At least three phenotypes exist among periodontitis patients.

AIM: To identify phenotypes of periodontitis patients by the use of an unsupervised modelling technique (clustering), based on pre-treatment radiographic and microbiological characteristics.

MATERIALS AND METHODS: This retrospective study included data from 392 untreated periodontitis patients. Co-regularized spectral clustering algorithm was used to cluster the patients. The resulting clusters were subsequently characterized based on their demographics, radiographic bone loss patterns and microbial data.

RESULTS: The vast majority of patients fitted into one of the three main clusters (accuracy 90%). Cluster A (n = 18) was characterized by high prevalence and high proportions of Aggregatibacter actinomycetemcomitans, a trend for a more localized pattern of alveolar bone loss and young individuals. Clusters B (n = 200) and C (n = 135) differed clearly in disease severity patterns and smoking habits, but not in microbiological characteristics.

CONCLUSION: On the basis of alveolar bone loss patterns and microbiological data, untreated periodontitis patients can be clustered into at least three phenotypes. These results should be validated in other cohorts, and the clinical utility needs to be explored on the basis of periodontal treatment outcomes and/or disease progression.