A Multi-Ancestry Study of Gene-Lifestyle Interactions and Multi-Omics in Cardiometabolic Traits

项目摘要/摘要 心脏代谢性疾病和危险因素，包括高血压、血脂异常、肥胖和2型 糖尿病是一种主要的公共卫生负担，对不同种族(非欧洲人)的影响不成比例 祖先)种群。心脏代谢特征受遗传和环境(生活方式)的影响 各种因素。因此，了解这些因素之间的相互作用(GxE)有助于深入了解 采取干预、预防和治疗战略，减轻疾病负担。许多是全基因组的 关联研究已经在许多复杂性状上取得了重要的遗传发现。 基于“遗传主效应”的方法。然而，全基因组相互作用研究(Gwi)仍在进行中。 有限的。因此，本研究的目的是确定与心脏代谢相关的新的遗传基因座 通过大样本中的GWI，研究心脏代谢性状基因与生活方式的相互作用， 并通过利用现有的“Omics”数据，如 作为DNA甲基化、基因表达和代谢物。通过研究基因组和生活方式对 通过不同人群和性别之间的互动产生的健康结果，我们的建议 反映了精准医学倡议(PMI)的优先事项，其重点是 生活方式/环境和遗传学，重点是不同的人群。 我们建议评估不同人群(欧洲人、非洲人、西班牙人、 和亚洲人)。我们在血压、血脂和二分法生活方式因素(吸烟、 饮酒、体力活动、教育程度、心理社会因素和睡眠) 统计能力有限。因此，我们建议将GWI的功率提高到原来的10倍 样本规模和扩大我们的重点，以包括其他心脏代谢特征(肥胖和糖尿病特征)， 量化的生活方式暴露(例如，每天吸烟)，以及总体生活方式风险得分 心脏代谢健康的生活方式危险因素；评估已识别的相互作用对临床终点的影响 (如冠心病)；评估已识别的相互作用的可药性；以及表征相互作用 使用多个组学数据。我们的建议包括我们最近的发现研究(N~130,000)，我们最近的 复制研究(N~252,000)，并增加了几项新的、规模大得多的研究，包括 百万退伍军人计划(N~234,000)、英国生物库(N~478,000)、日本生物库(N~160,000)和 对拉丁裔(N~13,000人)等的研究。总体样本包括91.2万名欧洲人，9.1万名非洲人， 33,000名西班牙裔和231,000名亚裔个人是迄今为止最重要的努力 调查总样本量约为126.7万人的相互作用。这些发现可以带来新的 诊断和治疗工具，有助于在心脏代谢性疾病的管理中进行精确护理， 并为PMI提供见解，最终目标是加强临床实践。

PROJECT SUMMAR/ABSTRACT Cardiometabolic diseases and risk factors, including hypertension, dyslipidemia, adiposity, and type 2 diabetes, represent a major public health burden that disproportionately affects diverse (non-European ancestry) populations. Cardiometabolic traits are influenced by both genetic and environmental (lifestyle) factors. Therefore, understanding interactions (GxE) between these factors could provide insights into intervention, prevention and therapeutic strategies to reduce the burden of disease. Many genome-wide association studies (GWAS) have made important genetic discoveries for many complex traits through approaches based on “genetic main effects”. However, genome-wide interaction studies (GWIS) are still limited. The objective of this study is therefore to identify novel genetic loci associated with cardiometabolic traits through GWIS in large samples, to investigate gene-lifestyle interactions in the cardiometabolic trait loci, and to characterize the molecular effects underlying the interactions by leveraging existing “Omics” data such as DNA methylation, gene expression, and metabolites. By investigating genomic and lifestyle contributors to health outcomes through their interactions across diverse populations and between sexes, our proposal reflects the priorities of the Precision Medicine Initiative (PMI) whose focus is the interplay between lifestyle/environment and genetics, with an emphasis on diverse populations. We propose to evaluate gene-lifestyle interactions across diverse populations (European, African, Hispanic, and Asian). Our recent progress with blood pressure, lipids, and dichotomized lifestyle factors (smoking, alcohol consumption, physical activity, educational attainment, psychosocial factors, and sleep) encountered limited statistical power. Therefore, we propose to vastly increase the power for GWIS with an ~10-fold larger sample size and expand our focus to include other cardiometabolic traits (adiposity and diabetes traits), quantitative lifestyle exposures (e.g., cigarettes per day), and aggregate Lifestyle Risk Scores as an overall lifestyle risk factor for cardiometabolic health; evaluate the impact of identified interactions on clinical endpoints (like coronary heart disease); assess the druggability of identified interactions; and characterize interactions using multiple omics data. Our proposal includes our recent discovery studies (N~130,000), our recent replication studies (N~252,000), and the addition of several new, substantially larger studies including the Million Veteran Program (N~234,000), the UK Biobank (N~478,000), the Biobank Japan (N~160,000), and the Study of Latinos (N~13,000), among others. The overall sample, including 912,000 European, 91,000 African, 33,000 Hispanic, and 231,000 Asian ancestry individuals, represents the most significant effort to date to investigate interactions with an aggregate sample size of about 1.267 million. Findings can lead to new diagnostic and therapeutic tools, contribute to precision care in the management of cardiometabolic disorders, and provide insights for the PMI with the ultimate goal of enhancing clinical practice.