Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, novel multiOMICs approaches are needed for deciphering the underlying molecular networks. Here, we integrated genomics, transcriptomics, and proteomics of human atrial tissue which allowed for identifying widespread effects of genetic variants on both transcript (cis eQTL) and protein (cis pQTL) abundance. We further established a novel targeted trans QTL approach based on polygenic risk scores to identify candidates for AF core genes. Using this approach, we identified two trans eQTLs and four trans pQTLs for AF GWAS hits, and elucidated the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multiOMICs method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.

中文翻译：

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心房颤动的组织特异性multiOMICs分析

心房颤动（AF）的全基因组关联研究（GWAS）发现了许多与疾病相关的变异。它们的潜在分子机制，特别是对mRNA和蛋白质表达的影响，仍然很难捉摸。因此，需要新颖的multiOMICs方法来解密基础分子网络。在这里，我们整合了人类心房组织的基因组学，转录组学和蛋白质组学，从而确定了遗传变异对转录本（cis eQTL）和蛋白质（cis pQTL）丰度的广泛影响。我们进一步建立了一种基于多基因风险评分的新型靶向反式QTL方法，以鉴定AF核心基因的候选基因。使用这种方法，我们为AF GWAS命中确定了两个反式eQTL和四个反式pQTL，并阐明了转录因子NKX2-5作为GWAS SNP rs9481842与AF之间的联系的作用。总而言之，我们提出了一种集成的multiOMICs方法，以在小型数据集中发现反式作用网络，并为心血管疾病基因优先排序的转录本和蛋白质水平提供了丰富的心房组织特异性调控变异体资源。