected retrospectively based on a medical file survey. Kaplan-Meier survival analyses and Cox proportional hazard regression were performed, and log-rank tests calculated, to evaluate the association between 12 confirmed UBC susceptibility variants and recurrence and progression in non-muscle invasive bladder cancer (NMIBC) patients. Among muscle-invasive or metastatic bladder cancer (MIBC) patients, association of these variants with overall survival was tested. Subgroup analyses by tumor aggressiveness and smoking status were performed in NMIBC patients. In the overall NMIBC group (n = 1,269), a statistically significant association between rs9642880 at 8q24 and risk of progression was observed (GT vs. TT: HR = 1.08 (95% CI: 0.76–1.54), GG vs. TT: HR = 1.81 (95% CI: 1.23–2.66), P for trend = 2.6×10−3). In subgroup analyses, several other variants showed suggestive, though non-significant, prognostic relevance for recurrence and progression in NMIBC and survival in MIBC. This study provides suggestive evidence that genetic loci involved in UBC etiology may influence disease prognosis. Elucidation of the causal variant(s) could further our understanding of the mechanism of disease, could point to new therapeutic targets, and might aid in improvement of prognostic tools. PMID:24586564
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Kim, Seon-Hee; Kong, Yoon; Bae, Young-An
2017-06-01
Autonomous retrotransposons, in which replication and transcription are coupled, encode the essential gag and pol genes as a fusion or separate overlapping form(s) that are expressed in single transcripts regulated by a common upstream promoter. The element-specific expression strategies have driven development of relevant translational recoding mechanisms including ribosomal frameshifting to satisfy the protein stoichiometry critical for the assembly of infectious virus-like particles. Retrotransposons with different recoding strategies exhibit a mosaic distribution pattern across the diverse families of reverse transcribing elements, even though their respective distributions are substantially skewed towards certain family groups. However, only a few investigations to date have focused on the emergence of retrotransposons evolving novel expression strategy and causal genetic drivers of the structural variants. In this study, the bulk of genomic and transcribed sequences of a Ty3/gypsy-like CsRn1 retrotransposon in Clonorchis sinensis were analyzed for the comprehensive examination of its expression strategy. Our results demonstrated that structural variants with single open reading frame (ORF) have recurrently emerged from precedential CsRn1 copies encoding overlapping gag-pol ORFs by a single-nucleotide insertion in an upstream region of gag stop codon. In the parasite genome, some of the newly evolved variants appeared to undergo proliferative burst as active master lineages together with their ancestral copies. The genetic event was similarly observed in Opisthorchis viverrini, the closest neighbor of C. sinensis, whereas the resulting structural variants might have failed to overcome purifying selection and comprised minor remnant copies in the Opisthorchis genome. Copyright © 2017 Elsevier B.V. All rights reserved.
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Describing the genetic architecture of epilepsy through heritability analysis.
Speed, Doug; O'Brien, Terence J; Palotie, Aarno; Shkura, Kirill; Marson, Anthony G; Balding, David J; Johnson, Michael R
2014-10-01
Epilepsy is a disease with substantial missing heritability; despite its high genetic component, genetic association studies have had limited success detecting common variants which influence susceptibility. In this paper, we reassess the role of common variants on epilepsy using extensions of heritability analysis. Our data set consists of 1258 UK patients with epilepsy, of which 958 have focal epilepsy, and 5129 population control subjects, with genotypes recorded for over 4 million common single nucleotide polymorphisms. Firstly, we show that on the liability scale, common variants collectively explain at least 26% (standard deviation 5%) of phenotypic variation for all epilepsy and 27% (standard deviation 5%) for focal epilepsy. Secondly we provide a new method for estimating the number of causal variants for complex traits; when applied to epilepsy, our most optimistic estimate suggests that at least 400 variants influence disease susceptibility, with potentially many thousands. Thirdly, we use bivariate analysis to assess how similar the genetic architecture of focal epilepsy is to that of non-focal epilepsy; we demonstrate both significant differences (P = 0.004) and significant similarities (P = 0.01) between the two subtypes, indicating that although the clinical definition of focal epilepsy does identify a genetically distinct epilepsy subtype, there is also scope to improve the classification of epilepsy by incorporating genotypic information. Lastly, we investigate the potential value in using genetic data to diagnose epilepsy following a single epileptic seizure; we find that a prediction model explaining 10% of phenotypic variation could have clinical utility for deciding which single-seizure individuals are likely to benefit from immediate anti-epileptic drug therapy. © The Author (2014). Published by Oxford University Press on behalf of the Guarantors of Brain.
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Sugiura, Kazumitsu
2014-06-01
Generalized pustular psoriasis (GPP) is often present in patients with existing or prior psoriasis vulgaris (PV; "GPP with PV"). However, cases of GPP have been known to arise without a history of PV ("GPP alone"). There has long been debate over whether GPP alone and GPP with PV are distinct subtypes that are etiologically different from each other. We recently reported that the majority of GPP alone cases is caused by recessive mutations of IL36RN. In contrast, only a few exceptional cases of GPP with PV were found to have recessive IL36RN mutations. Very recently, we also reported that CARD14 p.Asp176His, a gain-of-function variant, is a predisposing factor for GPP with PV; in contrast, the variant is not associated with GPP alone in the Japanese population. These results suggest that GPP alone is genetically different from GPP with PV. IL36RN mutations are also found in some patients with severe acute generalized exanthematous pustulosis, palmar-plantar pustulosis, and acrodermatitis continua of hallopeau. CARD14 mutations and variants are causal or disease susceptibility factors of PV, GPP, or pityriasis rubra pilaris, depending on the mutation or variant position of CARD14. It is clinically important to analyze IL36RN mutations in patients with sterile pustulosis. For example, identifying recessive IL36RN mutations leads to early diagnosis of GPP, even at the first episode of pustulosis. In addition, individuals with IL36RN mutations are very susceptible to GPP or GPP-related generalized pustulosis induced by drugs (e.g., amoxicillin), infections, pregnancy, or menstruation. Copyright © 2014 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.
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MetaSeq: privacy preserving meta-analysis of sequencing-based association studies.
