# Dimensional outcomes and neural circuitry associated with psychosis risk

> **NIH NIH R01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $522,327

## Abstract

Abstract: Prediction of risk for mental disorders is the cornerstone of “preventive psychiatry”. Emerging data
report that up to 45% of subjects at familial high risk for schizophrenia (FHR) develop broad psychosis spectrum
psychopathology and cognitive impairments although conversion to psychosis is less than 15%. Long term
prospective examination of FHR adolescents/young adults to characterize early predictors of risk for psychosis,
broad psychosis spectrum psychopathology and cognitive impairments is critical for prevention and early
intervention. Our well characterized unique cohort of FHR adolescents/young adults that were extensively
phenotyped between 2003 and 2008 is uniquely suited to address these goals. We published one predictive
model each for the emergence of psychopathology with 80% accuracy (sensitivity 0.5, specificity 0.92, positive
likelihood ratio 6.25, negative likelihood ratio 0.54), and for psychosis with 88% accuracy (sensitivity 0.17,
specificity 0.99, positive and negative likelihood ratios 17 and 0.83, respectively). Our goal is to call back 75 FHR
subjects from this cohort (≈75%) and examine the validity of these predictions with real-world outcomes of
psychosis, broad psychosis spectrum psychopathology and cognitive impairments by including more refined
baseline variables and genetic vulnerability using genomewide polygenic risk score and variants of complement
gene C4. Independent lines of evidence recently showed association of C4 variants with schizophrenia risk at
genomewide significance and increased synaptic pruning. The broad range of outcomes are examined within
the Research Domain Criteria (RDoC) framework using dimensional changes in working memory and executive
function constructs. We will also build a predictive model and a long range multimodal risk calculator for outcome
incorporating the real world outcomes to improve sensitivity and positive likelihood ratio while preserving higher
specificity and prediction accuracy, elucidate dimensional changes in working memory and executive function,
and test these predictions in a replicate sample of FHR from the Edinburgh High Risk Study, which is the largest
in the world (aim 1). Using a “top-down” approach, we will examine how the psychopathological outcomes and
dimensional changes in working memory and executive function map on to neural circuitry with hippocampus as
a hub. Ultra-high field (7 Tesla) structural MRI, diffusion tensor imaging (DTI) and blood oxygenation level
dependent (BOLD) fMRI will examine hippocampal subfields and subdivisions, anatomical circuitry, and
functional changes to the working memory and executive function tasks (aim 2). We will also derive preliminary
outcome biotypes that may be biologically more meaningful for future validation. On successful completion of
the project, our data is likely to provide useful leads to long-term biologically-based dimensional phenotypic
outcomes of FHR subjects as well as for broad psychosis spectr...

## Key facts

- **NIH application ID:** 9832202
- **Project number:** 5R01MH112584-03
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Konasale M Prasad
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $522,327
- **Award type:** 5
- **Project period:** 2017-11-22 → 2021-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9832202

## Citation

> US National Institutes of Health, RePORTER application 9832202, Dimensional outcomes and neural circuitry associated with psychosis risk (5R01MH112584-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9832202. Licensed CC0.

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