Transcriptomes in Healthy and Diseased Gingival Tissues

Objectives: Clinical and radiographic measures are gold standards for diagnosing periodontitis but offer little information regarding the pathogenesis of the disease. We hypothesized that a comparison of gene expression signatures between healthy and diseased gingival tissues would provide novel insights in the pathobiology of periodontitis, and would inform the design of future, hypothesis-driven studies.

Methods: Ninety systemically healthy non-smokers with moderate to advanced periodontitis (63 with chronic and 27 with aggressive periodontitis) each contributed with ³2 “diseased” interproximal papillae [with bleeding on probing (BoP), pocket depth (PD) ³4mm, and attachment loss (AL) ³3mm)] and a “healthy” papilla, if available (no BoP, PD ≤4mm and AL ≤2mm). RNA was extracted, amplified, reverse-transcribed, labeled, and hybridized with AffymetrixU133Plus2.0 arrays. Differential expression was assayed in 247 individual tissue samples (183 from diseased and 64 from healthy sites) using a standard mixed-effects linear model approach, with patient effects considered random with a normal distribution, and gingival tissue status considered a two-level fixed effect. Gene ontology analysis summarized the expression patterns into biologically relevant categories.

Results: Transcriptome analysis revealed that a total of 12,744 probe sets were differentially expressed after adjusting for multiple comparisons (p<9.15x10^-7). Of those, 5,295 were up-regulated and 7,449 down-regulated in disease when compared to health. Gene ontology analysis identified 61 differentially expressed groups (adjusted p<0.05) including apoptosis, antimicrobial humoral response, antigen presentation, regulation of metabolic processes, signal transduction, and angiogenesis.

Conclusions: Gingival tissue transcriptomes provide a valuable scientific tool for further hypothesis-driven studies of the pathobiology of periodontitis.

Supported by NIH grant DE015649 to PNP. PP was supported by NIH grant 20R48583 and a Michael Smith Foundation for Health Career Investigator Award; MH by NIH grant DE16715; MK by Neue Gruppe Wissenschaftsstiftung, Germany.