Singh, Angad Pal; Zafer, Samreen; Pe'er, Itsik
2013-01-01
Human genetics recently transitioned from GWAS to studies based on NGS data. For GWAS, small effects dictated large sample sizes, typically made possible through meta-analysis by exchanging summary statistics across consortia. NGS studies groupwise-test for association of multiple potentially-causal alleles along each gene. They are subject to similar power constraints and therefore likely to resort to meta-analysis as well. The problem arises when considering privacy of the genetic information during the data-exchange process. Many scoring schemes for NGS association rely on the frequency of each variant thus requiring the exchange of identity of the sequenced variant. As such variants are often rare, potentially revealing the identity of their carriers and jeopardizing privacy. We have thus developed MetaSeq, a protocol for meta-analysis of genome-wide sequencing data by multiple collaborating parties, scoring association for rare variants pooled per gene across all parties. We tackle the challenge of tallying frequency counts of rare, sequenced alleles, for metaanalysis of sequencing data without disclosing the allele identity and counts, thereby protecting sample identity. This apparent paradoxical exchange of information is achieved through cryptographic means. The key idea is that parties encrypt identity of genes and variants. When they transfer information about frequency counts in cases and controls, the exchanged data does not convey the identity of a mutation and therefore does not expose carrier identity. The exchange relies on a 3rd party, trusted to follow the protocol although not trusted to learn about the raw data. We show applicability of this method to publicly available exome-sequencing data from multiple studies, simulating phenotypic information for powerful meta-analysis. The MetaSeq software is publicly available as open source.
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SEPTIN12 Genetic Variants Confer Susceptibility to Teratozoospermia
Lin, Ying-Hung; Wang, Ya-Yun; Chen, Hau-Inh; Kuo, Yung-Che; Chiou, Yu-Wei; Lin, Hsi-Hui; Wu, Ching-Ming; Hsu, Chao-Chin; Chiang, Han-Sun; Kuo, Pao-Lin
2012-01-01
It is estimated that 10–15% of couples are infertile and male factors account for about half of these cases. With the advent of intracytoplasmic sperm injection (ICSI), many infertile men have been able to father offspring. However, teratozoospermia still remains a big challenge to tackle. Septins belong to a family of cytoskeletal proteins with GTPase activity and are involved in various biological processes e.g. morphogenesis, compartmentalization, apoptosis and cytokinesis. SEPTIN12, identified by c-DNA microarray analysis of infertile men, is exclusively expressed in the post meiotic male germ cells. Septin12+/+/Septin12+/− chimeric mice have multiple reproductive defects including the presence of immature sperm in the semen, and sperm with bent neck (defect of the annulus) and nuclear DNA damage. These facts make SEPTIN12 a potential sterile gene in humans. In this study, we sequenced the entire coding region of SEPTIN12 in infertile men (n = 160) and fertile controls (n = 200) and identified ten variants. Among them is the c.474 G>A variant within exon 5 that encodes part of the GTP binding domain. The variant creates a novel splice donor site that causes skipping of a portion of exon 5, resulting in a truncated protein lacking the C-terminal half of SEPTIN12. Most individuals homozygous for the c.474 A allele had teratozoospermia (abnormal sperm <14%) and their sperm showed bent tail and de-condensed nucleus with significant DNA damage. Ex vivo experiment showed truncated SEPT12 inhibits filament formation in a dose-dependent manner. This study provides the first causal link between SEPTIN12 genetic variant and male infertility with distinctive sperm pathology. Our finding also suggests vital roles of SEPT12 in sperm nuclear integrity and tail development. PMID:22479503
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Effects of BMI, Fat Mass, and Lean Mass on Asthma in Childhood: A Mendelian Randomization Study
Granell, Raquel; Henderson, A. John; Evans, David M.; Smith, George Davey; Ness, Andrew R.; Lewis, Sarah; Palmer, Tom M.; Sterne, Jonathan A. C.
2014-01-01
Background Observational studies have reported associations between body mass index (BMI) and asthma, but confounding and reverse causality remain plausible explanations. We aim to investigate evidence for a causal effect of BMI on asthma using a Mendelian randomization approach. Methods and Findings We used Mendelian randomization to investigate causal effects of BMI, fat mass, and lean mass on current asthma at age 7½ y in the Avon Longitudinal Study of Parents and Children (ALSPAC). A weighted allele score based on 32 independent BMI-related single nucleotide polymorphisms (SNPs) was derived from external data, and associations with BMI, fat mass, lean mass, and asthma were estimated. We derived instrumental variable (IV) estimates of causal risk ratios (RRs). 4,835 children had available data on BMI-associated SNPs, asthma, and BMI. The weighted allele score was strongly associated with BMI, fat mass, and lean mass (all p-values<0.001) and with childhood asthma (RR 2.56, 95% CI 1.38–4.76 per unit score, p = 0.003). The estimated causal RR for the effect of BMI on asthma was 1.55 (95% CI 1.16–2.07) per kg/m2, p = 0.003. This effect appeared stronger for non-atopic (1.90, 95% CI 1.19–3.03) than for atopic asthma (1.37, 95% CI 0.89–2.11) though there was little evidence of heterogeneity (p = 0.31). The estimated causal RRs for the effects of fat mass and lean mass on asthma were 1.41 (95% CI 1.11–1.79) per 0.5 kg and 2.25 (95% CI 1.23–4.11) per kg, respectively. The possibility of genetic pleiotropy could not be discounted completely; however, additional IV analyses using FTO variant rs1558902 and the other BMI-related SNPs separately provided similar causal effects with wider confidence intervals. Loss of follow-up was unlikely to bias the estimated effects. Conclusions Higher BMI increases the risk of asthma in mid-childhood. Higher BMI may have contributed to the increase in asthma risk toward the end of the 20th century. Please see later in the article for the Editors' Summary PMID:24983943
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Xu, Min; Bi, Yufang; Huang, Ya; Xie, Lan; Hao, Mingli; Zhao, Zhiyun; Xu, Yu; Lu, Jieli; Chen, Yuhong; Sun, Yimin; Qi, Lu; Wang, Weiqing; Ning, Guang
2016-01-01
Background Type 2 diabetes (T2D) is a risk factor for dysregulation of glomerular filtration rate (GFR) and albuminuria. However, whether the association is causal remains unestablished. Research Design and Methods We performed a Mendelian Randomization (MR) analysis in 11,502 participants aged 40 and above, from a well-defined community in Shanghai during 2011–2013, to explore the causal association between T2D and decreased estimated GFR (eGFR) and increased urinary albumin-to-creatinine ratio (uACR). We genotyped 34 established T2D common variants in East Asians, and created a T2D-genetic risk score (GRS). We defined decreased eGFR as eGFR < 90 ml/min/1.73 m2 and increased uACR as uACR ≥ 30 mg/g. We used the T2D_GRS as the instrumental variable (IV) to quantify the causal effect of T2D on decreased eGFR and increased uACR. Results Each 1-standard deviation (SD, 3.90 points) increment in T2D_GRS was associated with decreased eGFR: odds ratio (OR) = 1.18 (95% confidence interval [CI]: 1.01, 1.30). In the MR analysis, we demonstrated a causal relationship between genetically determined T2D and decreased eGFR (OR = 1.47, 95% CI: 1.15, 1.88, P = 0.0003). When grouping the genetic loci according to their relations with either insulin secretion (IS) or insulin resistance (IR), we found both IS_GRS and IR_GRS were significantly related to decreased eGFR (both P < 0.02). In addition, T2D_GRS and IS_GRS were significantly associated with Log-uACR (both P = 0.04). Conclusion Our results provide novel evidence for a causal association between T2D and decreased eGFR by using MR approach in a Chinese population. PMID:27211558
