Hypertrophic cardiomyopathy (HCM) is a common, serious, genetic heart disorder. Rare pathogenic variants in sarcomere genes cause HCM, but with unexplained phenotypic heterogeneity. Moreover, most patients do not carry such variants. We report a genome-wide association study of 2,780 cases and 47,486 controls that identified 12 genome-wide-significant susceptibility loci for HCM. Single-nucleotide polymorphism heritability indicated a strong polygenic influence, especially for sarcomere-negative HCM (64% of cases; h2g = 0.34 ± 0.02). A genetic risk score showed substantial influence on the odds of HCM in a validation study, halving the odds in the lowest quintile and doubling them in the highest quintile, and also influenced phenotypic severity in sarcomere variant carriers. Mendelian randomization identified diastolic blood pressure (DBP) as a key modifiable risk factor for sarcomere-negative HCM, with a one standard deviation increase in DBP increasing the HCM risk fourfold. Common variants and modifiable risk factors have important roles in HCM that we suggest will be clinically actionable.
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All of the relevant data are included within the paper and/or its Supplementary Information files. The datasets generated during this study are available from the corresponding author upon reasonable request. The institutional domain www.well.ox.ac.uk/hcm will provide summary-level statistics.
Publicly available software tools were used to analyze these data. These include: SAIGE (https://github.com/weizhouUMICH/SAIGE), SNPTEST (https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html), GCTA (https://cnsgenomics.com/software/gcta/), PLINK (https://www.cog-genomics.org/plink/1.9/data), BGENIX (https://bitbucket.org/gavinband/bgen/wiki/bgenix), QCTOOL (https://www.well.ox.ac.uk/~gav/qctool_v2/), GWAMA (https://genomics.ut.ee/en/tools/gwama) and MR-Base (http://www.mrbase.org/).
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This work was supported by funding from the British Heart Foundation (BHF), the Medical Research Council (MRC), the National Heart, Lung, and Blood Institute (NIH grant U01HL117006-01A1), the Wellcome Trust (201543/B/16/Z), Wellcome Trust core awards (090532/Z/09/Z and 203141/Z/16/Z) and the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. A.R.H. has received support from the MRC Doctoral Training Partnership. A.G. has received support from the BHF, European Commission (LSHM-CT-2007-037273 and HEALTH-F2-2013-601456) and Tripartite Immunometabolism Consortium (TrIC)-NovoNordisk Foundation (NNF15CC0018486). S.E.P. acknowledges support from the NIHR Barts Biomedical Research Centre. A.W. has received support from the Wellcome Trust. S.N., M.F. and H.W. are members of the Oxford BHF Centre of Research Excellence (RE/13/1/30181). We are grateful for access to the high-performance Oxford Biomedical Research Computing (BMRC) facility, a joint development between the Wellcome Centre for Human Genetics and the Big Data Institute that is supported by Health Data Research UK and the NIHR Oxford Biomedical Research Centre. The views expressed are those of the author(s) and do not necessarily reflect those of the NHS, NIHR, Department of Health or Department of Health and Social Care. We thank the NIHR BioResource volunteers for their participation and gratefully acknowledge the NIHR BioResource centers, NHS Trusts and staff for their contribution. We thank the NIHR and NHS Blood and Transplant. This research was made possible through access to the data and findings generated by the 100,000 Genomes Project, which is managed by Genomics England (a wholly owned company of the Department of Health and Social Care) and funded by the NIHR and NHS England with research infrastructure funding from the Wellcome Trust, Cancer Research UK and the MRC. The 100,000 Genomes Project uses data provided by patients and collected by the National Health Service as part of their care and support. We acknowledge the contribution of the Oxford Medical Genetics Laboratories.
As of April 2020, A.R.H. is an employee of AstraZeneca.
Peer review information Nature Genetics thanks the anonymous reviewers for their contribution to the peer review of this work.
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Harper, A.R., Goel, A., Grace, C. et al. Common genetic variants and modifiable risk factors underpin hypertrophic cardiomyopathy susceptibility and expressivity. Nat Genet 53, 135–142 (2021). https://doi.org/10.1038/s41588-020-00764-0
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