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Polygenic Susceptibility in Peripartum, Alcohol-Induced, and Cancer Therapy–Related Cardiomyopathies

  • Dimitri J. Maamari
  • , Kiran J. Biddinger
  • , Sean J. Jurgens
  • , Joel T. Rämö
  • , Liam Gaziano
  • , Alice Zheng
  • , Saketh P. Challa
  • , Dolphurs Hayes
  • , Carlos A. Gongora
  • , Seung Hoan Choi
  • , Kyong-Mi Chang
  • , Philip S. Tsao
  • , Zoltan Arany
  • , Paaladinesh Thavendiranathan
  • , Jennifer E. Huffman
  • , Akl C. Fahed
  • , Amy A. Sarma
  • , Tomas G. Neilan
  • , Amit V. Khera
  • , Patrick T. Ellinor
  • Krishna G. Aragam*
*Corresponding author for this work
  • Broad Institute of MIT and Harvard
  • University of Texas Southwestern Medical Center
  • Harvard University
  • Princeton University
  • Amsterdam UMC
  • University of Helsinki
  • Emory University
  • Albert Einstein College of Medicine
  • VA Medical Center
  • University of Pennsylvania
  • Department of Veterans Affairs
  • Stanford University
  • Peter Munk Cardiac Centre
  • Massachusetts General Hospital
  • Brigham and Women’s Hospital
  • Verve Therapeutics

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

IMPORTANCE Rare monogenic variants linked to nonischemic dilated cardiomyopathy (DCM) are enriched among individuals with secondary cardiomyopathies, such as peripartum (PPCM), alcohol-induced (ACM), and cancer therapy–related (CCM) cardiomyopathies. However, it remains unclear whether a polygenic predisposition to DCM also contributes to these conditions. OBJECTIVE To assess the association of a DCM polygenic score with PPCM, ACM, and CCM, and to evaluate the contributions of monogenic and polygenic susceptibilities to these secondary cardiomyopathies. DESIGN, SETTING, AND PARTICIPANTS This was a retrospective genetic association analysis of data from the Mass General Brigham (MGB) Biobank (n = 42 137, 2008-2025), with replication in the UK Biobank (n = 295 160, 2005-2010), FinnGen (n = 417 950, 2017-2025), and the Veterans Affairs Million Veteran Program (n = 516 066, 2011-2025). In MGB Biobank, medical records were reviewed to ascertain secondary cardiomyopathy cases and antecedent clinical risk factors. EXPOSURES DCM polygenic risk score and DCM monogenic variants. MAIN OUTCOMES AND MEASURES The primary outcomes were the association of the DCM polygenic risk score with PPCM, ACM, and CCM and the prevalence of monogenic variants and a high polygenic score among individuals with cardiomyopathy. RESULTS The mean (SD) age in the MGB Biobank was 55.7 (17.0) years at enrollment, and 24 551 (58.3%) were female. Across the 4 study cohorts, 3414 individuals with secondary cardiomyopathy were identified, including 70 with PPCM, 2281 with ACM, and 1063 with CCM. The DCM polygenic score was associated with PPCM (odds ratio [OR], 1.82 per SD; 95% CI, 1.43-2.30), ACM (OR, 1.56; 95% CI,1.34-1.82), and CCM (OR, 1.64; 95% CI,1.24-2.15) (all with P < .001). Monogenic variants were enriched but present in 7 of 113 individuals with medical record–reviewed cardiomyopathy in MGB, while 66 had a high polygenic score, which conferred an approximately 3-fold increased odds of cardiomyopathy. Most individuals with cardiomyopathy lacked antecedent clinical risk factors. CONCLUSIONS AND RELEVANCE In this cohort study, individuals with PPCM, ACM, and CCM were enriched for monogenic DCM variants and a high DCM polygenic score, suggesting a shared genetic susceptibility influenced by distinct environmental precipitants. These findings support a shared genetic architecture between secondary cardiomyopathies and DCM, although additional work with larger numbers of individuals with cardiomyopathy is needed to confirm these findings.

Original languageEnglish
Pages (from-to)1138-1146
Number of pages9
JournalJAMA cardiology
Volume10
Issue number11
Early online date2025
DOIs
Publication statusPublished - 12 Nov 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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