Properties of global ‐ and local‐ancestry adjustments in genetic association tests in admixed populations
Abstract
Population substructure can lead to confounding in tests for genetic association, and failure to adjust properly can result in spurious findings. Here we address this issue of confounding by considering the impact of global ancestry (average ancestry across the genome) and local ancestry (ancestry at a specific chromosomal location) on regression parameters and relative power in ancestry‐adjusted and ‐unadjusted models. We examine theoretical expectations under different scenarios for population substructure; applying different regression models, verifying and generalizing using simulations, and exploring the ...
Source: Genetic Epidemiology - December 1, 2017 Category: Epidemiology Authors: Eden R. Martin, Ilker Tunc, Zhi Liu, Susan H. Slifer, Ashley H. Beecham, Gary W. Beecham Tags: RESEARCH ARTICLE Source Type: research
Kernel machine methods for integrative analysis of genome ‐wide methylation and genotyping studies
ABSTRACT
Many large GWAS consortia are expanding to simultaneously examine the joint role of DNA methylation in addition to genotype in the same subjects. However, integrating information from both data types is challenging. In this paper, we propose a composite kernel machine regression model to test the joint epigenetic and genetic effect. Our approach works at the gene level, which allows for a common unit of analysis across different data types. The model compares the pairwise similarities in the phenotype to the pairwise similarities in the genotype and methylation values; and high correspondence is suggestive of asso...
Source: Genetic Epidemiology - December 1, 2017 Category: Epidemiology Authors: Ni Zhao, Xiang Zhan, Yen ‐Tsung Huang, Lynn M Almli, Alicia Smith, Michael P. Epstein, Karen Conneely, Michael C. Wu Tags: RESEARCH ARTICLE Source Type: research
On the substructure controls in rare variant analysis: Principal components or variance components?
Abstract
Recent studies showed that population substructure (PS) can have more complex impact on rare variant tests and that similarity‐based collapsing tests (e.g., SKAT) may suffer more severely by PS than burden‐based tests. In this work, we evaluate the performance of SKAT coupling with principal components (PC) or variance components (VC) based PS correction methods. We consider confounding effects caused by PS including stratified populations, admixed populations, and spatially distributed nongenetic risk; we investigate which types of variants (e.g., common, less frequent, rare, or all variants) should be used t...
Source: Genetic Epidemiology - December 1, 2017 Category: Epidemiology Authors: Yiwen Luo, Arnab Maity, Michael C. Wu, Chris Smith, Qing Duan, Yun Li, Jung ‐Ying Tzeng Tags: RESEARCH ARTICLE Source Type: research
Integrating genome ‐wide association study summaries and element‐gene interaction datasets identified multiple associations between elements and complex diseases
In this study, we applied gene set enrichment analysis (GSEA) approach to detect the associations between elements and complex diseases/traits though integrating element‐gene interaction datasets and genome‐wide association study (GWAS) data of complex diseases/traits. To illustrate the performance of GSEA, the element‐gene interaction datasets of 24 elements were extracted from the comparative toxicogenomics database (CTD). GWAS summary datasets of 24 complex diseases or traits were downloaded from the dbGaP or GEFOS websites. We observed significant associations between 7 elements and 13 complex diseases or traits ...
Source: Genetic Epidemiology - December 1, 2017 Category: Epidemiology Authors: Awen He, Wenyu Wang, N. Tejo Prakash, Alexey A. Tinkov, Anatoly V. Skaln, Yan Wen, Jingcan Hao, Xiong Guo, Feng Zhang Tags: RESEARCH ARTICLE Source Type: research
Two ‐phase designs for joint quantitative‐trait‐dependent and genotype‐dependent sampling in post‐GWAS regional sequencing
ABSTRACT
We evaluate two‐phase designs to follow‐up findings from genome‐wide association study (GWAS) when the cost of regional sequencing in the entire cohort is prohibitive. We develop novel expectation‐maximization‐based inference under a semiparametric maximum likelihood formulation tailored for post‐GWAS inference. A GWAS‐SNP (where SNP is single nucleotide polymorphism) serves as a surrogate covariate in inferring association between a sequence variant and a normally distributed quantitative trait (QT). We assess test validity and quantify efficiency and power of joint QT‐SNP‐dependent sampling and...
Source: Genetic Epidemiology - December 1, 2017 Category: Epidemiology Authors: Osvaldo Espin ‐Garcia, Radu V. Craiu, Shelley B. Bull Tags: RESEARCH ARTICLE Source Type: research
A robust and powerful two ‐step testing procedure for local ancestry adjusted allelic association analysis in admixed populations
ABSTRACT
Genetic association studies in admixed populations allow us to gain deeper understanding of the genetic architecture of human diseases and traits. However, population stratification, complicated linkage disequilibrium (LD) patterns, and the complex interplay of allelic and ancestry effects on phenotypic traits pose challenges in such analyses. These issues may lead to detecting spurious associations and/or result in reduced statistical power. Fortunately, if handled appropriately, these same challenges provide unique opportunities for gene mapping. To address these challenges and to take these opportunities, we pr...
Source: Genetic Epidemiology - December 1, 2017 Category: Epidemiology Authors: Qing Duan, Zheng Xu, Laura M. Raffield, Suhua Chang, Di Wu, Ethan M. Lange, Alex P. Reiner, Yun Li Tags: RESEARCH ARTICLE Source Type: research
Estimating the number of potential family members eligible for BRCA1 and BRCA2 mutation testing in a “Traceback” approach
ABSTRACT
U.S. guidelines recommend BRCA1/2 mutation testing for women diagnosed with high‐grade ovarian cancer (HGOC) to increase recognition of carriers, but most remain unidentified and at risk. Accordingly, an approach termed “Traceback” has been proposed in which probands are retrospectively identified by testing archived pathology specimens, and family members are traced to provide genetic counseling and testing. We used population‐based data to estimate the number of family members who might be contacted through such a program. We used incidence data from the Surveillance, Epidemiology, and End Results (SEER)...
