Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A selective machine learning algorithm for severe periodontitis labeling from questionnaire data.

Scientific reports·2026

Same author

Longitudinal proteomic analysis of GCF in regenerative healing of molar furcation degree II defects treated with OFD, EMD, or A-PRF + : a pilot study.

Scientific reports·2026

Same author

Estimating the Causal Effect of Tooth Loss on the Critical Outcome of COVID-19.

JDR clinical and translational research·2025

Same author

Effects of Advanced Platelet Rich Fibrin (A-PRF+), Enamel Matrix Derivative (EMD) and Open Flap Debridement on clinical and wound healing parameters in molar furcation sites: A case series from a RCT study.

Frontiers in dental medicine·2025

Same author

[A PhD Completed. Restoring saliva production and quality by means of olfactory stimulation and synthetic peptides].

Nederlands tijdschrift voor tandheelkunde·2025

Same author

Attempts to Modify Periodontal Screening Models Based on a Self-Reported Oral Health Questionnaire in the Medical Care Setting.

Journal of clinical periodontology·2024

Search research articles

Related Experiment Video

Updated: May 17, 2026

Robust Ligature-Induced Model of Murine Periodontitis for the Evaluation of Oral Neutrophils

Robust Ligature-Induced Model of Murine Periodontitis for the Evaluation of Oral Neutrophils

Published on: January 21, 2020

Modeling susceptibility to periodontitis.

M L Laine¹, V Moustakis, L Koumakis

¹Academic Centre for Dentistry Amsterdam (ACTA), University of Amsterdam, Amsterdam, The Netherlands. M.Laine@acta.nl

Journal of Dental Research

|October 27, 2012

Summary

This summary is machine-generated.

Identifying specific bacteria and genetic markers can help predict chronic periodontitis risk. This study found that Tannerella forsythia, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and certain gene variations are key indicators.

More Related Videos

Murine Model of Advanced Periodontitis Induced by Nylon Ligature in the Second Upper Molar

Murine Model of Advanced Periodontitis Induced by Nylon Ligature in the Second Upper Molar

Published on: May 30, 2025

Induction of Periodontitis via a Combination of Ligature and Lipopolysaccharide Injection in a Rat Model

Induction of Periodontitis via a Combination of Ligature and Lipopolysaccharide Injection in a Rat Model

Published on: February 17, 2023

Related Experiment Videos

Last Updated: May 17, 2026

Robust Ligature-Induced Model of Murine Periodontitis for the Evaluation of Oral Neutrophils

Robust Ligature-Induced Model of Murine Periodontitis for the Evaluation of Oral Neutrophils

Published on: January 21, 2020

Murine Model of Advanced Periodontitis Induced by Nylon Ligature in the Second Upper Molar

Murine Model of Advanced Periodontitis Induced by Nylon Ligature in the Second Upper Molar

Published on: May 30, 2025

Induction of Periodontitis via a Combination of Ligature and Lipopolysaccharide Injection in a Rat Model

Induction of Periodontitis via a Combination of Ligature and Lipopolysaccharide Injection in a Rat Model

Published on: February 17, 2023

Area of Science:

Oral Health
Genetics
Microbiology

Background:

Chronic periodontitis is a complex inflammatory disease with multifactorial causes.
Genetic factors and infectious agents play significant roles in its development.

Purpose of the Study:

To investigate the combined influence of genetic polymorphisms and specific bacteria on the risk of chronic periodontitis.
To identify key bacterial species and single-nucleotide polymorphisms (SNPs) that discriminate between periodontitis patients and healthy controls.

Main Methods:

Prevalence of 12 immune response gene SNPs and 7 bacterial species were determined in 385 individuals (periodontitis patients and controls).
Decision tree analysis was employed to identify significant discriminators.
Bioinformatics tools were utilized for modeling complex interactions.

Main Results:

The presence of Tannerella forsythia, Porphyromonas gingivalis, Aggregatibacter actinomycetemcomitans, and SNPs TNF -857 and IL-1A -889 were identified as key discriminators.
The developed model achieved 80% accuracy, 85% sensitivity, and 73% specificity.
A significant association was found between specific bacterial profiles, genetic variations, and periodontitis risk.

Conclusions:

A combination of three periodontal pathogens and specific genetic markers can help identify individuals at risk for chronic periodontitis.
This pilot study highlights the utility of bioinformatics in understanding the complex etiology of periodontitis.
Further research is warranted to validate these findings and develop predictive diagnostic tools.