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NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis

This study aims to explore the predictive noninvasive biomarker for obstructive coronary artery disease (CAD). By using the data set GSE90074, weighted gene co‐expression network analysis (WGCNA), and protein–protein interactive network, construction of differentially expressed genes in peripheral b...

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Autores principales: Mo, Xian‐Gang, Liu, Wei, Yang, Yao, Imani, Saber, Lu, Shan, Dan, Guorong, Nie, Xuqiang, Yan, Jun, Zhan, Rixing, Li, Xiaohui, Deng, Youcai, Chen, Bingbo, Cai, Yue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6771964/
https://www.ncbi.nlm.nih.gov/pubmed/31245869
http://dx.doi.org/10.1002/jcb.29128
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author Mo, Xian‐Gang
Liu, Wei
Yang, Yao
Imani, Saber
Lu, Shan
Dan, Guorong
Nie, Xuqiang
Yan, Jun
Zhan, Rixing
Li, Xiaohui
Deng, Youcai
Chen, Bingbo
Cai, Yue
author_facet Mo, Xian‐Gang
Liu, Wei
Yang, Yao
Imani, Saber
Lu, Shan
Dan, Guorong
Nie, Xuqiang
Yan, Jun
Zhan, Rixing
Li, Xiaohui
Deng, Youcai
Chen, Bingbo
Cai, Yue
author_sort Mo, Xian‐Gang
collection PubMed
description This study aims to explore the predictive noninvasive biomarker for obstructive coronary artery disease (CAD). By using the data set GSE90074, weighted gene co‐expression network analysis (WGCNA), and protein–protein interactive network, construction of differentially expressed genes in peripheral blood mononuclear cells was conducted to identify the most significant gene clusters associated with obstructive CAD. Univariate and multivariate stepwise logistic regression analyses and receiver operating characteristic analysis were used to predicate the diagnostic accuracy of biomarker candidates in the detection of obstructive CAD. Furthermore, functional prediction of candidate gene biomarkers was further confirmed in ST‐segment elevation myocardial infarction (STEMI) patients or stable CAD patients by using the datasets of GSE62646 and GSE59867. We found that the blue module discriminated by WGCNA contained 13 hub‐genes that could be independent risk factors for obstructive CAD (P < .05). Among these 13 hub‐genes, a four‐gene signature including neutrophil cytosol factor 2 (NCF2, P = .025), myosin‐If (MYO1F, P = .001), sphingosine‐1‐phosphate receptor 4 (S1PR4, P = .015), and ficolin‐1 (FCN1, P = .012) alone or combined with two risk factors (male sex and hyperlipidemia) may represent potential diagnostic biomarkers in obstructive CAD. Furthermore, the messenger RNA levels of NCF2, MYO1F, S1PR4, and FCN1 were higher in STEMI patients than that in stable CAD patients, although S1PR4 showed no statistical difference (P > .05). This four‐gene signature could also act as a prognostic biomarker to discriminate STEMI patients from stable CAD patients. These findings suggest a four‐gene signature (NCF2, MYO1F, S1PR4, and FCN1) alone or combined with two risk factors (male sex and hyperlipidemia) as a promising prognostic biomarker in the diagnosis of STEMI. Well‐designed cohort studies should be implemented to warrant the diagnostic value of these genes in clinical purpose.
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spelling pubmed-67719642019-10-07 NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis Mo, Xian‐Gang Liu, Wei Yang, Yao Imani, Saber Lu, Shan Dan, Guorong Nie, Xuqiang Yan, Jun Zhan, Rixing Li, Xiaohui Deng, Youcai Chen, Bingbo Cai, Yue J Cell Biochem Research Articles This study aims to explore the predictive noninvasive biomarker for obstructive coronary artery disease (CAD). By using the data set GSE90074, weighted gene co‐expression network analysis (WGCNA), and protein–protein interactive network, construction of differentially expressed genes in peripheral blood mononuclear cells was conducted to identify the most significant gene clusters associated with obstructive CAD. Univariate and multivariate stepwise logistic regression analyses and receiver operating characteristic analysis were used to predicate the diagnostic accuracy of biomarker candidates in the detection of obstructive CAD. Furthermore, functional prediction of candidate gene biomarkers was further confirmed in ST‐segment elevation myocardial infarction (STEMI) patients or stable CAD patients by using the datasets of GSE62646 and GSE59867. We found that the blue module discriminated by WGCNA contained 13 hub‐genes that could be independent risk factors for obstructive CAD (P < .05). Among these 13 hub‐genes, a four‐gene signature including neutrophil cytosol factor 2 (NCF2, P = .025), myosin‐If (MYO1F, P = .001), sphingosine‐1‐phosphate receptor 4 (S1PR4, P = .015), and ficolin‐1 (FCN1, P = .012) alone or combined with two risk factors (male sex and hyperlipidemia) may represent potential diagnostic biomarkers in obstructive CAD. Furthermore, the messenger RNA levels of NCF2, MYO1F, S1PR4, and FCN1 were higher in STEMI patients than that in stable CAD patients, although S1PR4 showed no statistical difference (P > .05). This four‐gene signature could also act as a prognostic biomarker to discriminate STEMI patients from stable CAD patients. These findings suggest a four‐gene signature (NCF2, MYO1F, S1PR4, and FCN1) alone or combined with two risk factors (male sex and hyperlipidemia) as a promising prognostic biomarker in the diagnosis of STEMI. Well‐designed cohort studies should be implemented to warrant the diagnostic value of these genes in clinical purpose. John Wiley and Sons Inc. 2019-06-27 2019-10 /pmc/articles/PMC6771964/ /pubmed/31245869 http://dx.doi.org/10.1002/jcb.29128 Text en © 2019 The Authors. Journal of Cellular Biochemistry Published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Mo, Xian‐Gang
Liu, Wei
Yang, Yao
Imani, Saber
Lu, Shan
Dan, Guorong
Nie, Xuqiang
Yan, Jun
Zhan, Rixing
Li, Xiaohui
Deng, Youcai
Chen, Bingbo
Cai, Yue
NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
title NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
title_full NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
title_fullStr NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
title_full_unstemmed NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
title_short NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
title_sort ncf2, myo1f, s1pr4, and fcn1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: a weighted gene co‐expression network analysis
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6771964/
https://www.ncbi.nlm.nih.gov/pubmed/31245869
http://dx.doi.org/10.1002/jcb.29128
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