2025/10/13 by Craig S. Miller, Qi Yan, Sreenatha S. Kirakodu +2
paper · doi:10.1111/jcpe.70049
ABSTRACT Aim This secondary analysis of a cross‐sectional study tested the hypothesis that a salivary biomarker panel (i.e., consisting of 2–6 features) could accurately identify periodontitis in persons with Type 2 diabetes (T2DM) compared with non‐periodontitis in systemically healthy persons. Materials and Methods Salivary concentrations of 12 protein biomarkers and 14 oral microbiome species were evaluated by immunoassays and 16S rRNA sequencing, respectively, from 28 systemically healthy non‐periodontitis adults and 28 T2DM patients with periodontitis. Data were analysed for the identification of periodontitis from non‐periodontitis using 5‐fold cross‐validation logistic regression, receiver operating characteristics (ROC) and odds ratios. Results Bacteria showed better predictive value than individual salivary proteins. Two bacteria ( Porphyromonas gingivalis and Mycoplasma faucium ) yielded specificities > 90%, Prevotella species yielded high sensitivity (86%) and Treponema socranskii demonstrated the top area under the curve (AUC) (0.81). A salivary panel consisting of bacteria ( Selenomonas sputigena , P. gingivalis , Prevotella nigrescens , Pr. dentalis ) and protein ratios (prostaglandin E2/tissue inhibitor of metalloproteinase‐1 or macrophage inflammatory protein‐1α/tissue inhibitor of metalloproteinase‐1) produced robust diagnostic accuracy (95%) and precision (96.6%) for the detection of periodontitis in T2DM. Conclusions A salivary panel using bacteria and ratios of host‐response biomarkers accurately identified periodontitis in T2DM compared with systemically healthy persons without periodontitis.