# Longitudinal neuroimaging and neurocognitive assessment of risk and protective factors across the schizophrenia spectrum

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2022 · $998,852

## Abstract

PROJECT SUMMARY
Schizotypal personality disorder (SPD) is similar to schizophrenia (SZ), but with fewer and attenuated
abnormalities, thus representing an important yet understudied intermediate SZ-spectrum phenotype.
Examination of abnormalities in SPD will provide information regarding etiology, genetics, treatment and risk
factors associated with psychosis. Although individuals with SPD demonstrate marked temporal lobe
abnormalities that resemble SZ, we hypothesize that relative “sparing” or “functional enhancement” in the
frontal lobes (e.g., dorsolateral prefrontal cortex), may protect these individuals from frank psychosis and the
severe social and cognitive deficits typically observed in SZ. Studying SPD is powerful as antipsychotic
medication and hospitalization confounds observed in SZ are not present. Moreover, there is no study
examining neurobiological changes in the SZ-spectrum that incorporates individuals with SPD using a
longitudinal design as proposed here. This novel approach will help disentangle potential risk and protective
factors for psychosis in the SZ spectrum. This is the first longitudinal study to utilize multimodal MR imaging
and Research Domain Criteria (RDoC) approaches in SZ-spectrum disorders to identify aberrant neural
circuitry along a continuum from healthy controls (HCs) to SPD to SZ and examine changes in these measures
in relationship to impairments in symptom severity, neurocognition and functional outcome. We propose
studying three groups (80 in each) of demographically matched and rigorously diagnosed individuals (age 18-
40): HCs (no Axis I or personality disorder), unmedicated individuals with SPD (and no Axis I disorder), and
early-onset (first 2 years of illness) SZ patients at baseline, 9-, and 18-month follow-up. Measures assessing
frontal and temporal lobe integrity include multimodal MR imaging (structural MRI, DTI, resting-state fMRI, and
task-based fMRI with a nonverbal event related working-memory task; baseline and 18-months) and
neuropsychological assessment (all three timepoints). We will utilize dynamic causal modeling to test
competing neurobiological models involving abnormal frontotemporal connectivity in the SZ-spectrum and
machine learning approaches to integrate multimodal neuroimaging, neurocognitive, and clinical assessment
data. We focus on three specific aims: (1) Investigate the longitudinal course of frontal-temporal lobe/circuitry
abnormalities in the SZ-spectrum using multimodal MR imaging; (2) Investigate the longitudinal course of
neurocognition, clinical, and functional outcome in the SZ spectrum; (3) Determine which factor or combination
of factors differentiate groups in the SZ-spectrum to identify those that are associated with risk for and
protection from SZ using machine learning.

## Key facts

- **NIH application ID:** 10319171
- **Project number:** 5R01MH121411-03
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** ERIN A. HAZLETT
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $998,852
- **Award type:** 5
- **Project period:** 2020-03-06 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10319171

## Citation

> US National Institutes of Health, RePORTER application 10319171, Longitudinal neuroimaging and neurocognitive assessment of risk and protective factors across the schizophrenia spectrum (5R01MH121411-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10319171. Licensed CC0.

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