Genetic determinants of leucocyte telomere length in children: a neglected and challenging field.

PubMed

Stathopoulou, Maria G; Petrelis, Alexandros M; Buxton, Jessica L; Froguel, Philippe; Blakemore, Alexandra I F; Visvikis-Siest, Sophie

2015-03-01

Telomere length is associated with a large range of human diseases. Genome-wide association studies (GWAS) have identified genetic variants that are associated with leucocyte telomere length (LTL). However, these studies are limited to adult populations. Nevertheless, childhood is a crucial period for the determination of LTL, and the assessment of age-specific genetic determinants, although neglected, could be of great importance. Our aim was to provide insights and preliminary results on genetic determinants of LTL in children. Healthy children (n = 322, age range = 6.75-17 years) with available GWAS data (Illumina Human CNV370-Duo array) were included. The LTL was measured using multiplex quantitative real-time polymerase chain reaction. Linear regression models adjusted for age, gender, parental age at child's birth, and body mass index were used to test the associations of LTL with polymorphisms identified in adult GWAS and to perform a discovery-only GWAS. The previously GWAS-identified variants in adults were not associated with LTL in our paediatric sample. This lack of association was not due to possible interactions with age or gene × gene interactions. Furthermore, a discovery-only GWAS approach demonstrated six novel variants that reached the level of suggestive association (P ≤ 5 × 10(-5)) and explain a high percentage of children's LTL. The study of genetic determinants of LTL in children may identify novel variants not previously identified in adults. Studies in large-scale children populations are needed for the confirmation of these results, possibly through a childhood consortium that could better handle the methodological challenges of LTL genetic epidemiology field. © 2015 John Wiley & Sons Ltd.

A new GWAS and meta-analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer.

PubMed

Al-Tassan, Nada A; Whiffin, Nicola; Hosking, Fay J; Palles, Claire; Farrington, Susan M; Dobbins, Sara E; Harris, Rebecca; Gorman, Maggie; Tenesa, Albert; Meyer, Brian F; Wakil, Salma M; Kinnersley, Ben; Campbell, Harry; Martin, Lynn; Smith, Christopher G; Idziaszczyk, Shelley; Barclay, Ella; Maughan, Timothy S; Kaplan, Richard; Kerr, Rachel; Kerr, David; Buchanan, Daniel D; Buchannan, Daniel D; Win, Aung Ko; Hopper, John; Jenkins, Mark; Lindor, Noralane M; Newcomb, Polly A; Gallinger, Steve; Conti, David; Schumacher, Fred; Casey, Graham; Dunlop, Malcolm G; Tomlinson, Ian P; Cheadle, Jeremy P; Houlston, Richard S

2015-05-20

Genome-wide association studies (GWAS) of colorectal cancer (CRC) have identified 23 susceptibility loci thus far. Analyses of previously conducted GWAS indicate additional risk loci are yet to be discovered. To identify novel CRC susceptibility loci, we conducted a new GWAS and performed a meta-analysis with five published GWAS (totalling 7,577 cases and 9,979 controls of European ancestry), imputing genotypes utilising the 1000 Genomes Project. The combined analysis identified new, significant associations with CRC at 1p36.2 marked by rs72647484 (minor allele frequency [MAF] = 0.09) near CDC42 and WNT4 (P = 1.21 × 10(-8), odds ratio [OR] = 1.21 ) and at 16q24.1 marked by rs16941835 (MAF = 0.21, P = 5.06 × 10(-8); OR = 1.15) within the long non-coding RNA (lncRNA) RP11-58A18.1 and ~500 kb from the nearest coding gene FOXL1. Additionally we identified a promising association at 10p13 with rs10904849 intronic to CUBN (MAF = 0.32, P = 7.01 × 10(-8); OR = 1.14). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC. Additionally, our analysis further demonstrates that imputation can be used to exploit GWAS data to identify novel disease-causing variants.

Genotype-based gene signature of glioma risk.

PubMed

Huang, Yen-Tsung; Zhang, Yi; Wu, Zhijin; Michaud, Dominique S

2017-07-01

Glioma accounts for 80% of malignant brain tumors, but its etiologic determinants remain elusive. Despite genetic susceptibility loci identified by genome-wide association study (GWAS), the agnostic approach leaves open the possibility that other susceptibility genes remain to be discovered. Here we conduct a gene-centric integrative GWAS (iGWAS) of glioma risk that combines transcriptomics and genetics. We synthesized a brain transcriptomics dataset (n = 354), a GWAS dataset (n = 4203), and an advanced glioma tumor transcriptomic dataset (n = 483) to conduct an iGWAS. Using the expression quantitative trait loci (eQTL) dataset, we built models to predict gene expression for the GWAS data, based on eQTL genotypes. With the predicted gene expression, iGWAS analyses were performed using a novel statistical method. Gene signature risk score was constructed using a penalized logistic regression model. A total of 30527 transcripts were analyzed using the iGWAS approach. Four novel glioma susceptibility genes were identified with internal and external validation, including DRD5 (P = 3.0 × 10-79), WDR1 (P = 8.4 × 10-77), NOMO1 (P = 1.3 × 10-25), and PDXDC1 (P = 8.3 × 10-24). The genotype-predicted transcription pattern between cases and controls is consistent with that between tumor and its matched normal tissue. The genotype-based 4-gene signature improved the classification between glioma cases and controls based on age, gender, and population stratification, with area under the receiver operating characteristic curve increasing from 0.77 to 0.85 (P = 8.1 × 10-23). A new genotype-based gene signature of glioma was identified using a novel iGWAS approach, which integrates multiplatform genomic data as well as different genetic association studies. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Genome-wide association studies and epigenome-wide association studies go together in cancer control

PubMed Central

Verma, Mukesh

2016-01-01

Completion of the human genome a decade ago laid the foundation for: using genetic information in assessing risk to identify individuals and populations that are likely to develop cancer, and designing treatments based on a person's genetic profiling (precision medicine). Genome-wide association studies (GWAS) completed during the past few years have identified risk-associated single nucleotide polymorphisms that can be used as screening tools in epidemiologic studies of a variety of tumor types. This led to the conduct of epigenome-wide association studies (EWAS). This article discusses the current status, challenges and research opportunities in GWAS and EWAS. Information gained from GWAS and EWAS has potential applications in cancer control and treatment. PMID:27079684

Cellular dissection of psoriasis for transcriptome analyses and the post-GWAS era

PubMed Central

2014-01-01

Background Genome-scale studies of psoriasis have been used to identify genes of potential relevance to disease mechanisms. For many identified genes, however, the cell type mediating disease activity is uncertain, which has limited our ability to design gene functional studies based on genomic findings. Methods We identified differentially expressed genes (DEGs) with altered expression in psoriasis lesions (n = 216 patients), as well as candidate genes near susceptibility loci from psoriasis GWAS studies. These gene sets were characterized based upon their expression across 10 cell types present in psoriasis lesions. Susceptibility-associated variation at intergenic (non-coding) loci was evaluated to identify sites of allele-specific transcription factor binding. Results Half of DEGs showed highest expression in skin cells, although the dominant cell type differed between psoriasis-increased DEGs (keratinocytes, 35%) and psoriasis-decreased DEGs (fibroblasts, 33%). In contrast, psoriasis GWAS candidates tended to have highest expression in immune cells (71%), with a significant fraction showing maximal expression in neutrophils (24%, P < 0.001). By identifying candidate cell types for genes near susceptibility loci, we could identify and prioritize SNPs at which susceptibility variants are predicted to influence transcription factor binding. This led to the identification of potentially causal (non-coding) SNPs for which susceptibility variants influence binding of AP-1, NF-κB, IRF1, STAT3 and STAT4. Conclusions These findings underscore the role of innate immunity in psoriasis and highlight neutrophils as a cell type linked with pathogenetic mechanisms. Assignment of candidate cell types to genes emerging from GWAS studies provides a first step towards functional analysis, and we have proposed an approach for generating hypotheses to explain GWAS hits at intergenic loci. PMID:24885462

Epigenetic profiling of growth plate chondrocytes sheds insight into regulatory genetic variation influencing height.

PubMed

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.

Efficiently Identifying Significant Associations in Genome-wide Association Studies

PubMed Central

Eskin, Eleazar

2013-01-01

Abstract Over the past several years, genome-wide association studies (GWAS) have implicated hundreds of genes in common disease. More recently, the GWAS approach has been utilized to identify regions of the genome that harbor variation affecting gene expression or expression quantitative trait loci (eQTLs). Unlike GWAS applied to clinical traits, where only a handful of phenotypes are analyzed per study, in eQTL studies, tens of thousands of gene expression levels are measured, and the GWAS approach is applied to each gene expression level. This leads to computing billions of statistical tests and requires substantial computational resources, particularly when applying novel statistical methods such as mixed models. We introduce a novel two-stage testing procedure that identifies all of the significant associations more efficiently than testing all the single nucleotide polymorphisms (SNPs). In the first stage, a small number of informative SNPs, or proxies, across the genome are tested. Based on their observed associations, our approach locates the regions that may contain significant SNPs and only tests additional SNPs from those regions. We show through simulations and analysis of real GWAS datasets that the proposed two-stage procedure increases the computational speed by a factor of 10. Additionally, efficient implementation of our software increases the computational speed relative to the state-of-the-art testing approaches by a factor of 75. PMID:24033261

Integration of mouse and human genome-wide association data identifies KCNIP4 as an asthma gene.

PubMed

Himes, Blanca E; Sheppard, Keith; Berndt, Annerose; Leme, Adriana S; Myers, Rachel A; Gignoux, Christopher R; Levin, Albert M; Gauderman, W James; Yang, James J; Mathias, Rasika A; Romieu, Isabelle; Torgerson, Dara G; Roth, Lindsey A; Huntsman, Scott; Eng, Celeste; Klanderman, Barbara; Ziniti, John; Senter-Sylvia, Jody; Szefler, Stanley J; Lemanske, Robert F; Zeiger, Robert S; Strunk, Robert C; Martinez, Fernando D; Boushey, Homer; Chinchilli, Vernon M; Israel, Elliot; Mauger, David; Koppelman, Gerard H; Postma, Dirkje S; Nieuwenhuis, Maartje A E; Vonk, Judith M; Lima, John J; Irvin, Charles G; Peters, Stephen P; Kubo, Michiaki; Tamari, Mayumi; Nakamura, Yusuke; Litonjua, Augusto A; Tantisira, Kelan G; Raby, Benjamin A; Bleecker, Eugene R; Meyers, Deborah A; London, Stephanie J; Barnes, Kathleen C; Gilliland, Frank D; Williams, L Keoki; Burchard, Esteban G; Nicolae, Dan L; Ober, Carole; DeMeo, Dawn L; Silverman, Edwin K; Paigen, Beverly; Churchill, Gary; Shapiro, Steve D; Weiss, Scott T

2013-01-01

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG) and two human AHR GWAS (i.e., SHARP, DAG), the Kv channel interacting protein 4 (KCNIP4) gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04), while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04). The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data.

Implications of genome wide association studies for addiction: are our a priori assumptions all wrong?

PubMed

Hall, F Scott; Drgonova, Jana; Jain, Siddharth; Uhl, George R

2013-12-01

Substantial genetic contributions to addiction vulnerability are supported by data from twin studies, linkage studies, candidate gene association studies and, more recently, Genome Wide Association Studies (GWAS). Parallel to this work, animal studies have attempted to identify the genes that may contribute to responses to addictive drugs and addiction liability, initially focusing upon genes for the targets of the major drugs of abuse. These studies identified genes/proteins that affect responses to drugs of abuse; however, this does not necessarily mean that variation in these genes contributes to the genetic component of addiction liability. One of the major problems with initial linkage and candidate gene studies was an a priori focus on the genes thought to be involved in addiction based upon the known contributions of those proteins to drug actions, making the identification of novel genes unlikely. The GWAS approach is systematic and agnostic to such a priori assumptions. From the numerous GWAS now completed several conclusions may be drawn: (1) addiction is highly polygenic; each allelic variant contributing in a small, additive fashion to addiction vulnerability; (2) unexpected, compared to our a priori assumptions, classes of genes are most important in explaining addiction vulnerability; (3) although substantial genetic heterogeneity exists, there is substantial convergence of GWAS signals on particular genes. This review traces the history of this research; from initial transgenic mouse models based upon candidate gene and linkage studies, through the progression of GWAS for addiction and nicotine cessation, to the current human and transgenic mouse studies post-GWAS. © 2013.

Statistical methods to detect novel genetic variants using publicly available GWAS summary data.

PubMed

Guo, Bin; Wu, Baolin

2018-03-01

We propose statistical methods to detect novel genetic variants using only genome-wide association studies (GWAS) summary data without access to raw genotype and phenotype data. With more and more summary data being posted for public access in the post GWAS era, the proposed methods are practically very useful to identify additional interesting genetic variants and shed lights on the underlying disease mechanism. We illustrate the utility of our proposed methods with application to GWAS meta-analysis results of fasting glucose from the international MAGIC consortium. We found several novel genome-wide significant loci that are worth further study. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assocplots: a Python package for static and interactive visualization of multiple-group GWAS results.

PubMed

Khramtsova, Ekaterina A; Stranger, Barbara E

2017-02-01

Over the last decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, requiring development of novel tools for data visualization. Quantile–quantile (QQ) plots and Manhattan plots are classical tools which have been utilized to visually summarize GWAS results and identify genetic variants significantly associated with traits of interest. However, static visualizations are limiting in the information that can be shown. Here, we present Assocplots, a Python package for viewing and exploring GWAS results not only using classic static Manhattan and QQ plots, but also through a dynamic extension which allows to interactively visualize the relationships between GWAS results from multiple cohorts or studies. The Assocplots package is open source and distributed under the MIT license via GitHub (https://github.com/khramts/assocplots) along with examples, documentation and installation instructions. ekhramts@medicine.bsd.uchicago.edu or bstranger@medicine.bsd.uchicago.edu

Genomewide association study of cocaine dependence and related traits: FAM53B identified as a risk gene

PubMed Central

Gelernter, Joel; Sherva, Richard; Koesterer, Ryan; Almasy, Laura; Zhao, Hongyu; Kranzler, Henry R.; Farrer, Lindsay

2013-01-01

We report a GWAS for cocaine dependence (CD) in three sets of African- and European-American subjects (AAs and EAs, respectively), to identify pathways, genes, and alleles important in CD risk. The discovery GWAS dataset (n=5,697 subjects) was genotyped using the Illumina OmniQuad microarray (890,000 analyzed SNPs). Additional genotypes were imputed based on the 1000 Genomes reference panel. Top-ranked findings were evaluated by incorporating information from publicly available GWAS data from 4,063 subjects. Then, the most significant GWAS SNPs were genotyped in 2,549 independent subjects. We observed one genomewide-significant (GWS) result: rs7086629 at the FAM53B (“family with sequence similarity 53, member B”) locus. This was supported in both AAs and EAs; p-value (meta-analysis of all samples) =4.28×10−8. The gene maps to the same chromosomal region as the maximum peak we observed in a previous linkage study. NCOR2 (nuclear receptor corepressor 1) SNP rs150954431 was associated with p=1.19×10−9 in the EA discovery sample. SNP rs2456778, which maps to CDK1 (“cyclin-dependent kinase 1”), was associated with cocaine-induced paranoia in AAs in the discovery sample only (p=4.68×10−8). This is the first study to identify risk variants for CD using GWAS. Our results implicate novel risk loci and provide insights into potential therapeutic and prevention strategies. PMID:23958962

Genome-wide association study of alcohol dependence

PubMed Central

Treutlein, Jens; Cichon, Sven; Ridinger, Monika; Wodarz, Norbert; Soyka, Michael; Zill, Peter; Maier, Wolfgang; Moessner, Rainald; Gaebel, Wolfgang; Dahmen, Norbert; Fehr, Christoph; Scherbaum, Norbert; Steffens, Michael; Ludwig, Kerstin U.; Frank, Josef; Wichmann, H.- Erich; Schreiber, Stefan; Dragano, Nico; Sommer, Wolfgang; Leonardi-Essmann, Fernando; Lourdusamy, Anbarasu; Gebicke-Haerter, Peter; Wienker, Thomas F.; Sullivan, Patrick F.; Nöthen, Markus M.; Kiefer, Falk; Spanagel, Rainer; Mann, Karl; Rietschel, Marcella

2014-01-01

Context Identification of genes contributing to alcohol dependence will improve our understanding of the mechanisms underlying this disorder. Objective To identify susceptibility genes for alcohol dependence through a genome-wide association study (GWAS) and follow-up study in a population of German male inpatients with an early age at onset. Design The GWAS included 487 male inpatients with DSM-IV alcohol dependence with an age at onset below 28 years and 1,358 population based control individuals. The follow-up study included 1,024 male inpatients and 996 age-matched male controls. All subjects were of German descent. The GWAS tested 524,396 single nucleotide polymorphisms (SNPs). All SNPs with p<10-4 were subjected to the follow-up study. In addition, nominally significant SNPs from those genes that had also shown expression changes in rat brains after chronic alcohol consumption were selected for the follow-up step. Results The GWAS produced 121 SNPs with nominal p<10-4. These, together with 19 additional SNPs from homologs of rat genes showing differential expression, were genotyped in the follow-up sample. Fifteen SNPs showed significant association with the same allele as in the GWAS. In the combined analysis, two closely linked intergenic SNPs met genome-wide significance (rs7590720 p=9.72×10-9; rs1344694 p=1.69×10-8). They are located on chromosome 2q35, a region which has been implicated in linkage studies for alcohol phenotypes. Nine SNPs were located in genes, including CDH13 and ADH1C genes which have been reported to be associated with alcohol dependence. Conclusion This is the first GWAS and follow-up study to identify a genome-wide significant association in alcohol dependence. Further independent studies are required to confirm these findings. PMID:19581569

Cross-disease Meta-analysis of Genome-wide Association Studies for Systemic Sclerosis and Rheumatoid Arthritis Reveals IRF4 as a New Common Susceptibility Locus

PubMed Central

López-Isac, Elena; Martín, Jose-Ezequiel; Assassi, Shervin; Simeón, Carmen P; Carreira, Patricia; Ortego-Centeno, Norberto; Freire, Mayka; Beltrán, Emma; Narváez, Javier; Alegre-Sancho, Juan J; Fernández-Gutiérrez, Benjamín; Balsa, Alejandro; Ortiz, Ana M; González-Gay, Miguel A; Beretta, Lorenzo; Santaniello, Alessandro; Bellocchi, Chiara; Lunardi, Claudio; Moroncini, Gianluca; Gabrielli, Armando; Witte, Torsten; Hunzelmann, Nicolas; Distler, Jörg HW; Riekemasten, Gabriella; van der Helm-van Mil, Annete H; de Vries-Bouwstra, Jeska; Magro-Checa, Cesar; Voskuyl, Alexandre E; Vonk, Madelon C; Molberg, Øyvind; Merriman, Tony; Hesselstrand, Roger; Nordin, Annika; Padyukov, Leonid; Herrick, Ariane; Eyre, Steve; Koeleman, Bobby PC; Denton, Christopher P; Fonseca, Carmen; Radstake, Timothy RDJ; Worthington, Jane; Mayes, Maureen D; Martín, Javier

2017-01-01

Objectives Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that share clinical and immunological characteristics. To date, several shared SSc-RA loci have been identified independently. In this study, we aimed to systematically search for new common SSc-RA loci through an inter-disease meta-GWAS strategy. Methods We performed a meta-analysis combining GWAS datasets of SSc and RA using a strategy that allowed identification of loci with both same-direction and opposing-direction allelic effects. The top single-nucleotide polymorphisms (SNPs) were followed-up in independent SSc and RA case-control cohorts. This allowed us to increase the sample size to a total of 8,830 SSc patients, 16,870 RA patients and 43,393 controls. Results The cross-disease meta-analysis of the GWAS datasets identified several loci with nominal association signals (P-value < 5 × 10-6), which also showed evidence of association in the disease-specific GWAS scan. These loci included several genomic regions not previously reported as shared loci, besides risk factors associated with both diseases in previous studies. The follow-up of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these two diseases (Pcombined = 3.29 × 10-12). In addition, the analysis of the biological relevance of the known SSc-RA shared loci pointed to the type I interferon and the interleukin 12 signaling pathways as the main common etiopathogenic factors. Conclusions Our study has identified a novel shared locus, IRF4, for SSc and RA and highlighted the usefulness of cross-disease GWAS meta-analysis in the identification of common risk loci. PMID:27111665

Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers

PubMed Central

Huo, Dezheng

2013-01-01

Numerous single nucleotide polymorphisms (SNPs) associated with breast cancer susceptibility have been identified by genome-wide association studies (GWAS). However, these SNPs were primarily discovered and validated in women of European and Asian ancestry. Because linkage disequilibrium is ancestry-dependent and heterogeneous among racial/ethnic populations, we evaluated common genetic variants at 22 GWAS-identified breast cancer susceptibility loci in a pooled sample of 1502 breast cancer cases and 1378 controls of African ancestry. None of the 22 GWAS index SNPs could be validated, challenging the direct generalizability of breast cancer risk variants identified in Caucasians or Asians to other populations. Novel breast cancer risk variants for women of African ancestry were identified in regions including 5p12 (odds ratio [OR] = 1.40, 95% confidence interval [CI] = 1.11–1.76; P = 0.004), 5q11.2 (OR = 1.22, 95% CI = 1.09–1.36; P = 0.00053) and 10p15.1 (OR = 1.22, 95% CI = 1.08–1.38; P = 0.0015). We also found positive association signals in three regions (6q25.1, 10q26.13 and 16q12.1–q12.2) previously confirmed by fine mapping in women of African ancestry. In addition, polygenic model indicated that eight best markers in this study, compared with 22 GWAS-identified SNPs, could better predict breast cancer risk in women of African ancestry (per-allele OR = 1.21, 95% CI = 1.16–1.27; P = 9.7 × 10–16). Our results demonstrate that fine mapping is a powerful approach to better characterize the breast cancer risk alleles in diverse populations. Future studies and new GWAS in women of African ancestry hold promise to discover additional variants for breast cancer susceptibility with clinical implications throughout the African diaspora. PMID:23475944

graph-GPA: A graphical model for prioritizing GWAS results and investigating pleiotropic architecture.

PubMed

Chung, Dongjun; Kim, Hang J; Zhao, Hongyu

2017-02-01

Genome-wide association studies (GWAS) have identified tens of thousands of genetic variants associated with hundreds of phenotypes and diseases, which have provided clinical and medical benefits to patients with novel biomarkers and therapeutic targets. However, identification of risk variants associated with complex diseases remains challenging as they are often affected by many genetic variants with small or moderate effects. There has been accumulating evidence suggesting that different complex traits share common risk basis, namely pleiotropy. Recently, several statistical methods have been developed to improve statistical power to identify risk variants for complex traits through a joint analysis of multiple GWAS datasets by leveraging pleiotropy. While these methods were shown to improve statistical power for association mapping compared to separate analyses, they are still limited in the number of phenotypes that can be integrated. In order to address this challenge, in this paper, we propose a novel statistical framework, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Markov random field approach. Application of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA improves statistical power to identify risk variants compared to statistical methods based on smaller number of GWAS datasets. In addition, graph-GPA also promotes better understanding of genetic mechanisms shared among phenotypes, which can potentially be useful for the development of improved diagnosis and therapeutics. The R implementation of graph-GPA is currently available at https://dongjunchung.github.io/GGPA/.

[Genome-wide association study for adolescent idiopathic scoliosis].

PubMed

Ogura, Yoji; Kou, Ikuyo; Scoliosis, Japan; Matsumoto, Morio; Watanabe, Kota; Ikegawa, Shiro

2016-04-01

Adolescent idiopathic scoliosis(AIS)is a polygenic disease. Genome-wide association studies(GWASs)have been performed for a lot of polygenic diseases. For AIS, we conducted GWAS and identified the first AIS locus near LBX1. After the discovery, we have extended our study by increasing the numbers of subjects and SNPs. In total, our Japanese GWAS has identified four susceptibility genes. GWASs for AIS have also been performed in the USA and China, which identified one and three susceptibility genes, respectively. Here we review GWASs in Japan and abroad and functional analysis to clarify the pathomechanism of AIS.

Overview of the Genetics of Alcohol Use Disorder

PubMed Central

Tawa, Elisabeth A.; Hall, Samuel D.; Lohoff, Falk W.

2016-01-01

Aims Alcohol Use Disorder (AUD) is a chronic psychiatric illness characterized by harmful drinking patterns leading to negative emotional, physical, and social ramifications. While the underlying pathophysiology of AUD is poorly understood, there is substantial evidence for a genetic component; however, identification of universal genetic risk variants for AUD has been difficult. Recent efforts in the search for AUD susceptibility genes will be reviewed in this article. Methods In this review, we provide an overview of genetic studies on AUD, including twin studies, linkage studies, candidate gene studies, and genome-wide association studies (GWAS). Results Several potential genetic susceptibility factors for AUD have been identified, but the genes of alcohol metabolism, alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), have been found to be protective against the development of AUD. GWAS have also identified a heterogeneous list of SNPs associated with AUD and alcohol-related phenotypes, emphasizing the complexity and heterogeneity of the disorder. In addition, many of these findings have small effect sizes when compared to alcohol metabolism genes, and biological relevance is often unknown. Conclusions Although studies spanning multiple approaches have suggested a genetic basis for AUD, identification of the genetic risk variants has been challenging. Some promising results are emerging from GWAS studies; however, larger sample sizes are needed to improve GWAS results and resolution. As the field of genetics is rapidly developing, whole genome sequencing could soon become the new standard of interrogation of the genes and neurobiological pathways which contribute to the complex phenotype of AUD. Short summary This review examines the genetic underpinnings of Alcohol Use Disorder (AUD), with an emphasis on GWAS approaches for identifying genetic risk variants. The most promising results associated with AUD and alcohol-related phenotypes have included SNPs of the alcohol metabolism genes ADH and ALDH. PMID:27445363

GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer

PubMed Central

Pharoah, Paul D. P.; Tsai, Ya-Yu; Ramus, Susan J.; Phelan, Catherine M.; Goode, Ellen L.; Lawrenson, Kate; Price, Melissa; Fridley, Brooke L.; Tyrer, Jonathan P.; Shen, Howard; Weber, Rachel; Karevan, Rod; Larson, Melissa C.; Song, Honglin; Tessier, Daniel C.; Bacot, François; Vincent, Daniel; Cunningham, Julie M.; Dennis, Joe; Dicks, Ed; Aben, Katja K.; Anton-Culver, Hoda; Antonenkova, Natalia; Armasu, Sebastian M.; Baglietto, Laura; Bandera, Elisa V.; Beckmann, Matthias W.; Birrer, Michael J.; Bloom, Greg; Bogdanova, Natalia; Brenton, James D.; Brinton, Louise A.; Brooks-Wilson, Angela; Brown, Robert; Butzow, Ralf; Campbell, Ian; Carney, Michael E; Carvalho, Renato S.; Chang-Claude, Jenny; Chen, Y. Anne; Chen, Zhihua; Chow, Wong-Ho; Cicek, Mine S.; Coetzee, Gerhard; Cook, Linda S.; Cramer, Daniel W.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Despierre, Evelyn; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Edwards, Robert; Ekici, Arif B.; Fasching, Peter A.; Fenstermacher, David; Flanagan, James; Gao, Yu-Tang; Garcia-Closas, Montserrat; Gentry-Maharaj, Aleksandra; Giles, Graham; Gjyshi, Anxhela; Gore, Martin; Gronwald, Jacek; Guo, Qi; Halle, Mari K; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hillemanns, Peter; Hoatlin, Maureen; Høgdall, Estrid; Høgdall, Claus K.; Hosono, Satoyo; Jakubowska, Anna; Jensen, Allan; Kalli, Kimberly R.; Karlan, Beth Y.; Kelemen, Linda E.; Kiemeney, Lambertus A.; Kjaer, Susanne Krüger; Konecny, Gottfried E.; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Nathan; Lee, Janet; Leminen, Arto; Lim, Boon Kiong; Lissowska, Jolanta; Lubiński, Jan; Lundvall, Lene; Lurie, Galina; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Nakanishi, Toru; Narod, Steven A.; Ness, Roberta B.; Nevanlinna, Heli; Nickels, Stefan; Noushmehr, Houtan; Odunsi, Kunle; Olson, Sara; Orlow, Irene; Paul, James; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jenny; Pike, Malcolm C; Poole, Elizabeth M; Qu, Xiaotao; Risch, Harvey A.; Rodriguez-Rodriguez, Lorna; Rossing, Mary Anne; Rudolph, Anja; Runnebaum, Ingo; Rzepecka, Iwona K; Salvesen, Helga B.; Schwaab, Ira; Severi, Gianluca; Shen, Hui; Shridhar, Vijayalakshmi; Shu, Xiao-Ou; Sieh, Weiva; Southey, Melissa C.; Spellman, Paul; Tajima, Kazuo; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S.; van Altena, Anne M.; Berg, David Van Den; Vergote, Ignace; Vierkant, Robert A.; Vitonis, Allison F.; Wang-Gohrke, Shan; Wentzensen, Nicolas; Whittemore, Alice S.; Wik, Elisabeth; Winterhoff, Boris; Woo, Yin Ling; Wu, Anna H; Yang, Hannah P.; Zheng, Wei; Ziogas, Argyrios; Zulkifli, Famida; Goodman, Marc T.; Hall, Per; Easton, Douglas F; Pearce, Celeste L; Berchuck, Andrew; Chenevix-Trench, Georgia; Iversen, Edwin; Monteiro, Alvaro N.A.; Gayther, Simon A.; Schildkraut, Joellen M.; Sellers, Thomas A.

2013-01-01

Genome wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC) with another two loci being close to genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the United Kingdom. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. Follow-up genotyping was carried out in 18,174 cases and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 previously near genome-wide significance and identified three novel loci associated with risk; two loci associated with all EOC subtypes, at 8q21 (rs11782652, P=5.5×10-9) and 10p12 (rs1243180; P=1.8×10-8), and another locus specific to the serous subtype at 17q12 (rs757210; P=8.1×10-10). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility that implicates CHMP4C in the pathogenesis of ovarian cancer. PMID:23535730

GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer.

PubMed

Pharoah, Paul D P; Tsai, Ya-Yu; Ramus, Susan J; Phelan, Catherine M; Goode, Ellen L; Lawrenson, Kate; Buckley, Melissa; Fridley, Brooke L; Tyrer, Jonathan P; Shen, Howard; Weber, Rachel; Karevan, Rod; Larson, Melissa C; Song, Honglin; Tessier, Daniel C; Bacot, François; Vincent, Daniel; Cunningham, Julie M; Dennis, Joe; Dicks, Ed; Aben, Katja K; Anton-Culver, Hoda; Antonenkova, Natalia; Armasu, Sebastian M; Baglietto, Laura; Bandera, Elisa V; Beckmann, Matthias W; Birrer, Michael J; Bloom, Greg; Bogdanova, Natalia; Brenton, James D; Brinton, Louise A; Brooks-Wilson, Angela; Brown, Robert; Butzow, Ralf; Campbell, Ian; Carney, Michael E; Carvalho, Renato S; Chang-Claude, Jenny; Chen, Y Anne; Chen, Zhihua; Chow, Wong-Ho; Cicek, Mine S; Coetzee, Gerhard; Cook, Linda S; Cramer, Daniel W; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Despierre, Evelyn; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Edwards, Robert; Ekici, Arif B; Fasching, Peter A; Fenstermacher, David; Flanagan, James; Gao, Yu-Tang; Garcia-Closas, Montserrat; Gentry-Maharaj, Aleksandra; Giles, Graham; Gjyshi, Anxhela; Gore, Martin; Gronwald, Jacek; Guo, Qi; Halle, Mari K; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hillemanns, Peter; Hoatlin, Maureen; Høgdall, Estrid; Høgdall, Claus K; Hosono, Satoyo; Jakubowska, Anna; Jensen, Allan; Kalli, Kimberly R; Karlan, Beth Y; Kelemen, Linda E; Kiemeney, Lambertus A; Kjaer, Susanne Krüger; Konecny, Gottfried E; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Nathan; Lee, Janet; Leminen, Arto; Lim, Boon Kiong; Lissowska, Jolanta; Lubiński, Jan; Lundvall, Lene; Lurie, Galina; Massuger, Leon F A G; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Nakanishi, Toru; Narod, Steven A; Ness, Roberta B; Nevanlinna, Heli; Nickels, Stefan; Noushmehr, Houtan; Odunsi, Kunle; Olson, Sara; Orlow, Irene; Paul, James; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jenny; Pike, Malcolm C; Poole, Elizabeth M; Qu, Xiaotao; Risch, Harvey A; Rodriguez-Rodriguez, Lorna; Rossing, Mary Anne; Rudolph, Anja; Runnebaum, Ingo; Rzepecka, Iwona K; Salvesen, Helga B; Schwaab, Ira; Severi, Gianluca; Shen, Hui; Shridhar, Vijayalakshmi; Shu, Xiao-Ou; Sieh, Weiva; Southey, Melissa C; Spellman, Paul; Tajima, Kazuo; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tworoger, Shelley S; van Altena, Anne M; van den Berg, David; Vergote, Ignace; Vierkant, Robert A; Vitonis, Allison F; Wang-Gohrke, Shan; Wentzensen, Nicolas; Whittemore, Alice S; Wik, Elisabeth; Winterhoff, Boris; Woo, Yin Ling; Wu, Anna H; Yang, Hannah P; Zheng, Wei; Ziogas, Argyrios; Zulkifli, Famida; Goodman, Marc T; Hall, Per; Easton, Douglas F; Pearce, Celeste L; Berchuck, Andrew; Chenevix-Trench, Georgia; Iversen, Edwin; Monteiro, Alvaro N A; Gayther, Simon A; Schildkraut, Joellen M; Sellers, Thomas A

2013-04-01

Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10(-9)) and 10p12 (rs1243180, P = 1.8 × 10(-8)) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10(-10)). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility and implicated CHMP4C in the pathogenesis of ovarian cancer.

Pooled Genome-Wide Analysis to Identify Novel Risk Loci for Pediatric Allergic Asthma

PubMed Central

Ricci, Giampaolo; Astolfi, Annalisa; Remondini, Daniel; Cipriani, Francesca; Formica, Serena; Dondi, Arianna; Pession, Andrea

2011-01-01

Background Genome-wide association studies of pooled DNA samples were shown to be a valuable tool to identify candidate SNPs associated to a phenotype. No such study was up to now applied to childhood allergic asthma, even if the very high complexity of asthma genetics is an appropriate field to explore the potential of pooled GWAS approach. Methodology/Principal Findings We performed a pooled GWAS and individual genotyping in 269 children with allergic respiratory diseases comparing allergic children with and without asthma. We used a modular approach to identify the most significant loci associated with asthma by combining silhouette statistics and physical distance method with cluster-adapted thresholding. We found 97% concordance between pooled GWAS and individual genotyping, with 36 out of 37 top-scoring SNPs significant at individual genotyping level. The most significant SNP is located inside the coding sequence of C5, an already identified asthma susceptibility gene, while the other loci regulate functions that are relevant to bronchial physiopathology, as immune- or inflammation-mediated mechanisms and airway smooth muscle contraction. Integration with gene expression data showed that almost half of the putative susceptibility genes are differentially expressed in experimental asthma mouse models. Conclusion/Significance Combined silhouette statistics and cluster-adapted physical distance threshold analysis of pooled GWAS data is an efficient method to identify candidate SNP associated to asthma development in an allergic pediatric population. PMID:21359210

Nonsyndromic cleft palate: An association study at GWAS candidate loci in a multiethnic sample.

PubMed

Ishorst, Nina; Francheschelli, Paola; Böhmer, Anne C; Khan, Mohammad Faisal J; Heilmann-Heimbach, Stefanie; Fricker, Nadine; Little, Julian; Steegers-Theunissen, Regine P M; Peterlin, Borut; Nowak, Stefanie; Martini, Markus; Kruse, Teresa; Dunsche, Anton; Kreusch, Thomas; Gölz, Lina; Aldhorae, Khalid; Halboub, Esam; Reutter, Heiko; Mossey, Peter; Nöthen, Markus M; Rubini, Michele; Ludwig, Kerstin U; Knapp, Michael; Mangold, Elisabeth

2018-06-01

Nonsyndromic cleft palate only (nsCPO) is a common and multifactorial form of orofacial clefting. In contrast to successes achieved for the other common form of orofacial clefting, that is, nonsyndromic cleft lip with/without cleft palate (nsCL/P), genome wide association studies (GWAS) of nsCPO have identified only one genome wide significant locus. Aim of the present study was to investigate whether common variants contribute to nsCPO and, if so, to identify novel risk loci. We genotyped 33 SNPs at 27 candidate loci from 2 previously published nsCPO GWAS in an independent multiethnic sample. It included: (i) a family-based sample of European ancestry (n = 212); and (ii) two case/control samples of Central European (n = 94/339) and Arabian ancestry (n = 38/231), respectively. A separate association analysis was performed for each genotyped dataset, and meta-analyses were performed. After association analysis and meta-analyses, none of the 33 SNPs showed genome-wide significance. Two variants showed nominally significant association in the imputed GWAS dataset and exhibited a further decrease in p-value in a European and an overall meta-analysis including imputed GWAS data, respectively (rs395572: P MetaEU  = 3.16 × 10 -4 ; rs6809420: P MetaAll  = 2.80 × 10 -4 ). Our findings suggest that there is a limited contribution of common variants to nsCPO. However, the individual effect sizes might be too small for detection of further associations in the present sample sizes. Rare variants may play a more substantial role in nsCPO than in nsCL/P, for which GWAS of smaller sample sizes have identified genome-wide significant loci. Whole-exome/genome sequencing studies of nsCPO are now warranted. © 2018 Wiley Periodicals, Inc.

Applications and Limitations of Mouse Models for Understanding Human Atherosclerosis

PubMed Central

von Scheidt, Moritz; Zhao, Yuqi; Kurt, Zeyneb; Pan, Calvin; Zeng, Lingyao; Yang, Xia; Schunkert, Heribert; Lusis, Aldons J.

2017-01-01

Most of the biological understanding of mechanisms underlying coronary artery disease (CAD) derives from studies of mouse models. The identification of multiple CAD loci and strong candidate genes in large human genome-wide association studies (GWAS) presented an opportunity to examine the relevance of mouse models for the human disease. We comprehensively reviewed the mouse literature, including 827 literature-derived genes, and compared it to human data. First, we observed striking concordance of risk factors for atherosclerosis in mice and humans. Second, there was highly significant overlap of mouse genes with human genes identified by GWAS. In particular, of the 46 genes with strong association signals in CAD-GWAS that were studied in mouse models all but one exhibited consistent effects on atherosclerosis-related phenotypes. Third, we compared 178 CAD-associated pathways derived from human GWAS with 263 from mouse studies and observed that over 50% were consistent between both species. PMID:27916529

Progress of genome wide association study in domestic animals

PubMed Central

2012-01-01

Domestic animals are invaluable resources for study of the molecular architecture of complex traits. Although the mapping of quantitative trait loci (QTL) responsible for economically important traits in domestic animals has achieved remarkable results in recent decades, not all of the genetic variation in the complex traits has been captured because of the low density of markers used in QTL mapping studies. The genome wide association study (GWAS), which utilizes high-density single-nucleotide polymorphism (SNP), provides a new way to tackle this issue. Encouraging achievements in dissection of the genetic mechanisms of complex diseases in humans have resulted from the use of GWAS. At present, GWAS has been applied to the field of domestic animal breeding and genetics, and some advances have been made. Many genes or markers that affect economic traits of interest in domestic animals have been identified. In this review, advances in the use of GWAS in domestic animals are described. PMID:22958308

The more from East-Asian, the better: risk prediction of colorectal cancer risk by GWAS-identified SNPs among Japanese.

PubMed

Abe, Makiko; Ito, Hidemi; Oze, Isao; Nomura, Masatoshi; Ogawa, Yoshihiro; Matsuo, Keitaro

2017-12-01

Little is known about the difference of genetic predisposition for CRC between ethnicities; however, many genetic traits common to colorectal cancer have been identified. This study investigated whether more SNPs identified in GWAS in East Asian population could improve the risk prediction of Japanese and explored possible application of genetic risk groups as an instrument of the risk communication. 558 Patients histologically verified colorectal cancer and 1116 first-visit outpatients were included for derivation study, and 547 cases and 547 controls were for replication study. Among each population, we evaluated prediction models for the risk of CRC that combined the genetic risk group based on SNPs from GWASs in European-population and a similarly developed model adding SNPs from GWASs in East Asian-population. We examined whether adding East Asian-specific SNPs would improve the discrimination. Six SNPs (rs6983267, rs4779584, rs4444235, rs9929218, rs10936599, rs16969681) from 23 SNPs by European-based GWAS and five SNPs (rs704017, rs11196172, rs10774214, rs647161, rs2423279) among ten SNPs by Asian-based GWAS were selected in CRC risk prediction model. Compared with a 6-SNP-based model, an 11-SNP model including Asian GWAS-SNPs showed improved discrimination capacity in Receiver operator characteristic analysis. A model with 11 SNPs resulted in statistically significant improvement in both derivation (P = 0.0039) and replication studies (P = 0.0018) compared with six SNP model. We estimated cumulative risk of CRC by using genetic risk group based on 11 SNPs and found that the cumulative risk at age 80 is approximately 13% in the high-risk group while 6% in the low-risk group. We constructed a more efficient CRC risk prediction model with 11 SNPs including newly identified East Asian-based GWAS SNPs (rs704017, rs11196172, rs10774214, rs647161, rs2423279). Risk grouping based on 11 SNPs depicted lifetime difference of CRC risk. This might be useful for effective individualized prevention for East Asian.

Family-Based Genome-Wide Association Scan of Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Mick, Eric; Todorov, Alexandre; Smalley, Susan; Hu, Xiaolan; Loo, Sandra; Todd, Richard D.; Biederman, Joseph; Byrne, Deirdre; Dechairo, Bryan; Guiney, Allan; McCracken, James; McGough, James; Nelson, Stanley F.; Reiersen, Angela M.; Wilens, Timothy E.; Wozniak, Janet; Neale, Benjamin M.; Faraone, Stephen V.

2010-01-01

Objective: Genes likely play a substantial role in the etiology of attention-deficit/hyperactivity disorder (ADHD). However, the genetic architecture of the disorder is unknown, and prior genome-wide association studies (GWAS) have not identified a genome-wide significant association. We have conducted a third, independent, multisite GWAS of…

Transcriptional risk scores link GWAS to eQTLs and predict complications in Crohn's disease.

PubMed

Marigorta, Urko M; Denson, Lee A; Hyams, Jeffrey S; Mondal, Kajari; Prince, Jarod; Walters, Thomas D; Griffiths, Anne; Noe, Joshua D; Crandall, Wallace V; Rosh, Joel R; Mack, David R; Kellermayer, Richard; Heyman, Melvin B; Baker, Susan S; Stephens, Michael C; Baldassano, Robert N; Markowitz, James F; Kim, Mi-Ok; Dubinsky, Marla C; Cho, Judy; Aronow, Bruce J; Kugathasan, Subra; Gibson, Greg

2017-10-01

Gene expression profiling can be used to uncover the mechanisms by which loci identified through genome-wide association studies (GWAS) contribute to pathology. Given that most GWAS hits are in putative regulatory regions and transcript abundance is physiologically closer to the phenotype of interest, we hypothesized that summation of risk-allele-associated gene expression, namely a transcriptional risk score (TRS), should provide accurate estimates of disease risk. We integrate summary-level GWAS and expression quantitative trait locus (eQTL) data with RNA-seq data from the RISK study, an inception cohort of pediatric Crohn's disease. We show that TRSs based on genes regulated by variants linked to inflammatory bowel disease (IBD) not only outperform genetic risk scores (GRSs) in distinguishing Crohn's disease from healthy samples, but also serve to identify patients who in time will progress to complicated disease. Our dissection of eQTL effects may be used to distinguish genes whose association with disease is through promotion versus protection, thereby linking statistical association to biological mechanism. The TRS approach constitutes a potential strategy for personalized medicine that enhances inference from static genotypic risk assessment.

Landscape of Conditional eQTL in Dorsolateral Prefrontal Cortex and Co-localization with Schizophrenia GWAS.

PubMed

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.

Genome-Wide Association Study of Bone Mineral Density in Premenopausal European-American Women and Replication in African-American Women

PubMed Central

Koller, Daniel L.; Ichikawa, Shoji; Lai, Dongbing; Padgett, Leah R.; Doheny, Kimberly F.; Pugh, Elizabeth; Paschall, Justin; Hui, Siu L.; Edenberg, Howard J.; Xuei, Xiaoling; Peacock, Munro; Econs, Michael J.; Foroud, Tatiana

2010-01-01

Context: Several genome-wide association studies (GWAS) have been performed to identify genes contributing to bone mineral density (BMD), typically in samples of elderly women and men. Objective: The objective of the study was to identify genes contributing to BMD in premenopausal women. Design: GWAS using the Illumina 610Quad array in premenopausal European-American (EA) women and replication of the top 50 single-nucleotide polymorphisms (SNPs) for two BMD measures in African-American (AA) women. Subjects: Subjects included 1524 premenopausal EA women aged 20–45 yr from 762 sibships and 669 AA premenopausal women aged 20–44 yr from 383 sibships. Interventions: There were no interventions. Main Outcome Measures: BMD was measured at the lumbar spine and femoral neck by dual-energy x-ray absorptiometry. Age- and weight-adjusted BMD values were tested for association with each SNP, with P values determined by permutation. Results: SNPs in CATSPERB on chromosome 14 provided evidence of association with femoral neck BMD (rs1298989, P = 2.7 × 10−5; rs1285635, P = 3.0 × 10−5) in the EA women, and some supporting evidence was also observed with these SNPs in the AA women (rs1285635, P = 0.003). Genes identified in other BMD GWAS studies, including IBSP and ADAMTS18, were also among the most significant findings in our GWAS. Conclusions: Evidence of association to several novel loci was detected in a GWAS of premenopausal EA women, and SNPs in one of these loci also provided supporting evidence in a sample of AA women. PMID:20164292

Age at menarche and age at natural menopause in East Asian women: a genome-wide association study.

PubMed

Shi, Jiajun; Zhang, Ben; Choi, Ji-Yeob; Gao, Yu-Tang; Li, Huaixing; Lu, Wei; Long, Jirong; Kang, Daehee; Xiang, Yong-Bing; Wen, Wanqing; Park, Sue K; Ye, Xingwang; Noh, Dong-Young; Zheng, Ying; Wang, Yiqin; Chung, Seokang; Lin, Xu; Cai, Qiuyin; Shu, Xiao-Ou

2016-12-01

Age at menarche (AM) and age at natural menopause (ANM) are complex traits with a high heritability. Abnormal timing of menarche or menopause is associated with a reduced span of fertility and risk for several age-related diseases including breast, endometrial and ovarian cancer, cardiovascular disease, and osteoporosis. To identify novel genetic loci for AM or ANM in East Asian women and to replicate previously identified loci primarily in women of European ancestry by genome-wide association studies (GWASs), we conducted a two-stage GWAS. Stage I aimed to discover promising novel AM and ANM loci using GWAS data of 8073 women from Shanghai, China. The Stage II replication study used the data from another Chinese GWAS (n = 1230 for AM and n = 1458 for ANM), a Korean GWAS (n = 4215 for AM and n = 1739 for ANM), and de novo genotyping of 2877 additional Chinese women. Previous GWAS-identified loci for AM and ANM were also evaluated. We identified two suggestive menarcheal age loci tagged by rs79195475 at 10q21.3 (beta = -0.118 years, P = 3.4 × 10 -6 ) and rs1023935 at 4p15.1 (beta = -0.145 years, P = 4.9 × 10 -6 ) and one menopausal age locus tagged by rs3818134 at 22q12.2 (beta = -0.276 years, P = 8.8 × 10 -6 ). These suggestive loci warrant a further validation in independent populations. Although limited by low statistical power, we replicated 19 of the 98 menarche loci and 5 of the 20 menopause loci previously identified in women of European ancestry in East Asian women, suggesting a shared genetic architecture for these two traits across populations.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans.

PubMed

Amin Al Olama, Ali; Dadaev, Tokhir; Hazelett, Dennis J; Li, Qiuyan; Leongamornlert, Daniel; Saunders, Edward J; Stephens, Sarah; Cieza-Borrella, Clara; Whitmore, Ian; Benlloch Garcia, Sara; Giles, Graham G; Southey, Melissa C; Fitzgerald, Liesel; Gronberg, Henrik; Wiklund, Fredrik; Aly, Markus; Henderson, Brian E; Schumacher, Fredrick; Haiman, Christopher A; Schleutker, Johanna; Wahlfors, Tiina; Tammela, Teuvo L; Nordestgaard, Børge G; Key, Tim J; Travis, Ruth C; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Pharoah, Paul; Pashayan, Nora; Khaw, Kay-Tee; Stanford, Janet L; Thibodeau, Stephen N; Mcdonnell, Shannon K; Schaid, Daniel J; Maier, Christiane; Vogel, Walther; Luedeke, Manuel; Herkommer, Kathleen; Kibel, Adam S; Cybulski, Cezary; Wokołorczyk, Dominika; Kluzniak, Wojciech; Cannon-Albright, Lisa; Brenner, Hermann; Butterbach, Katja; Arndt, Volker; Park, Jong Y; Sellers, Thomas; Lin, Hui-Yi; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Batra, Jyotsna; Clements, Judith A; Spurdle, Amanda; Teixeira, Manuel R; Paulo, Paula; Maia, Sofia; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Govindasami, Koveela; Guy, Michelle; Lophatonanon, Artitaya; Muir, Kenneth; Viñuela, Ana; Brown, Andrew A; Freedman, Mathew; Conti, David V; Easton, Douglas; Coetzee, Gerhard A; Eeles, Rosalind A; Kote-Jarai, Zsofia

2015-10-01

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region. © The Author 2015. Published by Oxford University Press.

Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine.

PubMed

Kim, Jihye; Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kang, Jaewoo; Tan, Aik Choon

2018-01-01

Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis.

Systems Pharmacology-Based Approach of Connecting Disease Genes in Genome-Wide Association Studies with Traditional Chinese Medicine

PubMed Central

Kim, Jihye; Yoo, Minjae; Shin, Jimin; Kim, Hyunmin; Kang, Jaewoo

2018-01-01

Traditional Chinese medicine (TCM) originated in ancient China has been practiced over thousands of years for treating various symptoms and diseases. However, the molecular mechanisms of TCM in treating these diseases remain unknown. In this study, we employ a systems pharmacology-based approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. We studied 102 TCM components and their target genes by analyzing microarray gene expression experiments. We constructed disease-gene networks from 2558 GWAS studies. We applied a systems pharmacology approach to prioritize disease-target genes. Using this bioinformatics approach, we analyzed 14,713 GWAS disease-TCM-target gene pairs and identified 115 disease-gene pairs with q value < 0.2. We validated several of these GWAS disease-TCM-target gene pairs with literature evidence, demonstrating that this computational approach could reveal novel indications for TCM. We also develop TCM-Disease web application to facilitate the traditional Chinese medicine drug repurposing efforts. Systems pharmacology is a promising approach for connecting GWAS diseases with TCM for potential drug repurposing and repositioning. The computational approaches described in this study could be easily expandable to other disease-gene network analysis. PMID:29765977

e-GRASP: an integrated evolutionary and GRASP resource for exploring disease associations.

PubMed

Karim, Sajjad; NourEldin, Hend Fakhri; Abusamra, Heba; Salem, Nada; Alhathli, Elham; Dudley, Joel; Sanderford, Max; Scheinfeldt, Laura B; Chaudhary, Adeel G; Al-Qahtani, Mohammed H; Kumar, Sudhir

2016-10-17

Genome-wide association studies (GWAS) have become a mainstay of biological research concerned with discovering genetic variation linked to phenotypic traits and diseases. Both discrete and continuous traits can be analyzed in GWAS to discover associations between single nucleotide polymorphisms (SNPs) and traits of interest. Associations are typically determined by estimating the significance of the statistical relationship between genetic loci and the given trait. However, the prioritization of bona fide, reproducible genetic associations from GWAS results remains a central challenge in identifying genomic loci underlying common complex diseases. Evolutionary-aware meta-analysis of the growing GWAS literature is one way to address this challenge and to advance from association to causation in the discovery of genotype-phenotype relationships. We have created an evolutionary GWAS resource to enable in-depth query and exploration of published GWAS results. This resource uses the publically available GWAS results annotated in the GRASP2 database. The GRASP2 database includes results from 2082 studies, 177 broad phenotype categories, and ~8.87 million SNP-phenotype associations. For each SNP in e-GRASP, we present information from the GRASP2 database for convenience as well as evolutionary information (e.g., rate and timespan). Users can, therefore, identify not only SNPs with highly significant phenotype-association P-values, but also SNPs that are highly replicated and/or occur at evolutionarily conserved sites that are likely to be functionally important. Additionally, we provide an evolutionary-adjusted SNP association ranking (E-rank) that uses cross-species evolutionary conservation scores and population allele frequencies to transform P-values in an effort to enhance the discovery of SNPs with a greater probability of biologically meaningful disease associations. By adding an evolutionary dimension to the GWAS results available in the GRASP2 database, our e-GRASP resource will enable a more effective exploration of SNPs not only by the statistical significance of trait associations, but also by the number of studies in which associations have been replicated, and the evolutionary context of the associated mutations. Therefore, e-GRASP will be a valuable resource for aiding researchers in the identification of bona fide, reproducible genetic associations from GWAS results. This resource is freely available at http://www.mypeg.info/egrasp .

HiView: an integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants.

PubMed

Xu, Zheng; Zhang, Guosheng; Duan, Qing; Chai, Shengjie; Zhang, Baqun; Wu, Cong; Jin, Fulai; Yue, Feng; Li, Yun; Hu, Ming

2016-03-11

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits and diseases. However, most of them are located in the non-protein coding regions, and therefore it is challenging to hypothesize the functions of these non-coding GWAS variants. Recent large efforts such as the ENCODE and Roadmap Epigenomics projects have predicted a large number of regulatory elements. However, the target genes of these regulatory elements remain largely unknown. Chromatin conformation capture based technologies such as Hi-C can directly measure the chromatin interactions and have generated an increasingly comprehensive catalog of the interactome between the distal regulatory elements and their potential target genes. Leveraging such information revealed by Hi-C holds the promise of elucidating the functions of genetic variants in human diseases. In this work, we present HiView, the first integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants. HiView is able to display Hi-C data and statistical evidence for chromatin interactions in genomic regions surrounding any given GWAS variant, enabling straightforward visualization and interpretation. We believe that as the first GWAS variants-centered Hi-C genome browser, HiView is a useful tool guiding post-GWAS functional genomics studies. HiView is freely accessible at: http://www.unc.edu/~yunmli/HiView .

Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density.

PubMed

Wang, W; Huang, S; Hou, W; Liu, Y; Fan, Q; He, A; Wen, Y; Hao, J; Guo, X; Zhang, F

2017-10-01

Several genome-wide association studies (GWAS) of bone mineral density (BMD) have successfully identified multiple susceptibility genes, yet isolated susceptibility genes are often difficult to interpret biologically. The aim of this study was to unravel the genetic background of BMD at pathway level, by integrating BMD GWAS data with genome-wide expression quantitative trait loci (eQTLs) and methylation quantitative trait loci (meQTLs) data METHOD: We employed the GWAS datasets of BMD from the Genetic Factors for Osteoporosis Consortium (GEFOS), analysing patients' BMD. The areas studied included 32 735 femoral necks, 28 498 lumbar spines, and 8143 forearms. Genome-wide eQTLs (containing 923 021 eQTLs) and meQTLs (containing 683 152 unique methylation sites with local meQTLs) data sets were collected from recently published studies. Gene scores were first calculated by summary data-based Mendelian randomisation (SMR) software and meQTL-aligned GWAS results. Gene set enrichment analysis (GSEA) was then applied to identify BMD-associated gene sets with a predefined significance level of 0.05. We identified multiple gene sets associated with BMD in one or more regions, including relevant known biological gene sets such as the Reactome Circadian Clock (GSEA p-value = 1.0 × 10 -4 for LS and 2.7 × 10 -2 for femoral necks BMD in eQTLs-based GSEA) and insulin-like growth factor receptor binding (GSEA p-value = 5.0 × 10 -4 for femoral necks and 2.6 × 10 -2 for lumbar spines BMD in meQTLs-based GSEA). Our results provided novel clues for subsequent functional analysis of bone metabolism, and illustrated the benefit of integrating eQTLs and meQTLs data into pathway association analysis for genetic studies of complex human diseases. Cite this article : W. Wang, S. Huang, W. Hou, Y. Liu, Q. Fan, A. He, Y. Wen, J. Hao, X. Guo, F. Zhang. Integrative analysis of GWAS, eQTLs and meQTLs data suggests that multiple gene sets are associated with bone mineral density. Bone Joint Res 2017;6:572-576. © 2017 Wang et al.

Bioinformatics challenges for genome-wide association studies.

PubMed

Moore, Jason H; Asselbergs, Folkert W; Williams, Scott M

2010-02-15

The sequencing of the human genome has made it possible to identify an informative set of >1 million single nucleotide polymorphisms (SNPs) across the genome that can be used to carry out genome-wide association studies (GWASs). The availability of massive amounts of GWAS data has necessitated the development of new biostatistical methods for quality control, imputation and analysis issues including multiple testing. This work has been successful and has enabled the discovery of new associations that have been replicated in multiple studies. However, it is now recognized that most SNPs discovered via GWAS have small effects on disease susceptibility and thus may not be suitable for improving health care through genetic testing. One likely explanation for the mixed results of GWAS is that the current biostatistical analysis paradigm is by design agnostic or unbiased in that it ignores all prior knowledge about disease pathobiology. Further, the linear modeling framework that is employed in GWAS often considers only one SNP at a time thus ignoring their genomic and environmental context. There is now a shift away from the biostatistical approach toward a more holistic approach that recognizes the complexity of the genotype-phenotype relationship that is characterized by significant heterogeneity and gene-gene and gene-environment interaction. We argue here that bioinformatics has an important role to play in addressing the complexity of the underlying genetic basis of common human diseases. The goal of this review is to identify and discuss those GWAS challenges that will require computational methods.

Integrated Post-GWAS Analysis Sheds New Light on the Disease Mechanisms of Schizophrenia

PubMed Central

Lin, Jhih-Rong; Cai, Ying; Zhang, Quanwei; Zhang, Wen; Nogales-Cadenas, Rubén; Zhang, Zhengdong D.

2016-01-01

Schizophrenia is a severe mental disorder with a large genetic component. Recent genome-wide association studies (GWAS) have identified many schizophrenia-associated common variants. For most of the reported associations, however, the underlying biological mechanisms are not clear. The critical first step for their elucidation is to identify the most likely disease genes as the source of the association signals. Here, we describe a general computational framework of post-GWAS analysis for complex disease gene prioritization. We identify 132 putative schizophrenia risk genes in 76 risk regions spanning 120 schizophrenia-associated common variants, 78 of which have not been recognized as schizophrenia disease genes by previous GWAS. Even more significantly, 29 of them are outside the risk regions, likely under regulation of transcriptional regulatory elements contained therein. These putative schizophrenia risk genes are transcriptionally active in both brain and the immune system, and highly enriched among cellular pathways, consistent with leading pathophysiological hypotheses about the pathogenesis of schizophrenia. With their involvement in distinct biological processes, these putative schizophrenia risk genes, with different association strengths, show distinctive temporal expression patterns, and play specific biological roles during brain development. PMID:27754856

Fast and accurate genotype imputation in genome-wide association studies through pre-phasing

PubMed Central

Howie, Bryan; Fuchsberger, Christian; Stephens, Matthew; Marchini, Jonathan; Abecasis, Gonçalo R.

2013-01-01

Sequencing efforts, including the 1000 Genomes Project and disease-specific efforts, are producing large collections of haplotypes that can be used for genotype imputation in genome-wide association studies (GWAS). Imputing from these reference panels can help identify new risk alleles, but the use of large panels with existing methods imposes a high computational burden. To keep imputation broadly accessible, we introduce a strategy called “pre-phasing” that maintains the accuracy of leading methods while cutting computational costs by orders of magnitude. In brief, we first statistically estimate the haplotypes for each GWAS individual (“pre-phasing”) and then impute missing genotypes into these estimated haplotypes. This reduces the computational cost because: (i) the GWAS samples must be phased only once, whereas standard methods would implicitly re-phase with each reference panel update; (ii) it is much faster to match a phased GWAS haplotype to one reference haplotype than to match unphased GWAS genotypes to a pair of reference haplotypes. This strategy will be particularly valuable for repeated imputation as reference panels evolve. PMID:22820512

Comment on 'Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets' by Lam et al.

PubMed

Hill, W David

2018-04-01

Intelligence and educational attainment are strongly genetically correlated. This relationship can be exploited by Multi-Trait Analysis of GWAS (MTAG) to add power to Genome-wide Association Studies (GWAS) of intelligence. MTAG allows the user to meta-analyze GWASs of different phenotypes, based on their genetic correlations, to identify association's specific to the trait of choice. An MTAG analysis using GWAS data sets on intelligence and education was conducted by Lam et al. (2017). Lam et al. (2017) reported 70 loci that they described as 'trait specific' to intelligence. This article examines whether the analysis conducted by Lam et al. (2017) has resulted in genetic information about a phenotype that is more similar to education than intelligence.

Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants

PubMed Central

Gala, Manish; Abecasis, Goncalo; Bezieau, Stephane; Brenner, Hermann; Butterbach, Katja; Caan, Bette J.; Carlson, Christopher S.; Casey, Graham; Chang-Claude, Jenny; Conti, David V.; Curtis, Keith R.; Duggan, David; Gallinger, Steven; Haile, Robert W.; Harrison, Tabitha A.; Hayes, Richard B.; Hoffmeister, Michael; Hopper, John L.; Hudson, Thomas J.; Jenkins, Mark A.; Küry, Sébastien; Le Marchand, Loic; Leal, Suzanne M.; Newcomb, Polly A.; Nickerson, Deborah A.; Potter, John D.; Schoen, Robert E.; Schumacher, Fredrick R.; Seminara, Daniela; Slattery, Martha L.; Hsu, Li; Chan, Andrew T.; White, Emily; Berndt, Sonja I.; Peters, Ulrike

2016-01-01

Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs). We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33). We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s). PMID:27379672

Pathway-driven gene stability selection of two rheumatoid arthritis GWAS identifies and validates new susceptibility genes in receptor mediated signalling pathways.

PubMed

Eleftherohorinou, Hariklia; Hoggart, Clive J; Wright, Victoria J; Levin, Michael; Coin, Lachlan J M

2011-09-01

Rheumatoid arthritis (RA) is the commonest chronic, systemic, inflammatory disorder affecting ∼1% of the world population. It has a strong genetic component and a growing number of associated genes have been discovered in genome-wide association studies (GWAS), which nevertheless only account for 23% of the total genetic risk. We aimed to identify additional susceptibility loci through the analysis of GWAS in the context of biological function. We bridge the gap between pathway and gene-oriented analyses of GWAS, by introducing a pathway-driven gene stability-selection methodology that identifies potential causal genes in the top-associated disease pathways that may be driving the pathway association signals. We analysed the WTCCC and the NARAC studies of ∼5000 and ∼2000 subjects, respectively. We examined 700 pathways comprising ∼8000 genes. Ranking pathways by significance revealed that the NARAC top-ranked ∼6% laid within the top 10% of WTCCC. Gene selection on those pathways identified 58 genes in WTCCC and 61 in NARAC; 21 of those were common (P(overlap)< 10(-21)), of which 16 were novel discoveries. Among the identified genes, we validated 10 known RA associations in WTCCC and 13 in NARAC, not discovered using single-SNP approaches on the same data. Gene ontology functional enrichment analysis on the identified genes showed significant over-representation of signalling activity (P< 10(-29)) in both studies. Our findings suggest a novel model of RA genetic predisposition, which involves cell-membrane receptors and genes in second messenger signalling systems, in addition to genes that regulate immune responses, which have been the focus of interest previously.

Integrative Analysis of Response to Tamoxifen Treatment in ER-Positive Breast Cancer Using GWAS Information and Transcription Profiling.

PubMed

Hicks, Chindo; Kumar, Ranjit; Pannuti, Antonio; Miele, Lucio

2012-01-01

Variable response and resistance to tamoxifen treatment in breast cancer patients remains a major clinical problem. To determine whether genes and biological pathways containing SNPs associated with risk for breast cancer are dysregulated in response to tamoxifen treatment, we performed analysis combining information from 43 genome-wide association studies with gene expression data from 298 ER(+) breast cancer patients treated with tamoxifen and 125 ER(+) controls. We identified 95 genes which distinguished tamoxifen treated patients from controls. Additionally, we identified 54 genes which stratified tamoxifen treated patients into two distinct groups. We identified biological pathways containing SNPs associated with risk for breast cancer, which were dysregulated in response to tamoxifen treatment. Key pathways identified included the apoptosis, P53, NFkB, DNA repair and cell cycle pathways. Combining GWAS with transcription profiling provides a unified approach for associating GWAS findings with response to drug treatment and identification of potential drug targets.

1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function

PubMed Central

Gorski, Mathias; van der Most, Peter J.; Teumer, Alexander; Chu, Audrey Y.; Li, Man; Mijatovic, Vladan; Nolte, Ilja M.; Cocca, Massimiliano; Taliun, Daniel; Gomez, Felicia; Li, Yong; Tayo, Bamidele; Tin, Adrienne; Feitosa, Mary F.; Aspelund, Thor; Attia, John; Biffar, Reiner; Bochud, Murielle; Boerwinkle, Eric; Borecki, Ingrid; Bottinger, Erwin P.; Chen, Ming-Huei; Chouraki, Vincent; Ciullo, Marina; Coresh, Josef; Cornelis, Marilyn C.; Curhan, Gary C.; d’Adamo, Adamo Pio; Dehghan, Abbas; Dengler, Laura; Ding, Jingzhong; Eiriksdottir, Gudny; Endlich, Karlhans; Enroth, Stefan; Esko, Tõnu; Franco, Oscar H.; Gasparini, Paolo; Gieger, Christian; Girotto, Giorgia; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Hancock, Stephen J.; Harris, Tamara B.; Helmer, Catherine; Höllerer, Simon; Hofer, Edith; Hofman, Albert; Holliday, Elizabeth G.; Homuth, Georg; Hu, Frank B.; Huth, Cornelia; Hutri-Kähönen, Nina; Hwang, Shih-Jen; Imboden, Medea; Johansson, Åsa; Kähönen, Mika; König, Wolfgang; Kramer, Holly; Krämer, Bernhard K.; Kumar, Ashish; Kutalik, Zoltan; Lambert, Jean-Charles; Launer, Lenore J.; Lehtimäki, Terho; de Borst, Martin; Navis, Gerjan; Swertz, Morris; Liu, Yongmei; Lohman, Kurt; Loos, Ruth J. F.; Lu, Yingchang; Lyytikäinen, Leo-Pekka; McEvoy, Mark A.; Meisinger, Christa; Meitinger, Thomas; Metspalu, Andres; Metzger, Marie; Mihailov, Evelin; Mitchell, Paul; Nauck, Matthias; Oldehinkel, Albertine J.; Olden, Matthias; WJH Penninx, Brenda; Pistis, Giorgio; Pramstaller, Peter P.; Probst-Hensch, Nicole; Raitakari, Olli T.; Rettig, Rainer; Ridker, Paul M.; Rivadeneira, Fernando; Robino, Antonietta; Rosas, Sylvia E.; Ruderfer, Douglas; Ruggiero, Daniela; Saba, Yasaman; Sala, Cinzia; Schmidt, Helena; Schmidt, Reinhold; Scott, Rodney J.; Sedaghat, Sanaz; Smith, Albert V.; Sorice, Rossella; Stengel, Benedicte; Stracke, Sylvia; Strauch, Konstantin; Toniolo, Daniela; Uitterlinden, Andre G.; Ulivi, Sheila; Viikari, Jorma S.; Völker, Uwe; Vollenweider, Peter; Völzke, Henry; Vuckovic, Dragana; Waldenberger, Melanie; Jin Wang, Jie; Yang, Qiong; Chasman, Daniel I.; Tromp, Gerard; Snieder, Harold; Heid, Iris M.; Fox, Caroline S.; Köttgen, Anna; Pattaro, Cristian; Böger, Carsten A.; Fuchsberger, Christian

2017-01-01

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10−8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples. PMID:28452372

1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.

PubMed

Gorski, Mathias; van der Most, Peter J; Teumer, Alexander; Chu, Audrey Y; Li, Man; Mijatovic, Vladan; Nolte, Ilja M; Cocca, Massimiliano; Taliun, Daniel; Gomez, Felicia; Li, Yong; Tayo, Bamidele; Tin, Adrienne; Feitosa, Mary F; Aspelund, Thor; Attia, John; Biffar, Reiner; Bochud, Murielle; Boerwinkle, Eric; Borecki, Ingrid; Bottinger, Erwin P; Chen, Ming-Huei; Chouraki, Vincent; Ciullo, Marina; Coresh, Josef; Cornelis, Marilyn C; Curhan, Gary C; d'Adamo, Adamo Pio; Dehghan, Abbas; Dengler, Laura; Ding, Jingzhong; Eiriksdottir, Gudny; Endlich, Karlhans; Enroth, Stefan; Esko, Tõnu; Franco, Oscar H; Gasparini, Paolo; Gieger, Christian; Girotto, Giorgia; Gottesman, Omri; Gudnason, Vilmundur; Gyllensten, Ulf; Hancock, Stephen J; Harris, Tamara B; Helmer, Catherine; Höllerer, Simon; Hofer, Edith; Hofman, Albert; Holliday, Elizabeth G; Homuth, Georg; Hu, Frank B; Huth, Cornelia; Hutri-Kähönen, Nina; Hwang, Shih-Jen; Imboden, Medea; Johansson, Åsa; Kähönen, Mika; König, Wolfgang; Kramer, Holly; Krämer, Bernhard K; Kumar, Ashish; Kutalik, Zoltan; Lambert, Jean-Charles; Launer, Lenore J; Lehtimäki, Terho; de Borst, Martin; Navis, Gerjan; Swertz, Morris; Liu, Yongmei; Lohman, Kurt; Loos, Ruth J F; Lu, Yingchang; Lyytikäinen, Leo-Pekka; McEvoy, Mark A; Meisinger, Christa; Meitinger, Thomas; Metspalu, Andres; Metzger, Marie; Mihailov, Evelin; Mitchell, Paul; Nauck, Matthias; Oldehinkel, Albertine J; Olden, Matthias; Wjh Penninx, Brenda; Pistis, Giorgio; Pramstaller, Peter P; Probst-Hensch, Nicole; Raitakari, Olli T; Rettig, Rainer; Ridker, Paul M; Rivadeneira, Fernando; Robino, Antonietta; Rosas, Sylvia E; Ruderfer, Douglas; Ruggiero, Daniela; Saba, Yasaman; Sala, Cinzia; Schmidt, Helena; Schmidt, Reinhold; Scott, Rodney J; Sedaghat, Sanaz; Smith, Albert V; Sorice, Rossella; Stengel, Benedicte; Stracke, Sylvia; Strauch, Konstantin; Toniolo, Daniela; Uitterlinden, Andre G; Ulivi, Sheila; Viikari, Jorma S; Völker, Uwe; Vollenweider, Peter; Völzke, Henry; Vuckovic, Dragana; Waldenberger, Melanie; Jin Wang, Jie; Yang, Qiong; Chasman, Daniel I; Tromp, Gerard; Snieder, Harold; Heid, Iris M; Fox, Caroline S; Köttgen, Anna; Pattaro, Cristian; Böger, Carsten A; Fuchsberger, Christian

2017-04-28

HapMap imputed genome-wide association studies (GWAS) have revealed >50 loci at which common variants with minor allele frequency >5% are associated with kidney function. GWAS using more complete reference sets for imputation, such as those from The 1000 Genomes project, promise to identify novel loci that have been missed by previous efforts. To investigate the value of such a more complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estimated glomerular filtration rate (eGFR) in 110,517 European ancestry participants using 1000 Genomes imputed data. We identified 10 novel loci with p-value < 5 × 10 -8 previously missed by HapMap-based GWAS. Six of these loci (HOXD8, ARL15, PIK3R1, EYA4, ASTN2, and EPB41L3) are tagged by common SNPs unique to the 1000 Genomes reference panel. Using pathway analysis, we identified 39 significant (FDR < 0.05) genes and 127 significantly (FDR < 0.05) enriched gene sets, which were missed by our previous analyses. Among those, the 10 identified novel genes are part of pathways of kidney development, carbohydrate metabolism, cardiac septum development and glucose metabolism. These results highlight the utility of re-imputing from denser reference panels, until whole-genome sequencing becomes feasible in large samples.

Genome-Wide Association of the Laboratory-Based Nicotine Metabolite Ratio in Three Ancestries.

PubMed

Baurley, James W; Edlund, Christopher K; Pardamean, Carissa I; Conti, David V; Krasnow, Ruth; Javitz, Harold S; Hops, Hyman; Swan, Gary E; Benowitz, Neal L; Bergen, Andrew W

2016-09-01

Metabolic enzyme variation and other patient and environmental characteristics influence smoking behaviors, treatment success, and risk of related disease. Population-specific variation in metabolic genes contributes to challenges in developing and optimizing pharmacogenetic interventions. We applied a custom genome-wide genotyping array for addiction research (Smokescreen), to three laboratory-based studies of nicotine metabolism with oral or venous administration of labeled nicotine and cotinine, to model nicotine metabolism in multiple populations. The trans-3'-hydroxycotinine/cotinine ratio, the nicotine metabolite ratio (NMR), was the nicotine metabolism measure analyzed. Three hundred twelve individuals of self-identified European, African, and Asian American ancestry were genotyped and included in ancestry-specific genome-wide association scans (GWAS) and a meta-GWAS analysis of the NMR. We modeled natural-log transformed NMR with covariates: principal components of genetic ancestry, age, sex, body mass index, and smoking status. African and Asian American NMRs were statistically significantly (P values ≤ 5E-5) lower than European American NMRs. Meta-GWAS analysis identified 36 genome-wide significant variants over a 43 kilobase pair region at CYP2A6 with minimum P = 2.46E-18 at rs12459249, proximal to CYP2A6. Additional minima were located in intron 4 (rs56113850, P = 6.61E-18) and in the CYP2A6-CYP2A7 intergenic region (rs34226463, P = 1.45E-12). Most (34/36) genome-wide significant variants suggested reduced CYP2A6 activity; functional mechanisms were identified and tested in knowledge-bases. Conditional analysis resulted in intergenic variants of possible interest (P values < 5E-5). This meta-GWAS of the NMR identifies CYP2A6 variants, replicates the top-ranked single nucleotide polymorphism from a recent Finnish meta-GWAS of the NMR, identifies functional mechanisms, and provides pan-continental population biomarkers for nicotine metabolism. This multiple ancestry meta-GWAS of the laboratory study-based NMR provides novel evidence and replication for genome-wide association of CYP2A6 single nucleotide and insertion-deletion polymorphisms. We identify three regions of genome-wide significance: proximal, intronic, and distal to CYP2A6. We replicate the top-ranking single nucleotide polymorphism from a recent GWAS of the NMR in Finnish smokers, identify a functional mechanism for this intronic variant from in silico analyses of RNA-seq data that is consistent with CYP2A6 expression measured in postmortem lung and liver, and provide additional support for the intergenic region between CYP2A6 and CYP2A7. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.

Genome-Wide Association of the Laboratory-Based Nicotine Metabolite Ratio in Three Ancestries

PubMed Central

Baurley, James W.; Edlund, Christopher K.; Pardamean, Carissa I.; Conti, David V.; Krasnow, Ruth; Javitz, Harold S.; Hops, Hyman; Swan, Gary E.; Benowitz, Neal L.

2016-01-01

Introduction: Metabolic enzyme variation and other patient and environmental characteristics influence smoking behaviors, treatment success, and risk of related disease. Population-specific variation in metabolic genes contributes to challenges in developing and optimizing pharmacogenetic interventions. We applied a custom genome-wide genotyping array for addiction research (Smokescreen), to three laboratory-based studies of nicotine metabolism with oral or venous administration of labeled nicotine and cotinine, to model nicotine metabolism in multiple populations. The trans-3′-hydroxycotinine/cotinine ratio, the nicotine metabolite ratio (NMR), was the nicotine metabolism measure analyzed. Methods: Three hundred twelve individuals of self-identified European, African, and Asian American ancestry were genotyped and included in ancestry-specific genome-wide association scans (GWAS) and a meta-GWAS analysis of the NMR. We modeled natural-log transformed NMR with covariates: principal components of genetic ancestry, age, sex, body mass index, and smoking status. Results: African and Asian American NMRs were statistically significantly (P values ≤ 5E-5) lower than European American NMRs. Meta-GWAS analysis identified 36 genome-wide significant variants over a 43 kilobase pair region at CYP2A6 with minimum P = 2.46E-18 at rs12459249, proximal to CYP2A6. Additional minima were located in intron 4 (rs56113850, P = 6.61E-18) and in the CYP2A6-CYP2A7 intergenic region (rs34226463, P = 1.45E-12). Most (34/36) genome-wide significant variants suggested reduced CYP2A6 activity; functional mechanisms were identified and tested in knowledge-bases. Conditional analysis resulted in intergenic variants of possible interest (P values < 5E-5). Conclusions: This meta-GWAS of the NMR identifies CYP2A6 variants, replicates the top-ranked single nucleotide polymorphism from a recent Finnish meta-GWAS of the NMR, identifies functional mechanisms, and provides pan-continental population biomarkers for nicotine metabolism. Implications: This multiple ancestry meta-GWAS of the laboratory study-based NMR provides novel evidence and replication for genome-wide association of CYP2A6 single nucleotide and insertion–deletion polymorphisms. We identify three regions of genome-wide significance: proximal, intronic, and distal to CYP2A6. We replicate the top-ranking single nucleotide polymorphism from a recent GWAS of the NMR in Finnish smokers, identify a functional mechanism for this intronic variant from in silico analyses of RNA-seq data that is consistent with CYP2A6 expression measured in postmortem lung and liver, and provide additional support for the intergenic region between CYP2A6 and CYP2A7. PMID:27113016

Genome-Wide Association Study of Multiple Sclerosis Confirms a Novel Locus at 5p13.1

PubMed Central

Sanna, Serena; Gayán, Javier; Urcelay, Elena; Zara, Ilenia; Pitzalis, Maristella; Cavanillas, María L.; Arroyo, Rafael; Zoledziewska, Magdalena; Marrosu, Marisa; Fernández, Oscar; Leyva, Laura; Alcina, Antonio; Fedetz, Maria; Moreno-Rey, Concha; Velasco, Juan; Real, Luis M.; Ruiz-Peña, Juan Luis; Cucca, Francesco

2012-01-01

Multiple Sclerosis (MS) is the most common progressive and disabling neurological condition affecting young adults in the world today. From a genetic point of view, MS is a complex disorder resulting from the combination of genetic and non-genetic factors. We aimed to identify previously unidentified loci conducting a new GWAS of Multiple Sclerosis (MS) in a sample of 296 MS cases and 801 controls from the Spanish population. Meta-analysis of our data in combination with previous GWAS was done. A total of 17 GWAS-significant SNPs, corresponding to three different loci were identified:HLA, IL2RA, and 5p13.1. All three have been previously reported as GWAS-significant. We confirmed our observation in 5p13.1 for rs9292777 using two additional independent Spanish samples to make a total of 4912 MS cases and 7498 controls (ORpooled = 0.84; 95%CI: 0.80–0.89; p = 1.36×10-9). This SNP differs from the one reported within this locus in a recent GWAS. Although it is unclear whether both signals are tapping the same genetic association, it seems clear that this locus plays an important role in the pathogenesis of MS. PMID:22570697

GWAS4D: multidimensional analysis of context-specific regulatory variant for human complex diseases and traits.

PubMed

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.

SUSCEPTIBILITY LOCI FOR UMBILICAL HERNIA IN SWINE DETECTED BY GENOME-WIDE ASSOCIATION.

PubMed

Liao, X J; Lia, L; Zhang, Z Y; Long, Y; Yang, B; Ruan, G R; Su, Y; Ai, H S; Zhang, W C; Deng, W Y; Xiao, S J; Ren, J; Ding, N S; Huang, L S

2015-10-01

Umbilical hernia (UH) is a complex disorder caused by both genetic and environmental factors. UH brings animal welfare problems and severe economic loss to the pig industry. Until now, the genetic basis of UH is poorly understood. The high-density 60K porcine SNP array enables the rapid application of genome-wide association study (GWAS) to identify genetic loci for phenotypic traits at genome wide scale in pigs. The objective of this research was to identify susceptibility loci for swine umbilical hernia using the GWAS approach. We genotyped 478 piglets from 142 families representing three Western commercial breeds with the Illumina PorcineSNP60 BeadChip. Then significant SNPs were detected by GWAS using ROADTRIPS (Robust Association-Detection Test for Related Individuals with Population Substructure) software base on a Bonferroni corrected threshold (P = 1.67E-06) or suggestive threshold (P = 3.34E-05) and false discovery rate (FDR = 0.05). After quality control, 29,924 qualified SNPs and 472 piglets were used for GWAS. Two suggestive loci predisposing to pig UH were identified at 44.25MB on SSC2 (rs81358018, P = 3.34E-06, FDR = 0.049933) and at 45.90MB on SSC17 (rs81479278, P = 3.30E-06, FDR = 0.049933) in Duroc population, respectively. And no SNP was detected to be associated with pig UH at significant level in neither Landrace nor Large White population. Furthermore, we carried out a meta-analysis in the combined pure-breed population containing all the 472 piglets. rs81479278 (P = 1.16E-06, FDR = 0.022475) was identified to associate with pig UH at genome-wide significant level. SRC was characterized as plausible candidate gene for susceptibility to pig UH according to its genomic position and biological functions. To our knowledge, this study gives the first description of GWAS identifying susceptibility loci for umbilical hernia in pigs. Our findings provide deeper insights to the genetic architecture of umbilical hernia in pigs.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

Unsupervised text mining for assessing and augmenting GWAS results.

PubMed

Ailem, Melissa; Role, François; Nadif, Mohamed; Demenais, Florence

2016-04-01

Text mining can assist in the analysis and interpretation of large-scale biomedical data, helping biologists to quickly and cheaply gain confirmation of hypothesized relationships between biological entities. We set this question in the context of genome-wide association studies (GWAS), an actively emerging field that contributed to identify many genes associated with multifactorial diseases. These studies allow to identify groups of genes associated with the same phenotype, but provide no information about the relationships between these genes. Therefore, our objective is to leverage unsupervised text mining techniques using text-based cosine similarity comparisons and clustering applied to candidate and random gene vectors, in order to augment the GWAS results. We propose a generic framework which we used to characterize the relationships between 10 genes reported associated with asthma by a previous GWAS. The results of this experiment showed that the similarities between these 10 genes were significantly stronger than would be expected by chance (one-sided p-value<0.01). The clustering of observed and randomly selected gene also allowed to generate hypotheses about potential functional relationships between these genes and thus contributed to the discovery of new candidate genes for asthma. Copyright © 2016 Elsevier Inc. All rights reserved.

Transethnic differences in GWAS signals: A simulation study.

PubMed

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.

Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes

PubMed Central

Imamura, Minako; Takahashi, Atsushi; Yamauchi, Toshimasa; Hara, Kazuo; Yasuda, Kazuki; Grarup, Niels; Zhao, Wei; Wang, Xu; Huerta-Chagoya, Alicia; Hu, Cheng; Moon, Sanghoon; Long, Jirong; Kwak, Soo Heon; Rasheed, Asif; Saxena, Richa; Ma, Ronald C. W.; Okada, Yukinori; Iwata, Minoru; Hosoe, Jun; Shojima, Nobuhiro; Iwasaki, Minaka; Fujita, Hayato; Suzuki, Ken; Danesh, John; Jørgensen, Torben; Jørgensen, Marit E.; Witte, Daniel R.; Brandslund, Ivan; Christensen, Cramer; Hansen, Torben; Mercader, Josep M.; Flannick, Jason; Moreno-Macías, Hortensia; Burtt, Noël P.; Zhang, Rong; Kim, Young Jin; Zheng, Wei; Singh, Jai Rup; Tam, Claudia H. T.; Hirose, Hiroshi; Maegawa, Hiroshi; Ito, Chikako; Kaku, Kohei; Watada, Hirotaka; Tanaka, Yasushi; Tobe, Kazuyuki; Kawamori, Ryuzo; Kubo, Michiaki; Cho, Yoon Shin; Chan, Juliana C. N.; Sanghera, Dharambir; Frossard, Philippe; Park, Kyong Soo; Shu, Xiao-Ou; Kim, Bong-Jo; Florez, Jose C.; Tusié-Luna, Teresa; Jia, Weiping; Tai, E Shyong; Pedersen, Oluf; Saleheen, Danish; Maeda, Shiro; Kadowaki, Takashi

2016-01-01

Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P<5 × 10−8), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P<0.007). These results indicate that expansion of single ethnic GWAS is still useful to identify novel susceptibility loci to complex traits not only for ethnicity-specific loci but also for common loci across different ethnicities. PMID:26818947

Combining Genome Wide Association Study and lung eQTL analysis provides evidence for novel genes associated with asthma

PubMed Central

Nieuwenhuis, Maartje A.; Siedlinski, Matteusz; van den Berge, Maarten; Granell, Raquel; Li, Xingnan; Niens, Marijke; van der Vlies, Pieter; Altmüller, Janine; Nürnberg, Peter; Kerkhof, Marjan; van Schayck, Onno C.; Riemersma, Ronald A.; van der Molen, Thys; de Monchy, Jan G.; Bossé, Yohan; Sandford, Andrew; Bruijnzeel-Koomen, Carla A.; van Wijk, Roy G.; ten Hacken, Nick H.; Timens, Wim; Boezen, H. Marike; Henderson, John; Kabesch, Michael; Vonk, Judith M.; Postma, Dirkje S.; Koppelman, Gerard H.

2016-01-01

Background Genome wide association studies (GWAS) of asthma have identified single nucleotide polymorphisms (SNPs) that modestly increase the risk for asthma. This could be due to phenotypic heterogeneity of asthma. Bronchial hyperresponsiveness (BHR) is a phenotypic hallmark of asthma. We aim to identify susceptibility genes for asthma combined with BHR and analyse the presence of cis-eQTLs among replicated SNPs. Secondly, we compare the genetic association of SNPs previously associated with (doctor diagnosed) asthma to our GWAS of asthma with BHR. Methods A GWAS was performed in 920 asthmatics with BHR and 980 controls. Top SNPs of our GWAS were analysed in four replication cohorts and lung cis-eQTL analysis was performed on replicated SNPs. We investigated association of SNPs previously associated with asthma in our data. Results 368 SNPs were followed up for replication. Six SNPs in genes encoding ABI3BP, NAF1, MICA and the 17q21 locus replicated in one or more cohorts, with one locus (17q21) achieving genome wide significance after meta-analysis. Five out of 6 replicated SNPs regulated 35 gene transcripts in whole lung. Eight of 20 asthma associated SNPs from previous GWAS were significantly associated with asthma and BHR. Three SNPs, in IL-33 and GSDMB, showed larger effect sizes in our data compared to published literature. Conclusions Combining GWAS with subsequent lung eQTL analysis revealed disease associated SNPs regulating lung mRNA expression levels of potential new asthma genes. Adding BHR to the asthma definition does not lead to an overall larger genetic effect size than analysing (doctor’s diagnosed) asthma. PMID:27439200

A Conceptual Framework for Pharmacodynamic Genome-wide Association Studies in Pharmacogenomics

PubMed Central

Wu, Rongling; Tong, Chunfa; Wang, Zhong; Mauger, David; Tantisira, Kelan; Szefler, Stanley J.; Chinchilli, Vernon M.; Israel, Elliot

2013-01-01

Summary Genome-wide association studies (GWAS) have emerged as a powerful tool to identify loci that affect drug response or susceptibility to adverse drug reactions. However, current GWAS based on a simple analysis of associations between genotype and phenotype ignores the biochemical reactions of drug response, thus limiting the scope of inference about its genetic architecture. To facilitate the inference of GWAS in pharmacogenomics, we sought to undertake the mathematical integration of the pharmacodynamic process of drug reactions through computational models. By estimating and testing the genetic control of pharmacodynamic and pharmacokinetic parameters, this mechanistic approach does not only enhance the biological and clinical relevance of significant genetic associations, but also improve the statistical power and robustness of gene detection. This report discusses the general principle and development of pharmacodynamics-based GWAS, highlights the practical use of this approach in addressing various pharmacogenomic problems, and suggests that this approach will be an important method to study the genetic architecture of drug responses or reactions. PMID:21920452

Effects of GWAS-Associated Genetic Variants on lncRNAs within IBD and T1D Candidate Loci

PubMed Central

Brorsson, Caroline A.; Pociot, Flemming

2014-01-01

Long non-coding RNAs are a new class of non-coding RNAs that are at the crosshairs in many human diseases such as cancers, cardiovascular disorders, inflammatory and autoimmune disease like Inflammatory Bowel Disease (IBD) and Type 1 Diabetes (T1D). Nearly 90% of the phenotype-associated single-nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) lie outside of the protein coding regions, and map to the non-coding intervals. However, the relationship between phenotype-associated loci and the non-coding regions including the long non-coding RNAs (lncRNAs) is poorly understood. Here, we systemically identified all annotated IBD and T1D loci-associated lncRNAs, and mapped nominally significant GWAS/ImmunoChip SNPs for IBD and T1D within these lncRNAs. Additionally, we identified tissue-specific cis-eQTLs, and strong linkage disequilibrium (LD) signals associated with these SNPs. We explored sequence and structure based attributes of these lncRNAs, and also predicted the structural effects of mapped SNPs within them. We also identified lncRNAs in IBD and T1D that are under recent positive selection. Our analysis identified putative lncRNA secondary structure-disruptive SNPs within and in close proximity (+/−5 kb flanking regions) of IBD and T1D loci-associated candidate genes, suggesting that these RNA conformation-altering polymorphisms might be associated with diseased-phenotype. Disruption of lncRNA secondary structure due to presence of GWAS SNPs provides valuable information that could be potentially useful for future structure-function studies on lncRNAs. PMID:25144376

Meta-genome-wide association studies identify a locus on chromosome 1 and multiple variants in the MHC region for serum C-peptide in type 1 diabetes.

PubMed

Roshandel, Delnaz; Gubitosi-Klug, Rose; Bull, Shelley B; Canty, Angelo J; Pezzolesi, Marcus G; King, George L; Keenan, Hillary A; Snell-Bergeon, Janet K; Maahs, David M; Klein, Ronald; Klein, Barbara E K; Orchard, Trevor J; Costacou, Tina; Weedon, Michael N; Oram, Richard A; Paterson, Andrew D

2018-05-01

The aim of this study was to identify genetic variants associated with beta cell function in type 1 diabetes, as measured by serum C-peptide levels, through meta-genome-wide association studies (meta-GWAS). We performed a meta-GWAS to combine the results from five studies in type 1 diabetes with cross-sectionally measured stimulated, fasting or random C-peptide levels, including 3479 European participants. The p values across studies were combined, taking into account sample size and direction of effect. We also performed separate meta-GWAS for stimulated (n = 1303), fasting (n = 2019) and random (n = 1497) C-peptide levels. In the meta-GWAS for stimulated/fasting/random C-peptide levels, a SNP on chromosome 1, rs559047 (Chr1:238753916, T>A, minor allele frequency [MAF] 0.24-0.26), was associated with C-peptide (p = 4.13 × 10 -8 ), meeting the genome-wide significance threshold (p < 5 × 10 -8 ). In the same meta-GWAS, a locus in the MHC region (rs9260151) was close to the genome-wide significance threshold (Chr6:29911030, C>T, MAF 0.07-0.10, p = 8.43 × 10 -8 ). In the stimulated C-peptide meta-GWAS, rs61211515 (Chr6:30100975, T/-, MAF 0.17-0.19) in the MHC region was associated with stimulated C-peptide (β [SE] = - 0.39 [0.07], p = 9.72 × 10 -8 ). rs61211515 was also associated with the rate of stimulated C-peptide decline over time in a subset of individuals (n = 258) with annual repeated measures for up to 6 years (p = 0.02). In the meta-GWAS of random C-peptide, another MHC region, SNP rs3135002 (Chr6:32668439, C>A, MAF 0.02-0.06), was associated with C-peptide (p = 3.49 × 10 -8 ). Conditional analyses suggested that the three identified variants in the MHC region were independent of each other. rs9260151 and rs3135002 have been associated with type 1 diabetes, whereas rs559047 and rs61211515 have not been associated with a risk of developing type 1 diabetes. We identified a locus on chromosome 1 and multiple variants in the MHC region, at least some of which were distinct from type 1 diabetes risk loci, that were associated with C-peptide, suggesting partly non-overlapping mechanisms for the development and progression of type 1 diabetes. These associations need to be validated in independent populations. Further investigations could provide insights into mechanisms of beta cell loss and opportunities to preserve beta cell function.

A conserved BDNF, glutamate- and GABA-enriched gene module related to human depression identified by coexpression meta-analysis and DNA variant genome-wide association studies.

PubMed

Chang, Lun-Ching; Jamain, Stephane; Lin, Chien-Wei; Rujescu, Dan; Tseng, George C; Sibille, Etienne

2014-01-01

Large scale gene expression (transcriptome) analysis and genome-wide association studies (GWAS) for single nucleotide polymorphisms have generated a considerable amount of gene- and disease-related information, but heterogeneity and various sources of noise have limited the discovery of disease mechanisms. As systematic dataset integration is becoming essential, we developed methods and performed meta-clustering of gene coexpression links in 11 transcriptome studies from postmortem brains of human subjects with major depressive disorder (MDD) and non-psychiatric control subjects. We next sought enrichment in the top 50 meta-analyzed coexpression modules for genes otherwise identified by GWAS for various sets of disorders. One coexpression module of 88 genes was consistently and significantly associated with GWAS for MDD, other neuropsychiatric disorders and brain functions, and for medical illnesses with elevated clinical risk of depression, but not for other diseases. In support of the superior discriminative power of this novel approach, we observed no significant enrichment for GWAS-related genes in coexpression modules extracted from single studies or in meta-modules using gene expression data from non-psychiatric control subjects. Genes in the identified module encode proteins implicated in neuronal signaling and structure, including glutamate metabotropic receptors (GRM1, GRM7), GABA receptors (GABRA2, GABRA4), and neurotrophic and development-related proteins [BDNF, reelin (RELN), Ephrin receptors (EPHA3, EPHA5)]. These results are consistent with the current understanding of molecular mechanisms of MDD and provide a set of putative interacting molecular partners, potentially reflecting components of a functional module across cells and biological pathways that are synchronously recruited in MDD, other brain disorders and MDD-related illnesses. Collectively, this study demonstrates the importance of integrating transcriptome data, gene coexpression modules and GWAS results for providing novel and complementary approaches to investigate the molecular pathology of MDD and other complex brain disorders.

