Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis.

PubMed

Lee, Hyokyeong; Moody-Davis, Asher; Saha, Utsab; Suzuki, Brian M; Asarnow, Daniel; Chen, Steven; Arkin, Michelle; Caffrey, Conor R; Singh, Rahul

2012-01-01

Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind.

Quantification and clustering of phenotypic screening data using time-series analysis for chemotherapy of schistosomiasis

PubMed Central

2012-01-01

Background Neglected tropical diseases, especially those caused by helminths, constitute some of the most common infections of the world's poorest people. Development of techniques for automated, high-throughput drug screening against these diseases, especially in whole-organism settings, constitutes one of the great challenges of modern drug discovery. Method We present a method for enabling high-throughput phenotypic drug screening against diseases caused by helminths with a focus on schistosomiasis. The proposed method allows for a quantitative analysis of the systemic impact of a drug molecule on the pathogen as exhibited by the complex continuum of its phenotypic responses. This method consists of two key parts: first, biological image analysis is employed to automatically monitor and quantify shape-, appearance-, and motion-based phenotypes of the parasites. Next, we represent these phenotypes as time-series and show how to compare, cluster, and quantitatively reason about them using techniques of time-series analysis. Results We present results on a number of algorithmic issues pertinent to the time-series representation of phenotypes. These include results on appropriate representation of phenotypic time-series, analysis of different time-series similarity measures for comparing phenotypic responses over time, and techniques for clustering such responses by similarity. Finally, we show how these algorithmic techniques can be used for quantifying the complex continuum of phenotypic responses of parasites. An important corollary is the ability of our method to recognize and rigorously group parasites based on the variability of their phenotypic response to different drugs. Conclusions The methods and results presented in this paper enable automatic and quantitative scoring of high-throughput phenotypic screens focused on helmintic diseases. Furthermore, these methods allow us to analyze and stratify parasites based on their phenotypic response to drugs. Together, these advancements represent a significant breakthrough for the process of drug discovery against schistosomiasis in particular and can be extended to other helmintic diseases which together afflict a large part of humankind. PMID:22369037

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

Unveiling network-based functional features through integration of gene expression into protein networks.

PubMed

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

A novel mutation m.8561C>G in MT-ATP6/8 causing a mitochondrial syndrome with ataxia, peripheral neuropathy, diabetes mellitus, and hypergonadotropic hypogonadism.

PubMed

Kytövuori, Laura; Lipponen, Joonas; Rusanen, Harri; Komulainen, Tuomas; Martikainen, Mika H; Majamaa, Kari

2016-11-01

Defects in the respiratory chain or mitochondrial ATP synthase (complex V) result in mitochondrial dysfunction that is an important cause of inherited neurological disease. Two of the subunits of complex V are encoded by MT-ATP6 and MT-ATP8 in the mitochondrial genome. Pathogenic mutations in MT-ATP6 are associated with the Leigh syndrome, the syndrome of neuropathy, ataxia, and retinitis pigmentosa (NARP), as well as with non-classical phenotypes, while MT-ATP8 is less frequently mutated in patients with mitochondrial disease. We investigated two adult siblings presenting with features of cerebellar ataxia, peripheral neuropathy, diabetes mellitus, sensorineural hearing impairment, and hypergonadotropic hypogonadism. As the phenotype was suggestive of mitochondrial disease, mitochondrial DNA was sequenced and a novel heteroplasmic mutation m.8561C>G in the overlapping region of the MT-ATP6 and MT-ATP8 was found. The mutation changed amino acids in both subunits. Mutation heteroplasmy correlated with the disease phenotype in five family members. An additional assembly intermediate of complex V and increased amount of subcomplex F 1 were observed in myoblasts of the two patients, but the total amount of complex V was unaffected. Furthermore, intracellular ATP concentration was lower in patient myoblasts indicating defective energy production. We suggest that the m.8561C>G mutation in MT-ATP6/8 is pathogenic, leads biochemically to impaired assembly and decreased ATP production of complex V, and results clinically in a phenotype with the core features of cerebellar ataxia, peripheral neuropathy, diabetes mellitus, and hypergonadotropic hypogonadism.

Retinal dystrophies, genomic applications in diagnosis and prospects for therapy

PubMed Central

Nash, Benjamin M.; Wright, Dale C.; Grigg, John R.; Bennetts, Bruce

2015-01-01

Retinal dystrophies (RDs) are degenerative diseases of the retina which have marked clinical and genetic heterogeneity. Common presentations among these disorders include night or colour blindness, tunnel vision and subsequent progression to complete blindness. The known causative disease genes have a variety of developmental and functional roles with mutations in more than 120 genes shown to be responsible for the phenotypes. In addition, mutations within the same gene have been shown to cause different disease phenotypes, even amongst affected individuals within the same family highlighting further levels of complexity. The known disease genes encode proteins involved in retinal cellular structures, phototransduction, the visual cycle, and photoreceptor structure or gene regulation. This review aims to demonstrate the high degree of genetic complexity in both the causative disease genes and their associated phenotypes, highlighting the more common clinical manifestation of retinitis pigmentosa (RP). The review also provides insight to recent advances in genomic molecular diagnosis and gene and cell-based therapies for the RDs. PMID:26835369

A functional U-statistic method for association analysis of sequencing data.

PubMed

Jadhav, Sneha; Tong, Xiaoran; Lu, Qing

2017-11-01

Although sequencing studies hold great promise for uncovering novel variants predisposing to human diseases, the high dimensionality of the sequencing data brings tremendous challenges to data analysis. Moreover, for many complex diseases (e.g., psychiatric disorders) multiple related phenotypes are collected. These phenotypes can be different measurements of an underlying disease, or measurements characterizing multiple related diseases for studying common genetic mechanism. Although jointly analyzing these phenotypes could potentially increase the power of identifying disease-associated genes, the different types of phenotypes pose challenges for association analysis. To address these challenges, we propose a nonparametric method, functional U-statistic method (FU), for multivariate analysis of sequencing data. It first constructs smooth functions from individuals' sequencing data, and then tests the association of these functions with multiple phenotypes by using a U-statistic. The method provides a general framework for analyzing various types of phenotypes (e.g., binary and continuous phenotypes) with unknown distributions. Fitting the genetic variants within a gene using a smoothing function also allows us to capture complexities of gene structure (e.g., linkage disequilibrium, LD), which could potentially increase the power of association analysis. Through simulations, we compared our method to the multivariate outcome score test (MOST), and found that our test attained better performance than MOST. In a real data application, we apply our method to the sequencing data from Minnesota Twin Study (MTS) and found potential associations of several nicotine receptor subunit (CHRN) genes, including CHRNB3, associated with nicotine dependence and/or alcohol dependence. © 2017 WILEY PERIODICALS, INC.

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers

PubMed Central

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-01-01

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait. PMID:16451570

A power study of bivariate LOD score analysis of a complex trait and fear/discomfort with strangers.

PubMed

Ji, Fei; Lee, Dayoung; Mendell, Nancy Role

2005-12-30

Complex diseases are often reported along with disease-related traits (DRT). Sometimes investigators consider both disease and DRT phenotypes separately and sometimes they consider individuals as affected if they have either the disease or the DRT, or both. We propose instead to consider the joint distribution of the disease and the DRT and do a linkage analysis assuming a pleiotropic model. We evaluated our results through analysis of the simulated datasets provided by Genetic Analysis Workshop 14. We first conducted univariate linkage analysis of the simulated disease, Kofendrerd Personality Disorder and one of its simulated associated traits, phenotype b (fear/discomfort with strangers). Subsequently, we considered the bivariate phenotype, which combined the information on Kofendrerd Personality Disorder and fear/discomfort with strangers. We developed a program to perform bivariate linkage analysis using an extension to the Elston-Stewart peeling method of likelihood calculation. Using this program we considered the microsatellites within 30 cM of the gene pleiotropic for this simulated disease and DRT. Based on 100 simulations of 300 families we observed excellent power to detect linkage within 10 cM of the disease locus using the DRT and the bivariate trait.

Phenotype-genotype correlations in Leigh syndrome: new insights from a multicentre study of 96 patients.

PubMed

Sofou, Kalliopi; de Coo, Irenaeus F M; Ostergaard, Elsebet; Isohanni, Pirjo; Naess, Karin; De Meirleir, Linda; Tzoulis, Charalampos; Uusimaa, Johanna; Lönnqvist, Tuula; Bindoff, Laurence Albert; Tulinius, Már; Darin, Niklas

2018-01-01

Leigh syndrome is a phenotypically and genetically heterogeneous mitochondrial disorder. While some genetic defects are associated with well-described phenotypes, phenotype-genotype correlations in Leigh syndrome are not fully explored. We aimed to identify phenotype-genotype correlations in Leigh syndrome in a large cohort of systematically evaluated patients. We studied 96 patients with genetically confirmed Leigh syndrome diagnosed and followed in eight European centres specialising in mitochondrial diseases. We found that ataxia, ophthalmoplegia and cardiomyopathy were more prevalent among patients with mitochondrial DNA defects. Patients with mutations in MT-ND and NDUF genes with complex I deficiency shared common phenotypic features, such as early development of central nervous system disease, followed by high occurrence of cardiac and ocular manifestations. The cerebral cortex was affected in patients with NDUF mutations significantly more often than the rest of the cohort. Patients with the m.8993T>G mutation in MT-ATP6 gene had more severe clinical and radiological manifestations and poorer disease outcome compared with patients with the m.8993T>C mutation. Our study provides new insights into phenotype-genotype correlations in Leigh syndrome and particularly in patients with complex I deficiency and with defects in the mitochondrial ATP synthase. © 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.

METAGENOMICS AND PERSONALIZED MEDICINE

PubMed Central

Virgin, Herbert W.; Todd, John A.

2015-01-01

The microbiome is a complex community of Bacteria, Archaea, Eukarya and viruses that infect humans and live in our tissues. It contributes the majority of genetic information to our metagenome, and consequently, to our resistance and susceptibility to diseases, especially common inflammatory diseases, such as type 1 diabetes, ulcerative colitis, and Crohn's disease. Here we discuss how host-gene-microbial interactions are major determinants for the development of these multifactorial chronic disorders and thus, for the relationship between genotype and phenotype. We also explore how genome-wide association studies (GWAS) on autoimmune and inflammatory diseases are uncovering mechanism-based sub-types for these disorders. Applying these emerging concepts will permit a more complete understanding of the etiologies of complex diseases and underpin the development of both next generation animal models and new therapeutic strategies for targeting personalized disease phenotypes. PMID:21962506

Mouse Models as Predictors of Human Responses: Evolutionary Medicine.

PubMed

Uhl, Elizabeth W; Warner, Natalie J

Mice offer a number of advantages and are extensively used to model human diseases and drug responses. Selective breeding and genetic manipulation of mice have made many different genotypes and phenotypes available for research. However, in many cases, mouse models have failed to be predictive. Important sources of the prediction problem have been the failure to consider the evolutionary basis for species differences, especially in drug metabolism, and disease definitions that do not reflect the complexity of gene expression underlying disease phenotypes. Incorporating evolutionary insights into mouse models allow for unique opportunities to characterize the effects of diet, different gene expression profiles, and microbiomics underlying human drug responses and disease phenotypes.

Real-Time Assessment of Wellness and Disease in Daily Life.

PubMed

Ausiello, Dennis; Lipnick, Scott

2015-09-01

The next frontier in medicine involves better quantifying human traits, known as "phenotypes." Biological markers have been directly associated with disease risks, but poor measurement of behaviors such as diet and exercise limits our understanding of preventive measures. By joining together an uncommonly wide range of disciplines and expertise, the Kavli HUMAN Project will advance measurement of behavioral phenotypes, as well as environmental factors that impact behavior. By following the same individuals over time, KHP will liberate new understanding of dynamic links between behavioral phenotypes, disease, and the broader environment. As KHP advances understanding of the bio-behavioral complex, it will seed new approaches to the diagnosis, prevention, and treatment of human disease.

A next generation multiscale view of inborn errors of metabolism

PubMed Central

Argmann, Carmen A.; Houten, Sander M.; Zhu, Jun; Schadt, Eric E.

2015-01-01

Inborn errors of metabolism (IEM) are not unlike common diseases. They often present as a spectrum of disease phenotypes that correlates poorly with the severity of the disease-causing mutations. This greatly impacts patient care and reveals fundamental gaps in our knowledge of disease modifying biology. Systems biology approaches that integrate multi-omics data into molecular networks have significantly improved our understanding of complex diseases. Similar approaches to study IEM are rare despite their complex nature. We highlight that existing common disease-derived datasets and networks can be repurposed to generate novel mechanistic insight in IEM and potentially identify candidate modifiers. While understanding disease pathophysiology will advance the IEM field, the ultimate goal should be to understand per individual how their phenotype emerges given their primary mutation on the background of their whole genome, not unlike personalized medicine. We foresee that panomics and network strategies combined with recent experimental innovations will facilitate this. PMID:26712461

Closed genomes and phenotypes of seven Histophilus somni isolates from beef calves with bovine respiratory disease complex

USDA-ARS?s Scientific Manuscript database

Background: Histophilus somni is a fastidious gram-negative opportunistic pathogenic Pasteurellacea that affects multiple organ systems and is one of three principle bacterial species contributing to bovine respiratory disease complex (BRDC) in North American feed yard cattle. BRDC outbreaks accoun...

Current concepts in targeting chronic obstructive pulmonary disease pharmacotherapy: making progress towards personalised management.

PubMed

Woodruff, Prescott G; Agusti, Alvar; Roche, Nicolas; Singh, Dave; Martinez, Fernando J

2015-05-02

Chronic obstructive pulmonary disease (COPD) is a common, complex, and heterogeneous disorder that is responsible for substantial and growing morbidity, mortality, and health-care expense worldwide. Of imperative importance to decipher the complexity of COPD is to identify groups of patients with similar clinical characteristics, prognosis, or therapeutic needs, the so-called clinical phenotypes. This strategy is logical for research but might be of little clinical value because clinical phenotypes can overlap in the same patient and the same clinical phenotype could result from different biological mechanisms. With the goal to match assessment with treatment choices, the latest iteration of guidelines from the Global Initiative for Chronic Obstructive Lung Disease reorganised treatment objectives into two categories: to improve symptoms (ie, dyspnoea and health status) and to decrease future risk (as predicted by forced expiratory volume in 1 s level and exacerbations history). This change thus moves treatment closer to individualised medicine with available bronchodilators and anti-inflammatory drugs. Yet, future treatment options are likely to include targeting endotypes that represent subtypes of patients defined by a distinct pathophysiological mechanism. Specific biomarkers of these endotypes would be particularly useful in clinical practice, especially in patients in which clinical phenotype alone is insufficient to identify the underlying endotype. A few series of potential COPD endotypes and biomarkers have been suggested. Empirical knowledge will be gained from proof-of-concept trials in COPD with emerging drugs that target specific inflammatory pathways. In every instance, specific endotype and biomarker efforts will probably be needed for the success of these trials, because the pathways are likely to be operative in only a subset of patients. Network analysis of human diseases offers the possibility to improve understanding of disease pathobiological complexity and to help with the development of new treatment alternatives and, importantly, a reclassification of complex diseases. All these developments should pave the way towards personalised treatment of patients with COPD in the clinic. Copyright © 2015 Elsevier Ltd. All rights reserved.

Linking rare and common disease: mapping clinical disease-phenotypes to ontologies in therapeutic target validation.

PubMed

Sarntivijai, Sirarat; Vasant, Drashtti; Jupp, Simon; Saunders, Gary; Bento, A Patrícia; Gonzalez, Daniel; Betts, Joanna; Hasan, Samiul; Koscielny, Gautier; Dunham, Ian; Parkinson, Helen; Malone, James

2016-01-01

The Centre for Therapeutic Target Validation (CTTV - https://www.targetvalidation.org/) was established to generate therapeutic target evidence from genome-scale experiments and analyses. CTTV aims to support the validity of therapeutic targets by integrating existing and newly-generated data. Data integration has been achieved in some resources by mapping metadata such as disease and phenotypes to the Experimental Factor Ontology (EFO). Additionally, the relationship between ontology descriptions of rare and common diseases and their phenotypes can offer insights into shared biological mechanisms and potential drug targets. Ontologies are not ideal for representing the sometimes associated type relationship required. This work addresses two challenges; annotation of diverse big data, and representation of complex, sometimes associated relationships between concepts. Semantic mapping uses a combination of custom scripting, our annotation tool 'Zooma', and expert curation. Disease-phenotype associations were generated using literature mining on Europe PubMed Central abstracts, which were manually verified by experts for validity. Representation of the disease-phenotype association was achieved by the Ontology of Biomedical AssociatioN (OBAN), a generic association representation model. OBAN represents associations between a subject and object i.e., disease and its associated phenotypes and the source of evidence for that association. The indirect disease-to-disease associations are exposed through shared phenotypes. This was applied to the use case of linking rare to common diseases at the CTTV. EFO yields an average of over 80% of mapping coverage in all data sources. A 42% precision is obtained from the manual verification of the text-mined disease-phenotype associations. This results in 1452 and 2810 disease-phenotype pairs for IBD and autoimmune disease and contributes towards 11,338 rare diseases associations (merged with existing published work [Am J Hum Genet 97:111-24, 2015]). An OBAN result file is downloadable at http://sourceforge.net/p/efo/code/HEAD/tree/trunk/src/efoassociations/. Twenty common diseases are linked to 85 rare diseases by shared phenotypes. A generalizable OBAN model for association representation is presented in this study. Here we present solutions to large-scale annotation-ontology mapping in the CTTV knowledge base, a process for disease-phenotype mining, and propose a generic association model, 'OBAN', as a means to integrate disease using shared phenotypes. EFO is released monthly and available for download at http://www.ebi.ac.uk/efo/.

FIG4 regulates lysosome membrane homeostasis independent of phosphatase function.

PubMed

Bharadwaj, Rajnish; Cunningham, Kathleen M; Zhang, Ke; Lloyd, Thomas E

2016-02-15

FIG4 is a phosphoinositide phosphatase that is mutated in several diseases including Charcot-Marie-Tooth Disease 4J (CMT4J) and Yunis-Varon syndrome (YVS). To investigate the mechanism of disease pathogenesis, we generated Drosophila models of FIG4-related diseases. Fig4 null mutant animals are viable but exhibit marked enlargement of the lysosomal compartment in muscle cells and neurons, accompanied by an age-related decline in flight ability. Transgenic animals expressing Drosophila Fig4 missense mutations corresponding to human pathogenic mutations can partially rescue lysosomal expansion phenotypes, consistent with these mutations causing decreased FIG4 function. Interestingly, Fig4 mutations predicted to inactivate FIG4 phosphatase activity rescue lysosome expansion phenotypes, and mutations in the phosphoinositide (3) phosphate kinase Fab1 that performs the reverse enzymatic reaction also causes a lysosome expansion phenotype. Since FIG4 and FAB1 are present together in the same biochemical complex, these data are consistent with a model in which FIG4 serves a phosphatase-independent biosynthetic function that is essential for lysosomal membrane homeostasis. Lysosomal phenotypes are suppressed by genetic inhibition of Rab7 or the HOPS complex, demonstrating that FIG4 functions after endosome-to-lysosome fusion. Furthermore, disruption of the retromer complex, implicated in recycling from the lysosome to Golgi, does not lead to similar phenotypes as Fig4, suggesting that the lysosomal defects are not due to compromised retromer-mediated recycling of endolysosomal membranes. These data show that FIG4 plays a critical noncatalytic function in maintaining lysosomal membrane homeostasis, and that this function is disrupted by mutations that cause CMT4J and YVS. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

FIG4 regulates lysosome membrane homeostasis independent of phosphatase function

PubMed Central

Bharadwaj, Rajnish; Cunningham, Kathleen M.; Zhang, Ke; Lloyd, Thomas E.

2016-01-01

FIG4 is a phosphoinositide phosphatase that is mutated in several diseases including Charcot-Marie-Tooth Disease 4J (CMT4J) and Yunis-Varon syndrome (YVS). To investigate the mechanism of disease pathogenesis, we generated Drosophila models of FIG4-related diseases. Fig4 null mutant animals are viable but exhibit marked enlargement of the lysosomal compartment in muscle cells and neurons, accompanied by an age-related decline in flight ability. Transgenic animals expressing Drosophila Fig4 missense mutations corresponding to human pathogenic mutations can partially rescue lysosomal expansion phenotypes, consistent with these mutations causing decreased FIG4 function. Interestingly, Fig4 mutations predicted to inactivate FIG4 phosphatase activity rescue lysosome expansion phenotypes, and mutations in the phosphoinositide (3) phosphate kinase Fab1 that performs the reverse enzymatic reaction also causes a lysosome expansion phenotype. Since FIG4 and FAB1 are present together in the same biochemical complex, these data are consistent with a model in which FIG4 serves a phosphatase-independent biosynthetic function that is essential for lysosomal membrane homeostasis. Lysosomal phenotypes are suppressed by genetic inhibition of Rab7 or the HOPS complex, demonstrating that FIG4 functions after endosome-to-lysosome fusion. Furthermore, disruption of the retromer complex, implicated in recycling from the lysosome to Golgi, does not lead to similar phenotypes as Fig4, suggesting that the lysosomal defects are not due to compromised retromer-mediated recycling of endolysosomal membranes. These data show that FIG4 plays a critical noncatalytic function in maintaining lysosomal membrane homeostasis, and that this function is disrupted by mutations that cause CMT4J and YVS. PMID:26662798

The QDREC web server: determining dose-response characteristics of complex macroparasites in phenotypic drug screens.

PubMed

Asarnow, Daniel; Rojo-Arreola, Liliana; Suzuki, Brian M; Caffrey, Conor R; Singh, Rahul

2015-05-01

Neglected tropical diseases (NTDs) caused by helminths constitute some of the most common infections of the world's poorest people. The etiological agents are complex and recalcitrant to standard techniques of molecular biology. Drug screening against helminths has often been phenotypic and typically involves manual description of drug effect and efficacy. A key challenge is to develop automated, quantitative approaches to drug screening against helminth diseases. The quantal dose-response calculator (QDREC) constitutes a significant step in this direction. It can be used to automatically determine quantitative dose-response characteristics and half-maximal effective concentration (EC50) values using image-based readouts from phenotypic screens, thereby allowing rigorous comparisons of the efficacies of drug compounds. QDREC has been developed and validated in the context of drug screening for schistosomiasis, one of the most important NTDs. However, it is equally applicable to general phenotypic screening involving helminths and other complex parasites. QDREC is publically available at: http://haddock4.sfsu.edu/qdrec2/. Source code and datasets are at: http://tintin.sfsu.edu/projects/phenotypicAssays.html. rahul@sfsu.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mitochondrial proteomic profile of complex IV deficiency fibroblasts: rearrangement of oxidative phosphorylation complex/supercomplex and other metabolic pathways.

PubMed

Salvador-Severo, Karina; Gómez-Caudillo, Leopoldo; Quezada, Héctor; García-Trejo, José de Jesús; Cárdenas-Conejo, Alan; Vázquez-Memije, Martha Elisa; Minauro-Sanmiguel, Fernando

Mitochondriopathies are multisystem diseases affecting the oxidative phosphorylation (OXPHOS) system. Skin fibroblasts are a good model for the study of these diseases. Fibroblasts with a complex IV mitochondriopathy were used to determine the molecular mechanism and the main affected functions in this disease. Skin fibroblast were grown to assure disease phenotype. Mitochondria were isolated from these cells and their proteome extracted for protein identification. Identified proteins were validated with the MitoMiner database. Disease phenotype was corroborated on skin fibroblasts, which presented a complex IV defect. The mitochondrial proteome of these cells showed that the most affected proteins belonged to the OXPHOS system, mainly to the complexes that form supercomplexes or respirosomes (I, III, IV, and V). Defects in complex IV seemed to be due to assembly issues, which might prevent supercomplexes formation and efficient substrate channeling. It was also found that this mitochondriopathy affects other processes that are related to DNA genetic information flow (replication, transcription, and translation) as well as beta oxidation and tricarboxylic acid cycle. These data, as a whole, could be used for the better stratification of these diseases, as well as to optimize management and treatment options. Copyright © 2017 Hospital Infantil de México Federico Gómez. Publicado por Masson Doyma México S.A. All rights reserved.

Whole genome sequencing of one complex pedigree illustrates challenges with genomic medicine.

PubMed

Fang, Han; Wu, Yiyang; Yang, Hui; Yoon, Margaret; Jiménez-Barrón, Laura T; Mittelman, David; Robison, Reid; Wang, Kai; Lyon, Gholson J

2017-02-23

Human Phenotype Ontology (HPO) has risen as a useful tool for precision medicine by providing a standardized vocabulary of phenotypic abnormalities to describe presentations of human pathologies; however, there have been relatively few reports combining whole genome sequencing (WGS) and HPO, especially in the context of structural variants. We illustrate an integrative analysis of WGS and HPO using an extended pedigree, which involves Prader-Willi Syndrome (PWS), hereditary hemochromatosis (HH), and dysautonomia-like symptoms. A comprehensive WGS pipeline was used to ensure reliable detection of genomic variants. Beyond variant filtering, we pursued phenotypic prioritization of candidate genes using Phenolyzer. Regarding PWS, WGS confirmed a 5.5 Mb de novo deletion of the parental allele at 15q11.2 to 15q13.1. Phenolyzer successfully returned the diagnosis of PWS, and pinpointed clinically relevant genes in the deletion. Further, Phenolyzer revealed how each of the genes is linked with the phenotypes represented by HPO terms. For HH, WGS identified a known disease variant (p.C282Y) in HFE of an affected female. Analysis of HPO terms alone fails to provide a correct diagnosis, but Phenolyzer successfully revealed the phenotype-genotype relationship using a disease-centric approach. Finally, Phenolyzer also revealed the complexity behind dysautonomia-like symptoms, and seven variants that might be associated with the phenotypes were identified by manual filtering based on a dominant inheritance model. The integration of WGS and HPO can inform comprehensive molecular diagnosis for patients, eliminate false positives and reveal novel insights into undiagnosed diseases. Due to extreme heterogeneity and insufficient knowledge of human diseases, it is also important that phenotypic and genomic data are standardized and shared simultaneously.

Towards improving phenotype representation in OWL

PubMed Central

2012-01-01

Background Phenotype ontologies are used in species-specific databases for the annotation of mutagenesis experiments and to characterize human diseases. The Entity-Quality (EQ) formalism is a means to describe complex phenotypes based on one or more affected entities and a quality. EQ-based definitions have been developed for many phenotype ontologies, including the Human and Mammalian Phenotype ontologies. Methods We analyze formalizations of complex phenotype descriptions in the Web Ontology Language (OWL) that are based on the EQ model, identify several representational challenges and analyze potential solutions to address these challenges. Results In particular, we suggest a novel, role-based approach to represent relational qualities such as concentration of iron in spleen, discuss its ontological foundation in the General Formal Ontology (GFO) and evaluate its representation in OWL and the benefits it can bring to the representation of phenotype annotations. Conclusion Our analysis of OWL-based representations of phenotypes can contribute to improving consistency and expressiveness of formal phenotype descriptions. PMID:23046625

Sensitive periods in epigenetics: bringing us closer to complex behavioral phenotypes.

PubMed

Nagy, Corina; Turecki, Gustavo

2012-08-01

Genetic studies have attempted to elucidate causal mechanisms for the development of complex disease, but genome-wide associations have been largely unsuccessful in establishing these links. As an alternative link between genes and disease, recent efforts have focused on mechanisms that alter the function of genes without altering the underlying DNA sequence. Known as epigenetic mechanisms, these include DNA methylation, chromatin conformational changes through histone modifications, ncRNAs and, most recently, 5-hydroxymethylcytosine. Although DNA methylation is involved in normal development, aging and gene regulation, altered methylation patterns have been associated with disease. It is generally believed that early life constitutes a period during which there is increased sensitivity to the regulatory effects of epigenetic mechanisms. The purpose of this review is to outline the contribution of epigenetic mechanisms to genomic function, particularly in the development of complex behavioral phenotypes, focusing on the sensitive periods.

Sensitive Periods in Epigenetics: bringing us closer to complex behavioral phenotypes

PubMed Central

Nagy, Corina; Turecki, Gustavo

2017-01-01

Genetic studies have attempted to elucidate causal mechanisms for the development of complex disease but genome-wide associations have been largely unsuccessful in establishing these links. As an alternative link between genes and disease, recent efforts have focused on mechanisms that alter the function of genes without altering the underlying DNA sequence. Known as epigenetic mechanisms, these include: DNA methylation, chromatin conformational changes through histone modifications, non-coding RNAs, and most recently, 5-hydroxymethylcytosine. Though DNA methylation is involved in normal development, aging and gene regulation, altered methylation patterns have been associated with disease. It is generally believed that early life constitutes a period during which there is increased sensitivity to the regulatory effects of epigenetic mechanisms. The purpose of this review is to outline the contribution of epigenetic mechanisms to genomic function, particularly in the development of complex behavioral phenotypes, focusing on the sensitive periods. PMID:22920183

Associations among multiple markers and complex disease: models, algorithms, and applications.

PubMed

Assimes, Themistocles L; Olshen, Adam B; Narasimhan, Balasubramanian; Olshen, Richard A

2008-01-01

This chapter is a report on collaborations among its authors and others over many years. It devolves from our goal of understanding genes, their main and epistatic effects combined with interactions involving demographic and environmental features also, as together they predict genetically complex diseases. Thus, our goal is "association." Particular phenotypes of interest to us are hypertension, insulin resistance, angina, and myocardial infarction. Prediction of complex disease is notoriously difficult, though it would be made easier were we given strand-specific information on genotype. Unfortunately, with current technology, genotypic information comes to us "unphased." While obviously we have strand-specific information when genotype is homozygous, we do not have such information when genotype is heterozygous. To summarize, the ultimate goals of approaches we provide is to predict phenotype, typically untoward or not, within a specific window of time. Our approach is neither through linkage nor from finding haplotype frequencies per se.

Paradigms in Chronic Obstructive Pulmonary Disease: Phenotypes, Immunobiology, and Therapy with a Focus on Vascular Disease

PubMed Central

Schivo, Michael; Albertson, Timothy E.; Haczku, Angela; Kenyon, Nicholas J.; Zeki, Amir A.; Kuhn, Brooks T.; Louie, Samuel; Avdalovic, Mark V.

2018-01-01

Chronic obstructive pulmonary disease (COPD) is a complex and heterogenous syndrome that represents a major global health burden. COPD phenotypes have recently emerged based on large cohort studies addressing the need to better characterize the syndrome. Though comprehensive phenotyping is still at an early stage, factors such as ethnicity and radiographic, serum, and exhaled breath biomarkers have shown promise. COPD is also an immunological disease where innate and adaptive immune responses to the environment and tobacco smoke are altered. The frequent overlap between COPD and other systemic diseases, such as cardiovascular disease, have influenced COPD therapy, and treatments for both conditions may lead to improved patient outcomes. Here we discuss current paradigms that center on improving the definition of COPD, understanding the immunological overlap between COPD and vascular inflammation, and the treatment of COPD—with a focus on comorbid cardiovascular disease. PMID:28258130

Physiological Informatics: Collection and Analyses of Data from Wearable Sensors and Smartphone for Healthcare.

PubMed

Bai, Jinwei; Shen, Li; Sun, Huimin; Shen, Bairong

2017-01-01

Physiological data from wearable sensors and smartphone are accumulating rapidly, and this provides us the chance to collect dynamic and personalized information as phenotype to be integrated to genotype for the holistic understanding of complex diseases. This integration can be applied to early prediction and prevention of disease, therefore promoting the shifting of disease care tradition to the healthcare paradigm. In this chapter, we summarize the physiological signals which can be detected by wearable sensors, the sharing of the physiological big data, and the mining methods for the discovery of disease-associated patterns for personalized diagnosis and treatment. We discuss the challenges of physiological informatics about the storage, the standardization, the analyses, and the applications of the physiological data from the wearable sensors and smartphone. At last, we present our perspectives on the models for disentangling the complex relationship between early disease prediction and the mining of physiological phenotype data.

Mapping rare and common causal alleles for complex human diseases

PubMed Central

Raychaudhuri, Soumya

2011-01-01

Advances in genotyping and sequencing technologies have revolutionized the genetics of complex disease by locating rare and common variants that influence an individual’s risk for diseases, such as diabetes, cancers, and psychiatric disorders. However, to capitalize on this data for prevention and therapies requires the identification of causal alleles and a mechanistic understanding for how these variants contribute to the disease. After discussing the strategies currently used to map variants for complex diseases, this Primer explores how variants may be prioritized for follow-up functional studies and the challenges and approaches for assessing the contributions of rare and common variants to disease phenotypes. PMID:21962507

The Genotype and Phenotype (GaP) registry: a living biobank for the analysis of quantitative traits.

PubMed

Gregersen, Peter K; Klein, Gila; Keogh, Mary; Kern, Marlena; DeFranco, Margaret; Simpfendorfer, Kim R; Kim, Sun Jung; Diamond, Betty

2015-12-01

We describe the development of the Genotype and Phenotype (GaP) Registry, a living biobank of normal volunteers who are genotyped for genetic markers related to human disease. Participants in the GaP can be recalled for hypothesis driven study of disease associated genetic variants. The GaP has facilitated functional studies of several autoimmune disease associated loci including Csk, Blk, PDRM1 (Blimp-1) and PTPN22. It is likely that expansion of such living biobank registries will play an important role in studying and understanding the function of disease associated alleles in complex disease.

A Non-Degenerate Code of Deleterious Variants in Mendelian Loci Contributes to Complex Disease Risk

PubMed Central

Blair, David R.; Lyttle, Christopher S.; Mortensen, Jonathan M.; Bearden, Charles F.; Jensen, Anders Boeck; Khiabanian, Hossein; Melamed, Rachel; Rabadan, Raul; Bernstam, Elmer V.; Brunak, Søren; Jensen, Lars Juhl; Nicolae, Dan; Shah, Nigam H.; Grossman, Robert L.; Cox, Nancy J.; White, Kevin P.; Rzhetsky, Andrey

2013-01-01

Summary Whereas countless highly penetrant variants have been associated with Mendelian disorders, the genetic etiologies underlying complex diseases remain largely unresolved. Here, we examine the extent to which Mendelian variation contributes to complex disease risk by mining the medical records of over 110 million patients. We detect thousands of associations between Mendelian and complex diseases, revealing a non-degenerate, phenotypic code that links each complex disorder to a unique collection of Mendelian loci. Using genome-wide association results, we demonstrate that common variants associated with complex diseases are enriched in the genes indicated by this “Mendelian code.” Finally, we detect hundreds of comorbidity associations among Mendelian disorders, and we use probabilistic genetic modeling to demonstrate that Mendelian variants likely contribute non-additively to the risk for a subset of complex diseases. Overall, this study illustrates a complementary approach for mapping complex disease loci and provides unique predictions concerning the etiologies of specific diseases. PMID:24074861

Network Medicine: From Cellular Networks to the Human Diseasome

NASA Astrophysics Data System (ADS)

Barabasi, Albert-Laszlo

2014-03-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The tools of network science offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction not only enrich our understanding of complex systems, but are also essential to identify new disease genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases.

Network Medicine: A Network-based Approach to Human Disease

PubMed Central

Barabási, Albert-László; Gulbahce, Natali; Loscalzo, Joseph

2011-01-01

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular network. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships between apparently distinct (patho)phenotypes. Advances in this direction are essential to identify new diseases genes, to uncover the biological significance of disease-associated mutations identified by genome-wide association studies and full genome sequencing, and to identify drug targets and biomarkers for complex diseases. PMID:21164525

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

PubMed

Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott

2018-05-01

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

A Novel Lung Disease Phenotype Adjusted for Mortality Attrition for Cystic Fibrosis Genetic Modifier Studies

PubMed Central

Taylor, Chelsea; Commander, Clayton W.; Collaco, Joseph M.; Strug, Lisa J.; Li, Weili; Wright, Fred A.; Webel, Aaron D.; Pace, Rhonda G.; Stonebraker, Jaclyn R.; Naughton, Kathleen; Dorfman, Ruslan; Sandford, Andrew; Blackman, Scott M.; Berthiaume, Yves; Paré, Peter; Drumm, Mitchell L.; Zielenski, Julian; Durie, Peter; Cutting, Garry R.; Knowles, Michael R.; Corey, Mary

2011-01-01

SUMMARY Genetic studies of lung disease in Cystic Fibrosis are hampered by the lack of a severity measure that accounts for chronic disease progression and mortality attrition. Further, combining analyses across studies requires common phenotypes that are robust to study design and patient ascertainment. Using data from the North American Cystic Fibrosis Modifier Consortium (Canadian Consortium for CF Genetic Studies, Johns Hopkins University CF Twin and Sibling Study, and University of North Carolina/Case Western Reserve University Gene Modifier Study), the authors calculated age-specific CF percentile values of FEV1 which were adjusted for CF age-specific mortality data. The phenotype was computed for 2061 patients representing the Canadian CF population, 1137 extreme phenotype patients in the UNC/Case Western study, and 1323 patients from multiple CF sib families in the CF Twin and Sibling Study. Despite differences in ascertainment and median age, our phenotype score was distributed in all three samples in a manner consistent with ascertainment differences, reflecting the lung disease severity of each individual in the underlying population. The new phenotype score was highly correlated with the previously recommended complex phenotype, but the new phenotype is more robust for shorter follow-up and for extreme ages. A disease progression and mortality adjusted phenotype reduces the need for stratification or additional covariates, increasing statistical power and avoiding possible distortions. This approach will facilitate large scale genetic and environmental epidemiological studies which will provide targeted therapeutic pathways for the clinical benefit of patients with CF. PMID:21462361

Systems Genetics as a Tool to Identify Master Genetic Regulators in Complex Disease.

PubMed

Moreno-Moral, Aida; Pesce, Francesco; Behmoaras, Jacques; Petretto, Enrico

2017-01-01

Systems genetics stems from systems biology and similarly employs integrative modeling approaches to describe the perturbations and phenotypic effects observed in a complex system. However, in the case of systems genetics the main source of perturbation is naturally occurring genetic variation, which can be analyzed at the systems-level to explain the observed variation in phenotypic traits. In contrast with conventional single-variant association approaches, the success of systems genetics has been in the identification of gene networks and molecular pathways that underlie complex disease. In addition, systems genetics has proven useful in the discovery of master trans-acting genetic regulators of functional networks and pathways, which in many cases revealed unexpected gene targets for disease. Here we detail the central components of a fully integrated systems genetics approach to complex disease, starting from assessment of genetic and gene expression variation, linking DNA sequence variation to mRNA (expression QTL mapping), gene regulatory network analysis and mapping the genetic control of regulatory networks. By summarizing a few illustrative (and successful) examples, we highlight how different data-modeling strategies can be effectively integrated in a systems genetics study.

MicroCT-based phenomics in the zebrafish skeleton reveals virtues of deep phenotyping in a distributed organ system.

PubMed

Hur, Matthew; Gistelinck, Charlotte A; Huber, Philippe; Lee, Jane; Thompson, Marjorie H; Monstad-Rios, Adrian T; Watson, Claire J; McMenamin, Sarah K; Willaert, Andy; Parichy, David M; Coucke, Paul; Kwon, Ronald Y

2017-09-08

Phenomics, which ideally involves in-depth phenotyping at the whole-organism scale, may enhance our functional understanding of genetic variation. Here, we demonstrate methods to profile hundreds of phenotypic measures comprised of morphological and densitometric traits at a large number of sites within the axial skeleton of adult zebrafish. We show the potential for vertebral patterns to confer heightened sensitivity, with similar specificity, in discriminating mutant populations compared to analyzing individual vertebrae in isolation. We identify phenotypes associated with human brittle bone disease and thyroid stimulating hormone receptor hyperactivity. Finally, we develop allometric models and show their potential to aid in the discrimination of mutant phenotypes masked by alterations in growth. Our studies demonstrate virtues of deep phenotyping in a spatially distributed organ system. Analyzing phenotypic patterns may increase productivity in genetic screens, and facilitate the study of genetic variants associated with smaller effect sizes, such as those that underlie complex diseases.

Clinical Applications of Molecular Genetic Discoveries

PubMed Central

Marian, A.J.

2015-01-01

Genome-wide association studies (GWAS) of complex traits have mapped more than 15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as Next Generation Sequencing, to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population as well as in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: “The good physician treats the disease; the great physician treats the patient who has the disease.” The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease. PMID:26548329

A protein domain-centric approach for the comparative analysis of human and yeast phenotypically relevant mutations

PubMed Central

2013-01-01

Background The body of disease mutations with known phenotypic relevance continues to increase and is expected to do so even faster with the advent of new experimental techniques such as whole-genome sequencing coupled with disease association studies. However, genomic association studies are limited by the molecular complexity of the phenotype being studied and the population size needed to have adequate statistical power. One way to circumvent this problem, which is critical for the study of rare diseases, is to study the molecular patterns emerging from functional studies of existing disease mutations. Current gene-centric analyses to study mutations in coding regions are limited by their inability to account for the functional modularity of the protein. Previous studies of the functional patterns of known human disease mutations have shown a significant tendency to cluster at protein domain positions, namely position-based domain hotspots of disease mutations. However, the limited number of known disease mutations remains the main factor hindering the advancement of mutation studies at a functional level. In this paper, we address this problem by incorporating mutations known to be disruptive of phenotypes in other species. Focusing on two evolutionarily distant organisms, human and yeast, we describe the first inter-species analysis of mutations of phenotypic relevance at the protein domain level. Results The results of this analysis reveal that phenotypic mutations from yeast cluster at specific positions on protein domains, a characteristic previously revealed to be displayed by human disease mutations. We found over one hundred domain hotspots in yeast with approximately 50% in the exact same domain position as known human disease mutations. Conclusions We describe an analysis using protein domains as a framework for transferring functional information by studying domain hotspots in human and yeast and relating phenotypic changes in yeast to diseases in human. This first-of-a-kind study of phenotypically relevant yeast mutations in relation to human disease mutations demonstrates the utility of a multi-species analysis for advancing the understanding of the relationship between genetic mutations and phenotypic changes at the organismal level. PMID:23819456

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/.

Targeted next-generation sequencing reveals novel USH2A mutations associated with diverse disease phenotypes: implications for clinical and molecular diagnosis.

PubMed

Chen, Xue; Sheng, Xunlun; Liu, Xiaoxing; Li, Huiping; Liu, Yani; Rong, Weining; Ha, Shaoping; Liu, Wenzhou; Kang, Xiaoli; Zhao, Kanxing; Zhao, Chen

2014-01-01

USH2A mutations have been implicated in the disease etiology of several inherited diseases, including Usher syndrome type 2 (USH2), nonsyndromic retinitis pigmentosa (RP), and nonsyndromic deafness. The complex genetic and phenotypic spectrums relevant to USH2A defects make it difficult to manage patients with such mutations. In the present study, we aim to determine the genetic etiology and to characterize the correlated clinical phenotypes for three Chinese pedigrees with nonsyndromic RP, one with RP sine pigmento (RPSP), and one with USH2. Family histories and clinical details for all included patients were reviewed. Ophthalmic examinations included best corrected visual acuities, visual field measurements, funduscopy, and electroretinography. Targeted next-generation sequencing (NGS) was applied using two sequence capture arrays to reveal the disease causative mutations for each family. Genotype-phenotype correlations were also annotated. Seven USH2A mutations, including four missense substitutions (p.P2762A, p.G3320C, p.R3719H, and p.G4763R), two splice site variants (c.8223+1G>A and c.8559-2T>C), and a nonsense mutation (p.Y3745*), were identified as disease causative in the five investigated families, of which three reported to have consanguineous marriage. Among all seven mutations, six were novel, and one was recurrent. Two homozygous missense mutations (p.P2762A and p.G3320C) were found in one individual family suggesting a potential double hit effect. Significant phenotypic divergences were revealed among the five families. Three families of the five families were affected with early, moderated, or late onset RP, one with RPSP, and the other one with USH2. Our study expands the genotypic and phenotypic variability relevant to USH2A mutations, which would help with a clear insight into the complex genetic and phenotypic spectrums relevant to USH2A defects, and is complementary for a better management of patients with such mutations. We have also demonstrated that a targeted NGS approach is a valuable tool for the genetic diagnosis of USH2 and RP.

Targeted Next-Generation Sequencing Reveals Novel USH2A Mutations Associated with Diverse Disease Phenotypes: Implications for Clinical and Molecular Diagnosis

PubMed Central

Li, Huiping; Liu, Yani; Rong, Weining; Ha, Shaoping; Liu, Wenzhou; Kang, Xiaoli; Zhao, Kanxing; Zhao, Chen

2014-01-01

USH2A mutations have been implicated in the disease etiology of several inherited diseases, including Usher syndrome type 2 (USH2), nonsyndromic retinitis pigmentosa (RP), and nonsyndromic deafness. The complex genetic and phenotypic spectrums relevant to USH2A defects make it difficult to manage patients with such mutations. In the present study, we aim to determine the genetic etiology and to characterize the correlated clinical phenotypes for three Chinese pedigrees with nonsyndromic RP, one with RP sine pigmento (RPSP), and one with USH2. Family histories and clinical details for all included patients were reviewed. Ophthalmic examinations included best corrected visual acuities, visual field measurements, funduscopy, and electroretinography. Targeted next-generation sequencing (NGS) was applied using two sequence capture arrays to reveal the disease causative mutations for each family. Genotype-phenotype correlations were also annotated. Seven USH2A mutations, including four missense substitutions (p.P2762A, p.G3320C, p.R3719H, and p.G4763R), two splice site variants (c.8223+1G>A and c.8559-2T>C), and a nonsense mutation (p.Y3745*), were identified as disease causative in the five investigated families, of which three reported to have consanguineous marriage. Among all seven mutations, six were novel, and one was recurrent. Two homozygous missense mutations (p.P2762A and p.G3320C) were found in one individual family suggesting a potential double hit effect. Significant phenotypic divergences were revealed among the five families. Three families of the five families were affected with early, moderated, or late onset RP, one with RPSP, and the other one with USH2. Our study expands the genotypic and phenotypic variability relevant to USH2A mutations, which would help with a clear insight into the complex genetic and phenotypic spectrums relevant to USH2A defects, and is complementary for a better management of patients with such mutations. We have also demonstrated that a targeted NGS approach is a valuable tool for the genetic diagnosis of USH2 and RP. PMID:25133613

Phenotypic similarities and differences in patients with a p.Met112Ile mutation in SOX10.

PubMed

Pingault, Veronique; Pierre-Louis, Laurence; Chaoui, Asma; Verloes, Alain; Sarrazin, Elisabeth; Brandberg, Goran; Bondurand, Nadege; Uldall, Peter; Manouvrier-Hanu, Sylvie

2014-09-01

Waardenburg syndrome (WS) is characterized by an association of pigmentation abnormalities and sensorineural hearing loss. Four types, defined on clinical grounds, have been delineated, but this phenotypic classification correlates imperfectly with known molecular anomalies. SOX10 mutations have been found in patients with type II and type IV WS (i.e., with Hirschsprung disease), more complex syndromes, and partial forms of the disease. The phenotype induced by SOX10 mutations is highly variable and, except for the neurological forms of the disease, no genotype-phenotype correlation has been characterized to date. There is no mutation hotspot in SOX10 and most cases are sporadic, making it particularly difficult to correlate the phenotypic and genetic variability. This study reports on three independent families with SOX10 mutations predicted to result in the same missense mutation at the protein level (p.Met112Ile), offering a rare opportunity to improve our understanding of the mechanisms underlying phenotypic variability. The pigmentation defects of these patients are very similar, and the neurological symptoms showed a somewhat similar evolution over time, indicating a potential partial genotype-phenotype correlation. However, variability in gastrointestinal symptoms suggests that other genetic factors contribute to the expression of these phenotypes. No correlation between the rs2435357 polymorphism of RET and the expression of Hirschsprung disease was found. In addition, one of the patients has esophageal achalasia, which has rarely been described in WS. © 2014 Wiley Periodicals, Inc.

Phenotypic similarities and differences in patients with a p.Met112Ile mutation in SOX10

PubMed Central

Pingault, Veronique; Pierre-Louis, Laurence; Chaoui, Asma; Verloes, Alain; Sarrazin, Elisabeth; Brandberg, Goran; Bondurand, Nadege; Uldall, Peter; Manouvrier-Hanu, Sylvie

2014-01-01

Waardenburg syndrome (WS) is characterized by an association of pigmentation abnormalities and sensorineural hearing loss. Four types, defined on clinical grounds, have been delineated, but this phenotypic classification correlates imperfectly with known molecular anomalies. SOX10 mutations have been found in patients with type II and type IV WS (i.e., with Hirschsprung disease), more complex syndromes, and partial forms of the disease. The phenotype induced by SOX10 mutations is highly variable and, except for the neurological forms of the disease, no genotype-phenotype correlation has been characterized to date. There is no mutation hotspot in SOX10 and most cases are sporadic, making it particularly difficult to correlate the phenotypic and genetic variability. This study reports on three independent families with SOX10 mutations predicted to result in the same missense mutation at the protein level (p.Met112Ile), offering a rare opportunity to improve our understanding of the mechanisms underlying phenotypic variability. The pigmentation defects of these patients are very similar, and the neurological symptoms showed a somewhat similar evolution over time, indicating a potential partial genotype-phenotype correlation. However, variability in gastrointestinal symptoms suggests that other genetic factors contribute to the expression of these phenotypes. No correlation between the rs2435357 polymorphism of RET and the expression of Hirschsprung disease was found. In addition, one of the patients has esophageal achalasia, which has rarely been described in WS. PMID:24845202

γ-Secretase Heterogeneity in the Aph1 Subunit: Relevance for Alzheimer’s Disease

PubMed Central

Serneels, Lutgarde; Van Biervliet, Jérôme; Craessaerts, Katleen; Dejaegere, Tim; Horré, Katrien; Van Houtvin, Tine; Esselmann, Hermann; Paul, Sabine; Schäfer, Martin K.; Berezovska, Oksana; Hyman, Bradley T.; Sprangers, Ben; Sciot, Raf; Moons, Lieve; Jucker, Mathias; Yang, Zhixiang; May, Patrick C.; Karran, Eric; Wiltfang, Jens; D’Hooge, Rudi; De Strooper, Bart

2009-01-01

The γ-secretase complex plays a role in Alzheimer’s disease (AD) and cancer progression. The development of clinical useful inhibitors, however, is complicated by the role of the γ-secretase complex in regulated intramembrane proteolysis of Notch and other essential proteins. Different γ-secretase complexes containing different Presenilin or Aph1 protein subunits are present in various tissues. Here we show that these complexes have heterogeneous biochemical and physiological properties. Specific inactivation of the Aph1B γ-secretase in a murine Alzheimer’s disease model led to improvements of Alzheimer’s disease-relevant phenotypic features without any Notch-related side effects. The Aph1B complex contributes to total γ-secretase activity in the human brain, thus specific targeting of Aph1B-containing γ-secretase complexes may be helpful in generating less toxic therapies for Alzheimer’s disease. PMID:19299585

Predicting disease-related proteins based on clique backbone in protein-protein interaction network.

PubMed

Yang, Lei; Zhao, Xudong; Tang, Xianglong

2014-01-01

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.

Bridging epigenomics and complex disease: the basics.

PubMed

Teperino, Raffaele; Lempradl, Adelheid; Pospisilik, J Andrew

2013-05-01

The DNA sequence largely defines gene expression and phenotype. However, it is becoming increasingly clear that an additional chromatin-based regulatory network imparts both stability and plasticity to genome output, modifying phenotype independently of the genetic blueprint. Indeed, alterations in this "epigenetic" control layer underlie, at least in part, the reason for monozygotic twins being discordant for disease. Functionally, this regulatory layer comprises post-translational modifications of DNA and histones, as well as small and large noncoding RNAs. Together these regulate gene expression by changing chromatin organization and DNA accessibility. Successive technological advances over the past decade have enabled researchers to map the chromatin state with increasing accuracy and comprehensiveness, catapulting genetic research into a genome-wide era. Here, aiming particularly at the genomics/epigenomics newcomer, we review the epigenetic basis that has helped drive the technological shift and how this progress is shaping our understanding of complex disease.

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

A generalized association test based on U statistics.

PubMed

Wei, Changshuai; Lu, Qing

2017-07-01

Second generation sequencing technologies are being increasingly used for genetic association studies, where the main research interest is to identify sets of genetic variants that contribute to various phenotypes. The phenotype can be univariate disease status, multivariate responses and even high-dimensional outcomes. Considering the genotype and phenotype as two complex objects, this also poses a general statistical problem of testing association between complex objects. We here proposed a similarity-based test, generalized similarity U (GSU), that can test the association between complex objects. We first studied the theoretical properties of the test in a general setting and then focused on the application of the test to sequencing association studies. Based on theoretical analysis, we proposed to use Laplacian Kernel-based similarity for GSU to boost power and enhance robustness. Through simulation, we found that GSU did have advantages over existing methods in terms of power and robustness. We further performed a whole genome sequencing (WGS) scan for Alzherimer's disease neuroimaging initiative data, identifying three genes, APOE , APOC1 and TOMM40 , associated with imaging phenotype. We developed a C ++ package for analysis of WGS data using GSU. The source codes can be downloaded at https://github.com/changshuaiwei/gsu . weichangshuai@gmail.com ; qlu@epi.msu.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

The Search for Autism Disease Genes

ERIC Educational Resources Information Center

Wassink, Thomas H.; Brzustowicz, Linda M.; Bartlett, Christopher W.; Szatmari, Peter

2004-01-01

Autism is a heritable disorder characterized by phenotypic and genetic complexity. This review begins by surveying current linkage, gene association, and cytogenetic studies performed with the goal of identifying autism disease susceptibility variants. Though numerous linkages and associations have been identified, they tend to diminish upon…

Disease modeling and phenotypic drug screening for diabetic cardiomyopathy using human induced pluripotent stem cells.

PubMed

Drawnel, Faye M; Boccardo, Stefano; Prummer, Michael; Delobel, Frédéric; Graff, Alexandra; Weber, Michael; Gérard, Régine; Badi, Laura; Kam-Thong, Tony; Bu, Lei; Jiang, Xin; Hoflack, Jean-Christophe; Kiialainen, Anna; Jeworutzki, Elena; Aoyama, Natsuyo; Carlson, Coby; Burcin, Mark; Gromo, Gianni; Boehringer, Markus; Stahlberg, Henning; Hall, Benjamin J; Magnone, Maria Chiara; Kolaja, Kyle; Chien, Kenneth R; Bailly, Jacques; Iacone, Roberto

2014-11-06

Diabetic cardiomyopathy is a complication of type 2 diabetes, with known contributions of lifestyle and genetics. We develop environmentally and genetically driven in vitro models of the condition using human-induced-pluripotent-stem-cell-derived cardiomyocytes. First, we mimic diabetic clinical chemistry to induce a phenotypic surrogate of diabetic cardiomyopathy, observing structural and functional disarray. Next, we consider genetic effects by deriving cardiomyocytes from two diabetic patients with variable disease progression. The cardiomyopathic phenotype is recapitulated in the patient-specific cells basally, with a severity dependent on their original clinical status. These models are incorporated into successive levels of a screening platform, identifying drugs that preserve cardiomyocyte phenotype in vitro during diabetic stress. In this work, we present a patient-specific induced pluripotent stem cell (iPSC) model of a complex metabolic condition, showing the power of this technique for discovery and testing of therapeutic strategies for a disease with ever-increasing clinical significance. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Genotypic and phenotypic predictors of inflammation in patients with chronic kidney disease.

PubMed

Luttropp, Karin; Debowska, Malgorzata; Lukaszuk, Tomasz; Bobrowski, Leon; Carrero, Juan Jesus; Qureshi, Abdul Rashid; Stenvinkel, Peter; Lindholm, Bengt; Waniewski, Jacek; Nordfors, Louise

2016-12-01

In complex diseases such as chronic kidney disease (CKD), the risk of clinical complications is determined by interactions between phenotypic and genotypic factors. However, clinical epidemiological studies rarely attempt to analyse the combined effect of large numbers of phenotype and genotype features. We have recently shown that the relaxed linear separability (RLS) model of feature selection can address such complex issues. Here, it is applied to identify risk factors for inflammation in CKD. The RLS model was applied in 225 CKD stage 5 patients sampled in conjunction with dialysis initiation. Fifty-seven anthropometric or biochemical measurements and 79 genetic polymorphisms were entered into the model. The model was asked to identify phenotypes and genotypes that, when combined, could separate inflamed from non-inflamed patients. Inflammation was defined as a high-sensitivity C-reactive protein concentration above the median (5 mg/L). Among the 60 genotypic and phenotypic features predicting inflammation, 31 were genetic. Among the 10 strongest predictors of inflammation, 8 were single nucleotide polymorphisms located in the NAMPT, CIITA, BMP2 and PIK3CB genes, whereas fibrinogen and bone mineral density were the only phenotypic biomarkers. These results indicate a larger involvement of hereditary factors in inflammation than might have been expected and suggest that inclusion of genotype features in risk assessment studies is critical. The RLS model demonstrates that inflammation in CKD is determined by an extensive panel of factors and may prove to be a suitable tool that could enable a much-needed multifactorial approach as opposed to the commonly utilized single-factor analysis. © The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Implications of sex-specific selection for the genetic basis of disease.

PubMed

Morrow, Edward H; Connallon, Tim

2013-12-01

Mutation and selection are thought to shape the underlying genetic basis of many common human diseases. However, both processes depend on the context in which they occur, such as environment, genetic background, or sex. Sex has widely known effects on phenotypic expression of genotype, but an analysis of how it influences the evolutionary dynamics of disease-causing variants has not yet been explored. We develop a simple population genetic model of disease susceptibility and evaluate it using a biologically plausible empirically based distribution of fitness effects among contributing mutations. The model predicts that alleles under sex-differential selection, including sexually antagonistic alleles, will disproportionately contribute to genetic variation for disease predisposition, thereby generating substantial sexual dimorphism in the genetic architecture of complex (polygenic) diseases. This is because such alleles evolve into higher population frequencies for a given effect size, relative to alleles experiencing equally strong purifying selection in both sexes. Our results provide a theoretical justification for expecting a sexually dimorphic genetic basis for variation in complex traits such as disease. Moreover, they suggest that such dimorphism is interesting - not merely something to control for - because it reflects the action of natural selection in molding the evolution of common disease phenotypes.

The mitochondrial 13513G>A mutation is associated with Leigh disease phenotypes independent of complex I deficiency in muscle.

PubMed

Brautbar, Ariel; Wang, Jing; Abdenur, Jose E; Chang, Richard C; Thomas, Janet A; Grebe, Theresa A; Lim, Cynthia; Weng, Shao-Wen; Graham, Brett H; Wong, Lee-Jun

2008-08-01

The mitochondrial 13513G>A (D393N) mutation in the ND5 subunit of the respiratory chain complex I was initially described in association with MELAS syndrome. Recent observations have linked this mutation to Leigh disease. We screened for the 13513G>A mutation in a cohort of 265 patients with Leigh and Leigh-like disease. The mutation was found in a total of 5 patients. An additional patient who had clinical presentation consistent with a Leigh-like phenotype but with a normal brain MRI was added to the cohort. None of an additional 88 patients meeting MELAS disease criteria, nor 56 patients with respiratory chain deficiency screened for the 13513G>A were found positive for the mutation. The most frequent clinical manifestations in our patients were hypotonia, ocular and cerebellar involvement. Low mutation heteroplasmy in the range of 20-40% was observed in all 6 patients. This observation is consistent with the previously reported low heteroplasmy of this mutation in some patients with the 13513G>A mutation and complex I deficiency. However, normal complex I activity was observed in two patients in our cohort. As most patients with Leigh-like disease and the 13513G>A mutation have been described with complex I deficiency, this report adds to the previously reported subset of patients with normal respiratory complex function. We conclude that in any patient with Leigh or Leigh-like disease, testing for the 13513G>A mutation is clinically relevant and low mutant loads in blood or muscle may be considered pathogenic, in the presence of normal respiratory chain enzyme activities.

Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease.

PubMed

2017-12-01

Genetic variants have been associated with myriad molecular phenotypes that provide new insight into the range of mechanisms underlying genetic traits and diseases. Identifying any particular genetic variant's cascade of effects, from molecule to individual, requires assaying multiple layers of molecular complexity. We introduce the Enhancing GTEx (eGTEx) project that extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health.

Physiogenomic analysis of localized FMRI brain activity in schizophrenia.

PubMed

Windemuth, Andreas; Calhoun, Vince D; Pearlson, Godfrey D; Kocherla, Mohan; Jagannathan, Kanchana; Ruaño, Gualberto

2008-06-01

The search for genetic factors associated with disease is complicated by the complexity of the biological pathways linking genotype and phenotype. This analytical complexity is particularly concerning in diseases historically lacking reliable diagnostic biological markers, such as schizophrenia and other mental disorders. We investigate the use of functional magnetic resonance imaging (fMRI) as an intermediate phenotype (endophenotype) to identify physiogenomic associations to schizophrenia. We screened 99 subjects, 30 subjects diagnosed with schizophrenia, 13 unaffected relatives of schizophrenia patients, and 56 unrelated controls, for gene polymorphisms associated with fMRI activation patterns at two locations in temporal and frontal lobes previously implied in schizophrenia. A total of 22 single nucleotide polymorphisms (SNPs) in 15 genes from the dopamine and serotonin neurotransmission pathways were genotyped in all subjects. We identified three SNPs in genes that are significantly associated with fMRI activity. SNPs of the dopamine beta-hydroxylase (DBH) gene and of the dopamine receptor D4 (DRD4) were associated with activity in the temporal and frontal lobes, respectively. One SNP of serotonin-3A receptor (HTR3A) was associated with temporal lobe activity. The results of this study support the physiogenomic analysis of neuroimaging data to discover associations between genotype and disease-related phenotypes.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

AFRICAN GENETIC DIVERSITY: Implications for Human Demographic History, Modern Human Origins, and Complex Disease Mapping

PubMed Central

Campbell, Michael C.; Tishkoff, Sarah A.

2010-01-01

Comparative studies of ethnically diverse human populations, particularly in Africa, are important for reconstructing human evolutionary history and for understanding the genetic basis of phenotypic adaptation and complex disease. African populations are characterized by greater levels of genetic diversity, extensive population substructure, and less linkage disequilibrium (LD) among loci compared to non-African populations. Africans also possess a number of genetic adaptations that have evolved in response to diverse climates and diets, as well as exposure to infectious disease. This review summarizes patterns and the evolutionary origins of genetic diversity present in African populations, as well as their implications for the mapping of complex traits, including disease susceptibility. PMID:18593304

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.

Advances in the genetically complex autoinflammatory diseases.

PubMed

Ombrello, Michael J

2015-07-01

Monogenic diseases usually demonstrate Mendelian inheritance and are caused by highly penetrant genetic variants of a single gene. In contrast, genetically complex diseases arise from a combination of multiple genetic and environmental factors. The concept of autoinflammation originally emerged from the identification of individual, activating lesions of the innate immune system as the molecular basis of the hereditary periodic fever syndromes. In addition to these rare, monogenic forms of autoinflammation, genetically complex autoinflammatory diseases like the periodic fever, aphthous stomatitis, pharyngitis, and cervical adenitis (PFAPA) syndrome, chronic recurrent multifocal osteomyelitis (CRMO), Behçet's disease, and systemic arthritis also fulfill the definition of autoinflammatory diseases-namely, the development of apparently unprovoked episodes of inflammation without identifiable exogenous triggers and in the absence of autoimmunity. Interestingly, investigations of these genetically complex autoinflammatory diseases have implicated both innate and adaptive immune abnormalities, blurring the line between autoinflammation and autoimmunity. This reinforces the paradigm of concerted innate and adaptive immune dysfunction leading to genetically complex autoinflammatory phenotypes.

Food allergy phenotypes: The key to personalized therapy.

PubMed

Deschildre, A; Lejeune, S; Cap, M; Flammarion, S; Jouannic, L; Amat, F; Just, J

2017-09-01

Food allergies (FAs) are of increasing public health concern and are characterized by a large spectrum of diseases. Their diversity is well known for immunologic pathways (IgE, non-IgE-mediated FAs) and natural history. Many other factors and patient characteristics are involved including type of food, exposure route, allergic comorbidities, gender, racial and ethnic backgrounds, cofactors and health conditions. Food allergen components and sensitization profiles are also involved in FA phenotypes. A new approach to chronic disorders based on the identification of phenotypes through extensive knowledge of all the complex components is also applicable to FAs and could lead towards integrative care management. Diagnostic biomarkers for FAs are emerging which also contribute to better care modalities. The aim of this article was to highlight current knowledge regarding the phenotypic diversity of FA. This review will focus on IgE-mediated FAs and how identifying phenotypes may help to better understand the pathophysiological complexity, improve diagnosis and lead to personalized treatment strategies. © 2017 John Wiley & Sons Ltd.

Cystic Fibrosis: A Review of Associated Phenotypes, Use of Molecular Diagnostic Approaches, Genetic Characteristics, Progress, and Dilemmas.

PubMed

Brennan, Marie-Luise; Schrijver, Iris

2016-01-01

Cystic fibrosis (CF) is an autosomal recessive disease with significant associated morbidity and mortality. It is now appreciated that the broad phenotypic CF spectrum is not explained by obvious genotype-phenotype correlations, suggesting that CF transmembrane conductance regulator (CFTR)-related disease may occur because of multiple additive effects. These contributing effects include complex CFTR alleles, modifier genes, mutations in alternative genes that produce CF-like phenotypes, epigenetic factors, and environmental influences. Most patients in the United States are now diagnosed through newborn screening and use of molecular testing methods. We review the molecular testing approaches and laboratory guidelines for carrier screening, prenatal testing, newborn screening, and clinical diagnostic testing, as well as recent developments in CF treatment, and reasons for the lack of a molecular diagnosis in some patients. Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

hnRNPA2B1 and hnRNPA1 mutations are rare in patients with "multisystem proteinopathy" and frontotemporal lobar degeneration phenotypes.

PubMed

Le Ber, Isabelle; Van Bortel, Inge; Nicolas, Gael; Bouya-Ahmed, Kawtar; Camuzat, Agnès; Wallon, David; De Septenville, Anne; Latouche, Morwena; Lattante, Serena; Kabashi, Edor; Jornea, Ludmila; Hannequin, Didier; Brice, Alexis

2014-04-01

hnRNPA2B1 and hnRNPA1 mutations have been recently identified by exome sequencing in three families presenting with multisystem proteinopathy (MSP), a rare complex phenotype associating frontotemporal lobar degeneration (FTLD), Paget disease of bone (PDB), inclusion body myopathy (IBM), and amyotrophic lateral sclerosis (ALS). No study has evaluated the exact frequency of these genes in cohorts of MSP or FTD patients so far. We sequenced both genes in 17 patients with MSP phenotypes, and in 60 patients with FTLD and FTLD-ALS to test whether mutations could be implicated in the pathogenesis of these disorders. No disease-causing mutation was identified. We conclude that hnRNPA2B1 and hnRNPA1 mutations are rare in MSP and FTLD spectrum of diseases, although further investigations in larger populations are needed. Copyright © 2014 Elsevier Inc. All rights reserved.

Exome sequence analysis suggests genetic burden contributes to phenotypic variability and complex neuropathy

PubMed Central

Gonzaga-Jauregui, Claudia; Harel, Tamar; Gambin, Tomasz; Kousi, Maria; Griffin, Laurie B.; Francescatto, Ludmila; Ozes, Burcak; Karaca, Ender; Jhangiani, Shalini; Bainbridge, Matthew N.; Lawson, Kim S.; Pehlivan, Davut; Okamoto, Yuji; Withers, Marjorie; Mancias, Pedro; Slavotinek, Anne; Reitnauer, Pamela J; Goksungur, Meryem T.; Shy, Michael; Crawford, Thomas O.; Koenig, Michel; Willer, Jason; Flores, Brittany N.; Pediaditrakis, Igor; Us, Onder; Wiszniewski, Wojciech; Parman, Yesim; Antonellis, Anthony; Muzny, Donna M.; Katsanis, Nicholas; Battaloglu, Esra; Boerwinkle, Eric; Gibbs, Richard A.; Lupski, James R.

2015-01-01

Charcot-Marie-Tooth (CMT) disease is a clinically and genetically heterogeneous distal symmetric polyneuropathy. Whole-exome sequencing (WES) of 40 individuals from 37 unrelated families with CMT-like peripheral neuropathy refractory to molecular diagnosis identified apparent causal mutations in ~45% (17/37) of families. Three candidate disease genes are proposed, supported by a combination of genetic and in vivo studies. Aggregate analysis of mutation data revealed a significantly increased number of rare variants across 58 neuropathy associated genes in subjects versus controls; confirmed in a second ethnically discrete neuropathy cohort, suggesting mutation burden potentially contributes to phenotypic variability. Neuropathy genes shown to have highly penetrant Mendelizing variants (HMPVs) and implicated by burden in families were shown to interact genetically in a zebrafish assay exacerbating the phenotype established by the suppression of single genes. Our findings suggest that the combinatorial effect of rare variants contributes to disease burden and variable expressivity. PMID:26257172

Informatics and machine learning to define the phenotype.

PubMed

Basile, Anna Okula; Ritchie, Marylyn DeRiggi

2018-03-01

For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.

Twin methodology in epigenetic studies.

PubMed

Tan, Qihua; Christiansen, Lene; von Bornemann Hjelmborg, Jacob; Christensen, Kaare

2015-01-01

Since the final decades of the last century, twin studies have made a remarkable contribution to the genetics of human complex traits and diseases. With the recent rapid development in modern biotechnology of high-throughput genetic and genomic analyses, twin modelling is expanding from analysis of diseases to molecular phenotypes in functional genomics especially in epigenetics, a thriving field of research that concerns the environmental regulation of gene expression through DNA methylation, histone modification, microRNA and long non-coding RNA expression, etc. The application of the twin method to molecular phenotypes offers new opportunities to study the genetic (nature) and environmental (nurture) contributions to epigenetic regulation of gene activity during developmental, ageing and disease processes. Besides the classical twin model, the case co-twin design using identical twins discordant for a trait or disease is becoming a popular and powerful design for epigenome-wide association study in linking environmental exposure to differential epigenetic regulation and to disease status while controlling for individual genetic make-up. It can be expected that novel uses of twin methods in epigenetic studies are going to help with efficiently unravelling the genetic and environmental basis of epigenomics in human complex diseases. © 2015. Published by The Company of Biologists Ltd.

The molecular genetics of von Willebrand disease.

PubMed

Berber, Ergül

2012-12-01

Quantitative and/or qualitative deficiency of von Willebrand factor (vWF) is associated with the most common inherited bleeding disease von Willebrand disease (vWD). vWD is a complex disease with clinical and genetic heterogeneity. Incomplete penetrance and variable expression due to genetic and environmental factors contribute to its complexity. vWD also has a complex molecular pathogenesis. Some vWF gene mutations are associated with the affected vWF biosynthesis and multimerization, whereas others are associated with increased clearance and functional impairment. Moreover, in addition to a particular mutation, type O blood may result in the more severe phenotype. The present review aimed to provide a summary of the current literature on the molecular genetics of vWD. None declared.

Neurophysiology of Drosophila Models of Parkinson's Disease

PubMed Central

West, Ryan J. H.; Furmston, Rebecca; Williams, Charles A. C.; Elliott, Christopher J. H.

2015-01-01

We provide an insight into the role Drosophila has played in elucidating neurophysiological perturbations associated with Parkinson's disease- (PD-) related genes. Synaptic signalling deficits are observed in motor, central, and sensory systems. Given the neurological impact of disease causing mutations within these same genes in humans the phenotypes observed in fly are of significant interest. As such we observe four unique opportunities provided by fly nervous system models of Parkinson's disease. Firstly, Drosophila models are instrumental in exploring the mechanisms of neurodegeneration, with several PD-related mutations eliciting related phenotypes including sensitivity to energy supply and vesicular deformities. These are leading to the identification of plausible cellular mechanisms, which may be specific to (dopaminergic) neurons and synapses rather than general cellular phenotypes. Secondly, models show noncell autonomous signalling within the nervous system, offering the opportunity to develop our understanding of the way pathogenic signalling propagates, resembling Braak's scheme of spreading pathology in PD. Thirdly, the models link physiological deficits to changes in synaptic structure. While the structure-function relationship is complex, the genetic tractability of Drosophila offers the chance to separate fundamental changes from downstream consequences. Finally, the strong neuronal phenotypes permit relevant first in vivo drug testing. PMID:25960916

Complex disease and phenotype mapping in the domestic dog

PubMed Central

Hayward, Jessica J.; Castelhano, Marta G.; Oliveira, Kyle C.; Corey, Elizabeth; Balkman, Cheryl; Baxter, Tara L.; Casal, Margret L.; Center, Sharon A.; Fang, Meiying; Garrison, Susan J.; Kalla, Sara E.; Korniliev, Pavel; Kotlikoff, Michael I.; Moise, N. S.; Shannon, Laura M.; Simpson, Kenneth W.; Sutter, Nathan B.; Todhunter, Rory J.; Boyko, Adam R.

2016-01-01

The domestic dog is becoming an increasingly valuable model species in medical genetics, showing particular promise to advance our understanding of cancer and orthopaedic disease. Here we undertake the largest canine genome-wide association study to date, with a panel of over 4,200 dogs genotyped at 180,000 markers, to accelerate mapping efforts. For complex diseases, we identify loci significantly associated with hip dysplasia, elbow dysplasia, idiopathic epilepsy, lymphoma, mast cell tumour and granulomatous colitis; for morphological traits, we report three novel quantitative trait loci that influence body size and one that influences fur length and shedding. Using simulation studies, we show that modestly larger sample sizes and denser marker sets will be sufficient to identify most moderate- to large-effect complex disease loci. This proposed design will enable efficient mapping of canine complex diseases, most of which have human homologues, using far fewer samples than required in human studies. PMID:26795439

A novel regulatory defect in the branched-chain α-keto acid dehydrogenase complex due to a mutation in the PPM1K gene causes a mild variant phenotype of maple syrup urine disease.

