Refinement of a published gene-physical activity interaction impacting HDL-cholesterol: Role of sex and lipoprotein subfractions

Authors: WESTERMAN, KENNETH - Massachusetts General Hospital; KILPELÄINEN, TUOMAS - University Of Copenhagen; SEVILLA-GONZALEZ, MAGDALENA - Massachusetts General Hospital; CONNELLY, MARGERY - Non ARS Employee; WOOD, ALEXIS - Children'S Nutrition Research Center (CNRC); TSAI, MICHAEL - University Of Minnesota; TAYLOR, KENT - Harbor-Ucla Medical Center; RICH, STEPHEN - University Of Virginia; ROTTER, JEROME - Harbor-Ucla Medical Center; OTVOS, JAMES - National Heart, Lung And Blood Institute(NHLBI, NIH); BENTLEY, AMY - National Human Genome Research Institute; MORA, SAMIA - Brigham & Women'S Hospital; ASCHARD, HUGUES - Institut Pasteur - France; RAO, D - Washington University; GU, CHARLES - Washington University; CHASMAN, DANIEL - Brigham & Women'S Hospital; MANNING, ALISA - Massachusetts General Hospital

Submitted to: Genetic Epidemiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/17/2024
Publication Date: 1/7/2025
Citation: Westerman, K.E., Kilpeläinen, T.O., Sevilla-Gonzalez, M., Connelly, M.A., Wood, A.C., Tsai, M.Y., Taylor, K.D., Rich, S.S., Rotter, J.I., Otvos, J.D., Bentley, A.R., Mora, S., Aschard, H., Rao, D.C., Gu, C., Chasman, D.I., Manning, A.K. 2025. Refinement of a published gene-physical activity interaction impacting HDL-cholesterol: Role of sex and lipoprotein subfractions. Genetic Epidemiology. 49(1). Article e22607. https://doi.org/10.1002/gepi.22607.
DOI: https://doi.org/10.1002/gepi.22607

Interpretive Summary: This study explores how a specific genetic variation near the LHX1 gene interacts with physical activity to influence HDL ("good") cholesterol, a key factor in cardiovascular health. Using data from three large cohorts, it was confirmed that the rarer forms of this gene experience a stronger boost in HDL cholesterol from physical activity. These differences were more prominent in women. Overall, the research emphasizes the health benefits of physical activity for all, and highlights the importance of better understanding gene-environment interactions, which can eventually improve precision medicine strategies.

Technical Abstract: Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C). We explored this GxE in the Women's Genome Health Study (WGHS; N=23,294; the strongest cohort-specific signal in the original meta-analysis), the UK Biobank (UKB; N=281,380), and the Multi-Ethnic Study of Atherosclerosis (MESA; N=4587), using self-reported PA (MET-min/wk) and genotypes at rs295849 (nearest gene: LHX1). As originally reported, minor allele carriers of rs295849 in WGHS had a stronger positive association between PA and HDL-C (p int=0.002). When testing available NMR metabolites to refine the HDL-C outcome, we found a stronger interaction effect on medium-sized HDL particle concentrations (M-HDL-P; p int=1.0×10**-4) than HDL-C. Meta-regression revealed a systematically larger interaction effect in cohorts from the original meta-analysis with a greater fraction of women (p=0.018). In the UKB, GxE effects were stronger in women and using M-HDL-P as the outcome. In MESA, the primary interaction for HDL-C showed nominal significance (p int=0.013), but without clear sex differences and with a greater magnitude for large HDL-P. Our work provides additional insights into a known gene-PA interaction while illustrating the importance of phenotype and model refinement toward understanding and replicating GxEs.