GENOME-WIDE ASSOCIATION STUDY OF PERIODONTAL DISEASE

描述(由申请人提供)：这项申请代表了一项令人兴奋的全基因组关联研究，以确定与缺牙、牙周炎和牙周炎相关的基因。我们打算使用两个初级数据库进行GWAS荟萃分析；一个数据库有6786名受试者[来自社区中的牙科动脉硬化风险研究]，另一个数据库有4308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Affymetrix Human SNP阵列6.0创建的完整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。我们打算使用荟萃分析的方法结合这两个数据集来识别与无牙牙、牙周炎和牙周炎相关的基因。使用Illumina 1M SNP芯片平台创建的牙周表型和基因数据的3075名受试者[健康与身体成分(HealthABC)研究]的第三个数据集将用于复制这些发现。这代表着一项合作，利用Dental ARIC数据将北卡罗来纳大学牙科学院的牙科研究人员、北卡罗来纳大学公共卫生学院(DARIC)的遗传流行病学家以及另外两个小组--德国格雷夫斯瓦尔德大学(SHIP)和匹兹堡大学洛杉矶分校(HealthABC)--聚集在一起。据我们所知，我们建议在一个有代表性的成人群体中，对与牙周病相关的基因进行首次全基因组调查。我们很幸运地与一位杰出的遗传流行病学家Kari North博士合作，他将领导基因调查和统计分析。我们有一个批准的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GWA。我们建议使用口腔疾病的各种定义来开发特定于种族的口腔疾病关联模型--或者使用临床相关的临床体征簇来定义病例状态，或者通过使用临床体征独立地作为连续变量来定义临床表型，例如平均近端附着丧失，来对疾病进行分类。我们建议独立分析这两个数据集，然后使用表型的协调变量定义将它们合并进行荟萃分析。我们还打算检查基因-环境的相互作用，重点放在吸烟、肥胖、糖尿病和微生物负担作为效果修饰物。最后，我们将使用HealthABC数据集执行复制分析。我们的目标是识别新的基因，赋予牙周病的易感性或抵抗力，使我们能够引入新一代牙周诊断、风险评估和靶向治疗；作为个性化药物的实现。 公共卫生相关性：该应用程序寻求进行全基因组关联研究(GWAS)，以确定与缺牙、牙周炎和牙周病相关的候选基因，使用两个具有代表性的社区居住人口，约11,084人。该项目旨在对这一人群进行GWASMeta分析，该分析拥有完整的基因分型、临床表型、医学和风险因素数据，并使用第三个数据库复制发现，该数据库包含1000多名受试者。这是一个独特的机会，可以在具有一系列疾病的代表性社区人群中对牙周病进行首次GWA，并使用微生物负荷、代谢状态(糖尿病和肥胖)和吸烟作为暴露条件进行基因-环境相互作用分析。我们的目标是识别新的基因，赋予牙周病的易感性和抵抗力，使我们能够开创牙周诊断、风险评估和靶向治疗的新纪元。

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.