Integrated bioinformatics analysis identifies glutathione metabolism-related genes as diagnostic biomarkers for periodontitis.

ABSTRACT:

Background

Periodontitis affects over 1 billion people globally, with oxidative stress and glutathione depletion playing crucial roles in disease progression. This study aimed to identify glutathione metabolism-related genes as diagnostic biomarkers for periodontitis using integrated bioinformatics approaches.

Methods

Weighted Gene Co-expression Network Analysis (WGCNA) was performed on independent datasets. Key genes were identified in combination with GSE16134 dataset differential expression analysis, which were then validated in the GSE10334 dataset. Immune infiltration analysis using CIBERSORT algorithm, consensus clustering for molecular subtyping, and competing endogenous RNA (ceRNA) network construction were conducted to explore regulatory mechanisms. Drug-gene intera

SUBMITTER: Meng L 

PROVIDER: S-EPMC12502236 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature