Cardiovascular disease causes proinflammatory microvascular changes in the human right atrium

Abstract

Ischemic heart disease is the single most common cause of death worldwide with an annual death rate of over 9 million people. Genome-wide association studies have uncovered over 200 genetic loci underlying the disease, providing a deeper understanding of the causal mechanisms leading to it. However, in order to understand ischemic heart disease at the cellular and molecular level, it is necessary to identify the cell-type-specific circuits enabling dissection of driver variants, genes, and signaling pathways in normal and diseased tissues. Here, we provide the first detailed single-cell dissection of the cell types and disease-associated gene expression changes in the living human heart, using cardiac biopsies collected during open-heart surgery from control, ischemic heart disease, and ischemic and non-ischemic heart failure patients. We identify 84 cell types/states, grouped in 12 major cell types. We define markers for each cell type, providing the first extensive reference set for the live human heart. These major cell types include cardiovascular cells (cardiomyocytes, endothelial cells, fibroblasts), rarer cell types (B lymphocytes, neurons, Schwann cells), and rich populations of previously understudied layer-specific epicardial and endocardial cells. In addition, we reveal substantial differences in disease-associated gene expression at the cell subtype level, revealing arterial pericytes as having a central role in the pathogenesis of ischemic heart disease and heart failure. Our results demonstrate the importance of high-resolution cellular subtype mapping in gaining mechanistic insight into human cardiovascular disease.

Spatially resolved multiomics of human cardiac niches

“…Moreover, clinical trials showed benefit for Canakinumab in heart failure, suggesting a causal role for IL-1β in its pathogenesis 106 . Although recent studies pointed to cytokine-mediated fibroblast activation 107 and expansion of stressed CMs in ischemia 108 , the precise cellular mechanisms responsible for fibroblast activation or CM transition to a stressed status remains unclear. Our finding of inflammatory cytokine receptor expression in the vCM3_stressed cells provides a potential mechanism mediating CM susceptibility to inflammation, remodelling, and death.…”

Fibrotic Signaling in Cardiac Fibroblasts and Vascular Smooth Muscle Cells: The Dual Roles of Fibrosis in HFpEF and CAD

“…Together with the findings in mice, it points towards the conserved disease role of Gli1 in myofibroblast differentiation and adds RUNX1 as a driver in humans. On the contrary, TCF21 was not reported as a marker of activated CFs [27,36]; thus, TCF21 might be a unique driver in mouse myofibroblast differentiation or important for the early onset of disease. It will be interesting to see if CF sub-populations produce ECM with specific compositional profiles and whether these activities can be recapitulated in vitro.…”

“…Convincing human single-cell RNAseq (scRNAseq) of diseased human hearts, with sampling more than three patients and having a sufficient cell depth, is rare. A recent publication by Koenig et al laid the foundation and will hopefully be followed by two major studies this year [27,36] (bioRxiv). Interestingly, RUNX1 and Gli1 are highlighted as important transcription factors (TF) for myofibroblast differentiation [27].…”

Tailoring Cardiac Synthetic Transcriptional Modulation Towards Precision Medicine

“…This will help to exactly specify their role for targeted functional phenotyping (64). For instance, ischemic and non-ischemic human heart samples subjected to SNS yielded a catalog of cardiomyocyte and non-cardiomyocyte (vascular endothelial cells, endocardial endothelial cells, fibroblasts, mesothelial cell, smooth muscle cells, adipocytes, immune cells, and neurons) and their individual, disease-specific gene expression profile (65). The authors identified gene regulatory networks and disease driver candidates by intersection of the SNS data sets with the disease risk GWAS data (65).…”

“…For instance, ischemic and non-ischemic human heart samples subjected to SNS yielded a catalog of cardiomyocyte and non-cardiomyocyte (vascular endothelial cells, endocardial endothelial cells, fibroblasts, mesothelial cell, smooth muscle cells, adipocytes, immune cells, and neurons) and their individual, disease-specific gene expression profile (65). The authors identified gene regulatory networks and disease driver candidates by intersection of the SNS data sets with the disease risk GWAS data (65). This data extended descriptive cellular characterization of the human heart (3,41) toward understanding the precise underlying disease progression mechanisms.…”