# Examining dietary modifiers of associations between air pollution and autism-related outcomes in two cohorts

> **NIH NIH R01** · DREXEL UNIVERSITY · 2022 · $496,480

## Abstract

PROJECT SUMMARY
Prenatal air pollution exposure has been repeatedly identified as risk factor for autism spectrum disorder (ASD),
with support for associations with particulate matter less than 2.5 microns in diameter (PM2.5), ozone, and
nitrogen dioxide (NO2). Research from other fields suggests diet may be a key modulator of air pollution risks in
pathways relevant to autism, yet only one study, examining the joint effects of folate and air pollution, has been
published on ASD risk. However, a range of dietary factors beyond folate, including polyunsaturated fatty acids
(PUFAs) and vitamin D, may serve to offset effects of exposures. In addition, given that nutrients do not act in
isolation, studying single nutrient-pollutant interactions may provide only part of the picture. Further, time-
windows for such modification have not been identified. In the proposed study, we will address these gaps and
examine how prenatal diet may modify air pollutant associations with ASD-related outcomes in two prospective
cohorts. The Nurses’ Health Study 3 (NHS3) is an ongoing, large prospective cohort of nurses from across the
US that includes a pregnancy sub-cohort (n>7,000). The Early Autism Risk Longitudinal Investigation (EARLI)
is a high-risk cohort that followed mothers who already had a child with ASD through a subsequent pregnancy
until that child was age 3 (n~200). ASD-related outcomes will be captured in both studies according to Social
Responsiveness Scale (SRS) scores, as well as ASD diagnosis, allowing us to consider both dimensional traits
across the population and diagnostic-level risks. Both studies will have air pollution exposure assignments for
PM2.5, NO2, and ozone from the same method and prenatal nutrient data from validated food frequency
questionnaires. Using these data, our aims are to: 1) Examine modification of air pollutant-ASD associations by
folate, vitamin D, and PUFAs; 2) Evaluate interactions between air pollutants and nutrients on ASD-related
outcomes within a multi-exposure framework; and 3) Examine time windows in the air pollution-ASD relationship
when dietary nutrients might be most impactful. Aim 1 analyses will use linear and logistic regression to examine
associations with SRS scores and ASD diagnosis, respectively, within strata of nutrients defined by deficiency
status and prior interaction in each cohort. In Aim 2, we will use Bayesian Kernel Machine Regression (BKMR)
to consider nutrient-pollutant interactions within the context of broader diet, accounting for a wider set of nutrients
and considering potential combined effects on ASD outcomes. In Aim 3, we will use distributed lag models to
consider potential critical windows of air pollutant associations with ASD-related outcomes in which nutrient
modifiers may have strongest effects. In this proposal we address a critical, yet understudied, area of research.
Due to the widespread occurrence of air pollution exposure, and because diet is a readily accessible, indi...

## Key facts

- **NIH application ID:** 10458729
- **Project number:** 5R01ES032469-02
- **Recipient organization:** DREXEL UNIVERSITY
- **Principal Investigator:** KRISTEN Lyall
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $496,480
- **Award type:** 5
- **Project period:** 2021-08-01 → 2026-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10458729

## Citation

> US National Institutes of Health, RePORTER application 10458729, Examining dietary modifiers of associations between air pollution and autism-related outcomes in two cohorts (5R01ES032469-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10458729. Licensed CC0.

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