A range of different cardiovascular disorders can result in heart failure, leading scientists to wonder whether mutations in various genes lead to heart failure in different ways.
An international research team co-led by Christine E. Seidman, MD, director of the Cardiovascular Genetics Center at Brigham and Women’s Hospital, published in Science, has confirmed this hypothesis in patients with cardiomyopathy. They found that molecular and cellular mechanisms of heart failure in patients with dilated cardiomyopathy (DCM) or arrhythmogenic cardiomyopathy (ACM) were determined by the specific gene variant each individual carried. The paper is the first comprehensive single-cell analysis of cardiac cells from healthy and failing hearts.
The researchers studied left and right ventricular tissue explanted from 61 patients with heart failure before any mechanical support and from 18 healthy donors. They performed single-nucleus RNA sequencing, focusing on tissue samples with pathogenic variants in DCM-related genes (LMNA, RBM20, and TTN), pathogenic variants in an ACM-related gene (PKP2), or no pathogenic variants.
Genotype-specific Transcripts and Cell States
From 881,081 nuclei isolated, the researchers identified 10 major cell types and 71 distinct transcriptional states. Both DCM and ACM tissues showed significant depletion of cardiomyocytes and increased endothelial and immune cells.
A series of genotype-specific differences were evident in DCM hearts. For example, in patients with mutated RBM20, fibrosis was not associated with an increase in the number of cardiac fibroblasts, as expected. Instead, there was an increase in the number of fibroblasts specializing in the production of extracellular matrix.
Genotype-stratified analyses identified multiple other transcriptional changes that were shared only among hearts harboring pathogenic variants or that were distinctive for individual DCM and ACM genotypes and their subsets.
The researchers also observed genotype-related changes in intercellular signaling and communications. They pinpointed specific cardiac cell lineages that express genes with common polymorphisms identified in validated association studies of DCM.
A Novel Algorithm
Using machine learning, the team developed an algorithm that predicts the genotype of each cardiac sample based on specific patterns of molecular changes in various cell types. This reinforces the idea that genotypes activate very specific heart failure pathways.
Toward Personalized Therapy
The team has made all results from this study available to the scientific community online. The database of potential therapeutic targets is expected to facilitate mechanistic studies that lead to a more individualized diagnosis, prevention, and treatment of cardiomyopathies and heart failure.