Novel genome-wide association study-based candidate loci for differentiated thyroid cancer risk.

PubMed

Figlioli, Gisella; Köhler, Aleksandra; Chen, Bowang; Elisei, Rossella; Romei, Cristina; Cipollini, Monica; Cristaudo, Alfonso; Bambi, Franco; Paolicchi, Elisa; Hoffmann, Per; Herms, Stefan; Kalemba, Michał; Kula, Dorota; Pastor, Susana; Marcos, Ricard; Velázquez, Antonia; Jarząb, Barbara; Landi, Stefano; Hemminki, Kari; Försti, Asta; Gemignani, Federica

2014-10-01

Genome-wide association studies (GWASs) on differentiated thyroid cancer (DTC) have identified robust associations with single nucleotide polymorphisms (SNPs) at 9q22.33 (FOXE1), 14q13.3 (NKX2-1), and 2q35 (DIRC3). Our recently published GWAS suggested additional susceptibility loci specific for the high-incidence Italian population. The purpose of this study was to identify novel Italian-specific DTC risk variants based on our GWAS and to test them further in low-incidence populations. We investigated 45 SNPs selected from our GWAS first in an Italian population. SNPs that showed suggestive evidence of association were investigated in the Polish and Spanish cohorts. The combined analysis of the GWAS and the Italian replication study (2260 case patients and 2218 control subjects) provided strong evidence of association with rs10136427 near BATF (odds ratio [OR] =1.40, P = 4.35 × 10(-7)) and rs7267944 near DHX35 (OR = 1.39, P = 2.13 × 10(-8)). A possible role in DTC susceptibility in the Italian populations was also found for rs13184587 (ARSB) (P = 8.54 × 10(-6)) and rs1220597 (SPATA13) (P = 3.25 × 10(-6)). Only the associations between rs10136427 and rs7267944 and DTC risk were replicated in the Polish and the Spanish populations with little evidence of population heterogeneity (GWAS and all replications combined, OR = 1.30, P = 9.30 × 10(-7) and OR = 1.32, P = 1.34 × 10(-8), respectively). In silico analyses provided new insights into the possible functional consequences of the SNPs that showed the strongest association with DTC. Our findings provide evidence for novel DTC susceptibility variants. Further studies are warranted to identify the specific genetic variants responsible for the observed associations and to functionally validate our in silico predictions.

Clinical review: Genome-wide association studies of skeletal phenotypes: what we have learned and where we are headed.

PubMed

Hsu, Yi-Hsiang; Kiel, Douglas P

2012-10-01

The primary goals of genome-wide association studies (GWAS) are to discover new molecular and biological pathways involved in the regulation of bone metabolism that can be leveraged for drug development. In addition, the identified genetic determinants may be used to enhance current risk factor profiles. There have been more than 40 published GWAS on skeletal phenotypes, predominantly focused on dual-energy x-ray absorptiometry-derived bone mineral density (BMD) of the hip and spine. Sixty-six BMD loci have been replicated across all the published GWAS, confirming the highly polygenic nature of BMD variation. Only seven of the 66 previously reported genes (LRP5, SOST, ESR1, TNFRSF11B, TNFRSF11A, TNFSF11, PTH) from candidate gene association studies have been confirmed by GWAS. Among 59 novel BMD GWAS loci that have not been reported by previous candidate gene association studies, some have been shown to be involved in key biological pathways involving the skeleton, particularly Wnt signaling (AXIN1, LRP5, CTNNB1, DKK1, FOXC2, HOXC6, LRP4, MEF2C, PTHLH, RSPO3, SFRP4, TGFBR3, WLS, WNT3, WNT4, WNT5B, WNT16), bone development: ossification (CLCN7, CSF1, MEF2C, MEPE, PKDCC, PTHLH, RUNX2, SOX6, SOX9, SPP1, SP7), mesenchymal-stem-cell differentiation (FAM3C, MEF2C, RUNX2, SOX4, SOX9, SP7), osteoclast differentiation (JAG1, RUNX2), and TGF-signaling (FOXL1, SPTBN1, TGFBR3). There are still 30 BMD GWAS loci without prior molecular or biological evidence of their involvement in skeletal phenotypes. Other skeletal phenotypes that either have been or are being studied include hip geometry, bone ultrasound, quantitative computed tomography, high-resolution peripheral quantitative computed tomography, biochemical markers, and fractures such as vertebral, nonvertebral, hip, and forearm. Although several challenges lie ahead as GWAS moves into the next generation, there are prospects of new discoveries in skeletal biology. This review integrates findings from previous GWAS and provides a roadmap for future directions building on current GWAS successes.

Genetic Overlap Between Schizophrenia and Volumes of Hippocampus, Putamen, and Intracranial Volume Indicates Shared Molecular Genetic Mechanisms.

PubMed

Smeland, Olav B; Wang, Yunpeng; Frei, Oleksandr; Li, Wen; Hibar, Derrek P; Franke, Barbara; Bettella, Francesco; Witoelar, Aree; Djurovic, Srdjan; Chen, Chi-Hua; Thompson, Paul M; Dale, Anders M; Andreassen, Ole A

2018-06-06

Schizophrenia (SCZ) is associated with differences in subcortical brain volumes and intracranial volume (ICV). However, little is known about the underlying etiology of these brain alterations. Here, we explored whether brain structure volumes and SCZ share genetic risk factors. Using conditional false discovery rate (FDR) analysis, we integrated genome-wide association study (GWAS) data on SCZ (n = 82315) and GWAS data on 7 subcortical brain volumes and ICV (n = 11840). By conditioning the FDR on overlapping associations, this statistical approach increases power to discover genetic loci. To assess the credibility of our approach, we studied the identified loci in larger GWAS samples on ICV (n = 26577) and hippocampal volume (n = 26814). We observed polygenic overlap between SCZ and volumes of hippocampus, putamen, and ICV. Based on conjunctional FDR < 0.05, we identified 2 loci shared between SCZ and ICV implicating genes FOXO3 (rs10457180) and ITIH4 (rs4687658), 2 loci shared between SCZ and hippocampal volume implicating SLC4A10 (rs4664442) and SPATS2L (rs1653290), and 2 loci shared between SCZ and volume of putamen implicating DCC (rs4632195) and DLG2 (rs11233632). The loci shared between SCZ and hippocampal volume or ICV had not reached significance in the primary GWAS on brain phenotypes. Proving our point of increased power, 2 loci did reach genome-wide significance with ICV (rs10457180) and hippocampal volume (rs4664442) in the larger GWAS. Three of the 6 identified loci are novel for SCZ. Altogether, the findings provide new insights into the relationship between SCZ and brain structure volumes, suggesting that their genetic architectures are not independent.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

PubMed

Trampush, J W; Yang, M L Z; Yu, J; Knowles, E; Davies, G; Liewald, D C; Starr, J M; Djurovic, S; Melle, I; Sundet, K; Christoforou, A; Reinvang, I; DeRosse, P; Lundervold, A J; Steen, V M; Espeseth, T; Räikkönen, K; Widen, E; Palotie, A; Eriksson, J G; Giegling, I; Konte, B; Roussos, P; Giakoumaki, S; Burdick, K E; Payton, A; Ollier, W; Horan, M; Chiba-Falek, O; Attix, D K; Need, A C; Cirulli, E T; Voineskos, A N; Stefanis, N C; Avramopoulos, D; Hatzimanolis, A; Arking, D E; Smyrnis, N; Bilder, R M; Freimer, N A; Cannon, T D; London, E; Poldrack, R A; Sabb, F W; Congdon, E; Conley, E D; Scult, M A; Dickinson, D; Straub, R E; Donohoe, G; Morris, D; Corvin, A; Gill, M; Hariri, A R; Weinberger, D R; Pendleton, N; Bitsios, P; Rujescu, D; Lahti, J; Le Hellard, S; Keller, M C; Andreassen, O A; Deary, I J; Glahn, D C; Malhotra, A K; Lencz, T

2017-03-01

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10 -8 ). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium

PubMed Central

Trampush, J W; Yang, M L Z; Yu, J; Knowles, E; Davies, G; Liewald, D C; Starr, J M; Djurovic, S; Melle, I; Sundet, K; Christoforou, A; Reinvang, I; DeRosse, P; Lundervold, A J; Steen, V M; Espeseth, T; Räikkönen, K; Widen, E; Palotie, A; Eriksson, J G; Giegling, I; Konte, B; Roussos, P; Giakoumaki, S; Burdick, K E; Payton, A; Ollier, W; Horan, M; Chiba-Falek, O; Attix, D K; Need, A C; Cirulli, E T; Voineskos, A N; Stefanis, N C; Avramopoulos, D; Hatzimanolis, A; Arking, D E; Smyrnis, N; Bilder, R M; Freimer, N A; Cannon, T D; London, E; Poldrack, R A; Sabb, F W; Congdon, E; Conley, E D; Scult, M A; Dickinson, D; Straub, R E; Donohoe, G; Morris, D; Corvin, A; Gill, M; Hariri, A R; Weinberger, D R; Pendleton, N; Bitsios, P; Rujescu, D; Lahti, J; Le Hellard, S; Keller, M C; Andreassen, O A; Deary, I J; Glahn, D C; Malhotra, A K; Lencz, T

2017-01-01

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10−8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness. PMID:28093568

How powerful are summary-based methods for identifying expression-trait associations under different genetic architectures?

PubMed

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.

Genomic Influences on Hyperuricemia and Gout.

PubMed

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.

Comprehensive evaluation of disease- and trait-specific enrichment for eight functional elements among GWAS-identified variants.

PubMed

Markunas, Christina A; Johnson, Eric O; Hancock, Dana B

2017-07-01

Genome-wide association study (GWAS)-identified variants are enriched for functional elements. However, we have limited knowledge of how functional enrichment may differ by disease/trait and tissue type. We tested a broad set of eight functional elements for enrichment among GWAS-identified SNPs (p < 5×10 -8 ) from the NHGRI-EBI Catalog across seven disease/trait categories: cancer, cardiovascular disease, diabetes, autoimmune disease, psychiatric disease, neurological disease, and anthropometric traits. SNPs were annotated using HaploReg for the eight functional elements across any tissue: DNase sites, expression quantitative trait loci (eQTL), sequence conservation, enhancers, promoters, missense variants, sequence motifs, and protein binding sites. In addition, tissue-specific annotations were considered for brain vs. blood. Disease/trait SNPs were compared to a control set of 4809 SNPs matched to the GWAS SNPs (N = 1639) on allele frequency, gene density, distance to nearest gene, and linkage disequilibrium at ~3:1 ratio. Enrichment analyses were conducted using logistic regression, with Bonferroni correction. Overall, a significant enrichment was observed for all functional elements, except sequence motifs. Missense SNPs showed the strongest magnitude of enrichment. eQTLs were the only functional element significantly enriched across all diseases/traits. Magnitudes of enrichment were generally similar across diseases/traits, where enrichment was statistically significant. Blood vs. brain tissue effects on enrichment were dependent on disease/trait and functional element (e.g., cardiovascular disease: eQTLs P TissueDifference  = 1.28 × 10 -6 vs. enhancers P TissueDifference  = 0.94). Identifying disease/trait-relevant functional elements and tissue types could provide new insight into the underlying biology, by guiding a priori GWAS analyses (e.g., brain enhancer elements for psychiatric disease) or facilitating post hoc interpretation.

Trans-ancestry Fine Mapping and Molecular Assays Identify Regulatory Variants at the ANGPTL8 HDL-C GWAS Locus

PubMed Central

Cannon, Maren E.; Duan, Qing; Wu, Ying; Zeynalzadeh, Monica; Xu, Zheng; Kangas, Antti J.; Soininen, Pasi; Ala-Korpela, Mika; Civelek, Mete; Lusis, Aldons J.; Kuusisto, Johanna; Collins, Francis S.; Boehnke, Michael; Tang, Hua; Laakso, Markku; Li, Yun; Mohlke, Karen L.

2017-01-01

Recent genome-wide association studies (GWAS) have identified variants associated with high-density lipoprotein cholesterol (HDL-C) located in or near the ANGPTL8 gene. Given the extensive sharing of GWAS loci across populations, we hypothesized that at least one shared variant at this locus affects HDL-C. The HDL-C–associated variants are coincident with expression quantitative trait loci for ANGPTL8 and DOCK6 in subcutaneous adipose tissue; however, only ANGPTL8 expression levels are associated with HDL-C levels. We identified a 400-bp promoter region of ANGPTL8 and enhancer regions within 5 kb that contribute to regulating expression in liver and adipose. To identify variants functionally responsible for the HDL-C association, we performed fine-mapping analyses and selected 13 candidate variants that overlap putative regulatory regions to test for allelic differences in regulatory function. Of these variants, rs12463177-G increased transcriptional activity (1.5-fold, P = 0.004) and showed differential protein binding. Six additional variants (rs17699089, rs200788077, rs56322906, rs3760782, rs737337, and rs3745683) showed evidence of allelic differences in transcriptional activity and/or protein binding. Taken together, these data suggest a regulatory mechanism at the ANGPTL8 HDL-C GWAS locus involving tissue-selective expression and at least one functional variant. PMID:28754724

Establishing the role of rare coding variants in known Parkinson's disease risk loci.

PubMed

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.

The relationship between the human genome and microbiome comes into view

PubMed Central

Goodrich, Julia K.; Davenport, Emily R.; Clark, Andrew G.; Ley, Ruth E.

2017-01-01

The microbiome’s involvement in health and disease, and the complexity of its composition and function, make it intriguing to consider human genetic factors that impact microbiome composition. Genes may influence health through their ability to promote a stable microbial community in the gut. Studies of heritability yield a consistent subset of microbes that are impacted by genes, but the use of genome-wide association studies (GWAS) to identify specific genetic variants associated with microbiota phenotypes has proven challenging. Processing microbiome datasets into traits to be modeled and reducing the burden of multiple testing are just some of the technical hurdles in microbiome GWAS. Studies to date are small by GWAS standards, making cross-study comparisons and validations particularly important in identifying authentic signals. Cross-study comparisons are hampered by differences in analytical approaches. Nevertheless, some consistent associations have emerged between populations, most notably between Bifidobacteria and the lactase non-persister genotype. These early successes open the way for the microbiome to be incorporated into studies that quantify interactions among genotype, environment, and the microbiome for predicting disease susceptibility. PMID:28934590

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

PubMed Central

Milne, Roger L; Kuchenbaecker, Karoline B; Michailidou, Kyriaki; Beesley, Jonathan; Kar, Siddhartha; Lindström, Sara; Hui, Shirley; Lemaçon, Audrey; Soucy, Penny; Dennis, Joe; Jiang, Xia; Rostamianfar, Asha; Finucane, Hilary; Bolla, Manjeet K; McGuffog, Lesley; Wang, Qin; Aalfs, Cora M; Adams, Marcia; Adlard, Julian; Agata, Simona; Ahmed, Shahana; Ahsan, Habibul; Aittomäki, Kristiina; Al-Ejeh, Fares; Allen, Jamie; Ambrosone, Christine B; Amos, Christopher I; Andrulis, Irene L; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Auber, Bernd; Auer, Paul L; Ausems, Margreet G E M; Azzollini, Jacopo; Bacot, François; Balmaña, Judith; Barile, Monica; Barjhoux, Laure; Barkardottir, Rosa B; Barrdahl, Myrto; Barnes, Daniel; Barrowdale, Daniel; Baynes, Caroline; Beckmann, Matthias W; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Bignon, Yves-Jean; Blazer, Kathleen R; Blok, Marinus J; Blomqvist, Carl; Blot, William; Bobolis, Kristie; Boeckx, Bram; Bogdanova, Natalia V; Bojesen, Anders; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Bozsik, Aniko; Bradbury, Angela R; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Bressac-de Paillerets, Brigitte; Brewer, Carole; Brinton, Louise; Broberg, Per; Brooks-Wilson, Angela; Brunet, Joan; Brüning, Thomas; Burwinkel, Barbara; Buys, Saundra S; Byun, Jinyoung; Cai, Qiuyin; Caldés, Trinidad; Caligo, Maria A; Campbell, Ian; Canzian, Federico; Caron, Olivier; Carracedo, Angel; Carter, Brian D; Castelao, J Esteban; Castera, Laurent; Caux-Moncoutier, Virginie; Chan, Salina B; Chang-Claude, Jenny; Chanock, Stephen J; Chen, Xiaoqing; Cheng, Ting-Yuan David; Chiquette, Jocelyne; Christiansen, Hans; Claes, Kathleen B M; Clarke, Christine L; Conner, Thomas; Conroy, Don M; Cook, Jackie; Cordina-Duverger, Emilie; Cornelissen, Sten; Coupier, Isabelle; Cox, Angela; Cox, David G; Cross, Simon S; Cuk, Katarina; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Damiola, Francesca; Darabi, Hatef; Davidson, Rosemarie; De Leeneer, Kim; Devilee, Peter; Dicks, Ed; Diez, Orland; Ding, Yuan Chun; Ditsch, Nina; Doheny, Kimberly F; Domchek, Susan M; Dorfling, Cecilia M; Dörk, Thilo; dos-Santos-Silva, Isabel; Dubois, Stéphane; Dugué, Pierre-Antoine; Dumont, Martine; Dunning, Alison M; Durcan, Lorraine; Dwek, Miriam; Dworniczak, Bernd; Eccles, Diana; Eeles, Ros; Ehrencrona, Hans; Eilber, Ursula; Ejlertsen, Bent; Ekici, Arif B; Engel, Christoph; Eriksson, Mikael; Fachal, Laura; Faivre, Laurence; Fasching, Peter A; Faust, Ulrike; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Foulkes, William D; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gabrielson, Marike; Gaddam, Pragna; Gammon, Marilie D; Ganz, Patricia A; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; García-Sáenz, José A; Gaudet, Mia M; Gauthier-Villars, Marion; Gehrig, Andrea; Georgoulias, Vassilios; Gerdes, Anne-Marie; Giles, Graham G; Glendon, Gord; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Goodfellow, Paul; Greene, Mark H; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Gschwantler-Kaulich, Daphne; Guénel, Pascal; Guo, Qi; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hallberg, Emily; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Hansen, Thomas V O; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Healey, Catherine S; Hein, Alexander; Helbig, Sonja; Henderson, Alex; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Hodgson, Shirley; Hogervorst, Frans B; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Bob; Hopper, John L; Hu, Chunling; Huang, Guanmengqian; Hulick, Peter J; Humphreys, Keith; Hunter, David J; Imyanitov, Evgeny N; Isaacs, Claudine; Iwasaki, Motoki; Izatt, Louise; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Janni, Wolfgang; Jensen, Uffe Birk; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kast, Karin; Keeman, Renske; Kerin, Michael J; Kets, Carolien M; Keupers, Machteld; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Konstantopoulou, Irene; Kosma, Veli-Matti; Kristensen, Vessela N; Kruse, Torben A; Kwong, Ava; Lænkholm, Anne-Vibeke; Laitman, Yael; Lalloo, Fiona; Lambrechts, Diether; Landsman, Keren; Lasset, Christine; Lazaro, Conxi; Le Marchand, Loic; Lecarpentier, Julie; Lee, Andrew; Lee, Eunjung; Lee, Jong Won; Lee, Min Hyuk; Lejbkowicz, Flavio; Lesueur, Fabienne; Li, Jingmei; Lilyquist, Jenna; Lincoln, Anne; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Loud, Jennifer T; Lubinski, Jan; Luccarini, Craig; Lush, Michael; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Kostovska, Ivana Maleva; Malone, Kathleen E; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Martens, John W M; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; Mazoyer, Sylvie; McLean, Catriona; Meijers-Heijboer, Hanne; Menéndez, Primitiva; Meyer, Jeffery; Miao, Hui; Miller, Austin; Miller, Nicola; Mitchell, Gillian; Montagna, Marco; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Nadesan, Sue; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Nevelsteen, Ines; Niederacher, Dieter; Nielsen, Sune F; Nordestgaard, Børge G; Norman, Aaron; Nussbaum, Robert L; Olah, Edith; Olopade, Olufunmilayo I; Olson, Janet E; Olswold, Curtis; Ong, Kai-ren; Oosterwijk, Jan C; Orr, Nick; Osorio, Ana; Pankratz, V Shane; Papi, Laura; Park-Simon, Tjoung-Won; Paulsson-Karlsson, Ylva; Lloyd, Rachel; Pedersen, Inge Søkilde; Peissel, Bernard; Peixoto, Ana; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Pfeiler, Georg; Phelan, Catherine M; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Poppe, Bruce; Porteous, Mary E; Prentice, Ross; Presneau, Nadege; Prokofieva, Darya; Pugh, Elizabeth; Pujana, Miquel Angel; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rantala, Johanna; Rappaport-Fuerhauser, Christine; Rennert, Gad; Rennert, Hedy S; Rhenius, Valerie; Rhiem, Kerstin; Richardson, Andrea; Rodriguez, Gustavo C; Romero, Atocha; Romm, Jane; Rookus, Matti A; Rudolph, Anja; Ruediger, Thomas; Saloustros, Emmanouil; Sanders, Joyce; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Schwentner, Lukas; Scott, Christopher; Scott, Rodney J; Seal, Sheila; Senter, Leigha; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Xin; Shimelis, Hermela; Shrubsole, Martha J; Shu, Xiao-Ou; Side, Lucy E; Singer, Christian F; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Spurdle, Amanda B; Stegmaier, Christa; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Surowy, Harald; Sutter, Christian; Swerdlow, Anthony; Szabo, Csilla I; Tamimi, Rulla M; Tan, Yen Y; Taylor, Jack A; Tejada, Maria-Isabel; Tengström, Maria; Teo, Soo H; Terry, Mary B; Tessier, Daniel C; Teulé, Alex; Thöne, Kathrin; Thull, Darcy L; Tibiletti, Maria Grazia; Tihomirova, Laima; Tischkowitz, Marc; Toland, Amanda E; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Tranchant, Martine; Truong, Thérèse; Tucker, Kathy; Tung, Nadine; Tyrer, Jonathan; Ulmer, Hans-Ulrich; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vega, Ana; Viel, Alessandra; Vijai, Joseph; Vincent, Daniel; Vollenweider, Jason; Walker, Lisa; Wang, Zhaoming; Wang-Gohrke, Shan; Wappenschmidt, Barbara; Weinberg, Clarice R; Weitzel, Jeffrey N; Wendt, Camilla; Wesseling, Jelle; Whittemore, Alice S; Wijnen, Juul T; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yang, Xiaohong R; Yannoukakos, Drakoulis; Zaffaroni, Daniela; Zheng, Wei; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Zorn, Kristin K; Gago-Dominguez, Manuela; Mannermaa, Arto; Olsson, Håkan; Teixeira, Manuel R; Stone, Jennifer; Offit, Kenneth; Ottini, Laura; Park, Sue K; Thomassen, Mads; Hall, Per; Meindl, Alfons; Schmutzler, Rita K; Droit, Arnaud; Bader, Gary D; Pharoah, Paul D P; Couch, Fergus J; Easton, Douglas F; Kraft, Peter; Chenevix-Trench, Georgia; García-Closas, Montserrat; Schmidt, Marjanka K; Antoniou, Antonis C; Simard, Jacques

2018-01-01

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease1. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10−8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 14% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer. PMID:29058716

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.

PubMed

Milne, Roger L; Kuchenbaecker, Karoline B; Michailidou, Kyriaki; Beesley, Jonathan; Kar, Siddhartha; Lindström, Sara; Hui, Shirley; Lemaçon, Audrey; Soucy, Penny; Dennis, Joe; Jiang, Xia; Rostamianfar, Asha; Finucane, Hilary; Bolla, Manjeet K; McGuffog, Lesley; Wang, Qin; Aalfs, Cora M; Adams, Marcia; Adlard, Julian; Agata, Simona; Ahmed, Shahana; Ahsan, Habibul; Aittomäki, Kristiina; Al-Ejeh, Fares; Allen, Jamie; Ambrosone, Christine B; Amos, Christopher I; Andrulis, Irene L; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Arnold, Norbert; Aronson, Kristan J; Auber, Bernd; Auer, Paul L; Ausems, Margreet G E M; Azzollini, Jacopo; Bacot, François; Balmaña, Judith; Barile, Monica; Barjhoux, Laure; Barkardottir, Rosa B; Barrdahl, Myrto; Barnes, Daniel; Barrowdale, Daniel; Baynes, Caroline; Beckmann, Matthias W; Benitez, Javier; Bermisheva, Marina; Bernstein, Leslie; Bignon, Yves-Jean; Blazer, Kathleen R; Blok, Marinus J; Blomqvist, Carl; Blot, William; Bobolis, Kristie; Boeckx, Bram; Bogdanova, Natalia V; Bojesen, Anders; Bojesen, Stig E; Bonanni, Bernardo; Børresen-Dale, Anne-Lise; Bozsik, Aniko; Bradbury, Angela R; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Bressac-de Paillerets, Brigitte; Brewer, Carole; Brinton, Louise; Broberg, Per; Brooks-Wilson, Angela; Brunet, Joan; Brüning, Thomas; Burwinkel, Barbara; Buys, Saundra S; Byun, Jinyoung; Cai, Qiuyin; Caldés, Trinidad; Caligo, Maria A; Campbell, Ian; Canzian, Federico; Caron, Olivier; Carracedo, Angel; Carter, Brian D; Castelao, J Esteban; Castera, Laurent; Caux-Moncoutier, Virginie; Chan, Salina B; Chang-Claude, Jenny; Chanock, Stephen J; Chen, Xiaoqing; Cheng, Ting-Yuan David; Chiquette, Jocelyne; Christiansen, Hans; Claes, Kathleen B M; Clarke, Christine L; Conner, Thomas; Conroy, Don M; Cook, Jackie; Cordina-Duverger, Emilie; Cornelissen, Sten; Coupier, Isabelle; Cox, Angela; Cox, David G; Cross, Simon S; Cuk, Katarina; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Damiola, Francesca; Darabi, Hatef; Davidson, Rosemarie; De Leeneer, Kim; Devilee, Peter; Dicks, Ed; Diez, Orland; Ding, Yuan Chun; Ditsch, Nina; Doheny, Kimberly F; Domchek, Susan M; Dorfling, Cecilia M; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dubois, Stéphane; Dugué, Pierre-Antoine; Dumont, Martine; Dunning, Alison M; Durcan, Lorraine; Dwek, Miriam; Dworniczak, Bernd; Eccles, Diana; Eeles, Ros; Ehrencrona, Hans; Eilber, Ursula; Ejlertsen, Bent; Ekici, Arif B; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Fachal, Laura; Faivre, Laurence; Fasching, Peter A; Faust, Ulrike; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Foulkes, William D; Friedman, Eitan; Fritschi, Lin; Frost, Debra; Gabrielson, Marike; Gaddam, Pragna; Gammon, Marilie D; Ganz, Patricia A; Gapstur, Susan M; Garber, Judy; Garcia-Barberan, Vanesa; García-Sáenz, José A; Gaudet, Mia M; Gauthier-Villars, Marion; Gehrig, Andrea; Georgoulias, Vassilios; Gerdes, Anne-Marie; Giles, Graham G; Glendon, Gord; Godwin, Andrew K; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Goodfellow, Paul; Greene, Mark H; Alnæs, Grethe I Grenaker; Grip, Mervi; Gronwald, Jacek; Grundy, Anne; Gschwantler-Kaulich, Daphne; Guénel, Pascal; Guo, Qi; Haeberle, Lothar; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hallberg, Emily; Hamann, Ute; Hamel, Nathalie; Hankinson, Susan; Hansen, Thomas V O; Harrington, Patricia; Hart, Steven N; Hartikainen, Jaana M; Healey, Catherine S; Hein, Alexander; Helbig, Sonja; Henderson, Alex; Heyworth, Jane; Hicks, Belynda; Hillemanns, Peter; Hodgson, Shirley; Hogervorst, Frans B; Hollestelle, Antoinette; Hooning, Maartje J; Hoover, Bob; Hopper, John L; Hu, Chunling; Huang, Guanmengqian; Hulick, Peter J; Humphreys, Keith; Hunter, David J; Imyanitov, Evgeny N; Isaacs, Claudine; Iwasaki, Motoki; Izatt, Louise; Jakubowska, Anna; James, Paul; Janavicius, Ramunas; Janni, Wolfgang; Jensen, Uffe Birk; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael; Jukkola-Vuorinen, Arja; Kaaks, Rudolf; Kabisch, Maria; Kaczmarek, Katarzyna; Kang, Daehee; Kast, Karin; Keeman, Renske; Kerin, Michael J; Kets, Carolien M; Keupers, Machteld; Khan, Sofia; Khusnutdinova, Elza; Kiiski, Johanna I; Kim, Sung-Won; Knight, Julia A; Konstantopoulou, Irene; Kosma, Veli-Matti; Kristensen, Vessela N; Kruse, Torben A; Kwong, Ava; Lænkholm, Anne-Vibeke; Laitman, Yael; Lalloo, Fiona; Lambrechts, Diether; Landsman, Keren; Lasset, Christine; Lazaro, Conxi; Le Marchand, Loic; Lecarpentier, Julie; Lee, Andrew; Lee, Eunjung; Lee, Jong Won; Lee, Min Hyuk; Lejbkowicz, Flavio; Lesueur, Fabienne; Li, Jingmei; Lilyquist, Jenna; Lincoln, Anne; Lindblom, Annika; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Long, Jirong; Loud, Jennifer T; Lubinski, Jan; Luccarini, Craig; Lush, Michael; MacInnis, Robert J; Maishman, Tom; Makalic, Enes; Kostovska, Ivana Maleva; Malone, Kathleen E; Manoukian, Siranoush; Manson, JoAnn E; Margolin, Sara; Martens, John W M; Martinez, Maria Elena; Matsuo, Keitaro; Mavroudis, Dimitrios; Mazoyer, Sylvie; McLean, Catriona; Meijers-Heijboer, Hanne; Menéndez, Primitiva; Meyer, Jeffery; Miao, Hui; Miller, Austin; Miller, Nicola; Mitchell, Gillian; Montagna, Marco; Muir, Kenneth; Mulligan, Anna Marie; Mulot, Claire; Nadesan, Sue; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Nevelsteen, Ines; Niederacher, Dieter; Nielsen, Sune F; Nordestgaard, Børge G; Norman, Aaron; Nussbaum, Robert L; Olah, Edith; Olopade, Olufunmilayo I; Olson, Janet E; Olswold, Curtis; Ong, Kai-Ren; Oosterwijk, Jan C; Orr, Nick; Osorio, Ana; Pankratz, V Shane; Papi, Laura; Park-Simon, Tjoung-Won; Paulsson-Karlsson, Ylva; Lloyd, Rachel; Pedersen, Inge Søkilde; Peissel, Bernard; Peixoto, Ana; Perez, Jose I A; Peterlongo, Paolo; Peto, Julian; Pfeiler, Georg; Phelan, Catherine M; Pinchev, Mila; Plaseska-Karanfilska, Dijana; Poppe, Bruce; Porteous, Mary E; Prentice, Ross; Presneau, Nadege; Prokofieva, Darya; Pugh, Elizabeth; Pujana, Miquel Angel; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rantala, Johanna; Rappaport-Fuerhauser, Christine; Rennert, Gad; Rennert, Hedy S; Rhenius, Valerie; Rhiem, Kerstin; Richardson, Andrea; Rodriguez, Gustavo C; Romero, Atocha; Romm, Jane; Rookus, Matti A; Rudolph, Anja; Ruediger, Thomas; Saloustros, Emmanouil; Sanders, Joyce; Sandler, Dale P; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Daniel F; Schoemaker, Minouk J; Schumacher, Fredrick; Schürmann, Peter; Schwentner, Lukas; Scott, Christopher; Scott, Rodney J; Seal, Sheila; Senter, Leigha; Seynaeve, Caroline; Shah, Mitul; Sharma, Priyanka; Shen, Chen-Yang; Sheng, Xin; Shimelis, Hermela; Shrubsole, Martha J; Shu, Xiao-Ou; Side, Lucy E; Singer, Christian F; Sohn, Christof; Southey, Melissa C; Spinelli, John J; Spurdle, Amanda B; Stegmaier, Christa; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Surowy, Harald; Sutter, Christian; Swerdlow, Anthony; Szabo, Csilla I; Tamimi, Rulla M; Tan, Yen Y; Taylor, Jack A; Tejada, Maria-Isabel; Tengström, Maria; Teo, Soo H; Terry, Mary B; Tessier, Daniel C; Teulé, Alex; Thöne, Kathrin; Thull, Darcy L; Tibiletti, Maria Grazia; Tihomirova, Laima; Tischkowitz, Marc; Toland, Amanda E; Tollenaar, Rob A E M; Tomlinson, Ian; Tong, Ling; Torres, Diana; Tranchant, Martine; Truong, Thérèse; Tucker, Kathy; Tung, Nadine; Tyrer, Jonathan; Ulmer, Hans-Ulrich; Vachon, Celine; van Asperen, Christi J; Van Den Berg, David; van den Ouweland, Ans M W; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vega, Ana; Viel, Alessandra; Vijai, Joseph; Vincent, Daniel; Vollenweider, Jason; Walker, Lisa; Wang, Zhaoming; Wang-Gohrke, Shan; Wappenschmidt, Barbara; Weinberg, Clarice R; Weitzel, Jeffrey N; Wendt, Camilla; Wesseling, Jelle; Whittemore, Alice S; Wijnen, Juul T; Willett, Walter; Winqvist, Robert; Wolk, Alicja; Wu, Anna H; Xia, Lucy; Yang, Xiaohong R; Yannoukakos, Drakoulis; Zaffaroni, Daniela; Zheng, Wei; Zhu, Bin; Ziogas, Argyrios; Ziv, Elad; Zorn, Kristin K; Gago-Dominguez, Manuela; Mannermaa, Arto; Olsson, Håkan; Teixeira, Manuel R; Stone, Jennifer; Offit, Kenneth; Ottini, Laura; Park, Sue K; Thomassen, Mads; Hall, Per; Meindl, Alfons; Schmutzler, Rita K; Droit, Arnaud; Bader, Gary D; Pharoah, Paul D P; Couch, Fergus J; Easton, Douglas F; Kraft, Peter; Chenevix-Trench, Georgia; García-Closas, Montserrat; Schmidt, Marjanka K; Antoniou, Antonis C; Simard, Jacques

2017-12-01

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 -8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Genome-wide association study of sex hormones, gonadotropins and sex hormone-binding protein in Chinese men.

PubMed

Chen, Zhuo; Tao, Sha; Gao, Yong; Zhang, Ju; Hu, Yanling; Mo, Linjian; Kim, Seong-Tae; Yang, Xiaobo; Tan, Aihua; Zhang, Haiying; Qin, Xue; Li, Li; Wu, Yongming; Zhang, Shijun; Zheng, S Lilly; Xu, Jianfeng; Mo, Zengnan; Sun, Jielin

2013-12-01

Sex hormones and gonadotropins exert a wide variety of effects in physiological and pathological processes. Accumulated evidence shows a strong heritable component of circulating concentrations of these hormones. Recently, several genome-wide association studies (GWASs) conducted in Caucasians have identified multiple loci that influence serum levels of sex hormones. However, the genetic determinants remain unknown in Chinese populations. In this study, we aimed to identify genetic variants associated with major sex hormones, gonadotropins, including testosterone, oestradiol, follicle-stimulating hormone (FSH), luteinising hormone (LH) and sex hormone binding globulin (SHBG) in a Chinese population. A two-stage GWAS was conducted in a total of 3495 healthy Chinese men (1999 subjects in the GWAS discovery stage and 1496 in the confirmation stage). We identified a novel genetic region at 15q21.2 (rs2414095 in CYP19A1), which was significantly associated with oestradiol and FSH in the Chinese population at a genome-wide significant level (p=6.54×10(-31) and 1.59×10(-16), respectively). Another single nucleotide polymorphism in CYP19A1 gene was significantly associated with oestradiol level (rs2445762, p=7.75×10(-28)). In addition, we confirmed the previous GWAS-identified locus at 17p13.1 for testosterone (rs2075230, p=1.13×10(-8)) and SHBG level (rs2075230, p=4.75×10(-19)) in the Chinese population. This study is the first GWAS investigation of genetic determinants of FSH and LH. The identification of novel susceptibility loci may provide more biological implications for the synthesis and metabolism of these hormones. More importantly, the confirmation of the genetic loci for testosterone and SHBG suggests common genetic components shared among different ethnicities.

Genome-wide association study identifies multiple loci associated with bladder cancer risk

PubMed Central

Figueroa, Jonine D.; Ye, Yuanqing; Siddiq, Afshan; Garcia-Closas, Montserrat; Chatterjee, Nilanjan; Prokunina-Olsson, Ludmila; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Dinney, Colin P.; Malats, Núria; Baris, Dalsu; Purdue, Mark; Jacobs, Eric J.; Albanes, Demetrius; Wang, Zhaoming; Deng, Xiang; Chung, Charles C.; Tang, Wei; Bas Bueno-de-Mesquita, H.; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Kamat, Ashish M.; Lerner, Seth P.; Barton Grossman, H.; Lin, Jie; Gu, Jian; Pu, Xia; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Kogevinas, Manolis; Tardón, Adonina; Serra, Consol; Carrato, Alfredo; García-Closas, Reina; Lloreta, Josep; Schwenn, Molly; Karagas, Margaret R.; Johnson, Alison; Schned, Alan; Armenti, Karla R.; Hosain, G.M.; Andriole, Gerald; Grubb, Robert; Black, Amanda; Ryan Diver, W.; Gapstur, Susan M.; Weinstein, Stephanie J.; Virtamo, Jarmo; Haiman, Chris A.; Landi, Maria T.; Caporaso, Neil; Fraumeni, Joseph F.; Vineis, Paolo; Wu, Xifeng; Silverman, Debra T.; Chanock, Stephen; Rothman, Nathaniel

2014-01-01

Candidate gene and genome-wide association studies (GWAS) have identified 11 independent susceptibility loci associated with bladder cancer risk. To discover additional risk variants, we conducted a new GWAS of 2422 bladder cancer cases and 5751 controls, followed by a meta-analysis with two independently published bladder cancer GWAS, resulting in a combined analysis of 6911 cases and 11 814 controls of European descent. TaqMan genotyping of 13 promising single nucleotide polymorphisms with P < 1 × 10−5 was pursued in a follow-up set of 801 cases and 1307 controls. Two new loci achieved genome-wide statistical significance: rs10936599 on 3q26.2 (P = 4.53 × 10−9) and rs907611 on 11p15.5 (P = 4.11 × 10−8). Two notable loci were also identified that approached genome-wide statistical significance: rs6104690 on 20p12.2 (P = 7.13 × 10−7) and rs4510656 on 6p22.3 (P = 6.98 × 10−7); these require further studies for confirmation. In conclusion, our study has identified new susceptibility alleles for bladder cancer risk that require fine-mapping and laboratory investigation, which could further understanding into the biological underpinnings of bladder carcinogenesis. PMID:24163127

Reprogramming neurodegeneration in the big data era.

PubMed

Zhou, Lujia; Verstreken, Patrik

2018-02-01

Recent genome-wide association studies (GWAS) have identified numerous genetic risk variants for late-onset Alzheimer's disease (AD) and Parkinson's disease (PD). However, deciphering the functional consequences of GWAS data is challenging due to a lack of reliable model systems to study the genetic variants that are often of low penetrance and non-coding identities. Pluripotent stem cell (PSC) technologies offer unprecedented opportunities for molecular phenotyping of GWAS variants in human neurons and microglia. Moreover, rapid technological advances in whole-genome RNA-sequencing and epigenome mapping fuel comprehensive and unbiased investigations of molecular alterations in PSC-derived disease models. Here, we review and discuss how integrated studies that utilize PSC technologies and genome-wide approaches may bring new mechanistic insight into the pathogenesis of AD and PD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessment of Parkinson’s disease risk loci in Greece

PubMed Central

Kara, Eleanna; Xiromerisiou, Georgia; Spanaki, Cleanthe; Bozi, Maria; Koutsis, Georgios; Panas, Marios; Dardiotis, Efthimios; Ralli, Styliani; Bras, Jose; Letson, Christopher; Edsall, Connor; Pliner, Hannah; Arepali, Sampath; Kalinderi, Kallirhoe; Fidani, Liana; Bostanjopoulou, Sevasti; Keller, Margaux F; Wood, Nicholas W; Hardy, John; Houlden, Henry; Stefanis, Leonidas; Plaitakis, Andreas; Hernandez, Dena; Hadjigeorgiou, Georgios M; Nalls, Mike A; Singleton, Andrew B

2013-01-01

Genome wide association studies (GWAS) have been shown to be a powerful approach to identify risk loci for neurodegenerative diseases. Recent GWAS in Parkinson’s disease (PD) have been successful in identifying numerous risk variants pointing to novel pathways potentially implicated in the pathogenesis of PD. Contributing to these GWAS efforts, we performed genotyping of previously identified risk alleles in PD patients and controls from Greece. We showed that previously published risk profiles for Northern European and American populations are also applicable to the Greek population. In addition, while we were largely underpowered to detect individual associations we replicated 5 of 32 previously published risk variants with nominal p-values <0.05. Genome-wide complex trait analysis (GCTA) revealed that known risk loci explain disease risk in 1.27% of Greek PD patients. Collectively, these results indicate that there is likely a substantial genetic component to PD in Greece similarly to other worldwide populations that remains to be discovered. PMID:24080174

Inflammation in Alzheimer's Disease and Molecular Genetics: Recent Update.

PubMed

Zhang, Zhi-Gang; Li, Yan; Ng, Cheung Toa; Song, You-Qiang

2015-10-01

Alzheimer's disease (AD) is a complex age-related neurodegenerative disorder of the central nervous system. Since the first description of AD in 1907, many hypotheses have been established to explain its causes. The inflammation theory is one of them. Pathological and biochemical studies of brains from AD individuals have provided solid evidence of the activation of inflammatory pathways. Furthermore, people with long-term medication of anti-inflammatory drugs have shown a reduced risk to develop the disease. After three decades of genetic study in AD, dozens of loci harboring genetic variants influencing inflammatory pathways in AD patients has been identified through genome-wide association studies (GWAS). The most well-known GWAS risk factor that is responsible for immune response and inflammation in AD development should be APOE ε4 allele. However, a growing number of other GWAS risk AD candidate genes in inflammation have recently been discovered. In the present study, we try to review the inflammation in AD and immunity-associated GWAS risk genes like HLA-DRB5/DRB1, INPP5D, MEF2C, CR1, CLU and TREM2.

Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins

PubMed Central

Postmus, Iris; Trompet, Stella; Deshmukh, Harshal A.; Barnes, Michael R.; Li, Xiaohui; Warren, Helen R.; Chasman, Daniel I.; Zhou, Kaixin; Arsenault, Benoit J.; Donnelly, Louise A.; Wiggins, Kerri L.; Avery, Christy L.; Griffin, Paula; Feng, QiPing; Taylor, Kent D.; Li, Guo; Evans, Daniel S.; Smith, Albert V.; de Keyser, Catherine E.; Johnson, Andrew D.; de Craen, Anton J. M.; Stott, David J.; Buckley, Brendan M.; Ford, Ian; Westendorp, Rudi G. J.; Eline Slagboom, P.; Sattar, Naveed; Munroe, Patricia B.; Sever, Peter; Poulter, Neil; Stanton, Alice; Shields, Denis C.; O’Brien, Eoin; Shaw-Hawkins, Sue; Ida Chen, Y.-D.; Nickerson, Deborah A.; Smith, Joshua D.; Pierre Dubé, Marie; Matthijs Boekholdt, S.; Kees Hovingh, G.; Kastelein, John J. P.; McKeigue, Paul M.; Betteridge, John; Neil, Andrew; Durrington, Paul N.; Doney, Alex; Carr, Fiona; Morris, Andrew; McCarthy, Mark I.; Groop, Leif; Ahlqvist, Emma; Bis, Joshua C.; Rice, Kenneth; Smith, Nicholas L.; Lumley, Thomas; Whitsel, Eric A.; Stürmer, Til; Boerwinkle, Eric; Ngwa, Julius S.; O’Donnell, Christopher J.; Vasan, Ramachandran S.; Wei, Wei-Qi; Wilke, Russell A.; Liu, Ching-Ti; Sun, Fangui; Guo, Xiuqing; Heckbert, Susan R; Post, Wendy; Sotoodehnia, Nona; Arnold, Alice M.; Stafford, Jeanette M.; Ding, Jingzhong; Herrington, David M.; Kritchevsky, Stephen B.; Eiriksdottir, Gudny; Launer, Leonore J.; Harris, Tamara B.; Chu, Audrey Y.; Giulianini, Franco; MacFadyen, Jean G.; Barratt, Bryan J.; Nyberg, Fredrik; Stricker, Bruno H.; Uitterlinden, André G.; Hofman, Albert; Rivadeneira, Fernando; Emilsson, Valur; Franco, Oscar H.; Ridker, Paul M.; Gudnason, Vilmundur; Liu, Yongmei; Denny, Joshua C.; Ballantyne, Christie M.; Rotter, Jerome I.; Adrienne Cupples, L.; Psaty, Bruce M.; Palmer, Colin N. A.; Tardif, Jean-Claude; Colhoun, Helen M.; Hitman, Graham; Krauss, Ronald M.; Wouter Jukema, J; Caulfield, Mark J.; Donnelly, Peter; Barroso, Ines; Blackwell, Jenefer M.; Bramon, Elvira; Brown, Matthew A.; Casas, Juan P.; Corvin, Aiden; Deloukas, Panos; Duncanson, Audrey; Jankowski, Janusz; Markus, Hugh S.; Mathew, Christopher G.; Palmer, Colin N. A.; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J.; Trembath, Richard C.; Viswanathan, Ananth C.; Wood, Nicholas W.; Spencer, Chris C. A.; Band, Gavin; Bellenguez, Céline; Freeman, Colin; Hellenthal, Garrett; Giannoulatou, Eleni; Pirinen, Matti; Pearson, Richard; Strange, Amy; Su, Zhan; Vukcevic, Damjan; Donnelly, Peter; Langford, Cordelia; Hunt, Sarah E.; Edkins, Sarah; Gwilliam, Rhian; Blackburn, Hannah; Bumpstead, Suzannah J.; Dronov, Serge; Gillman, Matthew; Gray, Emma; Hammond, Naomi; Jayakumar, Alagurevathi; McCann, Owen T.; Liddle, Jennifer; Potter, Simon C.; Ravindrarajah, Radhi; Ricketts, Michelle; Waller, Matthew; Weston, Paul; Widaa, Sara; Whittaker, Pamela; Barroso, Ines; Deloukas, Panos; Mathew, Christopher G.; Blackwell, Jenefer M.; Brown, Matthew A.; Corvin, Aiden; McCarthy, Mark I.; Spencer, Chris C. A.

2014-01-01

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response. PMID:25350695

easyGWAS: A Cloud-Based Platform for Comparing the Results of Genome-Wide Association Studies.

PubMed

Grimm, Dominik G; Roqueiro, Damian; Salomé, Patrice A; Kleeberger, Stefan; Greshake, Bastian; Zhu, Wangsheng; Liu, Chang; Lippert, Christoph; Stegle, Oliver; Schölkopf, Bernhard; Weigel, Detlef; Borgwardt, Karsten M

2017-01-01

The ever-growing availability of high-quality genotypes for a multitude of species has enabled researchers to explore the underlying genetic architecture of complex phenotypes at an unprecedented level of detail using genome-wide association studies (GWAS). The systematic comparison of results obtained from GWAS of different traits opens up new possibilities, including the analysis of pleiotropic effects. Other advantages that result from the integration of multiple GWAS are the ability to replicate GWAS signals and to increase statistical power to detect such signals through meta-analyses. In order to facilitate the simple comparison of GWAS results, we present easyGWAS, a powerful, species-independent online resource for computing, storing, sharing, annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the uploading of private genotype data and summary statistics of existing GWAS, as well as advanced methods for comparing GWAS results across different experiments and data sets in an interactive and user-friendly interface. easyGWAS is also a public data repository for GWAS data and summary statistics and already includes published data and results from several major GWAS. We demonstrate the potential of easyGWAS with a case study of the model organism Arabidopsis thaliana , using flowering and growth-related traits. © 2016 American Society of Plant Biologists. All rights reserved.

Genomic prediction and genome-wide association analysis of female longevity in a composite beef cattle breed.

PubMed

Hamidi Hay, E; Roberts, A

2017-04-01

Longevity is a highly important trait to the efficiency of beef cattle production. The objective of this study was to evaluate the genomic prediction of longevity and identify genomic regions associated with this trait. The data used in this study consisted of 547 Composite Gene Combination cows (1/2 Red Angus, 1/4 Charolais, 1/4 Tarentaise) born from 2002 to 2011 genotyped with Illumina BovineSNP50 BeadChip. Three models were used to assess genomic prediction: Bayes A, Bayes B and GBLUP using a genomic relationship matrix. To identify genomic regions associated with longevity 2 approaches were adopted: single marker genome wide association and Bayesian approach using GenSel software. The genomic prediction accuracy was low 0.28, 0.25, and 0.22 for Bayes A, Bayes B and GBLUP, respectively. The single-marker genome wide association study (GWAS)identified 5 loci with -value less than 0.05 after false discovery correction: UA-IFASA-7571 on chromosome 19 (58.03 Mb), ARS-BFGL-BAC-15059 on BTA 1 (28.8 Mb), ARS-BFGL-NGS-104159 on BTA3 (29.4 Mb), ARS-BFGL-NGS-32882 on BTA9 (104.07 Mb) and ARS-BFGL-NGS-32883 on BTA25 (33.77 Mb). The Bayesian GWAS yielded 4 genomic regions overlapping with the single marker GWAS results. The region with the highest percentage of genomic variance (3.73%) was detected on chromosome 19. Both GWAS approaches adopted in this study showed evidence for association with various chromosomal locations.

Genetic architecture for susceptibility to gout in the KARE cohort study.

PubMed

Shin, Jimin; Kim, Younyoung; Kong, Minyoung; Lee, Chaeyoung

2012-06-01

This study aimed to identify functional associations of cis-regulatory regions with gout susceptibility using data resulted from a genome-wide association study (GWAS), and to show a genetic architecture for gout with interaction effects among genes within each of the identified functions. The GWAS was conducted with 8314 control subjects and 520 patients with gout in the Korea Association REsource cohort. However, genetic associations with any individual nucleotide variants were not discovered by Bonferroni multiple testing in the GWAS (P>1.42 × 10(-7)). Genomic regions enrichment analysis was employed to identify functional associations of cis-regulatory regions. This analysis revealed several biological processes associated with gout susceptibility, and they were quite different from those with serum uric acid level. Epistasis for susceptibility to gout was estimated using entropy decomposition with selected genes within each biological process identified by the genomic regions enrichment analysis. Some epistases among nucleotide sequence variants for gout susceptibility were found to be larger than their individual effects. This study provided the first evidence that genetic factors for gout susceptibility greatly differed from those for serum uric acid level, which may suggest that research endeavors for identifying genetic factors for gout susceptibility should not be heavily dependent on pathogenesis of uric acid. Interaction effects between genes should be examined to explain a large portion of phenotypic variability for gout susceptibility.

Further support for association between GWAS variant for positive emotion and reward systems.

PubMed

Lancaster, T M; Ihssen, N; Brindley, L M; Linden, D E J

2017-01-31

A recent genome-wide association study (GWAS) identified a significant single-nucleotide polymorphism (SNP) for trait-positive emotion at rs322931 on chromosome 1, which was also associated with brain activation in the reward system of healthy individuals when observing positive stimuli in a functional magnetic resonance imaging (fMRI) study. In the current study, we aimed to further validate the role of variation at rs322931 in reward processing. Using a similar fMRI approach, we use two paradigms that elicit a strong ventral striatum (VS) blood oxygen-level dependency (BOLD) response in a sample of young, healthy individuals (N=82). In the first study we use a similar picture-viewing task to the discovery sample (positive>neutral stimuli) to replicate an effect of the variant on emotion processing. In the second study we use a probabilistic reversal learning procedure to identify reward processing during decision-making under uncertainly (reward>punishment). In a region of interest (ROI) analysis of the bilateral VS, we show that the rs322931 genotype was associated with BOLD in the left VS during the positive>neutral contrast (P ROI-CORRECTED =0.045) and during the reward>punishment contrast (P ROI-CORRECTED =0.018), although the effect of passive picture viewing was in the opposite direction from that reported in the discovery sample. These findings suggest that the recently identified GWAS hit may influence positive emotion via individual differences in activity in the key hubs of the brain's reward system. Furthermore, these effects may not be limited to the passive viewing of positive emotional scenes, but may also be observed during dynamic decision-making. This study suggests that future studies of this GWAS locus may yield further insight into the biological mechanisms of psychopathologies characterised by deficits in reward processing and positive emotion.

Meta-analysis of genome wide association studies (GWAS) on the intolerance of Angiotensin converting enzyme inhibitors

PubMed Central

Mahmoudpour, Seyed Hamidreza; Veluchamy, Abirami; Siddiqui, Moneeza Kalhan; Asselbergs, Folkert W.; Souverein, Patrick C.; de Keyser, Catherine E.; Hofman, Albert; Lang, Chim C.; Doney, Alexander SF.; Stricker, Bruno H.; de Boer, Anthonius; Maitland-van der Zee, Anke-Hilse; Palmer, Colin NA.

2016-01-01

Objectives To identify SNPs associated with switching from an ACE-inhibitor to an angiotensin receptor blocker (ARB). Methods Two cohorts of patients starting ACE-inhibitors were identified within the Rotterdam Study in the Netherlands and the GoDARTS study in Scotland. Cases were intolerant subjects who switched from an ACE-inhibitor to an ARB, controls were subjects who used ACE-inhibitors continuously for at least 2 years and did not switch. GWAS using an additive model was run in these sets and results were meta-analysed using GWAMA. Results 972 cases out of 5 161 ACE-inhibitor starters were identified. 8 SNPs within 4 genes reached the GWAS significance level (P<5×10-8) in the meta-analysis (RBFOX3, GABRG2, SH2B1 and MBOAT1). The strongest associated SNP was located in an intron of RBFOX3, which contains a RNA binding protein (rs2061538: MAF=0.16, OR=1.52[95%CI: 1.32-1.76], p=6.2x10-9). Conclusions These results indicate that genetic variation in abovementioned genes may increase the risk of ACE-inhibitors induced adverse reactions. PMID:28030426

Schizophrenia interactome with 504 novel protein–protein interactions

PubMed Central

Ganapathiraju, Madhavi K; Thahir, Mohamed; Handen, Adam; Sarkar, Saumendra N; Sweet, Robert A; Nimgaonkar, Vishwajit L; Loscher, Christine E; Bauer, Eileen M; Chaparala, Srilakshmi

2016-01-01

Genome-wide association studies of schizophrenia (GWAS) have revealed the role of rare and common genetic variants, but the functional effects of the risk variants remain to be understood. Protein interactome-based studies can facilitate the study of molecular mechanisms by which the risk genes relate to schizophrenia (SZ) genesis, but protein–protein interactions (PPIs) are unknown for many of the liability genes. We developed a computational model to discover PPIs, which is found to be highly accurate according to computational evaluations and experimental validations of selected PPIs. We present here, 365 novel PPIs of liability genes identified by the SZ Working Group of the Psychiatric Genomics Consortium (PGC). Seventeen genes that had no previously known interactions have 57 novel interactions by our method. Among the new interactors are 19 drug targets that are targeted by 130 drugs. In addition, we computed 147 novel PPIs of 25 candidate genes investigated in the pre-GWAS era. While there is little overlap between the GWAS genes and the pre-GWAS genes, the interactomes reveal that they largely belong to the same pathways, thus reconciling the apparent disparities between the GWAS and prior gene association studies. The interactome including 504 novel PPIs overall, could motivate other systems biology studies and trials with repurposed drugs. The PPIs are made available on a webserver, called Schizo-Pi at http://severus.dbmi.pitt.edu/schizo-pi with advanced search capabilities. PMID:27336055

Identification of a New Susceptibility Locus for Systemic Lupus Erythematosus on Chromosome 12 in Individuals of European Ancestry

PubMed Central

Demirci, F. Yesim; Wang, Xingbin; Kelly, Jennifer A.; Morris, David L.; Barmada, M. Michael; Feingold, Eleanor; Kao, Amy H.; Sivils, Kathy L.; Bernatsky, Sasha; Pineau, Christian; Clarke, Ann; Ramsey-Goldman, Rosalind; Vyse, Timothy J.; Gaffney, Patrick M.; Manzi, Susan; Kamboh, M. Ilyas

2016-01-01

Objective Genome-wide association studies (GWASs) in individuals of European ancestry identified a number of systemic lupus erythematosus (SLE) susceptibility loci using earlier versions of high-density genotyping platforms. Follow-up studies on suggestive GWAS regions using larger samples and more markers identified additional SLE loci in European-descent subjects. Here we report the results of a multi-stage study that we performed to identify novel SLE loci. Methods In Stage 1, we conducted a new GWAS of SLE in a North American case-control sample of European ancestry (n=1,166) genotyped on Affymetrix Genome-Wide Human SNP Array 6.0. In Stage 2, we further investigated top new suggestive GWAS hits by in silico evaluation and meta-analysis using an additional dataset of European-descent subjects (>2,500 individuals), followed by replication of top meta-analysis findings in another dataset of European-descent subjects (>10,000 individuals) in Stage 3. Results As expected, our GWAS revealed most significant associations at the major histocompatibility complex locus (6p21), which easily surpassed genome-wide significance threshold (P<5×10−8). Several other SLE signals/loci previously implicated in Caucasians and/or Asians were also supported in Stage 1 discovery sample and strongest signals were observed at 2q32/STAT4 (P=3.6×10−7) and at 8p23/BLK (P=8.1×10−6). Stage 2 meta-analyses identified a new genome-wide significant SLE locus at 12q12 (meta P=3.1×10−8), which was replicated in Stage 3. Conclusion Our multi-stage study identified and replicated a new SLE locus that warrants further follow-up in additional studies. Publicly available databases suggest that this new SLE signal falls within a functionally relevant genomic region and near biologically important genes. PMID:26316170

Genome-wide association study meta-analysis of European and Asian-ancestry samples identifies three novel loci associated with bipolar disorder.

PubMed

Chen, D T; Jiang, X; Akula, N; Shugart, Y Y; Wendland, J R; Steele, C J M; Kassem, L; Park, J-H; Chatterjee, N; Jamain, S; Cheng, A; Leboyer, M; Muglia, P; Schulze, T G; Cichon, S; Nöthen, M M; Rietschel, M; McMahon, F J; Farmer, A; McGuffin, P; Craig, I; Lewis, C; Hosang, G; Cohen-Woods, S; Vincent, J B; Kennedy, J L; Strauss, J

2013-02-01

Meta-analyses of bipolar disorder (BD) genome-wide association studies (GWAS) have identified several genome-wide significant signals in European-ancestry samples, but so far account for little of the inherited risk. We performed a meta-analysis of ∼750,000 high-quality genetic markers on a combined sample of ∼14,000 subjects of European and Asian-ancestry (phase I). The most significant findings were further tested in an extended sample of ∼17,700 cases and controls (phase II). The results suggest novel association findings near the genes TRANK1 (LBA1), LMAN2L and PTGFR. In phase I, the most significant single nucleotide polymorphism (SNP), rs9834970 near TRANK1, was significant at the P=2.4 × 10(-11) level, with no heterogeneity. Supportive evidence for prior association findings near ANK3 and a locus on chromosome 3p21.1 was also observed. The phase II results were similar, although the heterogeneity test became significant for several SNPs. On the basis of these results and other established risk loci, we used the method developed by Park et al. to estimate the number, and the effect size distribution, of BD risk loci that could still be found by GWAS methods. We estimate that >63,000 case-control samples would be needed to identify the ∼105 BD risk loci discoverable by GWAS, and that these will together explain <6% of the inherited risk. These results support previous GWAS findings and identify three new candidate genes for BD. Further studies are needed to replicate these findings and may potentially lead to identification of functional variants. Sample size will remain a limiting factor in the discovery of common alleles associated with BD.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

PubMed Central

2012-01-01

Background Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD). Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci. PMID:23281813

Genetic Susceptibility to Vitiligo: GWAS Approaches for Identifying Vitiligo Susceptibility Genes and Loci

PubMed Central

Shen, Changbing; Gao, Jing; Sheng, Yujun; Dou, Jinfa; Zhou, Fusheng; Zheng, Xiaodong; Ko, Randy; Tang, Xianfa; Zhu, Caihong; Yin, Xianyong; Sun, Liangdan; Cui, Yong; Zhang, Xuejun

2016-01-01

Vitiligo is an autoimmune disease with a strong genetic component, characterized by areas of depigmented skin resulting from loss of epidermal melanocytes. Genetic factors are known to play key roles in vitiligo through discoveries in association studies and family studies. Previously, vitiligo susceptibility genes were mainly revealed through linkage analysis and candidate gene studies. Recently, our understanding of the genetic basis of vitiligo has been rapidly advancing through genome-wide association study (GWAS). More than 40 robust susceptible loci have been identified and confirmed to be associated with vitiligo by using GWAS. Most of these associated genes participate in important pathways involved in the pathogenesis of vitiligo. Many susceptible loci with unknown functions in the pathogenesis of vitiligo have also been identified, indicating that additional molecular mechanisms may contribute to the risk of developing vitiligo. In this review, we summarize the key loci that are of genome-wide significance, which have been shown to influence vitiligo risk. These genetic loci may help build the foundation for genetic diagnosis and personalize treatment for patients with vitiligo in the future. However, substantial additional studies, including gene-targeted and functional studies, are required to confirm the causality of the genetic variants and their biological relevance in the development of vitiligo. PMID:26870082

AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

PubMed

Zhang, Qingrun; Long, Quan; Ott, Jurg

2014-06-01

Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term "glycosaminoglycan biosynthetic process" was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple evidences.

Genetics of common forms of heart failure: challenges and potential solutions.

PubMed

Rau, Christoph D; Lusis, Aldons J; Wang, Yibin

2015-05-01

In contrast to many other human diseases, the use of genome-wide association studies (GWAS) to identify genes for heart failure (HF) has had limited success. We will discuss the underlying challenges as well as potential new approaches to understanding the genetics of common forms of HF. Recent research using intermediate phenotypes, more detailed and quantitative stratification of HF symptoms, founder populations and novel animal models has begun to allow researchers to make headway toward explaining the genetics underlying HF using GWAS techniques. By expanding analyses of HF to improved clinical traits, additional HF classifications and innovative model systems, the intractability of human HF GWAS should be ameliorated significantly.

Genotyping of the Alzheimer's Disease Genome-Wide Association Study Index Single Nucleotide Polymorphisms in the Brains for Dementia Research Cohort.

PubMed

Brookes, Keeley J; McConnell, George; Williams, Kirsty; Chaudhury, Sultan; Madhan, Gaganjit; Patel, Tulsi; Turley, Christopher; Guetta-Baranes, Tamar; Bras, Jose; Guerreiro, Rita; Hardy, John; Francis, Paul T; Morgan, Kevin

2018-06-08

The Brains for Dementia Research project is a recently established longitudinal cohort which aims to provide brain tissue for research purposes from neuropathologically defined samples. Here we present the findings from our analysis on the 19 established GWAS index SNPs for Alzheimer's disease, in order to demonstrate if the BDR sample also displays association to these variants. A highly significant association of the APOEɛ4 allele was identified (p = 3.99×10-12). Association tests for the 19 GWAS SNPs found that although no SNPs survive multiple testing, nominal significant findings were detected and concordance with the Lambert et al. GWAS meta-analysis was observed.

Genome-wide association studies in preterm birth: implications for the practicing obstetrician-gynaecologist

PubMed Central

2013-01-01

Preterm birth has the highest mortality and morbidity of all pregnancy complications. The burden of preterm birth on public health worldwide is enormous, yet there are few effective means to prevent a preterm delivery. To date, much of its etiology is unexplained, but genetic predisposition is thought to play a major role. In the upcoming year, the international Preterm Birth Genome Project (PGP) consortium plans to publish a large genome wide association study in early preterm birth. Genome-wide association studies (GWAS) are designed to identify common genetic variants that influence health and disease. Despite the many challenges that are involved, GWAS can be an important discovery tool, revealing genetic variations that are associated with preterm birth. It is highly unlikely that findings of a GWAS can be directly translated into clinical practice in the short run. Nonetheless, it will help us to better understand the etiology of preterm birth and the GWAS results will generate new hypotheses for further research, thus enhancing our understanding of preterm birth and informing prevention efforts in the long run. PMID:23445776

Genome-wide association studies in preterm birth: implications for the practicing obstetrician-gynaecologist.

PubMed

Dolan, Siobhan M; Christiaens, Inge

2013-01-01

Preterm birth has the highest mortality and morbidity of all pregnancy complications. The burden of preterm birth on public health worldwide is enormous, yet there are few effective means to prevent a preterm delivery. To date, much of its etiology is unexplained, but genetic predisposition is thought to play a major role. In the upcoming year, the international Preterm Birth Genome Project (PGP) consortium plans to publish a large genome wide association study in early preterm birth. Genome-wide association studies (GWAS) are designed to identify common genetic variants that influence health and disease. Despite the many challenges that are involved, GWAS can be an important discovery tool, revealing genetic variations that are associated with preterm birth. It is highly unlikely that findings of a GWAS can be directly translated into clinical practice in the short run. Nonetheless, it will help us to better understand the etiology of preterm birth and the GWAS results will generate new hypotheses for further research, thus enhancing our understanding of preterm birth and informing prevention efforts in the long run.

Genetic variations and risk of placental abruption: A genome-wide association study and meta-analysis of genome-wide association studies.

PubMed

Workalemahu, Tsegaselassie; Enquobahrie, Daniel A; Gelaye, Bizu; Sanchez, Sixto E; Garcia, Pedro J; Tekola-Ayele, Fasil; Hajat, Anjum; Thornton, Timothy A; Ananth, Cande V; Williams, Michelle A

2018-06-01

Accumulating epidemiological evidence points to strong genetic susceptibility to placental abruption (PA). However, characterization of genes associated with PA remains incomplete. We conducted a genome-wide association study (GWAS) of PA and a meta-analysis of GWAS. Participants of the Placental Abruption Genetic Epidemiology (PAGE) study, a population based case-control study of PA conducted in Lima, Peru, were genotyped using the Illumina HumanCore-24 BeadChip platform. Genotypes were imputed using the 1000 genomes reference panel, and >4.9 million SNPs that passed quality control were analyzed. We performed a GWAS in PAGE participants (507 PA cases and 1090 controls) and a GWAS meta-analysis in 2512 participants (959 PA cases and 1553 controls) that included PAGE and the previously reported Peruvian Abruptio Placentae Epidemiology (PAPE) study. We fitted population stratification-adjusted logistic regression models and fixed-effects meta-analyses using inverse-variance weighting. Independent loci (linkage-disequilibrium<0.80) suggestively associated with PA (P-value<5e-5) included rs4148646 and rs2074311 in ABCC8, rs7249210, rs7250184, rs7249100 and rs10401828 in ZNF28, rs11133659 in CTNND2, and rs2074314 and rs35271178 near KCNJ11 in the PAGE GWAS. Similarly, independent loci suggestively associated with PA in the GWAS meta-analysis included rs76258369 near IRX1, and rs7094759 and rs12264492 in ADAM12. Functional analyses of these genes showed trophoblast-like cell interaction, as well as networks involved in endocrine system disorders, cardiovascular diseases, and cellular function. We identified several genetic loci and related functions that may play a role in PA risk. Understanding genetic factors underlying pathophysiological mechanisms of PA may facilitate prevention and early diagnostic efforts. Published by Elsevier Ltd.

Genome-wide association studies in pharmacogenetics research debate

PubMed Central

Bailey, Kent R; Cheng, Cheng

2016-01-01

Will genome-wide association studies (GWAS) ‘work’ for pharmacogenetics research? This question was the topic of a staged debate, with pro and con sides, aimed to bring out the strengths and weaknesses of GWAS for pharmacogenetics studies. After a full day of seminars at the Fifth Statistical Analysis Workshop of the Pharmacogenetics Research Network, the lively debate was held – appropriately – at Goonies Comedy Club in Rochester (MN, USA). The pro side emphasized that the many GWAS successes for identifying genetic variants associated with disease risk show that it works; that the current genotyping platforms are efficient, with good imputation methods to fill in missing data; that its global assessment is always a success even if no significant associations are detected; and that genetic effects are likely to be large because humans have not evolved in a drug-therapy environment. By contrast, the con side emphasized that we have limited knowledge of the complexity of the genome; limited clinical phenotypes compromise studies; the likely multifactorial nature of drug response clouding the small genetic effects; and limitations of sample size and replication studies in pharmacogenetic studies. Lively and insightful discussions emphasized further research efforts that might benefit GWAS in pharmacogenetics. PMID:20235786

A genome-wide association study of seed protein and oil content in soybean

PubMed Central

2014-01-01

Background Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content. Results A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r 2 ) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil. Conclusions This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s). PMID:24382143

A genome-wide association study of seed protein and oil content in soybean.

PubMed

Hwang, Eun-Young; Song, Qijian; Jia, Gaofeng; Specht, James E; Hyten, David L; Costa, Jose; Cregan, Perry B

2014-01-02

Association analysis is an alternative to conventional family-based methods to detect the location of gene(s) or quantitative trait loci (QTL) and provides relatively high resolution in terms of defining the genome position of a gene or QTL. Seed protein and oil concentration are quantitative traits which are determined by the interaction among many genes with small to moderate genetic effects and their interaction with the environment. In this study, a genome-wide association study (GWAS) was performed to identify quantitative trait loci (QTL) controlling seed protein and oil concentration in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content. A total of 55,159 single nucleotide polymorphisms (SNPs) were genotyped using various methods including Illumina Infinium and GoldenGate assays and 31,954 markers with minor allele frequency >0.10 were used to estimate linkage disequilibrium (LD) in heterochromatic and euchromatic regions. In euchromatic regions, the mean LD (r2) rapidly declined to 0.2 within 360 Kbp, whereas the mean LD declined to 0.2 at 9,600 Kbp in heterochromatic regions. The GWAS results identified 40 SNPs in 17 different genomic regions significantly associated with seed protein. Of these, the five SNPs with the highest associations and seven adjacent SNPs were located in the 27.6-30.0 Mbp region of Gm20. A major seed protein QTL has been previously mapped to the same location and potential candidate genes have recently been identified in this region. The GWAS results also detected 25 SNPs in 13 different genomic regions associated with seed oil. Of these markers, seven SNPs had a significant association with both protein and oil. This research indicated that GWAS not only identified most of the previously reported QTL controlling seed protein and oil, but also resulted in narrower genomic regions than the regions reported as containing these QTL. The narrower GWAS-defined genome regions will allow more precise marker-assisted allele selection and will expedite positional cloning of the causal gene(s).

Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice

PubMed Central

Yang, Wanneng; Guo, Zilong; Huang, Chenglong; Duan, Lingfeng; Chen, Guoxing; Jiang, Ni; Fang, Wei; Feng, Hui; Xie, Weibo; Lian, Xingming; Wang, Gongwei; Luo, Qingming; Zhang, Qifa; Liu, Qian; Xiong, Lizhong

2014-01-01

Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits. PMID:25295980

PExFInS: An Integrative Post-GWAS Explorer for Functional Indels and SNPs

PubMed Central

Cheng, Zhongshan; Chu, Hin; Fan, Yanhui; Li, Cun; Song, You-Qiang; Zhou, Jie; Yuen, Kwok-Yung

2015-01-01

Expression quantitative trait loci (eQTLs) mapping and linkage disequilibrium (LD) analysis have been widely employed to interpret findings of genome-wide association studies (GWAS). With the availability of deep sequencing data of 423 lymphoblastoid cell lines (LCLs) from six global populations and the microarray expression data, we performed eQTL analysis, identified more than 228 K SNP cis-eQTLs and 21 K indel cis-eQTLs and generated a LCL cis-eQTL database. We demonstrate that the percentages of population-shared and population-specific cis-eQTLs are comparable; while indel cis-eQTLs in the population-specific subsection make more contribution to gene expression variations than those in the population-shared subsection. We found cis-eQTLs, especially the population-shared cis-eQTLs are significantly enriched toward transcription start site. Moreover, the National Human Genome Research Institute cataloged GWAS SNPs are enriched for LCL cis-eQTLs. Specifically, 32.8% GWAS SNPs are LCL cis-eQTLs, among which 12.5% can be tagged by indel cis-eQTLs, suggesting the fundamental contribution of indel cis-eQTLs to GWAS association signals. To search for functional indels and SNPs tagging GWAS SNPs, a pipeline Post-GWAS Explorer for Functional Indels and SNPs (PExFInS) has been developed, integrating LD analysis, functional annotation from public databases, cis-eQTL mapping with our LCL cis-eQTL database and other published cis-eQTL datasets. PMID:26612672

Recapitulation of genome-wide association studies on pulse pressure and mean arterial pressure in the Korean population.

PubMed

Hong, Kyung-Won; Min, Haesook; Heo, Byeong-Mun; Joo, Seong Eun; Kim, Sung Soo; Kim, Yeonjung

2012-06-01

Increased pulse pressure (PP) and decreased mean arterial pressure (MAP) are strong prognostic predictors of adverse cardiovascular events. Recently, the International Consortium for Blood Pressure Genome-Wide Association Studies (ICBP-GWAS) reported eight loci that influenced PP and MAP. The ICBP-GWAS examined 51 cohorts--comprising 122 671 individuals of European ancestry--and identified eight SNPs: five that governed PP and three that controlled MAP. Six of these loci were novel. To replicate these newly identified loci and examine genetic architecture of PP and MAP between European and Asian populations, we conducted a meta-analysis of the eight SNPs combining data from ICBP and general population-based Korean cohorts. Two SNPs (rs13002573 (FIGN) and rs871606 (CHIC2)) for PP and two SNPs (rs1446468 (FIGN) and rs319690 (MAP4)) for MAP were replicated in Koreans. Although our GWAS only found moderate association, we believe that the findings promote us to propose that a similar genetic architecture governs PP and MAP in Asians and Europeans. However, further studies will be needed to confirm the possibility using other Asian population.

Multi-ethnic genome-wide association study identifies novel locus for type 2 diabetes susceptibility

PubMed Central

Cook, James P; Morris, Andrew P

2016-01-01

Genome-wide association studies (GWAS) have traditionally been undertaken in homogeneous populations from the same ancestry group. However, with the increasing availability of GWAS in large-scale multi-ethnic cohorts, we have evaluated a framework for detecting association of genetic variants with complex traits, allowing for population structure, and developed a powerful test of heterogeneity in allelic effects between ancestry groups. We have applied the methodology to identify and characterise loci associated with susceptibility to type 2 diabetes (T2D) using GWAS data from the Resource for Genetic Epidemiology on Adult Health and Aging, a large multi-ethnic population-based cohort, created for investigating the genetic and environmental basis of age-related diseases. We identified a novel locus for T2D susceptibility at genome-wide significance (P<5 × 10−8) that maps to TOMM40-APOE, a region previously implicated in lipid metabolism and Alzheimer's disease. We have also confirmed previous reports that single-nucleotide polymorphisms at the TCF7L2 locus demonstrate the greatest extent of heterogeneity in allelic effects between ethnic groups, with the lowest risk observed in populations of East Asian ancestry. PMID:27189021

Pleiotropic analysis of cancer risk loci on esophageal adenocarcinoma risk

PubMed Central

Lee, Eunjung; Stram, Daniel O.; Ek, Weronica E.; Onstad, Lynn E; MacGregor, Stuart; Gharahkhani, Puya; Ye, Weimin; Lagergren, Jesper; Shaheen, Nicholas J.; Murray, Liam J.; Hardie, Laura J; Gammon, Marilie D.; Chow, Wong-Ho; Risch, Harvey A.; Corley, Douglas A.; Levine, David M; Whiteman, David C.; Bernstein, Leslie; Bird, Nigel C.; Vaughan, Thomas L.; Wu, Anna H.

2015-01-01

Background Several cancer-associated loci identified from genome-wide association studies (GWAS) have been associated with risks of multiple cancer sites, suggesting pleiotropic effects. We investigated whether GWAS-identified risk variants for other common cancers are associated with risk of esophageal adenocarcinoma (EA) or its precursor, Barrett's esophagus (BE). Methods We examined the associations between risks of EA and BE and 387 single nucleotide polymorphisms (SNPs) that have been associated with risks of other cancers, by using genotype imputation data on 2,163 control participants and 3,885 (1,501 EA and 2,384 BE) case patients from the Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study, and investigated effect modification by smoking history, body mass index (BMI), and reflux/heartburn. Results After correcting for multiple testing, none of the tested 387 SNPs were statistically significantly associated with risk of EA or BE. No evidence of effect modification by smoking, BMI, or reflux/heartburn was observed. Conclusions Genetic risk variants for common cancers identified from GWAS appear not to be associated with risks of EA or BE. Impact To our knowledge, this is the first investigation of pleiotropic genetic associations with risks of EA and BE. PMID:26364162

Privacy-Preserving Data Exploration in Genome-Wide Association Studies.

PubMed

Johnson, Aaron; Shmatikov, Vitaly

2013-08-01

Genome-wide association studies (GWAS) have become a popular method for analyzing sets of DNA sequences in order to discover the genetic basis of disease. Unfortunately, statistics published as the result of GWAS can be used to identify individuals participating in the study. To prevent privacy breaches, even previously published results have been removed from public databases, impeding researchers' access to the data and hindering collaborative research. Existing techniques for privacy-preserving GWAS focus on answering specific questions, such as correlations between a given pair of SNPs (DNA sequence variations). This does not fit the typical GWAS process, where the analyst may not know in advance which SNPs to consider and which statistical tests to use, how many SNPs are significant for a given dataset, etc. We present a set of practical, privacy-preserving data mining algorithms for GWAS datasets. Our framework supports exploratory data analysis, where the analyst does not know a priori how many and which SNPs to consider. We develop privacy-preserving algorithms for computing the number and location of SNPs that are significantly associated with the disease, the significance of any statistical test between a given SNP and the disease, any measure of correlation between SNPs, and the block structure of correlations. We evaluate our algorithms on real-world datasets and demonstrate that they produce significantly more accurate results than prior techniques while guaranteeing differential privacy.

Genome-Wide Association Study Identifies Risk Variants for Lichen Planus in Patients With Hepatitis C Virus Infection.

PubMed

Nagao, Yumiko; Nishida, Nao; Toyo-Oka, Licht; Kawaguchi, Atsushi; Amoroso, Antonio; Carrozzo, Marco; Sata, Michio; Mizokami, Masashi; Tokunaga, Katsushi; Tanaka, Yasuhito

2017-06-01

There is a close relationship between hepatitis C virus (HCV) infection and lichen planus, a chronic inflammatory mucocutaneous disease. We performed a genome-wide association study (GWAS) to identify genetic variants associated with HCV-related lichen planus. We conducted a GWAS of 261 patients with HCV infection treated at a tertiary medical center in Japan from October 2007 through January 2013; a total of 71 had lichen planus and 190 had normal oral mucosa. We validated our findings in a GWAS of 38 patients with HCV-associated lichen planus and 7 HCV-infected patients with normal oral mucosa treated at a medical center in Italy. Single-nucleotide polymorphisms in NRP2 (rs884000) and IGFBP4 (rs538399) were associated with risk of HCV-associated lichen planus (P < 1 × 10 -4 ). We also found an association between a single-nucleotide polymorphism in the HLA-DR/DQ genes (rs9461799) and susceptibility to HCV-associated lichen planus. The odds ratios for the minor alleles of rs884000, rs538399, and rs9461799 were 3.25 (95% confidence interval, 1.95-5.41), 0.40 (95% confidence interval, 0.25-0.63), and 2.15 (95% confidence interval, 1.41-3.28), respectively. In a GWAS of Japanese patients with HCV infection, we replicated associations between previously reported polymorphisms in HLA class II genes and risk for lichen planus. We also identified single-nucleotide polymorphisms in NRP2 and IGFBP4 loci that increase and reduce risk of lichen planus, respectively. These genetic variants might be used to identify patients with HCV infection who are at risk for lichen planus. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Discovery and characterization of two new stem rust resistance genes in Aegilops sharonensis.

PubMed

Yu, Guotai; Champouret, Nicolas; Steuernagel, Burkhard; Olivera, Pablo D; Simmons, Jamie; Williams, Cole; Johnson, Ryan; Moscou, Matthew J; Hernández-Pinzón, Inmaculada; Green, Phon; Sela, Hanan; Millet, Eitan; Jones, Jonathan D G; Ward, Eric R; Steffenson, Brian J; Wulff, Brande B H

2017-06-01

We identified two novel wheat stem rust resistance genes, Sr-1644-1Sh and Sr-1644-5Sh in Aegilops sharonensis that are effective against widely virulent African races of the wheat stem rust pathogen. Stem rust is one of the most important diseases of wheat in the world. When single stem rust resistance (Sr) genes are deployed in wheat, they are often rapidly overcome by the pathogen. To this end, we initiated a search for novel sources of resistance in diverse wheat relatives and identified the wild goatgrass species Aegilops sharonesis (Sharon goatgrass) as a rich reservoir of resistance to wheat stem rust. The objectives of this study were to discover and map novel Sr genes in Ae. sharonensis and to explore the possibility of identifying new Sr genes by genome-wide association study (GWAS). We developed two biparental populations between resistant and susceptible accessions of Ae. sharonensis and performed QTL and linkage analysis. In an F 6 recombinant inbred line and an F 2 population, two genes were identified that mapped to the short arm of chromosome 1S sh , designated as Sr-1644-1Sh, and the long arm of chromosome 5S sh , designated as Sr-1644-5Sh. The gene Sr-1644-1Sh confers a high level of resistance to race TTKSK (a member of the Ug99 race group), while the gene Sr-1644-5Sh conditions strong resistance to TRTTF, another widely virulent race found in Yemen. Additionally, GWAS was conducted on 125 diverse Ae. sharonensis accessions for stem rust resistance. The gene Sr-1644-1Sh was detected by GWAS, while Sr-1644-5Sh was not detected, indicating that the effectiveness of GWAS might be affected by marker density, population structure, low allele frequency and other factors.

Evaluating the transferability of 15 European-derived fasting plasma glucose SNPs in Mexican children and adolescents

PubMed Central

Langlois, Christine; Abadi, Arkan; Peralta-Romero, Jesus; Alyass, Akram; Suarez, Fernando; Gomez-Zamudio, Jaime; Burguete-Garcia, Ana I.; Yazdi, Fereshteh T.; Cruz, Miguel; Meyre, David

2016-01-01

Genome wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) that are associated with fasting plasma glucose (FPG) in adult European populations. The contribution of these SNPs to FPG in non-Europeans and children is unclear. We studied the association of 15 GWAS SNPs and a genotype score (GS) with FPG and 7 metabolic traits in 1,421 Mexican children and adolescents from Mexico City. Genotyping of the 15 SNPs was performed using TaqMan Open Array. We used multivariate linear regression models adjusted for age, sex, body mass index standard deviation score, and recruitment center. We identified significant associations between 3 SNPs (G6PC2 (rs560887), GCKR (rs1260326), MTNR1B (rs10830963)), the GS and FPG level. The FPG risk alleles of 11 out of the 15 SNPs (73.3%) displayed significant or non-significant beta values for FPG directionally consistent with those reported in adult European GWAS. The risk allele frequencies for 11 of 15 (73.3%) SNPs differed significantly in Mexican children and adolescents compared to European adults from the 1000G Project, but no significant enrichment in FPG risk alleles was observed in the Mexican population. Our data support a partial transferability of European GWAS FPG association signals in children and adolescents from the admixed Mexican population. PMID:27782183

Multi-trait analysis of genome-wide association summary statistics using MTAG.

PubMed

Turley, Patrick; Walters, Raymond K; Maghzian, Omeed; Okbay, Aysu; Lee, James J; Fontana, Mark Alan; Nguyen-Viet, Tuan Anh; Wedow, Robbee; Zacher, Meghan; Furlotte, Nicholas A; Magnusson, Patrik; Oskarsson, Sven; Johannesson, Magnus; Visscher, Peter M; Laibson, David; Cesarini, David; Neale, Benjamin M; Benjamin, Daniel J

2018-02-01

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff  = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.

Meta-GWAS and Meta-Analysis of Exome Array Studies Do Not Reveal Genetic Determinants of Serum Hepcidin

PubMed Central

Galesloot, Tessel E.; van Dijk, Freerk; Geurts-Moespot, Anneke J.; Girelli, Domenico; Kiemeney, Lambertus A. L. M.; Sweep, Fred C. G. J.; Swertz, Morris A.; van der Meer, Peter; Camaschella, Clara; Toniolo, Daniela; Vermeulen, Sita H.; van der Harst, Pim; Swinkels, Dorine W.

2016-01-01

Serum hepcidin concentration is regulated by iron status, inflammation, erythropoiesis and numerous other factors, but underlying processes are incompletely understood. We studied the association of common and rare single nucleotide variants (SNVs) with serum hepcidin in one Italian study and two large Dutch population-based studies. We genotyped common SNVs with genome-wide association study (GWAS) arrays and subsequently performed imputation using the 1000 Genomes reference panel. Cohort-specific GWAS were performed for log-transformed serum hepcidin, adjusted for age and gender, and results were combined in a fixed-effects meta-analysis (total N 6,096). Six top SNVs (p<5x10-6) were genotyped in 3,821 additional samples, but associations were not replicated. Furthermore, we meta-analyzed cohort-specific exome array association results of rare SNVs with serum hepcidin that were available for two of the three cohorts (total N 3,226), but no exome-wide significant signal (p<1.4x10-6) was identified. Gene-based meta-analyses revealed 19 genes that showed significant association with hepcidin. Our results suggest the absence of common SNVs and rare exonic SNVs explaining a large proportion of phenotypic variation in serum hepcidin. We recommend extension of our study once additional substantial cohorts with hepcidin measurements, GWAS and/or exome array data become available in order to increase power to identify variants that explain a smaller proportion of hepcidin variation. In addition, we encourage follow-up of the potentially interesting genes that resulted from the gene-based analysis of low-frequency and rare variants. PMID:27846281

A Genome-wide Association Analysis of a Broad Psychosis Phenotype Identifies Three Loci for Further Investigation

PubMed Central

2014-01-01

Background Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. Methods 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). Results No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium’s panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10–14) and explained approximately 2% of the phenotypic variance. Conclusions Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data. PMID:23871474

A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation.

PubMed

Bramon, Elvira; Pirinen, Matti; Strange, Amy; Lin, Kuang; Freeman, Colin; Bellenguez, Céline; Su, Zhan; Band, Gavin; Pearson, Richard; Vukcevic, Damjan; Langford, Cordelia; Deloukas, Panos; Hunt, Sarah; Gray, Emma; Dronov, Serge; Potter, Simon C; Tashakkori-Ghanbaria, Avazeh; Edkins, Sarah; Bumpstead, Suzannah J; Arranz, Maria J; Bakker, Steven; Bender, Stephan; Bruggeman, Richard; Cahn, Wiepke; Chandler, David; Collier, David A; Crespo-Facorro, Benedicto; Dazzan, Paola; de Haan, Lieuwe; Di Forti, Marta; Dragović, Milan; Giegling, Ina; Hall, Jeremy; Iyegbe, Conrad; Jablensky, Assen; Kahn, René S; Kalaydjieva, Luba; Kravariti, Eugenia; Lawrie, Stephen; Linszen, Don H; Mata, Ignacio; McDonald, Colm; McIntosh, Andrew; Myin-Germeys, Inez; Ophoff, Roel A; Pariante, Carmine M; Paunio, Tiina; Picchioni, Marco; Ripke, Stephan; Rujescu, Dan; Sauer, Heinrich; Shaikh, Madiha; Sussmann, Jessika; Suvisaari, Jaana; Tosato, Sarah; Toulopoulou, Timothea; Van Os, Jim; Walshe, Muriel; Weisbrod, Matthias; Whalley, Heather; Wiersma, Durk; Blackwell, Jenefer M; Brown, Matthew A; Casas, Juan P; Corvin, Aiden; Duncanson, Audrey; Jankowski, Janusz A Z; Markus, Hugh S; Mathew, Christopher G; Palmer, Colin N A; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J; Trembath, Richard C; Wood, Nicholas W; Barroso, Ines; Peltonen, Leena; Lewis, Cathryn M; Murray, Robin M; Donnelly, Peter; Powell, John; Spencer, Chris C A

2014-03-01

Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium's panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10(-14)) and explained approximately 2% of the phenotypic variance. Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium.

PubMed

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.

Gene- and pathway-based association tests for multiple traits with GWAS summary statistics.

PubMed

Kwak, Il-Youp; Pan, Wei

2017-01-01

To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. The methods are implemented in R package aSPU, freely and publicly available at: https://cran.r-project.org/web/packages/aSPU/ CONTACT: weip@biostat.umn.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.

A GWAS meta-analysis from 5 population-based cohorts implicates ion channel genes in the pathogenesis of irritable bowel syndrome.

PubMed

Bonfiglio, F; Henström, M; Nag, A; Hadizadeh, F; Zheng, T; Cenit, M C; Tigchelaar, E; Williams, F; Reznichenko, A; Ek, W E; Rivera, N V; Homuth, G; Aghdassi, A A; Kacprowski, T; Männikkö, M; Karhunen, V; Bujanda, L; Rafter, J; Wijmenga, C; Ronkainen, J; Hysi, P; Zhernakova, A; D'Amato, M

2018-04-19

Irritable bowel syndrome (IBS) shows genetic predisposition, however, large-scale, powered gene mapping studies are lacking. We sought to exploit existing genetic (genotype) and epidemiological (questionnaire) data from a series of population-based cohorts for IBS genome-wide association studies (GWAS) and their meta-analysis. Based on questionnaire data compatible with Rome III Criteria, we identified a total of 1335 IBS cases and 9768 asymptomatic individuals from 5 independent European genotyped cohorts. Individual GWAS were carried out with sex-adjusted logistic regression under an additive model, followed by meta-analysis using the inverse variance method. Functional annotation of significant results was obtained via a computational pipeline exploiting ontology and interaction networks, and tissue-specific and gene set enrichment analyses. Suggestive GWAS signals (P ≤ 5.0 × 10 -6 ) were detected for 7 genomic regions, harboring 64 gene candidates to affect IBS risk via functional or expression changes. Functional annotation of this gene set convincingly (best FDR-corrected P = 3.1 × 10 -10 ) highlighted regulation of ion channel activity as the most plausible pathway affecting IBS risk. Our results confirm the feasibility of population-based studies for gene-discovery efforts in IBS, identify risk genes and loci to be prioritized in independent follow-ups, and pinpoint ion channels as important players and potential therapeutic targets warranting further investigation. © 2018 John Wiley & Sons Ltd.

Mapping of Gene Expression Reveals CYP27A1 as a Susceptibility Gene for Sporadic ALS

PubMed Central

van Rheenen, Wouter; Franke, Lude; Jansen, Ritsert C.; van Es, Michael A.; van Vught, Paul W. J.; Blauw, Hylke M.; Groen, Ewout J. N.; Horvath, Steve; Estrada, Karol; Rivadeneira, Fernando; Hofman, Albert; Uitterlinden, Andre G.; Robberecht, Wim; Andersen, Peter M.; Melki, Judith; Meininger, Vincent; Hardiman, Orla; Landers, John E.; Brown, Robert H.; Shatunov, Aleksey; Shaw, Christopher E.; Leigh, P. Nigel; Al-Chalabi, Ammar; Ophoff, Roel A.

2012-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive, neurodegenerative disease characterized by loss of upper and lower motor neurons. ALS is considered to be a complex trait and genome-wide association studies (GWAS) have implicated a few susceptibility loci. However, many more causal loci remain to be discovered. Since it has been shown that genetic variants associated with complex traits are more likely to be eQTLs than frequency-matched variants from GWAS platforms, we conducted a two-stage genome-wide screening for eQTLs associated with ALS. In addition, we applied an eQTL analysis to finemap association loci. Expression profiles using peripheral blood of 323 sporadic ALS patients and 413 controls were mapped to genome-wide genotyping data. Subsequently, data from a two-stage GWAS (3,568 patients and 10,163 controls) were used to prioritize eQTLs identified in the first stage (162 ALS, 207 controls). These prioritized eQTLs were carried forward to the second sample with both gene-expression and genotyping data (161 ALS, 206 controls). Replicated eQTL SNPs were then tested for association in the second-stage GWAS data to find SNPs associated with disease, that survived correction for multiple testing. We thus identified twelve cis eQTLs with nominally significant associations in the second-stage GWAS data. Eight SNP-transcript pairs of highest significance (lowest p = 1.27×10−51) withstood multiple-testing correction in the second stage and modulated CYP27A1 gene expression. Additionally, we show that C9orf72 appears to be the only gene in the 9p21.2 locus that is regulated in cis, showing the potential of this approach in identifying causative genes in association loci in ALS. This study has identified candidate genes for sporadic ALS, most notably CYP27A1. Mutations in CYP27A1 are causal to cerebrotendinous xanthomatosis which can present as a clinical mimic of ALS with progressive upper motor neuron loss, making it a plausible susceptibility gene for ALS. PMID:22509407

A genome-wide association study identifies risk loci to equine recurrent uveitis in German warmblood horses.

PubMed

Kulbrock, Maike; Lehner, Stefanie; Metzger, Julia; Ohnesorge, Bernhard; Distl, Ottmar

2013-01-01

Equine recurrent uveitis (ERU) is a common eye disease affecting up to 3-15% of the horse population. A genome-wide association study (GWAS) using the Illumina equine SNP50 bead chip was performed to identify loci conferring risk to ERU. The sample included a total of 144 German warmblood horses. A GWAS showed a significant single nucleotide polymorphism (SNP) on horse chromosome (ECA) 20 at 49.3 Mb, with IL-17A and IL-17F being the closest genes. This locus explained a fraction of 23% of the phenotypic variance for ERU. A GWAS taking into account the severity of ERU, revealed a SNP on ECA18 nearby to the crystalline gene cluster CRYGA-CRYGF. For both genomic regions on ECA18 and 20, significantly associated haplotypes containing the genome-wide significant SNPs could be demonstrated. In conclusion, our results are indicative for a genetic component regulating the possible critical role of IL-17A and IL-17F in the pathogenesis of ERU. The associated SNP on ECA18 may be indicative for cataract formation in the course of ERU.

Convergent evidence from systematic analysis of GWAS revealed genetic basis of esophageal cancer.

