Genome-wide association analysis reveals insights into the molecular etiology underlying dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a clinical disorder characterised by reduced contractility of the heart muscle that is not explained by coronary artery disease or abnormal haemodynamic loading. Although Mendelian disease is well described, clinical testing yields a genetic cause in a minority of patients. The role of complex inheritance is emerging, however the common genetic architecture is relatively unexplored. To improve our understanding of the genetic basis of DCM, we perform a genome-wide association study (GWAS) meta-analysis comprising 14,255 DCM cases and 1,199,156 controls, and a multi-trait GWAS incorporating correlated cardiac magnetic resonance imaging traits of 36,203 participants. We identify 80 genetic susceptibility loci and prioritize 61 putative effector genes for DCM by synthesizing evidence from 8 gene prioritization strategies. Rare variant association testing identifies genes associated with DCM, including MAP3K7, NEDD4L , and SSPN . Through integration with single-nuclei transcriptomics from 52 end-stage DCM patients and 18 controls, we identify cellular states, biological pathways, and intercellular communications driving DCM pathogenesis. Finally, we demonstrate that a polygenic score predicts DCM in the general population and modulates the penetrance of rare pathogenic and likely pathogenic variants in DCM-causing genes. Our findings may inform the design of novel clinical genetic testing strategies incorporating polygenic background and the genes and pathways identified may inform the development of targeted therapeutics. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by funding from the British Heart Foundation [RE/18/4/34215, FS/IPBSRF/22/27059, FS/15/81/31817, FS/ICRF/21/26019, RG/19/6/34387, BC/F/21/220106, FS/18/65/34186]; the Medical Research Council [MC\_UP\_1605/13]; Wellcome Trust [107469/Z/15/Z]; the National Institute for Health Research (NIHR) Imperial College Biomedical Research Centre; NIHR Royal Brompton Cardiovascular Biomedical Research Unit; Sir Jules Thorn Charitable Trust [21JTA]; National Heart Lung Institute Foundation; Royston Centre for Cardiomyopathy Research; Rosetrees Trust. This research has been conducted in part using the UK Biobank Resource under Application Numbers 9922, 15422, 18545, 40616 and 47602.  ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: N/A I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data from UK Biobank can be requested from the UK Biobank Access Management System. Data from 100,000 Genomes Project can be accessed following application to join the Genomics England Clinical Interpretation Partnership. GWAS summary statistics will be made available on the Cardiovascular Disease Knowledge Portal () upon publication following peer-review. The PGS will be made available on the Polygenic Score Catalog ([www.pgscatalog.org][1]) following peer-review. The raw single nuclei gene expression dataset is available from CZI CELLxGENE ([cellxgene.cziscience.com][2]). The analyses reported in this article rely on previously published software, as detailed in the Methods. [1]: http://www.pgscatalog.org [2]: https://cellxgene.cziscience.com