Objective: This study aimed to explore the key genes, metabolites, and pathways that influence periodontitis pathogenesis by integrating transcriptomic and metabolomic studies.
Design: Gingival crevicular fluid samples from periodontitis patients and healthy controls were collected for liquid chromatography/tandem mass-based metabolomics. RNA-seq data for periodontitis and control samples were obtained from the GSE16134 dataset. Differential metabolites and differentially expressed genes (DEGs) between the two groups were then compared. Based on the protein-protein interaction (PPI) network module analysis, key module genes were selected from immune-related DEGs. Correlation and pathway enrichment analyses were performed for differential metabolites and key module genes. A multi-omics integrative analysis was performed using bioinformatic methods to construct a gene-metabolite-pathway network.
Results: From the metabolomics study, 146 differential metabolites were identified, which were mainly enriched in the pathways of purine metabolism and Adenosine triphosphate binding cassette transporters (ABC transporters). The GSE16134 dataset revealed 102 immune-related DEGs (458 upregulated and 264 downregulated genes), 33 of which may play core roles in the key modules of the PPI network and are involved in cytokine-related regulatory pathways. Through a multi-omics integrative analysis, a gene-metabolite-pathway network was constructed, including 28 genes (such as platelet derived growth factor D (PDGFD), neurturin (NRTN), and interleukin 2 receptor, gamma (IL2RG)); 47 metabolites (such as deoxyinosine); and 8 pathways (such as ABC transporters).
Conclusion: PDGFD, NRTN, and IL2RG may be potential biomarkers of periodontitis and may affect disease progression by regulating deoxyinosine to participate in the ABC transporter pathway.
Keywords: Integrated multi-omics study; Metabolomics; Periodontitis; Potential biomarkers; Transcriptomics.
Copyright © 2023. Published by Elsevier Ltd.