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Regional Structural-Functional Connectivity Coupling in Major Depressive Disorder Is Associated With Neurotransmitter
Tongpeng Chu1, Xiaopeng Si2, Haizhu Xie3
1Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China; Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, Shandong, China; State Key Laboratory of Advanced Medical Materials and Devices, Tianjin, China; Haihe Laboratory of Brain-computer Interaction and Human-machine Integration, Tianjin, China; Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin University, Tianjin, 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.
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 (t337 = 3.233) and decreased coupling in the frontoparietal network (t337 = -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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