Characterizing pleiotropy in cardiometabolic phenotypes among diverse populations

表征不同人群心脏代谢表型的多效性

基本信息

批准号：
10577753
负责人：
Christy Leigh Avery
金额：
$ 65.62万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-02-10 至 2025-01-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10577753
关键词：
Affect African American population Animals Architecture Biological Biology Blood Pressure Body mass index C-reactive protein Cardiac Cardiovascular Diseases Cardiovascular system Cholesterol Classification Clinical Data Diabetes Mellitus Diagnosis Diastolic blood pressure Disease Disparity EKG P Wave Ensure Epidemiology Ethnic Population Etiology European European ancestry Evaluation Event Foundations GRB14 gene Genes Genetic Genetic Predisposition to Disease Genomic medicine Genomics Genotype Glucose Glycosylated hemoglobin A Haplotypes High Density Lipoproteins Hispanic Human Hypertension Inflammatory Insulin Investigation LDL Cholesterol Lipoproteins Latino Population Link Maps Mediating Mendelian randomization Modeling Molecular Myocardial Infarction Obesity Participant Pathway interactions Phenotype Population Population Heterogeneity Public Health Applications Research Reasons for Geographic And Racial Differences in Stroke Reporting Research Resources Role Statistical Methods Stroke Structure Sum Thinking Translations Triglycerides Variant Waist-Hip Ratio White Blood Cell Count procedure adverse drug reaction cardiometabolism cardiovascular disorder prevention clinically relevant disease classification disease phenotype disorder prevention drug development drug repurposing ethnic minority population expectation experience genetic architecture genetic association genetic testing genome wide association study genome-wide insight multi-ethnic next generation sequencing novel phenotypic data pleiotropism pre-clinical precision medicine racial minority population translational genetics translational study

项目摘要

ABSTRACT Genetic susceptibility underlies a majority of cardiovascular diseases (CVD) and their antecedents, underscored by genome-wide association studies (GWAS) that identified >1,500 loci to-date. Each GWAS-identified locus potentially provides novel mechanistic insight, yet translation of study findings remains largely incomplete, representing a critical barrier to progress. Pleiotropy, a variant that affects multiple phenotypes, is a long- described and pervasive, but largely uncharacterized avenue to advance genomic medicine. Specifically, studies of pleiotropy have the potential to clarify molecular functions, identify mechanistic “common denominators", inform diagnosis and treatment, and prioritize variants for functional interrogation. Systematic and comprehensive interrogation of pleiotropy is particularly relevant for CVD phenotypes, as decades of human and animal studies support a shared genetic architecture that collectively affects downstream clinical disease. Yet, few studies have comprehensively and systematically evaluated pleiotropy within or across cardiovascular phenotypes or extended investigations to examine how pleiotropic variants affect clinical disease. Further, many CVDs and their antecedents disproportionately affect African Americans (AA) and Hispanic/Latinos (HL). However, the majority (>80%) of participants included in GWAS to-date are of European (EU) ancestry. This research disparity creates a biased view of human variation, fails to leverage the unique genetic architecture of AAs and HLs for fine-mapping, and hinders translation of genetic findings into clinical and public health applications relevant for broad populations. We respond to these gaps by leveraging high-quality, harmonized, and centrally available phenotype and genotype data from the Population Architecture Using Genomics in Epidemiology (PAGE) consortium and the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study (n=100,917; 35% AA; 32% EU; 24% HL) as well as cutting edge statistical methods to comprehensively identify loci with potential evidence of pleiotropy within and across blood pressure, cholesterol, cardiac conduction, glycemic, inflammatory, and obesity cardiovascular domains as well as incident MI and stroke (Aim 1). At known and novel loci with strong evidence of potential pleiotropy, we will leverage population structure, haplotypic architecture, and phenotype correlation through multi-ethnic, multi-phenotype fine-mapping to prioritize variants for further interrogation (Aim 2). Finally, we will leverage longitudinal data and pathway models to disaggregate variants displaying evidence of biological pleiotropy (i.e. variant affects multiple phenotypes due to shared biology) from variants displaying evidence of mediated pleiotropy (e.g. variant influences one phenotype and this phenotype influences a second phenotype) (Aim 3). We hypothesize that CVD phenotypes and clinical disease may be more accurately characterized as variations in clinical expression, with common biological mechanisms. By investigating pleiotropy, we hope to clarify these mechanisms, which has the potential to inform phenotype classification, drug development and repurposing, and CVD prevention.

抽象的遗传敏感性是大多数心血管疾病（CVD）及其前因的基础由全基因组关联研究（GWAS）确定了> 1,500个基因座迄今。每个GWAS识别的基因座潜在地提供了新颖的机械洞察力，但是研究结果的翻译基本上不完整，代表了进步的关键障碍。多效性是一种影响多种表型的变体，是一个长期描述的和普遍的，但在很大程度上没有特色的大道来推进基因组医学。具体而言，研究多效性的潜力有可能阐明分子功能，确定机械的“共同点”，告知诊断和治疗，并确定功能询问的变体。系统和多数数十年和动物研究支持共同影响下游临床疾病的共同遗传结构。然而，很少有研究对心血管内或跨性的多效性进行了全面和系统评估表型或扩展研究，以检查多效性变体如何影响临床疾病。此外，许多 CVD及其先决条件不成比例地影响非洲裔美国人（AA）和西班牙裔/拉丁裔（HL）。但是，GWAS待办事项中包括的大多数（> 80％）的参与者是欧洲（EU）的血统。这研究差异会产生对人类变异的有偏见的看法，无法利用 AAS和HLS用于精细映射，并阻碍将遗传发现转化为临床和公共卫生与广泛人群有关的应用程序。我们通过利用高质量，协调，并使用基因组学中的基因组学中心可用的表型和基因型数据流行病学（页）财团和中风的地理和种族差异的原因（在）研究（n = 100,917; 35％AA; 32％EU; 24％HL）以及尖端的统计方法全面识别基因座，具有潜在的多效性证据，胆固醇，胆固醇，胆固醇心脏传导，血糖，炎症和肥胖心血管域以及事件MI和中风（目标1）。在已知和新颖的基因座，有强烈的潜在多效性证据，我们将利用种群结构，单倍型结构和表型相关性通过多种族的多种型精细映射优先考虑变体以进行进一步审问（AIM 2）。最后，我们将利用纵向数据和途径分解显示生物多效性证据的变体的模型（即变体影响多个由于共享生物学而引起的表型）来自显示介导的多效性证据的变体（例如变体影响一种表型，该表型会影响第二个表型）（AIM 3）。我们假设这一点 CVD表型和临床疾病可能更准确地表征为临床表达的变化，具有常见的生物学机制。通过研究多效性，我们希望澄清这些机制，这些机制有可能为表型分类，药物开发和重新利用以及CVD预防提供信息。