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Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses

BACKGROUND: Ulcerative colitis (UC) is an inflammatory bowel disease that is difficult to diagnose and treat. To date, the degree of inflammation in patients with UC has mainly been determined by measuring the levels of nonspecific indicators, such as C-reactive protein and the erythrocyte sedimenta...

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Autores principales: Shi, Lei, Han, Xiao, Li, Jun-Xiang, Liao, Yu-Ting, Kou, Fu-Shun, Wang, Zhi-Bin, Shi, Rui, Zhao, Xing-Jie, Sun, Zhong-Mei, Hao, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584051/
https://www.ncbi.nlm.nih.gov/pubmed/33132649
http://dx.doi.org/10.3748/wjg.v26.i39.5983
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author Shi, Lei
Han, Xiao
Li, Jun-Xiang
Liao, Yu-Ting
Kou, Fu-Shun
Wang, Zhi-Bin
Shi, Rui
Zhao, Xing-Jie
Sun, Zhong-Mei
Hao, Yu
author_facet Shi, Lei
Han, Xiao
Li, Jun-Xiang
Liao, Yu-Ting
Kou, Fu-Shun
Wang, Zhi-Bin
Shi, Rui
Zhao, Xing-Jie
Sun, Zhong-Mei
Hao, Yu
author_sort Shi, Lei
collection PubMed
description BACKGROUND: Ulcerative colitis (UC) is an inflammatory bowel disease that is difficult to diagnose and treat. To date, the degree of inflammation in patients with UC has mainly been determined by measuring the levels of nonspecific indicators, such as C-reactive protein and the erythrocyte sedimentation rate, but these indicators have an unsatisfactory specificity. In this study, we performed bioinformatics analysis using data from the National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) databases and verified the selected core genes in a mouse model of dextran sulfate sodium (DSS)-induced colitis. AIM: To identify UC-related differentially expressed genes (DEGs) using a bioinformatics analysis and verify them in vivo and to identify novel biomarkers and the underlying mechanisms of UC. METHODS: Two microarray datasets from the NCBI-GEO database were used, and DEGs between patients with UC and healthy controls were analyzed using GEO2R and Venn diagrams. We annotated these genes based on their functions and signaling pathways, and then protein-protein interactions (PPIs) were identified using the Search Tool for the Retrieval of Interacting Genes. The data were further analyzed with Cytoscape software and the Molecular Complex Detection (MCODE) app. The core genes were selected and a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed. Finally, colitis model mice were established by administering DSS, and the top three core genes were verified in colitis mice using real-time polymerase chain reaction (PCR). RESULTS: One hundred and seventy-seven DEGs, 118 upregulated and 59 downregulated, were initially identified from the GEO2R analysis and predominantly participated in inflammation-related pathways. Seven clusters with close interactions in UC formed: Seventeen core genes were upregulated [C-X-C motif chemokine ligand 13 (CXCL13), C-X-C motif chemokine receptor 2 (CXCR2), CXCL9, CXCL5, C-C motif chemokine ligand 18, interleukin 1 beta, matrix metallopeptidase 9, CXCL3, formyl peptide receptor 1, complement component 3, CXCL8, CXCL1, CXCL10, CXCL2, CXCL6, CXCL11 and hydroxycarboxylic acid receptor 3] and one was downregulated [neuropeptide Y receptor Y1 (NYP1R)] in the top cluster according to the PPI and MCODE analyses. These genes were substantially enriched in the cytokine-cytokine receptor interaction and chemokine signaling pathways. The top three core genes (CXCL13, NYP1R, and CXCR2) were selected and verified in a mouse model of colitis using real-time PCR Increased expression was observed compared with the control mice, but only CXCR2 expression was significantly different. CONCLUSION: Core DEGs identified in UC are related to inflammation and immunity inflammation, indicating that these reactions are core features of the pathogenesis of UC. CXCR2 may reflect the degree of inflammation in patients with UC.
