Relationship loci (rQTL) exist when the correlation between multiple traits varies by genotype. rQTL often occur due to gene-by-gene (GxG) or gene-by-environmental interactions, making them a powerful tool for detecting GxG. Here we present an empirical analysis of Apolipoprotein E with respect to lipid traits and incident CHD leading to the discovery of loci that interact with APOE to affect these traits. We found that the relationship between Total Cholesterol (TC) and Triglycerides (lnTG) varies by APOE isoform genotype in African (AA) and European-American (EA) populations. The e2 allele is associated with strong correlation between lnTG and TC while the e4 allele leads to little or no correlation. This led to a priori hypotheses that APOE genotypes affect the relationship of TC and/or lnTG with incident CHD. We found that APOE*TC was significant (p=0.016) for AA but not EA while APOE*lnTG was significant for EA (p=0.027) but not AA. In both cases, e2e2 and e2e3 had strong relationships between TC and lnTG with CHD while e2e4 and e4e4 results in little or no relationship between TC and lnTG with CHD. Using ARIC GWAS data, scans for loci that significantly interact with APOE produced four loci for African-Americans (1 CHD, 1 TC, 2 HDL). These interactions contribute to the rQTL pattern. rQTL are a powerful tool to identify loci that modify the relationship between risk factors and disease and substantially increase statistical power for detecting GxG.
[Show abstract][Hide abstract] ABSTRACT: Epistasis has been suggested to underlie part of the missing heritability in genome-wide association studies. In this study, we first report an analysis of gene-gene interactions affecting HDL cholesterol (HDL-C) levels in a candidate gene study of 2,091 individuals with mixed dyslipidemia from a clinical trial. Two additional studies, the Atherosclerosis Risk in Communities study (ARIC; n = 9,713) and the Multi-Ethnic Study of Atherosclerosis (MESA; n = 2,685), were considered for replication. We identified a gene-gene interaction between rs1532085 and rs12980554 (P = 7.1×10-7) in their effect on HDL-C levels, which is significant after Bonferroni correction (Pc = 0.017) for the number of SNP pairs tested. The interaction successfully replicated in the ARIC study (P = 7.0×10-4; Pc = 0.02). Rs1532085, an expression QTL (eQTL) of LIPC, is one of the two SNPs involved in another, well-replicated gene-gene interaction underlying HDL-C levels. To further investigate the role of this eQTL SNP in gene-gene interactions affecting HDL-C, we tested in the ARIC study for interaction between this SNP and any other SNP genome-wide. We found the eQTL to be involved in a few suggestive interactions, one of which significantly replicated in MESA. Importantly, these gene-gene interactions, involving only rs1532085, explain an additional 1.4% variation of HDL-C, on top of the 0.65% explained by rs1532085 alone. LIPC plays a key role in the lipid metabolism pathway and it, and rs1532085 in particular, has been associated with HDL-C and other lipid levels. Collectively, we discovered several novel gene-gene interactions, all involving an eQTL of LIPC, thus suggesting a hub role of LIPC in the gene-gene interaction network that regulates HDL-C levels, which in turn raises the hypothesis that LIPC's contribution is largely via interactions with other lipid metabolism related genes.
PLoS ONE 03/2014; 9(3):e92469. DOI:10.1371/journal.pone.0092469 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background. Dyslipidemia is a major risk factor for cardiovascular disease. Previous studies of lipid heritability have largely focused on white populations assessed after the obesity epidemic. Given secular trends and racial differences in lipid levels, this study explored whether lipid heritability is consistent across time and between races. Methods and Results. African-American and white nuclear families had fasting lipids measured in the 1970s and 22-30 years later. Heritability was estimated and bivariate analyses between visits were conducted by race using variance components analysis. 1454 individuals (age 14.1/ 40.6 for offspring/ parents at baseline; 39.6/ 66.5 at follow-up) in 373 families (286 white, 87 African-American) were included. Lipid trait heritabilities were typically stronger during the 1970s than the 2000s. At baseline, additive genetic variation for LDL was significantly lower in African-Americans than whites (p=0.015). Shared genetic contribution to lipid variability over time was significant in both whites (all p<0.0001) and African-Americans (p≤0.05 for total, LDL and HDL cholesterol). African-American families demonstrated shared environmental contributions to lipid variation over time (all p≤0.05). Conclusions. Lower heritability, lower LDL genetic variance and durable environmental effects across the obesity epidemic in African-American families suggest race-specific approaches are needed to clarify the genetic etiology of lipids.
The Journal of Lipid Research 05/2014; 55(7). DOI:10.1194/jlr.M049932 · 4.42 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Importance
Genetic association studies of psychiatric outcomes often consider interactions with environmental exposures and, in particular, apply tests that jointly consider gene and gene-environment interaction effects for analysis. Using a genome-wide association study (GWAS) of posttraumatic stress disorder (PTSD), we report that heteroscedasticity (defined as variability in outcome that differs by the value of the environmental exposure) can invalidate traditional joint tests of gene and gene-environment interaction.Objectives
To identify the cause of bias in traditional joint tests of gene and gene-environment interaction in a PTSD GWAS and determine whether proposed robust joint tests are insensitive to this problem.Design, Setting, and Participants
The PTSD GWAS data set consisted of 3359 individuals (978 men and 2381 women) from the Grady Trauma Project (GTP), a cohort study from Atlanta, Georgia. The GTP performed genome-wide genotyping of participants and collected environmental exposures using the Childhood Trauma Questionnaire and Trauma Experiences Inventory.Main Outcomes and Measures
We performed joint interaction testing of the Beck Depression Inventory and modified PTSD Symptom Scale in the GTP GWAS. We assessed systematic bias in our interaction analyses using quantile-quantile plots and genome-wide inflation factors.Results
Application of the traditional joint interaction test to the GTP GWAS yielded systematic inflation across different outcomes and environmental exposures (inflation-factor estimates ranging from 1.07 to 1.21), whereas application of the robust joint test to the same data set yielded no such inflation (inflation-factor estimates ranging from 1.01 to 1.02). Simulated data further revealed that the robust joint test is valid in different heteroscedasticity models, whereas the traditional joint test is invalid. The robust joint test also has power similar to the traditional joint test when heteroscedasticity is not an issue.Conclusions and Relevance
We believe the robust joint test should be used in candidate-gene studies and GWASs of psychiatric outcomes that consider environmental interactions. To make the procedure useful for applied investigators, we created a software tool that can be called from the popular PLINK package for analysis.
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