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），以确定与牙龈炎，牙龈炎和牙周炎相关的基因。我们打算使用两个主数据库进行GWAS荟萃分析；一项研究有6786名受试者[来自社区牙齿-动脉粥样硬化风险（DARIC）研究]，另一项研究有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 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。我们打算使用荟萃分析方法结合这两个数据集来确定与牙龈炎、牙龈炎和牙周炎风险相关的基因。使用Illumina 1m SNP芯片平台创建的第三个数据集[健康与身体成分（HealthABC）研究]包含牙周表型和基因型数据，将用于复制这些发现。这代表了北卡罗来纳大学牙科学院的牙科研究人员使用牙科ARIC数据，北卡罗来纳大学公共卫生学院（DARIC）的遗传流行病学家和另外两个小组-德国格雷夫斯瓦尔德大学（SHIP）和加州大学洛杉矶分校/匹兹堡大学（HealthABC）的合作。据我们所知，我们将对具有代表性的成人牙周病相关基因进行首次全基因组调查。我们有幸与一位杰出的遗传流行病学家Kari North博士合作，她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，以确定牙周病的基因关联，并承诺共享SHIP和HealthABC数据集，以进行meta分析和复制。我们打算利用D-ARIC （n=6786）和SHIP （n= 4308）的现有数据，应用各种牙周病临床病例定义进行GWAS。我们建议使用不同的口腔疾病定义来开发种族特异性的基因关联模型——或者使用临床相关的临床症状集群来定义病例状态的疾病分类，或者使用独立的临床症状作为连续变量来定义临床表型，例如平均近端间附着丧失。我们建议独立分析这两个数据集，然后对它们进行荟萃分析，使用统一的表型变量定义。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效应修饰因子。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抗性的新基因，使我们能够迎来新一代牙周病诊断、风险评估和靶向治疗；作为个体化医疗的实现。

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.