# Prenatal Exposure to Endocrine Disrupting Chemical Mixtures and ASD Risk

> **NIH NIH R01** · PENNSYLVANIA STATE UNIVERSITY, THE · 2020 · $363,425

## Abstract

With 1 in 68 US children affected by ASD, it is critical to identify modifiable risk factors. Recent evidence from
twin and family studies supports a substantive role for environmental factors originating in utero in addition to
predisposing genetic factors. Prenatal brain development is heavily influenced by hormonal mechanisms, and
endocrine disrupting chemicals (EDCs) cross the placenta to reach a fetus that is without full capacity to
metabolize and clear xenobiotics. Exposure to EDCs is ubiquitous, and such exposure has been linked to a
broad range of adverse neurodevelopmental outcomes. The evidence for EDCs as an ASD risk factor is currently
more limited, largely given the need for sufficient sample sizes and exposure assessments during critical
windows. In studying potential impacts of EDCs on ASD, it may also be particularly important to consider EDCs
as mixtures. This is because low-dose exposure still affects hormone levels, small changes in hormone levels
are known to have biologically important consequences, and combined effects of EDC mixtures exceed those
expected from single EDC exposures at comparable levels or from models assuming simple additive effects
among mixture components. The proposed project uniquely and efficiently leverages the availability of EDC
exposure biomarkers in two similarly designed pregnancy cohorts (the HOME and EARLI cohorts) in order to
study prenatal EDC mixture exposure and ASD-related phenotype in 474 maternal child dyads. The principal
outcome will be the Social Responsiveness Scale (SRS), a validated parent-report measure of quantitative
autism traits. We will use a novel two-step statistical approach combining Bayesian Kernel Machine Regression
(BKMR) with elastic net regularization to assess the cumulative effect of EDC mixtures and to highlight specific
chemicals driving the mixture association - key priorities for understanding the impact of these environmental
exposures. This approach will be applied to available biomarkers for a group of 73 EDCs. We will also re-run
this modeling approach in subgroups defined by sex, cognitive status, and presence or absence of an older
sibling with an ASD (all subjects in EARLI have affected older siblings) in order to explore effect modification.
Finally, because prenatal maternal thyroid hormone disruption has been linked to neurodevelopmental
outcomes, we will apply our modeling approach to estimate complex EDC mixture associations with maternal
prenatal thyroid hormone levels in exploratory analyses. Sensitivity analyses will be performed on the subgroup
of children meeting ASD diagnostic criteria. This study will investigate a prevalent, modifiable class of candidate
environmental ASD risk factors as assessed through biomarkers. Our work will be the largest prospective study
to date of EDC mixture effects on ASD-related outcomes and among the first to employ the latest sophisticated
analytic methods that acknowledge the complexity of mixture exposure; th...

## Key facts

- **NIH application ID:** 10020188
- **Project number:** 5R01ES026903-04
- **Recipient organization:** PENNSYLVANIA STATE UNIVERSITY, THE
- **Principal Investigator:** Craig J Newschaffer
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $363,425
- **Award type:** 5
- **Project period:** 2017-09-15 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10020188

## Citation

> US National Institutes of Health, RePORTER application 10020188, Prenatal Exposure to Endocrine Disrupting Chemical Mixtures and ASD Risk (5R01ES026903-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10020188. Licensed CC0.

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