A Genome-wide Association Study for Early-Onset Myocardial Infarction

描述(由申请人提供)： 在美国，心肌梗死(Ml)是主要的死亡原因。ML在不受传统危险因素影响的家庭中呈聚集性，当ML发生在生命早期时，遗传率大大增加。因此，遗传性DNA变异在多发性骨髓瘤中起着因果作用，尤其是在早发性多发性骨髓瘤中的作用尤为明显。然而，到目前为止，ML(早期和晚期)的家族聚集在很大程度上仍然不能用已知的基因变异来解释。最近的证据表明，常见的基因变异会增加常见疾病的风险。由于遗传学的最新进展，现在在全基因组范围内搜索影响ML风险的常见DNA变异是可行的。在这种方法中，成功的关键决定因素包括：表型的选择、样本大小、有效的研究设计、对系统性偏差的潜在来源的关注、严格的分析以及区分真阳性和假线索的验证。我们假设：(A)早发性ML是一个特别有希望的基因发现目标；(B)常见的DNA变异影响早发性ML的风险；(C)许多这样的变异不在“候选基因”或已确定的连锁峰中；(D)影响通常不大且先证者低，需要大量样本；以及(E)如果提供足够数量的SNPs、样本量和分析的严谨性，风险变异可以通过与人群中的疾病相关联来识别。 为了验证这些假设，我们提出了以下具体目标：(1)在两阶段设计的第一阶段，收集和整理1500例早发性ML患者和1500名没有ML的匹配对照组中每一组550,000个SNPs的基因数据；(2)使用Aim 1中收集的数据，系统地分析SNPs与早发性ML风险之间的关联，根据统计证据确定前0.1%；(3)在第二阶段，在另外1748例早发性ML患者和1743名对照组中，对I阶段前0.1%的SNPs进行基因分型；联合分析第一阶段和第二阶段，以确定与疾病相关的变异。 拟议的项目将史无前例的早发性ML流行病学研究与基因组学和统计/人口遗传学方面的独特专业知识结合在一起。我们的研究将彻底检验常见基因变异在早发性ML中起作用的假设。成功识别常见的基因变异和潜在的ML潜在风险的新途径有可能改变对美国主要死亡原因的理解、治疗和预防。

DESCRIPTION (provided by applicant): Myocardial infarction (Ml) is the leading cause of death in the US. Ml clusters in families independent of traditional risk factors and when Ml occurs early in life, heritability is substantially greater. Thus, inherited DNA variation plays a causal role in Ml, with a particularly strong role in early-onset Ml. To date, however, the familial aggregation of Ml (early and late) remains largely unexplained by known gene variants. Recent evidence shows that common genetic variants contribute to risk of common diseases. Due to recent progress in genetics, it is now practical to search genome-wide for common DNA variants influencing Ml risk. In such an approach, critical determinants of success include: the choice of phenotype, sample size, an efficient study design, attention to potential sources of systematic bias, rigorous analysis, and validation to distinguish true positives from false leads. We hypothesize that: (a) that early-onset Ml is a particularly promising target for gene discovery;(b) that common DNA variants influence risk of early-onset Ml;(c) that many such variants are not in "candidate genes" or identified linkage peaks; (d) that effects will often be modest and priors low, requiring large sample sizes; and (e) provided adequate numbers of SNPs, sample size and analytical rigor, that risk variants can be recognized by association with disease in the population. To test these hypotheses, we propose the following specific aims: (1) In Stage I of a two-stage design, collect and curate genotype data for each of 550,000 SNPs in each of 1500 cases with early-onset Ml and 1500 matched controls without Ml; (2) Using data collected in Aim 1, systematically analyze associations between SNPs and risk of early-onset Ml, identifying the top 0.1% based on strength of statistical evidence; (3) In Stage II, genotype the top 0.1% from Stage I in 1748 additional cases of early-onset Ml and 1743 controls; jointly analyze Stages I and II to identify variants associated with disease. The proposed project combines an unprecedented collection of epidemiologic studies of early-onset Ml with unique expertise in genomics and statistical/population genetics. Our study will thoroughly test the hypothesis that common gene variants play a role in early-onset Ml. Successfully identifying common gene variants and novel pathways underlying risk of Ml has the potential to transform understanding, treatment, and prevention of the leading cause of death in the U.S. (End of Abstract)