# Maternal health in pregnancy and autism risk - genetic and non-genetic mechanisms

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2024 · $1

## Abstract

Autism spectrum disorder (ASD) affects 1 in 59 children1, and is caused by both genetic and environmental
factors. Nevertheless, the modifiable risk factors for this disorder remain unknown, creating a pressing public
health need. As ASD likely arises early in prenatal development considerable efforts in identifying such
modifiable risk factors have focused on maternal exposures in pregnancy. Some of those studies have shown
higher rates of ASD among children of women with e.g. diabetes, depression or recurrent infections. However,
(1) women experience many other conditions in pregnancy, most of which have not been studied in the context
of offspring ASD risk; and (2) the mechanisms underlying the association between maternal diagnoses and ASD
remain unknown. While placental permeability to multiple factors in maternal circulation renders direct effects of
maternal health on fetus plausible, this explanation has not been rigorously evaluated against the possibility that
both maternal diagnosis and child’s ASD are caused by overlapping genetic factors, transmitted from mother to
the child. In response, the key objectives of our proposal are to (1) test the associations between maternal health
and ASD systematically, across the full spectrum of maternal diagnoses, and accounting for their correlation,
and (2) elucidate the genetic and/or non-genetic mechanisms underlying those associations. To achieve this,
we propose independent, but synergistic, aims to increase the reliability and generalizability of our results.
Aim 1: Systematically identify maternal diagnoses in pregnancy associated with ASD in offspring. Aim 2:
Determine if the association between maternal diagnoses and ASD is due to transmitted genetic factors, using
information on family relations available in Denmark. Aim 3: Test the association between maternal diagnoses
in pregnancy and child’s genetic liability for ASD using molecular genetic data. We will use large, well-powered
sample of >723k live births from Denmark with full demographic, medical and pedigree information, as well as
genetic data for a subset of those individuals (N~26k). All significant associations will be replicated in an
American dataset (Kaiser Permanente Northern California) with ~320k births, ensuring external validity of our
results. The innovation of this project is three-fold: (1) it has a potential to identify novel risk factors (shown in
our preliminary data), (2) it introduces a methodological shift in ASD epidemiology, with large-scale, exposure-
wide and rigorous inference process, akin to that already applied in the field of genetics; and (3) for the first time,
it integrates national data from Nordic registries with one of the largest US-based cohorts (Kaiser Permanente).
This project will deliver a systematic list of high-confidence, maternal diagnoses around pregnancy associated
with ASD risk in two, independent cohorts, and triangulated evidence regarding genetic and non-genetic
mechanisms linkin...

## Key facts

- **NIH application ID:** 10739319
- **Project number:** 5R01MH124817-04
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** MAGDALENA JANECKA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1
- **Award type:** 5
- **Project period:** 2020-12-01 → 2023-11-02

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10739319

## Citation

> US National Institutes of Health, RePORTER application 10739319, Maternal health in pregnancy and autism risk - genetic and non-genetic mechanisms (5R01MH124817-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10739319. Licensed CC0.

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