Early Life Social, Environmental, and Nutritional Determinants of Disease

This project will continue our work in two birth cohorts of mother-infant Latino dyads (NCT04434027 & NCT03141346) through a series of new assessments at age 6y, with a focus on examining the role of early nutritional exposures, exposures to environmental toxins, and social determinants of health (SDOH) on adiposity, eating behaviors, brain structure and function, cognitive outcomes, and chronic disease risk. This collection of assessments at 6 years of age is funded by two grants (R01 DK110793 01A1 & P50 MD017344). Breast milk has been shown to contain certain macronutrients (human milk oligosaccharides; HMOs) that vary greatly among women. Research from our lab recently characterized associations of HMOs with infant obesity, eating behaviors, and brain development as well as dynamic changes in HMOs over the course of breastfeeding and suggests that these factors are significant predictors of infant weight gain and adiposity. Additionally, we already obtained detailed individual measures of ambient and near-roadway air pollution exposure from pregnancy to 2y of age. Our previous work in a subset of participants from the proposed cohort found that increased prenatal exposure to ambient air pollutants was associated with increased infant growth and adiposity after adjusting for infant sex and age, pre-pregnancy BMI, breastfeeding, maternal age, season of birth, and SES. By conducting longer-term follow-up with more rigorous outcomes at age 6y, we will be able to more definitively determine if and how early nutrition, particularly specific HMOs, impact chronic disease risk in Latino children as well as how environmental exposure to toxins and the food environment may exacerbate these health outcomes. Here, we will explore:

1. The impact of infant exposure to environmental toxins on subclinical markers of chronic disease risk at age 6y.
2. The impact of infant exposure to environmental toxins and nutrition, especially the HMOs 2'FL, LNFPI, LNFPII, LNnT & LNH, in early life on adiposity and chronic disease risk at age 6y.
3. The impact of infant exposure to HMOs containing fructose and sialic acid on brain development at age 6y using image-based measures of brain structure (anatomical MRI), function (resting state fMRI), blood flow (arterial spin labeling), myelination and tissue microstructure (diffusion tensor imaging) as well as cognitive outcomes.
4. The impact of breast feeding (at breast vs delivered via a bottle) and the changing HMO profile on eating in the absence of hunger at age 6y, and structural and functional differences in key areas of the brain involved with appetite regulation (frontal cortex, basal ganglia, hippocampus, hypothalamus).
5. The impact of the food environment and broader SDOH on subclinical markers of chronic disease and how these relationships may exacerbate the effects of poor nutrition and environmental toxins.

Exposures:

Ambient Air pollution: Addresses will be used to generate x,y coordinates of latitude and longitude, geoIDs, and census tracts. These spatial elements will be used to query several databases to generate new geocoded social and environmental exposure variables. In addition, child dates of birth will be used to assign air pollution exposure estimates and community contextual variables for relevant time windows in early life through 6 years of age. Ambient air pollution will be measured by assigning PM2.5, NO2, and O3 exposures using hybrid model outputs developed by a team lead by Dr. Joel Schwartz (Harvard) over many years.

Near-Roadway Air Pollution (NRAP) : Addresses will be used to generate x,y coordinates of latitude and longitude, geoIDs, and census tracts. These spatial elements will be used to query several databases to generate new geocoded social and environmental exposure variables. In addition, child dates of birth will be used to assign air pollution exposure estimates and community contextual variables for relevant time windows in early life through 6 years of age. NRAP is a complex mixture of particles and gases, including particulate matter, organic compounds, elemental carbon, and polycyclic aromatic hydrocarbons. In this study, NRAP exposure will be characterized using the CALINE4 air quality dispersion model that incorporate HERE (www.here.com) detailed roadway geometry, traffic volumes from Streetlytics™ by Citilabs, Inc. (www.citilabs.com), vehicle emission rates from CARB's EMFAC2017 model, and atmospheric transport and dispersion (using wind speed, wind direction, atmospheric stability, and height of the mixing layer).