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Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis

Biliary atresia (BA) is the most common cause of obstructive jaundice during the neonatal period. This study aimed to identify gene expression signature in BA. The datasets were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis identified a critical mod...

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Autores principales: Wang, Yongliang, Yuan, Hongtao, Zhao, Maojun, Fang, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9478247/
https://www.ncbi.nlm.nih.gov/pubmed/36123893
http://dx.doi.org/10.1097/MD.0000000000030232
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author Wang, Yongliang
Yuan, Hongtao
Zhao, Maojun
Fang, Li
author_facet Wang, Yongliang
Yuan, Hongtao
Zhao, Maojun
Fang, Li
author_sort Wang, Yongliang
collection PubMed
description Biliary atresia (BA) is the most common cause of obstructive jaundice during the neonatal period. This study aimed to identify gene expression signature in BA. The datasets were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis identified a critical module associated with BA, whereas Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed the functions of the essential modules. The high-connectivity genes in the most relevant module constructed protein–protein interaction networks via the string website and Cytoscape software. Hub genes screened by lasso regression consisted of a disease classification model using the randomforest method. Receiver operating characteristic curves were used to assess models’ sensitivity and specificity and the model was verified using the internal and external validation sets. Ten gene modules were constructed by WGCNA, of which the brown module had a strong positive correlation with BA, comprising 443 genes. Functional enrichment analysis revealed that module genes were mainly involved in biological processes, such as extracellular matrix organization, cell adhesion, inflammatory response, and the Notch pathway (P < .001), whereas these genes were involved in the metabolic pathways and cell adhesion molecules (P < .001). Thirty-nine high-connectivity genes in the brown module constructed protein-protein interaction networks. keratin 7 (KRT7) and C-X-C motif chemokine ligand 8 (CXCL8) were used to construct a diagnostic model that had an accuracy of 93.6% and the area under the receiver operating curves for the model was 0.93. The study provided insight into the signature of gene expression and possible pathogenesis of BA; furthermore, it identified that the combination of KRT7 and CXCL8 could be a potential diagnostic model for BA.
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spelling pubmed-94782472022-09-19 Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis Wang, Yongliang Yuan, Hongtao Zhao, Maojun Fang, Li Medicine (Baltimore) Research Article Biliary atresia (BA) is the most common cause of obstructive jaundice during the neonatal period. This study aimed to identify gene expression signature in BA. The datasets were obtained from the Gene Expression Omnibus database. Weighted gene co-expression network analysis identified a critical module associated with BA, whereas Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed the functions of the essential modules. The high-connectivity genes in the most relevant module constructed protein–protein interaction networks via the string website and Cytoscape software. Hub genes screened by lasso regression consisted of a disease classification model using the randomforest method. Receiver operating characteristic curves were used to assess models’ sensitivity and specificity and the model was verified using the internal and external validation sets. Ten gene modules were constructed by WGCNA, of which the brown module had a strong positive correlation with BA, comprising 443 genes. Functional enrichment analysis revealed that module genes were mainly involved in biological processes, such as extracellular matrix organization, cell adhesion, inflammatory response, and the Notch pathway (P < .001), whereas these genes were involved in the metabolic pathways and cell adhesion molecules (P < .001). Thirty-nine high-connectivity genes in the brown module constructed protein-protein interaction networks. keratin 7 (KRT7) and C-X-C motif chemokine ligand 8 (CXCL8) were used to construct a diagnostic model that had an accuracy of 93.6% and the area under the receiver operating curves for the model was 0.93. The study provided insight into the signature of gene expression and possible pathogenesis of BA; furthermore, it identified that the combination of KRT7 and CXCL8 could be a potential diagnostic model for BA. Lippincott Williams & Wilkins 2022-09-16 /pmc/articles/PMC9478247/ /pubmed/36123893 http://dx.doi.org/10.1097/MD.0000000000030232 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle Research Article
Wang, Yongliang
Yuan, Hongtao
Zhao, Maojun
Fang, Li
Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
title Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
title_full Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
title_fullStr Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
title_full_unstemmed Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
title_short Identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
title_sort identification of signature of gene expression in biliary atresia using weighted gene co-expression network analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9478247/
https://www.ncbi.nlm.nih.gov/pubmed/36123893
http://dx.doi.org/10.1097/MD.0000000000030232
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