Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
Nat Commun. 2024 Apr 22;15(1):3385. doi: 10.1038/s41467-024-47806-3.
There is a long-standing debate about the magnitude of the contribution of gene-environment interactions to phenotypic variations of complex traits owing to the low statistical power and few reported interactions to date. To address this issue, the Gene-Lifestyle Interactions Working Group within the Cohorts for Heart and Aging Research in Genetic Epidemiology Consortium has been spearheading efforts to investigate G × E in large and diverse samples through meta-analysis. Here, we present a powerful new approach to screen for interactions across the genome, an approach that shares substantial similarity to the Mendelian randomization framework. We identify and confirm 5 loci (6 independent signals) interacted with either cigarette smoking or alcohol consumption for serum lipids, and empirically demonstrate that interaction and mediation are the major contributors to genetic effect size heterogeneity across populations. The estimated lower bound of the interaction and environmentally mediated heritability is significant (P < 0.02) for low-density lipoprotein cholesterol and triglycerides in Cross-Population data. Our study improves the understanding of the genetic architecture and environmental contributions to complex traits.
由于统计功效低以及迄今为止报道的相互作用较少，对于基因-环境相互作用对复杂性状表型变异的贡献程度，一直存在着长期的争论。为了解决这个问题，遗传流行病学协作组中的心脏和衰老研究队列中的基因-生活方式相互作用工作组一直在牵头努力，通过荟萃分析在大型和多样化的样本中研究 G×E。在这里，我们提出了一种强大的新方法来筛选全基因组中的相互作用，这种方法与孟德尔随机化框架有很大的相似之处。我们确定并证实了 5 个与血清脂质有关的位点（6 个独立信号）与吸烟或饮酒相互作用，并且经验性地证明，相互作用和中介作用是人群间遗传效应大小异质性的主要贡献者。在跨人群数据中，低密度脂蛋白胆固醇和甘油三酯的交互作用和环境介导的遗传率的下限估计值具有统计学意义（P<0.02）。我们的研究提高了对复杂性状遗传结构和环境贡献的理解。
