Objective Periodontitis is a chronic inflammatory infectious disease caused by the deposition of dental plaque on the tooth surface, leading to adverse systemic consequences. Accumulating evidence shows that dysregulated microRNAs (miRNAs) are associated with the disease severity of periodontitis. Herein, we report two novel miRNAs, miR-30b-3p and miR-125b-1-3p, in the context of periodontitis and their relationships with disease severity of periodontitis. Methods The miRNA profiles of gingival crevicular fluid (GCF) samples were used to screen differentially expressed miRNAs (DEmiRNAs) between periodontitis patients and periodontally healthy individuals. Clinical human GCF samples were collected from 80 patients diagnosed with periodontitis (PD +) for the first time and 100 periodontally healthy individuals (PD-). The severity of periodontitis was categorized into mild/moderate (MPD) and severe (SPD) groups. The expressions of miR-30b-3p and miR-125b-1-3p were determined by quantitative real-time PCR. The levels of IL-1β, IL-6, and TNF-α were determined by ELISA methods. Results We applied GEO2R bioinformatics tool to analyze the raw data of the GSE89081 dataset and identified miR-30b-3p (|logFC|= 1.987) and miR-125b-1-3p (|logFC|= 1.878) between periodontitis patients and periodontally healthy individuals. It was found that PPD, CAL, BOP, and the relative expression levels of miR-30b-3p and miR-125b-1-3p were all higher in the PD + group than the PD- group, in the SPD group than the MPD group (P < 0.05). The periodontitis patients with high-miR-30b-3p expression exhibited increased PPD, CAL, and BOP compared to those low-miR-30b-3p expression, while high-miR-125b-1-3p expression group showed significant differences on PPD and BOP from low-miR-125b-1-3p expression group (P < 0.05). Pearson correlation analysis demonstrated a significantly positive correlation between the levels of inflammatory cytokines, miR-30b-3p expression, and miR-125b-1-3p expression (P < 0.001). Results of ROC curves showed AUC of 0.878 and 0.927, sensitivity of 0.843 and 0.855, and specificity of 0.791 and 0.801, respectively, when miR-30b-3p and miR-125b-1-3p expression levels were used to diagnose periodontitis. Conclusion These data unveiled that miR-30b-3p and miR-125b-1-3p expressions may be associated with the pathogenesis of periodontitis.

The modulation of gene expression via DNA methylation modifications is relevant to the pathogenesis of periodontitis. This study aimed at identifying novel biomarkers in gingival tissues from periodontitis by integrally analyzing methylation profiles and gene expression data. Differential gene expressions (DGEs) of dataset GSE106090 were obtained from the Gene Expression Omnibus (GEO) database for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. DNA methylation DGEs (DM-DGEs) were analyzed from dataset GSE173082.After integrating these two datasets, expressions of common genes were validated in gingival tissues from healthy controls and periodontitis patients by real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting. GO analysis of 748 upregulated and 847 downregulated DEGs from the GSE106090 dataset revealed that immune response-regulating signaling pathway, cell-cell junction and signaling receptor activator activity as the top enriched biological process (BP), cellular component (CC) and molecular function (MF), respectively. DEGs were mainly enriched in cytokinecytokine receptor interaction, Ras signaling pathway, and chemokine signaling pathway. There was one up-regulated mRNA with hypo-methylated gene [ADAM28 (a disintegrin and metalloproteinase 28)] and one down-regulated mRNA with hyper-methylated gene [ADAMTSL3 (a disintegrin-like and metalloprotease domain with thrombospondin type I motifs-like-3)] after integrating GSE106090 and GSE173082 datasets. Increased ADAM28 expression was validated in gingival tissues from periodontitis patients as compared to the healthy controls with decreased ADAMTSL3 expression, which were correlated with disease stage. ADAM28 and ADAMTSL3 as novel biomarkers in gingival tissues from periodontitis by a comprehensive analysis of bioinformatics methods and executed validation.