An integrative approach to functionalize GWAS hits in MI and stroke

 描述(申请人提供)：冠心病(CHD)和脑血管疾病是由动脉粥样硬化斑块破裂部位的血小板血栓形成引起的。大量研究表明，血小板反应性增强、血小板数量和体积增加是冠心病事件和死亡率的危险因素，最近NHLBI工作组得出结论，血小板反应性的变化是心肌梗死或中风等缺血性事件的主要决定因素。全基因组关联研究(GWASs)已经发现了许多与冠心病风险和血小板功能参数相关的常见遗传变异，但大多数阳性“命中”并不是表型的原因。为了了解这些变体影响血小板功能的细胞机制，必须知道在感兴趣的细胞中表达的mRNAs、miRNAs和lncRNAs的谱系。我们的团队在血小板转录和血小板基因变异的功能评估领域一直处于领先地位。我们使用多个平台对183名受试者的mRNAs和miRNAs进行了分析，并对14名不同的受试者进行了血小板RNA-SEQ。这些信息为评估与心肌梗死、卒中和血小板参数相关的GWASNPs提供了筛选、优先排序和获得不同功能见解的关键能力。我们已经鉴定出142个mRNAs和9个miRNAs在血小板中表达，并与这些GWAHs有关。这项建议的目标是识别、检测和验证先前在GWAS中标记的血小板介导的缺血性动脉疾病和血小板表型的功能变异。目标1将确定在血小板中具有功能的GWAS连接的mRNAs、miRNAs和lncRNAs。候选RNA将通过与血小板功能、eQTL和QTL的关联来提炼，使用我们之前生成的血小板RNA数据。我们将开发一种有监督的机器学习、统计模式匹配算法，以确定可能的血小板功能基因的优先顺序。基因水平的分析，即我们在我们的人类巨核细胞培养系统中下调mRNAs、miRNA和lncRNA，然后是整合素激活的分析以及血小板数量和体积的量化，将用于确认血小板的功能。目标2将识别功能不同的SNPs和单倍型。我们将归因于缺失的SNP，并对感兴趣的表型进行精细定位。变异将根据关联强度、注释数据和使用公共可用资源和我们自己的小分子eQTL数据预测的功能来确定优先级。非编码候选基因将通过报告基因测试进行测试，非同义变体将在内源性基因已被沉默的细胞系中使用功能测试进行测试。我们将通过复制分析来验证我们的发现，在该分析中，我们使用独立的队列数据集来量化测试的变体与原始GWA型的关联。

 DESCRIPTION (provided by applicant): Coronary heart disease (CHD) and cerebrovascular disease result from platelet thrombus formation at the site of a ruptured atherosclerotic plaque. Numerous studies have shown enhanced platelet reactivity, and increased platelet count and volume are risk factors for CHD events and fatality, and a recent NHLBI Working Group concluded that variation in platelet reactivity is a major determinant of ischemic events, like MI or stroke. Genome wide association studies (GWASs) have identified numerous common genetic variants associated with the risk of CHD and platelet function parameters, but most of the positive "hits" are not causative of the phenotype. To understand the cellular mechanisms by which these variants affect platelet function it is imperative to know the repertoire of mRNAs, miRNAs and lncRNAs expressed in the cell of interest. Our team has been a leader in the field of platelet transcriptomics as well as functional assessment of variants in platelet genes. We have profiled mRNAs and miRNAs from 183 subjects using multiple platforms and have also performed platelet RNA-seq on 14 different subjects. This information provides a critical ability to filter, prioritize and obtain variant functional insights for evaluating GWAS SNPs associated with MI, stroke and platelet parameters. We have identified 142 mRNAs and 9 miRNAs that are expressed in platelets and linked to these GWAS hits. The goals of this proposal are to identify, assay, and validate functional variation previously tagged in GWASs of platelet-mediated ischemic arterial disease and of platelet phenotypes. Aim 1 will identify GWAS-linked mRNAs, miRNAs and lncRNAs that are functional in platelets. Candidate RNAs will be refined by association with platelet function, eQTLs and QTLs using our previously generated platelet RNA data. We will develop a supervised machine-learning, statistical pattern matching algorithm to prioritize likely platelet-functional genes. Gene-level assays in which we knock down mRNA, miRNA and lncRNA in our human megakaryocyte culture system, followed by assays for integrin activation and quantification of platelet number and volume will be used to confirm platelet functionality. Aim 2 will identify functionally divergent SNPs and haplotypes. We will impute missing SNPs and perform fine-mapping to the phenotypes of interest. Variants will be prioritized by association strength, annotation data, and predicted function using publically available resources and our own platelet eQTL data. Non-coding candidates will be tested by reporter gene assay and non-synonymous variants will be tested using functional assays in cell lines in which the endogenous gene has been silenced. We will validate our findings with a replication analysis in which we use an independent cohort dataset to quantify the association of the tested variants with the original GWAS phenotype.