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Accuracy of Metabolomics in Peri‐Implant Crevicular Fluid for Diagnosis and Prognosis of Peri‐Implantitis

Year: 2025

Type: article

Abstract: ABSTRACT Aims Poor accuracy of diagnostic and prognostic tools prevents the prediction of peri‐implant disease stability or progression. We analyzed metabolites from peri‐implant crevicular fluid (PICF) samples from healthy and diseased implants to identify those diagnostic of health and peri‐implant disease and predictive of peri‐implant bone loss over time. Methods Clinical, radiographic examinations and PICF samples were collected from 59 healthy implants, 33 implants with peri‐implantitis, and 38 implants with peri‐implant mucositis in 71 subjects. A subset of implants was evaluated at 6, 12, 18, and 24 months. Over time, all initially healthy implants remained stable (Group B, N = 28), whereas 6 initially diseased implants continued to lose bone and 8 did not (Group C). PICF metabolites were measured using proton‐nuclear magnetic resonance (1H‐NMR) 2‐dimensional Total Correlation Spectroscopy. PCA and PLS‐DA tested the cross‐sectional clustering and importance of each metabolite, while the AUC summarized the accuracy of predicting radiographic bone changes ≥ 1 mm at 6‐month intervals. Results At baseline, the Cadaverine/Lysine and Putrescine/Lysine signatures diagnosed peri‐implantitis (AUC = 0.76 and 0.70; p < 0.000) with good accuracy, while alpha‐ketoglutarate diagnosed implant health (AUC = 0.706; p = 0.002). Combining metabolites increased diagnostic accuracy (AUCCadaverine/Lysine+Methionine = 0.81; p < 0.01). Proline and 1‐3‐diaminopropane predicted future bone loss (AUCProline = 0.917 and AUC1‐3‐diaminopropane = 0.854). ANOVA post hoc analysis established that biotin and propionate levels were higher in Group C compared to Groups A and B (p < 0.001; AUCbiotin = 0.889; AUCpropionate = 0.87). Valine levels were higher in Groups A and C compared to Group B (p = 0.002; AUC = 0.841). Conclusions 1H‐NMR 2‐dimensional spectroscopy identified PICF metabolites diagnostic of peri‐implantitis with high accuracy. Despite the small number of affected implants, metabolite signatures that predict future bone loss in peri‐implantitis appear to be different from those diagnostic of peri‐implantitis.

Source: Journal of Periodontal Research

DOI: 10.1111/jre.13400