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News|Articles|February 19, 2026

RPLC-MS and HILIC Platforms Reveal Distinct Metabolomic Signatures in Periodontal Disease

Author(s)John Chasse

Using reversed-phase and hydrophilic interaction liquid chromatography-mass spectrometry, researchers identified 256 metabolites in gingival crevicular fluid, revealing elevated purine degradation and ceramide metabolites alongside diminished oxy fatty acids in periodontitis patients, advancing precision diagnostics through untargeted metabolomic profiling of this chronic inflammatory disease.

Across-sectional clinical study aiming to study the untargeted metabolomic and lipidomic profiles in gingival crevicular fluid (GCF) obtained from healthy individuals and patients with periodontitis employed hydrophilic interaction and reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) platforms for the unbiased characterization of positively and negatively charged polar metabolite and lipid compounds. This was followed by a semi-supervised deep learning-based approach for metabolomic peak curation and data analysis. A paper based on this study was published in the Journal of Clinical Periodontology.1

A chronic inflammatory disease, periodontitis can lead to tooth loss and serve as a risk factor for several systemic diseases, such as diabetes mellitus, cardiovascular disease and dementia.2 While there are clinical measurements which present vital information regarding the status of the tissues surrounding the tooth (for example, probing depth [PD], clinical attachment level [CAL], bleeding on probing [BOP] and the severity of radiographic bone loss [RBL]), they are subject to technical biases, that can obstruct accurate evaluation of the severity of the periodontitis.3 Previous studies insinuate that screening for polar metabolites and lipids in GCF offers significant possibilities for periodontitis diagnosis.4,5 However, due to the lack of untargeted metabolomic datasets, understanding of the relationship between clinical metabolomic signatures of GCF and periodontitis currently remains limited, thus inspiring the research presented.4,6

The research team collected GCF from 17 periodontally healthy and 19 periodontitis patients, and a total of 256 metabolites were identified with Metabolomics Standards Initiative (MSI) confidence Levels 1-3; this included 198 elevated and 58 diminished compounds in periodontal lesions (q < 0.05, |log2-transformed Fold Change (FC)| > 1). Periodontitis samples exhibited a significant positive accumulation of purine degradation and ceramide metabolites, along with a negative regulation of oxy fatty acids metabolism. Furthermore, the team observed a noteworthy rise in established periodontitis biomarkers, including N-acetylneuraminic acid, citrulline and 2-pyrrolidineacetic acid. The research also characterized distinct differences in bacterial and fungal metabolite profiles between the healthy and diseased samples.1

“These findings,” write the authors of the paper,1 “suggest that untargeted metabolomic screening of GCF may significantly improve our understanding of biochemical changes between healthy tissue and periodontitis. This knowledge is pivotal for the development of a precision paradigm in periodontitis.” However, they admit to the necessity to consider the study limitations and potential for bias, as their data simply compared metabolomic signatures between healthy and periodontitis samples.1

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References

  1. Henderzahs C. H.; Yamada, C.; Morozov, A. et al. Untargeted Metabolomic and Lipidomic Profiles of Gingival Crevicular Fluid in the Context of Periodontitis. J Clin Periodontol. 2026. DOI: 10.1111/jcpe.70105
  2. Albandar, J. M.; Susin, C.; Hughes, F. J. Manifestations of Systemic Diseases and Conditions that Affect the Periodontal Attachment Apparatus: Case Definitions and Diagnostic Considerations. J Periodontol. 2018, 89 (Suppl 1), S183-S203. DOI: 10.1002/JPER.16-0480
  3. Dursun, E.; Tözüm, T. F. Peri-Implant Crevicular Fluid Analysis, Enzymes and Biomarkers: A Systemetic Review. J Oral Maxillofac Res. 2016, 7 (3), e9. DOI: 10.5037/jomr.2016.7309
  4. Baima, G.; Corana, M.; Iaderosa, G. et al. Metabolomics of Gingival Crevicular Fluid to Identify Biomarkers for Periodontitis: A Systematic Review with Meta-Analysis. J Periodontal Res. 2021, 56 (4), 633-645. DOI: 10.1111/jre.12872
  5. Barnes, V. M.; Teles, R.; Trivedi, H. M. et al. Acceleration of Purine Degradation by Periodontal Diseases. J Dent Res. 2009, 88 (9), 851-855. DOI: 10.1177/0022034509341967
  6. Brito, F.; Curcio, H. F. Q.; da Silva Fidalgo, T. K. Periodontal Disease Metabolomics Signatures from Different Biofluids: A Systematic Review. Metabolomics 2022, 18 (11), 83. DOI: 10.1007/s11306-022-01940-5

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