High-resolution transcriptomic profiling of the heart during chronic stress reveals cellular drivers of cardiac fibrosis and hypertrophy

Abstract

Background: Cardiac fibrosis is a key antecedent to many types of cardiac dysfunction including heart failure. Physiological factors leading to cardiac fibrosis have been recognized for decades. However, the specific cellular and molecular mediators that drive cardiac fibrosis, and the relative impact of disparate cell populations on cardiac fibrosis, remain unclear. Methods:We developed a novel cardiac single-cell transcriptomics strategy to characterize the cardiac cellulome-the network of cells that forms the heart. This method was utilized to profile the cardiac cellular ecosystem in response to two weeks of continuous administration of Angiotensin II, a pro-fibrotic stimulus which drives pathological cardiac remodeling. Results: This analysis uncovered multiple cell populations contributing to pathological remodeling of the extracellular matrix of the heart. Two phenotypically distinct fibroblast populations emerged after induction of tissue stress to promote fibrosis in the absence of smooth muscle actin-expressing myofibroblasts, a key pro-fibrotic cell population. Further, the cellular responses to Angiotensin II and the relative abundance of fibrogenic cells were sexually dimorphic. Conclusions: These results offer a valuable resource for exploring the cardiac cellular landscape in health and after chronic cardiovascular stress. These data provide insights into the cellular and molecular mechanisms that promote pathological remodeling of the mammalian heart, highlighting early transcriptional changes which precede chronic cardiac fibrosis.35

Prognostic value of cartilage intermediate layer protein 1 in chronic heart failure

“…Similar results have been observed in human myocardial tissues with AMI and HF 11,13 . In a single‐cell transcriptomic analysis of cardiac fibrosis, fibroblast‐CILP emerged as the most abundant fibroblast subpopulation 9 . In a mouse model of transverse aortic constriction, ventricular remodelling and dysfunction were significantly aggravated by CILP‐1 knockdown but alleviated by CILP‐1 delivery 8 …”

“…All three protein variants have been reported to be functional; in particular, F ‐ CILP‐1 and N‐CILP‐1 can directly bind to transforming growth factor‐β1 (TGF‐β1) via the thrombospondin type 1 domain and inhibit its signalling pathway 7,8 . Of note, a growing number of studies suggest that CILP‐1 is expressed in cardiac fibroblasts and exerts anti‐fibrotic effects by interfering with TGF‐β1 signalling 7,9–11 . Myocardial CILP‐1 protein was found to be significantly up‐regulated in animal models of left ventricular pressure overload, 8 acute myocardial infarction (AMI), 11 ischaemia/reperfusion injury, 12 and angiotensin II treatment 9 .…”

“…7,8 Of note, a growing number of studies suggest that CILP-1 is expressed in cardiac fibroblasts and exerts anti-fibrotic effects by interfering with TGF-β1 signalling. 7,[9][10][11] Myocardial CILP-1 protein was found to be significantly up-regulated in animal models of left ventricular pressure overload, 8 acute myocardial infarction (AMI), 11 ischaemia/reperfusion injury, 12 and angiotensin II treatment. 9 Similar results have been observed in human myocardial tissues with AMI and HF.…”

“…7,[9][10][11] Myocardial CILP-1 protein was found to be significantly up-regulated in animal models of left ventricular pressure overload, 8 acute myocardial infarction (AMI), 11 ischaemia/reperfusion injury, 12 and angiotensin II treatment. 9 Similar results have been observed in human myocardial tissues with AMI and HF. 11,13 In a single-cell transcriptomic analysis of cardiac fibrosis, fibroblast-CILP emerged as the most abundant fibroblast subpopulation.…”

Single nucleus RNA-sequencing reveals altered intercellular communication and dendritic cell activation in nonobstructive hypertrophic cardiomyopathy

“…Assignment of cell identity to each cluster was performed using four separate analyses. Expression of known cell-specific gene markers were used to identify major cell types, as done previously 13, 15, 24, 35 . The top 20-30 differentially expressed genes in each cluster were also compared with cell type gene expression markers from the PanglaoDB database https://panglaodb.se 19 to independently assign cell type.…”