Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension

Despite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH....

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Main Authors: Han Yang, Yang Lu, Hongmin Yang, Yaoxi Zhu, Yaohan Tang, Lixia Li, Changhu Liu, Jing Yuan
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Bioengineered
Subjects:
Online Access:http://dx.doi.org/10.1080/21655979.2021.1972200
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spelling doaj-6c026e05af1447ab8ba02a52bcb3215e2021-09-20T13:17:22ZengTaylor & Francis GroupBioengineered2165-59792165-59872021-01-011216021603410.1080/21655979.2021.19722001972200Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertensionHan Yang0Yang Lu1Hongmin Yang2Yaoxi Zhu3Yaohan Tang4Lixia Li5Changhu Liu6Jing Yuan7Tongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyTongji Medical College, Huazhong University of Science and TechnologyDespite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH. In this research, we aimed to examine the mechanisms underlying PAH and identify key genes with potential usefulness as clinical biomarkers of PAH and thereby establish therapeutic targets for PAH. The datasets GSE117261, GSE113439, and GSE53408 were downloaded from the Gene Expression Omnibus (GEOs) database. We used weighted gene coexpression network analysis (WGCNA) to identify networks and the most relevant modules in PAH. Functional enrichment analysis was performed for the selected clinically relevant modules. The least absolute shrinkage and selection operator (LASSO) was applied to identify key genes in lung samples from patients with PAH. The genes were validated in a monocrotaline-induced PAH rat model. Three clinically relevant modules were identified through average linkage hierarchical clustering. The genes in the clinically relevant modules were related to endothelial cell differentiation, inflammation, and autoimmunity. Seven genes were screened as key genes significantly associated with PAH. Interferon-induced protein 44-like (IFI44L) and signal transducer and activator of transcription 1 (STAT1) were expressed at higher levels in the lung tissues of the PAH rat model than in those of the controls. Our findings reveal the novel pathological mechanisms underlying PAH and indicate that STAT1 and IFI44L may represent potential therapeutic targets in PAH.http://dx.doi.org/10.1080/21655979.2021.1972200pulmonary arterial hypertensionstat1ifi44lgene expressionwgcna
collection DOAJ
language English
format Article
sources DOAJ
author Han Yang
Yang Lu
Hongmin Yang
Yaoxi Zhu
Yaohan Tang
Lixia Li
Changhu Liu
Jing Yuan
spellingShingle Han Yang
Yang Lu
Hongmin Yang
Yaoxi Zhu
Yaohan Tang
Lixia Li
Changhu Liu
Jing Yuan
Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
Bioengineered
pulmonary arterial hypertension
stat1
ifi44l
gene expression
wgcna
author_facet Han Yang
Yang Lu
Hongmin Yang
Yaoxi Zhu
Yaohan Tang
Lixia Li
Changhu Liu
Jing Yuan
author_sort Han Yang
title Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
title_short Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
title_full Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
title_fullStr Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
title_full_unstemmed Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
title_sort integrated weighted gene co-expression network analysis uncovers stat1(signal transducer and activator of transcription 1) and ifi44l (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension
publisher Taylor & Francis Group
series Bioengineered
issn 2165-5979
2165-5987
publishDate 2021-01-01
description Despite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH. In this research, we aimed to examine the mechanisms underlying PAH and identify key genes with potential usefulness as clinical biomarkers of PAH and thereby establish therapeutic targets for PAH. The datasets GSE117261, GSE113439, and GSE53408 were downloaded from the Gene Expression Omnibus (GEOs) database. We used weighted gene coexpression network analysis (WGCNA) to identify networks and the most relevant modules in PAH. Functional enrichment analysis was performed for the selected clinically relevant modules. The least absolute shrinkage and selection operator (LASSO) was applied to identify key genes in lung samples from patients with PAH. The genes were validated in a monocrotaline-induced PAH rat model. Three clinically relevant modules were identified through average linkage hierarchical clustering. The genes in the clinically relevant modules were related to endothelial cell differentiation, inflammation, and autoimmunity. Seven genes were screened as key genes significantly associated with PAH. Interferon-induced protein 44-like (IFI44L) and signal transducer and activator of transcription 1 (STAT1) were expressed at higher levels in the lung tissues of the PAH rat model than in those of the controls. Our findings reveal the novel pathological mechanisms underlying PAH and indicate that STAT1 and IFI44L may represent potential therapeutic targets in PAH.
topic pulmonary arterial hypertension
stat1
ifi44l
gene expression
wgcna
url http://dx.doi.org/10.1080/21655979.2021.1972200
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