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Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect

Nature Genetics volume 53, pages 128–134 (2021)Cite this article

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Abstract

The heart muscle diseases hypertrophic (HCM) and dilated (DCM) cardiomyopathies are leading causes of sudden death and heart failure in young, otherwise healthy, individuals. We conducted genome-wide association studies and multi-trait analyses in HCM (1,733 cases), DCM (5,521 cases) and nine left ventricular (LV) traits (19,260 UK Biobank participants with structurally normal hearts). We identified 16 loci associated with HCM, 13 with DCM and 23 with LV traits. We show strong genetic correlations between LV traits and cardiomyopathies, with opposing effects in HCM and DCM. Two-sample Mendelian randomization supports a causal association linking increased LV contractility with HCM risk. A polygenic risk score explains a significant portion of phenotypic variability in carriers of HCM-causing rare variants. Our findings thus provide evidence that polygenic risk score may account for variability in Mendelian diseases. More broadly, we provide insights into how genetic pathways may lead to distinct disorders through opposing genetic effects.

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Fig. 1: Study flowchart.
Fig. 2: Summary results of HCM single-trait GWAS and multi-trait analysis.
Fig. 3: Genetic correlation between LV traits, HCM and DCM.
Fig. 4: Cross-trait associations of HCM and DCM loci.
Fig. 5: A PRS for HCM stratifies event-free survival in carriers of disease-causing variants in sarcomere-encoding genes.

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Data availability

Data from the Genome Aggregation Database (gnomAD, v.2.1) are available at https://gnomad.broadinstitute.org. Data from the UKBB participants can be requested from the UKBB Access Management System (https://bbams.ndph.ox.ac.uk). Data from the GTEx consortium are available at the GTEx portal (https://gtexportal.org). Other datasets generated during and/or analyzed during the current study can be made available upon reasonable request to the corresponding authors. Individual level data sharing is subject to restrictions imposed by patient consent and local ethics review boards. Results from meta-analyses of GWAS reported in this article are available at https://www.heart-institute.nl/gwas and https://data.hpc.imperial.ac.uk (https://doi.org/10.14469/hpc/7468).

