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Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis

BACKGROUND: Ulcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affects mucosal homeostasis and triggers an inappropriate immune response. Single-cell RNA sequencing (scRNA-seq) can be used to rapidly obtain the precise gene expre...

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Autores principales: Dai, Yan-Cheng, Qiao, Dan, Fang, Chen-Ye, Chen, Qiu-Qin, Que, Ren-Ye, Xiao, Tie-Gang, Zheng, Lie, Wang, Li-Juan, Zhang, Ya-Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9724533/
https://www.ncbi.nlm.nih.gov/pubmed/36483809
http://dx.doi.org/10.12998/wjcc.v10.i33.12116
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author Dai, Yan-Cheng
Qiao, Dan
Fang, Chen-Ye
Chen, Qiu-Qin
Que, Ren-Ye
Xiao, Tie-Gang
Zheng, Lie
Wang, Li-Juan
Zhang, Ya-Li
author_facet Dai, Yan-Cheng
Qiao, Dan
Fang, Chen-Ye
Chen, Qiu-Qin
Que, Ren-Ye
Xiao, Tie-Gang
Zheng, Lie
Wang, Li-Juan
Zhang, Ya-Li
author_sort Dai, Yan-Cheng
collection PubMed
description BACKGROUND: Ulcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affects mucosal homeostasis and triggers an inappropriate immune response. Single-cell RNA sequencing (scRNA-seq) can be used to rapidly obtain the precise gene expression patterns of thousands of cells in the intestine, analyze the characteristics of cells with the same phenotype, and provide new insights into the growth and development of intestinal organs, the clonal evolution of cells, and immune cell changes. These findings can provide new ideas for the diagnosis and treatment of intestinal diseases. AIM: To identify clinical phenotypes and biomarkers that can predict the response of UC patients to specific therapeutic drugs and thus aid the diagnosis and treatment of UC. METHODS: Using the Gene Expression Omnibus (GEO) database, we analyzed peripheral blood cell subtypes of patients with UC by scRNA-seq combined with bulk RNA sequencing (RNA-seq) to reveal the core genes of UC. We then combined weighted gene correlation network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analysis to reveal diagnostic markers of UC. RESULTS: After processing the scRNA-seq data, we obtained data from approximately 24340 cells and identified 17 cell types. Through intercellular communication analysis, we selected monocyte marker genes as the candidate gene set for the prediction model. Construction of a WGCNA coexpression network identified RhoB, cathepsin D (CTSD) and zyxin (ZYX) as core genes. Immune infiltration analysis showed that these three core genes were strongly correlated with immune cells. Functional enrichment analysis showed that the differentially expressed genes were closely related to immune and inflammatory responses, which are associated with many challenges in the diagnosis and treatment of UC. CONCLUSION: Through scRNA-seq analysis, LASSO diagnostic model building and WGCNA, we identified RhoB, CTSD and ZYX as core genes of UC that are closely related to monocyte infiltration that may serve as diagnostic markers and molecular targets for UC therapeutic intervention.
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spelling pubmed-97245332022-12-07 Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis Dai, Yan-Cheng Qiao, Dan Fang, Chen-Ye Chen, Qiu-Qin Que, Ren-Ye Xiao, Tie-Gang Zheng, Lie Wang, Li-Juan Zhang, Ya-Li World J Clin Cases Clinical and Translational Research BACKGROUND: Ulcerative colitis (UC) is a complicated disease caused by the interaction between genetic and environmental factors that affects mucosal homeostasis and triggers an inappropriate immune response. Single-cell RNA sequencing (scRNA-seq) can be used to rapidly obtain the precise gene expression patterns of thousands of cells in the intestine, analyze the characteristics of cells with the same phenotype, and provide new insights into the growth and development of intestinal organs, the clonal evolution of cells, and immune cell changes. These findings can provide new ideas for the diagnosis and treatment of intestinal diseases. AIM: To identify clinical phenotypes and biomarkers that can predict the response of UC patients to specific therapeutic drugs and thus aid the diagnosis and treatment of UC. METHODS: Using the Gene Expression Omnibus (GEO) database, we analyzed peripheral blood cell subtypes of patients with UC by scRNA-seq combined with bulk RNA sequencing (RNA-seq) to reveal the core genes of UC. We then combined weighted gene correlation network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) analysis to reveal diagnostic markers of UC. RESULTS: After processing the scRNA-seq data, we obtained data from approximately 24340 cells and identified 17 cell types. Through intercellular communication analysis, we selected monocyte marker genes as the candidate gene set for the prediction model. Construction of a WGCNA coexpression network identified RhoB, cathepsin D (CTSD) and zyxin (ZYX) as core genes. Immune infiltration analysis showed that these three core genes were strongly correlated with immune cells. Functional enrichment analysis showed that the differentially expressed genes were closely related to immune and inflammatory responses, which are associated with many challenges in the diagnosis and treatment of UC. CONCLUSION: Through scRNA-seq analysis, LASSO diagnostic model building and WGCNA, we identified RhoB, CTSD and ZYX as core genes of UC that are closely related to monocyte infiltration that may serve as diagnostic markers and molecular targets for UC therapeutic intervention. Baishideng Publishing Group Inc 2022-11-26 2022-11-26 /pmc/articles/PMC9724533/ /pubmed/36483809 http://dx.doi.org/10.12998/wjcc.v10.i33.12116 Text en ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved. https://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: https://creativecommons.org/Licenses/by-nc/4.0/
spellingShingle Clinical and Translational Research
Dai, Yan-Cheng
Qiao, Dan
Fang, Chen-Ye
Chen, Qiu-Qin
Que, Ren-Ye
Xiao, Tie-Gang
Zheng, Lie
Wang, Li-Juan
Zhang, Ya-Li
Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
title Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
title_full Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
title_fullStr Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
title_full_unstemmed Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
title_short Single-cell RNA-sequencing combined with bulk RNA-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
title_sort single-cell rna-sequencing combined with bulk rna-sequencing analysis of peripheral blood reveals the characteristics and key immune cell genes of ulcerative colitis
topic Clinical and Translational Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9724533/
https://www.ncbi.nlm.nih.gov/pubmed/36483809
http://dx.doi.org/10.12998/wjcc.v10.i33.12116
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