# ProNET: Psychosis-Risk Outcomes Network

> **NIH NIH U01** · YALE UNIVERSITY · 2022 · $15,918,096

## Abstract

PROJECT SUMMARY
It has now been two decades since the clinical high risk for psychosis (CHR) criteria were first formulated in service of
the goal of preventing psychotic disorders, one of the most urgent unmet clinical needs in behavioral health if not in all of
medicine. As with most psychiatric patients, CHR patients benefit from psychotherapies but are also often left with important
treatment needs not fully addressed. Despite the critical public health need, drug development for CHR is viewed in many
quarters as risky. The most daunting obstacle may be the heterogeneity of CHR course. In Aim 1 we will deeply pheno-
type 1040 CHR patients across the ProNET network of 26 international sites with multi-modal biomarkers that span brain
structure-function (MRI and EEG), psychopathology and cognition, genetics, body fluid analytes, natural speech/language,
and passive/ecological momentary digital phenotyping, and map these biomarkers onto a core set of clinical outcome mea-
sures and trajectories over a treatment-relevant time window at eight timepoints over 24 months. Biomarkers will be collected
at two timepoints to map brain-behavior trajectories. Healthy volunteers (N=260) will complete a baseline assessment to quan-
tify typical variation. We will also conduct exploratory studies to assess real-time behavioral data from smartphone sensors
and symptom reports from surveys; novel repetition positivity and alpha-desynchronization measures derived from standard
EEG paradigms; and pilot an evaluation of excitatory/inhibitory imbalance with MR spectroscopy for glutamate, glutamine,
and GABA at 7 Tesla. In Aim 2 we will partner with the NIMH-selected Data Processing, Analysis, and Coordinating
Center for rapid data integration and NIMH Data Archive (NDA) uploads with the proposed informatics platform. We will
implement ProNET-wide standardized and near real-time data integration with the DPACC architecture to facilitate on-site
monitoring, unification of standard operating procedures, and rapid data aggregation across ProNET for seamless DPACC to
NDA transfer. In Aim 3 we will test the hypothesis that data-driven variation assessed by multivariate neural, genetic, and
behavioral measures within the CHR syndrome predicts individualized clinical trajectories, expanding CHR stratification
for broad clinical endpoints encompassing affect, anxiety, cognition, and APS with the goal of identifying behavioral and
biomarker-driven patterns that can refine the CHR syndrome and promote personalized treatment decisions. These analy-
ses will yield expanded outcome stratification calculators for the CHR syndrome that can predict actionable mental health
trajectories in individual patients. The stratification calculators will allow future clinical trial designers to select optimal
samples for determining whether a novel compound improves the particular CHR outcome of interest and pave the way for
phase-specific and safe new interventions to benefit patients and t...

## Key facts

- **NIH application ID:** 10440486
- **Project number:** 5U01MH124639-03
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** CARRIE E BEARDEN
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $15,918,096
- **Award type:** 5
- **Project period:** 2020-09-08 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10440486

## Citation

> US National Institutes of Health, RePORTER application 10440486, ProNET: Psychosis-Risk Outcomes Network (5U01MH124639-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10440486. Licensed CC0.

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