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Increased MMP12 mRNA expression in induced sputum was correlated with airway eosinophilic inflammation in asthma patients: Evidence from bioinformatic analysis and experiment verification

•MMP12 mRNA expression in induced sputum was significantly upregulated in asthmatic patients compared to the healthy control.•MMP12 mRNA expression was positively correlated with airway and peripheral blood eosinophilia.•WGCNA analysis that employed in this study can provided a framework of co-expre...

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Published in:Gene 2021-12, Vol.804, p.145896-145896, Article 145896
Main Authors: Du, Lijuan, Chen, Fengjia, Xu, Changyi, Tan, Weiping, Shi, Jia, Tang, Lu, Xiao, Lisha, Xie, Canmao, Zeng, Zhimin, Liang, Yuxia, Guo, Yubiao
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container_title Gene
container_volume 804
creator Du, Lijuan
Chen, Fengjia
Xu, Changyi
Tan, Weiping
Shi, Jia
Tang, Lu
Xiao, Lisha
Xie, Canmao
Zeng, Zhimin
Liang, Yuxia
Guo, Yubiao
description •MMP12 mRNA expression in induced sputum was significantly upregulated in asthmatic patients compared to the healthy control.•MMP12 mRNA expression was positively correlated with airway and peripheral blood eosinophilia.•WGCNA analysis that employed in this study can provided a framework of co-expression gene modules of asthma and led to the identification of some new biomarkers that might be potential targets for the development of new drugs and diagnostic markers. Asthma is a common chronic airway inflammatory disease worldwide. Studies on gene expression profiles in induced sputum may provide noninvasive diagnostic biomarkers and therapeutic targets for asthma. To investigate mRNA expression of MMP12 in induced sputum and its relationship with asthma airway eosinophilic inflammation. GSE76262 dataset was analyzed using R software, weighted gene coexpression network analysis (WGCNA), and protein–protein interaction (PPI) network construction. The top ten hub genes were screened with Cytoscape software (version 3.8.4). We then verified the mRNA expression of MMP12 in two other datasets (GSE137268 and GSE74075) via ROC curve estimates and our induced sputum samples using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Finally, we explored the correlation between MMP12 with asthmatic eosinophilic-related indicators. We obtained the top ten hub genes, namely, CCL17, CCL2, CSF1, CCL22, CCR3, CD69, FCGR2B, CD1C, CD1E, and MMP12 via expression profile screening and validation on the GSE76262 dataset. MMP12 was selected as the candidate gene through further validation on GSE137268 and GSE74075 datasets. Finally, we demonstrated that the mRNA expression of MMP12 is significantly upregulated in induced sputum of asthmatic patients (p 
doi_str_mv 10.1016/j.gene.2021.145896
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Asthma is a common chronic airway inflammatory disease worldwide. Studies on gene expression profiles in induced sputum may provide noninvasive diagnostic biomarkers and therapeutic targets for asthma. To investigate mRNA expression of MMP12 in induced sputum and its relationship with asthma airway eosinophilic inflammation. GSE76262 dataset was analyzed using R software, weighted gene coexpression network analysis (WGCNA), and protein–protein interaction (PPI) network construction. The top ten hub genes were screened with Cytoscape software (version 3.8.4). We then verified the mRNA expression of MMP12 in two other datasets (GSE137268 and GSE74075) via ROC curve estimates and our induced sputum samples using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Finally, we explored the correlation between MMP12 with asthmatic eosinophilic-related indicators. We obtained the top ten hub genes, namely, CCL17, CCL2, CSF1, CCL22, CCR3, CD69, FCGR2B, CD1C, CD1E, and MMP12 via expression profile screening and validation on the GSE76262 dataset. MMP12 was selected as the candidate gene through further validation on GSE137268 and GSE74075 datasets. Finally, we demonstrated that the mRNA expression of MMP12 is significantly upregulated in induced sputum of asthmatic patients (p &lt; 0.05) and significantly correlated with eosinophilic-related indicators (p &lt; 0.05). These findings indicated that MMP12 can act as a diagnostic biomarker for asthma. Our study successfully identified and demonstrated that MMP12 is a potential diagnostic biomarker for asthma due to its high expression and association with eosinophilic-related indicators. 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Asthma is a common chronic airway inflammatory disease worldwide. Studies on gene expression profiles in induced sputum may provide noninvasive diagnostic biomarkers and therapeutic targets for asthma. To investigate mRNA expression of MMP12 in induced sputum and its relationship with asthma airway eosinophilic inflammation. GSE76262 dataset was analyzed using R software, weighted gene coexpression network analysis (WGCNA), and protein–protein interaction (PPI) network construction. The top ten hub genes were screened with Cytoscape software (version 3.8.4). We then verified the mRNA expression of MMP12 in two other datasets (GSE137268 and GSE74075) via ROC curve estimates and our induced sputum samples using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Finally, we explored the correlation between MMP12 with asthmatic eosinophilic-related indicators. We obtained the top ten hub genes, namely, CCL17, CCL2, CSF1, CCL22, CCR3, CD69, FCGR2B, CD1C, CD1E, and MMP12 via expression profile screening and validation on the GSE76262 dataset. MMP12 was selected as the candidate gene through further validation on GSE137268 and GSE74075 datasets. Finally, we demonstrated that the mRNA expression of MMP12 is significantly upregulated in induced sputum of asthmatic patients (p &lt; 0.05) and significantly correlated with eosinophilic-related indicators (p &lt; 0.05). These findings indicated that MMP12 can act as a diagnostic biomarker for asthma. Our study successfully identified and demonstrated that MMP12 is a potential diagnostic biomarker for asthma due to its high expression and association with eosinophilic-related indicators. 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Asthma is a common chronic airway inflammatory disease worldwide. Studies on gene expression profiles in induced sputum may provide noninvasive diagnostic biomarkers and therapeutic targets for asthma. To investigate mRNA expression of MMP12 in induced sputum and its relationship with asthma airway eosinophilic inflammation. GSE76262 dataset was analyzed using R software, weighted gene coexpression network analysis (WGCNA), and protein–protein interaction (PPI) network construction. The top ten hub genes were screened with Cytoscape software (version 3.8.4). We then verified the mRNA expression of MMP12 in two other datasets (GSE137268 and GSE74075) via ROC curve estimates and our induced sputum samples using real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Finally, we explored the correlation between MMP12 with asthmatic eosinophilic-related indicators. We obtained the top ten hub genes, namely, CCL17, CCL2, CSF1, CCL22, CCR3, CD69, FCGR2B, CD1C, CD1E, and MMP12 via expression profile screening and validation on the GSE76262 dataset. MMP12 was selected as the candidate gene through further validation on GSE137268 and GSE74075 datasets. Finally, we demonstrated that the mRNA expression of MMP12 is significantly upregulated in induced sputum of asthmatic patients (p &lt; 0.05) and significantly correlated with eosinophilic-related indicators (p &lt; 0.05). These findings indicated that MMP12 can act as a diagnostic biomarker for asthma. Our study successfully identified and demonstrated that MMP12 is a potential diagnostic biomarker for asthma due to its high expression and association with eosinophilic-related indicators. The results of this study can provide novel insights into asthmatic diagnosis and therapy in the future.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.gene.2021.145896</doi><tpages>1</tpages></addata></record>
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subjects Asthma
MMP12
Sputum gene expression
WGCNA
title Increased MMP12 mRNA expression in induced sputum was correlated with airway eosinophilic inflammation in asthma patients: Evidence from bioinformatic analysis and experiment verification
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