PubMed

Oyarzabal, Alfonso; Martínez-Pardo, Mercedes; Merinero, Begoña; Navarrete, Rosa; Desviat, Lourdes R; Ugarte, Magdalena; Rodríguez-Pombo, Pilar

2013-02-01

This article describes a hitherto unreported involvement of the phosphatase PP2Cm, a recently described member of the branched-chain α-keto acid dehydrogenase (BCKDH) complex, in maple syrup urine disease (MSUD). The disease-causing mutation was identified in a patient with a mild variant phenotype, involving a gene not previously associated with MSUD. SNP array-based genotyping showed a copy-neutral homozygous pattern for chromosome 4 compatible with uniparental isodisomy. Mutation analysis of the candidate gene, PPM1K, revealed a homozygous c.417_418delTA change predicted to result in a truncated, unstable protein. No PP2Cm mutant protein was detected in immunocytochemical or Western blot expression analyses. The transient expression of wild-type PPM1K in PP2Cm-deficient fibroblasts recovered 35% of normal BCKDH activity. As PP2Cm has been described essential for cell survival, apoptosis and metabolism, the impact of its deficiency on specific metabolic stress variables was evaluated in PP2Cm-deficient fibroblasts. Increases were seen in ROS levels along with the activation of specific stress-signaling MAP kinases. Similar to that described for the pyruvate dehydrogenase complex, a defect in the regulation of BCKDH caused the aberrant metabolism of its substrate, contributing to the patient's MSUD phenotype--and perhaps others. © 2012 WILEY PERIODICALS, INC.

Evolution in health and medicine Sackler colloquium: Stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease.

PubMed

Feinberg, Andrew P; Irizarry, Rafael A

2010-01-26

Neo-Darwinian evolutionary theory is based on exquisite selection of phenotypes caused by small genetic variations, which is the basis of quantitative trait contribution to phenotype and disease. Epigenetics is the study of nonsequence-based changes, such as DNA methylation, heritable during cell division. Previous attempts to incorporate epigenetics into evolutionary thinking have focused on Lamarckian inheritance, that is, environmentally directed epigenetic changes. Here, we propose a new non-Lamarckian theory for a role of epigenetics in evolution. We suggest that genetic variants that do not change the mean phenotype could change the variability of phenotype; and this could be mediated epigenetically. This inherited stochastic variation model would provide a mechanism to explain an epigenetic role of developmental biology in selectable phenotypic variation, as well as the largely unexplained heritable genetic variation underlying common complex disease. We provide two experimental results as proof of principle. The first result is direct evidence for stochastic epigenetic variation, identifying highly variably DNA-methylated regions in mouse and human liver and mouse brain, associated with development and morphogenesis. The second is a heritable genetic mechanism for variable methylation, namely the loss or gain of CpG dinucleotides over evolutionary time. Finally, we model genetically inherited stochastic variation in evolution, showing that it provides a powerful mechanism for evolutionary adaptation in changing environments that can be mediated epigenetically. These data suggest that genetically inherited propensity to phenotypic variability, even with no change in the mean phenotype, substantially increases fitness while increasing the disease susceptibility of a population with a changing environment.

Minireview: Genetic basis of heterogeneity and severity in sickle cell disease

PubMed Central

Habara, Alawi

2016-01-01

Sickle cell disease, a common single gene disorder, has a complex pathophysiology that at its root is initiated by the polymerization of deoxy sickle hemoglobin. Sickle vasoocclusion and hemolytic anemia drive the development of disease complications. In this review, we focus on the genetic modifiers of disease heterogeneity. The phenotypic heterogeneity of disease is only partially explained by genetic variability of fetal hemoglobin gene expression and co-inheritance of α thalassemia. Given the complexity of pathophysiology, many different definitions of severity are possible complicating a full understanding of its genetic foundation. The pathophysiological complexity and the interlocking nature of the biological processes underpinning disease severity are becoming better understood. Nevertheless, useful genetic signatures of severity, regardless of how this is defined, are insufficiently developed to be used for treatment decisions and for counseling. PMID:26936084

Platelet Dysfunction and a High Bone Mass Phenotype in a Murine Model of Platelet-Type von Willebrand Disease

PubMed Central

Suva, Larry J.; Hartman, Eric; Dilley, Joshua D.; Russell, Susan; Akel, Nisreen S.; Skinner, Robert A.; Hogue, William R.; Budde, Ulrich; Varughese, Kottayil I.; Kanaji, Taisuke; Ware, Jerry

2008-01-01

The platelet glycoprotein Ib-IX receptor binds surface-bound von Willebrand factor and supports platelet adhesion to damaged vascular surfaces. A limited number of mutations within the glycoprotein Ib-IX complex have been described that permit a structurally altered receptor to interact with soluble von Willebrand factor, and this is the molecular basis of platelet-type von Willebrand disease. We have developed and characterized a mouse model of platelet-type von Willebrand disease (G233V) and have confirmed a platelet phenotype mimicking the human disorder. The mice have a dramatic increase in splenic megakaryocytes and splenomegaly. Recent studies have demonstrated that hematopoetic cells can influence the differentiation of osteogenic cells. Thus, we examined the skeletal phenotype of mice expressing the G233V variant complex. At 6 months of age, G233V mice exhibit a high bone mass phenotype with an approximate doubling of trabecular bone volume in both the tibia and femur. Serum measures of bone resorption were significantly decreased in G233V animals. With decreased bone resorption, cortical thickness was increased, medullary area decreased, and consequently, the mechanical strength of the femur was significantly increased. Using ex vivo bone marrow cultures, osteoclast-specific staining in the G233V mutant marrow was diminished, whereas osteoblastogenesis was unaffected. These studies provide new insights into the relationship between the regulation of megakaryocytopoiesis and bone mass. PMID:18187573

Construction of the model for the Genetic Analysis Workshop 14 simulated data: genotype-phenotype relationships, gene interaction, linkage, association, disequilibrium, and ascertainment effects for a complex phenotype.

PubMed

Greenberg, David A; Zhang, Junying; Shmulewitz, Dvora; Strug, Lisa J; Zimmerman, Regina; Singh, Veena; Marathe, Sudhir

2005-12-30

The Genetic Analysis Workshop 14 simulated dataset was designed 1) To test the ability to find genes related to a complex disease (such as alcoholism). Such a disease may be given a variety of definitions by different investigators, have associated endophenotypes that are common in the general population, and is likely to be not one disease but a heterogeneous collection of clinically similar, but genetically distinct, entities. 2) To observe the effect on genetic analysis and gene discovery of a complex set of gene x gene interactions. 3) To allow comparison of microsatellite vs. large-scale single-nucleotide polymorphism (SNP) data. 4) To allow testing of association to identify the disease gene and the effect of moderate marker x marker linkage disequilibrium. 5) To observe the effect of different ascertainment/disease definition schemes on the analysis. Data was distributed in two forms. Data distributed to participants contained about 1,000 SNPs and 400 microsatellite markers. Internet-obtainable data consisted of a finer 10,000 SNP map, which also contained data on controls. While disease characteristics and parameters were constant, four "studies" used varying ascertainment schemes based on differing beliefs about disease characteristics. One of the studies contained multiplex two- and three-generation pedigrees with at least four affected members. The simulated disease was a psychiatric condition with many associated behaviors (endophenotypes), almost all of which were genetic in origin. The underlying disease model contained four major genes and two modifier genes. The four major genes interacted with each other to produce three different phenotypes, which were themselves heterogeneous. The population parameters were calibrated so that the major genes could be discovered by linkage analysis in most datasets. The association evidence was more difficult to calibrate but was designed to find statistically significant association in 50% of datasets. We also simulated some marker x marker linkage disequilibrium around some of the genes and also in areas without disease genes. We tried two different methods to simulate the linkage disequilibrium.

Getting ready for the Human Phenome Project: the 2012 forum of the Human Variome Project.

PubMed

Oetting, William S; Robinson, Peter N; Greenblatt, Marc S; Cotton, Richard G; Beck, Tim; Carey, John C; Doelken, Sandra C; Girdea, Marta; Groza, Tudor; Hamilton, Carol M; Hamosh, Ada; Kerner, Berit; MacArthur, Jacqueline A L; Maglott, Donna R; Mons, Barend; Rehm, Heidi L; Schofield, Paul N; Searle, Beverly A; Smedley, Damian; Smith, Cynthia L; Bernstein, Inge Thomsen; Zankl, Andreas; Zhao, Eric Y

2013-04-01

A forum of the Human Variome Project (HVP) was held as a satellite to the 2012 Annual Meeting of the American Society of Human Genetics in San Francisco, California. The theme of this meeting was "Getting Ready for the Human Phenome Project." Understanding the genetic contribution to both rare single-gene "Mendelian" disorders and more complex common diseases will require integration of research efforts among many fields and better defined phenotypes. The HVP is dedicated to bringing together researchers and research populations throughout the world to provide the resources to investigate the impact of genetic variation on disease. To this end, there needs to be a greater sharing of phenotype and genotype data. For this to occur, many databases that currently exist will need to become interoperable to allow for the combining of cohorts with similar phenotypes to increase statistical power for studies attempting to identify novel disease genes or causative genetic variants. Improved systems and tools that enhance the collection of phenotype data from clinicians are urgently needed. This meeting begins the HVP's effort toward this important goal. © 2013 Wiley Periodicals, Inc.

Integration of Neuroimaging and Microarray Datasets through Mapping and Model-Theoretic Semantic Decomposition of Unstructured Phenotypes

PubMed Central

Pantazatos, Spiro P.; Li, Jianrong; Pavlidis, Paul; Lussier, Yves A.

2009-01-01

An approach towards heterogeneous neuroscience dataset integration is proposed that uses Natural Language Processing (NLP) and a knowledge-based phenotype organizer system (PhenOS) to link ontology-anchored terms to underlying data from each database, and then maps these terms based on a computable model of disease (SNOMED CT®). The approach was implemented using sample datasets from fMRIDC, GEO, The Whole Brain Atlas and Neuronames, and allowed for complex queries such as “List all disorders with a finding site of brain region X, and then find the semantically related references in all participating databases based on the ontological model of the disease or its anatomical and morphological attributes”. Precision of the NLP-derived coding of the unstructured phenotypes in each dataset was 88% (n = 50), and precision of the semantic mapping between these terms across datasets was 98% (n = 100). To our knowledge, this is the first example of the use of both semantic decomposition of disease relationships and hierarchical information found in ontologies to integrate heterogeneous phenotypes across clinical and molecular datasets. PMID:20495688

Protein Interactome of Muscle Invasive Bladder Cancer

PubMed Central

Bhat, Akshay; Heinzel, Andreas; Mayer, Bernd; Perco, Paul; Mühlberger, Irmgard; Husi, Holger; Merseburger, Axel S.; Zoidakis, Jerome; Vlahou, Antonia; Schanstra, Joost P.; Mischak, Harald; Jankowski, Vera

2015-01-01

Muscle invasive bladder carcinoma is a complex, multifactorial disease caused by disruptions and alterations of several molecular pathways that result in heterogeneous phenotypes and variable disease outcome. Combining this disparate knowledge may offer insights for deciphering relevant molecular processes regarding targeted therapeutic approaches guided by molecular signatures allowing improved phenotype profiling. The aim of the study is to characterize muscle invasive bladder carcinoma on a molecular level by incorporating scientific literature screening and signatures from omics profiling. Public domain omics signatures together with molecular features associated with muscle invasive bladder cancer were derived from literature mining to provide 286 unique protein-coding genes. These were integrated in a protein-interaction network to obtain a molecular functional map of the phenotype. This feature map educated on three novel disease-associated pathways with plausible involvement in bladder cancer, namely Regulation of actin cytoskeleton, Neurotrophin signalling pathway and Endocytosis. Systematic integration approaches allow to study the molecular context of individual features reported as associated with a clinical phenotype and could potentially help to improve the molecular mechanistic description of the disorder. PMID:25569276

MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model

USDA-ARS?s Scientific Manuscript database

Bovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per annum. Because disease susceptibility is a multi-factorial complex phenotype, a multi-omic integrative biology approach is required to dissect the multilayer...

Comprehensive Genome-wide Screen for Genes with Cis-acting Regulatory Elements That Respond to Marek's Disease Virus Infection

USDA-ARS?s Scientific Manuscript database

The comprehensive identification of genes underlying phenotypic variation of complex traits such as disease resistance remains one of the greatest challenges in biology despite having genome sequences and more powerful tools. Most genome-wide screens lack sufficient resolving power as they typically...

Connecting the Human Variome Project to nutrigenomics.

PubMed

Kaput, Jim; Evelo, Chris T; Perozzi, Giuditta; van Ommen, Ben; Cotton, Richard

2010-12-01

Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.

Connecting the Human Variome Project to nutrigenomics

PubMed Central

Evelo, Chris T.; Perozzi, Giuditta; van Ommen, Ben; Cotton, Richard

2010-01-01

Nutrigenomics is the science of analyzing and understanding gene–nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene–nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts. PMID:28300226

Genetic heterogeneity of hemoglobin AEBart's disease: a large cohort data from a single referral center in northeast Thailand.

PubMed

Chaibunruang, Attawut; Karnpean, Rossarin; Fucharoen, Goonnapa; Fucharoen, Supan

2014-04-01

AEBart's disease is a thalassemia intermedia usually characterized by the interaction of α(0)-thalassemia with either deletional or non-deletional α(+)-thalassemia in Hb E heterozygote. Genotypic and phenotypic features are heterogeneous. We studied the hematologic and molecular characteristics of this disease in a cohort of 173 Thai patients encountered at our center in northeast Thailand. Hemoglobin and DNA analyses identified patients with deletional AEBart's disease (n=84), Hb Constant Spring AEBart's disease (n=81), Hb Paksé-AEBart's disease (n=5), AEBart's disease with codon 30 mutation (n=1) and two hitherto un-described forms of AEBart's disease due to interaction of Hb E heterozygote and α(0)-thalassemia with the -α(16.6)kb deletional α(+)-thalassemia (n=1) and Hb Q-Thailand (n=1). Different phenotypic expression of these AEBart's diseases with low Hb, Hct and MCV and increased RDW values with marked reduction in Hb E levels were observed. It was found that all these forms of AEBart's disease showed similar thalassemia intermedia phenotypes but those with non-deletional forms were relatively more anemic. Our data confirm that in such area with high prevalence of hemoglobinopathies such as Southeast Asia, identification of rare thalassemia alleles in a thalassemia intermedia patient should not be ignored. Careful consideration of different phenotypic expression may help in providing presumptive diagnosis of this disease where access to molecular testing is limited. However, molecular diagnostic is useful for predicting the clinical outcome and improving genetic counseling of these complex hemoglobinopathies. Copyright © 2013 Elsevier Inc. All rights reserved.

Systems genetics approaches to understand complex traits

PubMed Central

Civelek, Mete; Lusis, Aldons J.

2014-01-01

Systems genetics is an approach to understand the flow of biological information that underlies complex traits. It uses a range of experimental and statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein or metabolite levels, in populations that vary for traits of interest. Systems genetics studies have provided the first global view of the molecular architecture of complex traits and are useful for the identification of genes, pathways and networks that underlie common human diseases. Given the urgent need to understand how the thousands of loci that have been identified in genome-wide association studies contribute to disease susceptibility, systems genetics is likely to become an increasingly important approach to understanding both biology and disease. PMID:24296534

Mito-Nuclear Interactions Affecting Lifespan and Neurodegeneration in a Drosophila Model of Leigh Syndrome.

PubMed

Loewen, Carin A; Ganetzky, Barry

2018-04-01

Proper mitochondrial activity depends upon proteins encoded by genes in the nuclear and mitochondrial genomes that must interact functionally and physically in a precisely coordinated manner. Consequently, mito-nuclear allelic interactions are thought to be of crucial importance on an evolutionary scale, as well as for manifestation of essential biological phenotypes, including those directly relevant to human disease. Nonetheless, detailed molecular understanding of mito-nuclear interactions is still lacking, and definitive examples of such interactions in vivo are sparse. Here we describe the characterization of a mutation in Drosophila ND23 , a nuclear gene encoding a highly conserved subunit of mitochondrial complex 1. This characterization led to the discovery of a mito-nuclear interaction that affects the ND23 mutant phenotype. ND23 mutants exhibit reduced lifespan, neurodegeneration, abnormal mitochondrial morphology, and decreased ATP levels. These phenotypes are similar to those observed in patients with Leigh syndrome, which is caused by mutations in a number of nuclear genes that encode mitochondrial proteins, including the human ortholog of ND23 A key feature of Leigh syndrome, and other mitochondrial disorders, is unexpected and unexplained phenotypic variability. We discovered that the phenotypic severity of ND23 mutations varies depending on the maternally inherited mitochondrial background. Sequence analysis of the relevant mitochondrial genomes identified several variants that are likely candidates for the phenotypic interaction with mutant ND23 , including a variant affecting a mitochondrially encoded component of complex I. Thus, our work provides an in vivo demonstration of the phenotypic importance of mito-nuclear interactions in the context of mitochondrial disease. Copyright © 2018 by the Genetics Society of America.

Complex Roads from Genotype to Phenotype in Dilated Cardiomyopathy: Scientific update from the Working Group of Myocardial Function of the European Society of Cardiology

PubMed

Bondue, Antoine; Arbustini, Eloisa; Bianco, Anna M; Ciccarelli, Michele; Dawson, Dana; De Rosa, Matteo; Hamdani, Nazha; Hilfiker-Kleiner, Denise; Meder, Benjamin; Leite Moreira, Adelino; Thum, Thomas; Gabriele Tocchetti, Carlo; Varricchi, Gilda; Van der Velden, Jolanda; Walsh, Roddy; Heymans, Stephane

2018-05-23

Dilated cardiomyopathy (DCM) frequently affects relatively young, economically and socially active adults, and is an important cause of heart failure and transplantation. DCM is a complex disease and its pathological architecture encounters many genetic determinants interacting with environmental factors. The old perspective that every pathogenic gene mutation would lead to a diseased heart, is now being replaced by the novel observation that the phenotype depends not only on the penetrance -malignancy of the mutated gene- but also on epigenetics, age, toxic factors, pregnancy and a diversity of acquired diseases. This review discusses how gene mutations will result in mutation-specific molecular alterations in the heart including increased mitochondrial oxidation (sarcomeric gene e.g. TTN), decreased calcium sensitivity (sarcomeric genes), fibrosis (e.g. LMNA and TTN) or inflammation. Therefore, getting a complete picture of the DCM patient will include genomic data, molecular assessment by preference from cardiac samples, stratification according to co-morbidities, and phenotypic description. Those data will help to better guide the heart failure and anti-arrhythmic treatment, predict response to therapy, develop novel siRNA-based gene silencing for malignant gene mutations, or intervene with mutation-specific altered gene pathways in the heart.

Physiogenomic Analysis of Localized fMRI Brain Activity in Schizophrenia

PubMed Central

Windemuth, Andreas; Calhoun, Vince D.; Pearlson, Godfrey D.; Kocherla, Mohan; Jagannathan, Kanchana; Ruaño, Gualberto

2009-01-01

The search for genetic factors associated with disease is complicated by the complexity of the biological pathways linking genotype and phenotype. This analytical complexity is particularly concerning in diseases historically lacking reliable diagnostic biological markers, such as schizophrenia and other mental disorders. We investigate the use of functional magnetic resonance imaging (fMRI) as an intermediate phenotype (endophenotype) to identify physiogenomic associations to schizophrenia. We screened 99 subjects, 30 subjects diagnosed with schizophrenia, 13 unaffected relatives of schizophrenia patients, and 56 unrelated controls, for gene polymorphisms associated with fMRI activation patterns at two locations in temporal and frontal lobes previously implied in schizophrenia. A total of 22 single nucleotide polymorphisms (SNPs) in 15 genes from the dopamine and serotonin neurotransmission pathways were genotyped in all subjects. We identified three SNPs in genes that are significantly associated with fMRI activity. SNPs of the dopamine beta-hydroxylase (DBH) gene and of the dopamine receptor D4 (DRD4) were associated with activity in the temporal and frontal lobes, respectively. One SNP of serotonin-3A receptor (HTR3A) was associated with temporal lobe activity. The results of this study support the physiogenomic analysis of neuroimaging data to discover associations between genotype and disease-related phenotypes. PMID:18330705

[Phenotypic heterogeneity of chronic obstructive pulmonary disease].

PubMed

Garcia-Aymerich, Judith; Agustí, Alvar; Barberà, Joan A; Belda, José; Farrero, Eva; Ferrer, Antoni; Ferrer, Jaume; Gáldiz, Juan B; Gea, Joaquim; Gómez, Federico P; Monsó, Eduard; Morera, Josep; Roca, Josep; Sauleda, Jaume; Antó, Josep M

2009-03-01

A functional definition of chronic obstructive pulmonary disease (COPD) based on airflow limitation has largely dominated the field. However, a view has emerged that COPD involves a complex array of cellular, organic, functional, and clinical events, with a growing interest in disentangling the phenotypic heterogeneity of COPD. The present review is based on the opinion of the authors, who have extensive research experience in several aspects of COPD. The starting assumption of the review is that current knowledge on the pathophysiology and clinical features of COPD allows us to classify phenotypic information in terms of the following dimensions: respiratory symptoms and health status, acute exacerbations, lung function, structural changes, local and systemic inflammation, and systemic effects. Twenty-six phenotypic traits were identified and assigned to one of the 6 dimensions. For each dimension, a summary is provided of the best evidence on the relationships among phenotypic traits, in particular among those corresponding to different dimensions, and on the relationship between these traits and relevant events in the natural history of COPD. The information has been organized graphically into a phenotypic matrix where each cell representing a pair of phenotypic traits is linked to relevant references. The information provided has the potential to increase our understanding of the heterogeneity of COPD phenotypes and help us plan future studies on aspects that are as yet unexplored.

The Qatar genome project: translation of whole-genome sequencing into clinical practice.

PubMed

Zayed, Hatem

2016-10-01

Qatar Genome Project was launched in 2013 with the intent to sequence the genome of each Qatari citizen in an effort to protect Qataris from the high rate of indigenous genetic diseases by allowing the mapping of disease-causing variants/rare variants and establishing a Qatari reference genome. Indeed, this project is expected to have numerous global benefits because the elevated homogeneity of the Qatari population, that will make Qatar an excellent genetic laboratory that will generate a wealth of data that will allow us to make sense of the genotype-phenotype correlations of many diseases, especially the complex multifactorial diseases, and will pave the way for changing the traditional medical practice of looking first at the phenotype rather than the genotype. © 2016 John Wiley & Sons Ltd.

Disease signatures for schizophrenia and bipolar disorder using patient-derived induced pluripotent stem cells.

PubMed

Watmuff, Bradley; Berkovitch, Shaunna S; Huang, Joanne H; Iaconelli, Jonathan; Toffel, Steven; Karmacharya, Rakesh

2016-06-01

Schizophrenia and bipolar disorder are complex psychiatric disorders that present unique challenges in the study of disease biology. There are no objective biological phenotypes for these disorders, which are characterized by complex genetics and prominent roles for gene-environment interactions. The study of the neurobiology underlying these severe psychiatric disorders has been hindered by the lack of access to the tissue of interest - neurons from patients. The advent of reprogramming methods that enable generation of induced pluripotent stem cells (iPSCs) from patient fibroblasts and peripheral blood mononuclear cells has opened possibilities for new approaches to study relevant disease biology using iPSC-derived neurons. While early studies with patient iPSCs have led to promising and intriguing leads, significant hurdles remain in our attempts to capture the complexity of these disorders in vitro. We present here an overview of studies to date of schizophrenia and bipolar disorder using iPSC-derived neuronal cells and discuss potential future directions that can result in the identification of robust and valid cellular phenotypes that in turn can lay the groundwork for meaningful clinical advances. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying Specific Genes Controlling Complex Traits Through A Genome-Wide Screen For cis-Acting Regulatory Elements - An Example Using Marek's Disease

USDA-ARS?s Scientific Manuscript database

The identification of specific genes underlying phenotypic variation of complex traits remains one of the greatest challenges in biology despite having genome sequences and more powerful tools. Most genome-wide screens lack sufficient resolving power as they typically depend on linkage. One altern...

Comprehensive Identification Of Specific Genes Controlling Complex Traits Through A Genome-Wide Screen for Cis-Acting Regulatory Elements - An Example Using Marek's Disease

USDA-ARS?s Scientific Manuscript database

The comprehensive identification of genes underlying phenotypic variation of complex traits remains a major challenge. Most genome-wide screens lack sufficient resolving power as they typically depend on linkage. An alternate method is to screen for allele-specific expression (ASE), a simple yet pow...

TYK2 Protein-Coding Variants Protect against Rheumatoid Arthritis and Autoimmunity, with No Evidence of Major Pleiotropic Effects on Non-Autoimmune Complex Traits

PubMed Central

Diogo, Dorothée; Bastarache, Lisa; Liao, Katherine P.; Graham, Robert R.; Fulton, Robert S.; Greenberg, Jeffrey D.; Eyre, Steve; Bowes, John; Cui, Jing; Lee, Annette; Pappas, Dimitrios A.; Kremer, Joel M.; Barton, Anne; Coenen, Marieke J. H.; Franke, Barbara; Kiemeney, Lambertus A.; Mariette, Xavier; Richard-Miceli, Corrine; Canhão, Helena; Fonseca, João E.; de Vries, Niek; Tak, Paul P.; Crusius, J. Bart A.; Nurmohamed, Michael T.; Kurreeman, Fina; Mikuls, Ted R.; Okada, Yukinori; Stahl, Eli A.; Larson, David E.; Deluca, Tracie L.; O'Laughlin, Michelle; Fronick, Catrina C.; Fulton, Lucinda L.; Kosoy, Roman; Ransom, Michael; Bhangale, Tushar R.; Ortmann, Ward; Cagan, Andrew; Gainer, Vivian; Karlson, Elizabeth W.; Kohane, Isaac; Murphy, Shawn N.; Martin, Javier; Zhernakova, Alexandra; Klareskog, Lars; Padyukov, Leonid; Worthington, Jane; Mardis, Elaine R.; Seldin, Michael F.; Gregersen, Peter K.; Behrens, Timothy; Raychaudhuri, Soumya; Denny, Joshua C.; Plenge, Robert M.

2015-01-01

Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3x10-21), A928V (rs35018800, OR = 0.53, P = 1.2x10-9), and I684S (rs12720356, OR = 0.86, P = 4.6x10-7). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6x10-18), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; Pomnibus = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases. PMID:25849893

TYK2 protein-coding variants protect against rheumatoid arthritis and autoimmunity, with no evidence of major pleiotropic effects on non-autoimmune complex traits.

PubMed

Diogo, Dorothée; Bastarache, Lisa; Liao, Katherine P; Graham, Robert R; Fulton, Robert S; Greenberg, Jeffrey D; Eyre, Steve; Bowes, John; Cui, Jing; Lee, Annette; Pappas, Dimitrios A; Kremer, Joel M; Barton, Anne; Coenen, Marieke J H; Franke, Barbara; Kiemeney, Lambertus A; Mariette, Xavier; Richard-Miceli, Corrine; Canhão, Helena; Fonseca, João E; de Vries, Niek; Tak, Paul P; Crusius, J Bart A; Nurmohamed, Michael T; Kurreeman, Fina; Mikuls, Ted R; Okada, Yukinori; Stahl, Eli A; Larson, David E; Deluca, Tracie L; O'Laughlin, Michelle; Fronick, Catrina C; Fulton, Lucinda L; Kosoy, Roman; Ransom, Michael; Bhangale, Tushar R; Ortmann, Ward; Cagan, Andrew; Gainer, Vivian; Karlson, Elizabeth W; Kohane, Isaac; Murphy, Shawn N; Martin, Javier; Zhernakova, Alexandra; Klareskog, Lars; Padyukov, Leonid; Worthington, Jane; Mardis, Elaine R; Seldin, Michael F; Gregersen, Peter K; Behrens, Timothy; Raychaudhuri, Soumya; Denny, Joshua C; Plenge, Robert M

2015-01-01

Despite the success of genome-wide association studies (GWAS) in detecting a large number of loci for complex phenotypes such as rheumatoid arthritis (RA) susceptibility, the lack of information on the causal genes leaves important challenges to interpret GWAS results in the context of the disease biology. Here, we genetically fine-map the RA risk locus at 19p13 to define causal variants, and explore the pleiotropic effects of these same variants in other complex traits. First, we combined Immunochip dense genotyping (n = 23,092 case/control samples), Exomechip genotyping (n = 18,409 case/control samples) and targeted exon-sequencing (n = 2,236 case/controls samples) to demonstrate that three protein-coding variants in TYK2 (tyrosine kinase 2) independently protect against RA: P1104A (rs34536443, OR = 0.66, P = 2.3 x 10(-21)), A928V (rs35018800, OR = 0.53, P = 1.2 x 10(-9)), and I684S (rs12720356, OR = 0.86, P = 4.6 x 10(-7)). Second, we show that the same three TYK2 variants protect against systemic lupus erythematosus (SLE, Pomnibus = 6 x 10(-18)), and provide suggestive evidence that two of the TYK2 variants (P1104A and A928V) may also protect against inflammatory bowel disease (IBD; P(omnibus) = 0.005). Finally, in a phenome-wide association study (PheWAS) assessing >500 phenotypes using electronic medical records (EMR) in >29,000 subjects, we found no convincing evidence for association of P1104A and A928V with complex phenotypes other than autoimmune diseases such as RA, SLE and IBD. Together, our results demonstrate the role of TYK2 in the pathogenesis of RA, SLE and IBD, and provide supporting evidence for TYK2 as a promising drug target for the treatment of autoimmune diseases.

CHALLENGES IN PHENOTYPE DEFINITION IN THE WHOLE-GENOME ERA: MULTIVARIATE MODELS OF MEMORY AND INTELLIGENCE

PubMed Central

SABB, F. W.; BURGGREN, A. C.; HIGIER, R. G.; FOX, J.; HE, J.; PARKER, D. S.; POLDRACK, R. A.; CHU, W.; CANNON, T. D.; FREIMER, N. B.; BILDER, R. M.

2009-01-01

Refining phenotypes for the study of neuropsychiatric disorders is of paramount importance in neuroscience. Poor phenotype definition provides the greatest obstacle for making progress in disorders like schizophrenia, bipolar disorder, Attention Deficit/Hyperactivity Disorder (ADHD), and autism. Using freely available informatics tools developed by the Consortium for Neuropsychiatric Phenomics (CNP), we provide a framework for defining and refining latent constructs used in neuroscience research and then apply this strategy to review known genetic contributions to memory and intelligence in healthy individuals. This approach can help us begin to build multi-level phenotype models that express the interactions between constructs necessary to understand complex neuropsychiatric diseases. PMID:19450667

[Epigenetics, interface between environment and genes: role in complex diseases].

PubMed

Scheen, A J; Junien, C

2012-01-01

Epigenetics is the study of heritable changes in gene expression or cellular phenotype caused by mechanisms other than changes in the underlying DNA sequence. Epigenetics is one of the major mechanisms explaining the "Developmental Origin of Health and Diseases" (DOHaD). Besides genetic background inherited from parents, which confers susceptibility to certain pathologies, epigenetic changes constitute the memory of previous events, either positive or negative, along the life cycle, including at the in utero stage. The later exposition to hostile environment may reveal such susceptibility, with the development of various pathologies, among them numerous chronic complex diseases. The demonstration of such a sequence of events has been shown for metabolic diseases as obesity, metabolic syndrome and type 2 diabetes, cardiovascular disease and cancer. In contrast to genetic predisposition, which is irreversible, epigenetic changes are potentially reversible, thus giving targets not only for prevention, but possibly also for the treatment of certain complex diseases.

Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature.

PubMed

Dell'Isola, A; Allan, R; Smith, S L; Marreiros, S S P; Steultjens, M

2016-10-12

Knee Osteoarthritis (KOA) is a heterogeneous pathology characterized by a complex and multifactorial nature. It has been hypothesised that these differences are due to the existence of underlying phenotypes representing different mechanisms of the disease. The aim of this study is to identify the current evidence for the existence of groups of variables which point towards the existence of distinct clinical phenotypes in the KOA population. A systematic literature search in PubMed was conducted. Only original articles were selected if they aimed to identify phenotypes of patients aged 18 years or older with KOA. The methodological quality of the studies was independently assessed by two reviewers and qualitative synthesis of the evidence was performed. Strong evidence for existence of specific phenotypes was considered present if the phenotype was supported by at least two high-quality studies. A total of 24 studies were included. Through qualitative synthesis of evidence, six main sets of variables proposing the existence of six phenotypes were identified: 1) chronic pain in which central mechanisms (e.g. central sensitisation) are prominent; 2) inflammatory (high levels of inflammatory biomarkers); 3) metabolic syndrome (high prevalence of obesity, diabetes and other metabolic disturbances); 4) Bone and cartilage metabolism (alteration in local tissue metabolism); 5) mechanical overload characterised primarily by varus malalignment and medial compartment disease; and 6) minimal joint disease characterised as minor clinical symptoms with slow progression over time. This study identified six distinct groups of variables which should be explored in attempts to better define clinical phenotypes in the KOA population.

Evolving Concepts of Asthma

PubMed Central

Ray, Anuradha; Wenzel, Sally E.

2015-01-01

Our understanding of asthma has evolved over time from a singular disease to a complex of various phenotypes, with varied natural histories, physiologies, and responses to treatment. Early therapies treated most patients with asthma similarly, with bronchodilators and corticosteroids, but these therapies had varying degrees of success. Similarly, despite initial studies that identified an underlying type 2 inflammation in the airways of patients with asthma, biologic therapies targeted toward these type 2 pathways were unsuccessful in all patients. These observations led to increased interest in phenotyping asthma. Clinical approaches, both biased and later unbiased/statistical approaches to large asthma patient cohorts, identified a variety of patient characteristics, but they also consistently identified the importance of age of onset of disease and the presence of eosinophils in determining clinically relevant phenotypes. These paralleled molecular approaches to phenotyping that developed an understanding that not all patients share a type 2 inflammatory pattern. Using biomarkers to select patients with type 2 inflammation, repeated trials of biologics directed toward type 2 cytokine pathways saw newfound success, confirming the importance of phenotyping in asthma. Further research is needed to clarify additional clinical and molecular phenotypes, validate predictive biomarkers, and identify new areas for possible interventions. PMID:26161792

Exome Sequencing and the Management of Neurometabolic Disorders.

PubMed

Tarailo-Graovac, Maja; Shyr, Casper; Ross, Colin J; Horvath, Gabriella A; Salvarinova, Ramona; Ye, Xin C; Zhang, Lin-Hua; Bhavsar, Amit P; Lee, Jessica J Y; Drögemöller, Britt I; Abdelsayed, Mena; Alfadhel, Majid; Armstrong, Linlea; Baumgartner, Matthias R; Burda, Patricie; Connolly, Mary B; Cameron, Jessie; Demos, Michelle; Dewan, Tammie; Dionne, Janis; Evans, A Mark; Friedman, Jan M; Garber, Ian; Lewis, Suzanne; Ling, Jiqiang; Mandal, Rupasri; Mattman, Andre; McKinnon, Margaret; Michoulas, Aspasia; Metzger, Daniel; Ogunbayo, Oluseye A; Rakic, Bojana; Rozmus, Jacob; Ruben, Peter; Sayson, Bryan; Santra, Saikat; Schultz, Kirk R; Selby, Kathryn; Shekel, Paul; Sirrs, Sandra; Skrypnyk, Cristina; Superti-Furga, Andrea; Turvey, Stuart E; Van Allen, Margot I; Wishart, David; Wu, Jiang; Wu, John; Zafeiriou, Dimitrios; Kluijtmans, Leo; Wevers, Ron A; Eydoux, Patrice; Lehman, Anna M; Vallance, Hilary; Stockler-Ipsiroglu, Sylvia; Sinclair, Graham; Wasserman, Wyeth W; van Karnebeek, Clara D

2016-06-09

Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.).

Exome Sequencing and the Management of Neurometabolic Disorders

PubMed Central

Tarailo-Graovac, M.; Shyr, C.; Ross, C.J.; Horvath, G.A.; Salvarinova, R.; Ye, X.C.; Zhang, L.-H.; Bhavsar, A.P.; Lee, J.J.Y.; Drögemöller, B.I.; Abdelsayed, M.; Alfadhel, M.; Armstrong, L.; Baumgartner, M.R.; Burda, P.; Connolly, M.B.; Cameron, J.; Demos, M.; Dewan, T.; Dionne, J.; Evans, A.M.; Friedman, J.M.; Garber, I.; Lewis, S.; Ling, J.; Mandal, R.; Mattman, A.; McKinnon, M.; Michoulas, A.; Metzger, D.; Ogunbayo, O.A.; Rakic, B.; Rozmus, J.; Ruben, P.; Sayson, B.; Santra, S.; Schultz, K.R.; Selby, K.; Shekel, P.; Sirrs, S.; Skrypnyk, C.; Superti-Furga, A.; Turvey, S.E.; Van Allen, M.I.; Wishart, D.; Wu, J.; Wu, J.; Zafeiriou, D.; Kluijtmans, L.; Wevers, R.A.; Eydoux, P.; Lehman, A.M.; Vallance, H.; Stockler-Ipsiroglu, S.; Sinclair, G.; Wasserman, W.W.; van Karnebeek, C.D.

2016-01-01

BACKGROUND Whole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level. METHODS To uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient’s clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes. RESULTS We performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%). CONCLUSIONS Deep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children’s Hospital Foundation and others.) PMID:27276562

A weighted U statistic for association analyses considering genetic heterogeneity.

PubMed

Wei, Changshuai; Elston, Robert C; Lu, Qing

2016-07-20

Converging evidence suggests that common complex diseases with the same or similar clinical manifestations could have different underlying genetic etiologies. While current research interests have shifted toward uncovering rare variants and structural variations predisposing to human diseases, the impact of heterogeneity in genetic studies of complex diseases has been largely overlooked. Most of the existing statistical methods assume the disease under investigation has a homogeneous genetic effect and could, therefore, have low power if the disease undergoes heterogeneous pathophysiological and etiological processes. In this paper, we propose a heterogeneity-weighted U (HWU) method for association analyses considering genetic heterogeneity. HWU can be applied to various types of phenotypes (e.g., binary and continuous) and is computationally efficient for high-dimensional genetic data. Through simulations, we showed the advantage of HWU when the underlying genetic etiology of a disease was heterogeneous, as well as the robustness of HWU against different model assumptions (e.g., phenotype distributions). Using HWU, we conducted a genome-wide analysis of nicotine dependence from the Study of Addiction: Genetics and Environments dataset. The genome-wide analysis of nearly one million genetic markers took 7h, identifying heterogeneous effects of two new genes (i.e., CYP3A5 and IKBKB) on nicotine dependence. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Novel mutations in IBA57 are associated with leukodystrophy and variable clinical phenotypes.

PubMed

Torraco, Alessandra; Ardissone, Anna; Invernizzi, Federica; Rizza, Teresa; Fiermonte, Giuseppe; Niceta, Marcello; Zanetti, Nadia; Martinelli, Diego; Vozza, Angelo; Verrigni, Daniela; Di Nottia, Michela; Lamantea, Eleonora; Diodato, Daria; Tartaglia, Marco; Dionisi-Vici, Carlo; Moroni, Isabella; Farina, Laura; Bertini, Enrico; Ghezzi, Daniele; Carrozzo, Rosalba

2017-01-01

Defects of the Fe/S cluster biosynthesis represent a subgroup of diseases affecting the mitochondrial energy metabolism. In the last years, mutations in four genes (NFU1, BOLA3, ISCA2 and IBA57) have been related to a new group of multiple mitochondrial dysfunction syndromes characterized by lactic acidosis, hyperglycinemia, multiple defects of the respiratory chain complexes, and impairment of four lipoic acid-dependent enzymes: α-ketoglutarate dehydrogenase complex, pyruvic dehydrogenase, branched-chain α-keto acid dehydrogenase complex and the H protein of the glycine cleavage system. Few patients have been reported with mutations in IBA57 and with variable clinical phenotype. Herein, we describe four unrelated patients carrying novel mutations in IBA57. All patients presented with combined or isolated defect of complex I and II. Clinical features varied widely, ranging from fatal infantile onset of the disease to acute and severe psychomotor regression after the first year of life. Brain MRI was characterized by cavitating leukodystrophy. The identified mutations were never reported previously and all had a dramatic effect on IBA57 stability. Our study contributes to expand the array of the genotypic variation of IBA57 and delineates the leukodystrophic pattern of IBA57 deficient patients.

Genome-Wide Architecture of Disease Resistance Genes in Lettuce

PubMed Central

Christopoulou, Marilena; Wo, Sebastian Reyes-Chin; Kozik, Alex; McHale, Leah K.; Truco, Maria-Jose; Wroblewski, Tadeusz; Michelmore, Richard W.

2015-01-01

Genome-wide motif searches identified 1134 genes in the lettuce reference genome of cv. Salinas that are potentially involved in pathogen recognition, of which 385 were predicted to encode nucleotide binding-leucine rich repeat receptor (NLR) proteins. Using a maximum-likelihood approach, we grouped the NLRs into 25 multigene families and 17 singletons. Forty-one percent of these NLR-encoding genes belong to three families, the largest being RGC16 with 62 genes in cv. Salinas. The majority of NLR-encoding genes are located in five major resistance clusters (MRCs) on chromosomes 1, 2, 3, 4, and 8 and cosegregate with multiple disease resistance phenotypes. Most MRCs contain primarily members of a single NLR gene family but a few are more complex. MRC2 spans 73 Mb and contains 61 NLRs of six different gene families that cosegregate with nine disease resistance phenotypes. MRC3, which is 25 Mb, contains 22 RGC21 genes and colocates with Dm13. A library of 33 transgenic RNA interference tester stocks was generated for functional analysis of NLR-encoding genes that cosegregated with disease resistance phenotypes in each of the MRCs. Members of four NLR-encoding families, RGC1, RGC2, RGC21, and RGC12 were shown to be required for 16 disease resistance phenotypes in lettuce. The general composition of MRCs is conserved across different genotypes; however, the specific repertoire of NLR-encoding genes varied particularly of the rapidly evolving Type I genes. These tester stocks are valuable resources for future analyses of additional resistance phenotypes. PMID:26449254

Complex Network Analysis of CA3 Transcriptome Reveals Pathogenic and Compensatory Pathways in Refractory Temporal Lobe Epilepsy

PubMed Central

Bando, Silvia Yumi; Silva, Filipi Nascimento; Costa, Luciano da Fontoura; Silva, Alexandre V.; Pimentel-Silva, Luciana R.; Castro, Luiz HM.; Wen, Hung-Tzu; Amaro, Edson; Moreira-Filho, Carlos Alberto

2013-01-01

We previously described – studying transcriptional signatures of hippocampal CA3 explants – that febrile (FS) and afebrile (NFS) forms of refractory mesial temporal lobe epilepsy constitute two distinct genomic phenotypes. That network analysis was based on a limited number (hundreds) of differentially expressed genes (DE networks) among a large set of valid transcripts (close to two tens of thousands). Here we developed a methodology for complex network visualization (3D) and analysis that allows the categorization of network nodes according to distinct hierarchical levels of gene-gene connections (node degree) and of interconnection between node neighbors (concentric node degree). Hubs are highly connected nodes, VIPs have low node degree but connect only with hubs, and high-hubs have VIP status and high overall number of connections. Studying the whole set of CA3 valid transcripts we: i) obtained complete transcriptional networks (CO) for FS and NFS phenotypic groups; ii) examined how CO and DE networks are related; iii) characterized genomic and molecular mechanisms underlying FS and NFS phenotypes, identifying potential novel targets for therapeutic interventions. We found that: i) DE hubs and VIPs are evenly distributed inside the CO networks; ii) most DE hubs and VIPs are related to synaptic transmission and neuronal excitability whereas most CO hubs, VIPs and high hubs are related to neuronal differentiation, homeostasis and neuroprotection, indicating compensatory mechanisms. Complex network visualization and analysis is a useful tool for systems biology approaches to multifactorial diseases. Network centrality observed for hubs, VIPs and high hubs of CO networks, is consistent with the network disease model, where a group of nodes whose perturbation leads to a disease phenotype occupies a central position in the network. Conceivably, the chance for exerting therapeutic effects through the modulation of particular genes will be higher if these genes are highly interconnected in transcriptional networks. PMID:24278214

Precision phenotyping, panomics, and system-level bioinformatics to delineate complex biologies of atherosclerosis: rationale and design of the "Genetic Loci and the Burden of Atherosclerotic Lesions" study.

PubMed

Voros, Szilard; Maurovich-Horvat, Pal; Marvasty, Idean B; Bansal, Aruna T; Barnes, Michael R; Vazquez, Gustavo; Murray, Sarah S; Voros, Viktor; Merkely, Bela; Brown, Bradley O; Warnick, G Russell

2014-01-01

Complex biological networks of atherosclerosis are largely unknown. The main objective of the Genetic Loci and the Burden of Atherosclerotic Lesions study is to assemble comprehensive biological networks of atherosclerosis using advanced cardiovascular imaging for phenotyping, a panomic approach to identify underlying genomic, proteomic, metabolomic, and lipidomic underpinnings, analyzed by systems biology-driven bioinformatics. By design, this is a hypothesis-free unbiased discovery study collecting a large number of biologically related factors to examine biological associations between genomic, proteomic, metabolomic, lipidomic, and phenotypic factors of atherosclerosis. The Genetic Loci and the Burden of Atherosclerotic Lesions study (NCT01738828) is a prospective, multicenter, international observational study of atherosclerotic coronary artery disease. Approximately 7500 patients are enrolled and undergo non-contrast-enhanced coronary calcium scanning by CT for the detection and quantification of coronary artery calcium, as well as coronary artery CT angiography for the detection and quantification of plaque, stenosis, and overall coronary artery disease burden. In addition, patients undergo whole genome sequencing, DNA methylation, whole blood-based transcriptome sequencing, unbiased proteomics based on mass spectrometry, as well as metabolomics and lipidomics on a mass spectrometry platform. The study is analyzed in 3 subsequent phases, and each phase consists of a discovery cohort and an independent validation cohort. For the primary analysis, the primary phenotype will be the presence of any atherosclerotic plaque, as detected by cardiac CT. Additional phenotypic analyses will include per patient maximal luminal stenosis defined as 50% and 70% diameter stenosis. Single-omic and multi-omic associations will be examined for each phenotype; putative biomarkers will be assessed for association, calibration, discrimination, and reclassification. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Getting Ready for the Human Phenome Project: The 2012 Forum of the Human Variome Project

PubMed Central

Oetting, William S.; Robinson, Peter N.; Greenblatt, Marc S.; Cotton, Richard G.; Beck, Tim; Carey, John C.; Doelken, Sandra C.; Girdea, Marta; Groza, Tudor; Hamilton, Carol M.; Hamosh, Ada; Kerner, Berit; MacArthur, Jacqueline A. L.; Maglott, Donna R.; Mons, Barend; Rehm, Heidi L.; Schofield, Paul N.; Searle, Beverly A.; Smedley, Damian; Smith, Cynthia L.; Bernstein, Inge Thomsen; Zankl, Andreas; Zhao, Eric Y.

2014-01-01

A forum of the Human Variome Project (HVP) was held as a satellite to the 2012 Annual Meeting of the American Society of Human Genetics in San Francisco, California. The theme of this meeting was “Getting Ready for the Human Phenome Project.” Understanding the genetic contribution to both rare single-gene “Mendelian” disorders and more complex common diseases will require integration of research efforts among many fields and better defined phenotypes. The HVP is dedicated to bringing together researchers and research populations throughout the world to provide the resources to investigate the impact of genetic variation on disease. To this end, there needs to be a greater sharing of phenotype and genotype data. For this to occur, many databases that currently exist will need to become interoperable to allow for the combining of cohorts with similar phenotypes to increase statistical power for studies attempting to identify novel disease genes or causative genetic variants. Improved systems and tools that enhance the collection of phenotype data from clinicians are urgently needed. This meeting begins the HVP’s effort toward this important goal. PMID:23401191

A Review of Imaging Techniques for Plant Phenotyping

PubMed Central

Li, Lei; Zhang, Qin; Huang, Danfeng

2014-01-01

Given the rapid development of plant genomic technologies, a lack of access to plant phenotyping capabilities limits our ability to dissect the genetics of quantitative traits. Effective, high-throughput phenotyping platforms have recently been developed to solve this problem. In high-throughput phenotyping platforms, a variety of imaging methodologies are being used to collect data for quantitative studies of complex traits related to the growth, yield and adaptation to biotic or abiotic stress (disease, insects, drought and salinity). These imaging techniques include visible imaging (machine vision), imaging spectroscopy (multispectral and hyperspectral remote sensing), thermal infrared imaging, fluorescence imaging, 3D imaging and tomographic imaging (MRT, PET and CT). This paper presents a brief review on these imaging techniques and their applications in plant phenotyping. The features used to apply these imaging techniques to plant phenotyping are described and discussed in this review. PMID:25347588

Genome sequencing, metabolic and antibiotic resistance phenotyping of diverse nasopharyngeal bacteria isolated from cattle in an epidemiological study of bovine respiratory disease

USDA-ARS?s Scientific Manuscript database

Problem: Despite over 100 years of research to reduce the incidence and impact of bovine respiratory disease complex (BRDC) in North American feed yard cattle, outbreaks still occur accounting for up to 75% of feed yard cattle morbidity. BRDC is the primary driver of health-related antibiotic trea...

Shadows of complexity: what biological networks reveal about epistasis and pleiotropy

PubMed Central

Tyler, Anna L.; Asselbergs, Folkert W.; Williams, Scott M.; Moore, Jason H.

2011-01-01

Pleiotropy, in which one mutation causes multiple phenotypes, has traditionally been seen as a deviation from the conventional observation in which one gene affects one phenotype. Epistasis, or gene-gene interaction, has also been treated as an exception to the Mendelian one gene-one phenotype paradigm. This simplified perspective belies the pervasive complexity of biology and hinders progress toward a deeper understanding of biological systems. We assert that epistasis and pleiotropy are not isolated occurrences, but ubiquitous and inherent properties of biomolecular networks. These phenomena should not be treated as exceptions, but rather as fundamental components of genetic analyses. A systems level understanding of epistasis and pleiotropy is, therefore, critical to furthering our understanding of human genetics and its contribution to common human disease. Finally, graph theory offers an intuitive and powerful set of tools with which to study the network bases of these important genetic phenomena. PMID:19204994

Human MHC architecture and evolution: implications for disease association studies

PubMed Central

Traherne, J A

2008-01-01

Major histocompatibility complex (MHC) variation is a key determinant of susceptibility and resistance to a large number of infectious, autoimmune and other diseases. Identification of the MHC variants conferring susceptibility to disease is problematic, due to high levels of variation and linkage disequilibrium. Recent cataloguing and analysis of variation over the complete MHC has facilitated localization of susceptibility loci for autoimmune diseases, and provided insight into the MHC's evolution. This review considers how the unusual genetic characteristics of the MHC impact on strategies to identify variants causing, or contributing to, disease phenotypes. It also considers the MHC in relation to novel mechanisms influencing gene function and regulation, such as epistasis, epigenetics and microRNAs. These developments, along with recent technological advances, shed light on genetic association in complex disease. PMID:18397301

Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross

PubMed Central

Gralinski, Lisa E.; Ferris, Martin T.; Aylor, David L.; Whitmore, Alan C.; Green, Richard; Frieman, Matthew B.; Deming, Damon; Menachery, Vineet D.; Miller, Darla R.; Buus, Ryan J.; Bell, Timothy A.; Churchill, Gary A.; Threadgill, David W.; Katze, Michael G.; McMillan, Leonard; Valdar, William; Heise, Mark T.; Pardo-Manuel de Villena, Fernando; Baric, Ralph S.

2015-01-01

New systems genetics approaches are needed to rapidly identify host genes and genetic networks that regulate complex disease outcomes. Using genetically diverse animals from incipient lines of the Collaborative Cross mouse panel, we demonstrate a greatly expanded range of phenotypes relative to classical mouse models of SARS-CoV infection including lung pathology, weight loss and viral titer. Genetic mapping revealed several loci contributing to differential disease responses, including an 8.5Mb locus associated with vascular cuffing on chromosome 3 that contained 23 genes and 13 noncoding RNAs. Integrating phenotypic and genetic data narrowed this region to a single gene, Trim55, an E3 ubiquitin ligase with a role in muscle fiber maintenance. Lung pathology and transcriptomic data from mice genetically deficient in Trim55 were used to validate its role in SARS-CoV-induced vascular cuffing and inflammation. These data establish the Collaborative Cross platform as a powerful genetic resource for uncovering genetic contributions of complex traits in microbial disease severity, inflammation and virus replication in models of outbred populations. PMID:26452100

[A complex case of diabetes due to LMNA mutation].

PubMed

Ambonville, C; Bouldouyre, M-A; Laforêt, P; Richard, P; Benveniste, O; Vigouroux, C

2017-10-01

Laminopathies (diseases related to A/C mutations of lamines) are rare genetic diseases with an extensive phenotypic spectrum, including lipodystrophic syndromes-characterized by a selective loss of adipose tissue-of which the partial Dunnigan family type is the most frequent. We report on a 55-year-old woman with diabetes and long-term disabling myalgia. Her cushingoid morphotype, associated with cutaneous lipo-atrophy and muscle hypertrophy in addition to a genetic heritage, led us to the diagnosis of complex partial familial lipodystrophy heterozygous LMNA_c.82C>T, p.Arg28Trp mutation. Familial partial lipodystrophic syndromes may have varied phenotypes, mainly cardio-metabolic, which could mimic a particularly severe type 2 diabetes. The diagnostic work-up of this disease has to include a careful investigation of gait troubles and paroxysmal conduction that could lead to sudden death, as well as a genetic examination. In some cases, recombinant leptin can be proposed. Copyright © 2017 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier SAS. All rights reserved.

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.

Psoriasis: the future.

PubMed

Menter, M Alan; Griffiths, Christopher E M

2015-01-01

The umbrella term psoriasis is now understood to incorporate several distinct phenotypes or endotypes along the disease spectrum that in turn will dictate different therapies. A stratified medicine approach to psoriasis using this clinical information coupled with pharmacogenomic and immunologic data will become more widely acceptable in the future. Comorbidities associated with psoriasis, such as diabetes, depression, and Crohn disease, and the debate about the interdependence of psoriasis and cardiovascular disease will also dictate future research and holistic and management plans for this complex disease.

Genotypic and Phenotypic Characterization of Carriage and Invasive Disease Isolates of Neisseria meningitidis in Finland

PubMed Central

Saukkoriipi, Annika; Bratcher, Holly B.; Bloigu, Aini; Juvonen, Raija; Silvennoinen-Kassinen, Sylvi; Peitso, Ari; Harju, Terttu; Vainio, Olli; Kuusi, Markku; Maiden, Martin C. J.; Leinonen, Maija; Käyhty, Helena; Toropainen, Maija

2012-01-01

The relationship between carriage and the development of invasive meningococcal disease is not fully understood. We investigated the changes in meningococcal carriage in 892 military recruits in Finland during a nonepidemic period (July 2004 to January 2006) and characterized all of the oropharyngeal meningococcal isolates obtained (n = 215) by using phenotypic (serogrouping and serotyping) and genotypic (porA typing and multilocus sequence typing) methods. For comparison, 84 invasive meningococcal disease strains isolated in Finland between January 2004 and February 2006 were also analyzed. The rate of meningococcal carriage was significantly higher at the end of military service than on arrival (18% versus 2.2%; P < 0.001). Seventy-four percent of serogroupable carriage isolates belonged to serogroup B, and 24% belonged to serogroup Y. Most carriage isolates belonged to the carriage-associated ST-60 clonal complex. However, 21.5% belonged to the hyperinvasive ST-41/44 clonal complex. Isolates belonging to the ST-23 clonal complex were cultured more often from oropharyngeal samples taken during the acute phase of respiratory infection than from samples taken at health examinations at the beginning and end of military service (odds ratio [OR], 6.7; 95% confidence interval [95% CI], 2.7 to 16.4). The ST-32 clonal complex was associated with meningococcal disease (OR, 17.8; 95% CI, 3.8 to 81.2), while the ST-60 clonal complex was associated with carriage (OR, 10.7; 95% CI, 3.3 to 35.2). These findings point to the importance of meningococcal vaccination for military recruits and also to the need for an efficacious vaccine against serogroup B isolates. PMID:22135261

Further insight into the phenotype associated with a mutation in the ORC6 gene, causing Meier-Gorlin syndrome 3.

PubMed

Shalev, Stavit Allon; Khayat, Morad; Etty, Daniel-Spiegl; Elpeleg, Orly

2015-03-01

Mutations in genes encoding the origin recognition complex subunits cause Meier-Gorlin syndrome. The disease manifests a triad of short stature, small ears, and small and/or absent patellae with variable expressivity. We report on the identification of a homozygous deleterious mutation in the ORC6 gene in previously described fetuses at the severe end of the Meier-Gorlin spectrum. The phenotype included severe intrauterine growth retardation, dislocation of knees, gracile bones, clubfeet, and small mandible and chest. To date, the clinical presentation of ORC6-associated Meier-Gorlin syndrome has been mild compared to other the phenotype associated with other loci. The present report expands the clinical phenotype associated with ORC6 mutations to include severely abnormal embryological development suggesting a possible genotype-phenotype correlation. © 2015 Wiley Periodicals, Inc.

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

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

Dyslipidemias and Cardiovascular Prevention: Tailoring Treatment According to Lipid Phenotype.

PubMed

Sanin, Veronika; Pfetsch, Vanessa; Koenig, Wolfgang

2017-07-01

This study aimed to present the current information on the genetic background of dyslipidemias and provide insights into the complex pathophysiological role of several plasma lipids/lipoproteins in the pathogenesis of atherosclerotic cardiovascular disease. Furthermore, we aim to summarize established therapies and describe the scientific rationale for the development of novel therapeutic strategies. Evidence from genetic studies suggests that besides lowering low-density lipoprotein cholesterol, pharmacological reduction of triglyceride-rich lipoproteins, or lipoprotein(a) will reduce risk for coronary heart disease. Dyslipidemia, in particular hypercholesterolemia, is a common clinical condition and represents an important determinant of atherosclerotic vascular disease. Treatment decisions are currently guided by the causative lipid phenotype and the presence of other risk factors suggesting a very high cardiovascular risk. Therefore, the identification of lipid disorders and the optimal combination of therapeutic strategies provide an outstanding opportunity for reducing the onset and burden of cardiovascular disease.

Mouse Phenome Database

PubMed Central

Grubb, Stephen C.; Maddatu, Terry P.; Bult, Carol J.; Bogue, Molly A.

2009-01-01

The Mouse Phenome Database (MPD; http://www.jax.org/phenome) is an open source, web-based repository of phenotypic and genotypic data on commonly used and genetically diverse inbred strains of mice and their derivatives. MPD is also a facility for query, analysis and in silico hypothesis testing. Currently MPD contains about 1400 phenotypic measurements contributed by research teams worldwide, including phenotypes relevant to human health such as cancer susceptibility, aging, obesity, susceptibility to infectious diseases, atherosclerosis, blood disorders and neurosensory disorders. Electronic access to centralized strain data enables investigators to select optimal strains for many systems-based research applications, including physiological studies, drug and toxicology testing, modeling disease processes and complex trait analysis. The ability to select strains for specific research applications by accessing existing phenotype data can bypass the need to (re)characterize strains, precluding major investments of time and resources. This functionality, in turn, accelerates research and leverages existing community resources. Since our last NAR reporting in 2007, MPD has added more community-contributed data covering more phenotypic domains and implemented several new tools and features, including a new interactive Tool Demo available through the MPD homepage (quick link: http://phenome.jax.org/phenome/trytools). PMID:18987003

Candidate genes for COPD in two large data sets.

PubMed

Bakke, P S; Zhu, G; Gulsvik, A; Kong, X; Agusti, A G N; Calverley, P M A; Donner, C F; Levy, R D; Make, B J; Paré, P D; Rennard, S I; Vestbo, J; Wouters, E F M; Anderson, W; Lomas, D A; Silverman, E K; Pillai, S G

2011-02-01

Lack of reproducibility of findings has been a criticism of genetic association studies on complex diseases, such as chronic obstructive pulmonary disease (COPD). We selected 257 polymorphisms of 16 genes with reported or potential relationships to COPD and genotyped these variants in a case-control study that included 953 COPD cases and 956 control subjects. We explored the association of these polymorphisms to three COPD phenotypes: a COPD binary phenotype and two quantitative traits (post-bronchodilator forced expiratory volume in 1 s (FEV₁) % predicted and FEV₁/forced vital capacity (FVC)). The polymorphisms significantly associated to these phenotypes in this first study were tested in a second, family-based study that included 635 pedigrees with 1,910 individuals. Significant associations to the binary COPD phenotype in both populations were seen for STAT1 (rs13010343) and NFKBIB/SIRT2 (rs2241704) (p<0.05). Single-nucleotide polymorphisms rs17467825 and rs1155563 of the GC gene were significantly associated with FEV₁ % predicted and FEV₁/FVC, respectively, in both populations (p<0.05). This study has replicated associations to COPD phenotypes in the STAT1, NFKBIB/SIRT2 and GC genes in two independent populations, the associations of the former two genes representing novel findings.

Spanish Guidelines for Management of Chronic Obstructive Pulmonary Disease (GesEPOC) 2017. Pharmacological Treatment of Stable Phase.

PubMed

Miravitlles, Marc; Soler-Cataluña, Juan José; Calle, Myriam; Molina, Jesús; Almagro, Pere; Quintano, José Antonio; Trigueros, Juan Antonio; Cosío, Borja G; Casanova, Ciro; Antonio Riesco, Juan; Simonet, Pere; Rigau, David; Soriano, Joan B; Ancochea, Julio

2017-06-01

The clinical presentation of chronic obstructive pulmonary disease (COPD) varies widely, so treatment must be tailored according to the level of risk and phenotype. In 2012, the Spanish COPD Guidelines (GesEPOC) first established pharmacological treatment regimens based on clinical phenotypes. These regimens were subsequently adopted by other national guidelines, and since then, have been backed up by new evidence. In this 2017 update, the original severity classification has been replaced by a much simpler risk classification (low or high risk), on the basis of lung function, dyspnea grade, and history of exacerbations, while determination of clinical phenotype is recommended only in high-risk patients. The same clinical phenotypes have been maintained: non-exacerbator, asthma-COPD overlap (ACO), exacerbator with emphysema, and exacerbator with bronchitis. Pharmacological treatment of COPD is based on bronchodilators, the only treatment recommended in low-risk patients. High-risk patients will receive different drugs in addition to bronchodilators, depending on their clinical phenotype. GesEPOC reflects a more individualized approach to COPD treatment, according to patient clinical characteristics and level of risk or complexity. Copyright © 2017 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

The genetic basis for survivorship in coronary artery disease

PubMed Central

Dungan, Jennifer R.; Hauser, Elizabeth R.; Qin, Xuejun; Kraus, William E.

2013-01-01

Survivorship is a trait characterized by endurance and virility in the face of hardship. It is largely considered a psychosocial attribute developed during fatal conditions, rather than a biological trait for robustness in the context of complex, age-dependent diseases like coronary artery disease (CAD). The purpose of this paper is to present the novel phenotype, survivorship in CAD as an observed survival advantage concurrent with clinically significant CAD. We present a model for characterizing survivorship in CAD and its relationships with overlapping time- and clinically-related phenotypes. We offer an optimal measurement interval for investigating survivorship in CAD. We hypothesize genetic contributions to this construct and review the literature for evidence of genetic contribution to overlapping phenotypes in support of our hypothesis. We also present preliminary evidence of genetic effects on survival in people with clinically significant CAD from a primary case-control study of symptomatic coronary disease. Identifying gene variants that confer improved survival in the context of clinically appreciable CAD may improve our understanding of cardioprotective mechanisms acting at the gene level and potentially impact patients clinically in the future. Further, characterizing other survival-variant genetic effects may improve signal-to-noise ratio in detecting gene associations for CAD. PMID:24143143

Strategic approaches to unraveling genetic causes of cardiovascular diseases

USDA-ARS?s Scientific Manuscript database

DNA sequence variants are major components of the "causal field" for virtually all medical phenotypes, whether single gene familial disorders or complex traits without a clear familial aggregation. The causal variants in single gene disorders are necessary and sufficient to impart large effects. In ...

Myopathology of Adult and Paediatric Mitochondrial Diseases

PubMed Central

Phadke, Rahul

2017-01-01

Mitochondria are dynamic organelles ubiquitously present in nucleated eukaryotic cells, subserving multiple metabolic functions, including cellular ATP generation by oxidative phosphorylation (OXPHOS). The OXPHOS machinery comprises five transmembrane respiratory chain enzyme complexes (RC). Defective OXPHOS gives rise to mitochondrial diseases (mtD). The incredible phenotypic and genetic diversity of mtD can be attributed at least in part to the RC dual genetic control (nuclear DNA (nDNA) and mitochondrial DNA (mtDNA)) and the complex interaction between the two genomes. Despite the increasing use of next-generation-sequencing (NGS) and various omics platforms in unravelling novel mtD genes and pathomechanisms, current clinical practice for investigating mtD essentially involves a multipronged approach including clinical assessment, metabolic screening, imaging, pathological, biochemical and functional testing to guide molecular genetic analysis. This review addresses the broad muscle pathology landscape including genotype–phenotype correlations in adult and paediatric mtD, the role of immunodiagnostics in understanding some of the pathomechanisms underpinning the canonical features of mtD, and recent diagnostic advances in the field. PMID:28677615

Mutations in KEOPS-complex genes cause nephrotic syndrome with primary microcephaly.

PubMed

Braun, Daniela A; Rao, Jia; Mollet, Geraldine; Schapiro, David; Daugeron, Marie-Claire; Tan, Weizhen; Gribouval, Olivier; Boyer, Olivia; Revy, Patrick; Jobst-Schwan, Tilman; Schmidt, Johanna Magdalena; Lawson, Jennifer A; Schanze, Denny; Ashraf, Shazia; Ullmann, Jeremy F P; Hoogstraten, Charlotte A; Boddaert, Nathalie; Collinet, Bruno; Martin, Gaëlle; Liger, Dominique; Lovric, Svjetlana; Furlano, Monica; Guerrera, I Chiara; Sanchez-Ferras, Oraly; Hu, Jennifer F; Boschat, Anne-Claire; Sanquer, Sylvia; Menten, Björn; Vergult, Sarah; De Rocker, Nina; Airik, Merlin; Hermle, Tobias; Shril, Shirlee; Widmeier, Eugen; Gee, Heon Yung; Choi, Won-Il; Sadowski, Carolin E; Pabst, Werner L; Warejko, Jillian K; Daga, Ankana; Basta, Tamara; Matejas, Verena; Scharmann, Karin; Kienast, Sandra D; Behnam, Babak; Beeson, Brendan; Begtrup, Amber; Bruce, Malcolm; Ch'ng, Gaik-Siew; Lin, Shuan-Pei; Chang, Jui-Hsing; Chen, Chao-Huei; Cho, Megan T; Gaffney, Patrick M; Gipson, Patrick E; Hsu, Chyong-Hsin; Kari, Jameela A; Ke, Yu-Yuan; Kiraly-Borri, Cathy; Lai, Wai-Ming; Lemyre, Emmanuelle; Littlejohn, Rebecca Okashah; Masri, Amira; Moghtaderi, Mastaneh; Nakamura, Kazuyuki; Ozaltin, Fatih; Praet, Marleen; Prasad, Chitra; Prytula, Agnieszka; Roeder, Elizabeth R; Rump, Patrick; Schnur, Rhonda E; Shiihara, Takashi; Sinha, Manish D; Soliman, Neveen A; Soulami, Kenza; Sweetser, David A; Tsai, Wen-Hui; Tsai, Jeng-Daw; Topaloglu, Rezan; Vester, Udo; Viskochil, David H; Vatanavicharn, Nithiwat; Waxler, Jessica L; Wierenga, Klaas J; Wolf, Matthias T F; Wong, Sik-Nin; Leidel, Sebastian A; Truglio, Gessica; Dedon, Peter C; Poduri, Annapurna; Mane, Shrikant; Lifton, Richard P; Bouchard, Maxime; Kannu, Peter; Chitayat, David; Magen, Daniella; Callewaert, Bert; van Tilbeurgh, Herman; Zenker, Martin; Antignac, Corinne; Hildebrandt, Friedhelm

2017-10-01

Galloway-Mowat syndrome (GAMOS) is an autosomal-recessive disease characterized by the combination of early-onset nephrotic syndrome (SRNS) and microcephaly with brain anomalies. Here we identified recessive mutations in OSGEP, TP53RK, TPRKB, and LAGE3, genes encoding the four subunits of the KEOPS complex, in 37 individuals from 32 families with GAMOS. CRISPR-Cas9 knockout in zebrafish and mice recapitulated the human phenotype of primary microcephaly and resulted in early lethality. Knockdown of OSGEP, TP53RK, or TPRKB inhibited cell proliferation, which human mutations did not rescue. Furthermore, knockdown of these genes impaired protein translation, caused endoplasmic reticulum stress, activated DNA-damage-response signaling, and ultimately induced apoptosis. Knockdown of OSGEP or TP53RK induced defects in the actin cytoskeleton and decreased the migration rate of human podocytes, an established intermediate phenotype of SRNS. We thus identified four new monogenic causes of GAMOS, describe a link between KEOPS function and human disease, and delineate potential pathogenic mechanisms.

LIPT1 deficiency presenting as early infantile epileptic encephalopathy, Leigh disease, and secondary pyruvate dehydrogenase complex deficiency.

PubMed

Stowe, Robert C; Sun, Qin; Elsea, Sarah H; Scaglia, Fernando

2018-05-01

Lipoic acid is an essential cofactor for the mitochondrial 2-ketoacid dehydrogenase complexes and the glycine cleavage system. Lipoyltransferase 1 catalyzes the covalent attachment of lipoate to these enzyme systems. Pathogenic variants in LIPT1 gene have recently been described in four patients from three families, commonly presenting with severe lactic acidosis resulting in neonatal death and/or poor neurocognitive outcomes. We report a 2-month-old male with severe lactic acidosis, refractory status epilepticus, and brain imaging suggestive of Leigh disease. Exome sequencing implicated compound heterozygous LIPT1 pathogenic variants. We describe the fifth case of LIPT1 deficiency, whose phenotype progressed to that of an early infantile epileptic encephalopathy, which is novel compared to previously described patients whom we will review. Due to the significant biochemical and phenotypic overlap that LIPT1 deficiency and mitochondrial energy cofactor disorders have with pyruvate dehydrogenase deficiency and/or nonketotic hyperglycinemia, they are and have been presumptively under-diagnosed without exome sequencing. © 2018 Wiley Periodicals, Inc.

Factor analysis in the Genetics of Asthma International Network family study identifies five major quantitative asthma phenotypes.

PubMed

Pillai, S G; Tang, Y; van den Oord, E; Klotsman, M; Barnes, K; Carlsen, K; Gerritsen, J; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Ortega, H G; Anderson, W H; Helms, P J

2008-03-01

Asthma is a clinically heterogeneous disease caused by a complex interaction between genetic susceptibility and diverse environmental factors. In common with other complex diseases the lack of a standardized scheme to evaluate the phenotypic variability poses challenges in identifying the contribution of genes and environments to disease expression. To determine the minimum number of sets of features required to characterize subjects with asthma which will be useful in identifying important genetic and environmental contributors. Methods Probands aged 7-35 years with physician diagnosed asthma and symptomatic siblings were identified in 1022 nuclear families from 11 centres in six countries forming the Genetics of Asthma International Network. Factor analysis was used to identify distinct phenotypes from questionnaire, clinical, and laboratory data, including baseline pulmonary function, allergen skin prick test (SPT). Five distinct factors were identified:(1) baseline pulmonary function measures [forced expiratory volume in 1 s (FEV(1)) and forced vital capacity (FVC)], (2) specific allergen sensitization by SPT, (3) self-reported allergies, (4) symptoms characteristic of rhinitis and (5) symptoms characteristic of asthma. Replication in symptomatic siblings was consistent with shared genetic and/or environmental effects, and was robust across age groups, gender, and centres. Cronbach's alpha ranged from 0.719 to 0.983 suggesting acceptable internal scale consistencies. Derived scales were correlated with serum IgE, methacholine PC(20), age and asthma severity (interrupted sleep). IgE correlated with all three atopy-related factors, the strongest with the SPT factor whereas severity only correlated with baseline lung function, and with symptoms characteristic of rhinitis and of asthma. In children and adolescents with established asthma, five distinct sets of correlated patient characteristics appear to represent important aspects of the disease. Factor scores as quantitative traits may be better phenotypes in epidemiological and genetic analyses than those categories derived from the presence or absence of combinations of +ve SPTs and/or elevated IgE.

High-Throughput Screening Enhances Kidney Organoid Differentiation from Human Pluripotent Stem Cells and Enables Automated Multidimensional Phenotyping.

PubMed

Czerniecki, Stefan M; Cruz, Nelly M; Harder, Jennifer L; Menon, Rajasree; Annis, James; Otto, Edgar A; Gulieva, Ramila E; Islas, Laura V; Kim, Yong Kyun; Tran, Linh M; Martins, Timothy J; Pippin, Jeffrey W; Fu, Hongxia; Kretzler, Matthias; Shankland, Stuart J; Himmelfarb, Jonathan; Moon, Randall T; Paragas, Neal; Freedman, Benjamin S

2018-05-15

Organoids derived from human pluripotent stem cells are a potentially powerful tool for high-throughput screening (HTS), but the complexity of organoid cultures poses a significant challenge for miniaturization and automation. Here, we present a fully automated, HTS-compatible platform for enhanced differentiation and phenotyping of human kidney organoids. The entire 21-day protocol, from plating to differentiation to analysis, can be performed automatically by liquid-handling robots, or alternatively by manual pipetting. High-content imaging analysis reveals both dose-dependent and threshold effects during organoid differentiation. Immunofluorescence and single-cell RNA sequencing identify previously undetected parietal, interstitial, and partially differentiated compartments within organoids and define conditions that greatly expand the vascular endothelium. Chemical modulation of toxicity and disease phenotypes can be quantified for safety and efficacy prediction. Screening in gene-edited organoids in this system reveals an unexpected role for myosin in polycystic kidney disease. Organoids in HTS formats thus establish an attractive platform for multidimensional phenotypic screening. Copyright © 2018 Elsevier Inc. All rights reserved.

A novel ANO3 variant identified in a 53-year-old woman presenting with hyperkinetic dysarthria, blepharospasm, hyperkinesias, and complex motor tics.

