Back to Search Start Over

Identification of Oxidative Stress-Related Biomarkers for Pain–Depression Comorbidity Based on Bioinformatics

Authors :
Tianyun Zhang
Menglu Geng
Xiaoke Li
Yulin Gu
Wenjing Zhao
Qi Ning
Zijie Zhao
Lei Wang
Huaxing Zhang
Fan Zhang
Source :
International Journal of Molecular Sciences, Vol 25, Iss 15, p 8353 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

Oxidative stress has been identified as a major factor in the development and progression of pain and psychiatric disorders, but the underlying biomarkers and molecular signaling pathways remain unclear. This study aims to identify oxidative stress-related biomarkers and signaling pathways in pain–depression comorbidity. Integrated bioinformatics analyses were applied to identify key genes by comparing pain–depression comorbidity-related genes and oxidative stress-related genes. A total of 580 differentially expressed genes and 35 differentially expressed oxidative stress-related genes (DEOSGs) were identified. By using a weighted gene co-expression network analysis and a protein–protein interaction network, 43 key genes and 5 hub genes were screened out, respectively. DEOSGs were enriched in biological processes and signaling pathways related to oxidative stress and inflammation. The five hub genes, RNF24, MGAM, FOS, and TKT, were deemed potential diagnostic and prognostic markers for patients with pain–depression comorbidity. These genes may serve as valuable targets for further research and may aid in the development of early diagnosis, prevention strategies, and pharmacotherapy tools for this particular patient population.

Details

Language :
English
ISSN :
14220067 and 16616596
Volume :
25
Issue :
15
Database :
Directory of Open Access Journals
Journal :
International Journal of Molecular Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.2ea650ba8e4c41bab42335bd3d0507db
Document Type :
article
Full Text :
https://doi.org/10.3390/ijms25158353