OVERALL - GENE-ENVIRONMENT INTERACTIONS IN HUMAN PARTURITION

描述(由申请者提供)：这项名为“人类分娩中的基因-环境相互作用”的计划项目建议评估关于候选易感基因中DMA序列变异和功能的信息的有效性，以了解和预测早产的风险及其发病率中的种族/民族差异。我们的目标是开发一个基因/表型资源和分析策略，以确定人类妊娠时间长短/自然分娩开始的遗传和环境决定因素，并对可能在三个种族/民族群体中可能导致早产风险的基因、环境和母胎交互作用进行建模：非洲裔美国人、西班牙裔和非西班牙裔白人。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数量以及显性、上位性、多效性和遗传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效应的相对频率的异质性而在不同种群之间变化，因此在我们的分析中将开发特定于种群的模型。我们的研究计划将由三个独立但相互关联的项目组成，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--怀孕期间遗传变异的群体结构(James Hixson，Pi)--将确定16个候选基因在三个目标种族/族裔群体之间和之间的遗传变异的全部程度和分布。项目2--人类分娩中的基因类型--表型关系(Charles F.Sing，Pi)--将研究基因-表型关联，以确定胎儿和母体基因变异的哪一个子集，结合特定的环境因素，预测三个目标种族/民族人群中每一个人的中间生理和临床终点的测量。项目3--怀孕中遗传变异的功能意义(Pathik D.Wadhwa，Pi)--将描述母婴遗传变异与分娩动态以及体内与应激相关的生理过程之间的功能关系。这四个核心是：A)行政核心(帕特里克·瓦德瓦主任)，作为中央协调所有项目和核心活动的行政办公室(将包括一个执行委员会以及内部和外部咨询委员会)；B)临床核心(卡尔文·霍贝尔主任)，收集1,200个母婴二联体的临床测量数据，包括DNA样本以及中间生理、临床终点和环境风险因素的测量；C)基因分型核心(詹姆斯·E·希克森主任)，广泛地对16个候选基因和1,200个母婴DNA样本和未连接的基因组控制多态标记进行重新排序；和d)数据库管理和统计分析核心(Charles F.Sing，主任)，负责维护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.