학술논문
Post-Genome-Wide Association Study Challenges for Lipid Traits: Describing Age as a Modifier of Gene-Lipid Associations in the Population Architecture Using Genomics and Epidemiology (PAGE) Study.
Document Type
Article
Author
Dumitrescu, Logan; Carty, Cara L.; Franceschini, Nora; Hindorff, Lucia A.; Cole, Shelley A.; Bůžková, Petra; Schumacher, Fredrick R.; Eaton, Charles B.; Goodloe, Robert J.; Duggan, David J.; Haessler, Jeff; Cochran, Barbara; Henderson, Brian E.; Cheng, Iona; Johnson, Karen C.; Carlson, Chris S.; Love, Shelly‐Ann; Brown‐Gentry, Kristin; Nato, Alejandro Q.; Quibrera, Miguel
Source
Subject
*LIPIDS
*POPULATION genetics
*HIGH-density lipoprotein receptors
*LOW density lipoproteins
*CHOLESTEROL
*TRIGLYCERIDES
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Language
ISSN
0003-4800
Abstract
Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), and triglyceride distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age-dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or postmenopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet < 0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet = 1.74E-03, I² = 89.8), with a significant association in older males (P = 1.39E-06) but not younger males (P = 0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes. [ABSTRACT FROM AUTHOR]