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Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection

OBJECTIVE: Very few clinical predictors of descending thoracic aorta dissection have been determined. Although aneurysms can dissect in a size-dependent process, most descending dissections will occur without prior enlargement. We compared the proteomic profiles of normal, dissected, aneurysm, and b...

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Autores principales: Saddic, Louis, Orosco, Amanda, Guo, Dongchuan, Milewicz, Dianna M., Troxlair, Dana, Heide, Richard Vander, Herrington, David, Wang, Yue, Azizzadeh, Ali, Parker, Sarah J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914561/
https://www.ncbi.nlm.nih.gov/pubmed/35280433
http://dx.doi.org/10.1016/j.jvssci.2022.01.001
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author Saddic, Louis
Orosco, Amanda
Guo, Dongchuan
Milewicz, Dianna M.
Troxlair, Dana
Heide, Richard Vander
Herrington, David
Wang, Yue
Azizzadeh, Ali
Parker, Sarah J.
author_facet Saddic, Louis
Orosco, Amanda
Guo, Dongchuan
Milewicz, Dianna M.
Troxlair, Dana
Heide, Richard Vander
Herrington, David
Wang, Yue
Azizzadeh, Ali
Parker, Sarah J.
author_sort Saddic, Louis
collection PubMed
description OBJECTIVE: Very few clinical predictors of descending thoracic aorta dissection have been determined. Although aneurysms can dissect in a size-dependent process, most descending dissections will occur without prior enlargement. We compared the proteomic profiles of normal, dissected, aneurysm, and both aneurysm and dissected descending thoracic aortas to identify novel biomarkers and further understand the molecular pathways that lead to tissue at risk of dissection. METHODS: We performed proteomic profiling of descending thoracic aortas with four phenotypes: normal (n = 46), aneurysm (n = 22), dissected (n = 12), and combined aneurysm and dissection (n = 8). Pairwise differential protein expression analyses using a Bayesian approach were then performed to identify common proteins that were dysregulated between each diseased tissue type and control aorta and to uncover unique proteins between aneurysmal and dissected aortas. Network and Markov cluster algorithms of differentially expressed proteins were used to find enriched ontology processes. A convex analysis of mixtures was also performed to identify the molecular subtypes within the different tissue types. RESULTS: The diseased aortas had 71 common differentially expressed proteins compared with the control, including higher amounts of the protein thrombospondin 1. We found 42 differentially expressed proteins between the aneurysm and dissected tissue, with an abundance of apolipoproteins in the former and higher quantities of extracellular matrix proteins in the latter. The convex analysis of mixtures showed enhancement of a molecular subtype enriched in contractile proteins within the control tissue compared with the diseased tissue, in addition to increased proportions of molecular subtypes enriched in inflammation and red blood cell expression in the aneurysmal compared with the dissected tissue. CONCLUSIONS: We found some overlapping differentially expressed proteins in aneurysmal and nonaneurysmal descending thoracic aortas at risk of dissection compared with normal aortas. However, we also found uniquely altered molecular pathways that might uncover mechanisms for dissection.
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spelling pubmed-89145612022-03-12 Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection Saddic, Louis Orosco, Amanda Guo, Dongchuan Milewicz, Dianna M. Troxlair, Dana Heide, Richard Vander Herrington, David Wang, Yue Azizzadeh, Ali Parker, Sarah J. JVS Vasc Sci Article OBJECTIVE: Very few clinical predictors of descending thoracic aorta dissection have been determined. Although aneurysms can dissect in a size-dependent process, most descending dissections will occur without prior enlargement. We compared the proteomic profiles of normal, dissected, aneurysm, and both aneurysm and dissected descending thoracic aortas to identify novel biomarkers and further understand the molecular pathways that lead to tissue at risk of dissection. METHODS: We performed proteomic profiling of descending thoracic aortas with four phenotypes: normal (n = 46), aneurysm (n = 22), dissected (n = 12), and combined aneurysm and dissection (n = 8). Pairwise differential protein expression analyses using a Bayesian approach were then performed to identify common proteins that were dysregulated between each diseased tissue type and control aorta and to uncover unique proteins between aneurysmal and dissected aortas. Network and Markov cluster algorithms of differentially expressed proteins were used to find enriched ontology processes. A convex analysis of mixtures was also performed to identify the molecular subtypes within the different tissue types. RESULTS: The diseased aortas had 71 common differentially expressed proteins compared with the control, including higher amounts of the protein thrombospondin 1. We found 42 differentially expressed proteins between the aneurysm and dissected tissue, with an abundance of apolipoproteins in the former and higher quantities of extracellular matrix proteins in the latter. The convex analysis of mixtures showed enhancement of a molecular subtype enriched in contractile proteins within the control tissue compared with the diseased tissue, in addition to increased proportions of molecular subtypes enriched in inflammation and red blood cell expression in the aneurysmal compared with the dissected tissue. CONCLUSIONS: We found some overlapping differentially expressed proteins in aneurysmal and nonaneurysmal descending thoracic aortas at risk of dissection compared with normal aortas. However, we also found uniquely altered molecular pathways that might uncover mechanisms for dissection. Elsevier 2022-01-22 /pmc/articles/PMC8914561/ /pubmed/35280433 http://dx.doi.org/10.1016/j.jvssci.2022.01.001 Text en © 2022 by the Society for Vascular Surgery. Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Saddic, Louis
Orosco, Amanda
Guo, Dongchuan
Milewicz, Dianna M.
Troxlair, Dana
Heide, Richard Vander
Herrington, David
Wang, Yue
Azizzadeh, Ali
Parker, Sarah J.
Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
title Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
title_full Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
title_fullStr Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
title_full_unstemmed Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
title_short Proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
title_sort proteomic analysis of descending thoracic aorta identifies unique and universal signatures of aneurysm and dissection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914561/
https://www.ncbi.nlm.nih.gov/pubmed/35280433
http://dx.doi.org/10.1016/j.jvssci.2022.01.001
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