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Acknowledgements

R.T. received funding from the Canadian Heart Rhythm Society (George Mines Award), the European Society of Cardiology (Research fellowship grant), the Canadian Institutes of Health Research (funding reference number 169063) and the Fonds de Recherche du Québec—Santé (reference number 135055). R.T. and J.C.-T. received support from the Philippa and Marvin Carsley Cardiology Chair. C.F. received funding from a British Heart Foundation Clinical Research Training Fellowship FS/15/81/31817. X.X. is currently a postdoctoral scientist funded by the Medical Research Council London Institute of Medical Sciences. A.R.H. received support from the Medical Research Council Doctoral Training Partnership. R.W. received support from an Amsterdam Cardiovascular Sciences fellowship. E.T.H. and W.P.t.R. received support from the Young Talent Program of the Dutch Heart Foundation (CVON PREDICT 2012-10). W.P.t.R. is supported by a postdoctoral fellowship CURE-PLaN (Netherlands Heart Institute) from the Leducq Foundation. J.A.O. received support from the Amsterdam UMC’s PhD scholarship. A.d.M. received support from the National Institute for Health Research (NIHR) Biomedical Research Centre based at Imperial College Healthcare NHS Trust and Imperial College London; the Medical Research Council, UK; the Academy of Medical Sciences (SGL015/1006) and a Mason Medical Research Trust grant. J.H.V. received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant no 772376 - EScORIAL). E.K. received support from the German Center for Cardiovascular Research (DZHK) Rotation Grant. F.M. is supported by a postdoctoral research fellowship from the University of Florence and by the European Union Horizon 2020 framework programme (SILICOFCM, GA 777204). H.S. received support from grants from the Japan Society for the Promotion of Science (18K15410). D.S.-L. received support from UK Med-Bio. P.R. received support from the Fédération Française de Cardiologie. P.R. and F.A. were supported by Ligue contre la cardiomyopathie. E.V. and P.C. received support from the CONNY-MAEVA charitable foundation and GenMed LABEX. The study was supported by the Dutch Heart Foundation Netherlands Cardiovascular Research Initiative (CVON; PREDICT2 2018-30 to J.P.v.T., A.A.M.W. and C.R.B.; eDETECT 2015-12 to J.P.v.T. and I.C.; DOSIS 2014-40 to J.P.v.T., F.W.A., J.v.d.V., R.A.d.B. and M.M.; PRIME to Y.M.P.; and DOLPHIN-GENESIS 2017-10 to I.C.). R.A.H. is supported by the Jacob J. Wolfe Distinguished Medical Research Chair, the Edith Schulich Vinet Research Chair in Human Genetics and the Martha G. Blackburn Chair in Cardiovascular Research, and has received operating grants from the Canadian Institutes of Health Research (Foundation award) and the Heart and Stroke Foundation of Canada (G-18-0022147). M.-P.D. holds a Canada Research Chair in Precision Medicine Data Analysis. J.-C.T. holds the Canada Research Chair in personalized medicine and the University of Montreal endowed research chair in atherosclerosis and is the principal investigator of the Montreal Heart Institute André and France Desmarais hospital cohort funded by the Montreal Heart Institute Foundation. R.T.L. is supported by a UK Research and Innovation Rutherford Fellowship. F.W.A. is supported by the UCL Hospitals NIHR Biomedical Research Centre. F.W.A. and P.C. received support from European Union’s Horizon 2020 research and innovation program under the ERA-NET Co-fund action no. 680969 (ERA-CVD DETECTIN-HF), jointly funded by the Dutch Heart Foundation (2016T096) and Netherlands Organization for Health Research and Development (ZonMw). P.J.R.B. and J.S.W. are supported by a Health Innovation Challenge Fund award from the Wellcome Trust and Department of Health, UK (HICF-R6–373). D.P.O’R. is funded by the Medical Research Council, NIHR Biomedical Research Centre based at Imperial College Healthcare NHS Trust and Imperial College London, and a British Heart Foundation Program Grant (RG/19/6/34387). K.J.H.V. receives support from the Foundation Volksbond Rotterdam. M.T. receives support from the Monat foundation. G.L. is funded by the Montreal Heart Institute Foundation, the J. C. Edwards Foundation and the Canada Research Chair Program. B.M. received support from DZHK, the German Ministry of Education and Research (CaRNAtion), Informatics for Life (Klaus Tschira Foundation) and the European Union (FP7 BestAgeing), and was supported by an excellence fellowship of the Else Kröner Fresenius Foundation. P.C. received funding from PROMEX charitable foundation. H.W. has received support from the Wellcome Trust core award (090532/Z/09/Z), the BHF Centre of Research Excellence, Oxford (RE/13/1/30181), the NIHR Oxford Biomedical Research Centre and a National Heart, Lung and Blood Institute grant (U01HL117006-01A1). P.M.M. acknowledges generous personal and research support from the Edmond J. Safra Foundation and Lily Safra, an NIHR Senior Investigator Award and the UK Dementia Research Institute. J.S.W. was supported by Wellcome Trust (107469/Z/15/Z); British Heart Foundation (SP/17/11/32885; RE/18/4/34215); Medical Research Council (UK); NIHR Royal Brompton Cardiovascular Biomedical Research Unit; NIHR Imperial College Biomedical Research Centre. C.R.B. acknowledges support from the Netherlands Organization for Scientific Research (VICI fellowship, 016.150.610) and the Leducq Foundation (project 17CVD02). This research has been conducted in part using the UK Biobank Resource under Application Number 18454, and the Genotype-Tissue Expression (GTEx) Project supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by National Cancer Institute (NCI), National Human Genome Research Institute (NHGRI), National Heart, Lung and Blood Institute (NHLBI), National Institute on Drug Abuse (NIDA), National Institute of Mental Health (NIMH), and National Institute of Neorological Disorders and Stroke (NINDS). This study was supported by a kind donation from family and friends of Jean-Paul Balkestein who died at 32 years of age from hypertrophic cardiomyopathy.

