Integrating GEO Database, Mendelian Randomization, and Molecular Docking to Identify HLA-C as a Potential Therapeutic Target for Periodontitis.

ABSTRACT: Background: Periodontitis is a chronic inflammatory disease that leads to the destruction of periodontal tissues, ultimately resulting in tooth loss. Current treatments primarily focus on mitigating inflammation and alleviating symptoms, but they often lack specificity. This study aims to explore the molecular mechanisms of periodontitis using gene expression databases (GEOs) and bioinformatics methods, combined with Mendelian randomization (MR) analysis, to identify key therapeutic targets. Methods: This study analyzed GSE10334 microarray data to identify differentially expressed genes (DEGs) in periodontitis using R. Weighted gene co-expression network analysis (WGCNA) identified key gene modules and enrichment analysis revealed functional pathways. Immune infiltration was

SUBMITTER: Shi C 

PROVIDER: S-EPMC12279435 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature