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Data driven clusters derived from resting state functional connectivity: Findings from the EMBARC study.

Cherise R Chin Fatt1, Abu Minhajuddin2, Manish K Jha1

  • 1Center for Depression Research and Clinical Care, Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA; Peter O'Donnell Jr. Brain Institute, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Journal of Psychiatric Research
|December 31, 2022
PubMed
Summary
This summary is machine-generated.

Resting-state fMRI identified three distinct subgroups of Major Depressive Disorder (MDD) patients. One subgroup showed higher remission rates with sertraline, suggesting brain connectivity patterns can predict treatment outcomes.

Keywords:
CLICKData drivenEMBARCFunctional connectivityMajor depressive disorderRemission

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Area of Science:

  • Neuroscience
  • Psychiatry
  • Medical Imaging

Background:

  • Major Depressive Disorder (MDD) exhibits significant clinical heterogeneity.
  • Identifying homogeneous subgroups within MDD is crucial for personalized treatment approaches.

Purpose of the Study:

  • To determine if resting-state functional magnetic resonance imaging (fMRI) can identify circuit-based homogeneous subgroups in MDD.
  • To investigate if these identified subgroups exhibit differential treatment outcomes.

Main Methods:

  • Resting-state fMRIs from 278 MDD outpatients were analyzed using CLICK clustering to identify data-driven subgroups.
  • Subgroups were compared based on baseline clinical data and changes in depression severity (HAMD17) after 8 weeks of treatment.

Main Results:

  • Three distinct subgroups were identified based on brain connectivity patterns.
  • Cluster-3, characterized by specific hypoconnectivity, demonstrated a significantly higher remission rate (51.6%) with sertraline compared to Cluster-1 (32.7%) and Cluster-2 (31.9%).
  • Baseline clinical measures did not differentiate these subgroups.

Conclusions:

  • Baseline functional connectivity patterns can effectively subgroup patients with MDD.
  • These subgroups show differential acute-phase treatment outcomes, indicating potential for personalized treatment strategies.
  • Brain connectivity measures may help address the clinical heterogeneity of MDD.