DATA MANAGEMENT AND STATISTICAL ANALYSIS CORE

University Of California-Irvine, Irvine CA

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Abstract

ABSTRACT OF RESEARCH PLAN Premature birth is recognized as the most significant problem in maternal-child health in the United States. The underlying genetic and environmental factors that contribute to spontaneous preterm birth are poorly understood due to the complex interactions that exist between the mother and fetus to ensure pregnancy continues to term and to the difficulty in applying standard statistical models to study these integrated pathways. This Program Project grant will identify the genetic and environmental factors that contribute in a multifactorial manner to preterm birth, and model the gene, environment and maternal-fetal interactions that may contribute to risk of prematurity. The broad goals of Project II are to model the contribution of genetic and environmental factors that explain inter-individual differences in measures of the maternal-placental-fetal (MPF) neuroendocrine pathway and in prematurity, incorporating maternal-fetal genotype interaction, gene-gene interaction (epistasis), gene-environment interaction and environment-environment interaction. Project II will utilize the phenotypic and clinical measures obtained by the Clinical Core B on 1,200 mother-child pairs, together with the genotypic information on the same individuals typed for multiple SNPs in 16 MPF-related genes collected by the Genotyping Core C. These goals will be accomplished by. 1) establishing for each of the three racial/ethnic populations which variable DNA sites in the mother and fetus, and environmental factors, statistically explain interindividual variation in measures of the MPF neuroendocrine pathway and prematurity (AIM 1), 2) establishing which combination of the variable DNA sites and environmental factors identified in AIM 1 statistically explain interindividual variation in prematurity-related outcomes beyond that predicted by measures of the MPF neuroendocrine pathway (via unmeasured intermediate physiological traits) separately in each racial/ethnic strata (AIM 2) and 3) using the genetic and environmental variables identified in AIM 1, model the genetic architecture of preterm birth incorporating maternal-fetal genotype interaction, gene-gene interaction (indicative of epistasis or non-additivity), gene-environment interaction and environment-environment interaction (AIM 3).