PubMed

Gao, Xue-Xin; Gao, Lei; Wang, Jiu-Qiang; Qu, Su-Su; Qu, Yue; Sun, Hong-Lei; Liu, Si-Dang; Shang, Ying-Li

2016-07-12

Recent genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with risk of esophageal cancer (EC). However, investigation of genetic basis from the perspective of systematic biology and integrative genomics remains scarce.In this study, we explored genetic basis of EC based on GWAS data and implemented a series of bioinformatics methods including functional annotation, expression quantitative trait loci (eQTL) analysis, pathway enrichment analysis and pathway grouped network analysis.Two hundred and thirteen risk SNPs were identified, in which 44 SNPs were found to have significantly differential gene expression in esophageal tissues by eQTL analysis. By pathway enrichment analysis, 170 risk genes mapped by risk SNPs were enriched into 38 significant GO terms and 17 significant KEGG pathways, which were significantly grouped into 9 sub-networks by pathway grouped network analysis. The 9 groups of interconnected pathways were mainly involved with muscle cell proliferation, cellular response to interleukin-6, cell adhesion molecules, and ethanol oxidation, which might participate in the development of EC.Our findings provide genetic evidence and new insight for exploring the molecular mechanisms of EC.

Use of modern tomato breeding germplasm for deciphering the genetic control of agronomical traits by Genome Wide Association study.

PubMed

Bauchet, Guillaume; Grenier, Stéphane; Samson, Nicolas; Bonnet, Julien; Grivet, Laurent; Causse, Mathilde

2017-05-01

A panel of 300 tomato accessions including breeding materials was built and characterized with >11,000 SNP. A population structure in six subgroups was identified. Strong heterogeneity in linkage disequilibrium and recombination landscape among groups and chromosomes was shown. GWAS identified several associations for fruit weight, earliness and plant growth. Genome-wide association studies (GWAS) have become a method of choice in quantitative trait dissection. First limited to highly polymorphic and outcrossing species, it is now applied in horticultural crops, notably in tomato. Until now GWAS in tomato has been performed on panels of heirloom and wild accessions. Using modern breeding materials would be of direct interest for breeding purpose. To implement GWAS on a large panel of 300 tomato accessions including 168 breeding lines, this study assessed the genetic diversity and linkage disequilibrium decay and revealed the population structure and performed GWA experiment. Genetic diversity and population structure analyses were based on molecular markers (>11,000 SNP) covering the whole genome. Six genetic subgroups were revealed and associated to traits of agronomical interest, such as fruit weight and disease resistance. Estimates of linkage disequilibrium highlighted the heterogeneity of its decay among genetic subgroups. Haplotype definition allowed a fine characterization of the groups and their recombination landscape revealing the patterns of admixture along the genome. Selection footprints showed results in congruence with introgressions. Taken together, all these elements refined our knowledge of the genetic material included in this panel and allowed the identification of several associations for fruit weight, plant growth and earliness, deciphering the genetic architecture of these complex traits and identifying several new loci useful for tomato breeding.

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

PubMed

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

A pleiotropy-informed Bayesian false discovery rate adapted to a shared control design finds new disease associations from GWAS summary statistics.

PubMed

Liley, James; Wallace, Chris

2015-02-01

Genome-wide association studies (GWAS) have been successful in identifying single nucleotide polymorphisms (SNPs) associated with many traits and diseases. However, at existing sample sizes, these variants explain only part of the estimated heritability. Leverage of GWAS results from related phenotypes may improve detection without the need for larger datasets. The Bayesian conditional false discovery rate (cFDR) constitutes an upper bound on the expected false discovery rate (FDR) across a set of SNPs whose p values for two diseases are both less than two disease-specific thresholds. Calculation of the cFDR requires only summary statistics and have several advantages over traditional GWAS analysis. However, existing methods require distinct control samples between studies. Here, we extend the technique to allow for some or all controls to be shared, increasing applicability. Several different SNP sets can be defined with the same cFDR value, and we show that the expected FDR across the union of these sets may exceed expected FDR in any single set. We describe a procedure to establish an upper bound for the expected FDR among the union of such sets of SNPs. We apply our technique to pairwise analysis of p values from ten autoimmune diseases with variable sharing of controls, enabling discovery of 59 SNP-disease associations which do not reach GWAS significance after genomic control in individual datasets. Most of the SNPs we highlight have previously been confirmed using replication studies or larger GWAS, a useful validation of our technique; we report eight SNP-disease associations across five diseases not previously declared. Our technique extends and strengthens the previous algorithm, and establishes robust limits on the expected FDR. This approach can improve SNP detection in GWAS, and give insight into shared aetiology between phenotypically related conditions.

Intergenic disease-associated regions are abundant in novel transcripts.

PubMed

Bartonicek, N; Clark, M B; Quek, X C; Torpy, J R; Pritchard, A L; Maag, J L V; Gloss, B S; Crawford, J; Taft, R J; Hayward, N K; Montgomery, G W; Mattick, J S; Mercer, T R; Dinger, M E

2017-12-28

Genotyping of large populations through genome-wide association studies (GWAS) has successfully identified many genomic variants associated with traits or disease risk. Unexpectedly, a large proportion of GWAS single nucleotide polymorphisms (SNPs) and associated haplotype blocks are in intronic and intergenic regions, hindering their functional evaluation. While some of these risk-susceptibility regions encompass cis-regulatory sites, their transcriptional potential has never been systematically explored. To detect rare tissue-specific expression, we employed the transcript-enrichment method CaptureSeq on 21 human tissues to identify 1775 multi-exonic transcripts from 561 intronic and intergenic haploblocks associated with 392 traits and diseases, covering 73.9 Mb (2.2%) of the human genome. We show that a large proportion (85%) of disease-associated haploblocks express novel multi-exonic non-coding transcripts that are tissue-specific and enriched for GWAS SNPs as well as epigenetic markers of active transcription and enhancer activity. Similarly, we captured transcriptomes from 13 melanomas, targeting nine melanoma-associated haploblocks, and characterized 31 novel melanoma-specific transcripts that include fusion proteins, novel exons and non-coding RNAs, one-third of which showed allelically imbalanced expression. This resource of previously unreported transcripts in disease-associated regions ( http://gwas-captureseq.dingerlab.org ) should provide an important starting point for the translational community in search of novel biomarkers, disease mechanisms, and drug targets.

Genomic Prediction and Association Mapping of Curd-Related Traits in Gene Bank Accessions of Cauliflower.

PubMed

Thorwarth, Patrick; Yousef, Eltohamy A A; Schmid, Karl J

2018-02-02

Genetic resources are an important source of genetic variation for plant breeding. Genome-wide association studies (GWAS) and genomic prediction greatly facilitate the analysis and utilization of useful genetic diversity for improving complex phenotypic traits in crop plants. We explored the potential of GWAS and genomic prediction for improving curd-related traits in cauliflower ( Brassica oleracea var. botrytis ) by combining 174 randomly selected cauliflower gene bank accessions from two different gene banks. The collection was genotyped with genotyping-by-sequencing (GBS) and phenotyped for six curd-related traits at two locations and three growing seasons. A GWAS analysis based on 120,693 single-nucleotide polymorphisms identified a total of 24 significant associations for curd-related traits. The potential for genomic prediction was assessed with a genomic best linear unbiased prediction model and BayesB. Prediction abilities ranged from 0.10 to 0.66 for different traits and did not differ between prediction methods. Imputation of missing genotypes only slightly improved prediction ability. Our results demonstrate that GWAS and genomic prediction in combination with GBS and phenotyping of highly heritable traits can be used to identify useful quantitative trait loci and genotypes among genetically diverse gene bank material for subsequent utilization as genetic resources in cauliflower breeding. Copyright © 2018 Thorwarth et al.

GENOME-WIDE GENETIC INTERACTION ANALYSIS OF GLAUCOMA USING EXPERT KNOWLEDGE DERIVED FROM HUMAN PHENOTYPE NETWORKS

PubMed Central

HU, TING; DARABOS, CHRISTIAN; CRICCO, MARIA E.; KONG, EMILY; MOORE, JASON H.

2014-01-01

The large volume of GWAS data poses great computational challenges for analyzing genetic interactions associated with common human diseases. We propose a computational framework for characterizing epistatic interactions among large sets of genetic attributes in GWAS data. We build the human phenotype network (HPN) and focus around a disease of interest. In this study, we use the GLAUGEN glaucoma GWAS dataset and apply the HPN as a biological knowledge-based filter to prioritize genetic variants. Then, we use the statistical epistasis network (SEN) to identify a significant connected network of pairwise epistatic interactions among the prioritized SNPs. These clearly highlight the complex genetic basis of glaucoma. Furthermore, we identify key SNPs by quantifying structural network characteristics. Through functional annotation of these key SNPs using Biofilter, a software accessing multiple publicly available human genetic data sources, we find supporting biomedical evidences linking glaucoma to an array of genetic diseases, proving our concept. We conclude by suggesting hypotheses for a better understanding of the disease. PMID:25592582

Meta-analysis identifies six new susceptibility loci for atrial fibrillation

PubMed Central

Ellinor, Patrick T; Lunetta, Kathryn L; Albert, Christine M; Glazer, Nicole L; Ritchie, Marylyn D; Smith, Albert V; Arking, Dan E; Müller-Nurasyid, Martina; Krijthe, Bouwe P; Lubitz, Steven A; Bis, Joshua C; Chung, Mina K; Dörr, Marcus; Ozaki, Kouichi; Roberts, Jason D; Smith, J Gustav; Pfeufer, Arne; Sinner, Moritz F; Lohman, Kurt; Ding, Jingzhong; Smith, Nicholas L; Smith, Jonathan D; Rienstra, Michiel; Rice, Kenneth M; Van Wagoner, David R; Magnani, Jared W; Wakili, Reza; Clauss, Sebastian; Rotter, Jerome I; Steinbeck, Gerhard; Launer, Lenore J; Davies, Robert W; Borkovich, Matthew; Harris, Tamara B; Lin, Honghuang; Völker, Uwe; Völzke, Henry; Milan, David J; Hofman, Albert; Boerwinkle, Eric; Chen, Lin Y; Soliman, Elsayed Z; Voight, Benjamin F; Li, Guo; Chakravarti, Aravinda; Kubo, Michiaki; Tedrow, Usha B; Rose, Lynda M; Ridker, Paul M; Conen, David; Tsunoda, Tatsuhiko; Furukawa, Tetsushi; Sotoodehnia, Nona; Xu, Siyan; Kamatani, Naoyuki; Levy, Daniel; Nakamura, Yusuke; Parvez, Babar; Mahida, Saagar; Furie, Karen L; Rosand, Jonathan; Muhammad, Raafia; Psaty, Bruce M; Meitinger, Thomas; Perz, Siegfried; Wichmann, H-Erich; Witteman, Jacqueline C M; Kao, W H Linda; Kathiresan, Sekar; Roden, Dan M; Uitterlinden, Andre G; Rivadeneira, Fernando; McKnight, Barbara; Sjögren, Marketa; Newman, Anne B; Liu, Yongmei; Gollob, Michael H; Melander, Olle; Tanaka, Toshihiro; Ch Stricker, Bruno H; Felix, Stephan B; Alonso, Alvaro; Darbar, Dawood; Barnard, John; Chasman, Daniel I; Heckbert, Susan R; Benjamin, Emelia J; Gudnason, Vilmundur; Kääb, Stefan

2012-01-01

Atrial fibrillation is a highly prevalent arrhythmia and a major risk factor for stroke, heart failure and death1. We conducted a genome-wide association study (GWAS) in individuals of European ancestry, including 6,707 with and 52,426 without atrial fibrillation. Six new atrial fibrillation susceptibility loci were identified and replicated in an additional sample of individuals of European ancestry, including 5,381 subjects with and 1 0,030 subjects without atrial fibrillation (P < 5 × 10−8). Four of the loci identified in Europeans were further replicated in silico in a GWAS of Japanese individuals, including 843 individuals with and 3,350 individuals without atrial fibrillation. The identified loci implicate candidate genes that encode transcription factors related to cardiopulmonary development, cardiac-expressed ion channels and cell signaling molecules. PMID:22544366

Using Semantic Web Technologies for Cohort Identification from Electronic Health Records for Clinical Research

PubMed Central

Pathak, Jyotishman; Kiefer, Richard C.; Chute, Christopher G.

2012-01-01

The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. One of the key requirements to perform GWAS is the identification of subject cohorts with accurate classification of disease phenotypes. In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical data stored in electronic health records (EHRs) to accurately identify subjects with specific diseases for inclusion in cohort studies. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR data and enabling federated querying and inferencing via standardized Web protocols for identifying subjects with Diabetes Mellitus. Our study highlights the potential of using Web-scale data federation approaches to execute complex queries. PMID:22779040

Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise

PubMed Central

Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M.

2014-01-01

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants. PMID:25409314

Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.

PubMed

Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M

2014-01-01

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical "noise" that warrant further analysis for causal variants.

Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

PubMed Central

Duell, Eric J.; Yu, Kai; Risch, Harvey A.; Olson, Sara H.; Kooperberg, Charles; Wolpin, Brian M.; Jiao, Li; Dong, Xiaoqun; Wheeler, Bill; Arslan, Alan A.; Bueno-de-Mesquita, H. Bas; Fuchs, Charles S.; Gallinger, Steven; Gross, Myron; Hartge, Patricia; Hoover, Robert N.; Holly, Elizabeth A.; Jacobs, Eric J.; Klein, Alison P.; LaCroix, Andrea; Mandelson, Margaret T.; Petersen, Gloria; Zheng, Wei; Agalliu, Ilir; Albanes, Demetrius; Boutron-Ruault, Marie-Christine; Bracci, Paige M.; Buring, Julie E.; Canzian, Federico; Chang, Kenneth; Chanock, Stephen J.; Cotterchio, Michelle; Gaziano, J.Michael; Giovannucci, Edward L.; Goggins, Michael; Hallmans, Göran; Hankinson, Susan E.; Hoffman Bolton, Judith A.; Hunter, David J.; Hutchinson, Amy; Jacobs, Kevin B.; Jenab, Mazda; Khaw, Kay-Tee; Kraft, Peter; Krogh, Vittorio; Kurtz, Robert C.; McWilliams, Robert R.; Mendelsohn, Julie B.; Patel, Alpa V.; Rabe, Kari G.; Riboli, Elio; Shu, Xiao-Ou; Tjønneland, Anne; Tobias, Geoffrey S.; Trichopoulos, Dimitrios; Virtamo, Jarmo; Visvanathan, Kala; Watters, Joanne; Yu, Herbert; Zeleniuch-Jacquotte, Anne; Stolzenberg-Solomon, Rachael Z.

2012-01-01

Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case–control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10−6, 1.6 × 10−5, 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10−5), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H. pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer. PMID:22523087

Common variants associated with breast cancer in genome-wide association studies are modifiers of breast cancer risk in BRCA1 and BRCA2 mutation carriers.

PubMed

Wang, Xianshu; Pankratz, V Shane; Fredericksen, Zachary; Tarrell, Robert; Karaus, Mary; McGuffog, Lesley; Pharaoh, Paul D P; Ponder, Bruce A J; Dunning, Alison M; Peock, Susan; Cook, Margaret; Oliver, Clare; Frost, Debra; Sinilnikova, Olga M; Stoppa-Lyonnet, Dominique; Mazoyer, Sylvie; Houdayer, Claude; Hogervorst, Frans B L; Hooning, Maartje J; Ligtenberg, Marjolijn J; Spurdle, Amanda; Chenevix-Trench, Georgia; Schmutzler, Rita K; Wappenschmidt, Barbara; Engel, Christoph; Meindl, Alfons; Domchek, Susan M; Nathanson, Katherine L; Rebbeck, Timothy R; Singer, Christian F; Gschwantler-Kaulich, Daphne; Dressler, Catherina; Fink, Anneliese; Szabo, Csilla I; Zikan, Michal; Foretova, Lenka; Claes, Kathleen; Thomas, Gilles; Hoover, Robert N; Hunter, David J; Chanock, Stephen J; Easton, Douglas F; Antoniou, Antonis C; Couch, Fergus J

2010-07-15

Recent studies have identified single nucleotide polymorphisms (SNPs) that significantly modify breast cancer risk in BRCA1 and BRCA2 mutation carriers. Since these risk modifiers were originally identified as genetic risk factors for breast cancer in genome-wide association studies (GWASs), additional risk modifiers for BRCA1 and BRCA2 may be identified from promising signals discovered in breast cancer GWAS. A total of 350 SNPs identified as candidate breast cancer risk factors (P < 1 x 10(-3)) in two breast cancer GWAS studies were genotyped in 3451 BRCA1 and 2006 BRCA2 mutation carriers from nine centers. Associations with breast cancer risk were assessed using Cox models weighted for penetrance. Eight SNPs in BRCA1 carriers and 12 SNPs in BRCA2 carriers, representing an enrichment over the number expected, were significantly associated with breast cancer risk (P(trend) < 0.01). The minor alleles of rs6138178 in SNRPB and rs6602595 in CAMK1D displayed the strongest associations in BRCA1 carriers (HR = 0.78, 95% CI: 0.69-0.90, P(trend) = 3.6 x 10(-4) and HR = 1.25, 95% CI: 1.10-1.41, P(trend) = 4.2 x 10(-4)), whereas rs9393597 in LOC134997 and rs12652447 in FBXL7 showed the strongest associations in BRCA2 carriers (HR = 1.55, 95% CI: 1.25-1.92, P(trend) = 6 x 10(-5) and HR = 1.37, 95% CI: 1.16-1.62, P(trend) = 1.7 x 10(-4)). The magnitude and direction of the associations were consistent with the original GWAS. In subsequent risk assessment studies, the loci appeared to interact multiplicatively for breast cancer risk in BRCA1 and BRCA2 carriers. Promising candidate SNPs from GWAS were identified as modifiers of breast cancer risk in BRCA1 and BRCA2 carriers. Upon further validation, these SNPs together with other genetic and environmental factors may improve breast cancer risk assessment in these populations.

Potential Susceptibility Loci Identified for Renal Cell Carcinoma by Targeting Obesity-Related Genes.

PubMed

Shu, Xiang; Purdue, Mark P; Ye, Yuanqing; Tu, Huakang; Wood, Christopher G; Tannir, Nizar M; Wang, Zhaoming; Albanes, Demetrius; Gapstur, Susan M; Stevens, Victoria L; Rothman, Nathaniel; Chanock, Stephen J; Wu, Xifeng

2017-09-01

Background: Obesity is an established risk factor for renal cell carcinoma (RCC). Although genome-wide association studies (GWAS) of RCC have identified several susceptibility loci, additional variants might be missed due to the highly conservative selection. Methods: We conducted a multiphase study utilizing three independent genome-wide scans at MD Anderson Cancer Center (MDA RCC GWAS and MDA RCC OncoArray) and National Cancer Institute (NCI RCC GWAS), which consisted of a total of 3,530 cases and 5,714 controls, to investigate genetic variations in obesity-related genes and RCC risk. Results: In the discovery phase, 32,946 SNPs located at ±10 kb of 2,001 obesity-related genes were extracted from MDA RCC GWAS and analyzed using multivariable logistic regression. Proxies ( R 2 > 0.8) were searched or imputation was performed if SNPs were not directly genotyped in the validation sets. Twenty-one SNPs with P < 0.05 in both MDA RCC GWAS and NCI RCC GWAS were subsequently evaluated in MDA RCC OncoArray. In the overall meta-analysis, significant ( P < 0.05) associations with RCC risk were observed for SNP mapping to IL1RAPL2 [rs10521506-G: OR meta = 0.87 (0.81-0.93), P meta = 2.33 × 10 -5 ], PLIN2 [rs2229536-A: OR meta = 0.87 (0.81-0.93), P meta = 2.33 × 10 -5 ], SMAD3 [rs4601989-A: OR meta = 0.86 (0.80-0.93), P meta = 2.71 × 10 -4 ], MED13L [rs10850596-A: OR meta = 1.14 (1.07-1.23), P meta = 1.50 × 10 -4 ], and TSC1 [rs3761840-G: OR meta = 0.90 (0.85-0.97), P meta = 2.47 × 10 -3 ]. We did not observe any significant cis-expression quantitative trait loci effect for these SNPs in the TCGA KIRC data. Conclusions: Taken together, we found that genetic variation of obesity-related genes could influence RCC susceptibility. Impact: The five identified loci may provide new insights into disease etiology that reveal importance of obesity-related genes in RCC development. Cancer Epidemiol Biomarkers Prev; 26(9); 1436-42. ©2017 AACR . ©2017 American Association for Cancer Research.

Investigation of 95 variants identified in a genome-wide study for association with mortality after acute coronary syndrome.

PubMed

Morgan, Thomas M; House, John A; Cresci, Sharon; Jones, Philip; Allayee, Hooman; Hazen, Stanley L; Patel, Yesha; Patel, Riyaz S; Eapen, Danny J; Waddy, Salina P; Quyyumi, Arshed A; Kleber, Marcus E; März, Winfried; Winkelmann, Bernhard R; Boehm, Bernhard O; Krumholz, Harlan M; Spertus, John A

2011-09-29

Genome-wide association studies (GWAS) have identified new candidate genes for the occurrence of acute coronary syndrome (ACS), but possible effects of such genes on survival following ACS have yet to be investigated. We examined 95 polymorphisms in 69 distinct gene regions identified in a GWAS for premature myocardial infarction for their association with post-ACS mortality among 811 whites recruited from university-affiliated hospitals in Kansas City, Missouri. We then sought replication of a positive genetic association in a large, racially diverse cohort of myocardial infarction patients (N = 2284) using Kaplan-Meier survival analyses and Cox regression to adjust for relevant covariates. Finally, we investigated the apparent association further in 6086 additional coronary artery disease patients. After Cox adjustment for other ACS risk factors, of 95 SNPs tested in 811 whites only the association with the rs6922269 in MTHFD1L was statistically significant, with a 2.6-fold mortality hazard (P = 0.007). The recessive A/A genotype was of borderline significance in an age- and race-adjusted analysis of the entire combined cohort (N = 3095; P = 0.052), but this finding was not confirmed in independent cohorts (N = 6086). We found no support for the hypothesis that the GWAS-identified variants in this study substantially alter the probability of post-ACS survival. Large-scale, collaborative, genome-wide studies may be required in order to detect genetic variants that are robustly associated with survival in patients with coronary artery disease.

An efficient empirical Bayes method for genomewide association studies.

PubMed

Wang, Q; Wei, J; Pan, Y; Xu, S

2016-08-01

Linear mixed model (LMM) is one of the most popular methods for genomewide association studies (GWAS). Numerous forms of LMM have been developed; however, there are two major issues in GWAS that have not been fully addressed before. The two issues are (i) the genomic background noise and (ii) low statistical power after Bonferroni correction. We proposed an empirical Bayes (EB) method by assigning each marker effect a normal prior distribution, resulting in shrinkage estimates of marker effects. We found that such a shrinkage approach can selectively shrink marker effects and reduce the noise level to zero for majority of non-associated markers. In the meantime, the EB method allows us to use an 'effective number of tests' to perform Bonferroni correction for multiple tests. Simulation studies for both human and pig data showed that EB method can significantly increase statistical power compared with the widely used exact GWAS methods, such as GEMMA and FaST-LMM-Select. Real data analyses in human breast cancer identified improved detection signals for markers previously known to be associated with breast cancer. We therefore believe that EB method is a valuable tool for identifying the genetic basis of complex traits. © 2015 Blackwell Verlag GmbH.

Evaluation of different sources of DNA for use in genome wide studies and forensic application.

PubMed

Al Safar, Habiba S; Abidi, Fatima H; Khazanehdari, Kamal A; Dadour, Ian R; Tay, Guan K

2011-02-01

In the field of epidemiology, Genome-Wide Association Studies (GWAS) are commonly used to identify genetic predispositions of many human diseases. Large repositories housing biological specimens for clinical and genetic investigations have been established to store material and data for these studies. The logistics of specimen collection and sample storage can be onerous, and new strategies have to be explored. This study examines three different DNA sources (namely, degraded genomic DNA, amplified degraded genomic DNA and amplified extracted DNA from FTA card) for GWAS using the Illumina platform. No significant difference in call rate was detected between amplified degraded genomic DNA extracted from whole blood and amplified DNA retrieved from FTA™ cards. However, using unamplified-degraded genomic DNA reduced the call rate to a mean of 42.6% compared to amplified DNA extracted from FTA card (mean of 96.6%). This study establishes the utility of FTA™ cards as a viable storage matrix for cells from which DNA can be extracted to perform GWAS analysis.

A Genome-Wide Association Study of the Human Metabolome in a Community-Based Cohort

PubMed Central

Rhee, Eugene P.; Ho, Jennifer E.; Chen, Ming-Huei; Shen, Dongxiao; Cheng, Susan; Larson, Martin G.; Ghorbani, Anahita; Shi, Xu; Helenius, Iiro T.; O’Donnell, Christopher J.; Souza, Amanda L.; Deik, Amy; Pierce, Kerry A.; Bullock, Kevin; Walford, Geoffrey A.; Vasan, Ramachandran S.; Florez, Jose C.; Clish, Clary; Yeh, J.-R. Joanna; Wang, Thomas J.; Gerszten, Robert E.

2014-01-01

SUMMARY Because metabolites are hypothesized to play key roles as markers and effectors of cardio-metabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We report a genome-wide association study (GWAS) of 217 plasma metabolites, including >100 not measured in prior GWAS, in 2,076 participants of the Framingham Heart Study. For the majority of analytes, we find that estimated heritability explains >20% of inter-individual variation, and that variation attributable to heritable factors is greater than that attributable to clinical factors. Further, we identify 31 genetic loci associated with plasma metabolites, including 23 that have not previously been reported. Importantly, we include GWAS results for all surveyed metabolites, and demonstrate how this information highlights a role for AGXT2 in cholesterol ester and triacylglycerol metabolism. Thus, our study outlines the relative contributions of inherited and clinical factors on the plasma metabolome and provides a resource for metabolism research. PMID:23823483

Statistical correction of the Winner’s Curse explains replication variability in quantitative trait genome-wide association studies

PubMed Central

Pe’er, Itsik

2017-01-01

Genome-wide association studies (GWAS) have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10−14), even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner’s Curse (p < 10−16). We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94). In contrast, ancestry differences between replication and discovery (13 studies, 385 loci) cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium. PMID:28715421

Meta-analysis and genome-wide interpretation of genetic susceptibility to drug addiction

PubMed Central

2011-01-01

Background Classical genetic studies provide strong evidence for heritable contributions to susceptibility to developing dependence on addictive substances. Candidate gene and genome-wide association studies (GWAS) have sought genes, chromosomal regions and allelic variants likely to contribute to susceptibility to drug addiction. Results Here, we performed a meta-analysis of addiction candidate gene association studies and GWAS to investigate possible functional mechanisms associated with addiction susceptibility. From meta-data retrieved from 212 publications on candidate gene association studies and 5 GWAS reports, we linked a total of 843 haplotypes to addiction susceptibility. We mapped the SNPs in these haplotypes to functional and regulatory elements in the genome and estimated the magnitude of the contributions of different molecular mechanisms to their effects on addiction susceptibility. In addition to SNPs in coding regions, these data suggest that haplotypes in gene regulatory regions may also contribute to addiction susceptibility. When we compared the lists of genes identified by association studies and those identified by molecular biological studies of drug-regulated genes, we observed significantly higher participation in the same gene interaction networks than expected by chance, despite little overlap between the two gene lists. Conclusions These results appear to offer new insights into the genetic factors underlying drug addiction. PMID:21999673

The AraGWAS Catalog: a curated and standardized Arabidopsis thaliana GWAS catalog

PubMed Central

Togninalli, Matteo; Seren, Ümit; Meng, Dazhe; Fitz, Joffrey; Nordborg, Magnus; Weigel, Detlef

2018-01-01

Abstract The abundance of high-quality genotype and phenotype data for the model organism Arabidopsis thaliana enables scientists to study the genetic architecture of many complex traits at an unprecedented level of detail using genome-wide association studies (GWAS). GWAS have been a great success in A. thaliana and many SNP-trait associations have been published. With the AraGWAS Catalog (https://aragwas.1001genomes.org) we provide a publicly available, manually curated and standardized GWAS catalog for all publicly available phenotypes from the central A. thaliana phenotype repository, AraPheno. All GWAS have been recomputed on the latest imputed genotype release of the 1001 Genomes Consortium using a standardized GWAS pipeline to ensure comparability between results. The catalog includes currently 167 phenotypes and more than 222 000 SNP-trait associations with P < 10−4, of which 3887 are significantly associated using permutation-based thresholds. The AraGWAS Catalog can be accessed via a modern web-interface and provides various features to easily access, download and visualize the results and summary statistics across GWAS. PMID:29059333

Evaluation of 19 susceptibility loci of breast cancer in women of African ancestry

PubMed Central

Huo, Dezheng; Zheng, Yonglan; Ogundiran, Temidayo O.; Adebamowo, Clement; Nathanson, Katherine L.; Domchek, Susan M.; Rebbeck, Timothy R.; Simon, Michael S.; John, Esther M.; Hennis, Anselm; Nemesure, Barbara; Wu, Suh-Yuh; Leske, M.Cristina; Ambs, Stefan; Niu, Qun; Zhang, Jing; Cox, Nancy J.; Olopade, Olufunmilayo I.

2012-01-01

Multiple breast cancer susceptibility loci have been identified in genome-wide association studies (GWAS) in populations of European and Asian ancestry using array chips optimized for populations of European ancestry. It is important to examine whether these loci are associated with breast cancer risk in women of African ancestry. We evaluated 25 single nucleotide polymorphisms (SNPs) at 19 loci in a pooled case–control study of breast cancer, which included 1509 cases and 1383 controls. Cases and controls were enrolled in Nigeria, Barbados and the USA; all women were of African ancestry. We found significant associations for three SNPs, which were in the same direction and of similar magnitude as those reported in previous fine-mapping studies in women of African ancestry. The allelic odds ratios were 1.24 [95% confidence interval (CI): 1.04–1.47; P = 0.018] for the rs2981578-G allele (10q26/FGFR2), 1.34 (95% CI: 1.10–1.63; P = 0.0035) for the rs9397435-G allele (6q25) and 1.12 (95% CI: 1.00–1.25; P = 0.04) for the rs3104793-C allele (16q12). Although a significant association was observed for an additional index SNP (rs3817198), it was in the opposite direction to prior GWAS studies. In conclusion, this study highlights the complexity of applying current GWAS findings across racial/ethnic groups, as none of GWAS-identified index SNPs could be replicated in women of African ancestry. Further fine-mapping studies in women of African ancestry will be needed to reveal additional and causal variants for breast cancer. PMID:22357627

A genome-wide association study of susceptibility to acute lymphoblastic leukemia in adolescents and young adults.

PubMed

Perez-Andreu, Virginia; Roberts, Kathryn G; Xu, Heng; Smith, Colton; Zhang, Hui; Yang, Wenjian; Harvey, Richard C; Payne-Turner, Debbie; Devidas, Meenakshi; Cheng, I-Ming; Carroll, William L; Heerema, Nyla A; Carroll, Andrew J; Raetz, Elizabeth A; Gastier-Foster, Julie M; Marcucci, Guido; Bloomfield, Clara D; Mrózek, Krzysztof; Kohlschmidt, Jessica; Stock, Wendy; Kornblau, Steven M; Konopleva, Marina; Paietta, Elisabeth; Rowe, Jacob M; Luger, Selina M; Tallman, Martin S; Dean, Michael; Burchard, Esteban G; Torgerson, Dara G; Yue, Feng; Wang, Yanli; Pui, Ching-Hon; Jeha, Sima; Relling, Mary V; Evans, William E; Gerhard, Daniela S; Loh, Mignon L; Willman, Cheryl L; Hunger, Stephen P; Mullighan, Charles G; Yang, Jun J

2015-01-22

Acute lymphoblastic leukemia (ALL) in adolescents and young adults (AYA) is characterized by distinct presenting features and inferior prognosis compared with pediatric ALL. We performed a genome-wide association study (GWAS) to comprehensively identify inherited genetic variants associated with susceptibility to AYA ALL. In the discovery GWAS, we compared genotype frequency at 635 297 single nucleotide polymorphisms (SNPs) in 308 AYA ALL cases and 6,661 non-ALL controls by using a logistic regression model with genetic ancestry as a covariate. SNPs that reached P ≤ 5 × 10(-8) in GWAS were tested in an independent cohort of 162 AYA ALL cases and 5,755 non-ALL controls. We identified a single genome-wide significant susceptibility locus in GATA3: rs3824662, odds ratio (OR), 1.77 (P = 2.8 × 10(-10)) and rs3781093, OR, 1.73 (P = 3.2 × 10(-9)). These findings were validated in the replication cohort. The risk allele at rs3824662 was most frequent in Philadelphia chromosome (Ph)-like ALL but also conferred susceptibility to non-Ph-like ALL in AYAs. In 1,827 non-selected ALL cases, the risk allele frequency at this SNP was positively correlated with age at diagnosis (P = 6.29 × 10(-11)). Our results from this first GWAS of AYA ALL susceptibility point to unique biology underlying leukemogenesis and potentially distinct disease etiology by age group.

Genomic regions associated with bovine milk fatty acids in both summer and winter milk samples

PubMed Central

2012-01-01

Background In this study we perform a genome-wide association study (GWAS) for bovine milk fatty acids from summer milk samples. This study replicates a previous study where we performed a GWAS for bovine milk fatty acids based on winter milk samples from the same population. Fatty acids from summer and winter milk are genetically similar traits and we therefore compare the regions detected in summer milk to the regions previously detected in winter milk GWAS to discover regions that explain genetic variation in both summer and winter milk. Results The GWAS of summer milk samples resulted in 51 regions associated with one or more milk fatty acids. Results are in agreement with most associations that were previously detected in a GWAS of fatty acids from winter milk samples, including eight ‘new’ regions that were not considered in the individual studies. The high correlation between the –log10(P-values) and effects of SNPs that were found significant in both GWAS imply that the effects of the SNPs were similar on winter and summer milk fatty acids. Conclusions The GWAS of fatty acids based on summer milk samples was in agreement with most of the associations detected in the GWAS of fatty acids based on winter milk samples. Associations that were in agreement between both GWAS are more likely to be involved in fatty acid synthesis compared to regions detected in only one GWAS and are therefore worthwhile to pursue in fine-mapping studies. PMID:23107417

Genetic characteristics of inflammatory bowel disease in a Japanese population.

PubMed

Fuyuno, Yuta; Yamazaki, Keiko; Takahashi, Atsushi; Esaki, Motohiro; Kawaguchi, Takaaki; Takazoe, Masakazu; Matsumoto, Takayuki; Matsui, Toshiyuki; Tanaka, Hiroki; Motoya, Satoshi; Suzuki, Yasuo; Kiyohara, Yutaka; Kitazono, Takanari; Kubo, Michiaki

2016-07-01

Crohn's disease (CD) and ulcerative colitis (UC) are two major forms of inflammatory bowel disease (IBD). Meta-analyses of genome-wide association studies (GWAS) have identified 163 susceptibility loci for IBD among European populations; however, there is limited information for IBD susceptibility in a Japanese population. We performed a GWAS using imputed genotypes of 743 IBD patients (372 with CD and 371 with UC) and 3321 controls. Using 100 tag single-nucleotide polymorphisms (SNPs) (P < 5 × 10(-5)), a replication study was conducted with an independent set of 1310 IBD patients (949 with CD and 361 with UC) and 4163 controls. In addition, 163 SNPs identified by a European IBD GWAS were genotyped, and genetic backgrounds were compared between the Japanese and European populations. In the IBD GWAS, two East Asia-specific IBD susceptibility loci were identified in the Japanese population: ATG16L2-FCHSD2 and SLC25A15-ELF1-WBP4. Among 163 reported SNPs in European IBD patients, significant associations were confirmed in 18 (8 CD-specific, 4 UC-specific, and 6 IBD-shared). In Japanese CD patients, genes in the Th17-IL23 pathway showed stronger genetic effects, whereas the association of genes in the autophagy pathway was limited. The association of genes in the epithelial barrier and the Th17-IL23R pathways were similar in the Japanese and European UC populations. We confirmed two IBD susceptibility loci as common for CD and UC, and East Asian-specific. The genetic architecture in UC appeared to be similar between Europeans and East Asians, but may have some differences in CD.

A Method for Gene-Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

PubMed Central

Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

2014-01-01

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed () with 12 of the 22 SNPs showing . Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, ), NRP1 (rs722988, ), BAD (rs694739, ), CTSB (rs1296023, ), FYN (rs11964650, ), UBE2G1 (rs9906760, ), MAP3K14 (rs17759555, ), ITGB1 (rs1557150, ), and IL7R (rs1445898, ). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. PMID:25371288

Genetics of alcoholism.

PubMed

Edenberg, Howard J; Foroud, Tatiana

2014-01-01

Multiple lines of evidence strongly indicate that genetic factors contribute to the risk for alcohol use disorders (AUD). There is substantial heterogeneity in AUD, which complicates studies seeking to identify specific genetic factors. To identify these genetic effects, several different alcohol-related phenotypes have been analyzed, including diagnosis and quantitative measures related to AUDs. Study designs have used candidate gene analyses, genetic linkage studies, genomewide association studies (GWAS), and analyses of rare variants. Two genes that encode enzymes of alcohol metabolism have the strongest effect on AUD: aldehyde dehydrogenase 2 and alcohol dehydrogenase 1B each has strongly protective variants that reduce risk, with odds ratios approximately 0.2-0.4. A number of other genes important in AUD have been identified and replicated, including GABRA2 and alcohol dehydrogenases 1B and 4. GWAS have identified additional candidates. Rare variants are likely also to play a role; studies of these are just beginning. A multifaceted approach to gene identification, targeting both rare and common variations and assembling much larger datasets for meta-analyses, is critical for identifying the key genes and pathways important in AUD. © 2014 Elsevier B.V. All rights reserved.

Incorporating Concomitant Medications into Genome-Wide Analyses for the Study of Complex Disease and Drug Response.

PubMed

Graham, Hillary T; Rotroff, Daniel M; Marvel, Skylar W; Buse, John B; Havener, Tammy M; Wilson, Alyson G; Wagner, Michael J; Motsinger-Reif, Alison A

2016-01-01

Given the high costs of conducting a drug-response trial, researchers are now aiming to use retrospective analyses to conduct genome-wide association studies (GWAS) to identify underlying genetic contributions to drug-response variation. To prevent confounding results from a GWAS to investigate drug response, it is necessary to account for concomitant medications, defined as any medication taken concurrently with the primary medication being investigated. We use data from the Action to Control Cardiovascular Disease (ACCORD) trial in order to implement a novel scoring procedure for incorporating concomitant medication information into a linear regression model in preparation for GWAS. In order to accomplish this, two primary medications were selected: thiazolidinediones and metformin because of the wide-spread use of these medications and large sample sizes available within the ACCORD trial. A third medication, fenofibrate, along with a known confounding medication, statin, were chosen as a proof-of-principle for the scoring procedure. Previous studies have identified SNP rs7412 as being associated with statin response. Here we hypothesize that including the score for statin as a covariate in the GWAS model will correct for confounding of statin and yield a change in association at rs7412. The response of the confounded signal was successfully diminished from p = 3.19 × 10 -7 to p = 1.76 × 10 -5 , by accounting for statin using the scoring procedure presented here. This approach provides the ability for researchers to account for concomitant medications in complex trial designs where monotherapy treatment regimens are not available.

Genome-wide association study of 40,000 individuals identifies two novel loci associated with bipolar disorder

PubMed Central

Hou, Liping; Bergen, Sarah E.; Akula, Nirmala; Song, Jie; Hultman, Christina M.; Landén, Mikael; Adli, Mazda; Alda, Martin; Ardau, Raffaella; Arias, Bárbara; Aubry, Jean-Michel; Backlund, Lena; Badner, Judith A.; Barrett, Thomas B.; Bauer, Michael; Baune, Bernhard T.; Bellivier, Frank; Benabarre, Antonio; Bengesser, Susanne; Berrettini, Wade H.; Bhattacharjee, Abesh Kumar; Biernacka, Joanna M.; Birner, Armin; Bloss, Cinnamon S.; Brichant-Petitjean, Clara; Bui, Elise T.; Byerley, William; Cervantes, Pablo; Chillotti, Caterina; Cichon, Sven; Colom, Francesc; Coryell, William; Craig, David W.; Cruceanu, Cristiana; Czerski, Piotr M.; Davis, Tony; Dayer, Alexandre; Degenhardt, Franziska; Del Zompo, Maria; DePaulo, J. Raymond; Edenberg, Howard J.; Étain, Bruno; Falkai, Peter; Foroud, Tatiana; Forstner, Andreas J.; Frisén, Louise; Frye, Mark A.; Fullerton, Janice M.; Gard, Sébastien; Garnham, Julie S.; Gershon, Elliot S.; Goes, Fernando S.; Greenwood, Tiffany A.; Grigoroiu-Serbanescu, Maria; Hauser, Joanna; Heilbronner, Urs; Heilmann-Heimbach, Stefanie; Herms, Stefan; Hipolito, Maria; Hitturlingappa, Shashi; Hoffmann, Per; Hofmann, Andrea; Jamain, Stephane; Jiménez, Esther; Kahn, Jean-Pierre; Kassem, Layla; Kelsoe, John R.; Kittel-Schneider, Sarah; Kliwicki, Sebastian; Koller, Daniel L.; König, Barbara; Lackner, Nina; Laje, Gonzalo; Lang, Maren; Lavebratt, Catharina; Lawson, William B.; Leboyer, Marion; Leckband, Susan G.; Liu, Chunyu; Maaser, Anna; Mahon, Pamela B.; Maier, Wolfgang; Maj, Mario; Manchia, Mirko; Martinsson, Lina; McCarthy, Michael J.; McElroy, Susan L.; McInnis, Melvin G.; McKinney, Rebecca; Mitchell, Philip B.; Mitjans, Marina; Mondimore, Francis M.; Monteleone, Palmiero; Mühleisen, Thomas W.; Nievergelt, Caroline M.; Nöthen, Markus M.; Novák, Tomas; Nurnberger, John I.; Nwulia, Evaristus A.; Ösby, Urban; Pfennig, Andrea; Potash, James B.; Propping, Peter; Reif, Andreas; Reininghaus, Eva; Rice, John; Rietschel, Marcella; Rouleau, Guy A.; Rybakowski, Janusz K.; Schalling, Martin; Scheftner, William A.; Schofield, Peter R.; Schork, Nicholas J.; Schulze, Thomas G.; Schumacher, Johannes; Schweizer, Barbara W.; Severino, Giovanni; Shekhtman, Tatyana; Shilling, Paul D.; Simhandl, Christian; Slaney, Claire M.; Smith, Erin N.; Squassina, Alessio; Stamm, Thomas; Stopkova, Pavla; Streit, Fabian; Strohmaier, Jana; Szelinger, Szabolcs; Tighe, Sarah K.; Tortorella, Alfonso; Turecki, Gustavo; Vieta, Eduard; Volkert, Julia; Witt, Stephanie H.; Wright, Adam; Zandi, Peter P.; Zhang, Peng; Zollner, Sebastian; McMahon, Francis J.

2016-01-01

Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behaviour. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ∼2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, P =  5.87 × 10 − 9; odds ratio (OR) = 1.12) and markers within ERBB2 (rs2517959, P =  4.53 × 10 − 9; OR = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS. PMID:27329760

Genome-wide association study of telomere length among South Asians identifies a second RTEL1 association signal

PubMed Central

Zhang, Chenan; Chen, Lin S; Gao, Jianjun; Roy, Shantanu; Shinkle, Justin; Sabarinathan, Mekala; Tong, Lin; Ahmed, Alauddin; Islam, Tariqul; Rakibuz-Zaman, Muhammad; Sarwar, Golam; Shahriar, Hasan; Rahman, Mahfuzar; Yunus, Mohammad; Jasmine, Farzana; Kibriya, Muhammad G; Ahsan, Habibul; Pierce, Brandon L

2018-01-01

Background Leucocyte telomere length (TL) is a potential biomarker of ageing and risk for age-related disease. Leucocyte TL is heritable and shows substantial differences by race/ethnicity. Recent genome-wide association studies (GWAS) report ~10 loci harbouring SNPs associated with leucocyte TL, but these studies focus primarily on populations of European ancestry. Objective This study aims to enhance our understanding of genetic determinants of TL across populations. Methods We performed a GWAS of TL using data on 5075 Bangladeshi adults. We measured TL using one of two technologies (qPCR or a Luminex-based method) and used standardised variables as TL phenotypes. Results Our results replicate previously reported associations in the TERC and TERT regions (P=2.2×10−8 and P=6.4×10−6, respectively). We observed a novel association signal in the RTEL1 gene (intronic SNP rs2297439; P=2.82×10−7) that is independent of previously reported TL-associated SNPs in this region. The minor allele for rs2297439 is common in South Asian populations (≥0.25) but at lower frequencies in other populations (eg, 0.07 in Northern Europeans). Among the eight other previously reported association signals, all were directionally consistent with our study, but only rs8105767 (ZNF208) was nominally significant (P=0.003). SNP-based heritability estimates were as high as 44% when analysing close relatives but much lower when analysing distant relatives only. Conclusions In this first GWAS of TL in a South Asian population, we replicate some, but not all, of the loci reported in prior GWAS of individuals of European ancestry, and we identify a novel second association signal at the RTEL1 locus. PMID:29151059

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

PubMed

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I; Padyukov, Leonid; Toes, Rene E M; Huizinga, Tom W J; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I W; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert M; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-12-01

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

PubMed Central

Beecham, Ashley H; Patsopoulos, Nikolaos A; Xifara, Dionysia K; Davis, Mary F; Kemppinen, Anu; Cotsapas, Chris; Shahi, Tejas S; Spencer, Chris; Booth, David; Goris, An; Oturai, Annette; Saarela, Janna; Fontaine, Bertrand; Hemmer, Bernhard; Martin, Claes; Zipp, Frauke; D’alfonso, Sandra; Martinelli-Boneschi, Filippo; Taylor, Bruce; Harbo, Hanne F; Kockum, Ingrid; Hillert, Jan; Olsson, Tomas; Ban, Maria; Oksenberg, Jorge R; Hintzen, Rogier; Barcellos, Lisa F; Agliardi, Cristina; Alfredsson, Lars; Alizadeh, Mehdi; Anderson, Carl; Andrews, Robert; Søndergaard, Helle Bach; Baker, Amie; Band, Gavin; Baranzini, Sergio E; Barizzone, Nadia; Barrett, Jeffrey; Bellenguez, Céline; Bergamaschi, Laura; Bernardinelli, Luisa; Berthele, Achim; Biberacher, Viola; Binder, Thomas M C; Blackburn, Hannah; Bomfim, Izaura L; Brambilla, Paola; Broadley, Simon; Brochet, Bruno; Brundin, Lou; Buck, Dorothea; Butzkueven, Helmut; Caillier, Stacy J; Camu, William; Carpentier, Wassila; Cavalla, Paola; Celius, Elisabeth G; Coman, Irène; Comi, Giancarlo; Corrado, Lucia; Cosemans, Leentje; Cournu-Rebeix, Isabelle; Cree, Bruce A C; Cusi, Daniele; Damotte, Vincent; Defer, Gilles; Delgado, Silvia R; Deloukas, Panos; di Sapio, Alessia; Dilthey, Alexander T; Donnelly, Peter; Dubois, Bénédicte; Duddy, Martin; Edkins, Sarah; Elovaara, Irina; Esposito, Federica; Evangelou, Nikos; Fiddes, Barnaby; Field, Judith; Franke, Andre; Freeman, Colin; Frohlich, Irene Y; Galimberti, Daniela; Gieger, Christian; Gourraud, Pierre-Antoine; Graetz, Christiane; Graham, Andrew; Grummel, Verena; Guaschino, Clara; Hadjixenofontos, Athena; Hakonarson, Hakon; Halfpenny, Christopher; Hall, Gillian; Hall, Per; Hamsten, Anders; Harley, James; Harrower, Timothy; Hawkins, Clive; Hellenthal, Garrett; Hillier, Charles; Hobart, Jeremy; Hoshi, Muni; Hunt, Sarah E; Jagodic, Maja; Jelčić, Ilijas; Jochim, Angela; Kendall, Brian; Kermode, Allan; Kilpatrick, Trevor; Koivisto, Keijo; Konidari, Ioanna; Korn, Thomas; Kronsbein, Helena; Langford, Cordelia; Larsson, Malin; Lathrop, Mark; Lebrun-Frenay, Christine; Lechner-Scott, Jeannette; Lee, Michelle H; Leone, Maurizio A; Leppä, Virpi; Liberatore, Giuseppe; Lie, Benedicte A; Lill, Christina M; Lindén, Magdalena; Link, Jenny; Luessi, Felix; Lycke, Jan; Macciardi, Fabio; Männistö, Satu; Manrique, Clara P; Martin, Roland; Martinelli, Vittorio; Mason, Deborah; Mazibrada, Gordon; McCabe, Cristin; Mero, Inger-Lise; Mescheriakova, Julia; Moutsianas, Loukas; Myhr, Kjell-Morten; Nagels, Guy; Nicholas, Richard; Nilsson, Petra; Piehl, Fredrik; Pirinen, Matti; Price, Siân E; Quach, Hong; Reunanen, Mauri; Robberecht, Wim; Robertson, Neil P; Rodegher, Mariaemma; Rog, David; Salvetti, Marco; Schnetz-Boutaud, Nathalie C; Sellebjerg, Finn; Selter, Rebecca C; Schaefer, Catherine; Shaunak, Sandip; Shen, Ling; Shields, Simon; Siffrin, Volker; Slee, Mark; Sorensen, Per Soelberg; Sorosina, Melissa; Sospedra, Mireia; Spurkland, Anne; Strange, Amy; Sundqvist, Emilie; Thijs, Vincent; Thorpe, John; Ticca, Anna; Tienari, Pentti; van Duijn, Cornelia; Visser, Elizabeth M; Vucic, Steve; Westerlind, Helga; Wiley, James S; Wilkins, Alastair; Wilson, James F; Winkelmann, Juliane; Zajicek, John; Zindler, Eva; Haines, Jonathan L; Pericak-Vance, Margaret A; Ivinson, Adrian J; Stewart, Graeme; Hafler, David; Hauser, Stephen L; Compston, Alastair; McVean, Gil; De Jager, Philip; Sawcer, Stephen; McCauley, Jacob L

2013-01-01

Using the ImmunoChip custom genotyping array, we analysed 14,498 multiple sclerosis subjects and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (p-value < 1.0 × 10-4). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 multiple sclerosis subjects and 26,703 healthy controls. In these 80,094 individuals of European ancestry we identified 48 new susceptibility variants (p-value < 5.0 × 10-8); three found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants in 103 discrete loci outside of the Major Histocompatibility Complex. With high resolution Bayesian fine-mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalogue of multiple sclerosis risk variants and illustrates the value of fine-mapping in the resolution of GWAS signals. PMID:24076602

SCOPA and META-SCOPA: software for the analysis and aggregation of genome-wide association studies of multiple correlated phenotypes.

PubMed

Mägi, Reedik; Suleimanov, Yury V; Clarke, Geraldine M; Kaakinen, Marika; Fischer, Krista; Prokopenko, Inga; Morris, Andrew P

2017-01-11

Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have been successful in identifying loci contributing genetic effects to a wide range of complex human diseases and quantitative traits. The traditional approach to GWAS analysis is to consider each phenotype separately, despite the fact that many diseases and quantitative traits are correlated with each other, and often measured in the same sample of individuals. Multivariate analyses of correlated phenotypes have been demonstrated, by simulation, to increase power to detect association with SNPs, and thus may enable improved detection of novel loci contributing to diseases and quantitative traits. We have developed the SCOPA software to enable GWAS analysis of multiple correlated phenotypes. The software implements "reverse regression" methodology, which treats the genotype of an individual at a SNP as the outcome and the phenotypes as predictors in a general linear model. SCOPA can be applied to quantitative traits and categorical phenotypes, and can accommodate imputed genotypes under a dosage model. The accompanying META-SCOPA software enables meta-analysis of association summary statistics from SCOPA across GWAS. Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, triglycerides and body mass index, and subsequent meta-analysis with META-SCOPA, highlighted stronger association signals than univariate phenotype analysis at established lipid and obesity loci. The META-SCOPA meta-analysis also revealed a novel signal of association at genome-wide significance for triglycerides mapping to GPC5 (lead SNP rs71427535, p = 1.1x10 -8 ), which has not been reported in previous large-scale GWAS of lipid traits. The SCOPA and META-SCOPA software enable discovery and dissection of multiple phenotype association signals through implementation of a powerful reverse regression approach.

Genome-wide association study of chemotherapeutic agent-induced severe neutropenia/leucopenia for patients in Biobank Japan.

PubMed

Low, Siew-Kee; Chung, Suyoun; Takahashi, Atsushi; Zembutsu, Hitoshi; Mushiroda, Taisei; Kubo, Michiaki; Nakamura, Yusuke

2013-08-01

Chemotherapeutic agents are notoriously known to have a narrow therapeutic range that often results in life-threatening toxicity. Hence, it is clinically important to identify the patients who are at high risk for severe toxicity to certain chemotherapy through a pharmacogenomics approach. In this study, we carried out multiple genome-wide association studies (GWAS) of 13 122 cancer patients who received different chemotherapy regimens, including cyclophosphamide- and platinum-based (cisplatin and carboplatin), anthracycline-based (doxorubicin and epirubicin), and antimetabolite-based (5-fluorouracil and gemcitabine) treatment, antimicrotubule agents (paclitaxel and docetaxel), and topoisomerase inhibitors (camptothecin and etoposide), as well as combination therapy with paclitaxel and carboplatin, to identify genetic variants that are associated with the risk of severe neutropenia/leucopenia in the Japanese population. In addition, we used a weighted genetic risk scoring system to evaluate the cumulative effects of the suggestive genetic variants identified from GWAS in order to predict the risk levels of individuals who carry multiple risk alleles. Although we failed to identify genetic variants that surpassed the genome-wide significance level (P < 5.0 × 10(-8) ) through GWAS, probably due to insufficient statistical power and complex clinical features, we were able to shortlist some of the suggestive associated loci. The current study is at the relatively preliminary stage, but does highlight the complexity and problematic issues associated with retrospective pharmacogenomics studies. However, we hope that verification of these genetic variants through local and international collaborations could improve the clinical outcome for cancer patients. © 2013 Japanese Cancer Association.

Replication of Genome Wide Association Studies of Alcohol Dependence: Support for Association with Variation in ADH1C

PubMed Central

Biernacka, Joanna M.; Geske, Jennifer R.; Schneekloth, Terry D.; Frye, Mark A.; Cunningham, Julie M.; Choi, Doo-Sup; Tapp, Courtney L.; Lewis, Bradley R.; Drews, Maureen S.; L.Pietrzak, Tracy; Colby, Colin L.; Hall-Flavin, Daniel K.; Loukianova, Larissa L.; Heit, John A.; Mrazek, David A.; Karpyak, Victor M.

2013-01-01

Genome-wide association studies (GWAS) have revealed many single nucleotide polymorphisms (SNPs) associated with complex traits. Although these studies frequently fail to identify statistically significant associations, the top association signals from GWAS may be enriched for true associations. We therefore investigated the association of alcohol dependence with 43 SNPs selected from association signals in the first two published GWAS of alcoholism. Our analysis of 808 alcohol-dependent cases and 1,248 controls provided evidence of association of alcohol dependence with SNP rs1614972 in the ADH1C gene (unadjusted p = 0.0017). Because the GWAS study that originally reported association of alcohol dependence with this SNP [1] included only men, we also performed analyses in sex-specific strata. The results suggest that this SNP has a similar effect in both sexes (men: OR (95%CI) = 0.80 (0.66, 0.95); women: OR (95%CI) = 0.83 (0.66, 1.03)). We also observed marginal evidence of association of the rs1614972 minor allele with lower alcohol consumption in the non-alcoholic controls (p = 0.081), and independently in the alcohol-dependent cases (p = 0.046). Despite a number of potential differences between the samples investigated by the prior GWAS and the current study, data presented here provide additional support for the association of SNP rs1614972 in ADH1C with alcohol dependence and extend this finding by demonstrating association with consumption levels in both non-alcoholic and alcohol-dependent populations. Further studies should investigate the association of other polymorphisms in this gene with alcohol dependence and related alcohol-use phenotypes. PMID:23516558

Analysis of 60 reported glioma risk SNPs replicates published GWAS findings but fails to replicate associations from published candidate-gene studies.

PubMed

Walsh, Kyle M; Anderson, Erik; Hansen, Helen M; Decker, Paul A; Kosel, Matt L; Kollmeyer, Thomas; Rice, Terri; Zheng, Shichun; Xiao, Yuanyuan; Chang, Jeffrey S; McCoy, Lucie S; Bracci, Paige M; Wiemels, Joe L; Pico, Alexander R; Smirnov, Ivan; Lachance, Daniel H; Sicotte, Hugues; Eckel-Passow, Jeanette E; Wiencke, John K; Jenkins, Robert B; Wrensch, Margaret R

2013-02-01

Genomewide association studies (GWAS) and candidate-gene studies have implicated single-nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case-control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate-gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate-gene studies was associated in the full case-control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate-gene approach lay in selecting both appropriate genes and relevant SNPs within these genes. © 2012 WILEY PERIODICALS, INC.

Understanding the pharmacogenetics of selective serotonin reuptake inhibitors.

PubMed

Fabbri, Chiara; Minarini, Alessandro; Niitsu, Tomihisa; Serretti, Alessandro

2014-08-01

The genetic background of antidepressant response represents a unique opportunity to identify biological markers of treatment outcome. Encouraging results alternating with inconsistent findings made antidepressant pharmacogenetics a stimulating but often discouraging field that requires careful discussion about cumulative evidence and methodological issues. The present review discusses both known and less replicated genes that have been implicated in selective serotonin reuptake inhibitors (SSRIs) efficacy and side effects. Candidate genes studies and genome-wide association studies (GWAS) were collected through MEDLINE database search (articles published till January 2014). Further, GWAS signals localized in promising genetic regions according to candidate gene studies are reported in order to assess the general comparability of results obtained through these two types of pharmacogenetic studies. Finally, a pathway enrichment approach is applied to the top genes (those harboring SNPs with p < 0.0001) outlined by previous GWAS in order to identify possible molecular mechanisms involved in SSRI effect. In order to improve the understanding of SSRI pharmacogenetics, the present review discusses the proposal of moving from the analysis of individual polymorphisms to genes and molecular pathways, and from the separation across different methodological approaches to their combination. Efforts in this direction are justified by the recent evidence of a favorable cost-utility of gene-guided antidepressant treatment.

Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium

PubMed Central

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

No association between telomere length-related loci and number of cutaneous nevi.

PubMed

Li, Xin; Liang, Geyu; Du, Mengmeng; De Vivo, Immaculata; Nan, Hongmei

2016-12-13

Longer telomeres have been associated both with increased melanoma risk and increased nevus counts. Nevus count is one of the strongest risk factors for melanoma. Recent data showed that a genetic score derived by telomere length-related single nucleotide polymorphisms (SNPs) was strongly associated with melanoma risk; however, the relationships between these SNPs and number of cutaneous nevi have not been investigated. We evaluated the associations between telomere length-related SNPs reported by previous genome-wide association study (GWAS) and nevus counts among 15,955 participants of European Ancestry in the Nurses' Health Study and Health Professionals Follow-up Study. None of the SNPs was associated with nevus counts, nor was the genetic score combining the dosage of alleles related to increased telomere length. The telomere length-related SNPs identified by published GWAS do not appear to play an important role in nevus formation. Genetic determinants of telomere length reported by GWAS do not explain the observed epidemiologic association between telomere length and nevus counts.

A Genome-Wide Association Study Identifies Risk Loci to Equine Recurrent Uveitis in German Warmblood Horses

PubMed Central

Kulbrock, Maike; Lehner, Stefanie; Metzger, Julia; Ohnesorge, Bernhard; Distl, Ottmar

2013-01-01

Equine recurrent uveitis (ERU) is a common eye disease affecting up to 3–15% of the horse population. A genome-wide association study (GWAS) using the Illumina equine SNP50 bead chip was performed to identify loci conferring risk to ERU. The sample included a total of 144 German warmblood horses. A GWAS showed a significant single nucleotide polymorphism (SNP) on horse chromosome (ECA) 20 at 49.3 Mb, with IL-17A and IL-17F being the closest genes. This locus explained a fraction of 23% of the phenotypic variance for ERU. A GWAS taking into account the severity of ERU, revealed a SNP on ECA18 nearby to the crystalline gene cluster CRYGA-CRYGF. For both genomic regions on ECA18 and 20, significantly associated haplotypes containing the genome-wide significant SNPs could be demonstrated. In conclusion, our results are indicative for a genetic component regulating the possible critical role of IL-17A and IL-17F in the pathogenesis of ERU. The associated SNP on ECA18 may be indicative for cataract formation in the course of ERU. PMID:23977091

Network-Guided GWAS Improves Identification of Genes Affecting Free Amino Acids.

PubMed

Angelovici, Ruthie; Batushansky, Albert; Deason, Nicholas; Gonzalez-Jorge, Sabrina; Gore, Michael A; Fait, Aaron; DellaPenna, Dean

2017-01-01

Amino acids are essential for proper growth and development in plants. Amino acids serve as building blocks for proteins but also are important for responses to stress and the biosynthesis of numerous essential compounds. In seed, the pool of free amino acids (FAAs) also contributes to alternative energy, desiccation, and seed vigor; thus, manipulating FAA levels can significantly impact a seed's nutritional qualities. While genome-wide association studies (GWAS) on branched-chain amino acids have identified some regulatory genes controlling seed FAAs, the genetic regulation of FAA levels, composition, and homeostasis in seeds remains mostly unresolved. Hence, we performed GWAS on 18 FAAs from a 313-ecotype Arabidopsis (Arabidopsis thaliana) association panel. Specifically, GWAS was performed on 98 traits derived from known amino acid metabolic pathways (approach 1) and then on 92 traits generated from an unbiased correlation-based metabolic network analysis (approach 2), and the results were compared. The latter approach facilitated the discovery of additional novel metabolic interactions and single-nucleotide polymorphism-trait associations not identified by the former approach. The most prominent network-guided GWAS signal was for a histidine (His)-related trait in a region containing two genes: a cationic amino acid transporter (CAT4) and a polynucleotide phosphorylase resistant to inhibition with fosmidomycin. A reverse genetics approach confirmed CAT4 to be responsible for the natural variation of His-related traits across the association panel. Given that His is a semiessential amino acid and a potent metal chelator, CAT4 orthologs could be considered as candidate genes for seed quality biofortification in crop plants. © 2017 American Society of Plant Biologists. All Rights Reserved.

A cross-ethnic survey of CFB and SLC44A4, Indian ulcerative colitis GWAS hits, underscores their potential role in disease susceptibility

PubMed Central

Gupta, Aditi; Juyal, Garima; Sood, Ajit; Midha, Vandana; Yamazaki, Keiko; Vich Vila, Arnau; Esaki, Motohiro; Matsui, Toshiyuki; Takahashi, Atsushi; Kubo, Michiaki; Weersma, Rinse K; Thelma, B K

2017-01-01

The first ever genome-wide association study (GWAS) of ulcerative colitis in genetically distinct north Indian population identified two novel genes namely CFB and SLC44A4. Considering their biological relevance, we investigated allelic/genetic heterogeneity in these genes among ulcerative colitis cohorts of north Indian, Japanese and Dutch origin using high-density ImmunoChip case–control genotype data. Comparative linkage disequilibrium profiling and test of association were performed. Of the 28 CFB SNPs, similar strength of association was observed for rs4151657 (novel ulcerative colitis GWAS SNP) in north Indians (P=1.73 × 10−10) and Japanese (P=2.02 × 10−12) but not in the Dutch. Further, a three-marker haplotype was shared between north Indians and Japanese (P<10−8), but a different five-marker haplotype was associated (P=2.07 × 10−6) in the Dutch. Of the 22 SLC44A4 SNPs, rs2736428 (novel ulcerative colitis GWAS SNP) was found significantly associated in north Indians (P=4.94 × 10−10) and Japanese (P=3.37 × 10−9), but not among the Dutch. These results suggest (i) apparent allelic heterogeneity in CFB and genetic heterogeneity in SLC44A4 across different ethnic groups; (ii) shared ulcerative colitis genetic etiological factors among Asians; and finally (iii) re-exploration of GWAS findings together with high-density genotyping/sequencing and trans-ethnic fine mapping approaches may help identify shared and population-specific risk variants and enable to explain missing disease heritability. PMID:27759029

A GWAS meta-analysis and replication study identifies a novel locus within CLPTM1L/TERT associated with nasopharyngeal carcinoma in individuals of Chinese ancestry

PubMed Central

Yu, Kai; Chin, Yoon-Ming; Lou, Pei-Jen; Hsu, Wan-Lun; McKay, James D.; Chen, Chien-Jen; Chang, Yu-Sun; Chen, Li-Zhen; Chen, Ming-Yuan; Cui, Qian; Feng, Fu-Tuo; Feng, Qi-Shen; Guo, Yun-Miao; Jia, Wei-Hua; Khoo, Alan Soo-Beng; Liu, Wen-Sheng; Mo, Hao-Yuan; Pua, Kin-Choo; Teo, Soo-Hwang; Tse, Ka-Po; Xia, Yun-Fei; Zhang, Hongxin; Zhou, Gang-Qiao; Liu, Jian-Jun; Zeng, Yi-Xin; Hildesheim, Allan

2015-01-01

Background Genetic loci within the major histocompatibility complex (MHC) have been associated with nasopharyngeal carcinoma (NPC), an Epstein-Barr virus (EBV)-associated cancer, in several GWAS. Results outside this region have varied. Methods We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases;3,740 controls). 43 noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of 4 independent case-control studies across 3 regions in Asia (4,716 cases;5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed. Results In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR=0.81;p-value 6.3*10−13). Our results also provide support for associations reported from published NPC GWAS - rs6774494 (p = 1.5*10−12;located in the MECOM gene region), rs9510787 (p = 5.0*10−10;located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (p = 2.8*10−8,p = 7.0*10−7,and p = 8.4*10−7 respectively;located in the CDKN2A/B gene region). Conclusion We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene is important for telomere maintenance and has been reported to be over-expressed in NPC, and an EBV protein expressed in NPC (LMP1) modulates TERT expression/telomerase activity. Impact Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis. PMID:26545403

Genetic Dissection of Photoperiod Response Based on GWAS of Pre-Anthesis Phase Duration in Spring Barley

PubMed Central

Alqudah, Ahmad M.; Sharma, Rajiv; Pasam, Raj K.; Graner, Andreas; Kilian, Benjamin; Schnurbusch, Thorsten

2014-01-01

Heading time is a complex trait, and natural variation in photoperiod responses is a major factor controlling time to heading, adaptation and grain yield. In barley, previous heading time studies have been mainly conducted under field conditions to measure total days to heading. We followed a novel approach and studied the natural variation of time to heading in a world-wide spring barley collection (218 accessions), comprising of 95 photoperiod-sensitive (Ppd-H1) and 123 accessions with reduced photoperiod sensitivity (ppd-H1) to long-day (LD) through dissecting pre-anthesis development into four major stages and sub-phases. The study was conducted under greenhouse (GH) conditions (LD; 16/8 h; ∼20/∼16°C day/night). Genotyping was performed using a genome-wide high density 9K single nucleotide polymorphisms (SNPs) chip which assayed 7842 SNPs. We used the barley physical map to identify candidate genes underlying genome-wide association scans (GWAS). GWAS for pre-anthesis stages/sub-phases in each photoperiod group provided great power for partitioning genetic effects on floral initiation and heading time. In addition to major genes known to regulate heading time under field conditions, several novel QTL with medium to high effects, including new QTL having major effects on developmental stages/sub-phases were found to be associated in this study. For example, highly associated SNPs tagged the physical regions around HvCO1 (barley CONSTANS1) and BFL (BARLEY FLORICAULA/LEAFY) genes. Based upon our GWAS analysis, we propose a new genetic network model for each photoperiod group, which includes several newly identified genes, such as several HvCO-like genes, belonging to different heading time pathways in barley. PMID:25420105

Genome-wide association study on legendre random regression coefficients for the growth and feed intake trajectory on Duroc Boars.

PubMed

Howard, Jeremy T; Jiao, Shihui; Tiezzi, Francesco; Huang, Yijian; Gray, Kent A; Maltecca, Christian

2015-05-30

Feed intake and growth are economically important traits in swine production. Previous genome wide association studies (GWAS) have utilized average daily gain or daily feed intake to identify regions that impact growth and feed intake across time. The use of longitudinal models in GWAS studies, such as random regression, allows for SNPs having a heterogeneous effect across the trajectory to be characterized. The objective of this study is therefore to conduct a single step GWAS (ssGWAS) on the animal polynomial coefficients for feed intake and growth. Corrected daily feed intake (DFI Adj) and average daily weight measurements (DBW Avg) on 8981 (n=525,240 observations) and 5643 (n=283,607 observations) animals were utilized in a random regression model using Legendre polynomials (order=2) and a relationship matrix that included genotyped and un-genotyped animals. A ssGWAS was conducted on the animal polynomials coefficients (intercept, linear and quadratic) for animals with genotypes (DFIAdj: n=855; DBWAvg: n=590). Regions were characterized based on the variance of 10-SNP sliding windows GEBV (WGEBV). A bootstrap analysis (n=1000) was conducted to declare significance. Heritability estimates for the traits trajectory ranged from 0.34-0.52 to 0.07-0.23 for DBWAvg and DFIAdj, respectively. Genetic correlations across age classes were large and positive for both DBWAvg and DFIAdj, albeit age classes at the beginning had a small to moderate genetic correlation with age classes towards the end of the trajectory for both traits. The WGEBV variance explained by significant regions (P<0.001) for each polynomial coefficient ranged from 0.2-0.9 to 0.3-1.01% for DBWAvg and DFIAdj, respectively. The WGEBV variance explained by significant regions for the trajectory was 1.54 and 1.95% for DBWAvg and DFIAdj. Both traits identified candidate genes with functions related to metabolite and energy homeostasis, glucose and insulin signaling and behavior. We have identified regions of the genome that have an impact on the intercept, linear and quadratic terms for DBWAvg and DFIAdj. These results provide preliminary evidence that individual growth and feed intake trajectories are impacted by different regions of the genome at different times.

A Genome-Wide Association Study of Chronic Obstructive Pulmonary Disease in Hispanics

PubMed Central

Chen, Wei; Brehm, John M.; Manichaikul, Ani; Cho, Michael H.; Boutaoui, Nadia; Yan, Qi; Burkart, Kristin M.; Enright, Paul L.; Rotter, Jerome I.; Petersen, Hans; Leng, Shuguang; Obeidat, Ma’en; Bossé, Yohan; Brandsma, Corry-Anke; Hao, Ke; Rich, Stephen S.; Powell, Rhea; Avila, Lydiana; Soto-Quiros, Manuel; Silverman, Edwin K.; Tesfaigzi, Yohannes; Barr, R. Graham

2015-01-01

Rationale: Genome-wide association studies (GWAS) of chronic obstructive pulmonary disease (COPD) have identified disease-susceptibility loci, mostly in subjects of European descent. Objectives: We hypothesized that by studying Hispanic populations we would be able to identify unique loci that contribute to COPD pathogenesis in Hispanics but remain undetected in GWAS of non-Hispanic populations. Methods: We conducted a metaanalysis of two GWAS of COPD in independent cohorts of Hispanics in Costa Rica and the United States (Multi-Ethnic Study of Atherosclerosis [MESA]). We performed a replication study of the top single-nucleotide polymorphisms in an independent Hispanic cohort in New Mexico (the Lovelace Smokers Cohort). We also attempted to replicate prior findings from genome-wide studies in non-Hispanic populations in Hispanic cohorts. Measurements and Main Results: We found no genome-wide significant association with COPD in our metaanalysis of Costa Rica and MESA. After combining the top results from this metaanalysis with those from our replication study in the Lovelace Smokers Cohort, we identified two single-nucleotide polymorphisms approaching genome-wide significance for an association with COPD. The first (rs858249, combined P value = 6.1 × 10−8) is near the genes KLHL7 and NUPL2 on chromosome 7. The second (rs286499, combined P value = 8.4 × 10−8) is located in an intron of DLG2. The two most significant single-nucleotide polymorphisms in FAM13A from a previous genome-wide study in non-Hispanics were associated with COPD in Hispanics. Conclusions: We have identified two novel loci (in or near the genes KLHL7/NUPL2 and DLG2) that may play a role in COPD pathogenesis in Hispanic populations. PMID:25584925

A genome-wide association study of chronic obstructive pulmonary disease in Hispanics.

PubMed

Chen, Wei; Brehm, John M; Manichaikul, Ani; Cho, Michael H; Boutaoui, Nadia; Yan, Qi; Burkart, Kristin M; Enright, Paul L; Rotter, Jerome I; Petersen, Hans; Leng, Shuguang; Obeidat, Ma'en; Bossé, Yohan; Brandsma, Corry-Anke; Hao, Ke; Rich, Stephen S; Powell, Rhea; Avila, Lydiana; Soto-Quiros, Manuel; Silverman, Edwin K; Tesfaigzi, Yohannes; Barr, R Graham; Celedón, Juan C

2015-03-01

Genome-wide association studies (GWAS) of chronic obstructive pulmonary disease (COPD) have identified disease-susceptibility loci, mostly in subjects of European descent. We hypothesized that by studying Hispanic populations we would be able to identify unique loci that contribute to COPD pathogenesis in Hispanics but remain undetected in GWAS of non-Hispanic populations. We conducted a metaanalysis of two GWAS of COPD in independent cohorts of Hispanics in Costa Rica and the United States (Multi-Ethnic Study of Atherosclerosis [MESA]). We performed a replication study of the top single-nucleotide polymorphisms in an independent Hispanic cohort in New Mexico (the Lovelace Smokers Cohort). We also attempted to replicate prior findings from genome-wide studies in non-Hispanic populations in Hispanic cohorts. We found no genome-wide significant association with COPD in our metaanalysis of Costa Rica and MESA. After combining the top results from this metaanalysis with those from our replication study in the Lovelace Smokers Cohort, we identified two single-nucleotide polymorphisms approaching genome-wide significance for an association with COPD. The first (rs858249, combined P value = 6.1 × 10(-8)) is near the genes KLHL7 and NUPL2 on chromosome 7. The second (rs286499, combined P value = 8.4 × 10(-8)) is located in an intron of DLG2. The two most significant single-nucleotide polymorphisms in FAM13A from a previous genome-wide study in non-Hispanics were associated with COPD in Hispanics. We have identified two novel loci (in or near the genes KLHL7/NUPL2 and DLG2) that may play a role in COPD pathogenesis in Hispanic populations.

Poisson Approximation-Based Score Test for Detecting Association of Rare Variants.

PubMed

Fang, Hongyan; Zhang, Hong; Yang, Yaning

2016-07-01

Genome-wide association study (GWAS) has achieved great success in identifying genetic variants, but the nature of GWAS has determined its inherent limitations. Under the common disease rare variants (CDRV) hypothesis, the traditional association analysis methods commonly used in GWAS for common variants do not have enough power for detecting rare variants with a limited sample size. As a solution to this problem, pooling rare variants by their functions provides an efficient way for identifying susceptible genes. Rare variant typically have low frequencies of minor alleles, and the distribution of the total number of minor alleles of the rare variants can be approximated by a Poisson distribution. Based on this fact, we propose a new test method, the Poisson Approximation-based Score Test (PAST), for association analysis of rare variants. Two testing methods, namely, ePAST and mPAST, are proposed based on different strategies of pooling rare variants. Simulation results and application to the CRESCENDO cohort data show that our methods are more powerful than the existing methods. © 2016 John Wiley & Sons Ltd/University College London.

Investigation of 95 variants identified in a genome-wide study for association with mortality after acute coronary syndrome

PubMed Central

2011-01-01

Background Genome-wide association studies (GWAS) have identified new candidate genes for the occurrence of acute coronary syndrome (ACS), but possible effects of such genes on survival following ACS have yet to be investigated. Methods We examined 95 polymorphisms in 69 distinct gene regions identified in a GWAS for premature myocardial infarction for their association with post-ACS mortality among 811 whites recruited from university-affiliated hospitals in Kansas City, Missouri. We then sought replication of a positive genetic association in a large, racially diverse cohort of myocardial infarction patients (N = 2284) using Kaplan-Meier survival analyses and Cox regression to adjust for relevant covariates. Finally, we investigated the apparent association further in 6086 additional coronary artery disease patients. Results After Cox adjustment for other ACS risk factors, of 95 SNPs tested in 811 whites only the association with the rs6922269 in MTHFD1L was statistically significant, with a 2.6-fold mortality hazard (P = 0.007). The recessive A/A genotype was of borderline significance in an age- and race-adjusted analysis of the entire combined cohort (N = 3095; P = 0.052), but this finding was not confirmed in independent cohorts (N = 6086). Conclusions We found no support for the hypothesis that the GWAS-identified variants in this study substantially alter the probability of post-ACS survival. Large-scale, collaborative, genome-wide studies may be required in order to detect genetic variants that are robustly associated with survival in patients with coronary artery disease. PMID:21957892

The challenges, advantages and future of phenome-wide association studies.

PubMed

Hebbring, Scott J

2014-02-01

Over the last decade, significant technological breakthroughs have revolutionized human genomic research in the form of genome-wide association studies (GWASs). GWASs have identified thousands of statistically significant genetic variants associated with hundreds of human conditions including many with immunological aetiologies (e.g. multiple sclerosis, ankylosing spondylitis and rheumatoid arthritis). Unfortunately, most GWASs fail to identify clinically significant associations. Identifying biologically significant variants by GWAS also presents a challenge. The GWAS is a phenotype-to-genotype approach. As a complementary/alternative approach to the GWAS, investigators have begun to exploit extensive electronic medical record systems to conduct a genotype-to-phenotype approach when studying human disease - specifically, the phenome-wide association study (PheWAS). Although the PheWAS approach is in its infancy, this method has already demonstrated its capacity to rediscover important genetic associations related to immunological diseases/conditions. Furthermore, PheWAS has the advantage of identifying genetic variants with pleiotropic properties. This is particularly relevant for HLA variants. For example, PheWAS results have demonstrated that the HLA-DRB1 variant associated with multiple sclerosis may also be associated with erythematous conditions including rosacea. Likewise, PheWAS has demonstrated that the HLA-B genotype is not only associated with spondylopathies, uveitis, and variability in platelet count, but may also play an important role in other conditions, such as mastoiditis. This review will discuss and compare general PheWAS methodologies, describe both the challenges and advantages of the PheWAS, and provide insight into the potential directions in which PheWAS may lead. © 2013 The Authors. Immunology Published by John Wiley & Sons Ltd.

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer

PubMed Central

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael; Maranian, Mel J; Bolla, Manjeet K; Wang, Qin; Shah, Mitul; Perkins, Barbara J; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Nielsen, Sune F; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G; Whittemore, Alice S; John, Esther M; Malone, Kathleen E; Gammon, Marilie D; Santella, Regina M; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F; Casey, Graham; Hunter, David J; Gapstur, Susan M; Gaudet, Mia M; Diver, W Ryan; Haiman, Christopher A; Schumacher, Fredrick; Henderson, Brian E; Le Marchand, Loic; Berg, Christine D; Chanock, Stephen; Figueroa, Jonine; Hoover, Robert N; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J; Olson, Janet E; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A; van der Luijt, Rob B; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guénel, Pascal; Truong, Thérèse; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O; González-Neira, Anna; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S; Reed, Malcolm WR; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; TAN, Gie-Hooi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John WM; Collée, J Margriet; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Hopper, John L; Southey, Melissa C; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N; Nord, Silje; Alnaes, Grethe I Grenaker; Giles, Graham G; Milne, Roger L; McLean, Catriona; Canzian, Federico; Trichopoulos, Dmitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Swerdlow, Anthony J; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V; Dörk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Devilee, Peter; Tollenaar, Robert AEM; Seynaeve, Caroline; Van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Slager, Susan; Toland, Amanda E; Ambrosone, Christine B; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul PDP; Kraft, Peter; Dunning, Alison M; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F

2015-01-01

Genome wide association studies (GWAS) and large scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ~14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS comprising of 15,748 breast cancer cases and 18,084 controls, and 46,785 cases and 42,892 controls from 41 studies genotyped on a 200K custom array (iCOGS). Analyses were restricted to women of European ancestry. Genotypes for more than 11M SNPs were generated by imputation using the 1000 Genomes Project reference panel. We identified 15 novel loci associated with breast cancer at P<5×10−8. Combining association analysis with ChIP-Seq data in mammary cell lines and ChIA-PET chromatin interaction data in ENCODE, we identified likely target genes in two regions: SETBP1 on 18q12.3 and RNF115 and PDZK1 on 1q21.1. One association appears to be driven by an amino-acid substitution in EXO1. PMID:25751625

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

PubMed

Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F; Graff, Misa; Fisher, Virginia A; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S; Ahluwalia, Tarunveer S; Chu, Audrey Y; Heard-Costa, Nancy L; Lim, Elise; Perez, Jeremiah; Eicher, John D; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E; Jackson, Anne U; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P S; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A; Stančáková, Alena; Strawbridge, Rona J; Stringham, Heather M; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van der Most, Peter J; Van Vliet-Ostaptchouk, Jana V; Vedantam, Sailaja L; Verweij, Niek; Vink, Jacqueline M; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E; Zubair, Niha; Abecasis, Gonçalo R; Adair, Linda S; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J L; Bartz, Traci M; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M; Buyske, Steve; Campbell, Harry; Chambers, John C; Collins, Francis S; Curran, Joanne E; de Borst, Gert J; de Craen, Anton J M; de Geus, Eco J C; Dedoussis, George; Delgado, Graciela E; den Ruijter, Hester M; Eiriksdottir, Gudny; Eriksson, Anna L; Esko, Tõnu; Faul, Jessica D; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B; Hartman, Catharina A; Hassinen, Maija; Hastie, Nicholas D; Heath, Andrew C; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A; Jørgensen, Marit E; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A; Langenberg, Claudia; Launer, Lenore J; Leander, Karin; Lee, Nanette R; Lind, Lars; Lindgren, Cecilia M; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A F; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G; McKenzie, Colin A; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W; Musk, Aw Bill; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Oldehinkel, Albertine J; Olden, Matthias; Ong, Ken K; Padmanabhan, Sandosh; Peyser, Patricia A; Pisinger, Charlotta; Porteous, David J; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rasmussen-Torvik, Laura J; Rawal, Rajesh; Rice, Treva; Ridker, Paul M; Rose, Lynda M; Bien, Stephanie A; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A; Sennblad, Bengt; Siemelink, Marten A; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A; Stott, David J; Swertz, Morris A; Swift, Amy J; Taylor, Kent D; Tayo, Bamidele O; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R G J; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H R; Wong, Andrew; Wright, Alan F; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A; Boomsma, Dorret I; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I; Chen, Yii-DerIda; Chines, Peter S; Cooper, Richard S; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans-Jörgen; Gudnason, Vilmundur; Haiman, Christopher A; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D; Wouter Jukema, J; Kardia, Sharon L R; Kivimaki, Mika; Kooner, Jaspal S; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I; Metspalu, Andres; Morris, Andrew P; Ohlsson, Claes; Palmer, Lyle J; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M; Qi, Lu; Rauramaa, Rainer; Smith, Blair H; Sørensen, Thorkild I A; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J; Weir, David R; Whitfield, John B; Wilson, James F; Tyrrell, Jessica; Frayling, Timothy M; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S; Hirschhorn, Joel N; Hunter, David J; Spector, Tim D; Strachan, David P; van Duijn, Cornelia M; Heid, Iris M; Mohlke, Karen L; Marchini, Jonathan; Loos, Ruth J F; Kilpeläinen, Tuomas O; Liu, Ching-Ti; Borecki, Ingrid B; North, Kari E; Cupples, L Adrienne

2017-04-26

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

PubMed Central

Justice, Anne E.; Winkler, Thomas W.; Feitosa, Mary F.; Graff, Misa; Fisher, Virginia A.; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S.; Ahluwalia, Tarunveer S.; Chu, Audrey Y.; Heard-Costa, Nancy L.; Lim, Elise; Perez, Jeremiah; Eicher, John D.; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F.; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E.; Jackson, Anne U.; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E.; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P. S.; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A.; Stančáková, Alena; Strawbridge, Rona J.; Stringham, Heather M.; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W.; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vedantam, Sailaja L.; Verweij, Niek; Vink, Jacqueline M.; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E.; Zubair, Niha; Abecasis, Gonçalo R.; Adair, Linda S.; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J. L.; Bartz, Traci M.; Beilby, John; Bergman, Richard N.; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L.; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M.; Buyske, Steve; Campbell, Harry; Chambers, John C.; Collins, Francis S.; Curran, Joanne E.; de Borst, Gert J.; de Craen, Anton J. M.; de Geus, Eco J. C.; Dedoussis, George; Delgado, Graciela E.; den Ruijter, Hester M.; Eiriksdottir, Gudny; Eriksson, Anna L.; Esko, Tõnu; Faul, Jessica D.; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B.; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B.; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas D.; Heath, Andrew C.; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J.; Hollensted, Mette; Holmen, Oddgeir L.; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L.; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A.; Jørgensen, Marit E.; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A.; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K.; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Leander, Karin; Lee, Nanette R.; Lind, Lars; Lindgren, Cecilia M.; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A. F.; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G.; McKenzie, Colin A.; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W.; Musk, AW (Bill); Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M.; Oldehinkel, Albertine J.; Olden, Matthias; Ong, Ken K.; Padmanabhan, Sandosh; Peyser, Patricia A.; Pisinger, Charlotta; Porteous, David J.; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rasmussen-Torvik, Laura J.; Rawal, Rajesh; Rice, Treva; Ridker, Paul M.; Rose, Lynda M.; Bien, Stephanie A.; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A.; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A.; Sennblad, Bengt; Siemelink, Marten A.; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A.; Stott, David J.; Swertz, Morris A.; Swift, Amy J.; Taylor, Kent D.; Tayo, Bamidele O.; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G.; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M.; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R. G. J.; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H. R.; Wong, Andrew; Wright, Alan F.; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A.; Boomsma, Dorret I.; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I.; Chen, Yii-DerIda; Chines, Peter S.; Cooper, Richard S.; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W.; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans- Jörgen; Gudnason, Vilmundur; Haiman, Christopher A.; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D.; Wouter Jukema, J; Kardia, Sharon L. R.; Kivimaki, Mika; Kooner, Jaspal S.; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I.; Metspalu, Andres; Morris, Andrew P.; Ohlsson, Claes; Palmer, Lyle J.; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Smith, Blair H.; Sørensen, Thorkild I. A.; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J.; Weir, David R.; Whitfield, John B.; Wilson, James F.; Tyrrell, Jessica; Frayling, Timothy M.; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S.; Hirschhorn, Joel N.; Hunter, David J.; Spector, Tim D.; Strachan, David P.; van Duijn, Cornelia M.; Heid, Iris M.; Mohlke, Karen L.; Marchini, Jonathan; Loos, Ruth J. F.; Kilpeläinen, Tuomas O.; Liu, Ching-Ti; Borecki, Ingrid B.; North, Kari E.; Cupples, L Adrienne

2017-01-01

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution. PMID:28443625

Research Guidelines in the Era of Large-scale Collaborations: An Analysis of Genome-wide Association Study Consortia

PubMed Central

Austin, Melissa A.; Hair, Marilyn S.; Fullerton, Stephanie M.

2012-01-01

Scientific research has shifted from studies conducted by single investigators to the creation of large consortia. Genetic epidemiologists, for example, now collaborate extensively for genome-wide association studies (GWAS). The effect has been a stream of confirmed disease-gene associations. However, effects on human subjects oversight, data-sharing, publication and authorship practices, research organization and productivity, and intellectual property remain to be examined. The aim of this analysis was to identify all research consortia that had published the results of a GWAS analysis since 2005, characterize them, determine which have publicly accessible guidelines for research practices, and summarize the policies in these guidelines. A review of the National Human Genome Research Institute’s Catalog of Published Genome-Wide Association Studies identified 55 GWAS consortia as of April 1, 2011. These consortia were comprised of individual investigators, research centers, studies, or other consortia and studied 48 different diseases or traits. Only 14 (25%) were found to have publicly accessible research guidelines on consortia websites. The available guidelines provide information on organization, governance, and research protocols; half address institutional review board approval. Details of publication, authorship, data-sharing, and intellectual property vary considerably. Wider access to consortia guidelines is needed to establish appropriate research standards with broad applicability to emerging forms of large-scale collaboration. PMID:22491085

Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis

PubMed Central

Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul

2014-01-01

Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240

Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean.

PubMed

Sonah, Humira; O'Donoughue, Louise; Cober, Elroy; Rajcan, Istvan; Belzile, François

2015-02-01

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Copy number variants in patients with short stature

PubMed Central

van Duyvenvoorde, Hermine A; Lui, Julian C; Kant, Sarina G; Oostdijk, Wilma; Gijsbers, Antoinet CJ; Hoffer, Mariëtte JV; Karperien, Marcel; Walenkamp, Marie JE; Noordam, Cees; Voorhoeve, Paul G; Mericq, Verónica; Pereira, Alberto M; Claahsen-van de Grinten, Hedi L; van Gool, Sandy A; Breuning, Martijn H; Losekoot, Monique; Baron, Jeffrey; Ruivenkamp, Claudia AL; Wit, Jan M

2014-01-01

Height is a highly heritable and classic polygenic trait. Recent genome-wide association studies (GWAS) have revealed that at least 180 genetic variants influence adult height. However, these variants explain only about 10% of the phenotypic variation in height. Genetic analysis of short individuals can lead to the discovery of novel rare gene defects with a large effect on growth. In an effort to identify novel genes associated with short stature, genome-wide analysis for copy number variants (CNVs), using single-nucleotide polymorphism arrays, in 162 patients (149 families) with short stature was performed. Segregation analysis was performed if possible, and genes in CNVs were compared with information from GWAS, gene expression in rodents' growth plates and published information. CNVs were detected in 40 families. In six families, a known cause of short stature was found (SHOX deletion or duplication, IGF1R deletion), in two combined with a de novo potentially pathogenic CNV. Thirty-three families had one or more potentially pathogenic CNVs (n=40). In 24 of these families, segregation analysis could be performed, identifying three de novo CNVs and nine CNVs segregating with short stature. Four were located near loci associated with height in GWAS (ADAMTS17, TULP4, PRKG2/BMP3 and PAPPA). Besides six CNVs known to be causative for short stature, 40 CNVs with possible pathogenicity were identified. Segregation studies and bioinformatics analysis suggested various potential candidate genes. PMID:24065112

Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio.

PubMed

Lloyd-Jones, Luke R; Robinson, Matthew R; Yang, Jian; Visscher, Peter M

2018-04-01

Genome-wide association studies (GWAS) have identified thousands of loci that are robustly associated with complex diseases. The use of linear mixed model (LMM) methodology for GWAS is becoming more prevalent due to its ability to control for population structure and cryptic relatedness and to increase power. The odds ratio (OR) is a common measure of the association of a disease with an exposure ( e.g. , a genetic variant) and is readably available from logistic regression. However, when the LMM is applied to all-or-none traits it provides estimates of genetic effects on the observed 0-1 scale, a different scale to that in logistic regression. This limits the comparability of results across studies, for example in a meta-analysis, and makes the interpretation of the magnitude of an effect from an LMM GWAS difficult. In this study, we derived transformations from the genetic effects estimated under the LMM to the OR that only rely on summary statistics. To test the proposed transformations, we used real genotypes from two large, publicly available data sets to simulate all-or-none phenotypes for a set of scenarios that differ in underlying model, disease prevalence, and heritability. Furthermore, we applied these transformations to GWAS summary statistics for type 2 diabetes generated from 108,042 individuals in the UK Biobank. In both simulation and real-data application, we observed very high concordance between the transformed OR from the LMM and either the simulated truth or estimates from logistic regression. The transformations derived and validated in this study improve the comparability of results from prospective and already performed LMM GWAS on complex diseases by providing a reliable transformation to a common comparative scale for the genetic effects. Copyright © 2018 by the Genetics Society of America.

Genome-wide association study identifies TF as a significant modifier gene of iron metabolism in HFE hemochromatosis.

PubMed

de Tayrac, Marie; Roth, Marie-Paule; Jouanolle, Anne-Marie; Coppin, Hélène; le Gac, Gérald; Piperno, Alberto; Férec, Claude; Pelucchi, Sara; Scotet, Virginie; Bardou-Jacquet, Edouard; Ropert, Martine; Bouvet, Régis; Génin, Emmanuelle; Mosser, Jean; Deugnier, Yves

2015-03-01

Hereditary hemochromatosis (HH) is the most common form of genetic iron loading disease. It is mainly related to the homozygous C282Y/C282Y mutation in the HFE gene that is, however, a necessary but not a sufficient condition to develop clinical and even biochemical HH. This suggests that modifier genes are likely involved in the expressivity of the disease. Our aim was to identify such modifier genes. We performed a genome-wide association study (GWAS) using DNA collected from 474 unrelated C282Y homozygotes. Associations were examined for both quantitative iron burden indices and clinical outcomes with 534,213 single nucleotide polymorphisms (SNP) genotypes, with replication analyses in an independent sample of 748 C282Y homozygotes from four different European centres. One SNP met genome-wide statistical significance for association with transferrin concentration (rs3811647, GWAS p value of 7×10(-9) and replication p value of 5×10(-13)). This SNP, located within intron 11 of the TF gene, had a pleiotropic effect on serum iron (GWAS p value of 4.9×10(-6) and replication p value of 3.2×10(-6)). Both serum transferrin and iron levels were associated with serum ferritin levels, amount of iron removed and global clinical stage (p<0.01). Serum iron levels were also associated with fibrosis stage (p<0.0001). This GWAS, the largest one performed so far in unselected HFE-associated HH (HFE-HH) patients, identified the rs3811647 polymorphism in the TF gene as the only SNP significantly associated with iron metabolism through serum transferrin and iron levels. Because these two outcomes were clearly associated with the biochemical and clinical expression of the disease, an indirect link between the rs3811647 polymorphism and the phenotypic presentation of HFE-HH is likely. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

The GTPase Activating Rap/RanGAP Domain-Like 1 Gene Is Associated with Chicken Reproductive Traits

PubMed Central

Shen, Xu; Zeng, Hua; Xie, Liang; He, Jun; Li, Jian; Xie, Xiujuan; Luo, Chenglong; Xu, Haiping; Zhou, Min; Nie, Qinghua; Zhang, Xiquan

2012-01-01

Background Abundant evidence indicates that chicken reproduction is strictly regulated by the hypothalamic-pituitary-gonad (HPG) axis, and the genes included in the HPG axis have been studied extensively. However, the question remains as to whether any other genes outside of the HPG system are involved in regulating chicken reproduction. The present study was aimed to identify, on a genome-wide level, novel genes associated with chicken reproductive traits. Methodology/Principal Finding Suppressive subtractive hybridization (SSH), genome-wide association study (GWAS), and gene-centric GWAS were used to identify novel genes underlying chicken reproduction. Single marker-trait association analysis with a large population and allelic frequency spectrum analysis were used to confirm the effects of candidate genes. Using two full-sib Ningdu Sanhuang (NDH) chickens, GARNL1 was identified as a candidate gene involved in chicken broodiness by SSH analysis. Its expression levels in the hypothalamus and pituitary were significantly higher in brooding chickens than in non-brooding chickens. GWAS analysis with a NDH two tail sample showed that 2802 SNPs were significantly associated with egg number at 300 d of age (EN300). Among the 2802 SNPs, 2 SNPs composed a block overlapping the GARNL1 gene. The gene-centric GWAS analysis with another two tail sample of NDH showed that GARNL1 was strongly associated with EN300 and age at first egg (AFE). Single marker-trait association analysis in 1301 female NDH chickens confirmed that variation in this gene was related to EN300 and AFE. The allelic frequency spectrum of the SNP rs15700989 among 5 different populations supported the above associations. Western blotting, RT-PCR, and qPCR were used to analyze alternative splicing of the GARNL1 gene. RT-PCR detected 5 transcripts and revealed that the transcript, which has a 141 bp insertion, was expressed in a tissue-specific manner. Conclusions/Significance Our findings demonstrate that the GARNL1 gene contributes to chicken reproductive traits. PMID:22496769

Emerging applications of genome-editing technology to examine functionality of GWAS-associated variants for complex traits.

