Title | Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue. |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Li, Y, Ren, P, Dawson, A, Vasquez, HG, Ageedi, W, Zhang, C, Luo, W, Chen, R, Li, Y, Kim, S, Lu, HS, Cassis, LA, Coselli, JS, Daugherty, A, Shen, YH, LeMaire, SA |
Journal | Circulation |
Volume | 142 |
Issue | 14 |
Pagination | 1374-1388 |
Date Published | 2020 Oct 06 |
ISSN | 1524-4539 |
Keywords | Aged, Aorta, Aortic Aneurysm, Thoracic, Female, Gene Expression Profiling, Gene Expression Regulation, Genome-Wide Association Study, Humans, Male, Middle Aged, Single-Cell Analysis |
Abstract | BACKGROUND: Ascending thoracic aortic aneurysm (ATAA) is caused by the progressive weakening and dilatation of the aortic wall and can lead to aortic dissection, rupture, and other life-threatening complications. To improve our understanding of ATAA pathogenesis, we aimed to comprehensively characterize the cellular composition of the ascending aortic wall and to identify molecular alterations in each cell population of human ATAA tissues.METHODS: We performed single-cell RNA sequencing analysis of ascending aortic tissues from 11 study participants, including 8 patients with ATAA (4 women and 4 men) and 3 control subjects (2 women and 1 man). Cells extracted from aortic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster identification. ATAA-related changes were then examined by comparing the proportions of each cell type and the gene expression profiles between ATAA and control tissues. We also examined which genes may be critical for ATAA by performing the integrative analysis of our single-cell RNA sequencing data with publicly available data from genome-wide association studies.RESULTS: We identified 11 major cell types in human ascending aortic tissue; the high-resolution reclustering of these cells further divided them into 40 subtypes. Multiple subtypes were observed for smooth muscle cells, macrophages, and T lymphocytes, suggesting that these cells have multiple functional populations in the aortic wall. In general, ATAA tissues had fewer nonimmune cells and more immune cells, especially T lymphocytes, than control tissues did. Differential gene expression data suggested the presence of extensive mitochondrial dysfunction in ATAA tissues. In addition, integrative analysis of our single-cell RNA sequencing data with public genome-wide association study data and promoter capture Hi-C data suggested that the erythroblast transformation-specific related gene() exerts an important role in maintaining normal aortic wall function.CONCLUSIONS: Our study provides a comprehensive evaluation of the cellular composition of the ascending aortic wall and reveals how the gene expression landscape is altered in human ATAA tissue. The information from this study makes important contributions to our understanding of ATAA formation and progression. |
DOI | 10.1161/CIRCULATIONAHA.120.046528 |
Alternate Journal | Circulation |
PubMed ID | 33017217 |
PubMed Central ID | PMC7539140 |
Grant List | S10 OD018033 / OD / NIH HHS / United States R01 HL143359 / HL / NHLBI NIH HHS / United States T32 HL139430 / HL / NHLBI NIH HHS / United States S10 OD025240 / OD / NIH HHS / United States S10 OD023469 / OD / NIH HHS / United States R01 HL131980 / HL / NHLBI NIH HHS / United States P30 EY002520 / EY / NEI NIH HHS / United States |
Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue.
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