Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue

BACKGROUNDAscending 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 characteri...

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Veröffentlicht in:Circulation (New York, N.Y.) N.Y.), 2020-10, Vol.142 (14), p.1374-1388
Hauptverfasser: Li, Yanming, Ren, Pingping, Dawson, Ashley, Vasquez, Hernan G., Ageedi, Waleed, Zhang, Chen, Luo, Wei, Chen, Rui, Li, Yumei, Kim, Sangbae, Lu, Hong S., Cassis, Lisa A., Coselli, Joseph S., Daugherty, Alan, Shen, Ying H., LeMaire, Scott A.
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container_end_page 1388
container_issue 14
container_start_page 1374
container_title Circulation (New York, N.Y.)
container_volume 142
creator Li, Yanming
Ren, Pingping
Dawson, Ashley
Vasquez, Hernan G.
Ageedi, Waleed
Zhang, Chen
Luo, Wei
Chen, Rui
Li, Yumei
Kim, Sangbae
Lu, Hong S.
Cassis, Lisa A.
Coselli, Joseph S.
Daugherty, Alan
Shen, Ying H.
LeMaire, Scott A.
description BACKGROUNDAscending 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. METHODSWe 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. RESULTSWe 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(ERG) exerts an important role in maintaining normal aortic wall function. CONCLUSIONSOur 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_str_mv 10.1161/CIRCULATIONAHA.120.046528
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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. METHODSWe 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. RESULTSWe 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(ERG) exerts an important role in maintaining normal aortic wall function. CONCLUSIONSOur 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.</description><identifier>ISSN: 0009-7322</identifier><identifier>EISSN: 1524-4539</identifier><identifier>DOI: 10.1161/CIRCULATIONAHA.120.046528</identifier><identifier>PMID: 33017217</identifier><language>eng</language><publisher>by the American College of Cardiology Foundation and the American Heart Association, Inc</publisher><ispartof>Circulation (New York, N.Y.), 2020-10, Vol.142 (14), p.1374-1388</ispartof><rights>by the American College of Cardiology Foundation and the American Heart Association, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5010-edf183267483b3c896f7e976c25735e77d3e47f8cfbd9ea925efe59aa2c3f4f83</citedby><cites>FETCH-LOGICAL-c5010-edf183267483b3c896f7e976c25735e77d3e47f8cfbd9ea925efe59aa2c3f4f83</cites><orcidid>0000-0002-0577-2558 ; 0000-0003-2093-3775 ; 0000-0002-8736-4266 ; 0000-0003-4119-115X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,3685,27922,27923</link.rule.ids></links><search><creatorcontrib>Li, Yanming</creatorcontrib><creatorcontrib>Ren, Pingping</creatorcontrib><creatorcontrib>Dawson, Ashley</creatorcontrib><creatorcontrib>Vasquez, Hernan G.</creatorcontrib><creatorcontrib>Ageedi, Waleed</creatorcontrib><creatorcontrib>Zhang, Chen</creatorcontrib><creatorcontrib>Luo, Wei</creatorcontrib><creatorcontrib>Chen, Rui</creatorcontrib><creatorcontrib>Li, Yumei</creatorcontrib><creatorcontrib>Kim, Sangbae</creatorcontrib><creatorcontrib>Lu, Hong S.</creatorcontrib><creatorcontrib>Cassis, Lisa A.</creatorcontrib><creatorcontrib>Coselli, Joseph S.</creatorcontrib><creatorcontrib>Daugherty, Alan</creatorcontrib><creatorcontrib>Shen, Ying H.</creatorcontrib><creatorcontrib>LeMaire, Scott A.</creatorcontrib><title>Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue</title><title>Circulation (New York, N.Y.)</title><description>BACKGROUNDAscending 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. METHODSWe 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. RESULTSWe 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(ERG) exerts an important role in maintaining normal aortic wall function. CONCLUSIONSOur 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.