PubMed

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.

Therapeutic approaches for celiac disease

PubMed Central

Plugis, Nicholas M.; Khosla, Chaitan

2015-01-01

Celiac disease is a common, lifelong autoimmune disorder for which dietary control is the only accepted form of therapy. A strict gluten-free diet is burdensome to patients and can be limited in efficacy, indicating there is an unmet need for novel therapeutic approaches to supplement or supplant dietary therapy. Many molecular events required for disease pathogenesis have been recently characterized and inspire most current and emerging drug-discovery efforts. Genome-wide association studies (GWAS) confirm the importance of human leukocyte antigen genes in our pathogenic model and identify a number of new risk loci in this complex disease. Here, we review the status of both emerging and potential therapeutic strategies in the context of disease pathophysiology. We conclude with a discussion of how genes identified during GWAS and follow-up studies that enhance susceptibility may offer insight into developing novel therapies. PMID:26060114

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

PubMed Central

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

Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism

PubMed Central

Matsuda, Fumio; Nakabayashi, Ryo; Yang, Zhigang; Okazaki, Yozo; Yonemaru, Jun-ichi; Ebana, Kaworu; Yano, Masahiro; Saito, Kazuki

2015-01-01

Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications. PMID:25267402

Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans

PubMed Central

Evans, Daniel S.; Avery, Christy L.; Nalls, Mike A.; Li, Guo; Barnard, John; Smith, Erin N.; Tanaka, Toshiko; Butler, Anne M.; Buxbaum, Sarah G.; Alonso, Alvaro; Arking, Dan E.; Berenson, Gerald S.; Bis, Joshua C.; Buyske, Steven; Carty, Cara L.; Chen, Wei; Chung, Mina K.; Cummings, Steven R.; Deo, Rajat; Eaton, Charles B.; Fox, Ervin R.; Heckbert, Susan R.; Heiss, Gerardo; Hindorff, Lucia A.; Hsueh, Wen-Chi; Isaacs, Aaron; Jamshidi, Yalda; Kerr, Kathleen F.; Liu, Felix; Liu, Yongmei; Lohman, Kurt K.; Magnani, Jared W.; Maher, Joseph F.; Mehra, Reena; Meng, Yan A.; Musani, Solomon K.; Newton-Cheh, Christopher; North, Kari E.; Psaty, Bruce M.; Redline, Susan; Rotter, Jerome I.; Schnabel, Renate B.; Schork, Nicholas J.; Shohet, Ralph V.; Singleton, Andrew B.; Smith, Jonathan D.; Soliman, Elsayed Z.; Srinivasan, Sathanur R.; Taylor, Herman A.; Van Wagoner, David R.; Wilson, James G.; Young, Taylor; Zhang, Zhu-Ming; Zonderman, Alan B.; Evans, Michele K.; Ferrucci, Luigi; Murray, Sarah S.; Tranah, Gregory J.; Whitsel, Eric A.; Reiner, Alex P.; Sotoodehnia, Nona

2016-01-01

The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 × 10−14) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 × 10−4). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 × 10−8) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 × 10−9). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 × 10−7), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS–SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved. PMID:27577874

Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans.

PubMed

Evans, Daniel S; Avery, Christy L; Nalls, Mike A; Li, Guo; Barnard, John; Smith, Erin N; Tanaka, Toshiko; Butler, Anne M; Buxbaum, Sarah G; Alonso, Alvaro; Arking, Dan E; Berenson, Gerald S; Bis, Joshua C; Buyske, Steven; Carty, Cara L; Chen, Wei; Chung, Mina K; Cummings, Steven R; Deo, Rajat; Eaton, Charles B; Fox, Ervin R; Heckbert, Susan R; Heiss, Gerardo; Hindorff, Lucia A; Hsueh, Wen-Chi; Isaacs, Aaron; Jamshidi, Yalda; Kerr, Kathleen F; Liu, Felix; Liu, Yongmei; Lohman, Kurt K; Magnani, Jared W; Maher, Joseph F; Mehra, Reena; Meng, Yan A; Musani, Solomon K; Newton-Cheh, Christopher; North, Kari E; Psaty, Bruce M; Redline, Susan; Rotter, Jerome I; Schnabel, Renate B; Schork, Nicholas J; Shohet, Ralph V; Singleton, Andrew B; Smith, Jonathan D; Soliman, Elsayed Z; Srinivasan, Sathanur R; Taylor, Herman A; Van Wagoner, David R; Wilson, James G; Young, Taylor; Zhang, Zhu-Ming; Zonderman, Alan B; Evans, Michele K; Ferrucci, Luigi; Murray, Sarah S; Tranah, Gregory J; Whitsel, Eric A; Reiner, Alex P; Sotoodehnia, Nona

2016-10-01

The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 × 10 -14 ) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 × 10 -4 ). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 × 10 -8 ) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 × 10 -9 ). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 × 10 -7 ), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS-SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Population Genetic Signal of Polygenic Adaptation

PubMed Central

Berg, Jeremy J.; Coop, Graham

2014-01-01

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153

Aromatase Inhibitor-Associated Bone Fractures: A Case-Cohort GWAS and Functional Genomics

PubMed Central

Liu, Mohan; Goss, Paul E.; Ingle, James N.; Kubo, Michiaki; Furukawa, Yoichi; Batzler, Anthony; Jenkins, Gregory D.; Carlson, Erin E.; Nakamura, Yusuke; Schaid, Daniel J.; Chapman, Judy-Anne W.; Shepherd, Lois E.; Ellis, Matthew J.; Khosla, Sundeep; Wang, Liewei

2014-01-01

Bone fractures are a major consequence of osteoporosis. There is a direct relationship between serum estrogen concentrations and osteoporosis risk. Aromatase inhibitors (AIs) greatly decrease serum estrogen levels in postmenopausal women, and increased incidence of fractures is a side effect of AI therapy. We performed a discovery case-cohort genome-wide association study (GWAS) using samples from 1071 patients, 231 cases and 840 controls, enrolled in the MA.27 breast cancer AI trial to identify genetic factors involved in AI-related fractures, followed by functional genomic validation. Association analyses identified 20 GWAS single nucleotide polymorphism (SNP) signals with P < 5E-06. After removal of signals in gene deserts and those composed entirely of imputed SNPs, we applied a functional validation “decision cascade” that resulted in validation of the CTSZ-SLMO2-ATP5E, TRAM2-TMEM14A, and MAP4K4 genes. These genes all displayed estradiol (E2)-dependent induction in human fetal osteoblasts transfected with estrogen receptor-α, and their knockdown altered the expression of known osteoporosis-related genes. These same genes also displayed SNP-dependent variation in E2 induction that paralleled the SNP-dependent induction of known osteoporosis genes, such as osteoprotegerin. In summary, our case-cohort GWAS identified SNPs in or near CTSZ-SLMO2-ATP5E, TRAM2-TMEM14A, and MAP4K4 that were associated with risk for bone fracture in estrogen receptor-positive breast cancer patients treated with AIs. These genes displayed E2-dependent induction, their knockdown altered the expression of genes related to osteoporosis, and they displayed SNP genotype-dependent variation in E2 induction. These observations may lead to the identification of novel mechanisms associated with fracture risk in postmenopausal women treated with AIs. PMID:25148458

Dissecting the genetic make-up of North-East Sardinia using a large set of haploid and autosomal markers.

PubMed

Pardo, Luba M; Piras, Giovanna; Asproni, Rosanna; van der Gaag, Kristiaan J; Gabbas, Attilio; Ruiz-Linares, Andres; de Knijff, Peter; Monne, Maria; Rizzu, Patrizia; Heutink, Peter

2012-09-01

Sardinia has been used for genetic studies because of its historical isolation, genetic homogeneity and increased prevalence of certain rare diseases. Controversy remains concerning the genetic substructure and the extent of genetic homogeneity, which has implications for the design of genome-wide association studies (GWAS). We revisited this issue by examining the genetic make-up of a sample from North-East Sardinia using a dense set of autosomal, Y chromosome and mitochondrial markers to assess the potential of the sample for GWAS and fine mapping studies. We genotyped individuals for 500K single-nucleotide polymorphisms, Y chromosome markers and sequenced the mitochondrial hypervariable (HVI-HVII) regions. We identified major haplogroups and compared these with other populations. We estimated linkage disequilibrium (LD) and haplotype diversity across autosomal markers, and compared these with other populations. Our results show that within Sardinia there is no major population substructure and thus it can be considered a genetically homogenous population. We did not find substantial differences in the extent of LD in Sardinians compared with other populations. However, we showed that at least 9% of genomic regions in Sardinians differed in LD structure, which is helpful for identifying functional variants using fine mapping. We concluded that Sardinia is a powerful setting for genetic studies including GWAS and other mapping approaches.

Eleven loci with new reproducible genetic associations with allergic disease risk.

PubMed

Ferreira, Manuel A R; Vonk, Judith M; Baurecht, Hansjörg; Marenholz, Ingo; Tian, Chao; Hoffman, Joshua D; Helmer, Quinta; Tillander, Annika; Ullemar, Vilhelmina; Lu, Yi; Rüschendorf, Franz; Hinds, David A; Hübner, Norbert; Weidinger, Stephan; Magnusson, Patrik K E; Jorgenson, Eric; Lee, Young-Ae; Boomsma, Dorret I; Karlsson, Robert; Almqvist, Catarina; Koppelman, Gerard H; Paternoster, Lavinia

2018-04-19

A recent genome-wide association study (GWAS) identified 99 loci that contain genetic risk variants shared between asthma, hay fever, and eczema. Many more risk loci shared between these common allergic diseases remain to be discovered, which could point to new therapeutic opportunities. We sought to identify novel risk loci shared between asthma, hay fever, and eczema by applying a gene-based test of association to results from a published GWAS that included data from 360,838 subjects. We used approximate conditional analysis to adjust the results from the published GWAS for the effects of the top risk variants identified in that study. We then analyzed the adjusted GWAS results with the EUGENE gene-based approach, which combines evidence for association with disease risk across regulatory variants identified in different tissues. Novel gene-based associations were followed up in an independent sample of 233,898 subjects from the UK Biobank study. Of the 19,432 genes tested, 30 had a significant gene-based association at a Bonferroni-corrected P value of 2.5 × 10 -6 . Of these, 20 were also significantly associated (P < .05/30 = .0016) with disease risk in the replication sample, including 19 that were located in 11 loci not reported to contain allergy risk variants in previous GWASs. Among these were 9 genes with a known function that is directly relevant to allergic disease: FOSL2, VPRBP, IPCEF1, PRR5L, NCF4, APOBR, IL27, ATXN2L, and LAT. For 4 genes (eg, ATXN2L), a genetically determined decrease in gene expression was associated with decreased allergy risk, and therefore drugs that inhibit gene expression or function are predicted to ameliorate disease symptoms. The opposite directional effect was observed for 14 genes, including IL27, a cytokine known to suppress T H 2 responses. Using a gene-based approach, we identified 11 risk loci for allergic disease that were not reported in previous GWASs. Functional studies that investigate the contribution of the 19 associated genes to the pathophysiology of allergic disease and assess their therapeutic potential are warranted. Copyright © 2018 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

A comparison of Cox and logistic regression for use in genome-wide association studies of cohort and case-cohort design.

PubMed

Staley, James R; Jones, Edmund; Kaptoge, Stephen; Butterworth, Adam S; Sweeting, Michael J; Wood, Angela M; Howson, Joanna M M

2017-06-01

Logistic regression is often used instead of Cox regression to analyse genome-wide association studies (GWAS) of single-nucleotide polymorphisms (SNPs) and disease outcomes with cohort and case-cohort designs, as it is less computationally expensive. Although Cox and logistic regression models have been compared previously in cohort studies, this work does not completely cover the GWAS setting nor extend to the case-cohort study design. Here, we evaluated Cox and logistic regression applied to cohort and case-cohort genetic association studies using simulated data and genetic data from the EPIC-CVD study. In the cohort setting, there was a modest improvement in power to detect SNP-disease associations using Cox regression compared with logistic regression, which increased as the disease incidence increased. In contrast, logistic regression had more power than (Prentice weighted) Cox regression in the case-cohort setting. Logistic regression yielded inflated effect estimates (assuming the hazard ratio is the underlying measure of association) for both study designs, especially for SNPs with greater effect on disease. Given logistic regression is substantially more computationally efficient than Cox regression in both settings, we propose a two-step approach to GWAS in cohort and case-cohort studies. First to analyse all SNPs with logistic regression to identify associated variants below a pre-defined P-value threshold, and second to fit Cox regression (appropriately weighted in case-cohort studies) to those identified SNPs to ensure accurate estimation of association with disease.

Genome-Wide Association Study with Targeted and Non-targeted NMR Metabolomics Identifies 15 Novel Loci of Urinary Human Metabolic Individuality

PubMed Central

Raffler, Johannes; Friedrich, Nele; Arnold, Matthias; Kacprowski, Tim; Rueedi, Rico; Altmaier, Elisabeth; Bergmann, Sven; Budde, Kathrin; Gieger, Christian; Homuth, Georg; Pietzner, Maik; Römisch-Margl, Werner; Strauch, Konstantin; Völzke, Henry; Waldenberger, Melanie; Wallaschofski, Henri; Nauck, Matthias; Völker, Uwe; Kastenmüller, Gabi; Suhre, Karsten

2015-01-01

Genome-wide association studies with metabolic traits (mGWAS) uncovered many genetic variants that influence human metabolism. These genetically influenced metabotypes (GIMs) contribute to our metabolic individuality, our capacity to respond to environmental challenges, and our susceptibility to specific diseases. While metabolic homeostasis in blood is a well investigated topic in large mGWAS with over 150 known loci, metabolic detoxification through urinary excretion has only been addressed by few small mGWAS with only 11 associated loci so far. Here we report the largest mGWAS to date, combining targeted and non-targeted 1H NMR analysis of urine samples from 3,861 participants of the SHIP-0 cohort and 1,691 subjects of the KORA F4 cohort. We identified and replicated 22 loci with significant associations with urinary traits, 15 of which are new (HIBCH, CPS1, AGXT, XYLB, TKT, ETNPPL, SLC6A19, DMGDH, SLC36A2, GLDC, SLC6A13, ACSM3, SLC5A11, PNMT, SLC13A3). Two-thirds of the urinary loci also have a metabolite association in blood. For all but one of the 6 loci where significant associations target the same metabolite in blood and urine, the genetic effects have the same direction in both fluids. In contrast, for the SLC5A11 locus, we found increased levels of myo-inositol in urine whereas mGWAS in blood reported decreased levels for the same genetic variant. This might indicate less effective re-absorption of myo-inositol in the kidneys of carriers. In summary, our study more than doubles the number of known loci that influence urinary phenotypes. It thus allows novel insights into the relationship between blood homeostasis and its regulation through excretion. The newly discovered loci also include variants previously linked to chronic kidney disease (CPS1, SLC6A13), pulmonary hypertension (CPS1), and ischemic stroke (XYLB). By establishing connections from gene to disease via metabolic traits our results provide novel hypotheses about molecular mechanisms involved in the etiology of diseases. PMID:26352407

Comparing power and precision of within-breed and multibreed genome-wide association studies of production traits using whole-genome sequence data for 5 French and Danish dairy cattle breeds.

PubMed

van den Berg, Irene; Boichard, Didier; Lund, Mogens Sandø

2016-11-01

The objective of this study was to compare mapping precision and power of within-breed and multibreed genome-wide association studies (GWAS) and to compare the results obtained by the multibreed GWAS with 3 meta-analysis methods. The multibreed GWAS was expected to improve mapping precision compared with a within-breed GWAS because linkage disequilibrium is conserved over shorter distances across breeds than within breeds. The multibreed GWAS was also expected to increase detection power for quantitative trait loci (QTL) segregating across breeds. GWAS were performed for production traits in dairy cattle, using imputed full genome sequences of 16,031 bulls, originating from 6 French and Danish dairy cattle populations. Our results show that a multibreed GWAS can be a valuable tool for the detection and fine mapping of quantitative trait loci. The number of QTL detected with the multibreed GWAS was larger than the number detected by the within-breed GWAS, indicating an increase in power, especially when the 2 Holstein populations were combined. The largest number of QTL was detected when all populations were combined. The analysis combining all breeds was, however, dominated by Holstein, and QTL segregating in other breeds but not in Holstein were sometimes overshadowed by larger QTL segregating in Holstein. Therefore, the GWAS combining all breeds except Holstein was useful to detect such peaks. Combining all breeds except Holstein resulted in smaller QTL intervals on average, but this outcome was not the case when the Holstein populations were included in the analysis. Although no decrease in the average QTL size was observed, mapping precision did improve for several QTL. Out of 3 different multibreed meta-analysis methods, the weighted z-scores model resulted in the most similar results to the full multibreed GWAS and can be useful as an alternative to a full multibreed GWAS. Differences between the multibreed GWAS and the meta-analyses were larger when different breeds were combined than when the 2 Holstein populations were combined. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Genome-wide pathway-based association analysis identifies risk pathways associated with Parkinson's disease.

PubMed

Zhang, Mingming; Mu, Hongbo; Shang, Zhenwei; Kang, Kai; Lv, Hongchao; Duan, Lian; Li, Jin; Chen, Xinren; Teng, Yanbo; Jiang, Yongshuai; Zhang, Ruijie

2017-01-06

Parkinson's disease (PD) is the second most common neurodegenerative disease. It is generally believed that it is influenced by both genetic and environmental factors, but the precise pathogenesis of PD is unknown to date. In this study, we performed a pathway analysis based on genome-wide association study (GWAS) to detect risk pathways of PD in three GWAS datasets. We first mapped all SNP markers to autosomal genes in each GWAS dataset. Then, we evaluated gene risk values using the minimum P-value of the tagSNPs. We took a pathway as a unit to identify the risk pathways based on the cumulative risks of the genes in the pathway. Finally, we combine the analysis results of the three datasets to detect the high risk pathways associated with PD. We found there were five same pathways in the three datasets. Besides, we also found there were five pathways which were shared in two datasets. Most of these pathways are associated with nervoussystem. Five pathways had been reported to be PD-related pathways in the previous literature. Our findings also implied that there was a close association between immune response and PD. Continued investigation of these pathways will further help us explain the pathogenesis of PD. Copyright © 2016. Published by Elsevier Ltd.

Common variants identified in genome-wide association studies of testicular germ cell tumour: an update, biological insights and clinical application.

PubMed

Litchfield, K; Shipley, J; Turnbull, C

2015-01-01

Testicular germ cell tumour (TGCT) is the most common cause of cancer in young men (aged 15-45 years) in many populations. Multiple genome-wide association studies (GWAS) of TGCT have now been conducted, yielding over 25 disease-associated single-nucleotide polymorphism (SNP)s at 19 independent loci. The genes at these loci have provided rich biological and genetic insight into possible mechanisms underlying testicular germ cell oncogenesis. In this review, we summarize these mechanisms which can be grouped into five distinct categories: KIT/KITLG signalling, other pathways of male germ cell development/differentiation, telomerase function, microtubule assembly and DNA damage repair. The TGCT risk markers identified through GWAS include individual SNPs carrying per allele odds ratios (OR) in excess of 2.5. These ORs are among the highest reported in GWAS of any cancer type, hence suggesting a potential clinical utility in risk determination. Here, we present analysis of such an approach, using polygenic risk scores to calculate the combined effect of all risk loci on overall TGCT risk and discuss how a potential screening strategy may fit within a broader clinical context. © 2015 American Society of Andrology and European Academy of Andrology.

A Genome-Wide Association Study on the Seedless Phenotype in Banana (Musa spp.) Reveals the Potential of a Selected Panel to Detect Candidate Genes in a Vegetatively Propagated Crop.

PubMed

Sardos, Julie; Rouard, Mathieu; Hueber, Yann; Cenci, Alberto; Hyma, Katie E; van den Houwe, Ines; Hribova, Eva; Courtois, Brigitte; Roux, Nicolas

2016-01-01

Banana (Musa sp.) is a vegetatively propagated, low fertility, potentially hybrid and polyploid crop. These qualities make the breeding and targeted genetic improvement of this crop a difficult and long process. The Genome-Wide Association Study (GWAS) approach is becoming widely used in crop plants and has proven efficient to detecting candidate genes for traits of interest, especially in cereals. GWAS has not been applied yet to a vegetatively propagated crop. However, successful GWAS in banana would considerably help unravel the genomic basis of traits of interest and therefore speed up this crop improvement. We present here a dedicated panel of 105 accessions of banana, freely available upon request, and their corresponding GBS data. A set of 5,544 highly reliable markers revealed high levels of admixture in most accessions, except for a subset of 33 individuals from Papua. A GWAS on the seedless phenotype was then successfully applied to the panel. By applying the Mixed Linear Model corrected for both kinship and structure as implemented in TASSEL, we detected 13 candidate genomic regions in which we found a number of genes potentially linked with the seedless phenotype (i.e. parthenocarpy combined with female sterility). An additional GWAS performed on the unstructured Papuan subset composed of 33 accessions confirmed six of these regions as candidate. Out of both sets of analyses, one strong candidate gene for female sterility, a putative orthologous gene to Histidine Kinase CKI1, was identified. The results presented here confirmed the feasibility and potential of GWAS when applied to small sets of banana accessions, at least for traits underpinned by a few loci. As phenotyping in banana is extremely space and time-consuming, this latest finding is of particular importance in the context of banana improvement.

A Genome-Wide Association Study on the Seedless Phenotype in Banana (Musa spp.) Reveals the Potential of a Selected Panel to Detect Candidate Genes in a Vegetatively Propagated Crop

PubMed Central

Sardos, Julie; Rouard, Mathieu; Hueber, Yann; Cenci, Alberto; Hyma, Katie E.; van den Houwe, Ines; Hribova, Eva; Courtois, Brigitte; Roux, Nicolas

2016-01-01

Banana (Musa sp.) is a vegetatively propagated, low fertility, potentially hybrid and polyploid crop. These qualities make the breeding and targeted genetic improvement of this crop a difficult and long process. The Genome-Wide Association Study (GWAS) approach is becoming widely used in crop plants and has proven efficient to detecting candidate genes for traits of interest, especially in cereals. GWAS has not been applied yet to a vegetatively propagated crop. However, successful GWAS in banana would considerably help unravel the genomic basis of traits of interest and therefore speed up this crop improvement. We present here a dedicated panel of 105 accessions of banana, freely available upon request, and their corresponding GBS data. A set of 5,544 highly reliable markers revealed high levels of admixture in most accessions, except for a subset of 33 individuals from Papua. A GWAS on the seedless phenotype was then successfully applied to the panel. By applying the Mixed Linear Model corrected for both kinship and structure as implemented in TASSEL, we detected 13 candidate genomic regions in which we found a number of genes potentially linked with the seedless phenotype (i.e. parthenocarpy combined with female sterility). An additional GWAS performed on the unstructured Papuan subset composed of 33 accessions confirmed six of these regions as candidate. Out of both sets of analyses, one strong candidate gene for female sterility, a putative orthologous gene to Histidine Kinase CKI1, was identified. The results presented here confirmed the feasibility and potential of GWAS when applied to small sets of banana accessions, at least for traits underpinned by a few loci. As phenotyping in banana is extremely space and time-consuming, this latest finding is of particular importance in the context of banana improvement. PMID:27144345

Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome-wide associations.

PubMed

Gupta, Mayetri; Cheung, Ching-Lung; Hsu, Yi-Hsiang; Demissie, Serkalem; Cupples, L Adrienne; Kiel, Douglas P; Karasik, David

2011-06-01

Genome-wide association studies (GWAS) using high-density genotyping platforms offer an unbiased strategy to identify new candidate genes for osteoporosis. It is imperative to be able to clearly distinguish signal from noise by focusing on the best phenotype in a genetic study. We performed GWAS of multiple phenotypes associated with fractures [bone mineral density (BMD), bone quantitative ultrasound (QUS), bone geometry, and muscle mass] with approximately 433,000 single-nucleotide polymorphisms (SNPs) and created a database of resulting associations. We performed analysis of GWAS data from 23 phenotypes by a novel modification of a block clustering algorithm followed by gene-set enrichment analysis. A data matrix of standardized regression coefficients was partitioned along both axes--SNPs and phenotypes. Each partition represents a distinct cluster of SNPs that have similar effects over a particular set of phenotypes. Application of this method to our data shows several SNP-phenotype connections. We found a strong cluster of association coefficients of high magnitude for 10 traits (BMD at several skeletal sites, ultrasound measures, cross-sectional bone area, and section modulus of femoral neck and shaft). These clustered traits were highly genetically correlated. Gene-set enrichment analyses indicated the augmentation of genes that cluster with the 10 osteoporosis-related traits in pathways such as aldosterone signaling in epithelial cells, role of osteoblasts, osteoclasts, and chondrocytes in rheumatoid arthritis, and Parkinson signaling. In addition to several known candidate genes, we also identified PRKCH and SCNN1B as potential candidate genes for multiple bone traits. In conclusion, our mining of GWAS results revealed the similarity of association results between bone strength phenotypes that may be attributed to pleiotropic effects of genes. This knowledge may prove helpful in identifying novel genes and pathways that underlie several correlated phenotypes, as well as in deciphering genetic and phenotypic modularity underlying osteoporosis risk. Copyright © 2011 American Society for Bone and Mineral Research.

Hemoglobin genetics: recent contributions of GWAS and gene editing

PubMed Central

Smith, Elenoe C.; Orkin, Stuart H.

2016-01-01

The β-hemoglobinopathies are inherited disorders resulting from altered coding potential or expression of the adult β-globin gene. Impaired expression of β-globin reduces adult hemoglobin (α2β2) production, the hallmark of β-thalassemia. A single-base mutation at codon 6 leads to formation of HbS (α2βS2) and sickle cell disease. While the basis of these diseases is known, therapy remains largely supportive. Bone marrow transplantation is the only curative therapy. Patients with elevated levels of fetal hemoglobin (HbF, α2γ2) as adults exhibit reduced symptoms and enhanced survival. The β-globin gene locus is a paradigm of cell- and developmental stage-specific regulation. Although the principal erythroid cell transcription factors are known, mechanisms responsible for silencing of the γ-globin gene were obscure until application of genome-wide association studies (GWAS). Here, we review findings in the field. GWAS identified BCL11A as a candidate negative regulator of γ-globin expression. Subsequent studies have established BCL11A as a quantitative repressor. GWAS-related single-nucleotide polymorphisms lie within an essential erythroid enhancer of the BCL11A gene. Disruption of a discrete region within the enhancer reduces BCL11A expression and induces HbF expression, providing the basis for gene therapy using gene editing tools. A recently identified, second silencing factor, leukemia/lymphoma-related factor/Pokemon, shares features with BCL11A, including interaction with the nucleosome remodeling deacetylase repressive complex. These findings suggest involvement of a common pathway for HbF silencing. In addition, we discuss other factors that may be involved in γ-globin gene silencing and their potential manipulation for therapeutic benefit in treating the β-hemoglobinopathies. PMID:27340226

Combined linkage and association analyses identify a novel locus for obesity near PROX1 in Asians.

PubMed

Kim, Hyun-Jin; Yoo, Yun Joo; Ju, Young Seok; Lee, Seungbok; Cho, Sung-Il; Sung, Joohon; Kim, Jong-Il; Seo, Jeong-Sun

2013-11-01

Although genome-wide association studies (GWAS) have substantially contributed to understanding the genetic architecture, unidentified variants for complex traits remain an issue. One of the efficient approaches is the improvement of the power of GWAS scan by weighting P values with prior linkage signals. Our objective was to identify the novel candidates for obesity in Asian populations by using genemapping strategies that combine linkage and association analyses. To obtain linkage information for body mass index (BMI) and waist circumference (WC), we performed a multipoint genome-wide linkage study in an isolated Mongolian sample of 1,049 individuals from 74 families. Next, a family-based GWAS, which integrates within- and between-family components, was performed using the genotype data of 756 individuals of the Mongolian sample, and P values for association were weighted using linkage information obtained previously. For both BMI (LOD = 3.3) and WC (LOD = 2.6), the highest linkage peak was discovered at chromosome 10q11.22. In family-based GWAS combined with linkage information, six single-nucleotide polymorphisms (SNPs) for BMI and five SNPs for WC reached a significant level of association (linkage weighted P < 1 × 10(-5) ). Of these, only one of the SNPs associated with WC (rs1704198) was replicated in 327 Korean families comprising 1,301 individuals. This SNP was located in the proximity of the prosperorelated homeobox 1 (PROX1) gene, the function of which was validated previously in a mouse model. Our powerful strategic analysis enabled the discovery of a novel candidate gene, PROX1, associated with WC in an Asian population. Copyright © 2012 The Obesity Society.

A methodology for multivariate phenotype-based genome-wide association studies to mine pleiotropic genes.

PubMed

Park, Sung Hee; Lee, Ji Young; Kim, Sangsoo

2011-01-01

Current Genome-Wide Association Studies (GWAS) are performed in a single trait framework without considering genetic correlations between important disease traits. Hence, the GWAS have limitations in discovering genetic risk factors affecting pleiotropic effects. This work reports a novel data mining approach to discover patterns of multiple phenotypic associations over 52 anthropometric and biochemical traits in KARE and a new analytical scheme for GWAS of multivariate phenotypes defined by the discovered patterns. This methodology applied to the GWAS for multivariate phenotype highLDLhighTG derived from the predicted patterns of the phenotypic associations. The patterns of the phenotypic associations were informative to draw relations between plasma lipid levels with bone mineral density and a cluster of common traits (Obesity, hypertension, insulin resistance) related to Metabolic Syndrome (MS). A total of 15 SNPs in six genes (PAK7, C20orf103, NRIP1, BCL2, TRPM3, and NAV1) were identified for significant associations with highLDLhighTG. Noteworthy findings were that the significant associations included a mis-sense mutation (PAK7:R335P), a frame shift mutation (C20orf103) and SNPs in splicing sites (TRPM3). The six genes corresponded to rat and mouse quantitative trait loci (QTLs) that had shown associations with the common traits such as the well characterized MS and even tumor susceptibility. Our findings suggest that the six genes may play important roles in the pleiotropic effects on lipid metabolism and the MS, which increase the risk of Type 2 Diabetes and cardiovascular disease. The use of the multivariate phenotypes can be advantageous in identifying genetic risk factors, accounting for the pleiotropic effects when the multivariate phenotypes have a common etiological pathway.

Integrative approaches for large-scale transcriptome-wide association studies

PubMed Central

Gusev, Alexander; Ko, Arthur; Shi, Huwenbo; Bhatia, Gaurav; Chung, Wonil; Penninx, Brenda W J H; Jansen, Rick; de Geus, Eco JC; Boomsma, Dorret I; Wright, Fred A; Sullivan, Patrick F; Nikkola, Elina; Alvarez, Marcus; Civelek, Mete; Lusis, Aldons J.; Lehtimäki, Terho; Raitoharju, Emma; Kähönen, Mika; Seppälä, Ilkka; Raitakari, Olli T.; Kuusisto, Johanna; Laakso, Markku; Price, Alkes L.; Pajukanta, Päivi; Pasaniuc, Bogdan

2016-01-01

Many genetic variants influence complex traits by modulating gene expression, thus altering the abundance levels of one or multiple proteins. Here, we introduce a powerful strategy that integrates gene expression measurements with summary association statistics from large-scale genome-wide association studies (GWAS) to identify genes whose cis-regulated expression is associated to complex traits. We leverage expression imputation to perform a transcriptome wide association scan (TWAS) to identify significant expression-trait associations. We applied our approaches to expression data from blood and adipose tissue measured in ~3,000 individuals overall. We imputed gene expression into GWAS data from over 900,000 phenotype measurements to identify 69 novel genes significantly associated to obesity-related traits (BMI, lipids, and height). Many of the novel genes are associated with relevant phenotypes in the Hybrid Mouse Diversity Panel. Our results showcase the power of integrating genotype, gene expression and phenotype to gain insights into the genetic basis of complex traits. PMID:26854917

High density genetic mapping identifies new susceptibility loci for rheumatoid arthritis

PubMed Central

Eyre, Steve; Bowes, John; Diogo, Dorothée; Lee, Annette; Barton, Anne; Martin, Paul; Zhernakova, Alexandra; Stahl, Eli; Viatte, Sebastien; McAllister, Kate; Amos, Christopher I.; Padyukov, Leonid; Toes, Rene E.M.; Huizinga, Tom W.J.; Wijmenga, Cisca; Trynka, Gosia; Franke, Lude; Westra, Harm-Jan; Alfredsson, Lars; Hu, Xinli; Sandor, Cynthia; de Bakker, Paul I.W.; Davila, Sonia; Khor, Chiea Chuen; Heng, Khai Koon; Andrews, Robert; Edkins, Sarah; Hunt, Sarah E; Langford, Cordelia; Symmons, Deborah; Concannon, Pat; Onengut-Gumuscu, Suna; Rich, Stephen S; Deloukas, Panos; Gonzalez-Gay, Miguel A.; Rodriguez-Rodriguez, Luis; Ärlsetig, Lisbeth; Martin, Javier; Rantapää-Dahlqvist, Solbritt; Plenge, Robert; Raychaudhuri, Soumya; Klareskog, Lars; Gregersen, Peter K; Worthington, Jane

2012-01-01

Summary Using the Immunochip custom single nucleotide polymorphism (SNP) array, designed for dense genotyping of 186 genome wide association study (GWAS) confirmed loci we analysed 11,475 rheumatoid arthritis cases of European ancestry and 15,870 controls for 129,464 markers. The data were combined in meta-analysis with GWAS data from additional independent cases (n=2,363) and controls (n=17,872). We identified fourteen novel loci; nine were associated with rheumatoid arthritis overall and 5 specifically in anti-citrillunated peptide antibody positive disease, bringing the number of confirmed European ancestry rheumatoid arthritis loci to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at six loci and association to low frequency variants (minor allele frequency <0.05) at 4 loci. Bioinformatic analysis of the data generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations. PMID:23143596

Replicability and Robustness of GWAS for Behavioral Traits

PubMed Central

Rietveld, Cornelius A.; Conley, Dalton; Eriksson, Nicholas; Esko, Tõnu; Medland, Sarah E.; Vinkhuyzen, Anna A.E.; Yang, Jian; Boardman, Jason D.; Chabris, Christopher F.; Dawes, Christopher T.; Domingue, Benjamin W.; Hinds, David A.; Johannesson, Magnus; Kiefer, Amy K.; Laibson, David; Magnusson, Patrik K. E.; Mountain, Joanna L.; Oskarsson, Sven; Rostapshova, Olga; Teumer, Alexander; Tung, Joyce Y.; Visscher, Peter M.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.

2015-01-01

A recent genome-wide association study (GWAS) of educational attainment identified three single-nucleotide polymorphisms (SNPs) that, despite their small effect sizes (each R2 ≈ 0.02%), reached genome-wide significance (p < 5×10−8) in a large discovery sample and replicated in an independent sample (p < 0.05). The study also reported associations between educational attainment and indices of SNPs called “polygenic scores.” We evaluate the robustness of these findings. Study 1 finds that all three SNPs replicate in another large (N = 34,428) independent sample. We also find that the scores remain predictive (R2 ≈ 2%) with stringent controls for stratification (Study 2) and in new within-family analyses (Study 3). Our results show that large and therefore well-powered GWASs can identify replicable genetic associations with behavioral traits. The small effect sizes of individual SNPs are likely to be a major contributing explanation for the striking contrast between our results and the disappointing replication record of most candidate gene studies. PMID:25287667

Systems Genetics Identifies a Novel Regulatory Domain of Amylose Synthesis1[OPEN

PubMed Central

Parween, Sabiha; Samson, Irene; de Guzman, Krishna; Alhambra, Crisline Mae; Misra, Gopal

2017-01-01

A deeper understanding of the regulation of starch biosynthesis in rice (Oryza sativa) endosperm is crucial in tailoring digestibility without sacrificing grain quality. In this study, significant association peaks on chromosomes 6 and 7 were identified through a genomewide association study (GWAS) of debranched starch structure from grains of a 320 indica rice diversity panel using genotyping data from the high-density rice array. A systems genetics approach that interrelates starch structure data from GWAS to functional pathways from a gene regulatory network identified known genes with high correlation to the proportion of amylose and amylopectin. An SNP in the promoter region of Granule Bound Starch Synthase I was identified along with seven other SNPs to form haplotypes that discriminate samples into different phenotypic ranges of amylose. A GWAS peak on chromosome 7 between LOC_Os07g11020 and LOC_Os07g11520 indexed by a nonsynonymous SNP mutation on exon 5 of a bHLH transcription factor was found to elevate the proportion of amylose at the expense of reduced short-chain amylopectin. Linking starch structure with starch digestibility by determining the kinetics of cooked grain amylolysis of selected haplotypes revealed strong association of starch structure with estimated digestibility kinetics. Combining all results from grain quality genomics, systems genetics, and digestibility phenotyping, we propose target haplotypes for fine-tuning starch structure in rice through marker-assisted breeding that can be used to alter the digestibility of rice grain, thus offering rice consumers a new diet-based intervention to mitigate the impact of nutrition-related noncommunicable diseases. PMID:27881726

Genome-wide association study (GWAS) for molar-incisor hypomineralization (MIH).

PubMed

Kühnisch, Jan; Thiering, Elisabeth; Heitmüller, Daniela; Tiesler, Carla M T; Grallert, Harald; Heinrich-Weltzien, Roswitha; Hickel, Reinhard; Heinrich, Joachim

2014-01-01

This genome-wide association study (GWAS) investigated the relationship between molar-incisor hypomineralization (MIH) and possible genetic loci. Clinical and genetic data from the 10-year follow-up of 668 children from the Munich GINI-plus and LISA-plus birth cohort studies were analyzed. The dental examinations included the diagnosis of MIH according to the criteria of the European Academy of Paediatric Dentistry (EAPD). Children with MIH were categorized as those with a minimum of one hypomineralized first permanent molar. A GWAS was implemented following a quality-control step and an additive genetic effect was assumed. A total of 2,013,491 single-nucleotide polymorphisms (SNPs) were available for analysis. Rs13058467, which is located near the SCUBE1 gene on chromosome 22 (p < 3.72E-7), was identified as a possible locus linked to MIH when using a threshold of p value <1E-6. After considering the limitations of the present study (e.g., limited sample size and lack of an independent replication sample), it can be concluded that (1) replication analyses in an independent cohort study are strongly recommended and (2) large-scale and well-powered studies are needed to investigate a possible genetic link to MIH.

Mapping Adipose and Muscle Tissue Expression Quantitative Trait Loci in African Americans to Identify Genes for Type 2 Diabetes and Obesity

PubMed Central

Sajuthi, Satria P.; Sharma, Neeraj K.; Chou, Jeff W.; Palmer, Nicholette D.; McWilliams, David R.; Beal, John; Comeau, Mary E.; Ma, Lijun; Calles-Escandon, Jorge; Demons, Jamehl; Rogers, Samantha; Cherry, Kristina; Menon, Lata; Kouba, Ethel; Davis, Donna; Burris, Marcie; Byerly, Sara J.; Ng, Maggie C.Y.; Maruthur, Nisa M.; Patel, Sanjay R.; Bielak, Lawrence F.; Lange, Leslie; Guo, Xiuqing; Sale, Michèle M.; Chan, Kei Hang; Monda, Keri L.; Chen, Gary K.; Taylor, Kira; Palmer, Cameron; Edwards, Todd L; North, Kari E.; Haiman, Christopher A.; Bowden, Donald W.; Freedman, Barry I.; Langefeld, Carl D.; Das, Swapan K.

2016-01-01

Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes were evaluated by mining GWAS datasets. eQTL analysis identified 1,971 and 2,078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2, were identified in both tissues. 62.1% of top cis-eSNPs were within ±50kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes, (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically-regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes. PMID:27193597

Genome-wide association study of telomere length among South Asians identifies a second RTEL1 association signal.

PubMed

Delgado, Dayana A; Zhang, Chenan; Chen, Lin S; Gao, Jianjun; Roy, Shantanu; Shinkle, Justin; Sabarinathan, Mekala; Argos, Maria; Tong, Lin; Ahmed, Alauddin; Islam, Tariqul; Rakibuz-Zaman, Muhammad; Sarwar, Golam; Shahriar, Hasan; Rahman, Mahfuzar; Yunus, Mohammad; Jasmine, Farzana; Kibriya, Muhammad G; Ahsan, Habibul; Pierce, Brandon L

2018-01-01

Leucocyte telomere length (TL) is a potential biomarker of ageing and risk for age-related disease. Leucocyte TL is heritable and shows substantial differences by race/ethnicity. Recent genome-wide association studies (GWAS) report ~10 loci harbouring SNPs associated with leucocyte TL, but these studies focus primarily on populations of European ancestry. This study aims to enhance our understanding of genetic determinants of TL across populations. We performed a GWAS of TL using data on 5075 Bangladeshi adults. We measured TL using one of two technologies (qPCR or a Luminex-based method) and used standardised variables as TL phenotypes. Our results replicate previously reported associations in the TERC and TERT regions (P=2.2×10 -8 and P=6.4×10 -6 , respectively). We observed a novel association signal in the RTEL1 gene (intronic SNP rs2297439; P=2.82×10 -7 ) that is independent of previously reported TL-associated SNPs in this region. The minor allele for rs2297439 is common in South Asian populations (≥0.25) but at lower frequencies in other populations (eg, 0.07 in Northern Europeans). Among the eight other previously reported association signals, all were directionally consistent with our study, but only rs8105767 ( ZNF208 ) was nominally significant (P=0.003). SNP-based heritability estimates were as high as 44% when analysing close relatives but much lower when analysing distant relatives only. In this first GWAS of TL in a South Asian population, we replicate some, but not all, of the loci reported in prior GWAS of individuals of European ancestry, and we identify a novel second association signal at the RTEL1 locus. © 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.

Genome-wide Association Studies from the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative | Office of Cancer Genomics

Cancer.gov

CGEMS identifies common inherited genetic variations associated with a number of cancers, including breast and prostate. Data from these genome-wide association studies (GWAS) are available through the Division of Cancer Epidemiology & Genetics website.

Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer’s disease

PubMed Central

Lambert, Jean-Charles; Ibrahim-Verbaas, Carla A; Harold, Denise; Naj, Adam C; Sims, Rebecca; Bellenguez, Céline; Jun, Gyungah; DeStefano, Anita L; Bis, Joshua C; Beecham, Gary W; Grenier-Boley, Benjamin; Russo, Giancarlo; Thornton-Wells, Tricia A; Jones, Nicola; Smith, Albert V; Chouraki, Vincent; Thomas, Charlene; Ikram, M Arfan; Zelenika, Diana; Vardarajan, Badri N; Kamatani, Yoichiro; Lin, Chiao-Feng; Gerrish, Amy; Schmidt, Helena; Kunkle, Brian; Dunstan, Melanie L; Ruiz, Agustin; Bihoreau, Marie-Thérèse; Choi, Seung-Hoan; Reitz, Christiane; Pasquier, Florence; Hollingworth, Paul; Ramirez, Alfredo; Hanon, Olivier; Fitzpatrick, Annette L; Buxbaum, Joseph D; Campion, Dominique; Crane, Paul K; Baldwin, Clinton; Becker, Tim; Gudnason, Vilmundur; Cruchaga, Carlos; Craig, David; Amin, Najaf; Berr, Claudine; Lopez, Oscar L; De Jager, Philip L; Deramecourt, Vincent; Johnston, Janet A; Evans, Denis; Lovestone, Simon; Letenneur, Luc; Morón, Francisco J; Rubinsztein, David C; Eiriksdottir, Gudny; Sleegers, Kristel; Goate, Alison M; Fiévet, Nathalie; Huentelman, Matthew J; Gill, Michael; Brown, Kristelle; Kamboh, M Ilyas; Keller, Lina; Barberger-Gateau, Pascale; McGuinness, Bernadette; Larson, Eric B; Green, Robert; Myers, Amanda J; Dufouil, Carole; Todd, Stephen; Wallon, David; Love, Seth; Rogaeva, Ekaterina; Gallacher, John; St George-Hyslop, Peter; Clarimon, Jordi; Lleo, Alberto; Bayer, Anthony; Tsuang, Debby W; Yu, Lei; Tsolaki, Magda; Bossù, Paola; Spalletta, Gianfranco; Proitsi, Petroula; Collinge, John; Sorbi, Sandro; Sanchez-Garcia, Florentino; Fox, Nick C; Hardy, John; Deniz Naranjo, Maria Candida; Bosco, Paolo; Clarke, Robert; Brayne, Carol; Galimberti, Daniela; Mancuso, Michelangelo; Matthews, Fiona; Moebus, Susanne; Mecocci, Patrizia; Zompo, Maria Del; Maier, Wolfgang; Hampel, Harald; Pilotto, Alberto; Bullido, Maria; Panza, Francesco; Caffarra, Paolo; Nacmias, Benedetta; Gilbert, John R; Mayhaus, Manuel; Lannfelt, Lars; Hakonarson, Hakon; Pichler, Sabrina; Carrasquillo, Minerva M; Ingelsson, Martin; Beekly, Duane; Alvarez, Victoria; Zou, Fanggeng; Valladares, Otto; Younkin, Steven G; Coto, Eliecer; Hamilton-Nelson, Kara L; Gu, Wei; Razquin, Cristina; Pastor, Pau; Mateo, Ignacio; Owen, Michael J; Faber, Kelley M; Jonsson, Palmi V; Combarros, Onofre; O’Donovan, Michael C; Cantwell, Laura B; Soininen, Hilkka; Blacker, Deborah; Mead, Simon; Mosley, Thomas H; Bennett, David A; Harris, Tamara B; Fratiglioni, Laura; Holmes, Clive; de Bruijn, Renee F A G; Passmore, Peter; Montine, Thomas J; Bettens, Karolien; Rotter, Jerome I; Brice, Alexis; Morgan, Kevin; Foroud, Tatiana M; Kukull, Walter A; Hannequin, Didier; Powell, John F; Nalls, Michael A; Ritchie, Karen; Lunetta, Kathryn L; Kauwe, John S K; Boerwinkle, Eric; Riemenschneider, Matthias; Boada, Mercè; Hiltunen, Mikko; Martin, Eden R; Schmidt, Reinhold; Rujescu, Dan; Wang, Li-san; Dartigues, Jean-François; Mayeux, Richard; Tzourio, Christophe; Hofman, Albert; Nöthen, Markus M; Graff, Caroline; Psaty, Bruce M; Jones, Lesley; Haines, Jonathan L; Holmans, Peter A; Lathrop, Mark; Pericak-Vance, Margaret A; Launer, Lenore J; Farrer, Lindsay A; van Duijn, Cornelia M; Van Broeckhoven, Christine; Moskvina, Valentina; Seshadri, Sudha; Williams, Julie; Schellenberg, Gerard D; Amouyel, Philippe

2013-01-01

Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease. PMID:24162737

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits.

PubMed

Wu, Yang; Zeng, Jian; Zhang, Futao; Zhu, Zhihong; Qi, Ting; Zheng, Zhili; Lloyd-Jones, Luke R; Marioni, Riccardo E; Martin, Nicholas G; Montgomery, Grant W; Deary, Ian J; Wray, Naomi R; Visscher, Peter M; McRae, Allan F; Yang, Jian

2018-03-02

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer.

PubMed

Michailidou, Kyriaki; Beesley, Jonathan; Lindstrom, Sara; Canisius, Sander; Dennis, Joe; Lush, Michael J; Maranian, Mel J; Bolla, Manjeet K; Wang, Qin; Shah, Mitul; Perkins, Barbara J; Czene, Kamila; Eriksson, Mikael; Darabi, Hatef; Brand, Judith S; Bojesen, Stig E; Nordestgaard, Børge G; Flyger, Henrik; Nielsen, Sune F; Rahman, Nazneen; Turnbull, Clare; Fletcher, Olivia; Peto, Julian; Gibson, Lorna; dos-Santos-Silva, Isabel; Chang-Claude, Jenny; Flesch-Janys, Dieter; Rudolph, Anja; Eilber, Ursula; Behrens, Sabine; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Khan, Sofia; Aaltonen, Kirsimari; Ahsan, Habibul; Kibriya, Muhammad G; Whittemore, Alice S; John, Esther M; Malone, Kathleen E; Gammon, Marilie D; Santella, Regina M; Ursin, Giske; Makalic, Enes; Schmidt, Daniel F; Casey, Graham; Hunter, David J; Gapstur, Susan M; Gaudet, Mia M; Diver, W Ryan; Haiman, Christopher A; Schumacher, Fredrick; Henderson, Brian E; Le Marchand, Loic; Berg, Christine D; Chanock, Stephen J; Figueroa, Jonine; Hoover, Robert N; Lambrechts, Diether; Neven, Patrick; Wildiers, Hans; van Limbergen, Erik; Schmidt, Marjanka K; Broeks, Annegien; Verhoef, Senno; Cornelissen, Sten; Couch, Fergus J; Olson, Janet E; Hallberg, Emily; Vachon, Celine; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Adank, Muriel A; van der Luijt, Rob B; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Yoo, Keun-Young; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Tajima, Kazuo; Guénel, Pascal; Truong, Thérèse; Mulot, Claire; Sanchez, Marie; Burwinkel, Barbara; Marme, Frederik; Surowy, Harald; Sohn, Christof; Wu, Anna H; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O; González-Neira, Anna; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Cross, Simon S; Reed, Malcolm W R; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Lindblom, Annika; Margolin, Sara; Teo, Soo Hwang; Yip, Cheng Har; Taib, Nur Aishah Mohd; Tan, Gie-Hooi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John W M; Collée, J Margriet; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Hopper, John L; Southey, Melissa C; Tsimiklis, Helen; Apicella, Carmel; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Kristensen, Vessela N; Nord, Silje; Alnaes, Grethe I Grenaker; Giles, Graham G; Milne, Roger L; McLean, Catriona; Canzian, Federico; Trichopoulos, Dimitrios; Peeters, Petra; Lund, Eiliv; Sund, Malin; Khaw, Kay-Tee; Gunter, Marc J; Palli, Domenico; Mortensen, Lotte Maxild; Dossus, Laure; Huerta, Jose-Maria; Meindl, Alfons; Schmutzler, Rita K; Sutter, Christian; Yang, Rongxi; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Hartman, Mikael; Miao, Hui; Chia, Kee Seng; Chan, Ching Wan; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Haeberle, Lothar; Brenner, Hermann; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Swerdlow, Anthony J; Brinton, Louise; Garcia-Closas, Montserrat; Zheng, Wei; Halverson, Sandra L; Shrubsole, Martha; Long, Jirong; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Brauch, Hiltrud; Hamann, Ute; Brüning, Thomas; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Bernard, Loris; Bogdanova, Natalia V; Dörk, Thilo; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline; Van Asperen, Christi J; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Huzarski, Tomasz; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Slager, Susan; Toland, Amanda E; Ambrosone, Christine B; Yannoukakos, Drakoulis; Kabisch, Maria; Torres, Diana; Neuhausen, Susan L; Anton-Culver, Hoda; Luccarini, Craig; Baynes, Caroline; Ahmed, Shahana; Healey, Catherine S; Tessier, Daniel C; Vincent, Daniel; Bacot, Francois; Pita, Guillermo; Alonso, M Rosario; Álvarez, Nuria; Herrero, Daniel; Simard, Jacques; Pharoah, Paul P D P; Kraft, Peter; Dunning, Alison M; Chenevix-Trench, Georgia; Hall, Per; Easton, Douglas F

2015-04-01

Genome-wide association studies (GWAS) and large-scale replication studies have identified common variants in 79 loci associated with breast cancer, explaining ∼14% of the familial risk of the disease. To identify new susceptibility loci, we performed a meta-analysis of 11 GWAS, comprising 15,748 breast cancer cases and 18,084 controls together with 46,785 cases and 42,892 controls from 41 studies genotyped on a 211,155-marker custom array (iCOGS). Analyses were restricted to women of European ancestry. We generated genotypes for more than 11 million SNPs by imputation using the 1000 Genomes Project reference panel, and we identified 15 new loci associated with breast cancer at P < 5 × 10(-8). Combining association analysis with ChIP-seq chromatin binding data in mammary cell lines and ChIA-PET chromatin interaction data from ENCODE, we identified likely target genes in two regions: SETBP1 at 18q12.3 and RNF115 and PDZK1 at 1q21.1. One association appears to be driven by an amino acid substitution encoded in EXO1.

Genome-wide association study to identify common variants associated with brachial circumference: a meta-analysis of 14 cohorts.

PubMed

Boraska, Vesna; Day-Williams, Aaron; Franklin, Christopher S; Elliott, Katherine S; Panoutsopoulou, Kalliope; Tachmazidou, Ioanna; Albrecht, Eva; Bandinelli, Stefania; Beilin, Lawrence J; Bochud, Murielle; Cadby, Gemma; Ernst, Florian; Evans, David M; Hayward, Caroline; Hicks, Andrew A; Huffman, Jennifer; Huth, Cornelia; James, Alan L; Klopp, Norman; Kolcic, Ivana; Kutalik, Zoltán; Lawlor, Debbie A; Musk, Arthur W; Pehlic, Marina; Pennell, Craig E; Perry, John R B; Peters, Annette; Polasek, Ozren; St Pourcain, Beate; Ring, Susan M; Salvi, Erika; Schipf, Sabine; Staessen, Jan A; Teumer, Alexander; Timpson, Nicholas; Vitart, Veronique; Warrington, Nicole M; Yaghootkar, Hanieh; Zemunik, Tatijana; Zgaga, Lina; An, Ping; Anttila, Verneri; Borecki, Ingrid B; Holmen, Jostein; Ntalla, Ioanna; Palotie, Aarno; Pietiläinen, Kirsi H; Wedenoja, Juho; Winsvold, Bendik S; Dedoussis, George V; Kaprio, Jaakko; Province, Michael A; Zwart, John-Anker; Burnier, Michel; Campbell, Harry; Cusi, Daniele; Smith, George Davey; Frayling, Timothy M; Gieger, Christian; Palmer, Lyle J; Pramstaller, Peter P; Rudan, Igor; Völzke, Henry; Wichmann, H-Erich; Wright, Alan F; Zeggini, Eleftheria

2012-01-01

Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC.

Genome-Wide Association Study to Identify Common Variants Associated with Brachial Circumference: A Meta-Analysis of 14 Cohorts

PubMed Central

Boraska, Vesna; Day-Williams, Aaron; Franklin, Christopher S.; Elliott, Katherine S.; Panoutsopoulou, Kalliope; Tachmazidou, Ioanna; Albrecht, Eva; Bandinelli, Stefania; Beilin, Lawrence J.; Bochud, Murielle; Cadby, Gemma; Ernst, Florian; Evans, David M.; Hayward, Caroline; Hicks, Andrew A.; Huffman, Jennifer; Huth, Cornelia; James, Alan L.; Klopp, Norman; Kolcic, Ivana; Kutalik, Zoltán; Lawlor, Debbie A.; Musk, Arthur W.; Pehlic, Marina; Pennell, Craig E.; Perry, John R. B.; Peters, Annette; Polasek, Ozren; Pourcain, Beate St; Ring, Susan M.; Salvi, Erika; Schipf, Sabine; Staessen, Jan A.; Teumer, Alexander; Timpson, Nicholas; Vitart, Veronique; Warrington, Nicole M.; Yaghootkar, Hanieh; Zemunik, Tatijana; Zgaga, Lina; An, Ping; Anttila, Verneri; Borecki, Ingrid B.; Holmen, Jostein; Ntalla, Ioanna; Palotie, Aarno; Pietiläinen, Kirsi H.; Wedenoja, Juho; Winsvold, Bendik S.; Dedoussis, George V.; Kaprio, Jaakko; Province, Michael A.; Zwart, John-Anker; Burnier, Michel; Campbell, Harry; Cusi, Daniele; Davey Smith, George; Frayling, Timothy M.; Gieger, Christian; Palmer, Lyle J.; Pramstaller, Peter P.; Rudan, Igor; Völzke, Henry; Wichmann, H. -Erich; Wright, Alan F.; Zeggini, Eleftheria

2012-01-01

Brachial circumference (BC), also known as upper arm or mid arm circumference, can be used as an indicator of muscle mass and fat tissue, which are distributed differently in men and women. Analysis of anthropometric measures of peripheral fat distribution such as BC could help in understanding the complex pathophysiology behind overweight and obesity. The purpose of this study is to identify genetic variants associated with BC through a large-scale genome-wide association scan (GWAS) meta-analysis. We used fixed-effects meta-analysis to synthesise summary results across 14 GWAS discovery and 4 replication cohorts comprising overall 22,376 individuals (12,031 women and 10,345 men) of European ancestry. Individual analyses were carried out for men, women, and combined across sexes using linear regression and an additive genetic model: adjusted for age and adjusted for age and BMI. We prioritised signals for follow-up in two-stages. We did not detect any signals reaching genome-wide significance. The FTO rs9939609 SNP showed nominal evidence for association (p<0.05) in the age-adjusted strata for men and across both sexes. In this first GWAS meta-analysis for BC to date, we have not identified any genome-wide significant signals and do not observe robust association of previously established obesity loci with BC. Large-scale collaborations will be necessary to achieve higher power to detect loci underlying BC. PMID:22479309

Genome-Wide Association Mapping for Yield and Other Agronomic Traits in an Elite Breeding Population of Tropical Rice (Oryza sativa)

PubMed Central

Lalusin, Antonio; Borromeo, Teresita; Gregorio, Glenn; Hernandez, Jose; Virk, Parminder; Collard, Bertrand; McCouch, Susan R.

2015-01-01

Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models. PMID:25785447

Interactions between household air pollution and GWAS-identified lung cancer susceptibility markers in the Female Lung Cancer Consortium in Asia (FLCCA).

PubMed

Hosgood, H Dean; Song, Minsun; Hsiung, Chao Agnes; Yin, Zhihua; Shu, Xiao-Ou; Wang, Zhaoming; Chatterjee, Nilanjan; Zheng, Wei; Caporaso, Neil; Burdette, Laurie; Yeager, Meredith; Berndt, Sonja I; Landi, Maria Teresa; Chen, Chien-Jen; Chang, Gee-Chen; Hsiao, Chin-Fu; Tsai, Ying-Huang; Chien, Li-Hsin; Chen, Kuan-Yu; Huang, Ming-Shyan; Su, Wu-Chou; Chen, Yuh-Min; Chen, Chung-Hsing; Yang, Tsung-Ying; Wang, Chih-Liang; Hung, Jen-Yu; Lin, Chien-Chung; Perng, Reury-Perng; Chen, Chih-Yi; Chen, Kun-Chieh; Li, Yao-Jen; Yu, Chong-Jen; Chen, Yi-Song; Chen, Ying-Hsiang; Tsai, Fang-Yu; Kim, Christopher; Seow, Wei Jie; Bassig, Bryan A; Wu, Wei; Guan, Peng; He, Qincheng; Gao, Yu-Tang; Cai, Qiuyin; Chow, Wong-Ho; Xiang, Yong-Bing; Lin, Dongxin; Wu, Chen; Wu, Yi-Long; Shin, Min-Ho; Hong, Yun-Chul; Matsuo, Keitaro; Chen, Kexin; Wong, Maria Pik; Lu, Dara; Jin, Li; Wang, Jiu-Cun; Seow, Adeline; Wu, Tangchun; Shen, Hongbing; Fraumeni, Joseph F; Yang, Pan-Chyr; Chang, I-Shou; Zhou, Baosen; Chanock, Stephen J; Rothman, Nathaniel; Lan, Qing

2015-03-01

We previously carried out a multi-stage genome-wide association study (GWAS) on lung cancer among never smokers in the Female Lung Cancer Consortium in Asia (FLCCA) (6,609 cases, 7,457 controls) that identified novel susceptibility loci at 10q25.2, 6q22.2, and 6p21.32, and confirmed two previously identified loci at 5p15.33 and 3q28. Household air pollution (HAP) attributed to solid fuel burning for heating and cooking, is the leading cause of the overall disease burden in Southeast Asia, and is known to contain lung carcinogens. To evaluate the gene-HAP interactions associated with lung cancer in loci independent of smoking, we analyzed data from studies participating in FLCCA with fuel use information available (n = 3; 1,731 cases; 1,349 controls). Coal use was associated with a 30% increased risk of lung cancer (OR 1.3, 95% CI 1.0-1.6). Among the five a priori SNPs identified by our GWAS, two showed a significant interaction with coal use (HLA Class II rs2395185, p = 0.02; TP63 rs4488809 (rs4600802), p = 0.04). The risk of lung cancer associated with coal exposure varied with the respective alleles for these two SNPs. Our observations provide evidence that genetic variation in HLA Class II and TP63 may modify the association between HAP and lung cancer risk. The roles played in the cell cycle and inflammation pathways by the proteins encoded by these two genes provide biological plausibility for these interactions; however, additional replication studies are needed in other non-smoking populations.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†

PubMed Central

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-01-01

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. PMID:26019233

A Genome-Wide Association Study of Resistance to Stripe Rust (Puccinia striiformis f. sp. tritici) in a Worldwide Collection of Hexaploid Spring Wheat (Triticum aestivum L.)

PubMed Central

Maccaferri, Marco; Zhang, Junli; Bulli, Peter; Abate, Zewdie; Chao, Shiaoman; Cantu, Dario; Bossolini, Eligio; Chen, Xianming; Pumphrey, Michael; Dubcovsky, Jorge

2015-01-01

New races of Puccinia striiformis f. sp. tritici (Pst), the causal pathogen of wheat stripe rust, show high virulence to previously deployed resistance genes and are responsible for large yield losses worldwide. To identify new sources of resistance we performed a genome-wide association study (GWAS) using a worldwide collection of 1000 spring wheat accessions. Adult plants were evaluated under field conditions in six environments in the western United States, and seedlings were tested with four Pst races. A single-nucleotide polymorphism (SNP) Infinium 9K-assay provided 4585 SNPs suitable for GWAS. High correlations among environments and high heritabilities were observed for stripe rust infection type and severity. Greater levels of Pst resistance were observed in a subpopulation from Southern Asia than in other groups. GWAS identified 97 loci that were significant for at least three environments, including 10 with an experiment-wise adjusted Bonferroni probability < 0.10. These 10 quantitative trait loci (QTL) explained 15% of the phenotypic variation in infection type, a percentage that increased to 45% when all QTL were considered. Three of these 10 QTL were mapped far from previously identified Pst resistance genes and QTL, and likely represent new resistance loci. The other seven QTL mapped close to known resistance genes and allelism tests will be required to test their relationships. In summary, this study provides an integrated view of stripe rust resistance resources in spring wheat and identifies new resistance loci that will be useful to diversify the current set of resistance genes deployed to control this devastating disease. PMID:25609748

A genome-wide association study of resistance to stripe rust (Puccinia striiformis f. sp. tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivum L.).

PubMed

Maccaferri, Marco; Zhang, Junli; Bulli, Peter; Abate, Zewdie; Chao, Shiaoman; Cantu, Dario; Bossolini, Eligio; Chen, Xianming; Pumphrey, Michael; Dubcovsky, Jorge

2015-01-20

New races of Puccinia striiformis f. sp. tritici (Pst), the causal pathogen of wheat stripe rust, show high virulence to previously deployed resistance genes and are responsible for large yield losses worldwide. To identify new sources of resistance we performed a genome-wide association study (GWAS) using a worldwide collection of 1000 spring wheat accessions. Adult plants were evaluated under field conditions in six environments in the western United States, and seedlings were tested with four Pst races. A single-nucleotide polymorphism (SNP) Infinium 9K-assay provided 4585 SNPs suitable for GWAS. High correlations among environments and high heritabilities were observed for stripe rust infection type and severity. Greater levels of Pst resistance were observed in a subpopulation from Southern Asia than in other groups. GWAS identified 97 loci that were significant for at least three environments, including 10 with an experiment-wise adjusted Bonferroni probability < 0.10. These 10 quantitative trait loci (QTL) explained 15% of the phenotypic variation in infection type, a percentage that increased to 45% when all QTL were considered. Three of these 10 QTL were mapped far from previously identified Pst resistance genes and QTL, and likely represent new resistance loci. The other seven QTL mapped close to known resistance genes and allelism tests will be required to test their relationships. In summary, this study provides an integrated view of stripe rust resistance resources in spring wheat and identifies new resistance loci that will be useful to diversify the current set of resistance genes deployed to control this devastating disease. Copyright © 2015 Maccaferri et al.

Mining the LIPG Allelic Spectrum Reveals the Contribution of Rare and Common Regulatory Variants to HDL Cholesterol

PubMed Central

Raghavan, Avanthi; Neeli, Hemanth; Jin, Weijun; Badellino, Karen O.; Demissie, Serkalem; Manning, Alisa K.; DerOhannessian, Stephanie L.; Wolfe, Megan L.; Cupples, L. Adrienne; Li, Mingyao; Kathiresan, Sekar; Rader, Daniel J.

2011-01-01

Genome-wide association studies (GWAS) have successfully identified loci associated with quantitative traits, such as blood lipids. Deep resequencing studies are being utilized to catalogue the allelic spectrum at GWAS loci. The goal of these studies is to identify causative variants and missing heritability, including heritability due to low frequency and rare alleles with large phenotypic impact. Whereas rare variant efforts have primarily focused on nonsynonymous coding variants, we hypothesized that noncoding variants in these loci are also functionally important. Using the HDL-C gene LIPG as an example, we explored the effect of regulatory variants identified through resequencing of subjects at HDL-C extremes on gene expression, protein levels, and phenotype. Resequencing a portion of the LIPG promoter and 5′ UTR in human subjects with extreme HDL-C, we identified several rare variants in individuals from both extremes. Luciferase reporter assays were used to measure the effect of these rare variants on LIPG expression. Variants conferring opposing effects on gene expression were enriched in opposite extremes of the phenotypic distribution. Minor alleles of a common regulatory haplotype and noncoding GWAS SNPs were associated with reduced plasma levels of the LIPG gene product endothelial lipase (EL), consistent with its role in HDL-C catabolism. Additionally, we found that a common nonfunctional coding variant associated with HDL-C (rs2000813) is in linkage disequilibrium with a 5′ UTR variant (rs34474737) that decreases LIPG promoter activity. We attribute the gene regulatory role of rs34474737 to the observed association of the coding variant with plasma EL levels and HDL-C. Taken together, the findings show that both rare and common noncoding regulatory variants are important contributors to the allelic spectrum in complex trait loci. PMID:22174694

A GWAS Meta-analysis and Replication Study Identifies a Novel Locus within CLPTM1L/TERT Associated with Nasopharyngeal Carcinoma in Individuals of Chinese Ancestry.

PubMed

Bei, Jin-Xin; Su, Wen-Hui; Ng, Ching-Ching; Yu, Kai; Chin, Yoon-Ming; Lou, Pei-Jen; Hsu, Wan-Lun; McKay, James D; Chen, Chien-Jen; Chang, Yu-Sun; Chen, Li-Zhen; Chen, Ming-Yuan; Cui, Qian; Feng, Fu-Tuo; Feng, Qi-Shen; Guo, Yun-Miao; Jia, Wei-Hua; Khoo, Alan Soo-Beng; Liu, Wen-Sheng; Mo, Hao-Yuan; Pua, Kin-Choo; Teo, Soo-Hwang; Tse, Ka-Po; Xia, Yun-Fei; Zhang, Hongxin; Zhou, Gang-Qiao; Liu, Jian-Jun; Zeng, Yi-Xin; Hildesheim, Allan

2016-01-01

Genetic loci within the major histocompatibility complex (MHC) have been associated with nasopharyngeal carcinoma (NPC), an Epstein-Barr virus (EBV)-associated cancer, in several GWAS. Results outside this region have varied. We conducted a meta-analysis of four NPC GWAS among Chinese individuals (2,152 cases; 3,740 controls). Forty-three noteworthy findings outside the MHC region were identified and targeted for replication in a pooled analysis of four independent case-control studies across three regions in Asia (4,716 cases; 5,379 controls). A meta-analysis that combined results from the initial GWA and replication studies was performed. In the combined meta-analysis, rs31489, located within the CLPTM1L/TERT region on chromosome 5p15.33, was strongly associated with NPC (OR = 0.81; P value 6.3 × 10(-13)). Our results also provide support for associations reported from published NPC GWAS-rs6774494 (P = 1.5 × 10(-12); located in the MECOM gene region), rs9510787 (P = 5.0 × 10(-10); located in the TNFRSF19 gene region), and rs1412829/rs4977756/rs1063192 (P = 2.8 × 10(-8), P = 7.0 × 10(-7), and P = 8.4 × 10(-7), respectively; located in the CDKN2A/B gene region). We have identified a novel association between genetic variation in the CLPTM1L/TERT region and NPC. Supporting our finding, rs31489 and other SNPs in this region have been reported to be associated with multiple cancer sites, candidate-based studies have reported associations between polymorphisms in this region and NPC, the TERT gene has been shown to be important for telomere maintenance and has been reported to be overexpressed in NPC, and an EBV protein expressed in NPC (LMP1) has been reported to modulate TERT expression/telomerase activity. Our finding suggests that factors involved in telomere length maintenance are involved in NPC pathogenesis. ©2015 American Association for Cancer Research.

Molecular mechanisms underlying variations in lung function: a systems genetics analysis

PubMed Central

Obeidat, Ma’en; Hao, Ke; Bossé, Yohan; Nickle, David C; Nie, Yunlong; Postma, Dirkje S; Laviolette, Michel; Sandford, Andrew J; Daley, Denise D; Hogg, James C; Elliott, W Mark; Fishbane, Nick; Timens, Wim; Hysi, Pirro G; Kaprio, Jaakko; Wilson, James F; Hui, Jennie; Rawal, Rajesh; Schulz, Holger; Stubbe, Beate; Hayward, Caroline; Polasek, Ozren; Järvelin, Marjo-Riitta; Zhao, Jing Hua; Jarvis, Deborah; Kähönen, Mika; Franceschini, Nora; North, Kari E; Loth, Daan W; Brusselle, Guy G; Smith, Albert Vernon; Gudnason, Vilmundur; Bartz, Traci M; Wilk, Jemma B; O’Connor, George T; Cassano, Patricia A; Tang, Wenbo; Wain, Louise V; Artigas, María Soler; Gharib, Sina A; Strachan, David P; Sin, Don D; Tobin, Martin D; London, Stephanie J; Hall, Ian P; Paré, Peter D

2016-01-01

Summary Background Lung function measures reflect the physiological state of the lung, and are essential to the diagnosis of chronic obstructive pulmonary disease (COPD). The SpiroMeta-CHARGE consortium undertook the largest genome-wide association study (GWAS) so far (n=48 201) for forced expiratory volume in 1 s (FEV1) and the ratio of FEV1 to forced vital capacity (FEV1/FVC) in the general population. The lung expression quantitative trait loci (eQTLs) study mapped the genetic architecture of gene expression in lung tissue from 1111 individuals. We used a systems genetics approach to identify single nucleotide polymorphisms (SNPs) associated with lung function that act as eQTLs and change the level of expression of their target genes in lung tissue; termed eSNPs. Methods The SpiroMeta-CHARGE GWAS results were integrated with lung eQTLs to map eSNPs and the genes and pathways underlying the associations in lung tissue. For comparison, a similar analysis was done in peripheral blood. The lung mRNA expression levels of the eSNP-regulated genes were tested for associations with lung function measures in 727 individuals. Additional analyses identified the pleiotropic effects of eSNPs from the published GWAS catalogue, and mapped enrichment in regulatory regions from the ENCODE project. Finally, the Connectivity Map database was used to identify potential therapeutics in silico that could reverse the COPD lung tissue gene signature. Findings SNPs associated with lung function measures were more likely to be eQTLs and vice versa. The integration mapped the specific genes underlying the GWAS signals in lung tissue. The eSNP-regulated genes were enriched for developmental and inflammatory pathways; by comparison, SNPs associated with lung function that were eQTLs in blood, but not in lung, were only involved in inflammatory pathways. Lung function eSNPs were enriched for regulatory elements and were over-represented among genes showing differential expression during fetal lung development. An mRNA gene expression signature for COPD was identified in lung tissue and compared with the Connectivity Map. This in-silico drug repurposing approach suggested several compounds that reverse the COPD gene expression signature, including a nicotine receptor antagonist. These findings represent novel therapeutic pathways for COPD. Interpretation The system genetics approach identified lung tissue genes driving the variation in lung function and susceptibility to COPD. The identification of these genes and the pathways in which they are enriched is essential to understand the pathophysiology of airway obstruction and to identify novel therapeutic targets and biomarkers for COPD, including drugs that reverse the COPD gene signature in silico. Funding The research reported in this article was not specifically funded by any agency. See Acknowledgments for a full list of funders of the lung eQTL study and the Spiro-Meta CHARGE GWAS. PMID:26404118

Identification and Functional Characterization of G6PC2 Coding Variants Influencing Glycemic Traits Define an Effector Transcript at the G6PC2-ABCB11 Locus

PubMed Central

Mahajan, Anubha; Sim, Xueling; Ng, Hui Jin; Manning, Alisa; Rivas, Manuel A.; Highland, Heather M.; Locke, Adam E.; Grarup, Niels; Im, Hae Kyung; Cingolani, Pablo; Flannick, Jason; Fontanillas, Pierre; Fuchsberger, Christian; Gaulton, Kyle J.; Teslovich, Tanya M.; Rayner, N. William; Robertson, Neil R.; Beer, Nicola L.; Rundle, Jana K.; Bork-Jensen, Jette; Ladenvall, Claes; Blancher, Christine; Buck, David; Buck, Gemma; Burtt, Noël P.; 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.; Syvänen, Ann-Christine; Trakalo, Joseph; Abecasis, Goncalo; Bell, Graeme I.; Blangero, John; Cox, Nancy J.; Duggirala, Ravindranath; Hanis, Craig L.; Seielstad, Mark; Wilson, James G.; Christensen, Cramer; Brandslund, Ivan; Rauramaa, Rainer; Surdulescu, Gabriela L.; Doney, Alex S. F.; Lannfelt, Lars; Linneberg, Allan; Isomaa, Bo; Tuomi, Tiinamaija; Jørgensen, Marit E.; Jørgensen, Torben; Kuusisto, Johanna; Uusitupa, Matti; Salomaa, Veikko; Spector, Timothy D.; Morris, Andrew D.; Palmer, Colin N. A.; Collins, Francis S.; Mohlke, Karen L.; Bergman, Richard N.; Ingelsson, Erik; Lind, Lars; Tuomilehto, Jaakko; Hansen, Torben; Watanabe, Richard M.; Prokopenko, Inga; Dupuis, Josee; Karpe, Fredrik; Groop, Leif; Laakso, Markku; Pedersen, Oluf; Florez, Jose C.; Morris, Andrew P.; Altshuler, David; Meigs, James B.; Boehnke, Michael; McCarthy, Mark I.; Lindgren, Cecilia M.; Gloyn, Anna L.

2015-01-01

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights. PMID:25625282

Identification and functional characterization of G6PC2 coding variants influencing glycemic traits define an effector transcript at the G6PC2-ABCB11 locus.

PubMed

Mahajan, Anubha; Sim, Xueling; Ng, Hui Jin; Manning, Alisa; Rivas, Manuel A; Highland, Heather M; Locke, Adam E; Grarup, Niels; Im, Hae Kyung; Cingolani, Pablo; Flannick, Jason; Fontanillas, Pierre; Fuchsberger, Christian; Gaulton, Kyle J; Teslovich, Tanya M; Rayner, N William; Robertson, Neil R; Beer, Nicola L; Rundle, Jana K; Bork-Jensen, Jette; Ladenvall, Claes; Blancher, Christine; Buck, David; Buck, Gemma; Burtt, Noël P; 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; Syvänen, Ann-Christine; Trakalo, Joseph; Abecasis, Goncalo; Bell, Graeme I; Blangero, John; Cox, Nancy J; Duggirala, Ravindranath; Hanis, Craig L; Seielstad, Mark; Wilson, James G; Christensen, Cramer; Brandslund, Ivan; Rauramaa, Rainer; Surdulescu, Gabriela L; Doney, Alex S F; Lannfelt, Lars; Linneberg, Allan; Isomaa, Bo; Tuomi, Tiinamaija; Jørgensen, Marit E; Jørgensen, Torben; Kuusisto, Johanna; Uusitupa, Matti; Salomaa, Veikko; Spector, Timothy D; Morris, Andrew D; Palmer, Colin N A; Collins, Francis S; Mohlke, Karen L; Bergman, Richard N; Ingelsson, Erik; Lind, Lars; Tuomilehto, Jaakko; Hansen, Torben; Watanabe, Richard M; Prokopenko, Inga; Dupuis, Josee; Karpe, Fredrik; Groop, Leif; Laakso, Markku; Pedersen, Oluf; Florez, Jose C; Morris, Andrew P; Altshuler, David; Meigs, James B; Boehnke, Michael; McCarthy, Mark I; Lindgren, Cecilia M; Gloyn, Anna L

2015-01-01

Genome wide association studies (GWAS) for fasting glucose (FG) and insulin (FI) have identified common variant signals which explain 4.8% and 1.2% of trait variance, respectively. It is hypothesized that low-frequency and rare variants could contribute substantially to unexplained genetic variance. To test this, we analyzed exome-array data from up to 33,231 non-diabetic individuals of European ancestry. We found exome-wide significant (P<5×10-7) evidence for two loci not previously highlighted by common variant GWAS: GLP1R (p.Ala316Thr, minor allele frequency (MAF)=1.5%) influencing FG levels, and URB2 (p.Glu594Val, MAF = 0.1%) influencing FI levels. Coding variant associations can highlight potential effector genes at (non-coding) GWAS signals. At the G6PC2/ABCB11 locus, we identified multiple coding variants in G6PC2 (p.Val219Leu, p.His177Tyr, and p.Tyr207Ser) influencing FG levels, conditionally independent of each other and the non-coding GWAS signal. In vitro assays demonstrate that these associated coding alleles result in reduced protein abundance via proteasomal degradation, establishing G6PC2 as an effector gene at this locus. Reconciliation of single-variant associations and functional effects was only possible when haplotype phase was considered. In contrast to earlier reports suggesting that, paradoxically, glucose-raising alleles at this locus are protective against type 2 diabetes (T2D), the p.Val219Leu G6PC2 variant displayed a modest but directionally consistent association with T2D risk. Coding variant associations for glycemic traits in GWAS signals highlight PCSK1, RREB1, and ZHX3 as likely effector transcripts. These coding variant association signals do not have a major impact on the trait variance explained, but they do provide valuable biological insights.

GWAS-identified risk variants for major depressive disorder: Preliminary support for an association with late-life depressive symptoms and brain structural alterations.

PubMed

Ryan, Joanne; Artero, Sylvaine; Carrière, Isabelle; Maller, Jerome J; Meslin, Chantal; Ritchie, Karen; Ancelin, Marie-Laure

2016-01-01

A number of genome-wide association studies (GWAS) have investigated risk factors for major depressive disorder (MDD), however there has been little attempt to replicate these findings in population-based studies of depressive symptoms. Variants within three genes, BICC1, PCLO and GRM7 were selected for replication in our study based on the following criteria: they were identified in a prior MDD GWAS study; a subsequent study found evidence that they influenced depression risk; and there is a solid biological basis for a role in depression. We firstly investigated whether these variants were associated with depressive symptoms in our population-based cohort of 929 elderly (238 with clinical depressive symptoms and 691 controls), and secondly to investigate associations with structural brain alterations. A number of nominally significant associations were identified, but none reached Bonferroni-corrected significance levels. Common SNPs in BICC1 and PCLO were associated with a 50% and 30% decreased risk of depression, respectively. PCLO rs2522833 was also associated with the volume of grey matter (p=1.6×10(-3)), and to a lesser extent with hippocampal volume and white matter lesions. Among depressed individuals rs9870680 (GRM7) was associated with the volume of grey and white matter (p=10(-4) and 8.3×10(-3), respectively). Our results provide some support for the involvement of BICC1 and PCLO in late-life depressive disorders and preliminary evidence that these genetic variants may also influence brain structural volumes. However effect sizes remain modest and associations did not reach corrected significance levels. Further large imaging studies are needed to confirm our findings. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

A note on the efficiencies of sampling strategies in two-stage Bayesian regional fine mapping of a quantitative trait.

PubMed

Chen, Zhijian; Craiu, Radu V; Bull, Shelley B

2014-11-01

In focused studies designed to follow up associations detected in a genome-wide association study (GWAS), investigators can proceed to fine-map a genomic region by targeted sequencing or dense genotyping of all variants in the region, aiming to identify a functional sequence variant. For the analysis of a quantitative trait, we consider a Bayesian approach to fine-mapping study design that incorporates stratification according to a promising GWAS tag SNP in the same region. Improved cost-efficiency can be achieved when the fine-mapping phase incorporates a two-stage design, with identification of a smaller set of more promising variants in a subsample taken in stage 1, followed by their evaluation in an independent stage 2 subsample. To avoid the potential negative impact of genetic model misspecification on inference we incorporate genetic model selection based on posterior probabilities for each competing model. Our simulation study shows that, compared to simple random sampling that ignores genetic information from GWAS, tag-SNP-based stratified sample allocation methods reduce the number of variants continuing to stage 2 and are more likely to promote the functional sequence variant into confirmation studies. © 2014 WILEY PERIODICALS, INC.

CONAN: copy number variation analysis software for genome-wide association studies

PubMed Central

2010-01-01

Background Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs. Results CONAN is a freely available client-server software solution which provides an intuitive graphical user interface for categorizing, analyzing and associating CNVs with phenotypes. Moreover, CONAN assists the evaluation process by visualizing detected associations via Manhattan plots in order to enable a rapid identification of genome-wide significant CNV regions. Various file formats including the information on CNVs in population samples are supported as input data. Conclusions CONAN facilitates the performance of GWAS based on CNVs and the visual analysis of calculated results. CONAN provides a rapid, valid and straightforward software solution to identify genetic variation underlying the 'missing' heritability for complex traits that remains unexplained by recent GWAS. The freely available software can be downloaded at http://genepi-conan.i-med.ac.at. PMID:20546565

[Fine mapping of complex disease susceptibility loci].

PubMed

Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

2014-01-01

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

Genome-wide association analysis identifies a meningioma risk locus at 11p15.5.

PubMed

Claus, Elizabeth B; Cornish, Alex J; Broderick, Peter; Schildkraut, Joellen M; Dobbins, Sara E; Holroyd, Amy; Calvocoressi, Lisa; Lu, Lingeng; Hansen, Helen M; Smirnov, Ivan; Walsh, Kyle M; Schramm, Johannes; Hoffmann, Per; Nöthen, Markus M; Jöckel, Karl-Heinz; Swerdlow, Anthony; Larsen, Signe Benzon; Johansen, Christoffer; Simon, Matthias; Bondy, Melissa; Wrensch, Margaret; Houlston, Richard; Wiemels, Joseph L

2018-05-12

Meningioma are adult brain tumors originating in the meningeal coverings of the brain and spinal cord, with significant heritable basis. Genome-wide association studies (GWAS) have previously identified only a single risk locus for meningioma, at 10p12.31. To identify a susceptibility locus for meningioma, we conducted a meta-analysis of two GWAS, imputed using a merged reference panel of 1,000 Genomes and UK10K data, with validation in two independent sample series totaling 2,138 cases and 12,081 controls. We identified a new susceptibility locus for meningioma at 11p15.5 (rs2686876, odds ratio = 1.44, P = 9.86 × 10-9). A number of genes localize to the region of linkage disequilibrium encompassing rs2686876, including RIC8A, which plays a central role in the development of neural crest-derived structures, such as the meninges. This finding advances our understanding of the genetic basis of meningioma development and provides additional support for a polygenic model of meningioma.

iPat: intelligent prediction and association tool for genomic research.

PubMed

Chen, Chunpeng James; Zhang, Zhiwu

2018-06-01

The ultimate goal of genomic research is to effectively predict phenotypes from genotypes so that medical management can improve human health and molecular breeding can increase agricultural production. Genomic prediction or selection (GS) plays a complementary role to genome-wide association studies (GWAS), which is the primary method to identify genes underlying phenotypes. Unfortunately, most computing tools cannot perform data analyses for both GWAS and GS. Furthermore, the majority of these tools are executed through a command-line interface (CLI), which requires programming skills. Non-programmers struggle to use them efficiently because of the steep learning curves and zero tolerance for data formats and mistakes when inputting keywords and parameters. To address these problems, this study developed a software package, named the Intelligent Prediction and Association Tool (iPat), with a user-friendly graphical user interface. With iPat, GWAS or GS can be performed using a pointing device to simply drag and/or click on graphical elements to specify input data files, choose input parameters and select analytical models. Models available to users include those implemented in third party CLI packages such as GAPIT, PLINK, FarmCPU, BLINK, rrBLUP and BGLR. Users can choose any data format and conduct analyses with any of these packages. File conversions are automatically conducted for specified input data and selected packages. A GWAS-assisted genomic prediction method was implemented to perform genomic prediction using any GWAS method such as FarmCPU. iPat was written in Java for adaptation to multiple operating systems including Windows, Mac and Linux. The iPat executable file, user manual, tutorials and example datasets are freely available at http://zzlab.net/iPat. zhiwu.zhang@wsu.edu.

Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms.

PubMed

Fanous, Ayman H; Zhou, Baiyu; Aggen, Steven H; Bergen, Sarah E; Amdur, Richard L; Duan, Jubao; Sanders, Alan R; Shi, Jianxin; Mowry, Bryan J; Olincy, Ann; Amin, Farooq; Cloninger, C Robert; Silverman, Jeremy M; Buccola, Nancy G; Byerley, William F; Black, Donald W; Freedman, Robert; Dudbridge, Frank; Holmans, Peter A; Ripke, Stephan; Gejman, Pablo V; Kendler, Kenneth S; Levinson, Douglas F

2012-12-01

Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia. Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor. No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples. The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

The genetic basis of gout.

PubMed

Merriman, Tony R; Choi, Hyon K; Dalbeth, Nicola

2014-05-01

Gout results from deposition of monosodium urate (MSU) crystals. Elevated serum urate concentrations (hyperuricemia) are not sufficient for the development of disease. Genome-wide association studies (GWAS) have identified 28 loci controlling serum urate levels. The largest genetic effects are seen in genes involved in the renal excretion of uric acid, with others being involved in glycolysis. Whereas much is understood about the genetic control of serum urate levels, little is known about the genetic control of inflammatory responses to MSU crystals. Extending knowledge in this area depends on recruitment of large, clinically ascertained gout sample sets suitable for GWAS. Copyright © 2014 Elsevier Inc. All rights reserved.

Characterizing Genetic Risk at Known Prostate Cancer Susceptibility Loci in African Americans

PubMed Central

Haiman, Christopher A.; Chen, Gary K.; Blot, William J.; Strom, Sara S.; Berndt, Sonja I.; Kittles, Rick A.; Rybicki, Benjamin A.; Isaacs, William B.; Ingles, Sue A.; Stanford, Janet L.; Diver, W. Ryan; Witte, John S.; Chanock, Stephen J.; Kolb, Suzanne; Signorello, Lisa B.; Yamamura, Yuko; Neslund-Dudas, Christine; Thun, Michael J.; Murphy, Adam; Casey, Graham; Sheng, Xin; Wan, Peggy; Pooler, Loreall C.; Monroe, Kristine R.; Waters, Kevin M.; Le Marchand, Loic; Kolonel, Laurence N.; Stram, Daniel O.; Henderson, Brian E.

2011-01-01

GWAS of prostate cancer have been remarkably successful in revealing common genetic variants and novel biological pathways that are linked with its etiology. A more complete understanding of inherited susceptibility to prostate cancer in the general population will come from continuing such discovery efforts and from testing known risk alleles in diverse racial and ethnic groups. In this large study of prostate cancer in African American men (3,425 prostate cancer cases and 3,290 controls), we tested 49 risk variants located in 28 genomic regions identified through GWAS in men of European and Asian descent, and we replicated associations (at p≤0.05) with roughly half of these markers. Through fine-mapping, we identified nearby markers in many regions that better define associations in African Americans. At 8q24, we found 9 variants (p≤6×10−4) that best capture risk of prostate cancer in African Americans, many of which are more common in men of African than European descent. The markers found to be associated with risk at each locus improved risk modeling in African Americans (per allele OR = 1.17) over the alleles reported in the original GWAS (OR = 1.08). In summary, in this detailed analysis of the prostate cancer risk loci reported from GWAS, we have validated and improved upon markers of risk in some regions that better define the association with prostate cancer in African Americans. Our findings with variants at 8q24 also reinforce the importance of this region as a major risk locus for prostate cancer in men of African ancestry. PMID:21637779

Identification of a Bipolar Disorder Vulnerable Gene CHDH at 3p21.1.

PubMed

Chang, Hong; Li, Lingyi; Peng, Tao; Grigoroiu-Serbanescu, Maria; Bergen, Sarah E; Landén, Mikael; Hultman, Christina M; Forstner, Andreas J; Strohmaier, Jana; Hecker, Julian; Schulze, Thomas G; Müller-Myhsok, Bertram; Reif, Andreas; Mitchell, Philip B; Martin, Nicholas G; Cichon, Sven; Nöthen, Markus M; Jamain, Stéphane; Leboyer, Marion; Bellivier, Frank; Etain, Bruno; Kahn, Jean-Pierre; Henry, Chantal; Rietschel, Marcella; Xiao, Xiao; Li, Ming

2017-09-01

Genome-wide analysis (GWA) is an effective strategy to discover extreme effects surpassing genome-wide significant levels in studying complex disorders; however, when sample size is limited, the true effects may fail to achieve genome-wide significance. In such case, there may be authentic results among the pools of nominal candidates, and an alternative approach is to consider nominal candidates but are replicable across different samples. Here, we found that mRNA expression of the choline dehydrogenase gene (CHDH) was uniformly upregulated in the brains of bipolar disorder (BPD) patients compared with healthy controls across different studies. Follow-up genetic analyses of CHDH variants in multiple independent clinical datasets (including 11,564 cases and 17,686 controls) identified a risk SNP rs9836592 showing consistent associations with BPD (P meta  = 5.72 × 10 -4 ), and the risk allele indicated an increased CHDH expression in multiple neuronal tissues (lowest P = 6.70 × 10 -16 ). These converging results may identify a nominal but true BPD susceptibility gene CHDH. Further exploratory analysis revealed suggestive associations of rs9836592 with childhood intelligence (P = 0.044) and educational attainment (P = 0.0039), a "proxy phenotype" of general cognitive abilities. Intriguingly, the CHDH gene is located at chromosome 3p21.1, a risk region implicated in previous BPD genome-wide association studies (GWAS), but CHDH is lying outside of the core GWAS linkage disequilibrium (LD) region, and our studied SNP rs9836592 is ∼1.2 Mb 3' downstream of the previous GWAS loci (e.g., rs2251219) with no LD between them; thus, the association observed here is unlikely a reflection of previous GWAS signals. In summary, our results imply that CHDH may play a previously unknown role in the etiology of BPD and also highlight the informative value of integrating gene expression and genetic code in advancing our understanding of its biological basis.

A genome-wide association study in soybean

USDA-ARS?s Scientific Manuscript database

A genome-wide association study (GWAS) was performed to estimate the feasibility of identifying genes controlling the quantitative traits, seed protein and oil concentration, in 298 soybean germplasm accessions exhibiting a wide range of seed protein and oil content. A total of 55,159 single nucleo...

Identification of FGF7 as a novel susceptibility locus for chronic obstructive pulmonary disease.

PubMed

Brehm, John M; Hagiwara, Koichi; Tesfaigzi, Yohannes; Bruse, Shannon; Mariani, Thomas J; Bhattacharya, Soumyaroop; Boutaoui, Nadia; Ziniti, John P; Soto-Quiros, Manuel E; Avila, Lydiana; Cho, Michael H; Himes, Blanca; Litonjua, Augusto A; Jacobson, Francine; Bakke, Per; Gulsvik, Amund; Anderson, Wayne H; Lomas, David A; Forno, Erick; Datta, Soma; Silverman, Edwin K; Celedón, Juan C

2011-12-01

Traditional genome-wide association studies (GWASs) of large cohorts of subjects with chronic obstructive pulmonary disease (COPD) have successfully identified novel candidate genes, but several other plausible loci do not meet strict criteria for genome-wide significance after correction for multiple testing. The authors hypothesise that by applying unbiased weights derived from unique populations we can identify additional COPD susceptibility loci. Methods The authors performed a homozygosity haplotype analysis on a group of subjects with and without COPD to identify regions of conserved homozygosity haplotype (RCHHs). Weights were constructed based on the frequency of these RCHHs in case versus controls, and used to adjust the p values from a large collaborative GWAS of COPD. The authors identified 2318 RCHHs, of which 576 were significantly (p<0.05) over-represented in cases. After applying the weights constructed from these regions to a collaborative GWAS of COPD, the authors identified two single nucleotide polymorphisms (SNPs) in a novel gene (fibroblast growth factor-7 (FGF7)) that gained genome-wide significance by the false discovery rate method. In a follow-up analysis, both SNPs (rs12591300 and rs4480740) were significantly associated with COPD in an independent population (combined p values of 7.9E-7 and 2.8E-6, respectively). In another independent population, increased lung tissue FGF7 expression was associated with worse measures of lung function. Weights constructed from a homozygosity haplotype analysis of an isolated population successfully identify novel genetic associations from a GWAS on a separate population. This method can be used to identify promising candidate genes that fail to meet strict correction for multiple testing.

Privacy-preserving GWAS analysis on federated genomic datasets.

PubMed

Constable, Scott D; Tang, Yuzhe; Wang, Shuang; Jiang, Xiaoqian; Chapin, Steve

2015-01-01

The biomedical community benefits from the increasing availability of genomic data to support meaningful scientific research, e.g., Genome-Wide Association Studies (GWAS). However, high quality GWAS usually requires a large amount of samples, which can grow beyond the capability of a single institution. Federated genomic data analysis holds the promise of enabling cross-institution collaboration for effective GWAS, but it raises concerns about patient privacy and medical information confidentiality (as data are being exchanged across institutional boundaries), which becomes an inhibiting factor for the practical use. We present a privacy-preserving GWAS framework on federated genomic datasets. Our method is to layer the GWAS computations on top of secure multi-party computation (MPC) systems. This approach allows two parties in a distributed system to mutually perform secure GWAS computations, but without exposing their private data outside. We demonstrate our technique by implementing a framework for minor allele frequency counting and χ2 statistics calculation, one of typical computations used in GWAS. For efficient prototyping, we use a state-of-the-art MPC framework, i.e., Portable Circuit Format (PCF) 1. Our experimental results show promise in realizing both efficient and secure cross-institution GWAS computations.