Author information

Author notes

  1. These authors contributed equally: Rafik Tadros, Catherine Francis, Xiao Xu, Alexa M. C. Vermeer, Hugh Watkins, Paul M. Matthews, James S. Ware, Connie R. Bezzina.

Authors and Affiliations

  1. Cardiovascular Genetics Center, Montreal Heart Institute, Faculty of Medicine, Université de Montréal, Montreal, Québec, Canada

    Rafik Tadros, Ken Kelu Bisabu, Julie Amyot, Julia Cadrin-Tourigny, Geneviève Giraldeau, Philippe L. L’Allier, Patrick Garceau & Mario Talajic

  2. Department of Clinical and Experimental Cardiology, Heart Center, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands

    Rafik Tadros, Alexa M. C. Vermeer, Roddy Walsh, Joost Allard Offerhaus, Najim Lahrouchi, Leander Beekman, Yigal M. Pinto, Arthur A. M. Wilde & Connie R. Bezzina

  3. Cardiovascular Research Centre, Royal Brompton and Harefield National Health Service Foundation Trust, London, UK

    Catherine Francis, Rachel J. Buchan, Antonis Pantazis, A. John Baksi, Nicola Whiffin, Francesco Mazzarotto, Geraldine Sloane, Paul J. R. Barton, Sanjay K. Prasad & James S. Ware

  4. National Heart and Lung Institute, Imperial College London, London, UK

    Catherine Francis, Rachel J. Buchan, A. John Baksi, Nicola Whiffin, Francesco Mazzarotto, Geraldine Sloane, Paul J. R. Barton, Stuart A. Cook, Sanjay K. Prasad & James S. Ware

  5. MRC London Institute of Medical Sciences, Imperial College London, London, UK

    Xiao Xu, Antonio de Marvao, Nicola Whiffin, Stuart A. Cook, Declan P. O’Regan & James S. Ware

  6. Department of Clinical Genetics, University of Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands

    Alexa M. C. Vermeer & J. Peter van Tintelen

  7. European Reference Network for Rare and Low Prevalence Complex Diseases of the Heart (ERN GUARD-HEART) https://guardheart.ern-net.eu/

    Alexa M. C. Vermeer, Yigal M. Pinto, Philippe Charron, Arthur A. M. Wilde & Connie R. Bezzina

  8. Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK

    Andrew R. Harper & Hugh Watkins

  9. Wellcome Centre for Human Genetics, Oxford, UK

    Andrew R. Harper & Hugh Watkins

  10. Department of Cardiology, Thoraxcenter, Erasmus University Medical Center, Rotterdam, the Netherlands

    Roy Huurman, Hannah G. van Velzen & Michelle Michels

  11. Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

    Edgar T. Hoorntje, Wouter P. te Rijdt & Imke Christiaans

  12. Netherlands Heart Institute, Utrecht, the Netherlands

    Edgar T. Hoorntje & Wouter P. te Rijdt

  13. Department of Clinical Genetics, Thoraxcenter, Erasmus University Medical Center, Rotterdam, the Netherlands

    Marjon A. van Slegtenhorst

  14. Department of Psychiatry, University of Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands

    Jentien M. Vermeulen & Karin J. H. Verweij

  15. Data Science Institute, Imperial College London, London, UK

    Wenjia Bai

  16. Department of Brain Sciences and UK Dementia Research Institute at Imperial College London, Hammersmith Hospital, Imperial College London, London, UK