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Xu, Min; Bi, Yufang; Huang, Ya; Xie, Lan; Hao, Mingli; Zhao, Zhiyun; Xu, Yu; Lu, Jieli; Chen, Yuhong; Sun, Yimin; Qi, Lu; Wang, Weiqing; Ning, Guang
2016-04-01
Type 2 diabetes (T2D) is a risk factor for dysregulation of glomerular filtration rate (GFR) and albuminuria. However, whether the association is causal remains unestablished. We performed a Mendelian Randomization (MR) analysis in 11,502 participants aged 40 and above, from a well-defined community in Shanghai during 2011-2013, to explore the causal association between T2D and decreased estimated GFR (eGFR) and increased urinary albumin-to-creatinine ratio (uACR). We genotyped 34 established T2D common variants in East Asians, and created a T2D-genetic risk score (GRS). We defined decreased eGFR as eGFR<90ml/min/1.73m(2) and increased uACR as uACR≥30mg/g. We used the T2D_GRS as the instrumental variable (IV) to quantify the causal effect of T2D on decreased eGFR and increased uACR. Each 1-standard deviation (SD, 3.90 points) increment in T2D_GRS was associated with decreased eGFR: odds ratio (OR)=1.18 (95% confidence interval [CI]: 1.01, 1.30). In the MR analysis, we demonstrated a causal relationship between genetically determined T2D and decreased eGFR (OR=1.47, 95% CI: 1.15, 1.88, P=0.0003). When grouping the genetic loci according to their relations with either insulin secretion (IS) or insulin resistance (IR), we found both IS_GRS and IR_GRS were significantly related to decreased eGFR (both P<0.02). In addition, T2D_GRS and IS_GRS were significantly associated with Log-uACR (both P=0.04). Our results provide novel evidence for a causal association between T2D and decreased eGFR by using MR approach in a Chinese population. Copyright © 2016. Published by Elsevier B.V.
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Causal Imprinting in Causal Structure Learning
Taylor, Eric G.; Ahn, Woo-kyoung
2012-01-01
Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures “causal imprinting.” Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. PMID:22859019
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A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.
Hu, Shoubo; Chen, Zhitang; Chan, Laiwan
2018-05-01
Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration. In this letter, we propose a kernel embedding-based approach, ENCI, for nonstationary causal model inference where data are collected from multiple domains with varying distributions. In ENCI, we transform the complicated relation of a cause-effect pair into a linear model of variables of which observations correspond to the kernel embeddings of the cause-and-effect distributions in different domains. In this way, we are able to estimate the causal direction by exploiting the causal asymmetry of the transformed linear model. Furthermore, we extend ENCI to causal graph discovery for multiple variables by transforming the relations among them into a linear nongaussian acyclic model. We show that by exploiting the nonstationarity of distributions, both cause-effect pairs and two kinds of causal graphs are identifiable under mild conditions. Experiments on synthetic and real-world data are conducted to justify the efficacy of ENCI over major existing methods.
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Use of model organism and disease databases to support matchmaking for human disease gene discovery.
Mungall, Christopher J; Washington, Nicole L; Nguyen-Xuan, Jeremy; Condit, Christopher; Smedley, Damian; Köhler, Sebastian; Groza, Tudor; Shefchek, Kent; Hochheiser, Harry; Robinson, Peter N; Lewis, Suzanna E; Haendel, Melissa A
2015-10-01
The Matchmaker Exchange application programming interface (API) allows searching a patient's genotypic or phenotypic profiles across clinical sites, for the purposes of cohort discovery and variant disease causal validation. This API can be used not only to search for matching patients, but also to match against public disease and model organism data. This public disease data enable matching known diseases and variant-phenotype associations using phenotype semantic similarity algorithms developed by the Monarch Initiative. The model data can provide additional evidence to aid diagnosis, suggest relevant models for disease mechanism and treatment exploration, and identify collaborators across the translational divide. The Monarch Initiative provides an implementation of this API for searching multiple integrated sources of data that contextualize the knowledge about any given patient or patient family into the greater biomedical knowledge landscape. While this corpus of data can aid diagnosis, it is also the beginning of research to improve understanding of rare human diseases. © 2015 WILEY PERIODICALS, INC.
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Molecular turnover, the H3.3 dilemma and organismal aging (hypothesis)
Saade, Evelyne; Pirozhkova, Iryna; Aimbetov, Rakhan; Lipinski, Marc; Ogryzko, Vasily
2015-01-01
The H3.3 histone variant has been a subject of increasing interest in the field of chromatin studies due to its two distinguishing features. First, its incorporation into chromatin is replication independent unlike the replication-coupled deposition of its canonical counterparts H3.1/2. Second, H3.3 has been consistently associated with an active state of chromatin. In accordance, this histone variant should be expected to be causally involved in the regulation of gene expression, or more generally, its incorporation should have downstream consequences for the structure and function of chromatin. This, however, leads to an apparent paradox: In cells that slowly replicate in the organism, H3.3 will accumulate with time, opening the way to aberrant effects on heterochromatin. Here, we review the indications that H3.3 is expected both to be incorporated in the heterochromatin of slowly replicating cells and to retain its functional downstream effects. Implications for organismal aging are discussed. PMID:25720734
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The severity of hereditary porphyria is modulated by the porphyrin exporter and Lan antigen ABCB6
Fukuda, Yu; Cheong, Pak Leng; Lynch, John; Brighton, Cheryl; Frase, Sharon; Kargas, Vasileios; Rampersaud, Evadnie; Wang, Yao; Sankaran, Vijay G.; Yu, Bing; Ney, Paul A.; Weiss, Mitchell J.; Vogel, Peter; Bond, Peter J.; Ford, Robert C.; Trent, Ronald J.; Schuetz, John D.
2016-01-01
Hereditary porphyrias are caused by mutations in genes that encode haem biosynthetic enzymes with resultant buildup of cytotoxic metabolic porphyrin intermediates. A long-standing open question is why the same causal porphyria mutations exhibit widely variable penetrance and expressivity in different individuals. Here we show that severely affected porphyria patients harbour variant alleles in the ABCB6 gene, also known as Lan, which encodes an ATP-binding cassette (ABC) transporter. Plasma membrane ABCB6 exports a variety of disease-related porphyrins. Functional studies show that most of these ABCB6 variants are expressed poorly and/or have impaired function. Accordingly, homozygous disruption of the Abcb6 gene in mice exacerbates porphyria phenotypes in the Fechm1Pas mouse model, as evidenced by increased porphyrin accumulation, and marked liver injury. Collectively, these studies support ABCB6 role as a genetic modifier of porphyria and suggest that porphyrin-inducing drugs may produce excessive toxicities in individuals with the rare Lan(−) blood type. PMID:27507172
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Illusions of causality: how they bias our everyday thinking and how they could be reduced.
