A Platform for Large-Scale Discovery in Common Disease

常见疾病大规模发现的平台

基本信息

批准号：
9924136
负责人：
Ira M Hall
金额：
$ 1303.19万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-01-14 至 2022-11-30
项目状态：
已结题

项目摘要

PROJECT SUMMARY This supplement will continue to fund our Center for Common Disease Genomics (UM1HG008853) at the McDonnell Genome Institute at Washington University entitled, “A platform for large-scale discovery in common disease.” In the supplemental period we will continue our multi-ethnic case-control whole genome sequencing (WGS) study focused on mapping novel disease genes and variants underlying risk and protection from early- onset coronary artery disease (EOCAD). Along with EOCAD cases, we aim to select deeply phenotyped controls whenever possible in order to study the genetic basis of quantitative cardiometabolic risk factors. After completing the WGS, we will assemble a joint callset that includes all EOCAD cases and controls from our center to enable association testing between genotypes and disease outcomes. Genotypes for the primary analysis will include testing common (individual) and rare (burden) single nucleotide variants (SNVs), insertion/deletion variants (indels), and structural variants (SVs) across coding and non-coding space. In secondary analyses, we will test for association with quantitative cardiometabolic risk factor traits and will leverage differential patterns of admixture to map causal variants underlying previously mapped disease and trait associated loci. Beyond disease association studies, we will continue to collaborate with consortium members to create genomic resources that will be used by the scientific community such as aggregated site frequencies, imputation resources, and open source analysis methods.

项目摘要该补充剂将继续为我们的普通疾病基因组学中心（UM1HG008853）提供资金华盛顿大学的麦克唐纳基因组学院题为“一个大规模发现的平台疾病。”在补充期，我们将继续我们的多种族病例对照整个基因组测序（WGS）的研究重点是绘制新型疾病基因和差异的风险和保护的变体，以免早期发作冠状动脉疾病（EOCAD）。除EOCAD案例外，我们旨在选择深层表型的控制尽可能研究定量心脏代谢风险因素的遗传基础。后完成WGS，我们将组装一个联合呼叫集，其中包括我们中心的所有EOCAD案件和控件使基因型和疾病结局之间的关联测试。主要分析的基因型将包括测试常见（个人）和稀有（负担）单核苷酸变体（SNV），插入/删除跨编码和非编码空间的变体（indels）和结构变体（SVS）。在二次分析中，我们将测试与定量心脏代谢危险因素特征相关联，并利用混合图来绘制先前映射的疾病和性状相关的地方的因果变异。超过疾病协会研究，我们将继续与财团成员合作创建基因组科学界将使用的资源，例如汇总现场频率，插补资源和开源分析方法。