PubMed

Blackburn, Patrick R; Zimmermann, Michael T; Gass, Jennifer M; Harris, Kimberly G; Cousin, Margot A; Boczek, Nicole J; Ross, Owen A; Klee, Eric W; Brazis, Paul W; Van Gerpen, Jay A; Atwal, Paldeep S

2016-12-05

Cervical dystonias have a variable presentation and underlying etiology, but collectively represent the most common form of focal dystonia. There are a number of known genetic forms of dystonia (DYT1-27); however the heterogeneity of disease presentation does not always make it easy to categorize the disease by phenotype-genotype comparison. In this report, we describe a 53-year-old female who presented initially with hand tremor following a total hip arthroplasty. The patient developed a mixed hyperkinetic disorder consisting of chorea, dystonia affecting the upper extremities, dysarthria, and blepharospasm. Whole exome sequencing of the patient revealed a novel heterozygous missense variant (Chr11(GRCh38): g.26525644C > G; NM_031418.2(ANO3): c.702C > G; NP_113606.2. p.C234W) in exon 7 in the ANO3 gene. ANO3 encodes anoctamin-3, a Ca +2 -dependent phospholipid scramblase expressed in striatal-neurons, that has been implicated in autosomal dominant craniocervical dystonia (Dystonia-24, DYT24, MIM# 615034). To date, only a handful of cases of DYT-24 have been described in the literature. The complex clinical presentation of the patient described includes hyperkinesias, complex motor movements, and vocal tics, which have not been reported in other patients with DYT24. This report highlights the utility of using clinical whole exome sequencing in patients with complex neurological phenotypes that would not normally fit a classical presentation of a defined genetic disease.

Clustering high-dimensional mixed data to uncover sub-phenotypes: joint analysis of phenotypic and genotypic data.

PubMed

McParland, D; Phillips, C M; Brennan, L; Roche, H M; Gormley, I C

2017-12-10

The LIPGENE-SU.VI.MAX study, like many others, recorded high-dimensional continuous phenotypic data and categorical genotypic data. LIPGENE-SU.VI.MAX focuses on the need to account for both phenotypic and genetic factors when studying the metabolic syndrome (MetS), a complex disorder that can lead to higher risk of type 2 diabetes and cardiovascular disease. Interest lies in clustering the LIPGENE-SU.VI.MAX participants into homogeneous groups or sub-phenotypes, by jointly considering their phenotypic and genotypic data, and in determining which variables are discriminatory. A novel latent variable model that elegantly accommodates high dimensional, mixed data is developed to cluster LIPGENE-SU.VI.MAX participants using a Bayesian finite mixture model. A computationally efficient variable selection algorithm is incorporated, estimation is via a Gibbs sampling algorithm and an approximate BIC-MCMC criterion is developed to select the optimal model. Two clusters or sub-phenotypes ('healthy' and 'at risk') are uncovered. A small subset of variables is deemed discriminatory, which notably includes phenotypic and genotypic variables, highlighting the need to jointly consider both factors. Further, 7 years after the LIPGENE-SU.VI.MAX data were collected, participants underwent further analysis to diagnose presence or absence of the MetS. The two uncovered sub-phenotypes strongly correspond to the 7-year follow-up disease classification, highlighting the role of phenotypic and genotypic factors in the MetS and emphasising the potential utility of the clustering approach in early screening. Additionally, the ability of the proposed approach to define the uncertainty in sub-phenotype membership at the participant level is synonymous with the concepts of precision medicine and nutrition. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Mitochondrial threshold effects.

PubMed Central

Rossignol, Rodrigue; Faustin, Benjamin; Rocher, Christophe; Malgat, Monique; Mazat, Jean-Pierre; Letellier, Thierry

2003-01-01

The study of mitochondrial diseases has revealed dramatic variability in the phenotypic presentation of mitochondrial genetic defects. To attempt to understand this variability, different authors have studied energy metabolism in transmitochondrial cell lines carrying different proportions of various pathogenic mutations in their mitochondrial DNA. The same kinds of experiments have been performed on isolated mitochondria and on tissue biopsies taken from patients with mitochondrial diseases. The results have shown that, in most cases, phenotypic manifestation of the genetic defect occurs only when a threshold level is exceeded, and this phenomenon has been named the 'phenotypic threshold effect'. Subsequently, several authors showed that it was possible to inhibit considerably the activity of a respiratory chain complex, up to a critical value, without affecting the rate of mitochondrial respiration or ATP synthesis. This phenomenon was called the 'biochemical threshold effect'. More recently, quantitative analysis of the effects of various mutations in mitochondrial DNA on the rate of mitochondrial protein synthesis has revealed the existence of a 'translational threshold effect'. In this review these different mitochondrial threshold effects are discussed, along with their molecular bases and the roles that they play in the presentation of mitochondrial diseases. PMID:12467494

Detecting phenotype-driven transitions in regulatory network structure.

PubMed

Padi, Megha; Quackenbush, John

2018-01-01

Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.

Translation of Genotype to Phenotype by a Hierarchy of Cell Subsystems.

PubMed

Yu, Michael Ku; Kramer, Michael; Dutkowski, Janusz; Srivas, Rohith; Licon, Katherine; Kreisberg, Jason; Ng, Cherie T; Krogan, Nevan; Sharan, Roded; Ideker, Trey

2016-02-24

Accurately translating genotype to phenotype requires accounting for the functional impact of genetic variation at many biological scales. Here we present a strategy for genotype-phenotype reasoning based on existing knowledge of cellular subsystems. These subsystems and their hierarchical organization are defined by the Gene Ontology or a complementary ontology inferred directly from previously published datasets. Guided by the ontology's hierarchical structure, we organize genotype data into an "ontotype," that is, a hierarchy of perturbations representing the effects of genetic variation at multiple cellular scales. The ontotype is then interpreted using logical rules generated by machine learning to predict phenotype. This approach substantially outperforms previous, non-hierarchical methods for translating yeast genotype to cell growth phenotype, and it accurately predicts the growth outcomes of two new screens of 2,503 double gene knockouts impacting DNA repair or nuclear lumen. Ontotypes also generalize to larger knockout combinations, setting the stage for interpreting the complex genetics of disease.

PhenoVar: a phenotype-driven approach in clinical genomics for the diagnosis of polymalformative syndromes

PubMed Central

2014-01-01

Background We propose a phenotype-driven analysis of encrypted exome data to facilitate the widespread implementation of exome sequencing as a clinical genetic screening test. Twenty test-patients with varied syndromes were selected from the literature. For each patient, the mutation, phenotypic data, and genetic diagnosis were available. Next, control exome-files, each modified to include one of these twenty mutations, were assigned to the corresponding test-patients. These data were used by a geneticist blinded to the diagnoses to test the efficiency of our software, PhenoVar. The score assigned by PhenoVar to any genetic diagnosis listed in OMIM (Online Mendelian Inheritance in Man) took into consideration both the patient’s phenotype and all variations present in the corresponding exome. The physician did not have access to the individual mutations. PhenoVar filtered the search using a cut-off phenotypic match threshold to prevent undesired discovery of incidental findings and ranked the OMIM entries according to diagnostic score. Results When assigning the same weight to all variants in the exome, PhenoVar predicted the correct diagnosis in 10/20 patients, while in 15/20 the correct diagnosis was among the 4 highest ranked diagnoses. When assigning a higher weight to variants known, or bioinformatically predicted, to cause disease, PhenoVar’s yield increased to 14/20 (18/20 in top 4). No incidental findings were identified using our cut-off phenotypic threshold. Conclusion The phenotype-driven approach described could render widespread use of ES more practical, ethical and clinically useful. The implications about novel disease identification, advancement of complex diseases and personalized medicine are discussed. PMID:24884844

Complex Adaptive System Models and the Genetic Analysis of Plasma HDL-Cholesterol Concentration

PubMed Central

Rea, Thomas J.; Brown, Christine M.; Sing, Charles F.

2006-01-01

Despite remarkable advances in diagnosis and therapy, ischemic heart disease (IHD) remains a leading cause of morbidity and mortality in industrialized countries. Recent efforts to estimate the influence of genetic variation on IHD risk have focused on predicting individual plasma high-density lipoprotein cholesterol (HDL-C) concentration. Plasma HDL-C concentration (mg/dl), a quantitative risk factor for IHD, has a complex multifactorial etiology that involves the actions of many genes. Single gene variations may be necessary but are not individually sufficient to predict a statistically significant increase in risk of disease. The complexity of phenotype-genotype-environment relationships involved in determining plasma HDL-C concentration has challenged commonly held assumptions about genetic causation and has led to the question of which combination of variations, in which subset of genes, in which environmental strata of a particular population significantly improves our ability to predict high or low risk phenotypes. We document the limitations of inferences from genetic research based on commonly accepted biological models, consider how evidence for real-world dynamical interactions between HDL-C determinants challenges the simplifying assumptions implicit in traditional linear statistical genetic models, and conclude by considering research options for evaluating the utility of genetic information in predicting traits with complex etiologies. PMID:17146134

Mapping, fine mapping, and molecular dissection of quantitative trait Loci in domestic animals.

PubMed

Georges, Michel

2007-01-01

Artificial selection has created myriad breeds of domestic animals, each characterized by unique phenotypes pertaining to behavior, morphology, physiology, and disease. Most domestic animal populations share features with isolated founder populations, making them well suited for positional cloning. Genome sequences are now available for most domestic species, and with them a panoply of tools including high-density single-nucleotide polymorphism panels. As a result, domestic animal populations are becoming invaluable resources for studying the molecular architecture of complex traits and of adaptation. Here we review recent progress and issues in the positional identification of genes underlying complex traits in domestic animals. As many phenotypes studied in animals are quantitative, we focus on mapping, fine mapping, and cloning of quantitative trait loci.

Heuristic Identification of Biological Architectures for Simulating Complex Hierarchical Genetic Interactions

PubMed Central

Moore, Jason H; Amos, Ryan; Kiralis, Jeff; Andrews, Peter C

2015-01-01

Simulation plays an essential role in the development of new computational and statistical methods for the genetic analysis of complex traits. Most simulations start with a statistical model using methods such as linear or logistic regression that specify the relationship between genotype and phenotype. This is appealing due to its simplicity and because these statistical methods are commonly used in genetic analysis. It is our working hypothesis that simulations need to move beyond simple statistical models to more realistically represent the biological complexity of genetic architecture. The goal of the present study was to develop a prototype genotype–phenotype simulation method and software that are capable of simulating complex genetic effects within the context of a hierarchical biology-based framework. Specifically, our goal is to simulate multilocus epistasis or gene–gene interaction where the genetic variants are organized within the framework of one or more genes, their regulatory regions and other regulatory loci. We introduce here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating data in this manner. This approach combines a biological hierarchy, a flexible mathematical framework, a liability threshold model for defining disease endpoints, and a heuristic search strategy for identifying high-order epistatic models of disease susceptibility. We provide several simulation examples using genetic models exhibiting independent main effects and three-way epistatic effects. PMID:25395175

Complex and multi-allelic copy number variation in human disease

PubMed Central

McCarroll, Steven A.

2015-01-01

Hundreds of copy number variants are complex and multi-allelic, in that they have many structural alleles and have rearranged multiple times in the ancestors who contributed chromosomes to current humans. Not only are the relationships of these multi-allelic CNVs (mCNVs) to phenotypes generally unknown, but many mCNVs have not yet been described at the basic levels—alleles, allele frequencies, structural features—that support genetic investigation. To date, most reported disease associations to these variants have been ascertained through candidate gene studies. However, only a few associations have reached the level of acceptance defined by durable replications in many cohorts. This likely stems from longstanding challenges in making precise molecular measurements of the alleles individuals have at these loci. However, approaches for mCNV analysis are improving quickly, and some of the unique characteristics of mCNVs may assist future association studies. Their various structural alleles are likely to have different magnitudes of effect, creating a natural allelic series of growing phenotypic impact and giving investigators a set of natural predictions and testable hypotheses about the extent to which each allele of an mCNV predisposes to a phenotype. Also, mCNVs’ low-to-modest correlation to individual single-nucleotide polymorphisms (SNPs) may make it easier to distinguish between mCNVs and nearby SNPs as the drivers of an association signal, and perhaps, make it possible to preliminarily screen candidate loci, or the entire genome, for the many mCNV–disease relationships that remain to be discovered. PMID:26163405

Multi-omics analysis of inflammatory bowel disease.

PubMed

Huang, Hu; Vangay, Pajau; McKinlay, Christopher E; Knights, Dan

2014-12-01

Crohn's disease and ulcerative colitis, known together as inflammatory bowel disease (IBD), are severe autoimmune disorders now causing gut inflammation and ulceration, among other symptoms, in up to 1 in 250 people worldwide. Incidence and prevalence of IBD have been increasing dramatically over the past several decades, although the causes for this increase are still unknown. IBD has both a complex genotype and a complex phenotype, and although it has received substantial attention from the medical research community over recent years, much of the etiology remains unexplained. Genome-wide association studies have identified a rich genetic signature of disease risk in patients with IBD, consisting of at least 163 genetic loci. Many of these loci contain genes directly involved in microbial handling, indicating that the genetic architecture of the disease has been driven by host-microbe interactions. In addition, systematic shifts in gut microbiome structure (enterotype) and function have been observed in patients with IBD. Furthermore, both the host genotype and enterotype are associated with aspects of the disease phenotype, including location of the disease. This provides strong evidence of interactions between host genotype and enterotype; however, there is a lack of published multi-omics data from IBD patients, and a lack of bioinformatics tools for modeling such systems. In this article we discuss, from a computational biologist's point of view, the potential benefits of and the challenges involved in designing and analyzing such multi-omics studies of IBD. Copyright © 2014 Elsevier B.V. All rights reserved.

Innate lymphoid cells and asthma.

PubMed

Yu, Sanhong; Kim, Hye Young; Chang, Ya-Jen; DeKruyff, Rosemarie H; Umetsu, Dale T

2014-04-01

Asthma is a complex and heterogeneous disease with several phenotypes, including an allergic asthma phenotype characterized by TH2 cytokine production and associated with allergen sensitization and adaptive immunity. Asthma also includes nonallergic asthma phenotypes, such as asthma associated with exposure to air pollution, infection, or obesity, that require innate rather than adaptive immunity. These innate pathways that lead to asthma involve macrophages, neutrophils, natural killer T cells, and innate lymphoid cells, newly described cell types that produce a variety of cytokines, including IL-5 and IL-13. We review the recent data regarding innate lymphoid cells and their role in asthma. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

SNPs located at CpG sites modulate genome-epigenome interaction

USDA-ARS?s Scientific Manuscript database

DNA methylation is an important molecular-level phenotype that links genotypes and complex disease traits. Previous studies have found local correlation between genetic variants and DNA methylation levels (cis-meQTLs). However, general mechanisms underlying cis-meQTLs are unclear. We conducted a cis...

Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis.

PubMed

Wei, Wen-Hua; Bowes, John; Plant, Darren; Viatte, Sebastien; Yarwood, Annie; Massey, Jonathan; Worthington, Jane; Eyre, Stephen

2016-04-25

Genotypic variability based genome-wide association studies (vGWASs) can identify potentially interacting loci without prior knowledge of the interacting factors. We report a two-stage approach to make vGWAS applicable to diseases: firstly using a mixed model approach to partition dichotomous phenotypes into additive risk and non-additive environmental residuals on the liability scale and secondly using the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups per marker. We found widespread significant (P < 2.5e-05) vGWAS signals within the major histocompatibility complex (MHC) across all three study cohorts of rheumatoid arthritis. We further identified 10 epistatic interactions between the vGWAS signals independent of the MHC additive effects, each with a weak effect but jointly explained 1.9% of phenotypic variance. PTPN22 was also identified in the discovery cohort but replicated in only one independent cohort. Combining the three cohorts boosted power of vGWAS and additionally identified TYK2 and ANKRD55. Both PTPN22 and TYK2 had evidence of interactions reported elsewhere. We conclude that vGWAS can help discover interacting loci for complex diseases but require large samples to find additional signals.

Mutations in the evolutionarily highly conserved KEOPS complex genes cause nephrotic syndrome with microcephaly

PubMed Central

Braun, Daniela A.; Rao, Jia; Mollet, Geraldine; Schapiro, David; Daugeron, Marie-Claire; Tan, Weizhen; Gribouval, Olivier; Boyer, Olivia; Revy, Patrick; Jobst-Schwan, Tilman; Schmidt, Johanna Magdalena; Lawson, Jennifer A.; Schanze, Denny; Ashraf, Shazia; Boddaert, Nathalie; Collinet, Bruno; Martin, Gaëlle; Liger, Dominique; Lovric, Svjetlana; Furlano, Monica; Guerrera, I. Chiara; Sanchez-Ferras, Oraly; Menten, Björn; Vergult, Sarah; De Rocker, Nina; Airik, Merlin; Hermle, Tobias; Shril, Shirlee; Widmeier, Eugen; Gee, Heon Yung; Choi, Won-Il; Sadowski, Carolin E.; Pabst, Werner L.; Warejko, Jillian; Daga, Ankana; LeBerre, Tamara Basta; Matejas, Verena; Behnam, Babak; Beeson, Brendan; Begtrup, Amber; Bruce, Malcolm; Ch'ng, Gaik-Siew; Lin, Shuan-Pei; Chang, Jui-Hsing; Chen, Chao-Huei; Cho, Megan T.; Gipson, Patrick E.; Hsu, Chyong-Hsin; Kari, Jameela A.; Ke, Yu-Yuan; Kiraly-Borri, Cathy; Lai, Wai-ming; Lemyre, Emmanuelle; Littlejohn, Rebecca Okasha; Masri, Amira; Moghtaderi, Mastaneh; Nakamura, Kazuyuki; Praet, Marleen; Prasad, Chitra; Prytula, Agnieszka; Roeder, Elizabeth; Rump, Patrick; Schnur, Rhonda E.; Shiihara, Takashi; Sinha, Manish; Soliman, Neveen A; Soulami, Kenza; Sweetser, David A.; Tsai, Wen-Hui; Tsai, Jeng-Daw; Vester, Udo; Viskochil, David H.; Vatanavicharn, Nithiwat; Waxler, Jessica L.; Wolf, Matthias T.F.; Wong, Sik-Nin; Poduri, Annapurna; Truglio, Gessica; Mane, Shrikant; Lifton, Richard P.; Bouchard, Maxime; Kannu, Peter; Chitayat, David; Magen, Daniella; Calleweart, Bert; van Tilbeurgh, Herman; Zenker, Martin; Antignac, Corinne; Hildebrandt, Friedhelm

2018-01-01

Galloway-Mowat syndrome (GAMOS) is a severe autosomal-recessive disease characterized by the combination of early-onset steroid-resistant nephrotic syndrome (SRNS) and microcephaly with brain anomalies. To date, mutations of WDR73 are the only known monogenic cause of GAMOS and in most affected individuals the molecular diagnosis remains elusive. We here identify recessive mutations of OSGEP, TP53RK, TPRKB, or LAGE3, encoding the 4 subunits of the KEOPS complex in 33 individuals of 30 families with GAMOS. CRISPR/Cas9 knockout in zebrafish and mice recapitulates the human phenotype of microcephaly and results in early lethality. Knockdown of OSGEP, TP53RK, or TPRKB inhibits cell proliferation, which human mutations fail to rescue, and knockdown of either gene activates DNA damage response signaling and induces apoptosis. OSGEP and TP53RK molecularly interact and co-localize with the actin-regulating ARP2/3 complex. Furthermore, knockdown of OSGEP and TP53RK induces defects of the actin cytoskeleton and reduces migration rate of human podocytes, an established intermediate phenotype of SRNS. We thus identify 4 novel monogenic causes of GAMOS, describe the first link between KEOPS function and human disease, and delineate potential pathogenic mechanisms. PMID:28805828

A Framework for Integrating Multiple Biological Networks to Predict MicroRNA-Disease Associations.

PubMed

Peng, Wei; Lan, Wei; Yu, Zeng; Wang, Jianxin; Pan, Yi

2017-03-01

MicroRNAs have close relationship with human diseases. Therefore, identifying disease related MicroRNAs plays an important role in disease diagnosis, prognosis and therapy. However, designing an effective computational method which can make good use of various biological resources and correctly predict the associations between MicroRNA and disease is still a big challenge. Previous researchers have pointed out that there are complex relationships among microRNAs, diseases and environment factors. There are inter-relationships between microRNAs, diseases or environment factors based on their functional similarity or phenotype similarity or chemical structure similarity and so on. There are also intra-relationships between microRNAs and diseases, microRNAs and environment factors, diseases and environment factors. Moreover, functionally similar microRNAs tend to associate with common diseases and common environment factors. The diseases with similar phenotypes are likely caused by common microRNAs and common environment factors. In this work, we propose a framework namely ThrRWMDE which can integrate these complex relationships to predict microRNA-disease associations. In this framework, microRNA similarity network (MFN), disease similarity network (DSN) and environmental factor similarity network (ESN) are constructed according to certain biological properties. Then, an unbalanced three random walking algorithm is implemented on the three networks so as to obtain information from neighbors in corresponding networks. This algorithm not only can flexibly infer information from different levels of neighbors with respect to the topological and structural differences of the three networks, but also in the course of working the functional information will be transferred from one network to another according to the associations between the nodes in different networks. The results of experiment show that our method achieves better prediction performance than other state-of-the-art methods.

Evaluation of Semantic Web Technologies for Storing Computable Definitions of Electronic Health Records Phenotyping Algorithms.

PubMed

Papež, Václav; Denaxas, Spiros; Hemingway, Harry

2017-01-01

Electronic Health Records are electronic data generated during or as a byproduct of routine patient care. Structured, semi-structured and unstructured EHR offer researchers unprecedented phenotypic breadth and depth and have the potential to accelerate the development of precision medicine approaches at scale. A main EHR use-case is defining phenotyping algorithms that identify disease status, onset and severity. Phenotyping algorithms utilize diagnoses, prescriptions, laboratory tests, symptoms and other elements in order to identify patients with or without a specific trait. No common standardized, structured, computable format exists for storing phenotyping algorithms. The majority of algorithms are stored as human-readable descriptive text documents making their translation to code challenging due to their inherent complexity and hinders their sharing and re-use across the community. In this paper, we evaluate the two key Semantic Web Technologies, the Web Ontology Language and the Resource Description Framework, for enabling computable representations of EHR-driven phenotyping algorithms.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Big insights from small volumes: deciphering complex leukocyte behaviors using microfluidics

PubMed Central

Irimia, Daniel; Ellett, Felix

2016-01-01

Inflammation is an indispensable component of the immune response, and leukocytes provide the first line of defense against infection. Although the major stereotypic leukocyte behaviors in response to infection are well known, the complexities and idiosyncrasies of these phenotypes in conditions of disease are still emerging. Novel tools are indispensable for gaining insights into leukocyte behavior, and in the past decade, microfluidic technologies have emerged as an exciting development in the field. Microfluidic devices are readily customizable, provide tight control of experimental conditions, enable high precision of ex vivo measurements of individual as well as integrated leukocyte functions, and have facilitated the discovery of novel leukocyte phenotypes. Here, we review some of the most interesting insights resulting from the application of microfluidic approaches to the study of the inflammatory response. The aim is to encourage leukocyte biologists to integrate these new tools into increasingly more sophisticated experimental designs for probing complex leukocyte functions. PMID:27194799

The GARP complex is required for cellular sphingolipid homeostasis.

PubMed

Fröhlich, Florian; Petit, Constance; Kory, Nora; Christiano, Romain; Hannibal-Bach, Hans-Kristian; Graham, Morven; Liu, Xinran; Ejsing, Christer S; Farese, Robert V; Walther, Tobias C

2015-09-10

Sphingolipids are abundant membrane components and important signaling molecules in eukaryotic cells. Their levels and localization are tightly regulated. However, the mechanisms underlying this regulation remain largely unknown. In this study, we identify the Golgi-associated retrograde protein (GARP) complex, which functions in endosome-to-Golgi retrograde vesicular transport, as a critical player in sphingolipid homeostasis. GARP deficiency leads to accumulation of sphingolipid synthesis intermediates, changes in sterol distribution, and lysosomal dysfunction. A GARP complex mutation analogous to a VPS53 allele causing progressive cerebello-cerebral atrophy type 2 (PCCA2) in humans exhibits similar, albeit weaker, phenotypes in yeast, providing mechanistic insights into disease pathogenesis. Inhibition of the first step of de novo sphingolipid synthesis is sufficient to mitigate many of the phenotypes of GARP-deficient yeast or mammalian cells. Together, these data show that GARP is essential for cellular sphingolipid homeostasis and suggest a therapeutic strategy for the treatment of PCCA2.

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.

Emerging understanding of the genotype-phenotype relationship in amyotrophic lateral sclerosis.

PubMed

Goutman, Stephen A; Chen, Kevin S; Paez-Colasante, Ximena; Feldman, Eva L

2018-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive, noncurable neurodegenerative disorder of the upper and lower motor neurons causing weakness and death within a few years of symptom onset. About 10% of patients with ALS have a family history of the disease; however, ALS-associated genetic mutations are also found in sporadic cases. There are over 100 ALS-associated mutations, and importantly, several genetic mutations, including C9ORF72, SOD1, and TARDBP, have led to mechanistic insight into this complex disease. In the clinical realm, knowledge of ALS genetics can also help explain phenotypic heterogeneity, aid in genetic counseling, and in the future may help direct treatment efforts. Copyright © 2018 Elsevier B.V. All rights reserved.

Familial Hypercholesterolaemia

PubMed Central

Marais, A David

2004-01-01

Familial hypercholesterolaemia (FH), defined as the heritable occurrence of severe hypercholesterolaemia with cholesterol deposits in tendons and premature heart disease, is caused by at least four genes in sterol and lipoprotein pathways and displays varying gene-dose effects. The genes are the low-density lipoprotein (LDL) receptor, apolipoprotein (apo) B, proprotein convertase subtilisin/kexin 9, and the autosomal recessive hypercholesterolaemia (ARH) adaptor protein. All of these disorders have in common defective clearance of LDL within a complex system of lipid and lipoprotein metabolism and regulation. Normal cellular cholesterol and lipoprotein metabolism is reviewed before describing the disorders, their metabolic derangements and their clinical effects. FH is classified as two simplified phenotypes of disease according to the severity of the metabolic derangement. The dominantly inherited heterozygous phenotype comprises defects in the LDL receptor, apoB100, and neural apoptosis regulatory cleavage protein. The homozygous phenotype is co-dominant in defects of the LDL receptor, and occurs also as the ARH of adapter protein mutations. Defective binding of apoB100 does not result in a significant gene dose effect, but enhances the severity of heterozygotes for LDL receptor mutations. The genetic diagnosis of FH has provided greater accuracy in definition and detection of disease and exposes information about migration of populations. All of these disorders pose a high risk of atherosclerosis, especially in the homozygous phenotype. Studies of influences on the phenotype and responses to treatment are also discussed in the context of the metabolic derangements. PMID:18516203

A Genotypic-Oriented View of CFTR Genetics Highlights Specific Mutational Patterns Underlying Clinical Macrocategories of Cystic Fibrosis

PubMed Central

Lucarelli, Marco; Bruno, Sabina Maria; Pierandrei, Silvia; Ferraguti, Giampiero; Stamato, Antonella; Narzi, Fabiana; Amato, Annalisa; Cimino, Giuseppe; Bertasi, Serenella; Quattrucci, Serena; Strom, Roberto

2015-01-01

Cystic fibrosis (CF) is a monogenic disease caused by mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The genotype–phenotype relationship in this disease is still unclear, and diagnostic, prognostic and therapeutic challenges persist. We enrolled 610 patients with different forms of CF and studied them from a clinical, biochemical, microbiological and genetic point of view. Overall, there were 125 different mutated alleles (11 with novel mutations and 10 with complex mutations) and 225 genotypes. A strong correlation between mutational patterns at the genotypic level and phenotypic macrocategories emerged. This specificity appears to largely depend on rare and individual mutations, as well as on the varying prevalence of common alleles in different clinical macrocategories. However, 19 genotypes appeared to underlie different clinical forms of the disease. The dissection of the pathway from the CFTR mutated genotype to the clinical phenotype allowed to identify at least two components of the variability usually found in the genotype–phenotype relationship. One component seems to depend on the genetic variation of CFTR, the other component on the cumulative effect of variations in other genes and cellular pathways independent from CFTR. The experimental dissection of the overall biological CFTR pathway appears to be a powerful approach for a better comprehension of the genotype–phenotype relationship. However, a change from an allele-oriented to a genotypic-oriented view of CFTR genetics is mandatory, as well as a better assessment of sources of variability within the CFTR pathway. PMID:25910067

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

PubMed Central

Rossin, Elizabeth J.; Lage, Kasper; Raychaudhuri, Soumya; Xavier, Ramnik J.; Tatar, Diana; Benita, Yair

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein–protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease. PMID:21249183

Careflow Mining Techniques to Explore Type 2 Diabetes Evolution.

PubMed

Dagliati, Arianna; Tibollo, Valentina; Cogni, Giulia; Chiovato, Luca; Bellazzi, Riccardo; Sacchi, Lucia

2018-03-01

In this work we describe the application of a careflow mining algorithm to detect the most frequent patterns of care in a type 2 diabetes patients cohort. The applied method enriches the detected patterns with clinical data to define temporal phenotypes across the studied population. Novel phenotypes are discovered from heterogeneous data of 424 Italian patients, and compared in terms of metabolic control and complications. Results show that careflow mining can help to summarize the complex evolution of the disease into meaningful patterns, which are also significant from a clinical point of view.

Cohesin and Human Disease

PubMed Central

Liu, Jinglan; Krantz, Ian D.

2016-01-01

Cornelia de Lange syndrome (CdLS) is a dominant multisystem disorder caused by a disruption of cohesin function. The cohesin ring complex is composed of four protein subunits and more than 25 additional proteins involved in its regulation. The discovery that this complex also has a fundamental role in long-range regulation of transcription in Drosophila has shed light on the mechanism likely responsible for its role in development. In addition to the three cohesin proteins involved in CdLS, a second multisystem, recessively inherited, developmental disorder, Roberts-SC phocomelia, is caused by mutations in another regulator of the cohesin complex, ESCO2. Here we review the phenotypes of these disorders, collectively termed cohesinopathies, as well as the mechanism by which cohesin disruption likely causes these diseases. PMID:18767966

The puzzle of immune phenotypes of childhood asthma.

PubMed

Landgraf-Rauf, Katja; Anselm, Bettina; Schaub, Bianca

2016-12-01

Asthma represents the most common chronic childhood disease worldwide. Whereas preschool children present with wheezing triggered by different factors (multitrigger and viral wheeze), clinical asthma manifestation in school children has previously been classified as allergic and non-allergic asthma. For both, the underlying immunological mechanisms are not yet understood in depth in children. Treatment is still prescribed regardless of underlying mechanisms, and children are not always treated successfully. This review summarizes recent key findings on the complex mechanisms of the development and manifestation of childhood asthma. Whereas traditional classification of childhood asthma is primarily based on clinical symptoms like wheezing and atopy, novel approaches to specify asthma phenotypes are under way and face challenges such as including the stability of phenotypes over time and transition into adulthood. Epidemiological studies enclose more information on the patient's disease history and environmental influences. Latest studies define endotypes based on molecular and cellular mechanisms, for example defining risk and protective single nucleotide polymorphisms (SNPs) and new immune phenotypes, showing promising results. Also, regulatory T cells and recently discovered T helper cell subtypes such as Th9 and Th17 cells were shown to be important for the development of asthma. Innate lymphoid cells (ILC) could play a critical role in asthma patients as they produce different cytokines associated with asthma. Epigenetic findings showed different acetylation and methylation patterns for children with allergic and non-allergic asthma. On a posttranscriptional level, miRNAs are regulating factors identified to differ between asthma patients and healthy controls and also indicate differences within asthma phenotypes. Metabolomics is another exciting chapter important for endotyping asthmatic children. Despite the development of new biomarkers and the discovery of new immunological molecules, the complex puzzle of childhood asthma is still far from being completed. Addressing the current challenges of distinct clinical asthma and wheeze phenotypes, including their stability and underlying endotypes, involves addressing the interplay of innate and adaptive immune regulatory mechanisms in large, interdisciplinary cohorts.

Comprehensive lipid analysis: a powerful metanomic tool for predictive and diagnostic medicine.

PubMed

Watkins, S M

2000-09-01

The power and accuracy of predictive diagnostics stand to improve dramatically as a result of lipid metanomics. The high definition of data obtained with this approach allows multiple rather than single metabolites to be used in markers for a group. Since as many as 40 fatty acids are quantified from each lipid class, and up to 15 lipid classes can be quantified easily, more than 600 individual lipid metabolites can be measured routinely for each sample. Because these analyses are comprehensive, only the most appropriate and unique metabolites are selected for their predictive value. Thus, comprehensive lipid analysis promises to greatly improve predictive diagnostics for phenotypes that directly or peripherally involve lipids. A broader and possibly more exciting aspect of this technology is the generation of metabolic profiles that are not simply markers for disease, but metabolic maps that can be used to identify specific genes or activities that cause or influence the disease state. Metanomics is, in essence, functional genomics from metabolite analysis. By defining the metabolic basis for phenotype, researchers and clinicians will have an extraordinary opportunity to understand and treat disease. Much in the same way that gene chips allow researchers to observe the complex expression response to a stimulus, metanomics will enable researchers to observe the complex metabolic interplay responsible for defining phenotype. By extending this approach beyond the observation of individual dysregulations, medicine will begin to profile not single diseases, but health. As health is the proper balance of all vital metabolic pathways, comprehensive or metanomic analysis lends itself very well to identifying the metabolite distributions necessary for optimum health. Comprehensive and quantitative analysis of lipids would provide this degree of diagnostic power to researchers and clinicians interested in mining metabolic profiles for biological meaning.

Can Creutzfeldt-Jakob disease unravel the mysteries of Alzheimer?

PubMed

Kovacs, Gabor G

2016-09-02

Recent studies on iatrogenic Creutzfeldt-Jakob disease (CJD) raised concerns that one of the hallmark lesions of Alzheimer disease (AD), amyloid-β (Aβ), may be transmitted from human-to-human. The neuropathology of AD-related lesions is complex. Therefore, many aspects need to be considered in deciding on this issue. Observations of recent studies can be summarized as follows: 1) The frequency of iatrogenic CJD cases with parencyhmal and vascular Aβ deposits is statistically higher than expected; 2) The morphology and distribution of Aβ deposition may show distinct features; 3) The pituitary and the dura mater themselves may serve as potential sources of Aβ seeds; 4) Cadaveric dura mater from 2 examined cases shows Aβ deposition; and 5) There is a lack of evidence that the clinical phenotype of AD appears following the application of cadaveric pituitary hormone or dura mater transplantation. These studies support the notion that neurodegenerative diseases have common features regarding propagation of disease-associated proteins as seeds. However, until further evidence emerges, prions of transmissible spongiform encephalopathies are the only neurodegenerative disease-related proteins proven to propagate clinicopathological phenotypes.

Primary hypertension is a disease of premature vascular aging associated with neuro-immuno-metabolic abnormalities.

PubMed

Litwin, Mieczysław; Feber, Janusz; Niemirska, Anna; Michałkiewicz, Jacek

2016-02-01

There is an increasing amount of data indicating that primary hypertension (PH) is not only a hemodynamic phenomenon but also a complex syndrome involving abnormal fat tissue distribution, over-activity of the sympathetic nervous system (SNS), metabolic abnormalities, and activation of the immune system. In children, PH usually presents with a typical phenotype of disturbed body composition, accelerated biological maturity, and subtle immunological and metabolic abnormalities. This stage of the disease is potentially reversible. However, long-lasting over-activity of the SNS and immuno-metabolic alterations usually lead to an irreversible stage of cardiovascular disease. We describe an intermediate phenotype of children with PH, showing that PH is associated with accelerated development, i.e., early premature aging of the immune, metabolic, and vascular systems. The associations and determinants of hypertensive organ damage, the principles of treatment, and the possibility of rejuvenation of the cardiovascular system are discussed.

HFE gene variants, iron, and lipids: a novel connection in Alzheimer's disease.

PubMed

Ali-Rahmani, Fatima; Schengrund, Cara-Lynne; Connor, James R

2014-01-01

Iron accumulation and associated oxidative stress in the brain have been consistently found in several neurodegenerative diseases. Multiple genetic studies have been undertaken to try to identify a cause of neurodegenerative diseases but direct connections have been rare. In the iron field, variants in the HFE gene that give rise to a protein involved in cellular iron regulation, are associated with iron accumulation in multiple organs including the brain. There is also substantial epidemiological, genetic, and molecular evidence of disruption of cholesterol homeostasis in several neurodegenerative diseases, in particular Alzheimer's disease (AD). Despite the efforts that have been made to identify factors that can trigger the pathological events associated with neurodegenerative diseases they remain mostly unknown. Because molecular phenotypes such as oxidative stress, synaptic failure, neuronal loss, and cognitive decline, characteristics associated with AD, have been shown to result from disruption of a number of pathways, one can easily argue that the phenotype seen may not arise from a linear sequence of events. Therefore, a multi-targeted approach is needed to understand a complex disorder like AD. This can be achieved only when knowledge about interactions between the different pathways and the potential influence of environmental factors on them becomes available. Toward this end, this review discusses what is known about the roles and interactions of iron and cholesterol in neurodegenerative diseases. It highlights the effects of gene variants of HFE (H63D- and C282Y-HFE) on iron and cholesterol metabolism and how they may contribute to understanding the etiology of complex neurodegenerative diseases.

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease.

PubMed

Baillie, J Kenneth; Bretherick, Andrew; Haley, Christopher S; Clohisey, Sara; Gray, Alan; Neyton, Lucile P A; Barrett, Jeffrey; Stahl, Eli A; Tenesa, Albert; Andersson, Robin; Brown, J Ben; Faulkner, Geoffrey J; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Itoh, Masayoshi; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Mole, Damian; Bajic, Vladimir B; Heutink, Peter; Rehli, Michael; Kawaji, Hideya; Sandelin, Albin; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A; Hacohen, Nir; Freeman, Thomas C; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Hume, David A

2018-03-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn's disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits.

HFE gene variants, iron, and lipids: a novel connection in Alzheimer’s disease

PubMed Central

Ali-Rahmani, Fatima; Schengrund, Cara-Lynne; Connor, James R.

2014-01-01

Iron accumulation and associated oxidative stress in the brain have been consistently found in several neurodegenerative diseases. Multiple genetic studies have been undertaken to try to identify a cause of neurodegenerative diseases but direct connections have been rare. In the iron field, variants in the HFE gene that give rise to a protein involved in cellular iron regulation, are associated with iron accumulation in multiple organs including the brain. There is also substantial epidemiological, genetic, and molecular evidence of disruption of cholesterol homeostasis in several neurodegenerative diseases, in particular Alzheimer’s disease (AD). Despite the efforts that have been made to identify factors that can trigger the pathological events associated with neurodegenerative diseases they remain mostly unknown. Because molecular phenotypes such as oxidative stress, synaptic failure, neuronal loss, and cognitive decline, characteristics associated with AD, have been shown to result from disruption of a number of pathways, one can easily argue that the phenotype seen may not arise from a linear sequence of events. Therefore, a multi-targeted approach is needed to understand a complex disorder like AD. This can be achieved only when knowledge about interactions between the different pathways and the potential influence of environmental factors on them becomes available. Toward this end, this review discusses what is known about the roles and interactions of iron and cholesterol in neurodegenerative diseases. It highlights the effects of gene variants of HFE (H63D- and C282Y-HFE) on iron and cholesterol metabolism and how they may contribute to understanding the etiology of complex neurodegenerative diseases. PMID:25071582

Shared activity patterns arising at genetic susceptibility loci reveal underlying genomic and cellular architecture of human disease

PubMed Central

Gray, Alan; Neyton, Lucile P. A.; Barrett, Jeffrey; Stahl, Eli A.; Tenesa, Albert; Andersson, Robin; Brown, J. Ben; Faulkner, Geoffrey J.; Lizio, Marina; Schaefer, Ulf; Daub, Carsten; Kondo, Naoto; Lassmann, Timo; Kawai, Jun; Kawaji, Hideya; Suzuki, Harukazu; Satsangi, Jack; Wells, Christine A.; Hacohen, Nir; Freeman, Thomas C.; Hayashizaki, Yoshihide; Forrest, Alistair R. R.; Hume, David A.

2018-01-01

Genetic variants underlying complex traits, including disease susceptibility, are enriched within the transcriptional regulatory elements, promoters and enhancers. There is emerging evidence that regulatory elements associated with particular traits or diseases share similar patterns of transcriptional activity. Accordingly, shared transcriptional activity (coexpression) may help prioritise loci associated with a given trait, and help to identify underlying biological processes. Using cap analysis of gene expression (CAGE) profiles of promoter- and enhancer-derived RNAs across 1824 human samples, we have analysed coexpression of RNAs originating from trait-associated regulatory regions using a novel quantitative method (network density analysis; NDA). For most traits studied, phenotype-associated variants in regulatory regions were linked to tightly-coexpressed networks that are likely to share important functional characteristics. Coexpression provides a new signal, independent of phenotype association, to enable fine mapping of causative variants. The NDA coexpression approach identifies new genetic variants associated with specific traits, including an association between the regulation of the OCT1 cation transporter and genetic variants underlying circulating cholesterol levels. NDA strongly implicates particular cell types and tissues in disease pathogenesis. For example, distinct groupings of disease-associated regulatory regions implicate two distinct biological processes in the pathogenesis of ulcerative colitis; a further two separate processes are implicated in Crohn’s disease. Thus, our functional analysis of genetic predisposition to disease defines new distinct disease endotypes. We predict that patients with a preponderance of susceptibility variants in each group are likely to respond differently to pharmacological therapy. Together, these findings enable a deeper biological understanding of the causal basis of complex traits. PMID:29494619

High content screening in neurodegenerative diseases.

PubMed

Jain, Shushant; van Kesteren, Ronald E; Heutink, Peter

2012-01-06

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention. High-throughput screening (HTS) is an ideal methodology to address these issues. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS). HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. HCS has many advantages over HTS, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism. Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets. Copyright © 2012 Creative Commons Attribution License

Mitochondrial respiratory chain Complex I defects in Fanconi anemia complementation group A.

PubMed

Ravera, Silvia; Vaccaro, Daniele; Cuccarolo, Paola; Columbaro, Marta; Capanni, Cristina; Bartolucci, Martina; Panfoli, Isabella; Morelli, Alessandro; Dufour, Carlo; Cappelli, Enrico; Degan, Paolo

2013-10-01

Fanconi anemia (FA) is a rare and complex inherited blood disorder of the child. At least 15 genes are associated with the disease. The highest frequency of mutations belongs to groups A, C and G. Genetic instability and cytokine hypersensitivity support the selection of leukemic over non-leukemic stem cells. FA cellular phenotype is characterized by alterations in red-ox state, mitochondrial functionality and energy metabolism as reported in the past however a clear picture of the altered biochemical phenotype in FA is still elusive and the final biochemical defect(s) still unknown. Here we report an analysis of the respiratory fluxes in FANCA primary fibroblasts, lymphocytes and lymphoblasts. FANCA mutants show defective respiration through Complex I, diminished ATP production and metabolic sufferance with an increased AMP/ATP ratio. Respiration in FANCC mutants is normal. Treatment with N-acetyl-cysteine (NAC) restores oxygen consumption to normal level. Defective respiration in FANCA mutants appear correlated with the FA pro-oxidative phenotype which is consistent with the altered morphology of FANCA mitochondria. Electron microscopy measures indeed show profound alterations in mitochondrial ultrastructure and shape. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

The Sex and Gender Intersection in Chronic Periodontitis

PubMed Central

Ioannidou, Effie

2017-01-01

Periodontitis, a complex polymicrobial inflammatory disease, is a public health burden affecting more than 100 million people and being partially responsible for tooth loss. Interestingly, periodontitis has a documented higher prevalence in men as compared to women signifying a possible sex/gender entanglement in the disease pathogenesis. Although relevant evidence has treated sex/gender in a simplistic dichotomous manner, periodontitis may represent a complex inflammatory disease model, in which sex biology may interfere with gender social and behavioral constructs affecting disease clinical phenotype. Even when it became clear that experimental oral health research needed to incorporate gender (and/or sex) framework in the hypothesis, researchers overwhelmingly ignored it unless the research question was directly related to reproductive system or sex-specific cancer. With the recognition of gender medicine as an independent field of research, this study challenged the current notion regarding sex/gender roles in periodontal disease. We aimed to develop the methodological and analytical framework with the recognition of sex/gender as important determinants of disease pathogenesis that require special attention. First, we aim to present relevant sex biologic evidence to understand the plausibility of the epidemiologic data. In periodontitis pathogenesis, sex dimorphism has been implicated in the disease etiology possibly affecting the bacterial component and the host immune response both in the innate and adaptive levels. With the clear distinction between sex and gender, gender oral health disparities have been explained by socioeconomic factors, cultural attitudes as well as access to preventive and regular care. Economic inequality and hardship for women have resulted in limited access to oral care. As a result, gender emerged as a complex socioeconomic and behavioral factor influencing oral health outcomes. Taken together, as disease phenotypic presentation is a multifactorial product of biology, behavior and the environment, sex dimorphism in immunity as well as gender socio-behavioral construct might play a role in the above model. Therefore, this paper will provide the conceptual framework and principles intergrading sex and gender within periodontal research in a complex biologic and socio-behavioral dimension. PMID:28824898

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

MECHANISMS IN ENDOCRINOLOGY: The sexually dimorphic role of androgens in human metabolic disease.

PubMed

Schiffer, Lina; Kempegowda, Punith; Arlt, Wiebke; O'Reilly, Michael W

2017-09-01

Female androgen excess and male androgen deficiency manifest with an overlapping adverse metabolic phenotype, including abdominal obesity, insulin resistance, type 2 diabetes mellitus, non-alcoholic fatty liver disease and an increased risk of cardiovascular disease. Here, we review the impact of androgens on metabolic target tissues in an attempt to unravel the complex mechanistic links with metabolic dysfunction; we also evaluate clinical studies examining the associations between metabolic disease and disorders of androgen metabolism in men and women. We conceptualise that an equilibrium between androgen effects on adipose tissue and skeletal muscle underpins the metabolic phenotype observed in female androgen excess and male androgen deficiency. Androgens induce adipose tissue dysfunction, with effects on lipid metabolism, insulin resistance and fat mass expansion, while anabolic effects on skeletal muscle may confer metabolic benefits. We hypothesise that serum androgen concentrations observed in female androgen excess and male hypogonadism are metabolically disadvantageous, promoting adipose and liver lipid accumulation, central fat mass expansion and insulin resistance. © 2017 The authors.

MECHANISMS IN ENDOCRINOLOGY: The sexually dimorphic role of androgens in human metabolic disease

PubMed Central

Schiffer, Lina; Kempegowda, Punith; Arlt, Wiebke

2017-01-01

Female androgen excess and male androgen deficiency manifest with an overlapping adverse metabolic phenotype, including abdominal obesity, insulin resistance, type 2 diabetes mellitus, non-alcoholic fatty liver disease and an increased risk of cardiovascular disease. Here, we review the impact of androgens on metabolic target tissues in an attempt to unravel the complex mechanistic links with metabolic dysfunction; we also evaluate clinical studies examining the associations between metabolic disease and disorders of androgen metabolism in men and women. We conceptualise that an equilibrium between androgen effects on adipose tissue and skeletal muscle underpins the metabolic phenotype observed in female androgen excess and male androgen deficiency. Androgens induce adipose tissue dysfunction, with effects on lipid metabolism, insulin resistance and fat mass expansion, while anabolic effects on skeletal muscle may confer metabolic benefits. We hypothesise that serum androgen concentrations observed in female androgen excess and male hypogonadism are metabolically disadvantageous, promoting adipose and liver lipid accumulation, central fat mass expansion and insulin resistance. PMID:28566439

Analysis of epidemiological studies: facts and artifacts.

PubMed

Wright, Anne L

2002-09-01

Cohort studies have provided the foundation for much of our knowledge of childhood asthma. Four important lessons have been learned from these longitudinal studies: that asthma is a complex disease, encompassing many phenotypes; that it is linked to the development of the immune system and respiratory tract in the first years of life; that early life events strongly affect the development of asthma risk and that relationships between certain exposures and asthma risk are age dependent. The Tucson Children's Respiratory Study is used to exemplify these lessons and to illustrate the advantages of cohort studies in investigating a complex disease. Copyright 2002 Elsevier Science Ltd.

Novel mutation in TSPAN12 leads to autosomal recessive inheritance of congenital vitreoretinal disease with intra-familial phenotypic variability.

PubMed

Gal, Moran; Levanon, Erez Y; Hujeirat, Yasir; Khayat, Morad; Pe'er, Jacob; Shalev, Stavit

2014-12-01

Developmental malformations of the vitreoretinal vasculature are a heterogeneous group of conditions with various modes of inheritance, and include familial exudative vitreoretinopathy (FEVR), persistent fetal vasculature (PFV), and Norrie disease. We investigated a large consanguineous kindred with multiple affected individuals exhibiting variable phenotypes of abnormal vitreoretinal vasculature, consistent with the three above-mentioned conditions and compatible with autosomal recessive inheritance. Exome sequencing identified a novel c.542G > T (p.C181F) apparently mutation in the TSPAN12 gene that segregated with the ocular disease in the family. The TSPAN12 gene was previously reported to cause dominant and recessive FEVR, but has not yet been associated with other vitreoretinal manifestations. The intra-familial clinical variability caused by a single mutation in the TSPAN12 gene underscores the complicated phenotype-genotype correlation of mutations in this gene, and suggests that there are additional genetic and environmental factors involved in the complex process of ocular vascularization during embryonic development. Our study supports considering PFV, FEVR, and Norrie disease a spectrum of disorders, with clinical and genetic overlap, caused by mutations in distinct genes acting in the Norrin/β-catenin signaling pathway. © 2014 Wiley Periodicals, Inc.

A novel nonsense mutation in the NDP gene in a Chinese family with Norrie disease.

PubMed

Liu, Deyuan; Hu, Zhengmao; Peng, Yu; Yu, Changhong; Liu, Yalan; Mo, Xiaoyun; Li, Xiaoping; Lu, Lina; Xu, Xiaojuan; Su, Wei; Pan, Qian; Xia, Kun

2010-12-08

Norrie disease (ND), a rare X-linked recessive disorder, is characterized by congenital blindness and, occasionally, mental retardation and hearing loss. ND is caused by the Norrie Disease Protein gene (NDP), which codes for norrin, a cysteine-rich protein involved in ocular vascular development. Here, we report a novel mutation of NDP that was identified in a Chinese family in which three members displayed typical ND symptoms and other complex phenotypes, such as cerebellar atrophy, motor disorders, and mental disorders. We conducted an extensive clinical examination of the proband and performed a computed tomography (CT) scan of his brain. Additionally, we performed ophthalmic examinations, haplotype analyses, and NDP DNA sequencing for 26 individuals from the proband's extended family. The proband's computed tomography scan, in which the fifth ventricle could be observed, indicated cerebellar atrophy. Genome scans and haplotype analyses traced the disease to chromosome Xp21.1-p11.22. Mutation screening of the NDP gene identified a novel nonsense mutation, c.343C>T, in this region. Although recent research has shown that multiple different mutations can be responsible for the ND phenotype, additional research is needed to understand the mechanism responsible for the diverse phenotypes caused by mutations in the NDP gene.

A novel nonsense mutation in the NDP gene in a Chinese family with Norrie disease

PubMed Central

Liu, Deyuan; Hu, Zhengmao; Peng, Yu; Yu, Changhong; Liu, Yalan; Mo, Xiaoyun; Li, Xiaoping; Lu, Lina; Xu, Xiaojuan; Su, Wei; Pan, Qian

2010-01-01

Purpose Norrie disease (ND), a rare X-linked recessive disorder, is characterized by congenital blindness and, occasionally, mental retardation and hearing loss. ND is caused by the Norrie Disease Protein gene (NDP), which codes for norrin, a cysteine-rich protein involved in ocular vascular development. Here, we report a novel mutation of NDP that was identified in a Chinese family in which three members displayed typical ND symptoms and other complex phenotypes, such as cerebellar atrophy, motor disorders, and mental disorders. Methods We conducted an extensive clinical examination of the proband and performed a computed tomography (CT) scan of his brain. Additionally, we performed ophthalmic examinations, haplotype analyses, and NDP DNA sequencing for 26 individuals from the proband’s extended family. Results The proband’s computed tomography scan, in which the fifth ventricle could be observed, indicated cerebellar atrophy. Genome scans and haplotype analyses traced the disease to chromosome Xp21.1-p11.22. Mutation screening of the NDP gene identified a novel nonsense mutation, c.343C>T, in this region. Conclusions Although recent research has shown that multiple different mutations can be responsible for the ND phenotype, additional research is needed to understand the mechanism responsible for the diverse phenotypes caused by mutations in the NDP gene. PMID:21179243

Has Neo-Darwinism failed clinical medicine: does systems biology have to?

PubMed

Joyner, Michael J

2015-01-01

In this essay I argue that Neo-Darwinism ultimately led to an oversimplified genotype equals phenotype view of human disease. This view has been called into question by the unexpected results of the Human Genome Project which has painted a far more complex picture of the genetic features of human disease than was anticipated. Cell centric Systems Biology is now attempting to reconcile this complexity. However, it too is limited because most common chronic diseases have systemic components not predicted by their intracellular responses alone. In this context, congestive heart failure is a classic example of this general problem and I discuss it as a systemic disease vs. one solely related to dysfunctional cardiomyocytes. I close by arguing that a physiological perspective is essential to reconcile reductionism with what is required to understand and treat disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease.

PubMed

Astle, William J; Elding, Heather; Jiang, Tao; Allen, Dave; Ruklisa, Dace; Mann, Alice L; Mead, Daniel; Bouman, Heleen; Riveros-Mckay, Fernando; Kostadima, Myrto A; Lambourne, John J; Sivapalaratnam, Suthesh; Downes, Kate; Kundu, Kousik; Bomba, Lorenzo; Berentsen, Kim; Bradley, John R; Daugherty, Louise C; Delaneau, Olivier; Freson, Kathleen; Garner, Stephen F; Grassi, Luigi; Guerrero, Jose; Haimel, Matthias; Janssen-Megens, Eva M; Kaan, Anita; Kamat, Mihir; Kim, Bowon; Mandoli, Amit; Marchini, Jonathan; Martens, Joost H A; Meacham, Stuart; Megy, Karyn; O'Connell, Jared; Petersen, Romina; Sharifi, Nilofar; Sheard, Simon M; Staley, James R; Tuna, Salih; van der Ent, Martijn; Walter, Klaudia; Wang, Shuang-Yin; Wheeler, Eleanor; Wilder, Steven P; Iotchkova, Valentina; Moore, Carmel; Sambrook, Jennifer; Stunnenberg, Hendrik G; Di Angelantonio, Emanuele; Kaptoge, Stephen; Kuijpers, Taco W; Carrillo-de-Santa-Pau, Enrique; Juan, David; Rico, Daniel; Valencia, Alfonso; Chen, Lu; Ge, Bing; Vasquez, Louella; Kwan, Tony; Garrido-Martín, Diego; Watt, Stephen; Yang, Ying; Guigo, Roderic; Beck, Stephan; Paul, Dirk S; Pastinen, Tomi; Bujold, David; Bourque, Guillaume; Frontini, Mattia; Danesh, John; Roberts, David J; Ouwehand, Willem H; Butterworth, Adam S; Soranzo, Nicole

2016-11-17

Many common variants have been associated with hematological traits, but identification of causal genes and pathways has proven challenging. We performed a genome-wide association analysis in the UK Biobank and INTERVAL studies, testing 29.5 million genetic variants for association with 36 red cell, white cell, and platelet properties in 173,480 European-ancestry participants. This effort yielded hundreds of low frequency (<5%) and rare (<1%) variants with a strong impact on blood cell phenotypes. Our data highlight general properties of the allelic architecture of complex traits, including the proportion of the heritable component of each blood trait explained by the polygenic signal across different genome regulatory domains. Finally, through Mendelian randomization, we provide evidence of shared genetic pathways linking blood cell indices with complex pathologies, including autoimmune diseases, schizophrenia, and coronary heart disease and evidence suggesting previously reported population associations between blood cell indices and cardiovascular disease may be non-causal. Copyright © 2016 Elsevier Inc. All rights reserved.

TMEM258 Is a Component of the Oligosaccharyltransferase Complex Controlling ER Stress and Intestinal Inflammation.

PubMed

Graham, Daniel B; Lefkovith, Ariel; Deelen, Patrick; de Klein, Niek; Varma, Mukund; Boroughs, Angela; Desch, A Nicole; Ng, Aylwin C Y; Guzman, Gaelen; Schenone, Monica; Petersen, Christine P; Bhan, Atul K; Rivas, Manuel A; Daly, Mark J; Carr, Steven A; Wijmenga, Cisca; Xavier, Ramnik J

2016-12-13

Significant insights into disease pathogenesis have been gleaned from population-level genetic studies; however, many loci associated with complex genetic disease contain numerous genes, and phenotypic associations cannot be assigned unequivocally. In particular, a gene-dense locus on chromosome 11 (61.5-61.65 Mb) has been associated with inflammatory bowel disease, rheumatoid arthritis, and coronary artery disease. Here, we identify TMEM258 within this locus as a central regulator of intestinal inflammation. Strikingly, Tmem258 haploinsufficient mice exhibit severe intestinal inflammation in a model of colitis. At the mechanistic level, we demonstrate that TMEM258 is a required component of the oligosaccharyltransferase complex and is essential for N-linked protein glycosylation. Consequently, homozygous deficiency of Tmem258 in colonic organoids results in unresolved endoplasmic reticulum (ER) stress culminating in apoptosis. Collectively, our results demonstrate that TMEM258 is a central mediator of ER quality control and intestinal homeostasis. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

Poly-Omic Prediction of Complex Traits: OmicKriging

PubMed Central

Wheeler, Heather E.; Aquino-Michaels, Keston; Gamazon, Eric R.; Trubetskoy, Vassily V.; Dolan, M. Eileen; Huang, R. Stephanie; Cox, Nancy J.; Im, Hae Kyung

2014-01-01

High-confidence prediction of complex traits such as disease risk or drug response is an ultimate goal of personalized medicine. Although genome-wide association studies have discovered thousands of well-replicated polymorphisms associated with a broad spectrum of complex traits, the combined predictive power of these associations for any given trait is generally too low to be of clinical relevance. We propose a novel systems approach to complex trait prediction, which leverages and integrates similarity in genetic, transcriptomic, or other omics-level data. We translate the omic similarity into phenotypic similarity using a method called Kriging, commonly used in geostatistics and machine learning. Our method called OmicKriging emphasizes the use of a wide variety of systems-level data, such as those increasingly made available by comprehensive surveys of the genome, transcriptome, and epigenome, for complex trait prediction. Furthermore, our OmicKriging framework allows easy integration of prior information on the function of subsets of omics-level data from heterogeneous sources without the sometimes heavy computational burden of Bayesian approaches. Using seven disease datasets from the Wellcome Trust Case Control Consortium (WTCCC), we show that OmicKriging allows simple integration of sparse and highly polygenic components yielding comparable performance at a fraction of the computing time of a recently published Bayesian sparse linear mixed model method. Using a cellular growth phenotype, we show that integrating mRNA and microRNA expression data substantially increases performance over either dataset alone. Using clinical statin response, we show improved prediction over existing methods. PMID:24799323

Next-generation sequencing to solve complex inherited retinal dystrophy: A case series of multiple genes contributing to disease in extended families.

PubMed

Jones, Kaylie D; Wheaton, Dianna K; Bowne, Sara J; Sullivan, Lori S; Birch, David G; Chen, Rui; Daiger, Stephen P

2017-01-01

With recent availability of next-generation sequencing (NGS), it is becoming more common to pursue disease-targeted panel testing rather than traditional sequential gene-by-gene dideoxy sequencing. In this report, we describe using NGS to identify multiple disease-causing mutations that contribute concurrently or independently to retinal dystrophy in three relatively small families. Family members underwent comprehensive visual function evaluations, and genetic counseling including a detailed family history. A preliminary genetic inheritance pattern was assigned and updated as additional family members were tested. Family 1 (FAM1) and Family 2 (FAM2) were clinically diagnosed with retinitis pigmentosa (RP) and had a suspected autosomal dominant pedigree with non-penetrance (n.p.). Family 3 (FAM3) consisted of a large family with a diagnosis of RP and an overall dominant pedigree, but the proband had phenotypically cone-rod dystrophy. Initial genetic analysis was performed on one family member with traditional Sanger single gene sequencing and/or panel-based testing, and ultimately, retinal gene-targeted NGS was required to identify the underlying cause of disease for individuals within the three families. Results obtained in these families necessitated further genetic and clinical testing of additional family members to determine the complex genetic and phenotypic etiology of each family. Genetic testing of FAM1 (n = 4 affected; 1 n.p.) identified a dominant mutation in RP1 (p.Arg677Ter) that was present for two of the four affected individuals but absent in the proband and the presumed non-penetrant individual. Retinal gene-targeted NGS in the fourth affected family member revealed compound heterozygous mutations in USH2A (p. Cys419Phe, p.Glu767Serfs*21). Genetic testing of FAM2 (n = 3 affected; 1 n.p.) identified three retinal dystrophy genes ( PRPH2 , PRPF8 , and USH2A ) with disease-causing mutations in varying combinations among the affected family members. Genetic testing of FAM3 (n = 7 affected) identified a mutation in PRPH2 (p.Pro216Leu) tracking with disease in six of the seven affected individuals. Additional retinal gene-targeted NGS testing determined that the proband also harbored a multiple exon deletion in the CRX gene likely accounting for her cone-rod phenotype; her son harbored only the mutation in CRX , not the familial mutation in PRPH2 . Multiple genes contributing to the retinal dystrophy genotypes within a family were discovered using retinal gene-targeted NGS. Families with noted examples of phenotypic variation or apparent non-penetrant individuals may offer a clue to suspect complex inheritance. Furthermore, this finding underscores that caution should be taken when attributing a single gene disease-causing mutation (or inheritance pattern) to a family as a whole. Identification of a disease-causing mutation in a proband, even with a clear inheritance pattern in hand, may not be sufficient for targeted, known mutation analysis in other family members.

Evolutionary history of human disease genes reveals phenotypic connections and comorbidity among genetic diseases

NASA Astrophysics Data System (ADS)

Park, Solip; Yang, Jae-Seong; Kim, Jinho; Shin, Young-Eun; Hwang, Jihye; Park, Juyong; Jang, Sung Key; Kim, Sanguk

2012-10-01

The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.

Evolutionary history of human disease genes reveals phenotypic connections and comorbidity among genetic diseases.

PubMed

Park, Solip; Yang, Jae-Seong; Kim, Jinho; Shin, Young-Eun; Hwang, Jihye; Park, Juyong; Jang, Sung Key; Kim, Sanguk

2012-01-01

The extent to which evolutionary changes have impacted the phenotypic relationships among human diseases remains unclear. In this work, we report that phenotypically similar diseases are connected by the evolutionary constraints on human disease genes. Human disease groups can be classified into slowly or rapidly evolving classes, where the diseases in the slowly evolving class are enriched with morphological phenotypes and those in the rapidly evolving class are enriched with physiological phenotypes. Our findings establish a clear evolutionary connection between disease classes and disease phenotypes for the first time. Furthermore, the high comorbidity found between diseases connected by similar evolutionary constraints enables us to improve the predictability of the relative risk of human diseases. We find the evolutionary constraints on disease genes are a new layer of molecular connection in the network-based exploration of human diseases.

PubMed Central

Ienco, Elena Caldarazzo; Orsucci, Daniele; Montano, Vincenzo; Ferrari, Elena; Petrozzi, Lucia; Cheli, Marta; LoGerfo, Annalisa; Simoncini, Costanza; Siciliano, Gabriele

2016-01-01

In recent years, there has been a surge of interest in mitochondrial diseases, a group of metabolic conditions caused by impairment of the oxidative phosphorylation system. The ubiquitous presence of mitochondria in all the cells of the body, their role as cell powerhouse and their particular genetic characteristics explain the phenotypic complexity and the diagnostic difficulties, bridging from paediatrician to neurologist.

Importance of resolving fungal nomenclature: the case of multiple pathogenic species in the Cryptococcus genus

USDA-ARS?s Scientific Manuscript database

Cryptococcosis is a major fungal disease caused by members of the Cryptococcus gattii and Cryptococcus neoformans species complexes. After more than 15 years of molecular genetic and phenotypic studies and much debate, a proposal for a taxonomic revision was made. The two varieties within C. neoform...

Common genetic variation drives molecular heterogeneity in human iPSCs.

PubMed

Kilpinen, Helena; Goncalves, Angela; Leha, Andreas; Afzal, Vackar; Alasoo, Kaur; Ashford, Sofie; Bala, Sendu; Bensaddek, Dalila; Casale, Francesco Paolo; Culley, Oliver J; Danecek, Petr; Faulconbridge, Adam; Harrison, Peter W; Kathuria, Annie; McCarthy, Davis; McCarthy, Shane A; Meleckyte, Ruta; Memari, Yasin; Moens, Nathalie; Soares, Filipa; Mann, Alice; Streeter, Ian; Agu, Chukwuma A; Alderton, Alex; Nelson, Rachel; Harper, Sarah; Patel, Minal; White, Alistair; Patel, Sharad R; Clarke, Laura; Halai, Reena; Kirton, Christopher M; Kolb-Kokocinski, Anja; Beales, Philip; Birney, Ewan; Danovi, Davide; Lamond, Angus I; Ouwehand, Willem H; Vallier, Ludovic; Watt, Fiona M; Durbin, Richard; Stegle, Oliver; Gaffney, Daniel J

2017-06-15

Technology utilizing human induced pluripotent stem cells (iPS cells) has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterization of many existing iPS cell lines limits their potential use for research and therapy. Here we describe the systematic generation, genotyping and phenotyping of 711 iPS cell lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative. Our study outlines the major sources of genetic and phenotypic variation in iPS cells and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPS cell phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of genomic copy-number alterations that are repeatedly observed in iPS cells. In addition, we present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells.

Common genetic variation drives molecular heterogeneity in human iPSCs

PubMed Central

Leha, Andreas; Afzal, Vackar; Alasoo, Kaur; Ashford, Sofie; Bala, Sendu; Bensaddek, Dalila; Casale, Francesco Paolo; Culley, Oliver J; Danecek, Petr; Faulconbridge, Adam; Harrison, Peter W; Kathuria, Annie; McCarthy, Davis; McCarthy, Shane A; Meleckyte, Ruta; Memari, Yasin; Moens, Nathalie; Soares, Filipa; Mann, Alice; Streeter, Ian; Agu, Chukwuma A; Alderton, Alex; Nelson, Rachel; Harper, Sarah; Patel, Minal; White, Alistair; Patel, Sharad R; Clarke, Laura; Halai, Reena; Kirton, Christopher M; Kolb-Kokocinski, Anja; Beales, Philip; Birney, Ewan; Danovi, Davide; Lamond, Angus I; Ouwehand, Willem H; Vallier, Ludovic; Watt, Fiona M; Durbin, Richard

2017-01-01

Induced pluripotent stem cell (iPSC) technology has enormous potential to provide improved cellular models of human disease. However, variable genetic and phenotypic characterisation of many existing iPSC lines limits their potential use for research and therapy. Here, we describe the systematic generation, genotyping and phenotyping of 711 iPSC lines derived from 301 healthy individuals by the Human Induced Pluripotent Stem Cells Initiative (HipSci: http://www.hipsci.org). Our study outlines the major sources of genetic and phenotypic variation in iPSCs and establishes their suitability as models of complex human traits and cancer. Through genome-wide profiling we find that 5-46% of the variation in different iPSC phenotypes, including differentiation capacity and cellular morphology, arises from differences between individuals. Additionally, we assess the phenotypic consequences of rare, genomic copy number mutations that are repeatedly observed in iPSC reprogramming and present a comprehensive map of common regulatory variants affecting the transcriptome of human pluripotent cells. PMID:28489815

Genetics of Mitochondrial Disease.

PubMed

Saneto, Russell P

2017-01-01

Mitochondria are intracellular organelles responsible for adenosine triphosphate production. The strict control of intracellular energy needs require proper mitochondrial functioning. The mitochondria are under dual controls of mitochondrial DNA (mtDNA) and nuclear DNA (nDNA). Mitochondrial dysfunction can arise from changes in either mtDNA or nDNA genes regulating function. There are an estimated ∼1500 proteins in the mitoproteome, whereas the mtDNA genome has 37 proteins. There are, to date, ∼275 genes shown to give rise to disease. The unique physiology of mitochondrial functioning contributes to diverse gene expression. The onset and range of phenotypic expression of disease is diverse, with onset from neonatal to seventh decade of life. The range of dysfunction is heterogeneous, ranging from single organ to multisystem involvement. The complexity of disease expression has severely limited gene discovery. Combining phenotypes with improvements in gene sequencing strategies are improving the diagnosis process. This chapter focuses on the interplay of the unique physiology and gene discovery in the current knowledge of genetically derived mitochondrial disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Interactome Networks and Human Disease

PubMed Central

Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

2011-01-01

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease. PMID:21414488

Assessment of canine BEST1 variations identifies new mutations and establishes an independent bestrophinopathy model (cmr3)

PubMed Central

Wickström, Kaisa; Slavik, Julianna; Lindauer, Sarah J.; Ahonen, Saija; Schelling, Claude; Lohi, Hannes; Guziewicz, Karina E.; Aguirre, Gustavo D.

2010-01-01

Purpose Mutations in bestrophin 1 (BEST1) are associated with a group of retinal disorders known as bestrophinopathies in man and canine multifocal retinopathies (cmr) in the dog. To date, the dog is the only large animal model suitable for the complex characterization and in-depth studies of Best-related disorders. In the first report of cmr, the disease was described in a group of mastiff-related breeds (cmr1) and the Coton de Tulear (cmr2). Additional breeds, e.g., the Lapponian herder (LH) and others, subsequently were recognized with similar phenotypes, but linked loci are unknown. Analysis of the BEST1 gene aimed to identify mutations in these additional populations and extend our understanding of genotype–phenotype associations. Methods Animals were subjected to routine eye exams, phenotypically characterized, and samples were collected for molecular studies. Known BEST1 mutations were assessed, and the canine BEST1 coding exons were amplified and sequenced in selected individuals that exhibited a cmr compatible phenotype but that did not carry known mutations. Resulting sequence changes were genotyped in several different breeds and evaluated in the context of the phenotype. Results Seven novel coding variants were identified in exon 10 of cBEST1. Two linked mutations were associated with cmr exclusive to the LH breed (cmr3). Two individuals of Jämthund and Norfolk terrier breeds were heterozygous for two conservative changes, but these were unlikely to have disease-causing potential. Another three substitutions were found in the Bernese mountain dog that were predicted to have a deleterious effect on protein function. Previously reported mutations were excluded from segregation in these populations, but cmr1 was confirmed in another mastiff-related breed, the Italian cane corso. Conclusions A third independent canine model for human bestrophinopathies has been established in the LH breed. While exhibiting a phenotype comparable to cmr1 and cmr2, the novel cmr3 mutation is predicted to be based on a distinctly different molecular mechanism. So far cmr2 and cmr3 are exclusive to a single dog breed each. In contrast, cmr1 is found in multiple related breeds. Additional sequence alterations identified in exon 10 of cBEST1 in other breeds exhibit potential disease-causing features. The inherent genetic and phenotypic variation observed with retinal disorders in canines is complicated further by cmr3 being one of four distinct genetic retinal traits found to segregate in LH. Thus, a combination of phenotypic, molecular, and population analysis is required to establish a strong phenotype–genotype association. These results indicate that cmr has a larger impact on the general dog population than was initially suspected. The complexity of these models further confirms the similarity to human bestrophinopathies. Moreover, analyses of multiple canine models will provide additional insight into the molecular basis underlying diseases caused by mutations in BEST1. PMID:21197113

Co-clustering phenome–genome for phenotype classification and disease gene discovery

PubMed Central

Hwang, TaeHyun; Atluri, Gowtham; Xie, MaoQiang; Dey, Sanjoy; Hong, Changjin; Kumar, Vipin; Kuang, Rui

2012-01-01

Understanding the categorization of human diseases is critical for reliably identifying disease causal genes. Recently, genome-wide studies of abnormal chromosomal locations related to diseases have mapped >2000 phenotype–gene relations, which provide valuable information for classifying diseases and identifying candidate genes as drug targets. In this article, a regularized non-negative matrix tri-factorization (R-NMTF) algorithm is introduced to co-cluster phenotypes and genes, and simultaneously detect associations between the detected phenotype clusters and gene clusters. The R-NMTF algorithm factorizes the phenotype–gene association matrix under the prior knowledge from phenotype similarity network and protein–protein interaction network, supervised by the label information from known disease classes and biological pathways. In the experiments on disease phenotype–gene associations in OMIM and KEGG disease pathways, R-NMTF significantly improved the classification of disease phenotypes and disease pathway genes compared with support vector machines and Label Propagation in cross-validation on the annotated phenotypes and genes. The newly predicted phenotypes in each disease class are highly consistent with human phenotype ontology annotations. The roles of the new member genes in the disease pathways are examined and validated in the protein–protein interaction subnetworks. Extensive literature review also confirmed many new members of the disease classes and pathways as well as the predicted associations between disease phenotype classes and pathways. PMID:22735708

Molecular and cellular alterations in Down syndrome: toward the identification of targets for therapeutics.

PubMed

Créau, Nicole

2012-01-01

Down syndrome is a complex disease that has challenged molecular and cellular research for more than 50 years. Understanding the molecular bases of morphological, cellular, and functional alterations resulting from the presence of an additional complete chromosome 21 would aid in targeting specific genes and pathways for rescuing some phenotypes. Recently, progress has been made by characterization of brain alterations in mouse models of Down syndrome. This review will highlight the main molecular and cellular findings recently described for these models, particularly with respect to their relationship to Down syndrome phenotypes.

Phenotype variability and allelic heterogeneity in KMT2B-Associated disease.

PubMed

Kawarai, Toshitaka; Miyamoto, Ryosuke; Nakagawa, Eiji; Koichihara, Reiko; Sakamoto, Takashi; Mure, Hideo; Morigaki, Ryoma; Koizumi, Hidetaka; Oki, Ryosuke; Montecchiani, Celeste; Caltagirone, Carlo; Orlacchio, Antonio; Hattori, Ayako; Mashimo, Hideaki; Izumi, Yuishin; Mezaki, Takahiro; Kumada, Satoko; Taniguchi, Makoto; Yokochi, Fusako; Saitoh, Shinji; Goto, Satoshi; Kaji, Ryuji

2018-04-05

Mutations in Lysine-Specific Histone Methyltransferase 2B gene (KMT2B) have been reported to be associated with complex early-onset dystonia. Almost all reported KMT2B mutations occurred de novo in the paternal germline or in the early development of the patient. We describe clinico-genetic features on four Japanese patients with novel de novo mutations and demonstrate the phenotypic spectrum of KMT2B mutations. We performed genetic studies, including trio-based whole exome sequencing (WES), in a cohort of Japanese patients with a seemingly sporadic early-onset generalized combined dystonia. Potential effects by the identified nucleotide variations were evaluated biologically. Genotype-phenotype correlations were also investigated. Four patients had de novo heterozygous mutations in KMT2B, c.309delG, c.1656dupC, c.3325_3326insC, and c.5636delG. Biological analysis of KMT2B mRNA levels showed a reduced expression of mutant transcript frame. All patients presented with motor milestone delay, microcephaly, mild psychomotor impairment, childhood-onset generalized dystonia and superimposed choreoathetosis or myoclonus. One patient cannot stand due to axial hypotonia associated with cerebellar dysfunction. Three patients had bilateral globus pallidal deep brain stimulation (DBS) with excellent or partial response. We further demonstrate the allelic heterogeneity and phenotypic variations of KMT2B-associated disease. Haploinsufficiency is one of molecular pathomechanisms underlying the disease. Cardinal clinical features include combined dystonia accompanying mild psychomotor disability. Cerebellum would be affected in KMT2B-associated disease. Copyright © 2018 Elsevier Ltd. All rights reserved.

