Genetic underpinnings of the heterogeneous impact of obesity on lipid levels and cardiovascular disease

作者：DaeEun Kim, Heather M. Highland, Roelof A. J. Smit, Micah R. Hysong, Victoria L. Buchanan, Kristin L. Young, Chi Zhao, Cassandra N. Spracklen, Tuomas O. Kilpeläinen, Boya Guo, Burcu F. Darst, Yanwei Cai, Zhe Wang, Jessica I. Lundin, Sonja I. Berndt, JoAnn E. Manson, Eirini Marouli, Leslie A. Lange, E.M. Lange, Myriam Fornage, Christopher R. Gignoux, Christopher A. Haiman, Stephen S. Rich, Steven Buyske, Ruth J. F. Loos, Charles Kooperberg, Ulrike Peters, Christy L. Avery, Penny Gordon-Larsen, M. Graff, Laura M. Raffield, Kari E. North · 发表于：Genome Medicine · 年份：2025 · DOI：10.1186/s13073-025-01522-9 · 被引用次数：5 · 研究领域：Genetic Associations and Epidemiology、Genetic Mapping and Diversity in Plants and Animals、Renin-Angiotensin System Studies

Abstract Background Obesity is thought to increase cardiovascular disease (CVD) risk partly through dyslipidemia. Yet, obesity’s effects on dyslipidemia are not uniform. Understanding the shared genetic basis between obesity and lipid traits can provide insight into this heterogeneity and its implications for CVD risk. Methods We examined local genetic correlations between three lipid measures [high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), and triglycerides (TG)] and body mass index (BMI) using genome-wide association study summary statistics from European ancestry UK Biobank participants. We identified genomic loci with opposing genetic effects on obesity and dyslipidemia risk (protective BMI-lipid loci) and those with concordant directions for both obesity and dyslipidemia risk (adverse BMI-lipid loci). Gene-based association analyses were used to prioritize potential causal genes. We then constructed polygenic risk scores for BMI (PRS BMI ) based on protective and adverse loci and assessed their associations with BMI, lipid levels, CVD, and related traits in the diverse Population Architecture using Genomics and Epidemiology (PAGE) study. PheWAS was performed in the All of Us cohort. Mendelian randomization (MR) was conducted to assess the causal impact of protective/adverse loci on cardiometabolic outcomes. Finally, we investigated the associations with fat distribution traits using MRI-based fat measures in the UK Biobank. Results...