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spelling pubmed-75840512020-10-30 Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses Shi, Lei Han, Xiao Li, Jun-Xiang Liao, Yu-Ting Kou, Fu-Shun Wang, Zhi-Bin Shi, Rui Zhao, Xing-Jie Sun, Zhong-Mei Hao, Yu World J Gastroenterol Basic Study BACKGROUND: Ulcerative colitis (UC) is an inflammatory bowel disease that is difficult to diagnose and treat. To date, the degree of inflammation in patients with UC has mainly been determined by measuring the levels of nonspecific indicators, such as C-reactive protein and the erythrocyte sedimentation rate, but these indicators have an unsatisfactory specificity. In this study, we performed bioinformatics analysis using data from the National Center for Biotechnology Information-Gene Expression Omnibus (NCBI-GEO) databases and verified the selected core genes in a mouse model of dextran sulfate sodium (DSS)-induced colitis. AIM: To identify UC-related differentially expressed genes (DEGs) using a bioinformatics analysis and verify them in vivo and to identify novel biomarkers and the underlying mechanisms of UC. METHODS: Two microarray datasets from the NCBI-GEO database were used, and DEGs between patients with UC and healthy controls were analyzed using GEO2R and Venn diagrams. We annotated these genes based on their functions and signaling pathways, and then protein-protein interactions (PPIs) were identified using the Search Tool for the Retrieval of Interacting Genes. The data were further analyzed with Cytoscape software and the Molecular Complex Detection (MCODE) app. The core genes were selected and a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed. Finally, colitis model mice were established by administering DSS, and the top three core genes were verified in colitis mice using real-time polymerase chain reaction (PCR). RESULTS: One hundred and seventy-seven DEGs, 118 upregulated and 59 downregulated, were initially identified from the GEO2R analysis and predominantly participated in inflammation-related pathways. Seven clusters with close interactions in UC formed: Seventeen core genes were upregulated [C-X-C motif chemokine ligand 13 (CXCL13), C-X-C motif chemokine receptor 2 (CXCR2), CXCL9, CXCL5, C-C motif chemokine ligand 18, interleukin 1 beta, matrix metallopeptidase 9, CXCL3, formyl peptide receptor 1, complement component 3, CXCL8, CXCL1, CXCL10, CXCL2, CXCL6, CXCL11 and hydroxycarboxylic acid receptor 3] and one was downregulated [neuropeptide Y receptor Y1 (NYP1R)] in the top cluster according to the PPI and MCODE analyses. These genes were substantially enriched in the cytokine-cytokine receptor interaction and chemokine signaling pathways. The top three core genes (CXCL13, NYP1R, and CXCR2) were selected and verified in a mouse model of colitis using real-time PCR Increased expression was observed compared with the control mice, but only CXCR2 expression was significantly different. CONCLUSION: Core DEGs identified in UC are related to inflammation and immunity inflammation, indicating that these reactions are core features of the pathogenesis of UC. CXCR2 may reflect the degree of inflammation in patients with UC. Baishideng Publishing Group Inc 2020-10-21 2020-10-21 /pmc/articles/PMC7584051/ /pubmed/33132649 http://dx.doi.org/10.3748/wjg.v26.i39.5983 Text en ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Basic Study
Shi, Lei
Han, Xiao
Li, Jun-Xiang
Liao, Yu-Ting
Kou, Fu-Shun
Wang, Zhi-Bin
Shi, Rui
Zhao, Xing-Jie
Sun, Zhong-Mei
Hao, Yu
Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
title Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
title_full Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
title_fullStr Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
title_full_unstemmed Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
title_short Identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
title_sort identification of differentially expressed genes in ulcerative colitis and verification in a colitis mouse model by bioinformatics analyses
topic Basic Study
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7584051/
https://www.ncbi.nlm.nih.gov/pubmed/33132649
http://dx.doi.org/10.3748/wjg.v26.i39.5983
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