Abstract
Introduction
Early diagnosis of periodontitis by means of a rapid, accurate and non-invasive method is highly desirable to reduce the individual and epidemiological burden of this largely prevalent disease.
Objectives
The aims of the present systematic review were to examine potential salivary metabolic biomarkers and pathways associated to periodontitis, and to assess the accuracy of salivary untargeted metabolomics for the diagnosis of periodontal diseases.
Methods
Relevant studies identified from MEDLINE (PubMed), Embase and Scopus databases were systematically examined for analytical protocols, metabolic biomarkers and results from the multivariate analysis (MVA). Pathway analysis was performed using the MetaboAnalyst online software and quality assessment by means of a modified version of the QUADOMICS tool.
Results
Twelve studies met the inclusion criteria, with sample sizes ranging from 19 to 130 subjects. Compared to periodontally healthy individuals, valine, phenylalanine, isoleucine, tyrosine and butyrate were found upregulated in periodontitis patients in most studies; while lactate, pyruvate and N-acetyl groups were the most significantly expressed in healthy individuals. Metabolic pathways that resulted dysregulated are mainly implicated in inflammation, oxidative stress, immune activation and bacterial energetic metabolism. The findings from MVA revealed that periodontitis is characterized by a specific metabolic signature in saliva, with coefficients of determination ranging from 0.52 to 0.99.
Conclusions
This systematic review summarizes candidate metabolic biomarkers and pathways related to periodontitis, which may provide opportunities for the validation of diagnostic or predictive models and the discovery of novel targets for monitoring and treating such a disease (PROSPERO CRD42020188482).
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Data availability
All data generated or analyzed during this study are included in this published article [and its supplementary information files].
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The authors would like to acknowledge special gratitude to Gaia Meoni, Leonardo Tenori and the CERM institute of Florence for providing missing data and technical support for writing the manuscript.
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GB, GI and MA made substantial contributions to conception of the study. GB, NB, FC and FR contributed to the study design. GI, SG, and GB searched and collected the data. GB and GNB performed data processing and interpretation. GB and NB prepared the first draft of the manuscript. All authors have read, revised critically, and approved the final manuscript.
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Baima, G., Iaderosa, G., Citterio, F. et al. Salivary metabolomics for the diagnosis of periodontal diseases: a systematic review with methodological quality assessment. Metabolomics 17, 1 (2021). https://doi.org/10.1007/s11306-020-01754-3
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DOI: https://doi.org/10.1007/s11306-020-01754-3