Matute, Helena; Blanco, Fernando; Yarritu, Ion; Díaz-Lago, Marcos; Vadillo, Miguel A; Barberia, Itxaso
2015-01-01
Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion.
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Illusions of causality: how they bias our everyday thinking and how they could be reduced
Matute, Helena; Blanco, Fernando; Yarritu, Ion; Díaz-Lago, Marcos; Vadillo, Miguel A.; Barberia, Itxaso
2015-01-01
Illusions of causality occur when people develop the belief that there is a causal connection between two events that are actually unrelated. Such illusions have been proposed to underlie pseudoscience and superstitious thinking, sometimes leading to disastrous consequences in relation to critical life areas, such as health, finances, and wellbeing. Like optical illusions, they can occur for anyone under well-known conditions. Scientific thinking is the best possible safeguard against them, but it does not come intuitively and needs to be taught. Teaching how to think scientifically should benefit from better understanding of the illusion of causality. In this article, we review experiments that our group has conducted on the illusion of causality during the last 20 years. We discuss how research on the illusion of causality can contribute to the teaching of scientific thinking and how scientific thinking can reduce illusion. PMID:26191014
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Veturi, Yogasudha; Ritchie, Marylyn D
2018-01-01
Transcriptome-wide association studies (TWAS) have recently been employed as an approach that can draw upon the advantages of genome-wide association studies (GWAS) and gene expression studies to identify genes associated with complex traits. Unlike standard GWAS, summary level data suffices for TWAS and offers improved statistical power. Two popular TWAS methods include either (a) imputing the cis genetic component of gene expression from smaller sized studies (using multi-SNP prediction or MP) into much larger effective sample sizes afforded by GWAS - TWAS-MP or (b) using summary-based Mendelian randomization - TWAS-SMR. Although these methods have been effective at detecting functional variants, it remains unclear how extensive variability in the genetic architecture of complex traits and diseases impacts TWAS results. Our goal was to investigate the different scenarios under which these methods yielded enough power to detect significant expression-trait associations. In this study, we conducted extensive simulations based on 6000 randomly chosen, unrelated Caucasian males from Geisinger's MyCode population to compare the power to detect cis expression-trait associations (within 500 kb of a gene) using the above-described approaches. To test TWAS across varying genetic backgrounds we simulated gene expression and phenotype using different quantitative trait loci per gene and cis-expression /trait heritability under genetic models that differentiate the effect of causality from that of pleiotropy. For each gene, on a training set ranging from 100 to 1000 individuals, we either (a) estimated regression coefficients with gene expression as the response using five different methods: LASSO, elastic net, Bayesian LASSO, Bayesian spike-slab, and Bayesian ridge regression or (b) performed eQTL analysis. We then sampled with replacement 50,000, 150,000, and 300,000 individuals respectively from the testing set of the remaining 5000 individuals and conducted GWAS on each set. Subsequently, we integrated the GWAS summary statistics derived from the testing set with the weights (or eQTLs) derived from the training set to identify expression-trait associations using (a) TWAS-MP (b) TWAS-SMR (c) eQTL-based GWAS, or (d) standalone GWAS. Finally, we examined the power to detect functionally relevant genes using the different approaches under the considered simulation scenarios. In general, we observed great similarities among TWAS-MP methods although the Bayesian methods resulted in improved power in comparison to LASSO and elastic net as the trait architecture grew more complex while training sample sizes and expression heritability remained small. Finally, we observed high power under causality but very low to moderate power under pleiotropy.
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Fairfield, Beth; Mammarella, Nicola; Di Domenico, Alberto; D'Aurora, Marco; Stuppia, Liborio; Gatta, Valentina
2017-08-30
False memories are common memory distortions in everyday life and seem to increase with affectively connoted complex information. In line with recent studies showing a significant interaction between the noradrenergic system and emotional memory, we investigated whether healthy volunteer carriers of the deletion variant of the ADRA2B gene that codes for the α2b-adrenergic receptor are more prone to false memories than non-carriers. In this study, we collected genotype data from 212 healthy female volunteers; 91 ADRA2B carriers and 121 non-carriers. To assess gene effects on false memories for affective information, factorial mixed model analysis of variances (ANOVAs) were conducted with genotype as the between-subjects factor and type of memory error as the within-subjects factor. We found that although carriers and non-carriers made comparable numbers of false memory errors, they showed differences in the direction of valence biases, especially for inferential causal errors. Specifically, carriers produced fewer causal false memory errors for scripts with a negative outcome, whereas non-carriers showed a more general emotional effect and made fewer causal errors with both positive and negative outcomes. These findings suggest that putatively higher levels of noradrenaline in deletion carriers may enhance short-term consolidation of negative information and lead to fewer memory distortions when facing negative events. Copyright © 2017 Elsevier B.V. All rights reserved.
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Staley, James R; Burgess, Stephen
2017-05-01
Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure-outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure-outcome relationship: a fractional polynomial method and a piecewise linear method. We divide the population into strata using the exposure distribution, and estimate a causal effect, referred to as a localized average causal effect (LACE), in each stratum of population. The fractional polynomial method performs metaregression on these LACE estimates. The piecewise linear method estimates a continuous piecewise linear function, the gradient of which is the LACE estimate in each stratum. Both methods were demonstrated in a simulation study to estimate the true exposure-outcome relationship well, particularly when the relationship was a fractional polynomial (for the fractional polynomial method) or was piecewise linear (for the piecewise linear method). The methods were used to investigate the shape of relationship of body mass index with systolic blood pressure and diastolic blood pressure. © 2017 The Authors Genetic Epidemiology Published by Wiley Periodicals, Inc.
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Staley, James R.
