scholarly journals PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits

2005 ◽  
Vol 21 (20) ◽  
pp. 3935-3937 ◽  
Author(s):  
D. Gordon ◽  
C. Haynes ◽  
J. Blumenfeld ◽  
S. J. Finch
Keyword(s):  
Complex Traits ◽  
Case Control ◽  
Genetic Studies

scholarly journals Shared associations identify causal relationships between gene expression and immune cell phenotypes

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Christiane Gasperi ◽  
Sung Chun ◽  
Shamil R. Sunyaev ◽  
Chris Cotsapas
Keyword(s):  
Complex Traits ◽  
Direct Evidence ◽  
Immune Cell ◽  
Genetic Locus ◽  
Causal Variant ◽  
Causal Relationships ◽  
Genetic Studies ◽  
Two Factors ◽  
Gene Regulatory ◽  
Cell Phenotypes

AbstractGenetic mapping studies have identified thousands of associations between common variants and hundreds of human traits. Translating these associations into mechanisms is complicated by two factors: they fall into gene regulatory regions; and they are rarely mapped to one causal variant. One way around these limitations is to find groups of traits that share associations, using this genetic link to infer a biological connection. Here, we assess how many trait associations in the same locus are due to the same genetic variant, and thus shared; and if these shared associations are due to causal relationships between traits. We find that only a subset of traits share associations, with many due to causal relationships rather than pleiotropy. We therefore suggest that simply observing overlapping associations at a genetic locus is insufficient to infer causality; direct evidence of shared associations is required to support mechanistic hypotheses in genetic studies of complex traits.

scholarly journals The limits of normal approximation for adult height

2021 ◽  
Author(s):  
Sergei A. Slavskii ◽  
Ivan A. Kuznetsov ◽  
Tatiana I. Shashkova ◽  
Georgii A. Bazykin ◽  
Tatiana I. Axenovich ◽  
...  
Keyword(s):  
Complex Traits ◽  
Adult Height ◽  
Normal Approximation ◽  
Classical Model ◽  
Model Complexity ◽  
Test Case ◽  
Genetic Studies ◽  
Quantitative Genetic ◽  
Profound Influence ◽  
Log Normal

AbstractAdult height inspired the first biometrical and quantitative genetic studies and is a test-case trait for understanding heritability. The studies of height led to formulation of the classical polygenic model, that has a profound influence on the way we view and analyse complex traits. An essential part of the classical model is an assumption of additivity of effects and normality of the distribution of the residuals. However, it may be expected that the normal approximation will become insufficient in bigger studies. Here, we demonstrate that when the height of hundreds of thousands of individuals is analysed, the model complexity needs to be increased to include non-additive interactions between sex, environment and genes. Alternatively, the use of log-normal approximation allowed us to still use the additive effects model. These findings are important for future genetic and methodologic studies that make use of adult height as an exemplar trait.

Replication in genetic studies of complex traits

2004 ◽  
Vol 68 (6) ◽  
pp. 646-657 ◽  
Author(s):  
Mikko J. Sillanpää ◽  
Kari Auranen
Keyword(s):  
Complex Traits ◽  
Genetic Studies

scholarly journals Case-control association mapping without cases

2016 ◽  
Author(s):  
Jimmy Z Liu ◽  
Yaniv Erlich ◽  
Joseph K Pickrell
Keyword(s):  
Association Mapping ◽  
Complex Traits ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Large Population ◽  
Case Control ◽  
Genome Wide Association Studies ◽  
The Uk ◽  
Control Association

AbstractThe case-control association study is a powerful method for identifying genetic variants that influence disease risk. However, the collection of cases can be time-consuming and expensive; if a disease occurs late in life or is rapidly lethal, it may be more practical to identify family members of cases. Here, we show that replacing cases with their first-degree relatives enables genome-wide association studies by proxy (GWAX). In randomly-ascertained cohorts, this approach enables previously infeasible studies of diseases that are absent (or nearly absent) in the cohort. As an illustration, we performed GWAX of 12 common diseases in 116,196 individuals from the UK Biobank. By combining these results with published GWAS summary statistics in a meta-analysis, we replicated established risk loci and identified 17 newly associated risk loci: four in Alzheimer’s disease, eight in coronary artery disease, and five in type 2 diabetes. In addition to informing disease biology, our results demonstrate the utility of association mapping using family history of disease as a phenotype to be mapped. We anticipate that this approach will prove useful in future genetic studies of complex traits in large population cohorts.

scholarly journals Shared associations identify causal relationships between gene expression and immune cell phenotypes

2020 ◽  
Author(s):  
Christiane Gasperi ◽  
Sung Chun ◽  
Shamil R. Sunyaev ◽  
Chris Cotsapas
Keyword(s):  
Complex Traits ◽  
Direct Evidence ◽  
Immune Cell ◽  
Genetic Locus ◽  
Causal Variant ◽  
Causal Relationships ◽  
Genetic Studies ◽  
Two Factors ◽  
Gene Regulatory ◽  
Cell Phenotypes

