Molecular Differences between Chronic and Aggressive Periodontitis

• Published in: Journal of dental research Vol. 92; no. 12; pp. 1081 - 1088
• Main Authors: Kebschull, M., Guarnieri, P., Demmer, R.T., Boulesteix, A.L., Pavlidis, P., Papapanou, P.N.
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01-12-2013; SAGE PUBLICATIONS, INC
• Subjects: Aggressive Periodontitis - genetics; Aggressive Periodontitis - immunology; Aggressive Periodontitis - pathology; Algorithms; Apoptosis; Apoptosis - genetics; Area Under Curve; Artificial Intelligence; Bleeding; Breast cancer; Chronic Periodontitis - genetics; Chronic Periodontitis - metabolism; Chronic Periodontitis - pathology; Classification; Epithelium - pathology; Gene expression; Gene Expression Profiling - methods; Genomes; Gingiva; Gingiva - pathology; Gum disease; Humans; Immune response; Immunoglobulins; Learning algorithms; Microarray Analysis; Papillae; Patients; Periodontal Attachment Loss - genetics; Periodontal Attachment Loss - pathology; Periodontal Index; Periodontal Pocket - genetics; Periodontal Pocket - pathology; Periodontitis; Protein expression; Proteins; Research Reports; ROC Curve; Sensitivity and Specificity; Signal Transduction - genetics; Transcription; Transcription, Genetic - genetics; Transcriptome - genetics; Transduction; Tumors; pathogenesis; microarray analysis; classification; machine learning; transcriptome; gene expression
• ISSN: 0022-0345; 1544-0591
• DOI: 10.1177/0022034513506011

The 2 major forms of periodontitis, chronic (CP) and aggressive (AgP), do not display sufficiently distinct histopathological characteristics or microbiological/immunological features. We used molecular profiling to explore biological differences between CP and AgP and subsequently carried out supervised classification using machine-learning algorithms including an internal validation. We used whole-genome gene expression profiles from 310 ‘healthy’ or ‘diseased’ gingival tissue biopsies from 120 systemically healthy non-smokers, 65 with CP and 55 with AgP, each contributing with ≥ 2 ‘diseased’ gingival papillae (n = 241; with bleeding-on-probing, probing depth ≥ 4 mm, and clinical attachment loss ≥ 3 mm), and, when available, a ‘healthy’ papilla (n = 69; no bleeding-on-probing, probing depth ≤ 4 mm, and clinical attachment loss ≤ 4 mm). Our analyses revealed limited differences between the gingival tissue transcriptional profiles of AgP and CP, with genes related to immune responses, apoptosis, and signal transduction overexpressed in AgP, and genes related to epithelial integrity and metabolism overexpressed in CP. Different classifying algorithms discriminated CP from AgP with an area under the curve ranging from 0.63 to 0.99. The small differences in gene expression and the highly variable classifier performance suggest limited dissimilarities between established AgP and CP lesions. Future analyses may facilitate the development of a novel, ‘intrinsic’ classification of periodontitis based on molecular profiling.