2017-01-01
ABSTRACT Mendelian randomization, the use of genetic variants as instrumental variables (IV), can test for and estimate the causal effect of an exposure on an outcome. Most IV methods assume that the function relating the exposure to the expected value of the outcome (the exposure‐outcome relationship) is linear. However, in practice, this assumption may not hold. Indeed, often the primary question of interest is to assess the shape of this relationship. We present two novel IV methods for investigating the shape of the exposure‐outcome relationship: a fractional polynomial method and a piecewise linear method. We divide the population into strata using the exposure distribution, and estimate a causal effect, referred to as a localized average causal effect (LACE), in each stratum of population. The fractional polynomial method performs metaregression on these LACE estimates. The piecewise linear method estimates a continuous piecewise linear function, the gradient of which is the LACE estimate in each stratum. Both methods were demonstrated in a simulation study to estimate the true exposure‐outcome relationship well, particularly when the relationship was a fractional polynomial (for the fractional polynomial method) or was piecewise linear (for the piecewise linear method). The methods were used to investigate the shape of relationship of body mass index with systolic blood pressure and diastolic blood pressure. PMID:28317167
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Grewal, S I; Han, B; Johnstone, K
1995-01-01
Pseudomonas tolaasii, the causal agent of brown blotch disease of Agaricus bisporus, spontaneously gives rise to morphologically distinct stable sectors, referred to as the phenotypic variant form, at the margins of the wild-type colonies. The phenotypic variant form is nonpathogenic and differs from the wild type in a range of biochemical and physiological characteristics. A genomic cosmid clone (pSISG29) from a wild-type P. tolaasii library was shown to be capable of restoring a range of characteristics of the phenotypic variant to those of the wild-type form, when present in trans. Subcloning and saturation mutagenesis analysis with Tn5lacZ localized a 3.0-kb region from pSISG29, designated the pheN locus, required for complementation of the phenotypic variant to the wild-type form. Marker exchange of the Tn5lacZ-mutagenized copy of the pheN locus into the wild-type strain demonstrated that a functional copy of the pheN gene is required to maintain the wild-type pathogenic phenotype and that loss of the pheN gene or its function results in conversion of the wild-type form to the phenotypic variant form. The pheN locus contained a 2,727-bp open reading frame encoding an 83-kDa protein. The predicted amino acid sequence of the PheN protein showed homology to the sensor and regulator domains of the conserved family of two component bacterial sensor regulator proteins. Southern hybridization analysis of pheN genes from the wild type and the phenotypic variant form revealed that DNA rearrangement occurs within the pheN locus during phenotypic variation. Analysis of pheN expression with a pheN::lacZ fusion demonstrated that expression is regulated by environmental factors. These results are related to a model for control for phenotypic variation in P. tolaasii. PMID:7642492
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Cao, Ying; Rajan, Suja S; Wei, Peng
2016-12-01
A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.
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Park, Soojin; Steiner, Peter M; Kaplan, David
2018-06-01
Considering that causal mechanisms unfold over time, it is important to investigate the mechanisms over time, taking into account the time-varying features of treatments and mediators. However, identification of the average causal mediation effect in the presence of time-varying treatments and mediators is often complicated by time-varying confounding. This article aims to provide a novel approach to uncovering causal mechanisms in time-varying treatments and mediators in the presence of time-varying confounding. We provide different strategies for identification and sensitivity analysis under homogeneous and heterogeneous effects. Homogeneous effects are those in which each individual experiences the same effect, and heterogeneous effects are those in which the effects vary over individuals. Most importantly, we provide an alternative definition of average causal mediation effects that evaluates a partial mediation effect; the effect that is mediated by paths other than through an intermediate confounding variable. We argue that this alternative definition allows us to better assess at least a part of the mediated effect and provides meaningful and unique interpretations. A case study using ECLS-K data that evaluates kindergarten retention policy is offered to illustrate our proposed approach.
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Interactive Planning under Uncertainty with Casual Modeling and Analysis
2006-01-01
Tool ( CAT ), a system for creating and analyzing causal models similar to Bayes networks. In order to use CAT as a tool for planning, users go through...an iterative process in which they use CAT to create and an- alyze alternative plans. One of the biggest difficulties is that the number of possible...Causal Analysis Tool ( CAT ), which is a tool for representing and analyzing causal networks sim- ilar to Bayesian networks. In order to represent plans
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Data-driven confounder selection via Markov and Bayesian networks.
Häggström, Jenny
2018-06-01
To unbiasedly estimate a causal effect on an outcome unconfoundedness is often assumed. If there is sufficient knowledge on the underlying causal structure then existing confounder selection criteria can be used to select subsets of the observed pretreatment covariates, X, sufficient for unconfoundedness, if such subsets exist. Here, estimation of these target subsets is considered when the underlying causal structure is unknown. The proposed method is to model the causal structure by a probabilistic graphical model, for example, a Markov or Bayesian network, estimate this graph from observed data and select the target subsets given the estimated graph. The approach is evaluated by simulation both in a high-dimensional setting where unconfoundedness holds given X and in a setting where unconfoundedness only holds given subsets of X. Several common target subsets are investigated and the selected subsets are compared with respect to accuracy in estimating the average causal effect. The proposed method is implemented with existing software that can easily handle high-dimensional data, in terms of large samples and large number of covariates. The results from the simulation study show that, if unconfoundedness holds given X, this approach is very successful in selecting the target subsets, outperforming alternative approaches based on random forests and LASSO, and that the subset estimating the target subset containing all causes of outcome yields smallest MSE in the average causal effect estimation. © 2017, The International Biometric Society.
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Skaaby, Tea; Taylor, Amy E; Jacobsen, Rikke K; Paternoster, Lavinia; Thuesen, Betina H; Ahluwalia, Tarunveer S; Larsen, Sofus C; Zhou, Ang; Wong, Andrew; Gabrielsen, Maiken E; Bjørngaard, Johan H; Flexeder, Claudia; Männistö, Satu; Hardy, Rebecca; Kuh, Diana; Barry, Sarah J; Tang Møllehave, Line; Cerqueira, Charlotte; Friedrich, Nele; Bonten, Tobias N; Noordam, Raymond; Mook-Kanamori, Dennis O; Taube, Christian; Jessen, Leon E; McConnachie, Alex; Sattar, Naveed; Upton, Mark N; McSharry, Charles; Bønnelykke, Klaus; Bisgaard, Hans; Schulz, Holger; Strauch, Konstantin; Meitinger, Thomas; Peters, Annette; Grallert, Harald; Nohr, Ellen A; Kivimaki, Mika; Kumari, Meena; Völker, Uwe; Nauck, Matthias; Völzke, Henry; Power, Chris; Hyppönen, Elina; Hansen, Torben; Jørgensen, Torben; Pedersen, Oluf; Salomaa, Veikko; Grarup, Niels; Langhammer, Arnulf; Romundstad, Pål R; Skorpen, Frank; Kaprio, Jaakko; R Munafò, Marcus; Linneberg, Allan
2017-05-22
Observational studies on smoking and risk of hay fever and asthma have shown inconsistent results. However, observational studies may be biased by confounding and reverse causation. Mendelian randomization uses genetic variants as markers of exposures to examine causal effects. We examined the causal effect of smoking on hay fever and asthma by using the smoking-associated single nucleotide polymorphism (SNP) rs16969968/rs1051730. We included 231,020 participants from 22 population-based studies. Observational analyses showed that current vs never smokers had lower risk of hay fever (odds ratio (OR) = 0·68, 95% confidence interval (CI): 0·61, 0·76; P < 0·001) and allergic sensitization (OR = 0·74, 95% CI: 0·64, 0·86; P < 0·001), but similar asthma risk (OR = 1·00, 95% CI: 0·91, 1·09; P = 0·967). Mendelian randomization analyses in current smokers showed a slightly lower risk of hay fever (OR = 0·958, 95% CI: 0·920, 0·998; P = 0·041), a lower risk of allergic sensitization (OR = 0·92, 95% CI: 0·84, 1·02; P = 0·117), but higher risk of asthma (OR = 1·06, 95% CI: 1·01, 1·11; P = 0·020) per smoking-increasing allele. Our results suggest that smoking may be causally related to a higher risk of asthma and a slightly lower risk of hay fever. However, the adverse events associated with smoking limit its clinical significance.
