Modeling childhood dental caries patterns for genomic and epigenetic analysis

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DESCRIPTION (provided by applicant): Dental caries is the most common chronic disease in US children, and has actually increased in prevalence among young children in the last decade. Untreated childhood dental caries has a profound negative impact on quality of life, leading to many serious comorbidities, including chronic pain, tooth loss, difficulty hearing, eating, and sleeping, and failure to thrive, as well as poor school performance, social relationships, and self image, and decreased success later in life. In response to these negative health and social consequences, dental caries has become a focal issue in efforts to reduce public health disparities for both the NIDCR and the American Academy of Pediatrics. Treatment of dental caries consumes over $50 billion annually in dental health care costs; however, these expenditures are unfortunately concentrated in a caries management paradigm of surgical restoration (or extraction), which treats the symptoms of dental caries, while ignoring the root causes of disease. This approach disadvantages those with socioeconomic, geographic, or logistical barriers to accessing routine dental care. In order to shift the caries management paradigm to a model of risk assessment, early intervention, and recurrence prevention, the etiological factors controlling caries susceptibility will need to be identified. Our project seeksto fill this need, focusing on the genetic factors contributing to disease and applying innovative statistical methods of modeling dental caries experience. Indeed, studies shown that up to 60% of variation in caries experience may be attributed to host genetics; however, little is presently known about the specific genetic variants that contribute to cariogenesis, how these genes interact with environmental risk factors, and whether inherited epigenetic factors are also involved. This proposal will seek to fill the gap in knowledge regarding the environmental and genetic factors leading to childhood dental caries by modeling the patterns of caries across the dentition. We will conduct genome-wide association analysis utilizing two existing samples totaling 1,500 children aged 3 to 12 years with quality caries and risk factor assessments and available genotype data from a high-throughput microarray platform. We hypothesize that the effects exerted by risk factors lead to patterns of decay, which can be modeled, and in turn used for identifying and characterizing the environmental, genetic, and epigenetic factors involved. Understanding the complex interplay between genetic and environmental contributors to dental caries may lead to never-before-considered targets for intervention, heralding the era of personalized medicine where dental caries management will be tailored to a patient's specific suite of genetic and environmental liabilities. The potential gains of this project are enormous and come at minimal costs.