Faculty Opinions recommendation of Most rare missense alleles are deleterious in humans: implications for complex disease and association studies.

2007 ◽  
Author(s):  
Thomas Mitchell-Olds
Keyword(s):  
Complex Disease ◽  
Association Studies

scholarly journals Twelve years of GWAS discoveries for osteoporosis and related traits: advances, challenges and applications

Bone Research ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Xiaowei Zhu ◽  
Weiyang Bai ◽  
Houfeng Zheng
Keyword(s):  
Drug Targets ◽  
Complex Disease ◽  
Association Studies ◽  
Osteoporotic Fractures ◽  
Disease Prediction ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Small Effect Size ◽  
Endocrine Status ◽  
Meta Analyses

AbstractOsteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction. Despite the fruitful GWAS discoveries in the bone field, most of these GWAS participants were of European descent, and more genetic studies should be carried out in other ethnic populations to benefit disease prediction in the corresponding population.

scholarly journals Host Genetics and Gut Microbiome: Perspectives for Multiple Sclerosis

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1181
Author(s):  
Alessandro Maglione ◽  
Miriam Zuccalà ◽  
Martina Tosi ◽  
Marinella Clerico ◽  
Simona Rolla
Keyword(s):  
Multiple Sclerosis ◽  
Environmental Factors ◽  
Lupus Erythematosus ◽  
Gut Microbiome ◽  
Complex Disease ◽  
Current Knowledge ◽  
Association Studies ◽  
Future Research ◽  
Genome Wide Association Studies ◽  
Host Genetics

As a complex disease, Multiple Sclerosis (MS)’s etiology is determined by both genetic and environmental factors. In the last decade, the gut microbiome has emerged as an important environmental factor, but its interaction with host genetics is still unknown. In this review, we focus on these dual aspects of MS pathogenesis: we describe the current knowledge on genetic factors related to MS, based on genome-wide association studies, and then illustrate the interactions between the immune system, gut microbiome and central nervous system in MS, summarizing the evidence available from Experimental Autoimmune Encephalomyelitis mouse models and studies in patients. Finally, as the understanding of influence of host genetics on the gut microbiome composition in MS is in its infancy, we explore this issue based on the evidence currently available from other autoimmune diseases that share with MS the interplay of genetic with environmental factors (Inflammatory Bowel Disease, Rheumatoid Arthritis and Systemic Lupus Erythematosus), and discuss avenues for future research.

scholarly journals Genetic Vectors as a Tool in Association Studies: Definitions and Application for Study of Rheumatoid Arthritis

2015 ◽  
Vol 2015 ◽  
pp. 1-13
Author(s):  
Igor Sandalov ◽  
Leonid Padyukov
Keyword(s):  
Rheumatoid Arthritis ◽  
Complex Disease ◽  
Association Studies ◽  
Healthy Population ◽  
Common Complex Disease ◽  
New Approach ◽  
Functional Studies ◽  
Biological Interpretation ◽  
Genetic Vectors ◽  
Efficient Selection

To identify putative relations between different genetic factors in the human genome in the development of common complex disease, we mapped the genetic data to an ensemble of spin chains and analysed the data as a quantum system. Each SNP is considered as a spin with three states corresponding to possible genotypes. The combined genotype represents a multispin state, described by the product of individual-spin states. Each person is characterized by a single genetic vector (GV) and individuals with identical GVs comprise the GV group. This consolidation of genotypes into GVs provides integration of multiple genetic variants for a single statistical test and excludes ambiguity of biological interpretation known for allele and haplotype associations. We analyzed two independent cohorts, with 2633 rheumatoid arthritis cases and 2108 healthy controls, and data for 6 SNPs from the HTR2A locus plus shared epitope allele. We found that GVs based on selected markers are highly informative and overlap for 98.3% of the healthy population between two cohorts. Interestingly, some of the GV groups contain either only controls or only cases, thus demonstrating extreme susceptibility or protection features. By using this new approach we confirmed previously detected univariate associations and demonstrated the most efficient selection of SNPs for combined analyses for functional studies.

scholarly journals Genetic and Epigenetic Modifiers of Alcoholic Liver Disease

2018 ◽  
Vol 19 (12) ◽  
pp. 3857 ◽  
Author(s):  
Marica Meroni ◽  
Miriam Longo ◽  
Raffaela Rametta ◽  
Paola Dongiovanni
Keyword(s):  
Liver Disease ◽  
Alcohol Consumption ◽  
Alcoholic Liver Disease ◽  
Complex Disease ◽  
Wide Spectrum ◽  
Association Studies ◽  
Phenotypic Variability ◽  
Genome Wide Association Studies ◽  
Epigenetic Factors ◽  
Excessive Alcohol Consumption

Alcoholic liver disease (ALD), a disorder caused by excessive alcohol consumption is a global health issue. More than two billion people consume alcohol in the world and about 75 million are classified as having alcohol disorders. ALD embraces a wide spectrum of hepatic lesions including steatosis, alcoholic steatohepatitis (ASH), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). ALD is a complex disease where environmental, genetic, and epigenetic factors contribute to its pathogenesis and progression. The severity of alcohol-induced liver disease depends on the amount, method of usage and duration of alcohol consumption as well as on age, gender, presence of obesity, and genetic susceptibility. Genome-wide association studies and candidate gene studies have identified genetic modifiers of ALD that can be exploited as non-invasive biomarkers, but which do not completely explain the phenotypic variability. Indeed, ALD development and progression is also modulated by epigenetic factors. The premise of this review is to discuss the role of genetic variants and epigenetic modifications, with particular attention being paid to microRNAs, as pathogenic markers, risk predictors, and therapeutic targets in ALD.