An in vivo multiplexed small molecule screening platform

PubMed Central

Yang, Dian; Ogasawara, Daisuke; Dix, Melissa M.; Rogers, Zoë N.; Chuang, Chen-Hua; McFarland, Christopher D.; Chiou, Shin-Heng; Brown, J. Mark; Cravatt, Benjamin F.; Bogyo, Matthew; Winslow, Monte M.

2016-01-01

Phenotype-based small molecule screening is a powerful method to identify regulators of cellular function. However, such screens are generally performed in vitro using conditions that do not necessarily model complex physiological conditions or disease states. Here, we use molecular cell barcoding to enable direct in vivo phenotypic screening of libraries of small molecules. The multiplexed nature of this approach allows rapid in vivo analysis of hundreds to thousands of compounds. Using this platform, we screened >700 covalent inhibitors directed towards hydrolases for their effect on pancreatic cancer metastatic seeding. We identified multiple hits and confirmed the relevant target of one compound as the lipase ABHD6. Pharmacological and genetic studies confirmed the role of this enzyme as a regulator of metastatic fitness. Our results highlight the applicability of this multiplexed screening platform for investigating complex processes in vivo. PMID:27617390

Sports genetics moving forward: lessons learned from medical research.

PubMed

Mattsson, C Mikael; Wheeler, Matthew T; Waggott, Daryl; Caleshu, Colleen; Ashley, Euan A

2016-03-01

Sports genetics can take advantage of lessons learned from human disease genetics. By righting past mistakes and increasing scientific rigor, we can magnify the breadth and depth of knowledge in the field. We present an outline of challenges facing sports genetics in the light of experiences from medical research. Sports performance is complex, resulting from a combination of a wide variety of different traits and attributes. Improving sports genetics will foremost require analyses based on detailed phenotyping. To find widely valid, reproducible common variants associated with athletic phenotypes, study sample sizes must be dramatically increased. One paradox is that in order to confirm relevance, replications in specific populations must be undertaken. Family studies of athletes may facilitate the discovery of rare variants with large effects on athletic phenotypes. The complexity of the human genome, combined with the complexity of athletic phenotypes, will require additional metadata and biological validation to identify a comprehensive set of genes involved. Analysis of personal genetic and multiomic profiles contribute to our conceptualization of precision medicine; the same will be the case in precision sports science. In the refinement of sports genetics it is essential to evaluate similarities and differences between sexes and among ethnicities. Sports genetics to date have been hampered by small sample sizes and biased methodology, which can lead to erroneous associations and overestimation of effect sizes. Consequently, currently available genetic tests based on these inherently limited data cannot predict athletic performance with any accuracy. Copyright © 2016 the American Physiological Society.

[Genotype/phenotype correlation in autism: genetic models and phenotypic characterization].

PubMed

Bonnet-Brilhault, F

2011-02-01

Autism spectrum disorders are a class of conditions categorized by communication problems, ritualistic behaviors, and deficits in social behaviors. This class of disorders merges a heterogeneous group of neurodevelopmental disorders regarding some phenotypic and probably physiopathological aspects. Genetic basis is well admitted, however, considering phenotypic and genotypic heterogeneity, correspondences between genotype and phenotype have yet to be established. To better identify such correspondences, genetic models have to be identified and phenotypic markers have to be characterized. Recent insights show that a variety of genetic mechanisms may be involved in autism spectrum disorders, i.e. single gene disorders, copy number variations and polygenic mechanisms. These current genetic models are described. Regarding clinical aspects, several approaches can be used in genetic studies. Nosographical approach, especially with the concept of autism spectrum disorders, merges a large group of disorders with clinical heterogeneity and may fail to identify clear genotype/phenotype correlations. Dimensional approach referred in genetic studies to the notion of "Broad Autism Phenotype" related to a constellation of language, personality, and social-behavioral features present in relatives that mirror the symptom domains of autism, but are much milder in expression. Studies of this broad autism phenotype may provide a potentially important complementary approach for detecting the genes involved in these domains. However, control population used in those studies need to be well characterized too. Identification of endophenotypes seems to offer more promising results. Endophenotypes, which are supposed to be more proximal markers of gene action in the same biological pathway, linking genes and complex clinical symptoms, are thought to be less genetically complex than the broader disease phenotype, indexing a limited aspect of genetic risk for the disorder as a whole. However, strategies useful to characterize such phenotypic markers (for example, electrophysiological markers) have to take into account that autism is an early neurodevelopmental disorder occurring during childhood when brain development and maturation are in process. Recent genetic results have improved our knowledge in genetic basis in autism. Nevertheless, correspondences with phenotypic markers remain challenging according to phenotypic and genotypic heterogeneity. Copyright © 2010 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

What do mouse models of muscular dystrophy tell us about the DAPC and its components?

PubMed

Whitmore, Charlotte; Morgan, Jennifer

2014-12-01

There are over 30 mouse models with mutations or inactivations in the dystrophin-associated protein complex. This complex is thought to play a crucial role in the functioning of muscle, as both a shock absorber and signalling centre, although its role in the pathogenesis of muscular dystrophy is not fully understood. The first mouse model of muscular dystrophy to be identified with a mutation in a component of the dystrophin-associated complex (dystrophin) was the mdx mouse in 1984. Here, we evaluate the key characteristics of the mdx in comparison with other mouse mutants with inactivations in DAPC components, along with key modifiers of the disease phenotype. By discussing the differences between the individual phenotypes, we show that the functioning of the DAPC and consequently its role in the pathogenesis is more complicated than perhaps currently appreciated. © 2014 The Authors. International Journal of Experimental Pathology © 2014 International Journal of Experimental Pathology.

GPT2 mutations cause developmental encephalopathy with microcephaly and features of complicated hereditary spastic paraplegia.

PubMed

Hengel, H; Keimer, R; Deigendesch, W; Rieß, A; Marzouqa, H; Zaidan, J; Bauer, P; Schöls, L

2018-06-07

Various genetic defects can cause intellectual and developmental disabilities (IDD). Often IDD is a symptom of a more complex neurodevelopmental or neurodegenerative syndrome. Identifying syndromic patterns is substantive for diagnostics and for understanding the pathomechanism of a disease. Recessive GPT2 mutations have recently been associated with IDD in four families. Here, we report a novel recessive GPT2 stop mutation p.Gln24* causing a complex IDD phenotype in a homozygous state in five patients from two consanguineous Arab families. By compiling clinical information of these individuals and previously described GPT2 patients a recognizable neurodevelopmental and potentially neurodegenerative phenotype can be assigned consisting of intellectual disability, pyramidal tract affection with spastic paraplegia, microcephaly and frequently epilepsy. Due to the consistent presence of pyramidal tract affection in GPT2 patients, we further suggest that GPT2 mutations should be considered in cases with complex hereditary spastic paraplegia. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Discovering disease-associated genes in weighted protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Stanley, H. Eugene

2018-04-01

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

Nuclear Receptor Variants in Liver Disease

PubMed Central

Müllenbach, Roman; Weber, Susanne N.; Lammert, Frank

2012-01-01

This review aims to provide a snapshot of the actual state of knowledge on genetic variants of nuclear receptors (NR) involved in regulating important aspects of liver metabolism. It recapitulates recent evidence for the application of NR in genetic diagnosis of monogenic (“Mendelian”) liver disease and their use in clinical diagnosis. Genetic analysis of multifactorial liver diseases such as viral hepatitis or fatty liver disease identifies key players in disease predisposition and progression. Evidence from these analyses points towards a role of NR polymorphisms in common diseases, linking regulatory networks to complex and variable phenotypes. The new insights into NR variants also offer perspectives and cautionary advice for their use as handles towards diagnosis and treatment. PMID:22523693

Mapping Gene Associations in Human Mitochondria using Clinical Disease Phenotypes

PubMed Central

Scharfe, Curt; Lu, Henry Horng-Shing; Neuenburg, Jutta K.; Allen, Edward A.; Li, Guan-Cheng; Klopstock, Thomas; Cowan, Tina M.; Enns, Gregory M.; Davis, Ronald W.

2009-01-01

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes. PMID:19390613

Burden of Common Complex Disease Variants in the Exomes of Two Healthy Centenarian Brothers.

PubMed

Tindale, Lauren C; Zeng, Andy; Bretherick, Karla L; Leach, Stephen; Thiessen, Nina; Brooks-Wilson, Angela R

2015-01-01

It is not understood whether long-term good health is promoted by the absence of disease risk variants, the presence of protective variants, or both. We characterized the exomes of two exceptionally healthy centenarian brothers aged 106 and 109 years who had never been diagnosed with cancer, cardiovascular disease, diabetes, Alzheimer's disease, or major pulmonary disease. The aim of this study was to gain insight into whether exceptional health and longevity are a result of carrying fewer disease-associated variants than typical individuals. We compared the number of disease-associated alleles, and the proportion of alleles predicted to be functionally damaging, between the centenarian brothers and published population data. Mitochondrial sequence reads were extracted from the exome data in order to analyze mitochondrial variants. The brothers carry a similar number of common disease-associated variants and predicted damaging variants compared to reference groups. They did not carry any high-penetrance clinically actionable variants. They carry mitochondrial haplogroup T, and one brother has a single heteroplasmic variant. Although our small sample size does not allow for definitive conclusions, a healthy aging and longevity phenotype is not necessarily due to a decreased burden of common disease-associated variants. Instead, it may be rare 'positive' variants that play a role in this desirable phenotype. © 2015 S. Karger AG, Basel.

LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems.

PubMed

Choquet, Remy; Maaroufi, Meriem; Fonjallaz, Yannick; de Carrara, Albane; Vandenbussche, Pierre-Yves; Dhombres, Ferdinand; Landais, Paul

Characterizing a rare disease diagnosis for a given patient is often made through expert's networks. It is a complex task that could evolve over time depending on the natural history of the disease and the evolution of the scientific knowledge. Most rare diseases have genetic causes and recent improvements of sequencing techniques contribute to the discovery of many new diseases every year. Diagnosis coding in the rare disease field requires data from multiple knowledge bases to be aggregated in order to offer the clinician a global information space from possible diagnosis to clinical signs (phenotypes) and known genetic mutations (genotype). Nowadays, the major barrier to the coding activity is the lack of consolidation of such information scattered in different thesaurus such as Orphanet, OMIM or HPO. The Linking Open data for Rare Diseases (LORD) web portal we developed stands as the first attempt to fill this gap by offering an integrated view of 8,400 rare diseases linked to more than 14,500 signs and 3,270 genes. The application provides a browsing feature to navigate through the relationships between diseases, signs and genes, and some Application Programming Interfaces to help its integration in health information systems in routine.

LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems

PubMed Central

Choquet, Remy; Maaroufi, Meriem; Fonjallaz, Yannick; de Carrara, Albane; Vandenbussche, Pierre-Yves; Dhombres, Ferdinand; Landais, Paul

2015-01-01

Characterizing a rare disease diagnosis for a given patient is often made through expert’s networks. It is a complex task that could evolve over time depending on the natural history of the disease and the evolution of the scientific knowledge. Most rare diseases have genetic causes and recent improvements of sequencing techniques contribute to the discovery of many new diseases every year. Diagnosis coding in the rare disease field requires data from multiple knowledge bases to be aggregated in order to offer the clinician a global information space from possible diagnosis to clinical signs (phenotypes) and known genetic mutations (genotype). Nowadays, the major barrier to the coding activity is the lack of consolidation of such information scattered in different thesaurus such as Orphanet, OMIM or HPO. The Linking Open data for Rare Diseases (LORD) web portal we developed stands as the first attempt to fill this gap by offering an integrated view of 8,400 rare diseases linked to more than 14,500 signs and 3,270 genes. The application provides a browsing feature to navigate through the relationships between diseases, signs and genes, and some Application Programming Interfaces to help its integration in health information systems in routine. PMID:26958175

Beyond disease susceptibility-Leveraging genome-wide association studies for new insights into complex disease biology.

PubMed

Lee, J C

2017-12-01

Genetic studies in complex diseases have been highly successful, but have also been largely one-dimensional: predominantly focusing on the genetic contribution to disease susceptibility. While this is undoubtedly important-indeed it is a pre-requisite for understanding the mechanisms underlying disease development-there are many other important aspects of disease biology that have received comparatively little attention. In this review, I will discuss how existing genetic data can be leveraged to provide new insights into other aspects of disease biology, why such insights could change the way we think about complex disease, and how this could provide opportunities for better therapies and/or facilitate personalised medicine. To do this, I will use the example of Crohn's disease-a chronic form of inflammatory bowel disease that has been one of the main success stories in complex disease genetics. Indeed, thanks to genetic studies, we now have a much more detailed understanding of the processes involved in Crohn's disease development, but still know relatively little about what determines the subsequent disease course (prognosis) and why this differs so considerably between individuals. I will discuss how we came to realise that genetic variation plays an important role in determining disease prognosis and how this has changed the way we think about Crohn's disease genetics. This will illustrate how phenotypic data can be used to leverage new insights from genetic data and will provide a broadly applicable framework that could yield new insights into the biology of multiple diseases. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Clinical metabolomics paves the way towards future healthcare strategies

PubMed Central

Collino, Sebastiano; Martin, François‐Pierre J.; Rezzi, Serge

2013-01-01

Metabolomics is recognized as a powerful top‐down system biological approach to understand genetic‐environment‐health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation. PMID:22348240

X chromosome regulation: diverse patterns in development, tissues and disease

PubMed Central

Deng, Xinxian; Berletch, Joel B.; Nguyen, Di K.; Disteche, Christine M.

2014-01-01

Genes on the mammalian X chromosome are present in one copy in males and two copies in females. The complex mechanisms that regulate the X chromosome lead to evolutionary and physiological variability in gene expression between species, the sexes, individuals, developmental stages, tissues and cell types. In early development, delayed and incomplete X chromosome inactivation (XCI) in some species causes variability in gene expression. Additional diversity stems from escape from XCI and from mosaicism or XCI skewing in females. This causes sex-specific differences that manifest as differential gene expression and associated phenotypes. Furthermore, the complexity and diversity of X dosage regulation affect the severity of diseases caused by X-linked mutations. PMID:24733023

Epilepsy with auditory features

PubMed Central

Licchetta, Laura; Baldassari, Sara; Palombo, Flavia; Menghi, Veronica; D'Aurizio, Romina; Leta, Chiara; Stipa, Carlotta; Boero, Giovanni; d'Orsi, Giuseppe; Magi, Alberto; Scheffer, Ingrid; Seri, Marco; Tinuper, Paolo; Bisulli, Francesca

2015-01-01

Objective: To identify novel genes implicated in epilepsy with auditory features (EAF) in phenotypically heterogeneous families with unknown molecular basis. Methods: We identified 15 probands with EAF in whom an LGI1 mutation had been excluded. We performed electroclinical phenotyping on all probands and available affected relatives. We used whole-exome sequencing (WES) in 20 individuals with EAF (including all the probands and 5 relatives) to identify single nucleotide variants, small insertions/deletions, and copy number variants. Results: WES revealed likely pathogenic variants in genes that had not been previously associated with EAF: a CNTNAP2 intragenic deletion, 2 truncating mutations of DEPDC5, and a missense SCN1A change. Conclusions: EAF is a clinically and molecularly heterogeneous disease. The association of EAF with CNTNAP2, DEPDC5, and SCN1A mutations widens the phenotypic spectrum related to these genes. CNTNAP2 encodes CASPR2, a member of the voltage-gated potassium channel complex in which LGI1 plays a role. The finding of a CNTNAP2 deletion emphasizes the importance of this complex in EAF and shows biological convergence. PMID:27066544

Development of allergic sensitization and its relevance to paediatric asthma.

PubMed

Oksel, Ceyda; Custovic, Adnan

2018-04-01

The purpose of this review is to summarize the recent evidence on the distinct atopic phenotypes and their relationship with childhood asthma. We start by considering definitions and phenotypic classification of atopy and then review evidence on its association with asthma in children. It is now well recognized that both asthma and atopy are complex entities encompassing various different sub-groups that also differ in the way they interconnect. The lack of gold standards for diagnostic markers of atopy and asthma further adds to the existing complexity over diagnostic accuracy and definitions. Although recent statistical phenotyping studies contributed significantly to our understanding of these heterogeneous disorders, translating these findings into meaningful information and effective therapies requires further work on understanding underpinning biological mechanisms. The disaggregation of allergic sensitization may help predict how the allergic disease is likely to progress. One of the important questions is how best to incorporate tests for the assessment of allergic sensitization into diagnostic algorithms for asthma, both in terms of confirming asthma diagnosis, and the assessment of future risk.

Integrated rare variant-based risk gene prioritization in disease case-control sequencing studies.

PubMed

Lin, Jhih-Rong; Zhang, Quanwei; Cai, Ying; Morrow, Bernice E; Zhang, Zhengdong D

2017-12-01

Rare variants of major effect play an important role in human complex diseases and can be discovered by sequencing-based genome-wide association studies. Here, we introduce an integrated approach that combines the rare variant association test with gene network and phenotype information to identify risk genes implicated by rare variants for human complex diseases. Our data integration method follows a 'discovery-driven' strategy without relying on prior knowledge about the disease and thus maintains the unbiased character of genome-wide association studies. Simulations reveal that our method can outperform a widely-used rare variant association test method by 2 to 3 times. In a case study of a small disease cohort, we uncovered putative risk genes and the corresponding rare variants that may act as genetic modifiers of congenital heart disease in 22q11.2 deletion syndrome patients. These variants were missed by a conventional approach that relied on the rare variant association test alone.

Mitochondrial disease associated with complex I (NADH-CoQ oxidoreductase) deficiency.

PubMed

Scheffler, Immo E

2015-05-01

Mitochondrial diseases due to a reduced capacity for oxidative phosphorylation were first identified more than 20 years ago, and their incidence is now recognized to be quite significant. In a large proportion of cases the problem can be traced to a complex I (NADH-CoQ oxidoreductase) deficiency (Phenotype MIM #252010). Because the complex consists of 44 subunits, there are many potential targets for pathogenic mutations, both on the nuclear and mitochondrial genomes. Surprisingly, however, almost half of the complex I deficiencies are due to defects in as yet unidentified genes that encode proteins other than the structural proteins of the complex. This review attempts to summarize what we know about the molecular basis of complex I deficiencies: mutations in the known structural genes, and mutations in an increasing number of genes encoding "assembly factors", that is, proteins required for the biogenesis of a functional complex I that are not found in the final complex I. More such genes must be identified before definitive genetic counselling can be applied in all cases of affected families.

Neisseria meningitidis; clones, carriage, and disease.

PubMed

Read, R C

2014-05-01

Neisseria meningitidis, the cause of meningococcal disease, has been the subject of sophisticated molecular epidemiological investigation as a consequence of the significant public health threat posed by this organism. The use of multilocus sequence typing and whole genome sequencing classifies the organism into clonal complexes. Extensive phenotypic, genotypic and epidemiological information is available on the PubMLST website. The human nasopharynx is the sole ecological niche of this species, and carrier isolates show extensive genetic diversity as compared with hyperinvasive lineages. Horizontal gene exchange and recombinant events within the meningococcal genome during residence in the human nasopharynx result in antigenic diversity even within clonal complexes, so that individual clones may express, for example, more than one capsular polysaccharide (serogroup). Successful clones are capable of wide global dissemination, and may be associated with explosive epidemics of invasive disease. © 2014 The Author Clinical Microbiology and Infection © 2014 European Society of Clinical Microbiology and Infectious Diseases.

Applications of systems approaches in the study of rheumatic diseases.

PubMed

Kim, Ki-Jo; Lee, Saseong; Kim, Wan-Uk

2015-03-01

The complex interaction of molecules within a biological system constitutes a functional module. These modules are then acted upon by both internal and external factors, such as genetic and environmental stresses, which under certain conditions can manifest as complex disease phenotypes. Recent advances in high-throughput biological analyses, in combination with improved computational methods for data enrichment, functional annotation, and network visualization, have enabled a much deeper understanding of the mechanisms underlying important biological processes by identifying functional modules that are temporally and spatially perturbed in the context of disease development. Systems biology approaches such as these have produced compelling observations that would be impossible to replicate using classical methodologies, with greater insights expected as both the technology and methods improve in the coming years. Here, we examine the use of systems biology and network analysis in the study of a wide range of rheumatic diseases to better understand the underlying molecular and clinical features.

Identification of mutations, genotype-phenotype correlation and prenatal diagnosis of maple syrup urine disease in Indian patients.

PubMed

Gupta, Deepti; Bijarnia-Mahay, Sunita; Saxena, Renu; Kohli, Sudha; Dua-Puri, Ratna; Verma, Jyotsna; Thomas, E; Shigematsu, Yosuke; Yamaguchi, Seiji; Deb, Roumi; Verma, Ishwar Chander

2015-09-01

Maple syrup urine disease (MSUD) is caused by mutations in genes BCKDHA, BCKDHB, DBT encoding E1α, E1β, and E2 subunits of enzyme complex, branched-chain alpha-ketoacid dehydrogenase (BCKDH). BCKDH participates in catabolism of branched-chain amino acids (BCAAs) - leucine, isoleucine and valine in the energy production pathway. Deficiency or defect in the enzyme complex causes accumulation of BCAAs and keto-acids leading to toxicity. Twenty-four patients with MSUD were enrolled in the study for molecular characterization and genotype-phenotype correlation. Molecular studies were carried out by sequencing of the 3 genes by Sanger method. Bioinformatics tools were employed to classify novel variations into pathogenic or benign. The predicted effects of novel changes on protein structure were elucidated by 3D modeling. Mutations were detected in 22 of 24 patients (11, 7 and 4 in BCKDHB, BCKDHA and DBT genes, respectively). Twenty mutations including 11 novel mutations were identified. Protein modeling in novel mutations showed alteration of structure and function of these subunits. Mutations, c.1065 delT (BCKDHB gene) and c.939G > C (DBT gene) were noted to be recurrent, identified in 6 of 22 alleles and 5 of 8 alleles, respectively. Two-third patients were of neonatal classical phenotype (16 of 24). BCKDHB gene mutations were present in 10 of these 16 patients. Prenatal diagnoses were performed in 4 families. Consanguinity was noted in 37.5% families. Although no obvious genotype-phenotype correlation could be found in our study, most cases with mutation in BCKDHB gene presented in neonatal period. Large number of novel mutations underlines the heterogeneity and distinctness of gene pool from India. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Linkage Analysis Using Co-Phenotypes in the BRIGHT Study Reveals Novel Potential Susceptibility Loci for Hypertension

PubMed Central

Wallace, Chris; Xue, Ming-Zhan; Newhouse, Stephen J.; Marçano, Ana Carolina B.; Onipinla, Abiodun K.; Burke, Beverley; Gungadoo, Johannie; Dobson, Richard J.; Brown, Morris; Connell, John M.; Dominiczak, Anna; Lathrop, G. Mark; Webster, John; Farrall, Martin; Mein, Charles; Samani, Nilesh J.; Caulfield, Mark J.; Clayton, David G.; Munroe, Patricia B.

2006-01-01

Identification of the genetic influences on human essential hypertension and other complex diseases has proved difficult, partly because of genetic heterogeneity. In many complex-trait resources, additional phenotypic data have been collected, allowing comorbid intermediary phenotypes to be used to characterize more genetically homogeneous subsets. The traditional approach to analyzing covariate-defined subsets has typically depended on researchers’ previous expectations for definition of a comorbid subset and leads to smaller data sets, with a concomitant attrition in power. An alternative is to test for dependence between genetic sharing and covariates across the entire data set. This approach offers the advantage of exploiting the full data set and could be widely applied to complex-trait genome scans. However, existing maximum-likelihood methods can be prohibitively computationally expensive, especially since permutation is often required to determine significance. We developed a less computationally intensive score test and applied it to biometric and biochemical covariate data, from 2,044 sibling pairs with severe hypertension, collected by the British Genetics of Hypertension (BRIGHT) study. We found genomewide-significant evidence for linkage with hypertension and several related covariates. The strongest signals were with leaner-body-mass measures on chromosome 20q (maximum LOD=4.24) and with parameters of renal function on chromosome 5p (maximum LOD=3.71). After correction for the multiple traits and genetic locations studied, our global genomewide P value was .046. This is the first identity-by-descent regression analysis of hypertension to our knowledge, and it demonstrates the value of this approach for the incorporation of additional phenotypic information in genetic studies of complex traits. PMID:16826522

Linkage analysis using co-phenotypes in the BRIGHT study reveals novel potential susceptibility loci for hypertension.

PubMed

Wallace, Chris; Xue, Ming-Zhan; Newhouse, Stephen J; Marcano, Ana Carolina B; Onipinla, Abiodun K; Burke, Beverley; Gungadoo, Johannie; Dobson, Richard J; Brown, Morris; Connell, John M; Dominiczak, Anna; Lathrop, G Mark; Webster, John; Farrall, Martin; Mein, Charles; Samani, Nilesh J; Caulfield, Mark J; Clayton, David G; Munroe, Patricia B

2006-08-01

Identification of the genetic influences on human essential hypertension and other complex diseases has proved difficult, partly because of genetic heterogeneity. In many complex-trait resources, additional phenotypic data have been collected, allowing comorbid intermediary phenotypes to be used to characterize more genetically homogeneous subsets. The traditional approach to analyzing covariate-defined subsets has typically depended on researchers' previous expectations for definition of a comorbid subset and leads to smaller data sets, with a concomitant attrition in power. An alternative is to test for dependence between genetic sharing and covariates across the entire data set. This approach offers the advantage of exploiting the full data set and could be widely applied to complex-trait genome scans. However, existing maximum-likelihood methods can be prohibitively computationally expensive, especially since permutation is often required to determine significance. We developed a less computationally intensive score test and applied it to biometric and biochemical covariate data, from 2,044 sibling pairs with severe hypertension, collected by the British Genetics of Hypertension (BRIGHT) study. We found genomewide-significant evidence for linkage with hypertension and several related covariates. The strongest signals were with leaner-body-mass measures on chromosome 20q (maximum LOD = 4.24) and with parameters of renal function on chromosome 5p (maximum LOD = 3.71). After correction for the multiple traits and genetic locations studied, our global genomewide P value was .046. This is the first identity-by-descent regression analysis of hypertension to our knowledge, and it demonstrates the value of this approach for the incorporation of additional phenotypic information in genetic studies of complex traits.

High Throughput Phenotypic Analysis of Mycobacterium tuberculosis and Mycobacterium bovis Strains' Metabolism Using Biolog Phenotype Microarrays

PubMed Central

Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R.

2013-01-01

Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the method. By looking for ≥5-fold differences in dye reduction, 12 substrates differentiated M. tuberculosis H37Rv and Mycobacterium bovis AF2122/97. H37Rv and a Beijing strain of M. tuberculosis could also be distinguished in this way, as could field strains of M. bovis; even pairs of strains within one spoligotype could be distinguished by 2 to 3 substrates. Cluster analysis gave three clear groups: H37Rv, Beijing, and all the M. bovis strains. The substrates used agreed well with prior knowledge, though an unexpected finding that AF2122/97 gave greater dye reduction than H37Rv with hexoses was investigated further, in culture flasks, revealing that hexoses and Tween 80 were synergistic for growth and used simultaneously rather than in a diauxic fashion. Potential new substrates for growth media were revealed, too, most promisingly N-acetyl glucosamine. Osmotic and pH arrays divided the mycobacteria into two groups with different salt tolerance, though in contrast to the substrate arrays the groups did not entirely correlate with taxonomic differences. More interestingly, these arrays suggested differences between the amines used by the M. tuberculosis complex and enteric bacteria in acid tolerance, with some hydrophobic amino acids being highly effective. In contrast, γ-aminobutyrate, used in the enteric bacteria, had no effect in the mycobacteria. This study proved principle that Phenotype MicroArrays can be used with slow-growing pathogenic mycobacteria and already has generated interesting data worthy of further investigation. PMID:23326347

Beyond the MHC: A canine model of dermatomyositis shows a complex pattern of genetic risk involving novel loci

PubMed Central

Evans, Jacquelyn M.; Hill, Cody M.; Anderson, Kendall J.

2017-01-01

Juvenile dermatomyositis (JDM) is a chronic inflammatory myopathy and vasculopathy driven by genetic and environmental influences. Here, we investigated the genetic underpinnings of an analogous, spontaneous disease of dogs also termed dermatomyositis (DMS). As in JDM, we observed a significant association with a haplotype of the major histocompatibility complex (MHC) (DLA-DRB1*002:01/-DQA1*009:01/-DQB1*001:01), particularly in homozygosity (P-val = 0.0001). However, the high incidence of the haplotype among healthy dogs indicated that additional genetic risk factors are likely involved in disease progression. We conducted genome-wide association studies in two modern breeds having common ancestry and detected strong associations with novel loci on canine chromosomes 10 (P-val = 2.3X10-12) and 31 (P-val = 3.95X10-8). Through whole genome resequencing, we identified primary candidate polymorphisms in conserved regions of PAN2 (encoding p.Arg492Cys) and MAP3K7CL (c.383_392ACTCCACAAA>GACT) on chromosomes 10 and 31, respectively. Analyses of these polymorphisms and the MHC haplotypes revealed that nine of 27 genotypic combinations confer high or moderate probability of disease and explain 93% of cases studied. The pattern of disease risk across PAN2 and MAP3K7CL genotypes provided clear evidence for a significant epistatic foundation for this disease, a risk further impacted by MHC haplotypes. We also observed a genotype-phenotype correlation wherein an earlier age of onset is correlated with an increased number of risk alleles at PAN2 and MAP3K7CL. High frequencies of multiple genetic risk factors are unique to affected breeds and likely arose coincident with artificial selection for desirable phenotypes. Described herein is the first three-locus association with a complex canine disease and two novel loci that provide targets for exploration in JDM and related immunological dysfunction. PMID:28158183

Phenome-Wide Association Study (PheWAS) for Detection of Pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE) Network

PubMed Central

Pendergrass, Sarah A.; Brown-Gentry, Kristin; Dudek, Scott; Frase, Alex; Torstenson, Eric S.; Goodloe, Robert; Ambite, Jose Luis; Avery, Christy L.; Buyske, Steve; Bůžková, Petra; Deelman, Ewa; Fesinmeyer, Megan D.; Haiman, Christopher A.; Heiss, Gerardo; Hindorff, Lucia A.; Hsu, Chu-Nan; Jackson, Rebecca D.; Kooperberg, Charles; Le Marchand, Loic; Lin, Yi; Matise, Tara C.; Monroe, Kristine R.; Moreland, Larry; Park, Sungshim L.; Reiner, Alex; Wallace, Robert; Wilkens, Lynn R.; Crawford, Dana C.; Ritchie, Marylyn D.

2013-01-01

Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype–phenotype associations, 26 represented phenotypes closely related to previously known genotype–phenotype associations, and 33 represented potentially novel genotype–phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits. PMID:23382687

A larval zebrafish model of bipolar disorder as a screening platform for neuro-therapeutics.

PubMed

Ellis, Lee David; Soanes, Kelly Howard

2012-08-01

Modelling neurological diseases has proven extraordinarily difficult due to the phenotypic complexity of each disorder. The zebrafish has become a useful model system with which to study abnormal neurological and behavioural activity and holds promise as a model of human disease. While most of the disease modelling using zebrafish has made use of adults, larvae hold tremendous promise for the high-throughput screening of potential therapeutics. The further development of larval disease models will strengthen their ability to contribute to the drug screening process. Here we have used zebrafish larvae to model the symptoms of bipolar disorder by treating larvae with sub-convulsive concentrations of the GABA antagonist pentylenetetrazol (PTZ). A number of therapeutics that act on different targets, in addition to those that have been used to treat bipolar disorder, were tested against this model to assess its predictive value. Carbamazepine, valproic acid, baclofen and honokiol, were found to oppose various aspects of the PTZ-induced changes in activity. Lidocaine and haloperidol exacerbated the PTZ-induced activity changes and sulpiride had no effect. By comparing the degree of phenotypic rescue with the mechanism of action of each therapeutic we have shown that the low-concentration PTZ model can produce a number of intermediate phenotypes that model symptoms of bipolar disorder, may be useful in modelling other disease states, and will help predict the efficacy of novel therapeutics. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Mining the Human Phenome using Semantic Web Technologies: A Case Study for Type 2 Diabetes

PubMed Central

Pathak, Jyotishman; Kiefer, Richard C.; Bielinski, Suzette J.; 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. 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 large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypothesis generation. 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 with Type 2 Diabetes for discovering gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries. PMID:23304343

Mining the human phenome using semantic web technologies: a case study for Type 2 Diabetes.

PubMed

Pathak, Jyotishman; Kiefer, Richard C; Bielinski, Suzette J; 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. 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 large number of subjects. This provides tremendous opportunities to discover novel genotype-phenotype associations and foster hypothesis generation. 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 with Type 2 Diabetes for discovering gene-disease associations. Our study highlights the potential of Web-scale data federation techniques to execute complex queries.

Phenotypic and genotypic data integration and exploration through a web-service architecture.

PubMed

Nuzzo, Angelo; Riva, Alberto; Bellazzi, Riccardo

2009-10-15

Linking genotypic and phenotypic information is one of the greatest challenges of current genetics research. The definition of an Information Technology infrastructure to support this kind of studies, and in particular studies aimed at the analysis of complex traits, which require the definition of multifaceted phenotypes and the integration genotypic information to discover the most prevalent diseases, is a paradigmatic goal of Biomedical Informatics. This paper describes the use of Information Technology methods and tools to develop a system for the management, inspection and integration of phenotypic and genotypic data. We present the design and architecture of the Phenotype Miner, a software system able to flexibly manage phenotypic information, and its extended functionalities to retrieve genotype information from external repositories and to relate it to phenotypic data. For this purpose we developed a module to allow customized data upload by the user and a SOAP-based communications layer to retrieve data from existing biomedical knowledge management tools. In this paper we also demonstrate the system functionality by an example application of the system in which we analyze two related genomic datasets. In this paper we show how a comprehensive, integrated and automated workbench for genotype and phenotype integration can facilitate and improve the hypothesis generation process underlying modern genetic studies.

Associations of different phenotypes of wheezing illness in early childhood with environmental variables implicated in the aetiology of asthma.

PubMed

Granell, Raquel; Sterne, Jonathan A C; Henderson, John

2012-01-01

Asthma is a complex heterogeneous disease that has increased in prevalence in many industrialised countries. However, the causes of asthma inception remain elusive. Consideration of sub-phenotypes of wheezing may reveal important clues to aetiological risk factors. Longitudinal phenotypes capturing population heterogeneity in wheezing reports from birth to 7 years were derived using latent class analysis in the Avon Longitudinal Study of Parents and Children (ALSPAC). Probability of class membership was used to examine the association between five wheezing phenotypes (transient early, prolonged early, intermediate-onset, late-onset, persistent) and early life risk factors for asthma. Phenotypes had similar patterns and strengths of associations with early environmental factors. Comparing transient early with prolonged early wheezing showed a similar pattern of association with most exposure variables considered in terms of the direction of the effect estimates but with prolonged early wheezing tending to have stronger associations than transient early wheezing except for parity and day care attendance. Associations with early life risk factors suggested that prolonged early wheeze might be a severe form of transient early wheezing. Although differences were found in the associations of early life risk factors with individual phenotypes, these did not point to novel aetiological pathways. Persistent wheezing phenotype has features suggesting overlap of early and late-onset phenotypes.

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

PubMed

Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

2016-06-20

A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field. Copyright © 2015 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

Autoimmune encephalitis associated with voltage-gated potassium channels-complex and leucine-rich glioma-inactivated 1 antibodies - a national cohort study.

PubMed

Celicanin, M; Blaabjerg, M; Maersk-Moller, C; Beniczky, S; Marner, L; Thomsen, C; Bach, F W; Kondziella, D; Andersen, H; Somnier, F; Illes, Z; Pinborg, L H

2017-08-01

The aim of this study was to describe clinical and paraclinical characteristics of all Danish patients who tested positive for anti-voltage-gated potassium channels (VGKC)-complex, anti-leucine-rich glioma-inactivated 1 (LGI1) and anti-contactin-associated protein-2 antibodies in the serum/cerebrospinal fluid between 2009 and 2013 with follow-up interviews in 2015 and 2016. We evaluated antibody status, symptoms leading to testing, course of disease, suspected diagnosis and time of admission as well as diagnosis and treatment. All magnetic resonance imaging, electroencephalography and 18 F-fluorodeoxyglucose positron emission tomography scans were re-evaluated by experts in the field. A total of 28/192 patients tested positive for VGKC-complex antibodies by radioimmunoassay and indirect immunofluorescence; 17 had antibodies to LGI1 and 6/7 of the available cerebrospinal fluids from these patients were seropositive. These 17 patients all had a clinical phenotype appropriate to LGI1 antibodies. The remaining 11 were LGI1 negative (n = 4) or not tested (n = 7). Of these, two had a phenotype consistent with limbic encephalitis. The remaining phenotypes were Guillain-Barré syndrome, Creutzfeldt-Jakob disease, neuromyotonia and anti-N-methyl-D-aspartate receptor encephalitis. Magnetic resonance imaging abnormalities were demonstrated in 69% of the LGI1-positive patients. Two patients with normal magnetic resonance imaging demonstrated temporal lobe hypermetabolism using 18 F-fluorodeoxyglucose positron emission tomography. Abnormal electroencephalography recordings were found in 86% of the patients. Upon follow-up (median 3.2 years), the median modified Rankin Scale score of anti-LGI1-positive patients was 2 and only two patients reported seizures in the past year. Patients diagnosed with anti-LGI1 autoimmune encephalitis increased significantly from 2009 to 2014, probably due to increased awareness. In contrast to seropositive anti-VGKC-complex patients, all anti-LGI1-positive patients presented with a classical limbic encephalitis. The majority of patients recovered well. © 2017 EAN.

A rolling phenotype in Crohn's disease.

PubMed

Irwin, James; Ferguson, Emma; Simms, Lisa A; Hanigan, Katherine; Carbonnel, Franck; Radford-Smith, Graham

2017-01-01

The Montreal classification of disease behaviour in Crohn's disease describes progression of disease towards a stricturing and penetrating phenotype. In the present paper, we propose an alternative representation of the long-term course of Crohn's disease complications, the rolling phenotype. As is commonly observed in clinical practice, this definition allows progression to a more severe phenotype (stricturing, penetrating) but also, regression to a less severe behaviour (inflammatory, or remission) over time. All patients diagnosed with Crohn's Disease between 01/01/1994 and 01/03/2008, managed at a single centre and observed for a minimum of 5 years, had development and resolution of all complications recorded. A rolling phenotype was defined at each time point based on all observed complications in the three years prior to the time point. Phenotype was defined as B1, B2, B3, or B23 (penetrating and stenotic). The progression over time of the rolling phenotype was compared to that of the cumulative Montreal phenotype. 305 patients were observed a median of 10.0 (Intraquartile range 7.3-13.7) years. Longitudinal progression of rolling phenotype demonstrated a consistent proportion of patients with B1 (70%), B2 (20%), B3 (5%) and B23 (5%) phenotypes. These proportions were observed regardless of initial phenotype. In contrast, the cumulative Montreal phenotype progressed towards a more severe phenotype with time (B1 (39%), B2 (26%), B3(35%) at 10 years). A rolling phenotype provides an alternative view of the longitudinal burden of intra-abdominal complications in Crohn's disease. From this viewpoint, 70% of patients have durable freedom from complication over time (>3 years).

ViSEN: methodology and software for visualization of statistical epistasis networks

PubMed Central

Hu, Ting; Chen, Yuanzhu; Kiralis, Jeff W.; Moore, Jason H.

2013-01-01

The non-linear interaction effect among multiple genetic factors, i.e. epistasis, has been recognized as a key component in understanding the underlying genetic basis of complex human diseases and phenotypic traits. Due to the statistical and computational complexity, most epistasis studies are limited to interactions with an order of two. We developed ViSEN to analyze and visualize epistatic interactions of both two-way and three-way. ViSEN not only identifies strong interactions among pairs or trios of genetic attributes, but also provides a global interaction map that shows neighborhood and clustering structures. This visualized information could be very helpful to infer the underlying genetic architecture of complex diseases and to generate plausible hypotheses for further biological validations. ViSEN is implemented in Java and freely available at https://sourceforge.net/projects/visen/. PMID:23468157

Adaptive Immunity to Cryptococcus neoformans Infections

PubMed Central

Mukaremera, Liliane; Nielsen, Kirsten

2017-01-01

The Cryptococcus neoformans/Cryptococcus gattii species complex is a group of fungal pathogens with different phenotypic and genotypic diversity that cause disease in immunocompromised patients as well as in healthy individuals. The immune response resulting from the interaction between Cryptococcus and the host immune system is a key determinant of the disease outcome. The species C. neoformans causes the majority of human infections, and therefore almost all immunological studies focused on C. neoformans infections. Thus, this review presents current understanding on the role of adaptive immunity during C. neoformans infections both in humans and in animal models of disease. PMID:29333430

Surgical management of Crohn's colitis.

PubMed

Moir, Christopher R

2007-08-01

Crohn's disease in childhood is changing. The incidence is increasing, colonic disease is becoming more prevalent in younger children, and colon reconstruction is more acceptable. Genetic phenotypes are influencing decisions for surgery, and targeted immunotherapy has renewed hope for more durable remissions following less extensive resections. The tasks facing the surgeon evaluating a child with Crohn's colitis include confirming the specific diagnostic subtype and selecting the correct procedure. This chapter will review the unique aspects of pediatric Crohn's colitis and the increased complexity of surgical choice for this most challenging presentation. Recent success with less extensive surgery offers renewed hope for children with intractable colonic disease.

Microparticles in the blood of patients with systemic lupus erythematosus (SLE): phenotypic characterization and clinical associations

PubMed Central

Mobarrez, Fariborz; Vikerfors, Anna; Gustafsson, Johanna T.; Gunnarsson, Iva; Zickert, Agneta; Larsson, Anders; Pisetsky, David S.; Wallén, Håkan; Svenungsson, Elisabet

2016-01-01

Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease characterized by circulating autoantibodies and the formation of immune complexes. In these responses, the selecting self-antigens likely derive from the remains of dead and dying cells, as well as from disturbances in clearance. During cell death/activation, microparticles (MPs) can be released to the circulation. Previous MP studies in SLE have been limited in size and differ regarding numbers and phenotypes. Therefore, to characterize MPs more completely, we investigated 280 SLE patients and 280 individually matched controls. MPs were measured with flow cytometry and phenotyped according to phosphatidylserine expression (PS+/PS−), cellular origin and inflammatory markers. MPs, regardless of phenotype, are 2–10 times more abundant in SLE blood compared to controls. PS− MPs predominated in SLE, but not in controls (66% vs. 42%). Selectively in SLE, PS− MPs were more numerous in females and smokers. MP numbers decreased with declining renal function, but no clear association with disease activity was observed. The striking abundance of MPs, especially PS− MPs, suggests a generalized disturbance in SLE. MPs may be regarded as “liquid biopsies” to assess the production and clearance of dead, dying and activated cells, i.e. pivotal events for SLE pathogenesis. PMID:27777414

Melanocortin-1 receptor, skin cancer and phenotypic characteristics (M-SKIP) project: study design and methods for pooling results of genetic epidemiological studies

PubMed Central

2012-01-01

Background For complex diseases like cancer, pooled-analysis of individual data represents a powerful tool to investigate the joint contribution of genetic, phenotypic and environmental factors to the development of a disease. Pooled-analysis of epidemiological studies has many advantages over meta-analysis, and preliminary results may be obtained faster and with lower costs than with prospective consortia. Design and methods Based on our experience with the study design of the Melanocortin-1 receptor (MC1R) gene, SKin cancer and Phenotypic characteristics (M-SKIP) project, we describe the most important steps in planning and conducting a pooled-analysis of genetic epidemiological studies. We then present the statistical analysis plan that we are going to apply, giving particular attention to methods of analysis recently proposed to account for between-study heterogeneity and to explore the joint contribution of genetic, phenotypic and environmental factors in the development of a disease. Within the M-SKIP project, data on 10,959 skin cancer cases and 14,785 controls from 31 international investigators were checked for quality and recoded for standardization. We first proposed to fit the aggregated data with random-effects logistic regression models. However, for the M-SKIP project, a two-stage analysis will be preferred to overcome the problem regarding the availability of different study covariates. The joint contribution of MC1R variants and phenotypic characteristics to skin cancer development will be studied via logic regression modeling. Discussion Methodological guidelines to correctly design and conduct pooled-analyses are needed to facilitate application of such methods, thus providing a better summary of the actual findings on specific fields. PMID:22862891

Prediction of Human Phenotype Ontology terms by means of hierarchical ensemble methods.

PubMed

Notaro, Marco; Schubach, Max; Robinson, Peter N; Valentini, Giorgio

2017-10-12

The prediction of human gene-abnormal phenotype associations is a fundamental step toward the discovery of novel genes associated with human disorders, especially when no genes are known to be associated with a specific disease. In this context the Human Phenotype Ontology (HPO) provides a standard categorization of the abnormalities associated with human diseases. While the problem of the prediction of gene-disease associations has been widely investigated, the related problem of gene-phenotypic feature (i.e., HPO term) associations has been largely overlooked, even if for most human genes no HPO term associations are known and despite the increasing application of the HPO to relevant medical problems. Moreover most of the methods proposed in literature are not able to capture the hierarchical relationships between HPO terms, thus resulting in inconsistent and relatively inaccurate predictions. We present two hierarchical ensemble methods that we formally prove to provide biologically consistent predictions according to the hierarchical structure of the HPO. The modular structure of the proposed methods, that consists in a "flat" learning first step and a hierarchical combination of the predictions in the second step, allows the predictions of virtually any flat learning method to be enhanced. The experimental results show that hierarchical ensemble methods are able to predict novel associations between genes and abnormal phenotypes with results that are competitive with state-of-the-art algorithms and with a significant reduction of the computational complexity. Hierarchical ensembles are efficient computational methods that guarantee biologically meaningful predictions that obey the true path rule, and can be used as a tool to improve and make consistent the HPO terms predictions starting from virtually any flat learning method. The implementation of the proposed methods is available as an R package from the CRAN repository.

Next Generation Analytic Tools for Large Scale Genetic Epidemiology Studies of Complex Diseases

PubMed Central

Mechanic, Leah E.; Chen, Huann-Sheng; Amos, Christopher I.; Chatterjee, Nilanjan; Cox, Nancy J.; Divi, Rao L.; Fan, Ruzong; Harris, Emily L.; Jacobs, Kevin; Kraft, Peter; Leal, Suzanne M.; McAllister, Kimberly; Moore, Jason H.; Paltoo, Dina N.; Province, Michael A.; Ramos, Erin M.; Ritchie, Marylyn D.; Roeder, Kathryn; Schaid, Daniel J.; Stephens, Matthew; Thomas, Duncan C.; Weinberg, Clarice R.; Witte, John S.; Zhang, Shunpu; Zöllner, Sebastian; Feuer, Eric J.; Gillanders, Elizabeth M.

2012-01-01

Over the past several years, genome-wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large-Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large-scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene-gene and gene-environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized. PMID:22147673

Mutant NDUFS3 subunit of mitochondrial complex I causes Leigh syndrome.

PubMed

Bénit, P; Slama, A; Cartault, F; Giurgea, I; Chretien, D; Lebon, S; Marsac, C; Munnich, A; Rötig, A; Rustin, P

2004-01-01

Respiratory chain complex I deficiency represents a genetically heterogeneous group of diseases resulting from mutations in mitochondrial or nuclear genes. Mutations have been reported in 13 of the 14 subunits encoding the core of complex I (seven mitochondrial and six nuclear genes) and these result in Leigh or Leigh-like syndromes or cardiomyopathy. In this study, a combination of denaturing high performance liquid chromatography and sequence analysis was used to study the NDUFS3 gene in a series of complex I deficient patients. Mutations found in this gene (NADH dehydrogenase iron-sulphur protein 3), coding for the seventh and last subunit of complex I core, were shown to cause late onset Leigh syndrome, optic atrophy, and complex I deficiency. A biochemical diagnosis of complex I deficiency on cultured amniocytes from a later pregnancy was confirmed through the identification of disease causing NDUFS3 mutations in these cells. While mutations in the NDUFS3 gene thus result in Leigh syndrome, a dissimilar clinical phenotype is observed in mutations in the NDUFV2 and NDUFS2 genes, resulting in encephalomyopathy and cardiomyopathy. The reasons for these differences are uncertain.

Corruption of the intra-gene DNA methylation architecture is a hallmark of cancer.

PubMed

Bartlett, Thomas E; Zaikin, Alexey; Olhede, Sofia C; West, James; Teschendorff, Andrew E; Widschwendter, Martin

2013-01-01

Epigenetic processes--including DNA methylation--are increasingly seen as having a fundamental role in chronic diseases like cancer. It is well known that methylation levels at particular genes or loci differ between normal and diseased tissue. Here we investigate whether the intra-gene methylation architecture is corrupted in cancer and whether the variability of levels of methylation of individual CpGs within a defined gene is able to discriminate cancerous from normal tissue, and is associated with heterogeneous tumour phenotype, as defined by gene expression. We analysed 270985 CpGs annotated to 18272 genes, in 3284 cancerous and 681 normal samples, corresponding to 14 different cancer types. In doing so, we found novel differences in intra-gene methylation pattern across phenotypes, particularly in those genes which are crucial for stem cell biology; our measures of intra-gene methylation architecture are a better determinant of phenotype than measures based on mean methylation level alone (K-S test [Formula: see text] in all 14 diseases tested). These per-gene methylation measures also represent a considerable reduction in complexity, compared to conventional per-CpG beta-values. Our findings strongly support the view that intra-gene methylation architecture has great clinical potential for the development of DNA-based cancer biomarkers.

A high-content platform to characterise human induced pluripotent stem cell lines.

PubMed

Leha, Andreas; Moens, Nathalie; Meleckyte, Ruta; Culley, Oliver J; Gervasio, Mia K; Kerz, Maximilian; Reimer, Andreas; Cain, Stuart A; Streeter, Ian; Folarin, Amos; Stegle, Oliver; Kielty, Cay M; Durbin, Richard; Watt, Fiona M; Danovi, Davide

2016-03-01

Induced pluripotent stem cells (iPSCs) provide invaluable opportunities for future cell therapies as well as for studying human development, modelling diseases and discovering therapeutics. In order to realise the potential of iPSCs, it is crucial to comprehensively characterise cells generated from large cohorts of healthy and diseased individuals. The human iPSC initiative (HipSci) is assessing a large panel of cell lines to define cell phenotypes, dissect inter- and intra-line and donor variability and identify its key determinant components. Here we report the establishment of a high-content platform for phenotypic analysis of human iPSC lines. In the described assay, cells are dissociated and seeded as single cells onto 96-well plates coated with fibronectin at three different concentrations. This method allows assessment of cell number, proliferation, morphology and intercellular adhesion. Altogether, our strategy delivers robust quantification of phenotypic diversity within complex cell populations facilitating future identification of the genetic, biological and technical determinants of variance. Approaches such as the one described can be used to benchmark iPSCs from multiple donors and create novel platforms that can readily be tailored for disease modelling and drug discovery. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Neurogenetic disorders in the Basque population.

PubMed

Martí Massó, José Félix; Zarranz, Juan José; Otaegui, David; López de Munain, Adolfo

2015-01-01

In the molecular era, the study of neurogenetic disorders in relict populations provides an opportunity to discover new genes by linkage studies and to establish clearer genotype-phenotype correlations in large cohorts of individuals carrying the same mutation. The Basque people are one of the most ancient populations living in Europe and represent an excellent resource for this type of analysis in certain genetic conditions. Our objective was to describe neurogenetic disorders reported in the Basque population due to the presence of ancestral mutations or an accumulation of cases or both. We conducted a search in PubMed with the terms: Basque, neurogenetic disorders, genetic risk, and neurological disorders. We identified nine autosomal and two recessive disorders in the Basque population attributable to ancestral mutations (such as in PNRP, PARK8, FTDP-TDP43, LGMD2A, VCP, c9ORF72, and CMT4A), highly prevalent (DM1) or involving unique mutations (PARK1 or MAPT). Other genes were reported for their role as protective/risk factors in complex diseases such as multiple sclerosis, Alzheimer's disease, and Parkinson's disease. At the present time, when powerful sequencing techniques are identifying large numbers of genetic variants associated with unique phenotypes, the scrutiny of these findings in genetically homogeneous populations can help analyze genotype-phenotype correlations. © 2014 John Wiley & Sons Ltd/University College London.

Concise Review: Cardiac Disease Modeling Using Induced Pluripotent Stem Cells.

PubMed

Yang, Chunbo; Al-Aama, Jumana; Stojkovic, Miodrag; Keavney, Bernard; Trafford, Andrew; Lako, Majlinda; Armstrong, Lyle

2015-09-01

Genetic cardiac diseases are major causes of morbidity and mortality. Although animal models have been created to provide some useful insights into the pathogenesis of genetic cardiac diseases, the significant species differences and the lack of genetic information for complex genetic diseases markedly attenuate the application values of such data. Generation of induced pluripotent stem cells (iPSCs) from patient-specific specimens and subsequent derivation of cardiomyocytes offer novel avenues to study the mechanisms underlying cardiac diseases, to identify new causative genes, and to provide insights into the disease aetiology. In recent years, the list of human iPSC-based models for genetic cardiac diseases has been expanding rapidly, although there are still remaining concerns on the level of functionality of iPSC-derived cardiomyocytes and their ability to be used for modeling complex cardiac diseases in adults. This review focuses on the development of cardiomyocyte induction from pluripotent stem cells, the recent progress in heart disease modeling using iPSC-derived cardiomyocytes, and the challenges associated with understanding complex genetic diseases. To address these issues, we examine the similarity between iPSC-derived cardiomyocytes and their ex vivo counterparts and how this relates to the method used to differentiate the pluripotent stem cells into a cardiomyocyte phenotype. We progress to examine categories of congenital cardiac abnormalities that are suitable for iPSC-based disease modeling. © AlphaMed Press.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits.

PubMed

Yadav, Anupama; Dhole, Kaustubh; Sinha, Himanshu

2016-12-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets.

Differential Regulation of Cryptic Genetic Variation Shapes the Genetic Interactome Underlying Complex Traits

PubMed Central

Yadav, Anupama; Dhole, Kaustubh

2016-01-01

Cryptic genetic variation (CGV) refers to genetic variants whose effects are buffered in most conditions but manifest phenotypically upon specific genetic and environmental perturbations. Despite having a central role in adaptation, contribution of CGV to regulation of quantitative traits is unclear. Instead, a relatively simplistic architecture of additive genetic loci is known to regulate phenotypic variation in most traits. In this paper, we investigate the regulation of CGV and its implication on the genetic architecture of quantitative traits at a genome-wide level. We use a previously published dataset of biparental recombinant population of Saccharomyces cerevisiae phenotyped in 34 diverse environments to perform single locus, two-locus, and covariance mapping. We identify loci that have independent additive effects as well as those which regulate the phenotypic manifestation of other genetic variants (variance QTL). We find that whereas additive genetic variance is predominant, a higher order genetic interaction network regulates variation in certain environments. Despite containing pleiotropic loci, with effects across environments, these genetic networks are highly environment specific. CGV is buffered under most allelic combinations of these networks and perturbed only in rare combinations resulting in high phenotypic variance. The presence of such environment specific genetic networks is the underlying cause of abundant gene–environment interactions. We demonstrate that overlaying identified molecular networks on such genetic networks can identify potential candidate genes and underlying mechanisms regulating phenotypic variation. Such an integrated approach applied to human disease datasets has the potential to improve the ability to predict disease predisposition and identify specific therapeutic targets. PMID:28172852

Identification of clinical target areas in the brainstem of prion‐infected mice

PubMed Central

Mirabile, Ilaria; Jat, Parmjit S.; Brandner, Sebastian

2015-01-01

Aims While prion infection ultimately involves the entire brain, it has long been thought that the abrupt clinical onset and rapid neurological decline in laboratory rodents relates to involvement of specific critical neuroanatomical target areas. The severity and type of clinical signs, together with the rapid progression, suggest the brainstem as a candidate location for such critical areas. In this study we aimed to correlate prion pathology with clinical phenotype in order to identify clinical target areas. Method We conducted a comprehensive survey of brainstem pathology in mice infected with two distinct prion strains, which produce different patterns of pathology, in mice overexpressing prion protein (with accelerated clinical onset) and in mice in which neuronal expression was reduced by gene targeting (which greatly delays clinical onset). Results We identified specific brainstem areas that are affected by prion pathology during the progression of the disease. In the early phase of disease the locus coeruleus, the nucleus of the solitary tract, and the pre‐Bötzinger complex were affected by prion protein deposition. This was followed by involvement of the motor and autonomic centres of the brainstem. Conclusions Neurodegeneration in the locus coeruleus, the nucleus of the solitary tract and the pre‐Bötzinger complex predominated and corresponded to the manifestation of the clinical phenotype. Because of their fundamental role in controlling autonomic function and the overlap with clinical signs in sporadic Creutzfeldt–Jakob disease, we suggest that these nuclei represent key clinical target areas in prion diseases. PMID:25311251

A unified genetic association test robust to latent population structure for a count phenotype.

PubMed

Song, Minsun

2018-06-04

Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure. Copyright © 2018 John Wiley & Sons, Ltd.

Analysis of the quantitative dermatoglyphics of the digito-palmar complex in patients with multiple sclerosis.

PubMed

Supe, S; Milicić, J; Pavićević, R

1997-06-01

Recent studies on the etiopathogenesis of multiple sclerosis (MS) all point out that there is a polygenetical predisposition for this illness. The so called "MS Trait" determines the reactivity of the immunological system upon ecological factors. The development of the glyphological science and the study of the characteristics of the digito-palmar dermatoglyphic complex (for which it was established that they are polygenetically determined characteristics) all enable a better insight into the genetic development during early embriogenesis. The aim of this study was to estimate certain differences in the dermatoglyphics of digito-palmar complexes between the group with multiple sclerosis and the comparable, phenotypically healthy groups of both sexes. This study is based on the analysis of 18 quantitative characteristics of the digito-palmar complex in 125 patients with multiple sclerosis (41 males and 84 females) in comparison to a group of 400 phenotypically healthy patients (200 males and 200 females). The conducted analysis pointed towards a statistically significant decrease of the number of digital and palmar ridges, as well as with lower values of atd angles in a group of MS patients of both sexes. The main discriminators were the characteristic palmar dermatoglyphics with the possibility that the discriminate analysis classifies over 80% of the examinees which exceeds the statistical significance. The results of this study suggest a possible discrimination of patients with MS and the phenotypically health population through the analysis of the dermatoglyphic status, and therefore the possibility that multiple sclerosis is genetically predisposed disease.

Mutations in mitochondrial complex I assembly factor NDUFAF3 cause Leigh syndrome.

PubMed

Baertling, Fabian; Sánchez-Caballero, Laura; Timal, Sharita; van den Brand, Mariël Am; Ngu, Lock Hock; Distelmaier, Felix; Rodenburg, Richard Jt; Nijtmans, Leo Gj

2017-03-01

NDUFAF3 is an assembly factor of mitochondrial respiratory chain complex I. Variants in NDUFAF3 have been identified as a cause of severe multisystem mitochondrial disease. In a patient presenting with Leigh syndrome, which has hitherto not been described as a clinical feature of NDUFAF3 deficiency, we identified a novel homozygous variant and confirmed its pathogenicity in patient fibroblasts studies. Furthermore, we present an analysis of complex I assembly routes representative of each functional module and, thereby, link NDUFAF3 to a specific step in complex I assembly. Therefore, our report expands the phenotype of NDUFAF3 deficiency and further characterizes the role of NDUFAF3 in complex I biogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

Non-coding variants contribute to the clinical heterogeneity of TTR amyloidosis.

PubMed

Iorio, Andrea; De Lillo, Antonella; De Angelis, Flavio; Di Girolamo, Marco; Luigetti, Marco; Sabatelli, Mario; Pradotto, Luca; Mauro, Alessandro; Mazzeo, Anna; Stancanelli, Claudia; Perfetto, Federico; Frusconi, Sabrina; My, Filomena; Manfellotto, Dario; Fuciarelli, Maria; Polimanti, Renato

2017-09-01

Coding mutations in TTR gene cause a rare hereditary form of systemic amyloidosis, which has a complex genotype-phenotype correlation. We investigated the role of non-coding variants in regulating TTR gene expression and consequently amyloidosis symptoms. We evaluated the genotype-phenotype correlation considering the clinical information of 129 Italian patients with TTR amyloidosis. Then, we conducted a re-sequencing of TTR gene to investigate how non-coding variants affect TTR expression and, consequently, phenotypic presentation in carriers of amyloidogenic mutations. Polygenic scores for genetically determined TTR expression were constructed using data from our re-sequencing analysis and the GTEx (Genotype-Tissue Expression) project. We confirmed a strong phenotypic heterogeneity across coding mutations causing TTR amyloidosis. Considering the effects of non-coding variants on TTR expression, we identified three patient clusters with specific expression patterns associated with certain phenotypic presentations, including late onset, autonomic neurological involvement, and gastrointestinal symptoms. This study provides novel data regarding the role of non-coding variation and the gene expression profiles in patients affected by TTR amyloidosis, also putting forth an approach that could be used to investigate the mechanisms at the basis of the genotype-phenotype correlation of the disease.

Molecular Mechanisms Modulating the Phenotype of Macrophages and Microglia

PubMed Central

Amici, Stephanie A.; Dong, Joycelyn; Guerau-de-Arellano, Mireia

2017-01-01

Macrophages and microglia play crucial roles during central nervous system development, homeostasis and acute events such as infection or injury. The diverse functions of tissue macrophages and microglia are mirrored by equally diverse phenotypes. A model of inflammatory/M1 versus a resolution phase/M2 macrophages has been widely used. However, the complexity of macrophage function can only be achieved by the existence of varied, plastic and tridimensional macrophage phenotypes. Understanding how tissue macrophages integrate environmental signals via molecular programs to define pathogen/injury inflammatory responses provides an opportunity to better understand the multilayered nature of macrophages, as well as target and modulate cellular programs to control excessive inflammation. This is particularly important in MS and other neuroinflammatory diseases, where chronic inflammatory macrophage and microglial responses may contribute to pathology. Here, we perform a comprehensive review of our current understanding of how molecular pathways modulate tissue macrophage phenotype, covering both classic pathways and the emerging role of microRNAs, receptor-tyrosine kinases and metabolism in macrophage phenotype. In addition, we discuss pathway parallels in microglia, novel markers helpful in the identification of peripheral macrophages versus microglia and markers linked to their phenotype. PMID:29176977

GC[Formula: see text]NMF: A Novel Matrix Factorization Framework for Gene-Phenotype Association Prediction.

PubMed

Zhang, Yaogong; Liu, Jiahui; Liu, Xiaohu; Hong, Yuxiang; Fan, Xin; Huang, Yalou; Wang, Yuan; Xie, Maoqiang

2018-04-24

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and facilitate drug development. Gene-phenotype associations are related to complex biological processes and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations and lack of integrated analysis of the joint effect of multiple factors, existing applications are limited to prediction accuracy and potential gene-phenotype association detection. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC[Formula: see text]NMF). Specifically, first we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchical phenotypic data as weighted graph constraint for a better phenotype understanding. Second, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us with the intuition that genes in a group probably result in similar phenotypes. The model not only allows us to achieve a high-grade prediction performance, but also helps us to learn interpretable representation of genes and phenotypes simultaneously to facilitate future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC[Formula: see text]NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-arts methods.

A novel method for identifying disease associated protein complexes based on functional similarity protein complex networks.

PubMed

Le, Duc-Hau

2015-01-01

Protein complexes formed by non-covalent interaction among proteins play important roles in cellular functions. Computational and purification methods have been used to identify many protein complexes and their cellular functions. However, their roles in terms of causing disease have not been well discovered yet. There exist only a few studies for the identification of disease-associated protein complexes. However, they mostly utilize complicated heterogeneous networks which are constructed based on an out-of-date database of phenotype similarity network collected from literature. In addition, they only apply for diseases for which tissue-specific data exist. In this study, we propose a method to identify novel disease-protein complex associations. First, we introduce a framework to construct functional similarity protein complex networks where two protein complexes are functionally connected by either shared protein elements, shared annotating GO terms or based on protein interactions between elements in each protein complex. Second, we propose a simple but effective neighborhood-based algorithm, which yields a local similarity measure, to rank disease candidate protein complexes. Comparing the predictive performance of our proposed algorithm with that of two state-of-the-art network propagation algorithms including one we used in our previous study, we found that it performed statistically significantly better than that of these two algorithms for all the constructed functional similarity protein complex networks. In addition, it ran about 32 times faster than these two algorithms. Moreover, our proposed method always achieved high performance in terms of AUC values irrespective of the ways to construct the functional similarity protein complex networks and the used algorithms. The performance of our method was also higher than that reported in some existing methods which were based on complicated heterogeneous networks. Finally, we also tested our method with prostate cancer and selected the top 100 highly ranked candidate protein complexes. Interestingly, 69 of them were evidenced since at least one of their protein elements are known to be associated with prostate cancer. Our proposed method, including the framework to construct functional similarity protein complex networks and the neighborhood-based algorithm on these networks, could be used for identification of novel disease-protein complex associations.

The Promise of Multi-Omics and Clinical Data Integration to Identify and Target Personalized Healthcare Approaches in Autism Spectrum Disorders

PubMed Central

Higdon, Roger; Earl, Rachel K.; Stanberry, Larissa; Hudac, Caitlin M.; Montague, Elizabeth; Stewart, Elizabeth; Janko, Imre; Choiniere, John; Broomall, William; Kolker, Natali

2015-01-01

Abstract Complex diseases are caused by a combination of genetic and environmental factors, creating a difficult challenge for diagnosis and defining subtypes. This review article describes how distinct disease subtypes can be identified through integration and analysis of clinical and multi-omics data. A broad shift toward molecular subtyping of disease using genetic and omics data has yielded successful results in cancer and other complex diseases. To determine molecular subtypes, patients are first classified by applying clustering methods to different types of omics data, then these results are integrated with clinical data to characterize distinct disease subtypes. An example of this molecular-data-first approach is in research on Autism Spectrum Disorder (ASD), a spectrum of social communication disorders marked by tremendous etiological and phenotypic heterogeneity. In the case of ASD, omics data such as exome sequences and gene and protein expression data are combined with clinical data such as psychometric testing and imaging to enable subtype identification. Novel ASD subtypes have been proposed, such as CHD8, using this molecular subtyping approach. Broader use of molecular subtyping in complex disease research is impeded by data heterogeneity, diversity of standards, and ineffective analysis tools. The future of molecular subtyping for ASD and other complex diseases calls for an integrated resource to identify disease mechanisms, classify new patients, and inform effective treatment options. This in turn will empower and accelerate precision medicine and personalized healthcare. PMID:25831060

Pericentrin in cellular function and disease

PubMed Central

Delaval, Benedicte

2010-01-01

Pericentrin is an integral component of the centrosome that serves as a multifunctional scaffold for anchoring numerous proteins and protein complexes. Through these interactions, pericentrin contributes to a diversity of fundamental cellular processes. Recent studies link pericentrin to a growing list of human disorders. Studies on pericentrin at the cellular, molecular, and, more recently, organismal level, provide a platform for generating models to elucidate the etiology of these disorders. Although the complexity of phenotypes associated with pericentrin-mediated disorders is somewhat daunting, insights into the cellular basis of disease are beginning to come into focus. In this review, we focus on human conditions associated with loss or elevation of pericentrin and propose cellular and molecular models that might explain them. PMID:19951897

Emerging Synaptic Molecules as Candidates in the Etiology of Neurological Disorders

PubMed Central

Torres, Viviana I.; Vallejo, Daniela

2017-01-01

Synapses are complex structures that allow communication between neurons in the central nervous system. Studies conducted in vertebrate and invertebrate models have contributed to the knowledge of the function of synaptic proteins. The functional synapse requires numerous protein complexes with specialized functions that are regulated in space and time to allow synaptic plasticity. However, their interplay during neuronal development, learning, and memory is poorly understood. Accumulating evidence links synapse proteins to neurodevelopmental, neuropsychiatric, and neurodegenerative diseases. In this review, we describe the way in which several proteins that participate in cell adhesion, scaffolding, exocytosis, and neurotransmitter reception from presynaptic and postsynaptic compartments, mainly from excitatory synapses, have been associated with several synaptopathies, and we relate their functions to the disease phenotype. PMID:28331639

Neurogenetics of Depression: A Focus on Reward Processing and Stress Sensitivity

PubMed Central

Bogdan, Ryan; Nikolova, Yuliya S.; Pizzagalli, Diego A.

2013-01-01

Major depressive disorder (MDD) is etiologically complex and has a heterogeneous presentation. This heterogeneity hinders the ability of molecular genetic research to reliably detect the small effects conferred by common genetic variation. As a result, significant research efforts have been directed at investigating more homogenous intermediate phenotypes believed to be more proximal to gene function and lie between genes and/or environmental effects and disease processes. In the current review we survey and integrate research on two promising intermediate phenotypes linked to depression: reward processing and stress sensitivity. A synthesis of this burgeoning literature indicates that a molecular genetic approach focused on intermediate phenotypes holds significant promise to fundamentally improve our understanding of the pathophysiology and etiology of depression, which will be required for improved diagnostic definitions and the development of novel and more efficacious treatment and prevention strategies. We conclude by highlighting challenges facing intermediate phenotype research and future development that will be required to propel this pivotal research into new directions. PMID:22659304

Cryopyrin-associated periodic syndrome: an update on diagnosis and treatment response.

PubMed

Yu, Justin R; Leslie, Kieron S

2011-02-01

Cryopyrin-associated periodic syndrome (CAPS) is a rare hereditary inflammatory disorder encompassing a continuum of three phenotypes: familial cold autoinflammatory syndrome, Muckle-Wells syndrome, and neonatal-onset multisystem inflammatory disease. Distinguishing features include cutaneous, neurological, ophthalmologic, and rheumatologic manifestations. CAPS results from a gain-of-function mutation of the NLRP3 gene coding for cryopyrin, which forms intracellular protein complexes known as inflammasomes. Defects of the inflammasomes lead to overproduction of interleukin-1, resulting in inflammatory symptoms seen in CAPS. Diagnosis is often delayed and requires a thorough review of clinical symptoms. Remarkable advances in our understanding of the genetics and the molecular pathway that is responsible for the clinical phenotype of CAPS has led to the development of effective treatments. It also has become clear that the NLRP3 inflammasome plays a critical role in innate immune defense and therefore has wider implications for other inflammatory disease states.

Monogenic Lupus.

PubMed

Lo, Mindy S

2016-12-01

Systemic lupus erythematosus (SLE) is a multisystem autoimmune disease known for its clinical heterogeneity. Over time, new insights into the complex genetic origin of SLE have started to explain some of this clinical variability. These findings, reviewed here, have also yielded important understanding in the immune mechanisms behind SLE pathogenesis. Several new monogenic disorders with lupus-like phenotype have been described. These can be organized into physiologic pathways that parallel mechanisms of disease in SLE. Examples include genes important for DNA damage repair (e.g., TREX1), nucleic acid sensing and type I interferon overproduction (e.g., STING, TREX1), apoptosis (FASLG), tolerance (PRKCD), and clearance of self-antigen (DNASE1L3). Further study of monogenic lupus may lead to better genotype/phenotype correlations in SLE. Eventually, the ability to understand individual patients according to their genetic profile may allow the development of more targeted and personalized approaches to therapy.

Phenotypic analysis of perennial airborne allergen-specific CD4+ T cells in atopic and non-atopic individuals.

PubMed

Crack, L R; Chan, H W; McPherson, T; Ogg, G S

2011-11-01

Accumulating evidence suggests that T cells play an important role in the pathogenesis of atopic dermatitis (AD); yet, little is known of the differentiation status of CD4+ T cells specific for common environmental allergens, such as the major cat allergen, Fel d 1. To determine the frequency, differentiation phenotype and function of circulating Fel d 1-specific CD4+ T cells in adult individuals with severe persistent AD in comparison with healthy controls. Using HLA class II tetrameric complexes based on a HLA-DPB1*0401-restricted Fel d 1 epitope, ex vivo and cultured T cell frequency and phenotype were analysed in individuals with AD and healthy controls. Cytokine secretion was measured by ex vivo and cultured IL-4 and IFN-γ ELISpots. Ex vivo Fel d 1-specific DPB1*0401-restricted CD4+ T cells in both atopics and non-atopics express high levels of CCR7, CD62L, CD27 and CD28, placing the cells largely within the central memory subgroup. However, the functional phenotype was distinct, with greater IL-4 production from the cells derived from atopics, which correlated with disease severity. Circulating Fel d 1-specific DPB1*0401-restricted CD4+ T cells in both atopic and non-atopic donors maintain a central memory phenotype; however in atopics, the cells had greater Th2 effector function, compatible with a disease model of altered antigen delivery in atopic individuals. © 2011 Blackwell Publishing Ltd.

Current Understanding of Usher Syndrome Type II

PubMed Central

Yang, Jun; Wang, Le; Song, Hongman; Sokolov, Maxim

2012-01-01

Usher syndrome is the most common deafness-blindness caused by genetic mutations. To date, three genes have been identified underlying the most prevalent form of Usher syndrome, the type II form (USH2). The proteins encoded by these genes are demonstrated to form a complex in vivo. This complex is localized mainly at the periciliary membrane complex in photoreceptors and the ankle-link of the stereocilia in hair cells. Many proteins have been found to interact with USH2 proteins in vitro, suggesting that they are potential additional components of this USH2 complex and that the genes encoding these proteins may be the candidate USH2 genes. However, further investigations are critical to establish their existence in the USH2 complex in vivo. Based on the predicted functional domains in USH2 proteins, their cellular localizations in photoreceptors and hair cells, the observed phenotypes in USH2 mutant mice, and the known knowledge about diseases similar to USH2, putative biological functions of the USH2 complex have been proposed. Finally, therapeutic approaches for this group of diseases are now being actively explored. PMID:22201796

Rhabdoid and Undifferentiated Phenotype in Renal Cell Carcinoma: Analysis of 32 Cases Indicating a Distinctive Common Pathway of Dedifferentiation Frequently Associated With SWI/SNF Complex Deficiency.

