Precision Phenotyping of Dilated Cardiomyopathy Using Multidimensional Data

Upasana Tayal*, Job A J Verdonschot, Mark R Hazebroek, James Howard, John Gregson, Simon Newsome, Ankur Gulati, Chee Jian Pua, Brian P Halliday, Amrit S Lota, Rachel J Buchan, Nicola Whiffin, Lina Kanapeckaite, Resham Baruah, Julian W E Jarman, Declan P O'Regan, Paul J R Barton, James S Ware, Dudley J Pennell, Bouke P AdriaansSebastiaan C A M Bekkers, Jackie Donovan, Michael Frenneaux, Leslie T Cooper, James L Januzzi, John G F Cleland, Stuart A Cook, Rahul C Deo, Stephane R B Heymans, Sanjay K Prasad*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


BACKGROUND: Dilated cardiomyopathy (DCM) is a final common manifestation of heterogenous etiologies. Adverse outcomes highlight the need for disease stratification beyond ejection fraction.

OBJECTIVES: The purpose of this study was to identify novel, reproducible subphenotypes of DCM using multiparametric data for improved patient stratification.

METHODS: Longitudinal, observational UK-derivation (n = 426; median age 54 years; 67% men) and Dutch-validation (n = 239; median age 56 years; 64% men) cohorts of DCM patients (enrolled 2009-2016) with clinical, genetic, cardiovascular magnetic resonance, and proteomic assessments. Machine learning with profile regression identified novel disease subtypes. Penalized multinomial logistic regression was used for validation. Nested Cox models compared novel groupings to conventional risk measures. Primary composite outcome was cardiovascular death, heart failure, or arrhythmia events (median follow-up 4 years).

RESULTS: In total, 3 novel DCM subtypes were identified: profibrotic metabolic, mild nonfibrotic, and biventricular impairment. Prognosis differed between subtypes in both the derivation (P < 0.0001) and validation cohorts. The novel profibrotic metabolic subtype had more diabetes, universal myocardial fibrosis, preserved right ventricular function, and elevated creatinine. For clinical application, 5 variables were sufficient for classification (left and right ventricular end-systolic volumes, left atrial volume, myocardial fibrosis, and creatinine). Adding the novel DCM subtype improved the C-statistic from 0.60 to 0.76. Interleukin-4 receptor-alpha was identified as a novel prognostic biomarker in derivation (HR: 3.6; 95% CI: 1.9-6.5; P = 0.00002) and validation cohorts (HR: 1.94; 95% CI: 1.3-2.8; P = 0.00005).

CONCLUSIONS: Three reproducible, mechanistically distinct DCM subtypes were identified using widely available clinical and biological data, adding prognostic value to traditional risk models. They may improve patient selection for novel interventions, thereby enabling precision medicine.

Original languageEnglish
Pages (from-to)2219-2232
Number of pages14
JournalJournal of the American College of Cardiology
Issue number22
Publication statusPublished - 7 Jun 2022


  • Cardiomyopathies
  • Cardiomyopathy, Dilated/diagnosis
  • Creatinine
  • Female
  • Fibrosis
  • Humans
  • Male
  • Middle Aged
  • Proteomics
  • Stroke Volume
  • proteomics
  • machine learning
  • heart

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