Title | APOE modulates the correlation between triglycerides, cholesterol, and CHD through pleiotropy, and gene-by-gene interactions. |
Publication Type | Journal Article |
Year of Publication | 2013 |
Authors | Maxwell TJ, Ballantyne CM, Cheverud JM, Guild CS, Ndumele CE |
Secondary Authors | Boerwinkle E |
Journal | Genetics |
Volume | 195 |
Issue | 4 |
Pagination | 1397-405 |
Date Published | 2013 Dec |
ISSN | 1943-2631 |
Keywords | African Americans, Alleles, Apolipoproteins E, Cholesterol, Coronary Disease, Epistasis, Genetic, European Continental Ancestry Group, Female, Genetic Pleiotropy, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Triglycerides |
Abstract | Relationship loci (rQTL) exist when the correlation between multiple traits varies by genotype. rQTL often occur due to gene-by-gene (G × G) or gene-by-environmental interactions, making them a powerful tool for detecting G × G. Here we present an empirical analysis of apolipoprotein E (APOE) 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 (ln TG) varies by APOE isoform genotype in African-American (AA) and European-American (EA) populations. The e2 allele is associated with strong correlation between ln TG 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 ln TG with incident CHD. We found that APOE*TC was significant (P = 0.016) for AA but not EA while APOE*ln TG was significant for EA (P = 0.027) but not AA. In both cases, e2e2 and e2e3 had strong relationships between TC and ln TG with CHD while e2e4 and e4e4 results in little or no relationship between TC and ln TG with CHD. Using ARIC GWAS data, scans for loci that significantly interact with APOE produced four loci for African Americans (one CHD, one TC, and two 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 G × G. |
DOI | 10.1534/genetics.113.157719 |
Alternate Journal | Genetics |
PubMed ID | 24097412 |
PubMed Central ID | PMC3832281 |
Grant List | HHSN268201100012C / HL / NHLBI NIH HHS / United States HHSN268201100009I / HL / NHLBI NIH HHS / United States HHSN268201100010C / HL / NHLBI NIH HHS / United States UL1 RR025005 / RR / NCRR NIH HHS / United States HHSN268201100008C / HL / NHLBI NIH HHS / United States HHSN268201100005G / HL / NHLBI NIH HHS / United States HHSN268201100008I / HL / NHLBI NIH HHS / United States R01 HL059367 / HL / NHLBI NIH HHS / United States HHSN268201100007C / HL / NHLBI NIH HHS / United States HHSN268201100011I / HL / NHLBI NIH HHS / United States HHSN268201100011C / HL / NHLBI NIH HHS / United States R01 HL086694 / HL / NHLBI NIH HHS / United States U01 HG004402 / HG / NHGRI NIH HHS / United States HL105502 / HL / NHLBI NIH HHS / United States HHSN268201100006C / HL / NHLBI NIH HHS / United States R01 HL105502 / HL / NHLBI NIH HHS / United States HHSN268201100005I / HL / NHLBI NIH HHS / United States HHSN268201100009C / HL / NHLBI NIH HHS / United States HHSN268201100005C / HL / NHLBI NIH HHS / United States HHSN268201100007I / HL / NHLBI NIH HHS / United States R01 HL087641 / HL / NHLBI NIH HHS / United States |