PubMed

Agaimy, Abbas; Cheng, Liang; Egevad, Lars; Feyerabend, Bernd; Hes, Ondřej; Keck, Bastian; Pizzolitto, Stefano; Sioletic, Stefano; Wullich, Bernd; Hartmann, Arndt

2017-02-01

Undifferentiated (anaplastic) and rhabdoid cell features are increasingly recognized as adverse prognostic findings in renal cell carcinoma (RCC), but their molecular pathogenesis has not been studied sufficiently. Recent studies identified alterations in the Switch Sucrose nonfermentable (SWI/SNF) chromatin remodeling complex as molecular mechanisms underlying dedifferentiation and rhabdoid features in carcinomas of different organs. We herein have analyzed 32 undifferentiated RCCs having in common an undifferentiated (anaplastic) phenotype, prominent rhabdoid features, or both, irrespective of the presence or absence of conventional RCC component. Cases were stained with 6 SWI/SNF pathway members (SMARCB1, SMARCA2, SMARCA4, ARID1A, SMARCC1, and SMARCC2) in addition to conventional RCC markers. Patients were 20 males and 12 females aged 32 to 85 years (mean, 59). A total of 22/27 patients with known stage presented with ≥pT3. A differentiated component varying from microscopic to major component was detected in 20/32 cases (16 clear cell and 2 cases each chromophobe and papillary RCC). The undifferentiated component varied from rhabdoid dyscohesive cells to large epithelioid to small monotonous anaplastic cells. Variable loss of at least 1 SWI/SNF complex subunit was noted in the undifferentiated/rhabdoid component of 21/32 cases (65%) compared with intact or reduced expression in the differentiated component. A total of 15/17 patients (88%) with follow-up died of metastatic disease (mostly within 1 y). Only 2 patients were disease free at last follow-up (1 and 6 y). No difference in survival, age distribution, or sex was observed between the SWI/SNF-deficient and the SWI/SNF-intact group. This is the first study exploring the role of SWI/SNF deficiency as a potential mechanism underlying undifferentiated and rhabdoid phenotype in RCC. Our results highlight the association between the aggressive rhabdoid phenotype and the SWI/SNF complex deficiency, consistent with studies on similar neoplasms in other organs. Thorough sampling of such tumors that are usually huge and locally advanced is necessary for recognizing the clone of origin and hence for proper subtyping and also for differentiating them from undifferentiated urothelial carcinoma.

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

PubMed Central

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; Vasilevsky, Nicole; Baynam, Gareth; Zemojtel, Tomasz; Schriml, Lynn Marie; Kibbe, Warren Alden; Schofield, Paul N.; Beck, Tim; Vasant, Drashtti; Brookes, Anthony J.; Zankl, Andreas; Washington, Nicole L.; Mungall, Christopher J.; Lewis, Suzanna E.; Haendel, Melissa A.; Parkinson, Helen; Robinson, Peter N.

2015-01-01

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000 rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available. PMID:26119816

Antennal phenotype of Mexican haplogroups of the Triatoma dimidiata complex, vectors of Chagas disease.

PubMed

May-Concha, Irving; Guerenstein, Pablo G; Ramsey, Janine M; Rojas, Julio C; Catalá, Silvia

2016-06-01

Triatoma dimidiata (Latreille) is a species complex that spans North, Central, and South America and which is a key vector of all known discrete typing units (DTU) of Trypanosoma cruzi, the etiologic agent of Chagas disease. Morphological and genetic studies indicate that T. dimidiata is a species complex with three principal haplogroups (hg) in Mexico. Different markers and traits are still inconclusive regarding if other morphological differentiation may indicate probable behavioral and vectorial divergences within this complex. In this paper we compared the antennae of three Mexican haplogroups (previously verified by molecular markers ND4 and ITS-2) and discussed possible relationships with their capacity to disperse and colonized new habitats. The abundance of each type of sensillum (bristles, basiconics, thick- and thin-walled trichoids) on the antennae of the three haplogroups, were measured under light microscopy and compared using Kruskal-Wallis non-parametric and multivariate non-parametric analyses. Discriminant analyses indicate significant differences among the antennal phenotype of haplogroups either for adults and some nymphal stages, indicating consistency of the character to analyze intraspecific variability within the complex. The present study shows that the adult antennal pedicel of the T. dimidiata complex have abundant chemosensory sensilla, according with good capacity for dispersal and invasion of different habitats also related to their high capacity to adapt to conserved as well as modified habitats. However, the numerical differences among the haplogroups are suggesting variations in that capacity. The results here presented support the evidence of T. dimidiata as a species complex but show females and males in a different way. Given the close link between the bug's sensory system and its habitat and host-seeking behavior, AP characterization could be useful to complement genetic, neurological and ethological studies of the closely related Dimidiata Complex haplogroups for a better knowledge of their vectorial capacity and a more robust species differentiation. Copyright © 2016 Elsevier B.V. All rights reserved.

The Impact of "Possible Patients" on Phenotyping Algorithms: Electronic Phenotype Algorithms Can Only Be Reproduced by Sharing Detailed Annotation Criteria.

PubMed

Kagawa, Rina; Kawazoe, Yoshimasa; Shinohara, Emiko; Imai, Takeshi; Ohe, Kazuhiko

2017-01-01

Phenotyping is an automated technique for identifying patients diagnosed with a particular disease based on electronic health records (EHRs). To evaluate phenotyping algorithms, which should be reproducible, the annotation of EHRs as a gold standard is critical. However, we have found that the different types of EHRs cannot be definitively annotated into CASEs or CONTROLs. The influence of such "possible patients" on phenotyping algorithms is unknown. To assess these issues, for four chronic diseases, we annotated EHRs by using information not directly referring to the diseases and developed two types of phenotyping algorithms for each disease. We confirmed that each disease included different types of possible patients. The performance of phenotyping algorithms differed depending on whether possible patients were considered as CASEs, and this was independent of the type of algorithms. Our results indicate that researchers must share annotation criteria for classifying the possible patients to reproduce phenotyping algorithms.

Contemporary theories of cervical carcinogenesis: the virus, the host, and the stem cell.

PubMed

Crum, C P

2000-03-01

Cervical cancer is a complex disease that, by its association with human papillomavirus (HPV), has elicited research in a broad range of areas pertaining to its basic diagnostic and clinical aspects. The complexity of this association lies not only in the fundamental relationship between virus and cancer but also in its translation to pathologic diagnosis and clinical management. Offshoots from the relationship of virus to pathology include studies targeting the link between papillomavirus infection and cervical epithelial abnormalities, the molecular epidemiology of papillomavirus infection, and the potential use of HPV testing as either a screening technique or a tool for managing women who have Pap smear abnormalities. A second variable that is critical to the pathogenesis of cervical neoplasia is the cervical transformation zone. The wide range of invasive and noninvasive lesion phenotypes associated with HPV infection in this region indicate that not only the virus but also specific host target epithelial cells in the transformation zone play an important part in the development of cervical neoplasia. Further understanding of this relationship between the virus and the host epithelium will hinge on determining the subtypes of epithelial cells in the transformation zone and their phenotypic response to infection. New technologies, such as expression arrays, promise to clarify, if not resolve, the complexity of molecular interactions leading to the multiplicity of tumor phenotypes associated with HPV infection of the uterine cervix.

The genotype-phenotype map of an evolving digital organism.

PubMed

Fortuna, Miguel A; Zaman, Luis; Ofria, Charles; Wagner, Andreas

2017-02-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable.

The genotype-phenotype map of an evolving digital organism

PubMed Central

Zaman, Luis; Wagner, Andreas

2017-01-01

To understand how evolving systems bring forth novel and useful phenotypes, it is essential to understand the relationship between genotypic and phenotypic change. Artificial evolving systems can help us understand whether the genotype-phenotype maps of natural evolving systems are highly unusual, and it may help create evolvable artificial systems. Here we characterize the genotype-phenotype map of digital organisms in Avida, a platform for digital evolution. We consider digital organisms from a vast space of 10141 genotypes (instruction sequences), which can form 512 different phenotypes. These phenotypes are distinguished by different Boolean logic functions they can compute, as well as by the complexity of these functions. We observe several properties with parallels in natural systems, such as connected genotype networks and asymmetric phenotypic transitions. The likely common cause is robustness to genotypic change. We describe an intriguing tension between phenotypic complexity and evolvability that may have implications for biological evolution. On the one hand, genotypic change is more likely to yield novel phenotypes in more complex organisms. On the other hand, the total number of novel phenotypes reachable through genotypic change is highest for organisms with simple phenotypes. Artificial evolving systems can help us study aspects of biological evolvability that are not accessible in vastly more complex natural systems. They can also help identify properties, such as robustness, that are required for both human-designed artificial systems and synthetic biological systems to be evolvable. PMID:28241039

Antimicrobial Resistance Profile and Genotypic Characteristics of Streptococcus suis Capsular Type 2 Isolated from Clinical Carrier Sows and Diseased Pigs in China.

PubMed

Zhang, Chunping; Zhang, Zhongqiu; Song, Li; Fan, Xuezheng; Wen, Fang; Xu, Shixin; Ning, Yibao

2015-01-01

Streptococcus suis serotype 2 is an important zoonotic pathogen. Antimicrobial resistance phenotypes and genotypic characterizations of S. suis 2 from carrier sows and diseased pigs remain largely unknown. In this study, 96 swine S. suis type 2, 62 from healthy sows and 34 from diseased pigs, were analyzed. High frequency of tetracycline resistance was observed, followed by sulfonamides. The lowest resistance of S. suis 2 for β-lactams supports their use as the primary antibiotics to treat the infection of serotype 2. In contrast, 35 of 37 S. suis 2 with MLSB phenotypes were isolated from healthy sows, mostly encoded by the ermB and/or the mefA genes. Significantly lower frequency of mrp+/epf+/sly+ was observed among serotype 2 from healthy sows compared to those from diseased pigs. Furthermore, isolates from diseased pigs showed more homogeneously genetic patterns, with most of them clustered in pulsotypes A and E. The data indicate the genetic complexity of S. suis 2 between herds and a close linkage among isolates from healthy sows and diseased pigs. Moreover, many factors, such as extensive use of tetracycline or diffusion of Tn916 with tetM, might have favored for the pathogenicity and widespread dissemination of S. suis serotype 2.

Antimicrobial Resistance Profile and Genotypic Characteristics of Streptococcus suis Capsular Type 2 Isolated from Clinical Carrier Sows and Diseased Pigs in China

PubMed Central

Zhang, Chunping; Zhang, Zhongqiu; Song, Li; Fan, Xuezheng; Wen, Fang; Xu, Shixin; Ning, Yibao

2015-01-01

Streptococcus suis serotype 2 is an important zoonotic pathogen. Antimicrobial resistance phenotypes and genotypic characterizations of S. suis 2 from carrier sows and diseased pigs remain largely unknown. In this study, 96 swine S. suis type 2, 62 from healthy sows and 34 from diseased pigs, were analyzed. High frequency of tetracycline resistance was observed, followed by sulfonamides. The lowest resistance of S. suis 2 for β-lactams supports their use as the primary antibiotics to treat the infection of serotype 2. In contrast, 35 of 37 S. suis 2 with MLSB phenotypes were isolated from healthy sows, mostly encoded by the ermB and/or the mefA genes. Significantly lower frequency of mrp+/epf+/sly+ was observed among serotype 2 from healthy sows compared to those from diseased pigs. Furthermore, isolates from diseased pigs showed more homogeneously genetic patterns, with most of them clustered in pulsotypes A and E. The data indicate the genetic complexity of S. suis 2 between herds and a close linkage among isolates from healthy sows and diseased pigs. Moreover, many factors, such as extensive use of tetracycline or diffusion of Tn916 with tetM, might have favored for the pathogenicity and widespread dissemination of S. suis serotype 2. PMID:26064892

Obstructive Sleep Apnea Syndrome: From Phenotype to Genetic Basis

PubMed Central

Casale, M; Pappacena, M; Rinaldi, V; Bressi, F; Baptista, P; Salvinelli, F

2009-01-01

Obstructive sleep apnea syndrome (OSAS) is a complex chronic clinical syndrome, characterized by snoring, periodic apnea, hypoxemia during sleep, and daytime hypersomnolence. It affects 4-5% of the general population. Racial studies and chromosomal mapping, familial studies and twin studies have provided evidence for the possible link between the OSAS and genetic factors and also most of the risk factors involved in the pathogenesis of OSAS are largely genetically determined. A percentage of 35-40% of its variance can be attributed to genetic factors. It is likely that genetic factors associated with craniofacial structure, body fat distribution and neural control of the upper airway muscles interact to produce the OSAS phenotype. Although the role of specific genes that influence the development of OSAS has not yet been identified, current researches, especially in animal model, suggest that several genetic systems may be important. In this chapter, we will first define the OSAS phenotype, the pathogenesis and the risk factors involved in the OSAS that may be inherited, then, we will review the current progress in the genetics of OSAS and suggest a few future perspectives in the development of therapeutic agents for this complex disease entity. PMID:19794884

The phenotypic spectrum of organic acidurias and urea cycle disorders. Part 2: the evolving clinical phenotype.

PubMed

Kölker, Stefan; Valayannopoulos, Vassili; Burlina, Alberto B; Sykut-Cegielska, Jolanta; Wijburg, Frits A; Teles, Elisa Leão; Zeman, Jiri; Dionisi-Vici, Carlo; Barić, Ivo; Karall, Daniela; Arnoux, Jean-Baptiste; Avram, Paula; Baumgartner, Matthias R; Blasco-Alonso, Javier; Boy, S P Nikolas; Rasmussen, Marlene Bøgehus; Burgard, Peter; Chabrol, Brigitte; Chakrapani, Anupam; Chapman, Kimberly; Cortès I Saladelafont, Elisenda; Couce, Maria L; de Meirleir, Linda; Dobbelaere, Dries; Furlan, Francesca; Gleich, Florian; González, Maria Julieta; Gradowska, Wanda; Grünewald, Stephanie; Honzik, Tomas; Hörster, Friederike; Ioannou, Hariklea; Jalan, Anil; Häberle, Johannes; Haege, Gisela; Langereis, Eveline; de Lonlay, Pascale; Martinelli, Diego; Matsumoto, Shirou; Mühlhausen, Chris; Murphy, Elaine; de Baulny, Hélène Ogier; Ortez, Carlos; Pedrón, Consuelo C; Pintos-Morell, Guillem; Pena-Quintana, Luis; Ramadža, Danijela Petković; Rodrigues, Esmeralda; Scholl-Bürgi, Sabine; Sokal, Etienne; Summar, Marshall L; Thompson, Nicholas; Vara, Roshni; Pinera, Inmaculada Vives; Walter, John H; Williams, Monique; Lund, Allan M; Garcia-Cazorla, Angeles; Garcia Cazorla, Angeles

2015-11-01

The disease course and long-term outcome of patients with organic acidurias (OAD) and urea cycle disorders (UCD) are incompletely understood. To evaluate the complex clinical phenotype of OAD and UCD patients at different ages. Acquired microcephaly and movement disorders were common in OAD and UCD highlighting that the brain is the major organ involved in these diseases. Cardiomyopathy [methylmalonic (MMA) and propionic aciduria (PA)], prolonged QTc interval (PA), optic nerve atrophy [MMA, isovaleric aciduria (IVA)], pancytopenia (PA), and macrocephaly [glutaric aciduria type 1 (GA1)] were exclusively found in OAD patients, whereas hepatic involvement was more frequent in UCD patients, in particular in argininosuccinate lyase (ASL) deficiency. Chronic renal failure was often found in MMA, with highest frequency in mut(0) patients. Unexpectedly, chronic renal failure was also observed in adolescent and adult patients with GA1 and ASL deficiency. It had a similar frequency in patients with or without a movement disorder suggesting different pathophysiology. Thirteen patients (classic OAD: 3, UCD: 10) died during the study interval, ten of them during the initial metabolic crisis in the newborn period. Male patients with late-onset ornithine transcarbamylase deficiency were presumably overrepresented in the study population. Neurologic impairment is common in OAD and UCD, whereas the involvement of other organs (heart, liver, kidneys, eyes) follows a disease-specific pattern. The identification of unexpected chronic renal failure in GA1 and ASL deficiency emphasizes the importance of a systematic follow-up in patients with rare diseases.

The spectrum of renal involvement in male patients with infertility related to excretory-system abnormalities: phenotypes, genotypes, and genetic counseling.

PubMed

Mieusset, Roger; Fauquet, Isabelle; Chauveau, Dominique; Monteil, Laetitia; Chassaing, Nicolas; Daudin, Myriam; Huart, Antoine; Isus, François; Prouheze, Cathy; Calvas, Patrick; Bieth, Eric; Bujan, Louis; Faguer, Stanislas

2017-04-01

While reproductive technologies are increasingly used worldwide, epidemiologic, clinical and genetic data regarding infertile men with combined genital tract and renal abnormalities remain scarce, preventing adequate genetic counseling. In a cohort-based study, we assessed the prevalence (1995-2014) and the clinical characteristics of renal disorders in infertile males with genital tract malformation. In a subset of 34 patients, we performed a detailed phenotype analysis of renal and genital tract disorders. Among the 180 patients with congenital uni- or bilateral absence of vas deferens (CU/BAVD), 45 (25 %) had a renal malformation. We also identified 14 infertile men with combined seminal vesicle (SV) and renal malformation but no CU/BAVD. Among the 34 patients with detailed clinical description, renal disease was unknown before the assessment of the infertility in 27 (79.4 %), and 7 (20.6 %) had chronic renal failure. Four main renal phenotypes were observed: solitary kidney (47 %); autosomal-dominant polycystic kidney disease (ADPKD, 0.6 %); uni- or bilateral hypoplastic kidneys (20.6 %); and a complex renal phenotype associated with a mutation of the HNF1B gene (5.8 %). Absence of SV and azoospermia were significantly associated with the presence of a solitary kidney, while dilatation of SV and necroasthenozoospermia were suggestive of ADPKD. A dominantly inherited renal disease (ADPKD or HNF1B-related nephropathy) is frequent in males with infertility and combined renal and genital tract abnormalities (26 %). A systematic renal screening should be proposed in infertile males with CU/BAVD or SV disorders.

Aicardi-Goutières syndrome: a model disease for systemic autoimmunity.

PubMed

Lee-Kirsch, M A; Wolf, C; Günther, C

2014-01-01

Systemic autoimmunity is a complex disease process that results from a loss of immunological tolerance characterized by the inability of the immune system to discriminate self from non-self. In patients with the prototypic autoimmune disease systemic lupus erythematosus (SLE), formation of autoantibodies targeting ubiquitous nuclear antigens and subsequent deposition of immune complexes in the vascular bed induces inflammatory tissue injury that can affect virtually any organ system. Given the extraordinary genetic and phenotypic heterogeneity of SLE, one approach to the genetic dissection of complex SLE is to study monogenic diseases, for which a single gene defect is responsible. Considerable success has been achieved from the analysis of the rare monogenic disorder Aicardi-Goutières syndrome (AGS), an inflammatory encephalopathy that clinically resembles in-utero-acquired viral infection and that also shares features with SLE. Progress in understanding the cellular and molecular functions of the AGS causing genes has revealed novel pathways of the metabolism of intracellular nucleic acids, the major targets of the autoimmune attack in patients with SLE. Induction of autoimmunity initiated by immune recognition of endogenous nucleic acids originating from processes such as DNA replication/repair or endogenous retro-elements represents novel paradigms of SLE pathogenesis. These findings illustrate how investigating rare monogenic diseases can also fuel discoveries that advance our understanding of complex disease. This will not only aid the development of improved tools for SLE diagnosis and disease classification, but also the development of novel targeted therapeutic approaches. © 2013 British Society for Immunology.

Distributed Cognition and Process Management Enabling Individualized Translational Research: The NIH Undiagnosed Diseases Program Experience

PubMed Central

Links, Amanda E.; Draper, David; Lee, Elizabeth; Guzman, Jessica; Valivullah, Zaheer; Maduro, Valerie; Lebedev, Vlad; Didenko, Maxim; Tomlin, Garrick; Brudno, Michael; Girdea, Marta; Dumitriu, Sergiu; Haendel, Melissa A.; Mungall, Christopher J.; Smedley, Damian; Hochheiser, Harry; Arnold, Andrew M.; Coessens, Bert; Verhoeven, Steven; Bone, William; Adams, David; Boerkoel, Cornelius F.; Gahl, William A.; Sincan, Murat

2016-01-01

The National Institutes of Health Undiagnosed Diseases Program (NIH UDP) applies translational research systematically to diagnose patients with undiagnosed diseases. The challenge is to implement an information system enabling scalable translational research. The authors hypothesized that similar complex problems are resolvable through process management and the distributed cognition of communities. The team, therefore, built the NIH UDP integrated collaboration system (UDPICS) to form virtual collaborative multidisciplinary research networks or communities. UDPICS supports these communities through integrated process management, ontology-based phenotyping, biospecimen management, cloud-based genomic analysis, and an electronic laboratory notebook. UDPICS provided a mechanism for efficient, transparent, and scalable translational research and thereby addressed many of the complex and diverse research and logistical problems of the NIH UDP. Full definition of the strengths and deficiencies of UDPICS will require formal qualitative and quantitative usability and process improvement measurement. PMID:27785453

Phenome-driven disease genetics prediction toward drug discovery.

PubMed

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-06-15

Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

The impact of network medicine in gastroenterology and hepatology.

PubMed

Baffy, György

2013-10-01

In the footsteps of groundbreaking achievements made by biomedical research, another scientific revolution is unfolding. Systems biology draws from the chaos and complexity theory and applies computational models to predict emerging behavior of the interactions between genes, gene products, and environmental factors. Adaptation of systems biology to translational and clinical sciences has been termed network medicine, and is likely to change the way we think about preventing, predicting, diagnosing, and treating complex human diseases. Network medicine finds gene-disease associations by analyzing the unparalleled digital information discovered and created by high-throughput technologies (dubbed as "omics" science) and links genetic variance to clinical disease phenotypes through intermediate organizational levels of life such as the epigenome, transcriptome, proteome, and metabolome. Supported by large reference databases, unprecedented data storage capacity, and innovative computational analysis, network medicine is poised to find links between conditions that were thought to be distinct, uncover shared disease mechanisms and key drivers of the pathogenesis, predict individual disease outcomes and trajectories, identify novel therapeutic applications, and help avoid off-target and undesirable drug effects. Recent advances indicate that these perspectives are increasingly within our reach for understanding and managing complex diseases of the digestive system. Copyright © 2013 AGA Institute. Published by Elsevier Inc. All rights reserved.

The NIH Undiagnosed Diseases Program and Network: Applications to modern medicine

PubMed Central

Gahl, William A.; Mulvihill, John J.; Toro, Camilo; Markello, Thomas C.; Wise, Anastasia L.; Ramoni, Rachel B.; Adams, David R.; Tifft, Cynthia J.

2017-01-01

Introduction The inability of some seriously and chronically ill individuals to receive a definitive diagnosis represents an unmet medical need. In 2008, the NIH Undiagnosed Diseases Program (UDP) was established to provide answers to patients with mysterious conditions that long eluded diagnosis and to advance medical knowledge. Patients admitted to the NIH UDP undergo a five-day hospitalization, facilitating highly collaborative clinical evaluations and a detailed, standardized documentation of the individual’s phenotype. Bedside and bench investigations are tightly coupled. Genetic studies include commercially available testing, single nucleotide polymorphism microarray analysis, and family exomic sequencing studies. Selected gene variants are evaluated by collaborators using informatics, in vitro cell studies, and functional assays in model systems (fly, zebrafish, worm, or mouse). Insights from the UDP In seven years, the UDP received 2954 complete applications and evaluated 863 individuals. Nine vignettes (two unpublished) illustrate the relevance of an undiagnosed diseases program to complex and common disorders, the coincidence of multiple rare single gene disorders in individual patients, newly recognized mechanisms of disease, and the application of precision medicine to patient care. Conclusions The UDP provides examples of the benefits expected to accrue with the recent launch of a national Undiagnosed Diseases Network (UDN). The UDN should accelerate rare disease diagnosis and new disease discovery, enhance the likelihood of diagnosing known diseases in patients with uncommon phenotypes, improve management strategies, and advance medical research. PMID:26846157

Settling the score: variant prioritization and Mendelian disease

PubMed Central

Eilbeck, Karen; Quinlan, Aaron; Yandell, Mark

2018-01-01

When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype–phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing. PMID:28804138

Epigenetics Mechanisms in Alzheimer’s disease

PubMed Central

Mastroeni, Diego; Grover, Andrew; Delvaux, Elaine; Whiteside, Charisse; Coleman, Paul D.; Rogers, Joseph

2011-01-01

Epigenetic modifications help orchestrate sweeping developmental, aging, and disease-causing changes in phenotype by altering transcriptional activity in multiple genes spanning multiple biologic pathways. Although previous epigenetic research has focused primarily on dividing cells, particularly in cancer, recent studies have shown rapid, dynamic, and persistent epigenetic modifications in neurons that have significant neuroendocrine, neurophysiologic, and neurodegenerative consequences. Here, we provide a review of the major mechanisms for epigenetic modification and how they are reportedly altered in aging and Alzheimer’s disease (AD). Because of their reach across the genome, epigenetic mechanisms may provide a unique integrative framework for the pathologic diversity and complexity of AD. PMID:21482442

Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease.

PubMed

Abraham, Gad; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2013-02-01

A central goal of medical genetics is to accurately predict complex disease from genotypes. Here, we present a comprehensive analysis of simulated and real data using lasso and elastic-net penalized support-vector machine models, a mixed-effects linear model, a polygenic score, and unpenalized logistic regression. In simulation, the sparse penalized models achieved lower false-positive rates and higher precision than the other methods for detecting causal SNPs. The common practice of prefiltering SNP lists for subsequent penalized modeling was examined and shown to substantially reduce the ability to recover the causal SNPs. Using genome-wide SNP profiles across eight complex diseases within cross-validation, lasso and elastic-net models achieved substantially better predictive ability in celiac disease, type 1 diabetes, and Crohn's disease, and had equivalent predictive ability in the rest, with the results in celiac disease strongly replicating between independent datasets. We investigated the effect of linkage disequilibrium on the predictive models, showing that the penalized methods leverage this information to their advantage, compared with methods that assume SNP independence. Our findings show that sparse penalized approaches are robust across different disease architectures, producing as good as or better phenotype predictions and variance explained. This has fundamental ramifications for the selection and future development of methods to genetically predict human disease. © 2012 WILEY PERIODICALS, INC.

New approaches to the representation and analysis of phenotype knowledge in human diseases and their animal models.

PubMed

Schofield, Paul N; Sundberg, John P; Hoehndorf, Robert; Gkoutos, Georgios V

2011-09-01

The systematic investigation of the phenotypes associated with genotypes in model organisms holds the promise of revealing genotype-phenotype relations directly and without additional, intermediate inferences. Large-scale projects are now underway to catalog the complete phenome of a species, notably the mouse. With the increasing amount of phenotype information becoming available, a major challenge that biology faces today is the systematic analysis of this information and the translation of research results across species and into an improved understanding of human disease. The challenge is to integrate and combine phenotype descriptions within a species and to systematically relate them to phenotype descriptions in other species, in order to form a comprehensive understanding of the relations between those phenotypes and the genotypes involved in human disease. We distinguish between two major approaches for comparative phenotype analyses: the first relies on evolutionary relations to bridge the species gap, while the other approach compares phenotypes directly. In particular, the direct comparison of phenotypes relies heavily on the quality and coherence of phenotype and disease databases. We discuss major achievements and future challenges for these databases in light of their potential to contribute to the understanding of the molecular mechanisms underlying human disease. In particular, we discuss how the use of ontologies and automated reasoning can significantly contribute to the analysis of phenotypes and demonstrate their potential for enabling translational research.

PhenomeExpress: a refined network analysis of expression datasets by inclusion of known disease phenotypes.

PubMed

Soul, Jamie; Hardingham, Timothy E; Boot-Handford, Raymond P; Schwartz, Jean-Marc

2015-01-29

We describe a new method, PhenomeExpress, for the analysis of transcriptomic datasets to identify pathogenic disease mechanisms. Our analysis method includes input from both protein-protein interaction and phenotype similarity networks. This introduces valuable information from disease relevant phenotypes, which aids the identification of sub-networks that are significantly enriched in differentially expressed genes and are related to the disease relevant phenotypes. This contrasts with many active sub-network detection methods, which rely solely on protein-protein interaction networks derived from compounded data of many unrelated biological conditions and which are therefore not specific to the context of the experiment. PhenomeExpress thus exploits readily available animal model and human disease phenotype information. It combines this prior evidence of disease phenotypes with the experimentally derived disease data sets to provide a more targeted analysis. Two case studies, in subchondral bone in osteoarthritis and in Pax5 in acute lymphoblastic leukaemia, demonstrate that PhenomeExpress identifies core disease pathways in both mouse and human disease expression datasets derived from different technologies. We also validate the approach by comparison to state-of-the-art active sub-network detection methods, which reveals how it may enhance the detection of molecular phenotypes and provide a more detailed context to those previously identified as possible candidates.

Gene-Disease Network Analysis Reveals Functional Modules in Mendelian, Complex and Environmental Diseases

PubMed Central

Bauer-Mehren, Anna; Bundschus, Markus; Rautschka, Michael; Mayer, Miguel A.; Sanz, Ferran; Furlong, Laura I.

2011-01-01

Background Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. Principal Findings We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. Conclusions For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. Availability The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download. PMID:21695124

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases.

PubMed

Bauer-Mehren, Anna; Bundschus, Markus; Rautschka, Michael; Mayer, Miguel A; Sanz, Ferran; Furlong, Laura I

2011-01-01

Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult. We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell. For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases. The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download.

Revisiting Type 2-high and Type 2-low airway inflammation in asthma: current knowledge and therapeutic implications.

PubMed

Robinson, D; Humbert, M; Buhl, R; Cruz, A A; Inoue, H; Korom, S; Hanania, N A; Nair, P

2017-02-01

Asthma is a complex respiratory disorder characterized by marked heterogeneity in individual patient disease triggers and response to therapy. Several asthma phenotypes have now been identified, each defined by a unique interaction between genetic and environmental factors, including inflammatory, clinical and trigger-related phenotypes. Endotypes further describe the functional or pathophysiologic mechanisms underlying the patient's disease. type 2-driven asthma is an emerging nomenclature for a common subtype of asthma and is characterized by the release of signature cytokines IL-4, IL-5 and IL-13 from cells of both the innate and adaptive immune systems. A number of well-recognized biomarkers have been linked to mechanisms involved in type 2 airway inflammation, including fractional exhaled nitric oxide, serum IgE, periostin, and blood and sputum eosinophils. These type 2 cytokines are targets for pharmaceutical intervention, and a number of therapeutic options are under clinical investigation for the management of patients with uncontrolled severe asthma. Anticipating and understanding the heterogeneity of asthma and subsequent improved characterization of different phenotypes and endotypes must guide the selection of treatment to meet individual patients' needs. © 2017 The Authors. Clinical & Experimental Allergy Published by John Wiley & Sons Ltd.

Evidence for complete epistasis of null mutations in murine Fanconi anemia genes Fanca and Fancg.

PubMed

van de Vrugt, Henri J; Koomen, Mireille; Bakker, Sietske; Berns, Mariska A D; Cheng, Ngan Ching; van der Valk, Martin A; de Vries, Yne; Rooimans, Martin A; Oostra, Anneke B; Hoatlin, Maureen E; Te Riele, Hein; Joenje, Hans; Arwert, Fré

2011-12-10

Fanconi anemia (FA) is a heritable disease characterized by bone marrow failure, congenital abnormalities, and cancer predisposition. The 15 identified FA genes operate in a molecular pathway to preserve genomic integrity. Within this pathway the FA core complex operates as an ubiquitin ligase that activates the complex of FANCD2 and FANCI to coordinate DNA repair. The FA core complex is formed by at least 12 proteins. However, only the FANCL subunit displays ubiquitin ligase activity. FANCA and FANCG are members of the FA core complex for which no other functions have been described than to participate in protein interactions. In this study we generated mice with combined null alleles for Fanca and Fancg to identify extended functions for these genes by characterizing the double mutant mice and cells. Double mutant a(-/-)/g(-/-) mice were born at near Mendelian frequencies without apparent developmental abnormalities. Histological analysis of a(-/-)/g(-/-) mice revealed a Leydig cell hyperplasia and frequent vacuolization of Sertoli cells in testes, while ovaries were depleted from developing follicles and displayed an interstitial cell hyperplasia. These gonadal aberrations were associated with a compromised fertility of a(-/-)/g(-/-) males and females. During the first year of life a(-/-)/g(-/-) did not develop malignancies or bone marrow failure. At the cellular level a(-/-)/g(-/-), Fanca(-/-), and Fancg(-/-) cells proved equally compromised in DNA crosslink and homology-directed repair. Overall the phenotype of a(-/-)/g(-/-) double knockout mice and cells appeared highly similar to the phenotype of Fanca or Fancg single knockouts. The lack of an augmented phenotype suggest that null mutations in Fanca or Fancg are fully epistatic, making additional important functions outside of the FA core complex highly unlikely. 2011 Elsevier B.V. All rights reserved.

Increased Transcript Complexity in Genes Associated with Chronic Obstructive Pulmonary Disease

PubMed Central

Lackey, Lela; McArthur, Evonne; Laederach, Alain

2015-01-01

Genome-wide association studies aim to correlate genotype with phenotype. Many common diseases including Type II diabetes, Alzheimer’s, Parkinson’s and Chronic Obstructive Pulmonary Disease (COPD) are complex genetic traits with hundreds of different loci that are associated with varied disease risk. Identifying common features in the genes associated with each disease remains a challenge. Furthermore, the role of post-transcriptional regulation, and in particular alternative splicing, is still poorly understood in most multigenic diseases. We therefore compiled comprehensive lists of genes associated with Type II diabetes, Alzheimer’s, Parkinson’s and COPD in an attempt to identify common features of their corresponding mRNA transcripts within each gene set. The SERPINA1 gene is a well-recognized genetic risk factor of COPD and it produces 11 transcript variants, which is exceptional for a human gene. This led us to hypothesize that other genes associated with COPD, and complex disorders in general, are highly transcriptionally diverse. We found that COPD-associated genes have a statistically significant enrichment in transcript complexity stemming from a disproportionately high level of alternative splicing, however, Type II Diabetes, Alzheimer’s and Parkinson’s disease genes were not significantly enriched. We also identified a subset of transcriptionally complex COPD-associated genes (~40%) that are differentially expressed between mild, moderate and severe COPD. Although the genes associated with other lung diseases are not extensively documented, we found preliminary data that idiopathic pulmonary disease genes, but not cystic fibrosis modulators, are also more transcriptionally complex. Interestingly, complex COPD transcripts are more often the product of alternative acceptor site usage. To verify the biological importance of these alternative transcripts, we used RNA-sequencing analyses to determine that COPD-associated genes are frequently expressed in lung and liver tissues and are regulated in a tissue-specific manner. Additionally, many complex COPD-associated genes are spliced differently between COPD and non-COPD patients. Our analysis therefore suggests that post-transcriptional regulation, particularly alternative splicing, is an important feature specific to COPD disease etiology that warrants further investigation. PMID:26480348

Cleft Palate, Retrognathia and Congenital Heart Disease in Velo-Cardio-Facial Syndrome: A Phenotype Correlation Study

PubMed Central

Friedman, Marcia A.; Miletta, Nathanial; Roe, Cheryl; Wang, Dongliang; Morrow, Bernice E.; Kates, Wendy R.; Higgins, Anne Marie; Shprintzen, Robert J.

2011-01-01

Objective Velo-cardio-facial syndrome (VCFS) is caused by a microdeletion of approximately 40 genes from one copy of chromosome 22. Expression of the syndrome is a variable combination of over 190 phenotypic characteristics. As of yet, little is known about how these phenotypes correlate with one another or whether there are predictable patterns of expression. Two of the most common phenotypic categories, congenital heart disease and cleft palate, have been proposed to have a common genetic relationship to the deleted T-box 1 gene (TBX1). The purpose of this study is to determine if congenital heart disease and cleft palate are correlated in a large cohort of human subjects with VCFS. Methods This study is a retrospective chart review including 316 Caucasian non-Hispanic subjects with FISH or CGH microarray confirmed chromosome 22q11.2 deletions. All subjects were evaluated by the interdisciplinary team at the Velo-Cardio-Facial Syndrome International Center at Upstate Medical University, Syracuse, NY. Each combination of congenital heart disease, cleft palates, and retrognathia was analyzed by chi square or Fisher exact test. Results For all categories of congenital heart disease and cleft palate or retrognathia no significant associations were found, with the exception of submucous cleft palate and retrognathia (nominal p=0.0325) and occult submucous cleft palate and retrognathia (nominal p=0.000013). Conclusions Congenital heart disease and cleft palate do not appear to be correlated in human subjects with VCFS despite earlier suggestions from animal models. Possible explanations include modification of the effect of TBX1 by genes outside of the 22q11.2 region that may further influence the formation of the palate or heart, or the presence of epigenetic factors that may effect genes within the deleted region, modifying genes elsewhere, or polymorphisms on the normal copy of chromosome 22. Lastly, it is possible that TBX1 plays a role in palate formation in some species, but not in humans. In VCFS, retrognathia is caused by an obtuse angulation of the skull base. It is unknown if the correlation between retrognathia and cleft palate in VCFS indicates a developmental sequence related to skull morphology, or direct gene effects of both anomalies. Much work remains to be done to fully understand the complex relationships between phenotypic characteristics in VCFS. PMID:21763005

Cleft palate, retrognathia and congenital heart disease in velo-cardio-facial syndrome: a phenotype correlation study.

PubMed

Friedman, Marcia A; Miletta, Nathanial; Roe, Cheryl; Wang, Dongliang; Morrow, Bernice E; Kates, Wendy R; Higgins, Anne Marie; Shprintzen, Robert J

2011-09-01

Velo-cardio-facial syndrome (VCFS) is caused by a microdeletion of approximately 40 genes from one copy of chromosome 22. Expression of the syndrome is a variable combination of over 190 phenotypic characteristics. As of yet, little is known about how these phenotypes correlate with one another or whether there are predictable patterns of expression. Two of the most common phenotypic categories, congenital heart disease and cleft palate, have been proposed to have a common genetic relationship to the deleted T-box 1 gene (TBX1). The purpose of this study is to determine if congenital heart disease and cleft palate are correlated in a large cohort of human subjects with VCFS. This study is a retrospective chart review including 316 Caucasian non-Hispanic subjects with FISH or CGH microarray confirmed chromosome 22q11.2 deletions. All subjects were evaluated by the interdisciplinary team at the Velo-Cardio-Facial Syndrome International Center at Upstate Medical University, Syracuse, NY. Each combination of congenital heart disease, cleft palates, and retrognathia was analyzed by Chi square or Fisher exact test. For all categories of congenital heart disease and cleft palate or retrognathia no significant associations were found, with the exception of submucous cleft palate and retrognathia (nominal p=0.0325) and occult submucous cleft palate and retrognathia (nominal p=0.000013). Congenital heart disease and cleft palate do not appear to be correlated in human subjects with VCFS despite earlier suggestions from animal models. Possible explanations include modification of the effect of TBX1 by genes outside of the 22q11.2 region that may further influence the formation of the palate or heart, or the presence of epigenetic factors that may effect genes within the deleted region, modifying genes elsewhere, or polymorphisms on the normal copy of chromosome 22. Lastly, it is possible that TBX1 plays a role in palate formation in some species, but not in humans. In VCFS, retrognathia is caused by an obtuse angulation of the skull base. It is unknown if the correlation between retrognathia and cleft palate in VCFS indicates a developmental sequence related to skull morphology, or direct gene effects of both anomalies. Much work remains to be done to fully understand the complex relationships between phenotypic characteristics in VCFS. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Respiration and substrate transport rates as well as reactive oxygen species production distinguish mitochondria from brain and liver.

PubMed

Gusdon, Aaron M; Fernandez-Bueno, Gabriel A; Wohlgemuth, Stephanie; Fernandez, Jenelle; Chen, Jing; Mathews, Clayton E

2015-09-10

Aberrant mitochondrial function, including excessive reactive oxygen species (ROS) production, has been implicated in the pathogenesis of human diseases. The use of mitochondrial inhibitors to ascertain the sites in the electron transport chain (ETC) resulting in altered ROS production can be an important tool. However, the response of mouse mitochondria to ETC inhibitors has not been thoroughly assessed. Here we set out to characterize the differences in phenotypic response to ETC inhibitors between the more energetically demanding brain mitochondria and less energetically demanding liver mitochondria in commonly utilized C57BL/6J mice. We show that in contrast to brain mitochondria, inhibiting distally within complex I or within complex III does not increase liver mitochondrial ROS production supported by complex I substrates, and liver mitochondrial ROS production supported by complex II substrates occurred primarily independent of membrane potential. Complex I, II, and III enzymatic activities and membrane potential were equivalent between liver and brain and responded to ETC. inhibitors similarly. Brain mitochondria exhibited an approximately two-fold increase in complex I and II supported respiration compared with liver mitochondria while exhibiting similar responses to inhibitors. Elevated NADH transport and heightened complex II-III coupled activity accounted for increased complex I and II supported respiration, respectively in brain mitochondria. We conclude that important mechanistic differences exist between mouse liver and brain mitochondria and that mouse mitochondria exhibit phenotypic differences compared with mitochondria from other species.

The Human Phenotype Ontology: Semantic Unification of Common and Rare Disease

DOE PAGES

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid; ...

2015-06-25

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000more » rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.« less

Induction of mesenchymal cell phenotypes in lung epithelial cells by adenovirus E1A.

PubMed

Behzad, A R; Morimoto, K; Gosselink, J; Green, J; Hogg, J C; Hayashi, S

2006-12-01

Epithelial-mesenchymal transformation is now recognised as an important feature of tissue remodelling. The present report concerns the role of adenovirus infection in inducing this transformation in an animal model of chronic obstructive pulmonary disease. Guinea pig primary peripheral lung epithelial cells (PLECs) transfected with adenovirus E1A (E1A-PLECs) were compared to guinea pig normal lung fibroblasts (NLFs) transfected with E1A (E1A-NLFs). These cells were characterised by PCR, immunocytochemistry, electron microscopy, and Western and Northern blot analyses. Electrophoretic mobility shift assays were performed in order to examine nuclear factor (NF)-kappaB and activator protein (AP)-1 binding activities. E1A-PLECs and E1A-NLFs positive for E1A DNA, mRNA and protein expressed cytokeratin and vimentin but not smooth muscle alpha-actin. Both exhibited cuboidal morphology and junctional complexes, but did not contain lamellar bodies or express surfactant protein A, B or C mRNAs. These two cell types differed, however, in their NF-kappaB and AP-1 binding after lipopolysaccharide stimulation, possibly due to differences in the expression of the subunits that comprise these transcriptional complexes. E1A transfection results in the transformation of peripheral lung epithelial cells and normal lung fibroblasts to a phenotype intermediate between that of the two primary cells. It is postulated that this intermediate phenotype may play a major role in the remodelling of the airways in chronic obstructive pulmonary disease associated with persistence of adenovirus E1A DNA.

Linking Genes to Cardiovascular Diseases: Gene Action and Gene–Environment Interactions

PubMed Central

2016-01-01

A unique myocardial characteristic is its ability to grow/remodel in order to adapt; this is determined partly by genes and partly by the environment and the milieu intérieur. In the “post-genomic” era, a need is emerging to elucidate the physiologic functions of myocardial genes, as well as potential adaptive and maladaptive modulations induced by environmental/epigenetic factors. Genome sequencing and analysis advances have become exponential lately, with escalation of our knowledge concerning sometimes controversial genetic underpinnings of cardiovascular diseases. Current technologies can identify candidate genes variously involved in diverse normal/abnormal morphomechanical phenotypes, and offer insights into multiple genetic factors implicated in complex cardiovascular syndromes. The expression profiles of thousands of genes are regularly ascertained under diverse conditions. Global analyses of gene expression levels are useful for cataloging genes and correlated phenotypes, and for elucidating the role of genes in maladies. Comparative expression of gene networks coupled to complex disorders can contribute insights as to how “modifier genes” influence the expressed phenotypes. Increasingly, a more comprehensive and detailed systematic understanding of genetic abnormalities underlying, for example, various genetic cardiomyopathies is emerging. Implementing genomic findings in cardiology practice may well lead directly to better diagnosing and therapeutics. There is currently evolving a strong appreciation for the value of studying gene anomalies, and doing so in a non-disjointed, cohesive manner. However, it is challenging for many—practitioners and investigators—to comprehend, interpret, and utilize the clinically increasingly accessible and affordable cardiovascular genomics studies. This survey addresses the need for fundamental understanding in this vital area. PMID:26545598

SM2PH-db: an interactive system for the integrated analysis of phenotypic consequences of missense mutations in proteins involved in human genetic diseases.

PubMed

Friedrich, Anne; Garnier, Nicolas; Gagnière, Nicolas; Nguyen, Hoan; Albou, Laurent-Philippe; Biancalana, Valérie; Bettler, Emmanuel; Deléage, Gilbert; Lecompte, Odile; Muller, Jean; Moras, Dino; Mandel, Jean-Louis; Toursel, Thierry; Moulinier, Luc; Poch, Olivier

2010-02-01

Understanding how genetic alterations affect gene products at the molecular level represents a first step in the elucidation of the complex relationships between genotypic and phenotypic variations, and is thus a major challenge in the postgenomic era. Here, we present SM2PH-db (http://decrypthon.igbmc.fr/sm2ph), a new database designed to investigate structural and functional impacts of missense mutations and their phenotypic effects in the context of human genetic diseases. A wealth of up-to-date interconnected information is provided for each of the 2,249 disease-related entry proteins (August 2009), including data retrieved from biological databases and data generated from a Sequence-Structure-Evolution Inference in Systems-based approach, such as multiple alignments, three-dimensional structural models, and multidimensional (physicochemical, functional, structural, and evolutionary) characterizations of mutations. SM2PH-db provides a robust infrastructure associated with interactive analysis tools supporting in-depth study and interpretation of the molecular consequences of mutations, with the more long-term goal of elucidating the chain of events leading from a molecular defect to its pathology. The entire content of SM2PH-db is regularly and automatically updated thanks to a computational grid data federation facilities provided in the context of the Decrypthon program. (c) 2009 Wiley-Liss, Inc.

A Phenotypic Change But Not Proliferation Underlies Glial Responses in Alzheimer Disease

PubMed Central

Serrano-Pozo, Alberto; Gómez-Isla, Teresa; Growdon, John H.; Frosch, Matthew P.; Hyman, Bradley T.

2014-01-01

Classical immunohistochemical studies in the Alzheimer disease (AD) brain reveal prominent glial reactions, but whether this pathological feature is due primarily to cell proliferation or to a phenotypic change of existing resting cells remains controversial. We performed double-fluorescence immunohistochemical studies of astrocytes and microglia, followed by unbiased stereology-based quantitation in temporal cortex of 40 AD patients and 32 age-matched nondemented subjects. Glial fibrillary acidic protein (GFAP) and major histocompatibility complex II (MHC2) were used as markers of astrocytic and microglial activation, respectively. Aldehyde dehydrogenase 1 L1 and glutamine synthetase were used as constitutive astrocytic markers, and ionized calcium-binding adaptor molecule 1 (IBA1) as a constitutive microglial marker. As expected, AD patients had higher numbers of GFAP+ astrocytes and MHC2+ microglia than the nondemented subjects. However, both groups had similar numbers of total astrocytes and microglia and, in the AD group, these total numbers remained essentially constant over the clinical course of the disease. The GFAP immunoreactivity of astrocytes, but not the MHC2 immunoreactivity of microglia, increased in parallel with the duration of the clinical illness in the AD group. Cortical atrophy contributed to the perception of increased glia density. We conclude that a phenotypic change of existing glial cells, rather than a marked proliferation of glial precursors, accounts for the majority of the glial responses observed in the AD brain. PMID:23602650

Mutations in B4GALNT1 (GM2 synthase) underlie a new disorder of ganglioside biosynthesis.

PubMed

Harlalka, Gaurav V; Lehman, Anna; Chioza, Barry; Baple, Emma L; Maroofian, Reza; Cross, Harold; Sreekantan-Nair, Ajith; Priestman, David A; Al-Turki, Saeed; McEntagart, Meriel E; Proukakis, Christos; Royle, Louise; Kozak, Radoslaw P; Bastaki, Laila; Patton, Michael; Wagner, Karin; Coblentz, Roselyn; Price, Joy; Mezei, Michelle; Schlade-Bartusiak, Kamilla; Platt, Frances M; Hurles, Matthew E; Crosby, Andrew H

2013-12-01

Glycosphingolipids are ubiquitous constituents of eukaryotic plasma membranes, and their sialylated derivatives, gangliosides, are the major class of glycoconjugates expressed by neurons. Deficiencies in their catabolic pathways give rise to a large and well-studied group of inherited disorders, the lysosomal storage diseases. Although many glycosphingolipid catabolic defects have been defined, only one proven inherited disease arising from a defect in ganglioside biosynthesis is known. This disease, because of defects in the first step of ganglioside biosynthesis (GM3 synthase), results in a severe epileptic disorder found at high frequency amongst the Old Order Amish. Here we investigated an unusual neurodegenerative phenotype, most commonly classified as a complex form of hereditary spastic paraplegia, present in families from Kuwait, Italy and the Old Order Amish. Our genetic studies identified mutations in B4GALNT1 (GM2 synthase), encoding the enzyme that catalyzes the second step in complex ganglioside biosynthesis, as the cause of this neurodegenerative phenotype. Biochemical profiling of glycosphingolipid biosynthesis confirmed a lack of GM2 in affected subjects in association with a predictable increase in levels of its precursor, GM3, a finding that will greatly facilitate diagnosis of this condition. With the description of two neurological human diseases involving defects in two sequentially acting enzymes in ganglioside biosynthesis, there is the real possibility that a previously unidentified family of ganglioside deficiency diseases exist. The study of patients and animal models of these disorders will pave the way for a greater understanding of the role gangliosides play in neuronal structure and function and provide insights into the development of effective treatment therapies.

Integrating microRNAs into a system biology approach to acute lung injury.

PubMed

Zhou, Tong; Garcia, Joe G N; Zhang, Wei

2011-04-01

Acute lung injury (ALI), including the ventilator-induced lung injury (VILI) and the more severe acute respiratory distress syndrome (ARDS), are common and complex inflammatory lung diseases potentially affected by various genetic and nongenetic factors. Using the candidate gene approach, genetic variants associated with immune response and inflammatory pathways have been identified and implicated in ALI. Because gene expression is an intermediate phenotype that resides between the DNA sequence variation and the higher level cellular or whole-body phenotypes, the illustration of gene expression regulatory networks potentially could enhance understanding of disease susceptibility and the development of inflammatory lung syndromes. MicroRNAs (miRNAs) have emerged as a novel class of gene regulators that play critical roles in complex diseases including ALI. Comparisons of global miRNA profiles in animal models of ALI and VILI identified several miRNAs (eg, miR-146a and miR-155) previously implicated in immune response and inflammatory pathways. Therefore, via regulation of target genes in these biological processes and pathways, miRNAs potentially contribute to the development of ALI. Although this line of inquiry exists at a nascent stage, miRNAs have the potential to be critical components of a comprehensive model for inflammatory lung disease built by a systems biology approach that integrates genetic, genomic, proteomic, epigenetic as well as environmental stimuli information. Given their particularly recognized role in regulation of immune and inflammatory responses, miRNAs also serve as novel therapeutic targets and biomarkers for ALI/ARDS or VILI, thus facilitating the realization of personalized medicine for individuals with acute inflammatory lung disease. Copyright © 2011 Mosby, Inc. All rights reserved.

Latent topic discovery of clinical concepts from hospital discharge summaries of a heterogeneous patient cohort.

PubMed

Lehman, Li-Wei; Long, William; Saeed, Mohammed; Mark, Roger

2014-01-01

Patients in critical care often exhibit complex disease patterns. A fundamental challenge in clinical research is to identify clinical features that may be characteristic of adverse patient outcomes. In this work, we propose a data-driven approach for phenotype discovery of patients in critical care. We used Hierarchical Dirichlet Process (HDP) as a non-parametric topic modeling technique to automatically discover the latent "topic" structure of diseases, symptoms, and findings documented in hospital discharge summaries. We show that the latent topic structure can be used to reveal phenotypic patterns of diseases and symptoms shared across subgroups of a patient cohort, and may contain prognostic value in stratifying patients' post hospital discharge mortality risks. Using discharge summaries of a large patient cohort from the MIMIC II database, we evaluate the clinical utility of the discovered topic structure in identifying patients who are at high risk of mortality within one year post hospital discharge. We demonstrate that the learned topic structure has statistically significant associations with mortality post hospital discharge, and may provide valuable insights in defining new feature sets for predicting patient outcomes.

RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

PubMed Central

Sojod, Bouchra; Chateau, Danielle; Mueller, Christopher G.; Babajko, Sylvie; Berdal, Ariane; Lézot, Frédéric; Castaneda, Beatriz

2017-01-01

Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg) and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases. PMID:28596739

Severe B cell hyperplasia and autoimmune disease in TALL-1 transgenic mice

PubMed Central

Khare, Sanjay D.; Sarosi, Ildiko; Xia, Xing-Zhong; McCabe, Susan; Miner, Kent; Solovyev, Irina; Hawkins, Nessa; Kelley, Michael; Chang, David; Van, Gwyneth; Ross, Larry; Delaney, John; Wang, Ling; Lacey, David; Boyle, William J.; Hsu, Hailing

2000-01-01

TALL-1/Blys/BAFF is a member of the tumor necrosis factor (TNF) ligand superfamily that is functionally involved in B cell proliferation. Here, we describe B cell hyperplasia and autoimmune lupus-like changes in transgenic mice expressing TALL-1 under the control of a β-actin promoter. The TALL-1 transgenic mice showed severe enlargement of spleen, lymph nodes, and Peyer's patches because of an increased number of B220+ cells. The transgenic mice also had hypergammaglobulinemia contributed by elevations of serum IgM, IgG, IgA, and IgE. In addition, a phenotype similar to autoimmune lupus-like disease was also seen in TALL-1 transgenic mice, characterized by the presence of autoantibodies to nuclear antigens and immune complex deposits in the kidney. Prolonged survival and hyperactivity of transgenic B cells may contribute to the autoimmune lupus-like phenotype in these animals. Our studies further confirm TALL-1 as a stimulator of B cells that affect Ig production. Thus, TALL-1 may be a primary mediator in B cell-associated autoimmune diseases. PMID:10716715

Pulmonary phenotypes associated with genetic variation in telomere-related genes.

PubMed

Hoffman, Thijs W; van Moorsel, Coline H M; Borie, Raphael; Crestani, Bruno

2018-05-01

Genomic mutations in telomere-related genes have been recognized as a cause of familial forms of idiopathic pulmonary fibrosis (IPF). However, it has become increasingly clear that telomere syndromes and telomere shortening are associated with various types of pulmonary disease. Additionally, it was found that also single nucleotide polymorphisms (SNPs) in telomere-related genes are risk factors for the development of pulmonary disease. This review focuses on recent updates on pulmonary phenotypes associated with genetic variation in telomere-related genes. Genomic mutations in seven telomere-related genes cause pulmonary disease. Pulmonary phenotypes associated with these mutations range from many forms of pulmonary fibrosis to emphysema and pulmonary vascular disease. Telomere-related mutations account for up to 10% of sporadic IPF, 25% of familial IPF, 10% of connective-tissue disease-associated interstitial lung disease, and 1% of COPD. Mixed disease forms have also been found. Furthermore, SNPs in TERT, TERC, OBFC1, and RTEL1, as well as short telomere length, have been associated with several pulmonary diseases. Treatment of pulmonary disease caused by telomere-related gene variation is currently based on disease diagnosis and not on the underlying cause. Pulmonary phenotypes found in carriers of telomere-related gene mutations and SNPs are primarily pulmonary fibrosis, sometimes emphysema and rarely pulmonary vascular disease. Genotype-phenotype relations are weak, suggesting that environmental factors and genetic background of patients determine disease phenotypes to a large degree. A disease model is presented wherever genomic variation in telomere-related genes cause specific pulmonary disease phenotypes whenever triggered by environmental exposure, comorbidity, or unknown factors.

An assessment of molecular pathways of obesity susceptible to nutrient, toxicant and genetically induced epigenetic perturbation

PubMed Central

Xue, Jing; Ideraabdullah, Folami Y.

2015-01-01

In recent years, the etiology of human disease has greatly improved with the inclusion of epigenetic mechanisms, in particular as a common link between environment and disease. However, for most diseases we lack a detailed interpretation of the epigenetic regulatory pathways perturbed by environment and causal mechanisms. Here, we focus on recent findings elucidating nutrient-related epigenetic changes linked to obesity. We highlight studies demonstrating that obesity is a complex disease linked to disruption of epigenetically regulated metabolic pathways in the brain, adipose tissue and liver. These pathways regulate (1) homeostatic and hedonic eating behaviors (2) adipocyte differentiation and fat accumulation, and (3) energy expenditure. By compiling these data we illustrate that obesity-related phenotypes are repeatedly linked to disruption of critical epigenetic mechanisms that regulate of key metabolic genes. These data are supported by genetic mutation of key epigenetic regulators and many of the diet induced epigenetic mechanisms of obesity are also perturbed by exposure to environmental toxicants. Identifying similarly perturbed epigenetic mechanisms in multiple experimental models of obesity strengthens the translational applications of these findings. We also discuss many of the ongoing challenges to understanding the role of environmentally-induced epigenetic pathways in obesity and suggest future studies to elucidate these roles. This assessment illustrates our current understanding of molecular pathways of obesity that are susceptible to environmental perturbation via epigenetic mechanisms. Thus, it lays the groundwork for dissecting the complex interactions between diet, genes, and toxicants that contribute to obesity and obesity-related phenotypes. PMID:27012616

Diverse forms of pulmonary hypertension remodel the arterial tree to a high shear phenotype

PubMed Central

Allen, Roblee P.; Schelegle, Edward S.

2014-01-01

Pulmonary hypertension (PH) is associated with progressive changes in arterial network complexity. An allometric model is derived that integrates diameter branching complexity between pulmonary arterioles of generation n and the main pulmonary artery (MPA) via a power-law exponent (X) in dn = dMPA2−n/X and the arterial area ratio β = 21–2/X. Our hypothesis is that diverse forms of PH demonstrate early decrements in X independent of etiology and pathogenesis, which alters the arteriolar shear stress load from a low-shear stress (X > 2, β > 1) to a high-shear stress phenotype (X < 2, β < 1). Model assessment was accomplished by comparing theoretical predictions to retrospective morphometric and hemodynamic measurements made available from a total of 221 PH-free and PH subjects diagnosed with diverse forms (World Health Organization; WHO groups I-IV) of PH: mitral stenosis, congenital heart disease, chronic obstructive pulmonary lung disease, chronic thromboembolism, idiopathic pulmonary arterial hypertension (IPAH), familial (FPAH), collagen vascular disease, and methamphetamine exposure. X was calculated from pulmonary artery pressure (PPA), cardiac output (Q) and body weight (M), utilizing an allometric power-law prediction of X relative to a PH-free state. Comparisons of X between PAH-free and PAH subjects indicates a characteristic reduction in area that elevates arteriolar shear stress, which may contribute to mechanisms of endothelial dysfunction and injury before clinically defined thresholds of pulmonary vascular resistance and PH. We conclude that the evaluation of X may be of use in identifying reversible and irreversible phases of PH in the early course of the disease process. PMID:24858853

Mutations in SURF1 are important genetic causes of Leigh syndrome in Slovak patients.

PubMed

Danis, Daniel; Brennerova, Katarina; Skopkova, Martina; Kurdiova, Timea; Ukropec, Jozef; Stanik, Juraj; Kolnikova, Miriam; Gasperikova, Daniela

2018-04-01

Leigh syndrome is a progressive early onset neurodegenerative disease typically presenting with psychomotor regression, signs of brainstem and/or basal ganglia disease, lactic acidosis, and characteristic magnetic resonance imaging findings. At molecular level, deficiency of respiratory complexes and/or pyruvate dehydrogenase complex is usually observed. Nuclear gene SURF1 encodes an assembly factor for cytochrome c-oxidase complex of the respiratory chain and autosomal recessive mutations in SURF1 are one of the most frequent causes of cytochrome c-oxidase-related Leigh syndrome cases. Here, we aimed to elucidate the genetic basis of Leigh syndrome in three Slovak families. Three probands presenting with Leigh syndrome were selected for DNA analysis. The first proband, presenting with atypical LS onset without abnormal basal ganglia magnetic resonance imaging findings, was analyzed with whole exome sequencing. In the two remaining probands, SURF1 was screened by Sanger sequencing. Four different heterozygous mutations were identified in SURF1: c.312_321delinsAT:p.(Pro104Profs*1), c.588+1G>A, c.823_833+7del:p. (?) and c.845_846del:p.(Ser282Cysfs*9). All the mutations are predicted to have a loss-of-function effect. We identified disease-causing mutations in all three probands, which points to the important role of SURF1 gene in etiology of Leigh syndrome in Slovakia. Our data showed that patients with atypical Leigh syndrome phenotype without lesions in basal ganglia may benefit from the whole exome sequencing method. In the case of probands presenting the typical phenotype, Sanger sequencing of the SURF1 gene seems to be an effective method of DNA analysis.

Unlocking Proteomic Heterogeneity in Complex Diseases through Visual Analytics

PubMed Central

Bhavnani, Suresh K.; Dang, Bryant; Bellala, Gowtham; Divekar, Rohit; Visweswaran, Shyam; Brasier, Allan; Kurosky, Alex

2015-01-01

Despite years of preclinical development, biological interventions designed to treat complex diseases like asthma often fail in phase III clinical trials. These failures suggest that current methods to analyze biomedical data might be missing critical aspects of biological complexity such as the assumption that cases and controls come from homogeneous distributions. Here we discuss why and how methods from the rapidly evolving field of visual analytics can help translational teams (consisting of biologists, clinicians, and bioinformaticians) to address the challenge of modeling and inferring heterogeneity in the proteomic and phenotypic profiles of patients with complex diseases. Because a primary goal of visual analytics is to amplify the cognitive capacities of humans for detecting patterns in complex data, we begin with an overview of the cognitive foundations for the field of visual analytics. Next, we organize the primary ways in which a specific form of visual analytics called networks have been used to model and infer biological mechanisms, which help to identify the properties of networks that are particularly useful for the discovery and analysis of proteomic heterogeneity in complex diseases. We describe one such approach called subject-protein networks, and demonstrate its application on two proteomic datasets. This demonstration provides insights to help translational teams overcome theoretical, practical, and pedagogical hurdles for the widespread use of subject-protein networks for analyzing molecular heterogeneities, with the translational goal of designing biomarker-based clinical trials, and accelerating the development of personalized approaches to medicine. PMID:25684269

New PAH gene promoter KLF1 and 3'-region C/EBPalpha motifs influence transcription in vitro.

PubMed

Klaassen, Kristel; Stankovic, Biljana; Kotur, Nikola; Djordjevic, Maja; Zukic, Branka; Nikcevic, Gordana; Ugrin, Milena; Spasovski, Vesna; Srzentic, Sanja; Pavlovic, Sonja; Stojiljkovic, Maja

2017-02-01

Phenylketonuria (PKU) is a metabolic disease caused by mutations in the phenylalanine hydroxylase (PAH) gene. Although the PAH genotype remains the main determinant of PKU phenotype severity, genotype-phenotype inconsistencies have been reported. In this study, we focused on unanalysed sequences in non-coding PAH gene regions to assess their possible influence on the PKU phenotype. We transiently transfected HepG2 cells with various chloramphenicol acetyl transferase (CAT) reporter constructs which included PAH gene non-coding regions. Selected non-coding regions were indicated by in silico prediction to contain transcription factor binding sites. Furthermore, electrophoretic mobility shift assay (EMSA) and supershift assays were performed to identify which transcriptional factors were engaged in the interaction. We found novel KLF1 motif in the PAH promoter, which decreases CAT activity by 50 % in comparison to basal transcription in vitro. The cytosine at the c.-170 promoter position creates an additional binding site for the protein complex involving KLF1 transcription factor. Moreover, we assessed for the first time the role of a multivariant variable number tandem repeat (VNTR) region located in the 3'-region of the PAH gene. We found that the VNTR3, VNTR7 and VNTR8 constructs had approximately 60 % of CAT activity. The regulation is mediated by the C/EBPalpha transcription factor, present in protein complex binding to VNTR3. Our study highlighted two novel promoter KLF1 and 3'-region C/EBPalpha motifs in the PAH gene which decrease transcription in vitro and, thus, could be considered as PAH expression modifiers. New transcription motifs in non-coding regions will contribute to better understanding of the PKU phenotype complexity and may become important for the optimisation of PKU treatment.

Phenotypic variability within the inclusion body spectrum of basophilic inclusion body disease and neuronal intermediate filament inclusion disease in frontotemporal lobar degenerations with FUS-positive inclusions.

PubMed

Gelpi, Ellen; Lladó, Albert; Clarimón, Jordi; Rey, Maria Jesús; Rivera, Rosa Maria; Ezquerra, Mario; Antonell, Anna; Navarro-Otano, Judith; Ribalta, Teresa; Piñol-Ripoll, Gerard; Pérez, Anna; Valldeoriola, Francesc; Ferrer, Isidre

2012-09-01

Basophilic inclusion body disease and neuronal intermediate filament inclusion disease (NIFID) are rare diseases included among frontotemporal lobar degenerations with FUS-positive inclusions (FTLD-FUS). We report clinical and pathologic features of 2 new patients and reevaluate neuropathologic characteristics of 2 previously described cases, including an early-onset case of basophilic inclusion body disease (aged 38 years) with a 5-year disease course and abundant FUS-positive inclusion bodies and 3 NIFID cases. One NIFID case (aged 37 years) presented with early-onset psychiatric disturbances and rapidly progressive cognitive decline. Two NIFID cases had later onset (aged 64 years and 70 years) and complex neurologic deficits. Postmortem neuropathologic studies in late-onset NIFID cases disclosed α-internexin-positive "hyaline conglomerate"-type inclusions that were positive with 1 commercial anti-FUS antibody directed to residues 200 and 250, but these were negative to amino acids 90 and 220 of human FUS. Early-onset NIFID had similar inclusions that were positive with both commercial anti-FUS antibodies. Genetic testing performed on all cases revealed no FUS gene mutations. These findings indicate that phenotypic variability in NIFID, including clinical manifestations and particular neuropathologic findings, may be related to the age at onset and individual differences in the evolution of lesions.

Caenorhabditis elegans as an experimental tool for the study of complex neurological diseases: Parkinson's disease, Alzheimer's disease and autism spectrum disorder.

PubMed

Calahorro, Fernando; Ruiz-Rubio, Manuel

2011-12-01

The nematode Caenorhabditis elegans has a very well-defined and genetically tractable nervous system which offers an effective model to explore basic mechanistic pathways that might be underpin complex human neurological diseases. Here, the role C. elegans is playing in understanding two neurodegenerative conditions, Parkinson's and Alzheimer's disease (AD), and a complex neurological condition, autism, is used as an exemplar of the utility of this model system. C. elegans is an imperfect model of Parkinson's disease because it lacks orthologues of the human disease-related genes PARK1 and LRRK2 which are linked to the autosomal dominant form of this disease. Despite this fact, the nematode is a good model because it allows transgenic expression of these human genes and the study of the impact on dopaminergic neurons in several genetic backgrounds and environmental conditions. For AD, C. elegans has orthologues of the amyloid precursor protein and both human presenilins, PS1 and PS2. In addition, many of the neurotoxic properties linked with Aβ amyloid and tau peptides can be studied in the nematode. Autism spectrum disorder is a complex neurodevelopmental disorder characterised by impairments in human social interaction, difficulties in communication, and restrictive and repetitive behaviours. Establishing C. elegans as a model for this complex behavioural disorder is difficult; however, abnormalities in neuronal synaptic communication are implicated in the aetiology of the disorder. Numerous studies have associated autism with mutations in several genes involved in excitatory and inhibitory synapses in the mammalian brain, including neuroligin, neurexin and shank, for which there are C. elegans orthologues. Thus, several molecular pathways and behavioural phenotypes in C. elegans have been related to autism. In general, the nematode offers a series of advantages that combined with knowledge from other animal models and human research, provides a powerful complementary experimental approach for understanding the molecular mechanisms and underlying aetiology of complex neurological diseases.

Genotypic Complexity of Fisher’s Geometric Model

PubMed Central

Hwang, Sungmin; Park, Su-Chan; Krug, Joachim

2017-01-01

Fisher’s geometric model was originally introduced to argue that complex adaptations must occur in small steps because of pleiotropic constraints. When supplemented with the assumption of additivity of mutational effects on phenotypic traits, it provides a simple mechanism for the emergence of genotypic epistasis from the nonlinear mapping of phenotypes to fitness. Of particular interest is the occurrence of reciprocal sign epistasis, which is a necessary condition for multipeaked genotypic fitness landscapes. Here we compute the probability that a pair of randomly chosen mutations interacts sign epistatically, which is found to decrease with increasing phenotypic dimension n, and varies nonmonotonically with the distance from the phenotypic optimum. We then derive expressions for the mean number of fitness maxima in genotypic landscapes comprised of all combinations of L random mutations. This number increases exponentially with L, and the corresponding growth rate is used as a measure of the complexity of the landscape. The dependence of the complexity on the model parameters is found to be surprisingly rich, and three distinct phases characterized by different landscape structures are identified. Our analysis shows that the phenotypic dimension, which is often referred to as phenotypic complexity, does not generally correlate with the complexity of fitness landscapes and that even organisms with a single phenotypic trait can have complex landscapes. Our results further inform the interpretation of experiments where the parameters of Fisher’s model have been inferred from data, and help to elucidate which features of empirical fitness landscapes can be described by this model. PMID:28450460

Epigenetic Inheritance and Its Role in Evolutionary Biology: Re-Evaluation and New Perspectives

PubMed Central

Burggren, Warren

2016-01-01

Epigenetics increasingly occupies a pivotal position in our understanding of inheritance, natural selection and, perhaps, even evolution. A survey of the PubMed database, however, reveals that the great majority (>93%) of epigenetic papers have an intra-, rather than an inter-generational focus, primarily on mechanisms and disease. Approximately ~1% of epigenetic papers even mention the nexus of epigenetics, natural selection and evolution. Yet, when environments are dynamic (e.g., climate change effects), there may be an “epigenetic advantage” to phenotypic switching by epigenetic inheritance, rather than by gene mutation. An epigenetically-inherited trait can arise simultaneously in many individuals, as opposed to a single individual with a gene mutation. Moreover, a transient epigenetically-modified phenotype can be quickly “sunsetted”, with individuals reverting to the original phenotype. Thus, epigenetic phenotype switching is dynamic and temporary and can help bridge periods of environmental stress. Epigenetic inheritance likely contributes to evolution both directly and indirectly. While there is as yet incomplete evidence of direct permanent incorporation of a complex epigenetic phenotype into the genome, doubtlessly, the presence of epigenetic markers and the phenotypes they create (which may sort quite separately from the genotype within a population) will influence natural selection and, so, drive the collective genotype of a population. PMID:27231949

Single and multiple phenotype QTL analyses of downy mildew resistance in interspecific grapevines.

PubMed

Divilov, Konstantin; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2018-05-01

Downy mildew resistance across days post-inoculation, experiments, and years in two interspecific grapevine F 1 families was investigated using linear mixed models and Bayesian networks, and five new QTL were identified. Breeding grapevines for downy mildew disease resistance has traditionally relied on qualitative gene resistance, which can be overcome by pathogen evolution. Analyzing two interspecific F 1 families, both having ancestry derived from Vitis vinifera and wild North American Vitis species, across 2 years and multiple experiments, we found multiple loci associated with downy mildew sporulation and hypersensitive response in both families using a single phenotype model. The loci explained between 7 and 17% of the variance for either phenotype, suggesting a complex genetic architecture for these traits in the two families studied. For two loci, we used RNA-Seq to detect differentially transcribed genes and found that the candidate genes at these loci were likely not NBS-LRR genes. Additionally, using a multiple phenotype Bayesian network analysis, we found effects between the leaf trichome density, hypersensitive response, and sporulation phenotypes. Moderate-high heritabilities were found for all three phenotypes, suggesting that selection for downy mildew resistance is an achievable goal by breeding for either physical- or non-physical-based resistance mechanisms, with the combination of the two possibly providing durable resistance.

Environmental Sensing of Expert Knowledge in a Computational Evolution System for Complex Problem Solving in Human Genetics

NASA Astrophysics Data System (ADS)

Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.

The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.

Explaining the disease phenotype of intergenic SNP through predicted long range regulation

PubMed Central

Chen, Jingqi; Tian, Weidong

2016-01-01

Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. PMID:27280978

Factors and processes modulating phenotypes in neuronopathic lysosomal storage diseases.

PubMed

Jakóbkiewicz-Banecka, Joanna; Gabig-Cimińska, Magdalena; Banecka-Majkutewicz, Zyta; Banecki, Bogdan; Węgrzyn, Alicja; Węgrzyn, Grzegorz

2014-03-01

Lysosomal storage diseases are inherited metabolic disorders caused by genetic defects causing deficiency of various lysosomal proteins, and resultant accumulation of non-degraded compounds. They are multisystemic diseases, and in most of them (>70%) severe brain dysfunctions are evident. However, expression of various phenotypes in particular diseases is extremely variable, from non-neuronopathic to severely neurodegenerative in the deficiency of the same enzyme. Although all lysosomal storage diseases are monogenic, clear genotype-phenotype correlations occur only in some cases. In this article, we present an overview on various factors and processes, both general and specific for certain disorders, that can significantly modulate expression of phenotypes in these diseases. On the basis of recent reports describing studies on both animal models and clinical data, we propose a hypothesis that efficiency of production of compounds that cannot be degraded due to enzyme deficiency might be especially important in modulation of phenotypes of patients suffering from lysosomal storage diseases.

Gene correction of HAX1 reversed Kostmann disease phenotype in patient-specific induced pluripotent stem cells.

