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Robust Ligature-Induced Model of Murine Periodontitis for the Evaluation of Oral Neutrophils
Published on: January 21, 2020
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At least three phenotypes exist among periodontitis patients
Chryssa Delatola1, Bruno G Loos1, Evgeni Levin2
1Department of Periodontology, Academic Center for Dentistry Amsterdam (ACTA), University of Amsterdam and Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
Journal of Clinical Periodontology
|August 12, 2017
Summary
This study identified three distinct patient phenotypes for periodontitis using clustering. These phenotypes are based on radiographic bone loss and microbiological data, aiding in personalized treatment approaches for periodontitis.
Area of Science:
- Periodontology
- Computational Biology
- Genomics
Background:
- Periodontitis is a complex oral disease with varying clinical presentations.
- Understanding patient heterogeneity is crucial for effective treatment strategies.
Purpose of the Study:
- To classify periodontitis patients into distinct phenotypes using unsupervised clustering.
- To analyze pre-treatment radiographic and microbiological data for phenotype identification.
Main Methods:
- Retrospective analysis of 392 untreated periodontitis patients.
- Application of co-regularized spectral clustering algorithm.
- Characterization of clusters by demographics, bone loss patterns, and microbial data.
Main Results:
- Three main patient clusters were identified with 90% accuracy.
- Cluster A: young individuals with localized bone loss and high Aggregatibacter actinomycetemcomitans.
- Clusters B and C: differed in disease severity and smoking habits, not microbiology.
Conclusions:
- Untreated periodontitis patients can be categorized into at least three phenotypes based on bone loss and microbial data.
- Further validation in diverse cohorts and exploration of clinical utility are recommended.
