{"doi":"10.1111/jcpe.70049","title":"Salivary Biomarker Panel That Identifies Periodontitis in Persons With Type 2 Diabetes: A Secondary Analysis of a Cross‐Sectional Study","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.","journal":"Journal Of Clinical Periodontology","year":2025,"id":535025,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8496,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1418169,"name":"Yan Qi","orcid":"0000-0003-4164-6257","position":1,"is_corresponding":false},{"id":382709,"name":"Sreenatha Kirakodu","orcid":"0000-0002-4473-1126","position":2,"is_corresponding":false},{"id":370878,"name":"Jeffrey L. Ebersole","orcid":"0000-0002-9743-6585","position":3,"is_corresponding":false},{"id":372098,"name":"Xiaohua Douglas Zhang","orcid":"0000-0002-2486-7931","position":4,"is_corresponding":false},{"id":492534,"name":"Craig S. Miller","orcid":"0000-0002-7657-4604","position":0,"is_corresponding":true}],"reference_count":45,"raw_metadata":null,"created_at":"2026-07-19T02:51:52.019261Z","pmid":"41084144","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}