Modeling childhood dental caries patterns for genomic and epigenetic analysis

描述(申请人提供)：龋齿是美国儿童中最常见的慢性疾病，在过去十年中，幼儿的患病率实际上有所上升。未经治疗的儿童龋齿对生活质量有严重的负面影响，导致许多严重的并存，包括慢性疼痛、牙齿脱落、听力、进食和睡眠困难、无法茁壮成长，以及学习成绩、社会关系和自我 形象，并减少在以后的生活中的成功。为了应对这些负面的健康和社会后果，龋齿已成为NIDCR和美国儿科学会努力减少公共卫生差距的一个焦点问题。治疗龋齿每年消耗超过500亿美元的牙齿保健费用；然而，不幸的是，这些支出集中在外科修复(或拔除)的龋齿管理模式上，即治疗龋齿症状，而忽视疾病的根本原因。这种方法对那些在获得常规牙科护理方面存在社会经济、地理或后勤障碍的人不利。为了将龋病管理模式转变为风险评估、早期干预和复发预防的模式，需要确定控制龋病易感性的病因因素。我们的项目寻求满足这一需求，专注于导致疾病的遗传因素，并应用创新的统计方法来模拟龋齿经验。事实上，研究表明，高达60%的龋病变异可能归因于宿主遗传学；然而，目前对导致龋病发生的特定遗传变异、这些基因如何与环境风险因素相互作用以及是否也涉及遗传表观遗传因素知之甚少。这项建议将寻求通过对整个牙列的龋齿模式进行建模，来填补导致儿童龋齿的环境和遗传因素方面的知识空白。我们将利用现有的两个样本，总计1,500名3至12岁的儿童进行全基因组关联分析，这些样本包括高质量的龋齿和风险因素评估，以及来自高通量微阵列平台的可用基因数据。我们假设风险因素施加的影响会导致腐烂的模式，可以对其进行建模，进而用于识别和描述所涉及的环境、遗传和表观遗传因素。了解导致龋齿的基因和环境因素之间的复杂相互作用可能会导致以前从未考虑过的干预目标，这预示着个性化医学时代的到来，在这个时代，龋齿管理将根据患者特定的遗传和环境责任套件而量身定做。这个项目的潜在收益是巨大的，而且成本很低。

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.