    Wenjia Bai, Hideaki Suzuki & Paul M. Matthews

  17. Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands

    Jacco C. Karper & Rudolf A. de Boer

  18. Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands

    Jan H. Veldink

  19. Institute for Cardiomyopathies, Heidelberg Heart Center, University of Heidelberg, Heidelberg, Germany

    Elham Kayvanpour & Benjamin Meder

  20. DZHK (German Center for Cardiovascular Research), Berlin, Germany

    Elham Kayvanpour

  21. Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy

    Francesco Mazzarotto

  22. Cardiomyopathy Unit, Careggi University Hospital, Florence, Italy

    Francesco Mazzarotto

  23. Department of Cardiovascular Medicine, Tohoku University Hospital, Seiryo, Aoba, Sendai, Japan

    Hideaki Suzuki

  24. Tohoku Medical Megabank Organization, Tohoku University, Seiryo, Aoba, Sendai, Japan

    Hideaki Suzuki

  25. The Francis Crick Institute, London, UK

    Deborah Schneider-Luftman

  26. Department of Epidemiology and Biostatistics, Imperial College London, London, UK

    Deborah Schneider-Luftman & Paul Elliott

  27. Service de biochimie métabolique, UF de cardiogénétique et myogénétique moléculaire et cellulaire, APHP, Hôpital Pitié-Salpêtrière, Paris, France

    Pascale Richard & Flavie Ader

  28. INSERM, UMR_S 1166 and ICAN Institute for Cardiometabolism and Nutrition, Faculté de Médecine, Sorbonne Université, Paris, France

    Pascale Richard, Flavie Ader, Eric Villard & Philippe Charron

  29. Faculté de Pharmacie, Université de Paris, Paris, France

    Flavie Ader

  30. Institute of Human Genetics, Helmholtz Zentrum Muenchen, Neuherberg, Germany

    Peter Lichtner & Thomas Meitinger

  31. Klinikum rechts der Isar der TU Muenchen School of Medicine, Institute of Human Genetics, Munich, Germany

    Thomas Meitinger

  32. DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany

    Thomas Meitinger

  33. Department of Clinical Epidemiology, Biostatistics and Bioinformatics, University of Amsterdam, Amsterdam Public Health (APH), Amsterdam UMC, Amsterdam, the Netherlands

    Michael W. T. Tanck

  34. Department of Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands

    J. Peter van Tintelen

  35. Department of Medicine and Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada

    Andrew Thain, David McCarty, Robert A. Hegele & Jason D. Roberts

  36. Montreal Heart Institute Research Center, Faculty of Medicine, Université de Montréal, Montreal, Québec, Canada

    Marie-Pierre Dubé, Jean-Claude Tardif & Guillaume Lettre

  37. Department of Cardiology, University of Amsterdam, Heartcenter, Amsterdam UMC, Amsterdam, the Netherlands

    S. Matthijs Boekholdt

  38. Institute of Health Informatics, University College London, London, UK

    R. Thomas Lumbers

  39. Health Data Research UK, Gibbs Building, London, UK

    R. Thomas Lumbers

  40. Barts Heart Centre, Saint Bartholomew’s Hospital, London, UK

    R. Thomas Lumbers

  41. Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands

    Folkert W. Asselbergs

  42. Institute of Cardiovascular Science and Institute of Health Informatics, Faculty of Population Health Sciences, University College London, London, UK

    Folkert W. Asselbergs

  43. National Heart Research Institute Singapore, National Heart Center Singapore, Singapore, Singapore

    Stuart A. Cook

  44. Cardiovascular and Metabolic Disorders Program, Duke‐National University of Singapore Medical School, Singapore, Singapore

    Stuart A. Cook

  45. Department of Physiology, Amsterdam Cardiovascular Sciences, Amsterdam UMC, Amsterdam, the Netherlands

    Jolanda van der Velden

  46. Département de Génétique, Centre de référence des maladies cardiaques héréditaires ou rares, APHP, Hôpital Pitié-Salpêtrière, Paris, France

    Philippe Charron

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  1. Rafik Tadros
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  2. Catherine Francis
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  3. Xiao Xu
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  4. Alexa M. C. Vermeer
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  5. Andrew R. Harper
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  12. Hannah G. van Velzen
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  18. Najim Lahrouchi
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  19. Leander Beekman
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  20. Jacco C. Karper
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Contributions

