Tissue-specific multi-omics analysis of atrial fibrillation

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.

Numerous disease-associated variants have been described in GWAS for atrial fibrillation. Here the authors integrate omics data to investigate the consequences of genetic variants for transcript and protein levels in the atrium of the human heart. With this multi-omics approach, authors reveal the regulatory network underlying atrial fibrillation and provide a resource for cardiac gene prioritization.