Discovery and Validation of Periodontitis Biomarkers

NCT07293481 | Recruiting DMC

• 1 other identifier: SH9H-2024-T358-2
• Study Type: observational
• Target: 228
• Locations: 1 country
• Sites: 1

Brief Summary

Periodontitis is a major public health issue in China: it is responsible for loss of masticatory function in 60 million older adults, and 400-500 million adults are on the same disease trajectory. In addition, gingivitis and early-stage periodontitis are highly prevalent in all age groups. The Lancet 2021 burden of disease study provides worrying projections for China's oral health, with a 47.8% increase in advanced-stage periodontitis and a 217% increase in edentulism by the year 2050. The numbers are not manageable by the Chinese health system unless a series of coordinated actions are implemented: i) health education promoting oral hygiene in school and the workplace; ii) effective AI-based self-detection strategies and accurate identification of high-risk subjects; iii) efficient treatment modalities; and iv) reorganization of the health system. We have developed, patented, and validated a self-detection AI-based screening test for the general population through an app. It is based on a few validated questions and the performance of a lateral flow immunoassay to detect activated matrix metalloproteinase 8 (aMMP8). The algorithm enables accurate self-detection of severe periodontitis. The system, however, cannot identify subjects without clinically evident periodontitis (subjects who present with superficial inflammation consistent with gingivitis and incipient periodontitis) who will develop the disease, which, therefore, should be the target of early interventions. This limitation is due to insufficient knowledge of the process that turns superficial inflammation (gingivitis) into periodontitis. This limitation is apparent in the recently published NIH-sponsored American diagnostic trial results to detect periodontitis onset biomarkers (and progression). In their study, Teles et al. (2024) show that almost 24% of gingivitis subjects progress to periodontitis over a 12-month period but failed to identify salivary or serum biomarkers. Similarly, our recently completed study (Li et al. in preparation) did not identify highly accurate biomarkers for disease onset and progression. Importantly, the American and our study have tested putative biomarkers identified based on the current crude knowledge of the disease process. Gaps in fundamental knowledge are now apparent and limit our ability to detect periodontitis early. In addition, the current crude differential diagnosis based on clinical examination with a periodontal probe with millimeter markings cannot accurately differentiate gingivitis from early-stage periodontitis, complicating the ground truth definition (gold standard). In the current study, we propose implementing a multi-omics approach to test the ability to discriminate a mixed population of clinically undifferentiable gingivitis and stage I periodontitis into two or more clusters. In this biomarker discovery phase, we plan to use multiple state-of-the-art methods: i) laser scanning microdissection proteomics of tissue biopsies, ii) conventional salivary proteomics, iii) tissue biopsy transcriptomics, and iv) shotgun microbiome analysis. The methods will be applied in an agnostic approach to test the following hypotheses:

1. 1.It is possible to identify two or more clusters of subjects from a mixed population of gingivitis and stage I periodontitis subjects.
2. 2.The clusters differ based on host-derived biomarkers and/or microbiome factors and the risk of progression to periodontitis.
3. 3.The biomarker pathways and microbial virulence factors among subjects identified according to the different approaches used to explore disease biology are generally consistent.
4. 4.It is possible to identify a limited set of biomarkers that can be used to predict periodontitis onset and thus target early interventions for this high-risk population.

Conditions

Periodontitis; Saliva; Biomarker in Early Diagnosis

Outcome Measures

Primary Outcomes (1)

• Accuracy of biomarker-defined clusters in predicting periodontitis progression

  Biomarker-based clusters will be created using multi-omics data (proteomics, transcriptomics, microbiome). Their predictive accuracy for periodontitis progression will be assessed by comparing them to clinical outcomes after 24-month follow-up. Models will be optimized using AI-based feature selection techniques.

  24 months

Study Arms (1)

A cohort of subjects with clinically undistinguishable gingivitis/stage I periodontitis

Diagnostic Test: Diagnostic procedures

Interventions

Diagnostic procedures DIAGNOSTIC_TEST

All clinical measurements will be taken by a single trained and calibrated examiner using a PCP-UNC15 periodontal probe at a pressure of 0.25-0.3N. Unstimulated saliva, oral rinse, gingival crevicular fluid samples, subgingival microbiome samples, and gingival biopsies will be taken from the participants. All samples will be stored at -80C in standardized vials. Tissue samples will be divided into two equal portions: one will be fixed in paraffin for laser capture microdissection the other will be stored in liquid nitrogen for tissue transcriptomics. In addition, we will perform in depth microbiome analysis (shotgun approach and 16S) following the currently employed methods in use at our center.

A cohort of subjects with clinically undistinguishable gingivitis/stage I periodontitis

Eligibility Criteria

• Age: 18 Years - 40 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of adult patients seeking care at Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, who are clinically diagnosed with gingivitis or stage I periodontitis. Participants are willing to contribute subgingival microbiome samples, oral fluid specimens, and optionally a small gingival tissue biopsy.

You may qualify if:

• Adults between 18 and 40 years of age;
• Diagnosed with varying degrees of periodontal disease, including gingivitis and stage I periodontitis;
• Voluntarily agree to participate in the study, have signed the informed consent form, and are able to comply with the study protocol.

You may not qualify if:

• Pregnant or breastfeeding women;
• Individuals who have received antibiotic treatment within the past 3 months;
• Individuals who have received periodontal treatment (including supragingival scaling) within the past 6 months;
• Individuals with mucosal or salivary gland diseases (e.g., Sjögren's syndrome);
• Individuals with severe systemic diseases, immune dysfunction, or health conditions that contraindicate surgery;
• Individuals who are unwilling to cooperate with the study.

Sponsors & Collaborators

• Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University: lead

Study Sites (1)

Shanghai 9th people's hospital

Shanghai, Shanghai Municipality, 200120, China

RECRUITING

MeSH Terms

Conditions

Periodontitis

Interventions

Diagnostic Techniques and Procedures

Condition Hierarchy (Ancestors)

Periodontal Diseases; Mouth Diseases; Stomatognathic Diseases

Intervention Hierarchy (Ancestors)

Diagnosis

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 2 Years
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: December 8, 2025
• First Posted: December 19, 2025
• Study Start: July 21, 2025
• Primary Completion (Estimated): March 31, 2027
• Study Completion (Estimated): October 31, 2027
• Last Updated: April 20, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)