Regional Structural-Functional Connectivity Coupling in Major Depressive Disorder Is Associated With Neurotransmitter and Genetic Profiles.

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  • Additional Information
    • Source:
      Publisher: Elsevier Country of Publication: United States NLM ID: 0213264 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2402 (Electronic) Linking ISSN: 00063223 NLM ISO Abbreviation: Biol Psychiatry Subsets: MEDLINE
    • Publication Information:
      Publication: New York, NY : Elsevier
      Original Publication: New York, Plenum Pub. Corp.
    • Subject Terms:
      Depressive Disorder, Major*/genetics ; Depressive Disorder, Major*/physiopathology ; Neurotransmitter Agents*/metabolism ; Brain*/physiopathology ; Brain*/diagnostic imaging; Humans ; Female ; Male ; Adult ; Magnetic Resonance Imaging ; Support Vector Machine ; Middle Aged ; Connectome ; Default Mode Network/physiopathology ; Default Mode Network/diagnostic imaging ; Young Adult ; Nerve Net/physiopathology ; Nerve Net/diagnostic imaging ; Case-Control Studies
    • Abstract:
      Background: Abnormalities in structural-functional connectivity (SC-FC) coupling have been identified globally in patients with major depressive disorder (MDD). However, investigations have neglected the variability and hierarchical distribution of these abnormalities across different brain regions. Furthermore, the biological mechanisms that underlie regional SC-FC coupling patterns are not well understood.
      Methods: We enrolled 182 patients with MDD and 157 healthy control participants and quantified the intergroup differences in regional SC-FC coupling. Extreme gradient boosting (XGBoost), support vector machine, and random forest models were constructed to assess the potential of SC-FC coupling as biomarkers for MDD diagnosis and symptom prediction. Then, we examined the link between changes in regional SC-FC coupling in patients with MDD, neurotransmitter distributions, and gene expression.
      Results: We observed increased regional SC-FC coupling in the default mode network (t 337  = 3.233) and decreased coupling in the frontoparietal network (t 337  = -3.471) in patients with MDD compared with healthy control participants. XGBoost (area under the receiver operating characteristic curve = 0.853), support vector machine (area under the receiver operating characteristic curve = 0.832), and random forest (p < .05) models exhibited good prediction performance. The alterations in regional SC-FC coupling in patients with MDD were correlated with the distributions of 4 neurotransmitters (p < .05) and expression maps of specific genes. These enriched genes were implicated in excitatory neurons, inhibitory neurons, cellular metabolism, synapse function, and immune signaling. These findings were replicated on 2 brain atlases.
      Conclusions: This work enhances our understanding of MDD and paves the way for the development of additional targeted therapeutic interventions.
      (Copyright © 2024 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)
    • Contributed Indexing:
      Keywords: Biological mechanisms; Default Mode Network; Frontoparietal Network; Major Depressive Disorder; Prediction; Regional
    • Accession Number:
      0 (Neurotransmitter Agents)
    • Publication Date:
      Date Created: 20240901 Date Completed: 20241226 Latest Revision: 20241226
    • Publication Date:
      20241227
    • Accession Number:
      10.1016/j.biopsych.2024.08.022
    • Accession Number:
      39218135