EPIDEMIOLOGY/GENE MAPPING OF EARLY ONSET PERIODONTITIS

项目二：早发性牙周炎的遗传流行病学和分子基因定位研究大量证据表明，个体间的遗传差异影响早发性牙周炎（EOP）的风险。然而，这种疾病显然具有复杂的病因。遗传变异和环境因素（例如，吸烟、卫生、接触病原体）似乎在确定疾病风险方面相互作用。我们以前的研究表明白细胞介素-1多态性与EOP易感性相关。其他可能的易感基因被定位到染色体区域，但尚未明确确定。我们还启动了EOP相关表型的基因定位研究，如吸烟行为和血清免疫球蛋白。人类分子基因组学和统计遗传流行病学的最新重大进展大大提高了人类分子基因组学的能力，统计遗传流行病学大大提高了识别复杂性状（如EOP）基因的能力。我们建议应用这些工具和方法来跟进我们先前对EOP的研究结果：i）通过分析额外的IL-1多态性和额外的EOP家族和病例对照受试者来验证IL-1在EOP中的作用; ii）使用额外的EOP家族复制我们的其他基因作图EOP发现，通过突变筛选鉴定疾病基因，评估新的候选基因多态性，以及，iii）分析风险因素表型如吸烟和免疫球蛋白水平，作为EOP分析的协变量和作为直接感兴趣的高度遗传性状;（iv）开发和评估EOP的定量测量，以代替当前的离散疾病状态分类，并使用这些定量特征利用方差分量分析和其他数量性状位点（QTL）方法对我们的基因定位数据进行重新分析。

Project 2: Genetic Epidemiology and Molecular Gene Mapping Studies of Early Onset Periodontitis Substantial evidence indicates that genetic differences among individuals influence risk of early onset periodontitis (EOP). However, this disease clearly has a complex etiology. Both heritable variation and factors in the environment (e.g., smoking, hygiene, exposure to pathogens) appear to interact in determining disease risk. Our previous studies demonstrated an association or interleukin-1 polymorphisms and EOP susceptibility. Other possible susceptibility genes were mapped to chromosomal regions but not yet specifically identified. We also initiated gene mapping studies of EOP-related phenotypes such as smoking behavior and serum immunoglobulins. Recent major advances in human molecular genomics and statistical genetic epidemiology provide greatly increased power in human molecular genomics and statistical genetic epidemiology provide greatly increased power to identify genes underlying complex traits such as EOP. We propose to apply these tools and approaches to follow up our previous findings for EOP by: i) verifying the role of IL-1 in EOP through analyses of additional IL-1 polymorphisms and additional EOP families and case-control subjects; ii) replicating our other gene mapping EOP findings using additional EOP families, identifying disease genes via mutational screening, evaluating new candidate gene polymorphisms and, when assay technologies mature, performing genome-wide disequilibrium mapping; iii) analyzing risk factor phenotypes such as smoking and immunoglobulin levels, both as covariates for EOP analyses and as highly heritable traits of direct interest; and iv) developing and evaluating quantitative measurements of EOP in lieu of the current discrete disease state classification and using these quantitative traits for re-analyses of our gen mapping data with variance components analyses and other quantitative trait locus (QTL) methods.