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Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data

BACKGROUND: Epilepsy encompasses a group of heterogeneous brain diseases that afflict about 1% of the world’s population. Accumulating evidence shows that the immune system plays a key role in epileptogenesis. Nevertheless, the immune-related mechanisms remain not been precisely understood. METHODS:...

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Autores principales: Hou, Yunqi, Chen, Zhen, Wang, Liping, Deng, Yingxin, Liu, Genglong, Zhou, Yongfen, Shi, Haiqin, Shi, Xiangqun, Jiang, Qianhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9084924/
https://www.ncbi.nlm.nih.gov/pubmed/35547834
http://dx.doi.org/10.2147/JIR.S360743
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author Hou, Yunqi
Chen, Zhen
Wang, Liping
Deng, Yingxin
Liu, Genglong
Zhou, Yongfen
Shi, Haiqin
Shi, Xiangqun
Jiang, Qianhua
author_facet Hou, Yunqi
Chen, Zhen
Wang, Liping
Deng, Yingxin
Liu, Genglong
Zhou, Yongfen
Shi, Haiqin
Shi, Xiangqun
Jiang, Qianhua
author_sort Hou, Yunqi
collection PubMed
description BACKGROUND: Epilepsy encompasses a group of heterogeneous brain diseases that afflict about 1% of the world’s population. Accumulating evidence shows that the immune system plays a key role in epileptogenesis. Nevertheless, the immune-related mechanisms remain not been precisely understood. METHODS: Three epilepsy datasets (GSE16969, GSE32534 and GSE143272) were screened to obtain differentially expressed immune-related genes (DEIRGs). Random forest (RF) and protein–protein interaction (PPI) network were constructed to identify core genes. Another dataset (GSE31718) and 60 clinical samples via quantitative real-time polymerase chain reaction (qRT-PCR) were utilized to validate core genes. Immune cell infiltration score was performed with CIBERSORTx tools and single-sample gene set enrichment analysis (ssGSEA). Gene set variation analysis (GSVA) and ssGSEA were conducted to determine the pathways that are significantly enriched during normal and epilepsy. The correlation between hub genes, immune cells, and enriched molecular pathways was evaluated by Pearson correlation analysis. RESULTS: Based on RF and PPI, 4 DEIRGs (CSF1R, IL6R, TLR2, and TNFRSF1A) were identified as hub genes. Results of qRT-PCR validated that higher expression levels of CSF1R, IL6R, TLR2, and TNFRSF1A in epilepsy samples compared to control sample. Immune infiltration analysis by CIBERSORTx displayed immune signatures that are significantly richer in epilepsy, T cell subsets in particular. Notably, ssGSEA found that Th1 signatures were more abundant in normal tissues; yet Th2 signatures were more abundant in epilepsy tissues. Cytokine cytokine receptor interaction (CCR) was significantly enriched in epilepsy based on multi-transcriptome data. Additionally, hub genes were significantly correlated with score of Th1/Th2 signatures and enrichment score of CCR in multi-transcriptome data. CONCLUSION: Four IRGs (CSF1R, IL6R, TLR2, and TNFRSF1A) were closely correlated pathogenesis of epilepsy, which may be by impacting CCR and the balance of Th1/Th2 signatures involved in the occurrence of epilepsy. Our data offer compelling insights into the pathogenesis and promising therapeutic targets for epilepsy.
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spelling pubmed-90849242022-05-10 Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data Hou, Yunqi Chen, Zhen Wang, Liping Deng, Yingxin Liu, Genglong Zhou, Yongfen Shi, Haiqin Shi, Xiangqun Jiang, Qianhua J Inflamm Res Original Research BACKGROUND: Epilepsy encompasses a group of heterogeneous brain diseases that afflict about 1% of the world’s population. Accumulating evidence shows that the immune system plays a key role in epileptogenesis. Nevertheless, the immune-related mechanisms remain not been precisely understood. METHODS: Three epilepsy datasets (GSE16969, GSE32534 and GSE143272) were screened to obtain differentially expressed immune-related genes (DEIRGs). Random forest (RF) and protein–protein interaction (PPI) network were constructed to identify core genes. Another dataset (GSE31718) and 60 clinical samples via quantitative real-time polymerase chain reaction (qRT-PCR) were utilized to validate core genes. Immune cell infiltration score was performed with CIBERSORTx tools and single-sample gene set enrichment analysis (ssGSEA). Gene set variation analysis (GSVA) and ssGSEA were conducted to determine the pathways that are significantly enriched during normal and epilepsy. The correlation between hub genes, immune cells, and enriched molecular pathways was evaluated by Pearson correlation analysis. RESULTS: Based on RF and PPI, 4 DEIRGs (CSF1R, IL6R, TLR2, and TNFRSF1A) were identified as hub genes. Results of qRT-PCR validated that higher expression levels of CSF1R, IL6R, TLR2, and TNFRSF1A in epilepsy samples compared to control sample. Immune infiltration analysis by CIBERSORTx displayed immune signatures that are significantly richer in epilepsy, T cell subsets in particular. Notably, ssGSEA found that Th1 signatures were more abundant in normal tissues; yet Th2 signatures were more abundant in epilepsy tissues. Cytokine cytokine receptor interaction (CCR) was significantly enriched in epilepsy based on multi-transcriptome data. Additionally, hub genes were significantly correlated with score of Th1/Th2 signatures and enrichment score of CCR in multi-transcriptome data. CONCLUSION: Four IRGs (CSF1R, IL6R, TLR2, and TNFRSF1A) were closely correlated pathogenesis of epilepsy, which may be by impacting CCR and the balance of Th1/Th2 signatures involved in the occurrence of epilepsy. Our data offer compelling insights into the pathogenesis and promising therapeutic targets for epilepsy. Dove 2022-05-05 /pmc/articles/PMC9084924/ /pubmed/35547834 http://dx.doi.org/10.2147/JIR.S360743 Text en © 2022 Hou et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Hou, Yunqi
Chen, Zhen
Wang, Liping
Deng, Yingxin
Liu, Genglong
Zhou, Yongfen
Shi, Haiqin
Shi, Xiangqun
Jiang, Qianhua
Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data
title Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data
title_full Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data
title_fullStr Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data
title_full_unstemmed Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data
title_short Characterization of Immune-Related Genes and Immune Infiltration Features in Epilepsy by Multi-Transcriptome Data
title_sort characterization of immune-related genes and immune infiltration features in epilepsy by multi-transcriptome data
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9084924/
https://www.ncbi.nlm.nih.gov/pubmed/35547834
http://dx.doi.org/10.2147/JIR.S360743
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