Extended data: Tissue-specific multi-omics analysis of atrial fibrillation

Summary statistics and result repository for the publication Tissue-specific multi-omics analysis of atrial fibrillation: Assum, I., Krause, J., Scheinhardt, M.O. <em>et al.</em> Tissue-specific multi-omics analysis of atrial fibrillation. <em>Nat Commun </em><strong>13, </strong>441 (2022). https://doi.org/10.1038/s41467-022-27953-1 For the related source code, see https://doi.org/https://doi.org/10.5281/zenodo.5094276 or https://github.com/heiniglab/symatrial. Additional information, such as a reference for effect alleles has been added in a newer version of this repository. Please refer to https://doi.org/10.5281/zenodo.5080228 for the newest version. Ines Assum^1,2,†, Julia Krause^3,4,†, Markus O. Scheinhardt⁵, Christian Müller^3,4, Elke Hammer^6,7, Christin S. Börschel^4,8, Uwe Vöker^6,7, Lenard Conradi⁹, Bastiaan Geelhoed^4,8,10, Tanja Zeller^3,4,*, Renate B. Schnabel^4,8,*, Matthias Heinig^1,2,11,* ^†,* These authors contributed equally. ¹ Computational Health Center, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany.<br> ² Department of Informatics, Technical University Munich, München, Germany.<br> ³ University Center of Cardiovascular Science, University Heart and Vascular Center Hamburg, Hamburg, Germany.<br> ⁴ Partner site Hamburg/Kiel/Lübeck, DZHK (German Center for Cardiovascular Research), Hamburg, Germany.<br> ⁵ Institute of Medical Biometry and Statistics, University of Lübeck, Lübeck, Germany.<br> ⁶ Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.<br> ⁷ Partner site Greifswald, DZHK (German Center for Cardiovascular Research), Greifswald, Germany.<br> ⁸ Department of Cardiology, University Heart and Vascular Center Hamburg, Hamburg, Germany.<br> ⁹ Department of Cardiovascular Surgery, University Heart and Vascular Center Hamburg, Hamburg, Germany.<br> ¹⁰Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.<br> ¹¹Partner site Munich, DZHK (German Center for Cardiovascular Research), Munich, Germany. ABSTRACT: 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 transQTL 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. TABLE OF CONTENTS: Single-omic <em>cis</em>-QTL results <em>cis</em>-eQTLs (all pairs, incl. LD clump info)<br> <em>eQTL_right_atrial_appendage_allpairs_clump.txt</em> <em>cis</em>-pQTLs (all pairs, incl. LD clump info)<br> <em>pQTL_right_atrial_appendage_allpairs_clump.txt</em> <em>cis</em>-res eQTLs (all pairs, incl. LD clump info)<br> <em>res_eQTL_right_atrial_appendage_allpairs_clump.txt</em> <em>cis</em>-res pQTLs (all pairs, incl. LD clump info)<br> <em>res_pQTL_right_atrial_appendage_allpairs_clump.txt</em> <em>cis</em>-ratioQTLs (all pairs, incl. LD clump info)<br> <em>ratioQTL_right_atrial_appendage_allpairs_clump.txt</em> Functional <em>cis</em>-QTL categories and eQTL/pQTL overlap: All eQTLs, pQTLs, res eQTLs, res pQTLs and ratioQTLs for all SNP-gene pairs with a significant eQTL and pQTL (FDR&lt;0.05)<br> <em>Fig2a_source_data_Shared_eQTL_pQTL_clump.txt</em> All eQTLs, pQTLs, res eQTLs, res pQTLs and ratioQTLs for all SNP-gene pairs with a significant eQTL but no pQTL (FDR&lt;0.05)<br> <em>Fig2b_source_data_Independent_eQTL_clump.txt</em> All eQTLs, pQTLs, res eQTLs, res pQTLs and ratioQTLs for all SNP-gene pairs with no eQTL but a significant pQTL (FDR&lt;0.05)<br> <em>Fig2c_source_data_Independent_pQTL_clump.txt</em> QTS rankings and enrichment results eQTS rankings and enrichments<br> <em>TableS6_source_data_eQTS_ranking.txt<br> TableS7_source_data_eQTS_GSEA_results.txt</em> pQTS rankings and enrichments<br> <em>TableS8_source_data_pQTS_ranking.txt<br> TableS9_source_data_pQTS_GSEA_results.txt</em> <em>Trans</em>-QTLs<br> all tested pairs including <em>trans</em>-pQTLs for <em>trans</em>-eQTLs and <em>trans</em>-eQTLs for <em>trans</em>-pQTLs<br> <em>Table2_source_data_Trans-QTL_results.txt</em>