Modeling childhood dental caries patterns for genomic and epigenetic analysis

为基因组和表观遗传分析建立儿童龋齿模式模型

基本信息

批准号：
8822554
负责人：
John R Shaffer
金额：
$ 23.1万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-01-01 至 2016-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8822554
关键词：
Academy Affect American Animal Model Appalachian Region Asthma Behavioral Genetics Child Childhood Chromosome Mapping Chronic Disease Cluster Analysis Comorbidity Complex Data Dental Care Dental Enamel Dental caries Dentition Development Disadvantaged Disease Early Intervention Eating Endogenous Factors Environment Environmental Risk Factor Epigenetic Process Expenditure Failure to Thrive Family Study Fluorides Future Genes Genetic Genetic Risk Genetic study Genome Genomics Genotype Hay fever Health Health Care Costs Hearing Heritability Immune response Inherited Intervention Iowa Knowledge Lead Lesion Life Measures Meta-Analysis Methods Modeling Morphology National Institute of Dental and Craniofacial Research Operative Surgical Procedures Oral health Other Genetics Parents Patients Pattern Pediatrics Performance Phenotype Philosophy Plant Roots Positioning Attribute Predisposition Prevalence Primary Dentition Public Health Public Policy Quality of life Research Resources Risk Risk Assessment Risk Factors Rural Sampling Schools Self Perception Sleep Statistical Methods Surface Symptoms Time Tooth Loss Tooth structure Twin Multiple Birth United States Validation Variant Vision aged base chronic pain cohort cost demographics disorder later incidence prevention disorder prevention experience genetic analysis genetic risk factor genetic variant genome wide association study health disparity high risk improved innovation novel personalized medicine prevent public health relevance response restoration saliva composition social socioeconomics suburb success tooth surface

项目摘要

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.

描述（由申请人提供）：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已经增加。未经治疗的儿童牙齿龋齿对生活质量产生了深远的负面影响，导致许多严重的合并症，包括慢性疼痛，牙齿丧失，听力，饮食和睡眠困难以及不壮成长，以及不良的学校表现，社会关系和自我，图像，并在以后的生活中降低。为了应对这些负面的健康和社会后果，龋齿已成为减少NIDCR和美国儿科学会的公共卫生差异的努力的重点问题。龋齿的治疗每年消耗超过500亿美元的牙科医疗保健费用；但是，不幸的是，这些支出集中在手术恢复（或提取）的龋齿管理范式上，这些范式治疗了龋齿的症状，同时忽略了疾病的根本原因。这种方法缺席具有社会经济，地理或后勤障碍的人，无法获得常规牙科护理。为了将龋齿管理范式转移到风险评估，早期干预和预防的模型中，需要确定控制龋齿敏感性的病因学因素。我们的项目Seeksto满足了这一需求，重点是导致疾病的遗传因素，并采用创新的统计方法来建模龋齿体验。实际上，研究表明，龋齿经验的变化中最多可以归因于宿主遗传学。然而，目前对有助于癌变的特定遗传变异，这些基因如何与环境风险因素相互作用以及是否涉及遗传性表观遗传因素的特定遗传变异知识知之甚少。该提议将寻求填补有关通过对牙齿的龋齿模型建模导致龋齿的环境和遗传因素的知识的空白。我们将利用两个现有样本进行全基因组关联分析，总计1,500名3至12岁的儿童，具有优质的龋齿和危险因素评估以及来自高通量微阵列平台的可用基因型数据。我们假设风险因素所产生的效果导致衰减模式，可以对此进行建模，进而用于识别和表征所涉及的环境，遗传和表观遗传因素。理解遗传和环境促进症状症状之间的复杂相互作用可能会导致从未考虑过干预的目标，这使牙齿龋齿管理将根据患者的特定遗传和环境责任量身定制。该项目的潜在收益是巨大的，成本最低。