Abstract 4346738: Genome-wide vQTL Analysis of Blood Lipid Traits

Background: Blood lipid levels are among the leading causal risk factors for cardiovascular disease. While genome-wide association studies (GWAS) have identified numerous loci associated with mean lipid levels, genetic contributions to blood lipid variability remain underexplored. To address this, we conducted a multi-population genome-wide variance quantitative trait loci (vQTL) analysis to identify single nucleotide polymorphisms (SNPs) influencing the variability of blood lipid traits. Methods: vQTL analyses were performed on five circulating lipid measures: high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglycerides (TG), and lipoprotein(a) (Lp(a)) in the Penn Medicine Biobank (PMBB). Analyses were implemented using QUAIL, which transforms the phenotype into a quantile integrated rank score and employs quantile regression to assess genetic effects on trait variance. Analyses were performed for each population, adjusting for age, sex, and genetic principal components. Genome-wide significance was set at p < 5e-8. Results: vQTL analysis identified 306 genome-wide significant loci associated with lipid variability. Nearby genes identified included CETP, CELSR2, APOA5, LPL, LPA, and PPM1H. Several loci overlapped with known GWAS loci for lipid levels, while others were novel, suggesting unexplored genetic mechanisms regulating variance. Conclusions: These findings provide new insights into the genetic regulation of lipid variability, which may improve risk stratification for cardiovascular disease and inform precision medicine approaches. Future analyses will replicate this work in the other cohorts (MVP, AoU, and UKB) to validate findings and further elucidate the genetic architecture of lipid variability.