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Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S
2014-11-01
COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
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Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis.
Bjørngaard, Johan H; Nordestgaard, Ask Tybjærg; Taylor, Amy E; Treur, Jorien L; Gabrielsen, Maiken E; Munafò, Marcus R; Nordestgaard, Børge Grønne; Åsvold, Bjørn Olav; Romundstad, Pål; Davey Smith, George
2017-12-01
There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake. We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies. Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: -0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption. Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association.
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Heavier smoking increases coffee consumption: findings from a Mendelian randomization analysis
Bjørngaard, Johan H; Nordestgaard, Ask Tybjærg; Taylor, Amy E; Treur, Jorien L; Gabrielsen, Maiken E; Munafò, Marcus R; Nordestgaard, Børge Grønne; Åsvold, Bjørn Olav; Romundstad, Pål; Davey Smith, George
2017-01-01
Abstract Background There is evidence for a positive relationship between cigarette and coffee consumption in smokers. Cigarette smoke increases metabolism of caffeine, so this may represent a causal effect of smoking on caffeine intake. Methods We performed Mendelian randomization analyses in the UK Biobank (N = 114 029), the Norwegian HUNT study (N = 56 664) and the Copenhagen General Population Study (CGPS) (N = 78 650). We used the rs16969968 genetic variant as a proxy for smoking heaviness in all studies and rs4410790 and rs2472297 as proxies for coffee consumption in UK Biobank and CGPS. Analyses were conducted using linear regression and meta-analysed across studies. Results Each additional cigarette per day consumed by current smokers was associated with higher coffee consumption (0.10 cups per day, 95% CI: 0.03, 0.17). There was weak evidence for an increase in tea consumption per additional cigarette smoked per day (0.04 cups per day, 95% CI: −0.002, 0.07). There was strong evidence that each additional copy of the minor allele of rs16969968 (which increases daily cigarette consumption) in current smokers was associated with higher coffee consumption (0.16 cups per day, 95% CI: 0.11, 0.20), but only weak evidence for an association with tea consumption (0.04 cups per day, 95% CI: -0.01, 0.09). There was no clear evidence that rs16969968 was associated with coffee or tea consumption in never or former smokers or that the coffee-related variants were associated with cigarette consumption. Conclusions Higher cigarette consumption causally increases coffee intake. This is consistent with faster metabolism of caffeine by smokers, but could also reflect a behavioural effect of smoking on coffee drinking. PMID:29025033
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Daily minority stress and affect among gay and bisexual men: A 30-day diary study.
Eldahan, Adam I; Pachankis, John E; Jonathon Rendina, H; Ventuneac, Ana; Grov, Christian; Parsons, Jeffrey T
2016-01-15
This study examined the time-variant association between daily minority stress and daily affect among gay and bisexual men. Tests of time-lagged associations allow for a stronger causal examination of minority stress-affect associations compared with static assessments. Multilevel modeling allows for comparison of associations between minority stress and daily affect when minority stress is modeled as a between-person factor and a within-person time-fluctuating state. 371 gay and bisexual men in New York City completed a 30-day daily diary, recording daily experiences of minority stress and positive affect (PA), negative affect (NA), and anxious affect (AA). Multilevel analyses examined associations between minority stress and affect in both same-day and time-lagged analyses, with minority stress assessed as both a between-person factor and a within-person state. Daily minority stress, modeled as both a between-person and within-person construct, significantly predicted lower PA and higher NA and AA. Daily minority stress also predicted lower subsequent-day PA and higher subsequent-day NA and AA. Self-report assessments and the unique sample may limit generalizability of this study. The time-variant association between sexual minority stress and affect found here substantiates the basic tenet of minority stress theory with a fine-grained analysis of gay and bisexual men's daily experience. Time-lagged effects suggest a potentially causal pathway between minority stress as a social determinant of mood and anxiety disorder symptoms among gay and bisexual men. When modeled as both a between-person factor and within-person state, minority stress demonstrated expected patterns with affect. Copyright © 2015 Elsevier B.V. All rights reserved.
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Daily Minority Stress and Affect among Gay and Bisexual Men: A 30-day Diary Study
Eldahan, Adam I.; Pachankis, John E.; Rendina, H. Jonathon; Ventuneac, Ana; Grov, Christian; Parsons, Jeffrey T.
2015-01-01
Background This study examined the time-variant association between daily minority stress and daily affect among gay and bisexual men. Tests of time-lagged associations allow for a stronger causal examination of minority stress-affect associations compared with static assessments. Multilevel modeling allows for comparison of associations between minority stress and daily affect when minority stress is modeled as a between-person factor and a within-person time-fluctuating state. Methods 371 gay and bisexual men in New York City completed a 30-day daily diary, recording daily experiences of minority stress and positive affect (PA), negative affect (NA), and anxious affect (AA). Multilevel analyses examined associations between minority stress and affect in both same-day and time-lagged analyses, with minority stress assessed as both a between-person factor and a within-person state. Results Daily minority stress, modeled as both a between-person and within-person construct, significantly predicted lower PA and higher NA and AA. Daily minority stress also predicted lower subsequent-day PA and higher subsequent-day NA and AA. Limitations Self-report assessments and the unique sample may limit generalizability of this study. Conclusions The time-variant association between sexual minority stress and affect found here substantiates the basic tenet of minority stress theory with a fine-grained analysis of gay and bisexual men’s daily experience. Time-lagged effects suggest a potentially causal pathway between minority stress as a social determinant of mood and anxiety disorder symptoms among gay and bisexual men. When modeled as both a between-person factor and within-person state, minority stress demonstrated expected patterns with affect. PMID:26625095
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NASA Astrophysics Data System (ADS)
Kireeva, I. V.; Platonova, Yu. N.; Chumlyakov, Yu. I.