PubMed

Pittermann, Erik; Lachmann, Nico; MacLean, Glenn; Emmrich, Stephan; Ackermann, Mania; Göhring, Gudrun; Schlegelberger, Brigitte; Welte, Karl; Schambach, Axel; Heckl, Dirk; Orkin, Stuart H; Cantz, Tobias; Klusmann, Jan-Henning

2017-06-13

Severe congenital neutropenia (SCN, Kostmann disease) is a heritable disorder characterized by a granulocytic maturation arrest. Biallelic mutations in HCLS1 associated protein X-1 ( HAX1 ) are frequently detected in affected individuals, including those of the original pedigree described by Kostmann in 1956. To date, no faithful animal model has been established to study SCN mediated by HAX1 deficiency. Here we demonstrate defective neutrophilic differentiation and compensatory monocyte overproduction from patient-derived induced pluripotent stem cells (iPSCs) carrying the homozygous HAX1 W44X nonsense mutation. Targeted correction of the HAX1 mutation using the CRISPR-Cas9 system and homologous recombination rescued neutrophil differentiation and reestablished an HAX1 and HCLS1 -centered transcription network in immature myeloid progenitors, which is involved in the regulation of apoptosis, apoptotic mitochondrial changes, and myeloid differentiation. These findings made in isogenic iPSC-derived myeloid cells highlight the complex transcriptional changes underlying Kostmann disease. Thus, we show that patient-derived HAX1 W44X -iPSCs recapitulate the Kostmann disease phenotype in vitro and confirm HAX1 mutations as the disease-causing monogenic lesion. Finally, our study paves the way for nonvirus-based gene therapy approaches in SCN.

Regression and Data Mining Methods for Analyses of Multiple Rare Variants in the Genetic Analysis Workshop 17 Mini-Exome Data

PubMed Central

Bailey-Wilson, Joan E.; Brennan, Jennifer S.; Bull, Shelley B; Culverhouse, Robert; Kim, Yoonhee; Jiang, Yuan; Jung, Jeesun; Li, Qing; Lamina, Claudia; Liu, Ying; Mägi, Reedik; Niu, Yue S.; Simpson, Claire L.; Wang, Libo; Yilmaz, Yildiz E.; Zhang, Heping; Zhang, Zhaogong

2012-01-01

Group 14 of Genetic Analysis Workshop 17 examined several issues related to analysis of complex traits using DNA sequence data. These issues included novel methods for analyzing rare genetic variants in an aggregated manner (often termed collapsing rare variants), evaluation of various study designs to increase power to detect effects of rare variants, and the use of machine learning approaches to model highly complex heterogeneous traits. Various published and novel methods for analyzing traits with extreme locus and allelic heterogeneity were applied to the simulated quantitative and disease phenotypes. Overall, we conclude that power is (as expected) dependent on locus-specific heritability or contribution to disease risk, large samples will be required to detect rare causal variants with small effect sizes, extreme phenotype sampling designs may increase power for smaller laboratory costs, methods that allow joint analysis of multiple variants per gene or pathway are more powerful in general than analyses of individual rare variants, population-specific analyses can be optimal when different subpopulations harbor private causal mutations, and machine learning methods may be useful for selecting subsets of predictors for follow-up in the presence of extreme locus heterogeneity and large numbers of potential predictors. PMID:22128066

XERODERMA PIGMENTOSUM, TRICHOTHIODYSTROPHY AND COCKAYNE SYNDROME: A COMPLEX GENOTYPE-PHENOTYPE RELATIONSHIP

PubMed Central

Kraemer, Kenneth H.; Patronas, Nicholas J.; Schiffmann, Raphael; Brooks, Brian P.; Tamura, Deborah; DiGiovanna, John J.

2008-01-01

Patients with the rare genetic disorders, xeroderma pigmentosum (XP), trichothiodystrophy (TTD) and Cockayne syndrome (CS) have defects in DNA nucleotide excision repair (NER). The NER pathway involves at least 28 genes. Three NER genes are also part of the basal transcription factor, TFIIH. Mutations in 11 NER genes have been associated with clinical diseases with at least 8 overlapping phenotypes. The clinical features of these patients have some similarities and but also have marked differences. NER is involved in protection against sunlight induced DNA damage. While XP patients have 1000-fold increase in susceptibility to skin cancer, TTD and CS patients have normal skin cancer risk. Several of the genes involved in NER also affect somatic growth and development. Some patients have short stature and immature sexual development. TTD patients have sulfur deficient brittle hair. Progressive sensorineural deafness is an early feature of XP and CS. Many of these clinical diseases are associated with developmental delay and progressive neurological degeneration. The main neuropathology of XP is a primary neuronal degeneration. In contrast, CS and TTD patients have reduced myelination of the brain. These complex neurological abnormalities are not related to sunlight exposure but may be caused by developmental defects as well as faulty repair of DNA damage to neuronal cells induced by oxidative metabolism or other endogenous processes. PMID:17276014

Phenome-driven disease genetics prediction toward drug discovery

PubMed Central

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-01-01

Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp.case.edu/public/data/DMN Contact: rxx@case.edu PMID:26072493

Integrative genetic risk prediction using non-parametric empirical Bayes classification.

PubMed

Zhao, Sihai Dave

2017-06-01

Genetic risk prediction is an important component of individualized medicine, but prediction accuracies remain low for many complex diseases. A fundamental limitation is the sample sizes of the studies on which the prediction algorithms are trained. One way to increase the effective sample size is to integrate information from previously existing studies. However, it can be difficult to find existing data that examine the target disease of interest, especially if that disease is rare or poorly studied. Furthermore, individual-level genotype data from these auxiliary studies are typically difficult to obtain. This article proposes a new approach to integrative genetic risk prediction of complex diseases with binary phenotypes. It accommodates possible heterogeneity in the genetic etiologies of the target and auxiliary diseases using a tuning parameter-free non-parametric empirical Bayes procedure, and can be trained using only auxiliary summary statistics. Simulation studies show that the proposed method can provide superior predictive accuracy relative to non-integrative as well as integrative classifiers. The method is applied to a recent study of pediatric autoimmune diseases, where it substantially reduces prediction error for certain target/auxiliary disease combinations. The proposed method is implemented in the R package ssa. © 2016, The International Biometric Society.

Phenotype at diagnosis predicts recurrence rates in Crohn's disease.

PubMed

Wolters, F L; Russel, M G; Sijbrandij, J; Ambergen, T; Odes, S; Riis, L; Langholz, E; Politi, P; Qasim, A; Koutroubakis, I; Tsianos, E; Vermeire, S; Freitas, J; van Zeijl, G; Hoie, O; Bernklev, T; Beltrami, M; Rodriguez, D; Stockbrügger, R W; Moum, B

2006-08-01

In Crohn's disease (CD), studies associating phenotype at diagnosis and subsequent disease activity are important for patient counselling and health care planning. To calculate disease recurrence rates and to correlate these with phenotypic traits at diagnosis. A prospectively assembled uniformly diagnosed European population based inception cohort of CD patients was classified according to the Vienna classification for disease phenotype at diagnosis. Surgical and non-surgical recurrence rates throughout a 10 year follow up period were calculated. Multivariate analysis was performed to classify risk factors present at diagnosis for recurrent disease. A total of 358 were classified for phenotype at diagnosis, of whom 262 (73.2%) had a first recurrence and 113 patients (31.6%) a first surgical recurrence during the first 10 years after diagnosis. Patients with upper gastrointestinal disease at diagnosis had an excess risk of recurrence (hazard ratio 1.54 (95% confidence interval (CI) 1.13-2.10)) whereas age >/=40 years at diagnosis was protective (hazard ratio 0.82 (95% CI 0.70-0.97)). Colonic disease was a protective characteristic for resective surgery (hazard ratio 0.38 (95% CI 0.21-0.69)). More frequent resective surgical recurrences were reported from Copenhagen (hazard ratio 3.23 (95% CI 1.32-7.89)). A mild course of disease in terms of disease recurrence was observed in this European cohort. Phenotype at diagnosis had predictive value for disease recurrence with upper gastrointestinal disease being the most important positive predictor. A phenotypic North-South gradient in CD may be present, illustrated by higher surgery risks in some of the Northern European centres.

Tissue damage drives co-localization of NF-κB, Smad3, and Nrf2 to direct Rev-erb sensitive wound repair in mouse macrophages

PubMed Central

Eichenfield, Dawn Z; Troutman, Ty Dale; Link, Verena M; Lam, Michael T; Cho, Han; Gosselin, David; Spann, Nathanael J; Lesch, Hanna P; Tao, Jenhan; Muto, Jun; Gallo, Richard L; Evans, Ronald M; Glass, Christopher K

2016-01-01

Although macrophages can be polarized to distinct phenotypes in vitro with individual ligands, in vivo they encounter multiple signals that control their varied functions in homeostasis, immunity, and disease. Here, we identify roles of Rev-erb nuclear receptors in regulating responses of mouse macrophages to complex tissue damage signals and wound repair. Rather than reinforcing a specific program of macrophage polarization, Rev-erbs repress subsets of genes that are activated by TLR ligands, IL4, TGFβ, and damage-associated molecular patterns (DAMPS). Unexpectedly, a complex damage signal promotes co-localization of NF-κB, Smad3, and Nrf2 at Rev-erb-sensitive enhancers and drives expression of genes characteristic of multiple polarization states in the same cells. Rev-erb-sensitive enhancers thereby integrate multiple damage-activated signaling pathways to promote a wound repair phenotype. DOI: http://dx.doi.org/10.7554/eLife.13024.001 PMID:27462873

An integrative, translational approach to understanding rare and orphan genetically based diseases

PubMed Central

Hoehndorf, Robert; Schofield, Paul N.; Gkoutos, Georgios V.

2013-01-01

PhenomeNet is an approach for integrating phenotypes across species and identifying candidate genes for genetic diseases based on the similarity between a disease and animal model phenotypes. In contrast to ‘guilt-by-association’ approaches, PhenomeNet relies exclusively on the comparison of phenotypes to suggest candidate genes, and can, therefore, be applied to study the molecular basis of rare and orphan diseases for which the molecular basis is unknown. In addition to disease phenotypes from the Online Mendelian Inheritance in Man (OMIM) database, we have now integrated the clinical signs from Orphanet into PhenomeNet. We demonstrate that our approach can efficiently identify known candidate genes for genetic diseases in Orphanet and OMIM. Furthermore, we find evidence that mutations in the HIP1 gene might cause Bassoe syndrome, a rare disorder with unknown genetic aetiology. Our results demonstrate that integration and computational analysis of human disease and animal model phenotypes using PhenomeNet has the potential to reveal novel insights into the pathobiology underlying genetic diseases. PMID:23853703

Parent-of-origin effects on schizophrenia-relevant behaviours of type III neuregulin 1 mutant mice.

PubMed

Shang, Kani; Talmage, David A; Karl, Tim

2017-08-14

A robust, disease-relevant phenotype is paramount to the validity of genetic mouse models, which are an important tool in understanding complex diseases. Recent evidence from genome-wide association studies suggests the genetic contribution of parents to offspring is not equivalent. Despite this, few studies to date have examined the potential impact of parent genotype (i.e. origin of mutation) on the offspring of disease-relevant genetic mouse models. To elucidate the potential impact of the sex of the mutant parent on offspring phenotype, we characterized male and female offspring of an established schizophrenia mouse model, which had been generated using two different breeding schemes, in a range of disease-relevant behaviours. We compared heterozygous type III neuregulin 1 mutant (type III Nrg1 +/- ) and wild type-like control (WT) offspring from mutant father x WT mother pairings with offspring from mutant mother x WT father pairings. Offspring were tested in schizophrenia-relevant paradigms including the elevated plus maze (EPM), fear conditioning (FC), prepulse inhibition (PPI), social interaction (SI), and open field (OF). We found type III Nrg1 +/- males from mutant fathers, but not mutant mothers, showed deficits in contextual fear-associated memory and exhibited increased social interaction, compared to their WT littermates. Type III Nrg1 +/- females across breeding colonies only exhibited a subtle change to their acoustic startle response and sensorimotor gating. These results suggest a paternal-dependent transmission of genetically induced behavioural characteristics. Though the mechanisms governing this phenomenon are unclear, our results show that parental origin of mutation can alter the behavioural phenotype of genetic mouse models. Thus, researchers should carefully consider their breeding scheme when dealing with genetic mouse models of diseases such as schizophrenia. Copyright © 2017. Published by Elsevier B.V.

Mechanisms of the Development of Allergy (MeDALL): Introducing novel concepts in allergy phenotypes.

PubMed

Anto, Josep M; Bousquet, Jean; Akdis, Mubeccel; Auffray, Charles; Keil, Thomas; Momas, Isabelle; Postma, Dirkje S; Valenta, Rudolf; Wickman, Magnus; Cambon-Thomsen, Anne; Haahtela, Tari; Lambrecht, Bart N; Lodrup Carlsen, Karin C; Koppelman, Gerard H; Sunyer, Jordi; Zuberbier, Torsten; Annesi-Maesano, Isabelle; Arno, Albert; Bindslev-Jensen, Carsten; De Carlo, Giuseppe; Forastiere, Francesco; Heinrich, Joachim; Kowalski, Marek L; Maier, Dieter; Melén, Erik; Smit, Henriette A; Standl, Marie; Wright, John; Asarnoj, Anna; Benet, Marta; Ballardini, Natalia; Garcia-Aymerich, Judith; Gehring, Ulrike; Guerra, Stefano; Hohmann, Cynthia; Kull, Inger; Lupinek, Christian; Pinart, Mariona; Skrindo, Ingebjorg; Westman, Marit; Smagghe, Delphine; Akdis, Cezmi; Andersson, Niklas; Bachert, Claus; Ballereau, Stephane; Ballester, Ferran; Basagana, Xavier; Bedbrook, Anna; Bergstrom, Anna; von Berg, Andrea; Brunekreef, Bert; Burte, Emilie; Carlsen, Kai-Hakon; Chatzi, Leda; Coquet, Jonathan M; Curin, Mirela; Demoly, Pascal; Eller, Esben; Fantini, Maria Pia; von Hertzen, Leena; Hovland, Vergard; Jacquemin, Benedicte; Just, Jocelyne; Keller, Theresa; Kiss, Renata; Kogevinas, Manolis; Koletzko, Sibylle; Lau, Susanne; Lehmann, Irina; Lemonnier, Nicolas; Mäkelä, Mika; Mestres, Jordi; Mowinckel, Peter; Nadif, Rachel; Nawijn, Martijn C; Pellet, Johan; Pin, Isabelle; Porta, Daniela; Rancière, Fanny; Rial-Sebbag, Emmanuelle; Saeys, Yvan; Schuijs, Martijn J; Siroux, Valerie; Tischer, Christina G; Torrent, Mathies; Varraso, Raphaelle; Wenzel, Kalus; Xu, Cheng-Jian

2017-02-01

Asthma, rhinitis, and eczema are complex diseases with multiple genetic and environmental factors interlinked through IgE-associated and non-IgE-associated mechanisms. Mechanisms of the Development of ALLergy (MeDALL; EU FP7-CP-IP; project no: 261357; 2010-2015) studied the complex links of allergic diseases at the clinical and mechanistic levels by linking epidemiologic, clinical, and mechanistic research, including in vivo and in vitro models. MeDALL integrated 14 European birth cohorts, including 44,010 participants and 160 cohort follow-ups between pregnancy and age 20 years. Thirteen thousand children were prospectively followed after puberty by using a newly standardized MeDALL Core Questionnaire. A microarray developed for allergen molecules with increased IgE sensitivity was obtained for 3,292 children. Estimates of air pollution exposure from previous studies were available for 10,000 children. Omics data included those from historical genome-wide association studies (23,000 children) and DNA methylation (2,173), targeted multiplex biomarker (1,427), and transcriptomic (723) studies. Using classical epidemiology and machine-learning methods in 16,147 children aged 4 years and 11,080 children aged 8 years, MeDALL showed the multimorbidity of eczema, rhinitis, and asthma and estimated that only 38% of multimorbidity was attributable to IgE sensitization. MeDALL has proposed a new vision of multimorbidity independent of IgE sensitization, and has shown that monosensitization and polysensitization represent 2 distinct phenotypes. The translational component of MeDALL is shown by the identification of a novel allergic phenotype characterized by polysensitization and multimorbidity, which is associated with the frequency, persistence, and severity of allergic symptoms. The results of MeDALL will help integrate personalized, predictive, preventative, and participatory approaches in allergic diseases. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Autosomal recessive Charcot-Marie-Tooth neuropathy.

PubMed

Espinós, Carmen; Calpena, Eduardo; Martínez-Rubio, Dolores; Lupo, Vincenzo

2012-01-01

Charcot-Marie-Tooth (CMT) disease, a hereditary motor and sensory neuropathy that comprises a complex group of more than 50 diseases, is the most common inherited neuropathy. CMT is generally divided into demyelinating forms, axonal forms and intermediate forms. CMT is also characterized by a wide genetic heterogeneity with 29 genes and more than 30 loci involved. The most common pattern of inheritance is autosomal dominant (AD), although autosomal recessive (AR) forms are more frequent in Mediterranean countries. In this chapter we give an overview of the associated genes, mechanisms and epidemiology of AR-CMT forms and their associated phenotypes.

Arrhythmogenic right ventricular cardiomyopathy in Boxer dogs: the diagnosis as a link to the human disease

PubMed Central

VISCHER, ANNINA S.; CONNOLLY, DAVID J.; COATS, CAROLINE J.; FUENTES, VIRGINIA LUIS; MCKENNA, WILLIAM J.; CASTELLETTI, SILVIA; PANTAZIS, ANTONIOS A.

2017-01-01

Background Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a myocardial disease with an increased risk for ventricular arrhythmias. The condition, which occurs in Boxer dogs, shares phenotypic features with the human disease arrhythmogenic cardiomyopathy (ACM) suggesting its potential as a natural animal model. However, there are currently no universally accepted clinical criteria to diagnose ARVC in Boxer dogs. We aimed to identify diagnostic criteria for ARVC in Boxer dogs defining a more uniform and consistent phenotype. Methods and Results Clinical records from 264 Boxer dogs from a referral veterinary hospital were retrospectively analysed. ARVC was initially diagnosed according to the number of ventricular premature complexes (VPCs) in the 24-hour-Holter-ECG in the absence of another obvious cause. Dogs diagnosed this way had more VPCs, polymorphic VPCs, couplets, triplets, VTs and R-on-T-phenomenon and syncope, decreased right ventricular function and dilatation in comparison to a control group of all other Boxer dogs seen by the Cardiology Service over the same period. Presence of couplets and R-on-T-phenomenon on a 24h-ECG were identified as independent predictors of the diagnosis. A diagnosis based on ≥100 VPCs in 24 hours, presence of couplets and R-on-T phenomenon on a 24h-ECG was able to select Boxer dogs with a phenotype most similar to human ACM. Conclusion We suggest the diagnosis of ARVC in Boxer dogs requires two out of the three following criteria: presence of ≥ 100 VPCs, presence of couplets or R-on-T-phenomenon on a 24 h-ECG. This results in a uniform phenotype similar to that described in human ACM and may result in the adoption of the term ACM for this analogous condition in Boxer dogs. PMID:29774304

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.

Evolutionary perspectives on wildlife disease: concepts and applications

PubMed Central

Vander Wal, Eric; Garant, Dany; Pelletier, Fanie

2014-01-01

Wildlife disease has the potential to cause significant ecological, socioeconomic, and health impacts. As a result, all tools available need to be employed when host–pathogen dynamics merit conservation or management interventions. Evolutionary principles, such as evolutionary history, phenotypic and genetic variation, and selection, have the potential to unravel many of the complex ecological realities of infectious disease in the wild. Despite this, their application to wildlife disease ecology and management remains in its infancy. In this article, we outline the impetus behind applying evolutionary principles to disease ecology and management issues in the wild. We then introduce articles from this special issue on Evolutionary Perspectives on Wildlife Disease: Concepts and Applications, outlining how each is exemplar of a practical wildlife disease challenge that can be enlightened by applied evolution. Ultimately, we aim to bring new insights to wildlife disease ecology and its management using tools and techniques commonly employed in evolutionary ecology. PMID:25469154

Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits*

PubMed Central

Sharma, Amitabh; Gulbahce, Natali; Pevzner, Samuel J.; Menche, Jörg; Ladenvall, Claes; Folkersen, Lasse; Eriksson, Per; Orho-Melander, Marju; Barabási, Albert-László

2013-01-01

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits. We apply a prediction pipeline incorporating interactome, co-expression, and comorbidity data to Global Lipids Genetics Consortium (GLGC) GWAS for four traits of interest, identifying phenotypically coherent modules. These modules provide insights regarding gene involvement in complex phenotypes with multiple susceptibility alleles and low effect sizes. To experimentally test our predictions, we selected four candidate genes and genotyped representative SNPs in the Malmö Diet and Cancer Cardiovascular Cohort. We found significant associations with LDL-C and total-cholesterol levels for a synonymous SNP (rs234706) in the cystathionine beta-synthase (CBS) gene (p = 1 × 10−5 and adjusted-p = 0.013, respectively). Further, liver samples taken from 206 patients revealed that patients with the minor allele of rs234706 had significant dysregulation of CBS (p = 0.04). Despite the known biological role of CBS in lipid metabolism, SNPs within the locus have not yet been identified in GWAS of lipoprotein traits. Thus, the GWAS-based Comorbidity Module (GCM) approach identifies candidate genes missed by GWAS studies, serving as a broadly applicable tool for the investigation of other complex disease phenotypes. PMID:23882023

Mouse models of ageing and their relevance to disease.

PubMed

Kõks, Sulev; Dogan, Soner; Tuna, Bilge Guvenc; González-Navarro, Herminia; Potter, Paul; Vandenbroucke, Roosmarijn E

2016-12-01

Ageing is a process that gradually increases the organism's vulnerability to death. It affects different biological pathways, and the underlying cellular mechanisms are complex. In view of the growing disease burden of ageing populations, increasing efforts are being invested in understanding the pathways and mechanisms of ageing. We review some mouse models commonly used in studies on ageing, highlight the advantages and disadvantages of the different strategies, and discuss their relevance to disease susceptibility. In addition to addressing the genetics and phenotypic analysis of mice, we discuss examples of models of delayed or accelerated ageing and their modulation by caloric restriction. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Cattle trypanosomosis: the diversity of trypanosomes and implications for disease epidemiology and control.

PubMed

Auty, H; Torr, S J; Michoel, T; Jayaraman, S; Morrison, L J

2015-08-01

Trypanosomosis is one of the most significant infectious threats to cattle in sub-Saharan Africa, and one form has also spread to Asia and South America. The disease is caused by a complex of trypanosome species, and the species and strain of parasite can have a profound influence upon the epidemiology of the host-parasite-vector relationships, the severity and course of infection, and, consequently, the implementation and development of control methods. This review will summarise our current knowledge of the relationship between trypanosome species/genotype and the phenotype of disease in cattle, and the implications that this has for ongoing efforts to develop diagnostics, drugs and vaccines for the control of cattle trypanosomosis.

Impact of age on markers of HIV-1 disease

PubMed Central

Pirrone, Vanessa; Libon, David J; Sell, Christian; Lerner, Chad A; Nonnemacher, Michael R; Wigdahl, Brian

2013-01-01

Aging is a complicated process characterized by a progressive loss of homeostasis, which results in an increased vulnerability to multiple diseases. HIV-1-infected patients demonstrate a premature aging phenotype and develop certain age-related diseases earlier in their lifespan than what is seen in the general population. Age-related comorbidities may include the development of bone disease, metabolic disorders, neurologic impairment and immunosenescence. Age also appears to have an effect on traditional markers of HIV-1 disease progression, including CD4+ T-cell count and viral load. These effects are not only a consequence of HIV-1 infection, but in many cases, are also linked to antiretroviral therapy. This review summarizes the complex interplay between HIV-1 infection and aging, and the impact that aging has on markers of HIV-1 disease. PMID:23596462

Phenotypic spectrum associated with mutations of the mitochondrial polymerase gamma gene.

PubMed

Horvath, Rita; Hudson, Gavin; Ferrari, Gianfrancesco; Fütterer, Nancy; Ahola, Sofia; Lamantea, Eleonora; Prokisch, Holger; Lochmüller, Hanns; McFarland, Robert; Ramesh, V; Klopstock, Thomas; Freisinger, Peter; Salvi, Fabrizio; Mayr, Johannes A; Santer, Rene; Tesarova, Marketa; Zeman, Jiri; Udd, Bjarne; Taylor, Robert W; Turnbull, Douglass; Hanna, Michael; Fialho, Doreen; Suomalainen, Anu; Zeviani, Massimo; Chinnery, Patrick F

2006-07-01

Mutations in the gene coding for the catalytic subunit of the mitochondrial DNA (mtDNA) polymerase gamma (POLG1) have recently been described in patients with diverse clinical presentations, revealing a complex relationship between genotype and phenotype in patients and their families. POLG1 was sequenced in patients from different European diagnostic and research centres to define the phenotypic spectrum and advance understanding of the recurrence risks. Mutations were identified in 38 cases, with the majority being sporadic compound heterozygotes. Eighty-nine DNA sequence changes were identified, including 2 predicted to alter a splice site, 1 predicted to cause a premature stop codon and 13 predicted to cause novel amino acid substitutions. The majority of children had a mutation in the linker region, often 1399G-->A (A467T), and a mutation affecting the polymerase domain. Others had mutations throughout the gene, and 11 had 3 or more substitutions. The clinical presentation ranged from the neonatal period to late adult life, with an overlapping phenotypic spectrum from severe encephalopathy and liver failure to late-onset external ophthalmoplegia, ataxia, myopathy and isolated muscle pain or epilepsy. There was a strong gender bias in children, with evidence of an environmental interaction with sodium valproate. POLG1 mutations cause an overlapping clinical spectrum of disease with both dominant and recessive modes of inheritance. 1399G-->A (A467T) is common in children, but complete POLG1 sequencing is required to identify multiple mutations that can have complex implications for genetic counselling.

NIH Mouse Metabolic Phenotyping Centers: the power of centralized phenotyping.

PubMed

Laughlin, Maren R; Lloyd, K C Kent; Cline, Gary W; Wasserman, David H

2012-10-01

The Mouse Metabolic Phenotyping Centers (MMPCs) were founded in 2001 by the National Institutes of Health (NIH) to advance biomedical research by providing the scientific community with standardized, high-quality phenotyping services for mouse models of diabetes, obesity, and their complications. The intent is to allow researchers to take optimum advantage of the many new mouse models produced in labs and in high-throughput public efforts. The six MMPCs are located at universities around the country and perform complex metabolic tests in intact mice and hormone and analyte assays in tissues on a fee-for-service basis. Testing is subsidized by the NIH in order to reduce the barriers for mouse researchers. Although data derived from these tests belong to the researcher submitting mice or tissues, these data are archived after publication in a public database run by the MMPC Coordinating and Bioinformatics Unit. It is hoped that data from experiments performed in many mouse models of metabolic diseases, using standard protocols, will be useful in understanding the nature of these complex disorders. The current areas of expertise include energy balance and body composition, insulin action and secretion, whole-body and tissue carbohydrate and lipid metabolism, cardiovascular and renal function, and metabolic pathway kinetics. In addition to providing services, the MMPC staff provides expertise and advice to researchers, and works to develop and refine test protocols to best meet the community's needs in light of current scientific developments. Test technology is disseminated by publications and through annual courses.

Contemporary genetic testing in inherited cardiac disease: tools, ethical issues, and clinical applications.

PubMed

Girolami, Francesca; Frisso, Giulia; Benelli, Matteo; Crotti, Lia; Iascone, Maria; Mango, Ruggiero; Mazzaccara, Cristina; Pilichou, Kalliope; Arbustini, Eloisa; Tomberli, Benedetta; Limongelli, Giuseppe; Basso, Cristina; Olivotto, Iacopo

2018-01-01

: Inherited cardiac diseases comprise a wide and heterogeneous spectrum of diseases of the heart, including the cardiomyopathies and the arrhythmic diseases in structurally normal hearts, that is, channelopathies. With a combined estimated prevalence of 3% in the general population, these conditions represent a relevant epidemiological entity worldwide, and are a major cause of cardiac morbidity and mortality in the young. The extraordinary progress achieved in molecular genetics over the last three decades has unveiled the complex molecular basis of many familial cardiac conditions, paving the way for routine use of gene testing in clinical practice. In current practice, genetic testing can be used in a clinically affected patient to confirm diagnosis, or to formulate a differential diagnosis among overlapping phenotypes or between hereditary and acquired (nongenetic) forms of disease. Although genotype-phenotype correlations are generally unpredictable, a precise molecular diagnosis can help predict prognosis in specific patient subsets and may guide management. In clinically unaffected relatives, genetic cascade testing is recommended, after the initial identification of a pathogenic variation, with the aim of identifying asymptomatic relatives who might be at risk of disease-related complications, including unexpected sudden cardiac death. Future implications include the identification of novel therapeutic targets and development of tailored treatments including gene therapy. This document reflects the multidisciplinary, 'real-world' experience required when implementing genetic testing in cardiomyopathies and arrhythmic syndromes, along the recommendations of various guidelines.

Contemporary genetic testing in inherited cardiac disease: tools, ethical issues, and clinical applications

PubMed Central

Girolami, Francesca; Frisso, Giulia; Benelli, Matteo; Crotti, Lia; Iascone, Maria; Mango, Ruggiero; Mazzaccara, Cristina; Pilichou, Kalliope; Arbustini, Eloisa; Tomberli, Benedetta; Limongelli, Giuseppe; Basso, Cristina; Olivotto, Iacopo

2018-01-01

Inherited cardiac diseases comprise a wide and heterogeneous spectrum of diseases of the heart, including the cardiomyopathies and the arrhythmic diseases in structurally normal hearts, that is, channelopathies. With a combined estimated prevalence of 3% in the general population, these conditions represent a relevant epidemiological entity worldwide, and are a major cause of cardiac morbidity and mortality in the young. The extraordinary progress achieved in molecular genetics over the last three decades has unveiled the complex molecular basis of many familial cardiac conditions, paving the way for routine use of gene testing in clinical practice. In current practice, genetic testing can be used in a clinically affected patient to confirm diagnosis, or to formulate a differential diagnosis among overlapping phenotypes or between hereditary and acquired (nongenetic) forms of disease. Although genotype–phenotype correlations are generally unpredictable, a precise molecular diagnosis can help predict prognosis in specific patient subsets and may guide management. In clinically unaffected relatives, genetic cascade testing is recommended, after the initial identification of a pathogenic variation, with the aim of identifying asymptomatic relatives who might be at risk of disease-related complications, including unexpected sudden cardiac death. Future implications include the identification of novel therapeutic targets and development of tailored treatments including gene therapy. This document reflects the multidisciplinary, ‘real-world’ experience required when implementing genetic testing in cardiomyopathies and arrhythmic syndromes, along the recommendations of various guidelines. PMID:29176389

Next generation phenotyping using narrative reports in a rare disease clinical data warehouse.

PubMed

Garcelon, Nicolas; Neuraz, Antoine; Salomon, Rémi; Bahi-Buisson, Nadia; Amiel, Jeanne; Picard, Capucine; Mahlaoui, Nizar; Benoit, Vincent; Burgun, Anita; Rance, Bastien

2018-05-31

Secondary use of data collected in Electronic Health Records opens perspectives for increasing our knowledge of rare diseases. The clinical data warehouse (named Dr. Warehouse) at the Necker-Enfants Malades Children's Hospital contains data collected during normal care for thousands of patients. Dr. Warehouse is oriented toward the exploration of clinical narratives. In this study, we present our method to find phenotypes associated with diseases of interest. We leveraged the frequency and TF-IDF to explore the association between clinical phenotypes and rare diseases. We applied our method in six use cases: phenotypes associated with the Rett, Lowe, Silver Russell, Bardet-Biedl syndromes, DOCK8 deficiency and Activated PI3-kinase Delta Syndrome (APDS). We asked domain experts to evaluate the relevance of the top-50 (for frequency and TF-IDF) phenotypes identified by Dr. Warehouse and computed the average precision and mean average precision. Experts concluded that between 16 and 39 phenotypes could be considered as relevant in the top-50 phenotypes ranked by descending frequency discovered by Dr. Warehouse (resp. between 11 and 41 for TF-IDF). Average precision ranges from 0.55 to 0.91 for frequency and 0.52 to 0.95 for TF-IDF. Mean average precision was 0.79. Our study suggests that phenotypes identified in clinical narratives stored in Electronic Health Record can provide rare disease specialists with candidate phenotypes that can be used in addition to the literature. Clinical Data Warehouses can be used to perform Next Generation Phenotyping, especially in the context of rare diseases. We have developed a method to detect phenotypes associated with a group of patients using medical concepts extracted from free-text clinical narratives.

Explaining the disease phenotype of intergenic SNP through predicted long range regulation.

PubMed

Chen, Jingqi; Tian, Weidong

2016-10-14

Thousands of disease-associated SNPs (daSNPs) are located in intergenic regions (IGR), making it difficult to understand their association with disease phenotypes. Recent analysis found that non-coding daSNPs were frequently located in or approximate to regulatory elements, inspiring us to try to explain the disease phenotypes of IGR daSNPs through nearby regulatory sequences. Hence, after locating the nearest distal regulatory element (DRE) to a given IGR daSNP, we applied a computational method named INTREPID to predict the target genes regulated by the DRE, and then investigated their functional relevance to the IGR daSNP's disease phenotypes. 36.8% of all IGR daSNP-disease phenotype associations investigated were possibly explainable through the predicted target genes, which were enriched with, were functionally relevant to, or consisted of the corresponding disease genes. This proportion could be further increased to 60.5% if the LD SNPs of daSNPs were also considered. Furthermore, the predicted SNP-target gene pairs were enriched with known eQTL/mQTL SNP-gene relationships. Overall, it's likely that IGR daSNPs may contribute to disease phenotypes by interfering with the regulatory function of their nearby DREs and causing abnormal expression of disease genes. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Prediction of gene-phenotype associations in humans, mice, and plants using phenologs.

PubMed

Woods, John O; Singh-Blom, Ulf Martin; Laurent, Jon M; McGary, Kriston L; Marcotte, Edward M

2013-06-21

Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such "orthologous phenotypes," or "phenologs," are examples of deep homology, and may be used to predict additional candidate disease genes. In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data--from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans--establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e.g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene-phenotype associations, as for the Arabidopsis response to vernalization phenotype. We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species.

Application of Genetic/Genomic Approaches to Allergic Disorders

PubMed Central

Baye, Tesfaye M.; Martin, Lisa J.; Khurana Hershey, Gurjit K.

2010-01-01

Completion of the human genome project and rapid progress in genetics and bioinformatics have enabled the development of large public databases, which include genetic and genomic data linked to clinical health data. With the massive amount of information available, clinicians and researchers have the unique opportunity to complement and integrate their daily practice with the existing resources to clarify the underlying etiology of complex phenotypes such as allergic diseases. The genome itself is now often utilized as a starting point for many studies and multiple innovative approaches have emerged applying genetic/genomic strategies to key questions in the field of allergy and immunology. There have been several successes, which have uncovered new insights into the biologic underpinnings of allergic disorders. Herein, we will provide an in depth review of genomic approaches to identifying genes and biologic networks involved in allergic diseases. We will discuss genetic and phenotypic variation, statistical approaches for gene discovery, public databases, functional genomics, clinical implications, and the challenges that remain. PMID:20638111

The FBXO7 homologue nutcracker and binding partner PI31 in Drosophila melanogaster models of Parkinson's disease.

PubMed

Merzetti, Eric M; Dolomount, Lindsay A; Staveley, Brian E

2017-01-01

Parkinsonian-pyramidal syndrome (PPS) is an early onset form of Parkinson's disease (PD) that shows degeneration of the extrapyramidal region of the brain to result in a severe form of PD. The toxic protein build-up has been implicated in the onset of PPS. Protein removal is mediated by an intracellular proteasome complex: an E3 ubiquitin ligase, the targeting component, is essential for function. FBXO7 encodes the F-box component of the SCF E3 ubiquitin ligase linked to familial forms of PPS. The Drosophila melanogaster homologue nutcracker (ntc) and a binding partner, PI31, have been shown to be active in proteasome function. We show that altered expression of either ntc or PI31 in dopaminergic neurons leads to a decrease in longevity and locomotor ability, phenotypes both associated with models of PD. Furthermore, expression of ntc-RNAi in an established α-synuclein-dependent model of PD rescues the phenotypes of diminished longevity and locomotor control.

Psoriasiform skin disease in transgenic pigs with high-copy ectopic expression of human integrins α2 and β1

PubMed Central

Staunstrup, Nicklas Heine; Stenderup, Karin; Mortensen, Sidsel; Primo, Maria Nascimento; Steiniche, Torben; Liu, Ying; Li, Rong; Schmidt, Mette; Purup, Stig; Dagnæs-Hansen, Frederik; Schrøder, Lisbeth Dahl; Svensson, Lars; Petersen, Thomas Kongstad; Callesen, Henrik; Bolund, Lars

2017-01-01

ABSTRACT Psoriasis is a complex human-specific disease characterized by perturbed keratinocyte proliferation and a pro-inflammatory environment in the skin. Porcine skin architecture and immunity are very similar to that in humans, rendering the pig a suitable animal model for studying the biology and treatment of psoriasis. Expression of integrins, which is normally confined to the basal layer of the epidermis, is maintained in suprabasal keratinocytes in psoriatic skin, modulating proliferation and differentiation as well as leukocyte infiltration. Here, we generated minipigs co-expressing integrins α2 and β1 in suprabasal epidermal layers. Integrin-transgenic minipigs born into the project displayed skin phenotypes that correlated with the number of inserted transgenes. Molecular analyses were in good concordance with histological observations of psoriatic hallmarks, including hypogranulosis and T-lymphocyte infiltration. These findings mark the first creation of minipigs with a psoriasiform phenotype resembling human psoriasis and demonstrate that integrin signaling plays a key role in psoriasis pathology. PMID:28679670

Bio-chemo-mechanics of thoracic aortic aneurysms.

PubMed

Wagenseil, Jessica E

2018-03-01

Most thoracic aortic aneurysms (TAAs) occur in the ascending aorta. This review focuses on the unique bio-chemo-mechanical environment that makes the ascending aorta susceptible to TAA. The environment includes solid mechanics, fluid mechanics, cell phenotype, and extracellular matrix composition. Advances in solid mechanics include quantification of biaxial deformation and complex failure behavior of the TAA wall. Advances in fluid mechanics include imaging and modeling of hemodynamics that may lead to TAA formation. For cell phenotype, studies demonstrate changes in cell contractility that may serve to sense mechanical changes and transduce chemical signals. Studies on matrix defects highlight the multi-factorial nature of the disease. We conclude that future work should integrate the effects of bio-chemo-mechanical factors for improved TAA treatment.

Text-mined phenotype annotation and vector-based similarity to improve identification of similar phenotypes and causative genes in monogenic disease patients.

PubMed

Saklatvala, Jake R; Dand, Nick; Simpson, Michael A

2018-05-01

The genetic diagnosis of rare monogenic diseases using exome/genome sequencing requires the true causal variant(s) to be identified from tens of thousands of observed variants. Typically a virtual gene panel approach is taken whereby only variants in genes known to cause phenotypes resembling the patient under investigation are considered. With the number of known monogenic gene-disease pairs exceeding 5,000, manual curation of personalized virtual panels using exhaustive knowledge of the genetic basis of the human monogenic phenotypic spectrum is challenging. We present improved probabilistic methods for estimating phenotypic similarity based on Human Phenotype Ontology annotation. A limitation of existing methods for evaluating a disease's similarity to a reference set is that reference diseases are typically represented as a series of binary (present/absent) observations of phenotypic terms. We evaluate a quantified disease reference set, using term frequency in phenotypic text descriptions to approximate term relevance. We demonstrate an improved ability to identify related diseases through the use of a quantified reference set, and that vector space similarity measures perform better than established information content-based measures. These improvements enable the generation of bespoke virtual gene panels, facilitating more accurate and efficient interpretation of genomic variant profiles from individuals with rare Mendelian disorders. These methods are available online at https://atlas.genetics.kcl.ac.uk/~jake/cgi-bin/patient_sim.py. © 2018 Wiley Periodicals, Inc.

Phenotype at diagnosis predicts recurrence rates in Crohn's disease

PubMed Central

Wolters, F L; Russel, M G; Sijbrandij, J; Ambergen, T; Odes, S; Riis, L; Langholz, E; Politi, P; Qasim, A; Koutroubakis, I; Tsianos, E; Vermeire, S; Freitas, J; van Zeijl, G; Hoie, O; Bernklev, T; Beltrami, M; Rodriguez, D; Stockbrügger, R W; Moum, B

2006-01-01

Background In Crohn's disease (CD), studies associating phenotype at diagnosis and subsequent disease activity are important for patient counselling and health care planning. Aims To calculate disease recurrence rates and to correlate these with phenotypic traits at diagnosis. Methods A prospectively assembled uniformly diagnosed European population based inception cohort of CD patients was classified according to the Vienna classification for disease phenotype at diagnosis. Surgical and non‐surgical recurrence rates throughout a 10 year follow up period were calculated. Multivariate analysis was performed to classify risk factors present at diagnosis for recurrent disease. Results A total of 358 were classified for phenotype at diagnosis, of whom 262 (73.2%) had a first recurrence and 113 patients (31.6%) a first surgical recurrence during the first 10 years after diagnosis. Patients with upper gastrointestinal disease at diagnosis had an excess risk of recurrence (hazard ratio 1.54 (95% confidence interval (CI) 1.13–2.10)) whereas age ⩾40 years at diagnosis was protective (hazard ratio 0.82 (95% CI 0.70–0.97)). Colonic disease was a protective characteristic for resective surgery (hazard ratio 0.38 (95% CI 0.21–0.69)). More frequent resective surgical recurrences were reported from Copenhagen (hazard ratio 3.23 (95% CI 1.32–7.89)). Conclusions A mild course of disease in terms of disease recurrence was observed in this European cohort. Phenotype at diagnosis had predictive value for disease recurrence with upper gastrointestinal disease being the most important positive predictor. A phenotypic North‐South gradient in CD may be present, illustrated by higher surgery risks in some of the Northern European centres. PMID:16361306

Changes in Crohn's disease phenotype over time in the Chinese population: validation of the Montreal classification system.

PubMed

Chow, Dorothy K L; Leong, Rupert W L; Lai, Larry H; Wong, Grace L H; Leung, Wai-Keung; Chan, Francis K L; Sung, Joseph J Y

2008-04-01

Phenotypic evolution of Crohn's disease occurs in whites but has never been described in other populations. The Montreal classification may describe phenotypes more precisely. The aim of this study was to validate the Montreal classification through a longitudinal sensitivity analysis in detecting phenotypic variation compared to the Vienna classification. This was a retrospective longitudinal study of consecutive Chinese Crohn's disease patients. All cases were classified by the Montreal classification and the Vienna classification for behavior and location. The evolution of these characteristics and the need for surgery were evaluated. A total of 109 patients were recruited (median follow-up: 4 years, range: 6 months-18 years). Crohn's disease behavior changed 3 years after diagnosis (P = 0.025), with an increase in stricturing and penetrating phenotypes, as determined by the Montreal classification, but was only detected by the Vienna classification after 5 years (P = 0.015). Disease location remained stable on follow-up in both classifications. Thirty-four patients (31%) underwent major surgery during the follow-up period with the stricturing [P = 0.002; hazard ratio (HR): 3.3; 95% CI: 1.5-7.0] and penetrating (P = 0.03; HR: 5.8; 95% CI: 1.2-28.2) phenotypes according to the Montreal classification associated with the need for major surgery. In contrast, colonic disease was protective against a major operation (P = 0.02; HR: 0.3; 95% CI: 0.08-0.8). This is the first study demonstrating phenotypic evolution of Crohn's disease in a nonwhite population. The Montreal classification is more sensitive to behavior phenotypic changes than is the Vienna classification after excluding perianal disease from the penetrating disease category and was useful in predicting course and the need for surgery.

Solving Immunology?

PubMed

Vodovotz, Yoram; Xia, Ashley; Read, Elizabeth L; Bassaganya-Riera, Josep; Hafler, David A; Sontag, Eduardo; Wang, Jin; Tsang, John S; Day, Judy D; Kleinstein, Steven H; Butte, Atul J; Altman, Matthew C; Hammond, Ross; Sealfon, Stuart C

2017-02-01

Emergent responses of the immune system result from the integration of molecular and cellular networks over time and across multiple organs. High-content and high-throughput analysis technologies, concomitantly with data-driven and mechanistic modeling, hold promise for the systematic interrogation of these complex pathways. However, connecting genetic variation and molecular mechanisms to individual phenotypes and health outcomes has proven elusive. Gaps remain in data, and disagreements persist about the value of mechanistic modeling for immunology. Here, we present the perspectives that emerged from the National Institute of Allergy and Infectious Disease (NIAID) workshop 'Complex Systems Science, Modeling and Immunity' and subsequent discussions regarding the potential synergy of high-throughput data acquisition, data-driven modeling, and mechanistic modeling to define new mechanisms of immunological disease and to accelerate the translation of these insights into therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

The clinical maze of mitochondrial neurology

PubMed Central

DiMauro, Salvatore; Schon, Eric A.; Carelli, Valerio; Hirano, Michio

2014-01-01

Mitochondrial diseases involve the respiratory chain, which is under the dual control of nuclear and mitochondrial DNA (mtDNA). The complexity of mitochondrial genetics provides one explanation for the clinical heterogeneity of mitochondrial diseases, but our understanding of disease pathogenesis remains limited. Classification of Mendelian mitochondrial encephalomyopathies has been laborious, but whole-exome sequencing studies have revealed unexpected molecular aetiologies for both typical and atypical mitochondrial disease phenotypes. Mendelian mitochondrial defects can affect five components of mitochondrial biology: subunits of respiratory chain complexes (direct hits); mitochondrial assembly proteins; mtDNA translation; phospholipid composition of the inner mitochondrial membrane; or mitochondrial dynamics. A sixth category—defects of mtDNA maintenance—combines features of Mendelian and mitochondrial genetics. Genetic defects in mitochondrial dynamics are especially important in neurology as they cause optic atrophy, hereditary spastic paraplegia, and Charcot–Marie–Tooth disease. Therapy is inadequate and mostly palliative, but promising new avenues are being identified. Here, we review current knowledge on the genetics and pathogenesis of the six categories of mitochondrial disorders outlined above, focusing on their salient clinical manifestations and highlighting novel clinical entities. An outline of diagnostic clues for the various forms of mitochondrial disease, as well as potential therapeutic strategies, is also discussed. PMID:23835535

High-Risk Screening for Fabry Disease: Analysis by Tandem Mass Spectrometry of Globotriaosylceramide (Gb3 ) in Urine Collected on Filter Paper.

PubMed

Auray-Blais, Christiane; Lavoie, Pamela; Boutin, Michel; Abaoui, Mona

2017-04-06

Fabry disease is a complex, panethnic lysosomal storage disorder. It is characterized by the accumulation of glycosphingolipids in tissues, organs, the vascular endothelium, and biological fluids. The reported incidence in different populations is quite variable, ranging from 1:1400 to 1:117,000. Its complexity lies in the marked genotypic and phenotypic heterogeneity. Despite the fact that it is an X-linked disease, more than 600 mutations affect both males and females. In fact, some females may be affected as severely as males. The purpose of this protocol is to focus on the high-risk screening of patients who might have Fabry disease using a simple, rapid, non-invasive high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for urinary globotriaosylceramide (Gb 3 ) analysis. Urine filter paper samples are easily collected at home by patients and sent by regular mail. This method has been successfully used for high-risk screening of patients with ophthalmologic manifestations and in an on-going study for high-risk screening of Fabry disease in patients with chronic kidney diseases. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

The Impact of the Emerging Genomics Data on the Management of Agerelated Phenotypes in the Context of Cellular Senescence.

PubMed

Montesanto, Alberto; Geracitano, Silvana; Garasto, Sabrina; Fusco, Sergio; Lattanzio, Fabrizia; Passarino, Giuseppe; Corsonello, Andrea

2016-01-01

Before the last decade, attempts to identify the genetic factors involved in the susceptibility to age-related complex diseases such as cardiovascular disease, diabetes and cancer had very limited success. Recently, two important advancements have provided new opportunities to improve our knowledge in this field. Firstly, it has emerged the concept of studying the molecular mechanisms underlying the age related decline of the organism (such as cellular senescence), rather than the genetics of single disorders. In addition, advances in DNA technology have uncovered an incredible number of common susceptibility variants for several complex traits. Despite these progresses, the translation of these discoveries into clinical practice has been very difficult. To date, several attempts in translating genomics to medicine are being carried out to look for the best way by which genomic discoveries may improve our understanding of fundamental issues in the prediction and prevention of some complex diseases. The successful strategy seems to be testing simultaneously multiple susceptibility variants in combination with traditional risk factors. In fact, such approach showed that genetic factors substantially improve the prediction of complex diseases especially for coronary heart disease and prostate cancer, making possible appropriate behavioural and medical interventions. In the future, the identification of new genetic variants and their inclusion into current risk profile models will probably improve the discrimination power of these models for other complex diseases such as type 2 diabetes mellitus and breast cancer. On the other hand, for traits with low heritability, this improvement will probably be negligible, and this will urge further researches on the role played by traditional and newly discovered non-genetic risk factors.

Behavioural phenotypes predict disease susceptibility and infectiousness

PubMed Central

Araujo, Alessandra; Kirschman, Lucas

2016-01-01

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. PMID:27555652

Behavioural phenotypes predict disease susceptibility and infectiousness.

PubMed

Araujo, Alessandra; Kirschman, Lucas; Warne, Robin W

2016-08-01

Behavioural phenotypes may provide a means for identifying individuals that disproportionally contribute to disease spread and epizootic outbreaks. For example, bolder phenotypes may experience greater exposure and susceptibility to pathogenic infection because of distinct interactions with conspecifics and their environment. We tested the value of behavioural phenotypes in larval amphibians for predicting ranavirus transmission in experimental trials. We found that behavioural phenotypes characterized by latency-to-food and swimming profiles were predictive of disease susceptibility and infectiousness defined as the capacity of an infected host to transmit an infection by contacts. While viral shedding rates were positively associated with transmission, we also found an inverse relationship between contacts and infections. Together these results suggest intrinsic traits that influence behaviour and the quantity of pathogens shed during conspecific interactions may be an important contributor to ranavirus transmission. These results suggest that behavioural phenotypes provide a means to identify individuals more likely to spread disease and thus give insights into disease outbreaks that threaten wildlife and humans. © 2016 The Author(s).

Loss of Pink1 modulates synaptic mitochondrial bioenergetics in the rat striatum prior to motor symptoms: concomitant complex I respiratory defects and increased complex II-mediated respiration.

PubMed

Stauch, Kelly L; Villeneuve, Lance M; Purnell, Phillip R; Ottemann, Brendan M; Emanuel, Katy; Fox, Howard S

2016-12-01

Mutations in PTEN-induced putative kinase 1 (Pink1), a mitochondrial serine/threonine kinase, cause a recessive inherited form of Parkinson's disease (PD). Pink1 deletion in rats results in a progressive PD-like phenotype, characterized by significant motor deficits starting at 4 months of age. Despite the evidence of mitochondrial dysfunction, the pathogenic mechanism underlying disease due to Pink1-deficiency remains obscure. Striatal synaptic mitochondria from 3-month-old Pink1-deficient rats were characterized using bioenergetic and mass spectroscopy (MS)-based proteomic analyses. Striatal synaptic mitochondria from Pink1-deficient rats exhibit decreased complex I-driven respiration and increased complex II-mediated respiration compared with wild-type rats. MS-based proteomics revealed 69 of the 811 quantified mitochondrial proteins were differentially expressed between Pink1-deficient rats and controls. Down-regulation of several electron carrier proteins, which shuttle electrons to reduce ubiquinone at complex III, in the Pink1-knockouts suggests disruption of the linkage between fatty acid, amino acid, and choline metabolism and the mitochondrial respiratory system. These results suggest that complex II activity is increased to compensate for loss of electron transfer mechanisms due to reduced complex I activity and loss of electron carriers within striatal nerve terminals early during disease progression. This may contribute to the pathogenesis of PD. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PCAN: phenotype consensus analysis to support disease-gene association.

PubMed

Godard, Patrice; Page, Matthew

2016-12-07

Bridging genotype and phenotype is a fundamental biomedical challenge that underlies more effective target discovery and patient-tailored therapy. Approaches that can flexibly and intuitively, integrate known gene-phenotype associations in the context of molecular signaling networks are vital to effectively prioritize and biologically interpret genes underlying disease traits of interest. We describe Phenotype Consensus Analysis (PCAN); a method to assess the consensus semantic similarity of phenotypes in a candidate gene's signaling neighborhood. We demonstrate that significant phenotype consensus (p < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high quality String interactions + Metabase pathways and use Joubert Syndrome to demonstrate the ease with which a significant result can be interrogated to highlight discriminatory traits linked to mechanistically related genes. We advocate phenotype consensus as an intuitive and versatile method to aid disease-gene association, which naturally lends itself to the mechanistic deconvolution of diverse phenotypes. We provide PCAN to the community as an R package ( http://bioconductor.org/packages/PCAN/ ) to allow flexible configuration, extension and standalone use or integration to supplement existing gene prioritization workflows.

Unraveling the autoimmune translational research process layer by layer

PubMed Central

Blumberg, Richard S; Dittel, Bonnie; Hafler, David; von Herrath, Matthias; Nestle, Frank O

2015-01-01

Autoimmune diseases have a complex etiology and despite great progress having been made in our comprehension of these disorders, there has been limited success in the development of approved medications based on these insights. Development of drugs and strategies for application in translational research and medicine are hampered by an inadequate molecular definition of the human autoimmune phenotype and the organizational models that are necessary to clarify this definition. PMID:22227670

β-Arrestin1 regulates γ-secretase complex assembly and modulates amyloid-β pathology

PubMed Central

Liu, Xiaosong; Zhao, Xiaohui; Zeng, Xianglu; Bossers, Koen; Swaab, Dick F; Zhao, Jian; Pei, Gang

2013-01-01

Alzheimer's disease (AD) is a progressive and complex neurodegenerative disease in which the γ-secretase-mediated amyloid-β (Aβ) pathology plays an important role. We found that a multifunctional protein, β-arrestin1, facilitated the formation of NCT/APH-1 (anterior pharynx-defective phenotype 1) precomplex and mature γ-secretase complex through its functional interaction with APH-1. Deficiency of β-arrestin1 or inhibition of binding of β-arrestin1 with APH-1 by small peptides reduced Aβ production without affecting Notch processing. Genetic ablation of β-arrestin1 diminished Aβ pathology and behavioral deficits in transgenic AD mice. Moreover, in brains of sporadic AD patients and transgenic AD mice, the expression of β-arrestin1 was upregulated and correlated well with neuropathological severity and senile Aβ plaques. Thus, our study identifies a regulatory mechanism underlying both γ-secretase assembly and AD pathogenesis, and indicates that specific reduction of Aβ pathology can be achieved by regulation of the γ-secretase assembly. PMID:23208420

Endosidin2 targets conserved exocyst complex subunit EXO70 to inhibit exocytosis

DOE PAGES

Zhang, Chunhua; Brown, Michelle Q.; van de Ven, Wilhelmina; ...

2015-11-25

The exocyst complex regulates the last steps of exocytosis, which is essential to organisms across kingdoms. In humans, its dysfunction is correlated with several significant diseases, such as diabetes and cancer progression. Investigation of the dynamic regulation of the evolutionarily conserved exocyst-related processes using mutants in genetically tractable organisms such as Arabidopsis thaliana is limited by the lethality or the severity of phenotypes. We discovered that the small molecule Endosidin2 (ES2) binds to the EXO70 (exocyst component of 70 kDa) subunit of the exocyst complex, resulting in inhibition of exocytosis and endosomal recycling in both plant and human cells andmore » enhancement of plant vacuolar trafficking. An EXO70 protein with a C-terminal truncation results in dominant ES2 resistance, uncovering possible distinct regulatory roles for the N terminus of the protein. Ultimately, this study not only provides a valuable tool in studying exocytosis regulation but also offers a potentially new target for drugs aimed at addressing human disease.« less

Endosidin2 targets conserved exocyst complex subunit EXO70 to inhibit exocytosis

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

Zhang, Chunhua; Brown, Michelle Q.; van de Ven, Wilhelmina

The exocyst complex regulates the last steps of exocytosis, which is essential to organisms across kingdoms. In humans, its dysfunction is correlated with several significant diseases, such as diabetes and cancer progression. Investigation of the dynamic regulation of the evolutionarily conserved exocyst-related processes using mutants in genetically tractable organisms such as Arabidopsis thaliana is limited by the lethality or the severity of phenotypes. We discovered that the small molecule Endosidin2 (ES2) binds to the EXO70 (exocyst component of 70 kDa) subunit of the exocyst complex, resulting in inhibition of exocytosis and endosomal recycling in both plant and human cells andmore » enhancement of plant vacuolar trafficking. An EXO70 protein with a C-terminal truncation results in dominant ES2 resistance, uncovering possible distinct regulatory roles for the N terminus of the protein. Ultimately, this study not only provides a valuable tool in studying exocytosis regulation but also offers a potentially new target for drugs aimed at addressing human disease.« less

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

Groza, Tudor; Köhler, Sebastian; Moldenhauer, Dawid

The Human Phenotype Ontology (HPO) is widely used in the rare disease community for differential diagnostics, phenotype-driven analysis of next-generation sequence-variation data, and translational research, but a comparable resource has not been available for common disease. Here, we have developed a concept-recognition procedure that analyzes the frequencies of HPO disease annotations as identified in over five million PubMed abstracts by employing an iterative procedure to optimize precision and recall of the identified terms. We derived disease models for 3,145 common human diseases comprising a total of 132,006 HPO annotations. The HPO now comprises over 250,000 phenotypic annotations for over 10,000more » rare and common diseases and can be used for examining the phenotypic overlap among common diseases that share risk alleles, as well as between Mendelian diseases and common diseases linked by genomic location. The annotations, as well as the HPO itself, are freely available.« less

Complex Changes in the Innate and Adaptive Immunity Accompany Progressive Degeneration of the Nigrostriatal Pathway Induced by Intrastriatal Injection of 6-Hydroxydopamine in the Rat.

PubMed

Ambrosi, Giulia; Kustrimovic, Natasa; Siani, Francesca; Rasini, Emanuela; Cerri, Silvia; Ghezzi, Cristina; Dicorato, Giuseppe; Caputo, Sofia; Marino, Franca; Cosentino, Marco; Blandini, Fabio

2017-07-01

We investigated changes in innate and adaptive immunity paralleling the progressive nigrostriatal damage occurring in a neurotoxic model of Parkinson's disease (PD) based on unilateral infusion of 6-hydroxydopamine (6-OHDA) into the rat striatum. A time-course analysis was conducted to assess changes in morphology (activation) and cell density of microglia and astrocytes, microglia polarization (M1 vs. M2 phenotype), lymphocyte infiltration in the lesioned substantia nigra pars compacta (SNc), and modifications of CD8+ and subsets of CD4+ T cell in peripheral blood accompanying nigrostriatal degeneration. Confirming previous results, we observed slightly different profiles of activation for astrocytes and microglia paralleling nigral neuronal loss. For astrocytes, morphological changes and cell density increases were mostly evident at the latest time points (14 and 28 days post-surgery), while moderate microglia activation was present since the earliest time point. For the first time, in this model, we described the time-dependent profile of microglia polarization. Activated microglia clearly expressed the M2 phenotype in the earlier phase of the experiment, before cell death became manifest, gradually shifting to the M1 phenotype as SNc cell death started. In parallel, a reduction in the percentage of circulating CD4+ T regulatory (Treg) cells, starting as early as day 3 post-6-OHDA injection, was detected in 6-OHDA-injected rats. Our data show that nigrostriatal degeneration is associated with complex changes in central and peripheral immunity. Microglia activation and polarization, Treg cells, and the factors involved in their cross-talk should be further investigated as targets for the development of therapeutic strategies for disease modification in PD.

Towards building a disease-phenotype knowledge base: extracting disease-manifestation relationship from literature

PubMed Central

Xu, Rong; Li, Li; Wang, QuanQiu

2013-01-01

Motivation: Systems approaches to studying phenotypic relationships among diseases are emerging as an active area of research for both novel disease gene discovery and drug repurposing. Currently, systematic study of disease phenotypic relationships on a phenome-wide scale is limited because large-scale machine-understandable disease–phenotype relationship knowledge bases are often unavailable. Here, we present an automatic approach to extract disease–manifestation (D-M) pairs (one specific type of disease–phenotype relationship) from the wide body of published biomedical literature. Data and Methods: Our method leverages external knowledge and limits the amount of human effort required. For the text corpus, we used 119 085 682 MEDLINE sentences (21 354 075 citations). First, we used D-M pairs from existing biomedical ontologies as prior knowledge to automatically discover D-M–specific syntactic patterns. We then extracted additional pairs from MEDLINE using the learned patterns. Finally, we analysed correlations between disease manifestations and disease-associated genes and drugs to demonstrate the potential of this newly created knowledge base in disease gene discovery and drug repurposing. Results: In total, we extracted 121 359 unique D-M pairs with a high precision of 0.924. Among the extracted pairs, 120 419 (99.2%) have not been captured in existing structured knowledge sources. We have shown that disease manifestations correlate positively with both disease-associated genes and drug treatments. Conclusions: The main contribution of our study is the creation of a large-scale and accurate D-M phenotype relationship knowledge base. This unique knowledge base, when combined with existing phenotypic, genetic and proteomic datasets, can have profound implications in our deeper understanding of disease etiology and in rapid drug repurposing. Availability: http://nlp.case.edu/public/data/DMPatternUMLS/ Contact: rxx@case.edu PMID:23828786

Phenotypic and Genotypic Characterisation of Inflammatory Bowel Disease Presenting Before the Age of 2 years.

PubMed

Kammermeier, Jochen; Dziubak, Robert; Pescarin, Matilde; Drury, Suzanne; Godwin, Heather; Reeve, Kate; Chadokufa, Sibongile; Huggett, Bonita; Sider, Sara; James, Chela; Acton, Nikki; Cernat, Elena; Gasparetto, Marco; Noble-Jamieson, Gabi; Kiparissi, Fevronia; Elawad, Mamoun; Beales, Phil L; Sebire, Neil J; Gilmour, Kimberly; Uhlig, Holm H; Bacchelli, Chiara; Shah, Neil

2017-01-01

Inflammatory bowel disease [IBD] presenting in early childhood is extremely rare. More recently, progress has been made to identify children with monogenic forms of IBD predominantly presenting very early in life. In this study, we describe the heterogeneous phenotypes and genotypes of patients with IBD presenting before the age of 2 years and establish phenotypic features associated with underlying monogenicity. Phenotype data of 62 children with disease onset before the age of 2 years presenting over the past 20 years were reviewed. Children without previously established genetic diagnosis were prospectively recruited for next-generation sequencing. In all, 62 patients [55% male] were identified. The median disease onset was 3 months of age (interquartile range [IQR]: 1 to 11). Conventional IBD classification only applied to 15 patients with Crohn's disease [CD]-like [24%] and three with ulcerative colitis [UC]-like [5%] phenotype; 44 patients [71%] were diagnosed with otherwise unclassifiable IBD. Patients frequently required parenteral nutrition [40%], extensive immunosuppression [31%], haematopoietic stem-cell transplantation [29%], and abdominal surgery [19%]. In 31% of patients, underlying monogenic diseases were established [EPCAM, IL10, IL10RA, IL10RB, FOXP3, LRBA, SKIV2L, TTC37, TTC7A]. Phenotypic features significantly more prevalent in monogenic IBD were: consanguinity, disease onset before the 6th month of life, stunting, extensive intestinal disease and histological evidence of epithelial abnormalities. IBD in children with disease onset before the age of 2 years is frequently unclassifiable into Crohn's disease and ulcerative colitis, particularly treatment resistant, and can be indistinguishable from monogenic diseases with IBD-like phenotype. Copyright © 2016 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Phenotypic and Genotypic Characterisation of Inflammatory Bowel Disease Presenting Before the Age of 2 years

PubMed Central

Dziubak, Robert; Pescarin, Matilde; Drury, Suzanne; Godwin, Heather; Reeve, Kate; Chadokufa, Sibongile; Huggett, Bonita; Sider, Sara; James, Chela; Acton, Nikki; Cernat, Elena; Gasparetto, Marco; Noble-Jamieson, Gabi; Kiparissi, Fevronia; Elawad, Mamoun; Beales, Phil L.; Sebire, Neil J.; Gilmour, Kimberly; Uhlig, Holm H.; Bacchelli, Chiara; Shah, Neil

2017-01-01

Abstract Objectives: Inflammatory bowel disease [IBD] presenting in early childhood is extremely rare. More recently, progress has been made to identify children with monogenic forms of IBD predominantly presenting very early in life. In this study, we describe the heterogeneous phenotypes and genotypes of patients with IBD presenting before the age of 2 years and establish phenotypic features associated with underlying monogenicity. Methods: Phenotype data of 62 children with disease onset before the age of 2 years presenting over the past 20 years were reviewed. Children without previously established genetic diagnosis were prospectively recruited for next-generation sequencing. Results: In all, 62 patients [55% male] were identified. The median disease onset was 3 months of age (interquartile range [IQR]: 1 to 11). Conventional IBD classification only applied to 15 patients with Crohn’s disease [CD]-like [24%] and three with ulcerative colitis [UC]-like [5%] phenotype; 44 patients [71%] were diagnosed with otherwise unclassifiable IBD. Patients frequently required parenteral nutrition [40%], extensive immunosuppression [31%], haematopoietic stem-cell transplantation [29%], and abdominal surgery [19%]. In 31% of patients, underlying monogenic diseases were established [EPCAM, IL10, IL10RA, IL10RB, FOXP3, LRBA, SKIV2L, TTC37, TTC7A]. Phenotypic features significantly more prevalent in monogenic IBD were: consanguinity, disease onset before the 6th month of life, stunting, extensive intestinal disease and histological evidence of epithelial abnormalities. Conclusions: IBD in children with disease onset before the age of 2 years is frequently unclassifiable into Crohn’s disease and ulcerative colitis, particularly treatment resistant, and can be indistinguishable from monogenic diseases with IBD-like phenotype. PMID:27302973

PhenoLines: Phenotype Comparison Visualizations for Disease Subtyping via Topic Models.

PubMed

Glueck, Michael; Naeini, Mahdi Pakdaman; Doshi-Velez, Finale; Chevalier, Fanny; Khan, Azam; Wigdor, Daniel; Brudno, Michael

2018-01-01

PhenoLines is a visual analysis tool for the interpretation of disease subtypes, derived from the application of topic models to clinical data. Topic models enable one to mine cross-sectional patient comorbidity data (e.g., electronic health records) and construct disease subtypes-each with its own temporally evolving prevalence and co-occurrence of phenotypes-without requiring aligned longitudinal phenotype data for all patients. However, the dimensionality of topic models makes interpretation challenging, and de facto analyses provide little intuition regarding phenotype relevance or phenotype interrelationships. PhenoLines enables one to compare phenotype prevalence within and across disease subtype topics, thus supporting subtype characterization, a task that involves identifying a proposed subtype's dominant phenotypes, ages of effect, and clinical validity. We contribute a data transformation workflow that employs the Human Phenotype Ontology to hierarchically organize phenotypes and aggregate the evolving probabilities produced by topic models. We introduce a novel measure of phenotype relevance that can be used to simplify the resulting topology. The design of PhenoLines was motivated by formative interviews with machine learning and clinical experts. We describe the collaborative design process, distill high-level tasks, and report on initial evaluations with machine learning experts and a medical domain expert. These results suggest that PhenoLines demonstrates promising approaches to support the characterization and optimization of topic models.

The SAM domain of ANKS6 has different interacting partners and mutations can induce different cystic phenotypes.

PubMed

Bakey, Zeineb; Bihoreau, Marie-Thérèse; Piedagnel, Rémi; Delestré, Laure; Arnould, Catherine; de Villiers, Alexandre d'Hotman; Devuyst, Olivier; Hoffmann, Sigrid; Ronco, Pierre; Gauguier, Dominique; Lelongt, Brigitte

2015-08-01

The ankyrin repeat and sterile α motif (SAM) domain-containing six gene (Anks6) is a candidate for polycystic kidney disease (PKD). Originally identified in the PKD/Mhm(cy/+) rat model of PKD, the disease is caused by a mutation (R823W) in the SAM domain of the encoded protein. Recent studies support the etiological role of the ANKS6 SAM domain in human cystic diseases, but its function in kidney remains unknown. To investigate the role of ANKS6 in cyst formation, we screened an archive of N-ethyl-N-nitrosourea-treated mice and derived a strain carrying a missense mutation (I747N) within the SAM domain of ANKS6. This mutation is only six amino acids away from the PKD-causing mutation (R823W) in cy/+ rats. Evidence of renal cysts in these mice confirmed the crucial role of the SAM domain of ANKS6 in kidney function. Comparative phenotype analysis in cy/+ rats and our Anks6(I747N) mice further showed that the two models display noticeably different PKD phenotypes and that there is a defective interaction between ANKS6 with ANKS3 in the rat and between ANKS6 and BICC1 (bicaudal C homolog 1) in the mouse. Thus, our data demonstrate the importance of ANKS6 for kidney structure integrity and the essential mediating role of its SAM domain in the formation of protein complexes.

Novel therapeutic strategy in the management of COPD: a systems medicine approach.

PubMed

Lococo, Filippo; Cesario, Alfredo; Del Bufalo, Alessandra; Ciarrocchi, Alessia; Prinzi, Giulia; Mina, Marco; Bonassi, Stefano; Russo, Patrizia

2015-01-01

Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as a result of a complex interaction between various genetic, environmental and life-style factors. In recent years, several investigations have been performed to better define such interactions, but the identification of the resulting phenotypes is still somewhat difficult, and may lead to inadequate assessment and management of COPD (usually based solely on the severity of airflow limitation parameter FEV1). In this new scenario, the management of COPD has been driven towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (also including advanced functional genomic assays) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for the development of new drugs). Therefore, according to the emerging "systems/network medicine", COPD should be re.-evaluated considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized and participatory ("P4-medicine"). It clearly emerges that in the next future, new opportunities will become available for clinical research on rare COPD patterns and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SMapproaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.

A weighted U-statistic for genetic association analyses of sequencing data.

PubMed

Wei, Changshuai; Li, Ming; He, Zihuai; Vsevolozhskaya, Olga; Schaid, Daniel J; Lu, Qing

2014-12-01

With advancements in next-generation sequencing technology, a massive amount of sequencing data is generated, which offers a great opportunity to comprehensively investigate the role of rare variants in the genetic etiology of complex diseases. Nevertheless, the high-dimensional sequencing data poses a great challenge for statistical analysis. The association analyses based on traditional statistical methods suffer substantial power loss because of the low frequency of genetic variants and the extremely high dimensionality of the data. We developed a Weighted U Sequencing test, referred to as WU-SEQ, for the high-dimensional association analysis of sequencing data. Based on a nonparametric U-statistic, WU-SEQ makes no assumption of the underlying disease model and phenotype distribution, and can be applied to a variety of phenotypes. Through simulation studies and an empirical study, we showed that WU-SEQ outperformed a commonly used sequence kernel association test (SKAT) method when the underlying assumptions were violated (e.g., the phenotype followed a heavy-tailed distribution). Even when the assumptions were satisfied, WU-SEQ still attained comparable performance to SKAT. Finally, we applied WU-SEQ to sequencing data from the Dallas Heart Study (DHS), and detected an association between ANGPTL 4 and very low density lipoprotein cholesterol. © 2014 WILEY PERIODICALS, INC.

Sequence analysis and transcript identification within 1.5 MB of DNA deleted together with the NDP and MAO genes in atypical Norrie disease patients presenting with a profound phenotype.

PubMed

Suárez-Merino, B; Bye, J; McDowall, J; Ross, M; Craig, I W

2001-06-01

Mutations at the Norrie disease gene locus, NDP, manifest in a broad range of defects. These range from a relatively mild, late-onset, exudative vitreoretinopathy to congenital blindness and sensorineural deafness combined, in some cases, with mental retardation. In addition, extensive deletions involving the NDP locus, located at Xp11.3, the adjacent monoamine oxidadase genes MAOA and MAOB, and additional material, result in a more severe pattern of symptoms. The phenotypes include all or some of the following; mental retardation, involuntary movements, hypertensive crises and hypogonadism. We extended an existing YAC contig to embrace the boundaries of three of the largest deletions and converted this into four PAC contigs. Computer analysis and experimental data have resulted in the identification of several putative loci, including a phosphatase inhibitor 2-like gene (dJ154.1) and a 250-bp sequence which resembles a homeobox domain (dA113.3), 1.2 Mb and 400 kb respectively from the MAO/NDP cluster. The pattern of expression of dJ154.1 suggests that it may represent an important factor contributing to the complex phenotypes of these deletion patients. Hum Mutat 17:523, 2001. Copyright 2001 Wiley-Liss, Inc.

Auditory hedonic phenotypes in dementia: A behavioural and neuroanatomical analysis

PubMed Central

Fletcher, Phillip D.; Downey, Laura E.; Golden, Hannah L.; Clark, Camilla N.; Slattery, Catherine F.; Paterson, Ross W.; Schott, Jonathan M.; Rohrer, Jonathan D.; Rossor, Martin N.; Warren, Jason D.

2015-01-01

Patients with dementia may exhibit abnormally altered liking for environmental sounds and music but such altered auditory hedonic responses have not been studied systematically. Here we addressed this issue in a cohort of 73 patients representing major canonical dementia syndromes (behavioural variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA) amnestic Alzheimer's disease (AD)) using a semi-structured caregiver behavioural questionnaire and voxel-based morphometry (VBM) of patients' brain MR images. Behavioural responses signalling abnormal aversion to environmental sounds, aversion to music or heightened pleasure in music (‘musicophilia’) occurred in around half of the cohort but showed clear syndromic and genetic segregation, occurring in most patients with bvFTD but infrequently in PNFA and more commonly in association with MAPT than C9orf72 mutations. Aversion to sounds was the exclusive auditory phenotype in AD whereas more complex phenotypes including musicophilia were common in bvFTD and SD. Auditory hedonic alterations correlated with grey matter loss in a common, distributed, right-lateralised network including antero-mesial temporal lobe, insula, anterior cingulate and nucleus accumbens. Our findings suggest that abnormalities of auditory hedonic processing are a significant issue in common dementias. Sounds may constitute a novel probe of brain mechanisms for emotional salience coding that are targeted by neurodegenerative disease. PMID:25929717

Copy number variation in metabolic phenotypes.

