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Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice
BACKGROUND: Abdominal aortic aneurysm (AAA) is a disease of high prevalence in old age, and its incidence gradually increases with increasing age. There were few studies about differences in the circulatory system in the incidence of AAA, mainly because younger patients with AAA are fewer and more c...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147329/ https://www.ncbi.nlm.nih.gov/pubmed/35637715 http://dx.doi.org/10.7717/peerj.13129 |
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author | Ren, Jinrui Wu, Jianqiang Tang, Xiaoyue Chen, Siliang Wang, Wei Lv, Yanze Wu, Lianglin Yang, Dan Zheng, Yuehong |
author_facet | Ren, Jinrui Wu, Jianqiang Tang, Xiaoyue Chen, Siliang Wang, Wei Lv, Yanze Wu, Lianglin Yang, Dan Zheng, Yuehong |
author_sort | Ren, Jinrui |
collection | PubMed |
description | BACKGROUND: Abdominal aortic aneurysm (AAA) is a disease of high prevalence in old age, and its incidence gradually increases with increasing age. There were few studies about differences in the circulatory system in the incidence of AAA, mainly because younger patients with AAA are fewer and more comorbid nonatherosclerotic factors. METHOD: We induced AAA in ApoE(−/−) male mice of different ages (10 or 24 weeks) and obtained plasma samples. After the top 14 most abundant proteins were detected, the plasma was analyzed by a proteomic study using the data-dependent acquisition (DDA) technique. The proteomic results were compared between different groups to identify age-related differentially expressed proteins (DEPs) in the circulation that contribute to AAA formation. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) network analyses were performed by R software. The top 10 proteins were determined with the MCC method of Cytoscape, and transcription factor (TF) prediction of the DEPs was performed with iRegulon (Cytoscape). RESULTS: The aortic diameter fold increase was higher in the aged group than in the youth group (p < 0.01). Overall, 92 DEPs related to age and involved in AAA formation were identified. GO analysis of the DEPs showed enrichment of the terms wounding healing, response to oxidative stress, regulation of body fluid levels, ribose phosphate metabolic process, and blood coagulation. The KEGG pathway analysis showed enrichment of the terms platelet activation, complement and coagulation cascades, glycolysis/gluconeogenesis, carbon metabolism, biosynthesis of amino acids, and ECM-receptor interaction. The top 10 proteins were Tpi1, Eno1, Prdx1, Ppia, Prdx6, Vwf, Prdx2, Fga, Fgg, and Fgb, and the predicted TFs of these proteins were Nfe2, Srf, Epas1, Tbp, and Hoxc8. CONCLUSION: The identified proteins related to age and involved in AAA formation were associated with the response to oxidative stress, coagulation and platelet activation, and complement and inflammation pathways, and the TFs of these proteins might be potential targets for AAA treatments. Further experimental and biological studies are needed to elucidate the role of these age-associated and AAA-related proteins in the progression of AAA. |
format | Online Article Text |
id | pubmed-9147329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91473292022-05-29 Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice Ren, Jinrui Wu, Jianqiang Tang, Xiaoyue Chen, Siliang Wang, Wei Lv, Yanze Wu, Lianglin Yang, Dan Zheng, Yuehong PeerJ Cardiology BACKGROUND: Abdominal aortic aneurysm (AAA) is a disease of high prevalence in old age, and its incidence gradually increases with increasing age. There were few studies about differences in the circulatory system in the incidence of AAA, mainly because younger patients with AAA are fewer and more comorbid nonatherosclerotic factors. METHOD: We induced AAA in ApoE(−/−) male mice of different ages (10 or 24 weeks) and obtained plasma samples. After the top 14 most abundant proteins were detected, the plasma was analyzed by a proteomic study using the data-dependent acquisition (DDA) technique. The proteomic results were compared between different groups to identify age-related differentially expressed proteins (DEPs) in the circulation that contribute to AAA formation. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein–protein interaction (PPI) network analyses were performed by R software. The top 10 proteins were determined with the MCC method of Cytoscape, and transcription factor (TF) prediction of the DEPs was performed with iRegulon (Cytoscape). RESULTS: The aortic diameter fold increase was higher in the aged group than in the youth group (p < 0.01). Overall, 92 DEPs related to age and involved in AAA formation were identified. GO analysis of the DEPs showed enrichment of the terms wounding healing, response to oxidative stress, regulation of body fluid levels, ribose phosphate metabolic process, and blood coagulation. The KEGG pathway analysis showed enrichment of the terms platelet activation, complement and coagulation cascades, glycolysis/gluconeogenesis, carbon metabolism, biosynthesis of amino acids, and ECM-receptor interaction. The top 10 proteins were Tpi1, Eno1, Prdx1, Ppia, Prdx6, Vwf, Prdx2, Fga, Fgg, and Fgb, and the predicted TFs of these proteins were Nfe2, Srf, Epas1, Tbp, and Hoxc8. CONCLUSION: The identified proteins related to age and involved in AAA formation were associated with the response to oxidative stress, coagulation and platelet activation, and complement and inflammation pathways, and the TFs of these proteins might be potential targets for AAA treatments. Further experimental and biological studies are needed to elucidate the role of these age-associated and AAA-related proteins in the progression of AAA. PeerJ Inc. 2022-05-25 /pmc/articles/PMC9147329/ /pubmed/35637715 http://dx.doi.org/10.7717/peerj.13129 Text en © 2022 Ren et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Cardiology Ren, Jinrui Wu, Jianqiang Tang, Xiaoyue Chen, Siliang Wang, Wei Lv, Yanze Wu, Lianglin Yang, Dan Zheng, Yuehong Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice |
title | Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice |
title_full | Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice |
title_fullStr | Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice |
title_full_unstemmed | Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice |
title_short | Ageing- and AAA-associated differentially expressed proteins identified by proteomic analysis in mice |
title_sort | ageing- and aaa-associated differentially expressed proteins identified by proteomic analysis in mice |
topic | Cardiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9147329/ https://www.ncbi.nlm.nih.gov/pubmed/35637715 http://dx.doi.org/10.7717/peerj.13129 |
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