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Identification of Pathogen and Host-Response Markers Correlated With Periodontal Disease

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Identification of Pathogenand Host-Response Markers CorrelatedWith Periodontal DiseaseChristoph A. Ramseier,* Janet S. Kinney,* Amy E. Herr,†Thomas Braun,*‡James V. Sugai,*Charlie A. Shelburne,§Lindsay A. Rayburn,* Huu M. Tran,iAnup K. Singh,iand William V. Giannobile*¶Background: Periodontitis is the major cause of tooth loss in adults and is linked to systemic illnesses, suchas cardiovascular disease and stroke. The development ofrapid point-of-care (POC) chairsidediagnostics hasthe potential for the early detection of periodontal infection and progression to identify incipient disease andreduce health care costs. However, validation of effective diagnostics requires the identification and verifica-tion of biomarkers correlated with disease progression. This clinical study sought to determine the ability ofputative host- and microbially derived biomarkers to identify periodontal disease status from whole salivaand plaque biofilm.Methods: One hundred human subjects were equally recruited into a healthy/gingivitis group or a periodontitispopulation. Whole saliva was collected from all subjects and analyzed using antibody arrays to measure the levelsof multiple proinflammatory cytokines and bone resorptive/turnover markers.Results: Salivary biomarker data were correlated to comprehensive clinical, radiographic, and microbialplaque biofilm levels measured by quantitative polymerase chain reaction (qPCR) for the generation of modelsfor periodontal disease identification. Significantly elevated levels of matrix metalloproteinase (MMP)-8 and -9were found in subjects with advanced periodontitis with Random Forest importance scores of 7.1 and 5.1, re-spectively. The generation of receiver operating characteristic curves demonstrated that permutations ofsalivary biomarkers and pathogen biofilm values augmented the prediction of disease category. Multiple com-binations of salivary biomarkers (especially MMP-8 and -9 and osteoprotegerin) combined with red-complex an-aerobic periodontal pathogens (such as Porphyromonas gingivalis or Treponema denticola) provided highlyaccurate predictions of periodontal disease category. Elevated salivary MMP-8 and T. denticola biofilm levelsdisplayed 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 bio-markers correlated with periodontal disease. This approach offers significant potential for the discovery ofbiomarker signatures useful in the development of rapid POC chairside diagnostics for oral and systemicdiseases. Studies are ongoing to apply this approach to the longitudinal predictions of disease activity.J Periodontol 2009;80:436-446.KEY WORDSDiagnosis; periodontal disease; saliva.doi: 10.1902/jop.2009.080480* Department of Periodontics and Oral Medicine, Michigan Center for Oral Health Research, University of Michigan School of Dentistry, Ann Arbor, MI.† Department of Bioengineering, University of California at Berkeley, Berkeley, CA.‡ Biostatistics Department, School of Public Health, University of Michigan, Ann Arbor, MI.§ Department of Biologic and Material Sciences, University of Michigan School of Dentistry.i Biosystems Research Department, Sandia National Laboratories, Livermore, CA.¶ Department of Biomedical Engineering, College of Engineering, University of Michigan.indicates supplementary slide presentation (with audio) in the online Journal of Periodontology.Volume 80 • Number 3436Periodontal disease is the leading cause of toothloss in adults.1Periodontitis is initiated by tooth-associated microbial biofilms triggering an al-tered host response leading to soft tissue inflammationand alveolar bone loss. Periodontal infections areimplicated in a variety of other diseases, such as car-diovascular disease, stroke, and aspiration pneumonia,whereby the microbial biofilm serves as a ‘‘slow-delivery system’’ of oral pathogens adhering to teeth,leading to a chronic microbial challenge and down-stream effects of an altered host response.2Diagnosticmethods used in clinical practice today lack the abilityto detect the onset of inflammation and to identify thosepatients who are susceptible to future disease progres-sion. Oral fluid–based point-of-care (POC) diagnosticsare commonly used in medicine and, more recently, arebeing adapted for the potential ‘‘chairside’’ determina-tion of oral diseases.3The latest clinical applicationsuse new ‘‘lab-on-a-chip’’ (LOC) technologies as rapidPOC diagnostic tests for systemic infectious dis-eases4,5and periodontal disease.6The human salivaryproteome project, supported by the United StatesNational Institute of Dental and Craniofacial Research,Bethesda, Maryland, has generated further emphasison the use of proteomic markers for disease diagnosis.7The identification of the proteomic content of humansaliva in diagnostic tests, assessing the fingerprint ofdifferent human illnesses, generally suggests the prob-ability that multianalyte detection approaches willsurpass conventional clinical diagnostic proceduresusing single biomarkers.The use of oral fluids in oral-based diagnostics haveproven to be easy to use for POC application8in the de-tection of oral cancer9,10or human immunodeficiencyvirus infection.11Furthermore, the use of microfluidicdevices as examples of LOC technology offers signifi-cant potential for rapid saliva diagnosis for widespreadpublic health purposes.6,12However, for periodontaldisease determination, most research has focused pri-marily on gingival crevicular fluid (GCF) biomarkersthat provide local disease status, but it represents acumbersome, difficult-to-use approach for clinical ap-plication.13Easy-to-access saliva contains locally andsystemically derived mediators of periodontal diseaseand, thus, offers significant potential for the assess-ment of periodontal disease status and risk.14Although a single specific target biomarker for peri-odontal disease has not been identified, combinationsof putative biomarkers of disease have been evaluatedin GCF and demonstrated significant potential aspanels of targets for the development of an oral fluidfingerprint of periodontal disease status. Given themultifaceted pattern of periodontal disease as a con-tinuum of infection to inflammatory dysregulationand subsequent bone loss, specific biomarkers,


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