Abstract
BACKGROUND: 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 studies. METHODS: Ninety systemically healthy non-smokers with moderate to advanced periodontitis (63 with chronic periodontitis and 27 with aggressive periodontitis) each contributed at least two diseased interproximal papillae (with bleeding on probing [BOP], probing depth [PD] > or =4 mm, and attachment loss [AL] > or =3 mm) and a healthy papilla, if available (no BOP, PD < or =4 mm, and AL < or =2 mm). RNA was extracted, amplified, reverse-transcribed, labeled, and hybridized with whole genome microarrays. Differential expression was assayed in 247 individual tissue samples (183 from diseased sites 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 classified the expression patterns into biologically relevant categories. RESULTS: Transcriptome analysis revealed that 12,744 probe sets were differentially expressed after adjusting for multiple comparisons (P <9.15 x 10(7)). Of those, 5,295 were upregulated and 7,449 were downregulated in disease 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. CONCLUSION: Gingival tissue transcriptomes provide a valuable scientific tool for further hypothesis-driven studies of the pathobiology of periodontitis.