ArticleBMC oral health2025
Feasibility of salivary lipid screening for caries biomarkers in young adults.
Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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6 authors.
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Abstract
backgroundTo identify distinct lipid metabolic profiles that differentiate young adults with dental caries (DC) from their caries-free (CF) counterparts and to investigate salivary lipid biomarkers indicative of DC status.
methodsWe analyzed salivary lipid profiles from 100 caries-free (CF) and 100 dental caries (DC) college students aged 17-20 years old. Lipidomic analysis was performed using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS). Data were analyzed using orthogonal partial least squares discriminant analysis (OPLS-DA), variable importance in projection (VIP), and fold change (FC) analysis to identify lipid metabolites that distinguished caries status. Receiver operating characteristic (ROC) curve analysis was performed to compare lipid profiles between groups, assess potential associations with caries, and calculate the area under the curve (AUC), positive predictive value (PPV), and negative predictive value (NPV) for each lipid species.
resultsAlterations in glycerophospholipid and sphingolipid metabolism were evident in participants with caries. Five salivary lipid metabolites, including ceramide (Cer) (d24:1/18:0(2OH)), phosphatidic acid (PA)(21:0_24:1), PA (25:0_20:1), phosphatidylcholine (PC)(16:0_24:0), and sphingosine (SPH)(d18:0), showed significant differences in both DC1 (decayed, missing, and filled teeth (DMFT) = 4-6) and DC2 (DMFT > 6) groups compared with CF controls (P < 0.001). Cer (d24:1/18:0(2OH)), PA (25:0_20:1), PA (21:0_24:1), and PC (16:0_24:0) were upregulated, whereas SPH (d18:0) was downregulated. Although lipid levels tended to be higher in DC2 than in DC1, the differences between these subgroups were not statistically significant. In receiver operating characteristic analysis, PA (25:0_20:1) demonstrated perfect discrimination between CF and DC2 (AUC = 1.000, PPV = 100%, NPV = 100%). For CF versus DC1, PA (25:0_20:1) achieved an AUC of 0.976, a PPV of 100%, and an NPV of 97.37%, while PC (16:0_24:0) yielded an AUC of 0.952, a PPV of 100%, and an NPV of 94.87%.
conclusionSalivary lipidomic profiling enables noninvasive differentiation between DC and CF individuals, highlighting specific lipid biomarkers with potential utility for diagnosis and disease monitoring. These findings could inform personalized prevention and management strategies.
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