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

Biol Psychiatry

Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China; Shandong Provincial Key Medical and Health Laboratory of Intelligent Diagnosis and Treatment for Women's Diseases, Yantai Yuhuangding Hospital, Yantai, Shandong, China; Big Data and Artificial Intelligence Laboratory, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China. Electronic address:

Published: February 2025

AI Article Synopsis

  • Abnormalities in the connectivity between brain structures and their functions have been found in patients with major depressive disorder (MDD), but the differences across brain regions and their biological mechanisms remain unclear.
  • A study involving 182 MDD patients and 157 healthy controls assessed these connectivity differences using machine learning models, showing promising results for using these patterns as diagnostic biomarkers.
  • Findings indicated increased connectivity in certain brain networks among MDD patients, linked to neurotransmitter distributions and gene expression related to neuron function and signaling, suggesting potential avenues for targeted treatments.

Article 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 = 3.233) and decreased coupling in the frontoparietal network (t = -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.

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http://dx.doi.org/10.1016/j.biopsych.2024.08.022DOI Listing

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