scholarly journals Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis

2019 ◽  
Author(s):  
Jing Yang ◽  
Amanda McGovern ◽  
Paul Martin ◽  
Kate Duffus ◽  
Xiangyu Ge ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gene Expression ◽  
T Cells ◽  
Complex Disease ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Dna Interaction ◽  
Genome Wide Association Studies ◽  
Causal Genes

AbstractGenome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T-cells over 24 hours, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T-cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.

scholarly journals An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

2018 ◽  
Author(s):  
Tom G. Richardson ◽  
Sean Harrison ◽  
Gibran Hemani ◽  
George Davey Smith
Keyword(s):  
Web Application ◽  
Large Scale ◽  
Complex Disease ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Polygenic Risk ◽  
The Uk

AbstractThe age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5×l0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.To demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

A Haplotype Analysis System for Genes Discovery of Common Diseases

2011 ◽  
pp. 590-604
Author(s):  
Takashi Kido
Keyword(s):  
Haplotype Analysis ◽  
Complex Disease ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Current Theory ◽  
Theory And Practice ◽  
Discovery Research ◽  
Common Diseases ◽  
The Common ◽  
Analysis System

This chapter introduces computational methods for detecting complex disease loci with haplotype analysis. It argues that the haplotype analysis, which plays a major role in the study of population genetics, can be computationally modeled and systematically implemented as a means for detecting causative genes of complex diseases. In this chapter, the author provides a review of issues on haplotype analysis and proposes the analysis system which integrates a comprehensive spectrum of functions on haplotype analysis for supporting disease association studies. The explanation of the system and some real examples of the haplotype analysis will not only provide researchers with better understanding of current theory and practice of genetic association studies, but also present a computational perspective on the gene discovery research for the common diseases.

scholarly journals Genetics of Atrial Fibrillation in 2020

2020 ◽  
Vol 127 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Carolina Roselli ◽  
Michiel Rienstra ◽  
Patrick T. Ellinor
Keyword(s):  
Atrial Fibrillation ◽  
Complex Disease ◽  
Association Studies ◽  
Heart Rhythm ◽  
Genome Wide Association Studies ◽  
Future Directions ◽  
Genetics Research ◽  
Genome Wide ◽  
Increased Risk ◽  
Rhythm Disorder

Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.

A Haplotype Analysis System for Genes Discovery of Common Diseases

2011 ◽  
pp. 214-230
Author(s):  
Takashi Kido
Keyword(s):  
Haplotype Analysis ◽  
Complex Disease ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Current Theory ◽  
Theory And Practice ◽  
Discovery Research ◽  
Common Diseases ◽  
The Common ◽  
Analysis System

This chapter introduces computational methods for detecting complex disease loci with haplotype analysis. It argues that the haplotype analysis, which plays a major role in the study of population genetics, can be computationally modeled and systematically implemented as a means for detecting causative genes of complex diseases. In this chapter, the author provides a review of issues on haplotype analysis and proposes the analysis system which integrates a comprehensive spectrum of functions on haplotype analysis for supporting disease association studies. The explanation of the system and some real examples of the haplotype analysis will not only provide researchers with better understanding of current theory and practice of genetic association studies, but also present a computational perspective on the gene discovery research for the common diseases.

scholarly journals Independent Replication and Meta-Analysis for Endometriosis Risk Loci

2015 ◽  
Vol 18 (5) ◽  
pp. 518-525 ◽  
Author(s):  
Yadav Sapkota ◽  
Amelie Fassbender ◽  
Lisa Bowdler ◽  
Jenny N. Fung ◽  
Daniëlle Peterse ◽  
...  
Keyword(s):  
Complex Disease ◽  
Association Studies ◽  
Meta Analysis ◽  
Candidate Gene Association ◽  
Genome Wide ◽  
Independent Population ◽  
Original Genome ◽  
Independent Replication ◽  
Successful Replication ◽  
Coding Variants

Endometriosis is a complex disease that affects 6–10% of women in their reproductive years and 20–50% of women with infertility. Genome-wide and candidate-gene association studies for endometriosis have identified 10 independent risk loci, and of these, nine (rs7521902, rs13394619, rs4141819, rs6542095, rs1519761, rs7739264, rs12700667, rs1537377, and rs10859871) are polymorphic in European populations. Here we investigate the replication of nine SNP loci in 998 laparoscopically and histologically confirmed endometriosis cases and 783 disease-free controls from Belgium. SNPs rs7521902, rs13394619, and rs6542095 show nominally significant (p < .05) associations with endometriosis, while the directions of effect for seven SNPs are consistent with the original reports. Association of rs6542095 at the IL1A locus with ‘All’ (p = .066) and ‘Grade_B’ (p = .01) endometriosis is noteworthy because this is the first successful replication in an independent population. Meta-analysis with the published results yields genome-wide significant evidence for rs7521902, rs13394619, rs6542095, rs12700667, rs7739264, and rs1537377. Notably, three coding variants in GREB1 (near rs13394619) and CDKN2B-AS1 (near rs1537377) also showed nominally significant associations with endometriosis. Overall, this study provides important replication in a uniquely characterized independent population, and indicates that the majority of the original genome-wide association findings are not due to chance alone.

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