PubMed

Lanktree, M; Hegele, R A

2008-01-01

Despite successes in identifying genetic contributors to common metabolic phenotypes, only part of the heritable component of these traits has thus far been explained. Copy number variation (CNV) is likely to be responsible for some of the unexplained variation. As observed with single nucleotide changes, it is probable that both rare and common CNVs will contribute to susceptibility to metabolic disease. For instance, CNVs in the LDLR gene underlie a substantial portion of disease in patients with heterozygous familial hypercholesterolemia. As well, a common CNV in LPA encoding apolipoprotein(a) is the primary determinant of plasma lipoprotein(a) concentrations, a risk factor for atherosclerosis. Recent efforts to map CNVs in control populations have defined their size, frequency and distribution. Many of the identified CNVs overlap genes with important functions in metabolic pathways. The overlap of CNVs that were found in control datasets with functional candidate genes or genes with previous evidence of association with metabolic syndrome presents an important subset for future CNV association studies. Finally, we describe an approach to search for CNVs in a rare high-penetrance metabolic disorder, namely lipodystrophy. As methods to identify CNVs increase in precision and accuracy, the prospect of identifying their role in both rare Mendelian and common complex metabolic phenotypes will become a reality. Copyright 2009 S. Karger AG, Basel.

Drug Discovery for Neglected Diseases: Molecular Target-Based and Phenotypic Approaches

PubMed Central

2013-01-01

Drug discovery for neglected tropical diseases is carried out using both target-based and phenotypic approaches. In this paper, target-based approaches are discussed, with a particular focus on human African trypanosomiasis. Target-based drug discovery can be successful, but careful selection of targets is required. There are still very few fully validated drug targets in neglected diseases, and there is a high attrition rate in target-based drug discovery for these diseases. Phenotypic screening is a powerful method in both neglected and non-neglected diseases and has been very successfully used. Identification of molecular targets from phenotypic approaches can be a way to identify potential new drug targets. PMID:24015767

Enabling phenotypic big data with PheNorm.

PubMed

Yu, Sheng; Ma, Yumeng; Gronsbell, Jessica; Cai, Tianrun; Ananthakrishnan, Ashwin N; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Liao, Katherine P; Cai, Tianxi

2018-01-01

Electronic health record (EHR)-based phenotyping infers whether a patient has a disease based on the information in his or her EHR. A human-annotated training set with gold-standard disease status labels is usually required to build an algorithm for phenotyping based on a set of predictive features. The time intensiveness of annotation and feature curation severely limits the ability to achieve high-throughput phenotyping. While previous studies have successfully automated feature curation, annotation remains a major bottleneck. In this paper, we present PheNorm, a phenotyping algorithm that does not require expert-labeled samples for training. The most predictive features, such as the number of International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes or mentions of the target phenotype, are normalized to resemble a normal mixture distribution with high area under the receiver operating curve (AUC) for prediction. The transformed features are then denoised and combined into a score for accurate disease classification. We validated the accuracy of PheNorm with 4 phenotypes: coronary artery disease, rheumatoid arthritis, Crohn's disease, and ulcerative colitis. The AUCs of the PheNorm score reached 0.90, 0.94, 0.95, and 0.94 for the 4 phenotypes, respectively, which were comparable to the accuracy of supervised algorithms trained with sample sizes of 100-300, with no statistically significant difference. The accuracy of the PheNorm algorithms is on par with algorithms trained with annotated samples. PheNorm fully automates the generation of accurate phenotyping algorithms and demonstrates the capacity for EHR-driven annotations to scale to the next level - phenotypic big data. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Metabotropic glutamate receptor 5 couples cellular prion protein to intracellular signalling in Alzheimer’s disease

PubMed Central

Haas, Laura T.; Salazar, Santiago V.; Kostylev, Mikhail A.; Um, Ji Won; Kaufman, Adam C.

2016-01-01

Alzheimer’s disease-related phenotypes in mice can be rescued by blockade of either cellular prion protein or metabotropic glutamate receptor 5. We sought genetic and biochemical evidence that these proteins function cooperatively as an obligate complex in the brain. We show that cellular prion protein associates via transmembrane metabotropic glutamate receptor 5 with the intracellular protein mediators Homer1b/c, calcium/calmodulin-dependent protein kinase II, and the Alzheimer’s disease risk gene product protein tyrosine kinase 2 beta. Coupling of cellular prion protein to these intracellular proteins is modified by soluble amyloid-β oligomers, by mouse brain Alzheimer’s disease transgenes or by human Alzheimer’s disease pathology. Amyloid-β oligomer-triggered phosphorylation of intracellular protein mediators and impairment of synaptic plasticity in vitro requires Prnp–Grm5 genetic interaction, being absent in transheterozygous loss-of-function, but present in either single heterozygote. Importantly, genetic coupling between Prnp and Grm5 is also responsible for signalling, for survival and for synapse loss in Alzheimer’s disease transgenic model mice. Thus, the interaction between metabotropic glutamate receptor 5 and cellular prion protein has a central role in Alzheimer’s disease pathogenesis, and the complex is a potential target for disease-modifying intervention. PMID:26667279

Integrating Epigenomics into the Understanding of Biomedical Insight.

PubMed

Han, Yixing; He, Ximiao

2016-01-01

Epigenetics is one of the most rapidly expanding fields in biomedical research, and the popularity of the high-throughput next-generation sequencing (NGS) highlights the accelerating speed of epigenomics discovery over the past decade. Epigenetics studies the heritable phenotypes resulting from chromatin changes but without alteration on DNA sequence. Epigenetic factors and their interactive network regulate almost all of the fundamental biological procedures, and incorrect epigenetic information may lead to complex diseases. A comprehensive understanding of epigenetic mechanisms, their interactions, and alterations in health and diseases genome widely has become a priority in biological research. Bioinformatics is expected to make a remarkable contribution for this purpose, especially in processing and interpreting the large-scale NGS datasets. In this review, we introduce the epigenetics pioneering achievements in health status and complex diseases; next, we give a systematic review of the epigenomics data generation, summarize public resources and integrative analysis approaches, and finally outline the challenges and future directions in computational epigenomics.

Integrating Epigenomics into the Understanding of Biomedical Insight

PubMed Central

Han, Yixing; He, Ximiao

2016-01-01

Epigenetics is one of the most rapidly expanding fields in biomedical research, and the popularity of the high-throughput next-generation sequencing (NGS) highlights the accelerating speed of epigenomics discovery over the past decade. Epigenetics studies the heritable phenotypes resulting from chromatin changes but without alteration on DNA sequence. Epigenetic factors and their interactive network regulate almost all of the fundamental biological procedures, and incorrect epigenetic information may lead to complex diseases. A comprehensive understanding of epigenetic mechanisms, their interactions, and alterations in health and diseases genome widely has become a priority in biological research. Bioinformatics is expected to make a remarkable contribution for this purpose, especially in processing and interpreting the large-scale NGS datasets. In this review, we introduce the epigenetics pioneering achievements in health status and complex diseases; next, we give a systematic review of the epigenomics data generation, summarize public resources and integrative analysis approaches, and finally outline the challenges and future directions in computational epigenomics. PMID:27980397

Man’s Best Friend Becomes Biology’s Best in Show: Genome Analyses in the Domestic Dog*

PubMed Central

Parker, Heidi G.; Shearin, Abigail L.; Ostrander, Elaine A.

2012-01-01

In the last five years, canine genetics has gone from map construction to complex disease deconstruction. The availability of a draft canine genome sequence, dense marker chips, and an understanding of the genome architecture has changed the types of studies canine geneticists can undertake. There is now a clear recognition that the dog system offers the opportunity to understand the genetics of both simple and complex traits, including those associated with morphology, disease susceptibility, and behavior. In this review, we summarize recent findings regarding canine domestication and review new information on the organization of the canine genome. We discuss studies aimed at finding genes controlling morphological phenotypes and provide examples of the way such paradigms may be applied to studies of behavior. We also discuss the many ways in which the dog has illuminated our understanding of human disease and conclude with a discussion on where the field is likely headed in the next five years. PMID:21047261

Mathematical modeling of atopic dermatitis reveals "double-switch" mechanisms underlying 4 common disease phenotypes.

PubMed

Domínguez-Hüttinger, Elisa; Christodoulides, Panayiotis; Miyauchi, Kosuke; Irvine, Alan D; Okada-Hatakeyama, Mariko; Kubo, Masato; Tanaka, Reiko J

2017-06-01

The skin barrier acts as the first line of defense against constant exposure to biological, microbial, physical, and chemical environmental stressors. Dynamic interplay between defects in the skin barrier, dysfunctional immune responses, and environmental stressors are major factors in the development of atopic dermatitis (AD). A systems biology modeling approach can yield significant insights into these complex and dynamic processes through integration of prior biological data. We sought to develop a multiscale mathematical model of AD pathogenesis that describes the dynamic interplay between the skin barrier, environmental stress, and immune dysregulation and use it to achieve a coherent mechanistic understanding of the onset, progression, and prevention of AD. We mathematically investigated synergistic effects of known genetic and environmental risk factors on the dynamic onset and progression of the AD phenotype, from a mostly asymptomatic mild phenotype to a severe treatment-resistant form. Our model analysis identified a "double switch," with 2 concatenated bistable switches, as a key network motif that dictates AD pathogenesis: the first switch is responsible for the reversible onset of inflammation, and the second switch is triggered by long-lasting or frequent activation of the first switch, causing irreversible onset of systemic T H 2 sensitization and worsening of AD symptoms. Our mathematical analysis of the bistable switch predicts that genetic risk factors decrease the threshold of environmental stressors to trigger systemic T H 2 sensitization. This analysis predicts and explains 4 common clinical AD phenotypes from a mild and reversible phenotype through to severe and recalcitrant disease and provides a mechanistic explanation for clinically demonstrated preventive effects of emollient treatments against development of AD. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Characterization of Classical and Nonclassical Fabry Disease: A Multicenter Study

PubMed Central

Wanner, Christoph; Hughes, Derralynn; Mehta, Atul; Oder, Daniel; Watkinson, Oliver T.; Elliott, Perry M.; Linthorst, Gabor E.; Wijburg, Frits A.; Biegstraaten, Marieke; Hollak, Carla E.

2017-01-01

Fabry disease leads to renal, cardiac, and cerebrovascular manifestations. Phenotypic differences between classically and nonclassically affected patients are evident, but there are few data on the natural course of classical and nonclassical disease in men and women. To describe the natural course of Fabry disease stratified by sex and phenotype, we retrospectively assessed event-free survival from birth to the first clinical visit (before enzyme replacement therapy) in 499 adult patients (mean age 43 years old; 41% men; 57% with the classical phenotype) from three international centers of excellence. We classified patients by phenotype on the basis of characteristic symptoms and enzyme activity. Men and women with classical Fabry disease had higher event rate than did those with nonclassical disease (hazard ratio for men, 5.63, 95% confidence interval, 3.17 to 10.00; P<0.001; hazard ratio for women, 2.88, 95% confidence interval, 1.54 to 5.40; P<0.001). Furthermore, men with classical Fabry disease had lower eGFR, higher left ventricular mass, and higher plasma globotriaosylsphingosine concentrations than men with nonclassical Fabry disease or women with either phenotype (P<0.001). In conclusion, before treatment with enzyme replacement therapy, men with classical Fabry disease had a history of more events than men with nonclassical disease or women with either phenotype; women with classical Fabry disease were more likely to develop complications than women with nonclassical disease. These data may support the development of new guidelines for the monitoring and treatment of Fabry disease and studies on the effects of intervention in subgroups of patients. PMID:27979989

Epigenetics in the Vascular Endothelium: Looking From a Different Perspective in the Epigenomics Era.

PubMed

Yan, Matthew S; Marsden, Philip A

2015-11-01

Cardiovascular diseases are commonly thought to be complex, non-Mendelian diseases that are influenced by genetic and environmental factors. A growing body of evidence suggests that epigenetic pathways play a key role in vascular biology and might be involved in defining and transducing cardiovascular disease inheritability. In this review, we argue the importance of epigenetics in vascular biology, especially from the perspective of endothelial cell phenotype. We highlight and discuss the role of epigenetic modifications across the transcriptional unit of protein-coding genes, especially the role of intragenic chromatin modifications, which are underappreciated and not well characterized in the current era of genome-wide studies. Importantly, we describe the practical application of epigenetics in cardiovascular disease therapeutics. © 2015 American Heart Association, Inc.

The choreography of neuroinflammation in Huntington’s disease

PubMed Central

Crotti, Andrea; Glass, Christopher K.

2016-01-01

Currently, the concept of ‘neuroinflammation’ includes inflammation associated with neurodegenerative diseases, in which there is little or no infiltration of blood-derived immune cells into the brain. The roles of brain-resident and peripheral immune cells in these inflammatory settings are poorly understood, and it is unclear whether neuroinflammation results from immune reaction to neuronal dysfunction/degeneration, and/or represents cell-autonomous phenotypes of dysfunctional immune cells. Here, we review recent studies examining these questions in the context of Huntington’s disease (HD), where mutant Huntingtin (HTT) is expressed in both neurons and glia. Insights into the cellular and molecular mechanisms underlying neuroinflammation in HD may provide a better understanding of inflammation in more complex neurodegenerative disorders, and of the contribution of the neuroinflammatory component to neurodegenerative disease pathogenesis. PMID:26001312

Dynamic self-guiding analysis of Alzheimer's disease

PubMed Central

Kurakin, Alexei; Bredesen, Dale E.

2015-01-01

We applied a self-guiding evolutionary algorithm to initiate the synthesis of the Alzheimer's disease-related data and literature. A protein interaction network associated with amyloid-beta precursor protein (APP) and a seed model that treats Alzheimer's disease as progressive dysregulation of APP-associated signaling were used as dynamic “guides” and structural “filters” in the recursive search, analysis, and assimilation of data to drive the evolution of the seed model in size, detail, and complexity. Analysis of data and literature across sub-disciplines and system-scale discovery platforms suggests a key role of dynamic cytoskeletal connectivity in the stability, plasticity, and performance of multicellular networks and architectures. Chronic impairment and/or dysregulation of cell adhesions/synapses, cytoskeletal networks, and/or reversible epithelial-to-mesenchymal-like transitions, which enable and mediate the stable and coherent yet dynamic and reconfigurable multicellular architectures, may lead to the emergence and persistence of the disordered, wound-like pockets/microenvironments of chronically disconnected cells. Such wound-like microenvironments support and are supported by pro-inflammatory, pro-secretion, de-differentiated cellular phenotypes with altered metabolism and signaling. The co-evolution of wound-like microenvironments and their inhabitants may lead to the selection and stabilization of degenerated cellular phenotypes, via acquisition of epigenetic modifications and mutations, which eventually result in degenerative disorders such as cancer and Alzheimer's disease. PMID:26041885

Recent advances in acute myeloid leukemia stem cell biology.

PubMed

Horton, Sarah J; Huntly, Brian J P

2012-07-01

The existence of cancer stem cells has long been postulated, but was proven less than 20 years ago following the demonstration that only a small sub-fraction of leukemic cells from acute myeloid leukemia patients were able to propagate the disease in xenografts. These cells were termed leukemic stem cells since they exist at the apex of a loose hierarchy, possess extensive self-renewal and the ability to undergo limited differentiation into leukemic blasts. Acute myeloid leukemia is a heterogeneous condition at both the phenotypic and molecular level with a variety of distinct genetic alterations giving rise to the disease. Recent studies have highlighted that this heterogeneity extends to the leukemic stem cell, with this dynamic compartment evolving to overcome various selection pressures imposed upon it during disease progression. The result is a complex situation in which multiple pools of leukemic stem cells may exist within individual patients which differ both phenotypically and molecularly. Since leukemic stem cells are thought to be resistant to current chemotherapeutic regimens and mediate disease relapse, their study also has potentially profound clinical implications. Numerous studies have generated important recent advances in the field, including the identification of novel leukemic stem cell-specific cell surface antigens and gene expression signatures. These tools will no doubt prove invaluable for the rational design of targeted therapies in the future.

Common variants in Mendelian kidney disease genes and their association with renal function.

PubMed

Parsa, Afshin; Fuchsberger, Christian; Köttgen, Anna; O'Seaghdha, Conall M; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M; Borecki, Ingrid; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Bochud, Murielle; Heid, Iris M; Siscovick, David S; Fox, Caroline S; Kao, W Linda; Böger, Carsten A

2013-12-01

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.

Recapitulating physiological and pathological shear stress and oxygen to model vasculature in health and disease

NASA Astrophysics Data System (ADS)

Abaci, Hasan Erbil; Shen, Yu-I.; Tan, Scott; Gerecht, Sharon

2014-05-01

Studying human vascular disease in conventional cell cultures and in animal models does not effectively mimic the complex vascular microenvironment and may not accurately predict vascular responses in humans. We utilized a microfluidic device to recapitulate both shear stress and O2 levels in health and disease, establishing a microfluidic vascular model (μVM). Maintaining human endothelial cells (ECs) in healthy-mimicking conditions resulted in conversion to a physiological phenotype namely cell elongation, reduced proliferation, lowered angiogenic gene expression and formation of actin cortical rim and continuous barrier. We next examined the responses of the healthy μVM to a vasotoxic cancer drug, 5-Fluorouracil (5-FU), in comparison with an in vivo mouse model. We found that 5-FU does not induce apoptosis rather vascular hyperpermeability, which can be alleviated by Resveratrol treatment. This effect was confirmed by in vivo findings identifying a vasoprotecting strategy by the adjunct therapy of 5-FU with Resveratrol. The μVM of ischemic disease demonstrated the transition of ECs from a quiescent to an activated state, with higher proliferation rate, upregulation of angiogenic genes, and impaired barrier integrity. The μVM offers opportunities to study and predict human ECs with physiologically relevant phenotypes in healthy, pathological and drug-treated environments.

Toward a mtDNA locus-specific mutation database using the LOVD platform.

PubMed

Elson, Joanna L; Sweeney, Mary G; Procaccio, Vincent; Yarham, John W; Salas, Antonio; Kong, Qing-Peng; van der Westhuizen, Francois H; Pitceathly, Robert D S; Thorburn, David R; Lott, Marie T; Wallace, Douglas C; Taylor, Robert W; McFarland, Robert

2012-09-01

The Human Variome Project (HVP) is a global effort to collect and curate all human genetic variation affecting health. Mutations of mitochondrial DNA (mtDNA) are an important cause of neurogenetic disease in humans; however, identification of the pathogenic mutations responsible can be problematic. In this article, we provide explanations as to why and suggest how such difficulties might be overcome. We put forward a case in support of a new Locus Specific Mutation Database (LSDB) implemented using the Leiden Open-source Variation Database (LOVD) system that will not only list primary mutations, but also present the evidence supporting their role in disease. Critically, we feel that this new database should have the capacity to store information on the observed phenotypes alongside the genetic variation, thereby facilitating our understanding of the complex and variable presentation of mtDNA disease. LOVD supports fast queries of both seen and hidden data and allows storage of sequence variants from high-throughput sequence analysis. The LOVD platform will allow construction of a secure mtDNA database; one that can fully utilize currently available data, as well as that being generated by high-throughput sequencing, to link genotype with phenotype enhancing our understanding of mitochondrial disease, with a view to providing better prognostic information. © 2012 Wiley Periodicals, Inc.

Toward a mtDNA Locus-Specific Mutation Database Using the LOVD Platform

PubMed Central

Elson, Joanna L.; Sweeney, Mary G.; Procaccio, Vincent; Yarham, John W.; Salas, Antonio; Kong, Qing-Peng; van der Westhuizen, Francois H.; Pitceathly, Robert D.S.; Thorburn, David R.; Lott, Marie T.; Wallace, Douglas C.; Taylor, Robert W.; McFarland, Robert

2015-01-01

The Human Variome Project (HVP) is a global effort to collect and curate all human genetic variation affecting health. Mutations of mitochondrial DNA (mtDNA) are an important cause of neurogenetic disease in humans; however, identification of the pathogenic mutations responsible can be problematic. In this article, we provide explanations as to why and suggest how such difficulties might be overcome. We put forward a case in support of a new Locus Specific Mutation Database (LSDB) implemented using the Leiden Open-source Variation Database (LOVD) system that will not only list primary mutations, but also present the evidence supporting their role in disease. Critically, we feel that this new database should have the capacity to store information on the observed phenotypes alongside the genetic variation, thereby facilitating our understanding of the complex and variable presentation of mtDNA disease. LOVD supports fast queries of both seen and hidden data and allows storage of sequence variants from high-throughput sequence analysis. The LOVD platform will allow construction of a secure mtDNA database; one that can fully utilize currently available data, as well as that being generated by high-throughput sequencing, to link genotype with phenotype enhancing our understanding of mitochondrial disease, with a view to providing better prognostic information. PMID:22581690

A kidney-disease gene panel allows a comprehensive genetic diagnosis of cystic and glomerular inherited kidney diseases.

PubMed

Bullich, Gemma; Domingo-Gallego, Andrea; Vargas, Iván; Ruiz, Patricia; Lorente-Grandoso, Laura; Furlano, Mónica; Fraga, Gloria; Madrid, Álvaro; Ariceta, Gema; Borregán, Mar; Piñero-Fernández, Juan Alberto; Rodríguez-Peña, Lidia; Ballesta-Martínez, Maria Juliana; Llano-Rivas, Isabel; Meñica, Mireia Aguirre; Ballarín, José; Torrents, David; Torra, Roser; Ars, Elisabet

2018-05-22

Molecular diagnosis of inherited kidney diseases remains a challenge due to their expanding phenotypic spectra as well as the constantly growing list of disease-causing genes. Here we develop a comprehensive approach for genetic diagnosis of inherited cystic and glomerular nephropathies. Targeted next generation sequencing of 140 genes causative of or associated with cystic or glomerular nephropathies was performed in 421 patients, a validation cohort of 116 patients with previously known mutations, and a diagnostic cohort of 207 patients with suspected inherited cystic disease and 98 patients with glomerular disease. In the validation cohort, a sensitivity of 99% was achieved. In the diagnostic cohort, causative mutations were found in 78% of patients with cystic disease and 62% of patients with glomerular disease, mostly familial cases, including copy number variants. Results depict the distribution of different cystic and glomerular inherited diseases showing the most likely diagnosis according to perinatal, pediatric and adult disease onset. Of all the genetically diagnosed patients, 15% were referred with an unspecified clinical diagnosis and in 2% genetic testing changed the clinical diagnosis. Therefore, in 17% of cases our genetic analysis was crucial to establish the correct diagnosis. Complex inheritance patterns in autosomal dominant polycystic kidney disease and Alport syndrome were suspected in seven and six patients, respectively. Thus, our kidney-disease gene panel is a comprehensive, noninvasive, and cost-effective tool for genetic diagnosis of cystic and glomerular inherited kidney diseases. This allows etiologic diagnosis in three-quarters of patients and is especially valuable in patients with unspecific or atypical phenotypes. Copyright © 2018 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

Analysis of five chronic inflammatory diseases identifies 27 new associations and highlights disease-specific patterns at shared loci

PubMed Central

Ellinghaus, David; Jostins, Luke; Spain, Sarah L; Cortes, Adrian; Bethune, Jörn; Han, Buhm; Park, Yu Rang; Raychaudhuri, Soumya; Pouget, Jennie G; Hübenthal, Matthias; Folseraas, Trine; Wang, Yunpeng; Esko, Tonu; Metspalu, Andres; Westra, Harm-Jan; Franke, Lude; Pers, Tune H; Weersma, Rinse K; Collij, Valerie; D'Amato, Mauro; Halfvarson, Jonas; Jensen, Anders Boeck; Lieb, Wolfgang; Degenhardt, Franziska; Forstner, Andreas J; Hofmann, Andrea; Schreiber, Stefan; Mrowietz, Ulrich; Juran, Brian D; Lazaridis, Konstantinos N; Brunak, Søren; Dale, Anders M; Trembath, Richard C; Weidinger, Stephan; Weichenthal, Michael; Ellinghaus, Eva; Elder, James T; Barker, Jonathan NWN; Andreassen, Ole A; McGovern, Dermot P; Karlsen, Tom H; Barrett, Jeffrey C; Parkes, Miles; Brown, Matthew A; Franke, Andre

2016-01-01

We simultaneously investigated the genetic landscape of ankylosing spondylitis, Crohn's disease, psoriasis, primary sclerosing cholangitis and ulcerative colitis to investigate pleiotropy and the relationship between these clinically related diseases. Using high-density genotype data from more than 86,000 individuals of European-ancestry we identified 244 independent multi-disease signals including 27 novel genome-wide significant susceptibility loci and 3 unreported shared risk loci. Complex pleiotropy was supported when contrasting multi-disease signals with expression data sets from human, rat and mouse, and epigenetic and expressed enhancer profiles. The comorbidities among the five immune diseases were best explained by biological pleiotropy rather than heterogeneity (a subgroup of cases that is genetically identical to another disease, possibly due to diagnostic misclassification, molecular subtypes, or excessive comorbidity). In particular, the strong comorbidity between primary sclerosing cholangitis and inflammatory bowel disease is likely the result of a unique disease, which is genetically distinct from classical inflammatory bowel disease phenotypes. PMID:26974007

Towards an Age-Phenome Knowledge-base

PubMed Central

2011-01-01

Background Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages. Results Here we present the Age-Phenome Knowledge-base (APK), in which knowledge about age-related phenotypic patterns and events can be modeled and stored for retrieval. The APK contains evidence connecting specific ages or age groups with phenotypes, such as disease and clinical traits. Using a simple text mining tool developed for this purpose, we extracted instances of age-phenotype associations from journal abstracts related to non-insulin-dependent Diabetes Mellitus. In addition, links between age and phenotype were extracted from clinical data obtained from the NHANES III survey. The knowledge stored in the APK is made available for the relevant research community in the form of 'Age-Cards', each card holds the collection of all the information stored in the APK about a particular age. These Age-Cards are presented in a wiki, allowing community review, amendment and contribution of additional information. In addition to the wiki interaction, complex searches can also be conducted which require the user to have some knowledge of database query construction. Conclusions The combination of a knowledge model based repository with community participation in the evolution and refinement of the knowledge-base makes the APK a useful and valuable environment for collecting and curating existing knowledge of the connections between age and phenotypes. PMID:21651792

The Effect of Parkinson Disease Tremor Phenotype on Cepstral Peak Prominence and Transglottal Airflow in Vowels and Speech.

PubMed

Burk, Brittany R; Watts, Christopher R

2018-02-19

The physiological manifestations of Parkinson disease are heterogeneous, as evidenced by disease subtypes. Dysphonia has been well documented as an early and progressively significant impairment associated with the disease. The purpose of this study was to investigate how acoustic and aerodynamic measures of vocal function were affected by Parkinson tremor subtype (phenotype) in an effort to better understand the heterogeneity of voice impairment severity in Parkinson disease. This is a prospective case-control study. Thirty-two speakers with Parkinson disease assigned to tremor and nontremor phenotypes and 10 healthy controls were recruited. Sustained vowels and connected speech were recorded from each speaker. Acoustic measures of cepstral peak prominence (CPP) and aerodynamic measures of transglottal airflow (TAF) were calculated from the recorded acoustic and aerodynamic waveforms. Speakers with a nontremor dominant phenotype exhibited significantly (P < 0.05) lower CPP and higher TAF in vowels compared with the tremor dominant phenotype and control speakers, who were not different from each other. No significant group differences were observed for CPP or TAF in connected speech. When producing vowels, participants with nontremor dominant phenotype exhibited reduced phonation periodicity and elevated TAF compared with tremor dominant and control participants. This finding is consistent with differential limb-motor and cognitive impairments between tremor and nontremor phenotypes reported in the extant literature. Results suggest that sustained vowel production may be sensitive to phonatory control as a function of Parkinson tremor phenotype in mild to moderate stages of the disease. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

The spectrum of clinical presentation, diagnosis, and management of mitochondrial forms of diabetes.

PubMed

Karaa, Amel; Goldstein, Amy

2015-02-01

Primary mitochondrial diseases refer to a group of heterogeneous and complex genetic disorders affecting 1:5000 people. The true prevalence is anticipated to be even higher because of the complexity of achieving a diagnosis in many patients who present with multisystemic complaints ranging from infancy to adulthood. Diabetes is a prominent feature of several of these disorders which might be overlooked by the endocrinologist. We here review mitochondrial disorders and describe the phenotypic and pathogenetic differences between mitochondrial diabetes mellitus (mDM) and other more common forms of diabetes mellitus. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Network for Early Onset Cystic Kidney Diseases-A Comprehensive Multidisciplinary Approach to Hereditary Cystic Kidney Diseases in Childhood.

PubMed

König, Jens Christian; Titieni, Andrea; Konrad, Martin

2018-01-01

Hereditary cystic kidney diseases comprise a complex group of genetic disorders representing one of the most common causes of end-stage renal failure in childhood. The main representatives are autosomal recessive polycystic kidney disease, nephronophthisis, Bardet-Biedl syndrome, and hepatocyte nuclear factor-1beta nephropathy. Within the last years, genetic efforts have brought tremendous progress for the molecular understanding of hereditary cystic kidney diseases identifying more than 70 genes. Yet, genetic heterogeneity, phenotypic variability, a lack of reliable genotype-phenotype correlations and the absence of disease-specific biomarkers remain major challenges for physicians treating children with cystic kidney diseases. To tackle these challenges comprehensive scientific approaches are urgently needed that match the ongoing "revolution" in genetics and molecular biology with an improved efficacy of clinical data collection. Network for early onset cystic kidney diseases (NEOCYST) is a multidisciplinary, multicenter collaborative combining a detailed collection of clinical data with translational scientific approaches addressing the genetic, molecular, and functional background of hereditary cystic kidney diseases. Consisting of seven work packages, including an international registry as well as a biobank, NEOCYST is not only dedicated to current scientific questions, but also provides a platform for longitudinal clinical surveillance and provides precious sources for high-quality research projects and future clinical trials. Funded by the German Federal Government, the NEOCYST collaborative started in February 2016. Here, we would like to introduce the rationale, design, and objectives of the network followed by a short overview on the current state of progress.

Ploidy-Regulated Variation in Biofilm-Related Phenotypes in Natural Isolates of Saccharomyces cerevisiae

PubMed Central

Hope, Elyse A.; Dunham, Maitreya J.

2014-01-01

The ability of yeast to form biofilms contributes to better survival under stressful conditions. We see the impact of yeast biofilms and “flocs” (clumps) in human health and industry, where forming clumps enables yeast to act as a natural filter in brewing and forming biofilms enables yeast to remain virulent in cases of fungal infection. Despite the importance of biofilms in yeast natural isolates, the majority of our knowledge about yeast biofilm genetics comes from work with a few tractable laboratory strains. A new collection of sequenced natural isolates from the Saccharomyces Genome Resequencing Project enabled us to examine the breadth of biofilm-related phenotypes in geographically, ecologically, and genetically diverse strains of Saccharomyces cerevisiae. We present a panel of 31 haploid and 24 diploid strains for which we have characterized six biofilm-related phenotypes: complex colony morphology, complex mat formation, flocculation, agar invasion, polystyrene adhesion, and psuedohyphal growth. Our results show that there is extensive phenotypic variation between and within strains, and that these six phenotypes are primarily uncorrelated or weakly correlated, with the notable exception of complex colony and complex mat formation. We also show that the phenotypic strength of these strains varies significantly depending on ploidy, and the diploid strains demonstrate both decreased and increased phenotypic strength with respect to their haploid counterparts. This is a more complex view of the impact of ploidy on biofilm-related phenotypes than previous work with laboratory strains has suggested, demonstrating the importance and enormous potential of working with natural isolates of yeast. PMID:25060625

Ploidy-regulated variation in biofilm-related phenotypes in natural isolates of Saccharomyces cerevisiae.

PubMed

Hope, Elyse A; Dunham, Maitreya J

2014-07-24

The ability of yeast to form biofilms contributes to better survival under stressful conditions. We see the impact of yeast biofilms and "flocs" (clumps) in human health and industry, where forming clumps enables yeast to act as a natural filter in brewing and forming biofilms enables yeast to remain virulent in cases of fungal infection. Despite the importance of biofilms in yeast natural isolates, the majority of our knowledge about yeast biofilm genetics comes from work with a few tractable laboratory strains. A new collection of sequenced natural isolates from the Saccharomyces Genome Resequencing Project enabled us to examine the breadth of biofilm-related phenotypes in geographically, ecologically, and genetically diverse strains of Saccharomyces cerevisiae. We present a panel of 31 haploid and 24 diploid strains for which we have characterized six biofilm-related phenotypes: complex colony morphology, complex mat formation, flocculation, agar invasion, polystyrene adhesion, and psuedohyphal growth. Our results show that there is extensive phenotypic variation between and within strains, and that these six phenotypes are primarily uncorrelated or weakly correlated, with the notable exception of complex colony and complex mat formation. We also show that the phenotypic strength of these strains varies significantly depending on ploidy, and the diploid strains demonstrate both decreased and increased phenotypic strength with respect to their haploid counterparts. This is a more complex view of the impact of ploidy on biofilm-related phenotypes than previous work with laboratory strains has suggested, demonstrating the importance and enormous potential of working with natural isolates of yeast. Copyright © 2014 Hope and Dunham.

Sherlock: Detecting Gene-Disease Associations by Matching Patterns of Expression QTL and GWAS

PubMed Central

He, Xin; Fuller, Chris K.; Song, Yi; Meng, Qingying; Zhang, Bin; Yang, Xia; Li, Hao

2013-01-01

Genetic mapping of complex diseases to date depends on variations inside or close to the genes that perturb their activities. A strong body of evidence suggests that changes in gene expression play a key role in complex diseases and that numerous loci perturb gene expression in trans. The information in trans variants, however, has largely been ignored in the current analysis paradigm. Here we present a statistical framework for genetic mapping by utilizing collective information in both cis and trans variants. We reason that for a disease-associated gene, any genetic variation that perturbs its expression is also likely to influence the disease risk. Thus, the expression quantitative trait loci (eQTL) of the gene, which constitute a unique “genetic signature,” should overlap significantly with the set of loci associated with the disease. We translate this idea into a computational algorithm (named Sherlock) to search for gene-disease associations from GWASs, taking advantage of independent eQTL data. Application of this strategy to Crohn disease and type 2 diabetes predicts a number of genes with possible disease roles, including several predictions supported by solid experimental evidence. Importantly, predicted genes are often implicated by multiple trans eQTL with moderate associations. These genes are far from any GWAS association signals and thus cannot be identified from the GWAS alone. Our approach allows analysis of association data from a new perspective and is applicable to any complex phenotype. It is readily generalizable to molecular traits other than gene expression, such as metabolites, noncoding RNAs, and epigenetic modifications. PMID:23643380

A Mild Form of COG5 Defect Showing Early-Childhood-Onset Friedreich's-Ataxia-Like Phenotypes with Isolated Cerebellar Atrophy.

PubMed

Kim, Young Ok; Yun, Misun; Jeong, Jae Ho; Choi, Seong Min; Kim, Seul Kee; Yoon, Woong; Park, Chungoo; Hong, Yeongjin; Woo, Young Jong

2017-11-01

Progressive cerebellar ataxias are rare diseases during childhood, especially under 6 years of age. In a single family, three affected siblings exhibited Friedreich's-ataxia-like phenotypes before 2 years of age. They had progressive cerebellar atrophy, intellectual disability, and scoliosis. Although their phenotypes were similar to those observed in patients with autosomal recessive cerebellar ataxias, other phenotypes (e.g., seizure, movement disorders, ophthalmologic disturbance, cardiomyopathy, and cutaneous disorders) were not noted in this family. Whole-exome sequencing of the family members revealed one potential heterozygous mutation (c.1209delG, NM_181733.2; p.Met403IlefsX3, NP_859422.2) of the gene encoding conserved oligomeric Golgi complex subunit 5 (COG5). The heterozygous deletion at the fifth base in exon 12 of COG5 caused a frameshift and premature stop. Western blotting of COG5 proteins in the skin tissues from an affected proband showed a significantly decreased level of full length COG5 and smaller, aberrant COG5 proteins. We reported a milder form of COG5 defect showing Friedreich's-ataxia-like phenotypes without hypotonia, microcephaly, and short stature that were observed in most patients with COG5 defect. © 2017 The Korean Academy of Medical Sciences.

Discovering susceptibility genes for allergic rhinitis and allergy using a genome-wide association study strategy.

PubMed

Li, Jingyun; Zhang, Yuan; Zhang, Luo

2015-02-01

Allergic rhinitis and allergy are complex conditions, in which both genetic and environmental factors contribute to the pathogenesis. Genome-wide association studies (GWASs) employing common single-nucleotide polymorphisms have accelerated the search for novel and interesting genes, and also confirmed the role of some previously described genes which may be involved in the cause of allergic rhinitis and allergy. The aim of this review is to provide an overview of the genetic basis of allergic rhinitis and the associated allergic phenotypes, with particular focus on GWASs. The last decade has been marked by the publication of more than 20 GWASs of allergic rhinitis and the associated allergic phenotypes. Allergic diseases and traits have been shown to share a large number of genetic susceptibility loci, of which IL33/IL1RL1, IL-13-RAD50 and C11orf30/LRRC32 appear to be important for more than two allergic phenotypes. GWASs have further reflected the genetic heterogeneity underlying allergic phenotypes. Large-scale genome-wide association strategies are underway to discover new susceptibility variants for allergic rhinitis and allergic phenotypes. Characterization of the underlying genetics provides us with an insight into the potential targets for future studies and the corresponding interventions.

Management and analysis of genomic functional and phenotypic controlled annotations to support biomedical investigation and practice.

PubMed

Masseroli, Marco

2007-07-01

The growing available genomic information provides new opportunities for novel research approaches and original biomedical applications that can provide effective data management and analysis support. In fact, integration and comprehensive evaluation of available controlled data can highlight information patterns leading to unveil new biomedical knowledge. Here, we describe Genome Function INtegrated Discover (GFINDer), a Web-accessible three-tier multidatabase system we developed to automatically enrich lists of user-classified genes with several functional and phenotypic controlled annotations, and to statistically evaluate them in order to identify annotation categories significantly over- or underrepresented in each considered gene class. Genomic controlled annotations from Gene Ontology (GO), KEGG, Pfam, InterPro, and Online Mendelian Inheritance in Man (OMIM) were integrated in GFINDer and several categorical tests were implemented for their analysis. A controlled vocabulary of inherited disorder phenotypes was obtained by normalizing and hierarchically structuring disease accompanying signs and symptoms from OMIM Clinical Synopsis sections. GFINDer modular architecture is well suited for further system expansion and for sustaining increasing workload. Testing results showed that GFINDer analyses can highlight gene functional and phenotypic characteristics and differences, demonstrating its value in supporting genomic biomedical approaches aiming at understanding the complex biomolecular mechanisms underlying patho-physiological phenotypes, and in helping the transfer of genomic results to medical practice.

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

PubMed

Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Ndufs4 related Leigh syndrome: A case report and review of the literature.

PubMed

Ortigoza-Escobar, Juan Darío; Oyarzabal, Alfonso; Montero, Raquel; Artuch, Rafael; Jou, Cristina; Jiménez, Cecilia; Gort, Laura; Briones, Paz; Muchart, Jordi; López-Gallardo, Ester; Emperador, Sonia; Pesini, Eduardo Ruiz; Montoya, Julio; Pérez, Belén; Rodríguez-Pombo, Pilar; Pérez-Dueñas, Belén

2016-05-01

The genetic causes of Leigh syndrome are heterogeneous, with a poor correlation between the phenotype and genotype. Here, we present a patient with an NDUFS4 mutation to expand the clinical and biochemical spectrum of the disease. A combined defect in the CoQ, PDH and RCC activities in our patient was due to an inappropriate assembly of the RCC complex I (CI), which was confirmed using Blue-Native polyacrylamide gel electrophoresis (BN-PAGE) analysis. Targeted exome sequencing analysis allowed for the genetic diagnosis of this patient. We reviewed 198 patients with 24 different genetic defects causing RCC I deficiency and compared them to 22 NDUFS4 patients. We concluded that NDUFS4-related Leigh syndrome is invariably linked to an early onset severe phenotype that results in early death. Some data, including the clinical phenotype, neuroimaging and biochemical findings, can guide the genetic study in patients with RCC I deficiency. Copyright © 2016 Elsevier B.V. and Mitochondria Research Society. All rights reserved.

Whole genome prediction and heritability of childhood asthma phenotypes.

PubMed

McGeachie, Michael J; Clemmer, George L; Croteau-Chonka, Damien C; Castaldi, Peter J; Cho, Michael H; Sordillo, Joanne E; Lasky-Su, Jessica A; Raby, Benjamin A; Tantisira, Kelan G; Weiss, Scott T

2016-12-01

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes. We applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV 1 ), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. We found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.

Genetics of pediatric obesity.

PubMed

Manco, Melania; Dallapiccola, Bruno

2012-07-01

Onset of obesity has been anticipated at earlier ages, and prevalence has dramatically increased worldwide over the past decades. Epidemic obesity is mainly attributable to modern lifestyle, but family studies prove the significant role of genes in the individual's predisposition to obesity. Advances in genotyping technologies have raised great hope and expectations that genetic testing will pave the way to personalized medicine and that complex traits such as obesity will be prevented even before birth. In the presence of the pressing offer of direct-to-consumer genetic testing services from private companies to estimate the individual's risk for complex phenotypes including obesity, the present review offers pediatricians an update of the state of the art on genomics obesity in childhood. Discrepancies with respect to genomics of adult obesity are discussed. After an appraisal of findings from genome-wide association studies in pediatric populations, the rare variant-common disease hypothesis, the theoretical soil for next-generation sequencing techniques, is discussed as opposite to the common disease-common variant hypothesis. Next-generation sequencing techniques are expected to fill the gap of "missing heritability" of obesity, identifying rare variants associated with the trait and clarifying the role of epigenetics in its heritability. Pediatric obesity emerges as a complex phenotype, modulated by unique gene-environment interactions that occur in periods of life and are "permissive" for the programming of adult obesity. With the advent of next-generation sequencing techniques and advances in the field of exposomics, sensitive and specific tools to predict the obesity risk as early as possible are the challenge for the next decade.

Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.

PubMed

Harrow, Ian; Jiménez-Ruiz, Ernesto; Splendiani, Andrea; Romacker, Martin; Woollard, Peter; Markel, Scott; Alam-Faruque, Yasmin; Koch, Martin; Malone, James; Waaler, Arild

2017-12-02

The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.

Beyond the zebrafish: diverse fish species for modeling human disease

PubMed Central

Schartl, Manfred

2014-01-01

ABSTRACT In recent years, zebrafish, and to a lesser extent medaka, have become widely used small animal models for human diseases. These organisms have convincingly demonstrated the usefulness of fish for improving our understanding of the molecular and cellular mechanisms leading to pathological conditions, and for the development of new diagnostic and therapeutic tools. Despite the usefulness of zebrafish and medaka in the investigation of a wide spectrum of traits, there is evidence to suggest that other fish species could be better suited for more targeted questions. With the emergence of new, improved sequencing technologies that enable genomic resources to be generated with increasing efficiency and speed, the potential of non-mainstream fish species as disease models can now be explored. A key feature of these fish species is that the pathological condition that they model is often related to specific evolutionary adaptations. By exploring these adaptations, new disease-causing and disease-modifier genes might be identified; thus, diverse fish species could be exploited to better understand the complexity of disease processes. In addition, non-mainstream fish models could allow us to study the impact of environmental factors, as well as genetic variation, on complex disease phenotypes. This Review will discuss the opportunities that such fish models offer for current and future biomedical research. PMID:24271780

Systems and precision medicine approaches to diabetes heterogeneity: a Big Data perspective.

PubMed

Capobianco, Enrico

2017-12-01

Big Data, and in particular Electronic Health Records, provide the medical community with a great opportunity to analyze multiple pathological conditions at an unprecedented depth for many complex diseases, including diabetes. How can we infer on diabetes from large heterogeneous datasets? A possible solution is provided by invoking next-generation computational methods and data analytics tools within systems medicine approaches. By deciphering the multi-faceted complexity of biological systems, the potential of emerging diagnostic tools and therapeutic functions can be ultimately revealed. In diabetes, a multidimensional approach to data analysis is needed to better understand the disease conditions, trajectories and the associated comorbidities. Elucidation of multidimensionality comes from the analysis of factors such as disease phenotypes, marker types, and biological motifs while seeking to make use of multiple levels of information including genetics, omics, clinical data, and environmental and lifestyle factors. Examining the synergy between multiple dimensions represents a challenge. In such regard, the role of Big Data fuels the rise of Precision Medicine by allowing an increasing number of descriptions to be captured from individuals. Thus, data curations and analyses should be designed to deliver highly accurate predicted risk profiles and treatment recommendations. It is important to establish linkages between systems and precision medicine in order to translate their principles into clinical practice. Equivalently, to realize their full potential, the involved multiple dimensions must be able to process information ensuring inter-exchange, reducing ambiguities and redundancies, and ultimately improving health care solutions by introducing clinical decision support systems focused on reclassified phenotypes (or digital biomarkers) and community-driven patient stratifications.

Functional Anatomy of the Outflow Facilities.

PubMed

Pizzirani, Stefano; Gong, Haiyan

2015-11-01

In order to understand the pathophysiology, select optimal therapeutic options for patients and provide clients with honest expectations for cases of canine glaucoma, clinicians should be familiar with a rational understanding of the functional anatomy of the ocular structures involved in this group of diseases. The topographical extension and the structural and humoral complexity of the regions involved with the production and the outflow of aqueous humor undergo numerous changes with aging and disease. Therefore, the anatomy relative to the fluid dynamics of aqueous has become a pivotal yet flexible concept to interpret the different phenotypes of glaucoma. Copyright © 2015 Elsevier Inc. All rights reserved.

Genomics and epigenomics in rheumatic diseases: what do they provide in terms of diagnosis and disease management?

PubMed

Castro-Santos, Patricia; Díaz-Peña, Roberto

2017-09-01

Most rheumatic diseases are complex or multifactorial entities with pathogeneses that interact with both multiple genetic factors and a high number of diverse environmental factors. Knowledge of the human genome sequence and its diversity among populations has provided a crucial step forward in our understanding of genetic diseases, identifying many genetic loci or genes associated with diverse phenotypes. In general, susceptibility to autoimmunity is associated with multiple risk factors, but the mechanism of the environmental component influence is poorly understood. Studies in twins have demonstrated that genetics do not explain the totality of the pathogenesis of rheumatic diseases. One method of modulating gene expression through environmental effects is via epigenetic modifications. These techniques open a new field for identifying useful new biomarkers and therapeutic targets. In this context, the development of "-omics" techniques is an opportunity to progress in our knowledge of complex diseases, impacting the discovery of new potential biomarkers suitable for their introduction into clinical practice. In this review, we focus on the recent advances in the fields of genomics and epigenomics in rheumatic diseases and their potential to be useful for the diagnosis, follow-up, and treatment of these diseases. The ultimate aim of genomic studies in any human disease is to understand its pathogenesis, thereby enabling the prediction of the evolution of the disease to establish new treatments and address the development of personalized therapies.

Peroxisome biogenesis disorders in the Zellweger spectrum: An overview of current diagnosis, clinical manifestations, and treatment guidelines.

PubMed

Braverman, Nancy E; Raymond, Gerald V; Rizzo, William B; Moser, Ann B; Wilkinson, Mark E; Stone, Edwin M; Steinberg, Steven J; Wangler, Michael F; Rush, Eric T; Hacia, Joseph G; Bose, Mousumi

2016-03-01

Peroxisome biogenesis disorders in the Zellweger spectrum (PBD-ZSD) are a heterogeneous group of genetic disorders caused by mutations in PEX genes responsible for normal peroxisome assembly and functions. As a result of impaired peroxisomal activities, individuals with PBD-ZSD can manifest a complex spectrum of clinical phenotypes that typically result in shortened life spans. The extreme variability in disease manifestation ranging from onset of profound neurologic symptoms in newborns to progressive degenerative disease in adults presents practical challenges in disease diagnosis and medical management. Recent advances in biochemical methods for newborn screening and genetic testing have provided unprecedented opportunities for identifying patients at the earliest possible time and defining the molecular bases for their diseases. Here, we provide an overview of current clinical approaches for the diagnosis of PBD-ZSD and provide broad guidelines for the treatment of disease in its wide variety of forms. Although we anticipate future progress in the development of more effective targeted interventions, the current guidelines are meant to provide a starting point for the management of these complex conditions in the context of personalized health care. Copyright © 2015 Elsevier Inc. All rights reserved.

Dissection of Host Susceptibility to Bacterial Infections and Its Toxins.

PubMed

Nashef, Aysar; Agbaria, Mahmoud; Shusterman, Ariel; Lorè, Nicola Ivan; Bragonzi, Alessandra; Wiess, Ervin; Houri-Haddad, Yael; Iraqi, Fuad A

2017-01-01

Infection is one of the leading causes of human mortality and morbidity. Exposure to microbial agents is obviously required. However, also non-microbial environmental and host factors play a key role in the onset, development and outcome of infectious disease, resulting in large of clinical variability between individuals in a population infected with the same microbe. Controlled and standardized investigations of the genetics of susceptibility to infectious disease are almost impossible to perform in humans whereas mouse models allow application of powerful genomic techniques to identify and validate causative genes underlying human diseases with complex etiologies. Most of current animal models used in complex traits diseases genetic mapping have limited genetic diversity. This limitation impedes the ability to create incorporated network using genetic interactions, epigenetics, environmental factors, microbiota, and other phenotypes. A novel mouse genetic reference population for high-resolution mapping and subsequently identifying genes underlying the QTL, namely the Collaborative Cross (CC) mouse genetic reference population (GRP) was recently developed. In this chapter, we discuss a variety of approaches using CC mice for mapping genes underlying quantitative trait loci (QTL) to dissect the host response to polygenic traits, including infectious disease caused by bacterial agents and its toxins.

A novel CISD2 mutation associated with a classical Wolfram syndrome phenotype alters Ca2+ homeostasis and ER-mitochondria interactions

PubMed Central

Rouzier, Cécile; Moore, David; Delorme, Cécile; Lacas-Gervais, Sandra; Ait-El-Mkadem, Samira; Fragaki, Konstantina; Burté, Florence; Serre, Valérie; Bannwarth, Sylvie; Chaussenot, Annabelle; Catala, Martin

2017-01-01

Abstract Wolfram syndrome (WS) is a progressive neurodegenerative disease characterized by early-onset optic atrophy and diabetes mellitus, which can be associated with more extensive central nervous system and endocrine complications. The majority of patients harbour pathogenic WFS1 mutations, but recessive mutations in a second gene, CISD2, have been described in a small number of families with Wolfram syndrome type 2 (WFS2). The defining diagnostic criteria for WFS2 also consist of optic atrophy and diabetes mellitus, but unlike WFS1, this phenotypic subgroup has been associated with peptic ulcer disease and an increased bleeding tendency. Here, we report on a novel homozygous CISD2 mutation (c.215A > G; p.Asn72Ser) in a Moroccan patient with an overlapping phenotype suggesting that Wolfram syndrome type 1 and type 2 form a continuous clinical spectrum with genetic heterogeneity. The present study provides strong evidence that this particular CISD2 mutation disturbs cellular Ca2+ homeostasis with enhanced Ca2+ flux from the ER to mitochondria and cytosolic Ca2+ abnormalities in patient-derived fibroblasts. This Ca2+ dysregulation was associated with increased ER-mitochondria contact, a swollen ER lumen and a hyperfused mitochondrial network in the absence of overt ER stress. Although there was no marked alteration in mitochondrial bioenergetics under basal conditions, culture of patient-derived fibroblasts in glucose-free galactose medium revealed a respiratory chain defect in complexes I and II, and a trend towards decreased ATP levels. Our results provide important novel insight into the potential disease mechanisms underlying the neurodegenerative consequences of CISD2 mutations and the subsequent development of multisystemic disease. PMID:28335035

Translational informatics approach for identifying the functional molecular communicators linking coronary artery disease, infection and inflammation

PubMed Central

SHARMA, ANKIT; GHATGE, MADANKUMAR; MUNDKUR, LAKSHMI; VANGALA, RAJANI KANTH

2016-01-01

Translational informatics approaches are required for the integration of diverse and accumulating data to enable the administration of effective translational medicine specifically in complex diseases such as coronary artery disease (CAD). In the current study, a novel approach for elucidating the association between infection, inflammation and CAD was used. Genes for CAD were collected from the CAD-gene database and those for infection and inflammation were collected from the UniProt database. The cytomegalovirus (CMV)-induced genes were identified from the literature and the CAD-associated clinical phenotypes were obtained from the Unified Medical Language System. A total of 55 gene ontologies (GO) termed functional communicator ontologies were identifed in the gene sets linking clinical phenotypes in the diseasome network. The network topology analysis suggested that important functions including viral entry, cell adhesion, apoptosis, inflammatory and immune responses networked with clinical phenotypes. Microarray data was extracted from the Gene Expression Omnibus (dataset: GSE48060) for highly networked disease myocardial infarction. Further analysis of differentially expressed genes and their GO terms suggested that CMV infection may trigger a xenobiotic response, oxidative stress, inflammation and immune modulation. Notably, the current study identified γ-glutamyl transferase (GGT)-5 as a potential biomarker with an odds ratio of 1.947, which increased to 2.561 following the addition of CMV and CMV-neutralizing antibody (CMV-NA) titers. The C-statistics increased from 0.530 for conventional risk factors (CRFs) to 0.711 for GGT in combination with the above mentioned infections and CRFs. Therefore, the translational informatics approach used in the current study identified a potential molecular mechanism for CMV infection in CAD, and a potential biomarker for risk prediction. PMID:27035874

The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species

PubMed Central

Mungall, Christopher J.; McMurry, Julie A.; Köhler, Sebastian; Balhoff, James P.; Borromeo, Charles; Brush, Matthew; Carbon, Seth; Conlin, Tom; Dunn, Nathan; Engelstad, Mark; Foster, Erin; Gourdine, J.P.; Jacobsen, Julius O.B.; Keith, Dan; Laraway, Bryan; Lewis, Suzanna E.; NguyenXuan, Jeremy; Shefchek, Kent; Vasilevsky, Nicole; Yuan, Zhou; Washington, Nicole; Hochheiser, Harry; Groza, Tudor; Smedley, Damian; Robinson, Peter N.; Haendel, Melissa A.

2017-01-01

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype–phenotype associations. Non-human organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research data can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative (monarchinitiative.org) is a collaborative, open science effort that aims to semantically integrate genotype–phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species. PMID:27899636

The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across species

DOE PAGES

Mungall, Christopher J.; McMurry, Julie A.; Köhler, Sebastian; ...

2016-11-29

The correlation of phenotypic outcomes with genetic variation and environmental factors is a core pursuit in biology and biomedicine. Numerous challenges impede our progress: patient phenotypes may not match known diseases, candidate variants may be in genes that have not been characterized, model organisms may not recapitulate human or veterinary diseases, filling evolutionary gaps is difficult, and many resources must be queried to find potentially significant genotype-phenotype associations. Nonhuman organisms have proven instrumental in revealing biological mechanisms. Advanced informatics tools can identify phenotypically relevant disease models in research and diagnostic contexts. Large-scale integration of model organism and clinical research datamore » can provide a breadth of knowledge not available from individual sources and can provide contextualization of data back to these sources. The Monarch Initiative (monarchinitiative.org) is a collaborative, open science effort that aims to semantically integrate genotype-phenotype data from many species and sources in order to support precision medicine, disease modeling, and mechanistic exploration. Our integrated knowledge graph, analytic tools, and web services enable diverse users to explore relationships between phenotypes and genotypes across species.« less

[Clinical and genetic study patients with tuberous sclerosis complex].

PubMed

Rubilar, Carla; López, Francisca; Troncoso, Mónica; Barrios, Andrés; Herrera, Luisa

2017-02-01

Tuberous sclerosis complex (TSC) is a multisystem autosomal dominant disease caused by mutations in the tumor suppressor genes TSC1 or TSC2. To characterize clinically and genetically patients diagnosed with TSC. Descriptive study of clinical records of 42 patients from a pediatric neuropsychiatry department diagnosed with TSC and genetic study in 21 of them. The exon 15 of TSC1 gene and exons 33, 36 and 37 of TSC2 gene were amplified by polymerase chain reaction and sequenced. The relationship between the mutations found with the severity and clinical course were analyzed. In 61.9% of the patients the symptoms began before 6 months of age. The initial most frequent manifestations of TSC were new onset of seizures (73.8%) and the detection of cardiac rhabdomyomas (16.6%). During the evolution of the disease all patients had neurological involvement; 92.9% had epilepsy. All patients presented hypomelanotic spots, 47.6% facial angiofibromas, 23.8% Shagreen patch, 47.6 heart rhabdomyomas and 35.7% retinal hamartomas. In the genetic study of 21 patients two heterozygous pathogenic mutations in TSC1 and one in TSC2 genes were identified. The latter had a more severe clinical phenotype. Neurological and dermatological manifestations were the most frequent ones in patients with TSC. Two pathogenic mutations in TSC1 and one in TSC2 genes were identified. The patient with TSC2 mutation manifested a more severe clinical phenotype.

Modulation of Microglial Activity by Rho-Kinase (ROCK) Inhibition as Therapeutic Strategy in Parkinson's Disease and Amyotrophic Lateral Sclerosis.

PubMed

Roser, Anna-Elisa; Tönges, Lars; Lingor, Paul

2017-01-01

Neurodegenerative diseases are characterized by the progressive degeneration of neurons in the central and peripheral nervous system (CNS, PNS), resulting in a reduced innervation of target structures and a loss of function. A shared characteristic of many neurodegenerative diseases is the infiltration of microglial cells into affected brain regions. During early disease stages microglial cells often display a rather neuroprotective phenotype, but switch to a more pro-inflammatory neurotoxic phenotype in later stages of the disease, contributing to the neurodegeneration. Activation of the Rho kinase (ROCK) pathway appears to be instrumental for the modulation of the microglial phenotype: increased ROCK activity in microglia mediates mechanisms of the inflammatory response and is associated with improved motility, increased production of reactive oxygen species (ROS) and release of inflammatory cytokines. Recently, several studies suggested inhibition of ROCK signaling as a promising treatment option for neurodegenerative diseases. In this review article, we discuss the contribution of microglial activity and phenotype switch to the pathophysiology of Parkinson's disease (PD) and Amyotrophic lateral sclerosis (ALS), two devastating neurodegenerative diseases without disease-modifying treatment options. Furthermore, we describe how ROCK inhibition can influence the microglial phenotype in disease models and explore ROCK inhibition as a future treatment option for PD and ALS.

Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis

PubMed Central

Shen, Feichen; Liu, Sijia; Wang, Yanshan; Wang, Liwei; Afzal, Naveed; Liu, Hongfang

2017-01-01

In the USA, rare diseases are defined as those affecting fewer than 200,000 patients at any given time. Patients with rare diseases are frequently misdiagnosed or undiagnosed which may due to the lack of knowledge and experience of care providers. We hypothesize that patients’ phenotypic information available in electronic medical records (EMR) can be leveraged to accelerate disease diagnosis based on the intuition that providers need to document associated phenotypic information to support the diagnosis decision, especially for rare diseases. In this study, we proposed a collaborative filtering system enriched with natural language processing and semantic techniques to assist rare disease diagnosis based on phenotypic characterization. Specifically, we leveraged four similarity measurements with two neighborhood algorithms on 2010-2015 Mayo Clinic unstructured large patient cohort and evaluated different approaches. Preliminary results demonstrated that the use of collaborative filtering with phenotypic information is able to stratify patients with relatively similar rare diseases. PMID:29854225

Leveraging Collaborative Filtering to Accelerate Rare Disease Diagnosis.

PubMed

Shen, Feichen; Liu, Sijia; Wang, Yanshan; Wang, Liwei; Afzal, Naveed; Liu, Hongfang

2017-01-01

In the USA, rare diseases are defined as those affecting fewer than 200,000 patients at any given time. Patients with rare diseases are frequently misdiagnosed or undiagnosed which may due to the lack of knowledge and experience of care providers. We hypothesize that patients' phenotypic information available in electronic medical records (EMR) can be leveraged to accelerate disease diagnosis based on the intuition that providers need to document associated phenotypic information to support the diagnosis decision, especially for rare diseases. In this study, we proposed a collaborative filtering system enriched with natural language processing and semantic techniques to assist rare disease diagnosis based on phenotypic characterization. Specifically, we leveraged four similarity measurements with two neighborhood algorithms on 2010-2015 Mayo Clinic unstructured large patient cohort and evaluated different approaches. Preliminary results demonstrated that the use of collaborative filtering with phenotypic information is able to stratify patients with relatively similar rare diseases.

Integrated platform for genome-wide screening and construction of high-density genetic interaction maps in mammalian cells

PubMed Central

Kampmann, Martin; Bassik, Michael C.; Weissman, Jonathan S.

2013-01-01

A major challenge of the postgenomic era is to understand how human genes function together in normal and disease states. In microorganisms, high-density genetic interaction (GI) maps are a powerful tool to elucidate gene functions and pathways. We have developed an integrated methodology based on pooled shRNA screening in mammalian cells for genome-wide identification of genes with relevant phenotypes and systematic mapping of all GIs among them. We recently demonstrated the potential of this approach in an application to pathways controlling the susceptibility of human cells to the toxin ricin. Here we present the complete quantitative framework underlying our strategy, including experimental design, derivation of quantitative phenotypes from pooled screens, robust identification of hit genes using ultra-complex shRNA libraries, parallel measurement of tens of thousands of GIs from a single double-shRNA experiment, and construction of GI maps. We describe the general applicability of our strategy. Our pooled approach enables rapid screening of the same shRNA library in different cell lines and under different conditions to determine a range of different phenotypes. We illustrate this strategy here for single- and double-shRNA libraries. We compare the roles of genes for susceptibility to ricin and Shiga toxin in different human cell lines and reveal both toxin-specific and cell line-specific pathways. We also present GI maps based on growth and ricin-resistance phenotypes, and we demonstrate how such a comparative GI mapping strategy enables functional dissection of physical complexes and context-dependent pathways. PMID:23739767

G-STRATEGY: Optimal Selection of Individuals for Sequencing in Genetic Association Studies

PubMed Central

Wang, Miaoyan; Jakobsdottir, Johanna; Smith, Albert V.; McPeek, Mary Sara

2017-01-01

In a large-scale genetic association study, the number of phenotyped individuals available for sequencing may, in some cases, be greater than the study’s sequencing budget will allow. In that case, it can be important to prioritize individuals for sequencing in a way that optimizes power for association with the trait. Suppose a cohort of phenotyped individuals is available, with some subset of them possibly already sequenced, and one wants to choose an additional fixed-size subset of individuals to sequence in such a way that the power to detect association is maximized. When the phenotyped sample includes related individuals, power for association can be gained by including partial information, such as phenotype data of ungenotyped relatives, in the analysis, and this should be taken into account when assessing whom to sequence. We propose G-STRATEGY, which uses simulated annealing to choose a subset of individuals for sequencing that maximizes the expected power for association. In simulations, G-STRATEGY performs extremely well for a range of complex disease models and outperforms other strategies with, in many cases, relative power increases of 20–40% over the next best strategy, while maintaining correct type 1 error. G-STRATEGY is computationally feasible even for large datasets and complex pedigrees. We apply G-STRATEGY to data on HDL and LDL from the AGES-Reykjavik and REFINE-Reykjavik studies, in which G-STRATEGY is able to closely-approximate the power of sequencing the full sample by selecting for sequencing a only small subset of the individuals. PMID:27256766

Network for Early Onset Cystic Kidney Diseases—A Comprehensive Multidisciplinary Approach to Hereditary Cystic Kidney Diseases in Childhood

PubMed Central

König, Jens Christian; Titieni, Andrea; Konrad, Martin; Bergmann, C.

2018-01-01

Hereditary cystic kidney diseases comprise a complex group of genetic disorders representing one of the most common causes of end-stage renal failure in childhood. The main representatives are autosomal recessive polycystic kidney disease, nephronophthisis, Bardet–Biedl syndrome, and hepatocyte nuclear factor-1beta nephropathy. Within the last years, genetic efforts have brought tremendous progress for the molecular understanding of hereditary cystic kidney diseases identifying more than 70 genes. Yet, genetic heterogeneity, phenotypic variability, a lack of reliable genotype–phenotype correlations and the absence of disease-specific biomarkers remain major challenges for physicians treating children with cystic kidney diseases. To tackle these challenges comprehensive scientific approaches are urgently needed that match the ongoing “revolution” in genetics and molecular biology with an improved efficacy of clinical data collection. Network for early onset cystic kidney diseases (NEOCYST) is a multidisciplinary, multicenter collaborative combining a detailed collection of clinical data with translational scientific approaches addressing the genetic, molecular, and functional background of hereditary cystic kidney diseases. Consisting of seven work packages, including an international registry as well as a biobank, NEOCYST is not only dedicated to current scientific questions, but also provides a platform for longitudinal clinical surveillance and provides precious sources for high-quality research projects and future clinical trials. Funded by the German Federal Government, the NEOCYST collaborative started in February 2016. Here, we would like to introduce the rationale, design, and objectives of the network followed by a short overview on the current state of progress. PMID:29497606

Exploring human disease using the Rat Genome Database.

PubMed

Shimoyama, Mary; Laulederkind, Stanley J F; De Pons, Jeff; Nigam, Rajni; Smith, Jennifer R; Tutaj, Marek; Petri, Victoria; Hayman, G Thomas; Wang, Shur-Jen; Ghiasvand, Omid; Thota, Jyothi; Dwinell, Melinda R

2016-10-01

Rattus norvegicus, the laboratory rat, has been a crucial model for studies of the environmental and genetic factors associated with human diseases for over 150 years. It is the primary model organism for toxicology and pharmacology studies, and has features that make it the model of choice in many complex-disease studies. Since 1999, the Rat Genome Database (RGD; http://rgd.mcw.edu) has been the premier resource for genomic, genetic, phenotype and strain data for the laboratory rat. The primary role of RGD is to curate rat data and validate orthologous relationships with human and mouse genes, and make these data available for incorporation into other major databases such as NCBI, Ensembl and UniProt. RGD also provides official nomenclature for rat genes, quantitative trait loci, strains and genetic markers, as well as unique identifiers. The RGD team adds enormous value to these basic data elements through functional and disease annotations, the analysis and visual presentation of pathways, and the integration of phenotype measurement data for strains used as disease models. Because much of the rat research community focuses on understanding human diseases, RGD provides a number of datasets and software tools that allow users to easily explore and make disease-related connections among these datasets. RGD also provides comprehensive human and mouse data for comparative purposes, illustrating the value of the rat in translational research. This article introduces RGD and its suite of tools and datasets to researchers - within and beyond the rat community - who are particularly interested in leveraging rat-based insights to understand human diseases. © 2016. Published by The Company of Biologists Ltd.

Genetics and Genomics of Single-Gene Cardiovascular Diseases: Common Hereditary Cardiomyopathies as Prototypes of Single-Gene Disorders

PubMed Central

Marian, Ali J.; van Rooij, Eva; Roberts, Robert

2016-01-01

This is the first of 2 review papers on genetics and genomics appearing as part of the series on “omics.” Genomics pertains to all components of an organism’s genes, whereas genetics involves analysis of a specific gene(s) in the context of heredity. The paper provides introductory comments, describes the basis of human genetic diversity, and addresses the phenotypic consequences of genetic variants. Rare variants with large effect sizes are responsible for single-gene disorders, whereas complex polygenic diseases are typically due to multiple genetic variants, each exerting a modest effect size. To illustrate the clinical implications of genetic variants with large effect sizes, 3 common forms of hereditary cardiomyopathies are discussed as prototypic examples of single-gene disorders, including their genetics, clinical manifestations, pathogenesis, and treatment. The genetic basis of complex traits is discussed in a separate paper. PMID:28007145

Novel mutations in CRB1 and ABCA4 genes cause Leber congenital amaurosis and Stargardt disease in a Swedish family

PubMed Central

Jonsson, Frida; Burstedt, Marie S; Sandgren, Ola; Norberg, Anna; Golovleva, Irina

2013-01-01

This study aimed to identify genetic mechanisms underlying severe retinal degeneration in one large family from northern Sweden, members of which presented with early-onset autosomal recessive retinitis pigmentosa and juvenile macular dystrophy. The clinical records of affected family members were analysed retrospectively and ophthalmological and electrophysiological examinations were performed in selected cases. Mutation screening was initially performed with microarrays, interrogating known mutations in the genes associated with recessive retinitis pigmentosa, Leber congenital amaurosis and Stargardt disease. Searching for homozygous regions with putative causative disease genes was done by high-density SNP-array genotyping, followed by segregation analysis of the family members. Two distinct phenotypes of retinal dystrophy, Leber congenital amaurosis and Stargardt disease were present in the family. In the family, four patients with Leber congenital amaurosis were homozygous for a novel c.2557C>T (p.Q853X) mutation in the CRB1 gene, while of two cases with Stargardt disease, one was homozygous for c.5461-10T>C in the ABCA4 gene and another was carrier of the same mutation and a novel ABCA4 mutation c.4773+3A>G. Sequence analysis of the entire ABCA4 gene in patients with Stargardt disease revealed complex alleles with additional sequence variants, which were evaluated by bioinformatics tools. In conclusion, presence of different genetic mechanisms resulting in variable phenotype within the family is not rare and can challenge molecular geneticists, ophthalmologists and genetic counsellors. PMID:23443024

Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci.

PubMed

Scelsi, Marzia A; Khan, Raiyan R; Lorenzi, Marco; Christopher, Leigh; Greicius, Michael D; Schott, Jonathan M; Ourselin, Sebastien; Altmann, Andre

2018-05-30

Identifying genetic risk factors underpinning different aspects of Alzheimer's disease has the potential to provide important insights into pathogenesis. Moving away from simple case-control definitions, there is considerable interest in using quantitative endophenotypes, such as those derived from imaging as outcome measures. Previous genome-wide association studies of imaging-derived biomarkers in sporadic late-onset Alzheimer's disease focused only on phenotypes derived from single imaging modalities. In contrast, we computed a novel multi-modal neuroimaging phenotype comprising cortical amyloid burden and bilateral hippocampal volume. Both imaging biomarkers were used as input to a disease progression modelling algorithm, which estimates the biomarkers' long-term evolution curves from population-based longitudinal data. Among other parameters, the algorithm computes the shift in time required to optimally align a subjects' biomarker trajectories with these population curves. This time shift serves as a disease progression score and it was used as a quantitative trait in a discovery genome-wide association study with n = 944 subjects from the Alzheimer's Disease Neuroimaging Initiative database diagnosed as Alzheimer's disease, mild cognitive impairment or healthy at the time of imaging. We identified a genome-wide significant locus implicating LCORL (rs6850306, chromosome 4; P = 1.03 × 10-8). The top variant rs6850306 was found to act as an expression quantitative trait locus for LCORL in brain tissue. The clinical role of rs6850306 in conversion from healthy ageing to mild cognitive impairment or Alzheimer's disease was further validated in an independent cohort comprising healthy, older subjects from the National Alzheimer's Coordinating Center database. Specifically, possession of a minor allele at rs6850306 was protective against conversion from mild cognitive impairment to Alzheimer's disease in the National Alzheimer's Coordinating Center cohort (hazard ratio = 0.593, 95% confidence interval = 0.387-0.907, n = 911, PBonf = 0.032), in keeping with the negative direction of effect reported in the genome-wide association study (βdisease progression score = -0.07 ± 0.01). The implicated locus is linked to genes with known connections to Alzheimer's disease pathophysiology and other neurodegenerative diseases. Using multimodal imaging phenotypes in association studies may assist in unveiling the genetic drivers of the onset and progression of complex diseases.

Complex inheritance in Pulmonary Arterial Hypertension patients with several mutations

PubMed Central

Pousada, Guillermo; Baloira, Adolfo; Valverde, Diana

2016-01-01

Pulmonary Arterial Hypertension (PAH) is a rare and progressive disease with low incidence and prevalence, and elevated mortality. PAH is characterized by increased mean pulmonary artery pressure. The aim of this study was to analyse patients with combined mutations in BMPR2, ACVRL1, ENG and KCNA5 genes and to establish a genotype-phenotype correlation. Major genes were analysed by polymerase chain reaction (PCR) and direct sequencing. Genotype-phenotype correlation was performed. Fifty-seven (28 idiopathic PAH, 29 associated PAH group I) were included. Several mutations in different genes, classified as pathogenic by in silico analysis, were present in 26% of PAH patients. The most commonly involved gene was BMPR2 (12 patients) followed by ENG gene (9 patients). ACVRL1 and KCNA5 genes showed very low incidence of mutations (5 and 1 patients, respectively). Genotype-phenotype correlation showed statistically significant differences for gender (p = 0.045), age at diagnosis (p = 0.035), pulmonary vascular resistance (p = 0.030), cardiac index (p = 0.035) and absence of response to treatment (p = 0.011). PAH is consequence of a heterogeneous constellation of genetic arrangements. Patients with several pathogenic mutations seem to display a more severe phenotype. PMID:27630060

Phenotypic approaches to gene mapping in platelet function disorders - identification of new variant of P2Y12, TxA2 and GPVI receptors.

PubMed

Watson, S; Daly, M; Dawood, B; Gissen, P; Makris, M; Mundell, S; Wilde, J; Mumford, A

2010-01-01

Platelet number or function disorders cause a range of bleeding symptoms from mild to severe. Patients with platelet dysfunction but normal platelet number are the most prevalent and typically have mild bleeding symptoms. The study of this group of patients is particularly difficult because of the lack of a gold-standard test of platelet function and the variable penetrance of the bleeding phenotype among affected individuals. The purpose of this short review is to discuss the way in which this group of patients can be investigated through platelet phenotyping in combination with targeted gene sequencing. This approach has been used recently to identify patients with mutations in key platelet activation receptors, namely those for ADP, collagen and thromboxane A2 (TxA2). One interesting finding from this work is that for some patients, mild bleeding is associated with heterozygous mutations in platelet proteins that are co-inherited with other genetic disorders of haemostasis such as type 1 von Willebrand's disease. Thus, the phenotype of mild bleeding may be multifactorial in some patients and may be considered to be a complex trait.

A Model of Compound Heterozygous, Loss-of-Function Alleles Is Broadly Consistent with Observations from Complex-Disease GWAS Datasets

PubMed Central

Sanjak, Jaleal S.; Long, Anthony D.; Thornton, Kevin R.

