GENE-ENVIRONMENT INTERACTIONS IN THE LONGITUDINAL FRAMINGHAM HEART STUDY

描述(由申请人提供)：心血管疾病(CVD)和代谢疾病(METS)构成了主要的公共卫生负担，因此，了解这些特征的遗传基础非常重要。最近的全基因组联合研究取得了很好的进展，但还不够。例如，两个大型财团(CHARE和ICBP)确定了13个血压(BP)基因座，它们总共解释了不到2%的BP方差(大多数遗传性仍然“缺失”)。对单一遗传标记的主效应的近乎排他性的依赖一直是识别更多这些疾病特征的基因的主要障碍之一。在这种背景下，众所周知，基因-环境相互作用(GEI)方法可以极大地提高基因发现(初步研究)的统计能力。此外，纵向数据的分析比横截面数据的分析要强大得多。将GEI和纵向数据结合起来，应该会产生更大的影响力。尽管人们知道GEI和纵向数据都极大地提高了基因发现的统计能力，但这种知识还没有得到利用，因此错过了从大量现有的Gwas数据中发现(希望有许多)新的疾病位点的机会。因此，我们建议利用现有的大型纵向弗雷明翰心脏研究(FHS)数据，使用我们的GEI方法，包括基因年龄、基因性别、基因肥胖和基因生活方式相互作用。这项研究将利用FHS的数据，对总共9,168名发现受试者使用GWAS数据，其中包括7次“后代队列”、相应的7次“原始队列”和“第3代队列”(G3)。数据包括Gwas数据、心血管和代谢表型，以及关于2至3代家庭的体力活动、饮酒、吸烟和社会经济状况(SES)的生活方式数据。所有重要的结果都将在涉及22,824名复制对象的四项外部研究中重复。该项目的完成有可能发现(希望有许多)新的疾病位点，这可以有效地激励其他人使用GEI方法重新分析现有的大量Gwas数据，最终导致新的诊断工具和治疗干预措施。 公共卫生相关性：拟议研究的主要目标是使用基因-环境相互作用(GEI)方法利用现有的大型全基因组关联研究(GWAS)数据，发现(希望有许多)更多心血管和代谢性疾病特征的遗传位点。这项研究将在现有的大型纵向弗雷明翰心脏研究中进行，共有9,168名受试者和4项外部复制研究，受试者为22,824名。

DESCRIPTION (provided by applicant): Cardiovascular (CVD) and metabolic (MetS) diseases constitute a major public-health burden and, therefore, understanding the genetic basis of these traits is very important. The recent Genome-Wide Association Studies (GWAS) made good progress, but not enough. For example, two large consortia (CHARGE and ICBP) identified 13 loci for blood pressure (BP) which collectively explain less than 2% of BP variance (with most of the heritability still "missing"). The near-exclusive reliance on main effects of single genetic markers has been one of the major barriers to identifying more of the genes underlying these disease traits. Against this background, Gene-Environment Interaction (GEI) methods are known to vastly increase the statistical power for gene discovery (preliminary studies). Also, analysis of longitudinal data can be much more powerful than that of cross-sectional data. Combining GEI and longitudinal data should yield even more power. Despite the knowledge that GEI and longitudinal data both vastly improve the statistical power for gene discovery, this knowledge has not been leveraged yet, thus missing an opportunity to find (hopefully many) novel disease loci from large volumes of existing GWAS data. Thusly motivated, we propose to harness the large existing longitudinal Framingham Heart Study (FHS) data using our GEI methods including gene-age, gene-sex, gene-obesity, and gene-lifestyle interactions. This study will use FHS data on the 7 visits of the 'Offspring Cohort', the corresponding 7 visits of the 'Original Cohort', and the 'Generation 3 Cohort' (G3), to a total of 9,168 discovery subjects with GWAS data. Data include GWAS data, cardiovascular and metabolic phenotypes, and lifestyle data on physical activity, alcohol consumption, smoking, and socio-economic status (SES) in 2 to 3 generation families. All significant results will be replicated in four external studies involving 22,824 replication subjects. Completion of this project has the potential to discover (hopefully many) novel disease loci, which could effectively motivate others to re-analyze large volumes of existing GWAS data using GEI methods, ultimately leading to new diagnostic tools and therapeutic interventions. PUBLIC HEALTH RELEVANCE: The primary goal of the proposed research is to exploit large existing genome-wide association study (GWAS) data using gene-environment interaction (GEI) methods to discover (hopefully many) more genetic loci for cardiovascular and metabolic disease traits. The investigation will be carried out in a large existing longitudinal Framingham Heart Study with 9,168 subjects and 4 external replication studies with 22,824 subjects.