Replication of Caucasian Loci Associated with Osteoporosis-related Traits in East Asians

PubMed Central

Kim, Beom-Jun; Ahn, Seong Hee; Kim, Hyeon-Mok; Ikegawa, Shiro; Yang, Tie-Lin; Guo, Yan; Deng, Hong-Wen; Koh, Jung-Min

2016-01-01

Background Most reported genome-wide association studies (GWAS) seeking to identify the loci of osteoporosis-related traits have involved Caucasian populations. We aimed to identify the single nucleotide polymorphisms (SNPs) of osteoporosis-related traits among East Asian populations from the bone mineral density (BMD)-related loci of an earlier GWAS meta-analysis. Methods A total of 95 SNPs, identified at the discovery stage of the largest GWAS meta-analysis of BMD, were tested to determine associations with osteoporosis-related traits (BMD, osteoporosis, or fracture) in Korean subjects (n=1,269). The identified SNPs of osteoporosis-related traits in Korean subjects were included in the replication analysis using Chinese (n=2,327) and Japanese (n=768) cohorts. Results A total of 17 SNPs were associated with low BMD in Korean subjects. Specifically, 9, 6, 9, and 5 SNPs were associated with the presence of osteoporosis, non-vertebral fractures, vertebral fractures, and any fracture, respectively. Collectively, 35 of the 95 SNPs (36.8%) were associated with one or more osteoporosis-related trait in Korean subjects. Of the 35 SNPs, 19 SNPs (54.3%) were also associated with one or more osteoporosis-related traits in East Asian populations. Twelve SNPs were associated with low BMD in the Chinese and Japanese cohorts. Specifically, 3, 4, and 2 SNPs were associated with the presence of hip fractures, vertebral fractures, and any fracture, respectively. Conclusions Our results identified the common SNPs of osteoporosis-related traits in both Caucasian and East Asian populations. These SNPs should be further investigated to assess whether they are true genetic markers of osteoporosis. PMID:27965945

Meta-analysis of loci associated with age at natural menopause in African-American women

PubMed Central

Chen, Christina T.L.; Liu, Ching-Ti; Chen, Gary K.; Andrews, Jeanette S.; Arnold, Alice M.; Dreyfus, Jill; Franceschini, Nora; Garcia, Melissa E.; Kerr, Kathleen F.; Li, Guo; Lohman, Kurt K.; Musani, Solomon K.; Nalls, Michael A.; Raffel, Leslie J.; Smith, Jennifer; Ambrosone, Christine B.; Bandera, Elisa V.; Bernstein, Leslie; Britton, Angela; Brzyski, Robert G.; Cappola, Anne; Carlson, Christopher S.; Couper, David; Deming, Sandra L.; Goodarzi, Mark O.; Heiss, Gerardo; John, Esther M.; Lu, Xiaoning; Le Marchand, Loic; Marciante, Kristin; Mcknight, Barbara; Millikan, Robert; Nock, Nora L.; Olshan, Andrew F.; Press, Michael F.; Vaiyda, Dhananjay; Woods, Nancy F.; Taylor, Herman A.; Zhao, Wei; Zheng, Wei; Evans, Michele K.; Harris, Tamara B.; Henderson, Brian E.; Kardia, Sharon L.R.; Kooperberg, Charles; Liu, Yongmei; Mosley, Thomas H.; Psaty, Bruce; Wellons, Melissa; Windham, Beverly G.; Zonderman, Alan B.; Cupples, L. Adrienne; Demerath, Ellen W.; Haiman, Christopher; Murabito, Joanne M.; Rajkovic, Aleksandar

2014-01-01

Age at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA. PMID:24493794

Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa

PubMed Central

Huckins, L M; Hatzikotoulas, K; Southam, L; Thornton, L M; Steinberg, J; Aguilera-McKay, F; Treasure, J; Schmidt, U; Gunasinghe, C; Romero, A; Curtis, C; Rhodes, D; Moens, J; Kalsi, G; Dempster, D; Leung, R; Keohane, A; Burghardt, R; Ehrlich, S; Hebebrand, J; Hinney, A; Ludolph, A; Walton, E; Deloukas, P; Hofman, A; Palotie, A; Palta, P; van Rooij, F J A; Stirrups, K; Adan, R; Boni, C; Cone, R; Dedoussis, G; van Furth, E; Gonidakis, F; Gorwood, P; Hudson, J; Kaprio, J; Kas, M; Keski-Rahonen, A; Kiezebrink, K; Knudsen, G-P; Slof-Op 't Landt, M C T; Maj, M; Monteleone, A M; Monteleone, P; Raevuori, A H; Reichborn-Kjennerud, T; Tozzi, F; Tsitsika, A; van Elburg, A; Adan, R A H; Alfredsson, L; Ando, T; Andreassen, O A; Aschauer, H; Baker, J H; Barrett, J C; Bencko, V; Bergen, A W; Berrettini, W H; Birgegard, A; Boni, C; Boraska Perica, V; Brandt, H; Breen, G; Bulik, C M; Carlberg, L; Cassina, M; Cichon, S; Clementi, M; Cohen-Woods, S; Coleman, J; Cone, R D; Courtet, P; Crawford, S; Crow, S; Crowley, J; Danner, U N; Davis, O S P; de Zwaan, M; Dedoussis, G; Degortes, D; DeSocio, J E; Dick, D M; Dikeos, D; Dina, C; Ding, B; Dmitrzak-Weglarz, M; Docampo, E; Duncan, L; Egberts, K; Ehrlich, S; Escaramís, G; Esko, T; Espeseth, T; Estivill, X; Favaro, A; Fernández-Aranda, F; Fichter, M M; Finan, C; Fischer, K; Floyd, J A B; Foretova, L; Forzan, M; Franklin, C S; Gallinger, S; Gambaro, G; Gaspar, H A; Giegling, I; Gonidakis, F; Gorwood, P; Gratacos, M; Guillaume, S; Guo, Y; Hakonarson, H; Halmi, K A; Hatzikotoulas, K; Hauser, J; Hebebrand, J; Helder, S; Herms, S; Herpertz-Dahlmann, B; Herzog, W; Hilliard, C E; Hinney, A; Hübel, C; Huckins, L M; Hudson, J I; Huemer, J; Inoko, H; Janout, V; Jiménez-Murcia, S; Johnson, C; Julià, A; Juréus, A; Kalsi, G; Kaminska, D; Kaplan, A S; Kaprio, J; Karhunen, L; Karwautz, A; Kas, M J H; Kaye, W; Kennedy, J L; Keski-Rahkonen, A; Kiezebrink, K; Klareskog, L; Klump, K L; Knudsen, G P S; Koeleman, B P C; Koubek, D; La Via, M C; Landén, M; Le Hellard, S; Levitan, R D; Li, D; Lichtenstein, P; Lilenfeld, L; Lissowska, J; Lundervold, A; Magistretti, P; Maj, M; Mannik, K; Marsal, S; Martin, N; Mattingsdal, M; McDevitt, S; McGuffin, P; Merl, E; Metspalu, A; Meulenbelt, I; Micali, N; Mitchell, J; Mitchell, K; Monteleone, P; Monteleone, A M; Mortensen, P; Munn-Chernoff, M A; Navratilova, M; Nilsson, I; Norring, C; Ntalla, I; Ophoff, R A; O'Toole, J K; Palotie, A; Pante, J; Papezova, H; Pinto, D; Rabionet, R; Raevuori, A; Rajewski, A; Ramoz, N; Rayner, N W; Reichborn-Kjennerud, T; Ripatti, S; Roberts, M; Rotondo, A; Rujescu, D; Rybakowski, F; Santonastaso, P; Scherag, A; Scherer, S W; Schmidt, U; Schork, N J; Schosser, A; Slachtova, L; Sladek, R; Slagboom, P E; Slof-Op 't Landt, M C T; Slopien, A; Soranzo, N; Southam, L; Steen, V M; Strengman, E; Strober, M; Sullivan, P F; Szatkiewicz, J P; Szeszenia-Dabrowska, N; Tachmazidou, I; Tenconi, E; Thornton, L M; Tortorella, A; Tozzi, F; Treasure, J; Tsitsika, A; Tziouvas, K; van Elburg, A A; van Furth, E F; Wagner, G; Walton, E; Watson, H; Wichmann, H-E; Widen, E; Woodside, D B; Yanovski, J; Yao, S; Yilmaz, Z; Zeggini, E; Zerwas, S; Zipfel, S; Collier, D A; Sullivan, P F; Breen, G; Bulik, C M; Zeggini, E

2018-01-01

Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10−6), and rs7700147, an intergenic variant (P=2.93 × 10−5). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes. PMID:29155802

Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa.

PubMed

Huckins, L M; Hatzikotoulas, K; Southam, L; Thornton, L M; Steinberg, J; Aguilera-McKay, F; Treasure, J; Schmidt, U; Gunasinghe, C; Romero, A; Curtis, C; Rhodes, D; Moens, J; Kalsi, G; Dempster, D; Leung, R; Keohane, A; Burghardt, R; Ehrlich, S; Hebebrand, J; Hinney, A; Ludolph, A; Walton, E; Deloukas, P; Hofman, A; Palotie, A; Palta, P; van Rooij, F J A; Stirrups, K; Adan, R; Boni, C; Cone, R; Dedoussis, G; van Furth, E; Gonidakis, F; Gorwood, P; Hudson, J; Kaprio, J; Kas, M; Keski-Rahonen, A; Kiezebrink, K; Knudsen, G-P; Slof-Op 't Landt, M C T; Maj, M; Monteleone, A M; Monteleone, P; Raevuori, A H; Reichborn-Kjennerud, T; Tozzi, F; Tsitsika, A; van Elburg, A; Collier, D A; Sullivan, P F; Breen, G; Bulik, C M; Zeggini, E

2018-05-01

Anorexia nervosa (AN) is a complex neuropsychiatric disorder presenting with dangerously low body weight, and a deep and persistent fear of gaining weight. To date, only one genome-wide significant locus associated with AN has been identified. We performed an exome-chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European origin and 15 485 ancestrally matched controls. Unlike previous studies, this GWAS also probed association in low-frequency and rare variants. Sixteen independent variants were taken forward for in silico and de novo replication (11 common and 5 rare). No findings reached genome-wide significance. Two notable common variants were identified: rs10791286, an intronic variant in OPCML (P=9.89 × 10 -6 ), and rs7700147, an intergenic variant (P=2.93 × 10 -5 ). No low-frequency variant associations were identified at genome-wide significance, although the study was well-powered to detect low-frequency variants with large effect sizes, suggesting that there may be no AN loci in this genomic search space with large effect sizes.

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number.

PubMed

Sukumaran, Sivakumar; Lopes, Marta; Dreisigacker, Susanne; Reynolds, Matthew

2018-04-01

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number. Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci-6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)-were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79-85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

A meta-analysis of genome-wide association studies of asthma in Puerto Ricans

PubMed Central

Yan, Qi; Brehm, John; Pino-Yanes, Maria; Forno, Erick; Lin, Jerome; Oh, Sam S.; Acosta-Perez, Edna; Laurie, Cathy C.; Cloutier, Michelle M.; Raby, Benjamin A.; Stilp, Adrienne M.; Sofer, Tamar; Hu, Donglei; Huntsman, Scott; Eng, Celeste S.; Conomos, Matthew P.; Rastogi, Deepa; Rice, Kenneth; Canino, Glorisa; Chen, Wei; Barr, R. Graham; Burchard, Esteban G.; Celedón, Juan C.

2017-01-01

Rationale No genome-wide association study (GWAS) of asthma has been conducted in Puerto Ricans. Objective To identify susceptibility genetic variants for asthma in Puerto Ricans. Methods We conducted a meta-analysis of GWAS of asthma, including Puerto Rican participants from: GALA I-II, the Hartford-Puerto Rico Study, and the Hispanic Community Health Study. Moreover, we examined whether susceptibility loci identified in previous meta-analyses of GWAS are associated with asthma in Puerto Ricans. Results The only locus to achieve a genome-wide significant association with asthma in an analysis of 2,144 cases and 2,893 controls was chromosome 17q21, as evidenced by our top SNP, rs907092 (OR = 0.71, P = 1.2 ×10−12) on IKZF3. Similar to findings in non-Puerto Ricans, SNPs in genes in the same LD block as IKZF3 (e.g. ZPBP2, ORMDL3 and GSDMB) were also significantly associated with asthma in Puerto Ricans. With regard to results from a meta-analysis in Europeans, we replicated findings for the SNP at GSDMB, but not for SNPs in any other genes. On the other hand, we replicated results from a meta-analysis of North American populations for SNPs in IL1RL1, TSLP and GSDMB but not for IL33. Conclusions Common variants on chromosome 17q21 have the greatest effects on asthma in Puerto Ricans, a high-risk ethnic group. PMID:28461288

DNA methylation in inflammatory bowel disease and beyond

PubMed Central

Low, Daren; Mizoguchi, Atsushi; Mizoguchi, Emiko

2013-01-01

Inflammatory bowel disease (IBD) is a consequence of the complex, dysregulated interplay between genetic predisposition, environmental factors, and microbial composition in the intestine. Despite a great advancement in identifying host-susceptibility genes using genome-wide association studies (GWAS), the majority of IBD cases are still underrepresented. The immediate challenge in post-GWAS era is to identify other causative genetic factors of IBD. DNA methylation has received increasing attention for its mechanistical role in IBD pathogenesis. This stable, yet dynamic DNA modification, can directly affect gene expression that have important implications in IBD development. The alterations in DNA methylation associated with IBD are likely to outset as early as embryogenesis all the way until old-age. In this review, we will discuss the recent advancement in understanding how DNA methylation alterations can contribute to the development of IBD. PMID:23983426

Genome-wide meta-analysis identifies novel gender specific loci associated with thyroid antibodies level in Croatians.

PubMed

Matana, Antonela; Popović, Marijana; Boutin, Thibaud; Torlak, Vesela; Brdar, Dubravka; Gunjača, Ivana; Kolčić, Ivana; Boraska Perica, Vesna; Punda, Ante; Polašek, Ozren; Hayward, Caroline; Barbalić, Maja; Zemunik, Tatijana

2018-04-18

Autoimmune thyroid diseases (AITD) are multifactorial endocrine diseases most frequently accompanied by Tg and TPO autoantibodies. Both antibodies have a higher prevalence in females and act under a strong genetic influence. To identify novel variants underlying thyroid antibody levels, we performed GWAS meta-analysis on the plasma levels of TgAb and TPOAb in three Croatian cohorts, as well as gender specific GWAS and a bivariate analysis. No significant association was detected with the level of TgAb and TPOAb in the meta-analysis of GWAS or bivariate results for all individuals. The bivariate analysis in females only revealed a genome-wide significant association for the locus near GRIN3A (rs4457391, P = 7.76 × 10 -9 ). The same locus had borderline association with TPOAb levels in females (rs1935377, P = 8.58 × 10 -8 ). In conclusion, we identified a novel gender specific locus associated with TgAb and TPOAb levels. Our findings provide a novel insight into genetic and gender differences associated with thyroid antibodies. Copyright © 2018 Elsevier Inc. All rights reserved.

Improving the detection of pathways in genome-wide association studies by combined effects of SNPs from Linkage Disequilibrium blocks.

PubMed

Zhao, Huiying; Nyholt, Dale R; Yang, Yuanhao; Wang, Jihua; Yang, Yuedong

2017-06-14

Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path .

Lack of association between arterial stiffness and genetic variants by genome-wide association scan.

PubMed

Park, Sungha; Lee, Ji-Young; Kim, Byeong-Keuk; Lee, Sang-Hak; Chang, Hyuk-Jae; Choi, DongHoon; Jang, Yangsoo

2015-01-01

Arterial stiffness is an independent predictor of cardiovascular disease risk. However, whether genetic risk variants are associated with arterial stiffness measures, such as pulse-wave velocity (PWV), is largely unknown. Therefore, we performed a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNPs) associated with PWV in a Korea population. Study participants consisted of 402 patients in the Yonsei cardiovascular genome center cohort. Arterial stiffness was measured as brachial-ankle pulse-wave velocity (baPWV). Genotyping was performed in 402 subjects with the Axiom Genome-Wide ASI 1 Array Plate containing more than 600,000 SNP markers. The findings were tested for replication in independent subjects from a community-based cohort of 1206 individuals, using a Taqman assay to include two candidate SNPs. Associations with PWV were evaluated using an additive genetic model that included age, gender, systolic blood pressure and diastolic blood pressure as covariates. GWAS and replication analyses were conducted using the measured genotype method implemented in PLINK and SAS. We observed two candidate SNPs associated with baPWV in GWAS: rs7271920 (p = 7.15 × 10(-9)) and rs10125157 (p = 8.25 × 10(-7)). However, neither of these was significant in the replication cohort. In summary, we did not identify any common genetic variants associated with baPWV in cardiovascular patients.

Gene-set analysis based on the pharmacological profiles of drugs to identify repurposing opportunities in schizophrenia.

PubMed

de Jong, Simone; Vidler, Lewis R; Mokrab, Younes; Collier, David A; Breen, Gerome

2016-08-01

Genome-wide association studies (GWAS) have identified thousands of novel genetic associations for complex genetic disorders, leading to the identification of potential pharmacological targets for novel drug development. In schizophrenia, 108 conservatively defined loci that meet genome-wide significance have been identified and hundreds of additional sub-threshold associations harbour information on the genetic aetiology of the disorder. In the present study, we used gene-set analysis based on the known binding targets of chemical compounds to identify the 'drug pathways' most strongly associated with schizophrenia-associated genes, with the aim of identifying potential drug repositioning opportunities and clues for novel treatment paradigms, especially in multi-target drug development. We compiled 9389 gene sets (2496 with unique gene content) and interrogated gene-based p-values from the PGC2-SCZ analysis. Although no single drug exceeded experiment wide significance (corrected p<0.05), highly ranked gene-sets reaching suggestive significance including the dopamine receptor antagonists metoclopramide and trifluoperazine and the tyrosine kinase inhibitor neratinib. This is a proof of principle analysis showing the potential utility of GWAS data of schizophrenia for the direct identification of candidate drugs and molecules that show polypharmacy. © The Author(s) 2016.

Joint genetic analysis of hippocampal size in mouse and human identifies a novel gene linked to neurodegenerative disease.

PubMed

Ashbrook, David G; Williams, Robert W; Lu, Lu; Stein, Jason L; Hibar, Derrek P; Nichols, Thomas E; Medland, Sarah E; Thompson, Paul M; Hager, Reinmar

2014-10-03

Variation in hippocampal volume has been linked to significant differences in memory, behavior, and cognition among individuals. To identify genetic variants underlying such differences and associated disease phenotypes, multinational consortia such as ENIGMA have used large magnetic resonance imaging (MRI) data sets in human GWAS studies. In addition, mapping studies in mouse model systems have identified genetic variants for brain structure variation with great power. A key challenge is to understand how genetically based differences in brain structure lead to the propensity to develop specific neurological disorders. We combine the largest human GWAS of brain structure with the largest mammalian model system, the BXD recombinant inbred mouse population, to identify novel genetic targets influencing brain structure variation that are linked to increased risk for neurological disorders. We first use a novel cross-species, comparative analysis using mouse and human genetic data to identify a candidate gene, MGST3, associated with adult hippocampus size in both systems. We then establish the coregulation and function of this gene in a comprehensive systems-analysis. We find that MGST3 is associated with hippocampus size and is linked to a group of neurodegenerative disorders, such as Alzheimer's.

Functional SNP associated with birth weight in independent populations identified with a permutation step added to GBLUP-GWAS

USDA-ARS?s Scientific Manuscript database

This study was conducted as an initial assessment of a newly available genotyping assay containing about 34,000 common SNP included on previous SNP chips, and 199,000 sequence variants predicted to affect gene function. Objectives were to identify functional variants associated with birth weight in...

The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases

PubMed Central

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

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

PubMed

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; 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 F; Edwards, Robert P; 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; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; 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; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; 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; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; 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; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

Network-based integration of GWAS and gene expression identifies a HOX-centric network associated with serous ovarian cancer risk

PubMed Central

Kar, Siddhartha P.; Tyrer, Jonathan P.; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie T.; Beckmann, Matthias W.; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel; 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 F.; Edwards, Robert P.; 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; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K.; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K.; Kelemen, Linda E.; Kellar, Melissa; Kelley, Joseph; 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; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain A.; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; 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; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston-Campbell, Lara E.; 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; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Monteiro, Alvaro N. A.; Freedman, Matthew L.; Gayther, Simon A.; Pharoah, Paul D. P.

2015-01-01

Background Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by co-expression may also be enriched for additional EOC risk associations. Methods We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly co-expressed with each selected TF gene in the unified microarray data set of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this data set were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Results Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P<0.05 and FDR<0.05). These results were replicated (P<0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. Conclusion We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Impact Network analysis integrating large, context-specific data sets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. PMID:26209509

Haplotype-based approach to known MS-associated regions increases the amount of explained risk

PubMed Central

Khankhanian, Pouya; Gourraud, Pierre-Antoine; Lizee, Antoine; Goodin, Douglas S

2015-01-01

Genome-wide association studies (GWAS), using single nucleotide polymorphisms (SNPs), have yielded 110 non-human leucocyte antigen genomic regions that are associated with multiple sclerosis (MS). Despite this large number of associations, however, only 28% of MS-heritability can currently be explained. Here we compare the use of multi-SNP-haplotypes to the use of single-SNPs as alternative methods to describe MS genetic risk. SNP-haplotypes (of various lengths from 1 up to 15 contiguous SNPs) were constructed at each of the 110 previously identified, MS-associated, genomic regions. Even after correcting for the larger number of statistical comparisons made when using the haplotype-method, in 32 of the regions, the SNP-haplotype based model was markedly more significant than the single-SNP based model. By contrast, in no region was the single-SNP based model similarly more significant than the SNP-haplotype based model. Moreover, when we included the 932 MS-associated SNP-haplotypes (that we identified from 102 regions) as independent variables into a logistic linear model, the amount of MS-heritability, as assessed by Nagelkerke's R-squared, was 38%, which was considerably better than 29%, which was obtained by using only single-SNPs. This study demonstrates that SNP-haplotypes can be used to fine-map the genetic associations within regions of interest previously identified by single-SNP GWAS. Moreover, the amount of the MS genetic risk explained by the SNP-haplotype associations in the 110 MS-associated genomic regions was considerably greater when using SNP-haplotypes than when using single-SNPs. Also, the use of SNP-haplotypes can lead to the discovery of new regions of interest, which have not been identified by a single-SNP GWAS. PMID:26185143

Inferring causal relationships between phenotypes using summary statistics from genome-wide association studies.

PubMed

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.

Pathway-based discovery of genetic interactions in breast cancer

PubMed Central

Xu, Zack Z.; Boone, Charles; Lange, Carol A.

2017-01-01

Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP-SNP interactions. PMID:28957314

Genome-wide Association Study for Ovarian Cancer Susceptibility using Pooled DNA

PubMed Central

Lu, Yi; Chen, Xiaoqing; Beesley, Jonathan; Johnatty, Sharon E.; deFazio, Anna; Lambrechts, Sandrina; Lambrechts, Diether; Despierre, Evelyn; Vergotes, Ignace; Chang-Claude, Jenny; Hein, Rebecca; Nickels, Stefan; Wang-Gohrke, Shan; Dörk, Thilo; Dürst, Matthias; Antonenkova, Natalia; Bogdanova, Natalia; Goodman, Marc T.; Lurie, Galina; Wilkens, Lynne R.; Carney, Michael E.; Butzow, Ralf; Nevanlinna, Heli; Heikkinen, Tuomas; Leminen, Arto; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; van Altena, Anne M.; Aben, Katja K.; Kjaer, Susanne Krüger; Høgdall, Estrid; Jensen, Allan; Brooks-Wilson, Angela; Le, Nhu; Cook, Linda; Earp, Madalene; Kelemen, Linda; Easton, Douglas; Pharoah, Paul; Song, Honglin; Tyrer, Jonathan; Ramus, Susan; Menon, Usha; Gentry-Maharaj, Alexandra; Gayther, Simon A.; Bandera, Elisa V.; Olson, Sara H.; Orlow, Irene; Rodriguez-Rodriguez, Lorna

2013-01-01

Recent genome-wide association studies (GWAS) have identified four low-penetrance ovarian cancer susceptibility loci. We hypothesized that further moderate or low penetrance variants exist among the subset of SNPs not well tagged by the genotyping arrays used in the previous studies which would account for some of the remaining risk. We therefore conducted a time- and cost-effective stage 1 GWAS on 342 invasive serous cases and 643 controls genotyped on pooled DNA using the high density Illumina 1M-Duo array. We followed up 20 of the most significantly associated SNPs, which are not well tagged by the lower density arrays used by the published GWAS, and genotyping them on individual DNA. Most of the top 20 SNPs were clearly validated by individually genotyping the samples used in the pools. However, none of the 20 SNPs replicated when tested for association in a much larger stage 2 set of 4,651 cases and 6,966 controls from the Ovarian Cancer Association Consortium. Given that most of the top 20 SNPs from pooling were validated in the same samples by individual genotyping, the lack of replication is likely to be due to the relatively small sample size in our stage 1 GWAS rather than due to problems with the pooling approach. We conclude that there are unlikely to be any moderate or large effects on ovarian cancer risk untagged by the less dense arrays. However our study lacked power to make clear statements on the existence of hitherto untagged small effect variants. PMID:22794196

Statistical power and utility of meta-analysis methods for cross-phenotype genome-wide association studies.

PubMed

Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H

2018-01-01

Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.

Association of human height-related genetic variants with familial short stature in Han Chinese in Taiwan.

PubMed

Lin, Ying-Ju; Liao, Wen-Ling; Wang, Chung-Hsing; Tsai, Li-Ping; Tang, Chih-Hsin; Chen, Chien-Hsiun; Wu, Jer-Yuarn; Liang, Wen-Miin; Hsieh, Ai-Ru; Cheng, Chi-Fung; Chen, Jin-Hua; Chien, Wen-Kuei; Lin, Ting-Hsu; Wu, Chia-Ming; Liao, Chiu-Chu; Huang, Shao-Mei; Tsai, Fuu-Jen

2017-07-25

Human height can be described as a classical and inherited trait model. Genome-wide association studies (GWAS) have revealed susceptible loci and provided insights into the polygenic nature of human height. Familial short stature (FSS) represents a suitable trait for investigating short stature genetics because disease associations with short stature have been ruled out in this case. In addition, FSS is caused only by genetically inherited factors. In this study, we explored the correlations of FSS risk with the genetic loci associated with human height in previous GWAS, alone and cumulatively. We systematically evaluated 34 known human height single nucleotide polymorphisms (SNPs) in relation to FSS in the additive model (p < 0.00005). A cumulative effect was observed: the odds ratios gradually increased with increasing genetic risk score quartiles (p < 0.001; Cochran-Armitage trend test). Six affected genes-ZBTB38, ZNF638, LCORL, CABLES1, CDK10, and TSEN15-are located in the nucleus and have been implicated in embryonic, organismal, and tissue development. In conclusion, our study suggests that 13 human height GWAS-identified SNPs are associated with FSS risk both alone and cumulatively.

A Meta-Analysis of Genome-Wide Association Scans Identifies IL18RAP, PTPN2, TAGAP, and PUS10 As Shared Risk Loci for Crohn's Disease and Celiac Disease

PubMed Central

Boucher, Gabrielle; Beauchamp, Claudine; Trynka, Gosia; Dubois, Patrick C.; Lagacé, Caroline; Stokkers, Pieter C. F.; Hommes, Daan W.; Barisani, Donatella; Palmieri, Orazio; Annese, Vito; van Heel, David A.; Weersma, Rinse K.; Daly, Mark J.; Wijmenga, Cisca; Rioux, John D.

2011-01-01

Crohn's disease (CD) and celiac disease (CelD) are chronic intestinal inflammatory diseases, involving genetic and environmental factors in their pathogenesis. The two diseases can co-occur within families, and studies suggest that CelD patients have a higher risk to develop CD than the general population. These observations suggest that CD and CelD may share common genetic risk loci. Two such shared loci, IL18RAP and PTPN2, have already been identified independently in these two diseases. The aim of our study was to explicitly identify shared risk loci for these diseases by combining results from genome-wide association study (GWAS) datasets of CD and CelD. Specifically, GWAS results from CelD (768 cases, 1,422 controls) and CD (3,230 cases, 4,829 controls) were combined in a meta-analysis. Nine independent regions had nominal association p-value <1.0×10−5 in this meta-analysis and showed evidence of association to the individual diseases in the original scans (p-value <1×10−2 in CelD and <1×10−3 in CD). These include the two previously reported shared loci, IL18RAP and PTPN2, with p-values of 3.37×10−8 and 6.39×10−9, respectively, in the meta-analysis. The other seven had not been reported as shared loci and thus were tested in additional CelD (3,149 cases and 4,714 controls) and CD (1,835 cases and 1,669 controls) cohorts. Two of these loci, TAGAP and PUS10, showed significant evidence of replication (Bonferroni corrected p-values <0.0071) in the combined CelD and CD replication cohorts and were firmly established as shared risk loci of genome-wide significance, with overall combined p-values of 1.55×10−10 and 1.38×10−11 respectively. Through a meta-analysis of GWAS data from CD and CelD, we have identified four shared risk loci: PTPN2, IL18RAP, TAGAP, and PUS10. The combined analysis of the two datasets provided the power, lacking in the individual GWAS for single diseases, to detect shared loci with a relatively small effect. PMID:21298027

The influence of polygenic risk for bipolar disorder on neural activation assessed using fMRI

PubMed Central

Whalley, H C; Papmeyer, M; Sprooten, E; Romaniuk, L; Blackwood, D H; Glahn, D C; Hall, J; Lawrie, S M; Sussmann, Je; McIntosh, A M

2012-01-01

Genome-wide association studies (GWAS) have demonstrated a significant polygenic contribution to bipolar disorder (BD) where disease risk is determined by the summation of many alleles of small individual magnitude. Modelling polygenic risk scores may be a powerful way of identifying disrupted brain regions whose genetic architecture is related to that of BD. We determined the extent to which common genetic variation underlying risk to BD affected neural activation during an executive processing/language task in individuals at familial risk of BD and healthy controls. Polygenic risk scores were calculated for each individual based on GWAS data from the Psychiatric GWAS Consortium Bipolar Disorder Working Group (PGC-BD) of over 16 000 subjects. The familial group had a significantly higher polygene score than the control group (P=0.04). There were no significant group by polygene interaction effects in terms of association with brain activation. However, we did find that an increasing polygenic risk allele load for BD was associated with increased activation in limbic regions previously implicated in BD, including the anterior cingulate cortex and amygdala, across both groups. The findings suggest that this novel polygenic approach to examine brain-imaging data may be a useful means of identifying genetically mediated traits mechanistically linked to the aetiology of BD. PMID:22760554

A Discovery Genome-Wide Association Study of Entrepreneurship

ERIC Educational Resources Information Center

Quaye, Lydia; Nicolaou, Nicos; Shane, Scott; Mangino, Massimo

2012-01-01

To identify specific genetic variants influencing the phenotype of entrepreneurship, we conducted a genome-wide association study (GWAS) with 3,933 Caucasian females from the TwinsUK Adult Twin Registry. Following stringent genotype quality control, GWAF (genome-wide association analyses for family data) software was used to assess the association…

Genome-Wide Association Mapping Combined with Reverse Genetics Identifies New Effectors of Low Water Potential-Induced Proline Accumulation in Arabidopsis1[W][OPEN

PubMed Central

Verslues, Paul E.; Lasky, Jesse R.; Juenger, Thomas E.; Liu, Tzu-Wen; Kumar, M. Nagaraj

2014-01-01

Arabidopsis (Arabidopsis thaliana) exhibits natural genetic variation in drought response, including varying levels of proline (Pro) accumulation under low water potential. As Pro accumulation is potentially important for stress tolerance and cellular redox control, we conducted a genome-wide association (GWAS) study of low water potential-induced Pro accumulation using a panel of natural accessions and publicly available single-nucleotide polymorphism (SNP) data sets. Candidate genomic regions were prioritized for subsequent study using metrics considering both the strength and spatial clustering of the association signal. These analyses found many candidate regions likely containing gene(s) influencing Pro accumulation. Reverse genetic analysis of several candidates identified new Pro effector genes, including thioredoxins and several genes encoding Universal Stress Protein A domain proteins. These new Pro effector genes further link Pro accumulation to cellular redox and energy status. Additional new Pro effector genes found include the mitochondrial protease LON1, ribosomal protein RPL24A, protein phosphatase 2A subunit A3, a MADS box protein, and a nucleoside triphosphate hydrolase. Several of these new Pro effector genes were from regions with multiple SNPs, each having moderate association with Pro accumulation. This pattern supports the use of summary approaches that incorporate clusters of SNP associations in addition to consideration of individual SNP probability values. Further GWAS-guided reverse genetics promises to find additional effectors of Pro accumulation. The combination of GWAS and reverse genetics to efficiently identify new effector genes may be especially applicable for traits difficult to analyze by other genetic screening methods. PMID:24218491

Genome-wide association study identifies common loci influencing circulating glycated hemoglobin (HbA1c) levels in non-diabetic subjects: the Long Life Family Study (LLFS).

PubMed

An, Ping; Miljkovic, Iva; Thyagarajan, Bharat; Kraja, Aldi T; Daw, E Warwick; Pankow, James S; Selvin, Elizabeth; Kao, W H Linda; Maruthur, Nisa M; Nalls, Micahel A; Liu, Yongmei; Harris, Tamara B; Lee, Joseph H; Borecki, Ingrid B; Christensen, Kaare; Eckfeldt, John H; Mayeux, Richard; Perls, Thomas T; Newman, Anne B; Province, Michael A

2014-04-01

Glycated hemoglobin (HbA1c) is a stable index of chronic glycemic status and hyperglycemia associated with progressive development of insulin resistance and frank diabetes. It is also associated with premature aging and increased mortality. To uncover novel loci for HbA1c that are associated with healthy aging, we conducted a genome-wide association study (GWAS) using non-diabetic participants in the Long Life Family Study (LLFS), a study with familial clustering of exceptional longevity in the US and Denmark. A total of 4088 non-diabetic subjects from the LLFS were used for GWAS discoveries, and a total of 8231 non-diabetic subjects from the Atherosclerosis Risk in Communities Study (ARIC, in the MAGIC Consortium) and the Health, Aging, and Body Composition Study (HABC) were used for GWAS replications. HbA1c was adjusted for age, sex, centers, 20 principal components, without and with BMI. A linear mixed effects model was used for association testing. Two known loci at GCK rs730497 (or rs2908282) and HK1 rs17476364 were confirmed (p<5e-8). Of 25 suggestive (5e-8

The 19q12 bladder cancer GWAS signal: association with cyclin E function and aggressive disease

PubMed Central

Fu, Yi-Ping; Kohaar, Indu; Moore, Lee E.; Lenz, Petra; Figueroa, Jonine D.; Tang, Wei; Porter-Gill, Patricia; Chatterjee, Nilanjan; Scott-Johnson, Alexandra; Garcia-Closas, Montserrat; Muchmore, Brian; Baris, Dalsu; Paquin, Ashley; Ylaya, Kris; Schwenn, Molly; Apolo, Andrea B.; Karagas, Margaret R.; Tarway, McAnthony; Johnson, Alison; Mumy, Adam; Schned, Alan; Guedez, Liliana; Jones, Michael A.; Kida, Masatoshi; Monawar Hosain, GM; Malats, Nuria; Kogevinas, Manolis; Tardon, Adonina; Serra, Consol; Carrato, Alfredo; Garcia-Closas, Reina; Lloreta, Josep; Wu, Xifeng; Purdue, Mark; Andriole, Gerald L.; Grubb, Robert L.; Black, Amanda; Landi, Maria T.; Caporaso, Neil E.; Vineis, Paolo; Siddiq, Afshan; Bueno-de-Mesquita, H. Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Severi, Gianluca; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth C.; Tjønneland, Anne; Brennan, Paul; Chang-Claude, Jenny; Riboli, Elio; Prescott, Jennifer; Chen, Constance; De Vivo, Immaculata; Govannucci, Edward; Hunter, David; Kraft, Peter; Lindstrom, Sara; Gapstur, Susan M.; Jacobs, Eric J.; Diver, W. Ryan; Albanes, Demetrius; Weinstein, Stephanie J.; Virtamo, Jarmo; Kooperberg, Charles; Hohensee, Chancellor; Rodabough, Rebecca J.; Cortessis, Victoria K.; Conti, David V.; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Haiman, Christopher A.; Cussenot, Olivier; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Porru, Stefano; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Grossman, H. Barton; Wang, Zhaoming; Deng, Xiang; Chung, Charles C.; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Fraumeni, Joseph; Chanock, Stephen J.; Hewitt, Stephen M.; Silverman, Debra T.; Rothman, Nathaniel; Prokunina-Olsson, Ludmila

2014-01-01

A genome-wide association study (GWAS) of bladder cancer identified a genetic marker rs8102137 within the 19q12 region as a novel susceptibility variant. This marker is located upstream of the CCNE1 gene, which encodes cyclin E, a cell cycle protein. We performed genetic fine mapping analysis of the CCNE1 region using data from two bladder cancer GWAS (5,942 cases and 10,857 controls). We found that the original GWAS marker rs8102137 represents a group of 47 linked SNPs (with r2≥0.7) associated with increased bladder cancer risk. From this group we selected a functional promoter variant rs7257330, which showed strong allele-specific binding of nuclear proteins in several cell lines. In both GWAS, rs7257330 was associated only with aggressive bladder cancer, with a combined per-allele odds ratio (OR) =1.18 (95%CI=1.09-1.27, p=4.67×10−5 vs. OR =1.01 (95%CI=0.93-1.10, p=0.79) for non-aggressive disease, with p=0.0015 for case-only analysis. Cyclin E protein expression analyzed in 265 bladder tumors was increased in aggressive tumors (p=0.013) and, independently, with each rs7257330-A risk allele (ptrend=0.024). Over-expression of recombinant cyclin E in cell lines caused significant acceleration of cell cycle. In conclusion, we defined the 19q12 signal as the first GWAS signal specific for aggressive bladder cancer. Molecular mechanisms of this genetic association may be related to cyclin E over-expression and alteration of cell cycle in carriers of CCNE1 risk variants. In combination with established bladder cancer risk factors and other somatic and germline genetic markers, the CCNE1 variants could be useful for inclusion into bladder cancer risk prediction models. PMID:25320178

Genetic analysis of inflorescence and plant height components in sorghum (Panicoidae) and comparative genetics with rice (Oryzoidae).

PubMed

Zhang, Dong; Kong, Wenqian; Robertson, Jon; Goff, Valorie H; Epps, Ethan; Kerr, Alexandra; Mills, Gabriel; Cromwell, Jay; Lugin, Yelena; Phillips, Christine; Paterson, Andrew H

2015-04-19

Domestication has played an important role in shaping characteristics of the inflorescence and plant height in cultivated cereals. Taking advantage of meta-analysis of QTLs, phylogenetic analyses in 502 diverse sorghum accessions, GWAS in a sorghum association panel (n = 354) and comparative data, we provide insight into the genetic basis of the domestication traits in sorghum and rice. We performed genome-wide association studies (GWAS) on 6 traits related to inflorescence morphology and 6 traits related to plant height in sorghum, comparing the genomic regions implicated in these traits by GWAS and QTL mapping, respectively. In a search for signatures of selection, we identify genomic regions that may contribute to sorghum domestication regarding plant height, flowering time and pericarp color. Comparative studies across taxa show functionally conserved 'hotspots' in sorghum and rice for awn presence and pericarp color that do not appear to reflect corresponding single genes but may indicate co-regulated clusters of genes. We also reveal homoeologous regions retaining similar functions for plant height and flowering time since genome duplication an estimated 70 million years ago or more in a common ancestor of cereals. In most such homoeologous QTL pairs, only one QTL interval exhibits strong selection signals in modern sorghum. Intersections among QTL, GWAS and comparative data advance knowledge of genetic determinants of inflorescence and plant height components in sorghum, and add new dimensions to comparisons between sorghum and rice.

Genetic analysis of inflorescence and plant height components in sorghum (Panicoidae) and comparative genetics with rice (Oryzoidae)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Dong; Kong, Wenqian; Robertson, Jon

Domestication has played an important role in shaping characteristics of the inflorescence and plant height in cultivated cereals. Taking advantage of meta-analysis of QTLs, phylogenetic analyses in 502 diverse sorghum accessions, GWAS in a sorghum association panel (n = 354) and comparative data, we provide insight into the genetic basis of the domestication traits in sorghum and rice. We performed genome-wide association studies (GWAS) on 6 traits related to inflorescence morphology and 6 traits related to plant height in sorghum, comparing the genomic regions implicated in these traits by GWAS and QTL mapping, respectively. In a search for signatures ofmore » selection, we identify genomic regions that may contribute to sorghum domestication regarding plant height, flowering time and pericarp color. Comparative studies across taxa show functionally conserved ‘hotspots’ in sorghum and rice for awn presence and pericarp color that do not appear to reflect corresponding single genes but may indicate co-regulated clusters of genes. We also reveal homoeologous regions retaining similar functions for plant height and flowering time since genome duplication an estimated 70 million years ago or more in a common ancestor of cereals. In most such homoeologous QTL pairs, only one QTL interval exhibits strong selection signals in modern sorghum. Intersections among QTL, GWAS and comparative data advance knowledge of genetic determinants of inflorescence and plant height components in sorghum, and add new dimensions to comparisons between sorghum and rice.« less

Genetic analysis of inflorescence and plant height components in sorghum (Panicoidae) and comparative genetics with rice (Oryzoidae)

DOE PAGES

Zhang, Dong; Kong, Wenqian; Robertson, Jon; ...

2015-12-01

Domestication has played an important role in shaping characteristics of the inflorescence and plant height in cultivated cereals. Taking advantage of meta-analysis of QTLs, phylogenetic analyses in 502 diverse sorghum accessions, GWAS in a sorghum association panel (n = 354) and comparative data, we provide insight into the genetic basis of the domestication traits in sorghum and rice. We performed genome-wide association studies (GWAS) on 6 traits related to inflorescence morphology and 6 traits related to plant height in sorghum, comparing the genomic regions implicated in these traits by GWAS and QTL mapping, respectively. In a search for signatures ofmore » selection, we identify genomic regions that may contribute to sorghum domestication regarding plant height, flowering time and pericarp color. Comparative studies across taxa show functionally conserved ‘hotspots’ in sorghum and rice for awn presence and pericarp color that do not appear to reflect corresponding single genes but may indicate co-regulated clusters of genes. We also reveal homoeologous regions retaining similar functions for plant height and flowering time since genome duplication an estimated 70 million years ago or more in a common ancestor of cereals. In most such homoeologous QTL pairs, only one QTL interval exhibits strong selection signals in modern sorghum. Intersections among QTL, GWAS and comparative data advance knowledge of genetic determinants of inflorescence and plant height components in sorghum, and add new dimensions to comparisons between sorghum and rice.« less

Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes

NASA Astrophysics Data System (ADS)

Oh, Jung Hun; Kerns, Sarah; Ostrer, Harry; Powell, Simon N.; Rosenstein, Barry; Deasy, Joseph O.

2017-02-01

The biological cause of clinically observed variability of normal tissue damage following radiotherapy is poorly understood. We hypothesized that machine/statistical learning methods using single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing complication risk, and furthermore could be used to identify key biological sources of variability. We developed a novel learning algorithm, called pre-conditioned random forest regression (PRFR), to construct polygenic risk models using hundreds of SNPs, thereby capturing genomic features that confer small differential risk. Predictive models were trained and validated on a cohort of 368 prostate cancer patients for two post-radiotherapy clinical endpoints: late rectal bleeding and erectile dysfunction. The proposed method results in better predictive performance compared with existing computational methods. Gene ontology enrichment analysis and protein-protein interaction network analysis are used to identify key biological processes and proteins that were plausible based on other published studies. In conclusion, we confirm that novel machine learning methods can produce large predictive models (hundreds of SNPs), yielding clinically useful risk stratification models, as well as identifying important underlying biological processes in the radiation damage and tissue repair process. The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints.

Case-Control Genome-Wide Association Study of Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Neale, Benjamin M.; Medland, Sarah; Ripke, Stephan; Anney, Richard J. L.; Asherson, Philip; Buitelaar, Jan; Franke, Barbara; Gill, Michael; Kent, Lindsey; Holmans, Peter; Middleton, Frank; Thapar, Anita; Lesch, Klaus-Peter; Faraone, Stephen V.; Daly, Mark; Nguyen, Thuy Trang; Schafer, Helmut; Steinhausen, Hans-Christoph; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Warnke, Andreas; Walitza, Susanne; Freitag, Christine; Meyer, Jobst; Palmason, Haukur; Rothenberger, Aribert; Hawi, Ziarih; Sergeant, Joseph; Roeyers, Herbert; Mick, Eric; Biederman, Joseph

2010-01-01

Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. Thus additional genome-wide association studies (GWAS) are needed. Method: We used case-control analyses of 896 cases…

Meta-Analysis of Genome-Wide Association Studies of Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Neale, Benjamin M.; Medland, Sarah E.; Ripke, Stephan; Asherson, Philip; Franke, Barbara; Lesch, Klaus-Peter; Faraone, Stephen V.; Nguyen, Thuy Trang; Schafer, Helmut; Holmans, Peter; Daly, Mark; Steinhausen, Hans-Christoph; Freitag, Christine; Reif, Andreas; Renner, Tobias J.; Romanos, Marcel; Romanos, Jasmin; Walitza, Susanne; Warnke, Andreas; Meyer, Jobst; Palmason, Haukur; Buitelaar, Jan; Vasquez, Alejandro Arias; Lambregts-Rommelse, Nanda; Gill, Michael; Anney, Richard J. L.; Langely, Kate; O'Donovan, Michael; Williams, Nigel; Owen, Michael; Thapar, Anita; Kent, Lindsey; Sergeant, Joseph; Roeyers, Herbert; Mick, Eric; Biederman, Joseph; Doyle, Alysa; Smalley, Susan; Loo, Sandra; Hakonarson, Hakon; Elia, Josephine; Todorov, Alexandre; Miranda, Ana; Mulas, Fernando; Ebstein, Richard P.; Rothenberger, Aribert; Banaschewski, Tobias; Oades, Robert D.; Sonuga-Barke, Edmund; McGough, James; Nisenbaum, Laura; Middleton, Frank; Hu, Xiaolan; Nelson, Stan

2010-01-01

Objective: Although twin and family studies have shown attention-deficit/hyperactivity disorder (ADHD) to be highly heritable, genetic variants influencing the trait at a genome-wide significant level have yet to be identified. As prior genome-wide association studies (GWAS) have not yielded significant results, we conducted a meta-analysis of…

Genetics of cortisol secretion and depressive symptoms: a candidate gene and genome wide association approach.

PubMed

Velders, Fleur P; Kuningas, Maris; Kumari, Meena; Dekker, Marieke J; Uitterlinden, Andre G; Kirschbaum, Clemens; Hek, Karin; Hofman, Albert; Verhulst, Frank C; Kivimaki, Mika; Van Duijn, Cornelia M; Walker, Brian R; Tiemeier, Henning

2011-08-01

Depressive patients often have altered cortisol secretion, but few studies have investigated genetic variants in relation to both cortisol secretion and depression. To identify genes related to both these conditions, we: (1) tested the association of single nucleotide polymorphisms (SNPs) in hypothalamic-pituitary-adrenal-axis (HPA-axis) candidate genes with a summary measure of total cortisol secretion during the day (cortisol(AUC)), (2) performed a genome wide association study (GWAS) of cortisol(AUC), and (3) tested the association of identified cortisol-related SNPs with depressive symptoms. We analyzed data on candidate SNPs for the HPA-axis, genome-wide scans, cortisol secretion (n=1711) and depressive symptoms (the Centre for Epidemiology Studies Depression Scale, CES-D) (n=2928) in elderly persons of the Rotterdam Study. We used data from the Whitehall II study (n=2836) to replicate the GWAS findings. Of the 1456 SNPs in 33 candidate genes, minor alleles of 4 SNPs (rs9470080, rs9394309, rs7748266 and rs1360780) in the FKBP5 gene were associated with a decreased cortisol(AUC) (p<1×10(-4) after correction for multiple testing using permutations). These SNPs were also associated with an increased risk of depressive symptoms (rs9470080: OR 1.19 (95%CI 1.0; 1.4)). The GWAS for cortisol yielded 2 SNPs with p-values of 1×10(-06) (rs8062512, rs2252459), but these associations could not be replicated. These results suggest that variation in the FKBP5 gene is associated with both cortisol(AUC) and the likelihood of depressive symptoms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Transcriptome study of differential expression in schizophrenia

PubMed Central

Sanders, Alan R.; Göring, Harald H. H.; Duan, Jubao; Drigalenko, Eugene I.; Moy, Winton; Freda, Jessica; He, Deli; Shi, Jianxin; Gejman, Pablo V.

2013-01-01

Schizophrenia genome-wide association studies (GWAS) have identified common SNPs, rare copy number variants (CNVs) and a large polygenic contribution to illness risk, but biological mechanisms remain unclear. Bioinformatic analyses of significantly associated genetic variants point to a large role for regulatory variants. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines (LCLs) from 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate (FDR) of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, microRNA (miRNA) processing and immunity. This functional diversity is consistent with schizophrenia's likely significant pathophysiological heterogeneity. The overall enrichment of immune-related genes among those differentially expressed by affection status is consistent with hypothesized immune contributions to schizophrenia risk. The observed differential expression of extended major histocompatibility complex (xMHC) region histones (HIST1H2BD, HIST1H2BC, HIST1H2BH, HIST1H2BG and HIST1H4K) converges with the genetic evidence from GWAS, which find the xMHC to be the most significant susceptibility locus. Among the differentially expressed immune-related genes, B3GNT2 is implicated in autoimmune disorders previously tied to schizophrenia risk (rheumatoid arthritis and Graves’ disease), and DICER1 is pivotal in miRNA processing potentially linking to miRNA alterations in schizophrenia (e.g. MIR137, the second strongest GWAS finding). Our analysis provides novel candidate genes for further study to assess their potential contribution to schizophrenia. PMID:23904455

A high throughput, functional screen of human Body Mass Index GWAS loci using tissue-specific RNAi Drosophila melanogaster crosses.

PubMed

Baranski, Thomas J; Kraja, Aldi T; Fink, Jill L; Feitosa, Mary; Lenzini, Petra A; Borecki, Ingrid B; Liu, Ching-Ti; Cupples, L Adrienne; North, Kari E; Province, Michael A

2018-04-01

Human GWAS of obesity have been successful in identifying loci associated with adiposity, but for the most part, these are non-coding SNPs whose function, or even whose gene of action, is unknown. To help identify the genes on which these human BMI loci may be operating, we conducted a high throughput screen in Drosophila melanogaster. Starting with 78 BMI loci from two recently published GWAS meta-analyses, we identified fly orthologs of all nearby genes (± 250KB). We crossed RNAi knockdown lines of each gene with flies containing tissue-specific drivers to knock down (KD) the expression of the genes only in the brain and the fat body. We then raised the flies on a control diet and compared the amount of fat/triglyceride in the tissue-specific KD group compared to the driver-only control flies. 16 of the 78 BMI GWAS loci could not be screened with this approach, as no gene in the 500-kb region had a fly ortholog. Of the remaining 62 GWAS loci testable in the fly, we found a significant fat phenotype in the KD flies for at least one gene for 26 loci (42%) even after correcting for multiple comparisons. By contrast, the rate of significant fat phenotypes in RNAi KD found in a recent genome-wide Drosophila screen (Pospisilik et al. (2010) is ~5%. More interestingly, for 10 of the 26 positive regions, we found that the nearest gene was not the one that showed a significant phenotype in the fly. Specifically, our screen suggests that for the 10 human BMI SNPs rs11057405, rs205262, rs9925964, rs9914578, rs2287019, rs11688816, rs13107325, rs7164727, rs17724992, and rs299412, the functional genes may NOT be the nearest ones (CLIP1, C6orf106, KAT8, SMG6, QPCTL, EHBP1, SLC39A8, ADPGK /ADPGK-AS1, PGPEP1, KCTD15, respectively), but instead, the specific nearby cis genes are the functional target (namely: ZCCHC8, VPS33A, RSRC2; SPDEF, NUDT3; PAGR1; SETD1, VKORC1; SGSM2, SRR; VASP, SIX5; OTX1; BANK1; ARIH1; ELL; CHST8, respectively). The study also suggests further functional experiments to elucidate mechanism of action for genes evolutionarily conserved for fat storage.

Genome-wide association study of ancestry-specific TB risk in the South African Coloured population

PubMed Central

Chimusa, Emile R.; Zaitlen, Noah; Daya, Michelle; Möller, Marlo; van Helden, Paul D.; Mulder, Nicola J.; Price, Alkes L.; Hoal, Eileen G.

2014-01-01

The worldwide burden of tuberculosis (TB) remains an enormous problem, and is particularly severe in the admixed South African Coloured (SAC) population residing in the Western Cape. Despite evidence from twin studies suggesting a strong genetic component to TB resistance, only a few loci have been identified to date. In this work, we conduct a genome-wide association study (GWAS), meta-analysis and trans-ethnic fine mapping to attempt the replication of previously identified TB susceptibility loci. Our GWAS results confirm the WT1 chr11 susceptibility locus (rs2057178: odds ratio = 0.62, P = 2.71e−06) previously identified by Thye et al., but fail to replicate previously identified polymorphisms in the TLR8 gene and locus 18q11.2. Our study demonstrates that the genetic contribution to TB risk varies between continental populations, and illustrates the value of including admixed populations in studies of TB risk and other complex phenotypes. Our evaluation of local ancestry based on the real and simulated data demonstrates that case-only admixture mapping is currently impractical in multi-way admixed populations, such as the SAC, due to spurious deviations in average local ancestry generated by current local ancestry inference methods. This study provides insights into identifying disease genes and ancestry-specific disease risk in multi-way admixed populations. PMID:24057671

Trans-ethnic meta-analysis of white blood cell phenotypes

PubMed Central

Keller, Margaux F.; Reiner, Alexander P.; Okada, Yukinori; van Rooij, Frank J.A.; Johnson, Andrew D.; Chen, Ming-Huei; Smith, Albert V.; Morris, Andrew P.; Tanaka, Toshiko; Ferrucci, Luigi; Zonderman, Alan B.; Lettre, Guillaume; Harris, Tamara; Garcia, Melissa; Bandinelli, Stefania; Qayyum, Rehan; Yanek, Lisa R.; Becker, Diane M.; Becker, Lewis C.; Kooperberg, Charles; Keating, Brendan; Reis, Jared; Tang, Hua; Boerwinkle, Eric; Kamatani, Yoichiro; Matsuda, Koichi; Kamatani, Naoyuki; Nakamura, Yusuke; Kubo, Michiaki; Liu, Simin; Dehghan, Abbas; Felix, Janine F.; Hofman, Albert; Uitterlinden, André G.; van Duijn, Cornelia M.; Franco, Oscar H.; Longo, Dan L.; Singleton, Andrew B.; Psaty, Bruce M.; Evans, Michelle K.; Cupples, L. Adrienne; Rotter, Jerome I.; O'Donnell, Christopher J.; Takahashi, Atsushi; Wilson, James G.; Ganesh, Santhi K.; Nalls, Mike A.

2014-01-01

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool. PMID:25096241

Prediction of breast cancer risk based on common genetic variants in women of East Asian ancestry.

PubMed

Wen, Wanqing; Shu, Xiao-Ou; Guo, Xingyi; Cai, Qiuyin; Long, Jirong; Bolla, Manjeet K; Michailidou, Kyriaki; Dennis, Joe; Wang, Qin; Gao, Yu-Tang; Zheng, Ying; Dunning, Alison M; García-Closas, Montserrat; Brennan, Paul; Chen, Shou-Tung; Choi, Ji-Yeob; Hartman, Mikael; Ito, Hidemi; Lophatananon, Artitaya; Matsuo, Keitaro; Miao, Hui; Muir, Kenneth; Sangrajrang, Suleeporn; Shen, Chen-Yang; Teo, Soo H; Tseng, Chiu-Chen; Wu, Anna H; Yip, Cheng Har; Simard, Jacques; Pharoah, Paul D P; Hall, Per; Kang, Daehee; Xiang, Yongbing; Easton, Douglas F; Zheng, Wei

2016-12-08

Approximately 100 common breast cancer susceptibility alleles have been identified in genome-wide association studies (GWAS). The utility of these variants in breast cancer risk prediction models has not been evaluated adequately in women of Asian ancestry. We evaluated 88 breast cancer risk variants that were identified previously by GWAS in 11,760 cases and 11,612 controls of Asian ancestry. SNPs confirmed to be associated with breast cancer risk in Asian women were used to construct a polygenic risk score (PRS). The relative and absolute risks of breast cancer by the PRS percentiles were estimated based on the PRS distribution, and were used to stratify women into different levels of breast cancer risk. We confirmed significant associations with breast cancer risk for SNPs in 44 of the 78 previously reported loci at P < 0.05. Compared with women in the middle quintile of the PRS, women in the top 1% group had a 2.70-fold elevated risk of breast cancer (95% CI: 2.15-3.40). The risk prediction model with the PRS had an area under the receiver operating characteristic curve of 0.606. The lifetime risk of breast cancer for Shanghai Chinese women in the lowest and highest 1% of the PRS was 1.35% and 10.06%, respectively. Approximately one-half of GWAS-identified breast cancer risk variants can be directly replicated in East Asian women. Collectively, common genetic variants are important predictors for breast cancer risk. Using common genetic variants for breast cancer could help identify women at high risk of breast cancer.

A post-GWAS confirming the SCD gene associated with milk medium- and long-chain unsaturated fatty acids in Chinese Holstein population.

PubMed

Li, C; Sun, D; Zhang, S; Liu, L; Alim, M A; Zhang, Q

2016-08-01

The stearoyl-CoA desaturase (delta-9-desaturase) gene encodes a key enzyme in the cellular biosynthesis of monounsaturated fatty acids. In our initial genome-wide association study (GWAS) of Chinese Holstein cows, 19 SNPs fell in a 1.8-Mb region (20.3-22.1 Mb) on chromosome 26 underlying the SCD gene and were highly significantly associated with C14:1 or C14 index. The aims of this study were to verify whether the SCD gene has significant genetic effects on milk fatty acid composition in dairy cattle. By resequencing the entire coding region of the bovine SCD gene, a total of six variations were identified, including three coding variations (g.10153G>A, g.10213T>C and g.10329C>T) and three intronic variations (g.6926A>G, g.8646G>A and g.16158G>C). The SNP in exon 3, g.10329C>T, was predicted to result in an amino acid replacement from alanine (GCG) to valine (GTG) in the SCD protein. An association study for 16 milk fatty acids using 346 Chinese Holstein cows with accurate phenotypes and genotypes was performed using the mixed animal model with the proc mixed procedure in sas 9.2. All six detected SNPs were revealed to be associated with six medium- and long-chain unsaturated fatty acids (P = 0.0457 to P < 0.0001), specifically for C14:1 and C14 index (P = 0.0005 to P < 0.0001). Subsequently, strong linkage disequilibrium (D' = 0.88-1.00) was observed among all six SNPs in SCD and the five SNPs (rs41623887, rs109923480, rs42090224, rs42092174 and rs42091426) within the 1.8-Mb region identified in our previous GWAS, indicating that the significant association of the SCD gene with milk fatty acid content traits reduced the observed significant 1.8-Mb chromosome region in GWAS. Haplotype-based analysis revealed significant associations of the haplotypes encompassing the six SCD SNPs and one SNP (rs109923480) in a GWAS with C14:1, C14 index, C16:1 and C16 index (P = 0.0011 to P < 0.0001). In summary, our findings provide replicate evidence for our previous GWAS and demonstrate that variants in the SCD gene are significantly associated with milk fatty acid composition in dairy cattle, which provides clear evidence for an increased understanding of milk fatty acid synthesis and enhances opportunities to improve milk-fat composition in dairy cattle. © 2016 Stichting International Foundation for Animal Genetics.

Controlling the Rate of GWAS False Discoveries

PubMed Central

Brzyski, Damian; Peterson, Christine B.; Sobczyk, Piotr; Candès, Emmanuel J.; Bogdan, Malgorzata; Sabatti, Chiara

2017-01-01

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study. PMID:27784720

Controlling the Rate of GWAS False Discoveries.

PubMed

Brzyski, Damian; Peterson, Christine B; Sobczyk, Piotr; Candès, Emmanuel J; Bogdan, Malgorzata; Sabatti, Chiara

2017-01-01

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study. Copyright © 2017 by the Genetics Society of America.

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

PubMed Central

Mäkinen, Ville-Petteri; Civelek, Mete; Meng, Qingying; Zhang, Bin; Zhu, Jun; Levian, Candace; Huan, Tianxiao; Segrè, Ayellet V.; Ghosh, Sujoy; Vivar, Juan; Nikpay, Majid; Stewart, Alexandre F. R.; Nelson, Christopher P.; Willenborg, Christina; Erdmann, Jeanette; Blakenberg, Stefan; O'Donnell, Christopher J.; März, Winfried; Laaksonen, Reijo; Epstein, Stephen E.; Kathiresan, Sekar; Shah, Svati H.; Hazen, Stanley L.; Reilly, Muredach P.; Lusis, Aldons J.; Samani, Nilesh J.; Schunkert, Heribert; Quertermous, Thomas; McPherson, Ruth; Yang, Xia; Assimes, Themistocles L.

2014-01-01

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions. PMID:25033284

A method for gene-based pathway analysis using genomewide association study summary statistics reveals nine new type 1 diabetes associations.

PubMed

Evangelou, Marina; Smyth, Deborah J; Fortune, Mary D; Burren, Oliver S; Walker, Neil M; Guo, Hui; Onengut-Gumuscu, Suna; Chen, Wei-Min; Concannon, Patrick; Rich, Stephen S; Todd, John A; Wallace, Chris

2014-12-01

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85×10-11) with 12 of the 22 SNPs showing P<0.05. Support, including replication evidence, was obtained for nine T1D associated variants in genes ITGB7 (rs11170466, P=7.86×10-9), NRP1 (rs722988, 4.88×10-8), BAD (rs694739, 2.37×10-7), CTSB (rs1296023, 2.79×10-7), FYN (rs11964650, P=5.60×10-7), UBE2G1 (rs9906760, 5.08×10-7), MAP3K14 (rs17759555, 9.67×10-7), ITGB1 (rs1557150, 1.93×10-6), and IL7R (rs1445898, 2.76×10-6). The proposed methodology can be applied to other GWAS datasets for which only summary level data are available. © 2014 The Authors. ** Genetic Epidemiology published by Wiley Periodicals, Inc.

Transethnic genome-wide scan identifies novel Alzheimer's disease loci.

PubMed

Jun, Gyungah R; Chung, Jaeyoon; Mez, Jesse; Barber, Robert; Beecham, Gary W; Bennett, David A; Buxbaum, Joseph D; Byrd, Goldie S; Carrasquillo, Minerva M; Crane, Paul K; Cruchaga, Carlos; De Jager, Philip; Ertekin-Taner, Nilufer; Evans, Denis; Fallin, M Danielle; Foroud, Tatiana M; Friedland, Robert P; Goate, Alison M; Graff-Radford, Neill R; Hendrie, Hugh; Hall, Kathleen S; Hamilton-Nelson, Kara L; Inzelberg, Rivka; Kamboh, M Ilyas; Kauwe, John S K; Kukull, Walter A; Kunkle, Brian W; Kuwano, Ryozo; Larson, Eric B; Logue, Mark W; Manly, Jennifer J; Martin, Eden R; Montine, Thomas J; Mukherjee, Shubhabrata; Naj, Adam; Reiman, Eric M; Reitz, Christiane; Sherva, Richard; St George-Hyslop, Peter H; Thornton, Timothy; Younkin, Steven G; Vardarajan, Badri N; Wang, Li-San; Wendlund, Jens R; Winslow, Ashley R; Haines, Jonathan; Mayeux, Richard; Pericak-Vance, Margaret A; Schellenberg, Gerard; Lunetta, Kathryn L; Farrer, Lindsay A

2017-07-01

Genetic loci for Alzheimer's disease (AD) have been identified in whites of European ancestry, but the genetic architecture of AD among other populations is less understood. We conducted a transethnic genome-wide association study (GWAS) for late-onset AD in Stage 1 sample including whites of European Ancestry, African-Americans, Japanese, and Israeli-Arabs assembled by the Alzheimer's Disease Genetics Consortium. Suggestive results from Stage 1 from novel loci were followed up using summarized results in the International Genomics Alzheimer's Project GWAS dataset. Genome-wide significant (GWS) associations in single-nucleotide polymorphism (SNP)-based tests (P < 5 × 10 -8 ) were identified for SNPs in PFDN1/HBEGF, USP6NL/ECHDC3, and BZRAP1-AS1 and for the interaction of the (apolipoprotein E) APOE ε4 allele with NFIC SNP. We also obtained GWS evidence (P < 2.7 × 10 -6 ) for gene-based association in the total sample with a novel locus, TPBG (P = 1.8 × 10 -6 ). Our findings highlight the value of transethnic studies for identifying novel AD susceptibility loci. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

pLARmEB: integration of least angle regression with empirical Bayes for multilocus genome-wide association studies.

PubMed

Zhang, J; Feng, J-Y; Ni, Y-L; Wen, Y-J; Niu, Y; Tamba, C L; Yue, C; Song, Q; Zhang, Y-M

2017-06-01

Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to identify quantitative trait nucleotides (QTNs) associated with complex traits. However, implementation of multilocus model in GWAS is still difficult. In this study, we integrated least angle regression with empirical Bayes to perform multilocus GWAS under polygenic background control. We used an algorithm of model transformation that whitened the covariance matrix of the polygenic matrix K and environmental noise. Markers on one chromosome were included simultaneously in a multilocus model and least angle regression was used to select the most potentially associated single-nucleotide polymorphisms (SNPs), whereas the markers on the other chromosomes were used to calculate kinship matrix as polygenic background control. The selected SNPs in multilocus model were further detected for their association with the trait by empirical Bayes and likelihood ratio test. We herein refer to this method as the pLARmEB (polygenic-background-control-based least angle regression plus empirical Bayes). Results from simulation studies showed that pLARmEB was more powerful in QTN detection and more accurate in QTN effect estimation, had less false positive rate and required less computing time than Bayesian hierarchical generalized linear model, efficient mixed model association (EMMA) and least angle regression plus empirical Bayes. pLARmEB, multilocus random-SNP-effect mixed linear model and fast multilocus random-SNP-effect EMMA methods had almost equal power of QTN detection in simulation experiments. However, only pLARmEB identified 48 previously reported genes for 7 flowering time-related traits in Arabidopsis thaliana.

Validation of Genome-Wide Prostate Cancer Associations in Men of African Descent

PubMed Central

Chang, Bao-Li; Spangler, Elaine; Gallagher, Stephen; Haiman, Christopher A.; Henderson, Brian; Isaacs, William; Benford, Marnita L.; Kidd, LaCreis R.; Cooney, Kathleen; Strom, Sara; Ann Ingles, Sue; Stern, Mariana C.; Corral, Roman; Joshi, Amit D.; Xu, Jianfeng; Giri, Veda N.; Rybicki, Benjamin; Neslund-Dudas, Christine; Kibel, Adam S.; Thompson, Ian M.; Leach, Robin J.; Ostrander, Elaine A.; Stanford, Janet L.; Witte, John; Casey, Graham; Eeles, Rosalind; Hsing, Ann W.; Chanock, Stephen; Hu, Jennifer J.; John, Esther M.; Park, Jong; Stefflova, Klara; Zeigler-Johnson, Charnita; Rebbeck, Timothy R.

2010-01-01

Background Genome-wide association studies (GWAS) have identified numerous prostate cancer susceptibility alleles, but these loci have been identified primarily in men of European descent. There is limited information about the role of these loci in men of African descent. Methods We identified 7,788 prostate cancer cases and controls with genotype data for 47 GWAS-identified loci. Results We identified significant associations for SNP rs10486567 at JAZF1, rs10993994 at MSMB, rs12418451 and rs7931342 at 11q13, and rs5945572 and rs5945619 at NUDT10/11. These associations were in the same direction and of similar magnitude as those reported in men of European descent. Significance was attained at all report prostate cancer susceptibility regions at chromosome 8q24, including associations reaching genome-wide significance in region 2. Conclusion We have validated in men of African descent the associations at some, but not all, prostate cancer susceptibility loci originally identified in European descent populations. This may be due to heterogeneity in genetic etiology or in the pattern of genetic variation across populations. Impact The genetic etiology of prostate cancer in men of African descent differs from that of men of European descent. PMID:21071540

Genetic Architecture of Natural Variation in Rice Nonphotochemical Quenching Capacity Revealed by Genome-Wide Association Study

PubMed Central

Wang, Quanxiu; Zhao, Hu; Jiang, Junpeng; Xu, Jiuyue; Xie, Weibo; Fu, Xiangkui; Liu, Chang; He, Yuqing; Wang, Gongwei

2017-01-01

The photoprotective processes conferred by nonphotochemical quenching (NPQ) serve fundamental roles in maintaining plant fitness and sustainable yield. So far, few loci have been reported to be involved in natural variation of NPQ capacity in rice (Oryza sativa), and the extents of variation explored are very limited. Here we conducted a genome-wide association study (GWAS) for NPQ capacity using a diverse worldwide collection of 529 O. sativa accessions. A total of 33 significant association loci were identified. To check the validity of the GWAS signals, three F2 mapping populations with parents selected from the association panel were constructed and assayed. All QTLs detected in mapping populations could correspond to at least one GWAS signal, indicating the GWAS results were quite reliable. OsPsbS1 was repeatedly detected and explained more than 40% of the variation in the whole association population in two years, and demonstrated to be a common major QTL in all three mapping populations derived from inter-group crosses. We revealed 43 single nucleotide polymorphisms (SNPs) and 7 insertions and deletions (InDels) within a 6,997-bp DNA fragment of OsPsbS1, but found no non-synonymous SNPs or InDels in the coding region, indicating the PsbS1 protein sequence is highly conserved. Haplotypes with the 2,674-bp insertion in the promoter region exhibited significantly higher NPQ values and higher expression levels of OsPsbS1. The OsPsbS1 RNAi plants and CRISPR/Cas9 mutants exhibited drastically decreased NPQ values. OsPsbS1 had specific and high-level expression in green tissues of rice. However, we didn't find significant function for OsPsbS2, the other rice PsbS homologue. Manipulation of the significant loci or candidate genes identified may enhance photoprotection and improve photosynthesis and yield in rice. PMID:29081789

Genetic Architecture of Natural Variation in Rice Nonphotochemical Quenching Capacity Revealed by Genome-Wide Association Study.

PubMed

Wang, Quanxiu; Zhao, Hu; Jiang, Junpeng; Xu, Jiuyue; Xie, Weibo; Fu, Xiangkui; Liu, Chang; He, Yuqing; Wang, Gongwei

2017-01-01

The photoprotective processes conferred by nonphotochemical quenching (NPQ) serve fundamental roles in maintaining plant fitness and sustainable yield. So far, few loci have been reported to be involved in natural variation of NPQ capacity in rice ( Oryza sativa ), and the extents of variation explored are very limited. Here we conducted a genome-wide association study (GWAS) for NPQ capacity using a diverse worldwide collection of 529 O. sativa accessions. A total of 33 significant association loci were identified. To check the validity of the GWAS signals, three F2 mapping populations with parents selected from the association panel were constructed and assayed. All QTLs detected in mapping populations could correspond to at least one GWAS signal, indicating the GWAS results were quite reliable. OsPsbS1 was repeatedly detected and explained more than 40% of the variation in the whole association population in two years, and demonstrated to be a common major QTL in all three mapping populations derived from inter-group crosses. We revealed 43 single nucleotide polymorphisms (SNPs) and 7 insertions and deletions (InDels) within a 6,997-bp DNA fragment of OsPsbS1 , but found no non-synonymous SNPs or InDels in the coding region, indicating the PsbS1 protein sequence is highly conserved. Haplotypes with the 2,674-bp insertion in the promoter region exhibited significantly higher NPQ values and higher expression levels of OsPsbS1 . The OsPsbS1 RNAi plants and CRISPR/Cas9 mutants exhibited drastically decreased NPQ values. OsPsbS1 had specific and high-level expression in green tissues of rice. However, we didn't find significant function for OsPsbS2 , the other rice PsbS homologue. Manipulation of the significant loci or candidate genes identified may enhance photoprotection and improve photosynthesis and yield in rice.

Age-related macular degeneration: genome-wide association studies to translation.

PubMed

Black, James R M; Clark, Simon J

2016-04-01

In recent years, genome-wide association studies (GWAS), which are able to analyze the contribution to disease of genetic variations that are common within a population, have attracted considerable investment. Despite identifying genetic variants for many conditions, they have been criticized for yielding data with minimal clinical utility. However, in this regard, age-related macular degeneration (AMD), the most common form of blindness in the Western world, is a striking exception. Through GWAS, common genetic variants at a number of loci have been discovered. Two loci in particular, including genes of the complement cascade on chromosome 1 and the ARMS2/HTRA1 genes on chromosome 10, have been shown to convey significantly increased susceptibility to developing AMD. Today, although it is possible to screen individuals for a genetic predisposition to the disease, effective interventional strategies for those at risk of developing AMD are scarce. Ongoing research in this area is nonetheless promising. After providing brief overviews of AMD and common disease genetics, we outline the main recent advances in the understanding of AMD, particularly those made through GWAS. Finally, the true merit of these findings and their current and potential translational value is examined.Genet Med 18 4, 283-289.

CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.

PubMed

Yang, Cheng-Hong; Chuang, Li-Yeh; Lin, Yu-Da

2017-08-01

Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to detect the potential epistasis in large-scale SNP datasets. We propose a new algorithm which combines the differential evolution (DE) algorithm with a classification based multifactor-dimensionality reduction (CMDR), termed DECMDR. DECMDR uses the CMDR as a fitness measure to evaluate values of solutions in DE process for scanning the potential statistical epistasis in GWAS. The results indicated that DECMDR outperforms the existing algorithms in terms of detection success rate by the large simulation and real data obtained from the Wellcome Trust Case Control Consortium. For running time comparison, DECMDR can efficient to apply the CMDR to detect the significant association between cases and controls amongst all possible SNP combinations in GWAS. DECMDR is freely available at https://goo.gl/p9sLuJ . chuang@isu.edu.tw or e0955767257@yahoo.com.tw. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A genome-wide association study of breast cancer in women of African ancestry

PubMed Central

Chen, Fang; Chen, Gary K.; Stram, Daniel O.; Millikan, Robert C.; Ambrosone, Christine B.; John, Esther M.; Bernstein, Leslie; Zheng, Wei; Palmer, Julie R.; Hu, Jennifer J.; Rebbeck, Tim R.; Ziegler, Regina G.; Nyante, Sarah; Bandera, Elisa V.; Ingles, Sue A.; Press, Michael F.; Ruiz-Narvaez, Edward A.; Deming, Sandra L.; Rodriguez-Gil, Jorge L.; DeMichele, Angela; Chanock, Stephen J.; Blot, William; Signorello, Lisa; Cai, Qiuyin; Li, Guoliang; Long, Jirong; Huo, Dezheng; Zheng, Yonglan; Cox, Nancy J.; Olopade, Olufunmilayo I.; Ogundiran, Temidayo O.; Adebamowo, Clement; Nathanson, Katherine L.; Domchek, Susan M.; Simon, Michael S.; Hennis, Anselm; Nemesure, Barbara; Wu, Suh-Yuh; Leske, M. Cristina; Ambs, Stefan; Hutter, Carolyn M.; Young, Alicia; Kooperberg, Charles; Peters, Ulrike; Rhie, Suhn K.; Wan, Peggy; Sheng, Xin; Pooler, Loreall C.; Van Den Berg, David J.; Le Marchand, Loic; Kolonel, Laurence N.; Henderson, Brian E.; Haiman, Christopher A.

2013-01-01

Genome-wide association studies (GWAS) in diverse populations are needed to reveal variants that are more common and/or limited to defined populations. We conducted a GWAS of breast cancer in women of African ancestry, with genotyping of > 1,000,000 SNPs in 3,153 African American cases and 2,831 controls, and replication testing of the top 66 associations in an additional 3,607 breast cancer cases and 11,330 controls of African ancestry. Two of the 66 SNPs replicated (p < 0.05) in stage 2, which reached statistical significance levels of 10−6 and 10−5 in the stage 1 and 2 combined analysis (rs4322600 at chromosome 14q31: OR = 1.18, p = 4.3×10−6; rs10510333 at chromosome 3p26: OR = 1.15, p = 1.5×10−5). These suggestive risk loci have not been identified in previous GWAS in other populations and will need to be examined in additional samples. Identification of novel risk variants for breast cancer in women of African ancestry will demand testing of a substantially larger set of markers from stage 1 in a larger replication sample. PMID:22923054

A genetic stochastic process model for genome-wide joint analysis of biomarker dynamics and disease susceptibility with longitudinal data.

PubMed

He, Liang; Zhbannikov, Ilya; Arbeev, Konstantin G; Yashin, Anatoliy I; Kulminski, Alexander M

2017-11-01

Unraveling the underlying biological mechanisms or pathways behind the effects of genetic variations on complex diseases remains one of the major challenges in the post-GWAS (where GWAS is genome-wide association study) era. To further explore the relationship between genetic variations, biomarkers, and diseases for elucidating underlying pathological mechanism, a huge effort has been placed on examining pleiotropic and gene-environmental interaction effects. We propose a novel genetic stochastic process model (GSPM) that can be applied to GWAS and jointly investigate the genetic effects on longitudinally measured biomarkers and risks of diseases. This model is characterized by more profound biological interpretation and takes into account the dynamics of biomarkers during follow-up when investigating the hazards of a disease. We illustrate the rationale and evaluate the performance of the proposed model through two GWAS. One is to detect single nucleotide polymorphisms (SNPs) having interaction effects on type 2 diabetes (T2D) with body mass index (BMI) and the other is to detect SNPs affecting the optimal BMI level for protecting from T2D. We identified multiple SNPs that showed interaction effects with BMI on T2D, including a novel SNP rs11757677 in the CDKAL1 gene (P = 5.77 × 10 -7 ). We also found a SNP rs1551133 located on 2q14.2 that reversed the effect of BMI on T2D (P = 6.70 × 10 -7 ). In conclusion, the proposed GSPM provides a promising and useful tool in GWAS of longitudinal data for interrogating pleiotropic and interaction effects to gain more insights into the relationship between genes, quantitative biomarkers, and risks of complex diseases. © 2017 WILEY PERIODICALS, INC.

Genome-wide interaction of genotype by erythrocyte n-3 PUFAs contributes to phenotypic variance of diabetes-related traits

USDA-ARS?s Scientific Manuscript database

While genome-wide association studies (GWAS) and candidate gene approach have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. The present study aimed to examine variance contribu...

Genome-wide association studies identified novel loci for non-high-density lipoprotein cholesterol and its postprandial lipemic response

USDA-ARS?s Scientific Manuscript database

Non-high-density lipoprotein cholesterol (NHDL) is an independent and superior predictor of CVD risk as compared to low-density lipoprotein alone. It represents a spectrum of atherogenic lipid fractions with possibly a distinct genomic signature. We performed genome-wide association studies (GWAS) t...

Genome-wide associations for water-soluble carbohydrate concentration and relative maturity in wheat using SNP and DArT marker arrays

USDA-ARS?s Scientific Manuscript database

Improving water-use efficiency by incorporating drought avoidance traits into new wheat varieties is an important objective for wheat breeding in water-limited environments. This study uses genome wide association studies (GWAS) to identify candidate loci for water-soluble carbohydrate accumulation,...

Genome-wide association studies identified novel loci for non-high-density lipoprotein cholesterol and its postprandial lipemic response.

PubMed

An, Ping; Straka, Robert J; Pollin, Toni I; Feitosa, Mary F; Wojczynski, Mary K; Daw, E Warwick; O'Connell, Jeffrey R; Gibson, Quince; Ryan, Kathleen A; Hopkins, Paul N; Tsai, Michael Y; Lai, Chao-Qiang; Province, Michael A; Ordovas, Jose M; Shuldiner, Alan R; Arnett, Donna K; Borecki, Ingrid B

2014-07-01

Non-high-density lipoprotein cholesterol(NHDL) is an independent and superior predictor of CVD risk as compared to low-density lipoprotein alone. It represents a spectrum of atherogenic lipid fractions with possibly a distinct genomic signature. We performed genome-wide association studies (GWAS) to identify loci influencing baseline NHDL and its postprandial lipemic (PPL) response. We carried out GWAS in 4,241 participants of European descent. Our discovery cohort included 928 subjects from the Genetics of Lipid-Lowering Drugs and Diet Network Study. Our replication cohorts included 3,313 subjects from the Heredity and Phenotype Intervention Heart Study and Family Heart Study. A linear mixed model using the kinship matrix was used for association tests. The best association signal was found in a tri-genic region at RHOQ-PIGF-CRIPT for baseline NHDL (lead SNP rs6544903, discovery p = 7e-7, MAF = 2 %; validation p = 6e-4 at 0.1 kb upstream neighboring SNP rs3768725, and 5e-4 at 0.7 kb downstream neighboring SNP rs6733143, MAF = 10 %). The lead and neighboring SNPs were not perfect surrogate proxies to each other (D' = 1, r (2) = 0.003) but they seemed to be partially dependent (likelihood ration test p = 0.04). Other suggestive loci (discovery p < 1e-6) included LOC100419812 and LOC100288337 for baseline NHDL, and LOC100420502 and CDH13 for NHDL PPL response that were not replicated (p > 0.01). The current and first GWAS of NHDL yielded an interesting common variant in RHOQ-PIGF-CRIPT influencing baseline NHDL levels. Another common variant in CDH13 for NHDL response to dietary high-fat intake challenge was also suggested. Further validations for both loci from large independent studies, especially interventional studies, are warranted.

Correcting systematic inflation in genetic association tests that consider interaction effects: application to a genome-wide association study of posttraumatic stress disorder.

PubMed

Almli, Lynn M; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B; Bradley, Bekh; Ressler, Kerry J; Conneely, Karen N; Epstein, Michael P

2014-12-01

Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.

Meta-analysis of loci associated with age at natural menopause in African-American women.

PubMed

Chen, Christina T L; Liu, Ching-Ti; Chen, Gary K; Andrews, Jeanette S; Arnold, Alice M; Dreyfus, Jill; Franceschini, Nora; Garcia, Melissa E; Kerr, Kathleen F; Li, Guo; Lohman, Kurt K; Musani, Solomon K; Nalls, Michael A; Raffel, Leslie J; Smith, Jennifer; Ambrosone, Christine B; Bandera, Elisa V; Bernstein, Leslie; Britton, Angela; Brzyski, Robert G; Cappola, Anne; Carlson, Christopher S; Couper, David; Deming, Sandra L; Goodarzi, Mark O; Heiss, Gerardo; John, Esther M; Lu, Xiaoning; Le Marchand, Loic; Marciante, Kristin; Mcknight, Barbara; Millikan, Robert; Nock, Nora L; Olshan, Andrew F; Press, Michael F; Vaiyda, Dhananjay; Woods, Nancy F; Taylor, Herman A; Zhao, Wei; Zheng, Wei; Evans, Michele K; Harris, Tamara B; Henderson, Brian E; Kardia, Sharon L R; Kooperberg, Charles; Liu, Yongmei; Mosley, Thomas H; Psaty, Bruce; Wellons, Melissa; Windham, Beverly G; Zonderman, Alan B; Cupples, L Adrienne; Demerath, Ellen W; Haiman, Christopher; Murabito, Joanne M; Rajkovic, Aleksandar

2014-06-15

Age at menopause marks the end of a woman's reproductive life and its timing associates with risks for cancer, cardiovascular and bone disorders. GWAS and candidate gene studies conducted in women of European ancestry have identified 27 loci associated with age at menopause. The relevance of these loci to women of African ancestry has not been previously studied. We therefore sought to uncover additional menopause loci and investigate the relevance of European menopause loci by performing a GWAS meta-analysis in 6510 women with African ancestry derived from 11 studies across the USA. We did not identify any additional loci significantly associated with age at menopause in African Americans. We replicated the associations between six loci and age at menopause (P-value < 0.05): AMHR2, RHBLD2, PRIM1, HK3/UMC1, BRSK1/TMEM150B and MCM8. In addition, associations of 14 loci are directionally consistent with previous reports. We provide evidence that genetic variants influencing reproductive traits identified in European populations are also important in women of African ancestry residing in USA. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genome-wide association study identifies 74 loci associated with educational attainment.

PubMed

Okbay, Aysu; Beauchamp, Jonathan P; Fontana, Mark Alan; Lee, James J; Pers, Tune H; Rietveld, Cornelius A; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S Fleur W; Oskarsson, Sven; Pickrell, Joseph K; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H; Pina Concas, Maria; Derringer, Jaime; Furlotte, Nicholas A; Galesloot, Tessel E; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M; Harris, Sarah E; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E; Kaasik, Kadri; Kalafati, Ioanna P; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J; deLeeuw, Christiaan; Lind, Penelope A; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B; van der Most, Peter J; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E; Shi, Jianxin; Smith, Albert V; Poot, Raymond A; St Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A; Campbell, Harry; Cappuccio, Francesco P; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans, David M; Faul, Jessica D; Feitosa, Mary F; Forstner, Andreas J; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V; Harris, Tamara B; Heath, Andrew C; Hocking, Lynne J; Holliday, Elizabeth G; Homuth, Georg; Horan, Michael A; Hottenga, Jouke-Jan; de Jager, Philip L; Joshi, Peter K; Jugessur, Astanand; Kaakinen, Marika A; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A L M; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J; Lebreton, Maël P; Levinson, Douglas F; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C M; Loukola, Anu; Madden, Pamela A; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E; Marques-Vidal, Pedro; Meddens, Gerardus A; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W; Myhre, Ronny; Nelson, Christopher P; Nyholt, Dale R; Ollier, William E R; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L; Petrovic, Katja E; Porteous, David J; Räikkönen, Katri; Ring, Susan M; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J; Smith, Blair H; Smith, Jennifer A; Staessen, Jan A; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J A; Venturini, Cristina; Vinkhuyzen, Anna A E; Völker, Uwe; Völzke, Henry; Vonk, Judith M; Vozzi, Diego; Waage, Johannes; Ware, Erin B; Willemsen, Gonneke; Attia, John R; Bennett, David A; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I; Borecki, Ingrid B; Bültmann, Ute; Chabris, Christopher F; Cucca, Francesco; Cusi, Daniele; Deary, Ian J; Dedoussis, George V; van Duijn, Cornelia M; Eriksson, Johan G; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J F; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L R; Lehtimäki, Terho; Lehrer, Steven F; Magnusson, Patrik K E; Martin, Nicholas G; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W J H; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A; Samani, Nilesh J; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I A; Spector, Tim D; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A Roy; Timpson, Nicholas J; Tiemeier, Henning; Tung, Joyce Y; Uitterlinden, André G; Vitart, Veronique; Vollenweider, Peter; Weir, David R; Wilson, James F; Wright, Alan F; Conley, Dalton C; Krueger, Robert F; Davey Smith, George; Hofman, Albert; Laibson, David I; Medland, Sarah E; Meyer, Michelle N; Yang, Jian; Johannesson, Magnus; Visscher, Peter M; Esko, Tõnu; Koellinger, Philipp D; Cesarini, David; Benjamin, Daniel J

2016-05-26

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Large-Scale Cognitive GWAS Meta-Analysis Reveals Tissue-Specific Neural Expression and Potential Nootropic Drug Targets.

PubMed

Lam, Max; Trampush, Joey W; Yu, Jin; Knowles, Emma; Davies, Gail; Liewald, David C; Starr, John M; Djurovic, Srdjan; Melle, Ingrid; Sundet, Kjetil; Christoforou, Andrea; Reinvang, Ivar; DeRosse, Pamela; Lundervold, Astri J; Steen, Vidar M; Espeseth, Thomas; Räikkönen, Katri; Widen, Elisabeth; Palotie, Aarno; Eriksson, Johan G; Giegling, Ina; Konte, Bettina; Roussos, Panos; Giakoumaki, Stella; Burdick, Katherine E; Payton, Antony; Ollier, William; Chiba-Falek, Ornit; Attix, Deborah K; Need, Anna C; Cirulli, Elizabeth T; Voineskos, Aristotle N; Stefanis, Nikos C; Avramopoulos, Dimitrios; Hatzimanolis, Alex; Arking, Dan E; Smyrnis, Nikolaos; Bilder, Robert M; Freimer, Nelson A; Cannon, Tyrone D; London, Edythe; Poldrack, Russell A; Sabb, Fred W; Congdon, Eliza; Conley, Emily Drabant; Scult, Matthew A; Dickinson, Dwight; Straub, Richard E; Donohoe, Gary; Morris, Derek; Corvin, Aiden; Gill, Michael; Hariri, Ahmad R; Weinberger, Daniel R; Pendleton, Neil; Bitsios, Panos; Rujescu, Dan; Lahti, Jari; Le Hellard, Stephanie; Keller, Matthew C; Andreassen, Ole A; Deary, Ian J; Glahn, David C; Malhotra, Anil K; Lencz, Todd

2017-11-28

Here, we present a large (n = 107,207) genome-wide association study (GWAS) of general cognitive ability ("g"), further enhanced by combining results with a large-scale GWAS of educational attainment. We identified 70 independent genomic loci associated with general cognitive ability. Results showed significant enrichment for genes causing Mendelian disorders with an intellectual disability phenotype. Competitive pathway analysis implicated the biological processes of neurogenesis and synaptic regulation, as well as the gene targets of two pharmacologic agents: cinnarizine, a T-type calcium channel blocker, and LY97241, a potassium channel inhibitor. Transcriptome-wide and epigenome-wide analysis revealed that the implicated loci were enriched for genes expressed across all brain regions (most strongly in the cerebellum). Enrichment was exclusive to genes expressed in neurons but not oligodendrocytes or astrocytes. Finally, we report genetic correlations between cognitive ability and disparate phenotypes including psychiatric disorders, several autoimmune disorders, longevity, and maternal age at first birth. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits.

PubMed

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.

A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

PubMed

Bush, W S; McCauley, J L; DeJager, P L; Dudek, S M; Hafler, D A; Gibson, R A; Matthews, P M; Kappos, L; Naegelin, Y; Polman, C H; Hauser, S L; Oksenberg, J; Haines, J L; Ritchie, M D

2011-07-01

Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven interaction analysis of a GWAS of 931 multiple sclerosis (MS) trios to discover gene-gene interactions within established biological contexts. We identify heterogeneous signals, including a gene-gene interaction between CHRM3 (muscarinic cholinergic receptor 3) and MYLK (myosin light-chain kinase) (joint P=0.0002), an interaction between two phospholipase C-β isoforms, PLCβ1 and PLCβ4 (joint P=0.0098), and a modest interaction between ACTN1 (actinin alpha 1) and MYH9 (myosin heavy chain 9) (joint P=0.0326), all localized to calcium-signaled cytoskeletal regulation. Furthermore, we discover a main effect (joint P=5.2E-5) previously unidentified by single-locus analysis within another related gene, SCIN (scinderin), a calcium-binding cytoskeleton regulatory protein. This work illustrates that knowledge-driven interaction analysis of GWAS data is a feasible approach to identify new genetic effects. The results of this study are among the first gene-gene interactions and non-immune susceptibility loci for MS. Further, the implicated genes cluster within inter-related biological mechanisms that suggest a neurodegenerative component to MS.

Genomic prediction using preselected DNA variants from a GWAS with whole-genome sequence data in Holstein-Friesian cattle.

PubMed

Veerkamp, Roel F; Bouwman, Aniek C; Schrooten, Chris; Calus, Mario P L

2016-12-01

Whole-genome sequence data is expected to capture genetic variation more completely than common genotyping panels. Our objective was to compare the proportion of variance explained and the accuracy of genomic prediction by using imputed sequence data or preselected SNPs from a genome-wide association study (GWAS) with imputed whole-genome sequence data. Phenotypes were available for 5503 Holstein-Friesian bulls. Genotypes were imputed up to whole-genome sequence (13,789,029 segregating DNA variants) by using run 4 of the 1000 bull genomes project. The program GCTA was used to perform GWAS for protein yield (PY), somatic cell score (SCS) and interval from first to last insemination (IFL). From the GWAS, subsets of variants were selected and genomic relationship matrices (GRM) were used to estimate the variance explained in 2087 validation animals and to evaluate the genomic prediction ability. Finally, two GRM were fitted together in several models to evaluate the effect of selected variants that were in competition with all the other variants. The GRM based on full sequence data explained only marginally more genetic variation than that based on common SNP panels: for PY, SCS and IFL, genomic heritability improved from 0.81 to 0.83, 0.83 to 0.87 and 0.69 to 0.72, respectively. Sequence data also helped to identify more variants linked to quantitative trait loci and resulted in clearer GWAS peaks across the genome. The proportion of total variance explained by the selected variants combined in a GRM was considerably smaller than that explained by all variants (less than 0.31 for all traits). When selected variants were used, accuracy of genomic predictions decreased and bias increased. Although 35 to 42 variants were detected that together explained 13 to 19% of the total variance (18 to 23% of the genetic variance) when fitted alone, there was no advantage in using dense sequence information for genomic prediction in the Holstein data used in our study. Detection and selection of variants within a single breed are difficult due to long-range linkage disequilibrium. Stringent selection of variants resulted in more biased genomic predictions, although this might be due to the training population being the same dataset from which the selected variants were identified.

