Key result
A polygenic score for dilated cardiomyopathy significantly predicted disease risk in the general population (OR 1.76 per standard deviation increase).
Why the study?
Clinical testing identifies a genetic cause in only a minority of dilated cardiomyopathy patients, and the common genetic architecture of complex inheritance remains relatively unexplored.
Meta-Analysis (n=1,213,411)
Yes
This large-scale GWAS meta-analysis identifies 80 genetic susceptibility loci for dilated cardiomyopathy, highlighting novel effector genes and demonstrating the utility of a polygenic risk score for predicting DCM.
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.
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Zheng et al. (2023) conducted a meta-analysis in Dilated cardiomyopathy (n=1,213,411). Polygenic score for dilated cardiomyopathy vs. Lower polygenic score was evaluated on Dilated cardiomyopathy risk per standard deviation increase in polygenic score (OR 1.76, 95% CI 1.64-1.90, p=<2x10-16). A polygenic score for dilated cardiomyopathy significantly predicted disease risk in the general population (OR 1.76 per standard deviation increase).
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