The currently recognized principal forms of periodontitis-chronic and aggressive-lack an unequivocal, pathobiology-based foundation. We explored whether gingival tissue transcriptomes can serve as the basis for an alternative classification of periodontitis. We used cross-sectional whole-genome gene expression data from 241 gingival tissue biopsies obtained from sites with periodontal pathology in 120 systemically healthy nonsmokers with periodontitis, with available data on clinical periodontal status, subgingival microbial profiles, and serum IgG antibodies to periodontal microbiota. Adjusted model-based clustering of transcriptomic data using finite mixtures generated two distinct clusters of patients that did not align with the current classification of chronic and aggressive periodontitis. Differential expression profiles primarily related to cell proliferation in cluster 1 and to lymphocyte activation and unfolded protein responses in cluster 2. Patients in the two clusters did not differ with respect to age but presented with distinct phenotypes (statistically significantly different whole-mouth clinical measures of extent/severity, subgingival microbial burden by several species, and selected serum antibody responses). Patients in cluster 2 showed more extensive/severe disease and were more often male. The findings suggest that distinct gene expression signatures in pathologic gingival tissues translate into phenotypic differences and can provide a basis for a novel classification.
Keywords: classification; cluster analysis; diagnosis; gene expression; genomics; periodontal diseases.