GENOME-WIDE ASSOCIATION STUDY OF PERIODONTAL DISEASE

描述（由申请人提供）：该申请代表了一项令人兴奋的GWAS（全基因组关联研究），以确定与缺牙、牙龈炎和牙周炎相关的基因。我们打算使用两个主要数据库进行GWAS荟萃分析;一个数据库包含6，786名受试者[来自牙科-社区动脉粥样硬化风险（DARIC）研究]，另一个数据库包含4，308名受试者[来自波美拉尼亚健康研究（SHIP）研究]。这两个数据集都有最近使用Affyscore Human SNP Array 6.0创建的全基因组基因分型数据，并有详细的临床牙周检查数据，以及完整的医疗和风险因素数据。我们打算使用一个荟萃分析的方法结合这两个数据集，以确定基因，赋予无牙，牙龈炎和牙周炎的风险。使用Illumina 1 m SNP芯片平台创建的具有牙周表型和基因型数据的3075名受试者的第三数据集[健康和身体成分（HealthABC）研究]将用于复制这些发现。这代表了一项合作，该合作汇集了使用牙科ARIC数据的牙科研究人员，以及公共卫生学院（DARIC）的遗传流行病学家和其他两个团体-Greifswald德国的U（SHIP）和匹兹堡的UCLA/U（HealthABC）。总之，我们建议进行什么，我们的知识将是第一个全基因组调查的基因与牙周病在一个有代表性的成年人口。我们很幸运能与一位杰出的遗传流行病学家Kari North博士合作，他将领导遗传调查和统计分析。我们有一个经批准的ARIC协议来分析这些数据与牙周病的基因关联，并承诺共享SHIP和HealthABC数据集，用于MET分析和复制。我们打算使用来自D-ARIC（n=6786）和SHIP（n=4,308）的现有数据，应用牙周病的各种临床病例定义进行GWAS。我们建议使用口腔疾病的各种定义来开发全基因关联的种族特异性模型-使用临床相关的临床体征集群来定义病例状态的疾病分类，或通过使用临床体征独立地定义临床表型作为连续变量，例如平均邻间附着丧失。我们建议独立分析这两个数据集，然后进行荟萃分析汇总它们，使用统一的变量定义的表型。我们还打算研究基因与环境的相互作用，重点是吸烟，肥胖，糖尿病和微生物负担作为影响因素。最后，我们将使用HealthABC数据集执行复制分析。我们的目标是确定赋予牙周病易感性或抵抗力的新基因，使我们能够迎来新一代牙周诊断，风险评估和靶向治疗;实现个性化医疗。 公共卫生相关性：本申请旨在进行全基因组关联研究（GWAS），以使用两个代表性社区居住人群（约11，084人）鉴定与缺牙、牙龈炎和牙周病相关的候选基因。该项目旨在对该人群进行GWAS荟萃分析，该人群具有完整的基因分型，临床表型医学和风险因素数据，并使用超过1000名受试者的第三个数据库复制研究结果。这是一个独特的机会，可以在患有一系列疾病的代表性社区人群中对牙周病进行第一次GWAS，并使用微生物负荷，代谢状态（糖尿病和肥胖）和吸烟作为暴露进行基因-环境相互作用分析。我们的目标是确定赋予牙周病易感性和抵抗力的新基因，使我们能够开创牙周诊断，风险评估和靶向治疗的新时代。

DESCRIPTION (provided by applicant): This application represents an exciting GWAS (Genome-Wide Association Study) to identify genes associated with edentulism, gingivitis and periodontitis. We intend to perform a GWAS meta-analysis using two primary databases; one with 6,786 subjects [from the Dental- Atherosclerosis Risk in Communities (DARIC) Study] and another with 4,308 subjects [from the Study of Health in Pomerania (SHIP) Study]. Both datasets have whole genomic genotyping data recently created using the Affymetrix Human SNP Array 6.0 and have detailed clinical periodontal examination data, and complete medical and risk factor data. We intend to use a meta-analysis approach combining these two datasets to identify genes that confer risk for edentulism, gingivitis and periodontitis. A third dataset of 3075 subjects [Health and Body Composition (HealthABC) Study] with periodontal phenotypes and genotype data created using the Illumina 1m SNP chip platform will be used for replication of these findings. This represents a collaboration that brings together the dental researchers at the UNC School of Dentistry using the Dental ARIC data, and the genetic epidemiologists at the UNC School of Public Health (DARIC) and two other groups - U of Greifswald Germany (SHIP) and UCLA/U of Pittsburgh (HealthABC). Together, we propose to perform what to our knowledge will be the first genome-wide survey for genes which are associated with periodontal disease in a representative adult population. We are fortunate to work with an outstanding genetic epidemiologist, Dr Kari North who will lead the genetic survey and statistical analyses. We have an approved ARIC protocol to analyze these data for gene associations for periodontal disease and have a commitment for the sharing of the SHIP and HealthABC datasets for the met-analysis and replication. We intend to conduct a GWAS applying various clinical case definitions of periodontal disease using existing data from both D-ARIC (n=6786) and SHIP (n=4,308). We propose to develop race-specific models for gene-wide associations using various definitions of oral disease - either categorical classifications of disease using clinically relevant clusters of clinical signs to define case status or by defining clinical phenotypes using clinical signs independently as continuous variables, such as mean interproximal attachment loss. We propose to analyze the two datasets independently and then conduct a meta-analysis pooling them, using harmonized variable definitions for the phenotypes. We also intend to examine for gene-environment interactions focusing on smoking, obesity, diabetes and microbial burden as effect modifiers. Finally, we will perform a replication analysis using the HealthABC dataset. Our goal is to identifying novel genes that confer either susceptibility or resistance to periodontal disease to enable us to usher in a new generation of periodontal diagnostics, risk assessments and enable targeted therapeutics; as a realization of personalized medicine. PUBLIC HEALTH RELEVANCE: This application seeks to conduct a genome-wide association study (GWAS) to identify candidate genes that are associated with edentulism, gingivitis and periodontal disease using two representative community dwelling populations of approximately 11,084 individuals. This project seeks to perform a GWAS meta-analysis on this population that has full genotyping, clinical phenotyping medical and risk factor data, and replicating the findings using a third database of over 1000 subjects. This is a unique opportunity to perform the first GWAS on periodontal disease in representative community populations with a range of disease, and to conduct gene-environment interaction analyses using microbial load, metabolic status (diabetes and obesity) and smoking as exposures. Our goal is to identify new genes that confer susceptibility and resistance to periodontal disease to enable us to usher in a new era of periodontal diagnostics, risk assessment and targeted therapy.