Single-nucleus RNA sequencing of 47 HCM patient cardiac tissues revealed multicellular, genotype-associated remodeling programs spanning cardiomyocyte hypertrophy, proarrhythmogenic states, fibrosis, and vascular dysfunction across disease stages.
Key Findings
Results
Pathogenic variant-positive early-stage HCM samples showed reduced cardiomyocyte abundance and expansion of a proarrhythmogenic cardiomyocyte state.
Single-nucleus RNA sequencing was performed on cardiac tissues from 47 patients with HCM spanning obstructive HCM with preserved systolic function and end-stage HCM.
Comparisons were made against nonfailing donor hearts and dilated cardiomyopathy hearts.
The proarrhythmogenic cardiomyocyte state was specifically enriched in pathogenic variant-positive (sarcomere gene variant) early-stage HCM.
Reduced cardiomyocyte abundance was identified as a genotype-specific feature in early-stage disease.
Results
PRR16 (proline-rich 16) was identified as a cardiomyocyte growth-associated gene in HCM.
PRR16 expression was increased in HCM cardiomyocytes based on single-nucleus RNA sequencing data.
Increased PRR16 expression was validated by RNA in situ hybridization in cardiac tissue.
PRR16 expression was also validated in a human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) HCM model.
PRR16 was identified through transcriptional programs associated with cardiomyocyte hypertrophy.
Results
Fibroblast compositional shifts in HCM were associated with profibrotic activation and adverse extracellular matrix remodeling.
HCM samples exhibited shifts in fibroblast subpopulations consistent with profibrotic activation.
Reduced expression of collagen IV genes (COL4A1 and COL4A2) was detected in HCM samples.
Ultrastructural basement membrane abnormalities were identified accompanying the reduced COL4A1/COL4A2 expression.
These fibroblast changes were identified across disease stages of HCM.
Results
HCM samples exhibited extensive vascular alterations including shifts in endothelial cell subpopulations, reduced pericyte abundance, and increased lymphangiogenic VEGF-C signaling.
Endothelial cell subpopulation shifts were identified by single-nucleus RNA sequencing in HCM cardiac tissues.
Reduced pericyte abundance was identified as suggestive of microvascular dysfunction in HCM.
Increased vascular endothelial growth factor C (VEGF-C) signaling was detected, indicating increased lymphangiogenic activity.
These vascular alterations were present across HCM disease stages and are proposed to underlie microvascular dysfunction.
Results
Machine learning approaches distinguished HCM from dilated cardiomyopathy and accurately predicted genotype status in early-stage HCM from cell type-resolved transcriptional profiles.
Both unsupervised and supervised machine learning approaches were applied to the single-nucleus RNA sequencing data.
Genotype status (pathogenic variant-positive vs. variant-negative) was accurately predicted in early-stage HCM samples.
The prediction was based on cell type-resolved transcriptional profiles, revealing widespread genotype-driven remodeling.
The models also distinguished HCM from dilated cardiomyopathy, demonstrating disease-specific transcriptional signatures.
Results
Transcriptional programs associated with cardiomyocyte hypertrophy, fibrosis, and vascular remodeling were identified across HCM disease stages and genotypes.
The study included 47 HCM patients spanning obstructive HCM with preserved systolic function and end-stage HCM.
Comparator groups included nonfailing donor hearts and dilated cardiomyopathy hearts.
Pathogenic sarcomere gene variants were present in a subset of HCM patients, enabling genotype-stratified analyses.
Multicellular remodeling programs were identified spanning cardiomyocytes, fibroblasts, endothelial cells, and pericytes.
Background
Patients with unexplained HCM (pathogenic variant-negative) exhibited comparable cardiac abnormalities to sarcomere variant-positive HCM but with fewer adverse events.
The study compared pathogenic variant-positive and variant-negative HCM patient groups.
Variant-negative HCM patients showed similar gross abnormalities including wall thickening, hypercontractility, diastolic dysfunction, and fibrosis.
Adverse event rates were lower in variant-negative HCM compared to sarcomere gene variant-positive HCM.
This research suggests that hypertrophic cardiomyopathy (HCM), a condition where the heart muscle becomes abnormally thick, involves widespread changes across multiple heart cell types that differ depending on both disease stage and the underlying genetic cause. By analyzing gene activity in individual cells from heart tissue samples of 47 HCM patients—ranging from early obstructive disease to end-stage heart failure—alongside donor and dilated cardiomyopathy hearts, the researchers created a detailed molecular map of how the heart changes in HCM. Patients who carry a disease-causing mutation in sarcomere genes (the proteins that make the heart contract) showed specific changes not seen in HCM patients without an identified genetic cause, including a dangerous shift in heart muscle cells toward a state associated with abnormal heart rhythms.
The study uncovered several previously underappreciated disease mechanisms. A gene called PRR16 was newly linked to abnormal heart muscle cell growth in HCM and was confirmed in both tissue samples and lab-grown heart cells derived from stem cells. The connective tissue-producing cells (fibroblasts) in HCM hearts shifted toward a pro-scarring state, while also producing less of a key structural protein (collagen IV) that supports the basement membrane surrounding heart cells. The blood vessel network in HCM hearts also showed significant disruption, with fewer stabilizing pericyte cells (suggesting poor small vessel function) and increased signals for lymphatic vessel growth.
This research suggests that HCM is not a single uniform disease but a collection of related conditions driven by distinct molecular programs depending on the patient's genetic makeup and how far the disease has progressed. The ability to use computer-based machine learning to identify a patient's genetic status purely from gene expression patterns in heart cells points toward the potential for more precise molecular classification of HCM. These findings may help explain why some HCM patients experience dangerous arrhythmias, progressive scarring, or heart failure, and could guide future efforts to develop treatments targeting specific disease mechanisms.
Adami E, Kim Y, Zheng S, Shvetsov N, Losert C, Maatz H, et al.. (2026). The molecular landscape of hypertrophic cardiomyopathy across disease stages and genotypes.. Science translational medicine. https://doi.org/10.1126/scitranslmed.aea2747