OVERALL - GENE-ENVIRONMENT INTERACTIONS IN HUMAN PARTURITION

描述（由申请人提供）：本项目名为“人类分娩中的基因-环境相互作用”，旨在评估关于DMA序列变异和候选易感基因功能的信息的效用，以了解和预测早产的风险和其患病率的种族/民族差异。我们的目标是开发基因型/表型资源和分析策略，以确定人类妊娠时间/自然分娩开始时间的遗传和环境决定因素，并模拟基因、环境和母胎相互作用，这些因素可能是三种种族/民族人群（非裔美国人、西班牙裔和非西班牙裔白人）早产风险的基础。分娩的遗传结构被定义为基因座的数量，它们的基因组位置，每个基因座的功能等位基因的数量，以及显性、上位性、多效性和基因环境相互作用的模式，这些模式表征了从基因型到表型的转变。由于分娩的遗传结构可能因遗传和环境影响相对频率的异质性而在不同种群中有所不同，因此我们将在分析中建立特定种群的模型。我们的研究计划将包括三个独立但相互关联的项目，这些项目提出并实证检验假设，以及为每个项目提供必要资源的四个核心。项目1 -孕期遗传变异的群体结构（James Hixson， PI） -将确定三个目标种族/民族群体之间16个感兴趣的候选基因的遗传变异的全部程度和分布。项目2 -人类分娩中的基因型-表型关系（Charles F. Sing， PI）-将检查基因型-表型关联，以确定胎儿和母亲遗传变异的哪个亚群，结合特定的环境因素，预测三个目标种族/民族人群的中间生理学和临床终点的测量。项目3 -遗传变异在妊娠中的功能意义（Pathik D. Wadhwa， PI） -将描述母体和胎儿遗传变异与分娩动力学和体内应激相关生理过程之间的功能关系。四个核心是A)行政核心（Pathik Wadhwa，主任），作为行政办公室，对所有项目和核心活动进行中央协调（将包括一个执行委员会和内部和外部咨询委员会）；B)临床核心（Calvin J. Hobel，主任）收集1200对母婴的临床数据，包括DNA样本和中间生理学、临床终点和环境风险因素的测量；C)基因分型核心（James E. Hixson，主任）对16个候选基因进行广泛的重测序，并对1200个母胎DNA样本和非连锁基因组控制多态性标记进行基因分型；D)数据库管理和统计分析中心（Charles F. Sing，主任）负责维护一个中央研究数据库，并对所有项目进行统计分析。

DESCRIPTION (provided by applicant): This Program Project, entitled Gene-Environment Interactions in Human Parturition, proposes to evaluate the utility of information about DMA sequence variation and function in candidate susceptibility genes to understand and predict the risk of preterm birth and racial/ethnic disparities in its prevalence. Our goal is to develop a genotype/phenotype resource and analytical strategies to identify the genetic and environmental determinants of the length of human gestation/ tinning of onset of spontaneous parturition, and to model the gene, environment, and maternal-fetal interactions that may underlie the risk of preterm birth among three racial/ ethnic populations: African-Americans, Hispanics and nonHispanic Whites. The genetic architecture of parturition is defined as the number of loci, their genomic positions, the number of functional alleles per locus, and the patterns of dominance, epistasis, pleiotropy, and geneenvironment interactions that characterize the transition from genotype to phenotype. Because the genetic architecture of parturition may vary among populations as a function of the heterogeneity of the relative frequencies of genetic and environmental effects, population-specific models will be developed in our analysis. Our research program will consist of three separate but inter-linked projects that propose and empirically test hypotheses, and four cores that provide the requisite resources for each of the projects. Project 1 - Population Structure of Genetic Variation in Pregnancy (James Hixson, PI) - will determine the full extent and distribution of genetic variation in the 16 candidate genes of interest among and between the three target racial/ethnic populations. Project 2 - Genotype- Phenotype Relationships in Human Parturition (Charles F. Sing, PI)- will examine genotype-phenotype associations to determine which subset of fetal and maternal genetic variations, in combination with specific environmental factors, predict measures of intermediate physiology and clinical end points in each of the three target racial/ethnic populations. Project 3 - Functional Significance of Genetic Variation in Pregnancy (Pathik D. Wadhwa, PI) - will characterize the functional relationships between maternal and fetal genetic variation and the dynamics of parturitionand stress-related physiological processes in vivo. The four cores are A) Administrative Core (Pathik Wadhwa, Director), to serve as an administrative office for the central co-ordination of all project and core activities (will include an Executive Committee and Internal and External Advisory Boards); B) Clinical Core (Calvin J. Hobel, Director) to collect clinical measures on 1,200 maternal-infant dyads, including DNA samples and measures of intermediate physiology, clinical end points and environmental risk factors; C) Genotyping Core (James E. Hixson, Director) to extensively resequence the 16 candidate genes and genotype 1,200 maternal-fetal DNA samples and unlinked genomic control polymorphismic markers; and D) Database Management and Statistical Analysis Core (Charles F. Sing, Director) to maintain a central study database and execute statistical analyses for all projects.