ArticleJournal of periodontal research2025
Metabolomic Profiles of Oral Rinse Samples to Distinguish Severe Periodontitis Patients From Non-Periodontitis Controls.
Article in Journal of periodontal research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Machine learning-based analysis of oral rinse samples to identify candidate proteomic signatures for severe periodontitis: a pilot study.Scientific reports · 2026Article
- Oral stem cells in combination with hydrogels as biomimetic bioactive platforms for periodontal tissue engineering.Frontiers in oral health · 2025Review
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Authors and funding
5 authors.
Funding
Abstract
aimsTo explore the potential of metabolomic profiles of oral rinse samples to distinguish between patients with severe periodontitis (stage III/IV) and non-periodontitis controls. This is coupled to an analysis of differences in metabolomic profiles between individuals without periodontitis, patients with localized periodontitis, and patients with generalized periodontitis.
methodsPeriodontitis patients and controls were recruited, all aged ≥ 40 years. Study participants were asked to rinse vigorously for 30 s with 10 mL phosphate buffered saline. Metabolites were identified using a semi-targeted liquid chromatography tandem mass spectrometry (LC-MS/MS) platform.
resultsIn total, 38 periodontitis patients (18 localized, 20 generalized stage III/IV periodontitis patients) and 16 controls were included. Metabolomic profiles of oral rinse samples were able to distinguish patients with severe periodontitis (stage III/IV) from non-periodontitis controls. Among various variables for the severity of periodontitis, we found that the number of sites with deep pockets (PPD) ≥ 6 mm explained best the differences in metabolomic profiles between controls and patients with severe periodontitis. Subjects with a high number of sites with PPD ≥ 6 mm were characterized by a higher level of phosphorylated nucleotides, amino acids, peptides, and dicarboxylic acids. Metabolomic profiles were also significantly different between controls vs. generalized periodontitis and between localized periodontitis vs. generalized periodontitis (p < 0.05).
conclusionOur study demonstrates that simply collected oral rinse samples are suitable for LC-MS/MS based metabolomic analysis. We show that a metabolomic profile with a substantial number of metabolites can distinguish severe periodontitis patients from non-periodontitis controls. These observations can be a basis for further studies into screening to identify subjects with the risk of having severe periodontitis.
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