Dataset Information

Single-Cell Transcriptomic Analysis Reveals Differential Cell Subpopulations and Distinct Phenotype Transition in Normal and Acute Dissected Ascending Aorta

ABSTRACT: Background: Acute thoracic aortic dissection (ATAD) is a fatal condition characterized by tear of intima and formation of false lumen whereby leading to the rupture of aorta. To better understand the potential mechanism of ATAD, we analyzed characterization of different cell types between ATAD and control group and predicted interactions among different cell types which might promote the progression of ATAD. Methods: Single-cell RNA sequencing (scRNA-seq) was performed including 5 patients with ATAD and 4 healthy controls. Cells were digested from ascending aortic tissues and subpopulations of most cell types were identified on the basis of scRNA-seq data. The gene expression profiles of each cell type and related changes between ATAD and control group were analyzed via bioinformatic analysis. We also predicted potential interaction among different cell types and verified the results by immunohistochemistry (IHC) and immunofluorescence (IF). Results: We got 8 cell types from human ascending aorta and 50 subpopulations were identified after re-clustering including vascular smooth muscle cells (VSMCs), endothelial cells, fibroblasts, neutrophils, monocytes and macrophages. Higher proportion of synthetic VSMCs, dysfunctional neutrophils and monocytes were seen in ATAD group compared with control group. Next, we predicted cell differentiation trajectory of VSMCs, fibroblasts and neutrophils via CytoTRACE, then identified subpopulations with higher differentiation potential. Moreover, the hub genes of VSMCs, fibroblasts and neutrophils were examined by weighted gene co-expression network analysis. Further analysis revealed that six transmembrane epithelial antigen of prostate 4 metalloreductase (STEAP4) might be a new marker for isolation of synthetic VSMCs by verification with IHC and IF. We also found synthetic VSMCs-derived C-X-C motif chemokine ligand 12 (CXCL12) might interact with neutrophils and fibroblasts via combination with C-X-C motif chemokine receptor 4 (CXCR4) and atypical chemokine receptor 3 (ACKR3), respectively, which might recruit neutrophils and induce transdifferentitation of FBs into synthetic VSMCs. Conclusion: In this study, we demonstrated integrative composition of different cell types in normal and dissected human ascending aorta and identified a new marker favorable to isolation of synthetic VSMCs. Furthermore, we also proposed a potential mechanism that synthetic VSMCs could interact with neutrophils and fibroblasts via CXCL12-CXCR4/ACKR3 axis whereby deteriorating the progression of ATAD. In total, these findings in our study might provide new insights to better understand the development and progression of ATAD.

ORGANISM(S): Homo sapiens

PROVIDER: GSE189795 | GEO | 2024/11/26

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:The ascending aorta is a common site for age-related aortic diseases. Therefore, age-related changes in the cellular composition and development in the normal human ascending aorta tissue is associated with the pathogenesis of aortic diseases. In this study, we performed single-cell transcriptome sequencing of the normal ascending aorta tissues from 6 organ donors of different ages, namely, the young group (3 months, 1 year, 3 years, and 12 years) and the old group (57 years and 58 years), and evaluated the changes in the composition of the cell types, cellular phenotypes, and the cell-cell communication. The single-cell sequencing data analysis of 65,470 cells from the 6 donor aortic wall specimens identified ten cell types (27 high-resolution subtypes of cells), including endothelial cells, smooth muscle cells, fibroblasts, mesenchymal cells, mesenchymal-fibroblast cells, macrophages, Schwann cells, T cells, natural killer cells, and B cells. In comparison with the young group, the aortic wall tissue of the old group showed significant reduction in the proportion of endothelial cells (young vs. old, 22.47% vs. 10.37%), smooth muscle cells (20.40% vs. 18.50%), fibroblasts (30.21% vs. 13.29%), and mesenchymal cells (5.12% vs 1.55%) and significant increase in the proportion of macrophages (10.94% vs. 17.02%) and T cells (3.80% vs. 26.01%). Functional enrichment analysis of the ligand-receptor pairs between the macrophages and the T cells demonstrated enrichment of pathways related to inflammation and endocrine resistance in the elderly group. Immunohistochemical analysis of the aortic tissue from the 58-year-old donor showed higher expression of the M2 macrophage marker, CD163, in comparison with the aortic tissue of the 12-year-old donor. This confirmed the results of the single-cell sequencing analysis. In summary, single-cell sequencing analysis of the normal ascending aorta tissues from multiple donors of different ages demonstrated significant age-related changes in the proportions of multiple cell types, cellular phenotypes, and cell-cell communications. These age-related changes are likely involved in the pathogenesis of age-related aortic diseases.

Project description:Stanford type A aortic dissection (STAAD) is an aortic degenerative remodeling disease carrying an exceedingly high mortality worldwide. The irreversible weakening, dilatation and dissection of the ascending aorta contributes to circulatory failure and premature death. Dissections manifest distinct patterns in both clinical presentations and histophathological features during disease temporal transition. Therefore, we delineate a full repertoire of cellular landscape and dynamic interplay in distinct temporal patterns of STAAD using single-cell transcriptomics for comprehensively understanding of disease features and temporal evolution. We performed single-cell RNA sequencing with ascending aortic tissues from 14 participants, including 9 patients with STAAD (4 acute, 3 subacute, and 2 chronic) and 5 control subjects. Unsupervised clustering was performed based on transcriptional profiles of highly variable genes. Single T cell analysis by RNA sequencing and TCR tracking (STARTRACT) was performed to quantitatively delineate the developmental trajectory of aortic T lymphocytes. On the basis of molecular signatures and distinct disease patterns, we draw a spatiotemporal map of disease subtype-specific alterations and complex interplay among cell types. The transcriptional profiles of 93,397 individual cells enable us to identify 12 major cell types and 37 subtypes in human ascending aorta. Comparisons of transcriptomes of disease subtypes reveal striking stage-specific cellular diversity and transcriptional dynamics in phenotypic switch, vascular inflammation, cell death and survival, extracellular matrix remodeling, and cell-cell interactions during disease temporal transition. Modeling of developmental trajectory revealed that the defects in mitochondrial OXPHOS drives phenotypic switch of contractile smooth muscle cells to synthetic myofibroblasts through AP-1 transcriptional complex. STARTRACT analysis revealed that CD8+ HSP are preferentially enriched and potentially clonally expanded in acute AD. Intersection of disease risk genes with our dataset reveals distinct gene panel in discriminating temporal-specifc AD. This compendium of transcriptome data provides valuable insights and a rich resource for understanding the cellular diversity and heterogeneity in human aorta. The distinct alterations of cell type- and disease subtype-specific spatiotemporal features will ultimately facilitate the design of more precisely tailored anti-AD therapies.

Dataset Information

Single-Cell Transcriptomic Analysis Reveals Differential Cell Subpopulations and Distinct Phenotype Transition in Normal and Acute Dissected Ascending Aorta

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets