Lieb Wolfgang, Vasan Ramachandran S
Institute of Epidemiology, Kiel University, Kiel, Germany.
Framingham Heart Study (FHS), Framingham, MA, United States.
Front Cardiovasc Med. 2018 Jun 7;5:57. doi: 10.3389/fcvm.2018.00057. eCollection 2018.
Longitudinal, well phenotyped, population-based cohort studies offer unique research opportunities in the context of genome-wide association studies (GWAS), including GWAS for new-onset (incident) cardiovascular disease (CVD) events, the assessment of gene x lifestyle interactions, and evaluating the incremental predictive utility of genetic information in apparently healthy individuals. Furthermore, comprehensively phenotyped community-dwelling samples have contributed to GWAS of numerous traits that reflect normal organ function (e.g., cardiac structure and systolic and diastolic function) and for many traits along the CVD continuum (e.g., risk factors, circulating biomarkers, and subclinical disease traits). These GWAS have heretofore identified many genetic loci implicated in normal organ function and different stages of the CVD continuum. Finally, population-based cohort studies have made important contributions to Mendelian Randomization analyses, a statistical approach that uses genetic information to assess observed associations between cardiovascular traits and clinical CVD outcomes for potential causality.
纵向、具有良好表型特征且基于人群的队列研究在全基因组关联研究(GWAS)的背景下提供了独特的研究机会,包括针对新发(偶发)心血管疾病(CVD)事件的GWAS、基因与生活方式相互作用的评估,以及评估遗传信息在看似健康个体中的增量预测效用。此外,具有全面表型特征的社区居住样本有助于对众多反映正常器官功能的性状(如心脏结构以及收缩和舒张功能)以及CVD连续体中的许多性状(如危险因素、循环生物标志物和亚临床疾病性状)进行GWAS。迄今为止,这些GWAS已经确定了许多与正常器官功能以及CVD连续体不同阶段相关的基因位点。最后,基于人群的队列研究对孟德尔随机化分析做出了重要贡献,孟德尔随机化分析是一种利用遗传信息来评估心血管性状与临床CVD结局之间观察到的关联以判断潜在因果关系的统计方法。