Dilated cardiomyopathy (DCM) is a highly morbid condition affecting relatively young and active adults. With an estimated prevalence of about 1/250, DCM is one of the leading causes of heart transplantation in the world.1,2 At the morphological level, DCM is characterized by ventricular dilatation, cardiomyocyte loss and fibrotic replacement, leading to impaired contractility, heart failure, arrhythmia and conduction disorders. With sudden cardiac death or arrhythmia being sometimes the first disease manifestation, a broad clinical and genetic overlap between DCM and arrhythmic cardiomyopathy (ACM) is now recognized, making the distinction between those subgroups more trivial.3 At the molecular level, and despite tremendous progress made in the recent years regarding DCM’s underlying genetics, there is still a broad heritability gap in DCM, highlighting its genetic complexity and its marked causal heterogeneity (including a complex interaction between genetic determinants and extrinsic factors).4 Nowadays, if genetic testing can provide a molecular explanation in about 50 % of DCM patients, clinicians and geneticists are still facing the challenge of incomplete penetrance, disease heterogeneity, variable expression, and difficult variant interpretation. In this context, better molecular insights into this complex disease would be more than welcome.
The heart is a complex organ made of various cell types including cardiomyocytes, endothelial and smooth muscle cells, but also fibroblasts and inflammatory cells, which could all be implicated in the disease process. How does a pathogenic variant lead to a change in the cellular content of the heart? How does this change trigger adverse remodeling of the chambers? What is the effect of a pathogenic variant on gene expression and signaling pathways? So far, all those questions remain unanswered. Performing single cell sequencing of cardiac right- and left-ventricular samples obtained from DCM and ACM patients, Reichart et al. provided for the first time a comprehensive cellular atlas of the DCM and ACM hearts, managing to obtain data from 500000 nuclei of patients and 380000 nuclei from controls.5 By clustering the cells based on their expression profile, by stratifying expression analysis by genotype and by comparing right and left ventricular samples, the authors provide an impressive set of data. Interestingly, those data give insights not only on the cell composition of DCM and ACM hearts, but also on the functional status and the signaling state of those cells. Filling an important gap between genomic and expression data, those single cell analyzes show that DCM and ACM are characterized by a depletion in cardiomyocytes (except in LMNA cardiomyopathy), and an enrichment in endothelial and inflammatory cells (myeloid and lymphoid cells). Surprisingly, despite the presence of increased fibrosis, fibroblasts are not over-represented in neither right- nor left-ventricular samples of DCM patients, supporting a phenotypic shift of DCM fibroblasts towards a secretory rather than a proliferative phenotype. Furthermore, cell clustering analysis based on expression mapping provided a molecular signature of all the cell types present in the diseased hearts including cardiomyocytes, fibroblasts, smooth muscle cells, pericytes, inflammatory (myeloid and lymphoid) as well as neuronal and adipose cells, providing an incredible resource for future research in the field. Also, the data supports that cardiomyopathies should be seen as a “pancardiac” disease with expression changes affecting all cell types (including endocardial cells by example in the presence of PKP2 pathogenic variants). Interestingly, those expression data reinforce the role of common variants in modulating DCM phenotype. And finally, diving into the world of artificial intelligence, the authors showed that the genotype of a given patient can be predicted based on expression patterns.
Through this huge data set, this work provides the first description of the molecular heterogeneity acting at the single cell level in DCM and ACM. Understanding this complex cellular architecture, this work provides incredible insights into disease mechanisms allowing to study DCM and ACM at the single cell level, deciphering their pathogenic molecular complexity.