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Brain functional connectivity patterns associated with adiposity in schizophrenia.

Keith Dodd1, Kristina T Legget2, Marc-Andre Cornier3

  • 1Department of Psychiatry, University of Colorado School of Medicine, Anschutz Medical Campus, Anschutz Health Sciences Building, 1890 N Revere Court, Aurora, CO 80045, USA; Department of Bioengineering, University of Colorado Denver, 12705 E Montview Blvd Suite 100, Aurora, CO 80045, USA.

Psychiatry Research. Neuroimaging
|June 20, 2026
PubMed
Summary
This summary is machine-generated.

Brain connectivity patterns linked to obesity in people with schizophrenia (SZ) differ between fasting and fed states, and from those without SZ. These findings may guide future obesity interventions for this population.

Keywords:
FastedFedFunctional connectivityMachine learningObesitySchizophreniafMRI

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Obesity Research

Background:

  • Individuals with schizophrenia (SZ) have higher obesity rates than the general population.
  • Biological mechanisms linking obesity and SZ are not well understood.
  • Brain functional connectivity (FC) is linked to obesity in the general population but is understudied in SZ.

Purpose of the Study:

  • To investigate the contribution of brain functional connectivity (FC) to adiposity in individuals with SZ and an obesity-matched comparison group.
  • To explore differences in FC patterns associated with adiposity in fasted and fed states between the two groups.

Main Methods:

  • Resting-state functional magnetic resonance imaging (fMRI) was used in 46 participants with SZ and 46 controls.
  • Participants completed fMRI scans in both fasted and fed states.
  • A machine learning approach identified FC patterns associated with adiposity (percent body fat).

Main Results:

  • Brain regions involved in reward and eating behaviors predicted adiposity in both groups in both states.
  • In the fasted state, SZ predictive FC involved limbic and sensorimotor networks; comparison group networks were more varied.
  • In the fed state, SZ predictive FC included visual, default mode, and executive control networks; comparison group networks involved limbic, sensorimotor, salience, and executive control networks.

Conclusions:

  • Shared and distinct FC patterns are associated with adiposity in individuals with SZ and controls.
  • Diagnosis- and state-specific FC patterns may influence obesity in SZ.
  • Findings may inform the development of targeted obesity interventions for individuals with SZ.