Genome-Wide association study identifies candidate genes for Parkinson's disease in an Ashkenazi Jewish population

PubMed Central

2011-01-01

Background To date, nine Parkinson disease (PD) genome-wide association studies in North American, European and Asian populations have been published. The majority of studies have confirmed the association of the previously identified genetic risk factors, SNCA and MAPT, and two studies have identified three new PD susceptibility loci/genes (PARK16, BST1 and HLA-DRB5). In a recent meta-analysis of datasets from five of the published PD GWAS an additional 6 novel candidate genes (SYT11, ACMSD, STK39, MCCC1/LAMP3, GAK and CCDC62/HIP1R) were identified. Collectively the associations identified in these GWAS account for only a small proportion of the estimated total heritability of PD suggesting that an 'unknown' component of the genetic architecture of PD remains to be identified. Methods We applied a GWAS approach to a relatively homogeneous Ashkenazi Jewish (AJ) population from New York to search for both 'rare' and 'common' genetic variants that confer risk of PD by examining any SNPs with allele frequencies exceeding 2%. We have focused on a genetic isolate, the AJ population, as a discovery dataset since this cohort has a higher sharing of genetic background and historically experienced a significant bottleneck. We also conducted a replication study using two publicly available datasets from dbGaP. The joint analysis dataset had a combined sample size of 2,050 cases and 1,836 controls. Results We identified the top 57 SNPs showing the strongest evidence of association in the AJ dataset (p < 9.9 × 10-5). Six SNPs located within gene regions had positive signals in at least one other independent dbGaP dataset: LOC100505836 (Chr3p24), LOC153328/SLC25A48 (Chr5q31.1), UNC13B (9p13.3), SLCO3A1(15q26.1), WNT3(17q21.3) and NSF (17q21.3). We also replicated published associations for the gene regions SNCA (Chr4q21; rs3775442, p = 0.037), PARK16 (Chr1q32.1; rs823114 (NUCKS1), p = 6.12 × 10-4), BST1 (Chr4p15; rs12502586, p = 0.027), STK39 (Chr2q24.3; rs3754775, p = 0.005), and LAMP3 (Chr3; rs12493050, p = 0.005) in addition to the two most common PD susceptibility genes in the AJ population LRRK2 (Chr12q12; rs34637584, p = 1.56 × 10-4) and GBA (Chr1q21; rs2990245, p = 0.015). Conclusions We have demonstrated the utility of the AJ dataset in PD candidate gene and SNP discovery both by replication in dbGaP datasets with a larger sample size and by replicating association of previously identified PD susceptibility genes. Our GWAS study has identified candidate gene regions for PD that are implicated in neuronal signalling and the dopamine pathway. PMID:21812969

A Genome Wide Association Study Identifies Common Variants Associated with Lipid Levels in the Chinese Population

PubMed Central

Wu, Chen; Yang, Handong; Yu, Dianke; Yang, Xiaobo; Zhang, Xiaomin; Wang, Yiqin; Sun, Jielin; Gao, Yong; Tan, Aihua; He, Yunfeng; Zhang, Haiying; Qin, Xue; Zhu, Jingwen; Li, Huaixing; Lin, Xu; Zhu, Jiang; Min, Xinwen; Lang, Mingjian; Li, Dongfeng; Zhai, Kan; Chang, Jiang; Tan, Wen; Yuan, Jing; Chen, Weihong; Wang, Youjie; Wei, Sheng; Miao, Xiaoping; Wang, Feng; Fang, Weimin; Liang, Yuan; Deng, Qifei; Dai, Xiayun; Lin, Dafeng; Huang, Suli; Guo, Huan; Lilly Zheng, S.; Xu, Jianfeng; Lin, Dongxin; Hu, Frank B.; Wu, Tangchun

2013-01-01

Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52×10-16, 1.38×10-6 and 5.59×10-9, respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population. PMID:24386095

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.

PubMed

Kirsten, Holger; Al-Hasani, Hoor; Holdt, Lesca; Gross, Arnd; Beutner, Frank; Krohn, Knut; Horn, Katrin; Ahnert, Peter; Burkhardt, Ralph; Reiche, Kristin; Hackermüller, Jörg; Löffler, Markus; Teupser, Daniel; Thiery, Joachim; Scholz, Markus

2015-08-15

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes. © The Author 2015. Published by Oxford University Press.

Human brain arousal in the resting state: a genome-wide association study.

PubMed

Jawinski, Philippe; Kirsten, Holger; Sander, Christian; Spada, Janek; Ulke, Christine; Huang, Jue; Burkhardt, Ralph; Scholz, Markus; Hensch, Tilman; Hegerl, Ulrich

2018-04-27

Arousal affects cognition, emotion, and behavior and has been implicated in the etiology of psychiatric disorders. Although environmental conditions substantially contribute to the level of arousal, stable interindividual characteristics are well-established and a genetic basis has been suggested. Here we investigated the molecular genetics of brain arousal in the resting state by conducting a genome-wide association study (GWAS). We selected N = 1877 participants from the population-based LIFE-Adult cohort. Participants underwent a 20-min eyes-closed resting state EEG, which was analyzed using the computerized VIGALL 2.1 (Vigilance Algorithm Leipzig). At the SNP-level, GWAS analyses revealed no genome-wide significant locus (p < 5E-8), although seven loci were suggestive (p < 1E-6). The strongest hit was an expression quantitative trait locus (eQTL) of TMEM159 (lead-SNP: rs79472635, p = 5.49E-8). Importantly, at the gene-level, GWAS analyses revealed significant evidence for TMEM159 (p = 0.013, Bonferroni-corrected). By mapping our SNPs to the GWAS results from the Psychiatric Genomics Consortium, we found that all corresponding markers of TMEM159 showed nominally significant associations with Major Depressive Disorder (MDD; 0.006 ≤ p ≤ 0.011). More specifically, variants associated with high arousal levels have previously been linked to an increased risk for MDD. In line with this, the MetaXcan database suggests increased expression levels of TMEM159 in MDD, as well as Autism Spectrum Disorder, and Alzheimer's Disease. Furthermore, our pathway analyses provided evidence for a role of sodium/calcium exchangers in resting state arousal. In conclusion, the present GWAS identifies TMEM159 as a novel candidate gene which may modulate the risk for psychiatric disorders through arousal mechanisms. Our results also encourage the elaboration of the previously reported interrelations between ion-channel modulators, sleep-wake behavior, and psychiatric disorders.

Genetic Association and Gene-Gene Interaction Analyses in African American Dialysis Patients With Nondiabetic Nephropathy

PubMed Central

Bostrom, Meredith A.; Kao, W.H. Linda; Li, Man; Abboud, Hanna E.; Adler, Sharon G.; Iyengar, Sudha K.; Kimmel, Paul L.; Hanson, Robert L.; Nicholas, Susanne B.; Rasooly, Rebekah S.; Sedor, John R.; Coresh, Josef; Kohn, Orly F.; Leehey, David J.; Thornley-Brown, Denyse; Bottinger, Erwin P.; Lipkowitz, Michael S.; Meoni, Lucy A.; Klag, Michael J.; Lu, Lingyi; Hicks, Pamela J.; Langefeld, Carl D.; Parekh, Rulan S.; Bowden, Donald W.; Freedman, Barry I.

2011-01-01

Background African Americans (AAs) have increased susceptibility to non-diabetic nephropathy relative to European Americans. Study Design Follow-up of a pooled genome-wide association study (GWAS) in AA dialysis patients with nondiabetic nephropathy; novel gene-gene interaction analyses. Setting & Participants Wake Forest sample: 962 AA nondiabetic nephropathy cases; 931 non-nephropathy controls. Replication sample: 668 Family Investigation of Nephropathy and Diabetes (FIND) AA nondiabetic nephropathy cases; 804 non-nephropathy controls. Predictors Individual genotyping of top 1420 pooled GWAS-associated single nucleotide polymorphisms (SNPs) and 54 SNPs in six nephropathy susceptibility genes. Outcomes APOL1 genetic association and additional candidate susceptibility loci interacting with, or independently from, APOL1. Results The strongest GWAS associations included two non-coding APOL1 SNPs, rs2239785 (odds ratio [OR], 0.33; dominant; p = 5.9 × 10−24) and rs136148 (OR, 0.54; additive; p = 1.1 × 10−7) with replication in FIND (p = 5.0 × 10−21 and 1.9 × 10−05, respectively). Rs2239785 remained significantly associated after controlling for the APOL1 G1 and G2 coding variants. Additional top hits included a CFH SNP(OR from meta-analysis in above 3367 AA cases and controls, 0.81; additive; p = 6.8 × 10−4). The 1420 SNPs were tested for interaction with APOL1 G1 and G2 variants. Several interactive SNPs were detected, the most significant was rs16854341 in the podocin gene (NPHS2) (p = 0.0001). Limitations Non-pooled GWAS have not been performed in AA nondiabetic nephropathy. Conclusions This follow-up of a pooled GWAS provides additional and independent evidence that APOL1 variants contribute to nondiabetic nephropathy in AAs and identified additional associated and interactive non-diabetic nephropathy susceptibility genes. PMID:22119407

Informed genome-wide association analysis with family history as a secondary phenotype identifies novel loci of lung cancer.

PubMed

Poirier, Julia G; Brennan, Paul; McKay, James D; Spitz, Margaret R; Bickeböller, Heike; Risch, Angela; Liu, Geoffrey; Le Marchand, Loic; Tworoger, Shelley; McLaughlin, John; Rosenberger, Albert; Heinrich, Joachim; Brüske, Irene; Muley, Thomas; Henderson, Brian E; Wilkens, Lynne R; Zong, Xuchen; Li, Yafang; Hao, Ke; Timens, Wim; Bossé, Yohan; Sin, Don D; Obeidat, Ma'en; Amos, Christopher I; Hung, Rayjean J

2015-03-01

Lung cancer is the leading cause of cancer death worldwide. Although several genetic variants associated with lung cancer have been identified in the past, stringent selection criteria of genome-wide association studies (GWAS) can lead to missed variants. The objective of this study was to uncover missed variants by using the known association between lung cancer and first-degree family history of lung cancer to enrich the variant prioritization for lung cancer susceptibility regions. In this two-stage GWAS study, we first selected a list of variants associated with both lung cancer and family history of lung cancer in four GWAS (3,953 cases, 4,730 controls), then replicated our findings for 30 variants in a meta-analysis of four additional studies (7,510 cases, 7,476 controls). The top ranked genetic variant rs12415204 in chr10q23.33 encoding FFAR4 in the Discovery set was validated in the Replication set with an overall OR of 1.09 (95% CI=1.04, 1.14, P=1.63×10(-4)). When combining the two stages of the study, the strongest association was found in rs1158970 at Ch4p15.2 encoding KCNIP4 with an OR of 0.89 (95% CI=0.85, 0.94, P=9.64×10(-6)). We performed a stratified analysis of rs12415204 and rs1158970 across all eight studies by age, gender, smoking status, and histology, and found consistent results across strata. Four of the 30 replicated variants act as expression quantitative trait loci (eQTL) sites in 1,111 nontumor lung tissues and meet the genome-wide 10% FDR threshold. © 2015 Wiley Periodicals, Inc.

Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia

PubMed Central

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

Identification of lung cancer histology-specific variants applying Bayesian framework variant prioritization approaches within the TRICL and ILCCO consortia.

PubMed

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.

Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

PubMed

Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

2017-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease.

INTEGRATIVE ANALYSIS OF GENETIC, GENOMIC AND PHENOTYPIC DATA FOR ETHANOL BEHAVIORS: A NETWORK-BASED PIPELINE FOR IDENTIFYING MECHANISMS AND POTENTIAL DRUG TARGETS

PubMed Central

Bogenpohl, James W.; Mignogna, Kristin M.; Smith, Maren L.; Miles, Michael F.

2016-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce non-biased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x environmental interactions affecting brain functioning in health and disease. PMID:27933543

Performance Comparison of Two Gene Set Analysis Methods for Genome-wide Association Study Results: GSA-SNP vs i-GSEA4GWAS.

PubMed

Kwon, Ji-Sun; Kim, Jihye; Nam, Dougu; Kim, Sangsoo

2012-06-01

Gene set analysis (GSA) is useful in interpreting a genome-wide association study (GWAS) result in terms of biological mechanism. We compared the performance of two different GSA implementations that accept GWAS p-values of single nucleotide polymorphisms (SNPs) or gene-by-gene summaries thereof, GSA-SNP and i-GSEA4GWAS, under the same settings of inputs and parameters. GSA runs were made with two sets of p-values from a Korean type 2 diabetes mellitus GWAS study: 259,188 and 1,152,947 SNPs of the original and imputed genotype datasets, respectively. When Gene Ontology terms were used as gene sets, i-GSEA4GWAS produced 283 and 1,070 hits for the unimputed and imputed datasets, respectively. On the other hand, GSA-SNP reported 94 and 38 hits, respectively, for both datasets. Similar, but to a lesser degree, trends were observed with Kyoto Encyclopedia of Genes and Genomes (KEGG) gene sets as well. The huge number of hits by i-GSEA4GWAS for the imputed dataset was probably an artifact due to the scaling step in the algorithm. The decrease in hits by GSA-SNP for the imputed dataset may be due to the fact that it relies on Z-statistics, which is sensitive to variations in the background level of associations. Judicious evaluation of the GSA outcomes, perhaps based on multiple programs, is recommended.

Gene-diet interaction effects on BMI levels in the Singapore Chinese population.

PubMed

Chang, Xuling; Dorajoo, Rajkumar; Sun, Ye; Han, Yi; Wang, Ling; Khor, Chiea-Chuen; Sim, Xueling; Tai, E-Shyong; Liu, Jianjun; Yuan, Jian-Min; Koh, Woon-Puay; van Dam, Rob M; Friedlander, Yechiel; Heng, Chew-Kiat

2018-02-24

Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies. Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10 - 15 ) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP interaction  = 0.043). The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels.

Validation of prostate cancer risk-related loci identified from genome-wide association studies using family-based association analysis: evidence from the International Consortium for Prostate Cancer Genetics (ICPCG).

PubMed

Jin, Guangfu; Lu, Lingyi; Cooney, Kathleen A; Ray, Anna M; Zuhlke, Kimberly A; Lange, Ethan M; Cannon-Albright, Lisa A; Camp, Nicola J; Teerlink, Craig C; Fitzgerald, Liesel M; Stanford, Janet L; Wiley, Kathleen E; Isaacs, Sarah D; Walsh, Patrick C; Foulkes, William D; Giles, Graham G; Hopper, John L; Severi, Gianluca; Eeles, Ros; Easton, Doug; Kote-Jarai, Zsofia; Guy, Michelle; Rinckleb, Antje; Maier, Christiane; Vogel, Walther; Cancel-Tassin, Geraldine; Egrot, Christophe; Cussenot, Olivier; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Wiklund, Fredrik; Grönberg, Henrik; Emanuelsson, Monica; Whittemore, Alice S; Oakley-Girvan, Ingrid; Hsieh, Chih-Lin; Wahlfors, Tiina; Tammela, Teuvo; Schleutker, Johanna; Catalona, William J; Zheng, S Lilly; Ostrander, Elaine A; Isaacs, William B; Xu, Jianfeng

2012-07-01

Multiple prostate cancer (PCa) risk-related loci have been discovered by genome-wide association studies (GWAS) based on case-control designs. However, GWAS findings may be confounded by population stratification if cases and controls are inadvertently drawn from different genetic backgrounds. In addition, since these loci were identified in cases with predominantly sporadic disease, little is known about their relationships with hereditary prostate cancer (HPC). The association between seventeen reported PCa susceptibility loci was evaluated with a family-based association test using 1,979 hereditary PCa families of European descent collected by members of the International Consortium for Prostate Cancer Genetics, with a total of 5,730 affected men. The risk alleles for 8 of the 17 loci were significantly over-transmitted from parents to affected offspring, including SNPs residing in 8q24 (regions 1, 2 and 3), 10q11, 11q13, 17q12 (region 1), 17q24 and Xp11. In subgroup analyses, three loci, at 8q24 (regions 1 and 2) plus 17q12, were significantly over-transmitted in hereditary PCa families with five or more affected members, while loci at 3p12, 8q24 (region 2), 11q13, 17q12 (region 1), 17q24 and Xp11 were significantly over-transmitted in HPC families with an average age of diagnosis at 65 years or less. Our results indicate that at least a subset of PCa risk-related loci identified by case-control GWAS are also associated with disease risk in HPC families.

Validation of prostate cancer risk-related loci identified from genome-wide association studies using family-based association analysis: evidence from the International Consortium for Prostate Cancer Genetics (ICPCG)

PubMed Central

Jin, Guangfu; Lu, Lingyi; Cooney, Kathleen A.; Ray, Anna M.; Zuhlke, Kimberly A.; Lange, Ethan M.; Cannon-Albright, Lisa A.; Camp, Nicola J.; Teerlink, Craig C.; FitzGerald, Liesel M.; Stanford, Janet L.; Wiley, Kathleen E.; Walsh, Patrick C.; Foulkes, William D.; Giles, Graham G.; Hopper, John L.; Severi, Gianluca; Eeles, Ros; Easton, Doug; Kote-Jarai, Zsofia; Guy, Michelle; Rinckleb, Antje; Maier, Christiane; Vogel, Walther; Cancel-Tassin, Geraldine; Egrot, Christophe; Cussenot, Olivier; Thibodeau, Stephen N.; McDonnell, Shannon K.; Schaid, Daniel J.; Wiklund, Fredrik; Grönberg, Henrik; Emanuelsson, Monica; Whittemore, Alice S.; Oakley-Girvan, Ingrid; Hsieh, Chih-Lin; Wahlfors, Tiina; Tammela, Teuvo; Schleutker, Johanna; Catalona, William J.; Zheng, S. Lilly; Isaacs, William B.

2012-01-01

Multiple prostate cancer (PCa) risk-related loci have been discovered by genome-wide association studies (GWAS) based on case–control designs. However, GWAS findings may be confounded by population stratification if cases and controls are inadvertently drawn from different genetic backgrounds. In addition, since these loci were identified in cases with predominantly sporadic disease, little is known about their relationships with hereditary prostate cancer (HPC). The association between seventeen reported PCa susceptibility loci was evaluated with a family-based association test using 1,979 hereditary PCa families of European descent collected by members of the International Consortium for Prostate Cancer Genetics, with a total of 5,730 affected men. The risk alleles for 8 of the 17 loci were significantly over-transmitted from parents to affected offspring, including SNPs residing in 8q24 (regions 1, 2 and 3), 10q11, 11q13, 17q12 (region 1), 17q24 and Xp11. In subgroup analyses, three loci, at 8q24 (regions 1 and 2) plus 17q12, were significantly over-transmitted in hereditary PCa families with five or more affected members, while loci at 3p12, 8q24 (region 2), 11q13, 17q12 (region 1), 17q24 and Xp11 were significantly over-transmitted in HPC families with an average age of diagnosis at 65 years or less. Our results indicate that at least a subset of PCa risk-related loci identified by case–control GWAS are also associated with disease risk in HPC families. PMID:22198737

Genome-wide association study reveals sex-specific selection signals against autosomal nucleotide variants.

PubMed

Ryu, Dongchan; Ryu, Jihye; Lee, Chaeyoung

2016-05-01

A genome-wide association study (GWAS) was conducted to examine genetic associations of common autosomal nucleotide variants with sex in a Korean population with 4183 males and 4659 females. Nine genetic association signals were identified in four intragenic and five intergenic regions (P<5 × 10(-8)). Further analysis with an independent data set confirmed two intragenic association signals in the genes encoding protein phosphatase 1, regulatory subunit 12B (PPP1R12B, intron 12, rs1819043) and dynein, axonemal, heavy chain 11 (DNAH11, intron 61, rs10255013), which are directly involved in the reproductive system. This study revealed autosomal genetic variants associated with sex ratio by GWAS for the first time. This implies that genetic variants in proximity to the association signals may influence sex-specific selection and contribute to sex ratio variation. Further studies are required to reveal the mechanisms underlying sex-specific selection.

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma.

PubMed

Law, Matthew H; Bishop, D Timothy; Lee, Jeffrey E; Brossard, Myriam; Martin, Nicholas G; Moses, Eric K; Song, Fengju; Barrett, Jennifer H; Kumar, Rajiv; Easton, Douglas F; Pharoah, Paul D P; Swerdlow, Anthony J; Kypreou, Katerina P; Taylor, John C; Harland, Mark; Randerson-Moor, Juliette; Akslen, Lars A; Andresen, Per A; Avril, Marie-Françoise; Azizi, Esther; Scarrà, Giovanna Bianchi; Brown, Kevin M; Dębniak, Tadeusz; Duffy, David L; Elder, David E; Fang, Shenying; Friedman, Eitan; Galan, Pilar; Ghiorzo, Paola; Gillanders, Elizabeth M; Goldstein, Alisa M; Gruis, Nelleke A; Hansson, Johan; Helsing, Per; Hočevar, Marko; Höiom, Veronica; Ingvar, Christian; Kanetsky, Peter A; Chen, Wei V; Landi, Maria Teresa; Lang, Julie; Lathrop, G Mark; Lubiński, Jan; Mackie, Rona M; Mann, Graham J; Molven, Anders; Montgomery, Grant W; Novaković, Srdjan; Olsson, Håkan; Puig, Susana; Puig-Butille, Joan Anton; Qureshi, Abrar A; Radford-Smith, Graham L; van der Stoep, Nienke; van Doorn, Remco; Whiteman, David C; Craig, Jamie E; Schadendorf, Dirk; Simms, Lisa A; Burdon, Kathryn P; Nyholt, Dale R; Pooley, Karen A; Orr, Nick; Stratigos, Alexander J; Cust, Anne E; Ward, Sarah V; Hayward, Nicholas K; Han, Jiali; Schulze, Hans-Joachim; Dunning, Alison M; Bishop, Julia A Newton; Demenais, Florence; Amos, Christopher I; MacGregor, Stuart; Iles, Mark M

2015-09-01

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5 × 10(-8)), as did 2 previously reported but unreplicated loci and all 13 established loci. Newly associated SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes in the associated regions, including one involved in telomere biology.

Genome-wide meta-analysis identifies five new susceptibility loci for cutaneous malignant melanoma

PubMed Central

Law, Matthew H.; Bishop, D. Timothy; Martin, Nicholas G.; Moses, Eric K.; Song, Fengju; Barrett, Jennifer H.; Kumar, Rajiv; Easton, Douglas F.; Pharoah, Paul D. P.; Swerdlow, Anthony J.; Kypreou, Katerina P.; Taylor, John C.; Harland, Mark; Randerson-Moor, Juliette; Akslen, Lars A.; Andresen, Per A.; Avril, Marie-Françoise; Azizi, Esther; Scarrà, Giovanna Bianchi; Brown, Kevin M.; Dębniak, Tadeusz; Duffy, David L.; Elder, David E.; Fang, Shenying; Friedman, Eitan; Galan, Pilar; Ghiorzo, Paola; Gillanders, Elizabeth M.; Goldstein, Alisa M.; Gruis, Nelleke A.; Hansson, Johan; Helsing, Per; Hočevar, Marko; Höiom, Veronica; Ingvar, Christian; Kanetsky, Peter A.; Chen, Wei V.; Landi, Maria Teresa; Lang, Julie; Lathrop, G. Mark; Lubiński, Jan; Mackie, Rona M.; Mann, Graham J.; Molven, Anders; Montgomery, Grant W.; Novaković, Srdjan; Olsson, Håkan; Puig, Susana; Puig-Butille, Joan Anton; Qureshi, Abrar A.; Radford-Smith, Graham L.; van der Stoep, Nienke; van Doorn, Remco; Whiteman, David C.; Craig, Jamie E.; Schadendorf, Dirk; Simms, Lisa A.; Burdon, Kathryn P.; Nyholt, Dale R.; Pooley, Karen A.; Orr, Nick; Stratigos, Alexander J.; Cust, Anne E.; Ward, Sarah V.; Hayward, Nicholas K.; Han, Jiali; Schulze, Hans-Joachim; Dunning, Alison M.; Bishop, Julia A. Newton; MacGregor, Stuart; Iles, Mark M.

2015-01-01

Thirteen common susceptibility loci have been reproducibly associated with cutaneous malignant melanoma (CMM). We report the results of an international 2-stage meta-analysis of CMM genome-wide association studies (GWAS). This meta-analysis combines 11 GWAS (5 previously unpublished) and a further three stage 2 data sets, totaling 15,990 CMM cases and 26,409 controls. Five loci not previously associated with CMM risk reached genome-wide significance (P < 5×10–8), as did two previously-reported but un-replicated loci and all thirteen established loci. Novel SNPs fall within putative melanocyte regulatory elements, and bioinformatic and expression quantitative trait locus (eQTL) data highlight candidate genes including one involved in telomere biology. PMID:26237428

Integrated pathway analysis of nasopharyngeal carcinoma implicates the axonemal dynein complex in the Malaysian cohort.

PubMed

Chin, Yoon-Ming; Tan, Lu Ping; Abdul Aziz, Norazlin; Mushiroda, Taisei; Kubo, Michiaki; Mohd Kornain, Noor Kaslina; Tan, Geok Wee; Khoo, Alan Soo-Beng; Krishnan, Gopala; Pua, Kin-Choo; Yap, Yoke-Yeow; Teo, Soo-Hwang; Lim, Paul Vey-Hong; Nakamura, Yusuke; Lum, Chee Lun; Ng, Ching-Ching

2016-10-15

Nasopharyngeal carcinoma (NPC) is an epithelial squamous cell carcinoma on the mucosal lining of the nasopharynx. The etiology of NPC remains elusive despite many reported studies. Most studies employ a single platform approach, neglecting the cumulative influence of both the genome and transcriptome toward NPC development. We aim to employ an integrated pathway approach to identify dysregulated pathways linked to NPC. Our approach combines imputation NPC GWAS data from a Malaysian cohort as well as published expression data GSE12452 from both NPC and non-NPC nasopharynx tissues. Pathway association for GWAS data was performed using MAGENTA while for expression data, GSA-SNP was used with gene p values derived from differential expression values from GEO2R. Our study identified NPC association in the gene ontology (GO) axonemal dynein complex pathway (pGWAS-GSEA  = 1.98 × 10(-2) ; pExpr-GSEA  = 1.27 × 10(-24) ; pBonf-Combined  = 4.15 × 10(-21) ). This association was replicated in a separate cohort using gene expression data from NPC and non-NPC nasopharynx tissues (pAmpliSeq-GSEA  = 6.56 × 10(-4) ). Loss of function in the axonemal dynein complex causes impaired cilia function, leading to poor mucociliary clearance and subsequently upper or lower respiratory tract infection, the former of which includes the nasopharynx. Our approach illustrates the potential use of integrated pathway analysis in detecting gene sets involved in the development of NPC in the Malaysian cohort. © 2016 UICC.

Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci

PubMed Central

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

Pool-based genome-wide association study identified novel candidate regions on BTA9 and 14 for oleic acid percentage in Japanese Black cattle.

PubMed

Kawaguchi, Fuki; Kigoshi, Hiroto; Nakajima, Ayaka; Matsumoto, Yuta; Uemoto, Yoshinobu; Fukushima, Moriyuki; Yoshida, Emi; Iwamoto, Eiji; Akiyama, Takayuki; Kohama, Namiko; Kobayashi, Eiji; Honda, Takeshi; Oyama, Kenji; Mannen, Hideyuki; Sasazaki, Shinji

2018-05-17

Fatty acid composition is an important indicator of beef quality. The objective of this study was to search the potential candidate region for fatty acid composition. We performed pool-based genome-wide association studies (GWAS) for oleic acid percentage (C18:1) in a Japanese Black cattle population from the Hyogo prefecture. GWAS analysis revealed two novel candidate regions on BTA9 and BTA14. The most significant single nucleotide polymorphisms (SNPs) in each region were genotyped in a population (n = 899) to verify their effect on C18:1. Statistical analysis revealed that both SNPs were significantly associated with C18:1 (p = .0080 and .0003), validating the quantitative trait loci (QTLs) detected in GWAS. We subsequently selected VNN1 and LYPLA1 genes as candidate genes from each region on BTA9 and BTA14, respectively. We sequenced full-length coding sequence (CDS) of these genes in eight individuals and identified a nonsynonymous SNP T66M on VNN1 gene as a putative candidate polymorphism. The polymorphism was also significantly associated with C18:1, but the p value (p = .0162) was higher than the most significant SNP on BTA9, suggesting that it would not be responsible for the QTL. Although further investigation will be needed to determine the responsible gene and polymorphism, our findings would contribute to development of selective markers for fatty acid composition in the Japanese Black cattle of Hyogo. © 2018 Japanese Society of Animal Science.

Genome-Wide Association Study Provides Insight into the Genetic Control of Plant Height in Rapeseed (Brassica napus L.).

PubMed

Sun, Chengming; Wang, Benqi; Yan, Lei; Hu, Kaining; Liu, Sheng; Zhou, Yongming; Guan, Chunyun; Zhang, Zhenqian; Li, Jiana; Zhang, Jiefu; Chen, Song; Wen, Jing; Ma, Chaozhi; Tu, Jinxing; Shen, Jinxiong; Fu, Tingdong; Yi, Bin

2016-01-01

Plant height is a key morphological trait of rapeseed. In this study, we measured plant height of a rapeseed population across six environments. This population contains 476 inbred lines representing the major Chinese rapeseed genepool and 44 lines from other countries. The 60K Brassica Infinium® SNP array was utilized to genotype the association panel. A genome-wide association study (GWAS) was performed via three methods, including a robust, novel, nonparametric Anderson-Darling (A-D) test. Consequently, 68 loci were identified as significantly associated with plant height (P < 5.22 × 10(-5)), and more than 70% of the loci (48) overlapped the confidence intervals of reported QTLs from nine mapping populations. Moreover, 24 GWAS loci were detected with selective sweep signals, which reflected the signatures of historical semi-dwarf breeding. In the linkage disequilibrium (LD) decay range up-and downstream of 65 loci (r (2) > 0.1), we found plausible candidates orthologous to the documented Arabidopsis genes involved in height regulation. One significant association found by GWAS colocalized with the established height locus BnRGA in rapeseed. Our results provide insights into the genetic basis of plant height in rapeseed and may facilitate marker-based breeding.

Interactome-transcriptome analysis discovers signatures complementary to GWAS Loci of Type 2 Diabetes

PubMed Central

Li, Jing-Woei; Lee, Heung-Man; Wang, Ying; Tong, Amy Hin-Yan; Yip, Kevin Y.; Tsui, Stephen Kwok-Wing; Lok, Si; Ozaki, Risa; Luk, Andrea O; Kong, Alice P. S.; So, Wing-Yee; Ma, Ronald C. W.; Chan, Juliana C. N.; Chan, Ting-Fung

2016-01-01

Protein interactions play significant roles in complex diseases. We analyzed peripheral blood mononuclear cells (PBMC) transcriptome using a multi-method strategy. We constructed a tissue-specific interactome (T2Di) and identified 420 molecular signatures associated with T2D-related comorbidity and symptoms, mainly implicated in inflammation, adipogenesis, protein phosphorylation and hormonal secretion. Apart from explaining the residual associations within the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study, the T2Di signatures were enriched in pathogenic cell type-specific regulatory elements related to fetal development, immunity and expression quantitative trait loci (eQTL). The T2Di revealed a novel locus near a well-established GWAS loci AChE, in which SRRT interacts with JAZF1, a T2D-GWAS gene implicated in pancreatic function. The T2Di also included known anti-diabetic drug targets (e.g. PPARD, MAOB) and identified possible druggable targets (e.g. NCOR2, PDGFR). These T2Di signatures were validated by an independent computational method, and by expression data of pancreatic islet, muscle and liver with some of the signatures (CEBPB, SREBF1, MLST8, SRF, SRRT and SLC12A9) confirmed in PBMC from an independent cohort of 66 T2D and 66 control subjects. By combining prior knowledge and transcriptome analysis, we have constructed an interactome to explain the multi-layered regulatory pathways in T2D. PMID:27752041

Genetic architecture of epigenetic and neuronal ageing rates in human brain regions

PubMed Central

Lu, Ake T.; Hannon, Eilis; Levine, Morgan E.; Crimmins, Eileen M.; Lunnon, Katie; Mill, Jonathan; Geschwind, Daniel H.; Horvath, Steve

2017-01-01

Identifying genes regulating the pace of epigenetic ageing represents a new frontier in genome-wide association studies (GWASs). Here using 1,796 brain samples from 1,163 individuals, we carry out a GWAS of two DNA methylation-based biomarkers of brain age: the epigenetic ageing rate and estimated proportion of neurons. Locus 17q11.2 is significantly associated (P=4.5 × 10−9) with the ageing rate across five brain regions and harbours a cis-expression quantitative trait locus for EFCAB5 (P=3.4 × 10−20). Locus 1p36.12 is significantly associated (P=2.2 × 10−8) with epigenetic ageing of the prefrontal cortex, independent of the proportion of neurons. Our GWAS of the proportion of neurons identified two genome-wide significant loci (10q26 and 12p13.31) and resulted in a gene set that overlaps significantly with sets found by GWAS of age-related macular degeneration (P=1.4 × 10−12), ulcerative colitis (P<1.0 × 10−20), type 2 diabetes (P=2.8 × 10−13), hip/waist circumference in men (P=1.1 × 10−9), schizophrenia (P=1.6 × 10−9), cognitive decline (P=5.3 × 10−4) and Parkinson's disease (P=8.6 × 10−3). PMID:28516910

Correcting Systematic Inflation in Genetic Association Tests That Consider Interaction Effects

PubMed Central

Almli, Lynn M.; Duncan, Richard; Feng, Hao; Ghosh, Debashis; Binder, Elisabeth B.; Bradley, Bekh; Ressler, Kerry J.; Conneely, Karen N.; Epstein, Michael P.

2015-01-01

IMPORTANCE Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction. OBJECTIVES To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem. DESIGN, SETTING, AND PARTICIPANTS The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory. MAIN OUTCOMES AND MEASURES We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors. RESULTS Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue. CONCLUSIONS AND RELEVANCE We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis. PMID:25354142

Variation at 2q35 (PNKD and TMBIM1) influences colorectal cancer risk and identifies a pleiotropic effect with inflammatory bowel disease.

PubMed

Orlando, Giulia; Law, Philip J; Palin, Kimmo; Tuupanen, Sari; Gylfe, Alexandra; Hänninen, Ulrika A; Cajuso, Tatiana; Tanskanen, Tomas; Kondelin, Johanna; Kaasinen, Eevi; Sarin, Antti-Pekka; Kaprio, Jaakko; Eriksson, Johan G; Rissanen, Harri; Knekt, Paul; Pukkala, Eero; Jousilahti, Pekka; Salomaa, Veikko; Ripatti, Samuli; Palotie, Aarno; Järvinen, Heikki; Renkonen-Sinisalo, Laura; Lepistö, Anna; Böhm, Jan; Mecklin, Jukka-Pekka; Al-Tassan, Nada A; Palles, Claire; Martin, Lynn; Barclay, Ella; Tenesa, Albert; Farrington, Susan; Timofeeva, Maria N; Meyer, Brian F; Wakil, Salma M; Campbell, Harry; Smith, Christopher G; Idziaszczyk, Shelley; Maughan, Timothy S; Kaplan, Richard; Kerr, Rachel; Kerr, David; Buchanan, Daniel D; Win, Aung Ko; Hopper, John; Jenkins, Mark; Lindor, Noralane M; Newcomb, Polly A; Gallinger, Steve; Conti, David; Schumacher, Fred; Casey, Graham; Taipale, Jussi; Cheadle, Jeremy P; Dunlop, Malcolm G; Tomlinson, Ian P; Aaltonen, Lauri A; Houlston, Richard S

2016-06-01

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 × 10 -8 , odds ratio = 1.10, 95% confidence interval = 1.06-1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r 2 = 0.90, D' = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR]) < 0.05). Our findings provide further insight into the biological basis of inherited genetic susceptibility to CRC, and identify risk factors that may influence the development of both CRC and IBD. © The Author 2016. Published by Oxford University Press.

Variation at 2q35 (PNKD and TMBIM1) influences colorectal cancer risk and identifies a pleiotropic effect with inflammatory bowel disease

PubMed Central

Orlando, Giulia; Law, Philip J.; Palin, Kimmo; Tuupanen, Sari; Gylfe, Alexandra; Hänninen, Ulrika A.; Cajuso, Tatiana; Tanskanen, Tomas; Kondelin, Johanna; Kaasinen, Eevi; Sarin, Antti-Pekka; Kaprio, Jaakko; Eriksson, Johan G.; Rissanen, Harri; Knekt, Paul; Pukkala, Eero; Jousilahti, Pekka; Salomaa, Veikko; Ripatti, Samuli; Palotie, Aarno; Järvinen, Heikki; Renkonen-Sinisalo, Laura; Lepistö, Anna; Böhm, Jan; Mecklin, Jukka-Pekka; Al-Tassan, Nada A.; Palles, Claire; Martin, Lynn; Barclay, Ella; Tenesa, Albert; Farrington, Susan; Timofeeva, Maria N.; Meyer, Brian F.; Wakil, Salma M.; Campbell, Harry; Smith, Christopher G.; Idziaszczyk, Shelley; Maughan, Timothy S.; Kaplan, Richard; Kerr, Rachel; Kerr, David; Buchanan, Daniel D.; Ko Win, Aung; Hopper, John; Jenkins, Mark; Lindor, Noralane M.; Newcomb, Polly A.; Gallinger, Steve; Conti, David; Schumacher, Fred; Casey, Graham; Taipale, Jussi; Cheadle, Jeremy P.; Dunlop, Malcolm G.; Tomlinson, Ian P.; Aaltonen, Lauri A.; Houlston, Richard S.

2016-01-01

To identify new risk loci for colorectal cancer (CRC), we conducted a meta-analysis of seven genome-wide association studies (GWAS) with independent replication, totalling 13 656 CRC cases and 21 667 controls of European ancestry. The combined analysis identified a new risk association for CRC at 2q35 marked by rs992157 (P = 3.15 × 10−8, odds ratio = 1.10, 95% confidence interval = 1.06–1.13), which is intronic to PNKD (paroxysmal non-kinesigenic dyskinesia) and TMBIM1 (transmembrane BAX inhibitor motif containing 1). Intriguingly this susceptibility single-nucleotide polymorphism (SNP) is in strong linkage disequilibrium (r2 = 0.90, D′ = 0.96) with the previously discovered GWAS SNP rs2382817 for inflammatory bowel disease (IBD). Following on from this observation we examined for pleiotropy, or shared genetic susceptibility, between CRC and the 200 established IBD risk loci, identifying an additional 11 significant associations (false discovery rate [FDR]) < 0.05). Our findings provide further insight into the biological basis of inherited genetic susceptibility to CRC, and identify risk factors that may influence the development of both CRC and IBD. PMID:27005424

Common variants at the promoter region of the APOM confer a risk of rheumatoid arthritis

PubMed Central

Hu, Hae-Jin; Jin, Eun-Heui; Yim, Seon-Hee; Yang, So-Young; Jung, Seung-Hyun; Shin, Seung-Hun; Kim, Wan-Uk; Shim, Seung-Cheol; Kim, Tai-Gyu

2011-01-01

Although the genetic component in the etiology of rheumatoid arthritis (RA) has been consistently suggested, many novel genetic loci remain to uncover. To identify RA risk loci, we performed a genome-wide association study (GWAS) with 100 RA cases and 600 controls using Affymetrix SNP array 5.0. The candidate risk locus (APOM gene) was re-sequenced to discover novel promoter and coding variants in a group of the subjects. Replication was performed with the independent case-control set comprising of 578 RAs and 711 controls. Through GWAS, we identified a novel SNP associated with RA at the APOM gene in the MHC class III region on 6p21.33 (rs805297, odds ratio (OR) = 2.28, P = 5.20 × 10-7). Three more polymorphisms were identified at the promoter region of the APOM by the re-sequencing. For the replication, we genotyped the four SNP loci in the independent case-control set. The association of rs805297 identified by GWAS was successfully replicated (OR = 1.40, P = 6.65 × 10-5). The association became more significant in the combined analysis of discovery and replication sets (OR = 1.56, P = 2.73 ± 10-10). The individuals with the rs805297 risk allele (A) at the promoter region showed a significantly lower level of APOM expression compared with those with the protective allele (C) homozygote. In the logistic regressions by the phenotype status, the homozygote risk genotype (A/A) consistently showed higher ORs than the heterozygote one (A/C) for the phenotype-positive RAs. These results indicate that APOM promoter polymorphisms are significantly associated with the susceptibility to RA. PMID:21844665

BioSMACK: a linux live CD for genome-wide association analyses.

PubMed

Hong, Chang Bum; Kim, Young Jin; Moon, Sanghoon; Shin, Young-Ah; Go, Min Jin; Kim, Dong-Joon; Lee, Jong-Young; Cho, Yoon Shin

2012-01-01

Recent advances in high-throughput genotyping technologies have enabled us to conduct a genome-wide association study (GWAS) on a large cohort. However, analyzing millions of single nucleotide polymorphisms (SNPs) is still a difficult task for researchers conducting a GWAS. Several difficulties such as compatibilities and dependencies are often encountered by researchers using analytical tools, during the installation of software. This is a huge obstacle to any research institute without computing facilities and specialists. Therefore, a proper research environment is an urgent need for researchers working on GWAS. We developed BioSMACK to provide a research environment for GWAS that requires no configuration and is easy to use. BioSMACK is based on the Ubuntu Live CD that offers a complete Linux-based operating system environment without installation. Moreover, we provide users with a GWAS manual consisting of a series of guidelines for GWAS and useful examples. BioSMACK is freely available at http://ksnp.cdc. go.kr/biosmack.

Birth Cohort, Age, and Sex Strongly Modulate Effects of Lipid Risk Alleles Identified in Genome-Wide Association Studies

PubMed Central

Kulminski, Alexander M.; Culminskaya, Irina; Arbeev, Konstantin G.; Arbeeva, Liubov; Ukraintseva, Svetlana V.; Stallard, Eric; Wu, Deqing; Yashin, Anatoliy I.

2015-01-01

Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care. PMID:26295473

Molecular genetic studies in Saudi population; identified variants from GWAS and meta-analysis in stroke.

PubMed

Alharbi, Khalid Khalaf; Ali Khan, Imran; Alotaibi, Mohammad Abdullah; Saud Aloyaid, Abdullah; Al-Basheer, Haifa Abdulaziz; Alghamdi, Naelah Abdullah; Al-Baradie, Raid Saleem; Al-Sulaiman, A M

2018-01-01

Stroke is a multifactorial and heterogeneous disorder, correlates with heritability and considered as one of the major diseases. The prior reports performed the variable models such as genome-wide association studies (GWAS), replication, case-control, cross-sectional and meta-analysis studies and still, we lack diagnostic marker in the global world. There are limited studies were carried out in Saudi population, and we aim to investigate the molecular association of single nucleotide polymorphisms (SNPs) identified through GWAS and meta-analysis studies in stroke patients in the Saudi population. In this case-control study, we have opted gender equality of 207 cases and 207 controls from the capital city of Saudi Arabia in King Saud University Hospital. The peripheral blood (5 ml) sample will be collected in two different vacutainers, and three mL of the coagulated blood will be used for lipid analysis (biochemical tests) and two mL will be used for DNA analysis (molecular tests). Genomic DNA will be extracted with the collected blood samples, and specific primers will be designed for the opted SNPs ( SORT1 -rs646218 and OLR1 -rs11053646 polymorphisms) and PCR-RFLP will be performed and randomly DNA sequencing will be carried out to cross check the results. The rs646218 and rs11053646 polymorphisms were significantly associated with allele, genotype and dominant models with and without crude odds ratios (OR's) and Multiple logistic regression analysis (p < 0.05). Correlation between lipid profile and genotypes has confirmed the significant relation between triglycerides and rs646218 and rs1105364 6polymorphisms. However, rs11053646 polymorphism was correlated with HDLC (p = 0.04). Genotypes were examined in both males' vs. males and females' vs. females in cases and control and we concluded that in rs11053646 polymorphisms with male subjects compared between cases and controls found to be associated with dominant model heterozygote genotypes (p < 0.05). The results of the current study confirmed the SORT1 and OLR1  SNPs were associated in the Saudi population. The current results were in the association with the prior study results documented through GWAS and meta-analysis association. However, other ethnic population studies should be performed to rule out in the human hereditary diseases.

SNP association study in PMS2-associated Lynch syndrome.

PubMed

Ten Broeke, Sanne W; Elsayed, Fadwa A; Pagan, Lisa; Olderode-Berends, Maran J W; Garcia, Encarna Gomez; Gille, Hans J P; van Hest, Liselot P; Letteboer, Tom G W; van der Kolk, Lizet E; Mensenkamp, Arjen R; van Os, Theo A; Spruijt, Liesbeth; Redeker, Bert J W; Suerink, Manon; Vos, Yvonne J; Wagner, Anja; Wijnen, Juul T; Steyerberg, E W; Tops, Carli M J; van Wezel, Tom; Nielsen, Maartje

2017-11-17

Lynch syndrome (LS) patients are at high risk of developing colorectal cancer (CRC). Phenotypic variability might in part be explained by common susceptibility loci identified in Genome Wide Association Studies (GWAS). Previous studies focused mostly on MLH1, MSH2 and MSH6 carriers, with conflicting results. We aimed to determine the role of GWAS SNPs in PMS2 mutation carriers. A cohort study was performed in 507 PMS2 carriers (124 CRC cases), genotyped for 24 GWAS SNPs, including SNPs at 11q23.1 and 8q23.3. Hazard ratios (HRs) were calculated using a weighted Cox regression analysis to correct for ascertainment bias. Discrimination was assessed with a concordance statistic in a bootstrap cross-validation procedure. Individual SNPs only had non-significant associations with CRC occurrence with HRs lower than 2, although male carriers of allele A at rs1321311 (6p21.31) may have increased risk of CRC (HR = 2.1, 95% CI 1.2-3.0). A polygenic risk score (PRS) based on 24 HRs had an HR of 2.6 (95% CI 1.5-4.6) for the highest compared to the lowest quartile, but had no discriminative ability (c statistic 0.52). Previously suggested SNPs do not modify CRC risk in PMS2 carriers. Future large studies are needed for improved risk stratification among Lynch syndrome patients.

Epigenomic elements analyses for promoters identify ESRRG as a new susceptibility gene for obesity-related traits.

PubMed

Dong, S-S; Guo, Y; Zhu, D-L; Chen, X-F; Wu, X-M; Shen, H; Chen, X-D; Tan, L-J; Tian, Q; Deng, H-W; Yang, T-L

2016-07-01

With ENCODE epigenomic data and results from published genome-wide association studies (GWASs), we aimed to find regulatory signatures of obesity genes and discover novel susceptibility genes. Obesity genes were obtained from public GWAS databases and their promoters were annotated based on the regulatory element information. Significantly enriched or depleted epigenomic elements in the promoters of obesity genes were evaluated and all human genes were then prioritized according to the existence of the selected elements to predict new candidate genes. Top-ranked genes were subsequently applied to validate their associations with obesity-related traits in three independent in-house GWAS samples. We identified RAD21 and EZH2 as over-represented, and STAT2 (signal transducer and activator of transcription 2) and IRF3 (interferon regulatory transcription factor 3) as depleted transcription factors. Histone modification of H3K9me3 and chromatin state segmentation of 'poised promoter' and 'repressed' were over-represented. All genes were prioritized and we selected the top five genes for validation at the population level. Combining results from the three GWAS samples, rs7522101 in ESRRG (estrogen-related receptor-γ) remained significantly associated with body mass index after multiple testing corrections (P=7.25 × 10(-5)). It was also associated with β-cell function (P=1.99 × 10(-3)) and fasting glucose level (P<0.05) in the meta-analyses of glucose and insulin-related traits consortium (MAGIC) data set.Cnoclusions:In summary, we identified epigenomic characteristics for obesity genes and suggested ESRRG as a novel obesity-susceptibility gene.

Genome-Wide Association Study Reveals a New QTL for Salinity Tolerance in Barley (Hordeum vulgare L.)

PubMed Central

Fan, Yun; Zhou, Gaofeng; Shabala, Sergey; Chen, Zhong-Hua; Cai, Shengguan; Li, Chengdao; Zhou, Meixue

2016-01-01

Salinity stress is one of the most severe abiotic stresses that affect agricultural production. Genome wide association study (GWAS) has been widely used to detect genetic variations in extensive natural accessions with more recombination and higher resolution. In this study, 206 barley accessions collected worldwide were genotyped with 408 Diversity Arrays Technology (DArT) markers and evaluated for salinity stress tolerance using salinity tolerance score – a reliable trait developed in our previous work. GWAS for salinity tolerance had been conducted through a general linkage model and a mixed linkage model based on population structure and kinship. A total of 24 significant marker-trait associations were identified. A QTL on 4H with the nearest marker of bPb-9668 was consistently detected in all different methods. This QTL has not been reported before and is worth to be further confirmed with bi-parental populations. PMID:27446173

Genetic polymorphism and chronic obstructive pulmonary disease.

PubMed

Yuan, Cunhua; Chang, De; Lu, Guangming; Deng, Xiaowei

2017-01-01

Chronic obstructive pulmonary disease (COPD) is a common chronic disease, and its morbidity and mortality are increasing. There are many studies that have tried to explain the pathogenesis of COPD from genetic susceptibility, to identify the susceptibility of COPD factors, which play a role in early prevention, early detection and the early treatment. However, it is well known that COPD is an inflammatory disease characterized by incomplete reversible airflow limitation in which genes interact with the environment. In recent years, many studies have proved gene polymorphisms and COPD correlation. However, there is less research on the relationship between COPD and genome-wide association study (GWAS), epigenetics and apoptosis. In this paper, we summarized the correlation between gene level and COPD from the following four aspects: the GWAS, the gene polymorphism, the epigenetics and the apoptosis, and the relationship between COPD and gene is summarized comprehensively.

An alternative covariance estimator to investigate genetic heterogeneity in populations.

PubMed

Heslot, Nicolas; Jannink, Jean-Luc

2015-11-26

For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative covariance estimator can be used to gain insight into trait-specific genetic heterogeneity by identifying relevant sub-populations that lack genetic correlation between them. Genetic correlation can be 0 between identified sub-populations by performing automatic selection of relevant sets of individuals to be included in the training population. It may also increase statistical power in GWAS.

Genome-wide association analysis identifies three new breast cancer susceptibility loci.

PubMed

Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki; Turnbull, Clare; Schmidt, Marjanka K; Dicks, Ed; Dennis, Joe; Wang, Qin; Humphreys, Manjeet K; Luccarini, Craig; Baynes, Caroline; Conroy, Don; Maranian, Melanie; Ahmed, Shahana; Driver, Kristy; Johnson, Nichola; Orr, Nicholas; dos Santos Silva, Isabel; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Uitterlinden, Andre G; Rivadeneira, Fernando; Hall, Per; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Chang-Claude, Jenny; Hein, Rebecca; Nickels, Stefan; Flesch-Janys, Dieter; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Hopper, John L; Apicella, Carmel; Park, Daniel J; Southey, Melissa; Hunter, David J; Chanock, Stephen J; Broeks, Annegien; Verhoef, Senno; Hogervorst, Frans B L; Fasching, Peter A; Lux, Michael P; Beckmann, Matthias W; Ekici, Arif B; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Menegaux, Florence; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L; Alonso, M Rosario; González-Neira, Anna; Benítez, Javier; Anton-Culver, Hoda; Ziogas, Argyrios; Bernstein, Leslie; Dur, Christina Clarke; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Justenhoven, Christina; Brauch, Hiltrud; Brüning, Thomas; Wang-Gohrke, Shan; Eilber, Ursula; Dörk, Thilo; Schürmann, Peter; Bremer, Michael; Hillemanns, Peter; Bogdanova, Natalia V; Antonenkova, Natalia N; Rogov, Yuri I; Karstens, Johann H; Bermisheva, Marina; Prokofieva, Darya; Khusnutdinova, Elza; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Lambrechts, Diether; Yesilyurt, Betul T; Floris, Giuseppe; Leunen, Karin; Manoukian, Siranoush; Bonanni, Bernardo; Fortuzzi, Stefano; Peterlongo, Paolo; Couch, Fergus J; Wang, Xianshu; Stevens, Kristen; Lee, Adam; Giles, Graham G; Baglietto, Laura; Severi, Gianluca; McLean, Catriona; Alnaes, Grethe Grenaker; Kristensen, Vessela; Børrensen-Dale, Anne-Lise; John, Esther M; Miron, Alexander; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L; Glendon, Gord; Mulligan, Anna Marie; Devilee, Peter; van Asperen, Christie J; Tollenaar, Rob A E M; Seynaeve, Caroline; Figueroa, Jonine D; Garcia-Closas, Montserrat; Brinton, Louise; Lissowska, Jolanta; Hooning, Maartje J; Hollestelle, Antoinette; Oldenburg, Rogier A; van den Ouweland, Ans M W; Cox, Angela; Reed, Malcolm W R; Shah, Mitul; Jakubowska, Ania; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Jones, Michael; Schoemaker, Minouk; Ashworth, Alan; Swerdlow, Anthony; Beesley, Jonathan; Chen, Xiaoqing; Muir, Kenneth R; Lophatananon, Artitaya; Rattanamongkongul, Suthee; Chaiwerawattana, Arkom; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Shen, Chen-Yang; Yu, Jyh-Cherng; Wu, Pei-Ei; Hsiung, Chia-Ni; Perkins, Annie; Swann, Ruth; Velentzis, Louiza; Eccles, Diana M; Tapper, Will J; Gerty, Susan M; Graham, Nikki J; Ponder, Bruce A J; Chenevix-Trench, Georgia; Pharoah, Paul D P; Lathrop, Mark; Dunning, Alison M; Rahman, Nazneen; Peto, Julian; Easton, Douglas F

2012-01-22

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.

Genome-wide association analysis identifies three new breast cancer susceptibility loci

PubMed Central

Ghoussaini, Maya; Fletcher, Olivia; Michailidou, Kyriaki; Turnbull, Clare; Schmidt, Marjanka K; Dicks, Ed; Dennis, Joe; Wang, Qin; Humphreys, Manjeet K; Luccarini, Craig; Baynes, Caroline; Conroy, Don; Maranian, Melanie; Ahmed, Shahana; Driver, Kristy; Johnson, Nichola; Orr, Nicholas; Silva, Isabel dos Santos; Waisfisz, Quinten; Meijers-Heijboer, Hanne; Uitterlinden, Andre G.; Rivadeneira, Fernando; Hall, Per; Czene, Kamila; Irwanto, Astrid; Liu, Jianjun; Nevanlinna, Heli; Aittomäki, Kristiina; Blomqvist, Carl; Meindl, Alfons; Schmutzler, Rita K; Müller-Myhsok, Bertram; Lichtner, Peter; Chang-Claude, Jenny; Hein, Rebecca; Nickels, Stefan; Flesch-Janys, Dieter; Tsimiklis, Helen; Makalic, Enes; Schmidt, Daniel; Bui, Minh; Hopper, John L; Apicella, Carmel; Park, Daniel J; Southey, Melissa; Hunter, David J; Chanock, Stephen J; Broeks, Annegien; Verhoef, Senno; Hogervorst, Frans BL; Fasching, Peter A.; Lux, Michael P.; Beckmann, Matthias W.; Ekici, Arif B.; Sawyer, Elinor; Tomlinson, Ian; Kerin, Michael; Marme, Frederik; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guénel, Pascal; Truong, Thérèse; Cordina-Duverger, Emilie; Menegaux, Florence; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L.; Alonso, M. Rosario; González-Neira, Anna; Benítez, Javier; Anton-Culver, Hoda; Ziogas, Argyrios; Bernstein, Leslie; Dur, Christina Clarke; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Justenhoven, Christina; Brauch, Hiltrud; Brüning, Thomas; Wang-Gohrke, Shan; Eilber, Ursula; Dörk, Thilo; Schürmann, Peter; Bremer, Michael; Hillemanns, Peter; Bogdanova, Natalia V.; Antonenkova, Natalia N.; Rogov, Yuri I.; Karstens, Johann H.; Bermisheva, Marina; Prokofieva, Darya; Khusnutdinova, Elza; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Lambrechts, Diether; Yesilyurt, Betul T.; Floris, Giuseppe; Leunen, Karin; Manoukian, Siranoush; Bonanni, Bernardo; Fortuzzi, Stefano; Peterlongo, Paolo; Couch, Fergus J; Wang, Xianshu; Stevens, Kristen; Lee, Adam; Giles, Graham G.; Baglietto, Laura; Severi, Gianluca; McLean, Catriona; Alnæs, Grethe Grenaker; Kristensen, Vessela; Børrensen-Dale, Anne-Lise; John, Esther M.; Miron, Alexander; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L.; Glendon, Gord; Mulligan, Anna Marie; Devilee, Peter; van Asperen, Christie J.; Tollenaar, Rob A.E.M.; Seynaeve, Caroline; Figueroa, Jonine D; Garcia-Closas, Montserrat; Brinton, Louise; Lissowska, Jolanta; Hooning, Maartje J.; Hollestelle, Antoinette; Oldenburg, Rogier A.; van den Ouweland, Ans M.W.; Cox, Angela; Reed, Malcolm WR; Shah, Mitul; Jakubowska, Ania; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Jones, Michael; Schoemaker, Minouk; Ashworth, Alan; Swerdlow, Anthony; Beesley, Jonathan; Chen, Xiaoqing; Muir, Kenneth R; Lophatananon, Artitaya; Rattanamongkongul, Suthee; Chaiwerawattana, Arkom; Kang, Daehee; Yoo, Keun-Young; Noh, Dong-Young; Shen, Chen-Yang; Yu, Jyh-Cherng; Wu, Pei-Ei; Hsiung, Chia-Ni; Perkins, Annie; Swann, Ruth; Velentzis, Louiza; Eccles, Diana M; Tapper, Will J; Gerty, Susan M; Graham, Nikki J; Ponder, Bruce A. J.; Chenevix-Trench, Georgia; Pharoah, Paul D.P.; Lathrop, Mark; Dunning, Alison M.; Rahman, Nazneen; Peto, Julian; Easton, Douglas F

2013-01-01

Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ~ 8% of the heritability of the disease. We followed up 72 promising associations from two independent Genome Wide Association Studies (GWAS) in ~70,000 cases and ~68,000 controls from 41 case-control studies and nine breast cancer GWAS. We identified three new breast cancer risk loci on 12p11 (rs10771399; P=2.7 × 10−35), 12q24 (rs1292011; P=4.3×10−19) and 21q21 (rs2823093; P=1.1×10−12). SNP rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) plays a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, while NRIP1 (21q21) encodes an ER co-factor and has a role in the regulation of breast cancer cell growth. PMID:22267197

Genome-wide association study identifies 74 loci associated with educational attainment

PubMed Central

Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E.R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Räikkönen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J.A.; Venturini, Cristina; Vinkhuyzen, Anna A.E.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, Terho; Lehrer, Steven F.; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W.J.H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

2016-01-01

Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129

Pathway Analysis in Attention Deficit Hyperactivity Disorder: An Ensemble Approach

PubMed Central

Mooney, Michael A.; McWeeney, Shannon K.; Faraone, Stephen V.; Hinney, Anke; Hebebrand, Johannes; Nigg, Joel T.; Wilmot, Beth

2016-01-01

Despite a wealth of evidence for the role of genetics in attention deficit hyperactivity disorder (ADHD), specific and definitive genetic mechanisms have not been identified. Pathway analyses, a subset of gene-set analyses, extend the knowledge gained from genome-wide association studies (GWAS) by providing functional context for genetic associations. However, there are numerous methods for association testing of gene sets and no real consensus regarding the best approach. The present study applied six pathway analysis methods to identify pathways associated with ADHD in two GWAS datasets from the Psychiatric Genomics Consortium. Methods that utilize genotypes to model pathway-level effects identified more replicable pathway associations than methods using summary statistics. In addition, pathways implicated by more than one method were significantly more likely to replicate. A number of brain-relevant pathways, such as RhoA signaling, glycosaminoglycan biosynthesis, fibroblast growth factor receptor activity, and pathways containing potassium channel genes, were nominally significant by multiple methods in both datasets. These results support previous hypotheses about the role of regulation of neurotransmitter release, neurite outgrowth and axon guidance in contributing to the ADHD phenotype and suggest the value of cross-method convergence in evaluating pathway analysis results. PMID:27004716

Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations.

PubMed

Lamontagne, Maxime; Bérubé, Jean-Christophe; Obeidat, Ma'en; Cho, Michael H; Hobbs, Brian D; Sakornsakolpat, Phuwanat; de Jong, Kim; Boezen, H Marike; Nickle, David; Hao, Ke; Timens, Wim; van den Berge, Maarten; Joubert, Philippe; Laviolette, Michel; Sin, Don D; Paré, Peter D; Bossé, Yohan

2018-05-15

Causal genes of chronic obstructive pulmonary disease (COPD) remain elusive. The current study aims at integrating genome-wide association studies (GWAS) and lung expression quantitative trait loci (eQTL) data to map COPD candidate causal genes and gain biological insights into the recently discovered COPD susceptibility loci. Two complementary genomic datasets on COPD were studied. First, the lung eQTL dataset which included whole-genome gene expression and genotyping data from 1038 individuals. Second, the largest COPD GWAS to date from the International COPD Genetics Consortium (ICGC) with 13 710 cases and 38 062 controls. Methods that integrated GWAS with eQTL signals including transcriptome-wide association study (TWAS), colocalization and Mendelian randomization-based (SMR) approaches were used to map causality genes, i.e. genes with the strongest evidence of being the functional effector at specific loci. These methods were applied at the genome-wide level and at COPD risk loci derived from the GWAS literature. Replication was performed using lung data from GTEx. We collated 129 non-overlapping risk loci for COPD from the GWAS literature. At the genome-wide scale, 12 new COPD candidate genes/loci were revealed and six replicated in GTEx including CAMK2A, DMPK, MYO15A, TNFRSF10A, BTN3A2 and TRBV30. In addition, we mapped candidate causal genes for 60 out of the 129 GWAS-nominated loci and 23 of them were replicated in GTEx. Mapping candidate causal genes in lung tissue represents an important contribution to the genetics of COPD, enriches our biological interpretation of GWAS findings, and brings us closer to clinical translation of genetic associations.

Association of the Polygenic Scores for Personality Traits and Response to Selective Serotonin Reuptake Inhibitors in Patients with Major Depressive Disorder

PubMed Central

Amare, Azmeraw T.; Schubert, Klaus Oliver; Tekola-Ayele, Fasil; Hsu, Yi-Hsiang; Sangkuhl, Katrin; Jenkins, Gregory; Whaley, Ryan M.; Barman, Poulami; Batzler, Anthony; Altman, Russ B.; Arolt, Volker; Brockmöller, Jürgen; Chen, Chia-Hui; Domschke, Katharina; Hall-Flavin, Daniel K.; Hong, Chen-Jee; Illi, Ari; Ji, Yuan; Kampman, Olli; Kinoshita, Toshihiko; Leinonen, Esa; Liou, Ying-Jay; Mushiroda, Taisei; Nonen, Shinpei; Skime, Michelle K.; Wang, Liewei; Kato, Masaki; Liu, Yu-Li; Praphanphoj, Verayuth; Stingl, Julia C.; Bobo, William V.; Tsai, Shih-Jen; Kubo, Michiaki; Klein, Teri E.; Weinshilboum, Richard M.; Biernacka, Joanna M.; Baune, Bernhard T.

2018-01-01

Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across PT thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs. PMID:29559929

Genomewide association study for susceptibility genes contributing to familial Parkinson disease

PubMed Central

Pankratz, Nathan; Wilk, Jemma B.; Latourelle, Jeanne C.; DeStefano, Anita L.; Halter, Cheryl; Pugh, Elizabeth W.; Doheny, Kimberly F.; Gusella, James F.; Nichols, William C.

2009-01-01

Five genes have been identified that contribute to Mendelian forms of Parkinson disease (PD); however, mutations have been found in fewer than 5% of patients, suggesting that additional genes contribute to disease risk. Unlike previous studies that focused primarily on sporadic PD, we have performed the first genomewide association study (GWAS) in familial PD. Genotyping was performed with the Illumina HumanCNV370Duo array in 857 familial PD cases and 867 controls. A logistic model was employed to test for association under additive and recessive modes of inheritance after adjusting for gender and age. No result met genomewide significance based on a conservative Bonferroni correction. The strongest association result was with SNPs in the GAK/DGKQ region on chromosome 4 (additive model: p = 3.4 × 10−6; OR = 1.69). Consistent evidence of association was also observed to the chromosomal regions containing SNCA (additive model: p = 5.5 × 10−5; OR = 1.35) and MAPT (recessive model: p = 2.0 × 10−5; OR = 0.56). Both of these genes have been implicated previously in PD susceptibility; however, neither was identified in previous GWAS studies of PD. Meta-analysis was performed using data from a previous case–control GWAS, and yielded improved p values for several regions, including GAK/DGKQ (additive model: p = 2.5 × 10−7) and the MAPT region (recessive model: p = 9.8 × 10−6; additive model: p = 4.8 × 10−5). These data suggest the identification of new susceptibility alleles for PD in the GAK/DGKQ region, and also provide further support for the role of SNCA and MAPT in PD susceptibility. PMID:18985386

A two-stage genome-wide association study of sporadic amyotrophic lateral sclerosis.

PubMed

Chiò, Adriano; Schymick, Jennifer C; Restagno, Gabriella; Scholz, Sonja W; Lombardo, Federica; Lai, Shiao-Lin; Mora, Gabriele; Fung, Hon-Chung; Britton, Angela; Arepalli, Sampath; Gibbs, J Raphael; Nalls, Michael; Berger, Stephen; Kwee, Lydia Coulter; Oddone, Eugene Z; Ding, Jinhui; Crews, Cynthia; Rafferty, Ian; Washecka, Nicole; Hernandez, Dena; Ferrucci, Luigi; Bandinelli, Stefania; Guralnik, Jack; Macciardi, Fabio; Torri, Federica; Lupoli, Sara; Chanock, Stephen J; Thomas, Gilles; Hunter, David J; Gieger, Christian; Wichmann, H Erich; Calvo, Andrea; Mutani, Roberto; Battistini, Stefania; Giannini, Fabio; Caponnetto, Claudia; Mancardi, Giovanni Luigi; La Bella, Vincenzo; Valentino, Francesca; Monsurrò, Maria Rosaria; Tedeschi, Gioacchino; Marinou, Kalliopi; Sabatelli, Mario; Conte, Amelia; Mandrioli, Jessica; Sola, Patrizia; Salvi, Fabrizio; Bartolomei, Ilaria; Siciliano, Gabriele; Carlesi, Cecilia; Orrell, Richard W; Talbot, Kevin; Simmons, Zachary; Connor, James; Pioro, Erik P; Dunkley, Travis; Stephan, Dietrich A; Kasperaviciute, Dalia; Fisher, Elizabeth M; Jabonka, Sibylle; Sendtner, Michael; Beck, Marcus; Bruijn, Lucie; Rothstein, Jeffrey; Schmidt, Silke; Singleton, Andrew; Hardy, John; Traynor, Bryan J

2009-04-15

The cause of sporadic amyotrophic lateral sclerosis (ALS) is largely unknown, but genetic factors are thought to play a significant role in determining susceptibility to motor neuron degeneration. To identify genetic variants altering risk of ALS, we undertook a two-stage genome-wide association study (GWAS): we followed our initial GWAS of 545 066 SNPs in 553 individuals with ALS and 2338 controls by testing the 7600 most associated SNPs from the first stage in three independent cohorts consisting of 2160 cases and 3008 controls. None of the SNPs selected for replication exceeded the Bonferroni threshold for significance. The two most significantly associated SNPs, rs2708909 and rs2708851 [odds ratio (OR) = 1.17 and 1.18, and P-values = 6.98 x 10(-7) and 1.16 x 10(-6)], were located on chromosome 7p13.3 within a 175 kb linkage disequilibrium block containing the SUNC1, HUS1 and C7orf57 genes. These associations did not achieve genome-wide significance in the original cohort and failed to replicate in an additional independent cohort of 989 US cases and 327 controls (OR = 1.18 and 1.19, P-values = 0.08 and 0.06, respectively). Thus, we chose to cautiously interpret our data as hypothesis-generating requiring additional confirmation, especially as all previously reported loci for ALS have failed to replicate successfully. Indeed, the three loci (FGGY, ITPR2 and DPP6) identified in previous GWAS of sporadic ALS were not significantly associated with disease in our study. Our findings suggest that ALS is more genetically and clinically heterogeneous than previously recognized. Genotype data from our study have been made available online to facilitate such future endeavors.

A two-stage genome-wide association study of sporadic amyotrophic lateral sclerosis

PubMed Central

Chiò, Adriano; Schymick, Jennifer C.; Restagno, Gabriella; Scholz, Sonja W.; Lombardo, Federica; Lai, Shiao-Lin; Mora, Gabriele; Fung, Hon-Chung; Britton, Angela; Arepalli, Sampath; Gibbs, J. Raphael; Nalls, Michael; Berger, Stephen; Kwee, Lydia Coulter; Oddone, Eugene Z.; Ding, Jinhui; Crews, Cynthia; Rafferty, Ian; Washecka, Nicole; Hernandez, Dena; Ferrucci, Luigi; Bandinelli, Stefania; Guralnik, Jack; Macciardi, Fabio; Torri, Federica; Lupoli, Sara; Chanock, Stephen J.; Thomas, Gilles; Hunter, David J.; Gieger, Christian; Wichmann, H. Erich; Calvo, Andrea; Mutani, Roberto; Battistini, Stefania; Giannini, Fabio; Caponnetto, Claudia; Mancardi, Giovanni Luigi; La Bella, Vincenzo; Valentino, Francesca; Monsurrò, Maria Rosaria; Tedeschi, Gioacchino; Marinou, Kalliopi; Sabatelli, Mario; Conte, Amelia; Mandrioli, Jessica; Sola, Patrizia; Salvi, Fabrizio; Bartolomei, Ilaria; Siciliano, Gabriele; Carlesi, Cecilia; Orrell, Richard W.; Talbot, Kevin; Simmons, Zachary; Connor, James; Pioro, Erik P.; Dunkley, Travis; Stephan, Dietrich A.; Kasperaviciute, Dalia; Fisher, Elizabeth M.; Jabonka, Sibylle; Sendtner, Michael; Beck, Marcus; Bruijn, Lucie; Rothstein, Jeffrey; Schmidt, Silke; Singleton, Andrew; Hardy, John; Traynor, Bryan J.

2009-01-01

The cause of sporadic amyotrophic lateral sclerosis (ALS) is largely unknown, but genetic factors are thought to play a significant role in determining susceptibility to motor neuron degeneration. To identify genetic variants altering risk of ALS, we undertook a two-stage genome-wide association study (GWAS): we followed our initial GWAS of 545 066 SNPs in 553 individuals with ALS and 2338 controls by testing the 7600 most associated SNPs from the first stage in three independent cohorts consisting of 2160 cases and 3008 controls. None of the SNPs selected for replication exceeded the Bonferroni threshold for significance. The two most significantly associated SNPs, rs2708909 and rs2708851 [odds ratio (OR) = 1.17 and 1.18, and P-values = 6.98 × 10−7 and 1.16 × 10−6], were located on chromosome 7p13.3 within a 175 kb linkage disequilibrium block containing the SUNC1, HUS1 and C7orf57 genes. These associations did not achieve genome-wide significance in the original cohort and failed to replicate in an additional independent cohort of 989 US cases and 327 controls (OR = 1.18 and 1.19, P-values = 0.08 and 0.06, respectively). Thus, we chose to cautiously interpret our data as hypothesis-generating requiring additional confirmation, especially as all previously reported loci for ALS have failed to replicate successfully. Indeed, the three loci (FGGY, ITPR2 and DPP6) identified in previous GWAS of sporadic ALS were not significantly associated with disease in our study. Our findings suggest that ALS is more genetically and clinically heterogeneous than previously recognized. Genotype data from our study have been made available online to facilitate such future endeavors. PMID:19193627

Design and analysis of multiple diseases genome-wide association studies without controls.

PubMed

Chen, Zhongxue; Huang, Hanwen; Ng, Hon Keung Tony

2012-11-15

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case-control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case-control GWAS as well as those with shared controls. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle

PubMed Central

Crispim, Aline Camporez; Kelly, Matthew John; Guimarães, Simone Eliza Facioni; e Silva, Fabyano Fonseca; Fortes, Marina Rufino Salinas; Wenceslau, Raphael Rocha; Moore, Stephen

2015-01-01

Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates. PMID:26445451

Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle.

PubMed

Crispim, Aline Camporez; Kelly, Matthew John; Guimarães, Simone Eliza Facioni; Fonseca e Silva, Fabyano; Fortes, Marina Rufino Salinas; Wenceslau, Raphael Rocha; Moore, Stephen

2015-01-01

Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

PubMed

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.

Genetic risk variants for membranous nephropathy: extension of and association with other chronic kidney disease aetiologies.

PubMed

Sekula, Peggy; Li, Yong; Stanescu, Horia C; Wuttke, Matthias; Ekici, Arif B; Bockenhauer, Detlef; Walz, Gerd; Powis, Stephen H; Kielstein, Jan T; Brenchley, Paul; Eckardt, Kai-Uwe; Kronenberg, Florian; Kleta, Robert; Köttgen, Anna

2017-02-01

Membranous nephropathy (MN) is a common cause of nephrotic syndrome in adults. Previous genome-wide association studies (GWAS) of 300 000 genotyped variants identified MN-associated loci at HLA-DQA1 and PLA2R1. We used a combined approach of genotype imputation, GWAS, human leucocyte antigen (HLA) imputation and extension to other aetiologies of chronic kidney disease (CKD) to investigate genetic MN risk variants more comprehensively. GWAS using 9 million high-quality imputed genotypes and classical HLA alleles were conducted for 323 MN European-ancestry cases and 345 controls. Additionally, 4960 patients with different CKD aetiologies in the German Chronic Kidney Disease (GCKD) study were genotyped for risk variants at HLA-DQA1 and PLA2R1. In GWAS, lead variants in known loci [rs9272729, HLA-DQA1, odds ratio (OR) = 7.3 per risk allele, P = 5.9 × 10 -27 and rs17830558, PLA2R1, OR = 2.2, P = 1.9 × 10 -8 ] were significantly associated with MN. No novel signals emerged in GWAS of X-chromosomal variants or in sex-specific analyses. Classical HLA alleles (DRB1*0301-DQA1*0501-DQB1*0201 haplotype) were associated with MN but provided little additional information beyond rs9272729. Associations were replicated in 137 GCKD patients with MN (HLA-DQA1: P = 6.4 × 10 -24 ; PLA2R1: P = 5.0 × 10 -4 ). MN risk increased steeply for patients with high-risk genotype combinations (OR > 79). While genetic variation in PLA2R1 exclusively associated with MN across 19 CKD aetiologies, the HLA-DQA1 risk allele was also associated with lupus nephritis (P = 2.8 × 10 -6 ), type 1 diabetic nephropathy (P = 6.9 × 10 -5 ) and focal segmental glomerulosclerosis (P = 5.1 × 10 -5 ), but not with immunoglobulin A nephropathy. PLA2R1 and HLA-DQA1 are the predominant risk loci for MN detected by GWAS. While HLA-DQA1 risk variants show an association with other CKD aetiologies, PLA2R1 variants are specific to MN. © The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Genome-wide association study of corticobasal degeneration identifies risk variants shared with progressive supranuclear palsy

PubMed Central

Kouri, Naomi; Ross, Owen A.; Dombroski, Beth; Younkin, Curtis S.; Serie, Daniel J.; Soto-Ortolaza, Alexandra; Baker, Matthew; Finch, Ni Cole A.; Yoon, Hyejin; Kim, Jungsu; Fujioka, Shinsuke; McLean, Catriona A.; Ghetti, Bernardino; Spina, Salvatore; Cantwell, Laura B.; Farlow, Martin R.; Grafman, Jordan; Huey, Edward D.; Ryung Han, Mi; Beecher, Sherry; Geller, Evan T.; Kretzschmar, Hans A.; Roeber, Sigrun; Gearing, Marla; Juncos, Jorge L.; Vonsattel, Jean Paul G.; Van Deerlin, Vivianna M.; Grossman, Murray; Hurtig, Howard I.; Gross, Rachel G.; Arnold, Steven E.; Trojanowski, John Q.; Lee, Virginia M.; Wenning, Gregor K.; White, Charles L.; Höglinger, Günter U.; Müller, Ulrich; Devlin, Bernie; Golbe, Lawrence I.; Crook, Julia; Parisi, Joseph E.; Boeve, Bradley F.; Josephs, Keith A.; Wszolek, Zbigniew K.; Uitti, Ryan J.; Graff-Radford, Neill R.; Litvan, Irene; Younkin, Steven G.; Wang, Li-San; Ertekin-Taner, Nilüfer; Rademakers, Rosa; Hakonarsen, Hakon; Schellenberg, Gerard D.; Dickson, Dennis W.

2015-01-01

Corticobasal degeneration (CBD) is a neurodegenerative disorder affecting movement and cognition, definitively diagnosed only at autopsy. Here, we conduct a genome-wide association study (GWAS) in CBD cases (n=152) and 3,311 controls, and 67 CBD cases and 439 controls in a replication stage. Associations with meta-analysis were 17q21 at MAPT (P=1.42 × 10−12), 8p12 at lnc-KIF13B-1, a long non-coding RNA (rs643472; P=3.41 × 10−8), and 2p22 at SOS1 (rs963731; P=1.76 × 10−7). Testing for association of CBD with top progressive supranuclear palsy (PSP) GWAS single-nucleotide polymorphisms (SNPs) identified associations at MOBP (3p22; rs1768208; P=2.07 × 10−7) and MAPT H1c (17q21; rs242557; P=7.91 × 10−6). We previously reported SNP/transcript level associations with rs8070723/MAPT, rs242557/MAPT, and rs1768208/MOBP and herein identified association with rs963731/SOS1. We identify new CBD susceptibility loci and show that CBD and PSP share a genetic risk factor other than MAPT at 3p22 MOBP (myelin-associated oligodendrocyte basic protein). PMID:26077951

Novel Sources of Stripe Rust Resistance Identified by Genome-Wide Association Mapping in Ethiopian Durum Wheat (Triticum turgidum ssp. durum)

PubMed Central

Liu, Weizhen; Maccaferri, Marco; Rynearson, Sheri; Letta, Tesfaye; Zegeye, Habtemariam; Tuberosa, Roberto; Chen, Xianming; Pumphrey, Michael

2017-01-01

Stripe rust of wheat, caused by Puccinia striiformis f. sp. tritici (Pst), is a global concern for wheat production, and has been increasingly destructive in Ethiopia, as well as in the United States and in many other countries. As Ethiopia has a long history of stripe rust epidemics, its native wheat germplasm harbors potentially valuable resistance loci. Moreover, the Ethiopian germplasm has been historically underutilized in breeding of modern wheat worldwide and thus the resistance alleles from the Ethiopian germplasm represent potentially novel sources. The objective of this study was to identify loci conferring resistance to predominant Pst races in Ethiopia and the United States. Using a high-density 90 K wheat single nucleotide polymorphism array, a genome-wide association analysis (GWAS) was conducted on 182 durum wheat landrace accessions and contemporary varieties originating from Ethiopia. Landraces were detected to be more resistant at the seedling stage while cultivars were more resistant at the adult-plant stages. GWAS identified 68 loci associated with seedling resistance to one or more races. Six loci on chromosome arms 1AS, 1BS, 3AS, 4BL, and 5BL were associated with resistance against at least two races at the seedling stage, and five loci were previously undocumented. GWAS analysis of field resistance reactions identified 12 loci associated with resistance on chromosomes 1A, 1B, 2BS, 3BL, 4AL, 4B and 5AL, which were detected in at least two of six field screening nurseries at the adult-plant stage. Comparison with previously mapped resistance loci indicates that six of the 12 resistance loci are newly documented. This study reports effective sources of resistance to contemporary races in Ethiopia and the United States and reveals that Ethiopian durum wheat landraces are abundant in novel Pst resistance loci that may be transferred into adapted cultivars to provide resistance against Pst. PMID:28553306

GWAS of clinically defined gout and subtypes identifies multiple susceptibility loci that include urate transporter genes

PubMed Central

Nakayama, Akiyoshi; Nakaoka, Hirofumi; Yamamoto, Ken; Sakiyama, Masayuki; Shaukat, Amara; Toyoda, Yu; Okada, Yukinori; Kamatani, Yoichiro; Nakamura, Takahiro; Takada, Tappei; Inoue, Katsuhisa; Yasujima, Tomoya; Yuasa, Hiroaki; Shirahama, Yuko; Nakashima, Hiroshi; Shimizu, Seiko; Higashino, Toshihide; Kawamura, Yusuke; Ogata, Hiraku; Kawaguchi, Makoto; Ohkawa, Yasuyuki; Danjoh, Inaho; Tokumasu, Atsumi; Ooyama, Keiko; Ito, Toshimitsu; Kondo, Takaaki; Wakai, Kenji; Stiburkova, Blanka; Pavelka, Karel; Stamp, Lisa K; Dalbeth, Nicola; Sakurai, Yutaka; Suzuki, Hiroshi; Hosoyamada, Makoto; Fujimori, Shin; Yokoo, Takashi; Hosoya, Tatsuo; Inoue, Ituro; Takahashi, Atsushi; Kubo, Michiaki; Ooyama, Hiroshi; Shimizu, Toru; Ichida, Kimiyoshi; Shinomiya, Nariyoshi; Merriman, Tony R; Matsuo, Hirotaka

2017-01-01

Objective A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. Methods Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were replicated with 1396 cases and 1268 controls using a custom chip of 1961 single nucleotide polymorphisms (SNPs). We also first conducted GWASs of gout subtypes. Replication with Caucasian and New Zealand Polynesian samples was done to further validate the loci identified in this study. Results In addition to the five loci we reported previously, further susceptibility loci were identified at a genome-wide significance level (p<5.0×10−8): urate transporter genes (SLC22A12 and SLC17A1) and HIST1H2BF-HIST1H4E for all gout cases, and NIPAL1 and FAM35A for the renal underexcretion gout subtype. While NIPAL1 encodes a magnesium transporter, functional analysis did not detect urate transport via NIPAL1, suggesting an indirect association with urate handling. Localisation analysis in the human kidney revealed expression of NIPAL1 and FAM35A mainly in the distal tubules, which suggests the involvement of the distal nephron in urate handling in humans. Clinically ascertained male patients with gout and controls of Caucasian and Polynesian ancestries were also genotyped, and FAM35A was associated with gout in all cases. A meta-analysis of the three populations revealed FAM35A to be associated with gout at a genome-wide level of significance (pmeta=3.58×10−8). Conclusions Our findings including novel gout risk loci provide further understanding of the molecular pathogenesis of gout and lead to a novel concept for the therapeutic target of gout/hyperuricaemia. PMID:27899376

Genome-Wide Association Study Implicates HLA-C*01: 02 as a Risk Factor at the Major Histocompatibility Complex Locus in Schizophrenia

PubMed Central

2012-01-01

Background We performed a genome-wide association study (GWAS) to identify common risk variants for schizophrenia. Methods The discovery scan included 1606 patients and 1794 controls from Ireland, using 6,212,339 directly genotyped or imputed single nucleotide polymorphisms (SNPs). A subset of this sample (270 cases and 860 controls) was subsequently included in the Psychiatric GWAS Consortium-schizophrenia GWAS meta-analysis. Results One hundred eight SNPs were taken forward for replication in an independent sample of 13,195 cases and 31,021 control subjects. The most significant associations in discovery, corrected for genomic inflation, were (rs204999, p combined = 1.34 × 10−9 and in combined samples (rs2523722 p combined = 2.88 × 10−16) mapped to the major histocompatibility complex (MHC) region. We imputed classical human leukocyte antigen (HLA) alleles at the locus; the most significant finding was with HLA-C*01:02. This association was distinct from the top SNP signal. The HLA alleles DRB1*03:01 and B*08:01 were protective, replicating a previous study. Conclusions This study provides further support for involvement of MHC class I molecules in schizophrenia. We found evidence of association with previously reported risk alleles at the TCF4, VRK2, and ZNF804A loci. PMID:22883433

Parallel and serial computing tools for testing single-locus and epistatic SNP effects of quantitative traits in genome-wide association studies

PubMed Central

Ma, Li; Runesha, H Birali; Dvorkin, Daniel; Garbe, John R; Da, Yang

2008-01-01

Background Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers provide opportunities to detect epistatic SNPs associated with quantitative traits and to detect the exact mode of an epistasis effect. Computational difficulty is the main bottleneck for epistasis testing in large scale GWAS. Results The EPISNPmpi and EPISNP computer programs were developed for testing single-locus and epistatic SNP effects on quantitative traits in GWAS, including tests of three single-locus effects for each SNP (SNP genotypic effect, additive and dominance effects) and five epistasis effects for each pair of SNPs (two-locus interaction, additive × additive, additive × dominance, dominance × additive, and dominance × dominance) based on the extended Kempthorne model. EPISNPmpi is the parallel computing program for epistasis testing in large scale GWAS and achieved excellent scalability for large scale analysis and portability for various parallel computing platforms. EPISNP is the serial computing program based on the EPISNPmpi code for epistasis testing in small scale GWAS using commonly available operating systems and computer hardware. Three serial computing utility programs were developed for graphical viewing of test results and epistasis networks, and for estimating CPU time and disk space requirements. Conclusion The EPISNPmpi parallel computing program provides an effective computing tool for epistasis testing in large scale GWAS, and the epiSNP serial computing programs are convenient tools for epistasis analysis in small scale GWAS using commonly available computer hardware. PMID:18644146

Evaluation of European Schizophrenia GWAS Loci in Asian Populations via Comprehensive Meta-Analyses.

PubMed

Xiao, Xiao; Luo, Xiong-Jian; Chang, Hong; Liu, Zichao; Li, Ming

2017-08-01

Schizophrenia is a severe and highly heritable neuropsychiatric disorder. Recent genetic analyses including genome-wide association studies (GWAS) have implicated multiple genome-wide significant variants for schizophrenia among European populations. However, many of these risk variants were not largely validated in other populations of different ancestry such as Asians. To validate whether these European GWAS significant loci are associated with schizophrenia in Asian populations, we conducted a systematic literature search and meta-analyses on 19 single nucleotide polymorphisms (SNPs) in Asian populations by combining all available case-control and family-based samples, including up to 30,000 individuals. We employed classical fixed (or random) effects inverse variance weighted methods to calculate summary odds ratios (ORs) and 95 % confidence intervals (CIs). Among the 19 GWAS loci, we replicated the risk associations of nine markers (e.g., SNPs at VRK2, ITIH3/4, NDST3, NOTCH4) surpassing significance level (two-tailed P < 0.05), and three additional SNPs in MIR137 and ZNF804A also showed trend associations (one-tailed P < 0.05). These risk associations are in the same directions of allelic effects between Asian replication samples and initial European GWAS findings, and the successful replications of these GWAS loci in a different ethnic group provide stronger evidence for their clinical associations with schizophrenia. Further studies, focusing on the molecular mechanisms of these GWAS significant loci, will become increasingly important for understanding of the pathogenesis to schizophrenia.

Genome-wide association study identified genetic variations and candidate genes for plant architecture component traits in Chinese upland cotton.

PubMed

Su, Junji; Li, Libei; Zhang, Chi; Wang, Caixiang; Gu, Lijiao; Wang, Hantao; Wei, Hengling; Liu, Qibao; Huang, Long; Yu, Shuxun

2018-06-01

Thirty significant associations between 22 SNPs and five plant architecture component traits in Chinese upland cotton were identified via GWAS. Four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits. A candidate gene, Gh_D03G0922, might be responsible for plant height in upland cotton. A compact plant architecture is increasingly required for mechanized harvesting processes in China. Therefore, cotton plant architecture is an important trait, and its components, such as plant height, fruit branch length and fruit branch angle, affect the suitability of a cultivar for mechanized harvesting. To determine the genetic basis of cotton plant architecture, a genome-wide association study (GWAS) was performed using a panel composed of 355 accessions and 93,250 single nucleotide polymorphisms (SNPs) identified using the specific-locus amplified fragment sequencing method. Thirty significant associations between 22 SNPs and five plant architecture component traits were identified via GWAS. Most importantly, four peak SNP loci located on chromosome D03 were simultaneously associated with more plant architecture component traits, and these SNPs were harbored in one linkage disequilibrium block. Furthermore, 21 candidate genes for plant architecture were predicted in a 0.95-Mb region including the four peak SNPs. One of these genes (Gh_D03G0922) was near the significant SNP D03_31584163 (8.40 kb), and its Arabidopsis homologs contain MADS-box domains that might be involved in plant growth and development. qRT-PCR showed that the expression of Gh_D03G0922 was upregulated in the apical buds and young leaves of the short and compact cotton varieties, and virus-induced gene silencing (VIGS) proved that the silenced plants exhibited increased PH. These results indicate that Gh_D03G0922 is likely the candidate gene for PH in cotton. The genetic variations and candidate genes identified in this study lay a foundation for cultivating moderately short and compact varieties in future Chinese cotton-breeding programs.

Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status.

PubMed

Hüsing, Anika; Canzian, Federico; Beckmann, Lars; Garcia-Closas, Montserrat; Diver, W Ryan; Thun, Michael J; Berg, Christine D; Hoover, Robert N; Ziegler, Regina G; Figueroa, Jonine D; Isaacs, Claudine; Olsen, Anja; Viallon, Vivian; Boeing, Heiner; Masala, Giovanna; Trichopoulos, Dimitrios; Peeters, Petra H M; Lund, Eiliv; Ardanaz, Eva; Khaw, Kay-Tee; Lenner, Per; Kolonel, Laurence N; Stram, Daniel O; Le Marchand, Loïc; McCarty, Catherine A; Buring, Julie E; Lee, I-Min; Zhang, Shumin; Lindström, Sara; Hankinson, Susan E; Riboli, Elio; Hunter, David J; Henderson, Brian E; Chanock, Stephen J; Haiman, Christopher A; Kraft, Peter; Kaaks, Rudolf

2012-09-01

There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.

Genome-wide association study (GWAS) for growth rate and age at sexual maturation in Atlantic salmon (Salmo salar).

PubMed

Gutierrez, Alejandro P; Yáñez, José M; Fukui, Steve; Swift, Bruce; Davidson, William S

2015-01-01

Early sexual maturation is considered a serious drawback for Atlantic salmon aquaculture as it retards growth, increases production times and affects flesh quality. Although both growth and sexual maturation are thought to be complex processes controlled by several genetic and environmental factors, selection for these traits has been continuously accomplished since the beginning of Atlantic salmon selective breeding programs. In this genome-wide association study (GWAS) we used a 6.5K single-nucleotide polymorphism (SNP) array to genotype ∼ 480 individuals from the Cermaq Canada broodstock program and search for SNPs associated with growth and age at sexual maturation. Using a mixed model approach we identified markers showing a significant association with growth, grilsing (early sexual maturation) and late sexual maturation. The most significant associations were found for grilsing, with markers located in Ssa10, Ssa02, Ssa13, Ssa25 and Ssa12, and for late maturation with markers located in Ssa28, Ssa01 and Ssa21. A lower level of association was detected with growth on Ssa13. Candidate genes, which were linked to these genetic markers, were identified and some of them show a direct relationship with developmental processes, especially for those in association with sexual maturation. However, the relatively low power to detect genetic markers associated with growth (days to 5 kg) in this GWAS indicates the need to use a higher density SNP array in order to overcome the low levels of linkage disequilibrium observed in Atlantic salmon before the information can be incorporated into a selective breeding program.

New gene functions in megakaryopoiesis and platelet formation

PubMed Central

Gieger, Christian; Radhakrishnan, Aparna; Cvejic, Ana; Tang, Weihong; Porcu, Eleonora; Pistis, Giorgio; Serbanovic-Canic, Jovana; Elling, Ulrich; Goodall, Alison H.; Labrune, Yann; Lopez, Lorna M.; Mägi, Reedik; Meacham, Stuart; Okada, Yukinori; Pirastu, Nicola; Sorice, Rossella; Teumer, Alexander; Voss, Katrin; Zhang, Weihua; Ramirez-Solis, Ramiro; Bis, Joshua C.; Ellinghaus, David; Gögele, Martin; Hottenga, Jouke-Jan; Langenberg, Claudia; Kovacs, Peter; O’Reilly, Paul F.; Shin, So-Youn; Esko, Tõnu; Hartiala, Jaana; Kanoni, Stavroula; Murgia, Federico; Parsa, Afshin; Stephens, Jonathan; van der Harst, Pim; van der Schoot, C. Ellen; Allayee, Hooman; Attwood, Antony; Balkau, Beverley; Bastardot, François; Basu, Saonli; Baumeister, Sebastian E.; Biino, Ginevra; Bomba, Lorenzo; Bonnefond, Amélie; Cambien, François; Chambers, John C.; Cucca, Francesco; D’Adamo, Pio; Davies, Gail; de Boer, Rudolf A.; de Geus, Eco J. C.; Döring, Angela; Elliott, Paul; Erdmann, Jeanette; Evans, David M.; Falchi, Mario; Feng, Wei; Folsom, Aaron R.; Frazer, Ian H.; Gibson, Quince D.; Glazer, Nicole L.; Hammond, Chris; Hartikainen, Anna-Liisa; Heckbert, Susan R.; Hengstenberg, Christian; Hersch, Micha; Illig, Thomas; Loos, Ruth J. F.; Jolley, Jennifer; Khaw, Kay Tee; Kühnel, Brigitte; Kyrtsonis, Marie-Christine; Lagou, Vasiliki; Lloyd-Jones, Heather; Lumley, Thomas; Mangino, Massimo; Maschio, Andrea; Leach, Irene Mateo; McKnight, Barbara; Memari, Yasin; Mitchell, Braxton D.; Montgomery, Grant W.; Nakamura, Yusuke; Nauck, Matthias; Navis, Gerjan; Nöthlings, Ute; Nolte, Ilja M.; Porteous, David J.; Pouta, Anneli; Pramstaller, Peter P.; Pullat, Janne; Ring, Susan M.; Rotter, Jerome I.; Ruggiero, Daniela; Ruokonen, Aimo; Sala, Cinzia; Samani, Nilesh J.; Sambrook, Jennifer; Schlessinger, David; Schreiber, Stefan; Schunkert, Heribert; Scott, James; Smith, Nicholas L.; Snieder, Harold; Starr, John M.; Stumvoll, Michael; Takahashi, Atsushi; Tang, W. H. Wilson; Taylor, Kent; Tenesa, Albert; Thein, Swee Lay; Tönjes, Anke; Uda, Manuela; Ulivi, Sheila; van Veldhuisen, Dirk J.; Visscher, Peter M.; Völker, Uwe; Wichmann, H.-Erich; Wiggins, Kerri L.; Willemsen, Gonneke; Yang, Tsun-Po; Zhao, Jing Hua; Zitting, Paavo; Bradley, John R.; Dedoussis, George V.; Gasparini, Paolo; Hazen, Stanley L.; Metspalu, Andres; Pirastu, Mario; Shuldiner, Alan R.; van Pelt, L. Joost; Zwaginga, Jaap-Jan; Boomsma, Dorret I.; Deary, Ian J.; Franke, Andre; Froguel, Philippe; Ganesh, Santhi K.; Jarvelin, Marjo-Riitta; Martin, Nicholas G.; Meisinger, Christa; Psaty, Bruce M.; Spector, Timothy D.; Wareham, Nicholas J.; Akkerman, Jan-Willem N.; Ciullo, Marina; Deloukas, Panos; Greinacher, Andreas; Jupe, Steve; Kamatani, Naoyuki; Khadake, Jyoti; Kooner, Jaspal S.; Penninger, Josef; Prokopenko, Inga; Stemple, Derek; Toniolo, Daniela; Wernisch, Lorenz; Sanna, Serena; Hicks, Andrew A.; Rendon, Augusto; Ferreira, Manuel A.; Ouwehand, Willem H.; Soranzo, Nicole

2012-01-01

Platelets are the second most abundant cell type in blood and are essential for maintaining haemostasis. Their count and volume are tightly controlled within narrow physiological ranges, but there is only limited understanding of the molecular processes controlling both traits. Here we carried out a high-powered meta-analysis of genome-wide association studies (GWAS) in up to 66,867 individuals of European ancestry, followed by extensive biological and functional assessment. We identified 68 genomic loci reliably associated with platelet count and volume mapping to established and putative novel regulators of megakaryopoiesis and platelet formation. These genes show megakaryocyte-specific gene expression patterns and extensive network connectivity. Using gene silencing in Danio rerio and Drosophila melanogaster, we identified 11 of the genes as novel regulators of blood cell formation. Taken together, our findings advance understanding of novel gene functions controlling fate-determining events during megakaryopoiesis and platelet formation, providing a new example of successful translation of GWAS to function. PMID:22139419

Lack of replication of previous autism spectrum disorder GWAS hits in European populations.