AbstractGenetic mapping studies have identified thousands of associations between common variants and hundreds of human traits. Translating these associations into mechanisms is complicated by two factors: they fall into gene regulatory regions; and they are rarely mapped to one causal variant. One way around these limitations is to find groups of traits that share associations, using this genetic link to infer a biological connection. Here, we assess how many trait associations in the same locus are due to the same genetic variant, and thus shared; and if these shared associations are due to causal relationships between traits. We find that only a subset of traits share associations, with most due to causal relationships rather than pleiotropy. We therefore suggest that simply observing overlapping associations at a genetic locus is insufficient to infer causality; direct evidence of shared associations is required to support mechanistic hypotheses in genetic studies of complex traits.

scholarly journals The Role Of rs1799883 Polymorphism Of The FABP2 Gene In The Pathogenesis Of Nosological Syntropy Of Gallstone Disease And Metabolic Syndrome

2021 ◽  
Vol 03 (06) ◽  
pp. 46-51
Author(s):  
Raximov Anvar Pulatboevich ◽  
◽  
Ismailov O’ktam Safaevich ◽  
Batirov Davronbek Yusupovich ◽  
◽  
...  
Keyword(s):  
Gallstone Disease ◽  
Molecular Genetic ◽  
Case Control ◽  
Control Model ◽  
Molecular Medicine ◽  
Genetic Studies ◽  
Homozygous Genotype ◽  
Risk Of Disease ◽  
Fabp2 Gene

Objective: to study the role of the rs1799883 polymorphism of the FABP2 gene in the pathogenesis of gallstone disease in combination with MS. Material and methods. Molecular genetic studies were carried out in the Department of Molecular Medicine and Cell Technologies of the RSNPMC Hematology. The analysis of the associations of the rs1799883 polymorphisms of the FABP2 gene was carried out using a case-control model. The main group consisted of 118 patients with cholelithiasis in combination with MS living in the Khorezm region. Results: As a result of our research, we identified a significant association of the homozygous genotype for the Thr allele with the development of gallstone disease in combination with MS. The indicator of the ratio of the chances of developing gallstone disease in combination with MS in carriers of this genotype was OR = 2.9 at 95% CI: 1.122- 7.424. The relative risk of disease was RR = 2.5 with 95% CI: 1.11-5.76. Conclusion: Our results allow us to conclude that the homozygous Thr/Thr genotype plays an important role in the formation of gallstone disease and obesity in people of Uzbek nationality.

scholarly journals Incorporation of Heterogeneity in a Case-Control Study Through a Mixture Model

2020 ◽  
Author(s):  
Subrata Paul ◽  
Stephanie A. Santorico
Keyword(s):  
Logistic Regression ◽  
Mixture Model ◽  
Genetic Variants ◽  
Complex Traits ◽  
Genetic Variant ◽  
Case Control Study ◽  
Case Control ◽  
Human Diseases ◽  
Disease Outcome ◽  
Control Study

AbstractMost common human diseases and complex traits are etiologically heterogeneous. Genome-wide Association Studies (GWAS) aim to discover common genetic variants that are associated with complex traits, typically without considering heterogeneity. Heterogeneity, as well as im-precise phenotyping, significantly reduces the power to find genetic variants associated with human diseases and complex traits. Disease subtyping through unsupervised clustering techniques such as latent class analysis can explain some of the heterogeneity; however, subtyping methods do not typically incorporate heterogeneity into the association framework. Here, we use a finite mixture model with logistic regression to incorporate heterogeneity into the association testing framework for a case-control study. In the proposed method, the disease outcome is modeled as a mixture of two binomial distributions. One of the component distributions refers to the subgroup of the population for which the genetic variant is not associated with the disease outcome and another component distribution corresponds to the subgroup for which the genetic variant is associated with the disease outcome. The mixing parameter corresponds to the proportion of the population for which the genetic variant is associated with the disease outcome. A simulation study of a trait with differing levels of prevalence, SNP minor allele frequency, and odds ratio was performed, and effect size estimates compared between the models with and without incorporating heterogeneity. The proposed mixture model yields lower bias of odds ratios while having comparable power compared to classical logistic regression.

scholarly journals Genome-wide methylation data improves dissection of the effect of smoking on body mass index

PLoS Genetics ◽  
2021 ◽  
Vol 17 (9) ◽  
pp. e1009750
Author(s):  
Carmen Amador ◽  
Yanni Zeng ◽  
Michael Barber ◽  
Rosie M. Walker ◽  
Archie Campbell ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Basis ◽  
Environmental Changes ◽  
Total Contribution ◽  
Genetic Studies ◽  
Socioeconomic Changes ◽  
Genome Wide ◽  
A Genome ◽  
Causes Of Disease ◽  
Wide Perspective

Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.

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