2017-01-01

The genetic component of complex disease risk in humans remains largely unexplained. A corollary is that the allelic spectrum of genetic variants contributing to complex disease risk is unknown. Theoretical models that relate population genetic processes to the maintenance of genetic variation for quantitative traits may suggest profitable avenues for future experimental design. Here we use forward simulation to model a genomic region evolving under a balance between recurrent deleterious mutation and Gaussian stabilizing selection. We consider multiple genetic and demographic models, and several different methods for identifying genomic regions harboring variants associated with complex disease risk. We demonstrate that the model of gene action, relating genotype to phenotype, has a qualitative effect on several relevant aspects of the population genetic architecture of a complex trait. In particular, the genetic model impacts genetic variance component partitioning across the allele frequency spectrum and the power of statistical tests. Models with partial recessivity closely match the minor allele frequency distribution of significant hits from empirical genome-wide association studies without requiring homozygous effect sizes to be small. We highlight a particular gene-based model of incomplete recessivity that is appealing from first principles. Under that model, deleterious mutations in a genomic region partially fail to complement one another. This model of gene-based recessivity predicts the empirically observed inconsistency between twin and SNP based estimated of dominance heritability. Furthermore, this model predicts considerable levels of unexplained variance associated with intralocus epistasis. Our results suggest a need for improved statistical tools for region based genetic association and heritability estimation. PMID:28103232

Poor maternal nutrition and accelerated postnatal growth induces an accelerated aging phenotype and oxidative stress in skeletal muscle of male rats

PubMed Central

Fernandez-Twinn, Denise S.; Chen, Jian Hua; Hargreaves, Iain P.; Neergheen, Viruna; Aiken, Catherine E.; Ozanne, Susan E.

2016-01-01

ABSTRACT ‘Developmental programming’, which occurs as a consequence of suboptimal in utero and early environments, can be associated with metabolic dysfunction in later life, including an increased incidence of cardiovascular disease and type 2 diabetes, and predisposition of older men to sarcopenia. However, the molecular mechanisms underpinning these associations are poorly understood. Many conditions associated with developmental programming are also known to be associated with the aging process. We therefore utilized our well-established rat model of low birth weight and accelerated postnatal catch-up growth (termed ‘recuperated’) in this study to establish the effects of suboptimal maternal nutrition on age-associated factors in skeletal muscle. We demonstrated accelerated telomere shortening (a robust marker of cellular aging) as evidenced by a reduced frequency of long telomeres (48.5-8.6 kb) and an increased frequency of short telomeres (4.2-1.3 kb) in vastus lateralis muscle from aged recuperated offspring compared to controls. This was associated with increased protein expression of the DNA-damage-repair marker 8-oxoguanine-glycosylase (OGG1) in recuperated offspring. Recuperated animals also demonstrated an oxidative stress phenotype, with decreased citrate synthase activity, increased electron-transport-complex activities of complex I, complex II-III and complex IV (all markers of functional mitochondria), and increased xanthine oxidase (XO), p67phox and nuclear-factor kappa-light-chain-enhancer of activated B-cells (NF-κB). Recuperated offspring also demonstrated increased antioxidant defense capacity, with increased protein expression of manganese superoxide dismutase (MnSOD), copper-zinc superoxide dismutase (CuZnSOD), catalase and heme oxygenase-1 (HO1), all of which are known targets of NF-κB and can be upregulated as a consequence of oxidative stress. Recuperated offspring also had a pro-inflammatory phenotype, as evidenced by increased tumor necrosis factor-α (TNFα) and interleukin-1β (IL1β) protein levels. Taken together, we demonstrate, for the first time to our knowledge, an accelerated aging phenotype in skeletal muscle in the context of developmental programming. These findings may pave the way for suitable interventions in at-risk populations. PMID:27585884

When should we test for voltage-gated potassium channel complex antibodies? A retrospective case control study.

PubMed

O'Sullivan, B J; Steele, T; Ellul, M A; Kirby, E; Duale, A; Kier, G; Crooks, D; Jacob, A; Solomon, T; Michael, B D

2016-11-01

Patients with voltage-gated potassium channel (VGKC)-complex antibodies are increasingly recognized as having central, peripheral or combined phenotypes. With increasing awareness, more patients are tested and the clinical spectrum is expanding. Consequently, clinicians may be uncertain as to which patients should or should not be tested. Previous studies have identified common clinical features, but none has looked at the usefulness of these in predicting seropositive disease. We conducted a case-control study of patients tested for VGKC-complex antibodies over 10years at a regional tertiary neurology centre determining which clinical/biochemical features were associated with antibody-positive disease. We found a marked increase in the numbers tested, although the percentage positive remained low. Antibody titre was highest in central disease (p<0.001). Time from presentation to testing was shorter in those with VGKC-disease (p=0.01). Seizures were present in 11 (69%) of those with VGKC-disease versus three (18%) without (odds ratio [OR] 10.3, 95% confidence interval [CI]: 2.0-52.7, p=0.005). There was an inverse correlation between the antibody titre and serum sodium. A multivariate model selected seizures and hyponatraemia as predictive of VGKC disease (sensitivity 75% and specificity 82%); faciobrachial dystonic movements were specific but insensitive. Interestingly serum alkaline phosphatase was higher in those with VGKC-disease (p=0.016) and highest in those with peripheral disease (p=0.015). An ALP>70u/L was strongly associated with antibody positivity (OR 4.11 95% CI: 1.43-11.8, p=0.007) with a sensitivity of 74.2%. The presence of seizures, faciobrachial movements, and hyponatraemia should raise suspicion of VGKC-disease; alkaline phosphatase may represent a novel biomarker, particularly in those with peripheral disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

Disease modeling using human induced pluripotent stem cells: lessons from the liver.

PubMed

Gieseck, Richard L; Colquhoun, Jennifer; Hannan, Nicholas R F

2015-01-01

Human pluripotent stem cells (hPSCs) have the capacity to differentiate into any of the hundreds of distinct cell types that comprise the human body. This unique characteristic has resulted in considerable interest in the field of regenerative medicine, given the potential for these cells to be used to protect, repair, or replace diseased, injured, and aged cells within the human body. In addition to their potential in therapeutics, hPSCs can be used to study the earliest stages of human development and to provide a platform for both drug screening and disease modeling using human cells. Recently, the description of human induced pluripotent stem cells (hIPSCs) has allowed the field of disease modeling to become far more accessible and physiologically relevant, as pluripotent cells can be generated from patients of any genetic background. Disease models derived from hIPSCs that manifest cellular disease phenotypes have been established to study several monogenic diseases; furthermore, hIPSCs can be used for phenotype-based drug screens to investigate complex diseases for which the underlying genetic mechanism is unknown. As a result, the use of stem cells as research tools has seen an unprecedented growth within the last decade as researchers look for in vitro disease models which closely mimic in vivo responses in humans. Here, we discuss the beginnings of hPSCs, starting with isolation of human embryonic stem cells, moving into the development and optimization of hIPSC technology, and ending with the application of hIPSCs towards disease modeling and drug screening applications, with specific examples highlighting the modeling of inherited metabolic disorders of the liver. This article is part of a Special Issue entitled Linking transcription to physiology in lipodomics. Crown Copyright © 2014. Published by Elsevier B.V. All rights reserved.

The hypertriglyceridemic-waist phenotype and the risk of coronary artery disease: results from the EPIC-Norfolk Prospective Population Study

PubMed Central

Arsenault, Benoit J.; Lemieux, Isabelle; Després, Jean-Pierre; Wareham, Nicholas J.; Kastelein, John J.P.; Khaw, Kay-Tee; Boekholdt, S. Matthijs

2010-01-01

Background Screening for increased waist circumference and hypertriglyceridemia (the hypertriglyceridemic-waist phenotype) has been proposed as an inexpensive approach to identify patients with excess intra-abdominal adiposity and associated metabolic abnormalities. We examined the relationship between the hypertriglyceridemic-waist phenotype to the risk of coronary artery disease in apparently healthy individuals. Methods A total of 21 787 participants aged 45–79 years were followed for a mean of 9.8 (standard deviation 1.7) years. Coronary artery disease developed in 2109 of them during follow-up. The hypertriglyceridemic-waist phenotype was defined as a waist circumference of 90 cm or more and a triglyceride level of 2.0 mmol/L or more in men, and a waist circumference of 85 cm or more and a triglyceride level of 1.5 mmol/L or more in women. Results Compared with participants who had a waist circumference and triglyceride level below the threshold, those with the hypertriglyceridemic-waist phenotype had higher blood pressure indices, higher levels of apolipoprotein B and C-reactive protein, lower levels of high-density lipoprotein cholesterol and apolipoprotein A-I, and smaller low-density lipoprotein particles. Among men, those with the hypertriglyceridemic-waist phenotype had an unadjusted hazard ratio for future coronary artery disease of 2.40 (95% confidence interval [CI] 2.02–2.87) compared with men who did not have the phenotype. Women with the phenotype had an unadjusted hazard ratio of 3.84 (95% CI 3.20–4.62) compared with women who did not have the phenotype. Interpretation Among participants from a European cohort representative of a contemporary Western population, the hypertriglyceridemic-waist phenotype was associated with a deteriorated cardiometabolic risk profile and an increased risk for coronary artery disease. PMID:20643837

In silico analysis of a disease-causing mutation in PCDH15 gene in a consanguineous Pakistani family with Usher phenotype.

PubMed

Saleha, Shamim; Ajmal, Muhammad; Jamil, Muhammad; Nasir, Muhammad; Hameed, Abdul

2016-01-01

To map Usher phenotype in a consanguineous Pakistani family and identify disease-associated mutation in a causative gene to establish phenotype-genotype correlation. A consanguineous Pakistani family in which Usher phenotype was segregating as an autosomal recessive trait was ascertained. On the basis of results of clinical investigations of affected members of this family disease was diagnosed as Usher syndrome (USH). To identify the locus responsible for the Usher phenotype in this family, genomic DNA from blood sample of each individual was genotyped using microsatellite Short Tandem Repeat (STR) markers for the known Usher syndrome loci. Then direct sequencing was performed to find out disease associated mutations in the candidate gene. By genetic linkage analysis, the USH phenotype of this family was mapped to PCDH15 locus on chromosome 10q21.1. Three different point mutations in exon 11 of PCDH15 were identified and one of them, c.1304A>C was found to be segregating with the disease phenotype in Pakistani family with Usher phenotype. This, c.1304A>C transversion mutation predicts an amino-acid substitution of aspartic acid with an alanine at residue number 435 (p.D435A) of its protein product. Moreover, in silico analysis revealed conservation of aspartic acid at position 435 and predicated this change as pathogenic. The identification of c.1304A>C pathogenic mutation in PCDH15 gene and its association with Usher syndrome in a consanguineous Pakistani family is the first example of a missense mutation of PCDH15 causing USH1 phenotype. In previous reports, it was hypothesized that severe mutations such as truncated protein of PCDH15 led to the Usher I phenotype and that missense variants are mainly responsible for non-syndromic hearing impairment.

Neurobehavioral phenotype in Prader-Willi syndrome.

PubMed

Whittington, Joyce; Holland, Anthony

2010-11-15

The focus of this article is on the lifetime development of people with Prader-Willi syndrome (PWS) and specifically on the neurobehavioral phenotype. We consider studies of this aspect of the phenotype (the "behavioral phenotype" of the syndrome) that have confirmed that there are specific behaviors and psychiatric disorders, the propensities to which are increased in those with PWS, and cannot be accounted for by other variables such as IQ or adaptive behavior. Beginning with a description of what is observed in people with PWS, we review the evolving PWS phenotype and consider how some aspects of the phenotype might be best explained, and how this complex phenotype may relate to the equally complex genotype. We then consider in more detail some of the neurobehavioral aspects of the phenotype listed above that raise the greatest management problems for parents and carers. © 2010 Wiley-Liss, Inc.

Genetic variants in Alzheimer disease – molecular and brain network approaches

PubMed Central

Gaiteri, Chris; Mostafavi, Sara; Honey, Christopher; De Jager, Philip L.; Bennett, David A.

2016-01-01

Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care for AD. However, due to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extracting actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effect of LOAD-associated genetic variants. We then discuss emerging combinations of omic data types in multiscale models, which provide a more comprehensive representation of the effect of LOAD-associated genetic variants at multiple biophysical scales. Further, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models. PMID:27282653

Of mice and men: molecular genetics of congenital heart disease.

PubMed

Andersen, Troels Askhøj; Troelsen, Karin de Linde Lind; Larsen, Lars Allan

2014-04-01

Congenital heart disease (CHD) affects nearly 1 % of the population. It is a complex disease, which may be caused by multiple genetic and environmental factors. Studies in human genetics have led to the identification of more than 50 human genes, involved in isolated CHD or genetic syndromes, where CHD is part of the phenotype. Furthermore, mapping of genomic copy number variants and exome sequencing of CHD patients have led to the identification of a large number of candidate disease genes. Experiments in animal models, particularly in mice, have been used to verify human disease genes and to gain further insight into the molecular pathology behind CHD. The picture emerging from these studies suggest that genetic lesions associated with CHD affect a broad range of cellular signaling components, from ligands and receptors, across down-stream effector molecules to transcription factors and co-factors, including chromatin modifiers.

Integrated Metagenomics/Metaproteomics Reveals Human Host-Microbiota Signatures of Crohn's Disease

PubMed Central

Darzi, Youssef; Mongodin, Emmanuel F.; Pan, Chongle; Shah, Manesh; Halfvarson, Jonas; Tysk, Curt; Henrissat, Bernard; Raes, Jeroen; Verberkmoes, Nathan C.; Jansson, Janet K.

2012-01-01

Crohn's disease (CD) is an inflammatory bowel disease of complex etiology, although dysbiosis of the gut microbiota has been implicated in chronic immune-mediated inflammation associated with CD. Here we combined shotgun metagenomic and metaproteomic approaches to identify potential functional signatures of CD in stool samples from six twin pairs that were either healthy, or that had CD in the ileum (ICD) or colon (CCD). Integration of these omics approaches revealed several genes, proteins, and pathways that primarily differentiated ICD from healthy subjects, including depletion of many proteins in ICD. In addition, the ICD phenotype was associated with alterations in bacterial carbohydrate metabolism, bacterial-host interactions, as well as human host-secreted enzymes. This eco-systems biology approach underscores the link between the gut microbiota and functional alterations in the pathophysiology of Crohn's disease and aids in identification of novel diagnostic targets and disease specific biomarkers. PMID:23209564

Serum Immune Responses Predict Rapid Disease Progression among Children with Crohn’s Disease: Immune Responses Predict Disease Progression

PubMed Central

Dubinsky, Marla C.; Lin, Ying-Chao; Dutridge, Debra; Picornell, Yoana; Landers, Carol J.; Farrior, Sharmayne; Wrobel, Iwona; Quiros, Antonio; Vasiliauskas, Eric A.; Grill, Bruce; Israel, David; Bahar, Ron; Christie, Dennis; Wahbeh, Ghassan; Silber, Gary; Dallazadeh, Saied; Shah, Praful; Thomas, Danny; Kelts, Drew; Hershberg, Robert M.; Elson, Charles O.; Targan, Stephan R.; Taylor, Kent D.; Rotter, Jerome I.; Yang, Huiying

2007-01-01

BACKGROUND AND AIM Crohn’s disease (CD) is a heterogeneous disorder characterized by diverse clinical phenotypes. Childhood-onset CD has been described as a more aggressive phenotype. Genetic and immune factors may influence disease phenotype and clinical course. We examined the association of immune responses to microbial antigens with disease behavior and prospectively determined the influence of immune reactivity on disease progression in pediatric CD patients. METHODS Sera were collected from 196 pediatric CD cases and tested for immune responses: anti-I2, anti-outer membrane protein C (anti-OmpC), anti-CBir1 flagellin (anti-CBir1), and anti-Saccharomyces-cerevisiae (ASCA) using ELISA. Associations between immune responses and clinical phenotype were evaluated. RESULTS Fifty-eight patients (28%) developed internal penetrating and/or stricturing (IP/S) disease after a median follow-up of 18 months. Both anti-OmpC (p < 0.0006) and anti-I2 (p < 0.003) were associated with IP/S disease. The frequency of IP/S disease increased with increasing number of immune responses (p trend = 0.002). The odds of developing IP/S disease were highest in patients positive for all four immune responses (OR (95% CI): 11 (1.5–80.4); p = 0.03). Pediatric CD patients positive for ≥1 immune response progressed to IP/S disease sooner after diagnosis as compared to those negative for all immune responses (p < 0.03). CONCLUSIONS The presence and magnitude of immune responses to microbial antigens are significantly associated with more aggressive disease phenotypes among children with CD. This is the first study to prospectively demonstrate that the time to develop a disease complication in children is significantly faster in the presence of immune reactivity, thereby predicting disease progression to more aggressive disease phenotypes among pediatric CD patients. PMID:16454844

The clinical heterogeneity of coenzyme Q10 deficiency results from genotypic differences in the Coq9 gene

PubMed Central

Luna-Sánchez, Marta; Díaz-Casado, Elena; Barca, Emanuele; Tejada, Miguel Ángel; Montilla-García, Ángeles; Cobos, Enrique Javier; Escames, Germaine; Acuña-Castroviejo, Dario; Quinzii, Catarina M; López, Luis Carlos

2015-01-01

Primary coenzyme Q10 (CoQ10) deficiency is due to mutations in genes involved in CoQ biosynthesis. The disease has been associated with five major phenotypes, but a genotype–phenotype correlation is unclear. Here, we compare two mouse models with a genetic modification in Coq9 gene (Coq9Q95X and Coq9R239X), and their responses to 2,4-dihydroxybenzoic acid (2,4-diHB). Coq9R239X mice manifest severe widespread CoQ deficiency associated with fatal encephalomyopathy and respond to 2,4-diHB increasing CoQ levels. In contrast, Coq9Q95X mice exhibit mild CoQ deficiency manifesting with reduction in CI+III activity and mitochondrial respiration in skeletal muscle, and late-onset mild mitochondrial myopathy, which does not respond to 2,4-diHB. We show that these differences are due to the levels of COQ biosynthetic proteins, suggesting that the presence of a truncated version of COQ9 protein in Coq9R239X mice destabilizes the CoQ multiprotein complex. Our study points out the importance of the multiprotein complex for CoQ biosynthesis in mammals, which may provide new insights to understand the genotype–phenotype heterogeneity associated with human CoQ deficiency and may have a potential impact on the treatment of this mitochondrial disorder. PMID:25802402

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 .

Metabolic phenotyping and systems biology approaches to understanding metabolic syndrome and fatty liver disease.

PubMed

Dumas, Marc-Emmanuel; Kinross, James; Nicholson, Jeremy K

2014-01-01

Metabolic syndrome, a cluster of risk factors for type 2 diabetes mellitus and cardiovascular disease, is becoming an increasing global health concern. Insulin resistance is often associated with metabolic syndrome and also typical hepatic manifestations such as nonalcoholic fatty liver disease. Profiling of metabolic products (metabolic phenotyping or metabotyping) has provided new insights into metabolic syndrome and nonalcoholic fatty liver disease. Data from nuclear magnetic resonance spectroscopy and mass spectrometry combined with statistical modeling and top-down systems biology have allowed us to analyze and interpret metabolic signatures in terms of metabolic pathways and protein interaction networks and to identify the genomic and metagenomic determinants of metabolism. For example, metabolic phenotyping has shown that relationships between host cells and the microbiome affect development of the metabolic syndrome and fatty liver disease. We review recent developments in metabolic phenotyping and systems biology technologies and how these methodologies have provided insights into the mechanisms of metabolic syndrome and nonalcoholic fatty liver disease. We discuss emerging areas of research in this field and outline our vision for how metabolic phenotyping could be used to study metabolic syndrome and fatty liver disease. Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.

Diversified Control Paths: A Significant Way Disease Genes Perturb the Human Regulatory Network

PubMed Central

Wang, Bingbo; Gao, Lin; Zhang, Qingfang; Li, Aimin; Deng, Yue; Guo, Xingli

2015-01-01

Background The complexity of biological systems motivates us to use the underlying networks to provide deep understanding of disease etiology and the human diseases are viewed as perturbations of dynamic properties of networks. Control theory that deals with dynamic systems has been successfully used to capture systems-level knowledge in large amount of quantitative biological interactions. But from the perspective of system control, the ways by which multiple genetic factors jointly perturb a disease phenotype still remain. Results In this work, we combine tools from control theory and network science to address the diversified control paths in complex networks. Then the ways by which the disease genes perturb biological systems are identified and quantified by the control paths in a human regulatory network. Furthermore, as an application, prioritization of candidate genes is presented by use of control path analysis and gene ontology annotation for definition of similarities. We use leave-one-out cross-validation to evaluate the ability of finding the gene-disease relationship. Results have shown compatible performance with previous sophisticated works, especially in directed systems. Conclusions Our results inspire a deeper understanding of molecular mechanisms that drive pathological processes. Diversified control paths offer a basis for integrated intervention techniques which will ultimately lead to the development of novel therapeutic strategies. PMID:26284649

Mutations in COA7 cause spinocerebellar ataxia with axonal neuropathy.

PubMed

Higuchi, Yujiro; Okunushi, Ryuta; Hara, Taichi; Hashiguchi, Akihiro; Yuan, Junhui; Yoshimura, Akiko; Murayama, Kei; Ohtake, Akira; Ando, Masahiro; Hiramatsu, Yu; Ishihara, Satoshi; Tanabe, Hajime; Okamoto, Yuji; Matsuura, Eiji; Ueda, Takehiro; Toda, Tatsushi; Yamashita, Sumimasa; Yamada, Kenichiro; Koide, Takashi; Yaguchi, Hiroaki; Mitsui, Jun; Ishiura, Hiroyuki; Yoshimura, Jun; Doi, Koichiro; Morishita, Shinichi; Sato, Ken; Nakagawa, Masanori; Yamaguchi, Masamitsu; Tsuji, Shoji; Takashima, Hiroshi

2018-06-01

Several genes related to mitochondrial functions have been identified as causative genes of neuropathy or ataxia. Cytochrome c oxidase assembly factor 7 (COA7) may have a role in assembling mitochondrial respiratory chain complexes that function in oxidative phosphorylation. Here we identified four unrelated patients with recessive mutations in COA7 among a Japanese case series of 1396 patients with Charcot-Marie-Tooth disease (CMT) or other inherited peripheral neuropathies, including complex forms of CMT. We also found that all four patients had characteristic neurological features of peripheral neuropathy and ataxia with cerebellar atrophy, and some patients showed leukoencephalopathy or spinal cord atrophy on MRI scans. Validated mutations were located at highly conserved residues among different species and segregated with the disease in each family. Nerve conduction studies showed axonal sensorimotor neuropathy. Sural nerve biopsies showed chronic axonal degeneration with a marked loss of large and medium myelinated fibres. An immunohistochemical assay with an anti-COA7 antibody in the sural nerve from the control patient showed the positive expression of COA7 in the cytoplasm of Schwann cells. We also observed mildly elevated serum creatine kinase levels in all patients and the presence of a few ragged-red fibres and some cytochrome c oxidase-negative fibres in a muscle biopsy obtained from one patient, which was suggestive of subclinical mitochondrial myopathy. Mitochondrial respiratory chain enzyme assay in skin fibroblasts from the three patients showed a definitive decrease in complex I or complex IV. Immunocytochemical analysis of subcellular localization in HeLa cells indicated that mutant COA7 proteins as well as wild-type COA7 were localized in mitochondria, which suggests that mutant COA7 does not affect the mitochondrial recruitment and may affect the stability or localization of COA7 interaction partners in the mitochondria. In addition, Drosophila COA7 (dCOA7) knockdown models showed rough eye phenotype, reduced lifespan, impaired locomotive ability and shortened synaptic branches of motor neurons. Our results suggest that loss-of-function COA7 mutation is responsible for the phenotype of the presented patients, and this new entity of disease would be referred to as spinocerebellar ataxia with axonal neuropathy type 3.

The mitochondrial and kidney disease phenotypes of kd/kd mice under germfree conditions

PubMed Central

Hallman, Troy M.; Peng, Min; Meade, Ray; Hancock, Wayne W.; Madaio, Michael P.; Gasser, David L.

2008-01-01

Interstitial nephritis occurs spontaneously in kd/kd mice, but the mechanisms leading to this disease have not been fully elucidated. The earliest manifestation of a phenotype is the appearance of ultrastructural defects in the mitochondria of mice as young as 42 days of age. To examine the influence of the environment on the phenotype, homozygous B6.kd/kd mice were transferred from specific pathogen-free (SPF) conditions to a germfree (GF) environment, and the development of the disease was observed. The GF state resulted in a highly significant reduction in the frequency of tubulointerstitial nephritis. In addition, GF conditions markedly reduced the appearance of the mitochondrial phenotype, with no sign of mitochondrial abnormalities in GF mice of up to 155 days of age. These results suggest that environmental factors are involved in the progression of all known manifestations of this disease phenotype. PMID:16337774

Understanding gene functions and disease mechanisms: Phenotyping pipelines in the German Mouse Clinic.

PubMed

Fuchs, Helmut; Aguilar-Pimentel, Juan Antonio; Amarie, Oana V; Becker, Lore; Calzada-Wack, Julia; Cho, Yi-Li; Garrett, Lillian; Hölter, Sabine M; Irmler, Martin; Kistler, Martin; Kraiger, Markus; Mayer-Kuckuk, Philipp; Moreth, Kristin; Rathkolb, Birgit; Rozman, Jan; da Silva Buttkus, Patricia; Treise, Irina; Zimprich, Annemarie; Gampe, Kristine; Hutterer, Christine; Stöger, Claudia; Leuchtenberger, Stefanie; Maier, Holger; Miller, Manuel; Scheideler, Angelika; Wu, Moya; Beckers, Johannes; Bekeredjian, Raffi; Brielmeier, Markus; Busch, Dirk H; Klingenspor, Martin; Klopstock, Thomas; Ollert, Markus; Schmidt-Weber, Carsten; Stöger, Tobias; Wolf, Eckhard; Wurst, Wolfgang; Yildirim, Ali Önder; Zimmer, Andreas; Gailus-Durner, Valérie; Hrabě de Angelis, Martin

2017-09-29

Since decades, model organisms have provided an important approach for understanding the mechanistic basis of human diseases. The German Mouse Clinic (GMC) was the first phenotyping facility that established a collaboration-based platform for phenotype characterization of mouse lines. In order to address individual projects by a tailor-made phenotyping strategy, the GMC advanced in developing a series of pipelines with tests for the analysis of specific disease areas. For a general broad analysis, there is a screening pipeline that covers the key parameters for the most relevant disease areas. For hypothesis-driven phenotypic analyses, there are thirteen additional pipelines with focus on neurological and behavioral disorders, metabolic dysfunction, respiratory system malfunctions, immune-system disorders and imaging techniques. In this article, we give an overview of the pipelines and describe the scientific rationale behind the different test combinations. Copyright © 2017 Elsevier B.V. All rights reserved.

Defining the clinical course of multiple sclerosis

PubMed Central

Reingold, Stephen C.; Cohen, Jeffrey A.; Cutter, Gary R.; Sørensen, Per Soelberg; Thompson, Alan J.; Wolinsky, Jerry S.; Balcer, Laura J.; Banwell, Brenda; Barkhof, Frederik; Bebo, Bruce; Calabresi, Peter A.; Clanet, Michel; Comi, Giancarlo; Fox, Robert J.; Freedman, Mark S.; Goodman, Andrew D.; Inglese, Matilde; Kappos, Ludwig; Kieseier, Bernd C.; Lincoln, John A.; Lubetzki, Catherine; Miller, Aaron E.; Montalban, Xavier; O'Connor, Paul W.; Petkau, John; Pozzilli, Carlo; Rudick, Richard A.; Sormani, Maria Pia; Stüve, Olaf; Waubant, Emmanuelle; Polman, Chris H.

2014-01-01

Accurate clinical course descriptions (phenotypes) of multiple sclerosis (MS) are important for communication, prognostication, design and recruitment of clinical trials, and treatment decision-making. Standardized descriptions published in 1996 based on a survey of international MS experts provided purely clinical phenotypes based on data and consensus at that time, but imaging and biological correlates were lacking. Increased understanding of MS and its pathology, coupled with general concern that the original descriptors may not adequately reflect more recently identified clinical aspects of the disease, prompted a re-examination of MS disease phenotypes by the International Advisory Committee on Clinical Trials of MS. While imaging and biological markers that might provide objective criteria for separating clinical phenotypes are lacking, we propose refined descriptors that include consideration of disease activity (based on clinical relapse rate and imaging findings) and disease progression. Strategies for future research to better define phenotypes are also outlined. PMID:24871874

Searching for Genotype-Phenotype Structure: Using Hierarchical Log-Linear Models in Crohn Disease

PubMed Central

Chapman, Juliet M.; Onnie, Clive M.; Prescott, Natalie J.; Fisher, Sheila A.; Mansfield, John C.; Mathew, Christopher G.; Lewis, Cathryn M.; Verzilli, Claudio J.; Whittaker, John C.

2009-01-01

There has been considerable recent success in the detection of gene-disease associations. We consider here the development of tools that facilitate the more detailed characterization of the effect of a genetic variant on disease. We replace the simplistic classification of individuals according to a single binary disease indicator with classification according to a number of subphenotypes. This more accurately reflects the underlying biological complexity of the disease process, but it poses additional analytical difficulties. Notably, the subphenotypes that make up a particular disease are typically highly associated, and it becomes difficult to distinguish which genes might be causing which subphenotypes. Such problems arise in many complex diseases. Here, we concentrate on an application to Crohn disease (CD). We consider this problem as one of model selection based upon log-linear models, fitted in a Bayesian framework via reversible-jump Metropolis-Hastings approach. We evaluate the performance of our suggested approach with a simple simulation study and then apply the method to a real data example in CD, revealing a sparse disease structure. Most notably, the associated NOD2.908G→R mutation appears to be directly related to more severe disease behaviors, whereas the other two associated NOD2 variants, 1007L→FS and 702R→W, are more generally related to disease in the small bowel (ileum and jejenum). The ATG16L1.300T→A variant appears to be directly associated with only disease of the small bowel. PMID:19185283

Application of Genome Wide Association and Genomic Prediction for Improvement of Cacao Productivity and Resistance to Black and Frosty Pod Diseases

PubMed Central

Romero Navarro, J. Alberto; Phillips-Mora, Wilbert; Arciniegas-Leal, Adriana; Mata-Quirós, Allan; Haiminen, Niina; Mustiga, Guiliana; Livingstone III, Donald; van Bakel, Harm; Kuhn, David N.; Parida, Laxmi; Kasarskis, Andrew; Motamayor, Juan C.

2017-01-01

Chocolate is a highly valued and palatable confectionery product. Chocolate is primarily made from the processed seeds of the tree species Theobroma cacao. Cacao cultivation is highly relevant for small-holder farmers throughout the tropics, yet its productivity remains limited by low yields and widespread pathogens. A panel of 148 improved cacao clones was assembled based on productivity and disease resistance, and phenotypic single-tree replicated clonal evaluation was performed for 8 years. Using high-density markers, the diversity of clones was expressed relative to 10 known ancestral cacao populations, and significant effects of ancestry were observed in productivity and disease resistance. Genome-wide association (GWA) was performed, and six markers were significantly associated with frosty pod disease resistance. In addition, genomic selection was performed, and consistent with the observed extensive linkage disequilibrium, high predictive ability was observed at low marker densities for all traits. Finally, quantitative trait locus mapping and differential expression analysis of two cultivars with contrasting disease phenotypes were performed to identify genes underlying frosty pod disease resistance, identifying a significant quantitative trait locus and 35 differentially expressed genes using two independent differential expression analyses. These results indicate that in breeding populations of heterozygous and recently admixed individuals, mapping approaches can be used for low complexity traits like pod color cacao, or in other species single gene disease resistance, however genomic selection for quantitative traits remains highly effective relative to mapping. Our results can help guide the breeding process for sustainable improved cacao productivity. PMID:29184558

Delineation of C12orf65-related phenotypes: a genotype-phenotype relationship.

PubMed

Spiegel, Ronen; Mandel, Hanna; Saada, Ann; Lerer, Issy; Burger, Ayala; Shaag, Avraham; Shalev, Stavit A; Jabaly-Habib, Haneen; Goldsher, Dorit; Gomori, John M; Lossos, Alex; Elpeleg, Orly; Meiner, Vardiella

2014-08-01

C12orf65 participates in the process of mitochondrial translation and has been shown to be associated with a spectrum of phenotypes, including early onset optic atrophy, progressive encephalomyopathy, peripheral neuropathy, and spastic paraparesis.We used whole-genome homozygosity mapping as well as exome sequencing and targeted gene sequencing to identify novel C12orf65 disease-causing mutations in seven affected individuals originating from two consanguineous families. In four family members affected with childhood-onset optic atrophy accompanied by slowly progressive peripheral neuropathy and spastic paraparesis, we identified a homozygous frame shift mutation c.413_417 delAACAA, which predicts a truncated protein lacking the C-terminal portion. In the second family, we studied three affected individuals who presented with early onset optic atrophy, peripheral neuropathy, and spastic gait in addition to moderate intellectual disability. Muscle biopsy in two of the patients revealed decreased activities of the mitochondrial respiratory chain complexes I and IV. In these patients, we identified a homozygous splice mutation, g.21043 T>A (c.282+2 T>A) which leads to skipping of exon 2. Our study broadens the phenotypic spectrum of C12orf65 defects and highlights the triad of optic atrophy, axonal neuropathy and spastic paraparesis as its key clinical features. In addition, a clear genotype-phenotype correlation is anticipated in which deleterious mutations which disrupt the GGQ-containing domain in the first coding exon are expected to result in a more severe phenotype, whereas down-stream C-terminal mutations may result in a more favorable phenotype, typically lacking cognitive impairment.

Continental Drift and Speciation of the Cryptococcus neoformans and Cryptococcus gattii Species Complexes

PubMed Central

Freij, Joudeh B.; Hann-Soden, Christopher; Taylor, John

2017-01-01

ABSTRACT Genomic analysis has placed the origins of two human-pathogenic fungi, the Cryptococcus gattii species complex and the Cryptococcus neoformans species complex, in South America and Africa, respectively. Molecular clock calculations suggest that the two species separated ~80 to 100 million years ago. This time closely approximates the breakup of the supercontinent Pangea, which gave rise to South America and Africa. On the basis of the geographic distribution of these two species complexes and the coincidence of the evolutionary divergence and Pangea breakup times, we propose that a spatial separation caused by continental drift resulted in the emergence of the C. gattii and C. neoformans species complexes from a Pangean ancestor. We note that, despite the spatial and temporal separation that occurred approximately 100 million years ago, these two species complexes are morphologically similar, share virulence factors, and cause very similar diseases. Continuation of these phenotypic characteristics despite ancient separation suggests the maintenance of similar selection pressures throughout geologic ages. PMID:28435888

Continental Drift and Speciation of the Cryptococcus neoformans and Cryptococcus gattii Species Complexes.

PubMed

Casadevall, Arturo; Freij, Joudeh B; Hann-Soden, Christopher; Taylor, John

2017-01-01

Genomic analysis has placed the origins of two human-pathogenic fungi, the Cryptococcus gattii species complex and the Cryptococcus neoformans species complex, in South America and Africa, respectively. Molecular clock calculations suggest that the two species separated ~80 to 100 million years ago. This time closely approximates the breakup of the supercontinent Pangea, which gave rise to South America and Africa. On the basis of the geographic distribution of these two species complexes and the coincidence of the evolutionary divergence and Pangea breakup times, we propose that a spatial separation caused by continental drift resulted in the emergence of the C. gattii and C. neoformans species complexes from a Pangean ancestor. We note that, despite the spatial and temporal separation that occurred approximately 100 million years ago, these two species complexes are morphologically similar, share virulence factors, and cause very similar diseases. Continuation of these phenotypic characteristics despite ancient separation suggests the maintenance of similar selection pressures throughout geologic ages.

Environment-wide association study (EWAS) for type 2 diabetes in the Marshfield Personalized Medicine Research Project Biobank.

PubMed

Hall, Molly A; Dudek, Scott M; Goodloe, Robert; Crawford, Dana C; Pendergrass, Sarah A; Peissig, Peggy; Brilliant, Murray; McCarty, Catherine A; Ritchie, Marylyn D

2014-01-01

Environment-wide association studies (EWAS) provide a way to uncover the environmental mechanisms involved in complex traits in a high-throughput manner. Genome-wide association studies have led to the discovery of genetic variants associated with many common diseases but do not take into account the environmental component of complex phenotypes. This EWAS assesses the comprehensive association between environmental variables and the outcome of type 2 diabetes (T2D) in the Marshfield Personalized Medicine Research Project Biobank (Marshfield PMRP). We sought replication in two National Health and Nutrition Examination Surveys (NHANES). The Marshfield PMRP currently uses four tools for measuring environmental exposures and outcome traits: 1) the PhenX Toolkit includes standardized exposure and phenotypic measures across several domains, 2) the Diet History Questionnaire (DHQ) is a food frequency questionnaire, 3) the Measurement of a Person's Habitual Physical Activity scores the level of an individual's physical activity, and 4) electronic health records (EHR) employs validated algorithms to establish T2D case-control status. Using PLATO software, 314 environmental variables were tested for association with T2D using logistic regression, adjusting for sex, age, and BMI in over 2,200 European Americans. When available, similar variables were tested with the same methods and adjustment in samples from NHANES III and NHANES 1999-2002. Twelve and 31 associations were identified in the Marshfield samples at p<0.01 and p<0.05, respectively. Seven and 13 measures replicated in at least one of the NHANES at p<0.01 and p<0.05, respectively, with the same direction of effect. The most significant environmental exposures associated with T2D status included decreased alcohol use as well as increased smoking exposure in childhood and adulthood. The results demonstrate the utility of the EWAS method and survey tools for identifying environmental components of complex diseases like type 2 diabetes. These high-throughput and comprehensive investigation methods can easily be applied to investigate the relation between environmental exposures and multiple phenotypes in future analyses.

Impact of Ultraviolet Light on Vitiligo.

PubMed

Singh, Rasnik K

2017-01-01

Vitiligo is a disorder of the melanocytes that results in a dynamic spectrum of skin depigmentation. Its etiology is complex and multifactorial, with data supporting several different hypotheses. Given its prominent phenotype, vitiligo has a significant negative impact on quality of life. Coupled with the chronic and incurable nature of the disease, this presents a formidable treatment challenge. Several treatment modalities have been instituted over the years, with varying efficacy. This chapter focuses on the use of ultraviolet light in vitiligo as an established therapeutic option.

Generation of Isogenic Human iPS Cell Line Precisely Corrected by Genome Editing Using the CRISPR/Cas9 System.

PubMed

Grobarczyk, Benjamin; Franco, Bénédicte; Hanon, Kevin; Malgrange, Brigitte

2015-10-01

Genome engineering and human iPS cells are two powerful technologies, which can be combined to highlight phenotypic differences and identify pathological mechanisms of complex diseases by providing isogenic cellular material. However, very few data are available regarding precise gene correction in human iPS cells. Here, we describe an optimized stepwise protocol to deliver CRISPR/Cas9 plasmids in human iPS cells. We highlight technical issues especially those associated to human stem cell culture and to the correction of a point mutation to obtain isogenic iPS cell line, without inserting any resistance cassette. Based on a two-steps clonal isolation protocol (mechanical picking followed by enzymatic dissociation), we succeed to select and expand corrected human iPS cell line with a great efficiency (more than 2% of the sequenced colonies). This protocol can also be used to obtain knock-out cell line from healthy iPS cell line by the NHEJ pathway (with about 15% efficiency) and reproduce disease phenotype. In addition, we also provide protocols for functional validation tests after every critical step.

Human genetic resistance to malaria.

PubMed

Williams, Thomas N

2009-01-01

This brief chapter highlights the need for caution when designing and interpreting studies aimed at seeking new genes that may be associated with malaria protection, or investigating the potential mechanisms for protection in promising candidates. Judging genetic effects on the basis of the wrong clinical phenotype and missing true protective genes because their protective effects are masked by unpredictable epistatic effects are major potential pitfalls. These issues are by no means unique to malaria: in recent years, the importance of larger sample sizes and careful phenotypic definitions have become appreciated increasingly, particularly for genome-wide studies of complex diseases (Cordell and Clayton, 2005; Burton, Tobin and Hopper, 2005). Until recently, research in the field of malaria genetics has not enjoyed the sort of funding afforded to similar work investigating diseases of importance to the developed world. However, in the last few years, coupled with advances in genetic diagnostics that have led to massive automation and falling costs per gene explored, momentum has grown towards more generous funding that brings with it the opportunity for much larger, multisite cohesive studies. The stage is set for a giant leap forward in the coming years.

Psoriasiform skin disease in transgenic pigs with high-copy ectopic expression of human integrins α2 and β1.

PubMed

Staunstrup, Nicklas Heine; Stenderup, Karin; Mortensen, Sidsel; Primo, Maria Nascimento; Rosada, Cecilia; Steiniche, Torben; Liu, Ying; Li, Rong; Schmidt, Mette; Purup, Stig; Dagnæs-Hansen, Frederik; Schrøder, Lisbeth Dahl; Svensson, Lars; Petersen, Thomas Kongstad; Callesen, Henrik; Bolund, Lars; Mikkelsen, Jacob Giehm

2017-07-01

Psoriasis is a complex human-specific disease characterized by perturbed keratinocyte proliferation and a pro-inflammatory environment in the skin. Porcine skin architecture and immunity are very similar to that in humans, rendering the pig a suitable animal model for studying the biology and treatment of psoriasis. Expression of integrins, which is normally confined to the basal layer of the epidermis, is maintained in suprabasal keratinocytes in psoriatic skin, modulating proliferation and differentiation as well as leukocyte infiltration. Here, we generated minipigs co-expressing integrins α2 and β1 in suprabasal epidermal layers. Integrin-transgenic minipigs born into the project displayed skin phenotypes that correlated with the number of inserted transgenes. Molecular analyses were in good concordance with histological observations of psoriatic hallmarks, including hypogranulosis and T-lymphocyte infiltration. These findings mark the first creation of minipigs with a psoriasiform phenotype resembling human psoriasis and demonstrate that integrin signaling plays a key role in psoriasis pathology. © 2017. Published by The Company of Biologists Ltd.

Peptide biomarkers used for the selective breeding of a complex polygenic trait in honey bees.

PubMed

Guarna, M Marta; Hoover, Shelley E; Huxter, Elizabeth; Higo, Heather; Moon, Kyung-Mee; Domanski, Dominik; Bixby, Miriam E F; Melathopoulos, Andony P; Ibrahim, Abdullah; Peirson, Michael; Desai, Suresh; Micholson, Derek; White, Rick; Borchers, Christoph H; Currie, Robert W; Pernal, Stephen F; Foster, Leonard J

2017-08-21

We present a novel way to select for highly polygenic traits. For millennia, humans have used observable phenotypes to selectively breed stronger or more productive livestock and crops. Selection on genotype, using single-nucleotide polymorphisms (SNPs) and genome profiling, is also now applied broadly in livestock breeding programs; however, selection on protein/peptide or mRNA expression markers has not yet been proven useful. Here we demonstrate the utility of protein markers to select for disease-resistant hygienic behavior in the European honey bee (Apis mellifera L.). Robust, mechanistically-linked protein expression markers, by integrating cis- and trans- effects from many genomic loci, may overcome limitations of genomic markers to allow for selection. After three generations of selection, the resulting marker-selected stock outperformed an unselected benchmark stock in terms of hygienic behavior, and had improved survival when challenged with a bacterial disease or a parasitic mite, similar to bees selected using a phenotype-based assessment for this trait. This is the first demonstration of the efficacy of protein markers for industrial selective breeding in any agricultural species, plant or animal.

XPD Helicase Structures And Activities: Insights Into the Cancer And Aging Phenotypes From XPD Mutations

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

Fan, L.; Fuss, J.O.; Cheng, Q.J.

2009-05-18

Mutations in XPD helicase, required for nucleotide excision repair (NER) as part of the transcription/repair complex TFIIH, cause three distinct phenotypes: cancer-prone xeroderma pigmentosum (XP), or aging disorders Cockayne syndrome (CS), and trichothiodystrophy (TTD). To clarify molecular differences underlying these diseases, we determined crystal structures of the XPD catalytic core from Sulfolobus acidocaldarius and measured mutant enzyme activities. Substrate-binding grooves separate adjacent Rad51/RecA-like helicase domains (HD1, HD2) and an arch formed by 4FeS and Arch domains. XP mutations map along the HD1 ATP-binding edge and HD2 DNA-binding channel and impair helicase activity essential for NER. XP/CS mutations both impair helicasemore » activity and likely affect HD2 functional movement. TTD mutants lose or retain helicase activity but map to sites in all four domains expected to cause framework defects impacting TFIIH integrity. These results provide a foundation for understanding disease consequences of mutations in XPD and related 4Fe-4S helicases including FancJ.« less

XPD Helicase Structures and Activities: Insights into the Cancer and Aging Phenotypes from XPD Mutations

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

Tainer, John; Fan, Li; Fuss, Jill O.

2008-06-02

Mutations in XPD helicase, required for nucleotide excision repair (NER) as part of the transcription/repair complex TFIIH, cause three distinct phenotypes: cancer-prone xeroderma pigmentosum (XP), or aging disorders Cockayne syndrome (CS), and trichothiodystrophy (TTD). To clarify molecular differences underlying these diseases, we determined crystal structures of the XPD catalytic core from Sulfolobus acidocaldarius and measured mutant enzyme activities. Substrate-binding grooves separate adjacent Rad51/RecA-like helicase domains (HD1, HD2) and an arch formed by 4FeS and Arch domains. XP mutations map along the HD1 ATP-binding edge and HD2 DNA-binding channel and impair helicase activity essential for NER. XP/CS mutations both impair helicasemore » activity and likely affect HD2 functional movement. TTD mutants lose or retain helicase activity but map to sites in all four domains expected to cause framework defects impacting TFIIH integrity. These results provide a foundation for understanding disease consequences of mutations in XPD and related 4Fe-4S helicases including FancJ.« less

Isoniazid resistant tuberculosis- a cause for concern?

PubMed Central

HR, Stagg; MC, Lipman; TD, McHugh; HE, Jenkins

2017-01-01

SUMMARY The drug isoniazid (INH) is a key component of global tuberculosis (TB) control programmes. It is estimated, however, that 16.1% of TB disease cases in Former Soviet Union countries and 7.5% of cases outside of those settings have non-multidrug resistant (MDR) INH resistance. Resistance has been linked to poorer treatment outcomes, post-treatment relapse and death, at least for specific sites of disease. Multiple genetic loci are associated with phenotypic resistance, but the relationship between genotype and phenotype is complex. This restricts the use of rapid sequencing techniques as part of the diagnostic process to determine the most appropriate treatment regimens for patients. The burden of resistance also influences the usefulness of INH preventative therapy (IPT). Despite seven decades of the use of INH our knowledge in key areas- such as the epidemiology of resistant strains, their clinical consequences, and their exact role in fuelling the MDR TB epidemic- is limited. The importance of non-MDR INH resistance needs to be re-evaluated both globally and by national TB control programmes. PMID:28234075

BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.

PubMed

Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong

2017-02-03

Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of phenotype on health care costs in Crohn's disease: A European study using the Montreal classification.

PubMed

Odes, Selwyn; Vardi, Hillel; Friger, Michael; Wolters, Frank; Hoie, Ole; Moum, Bjørn; Bernklev, Tomm; Yona, Hagit; Russel, Maurice; Munkholm, Pia; Langholz, Ebbe; Riis, Lene; Politi, Patrizia; Bondini, Paolo; Tsianos, Epameinondas; Katsanos, Kostas; Clofent, Juan; Vermeire, Severine; Freitas, João; Mouzas, Iannis; Limonard, Charles; O'Morain, Colm; Monteiro, Estela; Fornaciari, Giovanni; Vatn, Morten; Stockbrugger, Reinhold

2007-12-01

Crohn's disease (CD) is a chronic inflammation of the gastrointestinal tract associated with life-long high health care costs. We aimed to determine the effect of disease phenotype on cost. Clinical and economic data of a community-based CD cohort with 10-year follow-up were analyzed retrospectively in relation to Montreal classification phenotypes. In 418 patients, mean total costs of health care for the behavior phenotypes were: nonstricturing-nonpenetrating 1690, stricturing 2081, penetrating 3133 and penetrating-with-perianal-fistula 3356 €/patient-phenotype-year (P<0.001), and mean costs of surgical hospitalization 215, 751, 1293 and 1275 €/patient-phenotype-year respectively (P<0.001). Penetrating-with-perianal-fistula patients incurred significantly greater expenses than penetrating patients for total care, diagnosis and drugs, but not surgical hospitalization. Total costs were similar in the location phenotypes: ileum 1893, colon 1748, ileo-colonic 2010 and upper gastrointestinal tract 1758 €/patient-phenotype-year, but surgical hospitalization costs differed significantly, 558, 209, 492 and 542 €/patient-phenotype-year respectively (P<0.001). By multivariate analysis, the behavior phenotype significantly impacted total, medical and surgical hospitalization costs, whereas the location phenotype affected only surgical costs. Younger age at diagnosis predicted greater surgical expenses. Behavior is the dominant phenotype driving health care cost. Use of the Montreal classification permits detection of cost differences caused by perianal fistula.

Interoperability between phenotype and anatomy ontologies.

PubMed

Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

2010-12-15

Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

Peripheral neuropathy in complex inherited diseases: an approach to diagnosis.

PubMed

Rossor, Alexander M; Carr, Aisling S; Devine, Helen; Chandrashekar, Hoskote; Pelayo-Negro, Ana Lara; Pareyson, Davide; Shy, Michael E; Scherer, Steven S; Reilly, Mary M

2017-10-01

Peripheral neuropathy is a common finding in patients with complex inherited neurological diseases and may be subclinical or a major component of the phenotype. This review aims to provide a clinical approach to the diagnosis of this complex group of patients by addressing key questions including the predominant neurological syndrome associated with the neuropathy, for example, spasticity, the type of neuropathy and the other neurological and non-neurological features of the syndrome. Priority is given to the diagnosis of treatable conditions. Using this approach, we associated neuropathy with one of three major syndromic categories: (1) ataxia, (2) spasticity and (3) global neurodevelopmental impairment. Syndromes that do not fall easily into one of these three categories can be grouped according to the predominant system involved in addition to the neuropathy, for example, cardiomyopathy and neuropathy. We also include a separate category of complex inherited relapsing neuropathy syndromes, some of which may mimic Guillain-Barré syndrome, as many will have a metabolic aetiology and be potentially treatable. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Red Blood Cell Antigen Genotyping for Sickle Cell Disease, Thalassemia, and Other Transfusion Complications.

PubMed

Fasano, Ross M; Chou, Stella T

2016-10-01

Since the discovery of the ABO blood group in the early 20th century, more than 300 blood group antigens have been categorized among 35 blood group systems. The molecular basis for most blood group antigens has been determined and demonstrates tremendous genetic diversity, particularly in the ABO and Rh systems. Several blood group genotyping assays have been developed, and 1 platform has been approved by the Food and Drug Administration as a "test of record," such that no phenotype confirmation with antisera is required. DNA-based red blood cell (RBC) phenotyping can overcome certain limitations of hemagglutination assays and is beneficial in many transfusion settings. Genotyping can be used to determine RBC antigen phenotypes in patients recently transfused or with interfering allo- or autoantibodies, to resolve discrepant serologic typing, and/or when typing antisera are not readily available. Molecular RBC antigen typing can facilitate complex antibody evaluations and guide RBC selection for patients with sickle cell disease (SCD), thalassemia, and autoimmune hemolytic anemia. High-resolution RH genotyping can identify variant RHD and RHCE in patients with SCD, which have been associated with alloimmunization. In the future, broader access to cost-efficient, high-resolution RBC genotyping technology for both patient and donor populations may be transformative for the field of transfusion medicine. Copyright © 2016. Published by Elsevier Inc.

Fused cerebral organoids model interactions between brain regions.

PubMed

Bagley, Joshua A; Reumann, Daniel; Bian, Shan; Lévi-Strauss, Julie; Knoblich, Juergen A

2017-07-01

Human brain development involves complex interactions between different regions, including long-distance neuronal migration or formation of major axonal tracts. Different brain regions can be cultured in vitro within 3D cerebral organoids, but the random arrangement of regional identities limits the reliable analysis of complex phenotypes. Here, we describe a coculture method combining brain regions of choice within one organoid tissue. By fusing organoids of dorsal and ventral forebrain identities, we generate a dorsal-ventral axis. Using fluorescent reporters, we demonstrate CXCR4-dependent GABAergic interneuron migration from ventral to dorsal forebrain and describe methodology for time-lapse imaging of human interneuron migration. Our results demonstrate that cerebral organoid fusion cultures can model complex interactions between different brain regions. Combined with reprogramming technology, fusions should offer researchers the possibility to analyze complex neurodevelopmental defects using cells from neurological disease patients and to test potential therapeutic compounds.

Mutation screening of 75 candidate genes in 152 complex I deficiency cases identifies pathogenic variants in 16 genes including NDUFB9.

PubMed

Haack, Tobias B; Madignier, Florence; Herzer, Martina; Lamantea, Eleonora; Danhauser, Katharina; Invernizzi, Federica; Koch, Johannes; Freitag, Martin; Drost, Rene; Hillier, Ingo; Haberberger, Birgit; Mayr, Johannes A; Ahting, Uwe; Tiranti, Valeria; Rötig, Agnes; Iuso, Arcangela; Horvath, Rita; Tesarova, Marketa; Baric, Ivo; Uziel, Graziella; Rolinski, Boris; Sperl, Wolfgang; Meitinger, Thomas; Zeviani, Massimo; Freisinger, Peter; Prokisch, Holger

2012-02-01

Mitochondrial complex I deficiency is the most common cause of mitochondrial disease in childhood. Identification of the molecular basis is difficult given the clinical and genetic heterogeneity. Most patients lack a molecular definition in routine diagnostics. A large-scale mutation screen of 75 candidate genes in 152 patients with complex I deficiency was performed by high-resolution melting curve analysis and Sanger sequencing. The causal role of a new disease allele was confirmed by functional complementation assays. The clinical phenotype of patients carrying mutations was documented using a standardised questionnaire. Causative mutations were detected in 16 genes, 15 of which had previously been associated with complex I deficiency: three mitochondrial DNA genes encoding complex I subunits, two mitochondrial tRNA genes and nuclear DNA genes encoding six complex I subunits and four assembly factors. For the first time, a causal mutation is described in NDUFB9, coding for a complex I subunit, resulting in reduction in NDUFB9 protein and both amount and activity of complex I. These features were rescued by expression of wild-type NDUFB9 in patient-derived fibroblasts. Mutant NDUFB9 is a new cause of complex I deficiency. A molecular diagnosis related to complex I deficiency was established in 18% of patients. However, most patients are likely to carry mutations in genes so far not associated with complex I function. The authors conclude that the high degree of genetic heterogeneity in complex I disorders warrants the implementation of unbiased genome-wide strategies for the complete molecular dissection of mitochondrial complex I deficiency.

Airway disease phenotypes in animal models of cystic fibrosis.

PubMed

McCarron, Alexandra; Donnelley, Martin; Parsons, David

2018-04-02

In humans, cystic fibrosis (CF) lung disease is characterised by chronic infection, inflammation, airway remodelling, and mucus obstruction. A lack of pulmonary manifestations in CF mouse models has hindered investigations of airway disease pathogenesis, as well as the development and testing of potential therapeutics. However, recently generated CF animal models including rat, ferret and pig models demonstrate a range of well characterised lung disease phenotypes with varying degrees of severity. This review discusses the airway phenotypes of currently available CF animal models and presents potential applications of each model in airway-related CF research.

Differential factors associated with challenge-proven food allergy phenotypes in a population cohort of infants: a latent class analysis.

PubMed

Peters, R L; Allen, K J; Dharmage, S C; Lodge, C J; Koplin, J J; Ponsonby, A-L; Wake, M; Lowe, A J; Tang, M L K; Matheson, M C; Gurrin, L C

2015-05-01

Food allergy, eczema and wheeze are early manifestations of allergic disease and commonly co-occur in infancy although their interrelationship is not well understood. Data from population studies are essential to determine whether there are differential drivers of multi-allergy phenotypes. We aimed to define phenotypes and risk factors of allergic disease using latent class analysis (LCA). The HealthNuts study is a prospective, population-based cohort of 5276 12-month-old infants in Melbourne, Australia. LCA was performed using the following baseline data collected at age 12 months: food sensitization (skin prick test ≥ 2 mm) and allergy (oral food challenge) to egg, peanut and sesame; early (< 4 months) and late-onset eczema; and wheeze in the first year of life. Risk factors were modelled using multinomial logistic regression. Five distinct phenotypes were identified: no allergic disease (70%), non-food-sensitized eczema (16%), single egg allergy (9%), multiple food allergies (predominantly peanut) (3%) and multiple food allergies (predominantly egg) (2%). Compared to the baseline group of no allergic disease, shared risk factors for all allergic phenotypes were parents born overseas (particularly Asia), delayed introduction of egg, male gender (except for single egg allergy) and family history of allergic disease, whilst exposure to pet dogs was protective for all phenotypes. Other factors including filaggrin mutations, vitamin D and the presence of older siblings differed by phenotype. Multiple outcomes in infancy can be used to determine five distinct allergy phenotypes at the population level, which have both shared and separate risk factors suggesting differential mechanisms of disease. © 2014 John Wiley & Sons Ltd.

Identification of genetic elements in metabolism by high-throughput mouse phenotyping.

PubMed

Rozman, Jan; Rathkolb, Birgit; Oestereicher, Manuela A; Schütt, Christine; Ravindranath, Aakash Chavan; Leuchtenberger, Stefanie; Sharma, Sapna; Kistler, Martin; Willershäuser, Monja; Brommage, Robert; Meehan, Terrence F; Mason, Jeremy; Haselimashhadi, Hamed; Hough, Tertius; Mallon, Ann-Marie; Wells, Sara; Santos, Luis; Lelliott, Christopher J; White, Jacqueline K; Sorg, Tania; Champy, Marie-France; Bower, Lynette R; Reynolds, Corey L; Flenniken, Ann M; Murray, Stephen A; Nutter, Lauryl M J; Svenson, Karen L; West, David; Tocchini-Valentini, Glauco P; Beaudet, Arthur L; Bosch, Fatima; Braun, Robert B; Dobbie, Michael S; Gao, Xiang; Herault, Yann; Moshiri, Ala; Moore, Bret A; Kent Lloyd, K C; McKerlie, Colin; Masuya, Hiroshi; Tanaka, Nobuhiko; Flicek, Paul; Parkinson, Helen E; Sedlacek, Radislav; Seong, Je Kyung; Wang, Chi-Kuang Leo; Moore, Mark; Brown, Steve D; Tschöp, Matthias H; Wurst, Wolfgang; Klingenspor, Martin; Wolf, Eckhard; Beckers, Johannes; Machicao, Fausto; Peter, Andreas; Staiger, Harald; Häring, Hans-Ulrich; Grallert, Harald; Campillos, Monica; Maier, Holger; Fuchs, Helmut; Gailus-Durner, Valerie; Werner, Thomas; Hrabe de Angelis, Martin

2018-01-18

Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.

Novel throughput phenotyping platforms in plant genetic studies.

PubMed

Montes, Juan M; Melchinger, Albrecht E; Reif, Jochen C

2007-10-01

Unraveling the genetic basis of complex traits in plants is limited by the lack of appropriate phenotyping platforms that enable high-throughput screening of many genotypes in multilocation field trials. Near-infrared spectroscopy on agricultural harvesters and spectral reflectance of plant canopies have recently been reported as promising components of novel phenotyping platforms. Understanding the genetic basis of complex traits is now within reach with the use of these new techniques.

Extensive Diversity of Prion Strains Is Defined by Differential Chaperone Interactions and Distinct Amyloidogenic Regions

PubMed Central

Stein, Kevin C.; True, Heather L.

2014-01-01

Amyloidogenic proteins associated with a variety of unrelated diseases are typically capable of forming several distinct self-templating conformers. In prion diseases, these different structures, called prion strains (or variants), confer dramatic variation in disease pathology and transmission. Aggregate stability has been found to be a key determinant of the diverse pathological consequences of different prion strains. Yet, it remains largely unclear what other factors might account for the widespread phenotypic variation seen with aggregation-prone proteins. Here, we examined a set of yeast prion variants of the [RNQ+] prion that differ in their ability to induce the formation of another yeast prion called [PSI+]. Remarkably, we found that the [RNQ+] variants require different, non-contiguous regions of the Rnq1 protein for both prion propagation and [PSI+] induction. This included regions outside of the canonical prion-forming domain of Rnq1. Remarkably, such differences did not result in variation in aggregate stability. Our analysis also revealed a striking difference in the ability of these [RNQ+] variants to interact with the chaperone Sis1. Thus, our work shows that the differential influence of various amyloidogenic regions and interactions with host cofactors are critical determinants of the phenotypic consequences of distinct aggregate structures. This helps reveal the complex interdependent factors that influence how a particular amyloid structure may dictate disease pathology and progression. PMID:24811344

Common Variants in Mendelian Kidney Disease Genes and Their Association with Renal Function

PubMed Central

Fuchsberger, Christian; Köttgen, Anna; O’Seaghdha, Conall M.; Pattaro, Cristian; de Andrade, Mariza; Chasman, Daniel I.; Teumer, Alexander; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Kim, Young J.; Taliun, Daniel; Li, Man; Feitosa, Mary; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C.; Glazer, Nicole; Isaacs, Aaron; Rao, Madhumathi; Smith, Albert V.; O’Connell, Jeffrey R.; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Hwang, Shih-Jen; Atkinson, Elizabeth J.; Lohman, Kurt; Cornelis, Marilyn C.; Johansson, Åsa; Tönjes, Anke; Dehghan, Abbas; Couraki, Vincent; Holliday, Elizabeth G.; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y.; Murgia, Federico; Trompet, Stella; Imboden, Medea; Kollerits, Barbara; Pistis, Giorgio; Harris, Tamara B.; Launer, Lenore J.; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D.; Boerwinkle, Eric; Schmidt, Helena; Hofer, Edith; Hu, Frank; Demirkan, Ayse; Oostra, Ben A.; Turner, Stephen T.; Ding, Jingzhong; Andrews, Jeanette S.; Freedman, Barry I.; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Döring, Angela; Wichmann, H.-Erich; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E.; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H.; Wright, Alan F.; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K.; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G.; Rivadeneira, Fernando; Aulchenko, Yurii S.; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K.; Portas, Laura; Ford, Ian; Buckley, Brendan M.; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J. Wouter; Probst-Hensch, Nicole M.; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R.; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; van Duijn, Cornelia M.; Borecki, Ingrid; Kardia, Sharon L.R.; Liu, Yongmei; Curhan, Gary C.; Rudan, Igor; Gyllensten, Ulf; Wilson, James F.; Franke, Andre; Pramstaller, Peter P.; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M.; Bochud, Murielle; Heid, Iris M.; Siscovick, David S.; Fox, Caroline S.; Kao, W. Linda; Böger, Carsten A.

2013-01-01

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research. PMID:24029420

Immune interactions in endometriosis

PubMed Central

Herington, Jennifer L; Bruner-Tran, Kaylon L; Lucas, John A; Osteen, Kevin G

2011-01-01

Endometriosis is a common, complex gynecologic disorder characterized by the presence of endometrial glands and stroma at extrauterine (ectopic) sites. In women who develop this disease, alterations in specific biological processes involving both the endocrine and immune systems have been observed, which may explain the survival and growth of displaced endometrial tissue in affected women. In the past decade, a considerable amount of research has implicated a role for alterations in progesterone action at both eutopic and ectopic sites of endometrial growth which may contribute to the excessive inflammation associated with progression of endometriosis; however, it remains unclear whether these anomalies induce the condition or are simply a consequence of the disease process. In this article, we summarize current knowledge of alterations within the immune system of endometriosis patients and discuss how endometrial cells from women with this disease not only have the capacity to escape immunosurveillance, but also use inflammatory mechanisms to promote their growth within the peritoneal cavity. Finally, we discuss evidence that exposure to an environmental endocrine disruptor, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin, can mediate the development of an endometrial phenotype that exhibits both reduced progesterone responsiveness and hypersensitivity to proinflammatory stimuli mimicking the endometriosis phenotype. Future studies in women with endometriosis should consider whether a heightened inflammatory response within the peritoneal microenvironment contributes to the development and persistence of this disease. PMID:21895474

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

Progranulin in neurodegenerative disease.

PubMed

Petkau, Terri L; Leavitt, Blair R

2014-07-01

Loss-of-function mutations in the progranulin gene are a common cause of familial frontotemporal dementia (FTD). The purpose of this review is to summarize the role of progranulin in health and disease, because the field is now poised to begin examining therapeutics that alter endogenous progranulin levels. We first review the clinical and neuropathological phenotype of FTD patients carrying mutations in the progranulin gene, which suggests that progranulin-mediated neurodegeneration is multifactorial and influenced by other genetic and/or environmental factors. We then examine evidence for the role of progranulin in the brain with a focus on mouse model systems. A better understanding of the complexity of progranulin biology in the brain will help guide the development of progranulin-modulating therapies for neurodegenerative disease. Copyright © 2014 Elsevier Ltd. All rights reserved.

Hypertrophic cardiomyopathy.

PubMed

Santos Mateo, Juan José; Sabater Molina, María; Gimeno Blanes, Juan Ramón

2018-06-08

Hypertrophic cardiomyopathy is the most common inherited cardiovascular disease. It is characterized by increased ventricular wall thickness and is highly complex due to its heterogeneous clinical presentation, several phenotypes, large number of associated causal mutations and broad spectrum of complications. It is caused by mutations in sarcomeric proteins, which are identified in up to 60% of cases of the disease. Clinical manifestations of Hypertrophic Cardiomyopathy include shortness of breath, chest pain, palpitations and syncope, which are related to the onset of diastolic dysfunction, left ventricular outflow tract obstruction, ischemia, atrial fibrillation and abnormal vascular responses. It is associated with an increased risk of sudden cardiac death, heart failure and thromboembolic events. In this article, we discuss the diagnostic and therapeutic aspects of this disease. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Enteroaggregative Escherichia coli have evolved independently as distinct complexes within the E. coli population with varying ability to cause disease.

PubMed

Chattaway, Marie Anne; Jenkins, Claire; Rajendram, Dunstan; Cravioto, Alejandro; Talukder, Kaisar Ali; Dallman, Tim; Underwood, Anthony; Platt, Steve; Okeke, Iruka N; Wain, John

2014-01-01

Enteroaggregative E. coli (EAEC) is an established diarrhoeagenic pathotype. The association with virulence gene content and ability to cause disease has been studied but little is known about the population structure of EAEC and how this pathotype evolved. Analysis by Multi Locus Sequence Typing of 564 EAEC isolates from cases and controls in Bangladesh, Nigeria and the UK spanning the past 29 years, revealed multiple successful lineages of EAEC. The population structure of EAEC indicates some clusters are statistically associated with disease or carriage, further highlighting the heterogeneous nature of this group of organisms. Different clusters have evolved independently as a result of both mutational and recombination events; the EAEC phenotype is distributed throughout the population of E. coli.

Quantitative phenotyping of X-disease resistance in chokecherry using real-time PCR.

PubMed

Huang, Danqiong; Walla, James A; Dai, Wenhao

2014-03-01

A quantitative real-time SYBR Green PCR (qPCR) assay has been developed to detect and quantify X-disease phytoplasmas in chokecherry. An X-disease phytoplasma-specific and high sensitivity primer pair was designed based on the 16S rRNA gene sequence of X-disease phytoplasmas. This primer pair was specific to the 16SrIII group (X-disease) phytoplasmas. The qPCR method can quantify phytoplasmas from a DNA mix (a mix of both chokecherry and X-disease phytoplasma DNA) at as low as 0.001 ng, 10-fold lower than conventional PCR using the same primer pair. A significant correlation between the copy number of phytoplasmas and visual phenotypic rating scores of X-disease resistance in chokecherry plants was observed. Disease resistant chokecherries had a significantly lower titer of X-disease phytoplasmas than susceptible plants. This suggests that the qPCR assay provides a more objective tool to phenotype phytoplasma disease severity, particularly for early evaluation of host resistance; therefore, this method will facilitate quantitative phenotyping of disease resistance and has great potential in enhancing plant breeding. Copyright © 2013 Elsevier B.V. All rights reserved.

Advantages and pitfalls of an extended gene panel for investigating complex neurometabolic phenotypes.

PubMed

Reid, Emma S; Papandreou, Apostolos; Drury, Suzanne; Boustred, Christopher; Yue, Wyatt W; Wedatilake, Yehani; Beesley, Clare; Jacques, Thomas S; Anderson, Glenn; Abulhoul, Lara; Broomfield, Alex; Cleary, Maureen; Grunewald, Stephanie; Varadkar, Sophia M; Lench, Nick; Rahman, Shamima; Gissen, Paul; Clayton, Peter T; Mills, Philippa B

2016-11-01

Neurometabolic disorders are markedly heterogeneous, both clinically and genetically, and are characterized by variable neurological dysfunction accompanied by suggestive neuroimaging or biochemical abnormalities. Despite early specialist input, delays in diagnosis and appropriate treatment initiation are common. Next-generation sequencing approaches still have limitations but are already enabling earlier and more efficient diagnoses in these patients. We designed a gene panel targeting 614 genes causing inborn errors of metabolism and tested its diagnostic efficacy in a paediatric cohort of 30 undiagnosed patients presenting with variable neurometabolic phenotypes. Genetic defects that could, at least partially, explain observed phenotypes were identified in 53% of cases. Where biochemical abnormalities pointing towards a particular gene defect were present, our panel identified diagnoses in 89% of patients. Phenotypes attributable to defects in more than one gene were seen in 13% of cases. The ability of in silico tools, including structure-guided prediction programmes to characterize novel missense variants were also interrogated. Our study expands the genetic, clinical and biochemical phenotypes of well-characterized (POMGNT1, TPP1) and recently identified disorders (PGAP2, ACSF3, SERAC1, AFG3L2, DPYS). Overall, our panel was accurate and efficient, demonstrating good potential for applying similar approaches to clinically and biochemically diverse neurometabolic disease cohorts. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

Directed evolution and synthetic biology applications to microbial systems.

PubMed

Bassalo, Marcelo C; Liu, Rongming; Gill, Ryan T

2016-06-01

Biotechnology applications require engineering complex multi-genic traits. The lack of knowledge on the genetic basis of complex phenotypes restricts our ability to rationally engineer them. However, complex phenotypes can be engineered at the systems level, utilizing directed evolution strategies that drive whole biological systems toward desired phenotypes without requiring prior knowledge of the genetic basis of the targeted trait. Recent developments in the synthetic biology field accelerates the directed evolution cycle, facilitating engineering of increasingly complex traits in biological systems. In this review, we summarize some of the most recent advances in directed evolution and synthetic biology that allows engineering of complex traits in microbial systems. Then, we discuss applications that can be achieved through engineering at the systems level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Whole genome sequencing and comparative genomics of closely related Fusarium Head Blight fungi: Fusarium graminearum, F. meridionale and F. asiaticum.

PubMed

Walkowiak, Sean; Rowland, Owen; Rodrigue, Nicolas; Subramaniam, Rajagopal

2016-12-09

The Fusarium graminearum species complex is composed of many distinct fungal species that cause several diseases in economically important crops, including Fusarium Head Blight of wheat. Despite being closely related, these species and individuals within species have distinct phenotypic differences in toxin production and pathogenicity, with some isolates reported as non-pathogenic on certain hosts. In this report, we compare genomes and gene content of six new isolates from the species complex, including the first available genomes of F. asiaticum and F. meridionale, with four other genomes reported in previous studies. A comparison of genome structure and gene content revealed a 93-99% overlap across all ten genomes. We identified more than 700 k base pairs (kb) of single nucleotide polymorphisms (SNPs), insertions, and deletions (indels) within common regions of the genome, which validated the species and genetic populations reported within species. We constructed a non-redundant pan gene list containing 15,297 genes from the ten genomes and among them 1827 genes or 12% were absent in at least one genome. These genes were co-localized in telomeric regions and select regions within chromosomes with a corresponding increase in SNPs and indels. Many are also predicted to encode for proteins involved in secondary metabolism and other functions associated with disease. Genes that were common between isolates contained high levels of nucleotide variation and may be pseudogenes, allelic, or under diversifying selection. The genomic resources we have contributed will be useful for the identification of genes that contribute to the phenotypic variation and niche specialization that have been reported among members of the F. graminearum species complex.

Defining a Contemporary Ischemic Heart Disease Genetic Risk Profile Using Historical Data.

PubMed

Mosley, Jonathan D; van Driest, Sara L; Wells, Quinn S; Shaffer, Christian M; Edwards, Todd L; Bastarache, Lisa; McCarty, Catherine A; Thompson, Will; Chute, Christopher G; Jarvik, Gail P; Crosslin, David R; Larson, Eric B; Kullo, Iftikhar J; Pacheco, Jennifer A; Peissig, Peggy L; Brilliant, Murray H; Linneman, James G; Denny, Josh C; Roden, Dan M

2016-12-01

Continued reductions in morbidity and mortality attributable to ischemic heart disease (IHD) require an understanding of the changing epidemiology of this disease. We hypothesized that we could use genetic correlations, which quantify the shared genetic architectures of phenotype pairs and extant risk factors from a historical prospective study to define the risk profile of a contemporary IHD phenotype. We used 37 phenotypes measured in the ARIC study (Atherosclerosis Risk in Communities; n=7716, European ancestry subjects) and clinical diagnoses from an electronic health record (EHR) data set (n=19 093). All subjects had genome-wide single-nucleotide polymorphism genotyping. We measured pairwise genetic correlations (rG) between the ARIC and EHR phenotypes using linear mixed models. The genetic correlation estimates between the ARIC risk factors and the EHR IHD were modestly linearly correlated with hazards ratio estimates for incident IHD in ARIC (Pearson correlation [r]=0.62), indicating that the 2 IHD phenotypes had differing risk profiles. For comparison, this correlation was 0.80 when comparing EHR and ARIC type 2 diabetes mellitus phenotypes. The EHR IHD phenotype was most strongly correlated with ARIC metabolic phenotypes, including total:high-density lipoprotein cholesterol ratio (rG=-0.44, P=0.005), high-density lipoprotein (rG=-0.48, P=0.005), systolic blood pressure (rG=0.44, P=0.02), and triglycerides (rG=0.38, P=0.02). EHR phenotypes related to type 2 diabetes mellitus, atherosclerotic, and hypertensive diseases were also genetically correlated with these ARIC risk factors. The EHR IHD risk profile differed from ARIC and indicates that treatment and prevention efforts in this population should target hypertensive and metabolic disease. © 2016 American Heart Association, Inc.