HUNTing for myocardial infarction genes by combined genome and exome sequencing

描述(由申请人提供)： 这份R01提案的目标是使用高通量DNA测序和基因分型技术来识别导致心肌梗死(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方面的优势，以及创新计算和统计方法的开发和应用，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1000名个体，700名心肌梗塞患者和300名对照的DNA进行测序，基因组覆盖率为~5倍，外显子组平均覆盖率为~100倍。我们将从Hunt Biobank收集的3,100例MI病例中选择有MI家族史的MI病例和发病最早的其他病例。在目标2中，我们将根据这1,000个样本和另外1,000个样本(500个早发性心肌梗死)的序列数据和NHLBI外显子组测序项目(ESP)的公开外显子组数据进行MI关联分析。我们将分别分析MAF&GT；0.5%的变种。对于MAF&lt；1%的变异，我们将使用“负担”测试，旨在识别病例中稀有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METABOB芯片定制的SNP阵列，对芬兰Fusion和METSIM研究中另外1,044例MI病例和4,919例MI对照的94个MI相关基因座的致密标记集进行基因分型。使用本项目(AIM 1)中的参考单倍型以及1000基因组计划、T2DGO和撒丁岛全基因组测序研究中的单倍型，我们将在具有代谢型芯片基因型的样本中注入变异，并在2,244例MI患者和5,719名对照中进行关联测试。在AIMS 4中，我们将从AIMS 2和AIMS 3中挑选出与心肌梗死相关的最有力证据的约200个基因进行随访。这200个基因将在另外2,100例MI病例和来自Hunt Biobank的2,100例MI对照中进行测序。在目标5中，我们将分享数据和方法，以支持对心肌梗死和其他心血管表型的类似研究，将其归因于使用Gwas数据的更大样本，以及更广泛的科学界。这些目标的完成将为疾病机制提供新的见解，有可能催化在心肌梗死预防、治疗和诊断方面的突破。

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.