# Predicting psychosis risk in youth using a novel structural neuroimaging score that measures deviation from normative development. Can we bring it to communities using portable, low-field MRI?

> **NIH NIH R01** · BOSTON CHILDREN'S HOSPITAL · 2024 · $773,425

## Abstract

Project Summary/Abstract
Converging lines of evidence support the hypothesis that deviations from typical brain structure development
take place prior to psychosis onset, while ‘big data’ neuroimaging studies of adults with psychosis find subtle,
widespread gray matter disruptions in the brain. In this proposal, we will synergize knowledge about normative
structural neurodevelopment and findings of structural brain aberrations in adults with psychosis to develop
cost-effective brain-based markers of psychosis risk in youth. To improve identification of those at greatest risk,
we leverage results from large-scale structural neuroimaging studies of psychosis to create a ‘Psychosis
Neuroimaging Score’, a cumulative summary score that reflects one’s psychosis liability. We first aim to
transport the Psychosis Neuroimaging Score to youth by incorporating crucial aspects of structural brain
development. In Aim 1, we will characterize the normative developmental trajectory of the Psychosis
Neuroimaging Score by harmonizing many archival datasets of normative development (N>5,000, 2-30 years
old). We will then evaluate how greater age-associated deviation from the aggregate Psychosis Neuroimaging
Score differentiates youth with psychosis spectrum symptoms from typically developing youth in the
Philadelphia Neurodevelopmental Cohort (N=1209, 10-22 years old). In Aim 2, we plan to examine how
greater age-associated deviation from the aggregate Psychosis Neuroimaging Score predicts distinct
developmental trajectories associated with psychotic-like experiences in youth from the Adolescent Brain and
Cognitive Development Study (N=11,875). We will also assess the extent to which known psychosis risk
factors (e.g., family history of psychosis, obstetric complications, trauma) contribute to characterization of these
trajectories. Finally, in Aim 3, we propose to use measurement-in-error modeling to establish a functional
relationship between Psychosis Neuroimaging scores generated from 3T MRI scans and those generated
using low-field MRI scans in a community sample of youth. Results from this study will allow us to create more
affordable, clinically accessible biological indicators of severe psychopathology, ultimately improving
identification of young people at greatest risk and allowing earlier, more effective interventions.

## Key facts

- **NIH application ID:** 10802330
- **Project number:** 5R01MH129636-03
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** MARIA JALBRZIKOWSKI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $773,425
- **Award type:** 5
- **Project period:** 2022-05-01 → 2027-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10802330

## Citation

> US National Institutes of Health, RePORTER application 10802330, Predicting psychosis risk in youth using a novel structural neuroimaging score that measures deviation from normative development. Can we bring it to communities using portable, low-field MRI? (5R01MH129636-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10802330. Licensed CC0.

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