Development of a diagnostic algorithm in periodontal disease and identification of genetic expression patterns: A preliminary report

Abstract

Background/purpose: To identify genetic expression patterns that can be used to define an appropriate diagnostic algorithm of clinical use in periodontal disease. Materials and methods: Total RNA was extracted from 13 samples corresponding to normal human gingiva (NHG) and human gingiva affected by periodontal disease (PDHG). A comprehensive gene expression analysis was carried out by microarray analysis using Affymetrix Human Genome U133 plus 2.0 oligonucleotide arrays. Results: Sixty-six probe sets (genes and expressed sequence tags – EST) overexpressed in all samples of one of the comparison groups, were used for the diagnostic algorithm. All samples, including an independent test sample, were correctly classified as normal or periodontally affected using the diagnostic algorithm. In addition, 2596 genes/EST were upregulated and 1542 genes/EST were downregulated in PDHG, with numerous gene functions impaired in PDHG, especially those related to the immune response, cell-cell junctions, and extracellular matrix remodeling. Conclusion: Our study reveals differential gene expression profiles in NHG and PDHG. The proposed diagnostic algorithm could have clinical usefulness for differential diagnosis in periodontal disease.

Keywords

• diagnostic algorithm
• gene expression
• gene functions
• microarray
• normal gingiva
• periodontal disease