2017-02-01
The ordinary and two-way shape memory effects (SMEs) are investigated for [ overline{1} 12] single crystals of Ti-51.3Ni (at.%) alloy aged at 823 K for 1.5 h in free state and under tensile stress of 150 MPa without hydrogen and after saturation by hydrogen. It is established that without hydrogen in [ overline{1} 12] single crystals with one and four variants of Ti3Ni4 particles the maximum magnitude of the ordinary SME is 1.9-2.6% under the external stress σext = 250 MPa. Under σext > 250 MPa, crystals are destroyed. The magnitude of the two-way SME caused by the B2- R- B19' MT equal to 1.1% at σext = 0 is observed in [ overline{1} 12] single crystals with one variant of Ti3Ni4 particles. The physical reason for the observed two-way SME is the internal compressive stresses oriented along the [ overline{1} 12] directions arising from one variant of Ti3Ni4 particles as a result of aging under tensile stress of 150 MPa. It is established that hydrogen does not influence the TR temperature, reduces the plasticity, and suppresses the two-way SME. The suppression of two-way SME in the [ overline{1} 12] single crystals of the Ti-51.3Ni (at.%) alloy with one variant of Ti3Ni4 particles is caused by shielding of stress fields from one variant of Ti3Ni4 particles and multiple nucleation of R- and B19' martensite variants under loading with saturation by hydrogen.
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Pride and Prejudice and Causal Indicators
ERIC Educational Resources Information Center
Lee, Nick; Chamberlain, Laura
2016-01-01
Aguirre-Urreta, Rönkkö, and Marakas' (2016) paper in "Measurement: Interdisciplinary Research and Perspectives" (hereafter referred to as ARM2016) is an important and timely piece of scholarship, in that it provides strong analytic support to the growing theoretical literature that questions the underlying ideas behind causal and…
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Causal imprinting in causal structure learning.
Taylor, Eric G; Ahn, Woo-Kyoung
2012-11-01
Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.
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Porta, Alberto; Bassani, Tito; Bari, Vlasta; Pinna, Gian D; Maestri, Roberto; Guzzetti, Stefano
2012-03-01
This study was designed to demonstrate the need of accounting for respiration (R) when causality between heart period (HP) and systolic arterial pressure (SAP) is under scrutiny. Simulations generated according to a bivariate autoregressive closed-loop model were utilized to assess how causality changes as a function of the model parameters. An exogenous (X) signal was added to the bivariate autoregressive closed-loop model to evaluate the bias on causality induced when the X source was disregarded. Causality was assessed in the time domain according to a predictability improvement approach (i.e., Granger causality). HP and SAP variability series were recorded with R in 19 healthy subjects during spontaneous and controlled breathing at 10, 15, and 20 breaths/min. Simulations proved the importance of accounting for X signals. During spontaneous breathing, assessing causality without taking into consideration R leads to a significantly larger percentage of closed-loop interactions and a smaller fraction of unidirectional causality from HP to SAP. This finding was confirmed during paced breathing and it was independent of the breathing rate. These results suggest that the role of baroreflex cannot be correctly assessed without accounting for R.
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Jain, Jay Prakash; Leong, F Joel; Chen, Lan; Kalluri, Sampath; Koradia, Vishal; Stein, Daniel S; Wolf, Marie-Christine; Sunkara, Gangadhar; Kota, Jagannath
2017-09-01
The artemether-lumefantrine combination requires food intake for the optimal absorption of lumefantrine. In an attempt to enhance the bioavailability of lumefantrine, new solid dispersion formulations (SDF) were developed, and the pharmacokinetics of two SDF variants were assessed in a randomized, open-label, sequential two-part study in healthy volunteers. In part 1, the relative bioavailability of the two SDF variants was compared with that of the conventional formulation after administration of a single dose of 480 mg under fasted conditions in three parallel cohorts. In part 2, the pharmacokinetics of lumefantrine from both SDF variants were evaluated after a single dose of 480 mg under fed conditions and a single dose of 960 mg under fasted conditions. The bioavailability of lumefantrine from SDF variant 1 and variant 2 increased up to ∼48-fold and ∼24-fold, respectively, relative to that of the conventional formulation. Both variants demonstrated a positive food effect and a less than proportional increase in exposure between the 480-mg and 960-mg doses. Most adverse events (AEs) were mild to moderate in severity and not suspected to be related to the study drug. All five drug-related AEs occurred in subjects taking SDF variant 2. No clinically significant treatment-emergent changes in vital signs, electrocardiograms, or laboratory blood assessments were noted. The solid dispersion formulation enhances the lumefantrine bioavailability to a significant extent, and SDF variant 1 is superior to SDF variant 2. Copyright © 2017 Jain et al.
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Updating during reading comprehension: why causality matters.
Kendeou, Panayiota; Smith, Emily R; O'Brien, Edward J
2013-05-01
The present set of 7 experiments systematically examined the effectiveness of adding causal explanations to simple refutations in reducing or eliminating the impact of outdated information on subsequent comprehension. The addition of a single causal-explanation sentence to a refutation was sufficient to eliminate any measurable disruption in comprehension caused by the outdated information (Experiment 1) but was not sufficient to eliminate its reactivation (Experiment 2). However, a 3 sentence causal-explanation addition to a refutation eliminated both any measurable disruption in comprehension (Experiment 3) and the reactivation of the outdated information (Experiment 4). A direct comparison between the 1 and 3 causal-explanation conditions provided converging evidence for these findings (Experiment 5). Furthermore, a comparison of the 3 sentence causal-explanation condition with a 3 sentence qualified-elaboration condition demonstrated that even though both conditions were sufficient to eliminate any measurable disruption in comprehension (Experiment 6), only the causal-explanation condition was sufficient to eliminate the reactivation of the outdated information (Experiment 7). These results establish a boundary condition under which outdated information will influence comprehension; they also have broader implications for both the updating process and knowledge revision in general.
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Thurner, Matthias; van de Bunt, Martijn; Torres, Jason M; Mahajan, Anubha; Nylander, Vibe; Bennett, Amanda J; Gaulton, Kyle J; Barrett, Amy; Burrows, Carla; Bell, Christopher G; Lowe, Robert; Beck, Stephan; Rakyan, Vardhman K; Gloyn, Anna L
2018-01-01
Human genetic studies have emphasised the dominant contribution of pancreatic islet dysfunction to development of Type 2 Diabetes (T2D). However, limited annotation of the islet epigenome has constrained efforts to define the molecular mechanisms mediating the, largely regulatory, signals revealed by Genome-Wide Association Studies (GWAS). We characterised patterns of chromatin accessibility (ATAC-seq, n = 17) and DNA methylation (whole-genome bisulphite sequencing, n = 10) in human islets, generating high-resolution chromatin state maps through integration with established ChIP-seq marks. We found enrichment of GWAS signals for T2D and fasting glucose was concentrated in subsets of islet enhancers characterised by open chromatin and hypomethylation, with the former annotation predominant. At several loci (including CDC123, ADCY5, KLHDC5) the combination of fine-mapping genetic data and chromatin state enrichment maps, supplemented by allelic imbalance in chromatin accessibility pinpointed likely causal variants. The combination of increasingly-precise genetic and islet epigenomic information accelerates definition of causal mechanisms implicated in T2D pathogenesis. PMID:29412141
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Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.