Source: Genetic Epidemiology - November 30, 2017 Category: Epidemiology Authors: Haley A. Moss, Goli Samimi, Laura J. Havrilesky, Mark E. Sherman, Evan R. Myers Tags: RESEARCH ARTICLE Source Type: research
Gene ‐based genetic association test with adaptive optimal weights
ABSTRACT
It is well known that using proper weights for genetic variants is crucial in enhancing the power of gene‐ or pathway‐based association tests. To increase the power, we propose a general approach that adaptively selects weights among a class of weight families and apply it to the popular sequencing kernel association test. Through comprehensive simulation studies, we demonstrate that the proposed method can substantially increase power under some conditions. Applications to real data are also presented. This general approach can be extended to all current set‐based rare variant association tests whose perfor...
Source: Genetic Epidemiology - November 27, 2017 Category: Epidemiology Authors: Zhongxue Chen, Yan Lu, Tong Lin, Qingzhong Liu, Kai Wang Tags: RESEARCH ARTICLE Source Type: research
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Genetic Epidemiology,Volume 42, Issue 2, Page 146-155, March 2018. (Source: Genetic Epidemiology)
Source: Genetic Epidemiology - November 26, 2017 Category: Epidemiology Source Type: research
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Genetic Epidemiology,Volume 42, Issue 2, Page 130-133, March 2018. (Source: Genetic Epidemiology)
Source: Genetic Epidemiology - November 26, 2017 Category: Epidemiology Source Type: research
A unified partial likelihood approach for X ‐chromosome association on time‐to‐event outcomes
Abstract
The expression of X‐chromosome undergoes three possible biological processes: X‐chromosome inactivation (XCI), escape of the X‐chromosome inactivation (XCI‐E), and skewed X‐chromosome inactivation (XCI‐S). Although these expressions are included in various predesigned genetic variation chip platforms, the X‐chromosome has generally been excluded from the majority of genome‐wide association studies analyses; this is most likely due to the lack of a standardized method in handling X‐chromosomal genotype data. To analyze the X‐linked genetic association for time‐to‐event outcomes with the actu...
Source: Genetic Epidemiology - November 26, 2017 Category: Epidemiology Authors: Wei Xu, Meiling Hao Tags: RESEARCH ARTICLE Source Type: research
Multifactorial disease risk calculator: Risk prediction for multifactorial disease pedigrees
ABSTRACT
Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user‐friendly interface, extending a reported methodology based on a liability‐threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves...
Source: Genetic Epidemiology - November 26, 2017 Category: Epidemiology Authors: Desmond D Campbell, Yiming Li, Pak C Sham Tags: BRIEF REPORT Source Type: research
Using imputed genotype data in the joint score tests for genetic association and gene –environment interactions in case‐control studies
ABSTRACT
Genome‐wide association studies (GWAS) are now routinely imputed for untyped single nucleotide polymorphisms (SNPs) based on various powerful statistical algorithms for imputation trained on reference datasets. The use of predicted allele counts for imputed SNPs as the dosage variable is known to produce valid score test for genetic association. In this paper, we investigate how to best handle imputed SNPs in various modern complex tests for genetic associations incorporating gene–environment interactions. We focus on case‐control association studies where inference for an underlying logistic regression mode...
Source: Genetic Epidemiology - November 26, 2017 Category: Epidemiology Authors: Minsun Song, William Wheeler, Neil E. Caporaso, Maria Teresa Landi, Nilanjan Chatterjee Tags: RESEARCH ARTICLE Source Type: research
Predictive accuracy of combined genetic and environmental risk scores
ABSTRACT
The substantial heritability of most complex diseases suggests that genetic data could provide useful risk prediction. To date the performance of genetic risk scores has fallen short of the potential implied by heritability, but this can be explained by insufficient sample sizes for estimating highly polygenic models. When risk predictors already exist based on environment or lifestyle, two key questions are to what extent can they be improved by adding genetic information, and what is the ultimate potential of combined genetic and environmental risk scores? Here, we extend previous work on the predictive accuracy...
Source: Genetic Epidemiology - November 26, 2017 Category: Epidemiology Authors: Frank Dudbridge, Nora Pashayan, Jian Yang Tags: RESEARCH ARTICLE Source Type: research
Family ‐based tests for associating haplotypes with general phenotype data
ABSTRACT
For family‐based association studies, Horvath et al. proposed an algorithm for the association analysis between haplotypes and arbitrary phenotypes when the phase of the haplotypes is unknown, that is, genotype data is given. Their approach to haplotype analysis maintains the original features of the TDT/FBAT‐approach, that is, complete robustness against genetic confounding and misspecification of the phenotype. The algorithm has been implemented in the FBAT and PBAT software package and has been used in numerous substantive manuscripts. Here, we propose a simplification of the original algorithm that mainta...
Source: Genetic Epidemiology - November 21, 2017 Category: Epidemiology Authors: Julian Hecker, Xin Xu, F. William Townes, Heide Loehlein Fier, Chris Corcoran, Nan Laird, Christoph Lange Tags: BRIEF COMMUNICATION Source Type: research
