1. Identification of pathogen and host-response markers correlated with periodontal disease.
- Author
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Ramseier CA, Kinney JS, Herr AE, Braun T, Sugai JV, Shelburne CA, Rayburn LA, Tran HM, Singh AK, and Giannobile WV
- Subjects
- Adult, Aged, Alveolar Bone Loss classification, Alveolar Bone Loss microbiology, Biofilms, Biomarkers analysis, Chronic Periodontitis microbiology, Dental Plaque microbiology, Disease Progression, Female, Gingivitis microbiology, Humans, Interferon-gamma analysis, Interleukins analysis, Leukocyte L1 Antigen Complex analysis, Male, Matrix Metalloproteinase 8 analysis, Matrix Metalloproteinase 9 analysis, Middle Aged, Osteoprotegerin analysis, Periodontal Attachment Loss classification, Periodontal Attachment Loss microbiology, Periodontal Diseases classification, Periodontium microbiology, Porphyromonas gingivalis isolation & purification, Saliva microbiology, Treponema denticola isolation & purification, Tumor Necrosis Factor-alpha analysis, Young Adult, Bacteria classification, Periodontal Diseases microbiology
- Abstract
Background: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, such as cardiovascular disease and stroke. The development of rapid point-of-care (POC) chairside diagnostics has the potential for the early detection of periodontal infection and progression to identify incipient disease and reduce health care costs. However, validation of effective diagnostics requires the identification and verification of biomarkers correlated with disease progression. This clinical study sought to determine the ability of putative host- and microbially derived biomarkers to identify periodontal disease status from whole saliva and plaque biofilm., Methods: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitis population. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levels of multiple proinflammatory cytokines and bone resorptive/turnover markers., Results: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbial plaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of models for periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9 were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, respectively. The generation of receiver operating characteristic curves demonstrated that permutations of salivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple combinations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex anaerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highly accurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levels displayed robust combinatorial characteristics in predicting periodontal disease severity (area under the curve = 0.88; odds ratio = 24.6; 95% confidence interval: 5.2 to 116.5)., Conclusions: Using qPCR and sensitive immunoassays, we identified host- and bacterially derived biomarkers correlated with periodontal disease. This approach offers significant potential for the discovery of biomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemic diseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.
- Published
- 2009
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