Maternal obesity is a serious health concern for pregnant women and their offspring. Recent studies revealed negative associations between maternal obesity during pregnancy and long-term cognitive functioning and neurodevelopment of children. There is likely a neuroprogramming effect of maternal obesity on fetal development, which may lead to differences in brain development and neurodevelopmental outcomes in children. The objective of this proposal is to identify the effects of maternal obesity on offspring brain structure and function. The rationale for the proposed research is that the combination of advanced magnetic resonance imaging (MRI) neuroimaging methods, electroencephalographic (EEG), and neurobehavioral assessments will provide new insights into the presence of in utero programing effects of maternal obesity on the developing brain. The overall hypothesis is that obesity in early pregnancy is associated with negative effects on brain structural and functional development in the newborn. This hypothesis will be tested with three Specific Aims:
Aim 1 : Determine whether brain structure differs in newborns of normal-weight verses obese mothers. At age 2 weeks, MRI will be used to assess infant brain volumetrics, and diffusion tensor imaging (DTI) will be performed to evaluate brain white matter microstructures. MRI/DTI parameters will be compared between groups and correlated with maternal body composition.
Aim 2 : Determine whether brain function and neurobehavioral measures differ in newborns of normal-weight verses obese mothers. At age 2 weeks, resting- state fMRI (RS-fMRI) will be used to compare the functional connectivity in infant brain networks between groups during natural sleep. In addition, measurements of resting brain electrical activity using EEG and assessments of neurobehavior using the NICU Network Neurobehavioral Scale (NNNS) will be obtained and compared between groups.
Aim 3 : Characterize neuroimaging biomarkers for the neuroprogramming effects of maternal obesity using a larger cohort, and identify additional prenatal factors that correlate with maternal obesity and influence offspring brain development.
Specific Aims 1 and 2 will be completed within two years and will provide preliminary data for an R01 application.
Specific Aim 3 will begin in Year 3 and will be the focus of the studies in the R01 application and those extending into independence. Up to 60 subjects in each group for each aim, including those in Aims 1 and 2, will be enrolled and studied. Using the COBRE Systems Biology Bioinformatics Core, a neuroinformatics approach will be applied to integrate the multimodality infant neuroimaging dataset with larger sample size to determine the ?neuro-signature? of maternal obesity. Multivariate statistical techniques will also be used to evaluate other prenatal factors, such as maternal metabolic health, diet, physical activity and stress during pregnancy, that may impact infant brain development, either independently or interactively with maternal obesity. In addition, neurodevelopmental outcomes will be measured at age 2 years to evaluate the predictive value of neuroimaging findings in the newborn.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Exploratory Grants (P20)
Project #
1P20GM121293-01
Application #
9210176
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
2017-06-01
Budget End
2018-05-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
Arkansas Children's Hospital Research Institute
Department
Type
DUNS #
002593692
City
Little Rock
State
AR
Country
United States
Zip Code
72202
Rahmatallah, Yasir; Khaidakov, Magomed; Lai, Keith K et al. (2017) Platform-independent gene expression signature differentiates sessile serrated adenomas/polyps and hyperplastic polyps of the colon. BMC Med Genomics 10:81
Holthoff, Emily R; Byrum, Stephanie D; Mackintosh, Samuel G et al. (2017) Vulvar squamous cell carcinoma aggressiveness is associated with differential expression of collagen and STAT1. Clin Proteomics 14:40