Molecular Differences between Chronic and Aggressive Periodontitis

Kebschull, M.; Guarnieri, P.; Demmer, R. T.; Boulesteix, Anne-Laure; Pavlidis, P. und Papapanou, P. N. (Dezember 2013): Molecular Differences between Chronic and Aggressive Periodontitis. In: Journal of Dental Research, Bd. 92, Nr. 12: S. 1081-1088

Abstract

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.

• Dokumententyp: Zeitschriftenartikel
• Publikationsform: Publisher's Version
• Keywords: pathogenesis; gene expression; transcriptome; microarray analysis; classification; machine learning
• Fakultät: Medizin > Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 0022-0345
• Allianz-/Nationallizenz: Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.
• Sprache: Englisch