Background: Molecular biomarkers are needed for diagnostic use in periodontal diseases. The aim of this study is to explore different gingival crevicular fluid (GCF) matrix metalloproteinase-8 (MMP-8) patterns in smokers and non-smokers with chronic periodontitis (CP) and test the utility of baseline GCF MMP-8 levels in predicting categorically assessed treatment outcomes.
Methods: The study population comprised 15 patients with CP (five non-smokers and 10 smokers). GCF sampling of five to seven periodontal sites per patient was done at baseline, post-treatment, and bimonthly during the maintenance period from 8 to 12 months. GCF MMP-8 levels were measured with an immunofluorometric assay. MMP-8 response patterns were explored by cluster analysis. The ability of baseline MMP-8 levels to predict categorical treatment outcomes was analyzed with receiver operating characteristic curves.
Results: GCF MMP-8 response patterns could be clustered into two different site profiles among both smokers and non-smokers. Smoker site profiles 1 and 2 had significantly different clinical attachment level and gingival recession changes by the end of the maintenance period. In smoker sites, baseline MMP-8 levels significantly predicted the categorical treatment outcome.
Conclusions: Baseline GCF MMP-8 levels strongly predict how MMP-8 levels behave during the maintenance period. In smoker sites, high baseline MMP-8 levels indicate weak treatment response.
Assessment of disease activity before and after periodontal therapy is of crucial importance in management of chronic periodontitis (CP) and other periodontal diseases. Clinical parameters such as probing depth (PD), bleeding on probing (BOP), and clinical attachment level (CAL), together with radiologic examination,1 are the framework for traditional clinical diagnostic parameters, but complementary molecular tools for diagnostics of periodontitis and risk assessment of disease progression are under intensive research.2-5 Much of the risk for development and progression of periodontitis is owed to the host response against bacterial biofilm, the initiating factor of the disease.1,6,7 Persistent and recurrent inflammation has been considered to be responsible for irreversible connective tissue breakdown in periodontitis.6,8,9 Thus, inflammatory biomarkers indicating periodontal connective tissue breakdown could be applied to evaluate risk and the course of disease progression and monitor the effect of treatment modalities, alone or combined with bacterial analysis.4,10-12 Matrix metalloproteinases (MMPs), together with their inhibitors, may be candidates for risk markers of periodontitis. Of MMPs, especially those in oral fluids (gingival crevicular fluid [GCF], saliva, and mouth rinse), MMP-8 levels have been found to be increased in periodontitis.13,14 Several studies have reported a clear association of increased oral fluid MMP-8 levels with CP disease status and decreased molecular levels after non-surgical periodontal treatment.13-18 GCF MMP-8 mainly originates from neutrophil granulocytes, although mesenchymal isoforms also exist.19 An impaired neutrophil granulocyte model is related to aggressive periodontitis, but constitutionally hyperreactive neutrophil granulocytes have also been observed in patients with CP.20-22 It is well known that smoking has a dysfunctional effect on neutrophils.23 Tobacco smoking has been related to decreased oral fluid MMP-8 levels compared with non-smokers with CP,14,24-26 but some sites in smokers have been shown to express exceptionally high GCF MMP-8 levels after non-surgical treatment (high responders).14 Those sites were also more likely to have progressive disease.14 However, the diversity in MMP-8 response patterns and their association with environmental versus constitutional factors need to be clarified.
The aim of this study is to research longitudinally the differences in GCF MMP-8 response patterns to non-surgical periodontal treatment, especially among smokers with CP at both patient and site levels, and to compare the MMP-8 response patterns of different treatment outcomes specified as different clinical parameters. Cluster analysis was used to explore different GCF MMP-8 level response patterns in individual periodontal sites on given treatment and whether these different site patterns are also prevalent in other sites in the same patient.
Cluster analysis is a statistical method used to explore meaningful patterns in complex data. To the best of our knowledge, it has not been used earlier in GCF MMP-8 studies, although it is widely used in bioinformatics, for example, with gene expression data.27,28 However, cluster analysis has been used in MMP-8�related studies in other fields of medical sciences. Mattey et al.29 used hierarchical cluster analysis to search certain cytokine and MMP profiles for useful disease activity markers in ankylosing spondylitis. In the present article, the k-means clustering method, one of the most commonly used, robust, and best understood methods for cluster analysis, is used to identify a predefined number of subgroups (response patterns) from the data.
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