R.T., C.F., A.M.C.V., J.M.V., W.B., N.L., P.E., E.V., M.W.T.T., J.P.v.T., P.J.R.B., S.A.C., S.K.P., J.v.d.V., K.J.H.V., G.L., B.M., P.C., I.C., M.M., A.A.M.W., H.W., P.M.M., J.S.W. and C.R.B. conceived or designed elements of the study. R.T., C.F., X.X., A.M.C.V., A.R.H., R.H., K.K.B., R.W., E.T.H., W.P.t.R., R.J.B., H.G.v.V., M.A.v.S., J.M.V., J.A.O., W.B., A.d.M., L.B., J.C.K., J.H.V., E.K., A.P., A.J.B., N.W., F.M., G.S., H.S., D.S.-L., P.R., F.A., E.V., P.L., T.M., A.T., D.M., R.A.H., J.D.R., J.A., M.-P.D., J.C.-T., G.G., P.L.L’A., P.G., J.-C.T., S.M.B., R.T.L., F.W.A., P.J.R.B., S.A.C., S.K.P., D.P.O’R., M.T., G.L., Y.M.P., B.M., P.C., R.A.d.B., M.M., A.A.M.W., H.W., J.S.W. and C.R.B. acquired, analyzed or interpreted data. R.T., C.F., X.X., R.W., J.A.O., W.B., J.S.W. and C.R.B. drafted the manuscript. All authors critically revised the manuscript for important intellectual content and approved the final version.

Corresponding authors

Correspondence to Rafik Tadros, James S. Ware or Connie R. Bezzina.

Ethics declarations

Competing interests

M.-P.D. is author on a patent pertaining to pharmacogenomics-guided CETP inhibition (US20170233812A1), has a minor equity interest in DalCor and has received honoraria from Dalcor and Servier and research support (access to samples and data) from AstraZeneca, Pfizer, Servier, Sanofi and GlaxoSmithKline. J.-C.T. has received research grants from Amarin, AstraZeneca, DalCor, Esperion, Ionis, Sanofi and Servier; honoraria from AstraZeneca, DalCor, HLS, Sanofi and Servier; holds minor equity interest in DalCor; and is an author of a patent on pharmacogenomics-guided CETP inhibition (US20170233812A1). B.M. has received research funding from Siemens Healtheneers, Daiichi Sankyo. The UMCG, which employs R.A.d.B., has received research grants and/or fees from AstraZeneca, Abbott, Bristol-Myers Squibb, Novartis, Novo Nordisk and Roche. R.A.d.B. received speaker fees from Abbott, AstraZeneca, Novartis and Roche. HW is a consultant for Cytokinetics. P.M.M. receives an honorarium as Chair of the UKRI Medical Research Council Neuroscience and Mental Health Board. He acknowledges consultancy fees from Adelphi Communications, MedScape, Neurodiem, Nodthera, Biogen, Celgene and Roche. He has received speakers’ honoraria from Celgene, Biogen, Novartis and Roche, and has received research or educational funds from Biogen, GlaxoSmithKline and Novartis. He is paid as a member of the Scientific Advisory Board for Ipsen Pharmaceuticals. J.S.W. has received research support and consultancy fees from Myokardia, Inc.

Additional information

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Extended data

Extended Data Fig. 1 Manhattan and QQ plots of DCM GWAS and MTAG.

a,b, Summary results of the dilated cardiomyopathy (DCM) GWAS meta-analysis of 5,521 cases and 397,323 controls shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using summary statistics of three previously published DCM GWAS, and multi-trait analysis results (b) were obtained using MTAG for DCM, including GWAS for hypertrophic cardiomyopathy (HCM) and nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.028 (single-trait) and 1.049 (MTAG). Numbering of signals as shown in Supplementary Table 7. Black numbers refer to loci reaching the statistical significance threshold in single-trait analysis, while red numbers refer to loci only reaching statistical significance in the multi-trait analysis. The low density of association signals in the single-trait analysis (a) is attributable to the inclusion of a large sample size study that used a low density array (Illumina Infinium HumanExome BeadChip; Supplementary Table 5).

Extended Data Fig. 2 Manhattan and QQ plots of LV ejection fraction GWAS and MTAG.

a,b, Summary results of the left ventricular ejection fraction (LVEF) GWAS in the UK Biobank (n = 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT–LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.041 (single-trait) and 1.049 (MTAG). Numbering of loci as shown in Supplementary Table 8. Black numbers refer to loci reaching the statistical significance threshold in any single-trait analysis, while red numbers refer to loci only reaching statistical significance in the multi-trait analysis.

