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Three-dimensional Inflammatory Human Tissue Equivalents of Gingiva

Three-dimensional Inflammatory Human Tissue Equivalents of Gingiva

Published on: April 3, 2018

Gingival tissue transcriptomes identify distinct periodontitis phenotypes.

M Kebschull¹, R T Demmer, B Grün

¹Division of Periodontics, Section of Oral and Diagnostic Sciences, College of Dental Medicine, Columbia University, New York, NY, USA.

Journal of Dental Research

|March 21, 2014

Summary

This summary is machine-generated.

This study reveals two distinct patient clusters in periodontitis based on gingival tissue gene expression, suggesting a new classification beyond chronic and aggressive forms. These gene expression signatures correlate with different disease phenotypes.

Keywords:

classification cluster analysis diagnosis gene expression genomics periodontal diseases

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Isolation, Characterization and Functional Examination of the Gingival Immune Cell Network

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Published on: February 16, 2016

Area of Science:

Periodontal disease research
Genomics
Translational medicine

Background:

Current periodontitis classifications (chronic and aggressive) lack a clear pathobiology-based foundation.
Need for a more precise classification system for periodontitis.

Purpose of the Study:

To investigate if gingival tissue transcriptomes can form the basis for an alternative periodontitis classification.
To explore novel groupings of periodontitis patients beyond current diagnostic criteria.

Main Methods:

Analysis of whole-genome gene expression data from 241 gingival tissue biopsies.
Utilized cross-sectional data from systemically healthy nonsmokers with periodontitis.
Applied model-based clustering of transcriptomic data to identify patient groups.

Main Results:

Identified two distinct patient clusters based on transcriptomic data, not aligning with chronic or aggressive periodontitis.
Cluster 1 showed differential expression related to cell proliferation; Cluster 2 showed lymphocyte activation and unfolded protein responses.
Clusters exhibited distinct phenotypes, including differences in disease severity, microbial burden, and antibody responses.

Conclusions:

Distinct gene expression signatures in pathologic gingival tissues correlate with phenotypic differences in periodontitis.
Transcriptomic data offers a potential foundation for a novel, pathobiology-driven classification of periodontitis.
This approach may lead to more targeted and effective periodontitis treatments.