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Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis

BACKGROUND: IgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune...

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Autores principales: Jia, Xianxian, Zhu, Hua, Jiang, Qinglian, Gu, Jia, Yu, Shihan, Chi, Xuyang, Wang, Rui, Shan, Yu, Jiang, Hong, Ma, Xiaoxue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10070996/
https://www.ncbi.nlm.nih.gov/pubmed/37026011
http://dx.doi.org/10.3389/fimmu.2023.1087293
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author Jia, Xianxian
Zhu, Hua
Jiang, Qinglian
Gu, Jia
Yu, Shihan
Chi, Xuyang
Wang, Rui
Shan, Yu
Jiang, Hong
Ma, Xiaoxue
author_facet Jia, Xianxian
Zhu, Hua
Jiang, Qinglian
Gu, Jia
Yu, Shihan
Chi, Xuyang
Wang, Rui
Shan, Yu
Jiang, Hong
Ma, Xiaoxue
author_sort Jia, Xianxian
collection PubMed
description BACKGROUND: IgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN. METHODS: GSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN. RESULT: A total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN. CONCLUSION: We screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN.
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spelling pubmed-100709962023-04-05 Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis Jia, Xianxian Zhu, Hua Jiang, Qinglian Gu, Jia Yu, Shihan Chi, Xuyang Wang, Rui Shan, Yu Jiang, Hong Ma, Xiaoxue Front Immunol Immunology BACKGROUND: IgAV, the most common systemic vasculitis in childhood, is an immunoglobulin A-associated immune complex-mediated disease and its underlying molecular mechanisms are not fully understood. This study attempted to identify differentially expressed genes (DEGs) and find dysregulated immune cell types in IgAV to find the underlying pathogenesis for IgAVN. METHODS: GSE102114 datasets were obtained from the Gene Expression Omnibus (GEO) database to identify DEGs. Then, the protein-protein interaction (PPI) network of the DEGs was constructed using the STRING database. And key hub genes were identified by cytoHubba plug-in, performed functional enrichment analyses and followed by verification using PCR based on patient samples. Finally, the abundance of 24 immune cells were detected by Immune Cell Abundance Identifier (ImmuCellAI) to estimate the proportions and dysregulation of immune cell types within IgAVN. RESULT: A total of 4200 DEGs were screened in IgAVN patients compared to Health Donor, including 2004 upregulated and 2196 downregulated genes. Of the top 10 hub genes from PPI network, STAT1, TLR4, PTEN, UBB, HSPA8, ATP5B, UBA52, and CDC42 were verified significantly upregulated in more patients. Enrichment analyses indicated that hub genes were primarily enriched in Toll-like receptor (TLR) signaling pathway, nucleotide oligomerization domain (NOD)-like receptor signaling pathway, and Th17 signaling pathways. Moreover, we found a diversity of immune cells in IgAVN, consisting mainly of T cells. Finally, this study suggests that the overdifferentiation of Th2 cells, Th17 cells and Tfh cells may be involved in the occurrence and development of IgAVN. CONCLUSION: We screened out the key genes, pathways and maladjusted immune cells and associated with the pathogenesis of IgAVN. The unique characteristics of IgAV-infiltrating immune cell subsets were confirmed, providing new insights for future molecular targeted therapy and a direction for immunological research on IgAVN. Frontiers Media S.A. 2023-03-21 /pmc/articles/PMC10070996/ /pubmed/37026011 http://dx.doi.org/10.3389/fimmu.2023.1087293 Text en Copyright © 2023 Jia, Zhu, Jiang, Gu, Yu, Chi, Wang, Shan, Jiang and Ma https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Jia, Xianxian
Zhu, Hua
Jiang, Qinglian
Gu, Jia
Yu, Shihan
Chi, Xuyang
Wang, Rui
Shan, Yu
Jiang, Hong
Ma, Xiaoxue
Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis
title Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis
title_full Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis
title_fullStr Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis
title_full_unstemmed Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis
title_short Identification of key genes and imbalance of immune cell infiltration in immunoglobulin A associated vasculitis nephritis by integrated bioinformatic analysis
title_sort identification of key genes and imbalance of immune cell infiltration in immunoglobulin a associated vasculitis nephritis by integrated bioinformatic analysis
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10070996/
https://www.ncbi.nlm.nih.gov/pubmed/37026011
http://dx.doi.org/10.3389/fimmu.2023.1087293
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