Extended Data Fig. 3 Manhattan and QQ plots of LV concentricity GWAS and MTAG.

a,b, Summary results of the left ventricular concentricity index (LVconc) GWAS in the UK Biobank (n = 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). LVconc is defined as the ratio of left ventricular mass to the left ventricular end-diastolic volume. Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.06 (single-trait) and 1.084 (MTAG). Numbering of signals as shown in Supplementary Table 8. Black numbers refer to loci reaching the statistical significance threshold in any single-trait analysis, while red numbers refer to loci only reaching statistical significance in the multi-trait analysis.

Extended Data Fig. 4 Manhattan and QQ plots of LV mass GWAS and MTAG.

a,b, Summary results of the left ventricular mass (LVM) GWAS in the UK Biobank (n = 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.081 (single-trait) and 1.071 (MTAG). Numbering of signals as shown in Supplementary Table 8.

Extended Data Fig. 5 Manhattan and QQ plots of LV end-diastolic volume GWAS and MTAG.

a,b, Summary results of the left ventricular end-diastolic volume (LVEDV) GWAS in the UK Biobank (N=19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.076 (single-trait) and 1.078 (MTAG). Numbering of signals as shown in Supplementary Table 8. Black numbers refer to loci reaching the statistical significance threshold in any single-trait analysis, while red numbers refer to loci only reaching statistical significance in the multi-trait analysis.

Extended Data Fig. 6 Manhattan and QQ plots of LV end-systolic volume GWAS and MTAG.

Summary results of the left ventricular end-systolic volume (LVESV) GWAS in the UK Biobank (n= 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.069 (single-trait) and 1.081 (MTAG). Numbering of signals as shown in Supplementary Table 8.

Extended Data Fig. 7 Manhattan and QQ plots of LV global circumferential strain GWAS and MTAG.

a,b, Summary results of the left ventricular global circumferential strain (straincirc) GWAS in the UK Biobank (N=19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.046 (single-trait) and 1.061 (MTAG). Numbering of signals as shown in Supplementary Table 8.

Extended Data Fig. 8 Manhattan and QQ plots of LV global radial strain GWAS and MTAG.

a,b, Summary results of the left ventricular global radial strain (strainrad) GWAS in the UK Biobank (n = 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.049 (single-trait) and 1.057 (MTAG). Numbering of signals as shown in Supplementary Table 8. Black numbers refer to loci reaching the statistical significance threshold in any single-trait analysis, while red numbers refer to loci only reaching statistical significance in the multi-trait analysis.

Extended Data Fig. 9 Manhattan and QQ plots of LV global longitudinal strain GWAS and MTAG.

a,b, Summary results of the left ventricular global longitudinal strain (strainlong) GWAS in the UK Biobank (n = 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10−8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.040 (single-trait) and 1.059 (MTAG). Numbering of signals as shown in Supplementary Table 8.

Extended Data Fig. 10 Manhattan and QQ plots of LV mean wall thickness GWAS and MTAG.

a,b, Summary results of the mean left ventricular wall thickness (meanWT) GWAS in the UK Biobank (n = 19,260) shown as Manhattan plots for the single-trait (a) and the multi-trait analyses (MTAG; b). Single-trait analysis (a) consisted of a fixed-effects meta-analysis of case–control GWAS using a linear mixed model (BOLT-LMM), and multi-trait analysis results (b) were obtained using MTAG including summary statistics for all nine left ventricular (LV) traits. Red dashed line shows the significance threshold of P = 1 × 10-8. Quantile-quantile (QQ) plots shown as inserts in corresponding panels. Genomic inflation (λ) = 1.065 (single-trait) and 1.072 (MTAG). Numbering of signals as shown in Supplementary Table 8.

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Supplementary Information

Supplementary Figs. 1–10 and Note

Reporting Summary

Supplementary Tables

Supplementary Tables 1–21

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Tadros, R., Francis, C., Xu, X. et al. Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect. Nat Genet 53, 128–134 (2021). https://doi.org/10.1038/s41588-020-00762-2

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