</description><issn>0009-7322</issn><issn>1524-4539</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNpVkc1u1DAUhSMEotPCO5gdm0z9lzjZIEXpz4w0olWZri1Pct0xOHawk5Z5Fl4Wt1MhdWXZPuce3fNl2ReCl4SU5Lxd37X3m2a7vvnerJoloXiJeVnQ6l22IAXlOS9Y_T5bYIzrXDBKT7LTGH-ma8lE8TE7YQwTQYlYZH9_GPdgIW_BWrQNysUumHHyA6DGKXuIJqI7eARlI7o4ODWYDr1ob_04WzUZ7yJSrkcXRmsI4CajLLoGB-jyzxggxqRAt2qaICSlcaj1bgrevpgaB3M4xCFZVvOgHGp8mFLC1sQ4w6fsg0658Pn1PMvury637Srf3Fyv22aTdwUmOIdek4rRUvCK7VhX1aUWUIuyo4VgBQjRM-BCV53e9TWomhagoaiVoh3TXFfsLPt2nDvOuwH6Li0RlJVjMIMKB-mVkW9_nNnLB_8oRaqZcJwGfH0dEPzvGeIkBxO71JJy4OcoKedVxUtciSStj9Iu-BgD6P8xBMtnuPItXJngyiPc5OVH75O3qc74y85PEOQ-wZn2MtHFz1hzimmqBZc4Ty8Es3_NE6xm</recordid><startdate>20201006</startdate><enddate>20201006</enddate><creator>Li, Yanming</creator><creator>Ren, Pingping</creator><creator>Dawson, Ashley</creator><creator>Vasquez, Hernan G.</creator><creator>Ageedi, Waleed</creator><creator>Zhang, Chen</creator><creator>Luo, Wei</creator><creator>Chen, Rui</creator><creator>Li, Yumei</creator><creator>Kim, Sangbae</creator><creator>Lu, Hong S.</creator><creator>Cassis, Lisa A.</creator><creator>Coselli, Joseph S.</creator><creator>Daugherty, Alan</creator><creator>Shen, Ying H.</creator><creator>LeMaire, Scott A.</creator><general>by the American College of Cardiology Foundation and the American Heart Association, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-0577-2558</orcidid><orcidid>https://orcid.org/0000-0003-2093-3775</orcidid><orcidid>https://orcid.org/0000-0002-8736-4266</orcidid><orcidid>https://orcid.org/0000-0003-4119-115X</orcidid></search><sort><creationdate>20201006</creationdate><title>Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue</title><author>Li, Yanming ; Ren, Pingping ; Dawson, Ashley ; Vasquez, Hernan G. ; Ageedi, Waleed ; Zhang, Chen ; Luo, Wei ; Chen, Rui ; Li, Yumei ; Kim, Sangbae ; Lu, Hong S. ; Cassis, Lisa A. ; Coselli, Joseph S. ; Daugherty, Alan ; Shen, Ying H. ; LeMaire, Scott A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5010-edf183267483b3c896f7e976c25735e77d3e47f8cfbd9ea925efe59aa2c3f4f83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Yanming</creatorcontrib><creatorcontrib>Ren, Pingping</creatorcontrib><creatorcontrib>Dawson, Ashley</creatorcontrib><creatorcontrib>Vasquez, Hernan G.</creatorcontrib><creatorcontrib>Ageedi, Waleed</creatorcontrib><creatorcontrib>Zhang, Chen</creatorcontrib><creatorcontrib>Luo, Wei</creatorcontrib><creatorcontrib>Chen, Rui</creatorcontrib><creatorcontrib>Li, Yumei</creatorcontrib><creatorcontrib>Kim, Sangbae</creatorcontrib><creatorcontrib>Lu, Hong S.</creatorcontrib><creatorcontrib>Cassis, Lisa A.</creatorcontrib><creatorcontrib>Coselli, Joseph S.</creatorcontrib><creatorcontrib>Daugherty, Alan</creatorcontrib><creatorcontrib>Shen, Ying H.</creatorcontrib><creatorcontrib>LeMaire, Scott A.</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Circulation (New York, N.Y.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Yanming</au><au>Ren, Pingping</au><au>Dawson, Ashley</au><au>Vasquez, Hernan G.</au><au>Ageedi, Waleed</au><au>Zhang, Chen</au><au>Luo, Wei</au><au>Chen, Rui</au><au>Li, Yumei</au><au>Kim, Sangbae</au><au>Lu, Hong S.</au><au>Cassis, Lisa A.</au><au>Coselli, Joseph S.</au><au>Daugherty, Alan</au><au>Shen, Ying H.</au><au>LeMaire, Scott A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue</atitle><jtitle>Circulation (New York, N.Y.)</jtitle><date>2020-10-06</date><risdate>2020</risdate><volume>142</volume><issue>14</issue><spage>1374</spage><epage>1388</epage><pages>1374-1388</pages><issn>0009-7322</issn><eissn>1524-4539</eissn><abstract>BACKGROUNDAscending 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. METHODSWe 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. RESULTSWe 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(ERG) exerts an important role in maintaining normal aortic wall function. CONCLUSIONSOur 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.</abstract><pub>by the American College of Cardiology Foundation and the American Heart Association, Inc</pub><pmid>33017217</pmid><doi>10.1161/CIRCULATIONAHA.120.046528</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0002-0577-2558</orcidid><orcidid>https://orcid.org/0000-0003-2093-3775</orcidid><orcidid>https://orcid.org/0000-0002-8736-4266</orcidid><orcidid>https://orcid.org/0000-0003-4119-115X</orcidid><oa>free_for_read</oa></addata></record>
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title Single-Cell Transcriptome Analysis Reveals Dynamic Cell Populations and Differential Gene Expression Patterns in Control and Aneurysmal Human Aortic Tissue
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