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.

抽象的遗传易感性是大多数心血管疾病（CVD）及其前因的基础，强调通过全基因组关联研究 (GWAS)，迄今为止已识别出超过 1,500 个基因座。可能提供新颖的机制见解，但研究结果的转化在很大程度上仍然不完整，多效性是一种影响多种表型的变异，是一个长期的障碍。具体来说，研究是推进基因组医学的描述和普遍但很大程度上不为人知的途径。多效性有可能阐明分子功能，识别机械“公分母”，为诊断和治疗提供信息，并确定变体的优先顺序以进行系统性和功能性检查。多效性的综合研究与 CVD 表型特别相关，因为几十年来人类和动物研究支持共同影响下游临床疾病的共同遗传结构。很少有研究全面、系统地评估心血管内或跨心血管的多效性表型或扩展研究以检查多效性变异如何影响临床疾病。 CVD 及其前因对非裔美国人 (AA) 和西班牙裔/拉丁裔 (HL) 的影响尤为严重。然而，迄今为止 GWAS 中的大多数（>80%）参与者都是欧洲（EU）血统。研究差异造成了对人类变异的偏见，未能利用人类独特的遗传结构 AA 和 HL 用于精细绘图，并阻碍将遗传发现转化为临床和公共卫生我们通过利用高质量、协调的、与广大人群相关的应用程序来应对这些差距。以及来自使用基因组学的群体架构的集中可用的表型和基因型数据流行病学 (PAGE) 联盟以及中风地理和种族差异的原因（问候）研究（n=100,917；35% AA；32% EU；24% HL）以及尖端统计方法全面识别具有潜在多效性证据的位点，包括血压、胆固醇、心脏传导、血糖、炎症和肥胖心血管领域以及事件性心肌梗死和在具有潜在多效性的有力证据的已知和新位点，我们将利用群体。通过多种族、多表型精细作图确定结构、单倍型结构和表型相关性确定变体的优先顺序以供进一步审讯（目标 2）。最后，我们将利用纵向数据和路径。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产生的表型）来自显示介导的多效性的证据（例如变异影响一种表型，而该表型影响第二种表型）（目标 3）。 CVD 表型和临床疾病可以更准确地表征为临床表达的变化，通过研究多效性，我们希望阐明这些机制。有潜力为表型分类、药物开发和再利用以及心血管疾病预防提供信息。