Mechanisms underlying the variation in rate and levels of gingival inflammatory responses among the human population

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Abstract The goal of this research is to provide a roadmap to maintain periodontal health by understanding the mechanisms which underlie the variation in inflammatory responses within the human population. Ultimately, this information will be translated to individualized preventive and treatment regimens based on host response phenotype. Periodontitis is one of the most prevalent non-communicable diseases in adults worldwide and a major public health concern. According to the latest World Workshop in Periodontics there is immense potential in studying gingivitis, an antecedent reversible disease state, as a means of primary prevention of periodontitis. Healthy periodontal tissue exists in a homeostatic relationship with its accompanying oral microbiome. In most individuals, this relationship results in a combination of host and microbial derived immune components that produce an active inflammatory surveillance protective state. This is termed healthy homeostasis. Disruptions of this healthy homeostatic state occur during episodes of both experimental and natural gingivitis, which is defined as reversible inflammation of the gingiva. The ability to induce a reversible inflammatory state in humans has provided a unique foundation to examine microbial-host interactions that dictate periodontal health and disease via the human Experimental Gingivitis (EG) model. We will capitalize on our previous work with the highly translational human experimental gingivitis model where we have identified three distinct clinical response phenotypes, which behave differently to bacterial-driven inflammation. We will use these clinical phenotypes as a foundation to explore the variability in the human inflammatory response. Specifically, we will determine the contributions of host components and microbial ecological succession patterns to the observed variations among responder types. The approach for this proposed research is to determine the bacterial and host processes in stages of health through disease using advanced parallel multi-omic measurements of both bacteria and host components coupled with ex vivo and in vitro mechanistic studies to determine the host and associated microbial functions that determine the variation in host responses. We will employ a comprehensive combination of functional meta-omics in parallel (DNA and RNA 16S sequencing, metagenomics, metabolomics, custom multiplex Immunoassay of host mediator panels) along with complementary cultivation approaches for hypothesis testing. We anticipate there will be an immediate benefit from our proposed detailed investigations in terms of the comprehensive multi-omic datasets we will generate and make available – enabling responder types to be identified and further characterized across studies. In the longer term, this fundamental mechanistic work has direct clinical and therapeutic value by identifying potential critical targets during disease initiation and development within each of the different response types that can translate to personalized treatment and intervention strategies.