PubMed

Torrico, Bàrbara; Chiocchetti, Andreas G; Bacchelli, Elena; Trabetti, Elisabetta; Hervás, Amaia; Franke, Barbara; Buitelaar, Jan K; Rommelse, Nanda; Yousaf, Afsheen; Duketis, Eftichia; Freitag, Christine M; Caballero-Andaluz, Rafaela; Martinez-Mir, Amalia; Scholl, Francisco G; Ribasés, Marta; Battaglia, Agatino; Malerba, Giovanni; Delorme, Richard; Benabou, Marion; Maestrini, Elena; Bourgeron, Thomas; Cormand, Bru; Toma, Claudio

2017-02-01

Common variants contribute significantly to the genetics of autism spectrum disorder (ASD), although the identification of individual risk polymorphisms remains still elusive due to their small effect sizes and limited sample sizes available for association studies. During the last decade several genome-wide association studies (GWAS) have enabled the detection of a few plausible risk variants. The three main studies are family-based and pointed at SEMA5A (rs10513025), MACROD2 (rs4141463) and MSNP1 (rs4307059). In our study we attempted to replicate these GWAS hits using a case-control association study in five European populations of ASD patients and gender-matched controls, all Caucasians. Results showed no association of individual variants with ASD in any of the population groups considered or in the combined European sample. We performed a meta-analysis study across five European populations for rs10513025 (1,904 ASD cases and 2,674 controls), seven European populations for rs4141463 (2,855 ASD cases and 36,177 controls) and five European populations for rs4307059 (2,347 ASD cases and 2,764 controls). The results showed an odds ratio (OR) of 1.05 (95% CI = 0.84-1.32) for rs10513025, 1.0002 (95% CI = 0.93-1.08) for rs4141463 and 1.01 (95% CI = 0.92-1.1) for rs4307059, with no significant P-values (rs10513025, P = 0.73; rs4141463, P = 0.95; rs4307059, P = 0.9). No association was found when we considered either only high functioning autism (HFA), genders separately or only multiplex families. Ongoing GWAS projects with larger ASD cohorts will contribute to clarify the role of common variation in the disorder and will likely identify risk variants of modest effect not detected previously. Autism Res 2017, 10: 202-211. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Multiple Testing in the Context of Gene Discovery in Sickle Cell Disease Using Genome-Wide Association Studies.

PubMed

Kuo, Kevin H M

2017-01-01

The issue of multiple testing, also termed multiplicity, is ubiquitous in studies where multiple hypotheses are tested simultaneously. Genome-wide association study (GWAS), a type of genetic association study that has gained popularity in the past decade, is most susceptible to the issue of multiple testing. Different methodologies have been employed to address the issue of multiple testing in GWAS. The purpose of the review is to examine the methodologies employed in dealing with multiple testing in the context of gene discovery using GWAS in sickle cell disease complications.

Bioenergetics and the Epigenome: Interface between the Environment and Genes in Common Diseases

ERIC Educational Resources Information Center

Wallace, Douglas C.

2010-01-01

Extensive efforts have been directed at using genome-wide association studies (GWAS) to identify the genes responsible for common metabolic and degenerative diseases, cancer, and aging, but with limited success. While environmental factors have been evoked to explain this conundrum, the nature of these environmental factors remains unexplained.…

Identification of genomic regions associated with resistance to clinical mastitis in US Holstein cattle

USDA-ARS?s Scientific Manuscript database

The objective of this research was to identify genomic regions associated with clinical mastitis (MAST) in US Holsteins using producer-reported data. Genome-wide association studies (GWAS) were performed on deregressed PTA using GEMMA v. 0.94. Genotypes included 60,671 SNP for all predictor bulls (n...

Genome-wide association study identifies three novel loci in Fuchs endothelial corneal dystrophy

PubMed Central

Afshari, Natalie A.; Igo, Robert P.; Morris, Nathan J.; Stambolian, Dwight; Sharma, Shiwani; Pulagam, V. Lakshmi; Dunn, Steven; Stamler, John F.; Truitt, Barbara J.; Rimmler, Jacqueline; Kuot, Abraham; Croasdale, Christopher R.; Qin, Xuejun; Burdon, Kathryn P.; Riazuddin, S. Amer; Mills, Richard; Klebe, Sonja; Minear, Mollie A.; Zhao, Jiagang; Balajonda, Elmer; Rosenwasser, George O.; Baratz, Keith H; Mootha, V. Vinod; Patel, Sanjay V.; Gregory, Simon G.; Bailey-Wilson, Joan E.; Price, Marianne O.; Price, Francis W.; Craig, Jamie E.; Fingert, John H.; Gottsch, John D.; Aldave, Anthony J.; Klintworth, Gordon K.; Lass, Jonathan H.; Li, Yi-Ju; Iyengar, Sudha K.

2017-01-01

The structure of the cornea is vital to its transparency, and dystrophies that disrupt corneal organization are highly heritable. To understand the genetic aetiology of Fuchs endothelial corneal dystrophy (FECD), the most prevalent corneal disorder requiring transplantation, we conducted a genome-wide association study (GWAS) on 1,404 FECD cases and 2,564 controls of European ancestry, followed by replication and meta-analysis, for a total of 2,075 cases and 3,342 controls. We identify three novel loci meeting genome-wide significance (P<5 × 10−8): KANK4 rs79742895, LAMC1 rs3768617 and LINC00970/ATP1B1 rs1200114. We also observe an overwhelming effect of the established TCF4 locus. Interestingly, we detect differential sex-specific association at LAMC1, with greater risk in women, and TCF4, with greater risk in men. Combining GWAS results with biological evidence we expand the knowledge of common FECD loci from one to four, and provide a deeper understanding of the underlying pathogenic basis of FECD. PMID:28358029

Identification of 15 genetic loci associated with risk of major depression in individuals of European descent

PubMed Central

Hyde, Craig L.; Nagle, Mike W.; Tian, Chao; Chen, Xing; Paciga, Sara A.; Wendland, Jens R.; Tung, Joyce; Hinds, David A.; Perlis, Roy H.; Winslow, Ashley R.

2016-01-01

Despite strong evidence supporting the heritability of Major Depressive Disorder, previous genome-wide studies were unable to identify risk loci among individuals of European descent. We used self-reported data from 75,607 individuals reporting clinical diagnosis of depression and 231,747 reporting no history of depression through 23andMe, and meta-analyzed these results with published MDD GWAS results. We identified five independent variants from four regions associated with self-report of clinical diagnosis or treatment for depression. Loci with pval<1.0×10−5 in the meta-analysis were further analyzed in a replication dataset (45,773 cases and 106,354 controls) from 23andMe. A total of 17 independent SNPs from 15 regions reached genome-wide significance after joint-analysis over all three datasets. Some of these loci were also implicated in GWAS of related psychiatric traits. These studies provide evidence for large-scale consumer genomic data as a powerful and efficient complement to traditional means of ascertainment for neuropsychiatric disease genomics. PMID:27479909

Genome-wide association analysis identifies 13 new risk loci for schizophrenia.

PubMed

Ripke, Stephan; O'Dushlaine, Colm; Chambert, Kimberly; Moran, Jennifer L; Kähler, Anna K; Akterin, Susanne; Bergen, Sarah E; Collins, Ann L; Crowley, James J; Fromer, Menachem; Kim, Yunjung; Lee, Sang Hong; Magnusson, Patrik K E; Sanchez, Nick; Stahl, Eli A; Williams, Stephanie; Wray, Naomi R; Xia, Kai; Bettella, Francesco; Borglum, Anders D; Bulik-Sullivan, Brendan K; Cormican, Paul; Craddock, Nick; de Leeuw, Christiaan; Durmishi, Naser; Gill, Michael; Golimbet, Vera; Hamshere, Marian L; Holmans, Peter; Hougaard, David M; Kendler, Kenneth S; Lin, Kuang; Morris, Derek W; Mors, Ole; Mortensen, Preben B; Neale, Benjamin M; O'Neill, Francis A; Owen, Michael J; Milovancevic, Milica Pejovic; Posthuma, Danielle; Powell, John; Richards, Alexander L; Riley, Brien P; Ruderfer, Douglas; Rujescu, Dan; Sigurdsson, Engilbert; Silagadze, Teimuraz; Smit, August B; Stefansson, Hreinn; Steinberg, Stacy; Suvisaari, Jaana; Tosato, Sarah; Verhage, Matthijs; Walters, James T; Levinson, Douglas F; Gejman, Pablo V; Kendler, Kenneth S; Laurent, Claudine; Mowry, Bryan J; O'Donovan, Michael C; Owen, Michael J; Pulver, Ann E; Riley, Brien P; Schwab, Sibylle G; Wildenauer, Dieter B; Dudbridge, Frank; Holmans, Peter; Shi, Jianxin; Albus, Margot; Alexander, Madeline; Campion, Dominique; Cohen, David; Dikeos, Dimitris; Duan, Jubao; Eichhammer, Peter; Godard, Stephanie; Hansen, Mark; Lerer, F Bernard; Liang, Kung-Yee; Maier, Wolfgang; Mallet, Jacques; Nertney, Deborah A; Nestadt, Gerald; Norton, Nadine; O'Neill, Francis A; Papadimitriou, George N; Ribble, Robert; Sanders, Alan R; Silverman, Jeremy M; Walsh, Dermot; Williams, Nigel M; Wormley, Brandon; Arranz, Maria J; Bakker, Steven; Bender, Stephan; Bramon, Elvira; Collier, David; Crespo-Facorro, Benedicto; Hall, Jeremy; Iyegbe, Conrad; Jablensky, Assen; Kahn, Rene S; Kalaydjieva, Luba; Lawrie, Stephen; Lewis, Cathryn M; Lin, Kuang; Linszen, Don H; Mata, Ignacio; McIntosh, Andrew; Murray, Robin M; Ophoff, Roel A; Powell, John; Rujescu, Dan; Van Os, Jim; Walshe, Muriel; Weisbrod, Matthias; Wiersma, Durk; Donnelly, Peter; Barroso, Ines; Blackwell, Jenefer M; Bramon, Elvira; Brown, Matthew A; Casas, Juan P; Corvin, Aiden P; Deloukas, Panos; Duncanson, Audrey; Jankowski, Janusz; Markus, Hugh S; Mathew, Christopher G; Palmer, Colin N A; Plomin, Robert; Rautanen, Anna; Sawcer, Stephen J; Trembath, Richard C; Viswanathan, Ananth C; Wood, Nicholas W; Spencer, Chris C A; Band, Gavin; Bellenguez, Céline; Freeman, Colin; Hellenthal, Garrett; Giannoulatou, Eleni; Pirinen, Matti; Pearson, Richard D; Strange, Amy; Su, Zhan; Vukcevic, Damjan; Donnelly, Peter; Langford, Cordelia; Hunt, Sarah E; Edkins, Sarah; Gwilliam, Rhian; Blackburn, Hannah; Bumpstead, Suzannah J; Dronov, Serge; Gillman, Matthew; Gray, Emma; Hammond, Naomi; Jayakumar, Alagurevathi; McCann, Owen T; Liddle, Jennifer; Potter, Simon C; Ravindrarajah, Radhi; Ricketts, Michelle; Tashakkori-Ghanbaria, Avazeh; Waller, Matthew J; Weston, Paul; Widaa, Sara; Whittaker, Pamela; Barroso, Ines; Deloukas, Panos; Mathew, Christopher G; Blackwell, Jenefer M; Brown, Matthew A; Corvin, Aiden P; McCarthy, Mark I; Spencer, Chris C A; Bramon, Elvira; Corvin, Aiden P; O'Donovan, Michael C; Stefansson, Kari; Scolnick, Edward; Purcell, Shaun; McCarroll, Steven A; Sklar, Pamela; Hultman, Christina M; Sullivan, Patrick F

2013-10-01

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

Impact of exome sequencing in inflammatory bowel disease

PubMed Central

Cardinale, Christopher J; Kelsen, Judith R; Baldassano, Robert N; Hakonarson, Hakon

2013-01-01

Approaches to understanding the genetic contribution to inflammatory bowel disease (IBD) have continuously evolved from family- and population-based epidemiology, to linkage analysis, and most recently, to genome-wide association studies (GWAS). The next stage in this evolution seems to be the sequencing of the exome, that is, the regions of the human genome which encode proteins. The GWAS approach has been very fruitful in identifying at least 163 loci as being associated with IBD, and now, exome sequencing promises to take our genetic understanding to the next level. In this review we will discuss the possible contributions that can be made by an exome sequencing approach both at the individual patient level to aid with disease diagnosis and future therapies, as well as in advancing knowledge of the pathogenesis of IBD. PMID:24187447

Convergence between biological, behavioural and genetic determinants of obesity.

PubMed

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.

Meta-dimensional data integration identifies critical pathways for susceptibility, tumorigenesis and progression of endometrial cancer.

PubMed

Wei, Runmin; De Vivo, Immaculata; Huang, Sijia; Zhu, Xun; Risch, Harvey; Moore, Jason H; Yu, Herbert; Garmire, Lana X

2016-08-23

Endometrial Cancer (EC) is one of the most common female cancers. Genome-wide association studies (GWAS) have been investigated to identify genetic polymorphisms that are predictive of EC risks. Here we utilized a meta-dimensional integrative approach to seek genetically susceptible pathways that may be associated with tumorigenesis and progression of EC. We analyzed GWAS data obtained from Connecticut Endometrial Cancer Study (CECS) and identified the top 20 EC susceptible pathways. To further verify the significance of top 20 EC susceptible pathways, we conducted pathway-level multi-omics analyses using EC exome-Seq, RNA-Seq and survival data, all based on The Cancer Genome Atlas (TCGA) samples. We measured the overall consistent rankings of these pathways in all four data types. Some well-studied pathways, such as p53 signaling and cell cycle pathways, show consistently high rankings across different analyses. Additionally, other cell signaling pathways (e.g. IGF-1/mTOR, rac-1 and IL-5 pathway), genetic information processing pathway (e.g. homologous recombination) and metabolism pathway (e.g. sphingolipid metabolism) are also highly associated with EC risks, diagnosis and prognosis. In conclusion, the meta-dimensional integration of EC cohorts has suggested some common pathways that may be associated from predisposition, tumorigenesis to progression.

Multispecies, Integrative GWAS for Focal Segmental Glomerulosclerosis

DTIC Science & Technology

2017-09-01

project are to identify genetic determinants of focal segmental glomerulosclerosis (FSGS) using genomewide association studies in mouse strains. We have... methodology used shall be provided. As the project progresses to completion, the emphasis in reporting in this section should shift from reporting...development” activities result in increased knowledge or skill in one’s area of expertise and may include workshops, conferences, seminars, study

A genome-wide association study of production traits in a commercial population of Large White pigs: evidence of haplotypes affecting meat quality

PubMed Central

2014-01-01

Background Numerous quantitative trait loci (QTL) have been detected in pigs over the past 20 years using microsatellite markers. However, due to the low density of these markers, the accuracy of QTL location has generally been poor. Since 2009, the dense genome coverage provided by the Illumina PorcineSNP60 BeadChip has made it possible to more accurately map QTL using genome-wide association studies (GWAS). Our objective was to perform high-density GWAS in order to identify genomic regions and corresponding haplotypes associated with production traits in a French Large White population of pigs. Methods Animals (385 Large White pigs from 106 sires) were genotyped using the PorcineSNP60 BeadChip and evaluated for 19 traits related to feed intake, growth, carcass composition and meat quality. Of the 64 432 SNPs on the chip, 44 412 were used for GWAS with an animal mixed model that included a regression coefficient for the tested SNPs and a genomic kinship matrix. SNP haplotype effects in QTL regions were then tested for association with phenotypes following phase reconstruction based on the Sscrofa10.2 pig genome assembly. Results Twenty-three QTL regions were identified on autosomes and their effects ranged from 0.25 to 0.75 phenotypic standard deviation units for feed intake and feed efficiency (four QTL), carcass (12 QTL) and meat quality traits (seven QTL). The 10 most significant QTL regions had effects on carcass (chromosomes 7, 10, 16, 17 and 18) and meat quality traits (two regions on chromosome 1 and one region on chromosomes 8, 9 and 13). Thirteen of the 23 QTL regions had not been previously described. A haplotype block of 183 kb on chromosome 1 (six SNPs) was identified and displayed three distinct haplotypes with significant (0.0001 < P < 0.03) associations with all evaluated meat quality traits. Conclusions GWAS analyses with the PorcineSNP60 BeadChip enabled the detection of 23 QTL regions that affect feed consumption, carcass and meat quality traits in a LW population, of which 13 were novel QTL. The proportionally larger number of QTL found for meat quality traits suggests a specific opportunity for improving these traits in the pig by genomic selection. PMID:24528607

An integrated analysis of genes and functional pathways for aggression in human and rodent models.

PubMed

Zhang-James, Yanli; Fernàndez-Castillo, Noèlia; Hess, Jonathan L; Malki, Karim; Glatt, Stephen J; Cormand, Bru; Faraone, Stephen V

2018-06-01

Human genome-wide association studies (GWAS), transcriptome analyses of animal models, and candidate gene studies have advanced our understanding of the genetic architecture of aggressive behaviors. However, each of these methods presents unique limitations. To generate a more confident and comprehensive view of the complex genetics underlying aggression, we undertook an integrated, cross-species approach. We focused on human and rodent models to derive eight gene lists from three main categories of genetic evidence: two sets of genes identified in GWAS studies, four sets implicated by transcriptome-wide studies of rodent models, and two sets of genes with causal evidence from online Mendelian inheritance in man (OMIM) and knockout (KO) mice reports. These gene sets were evaluated for overlap and pathway enrichment to extract their similarities and differences. We identified enriched common pathways such as the G-protein coupled receptor (GPCR) signaling pathway, axon guidance, reelin signaling in neurons, and ERK/MAPK signaling. Also, individual genes were ranked based on their cumulative weights to quantify their importance as risk factors for aggressive behavior, which resulted in 40 top-ranked and highly interconnected genes. The results of our cross-species and integrated approach provide insights into the genetic etiology of aggression.

Identification and Evolutionary Analysis of Potential Candidate Genes in a Human Eating Disorder.

PubMed

Sabbagh, Ubadah; Mullegama, Saman; Wyckoff, Gerald J

2016-01-01

The purpose of this study was to find genes linked with eating disorders and associated with both metabolic and neural systems. Our operating hypothesis was that there are genetic factors underlying some eating disorders resting in both those pathways. Specifically, we are interested in disorders that may rest in both sleep and metabolic function, generally called Night Eating Syndrome (NES). A meta-analysis of the Gene Expression Omnibus targeting the mammalian nervous system, sleep, and obesity studies was performed, yielding numerous genes of interest. Through a text-based analysis of the results, a number of potential candidate genes were identified. VGF, in particular, appeared to be relevant both to obesity and, broadly, to brain or neural development. VGF is a highly connected protein that interacts with numerous targets via proteolytically digested peptides. We examined VGF from an evolutionary perspective to determine whether other available evidence supported a role for the gene in human disease. We conclude that some of the already identified variants in VGF from human polymorphism studies may contribute to eating disorders and obesity. Our data suggest that there is enough evidence to warrant eGWAS and GWAS analysis of these genes in NES patients in a case-control study.

Genetic variants near MLST8 and DHX57 affect the epigenetic age of the cerebellum

NASA Astrophysics Data System (ADS)

Lu, Ake T.; Hannon, Eilis; Levine, Morgan E.; Hao, Ke; Crimmins, Eileen M.; Lunnon, Katie; Kozlenkov, Alexey; Mill, Jonathan; Dracheva, Stella; Horvath, Steve

2016-02-01

DNA methylation (DNAm) levels lend themselves for defining an epigenetic biomarker of aging known as the `epigenetic clock'. Our genome-wide association study (GWAS) of cerebellar epigenetic age acceleration identifies five significant (P<5.0 × 10-8) SNPs in two loci: 2p22.1 (inside gene DHX57) and 16p13.3 near gene MLST8 (a subunit of mTOR complex 1 and 2). We find that the SNP in 16p13.3 has a cis-acting effect on the expression levels of MLST8 (P=6.9 × 10-18) in most brain regions. In cerebellar samples, the SNP in 2p22.1 has a cis-effect on DHX57 (P=4.4 × 10-5). Gene sets found by our GWAS analysis of cerebellar age acceleration exhibit significant overlap with those of Alzheimer's disease (P=4.4 × 10-15), age-related macular degeneration (P=6.4 × 10-6), and Parkinson's disease (P=2.6 × 10-4). Overall, our results demonstrate the utility of a new paradigm for understanding aging and age-related diseases: it will be fruitful to use epigenetic tissue age as endophenotype in GWAS.

Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations

PubMed Central

Vallejo, Roger L.; Liu, Sixin; Gao, Guangtu; Fragomeni, Breno O.; Hernandez, Alvaro G.; Leeds, Timothy D.; Parsons, James E.; Martin, Kyle E.; Evenhuis, Jason P.; Welch, Timothy J.; Wiens, Gregory D.; Palti, Yniv

2017-01-01

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect quantitative trait loci (QTL) for BCWD resistance in rainbow trout (Oncorhynchus mykiss). However, the recent availability of a 57 K SNP array and a reference genome assembly have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57 K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57 K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered. PMID:29109734

Similar Genetic Architecture with Shared and Unique Quantitative Trait Loci for Bacterial Cold Water Disease Resistance in Two Rainbow Trout Breeding Populations.

PubMed

Vallejo, Roger L; Liu, Sixin; Gao, Guangtu; Fragomeni, Breno O; Hernandez, Alvaro G; Leeds, Timothy D; Parsons, James E; Martin, Kyle E; Evenhuis, Jason P; Welch, Timothy J; Wiens, Gregory D; Palti, Yniv

2017-01-01

Bacterial cold water disease (BCWD) causes significant mortality and economic losses in salmonid aquaculture. In previous studies, we identified moderate-large effect quantitative trait loci (QTL) for BCWD resistance in rainbow trout ( Oncorhynchus mykiss ). However, the recent availability of a 57 K SNP array and a reference genome assembly have enabled us to conduct genome-wide association studies (GWAS) that overcome several experimental limitations from our previous work. In the current study, we conducted GWAS for BCWD resistance in two rainbow trout breeding populations using two genotyping platforms, the 57 K Affymetrix SNP array and restriction-associated DNA (RAD) sequencing. Overall, we identified 14 moderate-large effect QTL that explained up to 60.8% of the genetic variance in one of the two populations and 27.7% in the other. Four of these QTL were found in both populations explaining a substantial proportion of the variance, although major differences were also detected between the two populations. Our results confirm that BCWD resistance is controlled by the oligogenic inheritance of few moderate-large effect loci and a large-unknown number of loci each having a small effect on BCWD resistance. We detected differences in QTL number and genome location between two GWAS models (weighted single-step GBLUP and Bayes B), which highlights the utility of using different models to uncover QTL. The RAD-SNPs detected a greater number of QTL than the 57 K SNP array in one population, suggesting that the RAD-SNPs may uncover polymorphisms that are more unique and informative for the specific population in which they were discovered.

Genome-Wide Association Study among Four Horse Breeds Identifies a Common Haplotype Associated with In Vitro CD3+ T Cell Susceptibility/Resistance to Equine Arteritis Virus Infection ▿

PubMed Central

Go, Yun Young; Bailey, Ernest; Cook, Deborah G.; Coleman, Stephen J.; MacLeod, James N.; Chen, Kuey-Chu; Timoney, Peter J.; Balasuriya, Udeni B. R.

2011-01-01

Previously, we have shown that horses could be divided into susceptible and resistant groups based on an in vitro assay using dual-color flow cytometric analysis of CD3+ T cells infected with equine arteritis virus (EAV). Here, we demonstrate that the differences in in vitro susceptibility of equine CD3+ T lymphocytes to EAV infection have a genetic basis. To investigate the possible hereditary basis for this trait, we conducted a genome-wide association study (GWAS) to compare susceptible and resistant phenotypes. Testing of 267 DNA samples from four horse breeds that had a susceptible or a resistant CD3+ T lymphocyte phenotype using both Illumina Equine SNP50 BeadChip and Sequenom's MassARRAY system identified a common, genetically dominant haplotype associated with the susceptible phenotype in a region of equine chromosome 11 (ECA11), positions 49572804 to 49643932. The presence of a common haplotype indicates that the trait occurred in a common ancestor of all four breeds, suggesting that it may be segregated among other modern horse breeds. Biological pathway analysis revealed several cellular genes within this region of ECA11 encoding proteins associated with virus attachment and entry, cytoskeletal organization, and NF-κB pathways that may be associated with the trait responsible for the in vitro susceptibility/resistance of CD3+ T lymphocytes to EAV infection. The data presented in this study demonstrated a strong association of genetic markers with the trait, representing de facto proof that the trait is under genetic control. To our knowledge, this is the first GWAS of an equine infectious disease and the first GWAS of equine viral arteritis. PMID:21994447

Genetic variation predicting cisplatin cytotoxicity associated with overall survival in lung cancer patients receiving platinum-based chemotherapy †, ‡

PubMed Central

Tan, Xiang-Lin; Moyer, Ann M.; Fridley, Brooke L.; Schaid, Daniel J.; Niu, Nifang; Batzler, Anthony J.; Jenkins, Gregory D.; Abo, Ryan P.; Li, Liang; Cunningham, Julie M.; Sun, Zhifu; Yang, Ping; Wang, Liewei

2011-01-01

Purpose Inherited variability in the prognosis of lung cancer patients treated with platinum-based chemotherapy has been widely investigated. However, the overall contribution of genetic variation to platinum response is not well established. To identify novel candidate SNPs/genes, we performed a genome-wide association study (GWAS) for cisplatin cytotoxicity using lymphoblastoid cell lines (LCLs), followed by an association study of selected SNPs from the GWAS with overall survival (OS) in lung cancer patients. Experimental Design GWAS for cisplatin were performed with 283 ethnically diverse LCLs. 168 top SNPs were genotyped in 222 small cell and 961 non-small cell lung cancer (SCLC, NSCLC) patients treated with platinum-based therapy. Association of the SNPs with OS was determined using the Cox regression model. Selected candidate genes were functionally validated by siRNA knockdown in human lung cancer cells. Results Among 157 successfully genotyped SNPs, 9 and 10 SNPs were top SNPs associated with OS for patients with NSCLC and SCLC, respectively, although they were not significant after adjusting for multiple testing. Fifteen genes, including 7 located within 200 kb up or downstream of the four top SNPs and 8 genes for which expression was correlated with three SNPs in LCLs were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which expression levels were correlated with the rs11169748 and rs2440915 SNPs, significantly decreased cisplatin sensitivity in lung cancer cells. Conclusions This series of clinical and complementary laboratory-based functional studies identified several candidate genes/SNPs that might help predict treatment outcomes for platinum-based therapy of lung cancer. PMID:21775533

Genome-wide association study of caffeine metabolites provides new insights to caffeine metabolism and dietary caffeine-consumption behavior.

PubMed

Cornelis, Marilyn C; Kacprowski, Tim; Menni, Cristina; Gustafsson, Stefan; Pivin, Edward; Adamski, Jerzy; Artati, Anna; Eap, Chin B; Ehret, Georg; Friedrich, Nele; Ganna, Andrea; Guessous, Idris; Homuth, Georg; Lind, Lars; Magnusson, Patrik K; Mangino, Massimo; Pedersen, Nancy L; Pietzner, Maik; Suhre, Karsten; Völzke, Henry; Bochud, Murielle; Spector, Tim D; Grabe, Hans J; Ingelsson, Erik

2016-12-15

Caffeine is the most widely consumed psychoactive substance in the world and presents with wide interindividual variation in metabolism. This variation may modify potential adverse or beneficial effects of caffeine on health. We conducted a genome-wide association study (GWAS) of plasma caffeine, paraxanthine, theophylline, theobromine and paraxanthine/caffeine ratio among up to 9,876 individuals of European ancestry from six population-based studies. A single SNP at 6p23 (near CD83) and several SNPs at 7p21 (near AHR), 15q24 (near CYP1A2) and 19q13.2 (near CYP2A6) met GW-significance (P < 5 × 10-8) and were associated with one or more metabolites. Variants at 7p21 and 15q24 associated with higher plasma caffeine and lower plasma paraxanthine/caffeine (slow caffeine metabolism) were previously associated with lower coffee and caffeine consumption behavior in GWAS. Variants at 19q13.2 associated with higher plasma paraxanthine/caffeine (slow paraxanthine metabolism) were also associated with lower coffee consumption in the UK Biobank (n = 94 343, P < 1.0 × 10-6). Variants at 2p24 (in GCKR), 4q22 (in ABCG2) and 7q11.23 (near POR) that were previously associated with coffee consumption in GWAS were nominally associated with plasma caffeine or its metabolites. Taken together, we have identified genetic factors contributing to variation in caffeine metabolism and confirm an important modulating role of systemic caffeine levels in dietary caffeine consumption behavior. Moreover, candidate genes identified encode proteins with important clinical functions that extend beyond caffeine metabolism. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Leveraging cell type specific regulatory regions to detect SNPs associated with tissue factor pathway inhibitor plasma levels.

PubMed

Dennis, Jessica; Medina-Rivera, Alejandra; Truong, Vinh; Antounians, Lina; Zwingerman, Nora; Carrasco, Giovana; Strug, Lisa; Wells, Phil; Trégouët, David-Alexandre; Morange, Pierre-Emmanuel; Wilson, Michael D; Gagnon, France

2017-07-01

Tissue factor pathway inhibitor (TFPI) regulates the formation of intravascular blood clots, which manifest clinically as ischemic heart disease, ischemic stroke, and venous thromboembolism (VTE). TFPI plasma levels are heritable, but the genetics underlying TFPI plasma level variability are poorly understood. Herein we report the first genome-wide association scan (GWAS) of TFPI plasma levels, conducted in 251 individuals from five extended French-Canadian Families ascertained on VTE. To improve discovery, we also applied a hypothesis-driven (HD) GWAS approach that prioritized single nucleotide polymorphisms (SNPs) in (1) hemostasis pathway genes, and (2) vascular endothelial cell (EC) regulatory regions, which are among the highest expressers of TFPI. Our GWAS identified 131 SNPs with suggestive evidence of association (P-value < 5 × 10 -8 ), but no SNPs reached the genome-wide threshold for statistical significance. Hemostasis pathway genes were not enriched for TFPI plasma level associated SNPs (global hypothesis test P-value = 0.147), but EC regulatory regions contained more TFPI plasma level associated SNPs than expected by chance (global hypothesis test P-value = 0.046). We therefore stratified our genome-wide SNPs, prioritizing those in EC regulatory regions via stratified false discovery rate (sFDR) control, and reranked the SNPs by q-value. The minimum q-value was 0.27, and the top-ranked SNPs did not show association evidence in the MARTHA replication sample of 1,033 unrelated VTE cases. Although this study did not result in new loci for TFPI, our work lays out a strategy to utilize epigenomic data in prioritization schemes for future GWAS studies. © 2017 WILEY PERIODICALS, INC.

Assessing the value of phenotypic information from non-genotyped animals for QTL mapping of complex traits in real and simulated populations.

PubMed

Melo, Thaise P; Takada, Luciana; Baldi, Fernando; Oliveira, Henrique N; Dias, Marina M; Neves, Haroldo H R; Schenkel, Flavio S; Albuquerque, Lucia G; Carvalheiro, Roberto

2016-06-21

QTL mapping through genome-wide association studies (GWAS) is challenging, especially in the case of low heritability complex traits and when few animals possess genotypic and phenotypic information. When most of the phenotypic information is from non-genotyped animals, GWAS can be performed using the weighted single-step GBLUP (WssGBLUP) method, which permits to combine all available information, even that of non-genotyped animals. However, it is not clear to what extent phenotypic information from non-genotyped animals increases the power of QTL detection, and whether factors such as the extent of linkage disequilibrium (LD) in the population and weighting SNPs in WssGBLUP affect the importance of using information from non-genotyped animals in GWAS. These questions were investigated in this study using real and simulated data. Analysis of real data showed that the use of phenotypes of non-genotyped animals affected SNP effect estimates and, consequently, QTL mapping. Despite some coincidence, the most important genomic regions identified by the analyses, either using or ignoring phenotypes of non-genotyped animals, were not the same. The simulation results indicated that the inclusion of all available phenotypic information, even that of non-genotyped animals, tends to improve QTL detection for low heritability complex traits. For populations with low levels of LD, this trend of improvement was less pronounced. Stronger shrinkage on SNPs explaining lower variance was not necessarily associated with better QTL mapping. The use of phenotypic information from non-genotyped animals in GWAS may improve the ability to detect QTL for low heritability complex traits, especially in populations in which the level of LD is high.

Combination Testing Using a Single MSH5 Variant alongside HLA Haplotypes Improves the Sensitivity of Predicting Coeliac Disease Risk in the Polish Population.

PubMed

Paziewska, Agnieszka; Cukrowska, Bozena; Dabrowska, Michalina; Goryca, Krzysztof; Piatkowska, Magdalena; Kluska, Anna; Mikula, Michal; Karczmarski, Jakub; Oralewska, Beata; Rybak, Anna; Socha, Jerzy; Balabas, Aneta; Zeber-Lubecka, Natalia; Ambrozkiewicz, Filip; Konopka, Ewa; Trojanowska, Ilona; Zagroba, Malgorzata; Szperl, Malgorzata; Ostrowski, Jerzy

2015-01-01

Assessment of non-HLA variants alongside standard HLA testing was previously shown to improve the identification of potential coeliac disease (CD) patients. We intended to identify new genetic variants associated with CD in the Polish population that would improve CD risk prediction when used alongside HLA haplotype analysis. DNA samples of 336 CD and 264 unrelated healthy controls were used to create DNA pools for a genome wide association study (GWAS). GWAS findings were validated with individual HLA tag single nucleotide polymorphism (SNP) typing of 473 patients and 714 healthy controls. Association analysis using four HLA-tagging SNPs showed that, as was found in other populations, positive predicting genotypes (HLA-DQ2.5/DQ2.5, HLA-DQ2.5/DQ2.2, and HLA-DQ2.5/DQ8) were found at higher frequencies in CD patients than in healthy control individuals in the Polish population. Both CD-associated SNPs discovered by GWAS were found in the CD susceptibility region, confirming the previously-determined association of the major histocompatibility (MHC) region with CD pathogenesis. The two most significant SNPs from the GWAS were rs9272346 (HLA-dependent; localized within 1 Kb of DQA1) and rs3130484 (HLA-independent; mapped to MSH5). Specificity of CD prediction using the four HLA-tagging SNPs achieved 92.9%, but sensitivity was only 45.5%. However, when a testing combination of the HLA-tagging SNPs and the MSH5 SNP was used, specificity decreased to 80%, and sensitivity increased to 74%. This study confirmed that improvement of CD risk prediction sensitivity could be achieved by including non-HLA SNPs alongside HLA SNPs in genetic testing.

A Genome-Wide Identified Risk Variant for PTSD is a Methylation Quantitative Trait Locus and Confers Decreased Cortical Activation to Fearful Faces

DTIC Science & Technology

2015-05-18

Department of Defense; Grant numbers: W81XWH-09-2-0044, W911NF-09-1-0298; Grant sponsor: Emory and Grady Memorial Hospital General Clinical Research...TERMS GWAS; PTSD; fMRI ; meQTL; epigenetic 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18. NUMBER OF PAGES 10...that contribute to this disorder. 2015 Wiley Periodicals, Inc. Key words: GWAS; PTSD; fMRI ; meQTL; epigenetic INTRODUCTION Although post-traumatic

An update on the genetics of hyperuricaemia and gout.

PubMed

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.

Genome Wide Association Study of Seedling and Adult Plant Leaf Rust Resistance in Elite Spring Wheat Breeding Lines.

PubMed

Gao, Liangliang; Turner, M Kathryn; Chao, Shiaoman; Kolmer, James; Anderson, James A

2016-01-01

Leaf rust is an important disease, threatening wheat production annually. Identification of resistance genes or QTLs for effective field resistance could greatly enhance our ability to breed durably resistant varieties. We applied a genome wide association study (GWAS) approach to identify resistance genes or QTLs in 338 spring wheat breeding lines from public and private sectors that were predominately developed in the Americas. A total of 46 QTLs were identified for field and seedling traits and approximately 20-30 confer field resistance in varying degrees. The 10 QTLs accounting for the most variation in field resistance explained 26-30% of the total variation (depending on traits: percent severity, coefficient of infection or response type). Similarly, the 10 QTLs accounting for most of the variation in seedling resistance to different races explained 24-34% of the variation, after correcting for population structure. Two potentially novel QTLs (QLr.umn-1AL, QLr.umn-4AS) were identified. Identification of novel genes or QTLs and validation of previously identified genes or QTLs for seedling and especially adult plant resistance will enhance understanding of leaf rust resistance and assist breeding for resistant wheat varieties. We also developed computer programs to automate field and seedling rust phenotype data conversions. This is the first GWAS study of leaf rust resistance in elite wheat breeding lines genotyped with high density 90K SNP arrays.

Genome-Wide Associations and Functional Genomic Studies of Musculoskeletal Adverse Events in Women Receiving Aromatase Inhibitors

PubMed Central

Ingle, James N.; Schaid, Daniel J.; Goss, Paul E.; Liu, Mohan; Mushiroda, Taisei; Chapman, Judy-Anne W.; Kubo, Michiaki; Jenkins, Gregory D.; Batzler, Anthony; Shepherd, Lois; Pater, Joseph; Wang, Liewei; Ellis, Matthew J.; Stearns, Vered; Rohrer, Daniel C.; Goetz, Matthew P.; Pritchard, Kathleen I.; Flockhart, David A.; Nakamura, Yusuke; Weinshilboum, Richard M.

2010-01-01

Purpose We performed a case-control genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) associated with musculoskeletal adverse events (MS-AEs) in women treated with aromatase inhibitors (AIs) for early breast cancer. Patients and Methods A nested case-control design was used to select patients enrolled onto the MA.27 phase III trial comparing anastrozole with exemestane. Cases were matched to two controls and were defined as patients with grade 3 or 4 MS-AEs (according to the National Cancer Institute's Common Terminology Criteria for Adverse Events v3.0) or those who discontinued treatment for any grade of MS-AE within the first 2 years. Genotyping was performed with the Illumina Human610-Quad BeadChip. Results The GWAS included 293 cases and 585 controls. A total of 551,358 SNPs were analyzed, followed by imputation and fine mapping of a region of interest on chromosome 14. Four SNPs on chromosome 14 had the lowest P values (2.23E-06 to 6.67E-07). T-cell leukemia 1A (TCL1A) was the gene closest (926-7000 bp) to the four SNPs. Functional genomic studies revealed that one of these SNPs (rs11849538) created an estrogen response element and that TCL1A expression was estrogen dependent, was associated with the variant SNP genotypes in estradiol-treated lymphoblastoid cells transfected with estrogen receptor alpha and was directly related to interleukin 17 receptor A (IL17RA) expression. Conclusion This GWAS identified SNPs associated with MS-AEs in women treated with AIs and with a gene (TCL1A) which, in turn, was related to a cytokine (IL17). These findings provide a focus for further research to identify patients at risk for MS-AEs and to explore the mechanisms for these adverse events. PMID:20876420

Genome-wide association study of Alzheimer's disease.

PubMed

Kamboh, M I; Demirci, F Y; Wang, X; Minster, R L; Carrasquillo, M M; Pankratz, V S; Younkin, S G; Saykin, A J; Jun, G; Baldwin, C; Logue, M W; Buros, J; Farrer, L; Pericak-Vance, M A; Haines, J L; Sweet, R A; Ganguli, M; Feingold, E; Dekosky, S T; Lopez, O L; Barmada, M M

2012-05-15

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer's disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer's disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ~2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69-180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P = 3.05E-07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples.

Genome-wide association study of Alzheimer's disease

PubMed Central

Kamboh, M I; Demirci, F Y; Wang, X; Minster, R L; Carrasquillo, M M; Pankratz, V S; Younkin, S G; Saykin, A J; Jun, G; Baldwin, C; Logue, M W; Buros, J; Farrer, L; Pericak-Vance, M A; Haines, J L; Sweet, R A; Ganguli, M; Feingold, E; DeKosky, S T; Lopez, O L; Barmada, M M

2012-01-01

In addition to apolipoprotein E (APOE), recent large genome-wide association studies (GWASs) have identified nine other genes/loci (CR1, BIN1, CLU, PICALM, MS4A4/MS4A6E, CD2AP, CD33, EPHA1 and ABCA7) for late-onset Alzheimer's disease (LOAD). However, the genetic effect attributable to known loci is about 50%, indicating that additional risk genes for LOAD remain to be identified. In this study, we have used a new GWAS data set from the University of Pittsburgh (1291 cases and 938 controls) to examine in detail the recently implicated nine new regions with Alzheimer's disease (AD) risk, and also performed a meta-analysis utilizing the top 1% GWAS single-nucleotide polymorphisms (SNPs) with P<0.01 along with four independent data sets (2727 cases and 3336 controls) for these SNPs in an effort to identify new AD loci. The new GWAS data were generated on the Illumina Omni1-Quad chip and imputed at ∼2.5 million markers. As expected, several markers in the APOE regions showed genome-wide significant associations in the Pittsburg sample. While we observed nominal significant associations (P<0.05) either within or adjacent to five genes (PICALM, BIN1, ABCA7, MS4A4/MS4A6E and EPHA1), significant signals were observed 69–180 kb outside of the remaining four genes (CD33, CLU, CD2AP and CR1). Meta-analysis on the top 1% SNPs revealed a suggestive novel association in the PPP1R3B gene (top SNP rs3848140 with P=3.05E–07). The association of this SNP with AD risk was consistent in all five samples with a meta-analysis odds ratio of 2.43. This is a potential candidate gene for AD as this is expressed in the brain and is involved in lipid metabolism. These findings need to be confirmed in additional samples. PMID:22832961

Ancestry-specific and sex-specific risk alleles identified in a genome-wide gene-by-alcohol dependence interaction study of risky sexual behaviors.

PubMed

Polimanti, Renato; Zhao, Hongyu; Farrer, Lindsay A; Kranzler, Henry R; Gelernter, Joel

2017-12-01

We previously mapped loci for the genome-wide association studies (GWAS) and genome-wide gene-by-alcohol dependence interaction (GW-GxAD) analyses of risky sexual behaviors (RSB). This study extends those findings by analyzing the ancestry- and sex-specific AD-stratified effects on RSB. We examined the concordance of findings for the AD-stratified GWAS and the GW-GxAD analysis of RSB, with concordance defined as genome-wide significance in one analysis and at least nominal significance in the second analysis. A total of 2,173 African-American (AA) and 1,751 European-American (EA) subjects were investigated. Information regarding RSB (lifetime experiences of unprotected sex and multiple sexual partners) and DSM-IV diagnosis of lifetime AD were derived from the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA). In our ancestry- and sex-specific analyses, we identified four independent genome-wide significant (GWS) loci (p < 5*10 -8 ) and one suggestive locus (p < 6*10 -8 ). In men, we observed a GWS signal in FAM162A (rs2002594, p = 4.96*10 -8 ). In women, there was a suggestive locus in PLGRKT (rs3824435, p = 5.52*10 -8 ). In AAs, there was a GWS signal in GRK5 (rs1316543, p = 1.25*10 -9 ). In AA men, we observed an intergenic GWS signal (rs12898370, p = 4.49*10 -8 ) near LINGO1. In EA men, there was a GWS signal in CCSER1 (rs62313897; p = 7.93*10 -10 ). The loci identified in this GWAS implicate molecular mechanisms related to psychiatric illness and personality features, suggesting that the interplay between AD and RSB is mediated by alleles associated with behavioral traits. © 2017 Wiley Periodicals, Inc.

A Combined Pathway and Regional Heritability Analysis Indicates NETRIN1 Pathway Is Associated With Major Depressive Disorder.

PubMed

Zeng, Yanni; Navarro, Pau; Fernandez-Pujals, Ana M; Hall, Lynsey S; Clarke, Toni-Kim; Thomson, Pippa A; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Wray, Naomi R; Deary, Ian J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

2017-02-15

Genome-wide association studies (GWASs) of major depressive disorder (MDD) have identified few significant associations. Testing the aggregation of genetic variants, in particular biological pathways, may be more powerful. Regional heritability analysis can be used to detect genomic regions that contribute to disease risk. We integrated pathway analysis and multilevel regional heritability analyses in a pipeline designed to identify MDD-associated pathways. The pipeline was applied to two independent GWAS samples [Generation Scotland: The Scottish Family Health Study (GS:SFHS, N = 6455) and Psychiatric Genomics Consortium (PGC:MDD) (N = 18,759)]. A polygenic risk score (PRS) composed of single nucleotide polymorphisms from the pathway most consistently associated with MDD was created, and its accuracy to predict MDD, using area under the curve, logistic regression, and linear mixed model analyses, was tested. In GS:SFHS, four pathways were significantly associated with MDD, and two of these explained a significant amount of pathway-level regional heritability. In PGC:MDD, one pathway was significantly associated with MDD. Pathway-level regional heritability was significant in this pathway in one subset of PGC:MDD. For both samples the regional heritabilities were further localized to the gene and subregion levels. The NETRIN1 signaling pathway showed the most consistent association with MDD across the two samples. PRSs from this pathway showed competitive predictive accuracy compared with the whole-genome PRSs when using area under the curve statistics, logistic regression, and linear mixed model. These post-GWAS analyses highlight the value of combining multiple methods on multiple GWAS data for the identification of risk pathways for MDD. The NETRIN1 signaling pathway is identified as a candidate pathway for MDD and should be explored in further large population studies. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals.

PubMed

Coleman, Jonathan R I; Bryois, Julien; Gaspar, Héléna A; Jansen, Philip R; Savage, Jeanne E; Skene, Nathan; Plomin, Robert; Muñoz-Manchado, Ana B; Linnarsson, Sten; Crawford, Greg; Hjerling-Leffler, Jens; Sullivan, Patrick F; Posthuma, Danielle; Breen, Gerome

2018-03-08

Variance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with a study comparing 1247 individuals with mean IQ ~170 to 8185 controls. Genes associated with intelligence implicate pyramidal neurons of the somatosensory cortex and CA1 region of the hippocampus, and midbrain embryonic GABAergic neurons. Tissue-specific analyses find the most significant enrichment for frontal cortex brain expressed genes. These results suggest specific neuronal cell types and genes may be involved in intelligence and provide new hypotheses for neuroscience experiments using model systems.

A genome-wide investigation of food addiction.

PubMed

Cornelis, Marilyn C; Flint, Alan; Field, Alison E; Kraft, Peter; Han, Jiali; Rimm, Eric B; van Dam, Rob M

2016-06-01

Evidence of parallels between drug addiction and eating behavior continues to accumulate. Genetic studies of addictive substances have yielded a number of susceptibility loci that point to common higher order genetic pathways underlying addiction. It was hypothesized that a genome-wide association study (GWAS) of food addiction would yield significant enrichment in genes and pathways linked to addiction. A GWAS of food addiction, determined by the modified Yale Food Addiction Scale (mYFAS), was conducted among 9,314 women of European ancestry, and results for enrichment of single-nucleotide polymorphisms (SNPs) (n = 44), genes (n = 238), and pathways (n = 11) implicated in drug addiction were examined. Two loci met GW-significance (P < 2.5 × 10(-8) ) mapping to 17q21.31 and 11q13.4 that harbor genes with no obvious roles in eating behavior. GW results were significantly enriched for gene members of the MAPK signaling pathway (P = 0.02). No candidate SNP or gene for drug addiction was significantly associated with food addiction after correction for multiple testing. In the first GWAS of mYFAS, suggestive loci worthy of further follow-up were identified, but limited support was provided for shared genetic underpinnings of food addiction and drug addiction. The latter might be due to limited study power and knowledge of the genetics of drug addiction. © 2016 The Obesity Society.

Genome-wide and gene-based association implicates FRMD6 in Alzheimer disease.

PubMed

Hong, Mun-Gwan; Reynolds, Chandra A; Feldman, Adina L; Kallin, Mikael; Lambert, Jean-Charles; Amouyel, Philippe; Ingelsson, Erik; Pedersen, Nancy L; Prince, Jonathan A

2012-03-01

Genome-wide association studies (GWAS) that allow for allelic heterogeneity may facilitate the discovery of novel genes not detectable by models that require replication of a single variant site. One strategy to accomplish this is to focus on genes rather than markers as units of association, and so potentially capture a spectrum of causal alleles that differ across populations. Here, we conducted a GWAS of Alzheimer disease (AD) in 2,586 Swedes and performed gene-based meta-analysis with three additional studies from France, Canada, and the United States, in total encompassing 4,259 cases and 8,284 controls. Implementing a newly designed gene-based algorithm, we identified two loci apart from the region around APOE that achieved study-wide significance in combined samples, the strongest finding being for FRMD6 on chromosome 14q (P = 2.6 × 10(-14)) and a weaker signal for NARS2 that is immediately adjacent to GAB2 on chromosome 11q (P = 7.8 × 10(-9)). Ontology-based pathway analyses revealed significant enrichment of genes involved in glycosylation. Results suggest that gene-based approaches that accommodate allelic heterogeneity in GWAS can provide a complementary avenue for gene discovery and may help to explain a portion of the missing heritability not detectable with single nucleotide polymorphisms (SNPs) derived from marker-specific meta-analysis. © 2011 Wiley Periodicals, Inc.

Bipartite Community Structure of eQTLs.

PubMed

Platig, John; Castaldi, Peter J; DeMeo, Dawn; Quackenbush, John

2016-09-01

Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network "hub" SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community ("core SNPs") and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.

Evaluating genetic risk for prostate cancer among Japanese and Latinos

PubMed Central

Cheng, Iona; Chen, Gary K.; Nakagawa, Hidewaki; He, Jing; Wan, Peggy; Laurie, Cathy; Shen, Jess; Sheng, Xin; Pooler, Loreall C.; Crenshaw, Andrew T.; Mirel, Daniel B.; Takahashi, Atsushi; Kubo, Michiaki; Nakamura, Yusuke; Al Olama, Ali Amin; Benlloch, Sara; Donovan, Jenny L.; Guy, Michelle; Hamdy, Freddie C.; Kote-Jarai, Zsofia; Neal, David E.; Wilkens, Lynne R.; Monroe, Kristine R.; Stram, Daniel O.; Muir, Kenneth; Eeles, Rosalind A.; Easton, Douglas F.; Kolonel, Laurence N.; Henderson, Brian E.; Le Marchand, Loïc; Haiman, Christopher A.

2012-01-01

Background There have been few genome-wide association studies (GWAS) of prostate cancer among diverse populations. To search for novel prostate cancer risk variants, we conducted GWAS of prostate cancer in Japanese and Latinos. In addition, we tested prostate cancer risk variants and developed genetic risk models of prostate cancer for Japanese and Latinos. Methods Our first stage GWAS of prostate cancer included Japanese (cases/controls=1,033/1,042) and Latino (cases/controls=1,043/1,057) from the Multiethnic Cohort. Significant associations from stage 1 (P < 1.0×10−4) were examined in silico in GWAS of prostate cancer (stage 2) in Japanese (cases/controls=1,583/3,386) and Europeans (cases/controls=1,854/1,894). Results No novel stage 1 SNPs outside of known risk regions reached genome-wide significance. For Japanese, in stage 1, the most notable putative novel association was seen with 10 SNPs (P<8.0. x10−6) at chromosome 2q33; however, this was not replicated in stage 2. For Latinos, the most significant association was observed with rs17023900 at the known 3p12 risk locus (stage 1: OR=1.45; P=7.01×10−5 and stage 2: OR=1.58; P =3.05×10−7). The majority of the established risk variants for prostate cancer, 79% and 88%, were positively associated with prostate cancer in Japanese and Latinos (stage I), respectively. The cumulative effects of these variants significantly influence prostate cancer risk (OR per allele=1.10; P = 2.71×10−25 and OR=1.07; P = 1.02×10−16 for Japanese and Latinos, respectively). Conclusion and Impact Our GWAS of prostate cancer did not identify novel genome-wide significant variants. However, our findings demonstrate that established risk variants for prostate cancer significantly contribute to risk among Japanese and Latinos. PMID:22923026

Evaluating genetic risk for prostate cancer among Japanese and Latinos.

PubMed

Cheng, Iona; Chen, Gary K; Nakagawa, Hidewaki; He, Jing; Wan, Peggy; Laurie, Cathy C; Shen, Jess; Sheng, Xin; Pooler, Loreall C; Crenshaw, Andrew T; Mirel, Daniel B; Takahashi, Atsushi; Kubo, Michiaki; Nakamura, Yusuke; Al Olama, Ali Amin; Benlloch, Sara; Donovan, Jenny L; Guy, Michelle; Hamdy, Freddie C; Kote-Jarai, Zsofia; Neal, David E; Wilkens, Lynne R; Monroe, Kristine R; Stram, Daniel O; Muir, Kenneth; Eeles, Rosalind A; Easton, Douglas F; Kolonel, Laurence N; Henderson, Brian E; Le Marchand, Loïc; Haiman, Christopher A

2012-11-01

There have been few genome-wide association studies (GWAS) of prostate cancer among diverse populations. To search for novel prostate cancer risk variants, we conducted GWAS of prostate cancer in Japanese and Latinos. In addition, we tested prostate cancer risk variants and developed genetic risk models of prostate cancer for Japanese and Latinos. Our first-stage GWAS of prostate cancer included Japanese (cases/controls = 1,033/1,042) and Latino (cases/controls = 1,043/1,057) from the Multiethnic Cohort (MEC). Significant associations from stage I (P < 1.0 × 10(-4)) were examined in silico in GWAS of prostate cancer (stage II) in Japanese (cases/controls = 1,583/3,386) and Europeans (cases/controls = 1,854/1,894). No novel stage I single-nucleotide polymorphism (SNP) outside of known risk regions reached genome-wide significance. For Japanese, in stage I, the most notable putative novel association was seen with 10 SNPs (P ≤ 8.0 × 10(-6)) at chromosome 2q33; however, this was not replicated in stage II. For Latinos, the most significant association was observed with rs17023900 at the known 3p12 risk locus (stage I: OR = 1.45; P = 7.01 × 10(-5) and stage II: OR = 1.58; P = 3.05 × 10(-7)). The majority of the established risk variants for prostate cancer, 79% and 88%, were positively associated with prostate cancer in Japanese and Latinos (stage I), respectively. The cumulative effects of these variants significantly influence prostate cancer risk (OR per allele = 1.10; P = 2.71 × 10(-25) and OR = 1.07; P = 1.02 × 10(-16) for Japanese and Latinos, respectively). Our GWAS of prostate cancer did not identify novel genome-wide significant variants. However, our findings show that established risk variants for prostate cancer significantly contribute to risk among Japanese and Latinos. ©2012 AACR.

The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies.

PubMed

McCarty, Catherine A; Chisholm, Rex L; Chute, Christopher G; Kullo, Iftikhar J; Jarvik, Gail P; Larson, Eric B; Li, Rongling; Masys, Daniel R; Ritchie, Marylyn D; Roden, Dan M; Struewing, Jeffery P; Wolf, Wendy A

2011-01-26

The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record (EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors. The five sites are supported by an Administrative Coordinating Center. Setting of network goals is initiated by working groups: (1) Genomics, (2) Informatics, and (3) Consent & Community Consultation, which also includes active participation by investigators outside the eMERGE funded sites, and (4) Return of Results Oversight Committee. The Steering Committee, comprised of site PIs and representatives and NHGRI staff, meet three times per year, once per year with the External Scientific Panel. The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in ≈ 2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped. Funded by ARRA supplements, secondary phenotypes have been added at all sites to leverage the genotyping data, and hypothyroidism is being analyzed as a cross-network phenotype. Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site. Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care. By combining advanced clinical informatics, genome science, and community consultation, eMERGE represents a first step in the development of data-driven approaches to incorporate genomic information into routine healthcare delivery.

Electronic medical records and genomics (eMERGE) network exploration in cataract: Several new potential susceptibility loci

PubMed Central

Verma, Shefali S.; Hall, Molly A.; Goodloe, Robert J.; Berg, Richard L.; Carrell, Dave S.; Carlson, Christopher S.; Chen, Lin; Crosslin, David R.; Denny, Joshua C.; Jarvik, Gail; Li, Rongling; Linneman, James G.; Pathak, Jyoti; Peissig, Peggy; Rasmussen, Luke V.; Ramirez, Andrea H.; Wang, Xiaoming; Wilke, Russell A.; Wolf, Wendy A.; Torstenson, Eric S.; Turner, Stephen D.; McCarty, Catherine A.

2014-01-01

Purpose Cataract is the leading cause of blindness in the world, and in the United States accounts for approximately 60% of Medicare costs related to vision. The purpose of this study was to identify genetic markers for age-related cataract through a genome-wide association study (GWAS). Methods In the electronic medical records and genomics (eMERGE) network, we ran an electronic phenotyping algorithm on individuals in each of five sites with electronic medical records linked to DNA biobanks. We performed a GWAS using 530,101 SNPs from the Illumina 660W-Quad in a total of 7,397 individuals (5,503 cases and 1,894 controls). We also performed an age-at-diagnosis case-only analysis. Results We identified several statistically significant associations with age-related cataract (45 SNPs) as well as age at diagnosis (44 SNPs). The 45 SNPs associated with cataract at p<1×10−5 are in several interesting genes, including ALDOB, MAP3K1, and MEF2C. All have potential biologic relationships with cataracts. Conclusions This is the first genome-wide association study of age-related cataract, and several regions of interest have been identified. The eMERGE network has pioneered the exploration of genomic associations in biobanks linked to electronic health records, and this study is another example of the utility of such resources. Explorations of age-related cataract including validation and replication of the association results identified herein are needed in future studies. PMID:25352737

Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank

PubMed Central

2012-01-01

Background The ability to conduct genome-wide association studies (GWAS) has enabled new exploration of how genetic variations contribute to health and disease etiology. However, historically GWAS have been limited by inadequate sample size due to associated costs for genotyping and phenotyping of study subjects. This has prompted several academic medical centers to form “biobanks” where biospecimens linked to personal health information, typically in electronic health records (EHRs), are collected and stored on a large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypotheses generation. Results In this work, we study how emerging Semantic Web technologies can be applied in conjunction with clinical and genotype data stored at the Mayo Clinic Biobank to mine the phenotype data for genetic associations. In particular, we demonstrate the role of using Resource Description Framework (RDF) for representing EHR diagnoses and procedure data, and enable federated querying via standardized Web protocols to identify subjects genotyped for Type 2 Diabetes and Hypothyroidism to discover gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries. Conclusions This study demonstrates how Semantic Web technologies can be applied in conjunction with clinical data stored in EHRs to accurately identify subjects with specific diseases and phenotypes, and identify genotype-phenotype associations. PMID:23244446

Comparison of GWAS models to identify non-additive genetic control of flowering time in sunflower hybrids.

PubMed

Bonnafous, Fanny; Fievet, Ghislain; Blanchet, Nicolas; Boniface, Marie-Claude; Carrère, Sébastien; Gouzy, Jérôme; Legrand, Ludovic; Marage, Gwenola; Bret-Mestries, Emmanuelle; Munos, Stéphane; Pouilly, Nicolas; Vincourt, Patrick; Langlade, Nicolas; Mangin, Brigitte

2018-02-01

This study compares five models of GWAS, to show the added value of non-additive modeling of allelic effects to identify genomic regions controlling flowering time of sunflower hybrids. Genome-wide association studies are a powerful and widely used tool to decipher the genetic control of complex traits. One of the main challenges for hybrid crops, such as maize or sunflower, is to model the hybrid vigor in the linear mixed models, considering the relatedness between individuals. Here, we compared two additive and three non-additive association models for their ability to identify genomic regions associated with flowering time in sunflower hybrids. A panel of 452 sunflower hybrids, corresponding to incomplete crossing between 36 male lines and 36 female lines, was phenotyped in five environments and genotyped for 2,204,423 SNPs. Intra-locus effects were estimated in multi-locus models to detect genomic regions associated with flowering time using the different models. Thirteen quantitative trait loci were identified in total, two with both model categories and one with only non-additive models. A quantitative trait loci on LG09, detected by both the additive and non-additive models, is located near a GAI homolog and is presented in detail. Overall, this study shows the added value of non-additive modeling of allelic effects for identifying genomic regions that control traits of interest and that could participate in the heterosis observed in hybrids.

Screen and clean: a tool for identifying interactions in genome-wide association studies.

PubMed

Wu, Jing; Devlin, Bernie; Ringquist, Steven; Trucco, Massimo; Roeder, Kathryn

2010-04-01

Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher-dimensional models). We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high-dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising single-nucleotide polymorphisms (SNPs) are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.

TEAM: efficient two-locus epistasis tests in human genome-wide association study.

PubMed

Zhang, Xiang; Huang, Shunping; Zou, Fei; Wang, Wei

2010-06-15

As a promising tool for identifying genetic markers underlying phenotypic differences, genome-wide association study (GWAS) has been extensively investigated in recent years. In GWAS, detecting epistasis (or gene-gene interaction) is preferable over single locus study since many diseases are known to be complex traits. A brute force search is infeasible for epistasis detection in the genome-wide scale because of the intensive computational burden. Existing epistasis detection algorithms are designed for dataset consisting of homozygous markers and small sample size. In human study, however, the genotype may be heterozygous, and number of individuals can be up to thousands. Thus, existing methods are not readily applicable to human datasets. In this article, we propose an efficient algorithm, TEAM, which significantly speeds up epistasis detection for human GWAS. Our algorithm is exhaustive, i.e. it does not ignore any epistatic interaction. Utilizing the minimum spanning tree structure, the algorithm incrementally updates the contingency tables for epistatic tests without scanning all individuals. Our algorithm has broader applicability and is more efficient than existing methods for large sample study. It supports any statistical test that is based on contingency tables, and enables both family-wise error rate and false discovery rate controlling. Extensive experiments show that our algorithm only needs to examine a small portion of the individuals to update the contingency tables, and it achieves at least an order of magnitude speed up over the brute force approach.

Genome-wide association studies (GWAS) identify a QTL close to PRKAG3 affecting meat pH and colour in crossbred commercial pigs.

PubMed

Zhang, Chunyan; Wang, Zhiquan; Bruce, Heather; Kemp, Robert Alan; Charagu, Patrick; Miar, Younes; Yang, Tianfu; Plastow, Graham

2015-04-07

Improving meat quality is a high priority for the pork industry to satisfy consumers' preferences. GWAS have become a state-of-the-art approach to genetically improve economically important traits. However, GWAS focused on pork quality are still relatively rare. Six genomic regions were shown to affect loin pH and Minolta colour a* and b* on both loin and ham through GWAS in 1943 crossbred commercial pigs. Five of them, located on Sus scrofa chromosome (SSC) 1, SSC5, SSC9, SSC16 and SSCX, were associated with meat colour. However, the most promising region was detected on SSC15 spanning 133-134 Mb which explained 3.51% - 17.06% of genetic variance for five measurements of pH and colour. Three SNPs (ASGA0070625, MARC0083357 and MARC0039273) in very strong LD were considered most likely to account for the effects in this region. ASGA0070625 is located in intron 2 of ZNF142, and the other two markers are close to PRKAG3, STK36, TTLL7 and CDK5R2. After fitting MARC0083357 (the closest SNP to PRKAG3) as a fixed factor, six SNPs still remained significant for at least one trait. Four of them are intragenic with ARPC2, TMBIM1, NRAMP1 and VIL1, while the remaining two are close to RUFY4 and CDK5R2. The gene network constructed demonstrated strong connections of these genes with two major hubs of PRKAG3 and UBC in the super-pathways of cell-to-cell signaling and interaction, cellular function and maintenance. All these pathways play important roles in maintaining the integral architecture and functionality of muscle cells facing the dramatic changes that occur after exsanguination, which is in agreement with the GWAS results found in this study. There may be other markers and/or genes in this region besides PRKAG3 that have an important effect on pH and colour. The potential markers and their interactions with PRKAG3 require further investigation.

A genome-wide association study for fat-related traits computed by image analysis in Japanese Black cattle.

PubMed

Nakajima, Ayaka; Kawaguchi, Fuki; Uemoto, Yoshinobu; Fukushima, Moriyuki; Yoshida, Emi; Iwamoto, Eiji; Akiyama, Takayuki; Kohama, Namiko; Kobayashi, Eiji; Honda, Takeshi; Oyama, Kenji; Mannen, Hideyuki; Sasazaki, Shinji

2018-05-01

The objective of this study was to identify genomic regions associated with fat-related traits using a Japanese Black cattle population in Hyogo. From 1836 animals, those with high or low values were selected on the basis of corrected phenotype and then pooled into high and low groups (n = 100 each), respectively. DNA pool-based genome-wide association study (GWAS) was performed using Illumina BovineSNP50 BeadChip v2 with three replicate assays for each pooled sample. GWAS detected that two single nucleotide polymorphisms (SNPs) on BTA7 (ARS-BFGL-NGS-35463 and Hapmap23838-BTA-163815) and one SNP on BTA12 (ARS-BFGL-NGS-2915) significantly affected fat percentage (FAR). The significance of ARS-BFGL-NGS-35463 on BTA7 was confirmed by individual genotyping in all pooled samples. Moreover, association analysis between SNP and FAR in 803 Japanese Black cattle revealed a significant effect of SNP on FAR. Thus, further investigation of these regions is required to identify FAR-associated genes and mutations, which can lead to the development of DNA markers for marker-assisted selection for the genetic improvement of beef quality. © 2018 Japanese Society of Animal Science.

Association between Prostinogen (KLK15) Genetic Variants and Prostate Cancer Risk and Aggressiveness in Australia and a Meta-Analysis of GWAS Data

PubMed Central

Batra, Jyotsna; Lose, Felicity; O'Mara, Tracy; Marquart, Louise; Stephens, Carson; Alexander, Kimberly; Srinivasan, Srilakshmi; Eeles, Rosalind A.; Easton, Douglas F.; Olama, Ali Amin Al; Kote-Jarai, Zsofia; Guy, Michelle; Muir, Kenneth; Lophatananon, Artitaya; Rahman, Aneela A.; Neal, David E.; Hamdy, Freddie C.; Donovan, Jenny L.; Chambers, Suzanne; Gardiner, Robert A.; Aitken, Joanne; Yaxley, John; Kedda, Mary-Anne

2011-01-01

Background Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p<0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77–0.93; p = 2.7×10−4). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes. PMID:22132073

From Genome-Wide Association Study to Phenome-Wide Association Study: New Paradigms in Obesity Research.

PubMed

Zhang, Y-P; Zhang, Y-Y; Duan, D D

2016-01-01

Obesity is a condition in which excess body fat has accumulated over an extent that increases the risk of many chronic diseases. The current clinical classification of obesity is based on measurement of body mass index (BMI), waist-hip ratio, and body fat percentage. However, these measurements do not account for the wide individual variations in fat distribution, degree of fatness or health risks, and genetic variants identified in the genome-wide association studies (GWAS). In this review, we will address this important issue with the introduction of phenome, phenomics, and phenome-wide association study (PheWAS). We will discuss the new paradigm shift from GWAS to PheWAS in obesity research. In the era of precision medicine, phenomics and PheWAS provide the required approaches to better definition and classification of obesity according to the association of obese phenome with their unique molecular makeup, lifestyle, and environmental impact. Copyright © 2016 Elsevier Inc. All rights reserved.

Layers of epistasis: genome-wide regulatory networks and network approaches to genome-wide association studies.

PubMed

Cowper-Sal lari, Richard; Cole, Michael D; Karagas, Margaret R; Lupien, Mathieu; Moore, Jason H

2011-01-01

The conceptual foundation of the genome-wide association study (GWAS) has advanced unchecked since its conception. A revision might seem premature as the potential of GWAS has not been fully realized. Multiple technical and practical limitations need to be overcome before GWAS can be fairly criticized. But with the completion of hundreds of studies and a deeper understanding of the genetic architecture of disease, warnings are being raised. The results compiled to date indicate that risk-associated variants lie predominantly in noncoding regions of the genome. Additionally, alternative methodologies are uncovering large and heterogeneous sets of rare variants underlying disease. The fear is that, even in its fulfillment, the current GWAS paradigm might be incapable of dissecting all kinds of phenotypes. In the following text, we review several initiatives that aim to overcome these limitations. The overarching theme of these studies is the inclusion of biological knowledge to both the analysis and interpretation of genotyping data. GWAS is uninformed of biology by design and although there is some virtue in its simplicity, it is also its most conspicuous deficiency. We propose a framework in which to integrate these novel approaches, both empirical and theoretical, in the form of a genome-wide regulatory network (GWRN). By processing experimental data into networks, emerging data types based on chromatin immunoprecipitation are made computationally tractable. This will give GWAS re-analysis efforts the most current and relevant substrates, and root them firmly on our knowledge of human disease. Copyright © 2010 John Wiley & Sons, Inc.

Cacao single-nucleotide polymorphism (SNP) markers: A discovery strategy to identify SNPs for genotyping, genetic mapping and genome wide association studies (GWAS)

USDA-ARS?s Scientific Manuscript database

Single-nucleotide polymorphisms (SNPs) are the most common genetic markers in Theobroma cacao, occurring approximately once in every 200 nucleotides. SNPs, like microsatellites, are co-dominant and PCR-based, but they have several advantages over microsatellites. They are unambiguous, so that a SN...

Genome-wide association mapping of fusarium head blight resistance in wheat (Triticum aestivum L.) using genotyping by sequencing

USDA-ARS?s Scientific Manuscript database

Fusarium head blight (FHB) is one of the most important wheat diseases worldwide and host resistance displays complex genetic control. A genome-wide association study (GWAS) was performed on 273 winter wheat breeding lines from the mid-western and eastern regions of the US to identify chromosomal re...

CIDR

Science.gov Websites

variety of arrays appropriate for a wide breadth of study design needs. Genomic coverage of many of the chromosomal anomalies are services offered at NO ADDITIONAL COST to study investigators with GWAS projects be submitted for both the initial GWAS study as well as replication using our custom SNP service

A GWAS follow-up study reveals the association of the IL12RB2 gene with systemic sclerosis in Caucasian populations

PubMed Central

Bossini-Castillo, Lara; Martin, Jose-Ezequiel; Broen, Jasper; Gorlova, Olga; Simeón, Carmen P.; Beretta, Lorenzo; Vonk, Madelon C.; Luis Callejas, Jose; Castellví, Ivan; Carreira, Patricia; José García-Hernández, Francisco; Fernández Castro, Mónica; Coenen, Marieke J.H.; Riemekasten, Gabriela; Witte, Torsten; Hunzelmann, Nicolas; Kreuter, Alexander; Distler, Jörg H.W.; Koeleman, Bobby P.; Voskuyl, Alexandre E.; Schuerwegh, Annemie J.; Palm, Øyvind; Hesselstrand, Roger; Nordin, Annika; Airó, Paolo; Lunardi, Claudio; Scorza, Raffaella; Shiels, Paul; van Laar, Jacob M.; Herrick, Ariane; Worthington, Jane; Denton, Christopher; Tan, Filemon K.; Arnett, Frank C.; Agarwal, Sandeep K.; Assassi, Shervin; Fonseca, Carmen; Mayes, Maureen D.; Radstake, Timothy R.D.J.; Martin, Javier

2012-01-01

A single-nucleotide polymorphism (SNP) at the IL12RB2 locus showed a suggestive association signal in a previously published genome-wide association study (GWAS) in systemic sclerosis (SSc). Aiming to reveal the possible implication of the IL12RB2 gene in SSc, we conducted a follow-up study of this locus in different Caucasian cohorts. We analyzed 10 GWAS-genotyped SNPs in the IL12RB2 region (2309 SSc patients and 5161 controls). We then selected three SNPs (rs3790567, rs3790566 and rs924080) based on their significance level in the GWAS, for follow-up in an independent European cohort comprising 3344 SSc and 3848 controls. The most-associated SNP (rs3790567) was further tested in an independent cohort comprising 597 SSc patients and 1139 controls from the USA. After conditional logistic regression analysis of the GWAS data, we selected rs3790567 [PMH= 1.92 × 10−5 odds ratio (OR) = 1.19] as the genetic variant with the firmest independent association observed in the analyzed GWAS peak of association. After the first follow-up phase, only the association of rs3790567 was consistent (PMH= 4.84 × 10−3 OR = 1.12). The second follow-up phase confirmed this finding (Pχ2 = 2.82 × 10−4 OR = 1.34). After performing overall pooled-analysis of all the cohorts included in the present study, the association found for the rs3790567 SNP in the IL12RB2 gene region reached GWAS-level significant association (PMH= 2.82 × 10−9 OR = 1.17). Our data clearly support the IL12RB2 genetic association with SSc, and suggest a relevant role of the interleukin 12 signaling pathway in SSc pathogenesis. PMID:22076442

Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels

USDA-ARS?s Scientific Manuscript database

Vitamin D is a steroid hormone precursor that is associated with a range of human traits and diseases. Previous GWAS of serum 25-hydroxyvitamin D concentrations have identified four genome-wide significant loci (GC, NADSYN1/DHCR7, CYP2R1, CYP24A1). In this study, we expand the previous SUNLIGHT Cons...

A genome-wide association study of resistance to stripe rust (Puccinia striiformis f. sp. tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

New races of Puccinia striiformis f. sp. tritici (Pst), the causal pathogen of wheat stripe rust, show high virulence to previously deployed resistance genes and are causing large yield losses worldwide. To identify new sources of resistance we performed a genome-wide association study (GWAS) using...

Beyond endometriosis GWAS: from Genomics to Phenomics to the Patient

PubMed Central

Zondervan, Krina T.; Rahmioglu, Nilufer; Morris, Andrew P.; Nyholt, Dale R.; Montgomery, Grant W.; Becker, Christian M.; Missmer, Stacey A.

2017-01-01

Endometriosis is a heritable, complex chronic inflammatory disease, for which much of the causal pathogenic mechanism remain unknown. Genome-wide association studies (GWAS) to date have identified 12 single nucleotide polymorphisms or SNPs at 10 independent genetic loci associated with endometriosis. Most of these were more strongly associated with rAFS stage III/IV, rather than I/II. The loci are almost all located in inter-genic regions that are known to play a role in the regulation of expression of target genes yet to be identified. To identify the target genes and pathways perturbed by the implicated variants, studies are required involving functional genomic annotation of the surrounding chromosomal regions, in terms of transcriptor factor binding, epigenetic modification (e.g. DNA methylation and histone modification) sites, as well as their correlation with RNA transcription. These studies need to be conducted in tissue types relevant to endometriosis – in particular endometrium. In addition, to allow biologically and clinically relevant interpretation of molecular profiling data, they need to be combined and correlated with detailed, systematically collected phenotypic information (surgical and clinical). The WERF Endometriosis Phenome and Biobanking Harmonization project (EPHect) is a global standardisation initiative that has produced consensus data and sample collection protocols for endometriosis research. These now pave the way for collaborative studies integrating phenomic with genomic data, to identify informative subtypes of endometriosis that will enhance understanding of the pathogenic mechanisms of the disease and discovery of novel, targeted treatments. PMID:27513026

Genome-wide association study identifies HLA 8.1 ancestral haplotype alleles as major genetic risk factors for myositis phenotypes.

PubMed

Miller, F W; Chen, W; O'Hanlon, T P; Cooper, R G; Vencovsky, J; Rider, L G; Danko, K; Wedderburn, L R; Lundberg, I E; Pachman, L M; Reed, A M; Ytterberg, S R; Padyukov, L; Selva-O'Callaghan, A; Radstake, T R; Isenberg, D A; Chinoy, H; Ollier, W E R; Scheet, P; Peng, B; Lee, A; Byun, J; Lamb, J A; Gregersen, P K; Amos, C I

2015-10-01

Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis, 473 juvenile dermatomyositis, 532 polymyositis and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl-tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (P<5×10(-8)) in GWAS were identified in the major histocompatibility complex (MHC) region for all myositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1 comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations.

Genome-wide Association Study Identifies HLA 8.1 Ancestral Haplotype Alleles as Major Genetic Risk Factors for Myositis Phenotypes

PubMed Central

Miller, Frederick W.; Chen, Wei; O’Hanlon, Terrance P.; Cooper, Robert G.; Vencovsky, Jiri; Rider, Lisa G.; Danko, Katalin; Wedderburn, Lucy R.; Lundberg, Ingrid E.; Pachman, Lauren M.; Reed, Ann M.; Ytterberg, Steven R.; Padyukov, Leonid; Selva-O’Callaghan, Albert; Radstake, Timothy R.; Isenberg, David A.; Chinoy, Hector; Ollier, William E.R.; Scheet, Paul; Peng, Bo; Lee, Annette; Byun, Jinyoung; Lamb, Janine A.; Gregersen, Peter K.; Amos, Christopher I.

2016-01-01

Autoimmune muscle diseases (myositis) comprise a group of complex phenotypes influenced by genetic and environmental factors. To identify genetic risk factors in patients of European ancestry, we conducted a genome-wide association study (GWAS) of the major myositis phenotypes in a total of 1710 cases, which included 705 adult dermatomyositis; 473 juvenile dermatomyositis; 532 polymyositis; and 202 adult dermatomyositis, juvenile dermatomyositis or polymyositis patients with anti-histidyl tRNA synthetase (anti-Jo-1) autoantibodies, and compared them with 4724 controls. Single-nucleotide polymorphisms showing strong associations (P < 5 × 10−8) in GWAS were identified in the major histocompatibility complex (MHC) region for all myositis phenotypes together, as well as for the four clinical and autoantibody phenotypes studied separately. Imputation and regression analyses found that alleles comprising the human leukocyte antigen (HLA) 8.1 ancestral haplotype (AH8.1) defined essentially all the genetic risk in the phenotypes studied. Although the HLA DRB1*03:01 allele showed slightly stronger associations with adult and juvenile dermatomyositis, and HLA B*08:01 with polymyositis and anti-Jo-1 autoantibody-positive myositis, multiple alleles of AH8.1 were required for the full risk effects. Our findings establish that alleles of the AH8.1haplotype comprise the primary genetic risk factors associated with the major myositis phenotypes in geographically diverse Caucasian populations. PMID:26291516

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability

PubMed Central

Chen, Huan; Gu, Xiao-hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-01-01

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10−10, maximum β −2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level. PMID:28155865

A Genome-Wide Association Study Identifies Genetic Variants Associated with Mathematics Ability.

PubMed

Chen, Huan; Gu, Xiao-Hong; Zhou, Yuxi; Ge, Zeng; Wang, Bin; Siok, Wai Ting; Wang, Guoqing; Huen, Michael; Jiang, Yuyang; Tan, Li-Hai; Sun, Yimin

2017-02-03

Mathematics ability is a complex cognitive trait with polygenic heritability. Genome-wide association study (GWAS) has been an effective approach to investigate genetic components underlying mathematic ability. Although previous studies reported several candidate genetic variants, none of them exceeded genome-wide significant threshold in general populations. Herein, we performed GWAS in Chinese elementary school students to identify potential genetic variants associated with mathematics ability. The discovery stage included 494 and 504 individuals from two independent cohorts respectively. The replication stage included another cohort of 599 individuals. In total, 28 of 81 candidate SNPs that met validation criteria were further replicated. Combined meta-analysis of three cohorts identified four SNPs (rs1012694, rs11743006, rs17778739 and rs17777541) of SPOCK1 gene showing association with mathematics ability (minimum p value 5.67 × 10 -10 , maximum β -2.43). The SPOCK1 gene is located on chromosome 5q31.2 and encodes a highly conserved glycoprotein testican-1 which was associated with tumor progression and prognosis as well as neurogenesis. This is the first study to report genome-wide significant association of individual SNPs with mathematics ability in general populations. Our preliminary results further supported the role of SPOCK1 during neurodevelopment. The genetic complexities underlying mathematics ability might contribute to explain the basis of human cognition and intelligence at genetic level.

A Meta-Analysis Identifies New Loci Associated with Body Mass index in Individuals of African Ancestry

PubMed Central

Monda, Keri L.; Chen, Gary K.; Taylor, Kira C.; Palmer, Cameron; Edwards, Todd L.; Lange, Leslie A.; Ng, Maggie C.Y.; Adeyemo, Adebowale A.; Allison, Matthew A.; Bielak, Lawrence F.; Chen, Guanji; Graff, Mariaelisa; Irvin, Marguerite R.; Rhie, Suhn K.; Li, Guo; Liu, Yongmei; Liu, Youfang; Lu, Yingchang; Nalls, Michael A.; Sun, Yan V.; Wojczynski, Mary K.; Yanek, Lisa R.; Aldrich, Melinda C.; Ademola, Adeyinka; Amos, Christopher I.; Bandera, Elisa V.; Bock, Cathryn H.; Britton, Angela; Broeckel, Ulrich; Cai, Quiyin; Caporaso, Neil E.; Carlson, Chris; Carpten, John; Casey, Graham; Chen, Wei-Min; Chen, Fang; Chen, Yii-Der I.; Chiang, Charleston W.K.; Coetzee, Gerhard A.; Demerath, Ellen; Deming-Halverson, Sandra L.; Driver, Ryan W.; Dubbert, Patricia; Feitosa, Mary F.; Freedman, Barry I.; Gillanders, Elizabeth M.; Gottesman, Omri; Guo, Xiuqing; Haritunians, Talin; Harris, Tamara; Harris, Curtis C.; Hennis, Anselm JM; Hernandez, Dena G.; McNeill, Lorna H.; Howard, Timothy D.; Howard, Barbara V.; Howard, Virginia J.; Johnson, Karen C.; Kang, Sun J.; Keating, Brendan J.; Kolb, Suzanne; Kuller, Lewis H.; Kutlar, Abdullah; Langefeld, Carl D.; Lettre, Guillaume; Lohman, Kurt; Lotay, Vaneet; Lyon, Helen; Manson, JoAnn E.; Maixner, William; Meng, Yan A.; Monroe, Kristine R.; Morhason-Bello, Imran; Murphy, Adam B.; Mychaleckyj, Josyf C.; Nadukuru, Rajiv; Nathanson, Katherine L.; Nayak, Uma; N’Diaye, Amidou; Nemesure, Barbara; Wu, Suh-Yuh; Leske, M. Cristina; Neslund-Dudas, Christine; Neuhouser, Marian; Nyante, Sarah; Ochs-Balcom, Heather; Ogunniyi, Adesola; Ogundiran, Temidayo O.; Ojengbede, Oladosu; Olopade, Olufunmilayo I.; Palmer, Julie R.; Ruiz-Narvaez, Edward A.; Palmer, Nicholette D.; Press, Michael F.; Rampersaud, Evandine; Rasmussen-Torvik, Laura J.; Rodriguez-Gil, Jorge L.; Salako, Babatunde; Schadt, Eric E.; Schwartz, Ann G.; Shriner, Daniel A.; Siscovick, David; Smith, Shad B.; Wassertheil-Smoller, Sylvia; Speliotes, Elizabeth K.; Spitz, Margaret R.; Sucheston, Lara; Taylor, Herman; Tayo, Bamidele O.; Tucker, Margaret A.; Van Den Berg, David J.; Velez Edwards, Digna R.; Wang, Zhaoming; Wiencke, John K.; Winkler, Thomas W.; Witte, John S.; Wrensch, Margaret; Wu, Xifeng; Yang, James J.; Levin, Albert M.; Young, Taylor R.; Zakai, Neil A.; Cushman, Mary; Zanetti, Krista A.; Zhao, Jing Hua; Zhao, Wei; Zheng, Yonglan; Zhou, Jie; Ziegler, Regina G.; Zmuda, Joseph M.; Fernandes, Jyotika K.; Gilkeson, Gary S.; Kamen, Diane L.; Hunt, Kelly J.; Spruill, Ida J.; Ambrosone, Christine B.; Ambs, Stefan; Arnett, Donna K.; Atwood, Larry; Becker, Diane M.; Berndt, Sonja I.; Bernstein, Leslie; Blot, William J.; Borecki, Ingrid B.; Bottinger, Erwin P.; Bowden, Donald W.; Burke, Gregory; Chanock, Stephen J.; Cooper, Richard S.; Ding, Jingzhong; Duggan, David; Evans, Michele K.; Fox, Caroline; Garvey, W. Timothy; Bradfield, Jonathan P.; Hakonarson, Hakon; Grant, Struan F.A.; Hsing, Ann; Chu, Lisa; Hu, Jennifer J.; Huo, Dezheng; Ingles, Sue A.; John, Esther M.; Jordan, Joanne M.; Kabagambe, Edmond K.; Kardia, Sharon L.R.; Kittles, Rick A.; Goodman, Phyllis J.; Klein, Eric A.; Kolonel, Laurence N.; Le Marchand, Loic; Liu, Simin; McKnight, Barbara; Millikan, Robert C.; Mosley, Thomas H.; Padhukasahasram, Badri; Williams, L. Keoki; Patel, Sanjay R.; Peters, Ulrike; Pettaway, Curtis A.; Peyser, Patricia A.; Psaty, Bruce M.; Redline, Susan; Rotimi, Charles N.; Rybicki, Benjamin A.; Sale, Michèle M.; Schreiner, Pamela J.; Signorello, Lisa B.; Singleton, Andrew B.; Stanford, Janet L.; Strom, Sara S.; Thun, Michael J.; Vitolins, Mara; Zheng, Wei; Moore, Jason H.; Williams, Scott M.; Zhu, Xiaofeng; Zonderman, Alan B.; Kooperberg, Charles; Papanicolaou, George; Henderson, Brian E.; Reiner, Alex P.; Hirschhorn, Joel N.; Loos, Ruth JF; North, Kari E.; Haiman, Christopher A.

2013-01-01

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry, and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one novel locus at 5q33 (GALNT10, rs7708584, p=3.4×10−11) and another at 7p15 when combined with data from the Giant consortium (MIR148A/NFE2L3, rs10261878, p=1.2×10−10). We also found suggestive evidence of an association at a third locus at 6q16 in the African ancestry sample (KLHL32, rs974417, p=6.9×10−8). Thirty-two of the 36 previously established BMI variants displayed directionally consistent effect estimates in our GWAS (binomial p=9.7×10−7), of which five reached genome-wide significance. These findings provide strong support for shared BMI loci across populations as well as for the utility of studying ancestrally diverse populations. PMID:23583978

Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits.

PubMed

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.

Identifying tagging SNPs for African specific genetic variation from the African Diaspora Genome

PubMed Central

Johnston, Henry Richard; Hu, Yi-Juan; Gao, Jingjing; O’Connor, Timothy D.; Abecasis, Gonçalo R.; Wojcik, Genevieve L; Gignoux, Christopher R.; Gourraud, Pierre-Antoine; Lizee, Antoine; Hansen, Mark; Genuario, Rob; Bullis, Dave; Lawley, Cindy; Kenny, Eimear E.; Bustamante, Carlos; Beaty, Terri H.; Mathias, Rasika A.; Barnes, Kathleen C.; Qin, Zhaohui S.; Preethi Boorgula, Meher; Campbell, Monica; Chavan, Sameer; Ford, Jean G.; Foster, Cassandra; Gao, Li; Hansel, Nadia N.; Horowitz, Edward; Huang, Lili; Ortiz, Romina; Potee, Joseph; Rafaels, Nicholas; Ruczinski, Ingo; Scott, Alan F.; Taub, Margaret A.; Vergara, Candelaria; Levin, Albert M.; Padhukasahasram, Badri; Williams, L. Keoki; Dunston, Georgia M.; Faruque, Mezbah U.; Gietzen, Kimberly; Deshpande, Aniket; Grus, Wendy E.; Locke, Devin P.; Foreman, Marilyn G.; Avila, Pedro C.; Grammer, Leslie; Kim, Kwang-Youn A.; Kumar, Rajesh; Schleimer, Robert; De La Vega, Francisco M.; Shringarpure, Suyash S.; Musharoff, Shaila; Burchard, Esteban G.; Eng, Celeste; Hernandez, Ryan D.; Pino-Yanes, Maria; Torgerson, Dara G.; Szpiech, Zachary A.; Torres, Raul; Nicolae, Dan L.; Ober, Carole; Olopade, Christopher O; Olopade, Olufunmilayo; Oluwole, Oluwafemi; Arinola, Ganiyu; Song, Wei; Correa, Adolfo; Musani, Solomon; Wilson, James G.; Lange, Leslie A.; Akey, Joshua; Bamshad, Michael; Chong, Jessica; Fu, Wenqing; Nickerson, Deborah; Reiner, Alexander; Hartert, Tina; Ware, Lorraine B.; Bleecker, Eugene; Meyers, Deborah; Ortega, Victor E.; Maul, Pissamai; Maul, Trevor; Watson, Harold; Ilma Araujo, Maria; Riccio Oliveira, Ricardo; Caraballo, Luis; Marrugo, Javier; Martinez, Beatriz; Meza, Catherine; Ayestas, Gerardo; Francisco Herrera-Paz, Edwin; Landaverde-Torres, Pamela; Erazo, Said Omar Leiva; Martinez, Rosella; Mayorga, Alvaro; Mayorga, Luis F.; Mejia-Mejia, Delmy-Aracely; Ramos, Hector; Saenz, Allan; Varela, Gloria; Marina Vasquez, Olga; Ferguson, Trevor; Knight-Madden, Jennifer; Samms-Vaughan, Maureen; Wilks, Rainford J.; Adegnika, Akim; Ateba-Ngoa, Ulysse; Yazdanbakhsh, Maria

2017-01-01

A primary goal of The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to develop an ‘African Diaspora Power Chip’ (ADPC), a genotyping array consisting of tagging SNPs, useful in comprehensively identifying African specific genetic variation. This array is designed based on the novel variation identified in 642 CAAPA samples of African ancestry with high coverage whole genome sequence data (~30× depth). This novel variation extends the pattern of variation catalogued in the 1000 Genomes and Exome Sequencing Projects to a spectrum of populations representing the wide range of West African genomic diversity. These individuals from CAAPA also comprise a large swath of the African Diaspora population and incorporate historical genetic diversity covering nearly the entire Atlantic coast of the Americas. Here we show the results of designing and producing such a microchip array. This novel array covers African specific variation far better than other commercially available arrays, and will enable better GWAS analyses for researchers with individuals of African descent in their study populations. A recent study cataloging variation in continental African populations suggests this type of African-specific genotyping array is both necessary and valuable for facilitating large-scale GWAS in populations of African ancestry. PMID:28429804

Genome-Wide Association Study of Erosive Tooth Wear in a Finnish Cohort.

PubMed

Alaraudanjoki, Viivi Karoliina; Koivisto, Salla; Pesonen, Paula; Männikkö, Minna; Leinonen, Jukka; Tjäderhane, Leo; Laitala, Marja-Liisa; Lussi, Adrian; Anttonen, Vuokko Anna-Marketta

2018-06-13

Erosive tooth wear is defined as irreversible loss of dental tissues due to intrinsic or extrinsic acids, exacerbated by mechanical forces. Recent studies have suggested a higher prevalence of erosive tooth wear in males, as well as a genetic contribution to susceptibility to erosive tooth wear. Our aim was to examine erosive tooth wear by performing a genome-wide association study (GWAS) in a sample of the Northern Finland Birth Cohort 1966 (n = 1,962). Erosive tooth wear was assessed clinically using the basic erosive wear examination. A GWAS was performed for the whole sample as well as separately for males and females. We identified one genome-wide significant signal (rs11681214) in the GWAS of the whole sample near the genes PXDN and MYT1L. When the sample was stratified by sex, the strongest genome-wide significant signals were observed in or near the genes FGFR1, C8orf86, CDH4, SCD5, F2R, and ING1. Additionally, multiple suggestive association signals were detected in all GWASs performed. Many of the signals were in or near the genes putatively related to oral environment or tooth development, and some were near the regions considered to be associated with dental caries, such as 2p24, 4q21, and 13q33. Replications of these associations in other samples, as well as experimental studies to determine the biological functions of associated genetic variants, are needed. © 2018 S. Karger AG, Basel.

Association of Liver Injury From Specific Drugs, or Groups of Drugs, With Polymorphisms in HLA and Other Genes in a Genome-wide Association Study

PubMed Central

Nicoletti, Paola; Aithal, Guruprasad P.; Bjornsson, Einar S.; Andrade, Raul J.; Sawle, Ashley; Arrese, Marco; Barnhart, Huiman X.; Bondon-Guitton, Emmanuelle; Hayashi, Paul H.; Bessone, Fernando; Carvajal, Alfonso; Cascorbi, Ingolf; Cirulli, Elizabeth T.; Chalasani, Naga; Conforti, Anita; Coulthard, Sally A.; Daly, Mark J.; Day, Christopher P.; Dillon, John F.; Fontana, Robert J.; Grove, Jane I.; Hallberg, Pär; Hernández, Nelia; Ibáñez, Luisa; Kullak-Ublick, Gerd A.; Laitinen, Tarja; Larrey, Dominique; Lucena, M. Isabel; Maitland-van der Zee, Anke H.; Martin, Jennifer H.; Molokhia, Mariam; Pirmohamed, Munir; Powell, Elizabeth E.; Qin, Shengying; Serrano, Jose; Stephens, Camilla; Stolz, Andrew; Wadelius, Mia; Watkins, Paul B.; Floratos, Aris; Shen, Yufeng; Nelson, Matthew R.; Urban, Thomas J.; Daly, Ann K.

