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Periodontal pathogens and clinical parameters in chronic periodontitis
Author(s) -
Boyer Emile,
Martin Bénédicte,
Le GallDavid Sandrine,
Fong Shao B.,
Deugnier Yves,
BonnaureMallet Martine,
Meuric Vincent
Publication year - 2020
Publication title -
molecular oral microbiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.18
H-Index - 77
eISSN - 2041-1014
pISSN - 2041-1006
DOI - 10.1111/omi.12274
Subject(s) - dysbiosis , periodontitis , treponema denticola , chronic periodontitis , porphyromonas gingivalis , aggregatibacter actinomycetemcomitans , population , tannerella forsythia , biology , medicine , microbiology and biotechnology , microbiome , dentistry , bioinformatics , pathology , honeysuckle , alternative medicine , environmental health , traditional chinese medicine
The use of next generation sequencing and bioinformatics has revealed the complexity and richness of the human oral microbiota. While some species are well known for their periodontal pathogenicity, the molecular‐based approaches for bacterial identification have raised awareness about new putative periodontal pathogens. Although they are found increased in case of periodontitis, there is currently a lack of data on their interrelationship with the periodontal measures. We processed the sequencing data of the subgingival microbiota of 75 patients with hemochromatosis and chronic periodontitis in order to characterize the well‐described and newly identified subgingival periodontal pathogens. We used correlation tests and statistical models to assess the association between the periodontal pathogens and mean pocket depth, and to determine the most relevant bacterial biomarkers of periodontitis severity. Based on correlation test results, nine taxa were selected and included in the statistical models. The multiple linear regression models adjusted for systemic and periodontal clinical variables showed that mean pocket depth was negatively associated with Aggregatibacter and Rothia , and positively associated with Porphyromonas . Furthermore, a bacterial ratio that was previously described as a signature of dysbiosis in periodontitis (% Porphyromonas +% Treponema +% Tannerella )/(% Rothia +% Corynebacterium ) was the most significant predictor. In this specific population, we found that the best model in predicting the mean pocket depth was microbial dysbiosis using the dysbiosis ratio taxa formula. While further studies are needed to assess the validity of these results on the general population, such a dysbiosis ratio could be used in the future to monitor the subgingival microbiota.