# Triple-network connectivity contributions to obesity in Schizophrenia

> **NIH NIH F31** · UNIVERSITY OF COLORADO DENVER · 2024 · $48,304

## Abstract

PROJECT SUMMARY
Schizophrenia (SZ), and related psychotic disorders, affects about 1% of the global population and is
associated with highly increased rates of cardiovascular disease, diabetes, and cancer compared to the
general population. Greater obesity severity and prevalence in this population are the primary contributors to
these increased risks. While antipsychotic (AP) treatment is a known contributor to weight gain, the
neurobiology underlying this and other contributing factors are largely unknown. Without an improved
understanding of the neurobiology of obesity in SZ, developing targeted treatments remains challenging.
A framework that may be useful in understanding this neurobiology is the "Triple Network Theory" of SZ, which
postulates that disruptions in three brain networks (default mode, executive control, and salience networks)
heavily contribute to SZ pathophysiology. Disruption of these networks are similarly strongly associated with
obesity severity in the general population. This proposal, therefore, aims to determine how disruptions in the
“triple network” in SZ contributes to the observed increased obesity risk.
Associations between triple-network disruptions and obesity in SZ will be assessed with functional magnetic
resonance imaging (fMRI) measurements of brain connectivity within the “triple network” in individuals with and
without SZ. Connectivity will be measured at rest and during visual food cues, both before and after consuming
a meal. Machine learning analyses will measure how AP-related weight gain correlates with disruptions in the
triple network in SZ, how obesity relates to these disruptions in individuals with and without SZ, and how other
factors (i.e., appetite-related hormones, eating behaviors, and mood ratings) may influence these relationships.
Mr. Dodd’s training plan focuses on the neurobiology of obesity and psychiatric disorders, advanced
neuroimaging analysis, and professional development (see Training Plan). He will be supported by mentors
with relevant expertise, as well as state-of-the-art resources in obesity, neuroimaging, and psychiatry research
at the University of Colorado Anschutz Medical Campus. This training will support both this proposal and his
career goal to become a neuroimaging physician-scientist investigating the neurobiology of psychiatric
conditions and their comorbidities.
The research conducted during this training has the potential for high clinical impact. Determining how the
Triple Network Theory relates to obesity in SZ, and related psychotic disorders, may lead to improved
treatment development and targeting for obesity and obesity-related comorbidities for this population.

## Key facts

- **NIH application ID:** 10994516
- **Project number:** 1F31MH137968-01
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Keith Dodd
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $48,304
- **Award type:** 1
- **Project period:** 2024-07-01 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10994516

## Citation

> US National Institutes of Health, RePORTER application 10994516, Triple-network connectivity contributions to obesity in Schizophrenia (1F31MH137968-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10994516. Licensed CC0.

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