Abstract
Although a distinct cytokine profile has been described in the gingival crevicular fluid (GCF) of patients with chronic periodontitis, there is no evidence of GCF cytokine-based predictive models being used to diagnose the disease. Our objectives were: to obtain GCF cytokine-based predictive models; and develop nomograms derived from them. A sample of 150 participants was recruited: 75 periodontally healthy controls and 75 subjects affected by chronic periodontitis. Sixteen mediators were measured in GCF using the Luminex 100™ instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha. Cytokine-based models were obtained using multivariate binary logistic regression. Models were selected for their ability to predict chronic periodontitis, considering the different role of the cytokines involved in the inflammatory process. The outstanding predictive accuracy of the resulting smoking-adjusted models showed that IL1alpha, IL1beta and IL17A in GCF are very good biomarkers for distinguishing patients with chronic periodontitis from periodontally healthy individuals. The predictive ability of these pro-inflammatory cytokines was increased by incorporating IFN gamma and IL10. The nomograms revealed the amount of periodontitis-associated imbalances between these cytokines with pro-inflammatory and anti-inflammatory effects in terms of a particular probability of having chronic periodontitis.
Highlights
TM in gingival crevicular fluid (GCF) using the Luminex 100 instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha
The analysis of clinical variables related to oral health status showed that, in comparison with the control group, the perio group had significantly higher values of bacterial plaque level (BPL), Bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL) at both the full mouth and sampling site levels (p < 0.001; Table 1)
The importance of cytokines in the pathogenesis of periodontal disease has been demonstrated in different stages
Summary
TM in GCF using the Luminex 100 instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha. The outstanding predictive accuracy of the resulting smoking-adjusted models showed that IL1alpha, IL1beta and IL17A in GCF are very good biomarkers for distinguishing patients with chronic periodontitis from periodontally healthy individuals. Traditional clinical measures are informative for evaluating the severity of periodontitis and the response to therapy, and these include: the presence or the level of bacterial plaque; gingival inflammation and bleeding upon probing; pocket depth and suppuration; the clinical attachment level; and radiographic bone loss[14]. These clinical criteria are unable to determine current disease activity or the future risk of structure loss[15, 16].
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