Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury
BackgroundSpinal cord injury (SCI) poses a substantial challenge in contemporary medicine, significantly impacting patients and society. Emerging research highlights a strong association between SCI and chronic pain, yet the molecular mechanisms remain poorly understood. To address this, we conducte...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Cellular Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fncel.2025.1457740/full |
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| author | Jinlong Zhang Jinlong Zhang Longju Qi Yuyu Sun Yuyu Sun Shiyuan Chen Jinyi Liu Jiaxi Chen Fangsu Yan Wenqi Wang Qinghua Wang Liang Chen |
| author_facet | Jinlong Zhang Jinlong Zhang Longju Qi Yuyu Sun Yuyu Sun Shiyuan Chen Jinyi Liu Jiaxi Chen Fangsu Yan Wenqi Wang Qinghua Wang Liang Chen |
| author_sort | Jinlong Zhang |
| collection | DOAJ |
| description | BackgroundSpinal cord injury (SCI) poses a substantial challenge in contemporary medicine, significantly impacting patients and society. Emerging research highlights a strong association between SCI and chronic pain, yet the molecular mechanisms remain poorly understood. To address this, we conducted bioinformatics and systems biology analyses to identify molecular biomarkers and pathways that link SCI to chronic pain. This study aims to elucidate these mechanisms and identify potential therapeutic targets.MethodsThrough analysis of the GSE151371 and GSE177034 databases, we identified differentially expressed genes (DEGs) linked to SCI and chronic pain. This analysis uncovered shared pathways, proteins, transcription factor networks, hub genes, and potential therapeutic drugs. Regression analysis on the hub genes facilitated the development of a prognostic risk model. Additionally, we conducted an in-depth examination of immune infiltration in SCI to elucidate its correlation with chronic pain.ResultsAnalyzing 101 DEGs associated with SCI and chronic pain, we constructed a protein interaction network and identified 15 hub genes. Using bioinformatics tools, we further identified 4 potential candidate genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed a strong correlation between SCI and chronic pain, particularly related to inflammation. Additionally, we examined the relationship between SCI and immune cell infiltration, discovering a significant link between SCI and T cell activation. This is notable as activated T cells can cause persistent inflammation and chronic pain. Lastly, we analyzed the hub genes to explore the transcription factor network, potential therapeutic drugs, and ceRNA networks.ConclusionThe analysis of 15 hub genes as significant biological markers for SCI and chronic pain has led to the identification of several potential drugs for treatment. |
| format | Article |
| id | doaj-art-cf7f3bf5cdd64e55844330b1e5eedefa |
| institution | Kabale University |
| issn | 1662-5102 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Cellular Neuroscience |
| spelling | doaj-art-cf7f3bf5cdd64e55844330b1e5eedefa2025-02-05T07:31:51ZengFrontiers Media S.A.Frontiers in Cellular Neuroscience1662-51022025-02-011910.3389/fncel.2025.14577401457740Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injuryJinlong Zhang0Jinlong Zhang1Longju Qi2Yuyu Sun3Yuyu Sun4Shiyuan Chen5Jinyi Liu6Jiaxi Chen7Fangsu Yan8Wenqi Wang9Qinghua Wang10Liang Chen11Department of Orthopaedic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaDepartment of Spine Surgery, Nantong City No.1 People's Hospital and Second Affiliated Hospital of Nantong University, Nantong, Jiangsu, ChinaAffiliated Nantong Hospital 3 of Nantong University Department of Orthopedic and Nantong Third People's Hospital of Nantong University, Nantong, Jiangsu, ChinaDepartment of Orthopaedic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaAffiliated Nantong Hospital 3 of Nantong University Department of Orthopedic and Nantong Third People's Hospital of Nantong University, Nantong, Jiangsu, ChinaSchool of Medicine, Nantong University, Nantong, Jiangsu, ChinaSchool of Medicine, Nantong University, Nantong, Jiangsu, ChinaSchool of Medicine, Nantong University, Nantong, Jiangsu, ChinaSchool of Medicine, Nantong University, Nantong, Jiangsu, ChinaSchool of Medical Imaging, Nanjing Medical University, Nanjing, Jiangsu, ChinaState-Owned Assets Administration Office, Nantong University, Nantong, Jiangsu, ChinaDepartment of Orthopaedic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, ChinaBackgroundSpinal cord injury (SCI) poses a substantial challenge in contemporary medicine, significantly impacting patients and society. Emerging research highlights a strong association between SCI and chronic pain, yet the molecular mechanisms remain poorly understood. To address this, we conducted bioinformatics and systems biology analyses to identify molecular biomarkers and pathways that link SCI to chronic pain. This study aims to elucidate these mechanisms and identify potential therapeutic targets.MethodsThrough analysis of the GSE151371 and GSE177034 databases, we identified differentially expressed genes (DEGs) linked to SCI and chronic pain. This analysis uncovered shared pathways, proteins, transcription factor networks, hub genes, and potential therapeutic drugs. Regression analysis on the hub genes facilitated the development of a prognostic risk model. Additionally, we conducted an in-depth examination of immune infiltration in SCI to elucidate its correlation with chronic pain.ResultsAnalyzing 101 DEGs associated with SCI and chronic pain, we constructed a protein interaction network and identified 15 hub genes. Using bioinformatics tools, we further identified 4 potential candidate genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses revealed a strong correlation between SCI and chronic pain, particularly related to inflammation. Additionally, we examined the relationship between SCI and immune cell infiltration, discovering a significant link between SCI and T cell activation. This is notable as activated T cells can cause persistent inflammation and chronic pain. Lastly, we analyzed the hub genes to explore the transcription factor network, potential therapeutic drugs, and ceRNA networks.ConclusionThe analysis of 15 hub genes as significant biological markers for SCI and chronic pain has led to the identification of several potential drugs for treatment.https://www.frontiersin.org/articles/10.3389/fncel.2025.1457740/fullspinal cord injurychronic paindisease biomarkerhub genesinflammatory cellsdrug |
| spellingShingle | Jinlong Zhang Jinlong Zhang Longju Qi Yuyu Sun Yuyu Sun Shiyuan Chen Jinyi Liu Jiaxi Chen Fangsu Yan Wenqi Wang Qinghua Wang Liang Chen Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury Frontiers in Cellular Neuroscience spinal cord injury chronic pain disease biomarker hub genes inflammatory cells drug |
| title | Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury |
| title_full | Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury |
| title_fullStr | Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury |
| title_full_unstemmed | Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury |
| title_short | Integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury |
| title_sort | integrated bioinformatics analysis of the effects of chronic pain on patients with spinal cord injury |
| topic | spinal cord injury chronic pain disease biomarker hub genes inflammatory cells drug |
| url | https://www.frontiersin.org/articles/10.3389/fncel.2025.1457740/full |
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