Prenatal stress biology, infant body composition and obesity risk

University Of California-Irvine, Irvine CA

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Abstract

DESCRIPTION (provided by applicant): The goal of our study is to examine the influence of adverse intrauterine conditions, or prenatal stress, on newborn and infant body composition and obesity risk. Obesity is one of the most important health issues facing our nation. The underlying causes at the individual level, and the reasons for its rapid increase in the population are not well-understood. Evidence suggests that the origins of obesity and its sequelae can be traced back to the intra-uterine period of life, at which time exposure to suboptimal conditions during development may result in fetal programming of physiological systems that then confer increased risk for obesity in childhood and adult life. The overwhelming majority of human epidemiological studies of fetal programming of obesity have relied on measures of either size at birth (such as low birth weight or small-for-gestational age birth), or fetal and early postnatal growth velocity, as markers of adverse intrauterine exposures. We propose an innovative and novel application of the fetal programming paradigm by emphasizing the use of a set of stress-related intrauterine maternal-placental-fetal (MPF) biological processes as the principal markers of exposure to intrauterine insult because MPF biological stress parameters may act as sensors of the quality of the intrauterine environment as well as transducers of its effects on the developing fetus and subsequent childhood and adult obesity risk. The specific questions addressed in our study include the following: (1) Do MPF indices of prenatal stress exposure over human gestation predict newborn body composition and change in body composition from birth until 6 months age, after accounting for the effects of other established risk factors for obesity? (2) Are there sensitive periods during gestation when the developing fetus is particularly vulnerable to the effects of prenatal biological stress on body composition? (3) Are MPF biological stress measures of the intrauterine environment more specific and sensitive predictors of newborn and infant body composition than currently-used measures of birth outcomes or fetal and early postnatal growth? (4) What are the consequences of MPF endocrine/immune-related changes in body composition on metabolic function (insulin sensitivity)? (5) Are the effects of prenatal biological stress on body composition mediated through a change in energy balance homeostasis set points and energy flux over time? We propose to conduct a prospective, longitudinal, follow-up study in a population-based cohort of infants born to mothers who will participate in a NIH-funded study of biological and behavioral processes in pregnancy. We will have extensive characterization in this infant cohort over the course of their intrauterine life and birth with all the prenatal measures required to address the above questions, including serial measures of the maternal-placental- fetal endocrine and immune/inflammatory milieu, serial ultrasound-based measures of fetal biometry, clinical measures of obstetric complications, measures of maternal biophysical, sociodemographic, behavioral, psychosocial characteristics, and measures of the birth phenotype. From this cohort we will recruit a sample of 120-140 children at birth and follow them up until 6 months age. We propose two major study assessments at T1=0-2 weeks and T2=6 months age. At each assessment our primary study outcome, child body composition, will be quantified by dual energy x-ray absorptiometry (DXA); total energy expenditure (TEE) will be quantified using the doubly labeled water (DLW) method; and metabolic function (insulin sensitivity) will be quantified from measures of blood glucose and insulin. Infant nutrition and feeding practices will be assessed concurrently using multiple-pass 24h diet recalls. State-of-the-art statistical modeling techniques for parametric and non-parametric repeated measures, time- series data, including generalized additive models, polynomial distributed lag, classification and regression trees, and multivariate regression analysis will be used to address the study aims. The significance and impact of this study derives from the importance of achieving at a better understanding of the underlying causes for increased susceptibility for obesity, thereby informing the development of new markers for early identification of risk and targets for intervention.