Elucidation of common molecular diagnostic biomarkers between chronic periodontitis and Parkinson's disease via bioinformatics analyses

Abstract

Background and ObjectivesParkinson's disease (PD) and chronic periodontitis (CP) are both inflammatory diseases; a correlation between the two diseases has been reported, but the underlying mechanisms of this association have not been investigated. We investigated the common molecular mechanisms between PD and CP and the role of immune cells in the pathogenesis of them using bioinformatics analyses to elucidate the association between the two diseases.MethodsWe obtained gene expression data from the Gene Expression Omnibus (GEO) database: GSE10334, GSE16134, and GSE23586 for CP gingival samples and GSE20146 for PD brain samples. Subsequently, we conducted an enrichment analysis of the differentially expressed genes (DEGs) using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. Moreover, all DEGs were analysed for protein–transcription factor interactions and protein–immune cell co‐expression. We constructed protein–transcription factor, protein–protein interaction (PPI), and protein–immune cell co‐expression networks using the Cytoscape software. Moreover, we identified the hub genes and investigated them for potential diagnostic value.Results and ConclusionWe identified 99 DEGs in the three CP datasets, 520 DEGs in the PD dataset and found five common DEGs in the CP and PD datasets, namely CXCR4, CXCL8, CD19, RPTN, and SLC16A9. These common DEGs identified in our study may have a potential impact on disease pathogenesis through the involvement of CXCR4‐CXCL8‐CD19 protein‐complexes in dendritic cells. Therefore, CD19, LCP2, CXCR4, and LYN could be used as target molecules for the clinical diagnosis of both diseases.

Investigating the Connection between Chronic Periodontitis and Parkinson’s Disease: Findings from a Korean National Cohort Study

“…This could render certain susceptible subgroups burdened with comorbidities more vulnerable to PD development. The most recent bioinformatic analyses identified certain differentially expressed genes (CXCR4, CXCL8, CD19, RPTN, and SLC16A9) in a few datasets of CP and PD [47]. This suggests the possible presence of susceptible individuals for both conditions, although the causal direction between CP and PD cannot be confirmed [47].…”

“…The most recent bioinformatic analyses identified certain differentially expressed genes (CXCR4, CXCL8, CD19, RPTN, and SLC16A9) in a few datasets of CP and PD [47]. This suggests the possible presence of susceptible individuals for both conditions, although the causal direction between CP and PD cannot be confirmed [47]. Indeed, a gradual increase in hazard ratios for incident PD has been observed with an increasing number of disease components [44], providing possible support for the notion that an increasing disease burden contributes to PD occurrence.…”