# Maternal adversity, inflammation, and neurodevelopment: How intergenerational processes perpetuate disadvantage in a low-resource setting

> **NIH NIH R01** · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · 2021 · $52,452

## Abstract

SUMMARY OR ABSTRACT OF THE FUNDED GRANT OR PROJECT
 Over 50% of US children are exposed to at least one Adverse Childhood Experience (ACE); in Brazil —
our site for the proposed work — this rate is even higher. Children with greater ACEs are at significantly in-
creased risk for ADHD/externalizing disorders [Odds ratio (OR) 1.5-6.8], as well as substance use disorders
(OR2.3 - 7.7), risky sexual behaviors and sexually transmitted diseases (OR 1.7-8.1). Moreover, ACEs in one
generation have been shown to confer risk for psychiatric dysfunction onto the next. However, the mechanisms
underlying ACE-related intergenerational effects are unclear, significantly limiting prevention efforts.
 This project will study maternal ACEs in relation to child brain-behavior development focusing on cogni-
tive control and related neural circuits implicated in externalizing and impulsivity-related conditions. We will test
the role of maternal prenatal inflammation as a key understudied pathway for these intergenerational effects.
Infants exposed to high maternal interleukin-6 (IL-6) and C-reactive protein (CRP) show atypical connectivity
within prefrontal temporoparietal, and insular cortices related to cognitive control. Preclinical research suggests
that maternal ACEs and related inflammation confer these neurodevelopment effects by altering expression of
pro-inflammatory genes (e.g. II-6, II-1β, TNF-α).
 Our proposal is a collaborative effort based on a fruitful partnership between CUIMC/NYSPI and the
Federal University of São Paulo (UNIFESP) focused on impoverished communities highly exposed to ACEs
with elevated rates of externalizing and impulsivity-related disorders. In our recently completed pilot infant MRI
study in São Paulo (n=44; 2-4 week old infants) we found associations between maternal ACEs, increased
prenatal maternal inflammation (CRP), and diminished functional connectivity within cognitive control sub-
strates in infants. Here, we aim to build on these findings and test a mechanistic model hypothesizing that (i)
ACEs give rise to increased maternal inflammatory markers and (ii) during gestation, maternal inflammation
alters placental gene regulation and, consequently, infant brain development. To identify neurodevelopment
effects specific to prenatal inflammation, we will measure and adjust for other perinatal influences on fetal/in-
fant neurodevelopment including maternal mood, perceived stress (self-report), third trimester maternal hypo-
thalamic-pituitary-adrenal axis activity (hair cortisol levels), home environment, and offspring genetic liability
(poly-genetic risk from GWAS-ADHD, a proxy for diminished cognitive control). We will enroll 580 pregnant
women [n=290 with low ACEs (0 or 1); n=290 with high ACEs (2 or more)] and follow their offspring for 24
months. Substantiating intergenerational effects of ACEs will dramatically impact current knowledge of the eti-
ologies of impulsivity and disorders related to poor cognitive control, bro...

## Key facts

- **NIH application ID:** 10369780
- **Project number:** 3R01MH121070-02S1
- **Recipient organization:** NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC
- **Principal Investigator:** Cristiane S. Duarte
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $52,452
- **Award type:** 3
- **Project period:** 2020-03-16 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10369780

## Citation

> US National Institutes of Health, RePORTER application 10369780, Maternal adversity, inflammation, and neurodevelopment: How intergenerational processes perpetuate disadvantage in a low-resource setting (3R01MH121070-02S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10369780. Licensed CC0.

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