HUNTing for myocardial infarction genes by combined genome and exome sequencing

通过基因组和外显子组测序相结合寻找心肌梗死基因

• 批准号: 8502753
• 负责人: Cristen J Willer
• 金额: $ 69.9万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-08-18 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8502753
• 关键词: American; Antiplatelet Drugs; Aspirin; Atherosclerosis; Biological; Candidate Disease Gene; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Communities; Complex; Computer software; Computing Methodologies; Coronary Arteriosclerosis; Custom; DNA; DNA Sequence; Data; Data Set; Development; Diagnosis; Disease; Drug Targeting; Etiology; Exons; Family history of; Family member; Gene Frequency; Genes; Genetic; Genome; Genomics; Genotype; Goals; Haplotypes; Hereditary Disease; Individual; Joints; LDL Cholesterol Lipoproteins; Lipids; Location; Maps; Methods; Minor; Myocardial Infarction; National Heart, Lung, and Blood Institute; Pathway interactions; Pharmacotherapy; Phenotype; Population; Prevention; Preventive; Probability; Protocols documentation; Recurrence; Research; Risk; Risk Factors; Sample Size; Sampling; Sardinia; Signal Transduction; Statistical Methods; Technology; Testing; Therapeutic; United States; Validation; Variant; Woman; analytical method; base; biobank; case control; cohort; cost effective; data sharing; design; early onset; exome; exome sequencing; follow-up; genetic variant; genome sequencing; genome wide association study; genotyping technology; improved; innovation; insight; men; next generation sequencing; novel; risk variant

DESCRIPTION (provided by applicant): The goal of this R01 proposal is to use high-throughput DNA sequencing and genotyping technologies to identify genes and pathways that contribute to the risk for myocardial infarction (MI). Our research team combines strengths in cardiovascular disease, high-throughput genetics and genomics and development and application of innovative computational and statistical methods to maximize the benefits of next-generation sequencing technologies. In Aim 1, we will sequence DNA from 1,000 individuals, 700 with MI and 300 controls, at ~5X coverage for the genome, and at ~100X average coverage for the exome. We will select MI cases with known family history of MI and additional cases with the earliest-onset from 3,100 MI cases collected by the HUNT Biobank. In Aim 2, we will carry out MI association analyses based on sequence data from these 1,000 samples and an additional 1,000 samples (500 with early-onset MI) with publically-available exome data from the NHLBI Exome Sequencing Project (ESP). We will analyze variants with MAF>0.5% individually. For variants with MAF<1%, we will use "burden" tests designed to identify regions where clusters of rare variants are more common in cases than controls (or vice versa). In Aim 3, we will use the Metabochip custom SNP array to genotype dense marker sets from 94 MI-related loci in 1,044 additional MI cases and 4,919 MI controls from the Finnish FUSION and METSIM studies. Using reference haplotypes from this project (Aim 1) together with haplotypes from the 1000 Genomes Project, T2DGO and Sardinia whole genome sequencing studies, we will impute variants into samples with Metabochip genotypes and perform association testing in 2,244 MI cases and 5,719 controls. In Aim 4, we will select for follow-up ~200 genes that show the strongest evidence for association with MI from Aims 2 and 3. These 200 genes will be sequenced in an additional 2,100 MI cases and 2,100 MI controls from the HUNT Biobank. In Aim 5, we will share data and methods to support similar studies for MI and other cardiovascular phenotypes, for imputation into larger samples with GWAS data, and more broadly across the scientific community. Completion of these aims will provide new insights into disease mechanism that have the potential to catalyze breakthroughs in MI prevention, treatment, and diagnosis.

描述（由申请人提供）： 本R 01提案的目标是使用高通量DNA测序和基因分型技术来鉴定导致心肌梗死（MI）风险的基因和途径。我们的研究团队结合了心血管疾病，高通量遗传学和基因组学以及创新计算和统计方法的开发和应用方面的优势，以最大限度地发挥下一代测序技术的优势。在目标1中，我们将对来自1,000个个体的DNA进行测序，其中700个患有MI，300个对照，基因组覆盖率约为5倍，外显子组平均覆盖率约为100倍。我们将从HUNT生物样本库收集的3,100例MI病例中选择具有已知MI家族史的MI病例和其他最早发作的病例。在目标2中，我们将基于来自这1,000个样本和另外1,000个样本（500个具有早发性MI）的序列数据与来自NHLBI外显子组测序项目（ESP）的公开可用的外显子组数据进行MI关联分析。我们将单独分析MAF>0.5%的变体。对于MAF<1%的变异，我们将使用“负担”检验，旨在确定病例中罕见变异簇比对照更常见的区域（反之亦然）。在目标3中，我们将使用Metabochip定制SNP阵列对来自芬兰FUSION和METSIM研究的另外1，044例MI病例和4，919例MI对照的94个MI相关基因座的密集标记集进行基因分型。使用来自该项目（目标1）的参考单倍型以及来自1000个基因组项目、T2 DGO和Sardinia全基因组测序研究的单倍型，我们将在2，244例MI病例和5，719例对照中对Metabochip基因型的样本进行变异插补，并进行相关性检验。在目标4中，我们将从目标2和3中选择约200个显示与MI相关的最强证据的基因进行随访。这200个基因将在HUNT生物库的另外2,100个MI病例和2,100个MI对照中进行测序。在目标5中，我们将分享数据和方法，以支持MI和其他心血管表型的类似研究，用于使用GWAS数据进行更大样本的插补，以及更广泛地在科学界进行。这些目标的实现将为疾病机制提供新的见解，有可能促进MI预防，治疗和诊断的突破。