Westerman Kenneth E, Kilpeläinen Tuomas O, Sevilla-Gonzalez Magdalena, Connelly Margery A, Wood Alexis C, Tsai Michael Y, Taylor Kent D, Rich Stephen S, Rotter Jerome I, Otvos James D, Bentley Amy R, Mora Samia, Aschard Hugues, Rao D C, Gu Charles, Chasman Daniel I, Manning Alisa K
Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA.
Genet Epidemiol. 2025 Jan;49(1):e22607. doi: 10.1002/gepi.22607.
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 = 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 = 1.0 × 10) 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 = 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.
大规模基因 - 环境相互作用（GxE）发现工作通常为了数据协调和统计功效而涉及分析上的妥协。细化暴露因素、协变量、结局和人群亚组可能有助于实现常常难以捉摸的重复研究，并评估潜在的临床效用。在此，我们使用了额外的数据集、一组扩展的统计模型，并通过基于核磁共振（NMR）的脂蛋白亚组分对脂蛋白代谢进行探究，以细化先前发现的一种GxE，该GxE改变了身体活动（PA）与高密度脂蛋白胆固醇（HDL - C）之间的关系。我们在女性基因组健康研究（WGHS；N = 23,294；原始荟萃分析中最强的队列特异性信号）、英国生物银行（UKB；N = 281,380）和动脉粥样硬化多族裔研究（MESA；N = 4587）中探索了这种GxE，使用自我报告的PA（代谢当量 - 分钟/周）和rs295849位点（最接近的基因：LHX1）的基因型。如最初报道的那样，WGHS中rs295849的次要等位基因携带者在PA与HDL - C之间具有更强的正相关（p = 0.002）。当测试可用的NMR代谢物以细化HDL - C结局时，我们发现对中等大小HDL颗粒浓度（M - HDL - P；p = 1.0×10）的相互作用效应比对HDL - C更强。荟萃回归显示，在原始荟萃分析中女性比例更高的队列中，相互作用效应系统性地更大（p = 0.018）。在UKB中，GxE效应在女性中更强，并且以M - HDL - P作为结局。在MESA中，HDL - C的主要相互作用显示出名义显著性（p = 0.013），但没有明显的性别差异，并且对大HDL - P的影响程度更大。我们的工作为已知的基因 - PA相互作用提供了更多见解，同时说明了表型和模型细化对于理解和重复GxEs的重要性。
