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Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis
BACKGROUND: Temporal lobe epilepsy (TLE) is a common brain disease. However, the pathogenesis of TLE and its relationship with immune infiltration remains unclear. We attempted to identify inflammation-related genes (IRGs) and the immune cell infiltration pattern involved in the pathological process...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648357/ https://www.ncbi.nlm.nih.gov/pubmed/36389252 http://dx.doi.org/10.3389/fnins.2022.996368 |
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author | Wang, Li Duan, Chunmei Wang, Ruodan Chen, Lifa Wang, Yue |
author_facet | Wang, Li Duan, Chunmei Wang, Ruodan Chen, Lifa Wang, Yue |
author_sort | Wang, Li |
collection | PubMed |
description | BACKGROUND: Temporal lobe epilepsy (TLE) is a common brain disease. However, the pathogenesis of TLE and its relationship with immune infiltration remains unclear. We attempted to identify inflammation-related genes (IRGs) and the immune cell infiltration pattern involved in the pathological process of TLE via bioinformatics analysis. MATERIALS AND METHODS: The GSE88992 dataset was downloaded from the Gene Expression Omnibus (GEO) database to perform differentially expressed genes screening and weighted gene co-expression network analysis (WGCNA). Subsequently, the functional enrichment analysis was performed to explore the biological function of the differentially expressed IRGs (DEIRGs). The hub genes were further identified by the CytoHubba algorithm and validated by an external dataset (GSE60772). Furthermore, the CIBERSORT algorithm was applied to assess the differential immune cell infiltration between control and TLE groups. Finally, we used the DGIbd database to screen the candidate drugs for TLE. RESULTS: 34 DEIRGs (33 up-regulated and 1 down-regulated gene) were identified, and they were significantly enriched in inflammation- and immune-related pathways. Subsequently, 4 hub DEIRGs (Ptgs2, Jun, Icam1, Il6) were further identified. Immune cell infiltration analysis revealed that T cells CD4 memory resting, NK cells activated, Monocytes and Dendritic cells activated were involved in the TLE development. Besides, there was a significant correlation between hub DEIRGs and some of the specific immune cells. CONCLUSION: 4 hub DEIRGs (Ptgs2, Jun, Icam1, Il6) were associated with the pathogenesis of TLE via regulation of immune cell functions, which provided a novel perspective for the understanding of TLE. |
format | Online Article Text |
id | pubmed-9648357 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96483572022-11-15 Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis Wang, Li Duan, Chunmei Wang, Ruodan Chen, Lifa Wang, Yue Front Neurosci Neuroscience BACKGROUND: Temporal lobe epilepsy (TLE) is a common brain disease. However, the pathogenesis of TLE and its relationship with immune infiltration remains unclear. We attempted to identify inflammation-related genes (IRGs) and the immune cell infiltration pattern involved in the pathological process of TLE via bioinformatics analysis. MATERIALS AND METHODS: The GSE88992 dataset was downloaded from the Gene Expression Omnibus (GEO) database to perform differentially expressed genes screening and weighted gene co-expression network analysis (WGCNA). Subsequently, the functional enrichment analysis was performed to explore the biological function of the differentially expressed IRGs (DEIRGs). The hub genes were further identified by the CytoHubba algorithm and validated by an external dataset (GSE60772). Furthermore, the CIBERSORT algorithm was applied to assess the differential immune cell infiltration between control and TLE groups. Finally, we used the DGIbd database to screen the candidate drugs for TLE. RESULTS: 34 DEIRGs (33 up-regulated and 1 down-regulated gene) were identified, and they were significantly enriched in inflammation- and immune-related pathways. Subsequently, 4 hub DEIRGs (Ptgs2, Jun, Icam1, Il6) were further identified. Immune cell infiltration analysis revealed that T cells CD4 memory resting, NK cells activated, Monocytes and Dendritic cells activated were involved in the TLE development. Besides, there was a significant correlation between hub DEIRGs and some of the specific immune cells. CONCLUSION: 4 hub DEIRGs (Ptgs2, Jun, Icam1, Il6) were associated with the pathogenesis of TLE via regulation of immune cell functions, which provided a novel perspective for the understanding of TLE. Frontiers Media S.A. 2022-10-27 /pmc/articles/PMC9648357/ /pubmed/36389252 http://dx.doi.org/10.3389/fnins.2022.996368 Text en Copyright © 2022 Wang, Duan, Wang, Chen and Wang. 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 | Neuroscience Wang, Li Duan, Chunmei Wang, Ruodan Chen, Lifa Wang, Yue Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
title | Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
title_full | Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
title_fullStr | Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
title_full_unstemmed | Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
title_short | Inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
title_sort | inflammation-related genes and immune infiltration landscape identified in kainite-induced temporal lobe epilepsy based on integrated bioinformatics analysis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648357/ https://www.ncbi.nlm.nih.gov/pubmed/36389252 http://dx.doi.org/10.3389/fnins.2022.996368 |
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