Distinct Subgroups in Hypertrophic Cardiomyopathy in the NHLBI HCM Registry
Stefan Neubauer1, Paul Kolm2, Carolyn Y Ho3
1Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom.
Journal of the American College of Cardiology
|November 9, 2019
Summary
The Hypertrophic Cardiomyopathy Registry (HCMR) study reveals distinct patient subgroups based on genetic and imaging markers. Incorporating cardiac magnetic resonance (CMR), genetic, and biomarker data can improve risk prediction in hypertrophic cardiomyopathy (HCM).
Area of Science:
- Cardiology
- Genetics
- Medical Imaging
Background:
- The Hypertrophic Cardiomyopathy Registry (HCMR) is a prospective study funded by the National Heart, Lung, and Blood Institute.
- It includes 2,755 patients with hypertrophic cardiomyopathy (HCM) from 44 sites across 6 countries.
Purpose of the Study:
- To enhance risk prediction models for HCM by integrating cardiac magnetic resonance (CMR) imaging, genetic data, and specific biomarkers.
- To identify distinct patient subgroups within the HCMR cohort.
Main Methods:
- Collected demographic and echocardiographic data.
- Performed CMR including cine imaging, late gadolinium enhancement (LGE) for fibrosis, and T1 mapping for interstitial fibrosis.
- Assessed biomarkers N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (cTnT), alongside genetic analysis.
Main Results:
- The HCMR cohort (n=2,755) showed characteristics of low-risk HCM, with 93% having mild functional limitation.
- Sarcomere mutation-positive patients often had reverse septal curvature, more fibrosis (LGE, extracellular volume), and less outflow tract obstruction.
- Sarcomere mutation-negative patients tended to have isolated basal septal hypertrophy, less fibrosis, and more outflow tract obstruction. Biomarker levels correlated with fibrosis extent.
Conclusions:
- The HCMR population can be broadly categorized into two groups based on genetic and imaging findings.
- These subgroups exhibit different morphological and obstructive patterns, suggesting potential differences in disease progression.
- Further analysis of this cohort will refine risk prediction models for HCM by incorporating comprehensive data.
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