Computational Health Center, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), München, Germany.
Department of Informatics, Technical University Munich, München, Germany.
Nat Commun. 2022 Jan 21;13(1):441. doi: 10.1038/s41467-022-27953-1.
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, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted trans-QTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics 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.
全基因组关联研究(GWAS)已经发现了许多与心房颤动(AF)相关的疾病变异。然而,这些变异的潜在分子机制,特别是对 mRNA 和蛋白质表达的影响,在很大程度上仍未被揭示。因此,需要更精细的多组学方法来破译潜在的分子网络。在这里,我们在一项横断面研究中整合了人类心房组织的基因组学、转录组学和蛋白质组学,以确定遗传变异对转录本(顺式-eQTL)和蛋白质(顺式-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跨 QTL 方法,以确定 AF 核心基因的候选基因。使用这种方法,我们确定了两个与 AF GWAS 命中相关的跨-eQTL 和五个跨-pQTL,并阐明了转录因子 NKX2-5 作为 GWAS SNP rs9481842 与 AF 之间联系的作用。总之,我们提出了一种整合的多组学方法,用于在小数据集上揭示转录因子的作用网络,并为心血管疾病基因优先级提供了丰富的心房组织特异性转录和蛋白质水平调节变异资源。