2017-01-01

BACKGROUND & AIMS We performed a genome-wide association study (GWAS) to identify genetic risk factors for drug-induced liver injury (DILI) from licensed drugs without previously reported genetic risk factors. METHODS We performed a GWAS of 862 persons with DILI and 10588 population-matched controls. The first set of cases was recruited prior to May 2009 in Europe (n=137) or the USA (n=274). The second set of cases were identified from May 2009 through May 2013 from international collaborative studies performed in Europe, the USA and South America. For the GWAS, we included only cases of European ancestry associated with a particular drug (but not flucloxacillin or amoxicillin-clavulanate). We used DNA samples from all subjects to analyze human leukocyte antigen (HLA) genes and single nucleotide polymorphisms (SNPs). After the discovery analysis was concluded, we validated our findings using data from 283 European patients with diagnosis of DILI associated with various drugs. RESULTS We associated DILI with rs114577328 (a proxy for A*33:01 a HLA class I allele; odds ratio [OR], 2.7; 95% CI, 1.9–3.8; P=2.4×10−8) and with rs72631567 on chromosome 2 (OR, 2.0; 95% CI, 1.6–2.5; P=9.7×10−9). The association with A*33:01 was mediated by large effects for terbinafine-, fenofibrate-, and ticlopidine-related DILI. The variant on chromosome 2 was associated with DILI from a variety of drugs. Further phenotypic analysis indicated that the association between DILI and A*33:01 was significant, genome wide, for cholestatic and mixed DILI, but not for hepatocellular DILI; the polymorphism on chromosome 2 associated with cholestatic and mixed DILI as well as hepatocellular DILI. We identified an association between rs28521457 (within the LRBA gene) and only hepatocellular DILI (OR, 2.1; 95% CI, 1.6–2.7; P=4.8×10−9). We did not associate any specific drug classes with genetic polymorphisms, except for statin-associated DILI, which was associated with rs116561224 on chromosome 18 (OR=5.4; 95% CI, 3.0–9.5; P=7.1×10−9). We validated the association between A*33:01 terbinafine- and sertraline-induced DILI. We could not validate the association between DILI and rs72631567, rs28521457, or rs116561224. CONCLUSIONS In a GWAS of persons of European descent with DILI, we associated HLA-A*33:01 with DILI due to terbinafine and possibly fenofibrate and ticlopidine. We identified polymorphisms that appear to be associated with DILI from statins, as well as 2 non–drug-specific risk factors. PMID:28043905

Genome-Wide Association Study for Indicator Traits of Sexual Precocity in Nellore Cattle

PubMed Central

Irano, Natalia; de Camargo, Gregório Miguel Ferreira; Costa, Raphael Bermal; Terakado, Ana Paula Nascimento; Magalhães, Ana Fabrícia Braga; Silva, Rafael Medeiros de Oliveira; Dias, Marina Mortati; Bignardi, Annaiza Braga; Baldi, Fernando; Carvalheiro, Roberto; de Oliveira, Henrique Nunes; de Albuquerque, Lucia Galvão

2016-01-01

The objective of this study was to perform a genome-wide association study (GWAS) to detect chromosome regions associated with indicator traits of sexual precocity in Nellore cattle. Data from Nellore animals belonging to farms which participate in the DeltaGen® and Paint® animal breeding programs, were used. The traits used in this study were the occurrence of early pregnancy (EP) and scrotal circumference (SC). Data from 72,675 females and 83,911 males with phenotypes were used; of these, 1,770 females and 1,680 males were genotyped. The SNP effects were estimated with a single-step procedure (WssGBLUP) and the observed phenotypes were used as dependent variables. All animals with available genotypes and phenotypes, in addition to those with only phenotypic information, were used. A single-trait animal model was applied to predict breeding values and the solutions of SNP effects were obtained from these breeding values. The results of GWAS are reported as the proportion of variance explained by windows with 150 adjacent SNPs. The 10 windows that explained the highest proportion of variance were identified. The results of this study indicate the polygenic nature of EP and SC, demonstrating that the indicator traits of sexual precocity studied here are probably controlled by many genes, including some of moderate effect. The 10 windows with large effects obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27, and together explained 7.91% of the total genetic variance. For SC, these windows are located on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of total variance. GWAS permitted to identify chromosome regions associated with EP and SC. The identification of these regions contributes to a better understanding and evaluation of these traits, and permits to indicate candidate genes for future investigation of causal mutations. PMID:27494397

GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies.

PubMed

Sulovari, Arvis; Li, Dawei

2014-07-19

Genome-wide association studies (GWAS) have successfully identified genes associated with complex human diseases. Although much of the heritability remains unexplained, combining single nucleotide polymorphism (SNP) genotypes from multiple studies for meta-analysis will increase the statistical power to identify new disease-associated variants. Meta-analysis requires same allele definition (nomenclature) and genome build among individual studies. Similarly, imputation, commonly-used prior to meta-analysis, requires the same consistency. However, the genotypes from various GWAS are generated using different genotyping platforms, arrays or SNP-calling approaches, resulting in use of different genome builds and allele definitions. Incorrect assumptions of identical allele definition among combined GWAS lead to a large portion of discarded genotypes or incorrect association findings. There is no published tool that predicts and converts among all major allele definitions. In this study, we have developed a tool, GACT, which stands for Genome build and Allele definition Conversion Tool, that predicts and inter-converts between any of the common SNP allele definitions and between the major genome builds. In addition, we assessed several factors that may affect imputation quality, and our results indicated that inclusion of singletons in the reference had detrimental effects while ambiguous SNPs had no measurable effect. Unexpectedly, exclusion of genotypes with missing rate > 0.001 (40% of study SNPs) showed no significant decrease of imputation quality (even significantly higher when compared to the imputation with singletons in the reference), especially for rare SNPs. GACT is a new, powerful, and user-friendly tool with both command-line and interactive online versions that can accurately predict, and convert between any of the common allele definitions and between genome builds for genome-wide meta-analysis and imputation of genotypes from SNP-arrays or deep-sequencing, particularly for data from the dbGaP and other public databases. http://www.uvm.edu/genomics/software/gact.

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

PubMed

Wu, Mengmeng; Zeng, Wanwen; Liu, Wenqiang; Lv, Hairong; Chen, Ting; Jiang, Rui

2018-06-03

Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is still a challenging task to extract biological knowledge from the GWAS data, due to such issues as missing heritability and weak interpretability. Indeed, the fact that the majority of discovered loci fall into noncoding regions without clear links to genes has been preventing the characterization of their functions and appealing for a sophisticated approach to bridge genetic and genomic studies. Towards this problem, network-based prioritization of candidate genes, which performs integrated analysis of gene networks with GWAS data, has emerged as a promising direction and attracted much attention. However, most existing methods overlook the sparse and noisy properties of gene networks and thus may lead to suboptimal performance. Motivated by this understanding, we proposed a novel method called REGENT for integrating multiple gene networks with GWAS data to prioritize candidate genes for complex diseases. We leveraged a technique called the network representation learning to embed a gene network into a compact and robust feature space, and then designed a hierarchical statistical model to integrate features of multiple gene networks with GWAS data for the effective inference of genes associated with a disease of interest. We applied our method to six complex diseases and demonstrated the superior performance of REGENT over existing approaches in recovering known disease-associated genes. We further conducted a pathway analysis and showed that the ability of REGENT to discover disease-associated pathways. We expect to see applications of our method to a broad spectrum of diseases for post-GWAS analysis. REGENT is freely available at https://github.com/wmmthu/REGENT. Copyright © 2018 Elsevier Inc. All rights reserved.

A genome-wide association study reveals candidate genes for the supernumerary nipple phenotype in sheep (Ovis aries).

PubMed

Peng, W-F; Xu, S-S; Ren, X; Lv, F-H; Xie, X-L; Zhao, Y-X; Zhang, M; Shen, Z-Q; Ren, Y-L; Gao, L; Shen, M; Kantanen, J; Li, M-H

2017-10-01

Genome-wide association studies (GWASs) have been widely applied in livestock to identify genes associated with traits of economic interest. Here, we conducted the first GWAS of the supernumerary nipple phenotype in Wadi sheep, a native Chinese sheep breed, based on Ovine Infinium HD SNP BeadChip genotypes in a total of 144 ewes (75 cases with four teats, including two normal and two supernumerary teats, and 69 control cases with two teats). We detected 63 significant SNPs at the chromosome-wise threshold. Additionally, one candidate region (chr1: 170.723-170.734 Mb) was identified by haplotype-based association tests, with one SNP (rs413490006) surrounding functional genes BBX and CD47 on chromosome 1 being commonly identified as significant by the two mentioned analyses. Moreover, Gene Ontology enrichment for the significant SNPs identified by the GWAS analysis was functionally clustered into the categories of receptor activity and synaptic membrane. In addition, pathway mapping revealed four promising pathways (Wnt, oxytocin, MAPK and axon guidance) involved in the development of the supernumerary nipple phenotype. Our results provide novel and important insights into the genetic mechanisms underlying the phenotype of supernumerary nipples in mammals, including humans. These findings may be useful for future breeding and genetics in sheep and other livestock. © 2017 Stichting International Foundation for Animal Genetics.

Identification of stable QTLs for seed oil content by combined linkage and association mapping in Brassica napus.

PubMed

Sun, Fengming; Liu, Jing; Hua, Wei; Sun, Xingchao; Wang, Xinfa; Wang, Hanzhong

2016-11-01

Seed oil content is an important agricultural trait in rapeseed breeding. Although numerous quantitative trait locus (QTL) have been identified, most of them cannot be applied in practical breeding mainly due to environmental instability or large confidence intervals. The purpose of this study was to identify and validate high quality and more stable QTLs by combining linkage mapping and genome-wide association study (GWAS). For linkage mapping, we constructed two F 2 populations from crosses of high-oil content (∼50%) lines 6F313 and 61616 with a low-oil content (∼40%) line 51070. Two high density linkage maps spanned 1987cM (1659 bins) and 1856cM (1746 bins), respectively. For GWAS, we developed more than 34,000 high-quality SNP markers based on 227 accessions. Finally, 40 QTLs and 29 associations were established by linkage and association mapping in different environments. After merging the results, 32 consensus QTLs were obtained and 7 of them were identified by both mapping methods. Seven overlapping QTLs covered an average confidence interval of 183kb and explained the phenotypic variation of 10.23 to 24.45%. We further developed allele-specific PCR primers to identify each of the seven QTLs. These stable QTLs should be useful in gene cloning and practical breeding application. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia.

PubMed

Ruderfer, Douglas M; Fanous, Ayman H; Ripke, Stephan; McQuillin, Andrew; Amdur, Richard L; Gejman, Pablo V; O'Donovan, Michael C; Andreassen, Ole A; Djurovic, Srdjan; Hultman, Christina M; Kelsoe, John R; Jamain, Stephane; Landén, Mikael; Leboyer, Marion; Nimgaonkar, Vishwajit; Nurnberger, John; Smoller, Jordan W; Craddock, Nick; Corvin, Aiden; Sullivan, Patrick F; Holmans, Peter; Sklar, Pamela; Kendler, Kenneth S

2014-09-01

Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined genome-wide association study (GWAS) of 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.

Genome-wide association studies in maize: praise and stargaze

USDA-ARS?s Scientific Manuscript database

Genome-wide association study (GWAS) has appeared as a widespread strategy in decoding genotype-phenotype associations in many species thanks to technical advances in next-generation sequencing (NGS) applications. Maize is an ideal crop for GWAS and significant progress has been made in the last dec...

Genetic variation in GPR133 is associated with height: genome wide association study in the self-contained population of Sorbs.

PubMed

Tönjes, Anke; Koriath, Moritz; Schleinitz, Dorit; Dietrich, Kerstin; Böttcher, Yvonne; Rayner, Nigel W; Almgren, Peter; Enigk, Beate; Richter, Olaf; Rohm, Silvio; Fischer-Rosinsky, Antje; Pfeiffer, Andreas; Hoffmann, Katrin; Krohn, Knut; Aust, Gabriela; Spranger, Joachim; Groop, Leif; Blüher, Matthias; Kovacs, Peter; Stumvoll, Michael

2009-12-01

Recently, associations of several common genetic variants with height have been reported in different populations. We attempted to identify further variants associated with adult height in a self-contained population (the Sorbs in Eastern Germany) as discovery set. We performed a genome wide association study (GWAS) (approximately 390,000 genetic polymorphisms, Affymetrix gene arrays) on adult height in 929 Sorbian individuals. Subsequently, the best SNPs (P < 0.001) were taken forward to a meta-analysis together with two independent cohorts [Diabetes Genetics Initiative, British 1958 Birth Cohort, (58BC, publicly available)]. Furthermore, we genotyped our best signal for replication in two additional German cohorts (Leipzig, n = 1044 and Berlin, n = 1728). In the primary Sorbian GWAS, we identified 5 loci with a P-value < 10(-5) and 455 SNPs with P-value < 0.001. In the meta-analysis on those 455 SNPs, only two variants in GPR133 (rs1569019 and rs1976930; in LD with each other) retained a P-value at or below 10(-6) and were associated with height in the three cohorts individually. Upon replication, the SNP rs1569019 showed significant effects on height in the Leipzig cohort (P = 0.004, beta = 1.166) and in 577 men of the Berlin cohort (P = 0.049, beta = 1.127) though not in women. The combined analysis of all five cohorts (n = 6,687) resulted in a P-value of 4.7 x 10(-8) (beta = 0.949). In conclusion, our GWAS suggests novel loci influencing height. In view of the robust replication in five different cohorts, we propose GPR133 to be a novel gene associated with adult height.

TATES: Efficient Multivariate Genotype-Phenotype Analysis for Genome-Wide Association Studies

PubMed Central

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

Loci associated with ischaemic stroke and its subtypes (SiGN): a genome-wide association study.

PubMed

2016-02-01

The discovery of disease-associated loci through genome-wide association studies (GWAS) is the leading genetic approach to the identification of novel biological pathways underlying diseases in humans. Until recently, GWAS in ischaemic stroke have been limited by small sample sizes and have yielded few loci associated with ischaemic stroke. We did a large-scale GWAS to identify additional susceptibility genes for stroke and its subtypes. To identify genetic loci associated with ischaemic stroke, we did a two-stage GWAS. In the first stage, we included 16 851 cases with state-of-the-art phenotyping data and 32 473 stroke-free controls. Cases were aged 16 to 104 years, recruited between 1989 and 2012, and subtypes of ischaemic stroke were recorded by centrally trained and certified investigators who used the web-based protocol, Causative Classification of Stroke (CCS). We constructed case-control strata by identifying samples that were genotyped on nearly identical arrays and were of similar genetic ancestral background. We cleaned and imputed data by use of dense imputation reference panels generated from whole-genome sequence data. We did genome-wide testing to identify stroke-associated loci within each stratum for each available phenotype, and we combined summary-level results using inverse variance-weighted fixed-effects meta-analysis. In the second stage, we did in-silico lookups of 1372 single nucleotide polymorphisms identified from the first stage GWAS in 20 941 cases and 364 736 unique stroke-free controls. The ischaemic stroke subtypes of these cases had previously been established with the Trial of Org 10 172 in Acute Stroke Treatment (TOAST) classification system, in accordance with local standards. Results from the two stages were then jointly analysed in a final meta-analysis. We identified a novel locus (G allele at rs12122341) at 1p13.2 near TSPAN2 that was associated with large artery atherosclerosis-related stroke (first stage odds ratio [OR] 1·21, 95% CI 1·13-1·30, p=4·50 × 10 -8 ; joint OR 1·19, 1·12-1·26, p=1·30 × 10 -9 ). Our results also supported robust associations with ischaemic stroke for four other loci that have been reported in previous studies, including PITX2 (first stage OR 1·39, 1·29-1·49, p=3·26 × 10 -19 ; joint OR 1·37, 1·30-1·45, p=2·79 × 10 -32 ) and ZFHX3 (first stage OR 1·19, 1·11-1·27, p=2·93 × 10 -7 ; joint OR 1·17, 1·11-1·23, p=2·29 × 10 -10 ) for cardioembolic stroke, and HDAC9 (first stage OR 1·29, 1·18-1·42, p=3·50 × 10 -8 ; joint OR 1·24, 1·15-1·33, p=4·52 × 10 -9 ) for large artery atherosclerosis stroke. The 12q24 locus near ALDH2, which has previously been associated with all ischaemic stroke but not with any specific subtype, exceeded genome-wide significance in the meta-analysis of small artery stroke (first stage OR 1·20, 1·12-1·28, p=6·82 × 10 -8 ; joint OR 1·17, 1·11-1·23, p=2·92 × 10 -9 ). Other loci associated with stroke in previous studies, including NINJ2, were not confirmed. Our results suggest that all ischaemic stroke-related loci previously implicated by GWAS are subtype specific. We identified a novel gene associated with large artery atherosclerosis stroke susceptibility. Follow-up studies will be necessary to establish whether the locus near TSPAN2 can be a target for a novel therapeutic approach to stroke prevention. In view of the subtype-specificity of the associations detected, the rich phenotyping data available in the Stroke Genetics Network (SiGN) are likely to be crucial for further genetic discoveries related to ischaemic stroke. US National Institute of Neurological Disorders and Stroke, National Institutes of Health. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genome-wide association analysis of metabolic traits in a birth cohort from a founder population.

PubMed

Sabatti, Chiara; Service, Susan K; Hartikainen, Anna-Liisa; Pouta, Anneli; Ripatti, Samuli; Brodsky, Jae; Jones, Chris G; Zaitlen, Noah A; Varilo, Teppo; Kaakinen, Marika; Sovio, Ulla; Ruokonen, Aimo; Laitinen, Jaana; Jakkula, Eveliina; Coin, Lachlan; Hoggart, Clive; Collins, Andrew; Turunen, Hannu; Gabriel, Stacey; Elliot, Paul; McCarthy, Mark I; Daly, Mark J; Järvelin, Marjo-Riitta; Freimer, Nelson B; Peltonen, Leena

2009-01-01

Genome-wide association studies (GWAS) of longitudinal birth cohorts enable joint investigation of environmental and genetic influences on complex traits. We report GWAS results for nine quantitative metabolic traits (triglycerides, high-density lipoprotein, low-density lipoprotein, glucose, insulin, C-reactive protein, body mass index, and systolic and diastolic blood pressure) in the Northern Finland Birth Cohort 1966 (NFBC1966), drawn from the most genetically isolated Finnish regions. We replicate most previously reported associations for these traits and identify nine new associations, several of which highlight genes with metabolic functions: high-density lipoprotein with NR1H3 (LXRA), low-density lipoprotein with AR and FADS1-FADS2, glucose with MTNR1B, and insulin with PANK1. Two of these new associations emerged after adjustment of results for body mass index. Gene-environment interaction analyses suggested additional associations, which will require validation in larger samples. The currently identified loci, together with quantified environmental exposures, explain little of the trait variation in NFBC1966. The association observed between low-density lipoprotein and an infrequent variant in AR suggests the potential of such a cohort for identifying associations with both common, low-impact and rarer, high-impact quantitative trait loci.

Effects of interactions between common genetic variants and alcohol consumption on colorectal cancer risk

PubMed Central

Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

2018-01-01

Background Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Results Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; ptrend<0.01). SNP rs6687758 near the DUSP10 gene at 1q41 had a statistically significant interaction with alcohol consumption in analyses of standardized drinks (p=4.6×10-3), although this did not surpass the corrected threshold for multiple testing. When stratified by alcohol consumption levels, in an additive model the risk of colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). Methods A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Conclusions Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer. PMID:29464080

Effects of interactions between common genetic variants and alcohol consumption on colorectal cancer risk.

PubMed

Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

2018-01-19

Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; p trend <0.01). SNP rs6687758 near the DUSP10 gene at 1q41 had a statistically significant interaction with alcohol consumption in analyses of standardized drinks ( p =4.6×10 -3 ), although this did not surpass the corrected threshold for multiple testing. When stratified by alcohol consumption levels, in an additive model the risk of colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer.

A multi-SNP association test for complex diseases incorporating an optimal P-value threshold algorithm in nuclear families.

PubMed

Wang, Yi-Ting; Sung, Pei-Yuan; Lin, Peng-Lin; Yu, Ya-Wen; Chung, Ren-Hua

2015-05-15

Genome-wide association studies (GWAS) have become a common approach to identifying single nucleotide polymorphisms (SNPs) associated with complex diseases. As complex diseases are caused by the joint effects of multiple genes, while the effect of individual gene or SNP is modest, a method considering the joint effects of multiple SNPs can be more powerful than testing individual SNPs. The multi-SNP analysis aims to test association based on a SNP set, usually defined based on biological knowledge such as gene or pathway, which may contain only a portion of SNPs with effects on the disease. Therefore, a challenge for the multi-SNP analysis is how to effectively select a subset of SNPs with promising association signals from the SNP set. We developed the Optimal P-value Threshold Pedigree Disequilibrium Test (OPTPDT). The OPTPDT uses general nuclear families. A variable p-value threshold algorithm is used to determine an optimal p-value threshold for selecting a subset of SNPs. A permutation procedure is used to assess the significance of the test. We used simulations to verify that the OPTPDT has correct type I error rates. Our power studies showed that the OPTPDT can be more powerful than the set-based test in PLINK, the multi-SNP FBAT test, and the p-value based test GATES. We applied the OPTPDT to a family-based autism GWAS dataset for gene-based association analysis and identified MACROD2-AS1 with genome-wide significance (p-value=2.5×10(-6)). Our simulation results suggested that the OPTPDT is a valid and powerful test. The OPTPDT will be helpful for gene-based or pathway association analysis. The method is ideal for the secondary analysis of existing GWAS datasets, which may identify a set of SNPs with joint effects on the disease.

Genome-Wide Association Mapping of Flowering and Ripening Periods in Apple.

PubMed

Urrestarazu, Jorge; Muranty, Hélène; Denancé, Caroline; Leforestier, Diane; Ravon, Elisa; Guyader, Arnaud; Guisnel, Rémi; Feugey, Laurence; Aubourg, Sébastien; Celton, Jean-Marc; Daccord, Nicolas; Dondini, Luca; Gregori, Roberto; Lateur, Marc; Houben, Patrick; Ordidge, Matthew; Paprstein, Frantisek; Sedlak, Jiri; Nybom, Hilde; Garkava-Gustavsson, Larisa; Troggio, Michela; Bianco, Luca; Velasco, Riccardo; Poncet, Charles; Théron, Anthony; Moriya, Shigeki; Bink, Marco C A M; Laurens, François; Tartarini, Stefano; Durel, Charles-Eric

2017-01-01

Deciphering the genetic control of flowering and ripening periods in apple is essential for breeding cultivars adapted to their growing environments. We implemented a large Genome-Wide Association Study (GWAS) at the European level using an association panel of 1,168 different apple genotypes distributed over six locations and phenotyped for these phenological traits. The panel was genotyped at a high-density of SNPs using the Axiom®Apple 480 K SNP array. We ran GWAS with a multi-locus mixed model (MLMM), which handles the putatively confounding effect of significant SNPs elsewhere on the genome. Genomic regions were further investigated to reveal candidate genes responsible for the phenotypic variation. At the whole population level, GWAS retained two SNPs as cofactors on chromosome 9 for flowering period, and six for ripening period (four on chromosome 3, one on chromosome 10 and one on chromosome 16) which, together accounted for 8.9 and 17.2% of the phenotypic variance, respectively. For both traits, SNPs in weak linkage disequilibrium were detected nearby, thus suggesting the existence of allelic heterogeneity. The geographic origins and relationships of apple cultivars accounted for large parts of the phenotypic variation. Variation in genotypic frequency of the SNPs associated with the two traits was connected to the geographic origin of the genotypes (grouped as North+East, West and South Europe), and indicated differential selection in different growing environments. Genes encoding transcription factors containing either NAC or MADS domains were identified as major candidates within the small confidence intervals computed for the associated genomic regions. A strong microsynteny between apple and peach was revealed in all the four confidence interval regions. This study shows how association genetics can unravel the genetic control of important horticultural traits in apple, as well as reduce the confidence intervals of the associated regions identified by linkage mapping approaches. Our findings can be used for the improvement of apple through marker-assisted breeding strategies that take advantage of the accumulating additive effects of the identified SNPs.

Genome-wide association study identified three major QTL for carcass weight including the PLAG1-CHCHD7 QTN for stature in Japanese Black cattle

PubMed Central

2012-01-01

Background Significant quantitative trait loci (QTL) for carcass weight were previously mapped on several chromosomes in Japanese Black half-sib families. Two QTL, CW-1 and CW-2, were narrowed down to 1.1-Mb and 591-kb regions, respectively. Recent advances in genomic tools allowed us to perform a genome-wide association study (GWAS) in cattle to detect associations in a general population and estimate their effect size. Here, we performed a GWAS for carcass weight using 1156 Japanese Black steers. Results Bonferroni-corrected genome-wide significant associations were detected in three chromosomal regions on bovine chromosomes (BTA) 6, 8, and 14. The associated single nucleotide polymorphisms (SNP) on BTA 6 were in linkage disequilibrium with the SNP encoding NCAPG Ile442Met, which was previously identified as a candidate quantitative trait nucleotide for CW-2. In contrast, the most highly associated SNP on BTA 14 was located 2.3-Mb centromeric from the previously identified CW-1 region. Linkage disequilibrium mapping led to a revision of the CW-1 region within a 0.9-Mb interval around the associated SNP, and targeted resequencing followed by association analysis highlighted the quantitative trait nucleotides for bovine stature in the PLAG1-CHCHD7 intergenic region. The association on BTA 8 was accounted for by two SNP on the BovineSNP50 BeadChip and corresponded to CW-3, which was simultaneously detected by linkage analyses using half-sib families. The allele substitution effects of CW-1, CW-2, and CW-3 were 28.4, 35.3, and 35.0 kg per allele, respectively. Conclusion The GWAS revealed the genetic architecture underlying carcass weight variation in Japanese Black cattle in which three major QTL accounted for approximately one-third of the genetic variance. PMID:22607022

Short communication: Improving the accuracy of genomic prediction of body conformation traits in Chinese Holsteins using markers derived from high-density marker panels.

PubMed

Song, H; Li, L; Ma, P; Zhang, S; Su, G; Lund, M S; Zhang, Q; Ding, X

2018-06-01

This study investigated the efficiency of genomic prediction with adding the markers identified by genome-wide association study (GWAS) using a data set of imputed high-density (HD) markers from 54K markers in Chinese Holsteins. Among 3,056 Chinese Holsteins with imputed HD data, 2,401 individuals born before October 1, 2009, were used for GWAS and a reference population for genomic prediction, and the 220 younger cows were used as a validation population. In total, 1,403, 1,536, and 1,383 significant single nucleotide polymorphisms (SNP; false discovery rate at 0.05) associated with conformation final score, mammary system, and feet and legs were identified, respectively. About 2 to 3% genetic variance of 3 traits was explained by these significant SNP. Only a very small proportion of significant SNP identified by GWAS was included in the 54K marker panel. Three new marker sets (54K+) were herein produced by adding significant SNP obtained by linear mixed model for each trait into the 54K marker panel. Genomic breeding values were predicted using a Bayesian variable selection (BVS) model. The accuracies of genomic breeding value by BVS based on the 54K+ data were 2.0 to 5.2% higher than those based on the 54K data. The imputed HD markers yielded 1.4% higher accuracy on average (BVS) than the 54K data. Both the 54K+ and HD data generated lower bias of genomic prediction, and the 54K+ data yielded the lowest bias in all situations. Our results show that the imputed HD data were not very useful for improving the accuracy of genomic prediction and that adding the significant markers derived from the imputed HD marker panel could improve the accuracy of genomic prediction and decrease the bias of genomic prediction. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

From Interaction to Co-Association —A Fisher r-To-z Transformation-Based Simple Statistic for Real World Genome-Wide Association Study

PubMed Central

Yuan, Zhongshang; Liu, Hong; Zhang, Xiaoshuai; Li, Fangyu; Zhao, Jinghua; Zhang, Furen; Xue, Fuzhong

2013-01-01

Currently, the genetic variants identified by genome wide association study (GWAS) generally only account for a small proportion of the total heritability for complex disease. One crucial reason is the underutilization of gene-gene joint effects commonly encountered in GWAS, which includes their main effects and co-association. However, gene-gene co-association is often customarily put into the framework of gene-gene interaction vaguely. From the causal graph perspective, we elucidate in detail the concept and rationality of gene-gene co-association as well as its relationship with traditional gene-gene interaction, and propose two Fisher r-to-z transformation-based simple statistics to detect it. Three series of simulations further highlight that gene-gene co-association refers to the extent to which the joint effects of two genes differs from the main effects, not only due to the traditional interaction under the nearly independent condition but the correlation between two genes. The proposed statistics are more powerful than logistic regression under various situations, cannot be affected by linkage disequilibrium and can have acceptable false positive rate as long as strictly following the reasonable GWAS data analysis roadmap. Furthermore, an application to gene pathway analysis associated with leprosy confirms in practice that our proposed gene-gene co-association concepts as well as the correspondingly proposed statistics are strongly in line with reality. PMID:23923021

Natural variation reveals that OsSAP16 controls low-temperature germination in rice.

PubMed

Wang, Xiang; Zou, Baohong; Shao, Qiaolin; Cui, Yongmei; Lu, Shan; Zhang, Yan; Huang, Quansheng; Huang, Ji; Hua, Jian

2018-01-23

Low temperature affects seed germination in plants, and low-temperature germination (LTG) is an important agronomic trait. Natural variation of LTG has been reported in rice, but the molecular basis for this variation is largely unknown. Here we report the phenotypic analysis of LTG in 187 rice natural accessions and a genome-wide association study (GWAS) of LTG in this collection. A total of 53 quantitative trait loci (QTLs) were found to be associated with LTG, of which 20 were located in previously reported QTLs. We further identified Stress-Associated Protein 16 (OsSAP16), coding for a zinc-finger domain protein, as a causal gene for one of the major LTG QTLs. Loss of OsSAP16 function reduces germination while greater expression of OsSAP16 enhances germination at low temperature. In addition, accessions with extremely high and low LTG values have correspondingly high and low OsSAP16 expression at low temperatures, suggesting that variation in expression of the OsSAP16 gene contributes to LTG variation. As the first case of identification of an LTG gene through GWAS, this study indicates that GWAS of natural accessions is an effective strategy in genetically dissecting LTG processes and gaining molecular understanding of low-temperature response and germination. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Genetics in Diabetic Retinopathy: Current Concepts and New Insights

PubMed Central

Simó-Servat, Olga; Hernández, Cristina; Simó, Rafael

2013-01-01

There is emerging evidence which indicates the essential role of genetic factors in the development of diabetic retinopathy (DR). In this regard it should be highlighted that genetic factors account for 25-50% of the risk of developing DR. Therefore, the use of genetic analysis to identify those diabetic patients most prone to developing DR might be useful in designing a more individualized treatment. In this regard, there are three main research strategies: candidate gene studies, linkage studies and Genome-Wide Association Studies (GWAS). In the candidate gene approach, several genes encoding proteins closely related to DR development have been analyzed. The linkage studies analyze shared alleles among family members with DR under the assumption that these predispose to a more aggressive development of DR. Finally, Genome-Wide Association Studies (GWAS) are a new tool involving a massive evaluation of single nucleotide polymorphisms (SNP) in large samples. In this review the available information using these three methodologies is critically analyzed. A genetic approach in order to identify new candidates in the pathogenesis of DR would permit us to design more targeted therapeutic strategies in order to decrease this devastating complication of diabetes. Basic researchers, ophthalmologists, diabetologists and geneticists should work together in order to gain new insights into this issue. PMID:24403848

A genome wide association study of alcohol dependence symptom counts in extended pedigrees identifies C15orf53

PubMed Central

Wang, Jen-Chyong; Foroud, Tatiana; Hinrichs, Anthony L; Le, Nhung XH; Bertelsen, Sarah; Budde, John P; Harari, Oscar; Koller, Daniel L; Wetherill, Leah; Agrawal, Arpana; Almasy, Laura; Brooks, Andrew I; Bucholz, Kathleen; Dick, Danielle; Hesselbrock, Victor; Johnson, Eric O; Kang, Sun; Kapoor, Manav; Kramer, John; Kuperman, Samuel; Madden, Pamela AF; Manz, Niklas; Martin, Nicholas G; McClintick, Jeanette N; Montgomery, Grant W; Nurnberger, John I; Rangaswamy, Madhavi; Rice, John; Schuckit, Marc; Tischfield, Jay A; Whitfield, John B; Xuei, Xiaoling; Porjesz, Bernice; Heath, Andrew C; Edenberg, Howard J; Bierut, Laura J; Goate, Alison M

2013-01-01

Several studies have identified genes associated with alcohol use disorders, but the variation in each of these genes explains only a small portion of the genetic vulnerability. The goal of the present study was to perform a genome-wide association study (GWAS) in extended families from the Collaborative Study on the Genetics of Alcoholism (COGA) to identify novel genes affecting risk for alcohol dependence. To maximize the power of the extended family design we used a quantitative endophenotype, measured in all individuals: number of alcohol dependence symptoms endorsed (symptom count). Secondary analyses were performed to determine if the single nucleotide polymorphisms (SNPs) associated with symptom count were also associated with the dichotomous phenotype, DSM-IV alcohol dependence. This family-based GWAS identified SNPs in C15orf53 that are strongly associated with DSM-IV alcohol (p=4.5×10−8, inflation corrected p=9.4×10−7). Results with DSM-IV alcohol dependence in the regions of interest support our findings with symptom count, though the associations were less significant. Attempted replications of the most promising association results were conducted in two independent samples: non-overlapping subjects from the Study of Addiction: Genes and Environment (SAGE) and the Australian twin-family study of alcohol use disorders (OZALC). Nominal association of C15orf53 with symptom count was observed in SAGE. The variant that showed strongest association with symptom count, rs12912251 and its highly correlated variants (D′=1, r2≥ 0.95), has previously been associated with risk for bipolar disorder. PMID:23089632

Moving into a new era of periodontal genetic studies: relevance of large case-control samples using severe phenotypes for genome-wide association studies.

PubMed

Vaithilingam, R D; Safii, S H; Baharuddin, N A; Ng, C C; Cheong, S C; Bartold, P M; Schaefer, A S; Loos, B G

2014-12-01

Studies to elucidate the role of genetics as a risk factor for periodontal disease have gone through various phases. In the majority of cases, the initial 'hypothesis-dependent' candidate-gene polymorphism studies did not report valid genetic risk loci. Following a large-scale replication study, these initially positive results are believed to be caused by type 1 errors. However, susceptibility genes, such as CDKN2BAS (Cyclin Dependend KiNase 2B AntiSense RNA; alias ANRIL [ANtisense Rna In the Ink locus]), glycosyltransferase 6 domain containing 1 (GLT6D1) and cyclooxygenase 2 (COX2), have been reported as conclusive risk loci of periodontitis. The search for genetic risk factors accelerated with the advent of 'hypothesis-free' genome-wide association studies (GWAS). However, despite many different GWAS being performed for almost all human diseases, only three GWAS on periodontitis have been published - one reported genome-wide association of GLT6D1 with aggressive periodontitis (a severe phenotype of periodontitis), whereas the remaining two, which were performed on patients with chronic periodontitis, were not able to find significant associations. This review discusses the problems faced and the lessons learned from the search for genetic risk variants of periodontitis. Current and future strategies for identifying genetic variance in periodontitis, and the importance of planning a well-designed genetic study with large and sufficiently powered case-control samples of severe phenotypes, are also discussed. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Optimizing Training Population Size and Genotyping Strategy for Genomic Prediction Using Association Study Results and Pedigree Information. A Case of Study in Advanced Wheat Breeding Lines.

PubMed

Cericola, Fabio; Jahoor, Ahmed; Orabi, Jihad; Andersen, Jeppe R; Janss, Luc L; Jensen, Just

2017-01-01

Wheat breeding programs generate a large amount of variation which cannot be completely explored because of limited phenotyping throughput. Genomic prediction (GP) has been proposed as a new tool which provides breeding values estimations without the need of phenotyping all the material produced but only a subset of it named training population (TP). However, genotyping of all the accessions under analysis is needed and, therefore, optimizing TP dimension and genotyping strategy is pivotal to implement GP in commercial breeding schemes. Here, we explored the optimum TP size and we integrated pedigree records and genome wide association studies (GWAS) results to optimize the genotyping strategy. A total of 988 advanced wheat breeding lines were genotyped with the Illumina 15K SNPs wheat chip and phenotyped across several years and locations for yield, lodging, and starch content. Cross-validation using the largest possible TP size and all the SNPs available after editing (~11k), yielded predictive abilities (rGP) ranging between 0.5-0.6. In order to explore the Training population size, rGP were computed using progressively smaller TP. These exercises showed that TP of around 700 lines were enough to yield the highest observed rGP. Moreover, rGP were calculated by randomly reducing the SNPs number. This showed that around 1K markers were enough to reach the highest observed rGP. GWAS was used to identify markers associated with the traits analyzed. A GWAS-based selection of SNPs resulted in increased rGP when compared with random selection and few hundreds SNPs were sufficient to obtain the highest observed rGP. For each of these scenarios, advantages of adding the pedigree information were shown. Our results indicate that moderate TP sizes were enough to yield high rGP and that pedigree information and GWAS results can be used to greatly optimize the genotyping strategy.

A hidden two-locus disease association pattern in genome-wide association studies

PubMed Central

2011-01-01

Background Recent association analyses in genome-wide association studies (GWAS) mainly focus on single-locus association tests (marginal tests) and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs). The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation. Results In this paper, we develop a computational method to detect this association pattern masked by unfaithfulness. We have applied our method to analyze seven data sets from the Wellcome Trust Case Control Consortium (WTCCC). The analysis for each data set takes about one week to finish the examination of all pairs of SNPs. Based on the empirical result of these real data, we show that this type of association masked by unfaithfulness widely exists in GWAS. Conclusions These newly identified associations enrich the discoveries of GWAS, which may provide new insights both in the analysis of tagSNPs and in the experiment design of GWAS. Since these associations may be easily missed by existing analysis tools, we can only connect some of them to publicly available findings from other association studies. As independent data set is limited at this moment, we also have difficulties to replicate these findings. More biological implications need further investigation. Availability The software is freely available at http://bioinformatics.ust.hk/hidden_pattern_finder.zip. PMID:21569557

Genome-wide association analysis in primary sclerosing cholangitis and ulcerative colitis identifies risk loci at GPR35 and TCF4.

PubMed

Ellinghaus, David; Folseraas, Trine; Holm, Kristian; Ellinghaus, Eva; Melum, Espen; Balschun, Tobias; Laerdahl, Jon K; Shiryaev, Alexey; Gotthardt, Daniel N; Weismüller, Tobias J; Schramm, Christoph; Wittig, Michael; Bergquist, Annika; Björnsson, Einar; Marschall, Hanns-Ulrich; Vatn, Morten; Teufel, Andreas; Rust, Christian; Gieger, Christian; Wichmann, H-Erich; Runz, Heiko; Sterneck, Martina; Rupp, Christian; Braun, Felix; Weersma, Rinse K; Wijmenga, Cisca; Ponsioen, Cyriel Y; Mathew, Christopher G; Rutgeerts, Paul; Vermeire, Séverine; Schrumpf, Erik; Hov, Johannes R; Manns, Michael P; Boberg, Kirsten M; Schreiber, Stefan; Franke, Andre; Karlsen, Tom H

2013-09-01

Approximately 60%-80% of patients with primary sclerosing cholangitis (PSC) have concurrent ulcerative colitis (UC). Previous genome-wide association studies (GWAS) in PSC have detected a number of susceptibility loci that also show associations in UC and other immune-mediated diseases. We aimed to systematically compare genetic associations in PSC with genotype data in UC patients with the aim of detecting new susceptibility loci for PSC. We performed combined analyses of GWAS for PSC and UC comprising 392 PSC cases, 987 UC cases, and 2,977 controls and followed up top association signals in an additional 1,012 PSC cases, 4,444 UC cases, and 11,659 controls. We discovered novel genome-wide significant associations with PSC at 2q37 [rs3749171 at G-protein-coupled receptor 35 (GPR35); P = 3.0 × 10(-9) in the overall study population, combined odds ratio [OR] and 95% confidence interval [CI] of 1.39 (1.24-1.55)] and at 18q21 [rs1452787 at transcription factor 4 (TCF4); P = 2.61 × 10(-8) , OR (95% CI) = 0.75 (0.68-0.83)]. In addition, several suggestive PSC associations were detected. The GPR35 rs3749171 is a missense single nucleotide polymorphism resulting in a shift from threonine to methionine. Structural modeling showed that rs3749171 is located in the third transmembrane helix of GPR35 and could possibly alter efficiency of signaling through the GPR35 receptor. By refining the analysis of a PSC GWAS by parallel assessments in a UC GWAS, we were able to detect two novel risk loci at genome-wide significance levels. GPR35 shows associations in both UC and PSC, whereas TCF4 represents a PSC risk locus not associated with UC. Both loci may represent previously unexplored aspects of PSC pathogenesis. Copyright © 2012 American Association for the Study of Liver Diseases.

Anonymization of electronic medical records for validating genome-wide association studies

PubMed Central

Loukides, Grigorios; Gkoulalas-Divanis, Aris; Malin, Bradley

2010-01-01

Genome-wide association studies (GWAS) facilitate the discovery of genotype–phenotype relations from population-based sequence databases, which is an integral facet of personalized medicine. The increasing adoption of electronic medical records allows large amounts of patients’ standardized clinical features to be combined with the genomic sequences of these patients and shared to support validation of GWAS findings and to enable novel discoveries. However, disseminating these data “as is” may lead to patient reidentification when genomic sequences are linked to resources that contain the corresponding patients’ identity information based on standardized clinical features. This work proposes an approach that provably prevents this type of data linkage and furnishes a result that helps support GWAS. Our approach automatically extracts potentially linkable clinical features and modifies them in a way that they can no longer be used to link a genomic sequence to a small number of patients, while preserving the associations between genomic sequences and specific sets of clinical features corresponding to GWAS-related diseases. Extensive experiments with real patient data derived from the Vanderbilt's University Medical Center verify that our approach generates data that eliminate the threat of individual reidentification, while supporting GWAS validation and clinical case analysis tasks. PMID:20385806

The TRiC/CCT chaperone is implicated in Alzheimer's disease based on patient GWAS and an RNAi screen in Aβ-expressing Caenorhabditis elegans.

PubMed

Khabirova, Eleonora; Moloney, Aileen; Marciniak, Stefan J; Williams, Julie; Lomas, David A; Oliver, Stephen G; Favrin, Giorgio; Sattelle, David B; Crowther, Damian C

2014-01-01

The human Aβ peptide causes progressive paralysis when expressed in the muscles of the nematode worm, C. elegans. We have exploited this model of Aβ toxicity by carrying out an RNAi screen to identify genes whose reduced expression modifies the severity of this locomotor phenotype. Our initial finding was that none of the human orthologues of these worm genes is identical with the genome-wide significant GWAS genes reported to date (the "white zone"); moreover there was no identity between worm screen hits and the longer list of GWAS genes which included those with borderline levels of significance (the "grey zone"). This indicates that Aβ toxicity should not be considered as equivalent to sporadic AD. To increase the sensitivity of our analysis, we then considered the physical interactors (+1 interactome) of the products of the genes in both the worm and the white+grey zone lists. When we consider these worm and GWAS gene lists we find that 4 of the 60 worm genes have a +1 interactome overlap that is larger than expected by chance. Two of these genes form a chaperonin complex, the third is closely associated with this complex and the fourth gene codes for actin, the major substrate of the same chaperonin.

Genetics of healthy aging and longevity.

PubMed

Brooks-Wilson, Angela R

2013-12-01

Longevity and healthy aging are among the most complex phenotypes studied to date. The heritability of age at death in adulthood is approximately 25 %. Studies of exceptionally long-lived individuals show that heritability is greatest at the oldest ages. Linkage studies of exceptionally long-lived families now support a longevity locus on chromosome 3; other putative longevity loci differ between studies. Candidate gene studies have identified variants at APOE and FOXO3A associated with longevity; other genes show inconsistent results. Genome-wide association scans (GWAS) of centenarians vs. younger controls reveal only APOE as achieving genome-wide significance (GWS); however, analyses of combinations of SNPs or genes represented among associations that do not reach GWS have identified pathways and signatures that converge upon genes and biological processes related to aging. The impact of these SNPs, which may exert joint effects, may be obscured by gene-environment interactions or inter-ethnic differences. GWAS and whole genome sequencing data both show that the risk alleles defined by GWAS of common complex diseases are, perhaps surprisingly, found in long-lived individuals, who may tolerate them by means of protective genetic factors. Such protective factors may 'buffer' the effects of specific risk alleles. Rare alleles are also likely to contribute to healthy aging and longevity. Epigenetics is quickly emerging as a critical aspect of aging and longevity. Centenarians delay age-related methylation changes, and they can pass this methylation preservation ability on to their offspring. Non-genetic factors, particularly lifestyle, clearly affect the development of age-related diseases and affect health and lifespan in the general population. To fully understand the desirable phenotypes of healthy aging and longevity, it will be necessary to examine whole genome data from large numbers of healthy long-lived individuals to look simultaneously at both common and rare alleles, with impeccable control for population stratification and consideration of non-genetic factors such as environment.

Quantifying the heritability of testicular germ cell tumour using both population-based and genomic approaches.

PubMed

Litchfield, Kevin; Thomsen, Hauke; Mitchell, Jonathan S; Sundquist, Jan; Houlston, Richard S; Hemminki, Kari; Turnbull, Clare

2015-09-09

A sizable fraction of testicular germ cell tumour (TGCT) risk is expected to be explained by heritable factors. Recent genome-wide association studies (GWAS) have successfully identified a number of common SNPs associated with TGCT. It is however, unclear how much common variation there is left to be accounted for by other, yet to be identified, common SNPs and what contribution common genetic variation makes to the heritable risk of TGCT. We approached this question using two complimentary analytical techniques. We undertook a population-based analysis of the Swedish family-cancer database, through which we estimated that the heritability of TGCT at 48.9% (CI:47.2%-52.3%). We also applied Genome-Wide Complex Trait Analysis to 922 cases and 4,842 controls to estimate the heritability of TGCT. The heritability explained by known common risk SNPs identified by GWAS was 9.1%, whereas the heritability explained by all common SNPs was 37.4% (CI:27.6%-47.2%). These complementary findings indicate that the known TGCT SNPs only explain a small proportion of the heritability and many additional common SNPs remain to be identified. The data also suggests that a fraction of the heritability of TGCT is likely to be explained by other classes of genetic variation, such as rare disease-causing alleles.

Re-Ranking Sequencing Variants in the Post-GWAS Era for Accurate Causal Variant Identification

PubMed Central

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

Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss).

PubMed

Gonzalez-Pena, Dianelys; Gao, Guangtu; Baranski, Matthew; Moen, Thomas; Cleveland, Beth M; Kenney, P Brett; Vallejo, Roger L; Palti, Yniv; Leeds, Timothy D

2016-01-01

Fillet yield (FY, %) is an economically-important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has received little attention in breeding programs because it is difficult to measure on a large number of fish and cannot be directly measured on breeding candidates. The recent development of a high-density SNP array for rainbow trout has provided the needed tool for studying the underlying genetic architecture of this trait. A genome-wide association study (GWAS) was conducted for FY, body weight at 10 (BW10) and 13 (BW13) months post-hatching, head-off carcass weight (CAR), and fillet weight (FW) in a pedigreed rainbow trout population selectively bred for improved growth performance. The GWAS analysis was performed using the weighted single-step GBLUP method (wssGWAS). Phenotypic records of 1447 fish (1.5 kg at harvest) from 299 full-sib families in three successive generations, of which 875 fish from 196 full-sib families were genotyped, were used in the GWAS analysis. A total of 38,107 polymorphic SNPs were analyzed in a univariate model with hatch year and harvest group as fixed effects, harvest weight as a continuous covariate, and animal and common environment as random effects. A new linkage map was developed to create windows of 20 adjacent SNPs for use in the GWAS. The two windows with largest effect for FY and FW were located on chromosome Omy9 and explained only 1.0-1.5% of genetic variance, thus suggesting a polygenic architecture affected by multiple loci with small effects in this population. One window on Omy5 explained 1.4 and 1.0% of the genetic variance for BW10 and BW13, respectively. Three windows located on Omy27, Omy17, and Omy9 (same window detected for FY) explained 1.7, 1.7, and 1.0%, respectively, of genetic variance for CAR. Among the detected 100 SNPs, 55% were located directly in genes (intron and exons). Nucleotide sequences of intragenic SNPs were blasted to the Mus musculus genome to create a putative gene network. The network suggests that differences in the ability to maintain a proliferative and renewable population of myogenic precursor cells may affect variation in growth and fillet yield in rainbow trout.

Genome-Wide Association Study for Identifying Loci that Affect Fillet Yield, Carcass, and Body Weight Traits in Rainbow Trout (Oncorhynchus mykiss)

PubMed Central

Gonzalez-Pena, Dianelys; Gao, Guangtu; Baranski, Matthew; Moen, Thomas; Cleveland, Beth M.; Kenney, P. Brett; Vallejo, Roger L.; Palti, Yniv; Leeds, Timothy D.

2016-01-01

Fillet yield (FY, %) is an economically-important trait in rainbow trout aquaculture that affects production efficiency. Despite that, FY has received little attention in breeding programs because it is difficult to measure on a large number of fish and cannot be directly measured on breeding candidates. The recent development of a high-density SNP array for rainbow trout has provided the needed tool for studying the underlying genetic architecture of this trait. A genome-wide association study (GWAS) was conducted for FY, body weight at 10 (BW10) and 13 (BW13) months post-hatching, head-off carcass weight (CAR), and fillet weight (FW) in a pedigreed rainbow trout population selectively bred for improved growth performance. The GWAS analysis was performed using the weighted single-step GBLUP method (wssGWAS). Phenotypic records of 1447 fish (1.5 kg at harvest) from 299 full-sib families in three successive generations, of which 875 fish from 196 full-sib families were genotyped, were used in the GWAS analysis. A total of 38,107 polymorphic SNPs were analyzed in a univariate model with hatch year and harvest group as fixed effects, harvest weight as a continuous covariate, and animal and common environment as random effects. A new linkage map was developed to create windows of 20 adjacent SNPs for use in the GWAS. The two windows with largest effect for FY and FW were located on chromosome Omy9 and explained only 1.0–1.5% of genetic variance, thus suggesting a polygenic architecture affected by multiple loci with small effects in this population. One window on Omy5 explained 1.4 and 1.0% of the genetic variance for BW10 and BW13, respectively. Three windows located on Omy27, Omy17, and Omy9 (same window detected for FY) explained 1.7, 1.7, and 1.0%, respectively, of genetic variance for CAR. Among the detected 100 SNPs, 55% were located directly in genes (intron and exons). Nucleotide sequences of intragenic SNPs were blasted to the Mus musculus genome to create a putative gene network. The network suggests that differences in the ability to maintain a proliferative and renewable population of myogenic precursor cells may affect variation in growth and fillet yield in rainbow trout. PMID:27920797

Genome-wide association studies and epistasis analyses of candidate genes related to age at menarche and age at natural menopause in a Korean population.

PubMed

Pyun, Jung-A; Kim, Sunshin; Cho, Nam H; Koh, InSong; Lee, Jong-Young; Shin, Chol; Kwack, KyuBum

2014-05-01

The aim of this study was to identify polymorphisms and gene-gene interactions that are significantly associated with age at menarche and age at menopause in a Korean population. A total of 3,452 and 1,827 women participated in studies of age at menarche and age at natural menopause, respectively. Linear regression analyses adjusted for residence area were used to perform genome-wide association studies (GWAS), candidate gene association studies, and interactions between the candidate genes for age at menarche and age at natural menopause. In GWAS, four single nucleotide polymorphisms (SNPs; rs7528241, rs1324329, rs11597068, and rs6495785) were strongly associated with age at natural menopause (lowest P = 9.66 × 10). However, GWAS of age at menarche did not reveal any strong associations. In candidate gene association studies, SNPs with P < 0.01 were selected to test their synergistic interactions. For age at natural menopause, there was a significant interaction between intronic SNPs on ADAM metallopeptidase with thrombospondin type I motif 9 (ADAMTS9) and SMAD family member 3 (SMAD3) genes (P = 9.52 × 10). For age at menarche, there were three significant interactions between three intronic SNPs on follicle-stimulating hormone receptor (FSHR) gene and one SNP located at the 3' flanking region of insulin-like growth factor 2 receptor (IGF2R) gene (lowest P = 1.95 × 10). Novel SNPs and synergistic interactions between candidate genes are significantly associated with age at menarche and age at natural menopause in a Korean population.

Genome-Wide Association Scan in HIV-1-Infected Individuals Identifying Variants Influencing Disease Course

PubMed Central

van Manen, Daniëlle; Delaneau, Olivier; Kootstra, Neeltje A.; Boeser-Nunnink, Brigitte D.; Limou, Sophie; Bol, Sebastiaan M.; Burger, Judith A.; Zwinderman, Aeilko H.; Moerland, Perry D.; van 't Slot, Ruben; Zagury, Jean-François; van 't Wout, Angélique B.; Schuitemaker, Hanneke

2011-01-01

Background AIDS develops typically after 7–11 years of untreated HIV-1 infection, with extremes of very rapid disease progression (<2 years) and long-term non-progression (>15 years). To reveal additional host genetic factors that may impact on the clinical course of HIV-1 infection, we designed a genome-wide association study (GWAS) in 404 participants of the Amsterdam Cohort Studies on HIV-1 infection and AIDS. Methods The association of SNP genotypes with the clinical course of HIV-1 infection was tested in Cox regression survival analyses using AIDS-diagnosis and AIDS-related death as endpoints. Results Multiple, not previously identified SNPs, were identified to be strongly associated with disease progression after HIV-1 infection, albeit not genome-wide significant. However, three independent SNPs in the top ten associations between SNP genotypes and time between seroconversion and AIDS-diagnosis, and one from the top ten associations between SNP genotypes and time between seroconversion and AIDS-related death, had P-values smaller than 0.05 in the French Genomics of Resistance to Immunodeficiency Virus cohort on disease progression. Conclusions Our study emphasizes that the use of different phenotypes in GWAS may be useful to unravel the full spectrum of host genetic factors that may be associated with the clinical course of HIV-1 infection. PMID:21811574

Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes.

PubMed

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.

Genetic Variants Associated With Glycine Metabolism and Their Role in Insulin Sensitivity and Type 2 Diabetes

PubMed Central

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

Genome-wide gene-based analysis suggests an association between Neuroligin 1 (NLGN1) and post-traumatic stress disorder.

PubMed

Kilaru, V; Iyer, S V; Almli, L M; Stevens, J S; Lori, A; Jovanovic, T; Ely, T D; Bradley, B; Binder, E B; Koen, N; Stein, D J; Conneely, K N; Wingo, A P; Smith, A K; Ressler, K J

2016-05-24

Post-traumatic stress disorder (PTSD) develops in only some people following trauma exposure, but the mechanisms differentially explaining risk versus resilience remain largely unknown. PTSD is heritable but candidate gene studies and genome-wide association studies (GWAS) have identified only a modest number of genes that reliably contribute to PTSD. New gene-based methods may help identify additional genes that increase risk for PTSD development or severity. We applied gene-based testing to GWAS data from the Grady Trauma Project (GTP), a primarily African American cohort, and identified two genes (NLGN1 and ZNRD1-AS1) that associate with PTSD after multiple test correction. Although the top SNP from NLGN1 did not replicate, we observed gene-based replication of NLGN1 with PTSD in the Drakenstein Child Health Study (DCHS) cohort from Cape Town. NLGN1 has previously been associated with autism, and it encodes neuroligin 1, a protein involved in synaptogenesis, learning, and memory. Within the GTP dataset, a single nucleotide polymorphism (SNP), rs6779753, underlying the gene-based association, associated with the intermediate phenotypes of higher startle response and greater functional magnetic resonance imaging activation of the amygdala, orbitofrontal cortex, right thalamus and right fusiform gyrus in response to fearful faces. These findings support a contribution of the NLGN1 gene pathway to the neurobiological underpinnings of PTSD.

Genome-wide gene-based analysis suggests an association between Neuroligin 1 (NLGN1) and post-traumatic stress disorder

PubMed Central

Kilaru, V; Iyer, S V; Almli, L M; Stevens, J S; Lori, A; Jovanovic, T; Ely, T D; Bradley, B; Binder, E B; Koen, N; Stein, D J; Conneely, K N; Wingo, A P; Smith, A K; Ressler, K J

2016-01-01

Post-traumatic stress disorder (PTSD) develops in only some people following trauma exposure, but the mechanisms differentially explaining risk versus resilience remain largely unknown. PTSD is heritable but candidate gene studies and genome-wide association studies (GWAS) have identified only a modest number of genes that reliably contribute to PTSD. New gene-based methods may help identify additional genes that increase risk for PTSD development or severity. We applied gene-based testing to GWAS data from the Grady Trauma Project (GTP), a primarily African American cohort, and identified two genes (NLGN1 and ZNRD1-AS1) that associate with PTSD after multiple test correction. Although the top SNP from NLGN1 did not replicate, we observed gene-based replication of NLGN1 with PTSD in the Drakenstein Child Health Study (DCHS) cohort from Cape Town. NLGN1 has previously been associated with autism, and it encodes neuroligin 1, a protein involved in synaptogenesis, learning, and memory. Within the GTP dataset, a single nucleotide polymorphism (SNP), rs6779753, underlying the gene-based association, associated with the intermediate phenotypes of higher startle response and greater functional magnetic resonance imaging activation of the amygdala, orbitofrontal cortex, right thalamus and right fusiform gyrus in response to fearful faces. These findings support a contribution of the NLGN1 gene pathway to the neurobiological underpinnings of PTSD. PMID:27219346

Genome Wide Association Study of Seedling and Adult Plant Leaf Rust Resistance in Elite Spring Wheat Breeding Lines

PubMed Central

Gao, Liangliang; Turner, M. Kathryn; Chao, Shiaoman; Kolmer, James; Anderson, James A.

2016-01-01

Leaf rust is an important disease, threatening wheat production annually. Identification of resistance genes or QTLs for effective field resistance could greatly enhance our ability to breed durably resistant varieties. We applied a genome wide association study (GWAS) approach to identify resistance genes or QTLs in 338 spring wheat breeding lines from public and private sectors that were predominately developed in the Americas. A total of 46 QTLs were identified for field and seedling traits and approximately 20–30 confer field resistance in varying degrees. The 10 QTLs accounting for the most variation in field resistance explained 26–30% of the total variation (depending on traits: percent severity, coefficient of infection or response type). Similarly, the 10 QTLs accounting for most of the variation in seedling resistance to different races explained 24–34% of the variation, after correcting for population structure. Two potentially novel QTLs (QLr.umn-1AL, QLr.umn-4AS) were identified. Identification of novel genes or QTLs and validation of previously identified genes or QTLs for seedling and especially adult plant resistance will enhance understanding of leaf rust resistance and assist breeding for resistant wheat varieties. We also developed computer programs to automate field and seedling rust phenotype data conversions. This is the first GWAS study of leaf rust resistance in elite wheat breeding lines genotyped with high density 90K SNP arrays. PMID:26849364

Genome-wide association and genomic prediction identifies associated loci and predicts the sensitivity of Tobacco ringspot virus in soybean plant introduction

USDA-ARS?s Scientific Manuscript database

The genome-wide association study (GWAS) is a useful tool for detecting and characterizing traits of interest including those associated with disease resistance in soybean. The availability of 50,000 single nucleotide polymorphism (SNP) markers (SoySNP50K iSelect BeadChip; www.soybase.org) on 19,652...

The impact of genotyping-by-sequencing pipelines on SNP discovery and identification of markers associated verticillium wilt resistance in autotetraploid alfalfa (sedicago sativa l.)

USDA-ARS?s Scientific Manuscript database

Verticillium wilt (VW) of alfalfa is a soilborne disease that causes severe yield loss in alfalfa. To identify molecular markers associated with VW resistance, an integrated framework of genome-wide association study (GWAS) with high-throughput genotyping by sequencing (GBS) was used for mapping lo...

Searching new signals for production traits through gene-based association analysis in three Italian cattle breeds.

PubMed

Capomaccio, Stefano; Milanesi, Marco; Bomba, Lorenzo; Cappelli, Katia; Nicolazzi, Ezequiel L; Williams, John L; Ajmone-Marsan, Paolo; Stefanon, Bruno

2015-08-01

Genome-wide association studies (GWAS) have been widely applied to disentangle the genetic basis of complex traits. In cattle breeds, classical GWAS approaches with medium-density marker panels are far from conclusive, especially for complex traits. This is due to the intrinsic limitations of GWAS and the assumptions that are made to step from the association signals to the functional variations. Here, we applied a gene-based strategy to prioritize genotype-phenotype associations found for milk production and quality traits with classical approaches in three Italian dairy cattle breeds with different sample sizes (Italian Brown n = 745; Italian Holstein n = 2058; Italian Simmental n = 477). Although classical regression on single markers revealed only a single genome-wide significant genotype-phenotype association, for Italian Holstein, the gene-based approach identified specific genes in each breed that are associated with milk physiology and mammary gland development. As no standard method has yet been established to step from variation to functional units (i.e., genes), the strategy proposed here may contribute to revealing new genes that play significant roles in complex traits, such as those investigated here, amplifying low association signals using a gene-centric approach. © 2015 Stichting International Foundation for Animal Genetics.

A Powerful Approach to Estimating Annotation-Stratified Genetic Covariance via GWAS Summary Statistics.

PubMed

Lu, Qiongshi; Li, Boyang; Ou, Derek; Erlendsdottir, Margret; Powles, Ryan L; Jiang, Tony; Hu, Yiming; Chang, David; Jin, Chentian; Dai, Wei; He, Qidu; Liu, Zefeng; Mukherjee, Shubhabrata; Crane, Paul K; Zhao, Hongyu

2017-12-07

Despite the success of large-scale genome-wide association studies (GWASs) on complex traits, our understanding of their genetic architecture is far from complete. Jointly modeling multiple traits' genetic profiles has provided insights into the shared genetic basis of many complex traits. However, large-scale inference sets a high bar for both statistical power and biological interpretability. Here we introduce a principled framework to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics. Through theoretical and numerical analyses, we demonstrate that our method provides accurate covariance estimates, thereby enabling researchers to dissect both the shared and distinct genetic architecture across traits to better understand their etiologies. Among 50 complex traits with publicly accessible GWAS summary statistics (N total ≈ 4.5 million), we identified more than 170 pairs with statistically significant genetic covariance. In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) and amyotrophic lateral sclerosis (ALS), two major neurodegenerative diseases, in single-nucleotide polymorphisms (SNPs) with high minor allele frequencies and in SNPs located in the predicted functional genome. Joint analysis of LOAD, ALS, and other traits highlights LOAD's correlation with cognitive traits and hints at an autoimmune component for ALS. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genome-Wide Association Mapping of Acid Soil Resistance in Barley (Hordeum vulgare L.)

PubMed Central

Zhou, Gaofeng; Broughton, Sue; Zhang, Xiao-Qi; Ma, Yanling; Zhou, Meixue; Li, Chengdao

2016-01-01

Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) have been used to detect QTLs underlying complex traits in major crops. In this study, we collected 218 barley (Hordeum vulgare L.) lines including wild barley and cultivated barley from China, Canada, Australia, and Europe. A total of 408 polymorphic markers were used for population structure and LD analysis. GWAS for acid soil resistance were performed on the population using a general linkage model (GLM) and a mixed linkage model (MLM), respectively. A total of 22 QTLs (quantitative trait loci) were detected with the GLM and MLM analyses. Two QTLs, close to markers bPb-1959 (133.1 cM) and bPb-8013 (86.7 cM), localized on chromosome 1H and 4H respectively, were consistently detected in two different trials with both the GLM and MLM analyses. Furthermore, bPb-8013, the closest marker to the major Al3+ resistance gene HvAACT1 in barley, was identified to be QTL5. The QTLs could be used in marker-assisted selection to identify and pyramid different loci for improved acid soil resistance in barley. PMID:27064793

The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)

PubMed Central

MacArthur, Jacqueline; Bowler, Emily; Cerezo, Maria; Gil, Laurent; Hall, Peggy; Hastings, Emma; Junkins, Heather; McMahon, Aoife; Milano, Annalisa; Morales, Joannella; Pendlington, Zoe May; Welter, Danielle; Burdett, Tony; Hindorff, Lucia; Flicek, Paul; Cunningham, Fiona; Parkinson, Helen

2017-01-01

The NHGRI-EBI GWAS Catalog has provided data from published genome-wide association studies since 2008. In 2015, the database was redesigned and relocated to EMBL-EBI. The new infrastructure includes a new graphical user interface (www.ebi.ac.uk/gwas/), ontology supported search functionality and an improved curation interface. These developments have improved the data release frequency by increasing automation of curation and providing scaling improvements. The range of available Catalog data has also been extended with structured ancestry and recruitment information added for all studies. The infrastructure improvements also support scaling for larger arrays, exome and sequencing studies, allowing the Catalog to adapt to the needs of evolving study design, genotyping technologies and user needs in the future. PMID:27899670

Pharmacoethnicity in Paclitaxel-Induced Sensory Peripheral Neuropathy

PubMed Central

Komatsu, Masaaki; Wheeler, Heather E.; Chung, Suyoun; Low, Siew-Kee; Wing, Claudia; Delaney, Shannon M.; Gorsic, Lidija K.; Takahashi, Atsushi; Kubo, Michiaki; Kroetz, Deanna L.; Zhang, Wei; Nakamura, Yusuke; Dolan, M. Eileen

2015-01-01

Purpose Paclitaxel is used worldwide in the treatment of breast, lung, ovarian and other cancers. Sensory peripheral neuropathy is an associated adverse effect that cannot be predicted, prevented or mitigated. To better understand the contribution of germline genetic variation to paclitaxel-induced peripheral neuropathy, we undertook an integrative approach that combines genome-wide association study (GWAS) data generated from HapMap lymphoblastoid cell lines (LCLs) and Asian patients. Methods GWAS was performed with paclitaxel-induced cytotoxicity generated in 363 LCLs and with paclitaxel-induced neuropathy from 145 Asian patients. A gene-based approach was used to identify overlapping genes and compare to a European clinical cohort of paclitaxel-induced neuropathy. Neurons derived from human induced pluripotent stem cells were used for functional validation of candidate genes. Results SNPs near AIPL1 were significantly associated with paclitaxel-induced cytotoxicity in Asian LCLs (P < 10−6). Decreased expression of AIPL1 resulted in decreased sensitivity of neurons to paclitaxel by inducing neurite morphological changes as measured by increased relative total outgrowth, number of processes and mean process length. Using a gene-based analysis, there were 32 genes that overlapped between Asian LCL cytotoxicity and Asian patient neuropathy (P < 0.05) including BCR. Upon BCR knockdown, there was an increase in neuronal sensitivity to paclitaxel as measured by neurite morphological characteristics. Conclusion We identified genetic variants associated with Asian paclitaxel-induced cytotoxicity and functionally validated the AIPL1 and BCR in a neuronal cell model. Furthermore, the integrative pharmacogenomics approach of LCL/patient GWAS may help prioritize target genes associated with chemotherapeutic-induced peripheral neuropathy. PMID:26015512

Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses.

PubMed

Painter, Jodie N; O'Mara, Tracy A; Morris, Andrew P; Cheng, Timothy H T; Gorman, Maggie; Martin, Lynn; Hodson, Shirley; Jones, Angela; Martin, Nicholas G; Gordon, Scott; Henders, Anjali K; Attia, John; McEvoy, Mark; Holliday, Elizabeth G; Scott, Rodney J; Webb, Penelope M; Fasching, Peter A; Beckmann, Matthias W; Ekici, Arif B; Hein, Alexander; Rübner, Matthias; Hall, Per; Czene, Kamila; Dörk, Thilo; Dürst, Matthias; Hillemanns, Peter; Runnebaum, Ingo; Lambrechts, Diether; Amant, Frederic; Annibali, Daniela; Depreeuw, Jeroen; Vanderstichele, Adriaan; Goode, Ellen L; Cunningham, Julie M; Dowdy, Sean C; Winham, Stacey J; Trovik, Jone; Hoivik, Erling; Werner, Henrica M J; Krakstad, Camilla; Ashton, Katie; Otton, Geoffrey; Proietto, Tony; Tham, Emma; Mints, Miriam; Ahmed, Shahana; Healey, Catherine S; Shah, Mitul; Pharoah, Paul D P; Dunning, Alison M; Dennis, Joe; Bolla, Manjeet K; Michailidou, Kyriaki; Wang, Qin; Tyrer, Jonathan P; Hopper, John L; Peto, Julian; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Zondervan, Krina T; Nyholt, Dale R; MacGregor, Stuart; Montgomery, Grant W; Tomlinson, Ian; Easton, Douglas F; Thompson, Deborah J; Spurdle, Amanda B

2018-05-01

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (r g  = 0.23, P = 9.3 × 10 -3 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10 -3 ) and concordance in effect direction (P = 2.0 × 10 -3 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10 -5 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10 -8 , OR = 1.11, 95% CI = 1.07-1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

How rare bone diseases have informed our knowledge of complex diseases.

PubMed

Johnson, Mark L

2016-01-01

Rare bone diseases, generally defined as monogenic traits with either autosomal recessive or dominant patterns of inheritance, have provided a rich database of genes and associated pathways over the past 2-3 decades. The molecular genetic dissection of these bone diseases has yielded some major surprises in terms of the causal genes and/or involved pathways. The discovery of genes/pathways involved in diseases such as osteopetrosis, osteosclerosis, osteogenesis imperfecta and many other rare bone diseases have all accelerated our understanding of complex traits. Importantly these discoveries have provided either direct validation for a specific gene embedded in a group of genes within an interval identified through a complex trait genome-wide association study (GWAS) or based upon the pathway associated with a monogenic trait gene, provided a means to prioritize a large number of genes for functional validation studies. In some instances GWAS studies have yielded candidate genes that fall within linkage intervals associated with monogenic traits and resulted in the identification of causal mutations in those rare diseases. Driving all of this discovery is a complement of technologies such as genome sequencing, bioinformatics and advanced statistical analysis methods that have accelerated genetic dissection and greatly reduced the cost. Thus, rare bone disorders in partnership with GWAS have brought us to the brink of a new era of personalized genomic medicine in which the prevention and management of complex diseases will be driven by the molecular understanding of each individuals contributing genetic risks for disease.

Natural resistance to Meningococcal Disease related to CFH loci: Meta-analysis of genome-wide association studies.

PubMed

Martinón-Torres, Federico; Png, Eileen; Khor, Chiea Chuen; Davila, Sonia; Wright, Victoria J; Sim, Kar Seng; Vega, Ana; Fachal, Laura; Inwald, David; Nadel, Simon; Carrol, Enitan D; Martinón-Torres, Nazareth; Alonso, Sonia Marcos; Carracedo, Angel; Morteruel, Elvira; López-Bayón, Julio; Torre, Andrés Concha; Monge, Cristina Calvo; de Aguilar, Pilar Azcón González; Torné, Elisabeth Esteban; Martínez-Padilla, María Del Carmen; Martinón-Sánchez, José María; Levin, Michael; Hibberd, Martin L; Salas, Antonio

2016-11-02

Meningococcal disease (MD) remains an important infectious cause of life threatening infection in both industrialized and resource poor countries. Genetic factors influence both occurrence and severity of presentation, but the genes responsible are largely unknown. We performed a genome-wide association study (GWAS) examining 5,440,063 SNPs in 422 Spanish MD patients and 910 controls. We then performed a meta-analysis of the Spanish GWAS with GWAS data from the United Kingdom (combined cohorts: 897 cases and 5,613 controls; 4,898,259 SNPs). The meta-analysis identified strong evidence of association (P-value ≤ 5 × 10 -8 ) in 20 variants located at the CFH gene. SNP rs193053835 showed the most significant protective effect (Odds Ratio (OR) = 0.62, 95% confidence interval (C.I.) = 0.52-0.73; P-value = 9.62 × 10 -9 ). Five other variants had been previously reported to be associated with susceptibility to MD, including the missense SNP rs1065489 (OR = 0.64, 95% C.I.) = 0.55-0.76, P-value = 3.25 × 10 -8 ). Theoretical predictions point to a functional effect of rs1065489, which may be directly responsible for protection against MD. Our study confirms the association of CFH with susceptibility to MD and strengthens the importance of this link in understanding pathogenesis of the disease.

Nutrigenetics and nutrigenomics of atherosclerosis.

PubMed

Merched, Aksam J; Chan, Lawrence

2013-06-01

The latest genome-wide association studies (GWAS) have re-energized our effort to understand the genetic basis of atherosclerotic cardiovascular disease. Although the knowledge generated by GWAS has confirmed that mediators of inflammation and perturbed lipid metabolism are major players in cardiovascular disease (CVD) development, much of individual disease heritability remains unexplained by the variants identified through GWAS. Moreover, results from interventions that aim at the pharmaceutical modification of lipid parameters fall short of expectation. These elusive treatment goals based on heritability studies highlight a key supportive, and perhaps even primary, role of nutritional therapy to achieve better health outcomes. Nonetheless, effective and specific interventions for CVD prevention using principles of "personalized" nutrition require a better knowledge of gene-diet interactions, an area that remains poorly explored. Dietary fatty acids such as omega-3 polyunsaturated fatty acids (PUFAs) are an excellent example of a widely studied "environment" that interacts with the genetic makeup in relation to CVD. A thorough exploration of the nutrigenomics and nutrigenetics of omega-3 PUFAs is key to understanding the etiology, and developing effective preventive measures. In this review, we will summarize the current state of knowledge of genetic interactions with omega-3 PUFAs in modulating lipid metabolism and inflammation, and defining health outcomes. Nutrigenetics and nutrigenomics are still in their infancy with respect to CVD prediction and therapy. Integration of the progress in the omics, including metabolomics, lipidomics, transcriptomics, and proteomics, coupled with advances in nutrigenomic and nutrigenetic research will move us towards personalized medicine as the ultimate paradigm of responsible clinical practice.

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure underpinning obesity

PubMed Central

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

Amerindian-specific regions under positive selection harbour new lipid variants in Latinos

PubMed Central

Ko, Arthur; Cantor, Rita M.; Weissglas-Volkov, Daphna; Nikkola, Elina; Reddy, Prasad M. V. Linga; Sinsheimer, Janet S.; Pasaniuc, Bogdan; Brown, Robert; Alvarez, Marcus; Rodriguez, Alejandra; Rodriguez-Guillen, Rosario; Bautista, Ivette C.; Arellano-Campos, Olimpia; Muñoz-Hernández, Linda L.; Salomaa, Veikko; Kaprio, Jaakko; Jula, Antti; Jauhiainen, Matti; Heliövaara, Markku; Raitakari, Olli; Lehtimäki, Terho; Eriksson, Johan G.; Perola, Markus; Lohmueller, Kirk E.; Matikainen, Niina; Taskinen, Marja-Riitta; Rodriguez-Torres, Maribel; Riba, Laura; Tusie-Luna, Teresa; Aguilar-Salinas, Carlos A.; Pajukanta, Päivi

2014-01-01

Dyslipidemia and obesity are especially prevalent in populations with Amerindian backgrounds, such as Mexican–Americans, which predispose these populations to cardiovascular disease. Here we design an approach, known as the cross-population allele screen (CPAS), which we conduct prior to a genome-wide association study (GWAS) in 19,273 Europeans and Mexicans, in order to identify Amerindian risk genes in Mexicans. Utilizing CPAS to restrict the GWAS input variants to only those differing in frequency between the two populations, we identify novel Amerindian lipid genes, receptor-related orphan receptor alpha (RORA) and salt-inducible kinase 3 (SIK3), and three loci previously unassociated with dyslipidemia or obesity. We also detect lipoprotein lipase (LPL) and apolipoprotein A5 (APOA5) harbouring specific Amerindian signatures of risk variants and haplotypes. Notably, we observe that SIK3 and one novel lipid locus underwent positive selection in Mexicans. Furthermore, after a high-fat meal, the SIK3 risk variant carriers display high triglyceride levels. These findings suggest that Amerindian-specific genetic architecture leads to a higher incidence of dyslipidemia and obesity in modern Mexicans. PMID:24886709

Genome-wide association study of perioperative myocardial infarction after coronary artery bypass surgery.

PubMed

Kertai, Miklos D; Li, Yi-Ju; Li, Yen-Wei; Ji, Yunqi; Alexander, John; Newman, Mark F; Smith, Peter K; Joseph, Diane; Mathew, Joseph P; Podgoreanu, Mihai V

2015-05-06

Identification of patient subpopulations susceptible to develop myocardial infarction (MI) or, conversely, those displaying either intrinsic cardioprotective phenotypes or highly responsive to protective interventions remain high-priority knowledge gaps. We sought to identify novel common genetic variants associated with perioperative MI in patients undergoing coronary artery bypass grafting using genome-wide association methodology. 107 secondary and tertiary cardiac surgery centres across the USA. We conducted a stage I genome-wide association study (GWAS) in 1433 ethnically diverse patients of both genders (112 cases/1321 controls) from the Genetics of Myocardial Adverse Outcomes and Graft Failure (GeneMAGIC) study, and a stage II analysis in an expanded population of 2055 patients (225 cases/1830 controls) combined from the GeneMAGIC and Duke Perioperative Genetics and Safety Outcomes (PEGASUS) studies. Patients undergoing primary non-emergent coronary bypass grafting were included. The primary outcome variable was perioperative MI, defined as creatine kinase MB isoenzyme (CK-MB) values ≥10× upper limit of normal during the first postoperative day, and not attributable to preoperative MI. Secondary outcomes included postoperative CK-MB as a quantitative trait, or a dichotomised phenotype based on extreme quartiles of the CK-MB distribution. Following quality control and adjustment for clinical covariates, we identified 521 single nucleotide polymorphisms in the stage I GWAS analysis. Among these, 8 common variants in 3 genes or intergenic regions met p<10(-5) in stage II. A secondary analysis using CK-MB as a quantitative trait (minimum p=1.26×10(-3) for rs609418), or a dichotomised phenotype based on extreme CK-MB values (minimum p=7.72×10(-6) for rs4834703) supported these findings. Pathway analysis revealed that genes harbouring top-scoring variants cluster in pathways of biological relevance to extracellular matrix remodelling, endoplasmic reticulum-to-Golgi transport and inflammation. Using a two-stage GWAS and pathway analysis, we identified and prioritised several potential susceptibility loci for perioperative MI. 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.

Genome-wide Pleiotropy Between Parkinson Disease and Autoimmune Diseases.

PubMed

Witoelar, Aree; Jansen, Iris E; Wang, Yunpeng; Desikan, Rahul S; Gibbs, J Raphael; Blauwendraat, Cornelis; Thompson, Wesley K; Hernandez, Dena G; Djurovic, Srdjan; Schork, Andrew J; Bettella, Francesco; Ellinghaus, David; Franke, Andre; Lie, Benedicte A; McEvoy, Linda K; Karlsen, Tom H; Lesage, Suzanne; Morris, Huw R; Brice, Alexis; Wood, Nicholas W; Heutink, Peter; Hardy, John; Singleton, Andrew B; Dale, Anders M; Gasser, Thomas; Andreassen, Ole A; Sharma, Manu

2017-07-01

Recent genome-wide association studies (GWAS) and pathway analyses supported long-standing observations of an association between immune-mediated diseases and Parkinson disease (PD). The post-GWAS era provides an opportunity for cross-phenotype analyses between different complex phenotypes. To test the hypothesis that there are common genetic risk variants conveying risk of both PD and autoimmune diseases (ie, pleiotropy) and to identify new shared genetic variants and their pathways by applying a novel statistical framework in a genome-wide approach. Using the conjunction false discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune diseases among 138 511 individuals of European ancestry and systemically investigated pleiotropy between PD and type 1 diabetes, Crohn disease, ulcerative colitis, rheumatoid arthritis, celiac disease, psoriasis, and multiple sclerosis. NeuroX data (6927 PD cases and 6108 controls) were used for replication. The study investigated the biological correlation between the top loci through protein-protein interaction and changes in the gene expression and methylation levels. The dates of the analysis were June 10, 2015, to March 4, 2017. The primary outcome was a list of novel loci and their pathways involved in PD and autoimmune diseases. Genome-wide conjunctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between PD and autoimmune diseases, including known PD loci adjacent to GAK, HLA-DRB5, LRRK2, and MAPT for rheumatoid arthritis, ulcerative colitis and Crohn disease. Replication confirmed the involvement of HLA, LRRK2, MAPT, TRIM10, and SETD1A in PD. Among the novel genes discovered, WNT3, KANSL1, CRHR1, BOLA2, and GUCY1A3 are within a protein-protein interaction network with known PD genes. A subset of novel loci was significantly associated with changes in methylation or expression levels of adjacent genes. The study findings provide novel mechanistic insights into PD and autoimmune diseases and identify a common genetic pathway between these phenotypes. The results may have implications for future therapeutic trials involving anti-inflammatory agents.

Female-specific Association Between Variants on Chromosome 9 and Self-reported Diagnosis of Irritable Bowel Syndrome.

PubMed

Bonfiglio, Ferdinando; Zheng, Tenghao; Garcia-Etxebarria, Koldo; Hadizadeh, Fatemeh; Bujanda, Luis; Bresso, Francesca; Agreus, Lars; Andreasson, Anna; Dlugosz, Aldona; Lindberg, Greger; Schmidt, Peter T; Karling, Pontus; Ohlsson, Bodil; Simren, Magnus; Walter, Susanna; Nardone, Gerardo; Cuomo, Rosario; Usai-Satta, Paolo; Galeazzi, Francesca; Neri, Matteo; Portincasa, Piero; Bellini, Massimo; Barbara, Giovanni; Latiano, Anna; Hübenthal, Matthias; Thijs, Vincent; Netea, Mihai G; Jonkers, Daisy; Chang, Lin; Mayer, Emeran A; Wouters, Mira M; Boeckxstaens, Guy; Camilleri, Michael; Franke, Andre; Zhernakova, Alexandra; D'Amato, Mauro

2018-04-04

Genetic factors are believed to affect risk for irritable bowel syndrome (IBS), but there have been no sufficiently powered and adequately sized studies. To identify DNA variants associated with IBS risk, we performed a genome-wide association study (GWAS) of the large UK Biobank population-based cohort, which includes genotype and health data from 500,000 participants. We studied 7,287,191 high-quality single-nucleotide polymorphisms in individuals who self-reported a doctor's diagnosis of IBS (cases; m=9576) compared to the remainder of the cohort (controls; n=336,499) (mean age of study subjects, 40-69 years). Genome-wide significant findings were further investigated in 2045 patients with IBS from tertiary centers and 7955 population controls from Europe and the United States, and a small general population sample from Sweden (n=249). Functional annotation of GWAS results was carried out by integrating data from multiple biorepositories, to obtain biological insights from the observed associations. We identified a genome-wide significant association on chromosome 9q31.2 (SNP rs10512344; P=3.57×10 -8 ), in a region previously linked to age at menarche, and 13 additional loci of suggestive significance (P<5.0×10 -6 ). Sex-stratified analyses revealed that the variants at 9q32.1 affect risk of IBS in only women (P=4.29×10 -10 in UK Biobank) and also associate with constipation-predominant IBS in women (P=.015 in the tertiary cohort) and harder stools in women (P=.0012 in the population-based sample). Functional annotation of the 9q32.1 locus identified 8 candidate genes, including the elongator complex protein 1 gene (ELP1 or IKBKAP), which is mutated in patients with familial dysautonomia. In a sufficiently powered GWAS of IBS, we associated variants at the locus 9q32.1 with risk of IBS in women. This observation may provide additional rationale for investigating the role of sex hormones and autonomic dysfunction in IBS. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.

Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle.

PubMed

Nayeri, Shadi; Sargolzaei, Mehdi; Abo-Ismail, Mohammed K; May, Natalie; Miller, Stephen P; Schenkel, Flavio; Moore, Stephen S; Stothard, Paul

2016-06-10

Genome-wide association studies (GWAS) are a powerful tool for detecting genomic regions explaining variation in phenotype. The objectives of the present study were to identify or refine the positions of genomic regions affecting milk production, milk components and fertility traits in Canadian Holstein cattle, and to use these positions to identify genes and pathways that may influence these traits. Several QTL regions were detected for milk production (MILK), fat production (FAT), protein production (PROT) and fat and protein deviation (FATD, PROTD respectively). The identified QTL regions for production traits (including milk production) support previous findings and some overlap with genes with known relevant biological functions identified in earlier studies such as DGAT1 and CPSF1. A significant region on chromosome 21 overlapping with the gene FAM181A and not previous linked to fertility in dairy cattle was identified for the calving to first service interval and days open. A functional enrichment analysis of the GWAS results yielded GO terms consistent with the specific phenotypes tested, for example GO terms GO:0007595 (lactation) and GO:0043627 (response to estrogen) for milk production (MILK), GO:0051057 (positive regulation of small GTPase mediated signal transduction) for fat production (FAT), GO:0040019 (positive regulation of embryonic development) for first service to calving interval (CTFS) and GO:0043268 (positive regulation of potassium ion transport) for days open (DO). In other cases the connection between the enriched GO terms and the traits were less clear, for example GO:0003279 (cardiac septum development) for FAT and GO:0030903 (notochord development) for DO trait. The chromosomal regions and enriched pathways identified in this study confirm several previous findings and highlight new regions and pathways that may contribute to variation in production or fertility traits in dairy cattle.

Rapid scoring of genes in microbial pan-genome-wide association studies with Scoary.

PubMed

Brynildsrud, Ola; Bohlin, Jon; Scheffer, Lonneke; Eldholm, Vegard

2016-11-25

Genome-wide association studies (GWAS) have become indispensable in human medicine and genomics, but very few have been carried out on bacteria. Here we introduce Scoary, an ultra-fast, easy-to-use, and widely applicable software tool that scores the components of the pan-genome for associations to observed phenotypic traits while accounting for population stratification, with minimal assumptions about evolutionary processes. We call our approach pan-GWAS to distinguish it from traditional, single nucleotide polymorphism (SNP)-based GWAS. Scoary is implemented in Python and is available under an open source GPLv3 license at https://github.com/AdmiralenOla/Scoary .

GWAS of clinically defined gout and subtypes identifies multiple susceptibility loci that include urate transporter genes.

PubMed

Nakayama, Akiyoshi; Nakaoka, Hirofumi; Yamamoto, Ken; Sakiyama, Masayuki; Shaukat, Amara; Toyoda, Yu; Okada, Yukinori; Kamatani, Yoichiro; Nakamura, Takahiro; Takada, Tappei; Inoue, Katsuhisa; Yasujima, Tomoya; Yuasa, Hiroaki; Shirahama, Yuko; Nakashima, Hiroshi; Shimizu, Seiko; Higashino, Toshihide; Kawamura, Yusuke; Ogata, Hiraku; Kawaguchi, Makoto; Ohkawa, Yasuyuki; Danjoh, Inaho; Tokumasu, Atsumi; Ooyama, Keiko; Ito, Toshimitsu; Kondo, Takaaki; Wakai, Kenji; Stiburkova, Blanka; Pavelka, Karel; Stamp, Lisa K; Dalbeth, Nicola; Sakurai, Yutaka; Suzuki, Hiroshi; Hosoyamada, Makoto; Fujimori, Shin; Yokoo, Takashi; Hosoya, Tatsuo; Inoue, Ituro; Takahashi, Atsushi; Kubo, Michiaki; Ooyama, Hiroshi; Shimizu, Toru; Ichida, Kimiyoshi; Shinomiya, Nariyoshi; Merriman, Tony R; Matsuo, Hirotaka

2017-05-01

A genome-wide association study (GWAS) of gout and its subtypes was performed to identify novel gout loci, including those that are subtype-specific. Putative causal association signals from a GWAS of 945 clinically defined gout cases and 1213 controls from Japanese males were replicated with 1396 cases and 1268 controls using a custom chip of 1961 single nucleotide polymorphisms (SNPs). We also first conducted GWASs of gout subtypes. Replication with Caucasian and New Zealand Polynesian samples was done to further validate the loci identified in this study. In addition to the five loci we reported previously, further susceptibility loci were identified at a genome-wide significance level (p<5.0×10 -8 ): urate transporter genes ( SLC22A12 and SLC17A1 ) and HIST1H2BF-HIST1H4E for all gout cases, and NIPAL1 and FAM35A for the renal underexcretion gout subtype. While NIPAL1 encodes a magnesium transporter, functional analysis did not detect urate transport via NIPAL1, suggesting an indirect association with urate handling. Localisation analysis in the human kidney revealed expression of NIPAL1 and FAM35A mainly in the distal tubules, which suggests the involvement of the distal nephron in urate handling in humans. Clinically ascertained male patients with gout and controls of Caucasian and Polynesian ancestries were also genotyped, and FAM35A was associated with gout in all cases. A meta-analysis of the three populations revealed FAM35A to be associated with gout at a genome-wide level of significance (p meta =3.58×10 -8 ). Our findings including novel gout risk loci provide further understanding of the molecular pathogenesis of gout and lead to a novel concept for the therapeutic target of gout/hyperuricaemia. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Novel Common Genetic Susceptibility Loci for Colorectal Cancer.

PubMed

Schmit, Stephanie L; Edlund, Christopher K; Schumacher, Fredrick R; Gong, Jian; Harrison, Tabitha A; Huyghe, Jeroen R; Qu, Chenxu; Melas, Marilena; Van Den Berg, David J; Wang, Hansong; Tring, Stephanie; Plummer, Sarah J; Albanes, Demetrius; Alonso, M Henar; Amos, Christopher I; Anton, Kristen; Aragaki, Aaron K; Arndt, Volker; Barry, Elizabeth L; Berndt, Sonja I; Bezieau, Stéphane; Bien, Stephanie; Bloomer, Amanda; Boehm, Juergen; Boutron-Ruault, Marie-Christine; Brenner, Hermann; Brezina, Stefanie; Buchanan, Daniel D; Butterbach, Katja; Caan, Bette J; Campbell, Peter T; Carlson, Christopher S; Castelao, Jose E; Chan, Andrew T; Chang-Claude, Jenny; Chanock, Stephen J; Cheng, Iona; Cheng, Ya-Wen; Chin, Lee Soo; Church, James M; Church, Timothy; Coetzee, Gerhard A; Cotterchio, Michelle; Cruz Correa, Marcia; Curtis, Keith R; Duggan, David; Easton, Douglas F; English, Dallas; Feskens, Edith J M; Fischer, Rocky; FitzGerald, Liesel M; Fortini, Barbara K; Fritsche, Lars G; Fuchs, Charles S; Gago-Dominguez, Manuela; Gala, Manish; Gallinger, Steven J; Gauderman, W James; Giles, Graham G; Giovannucci, Edward L; Gogarten, Stephanie M; Gonzalez-Villalpando, Clicerio; Gonzalez-Villalpando, Elena M; Grady, William M; Greenson, Joel K; Gsur, Andrea; Gunter, Marc; Haiman, Christopher A; Hampe, Jochen; Harlid, Sophia; Harju, John F; Hayes, Richard B; Hofer, Philipp; Hoffmeister, Michael; Hopper, John L; Huang, Shu-Chen; Huerta, Jose Maria; Hudson, Thomas J; Hunter, David J; Idos, Gregory E; Iwasaki, Motoki; Jackson, Rebecca D; Jacobs, Eric J; Jee, Sun Ha; Jenkins, Mark A; Jia, Wei-Hua; Jiao, Shuo; Joshi, Amit D; Kolonel, Laurence N; Kono, Suminori; Kooperberg, Charles; Krogh, Vittorio; Kuehn, Tilman; Küry, Sébastien; LaCroix, Andrea; Laurie, Cecelia A; Lejbkowicz, Flavio; Lemire, Mathieu; Lenz, Heinz-Josef; Levine, David; Li, Christopher I; Li, Li; Lieb, Wolfgang; Lin, Yi; Lindor, Noralane M; Liu, Yun-Ru; Loupakis, Fotios; Lu, Yingchang; Luh, Frank; Ma, Jing; Mancao, Christoph; Manion, Frank J; Markowitz, Sanford D; Martin, Vicente; Matsuda, Koichi; Matsuo, Keitaro; McDonnell, Kevin J; McNeil, Caroline E; Milne, Roger; Molina, Antonio J; Mukherjee, Bhramar; Murphy, Neil; Newcomb, Polly A; Offit, Kenneth; Omichessan, Hanane; Palli, Domenico; Cotoré, Jesus P Paredes; Pérez-Mayoral, Julyann; Pharoah, Paul D; Potter, John D; Qu, Conghui; Raskin, Leon; Rennert, Gad; Rennert, Hedy S; Riggs, Bridget M; Schafmayer, Clemens; Schoen, Robert E; Sellers, Thomas A; Seminara, Daniela; Severi, Gianluca; Shi, Wei; Shibata, David; Shu, Xiao-Ou; Siegel, Erin M; Slattery, Martha L; Southey, Melissa; Stadler, Zsofia K; Stern, Mariana C; Stintzing, Sebastian; Taverna, Darin; Thibodeau, Stephen N; Thomas, Duncan C; Trichopoulou, Antonia; Tsugane, Shoichiro; Ulrich, Cornelia M; van Duijnhoven, Franzel J B; van Guelpan, Bethany; Vijai, Joseph; Virtamo, Jarmo; Weinstein, Stephanie J; White, Emily; Win, Aung Ko; Wolk, Alicja; Woods, Michael; Wu, Anna H; Wu, Kana; Xiang, Yong-Bing; Yen, Yun; Zanke, Brent W; Zeng, Yi-Xin; Zhang, Ben; Zubair, Niha; Kweon, Sun-Seog; Figueiredo, Jane C; Zheng, Wei; Marchand, Loic Le; Lindblom, Annika; Moreno, Victor; Peters, Ulrike; Casey, Graham; Hsu, Li; Conti, David V; Gruber, Stephen B

2018-06-16

Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. We conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Dissection of complicate genetic architecture and breeding perspective of cottonseed traits by genome-wide association study.

PubMed

Du, Xiongming; Liu, Shouye; Sun, Junling; Zhang, Gengyun; Jia, Yinhua; Pan, Zhaoe; Xiang, Haitao; He, Shoupu; Xia, Qiuju; Xiao, Songhua; Shi, Weijun; Quan, Zhiwu; Liu, Jianguang; Ma, Jun; Pang, Baoyin; Wang, Liru; Sun, Gaofei; Gong, Wenfang; Jenkins, Johnie N; Lou, Xiangyang; Zhu, Jun; Xu, Haiming

2018-06-13

Cottonseed is one of the most important raw materials for plant protein, oil and alternative biofuel for diesel engines. Understanding the complex genetic basis of cottonseed traits is requisite for achieving efficient genetic improvement of the traits. However, it is not yet clear about their genetic architecture in genomic level. GWAS has been an effective way to explore genetic basis of quantitative traits in human and many crops. This study aims to dissect genetic mechanism seven cottonseed traits by a GWAS for genetic improvement. A genome-wide association study (GWAS) based on a full gene model with gene effects as fixed and gene-environment interaction as random, was conducted for protein, oil and 5 fatty acids using 316 accessions and ~ 390 K SNPs. Totally, 124 significant quantitative trait SNPs (QTSs), consisting of 16, 21, 87 for protein, oil and fatty acids (palmitic, linoleic, oleic, myristic, stearic), respectively, were identified and the broad-sense heritability was estimated from 71.62 to 93.43%; no QTS-environment interaction was detected for the protein, the palmitic and the oleic contents; the protein content was predominantly controlled by epistatic effects accounting for 65.18% of the total variation, but the oil content and the fatty acids except the palmitic were mainly determined by gene main effects and no epistasis was detected for the myristic and the stearic. Prediction of superior pure line and hybrid revealed the potential of the QTSs in the improvement of cottonseed traits, and the hybrid could achieve higher or lower genetic values compared with pure lines. This study revealed complex genetic architecture of seven cottonseed traits at whole genome-wide by mixed linear model approach; the identified genetic variants and estimated genetic component effects of gene, gene-gene and gene-environment interaction provide cotton geneticist or breeders new knowledge on the genetic mechanism of the traits and the potential molecular breeding design strategy.