Uncovering periodontitis-associated markers through the aggregation of transcriptomics information from diverse sources.

ABSTRACT:

Introduction

Periodontitis, a common chronic inflammatory disease, significantly impacted oral health. To provide novel biological indicators for the diagnosis and treatment of periodontitis, we analyzed public microarray datasets to identify biomarkers associated with periodontitis.

Method

The Gene Expression Omnibus (GEO) datasets GSE16134 and GSE106090 were downloaded. We performed differential analysis and robust rank aggregation (RRA) to obtain a list of differential genes. To obtain the core modules and core genes related to periodontitis, we evaluated differential genes through enrichment analysis, correlation analysis, protein-protein interaction (PPI) network and competing endogenous RNA (ceRNA) network analysis. Potential biomarkers for periodontitis were identifie

SUBMITTER: Peng C 

PROVIDER: S-EPMC11196414 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature