Genome-wide study of sudden cardiac arrest in the community

社区心脏骤停的全基因组研究

• 批准号: 8110690
• 负责人: Nona Sotoodehnia
• 金额: $ 167.54万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2014-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8110690
• 关键词: Accounting; African American; American; Architecture; Arrhythmia; Atherosclerosis; Basic Science; Blood; Blood Pressure; Candidate Disease Gene; Cardiac; Cardiology; Cardiovascular Diseases; Cardiovascular system; Cohort Studies; Communities; Complement; County; DNA; Data; Data Set; Development; Diabetes Mellitus; European; Event; Family; Frequencies; Future; Gene Frequency; Genes; Genetic; Genetic Materials; Genetic Variation; Genome; Genomics; Genotype; Health; Heart Arrest; Heart failure; Human; Human Genome; Inherited; Intervention; Lipids; Maps; Molecular; Molecular Genetics; Myocardial Infarction; Nucleic Acid Regulatory Sequences; Pacific Northwest; Pathway interactions; Pattern; Pharmacotherapy; Phenotype; Population; Population Control; Predisposition; Recording of previous events; Research Design; Resources; Risk; Sample Size; Sampling; Scanning; Signal Transduction; Single Nucleotide Polymorphism; Site; Source; Stratification; Structure; Variant; Ventricular Fibrillation; Washington; Work; base; cardiovascular disorder epidemiology; cardiovascular risk factor; case control; clinical material; cost; design; follow-up; genetic association; genome wide association study; genome-wide; insight; mortality; novel; population based; repository; sound

DESCRIPTION (provided by applicant): There is mounting evidence from studies of familial aggregation, candidate genes, and the molecular genetics of inherited arrhythmias that genetic variation influences susceptibility to sudden cardiac arrest (SCA), but the genetic architecture of SCA in the community remains unknown. This is a final submission of a revised application to identify novel associations (main effects) of common genetic variation across the genome with SCA, using a case-control, genome-wide association study (GWAS), design. We take advantage of available DNA from a large, population-based study of SCA from Seattle and King County (Washington); and, we use existing whole genome scan (WGS) data for controls. Among European Americans (EAs), we will conduct a GWAS of 2500 SCA cases and 7500 controls (step 1), followed by fine mapping of 100 genomic regions among 2500 SCA cases and 2500 controls (step 2); and replication in an independent sample of 1000 SCA cases and 1000 controls (step 3). We will obtain a WGS on 2500 SCA cases included in the Cardiac Arrest Blood Study - Repository (CABS-R) and 750 controls from the Cardiac Arrest Blood Study (CABS). We use existing WGS data from 600 controls (non-cases) from the Heart Attack Risk in Puget Sound (HARPS) Study and 6150 controls from the Atherosclerosis Risk in Communities (ARIC) study. Using WGS data from the Affymetrix 6.0 array, we will examine the associations of 700k single nucleotide polymorphisms (SNPs) with SCA to identify 100 genomic regions, based upon the "top hit" p-values, in EAs (step 1). Using an Illumina Bead Array, we will genotype 1536 SNPs, including approximately 15 SNPs from each of the 100 genomic regions from step 1, in 2500 EA cases and 2500 EA controls (step 2). Finally, we will replicate the findings from steps 1 and 2 (for those SNPs with a p-value < 0.0000014) using an independent sample of 1000 EA cases and 1000 EA controls (step 3). We will frequency match the selection of controls used in the GWAS (step 1) to the population (allelic) structure of the SCA cases; and, we will use genomic control in step 2 to minimize bias from population stratification. Given the large sample sizes and the three step design, we will have >80% statistical power to detect modest size genetic effects, while limiting the expected number of false positive associations. While underpowered, we include an exploratory WGS of 400 African-American (AA) SCA cases from the CABS-R and 900 AA controls (with available WGS data) from ARIC that also will provide a resource for future collaborative efforts. The identification of genetic variation across the genome associated with SCA using a large, case-control, GWAS followed by fine mapping and replication will minimize false negative and positive associations and provide insight into the mechanisms of SCA that will help to target interventions to reduce mortality from SCA. PUBLIC HEALTH RELEVANCE: There is mounting evidence that family history influences the risk of sudden cardiac arrest (SCA), a devastating cardiac event that accounts for 10% of total mortality in the US; however, the variation in the human genome associated with SCA remains unknown. We will investigate variation throughout the human genome to identify novel genes that influence SCA. The study results will provide insight into the molecular mechanisms of SCA and potentially help target the development of novel drug therapies to reduce mortality from SCA.

描述（由申请人提供）：来自家族聚集、候选基因和遗传性心律失常分子遗传学研究的越来越多证据表明，遗传变异影响心脏骤停（SCA）的易感性，但社区中 SCA 的遗传结构仍然未知。这是修订后的申请的最终提交，旨在使用病例对照、全基因组关联研究 (GWAS) 设计来确定整个基因组中常见遗传变异与 SCA 的新关联（主要影响）。我们利用来自西雅图和金县（华盛顿）的一项大型、基于人群的 SCA 研究中的可用 DNA；并且，我们使用现有的全基因组扫描（WGS）数据进行对照。在欧洲裔美国人 (EA) 中，我们将对 2500 个 SCA 病例和 7500 个对照进行 GWAS（步骤 1），然后对 2500 个 SCA 病例和 2500 个对照中的 100 个基因组区域进行精细定位（步骤 2）；并在 1000 个 SCA 病例和 1000 个对照的独立样本中进行复制（步骤 3）。我们将获得心脏骤停血液研究 - 存储库 (CABS-R) 中包含的 2500 个 SCA 病例和心脏骤停血液研究 (CABS) 中的 750 个对照病例的全基因组测序 (WGS)。我们使用来自普吉特海湾心脏病发作风险 (HARPS) 研究的 600 名对照（非病例）和来自社区动脉粥样硬化风险 (ARIC) 研究的 6150 名对照的现有 WGS 数据。使用 Affymetrix 6.0 阵列中的 WGS 数据，我们将检查 700k 个单核苷酸多态性 (SNP) 与 SCA 的关联，以根据 EA 中的“热门命中”p 值识别 100 个基因组区域（步骤 1）。使用 Illumina Bead Array，我们将对 2500 个 EA 病例和 2500 个 EA 对照（步骤 2）中的 1536 个 SNP 进行基因分型，其中包括来自步骤 1 的 100 个基因组区域中每个区域的大约 15 个 SNP。最后，我们将使用 1000 个 EA 病例和 1000 个 EA 对照的独立样本复制步骤 1 和 2 的结果（对于那些 p 值 < 0.0000014 的 SNP）（步骤 3）。我们将 GWAS（步骤 1）中使用的对照选择与 SCA 病例的群体（等位基因）结构进行频率匹配；并且，我们将在步骤 2 中使用基因组控制来最大程度地减少群体分层带来的偏差。考虑到大样本量和三步设计，我们将有 >80% 的统计功效来检测适度大小的遗传效应，同时限制假阳性关联的预期数量。虽然动力不足，但我们纳入了来自 CABS-R 的 400 个非裔美国人 (AA) SCA 病例的探索性 WGS 和来自 ARIC 的 900 个 AA 对照（具有可用的 WGS 数据），这也将为未来的合作工作提供资源。使用大型病例对照 GWAS 来识别与 SCA 相关的整个基因组的遗传变异，然后进行精细绘图和复制，将最大限度地减少假阴性和阳性关联，并深入了解 SCA 的机制，这将有助于有针对性的干预措施，以降低 SCA 的死亡率。公共卫生相关性：越来越多的证据表明，家族史会影响心脏骤停 (SCA) 的风险，这是一种毁灭性的心脏事件，占美国总死亡率的 10%；然而，与 SCA 相关的人类基因组变异仍然未知。我们将研究整个人类基因组的变异，以确定影响 SCA 的新基因。该研究结果将深入了解 SCA 的分子机制，并可能有助于开发新的药物疗法以降低 SCA 的死亡率。