McLean, Jeffrey SKerns, Kristopher Alan2021-10-292021-10-292021Kerns_washington_0250E_23491.pdfhttp://hdl.handle.net/1773/47875Thesis (Ph.D.)--University of Washington, 2021Gingival inflammation as the result of microbial plaque accumulation during cessation of oral hygiene within humans has been investigated for over 50 years; however, it was not until recently in which variation in clinical response had been temporally characterized through the simultaneous application of high resolution clinical, host, and microbiome analysis in parallel – resulting in characterization of key host and microbial factors distinguishing High and Low clinical responders as well as a discovery of a novel third responder phenotype (Slow). Additionally, only a limited number of studies within the literature have aimed to temporally characterize the molecular and subclinical changes within distant otherwise generally healthy tissues in the oral cavity with the same resolution. In the present study, using the plaque-induced experimental gingivitis model with a split mouth design, in which each individual provides their own intra-oral control, we were able to robustly characterize the temporal dynamics of a panel of 41 host mediators (chemokines, cytokines) as well as the subgingival microbiome within healthy control sites among these different Clinical Responder Phenotypes (CRPs) (High, Low, Slow) while plaque-induced inflammation was being induced in a controlled way within test sites located contralaterally in the mouth. Our results highlight a temporal shift in host mediators, including pro-inflammatory markers IL-8, IL-6, and TNF-a, within healthy contralateral control sites across CRPs, similarly to respective test sites, despite maintained normal oral hygiene, no significant visible plaque accumulation (VPI or PI), or clinical gingival inflammation (GI, BOP) among control sites. Additionally, through the application of the inverse Firmicutes/Bacteroidetes Ratio (iFBR), our results highlight a significant dysbiotic shift within healthy control sites that is also similarly observed within the respective contralateral test sites among the different CRPs. Together these results provide new comprehensive evidence of an oral contralateral effect within the human oral cavity in which healthy homeostasis within control sites is altered due to microbially-induced inflammation occurring in distant test sites within the mouth – with the variation in this contralateral effect being directly related to an individual’s CRP. These results ultimately led to the development of multiple predictive models using the Random Forest Machine Learning algorithm in order to identify an individual’s Clinical Responder Phenotype from their natural oral health state. In conclusion, results from this study as part of this dissertation research project have great implications for future clinical gingivitis research with the major findings being that distant otherwise generally healthy sites are affected by microbially-induced inflammation occurring elsewhere in the mouth with the severity being related to an individual’s Clinical Responder Phenotype. While clinical implications of these results highlight our ability to now predict an individual’s likelihood to be one of the three Clinical Responder Phenotype which may be related to their risk and severity of inflammation that results in progression to a more devastating gingival disease state (periodontitis) and may even be used to dictate patient surveillance and treatment planning – together representing a major advance.application/pdfen-USnoneContralateralExperimental GingivitisHost MediatorsInflammationMicrobiomePredictive ModelMicrobiologyDentistryBioinformaticsThesis