Genetics of Cardiometabolic Diseases in the VA Population

 描述(由申请人提供)： 肥胖、2型糖尿病(T2 DM)和血脂异常是促进冠状动脉(CAD)和外周动脉疾病(PAD)发展的代谢紊乱。总的来说，这些心脏代谢状况是退伍军人患病和死亡的主要原因。尽管了解了相关的根本因素，但与这些情况相关的临床并发症风险变化的很大一部分仍未得到解释。退伍军人百万计划(MVP)将退伍军人电子健康记录(EHR)的信息与从血液测量的生物标记物数据联系起来，为进一步探索心脏代谢性疾病的遗传基础提供了无与伦比的机会。我们建议使用来自与EHR相关的MVP的前200,000名参与者的全基因组基因分型数据，以揭示基因变异和心脏代谢性疾病风险之间的新关联。为了进行这项研究，我们组建了一支在基于VA的临床研究和群体遗传学方面具有丰富经验的研究团队。我们团队的许多成员不仅参与了过去10年来最富有成效的国际合作，而且还领导了这些合作 研究了心脏代谢性疾病的遗传基础。我们的联盟包括来自帕洛阿尔托、费城、凤凰城、贝德福德和奥尔巴尼的5个VISN以及斯坦福大学和宾夕法尼亚大学的调查人员。在目标1中，我们将使用EHR得出的关于医疗诊断和治疗、体检和实验室测量以及药物使用的信息，建立五种心脏代谢特征的最佳定义：体重指数、血液胆固醇水平，以及2型糖尿病(T2 DM)、CAD、PAD的诊断。我们使用最自由的特征定义查询VA EHR数据的初步结果表明，大约有160,000名参与者进行了血脂测量，195,000名参与者进行了体重指数测量，100,000名参与者患有T2 DM或糖尿病前期，46,000名参与者患有冠心病，9000名参与者患有PAD。对于数量性状，我们将不仅推导和研究单个时间点的衡量标准，还将推导和研究每个个体的长期平均值。对于结果，我们将通过评估已建立的危险因素之间的关系来优化我们的定义，包括表型特定的遗传风险分数和病例对照状态。在目标2中，我们将进行一系列全基因组关联研究，以确认已知的基因座，并识别与我们感兴趣的性状相关的新的遗传变异。我们还将使用全面的VA EHR来检查基因-环境相互作用的存在。最后，在目标3中，我们将应用新的统计算法，以提高我们对导致心脏代谢疾病风险的遗传变异的理解。 非裔美国人和西班牙裔美国人通过利用不同种族/民族之间遗传结构的相似性。该项目的成功完成将有助于我们更彻底地了解心脏代谢性疾病的潜在原因，并开发安全、有效和个性化的新疗法。这些发现还将导致更可靠地确定处于这些疾病风险中的个人，使退伍军人管理局人群中的初级预防策略能够得到更优化的交付。

 DESCRIPTION (provided by applicant): Obesity, Type 2 diabetes (T2DM), and dyslipidemia are metabolic disorders that promote the development of coronary artery (CAD) and peripheral arterial disease (PAD). Collectively, these cardio metabolic conditions are leading causes of illness and death among Veterans. A substantial proportion of the variation in risk of clinical complications related to these conditios remains unexplained despite an understanding of the root factors involved. The VA Million Veteran Program (MVP) links information from Veterans' electronic heath record (EHR) to biomarker data measured from blood and provides an unparalleled opportunity to further explore the genetic basis of cardio metabolic diseases. We propose to use the genome wide genotyping data from the first 200,000 participants in MVP linked to the EHR to uncover novel associations between genetic variation and risk of cardio metabolic disease. To perform this research, we have assembled a team of investigators with extensive experience in VA based clinical research and population genetics. Many members of our team have not only participated in, but also have led, the most productive international collaborations over the last 10 years that have studied the genetic basis of cardio metabolic diseases. Our consortium includes investigators from 5 VISNs based at Palo Alto, Philadelphia, Phoenix, Bedford, and Albany as well as from Stanford University and the University of Pennsylvania. In Aim 1, we will establish optimal definitions of five cardio metabolic traits: body mass index, blood levels of cholesterol, as well as diagnoses of Type 2 diabetes (T2DM), CAD, PAD, using EHR derived information on medical diagnoses and treatments, physical exam and lab measures, and medication usage. Preliminary results of our queries of VA EHR data using the most liberal definitions of the traits have identified approximately 160,000 participants with lipid measurements, 195,000 participants with measurements of body-mass index, 100,000 participants with T2DM or prediabetes, 46,000 participants with CAD, and 9,000 participants with PAD. For quantitative traits, we will derive and study not only single time point measures but also long term averages for each individual. For outcomes, we will optimize our definitions by assessing the relationship between established risk factors including phenotype specific genetic risk scores and case-control status. In Aim 2, we will perform a series of genome wide association studies to confirm known loci and to identify novel genetic variation associated with our traits of interest. We will also use the comprehensive VA EHR to examine for the presence of gene-environment interactions. Finally, in Aim 3, we will apply novel statistical algorithms that will improve our understanding of the genetic variation that contributes to the risk of cardio metabolic diseases in both the African American and the Hispanic American populations by leveraging similarities in the genetic architecture among different race/ethnic groups. Successful completion of this project will help us to more thoroughly comprehend the underlying causes of cardio metabolic disease and to develop novel therapies that are safe, effective, and personalized. These discoveries will also result in the more reliable identification of individuals at risk for these disorders, allowing for the more optimal delivery of primary prevention strategies within the VA population.