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Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis
BACKGROUND: Epilepsy is a prevalent neurological disorder, and while its precise mechanism remains elusive, a connection to ferroptosis has been established. This study investigates the potential clinical diagnostic significance of ferroptosis-related genes (FRGs) during the acute phase of temporal...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636915/ https://www.ncbi.nlm.nih.gov/pubmed/37946105 http://dx.doi.org/10.1186/s12864-023-09782-8 |
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author | Chen, Shihao Jin, Xing He, Tao Zhang, Mulan Xu, Huiqin |
author_facet | Chen, Shihao Jin, Xing He, Tao Zhang, Mulan Xu, Huiqin |
author_sort | Chen, Shihao |
collection | PubMed |
description | BACKGROUND: Epilepsy is a prevalent neurological disorder, and while its precise mechanism remains elusive, a connection to ferroptosis has been established. This study investigates the potential clinical diagnostic significance of ferroptosis-related genes (FRGs) during the acute phase of temporal lobe epilepsy. METHODS: To identify differentially expressed genes (DEGs), we accessed data from the GEO database and performed an intersection analysis with the FerrDB database to pinpoint FRGs. A protein-protein interaction (PPI) network was constructed. To assess the diagnostic utility of the discovered feature genes for the disease, ROC curve analysis was conducted. Subsequently, qRT-PCR was employed to validate the expression levels of these feature genes. RESULTS: This study identified a total of 25 FRGs. PPI network analysis revealed six feature genes: IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN. ROC curve analysis demonstrated that the combination of these six feature genes exhibited the highest diagnostic potential. qRT-PCR validation confirmed the expression of these feature genes. CONCLUSION: We have identified six feature genes (IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN) strongly associated with ferroptosis in epilepsy, suggesting their potential as biomarkers for the diagnosis of temporal lobe epilepsy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09782-8. |
format | Online Article Text |
id | pubmed-10636915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106369152023-11-11 Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis Chen, Shihao Jin, Xing He, Tao Zhang, Mulan Xu, Huiqin BMC Genomics Research BACKGROUND: Epilepsy is a prevalent neurological disorder, and while its precise mechanism remains elusive, a connection to ferroptosis has been established. This study investigates the potential clinical diagnostic significance of ferroptosis-related genes (FRGs) during the acute phase of temporal lobe epilepsy. METHODS: To identify differentially expressed genes (DEGs), we accessed data from the GEO database and performed an intersection analysis with the FerrDB database to pinpoint FRGs. A protein-protein interaction (PPI) network was constructed. To assess the diagnostic utility of the discovered feature genes for the disease, ROC curve analysis was conducted. Subsequently, qRT-PCR was employed to validate the expression levels of these feature genes. RESULTS: This study identified a total of 25 FRGs. PPI network analysis revealed six feature genes: IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN. ROC curve analysis demonstrated that the combination of these six feature genes exhibited the highest diagnostic potential. qRT-PCR validation confirmed the expression of these feature genes. CONCLUSION: We have identified six feature genes (IL6, PTGS2, HMOX1, NFE2L2, TLR4, and JUN) strongly associated with ferroptosis in epilepsy, suggesting their potential as biomarkers for the diagnosis of temporal lobe epilepsy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-023-09782-8. BioMed Central 2023-11-09 /pmc/articles/PMC10636915/ /pubmed/37946105 http://dx.doi.org/10.1186/s12864-023-09782-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Chen, Shihao Jin, Xing He, Tao Zhang, Mulan Xu, Huiqin Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
title | Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
title_full | Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
title_fullStr | Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
title_full_unstemmed | Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
title_short | Identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
title_sort | identification of ferroptosis-related genes in acute phase of temporal lobe epilepsy based on bioinformatic analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10636915/ https://www.ncbi.nlm.nih.gov/pubmed/37946105 http://dx.doi.org/10.1186/s12864-023-09782-8 |
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