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EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration

BACKGROUND: Formation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we...

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Autores principales: Guo, Chunguang, Liu, Zaoqu, Yu, Yin, Zhou, Zhibin, Ma, Ke, Zhang, Linfeng, Dang, Qin, Liu, Long, Wang, Libo, Zhang, Shuai, Hua, Zhaohui, Han, Xinwei, Li, Zhen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863960/
https://www.ncbi.nlm.nih.gov/pubmed/35224035
http://dx.doi.org/10.3389/fcvm.2022.781207
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author Guo, Chunguang
Liu, Zaoqu
Yu, Yin
Zhou, Zhibin
Ma, Ke
Zhang, Linfeng
Dang, Qin
Liu, Long
Wang, Libo
Zhang, Shuai
Hua, Zhaohui
Han, Xinwei
Li, Zhen
author_facet Guo, Chunguang
Liu, Zaoqu
Yu, Yin
Zhou, Zhibin
Ma, Ke
Zhang, Linfeng
Dang, Qin
Liu, Long
Wang, Libo
Zhang, Shuai
Hua, Zhaohui
Han, Xinwei
Li, Zhen
author_sort Guo, Chunguang
collection PubMed
description BACKGROUND: Formation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we aim to explore the potential association between PVAT and AAA. METHODS: We analyzed gene expression and clinical data of 30 PVAT around AAA and 30 PVAT around normal abdominal aorta (NAA). The diagnostic markers and immune cell infiltration of PVAT were further investigated by WGCNA, CIBERSORT, PPI, and multiple machine learning algorisms (including LASSO, RF, and SVM). Subsequently, eight-week-old C57BL/6 male mice (n = 10) were used to construct AAA models, and aorta samples were collected for molecular validation. Meanwhile, fifty-five peripheral venous blood samples from patients (AAA vs. normal: 40:15) in our hospital were used as an inhouse cohort to validate the diagnostic markers by qRT-PCR. The diagnostic efficacy of biomarkers was assessed by receiver operating characteristic (ROC) curve, area under the ROC (AUC), and concordance index (C-index). RESULTS: A total of 75 genes in the Grey60 module were identified by WGCNA. To select the genes most associated with PVAT in the grey60 module, three algorithms (including LASSO, RF, and SVM) and PPI were applied. EGR1 and KLF4 were identified as diagnostic markers of PVAT, with high accurate AUCs of 0.916, 0.926, and 0.948 (combined two markers). Additionally, the two biomarkers also displayed accurate diagnostic efficacy in the mice and inhouse cohorts, with AUCs and C-indexes all >0.8. Compared with the NAA group, PVAT around AAA was more abundant in multiple immune cell infiltration. Ultimately, the immune-related analysis revealed that EGR1 and KLF4 were associated with mast cells, T cells, and plasma cells. CONCLUSION: EGR1 and KLF4 were diagnostic markers of PVAT around AAA and associated with multiple immune cells.
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spelling pubmed-88639602022-02-24 EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration Guo, Chunguang Liu, Zaoqu Yu, Yin Zhou, Zhibin Ma, Ke Zhang, Linfeng Dang, Qin Liu, Long Wang, Libo Zhang, Shuai Hua, Zhaohui Han, Xinwei Li, Zhen Front Cardiovasc Med Cardiovascular Medicine BACKGROUND: Formation and rupture of abdominal aortic aneurysm (AAA) is fatal, and the pathological processes and molecular mechanisms underlying its formation and development are unclear. Perivascular adipose tissue (PVAT) has attracted extensive attention as a newly defined secretory organ, and we aim to explore the potential association between PVAT and AAA. METHODS: We analyzed gene expression and clinical data of 30 PVAT around AAA and 30 PVAT around normal abdominal aorta (NAA). The diagnostic markers and immune cell infiltration of PVAT were further investigated by WGCNA, CIBERSORT, PPI, and multiple machine learning algorisms (including LASSO, RF, and SVM). Subsequently, eight-week-old C57BL/6 male mice (n = 10) were used to construct AAA models, and aorta samples were collected for molecular validation. Meanwhile, fifty-five peripheral venous blood samples from patients (AAA vs. normal: 40:15) in our hospital were used as an inhouse cohort to validate the diagnostic markers by qRT-PCR. The diagnostic efficacy of biomarkers was assessed by receiver operating characteristic (ROC) curve, area under the ROC (AUC), and concordance index (C-index). RESULTS: A total of 75 genes in the Grey60 module were identified by WGCNA. To select the genes most associated with PVAT in the grey60 module, three algorithms (including LASSO, RF, and SVM) and PPI were applied. EGR1 and KLF4 were identified as diagnostic markers of PVAT, with high accurate AUCs of 0.916, 0.926, and 0.948 (combined two markers). Additionally, the two biomarkers also displayed accurate diagnostic efficacy in the mice and inhouse cohorts, with AUCs and C-indexes all >0.8. Compared with the NAA group, PVAT around AAA was more abundant in multiple immune cell infiltration. Ultimately, the immune-related analysis revealed that EGR1 and KLF4 were associated with mast cells, T cells, and plasma cells. CONCLUSION: EGR1 and KLF4 were diagnostic markers of PVAT around AAA and associated with multiple immune cells. Frontiers Media S.A. 2022-02-09 /pmc/articles/PMC8863960/ /pubmed/35224035 http://dx.doi.org/10.3389/fcvm.2022.781207 Text en Copyright © 2022 Guo, Liu, Yu, Zhou, Ma, Zhang, Dang, Liu, Wang, Zhang, Hua, Han and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Guo, Chunguang
Liu, Zaoqu
Yu, Yin
Zhou, Zhibin
Ma, Ke
Zhang, Linfeng
Dang, Qin
Liu, Long
Wang, Libo
Zhang, Shuai
Hua, Zhaohui
Han, Xinwei
Li, Zhen
EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration
title EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration
title_full EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration
title_fullStr EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration
title_full_unstemmed EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration
title_short EGR1 and KLF4 as Diagnostic Markers for Abdominal Aortic Aneurysm and Associated With Immune Infiltration
title_sort egr1 and klf4 as diagnostic markers for abdominal aortic aneurysm and associated with immune infiltration
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863960/
https://www.ncbi.nlm.nih.gov/pubmed/35224035
http://dx.doi.org/10.3389/fcvm.2022.781207
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