Shi, Huwenbo; Mancuso, Nicholas; Spendlove, Sarah; Pasaniuc, Bogdan
2017-11-02
Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
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Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis
ERIC Educational Resources Information Center
Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A.
2011-01-01
In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…
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ERIC Educational Resources Information Center
Mahasinpaisan, Tippaporn
2011-01-01
The purpose of this study was to propose causal model of the relationship among transformational leadership, organizational culture, knowledge management, and organizational performance. A sample of 389 was randomly drawn from instructors of private higher education institutions under the Office of the Higher Education Commission. Data were…
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Dávalos, I P; Olivares, N; Castillo, M T; Cantú, J M; Ibarra, B; Sandoval, L; Morán, M C; Gallegos, M P; Chakraborty, R; Rivas, F
2000-01-01
The C677T mutation of the methylenetetrahydrofolate reductase (MTHFR) gene, associated with the thermolabile form of the enzyme, has reportedly been found to be increased in neural-tube defects (NTD), though this association is still unclear. A group of 107 mestizo parents of NTD children and five control populations: 101 mestizo (M), 50 Huichol (H), 38 Tarahumara (T), 21 Purepecha (P) and 20 Caucasian (C) individuals were typed for the MTHFR C677T variant by the PCR/RFLP (HinfI) method. Genotype frequencies were in agreement with the Hardy-Weinberg expectations in all six populations. Allele frequency (%) of the C677T variant was 45 in NTD, 44 in M, 56 in H, 36 in T, 57 in P, 35 in C. Pairwise inter-population comparisons of allele frequency disclosed a very similar distribution between NTD and M groups (exact test, P=0.92). Among controls, differences between M and individual native groups were NS (0.06
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Trans-ethnic meta-analysis of genome-wide association studies for Hirschsprung disease.
Tang, Clara Sze-Man; Gui, Hongsheng; Kapoor, Ashish; Kim, Jeong-Hyun; Luzón-Toro, Berta; Pelet, Anna; Burzynski, Grzegorz; Lantieri, Francesca; So, Man-Ting; Berrios, Courtney; Shin, Hyoung Doo; Fernández, Raquel M; Le, Thuy-Linh; Verheij, Joke B G M; Matera, Ivana; Cherny, Stacey S; Nandakumar, Priyanka; Cheong, Hyun Sub; Antiñolo, Guillermo; Amiel, Jeanne; Seo, Jeong-Meen; Kim, Dae-Yeon; Oh, Jung-Tak; Lyonnet, Stanislas; Borrego, Salud; Ceccherini, Isabella; Hofstra, Robert M W; Chakravarti, Aravinda; Kim, Hyun-Young; Sham, Pak Chung; Tam, Paul K H; Garcia-Barceló, Maria-Mercè
2016-12-01
Hirschsprung disease (HSCR) is the most common cause of neonatal intestinal obstruction. It is characterized by the absence of ganglia in the nerve plexuses of the lower gastrointestinal tract. So far, three common disease-susceptibility variants at the RET, SEMA3 and NRG1 loci have been detected through genome-wide association studies (GWAS) in Europeans and Asians to understand its genetic etiologies. Here we present a trans-ethnic meta-analysis of 507 HSCR cases and 1191 controls, combining all published GWAS results on HSCR to fine-map these loci and narrow down the putatively causal variants to 99% credible sets. We also demonstrate that the effects of RET and NRG1 are universal across European and Asian ancestries. In contrast, we detected a European-specific association of a low-frequency variant, rs80227144, in SEMA3 [odds ratio (OR) = 5.2, P = 4.7 × 10-10]. Conditional analyses on the lead SNPs revealed a secondary association signal, corresponding to an Asian-specific, low-frequency missense variant encoding RET p.Asp489Asn (rs9282834, conditional OR = 20.3, conditional P = 4.1 × 10-14). When in trans with the RET intron 1 enhancer risk allele, rs9282834 increases the risk of HSCR from 1.1 to 26.7. Overall, our study provides further insights into the genetic architecture of HSCR and has profound implications for future study designs. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Sample size requirements for indirect association studies of gene-environment interactions (G x E).
Hein, Rebecca; Beckmann, Lars; Chang-Claude, Jenny
2008-04-01
Association studies accounting for gene-environment interactions (G x E) may be useful for detecting genetic effects. Although current technology enables very dense marker spacing in genetic association studies, the true disease variants may not be genotyped. Thus, causal genes are searched for by indirect association using genetic markers in linkage disequilibrium (LD) with the true disease variants. Sample sizes needed to detect G x E effects in indirect case-control association studies depend on the true genetic main effects, disease allele frequencies, whether marker and disease allele frequencies match, LD between loci, main effects and prevalence of environmental exposures, and the magnitude of interactions. We explored variables influencing sample sizes needed to detect G x E, compared these sample sizes with those required to detect genetic marginal effects, and provide an algorithm for power and sample size estimations. Required sample sizes may be heavily inflated if LD between marker and disease loci decreases. More than 10,000 case-control pairs may be required to detect G x E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G x E effects may be detected with smaller sample sizes than those needed for the detection of genetic marginal effects. Moreover, in this scenario, rare disease variants may only be detectable when G x E is included in the analyses. Thus, the analysis of G x E appears to be an attractive option for the detection of weak genetic main effects of rare variants that may not be detectable in the analysis of genetic marginal effects only.
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Lin, Yi-Chun; Hsu, Ju-Yu; Shu, Jui-Hsu; Chi, Yi; Chiang, Su-Chi; Lee, Sho Tone
2008-11-01
Genome-wide search for the genes involved in arsenite resistance in two distinct variants A and A' of Leishmania amazonensis revealed that the two variants used two different mechanisms to achieve resistance, even though these two variants were derived from the same clone and selected against arsenite under the same conditions. In variant A, the variant with DNA amplification, the biochemical pathways for detoxification of oxidative stress, the energy generation system to support the biochemical and physiological needs of the variant for DNA and protein synthesis and the arsenite translocating system to dispose arsenite are among the primary biochemical events that are upregulated under the arsenite stress to gain resistance. In variant A', the variant without DNA amplification, the upregulation of aquaglyceroporin (AQP) gene and the high level of resistance to arsenate point to the direction that the resistance gained by the variant is due to arsenate which is probably oxidized from arsenite in the arsenite solution used for selection and the maintenance of the cell culture. As a result of the AQP upregulation for arsenite disposal, a different set of biochemical pathways for detoxification of oxidative stress, energy generation and cellular signaling are upregulated to sustain the growth of the variant to gain resistance to arsenate. From current evidences, reactive oxygen species (ROS) overproduced by the parasite soon after exposure to arsenite appear to play an instrumental role in both variants to initiate the subsequent biochemical events that allow the same clone of L. amazonensis to take two totally different routes to diverge into two different variants.
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Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information
NASA Astrophysics Data System (ADS)
Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David
2018-05-01
The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.