Zhiliang Long1, Lian Du2, Jia Zhao3, Shiyang Wu3, Qiaoqiao Zheng4, Xu Lei4. 1. Sleep and NeuroImaging Center, Faculty of psychology, Southwest University, Chongqing, PR China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, PR China. Electronic address: longzhiliang1987@gmail.com. 2. Department of Psychiatry, the First Affiliated Hospital of Chongqing Medical University, Chongqing, PR China. 3. Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, PR China. 4. Sleep and NeuroImaging Center, Faculty of psychology, Southwest University, Chongqing, PR China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing, PR China.
Abstract
BACKGROUND: Previous neuroimaging studies revealed abnormal resting-state functional connectivity between distributed brain areas in patients with major depressive disorder. Those abnormalities were normalized after treatment. Moreover, the functional connectivity could predict clinical response to those treatments. However, there has currently been no meta-analysis to verify these findings. METHODS: The current study aimed to investigate how the resting-state connectivity patterns predict antidepressant response to various treatments across depressive studies by using coordinate-based meta-analysis named activation likelihood estimation. The relevant articles were obtained by searching on PubMed and Web of Science. RESULTS: Following exclusion criteria of inappropriate studies, seventeen papers with 392 individual depressive patients were included. Those articles contained repetitive transcranial magnetic stimulation (rTMS) treatment, pharmacotherapy, cognitive behavioral therapy (CBT), electroconvulsive therapy (ECT) and transcutaneous vagus nerve stimulation in patients with depression. Meta-analysis revealed that clinical response to all treatments could be predicted by baseline default mode network connectivity in patients with depression. The rTMS treatment had larger effect size compared to other treatment strategies. Furthermore, subgroup meta-analysis showed that the baseline connectivity of perigenual anterior cingulate cortex (pgACC) and ventral medial prefrontal cortex could predict symptoms improvement of rTMS treatment. LIMITATIONS: More resting-state connectivity studies of CBT and ECT treatment are needed. CONCLUSIONS: This study highlighted crucial role of DMN, especially the pgACC, in understanding the underlying treatment mechanism of depression.
BACKGROUND: Previous neuroimaging studies revealed abnormal resting-state functional connectivity between distributed brain areas in patients with major depressive disorder. Those abnormalities were normalized after treatment. Moreover, the functional connectivity could predict clinical response to those treatments. However, there has currently been no meta-analysis to verify these findings. METHODS: The current study aimed to investigate how the resting-state connectivity patterns predict antidepressant response to various treatments across depressive studies by using coordinate-based meta-analysis named activation likelihood estimation. The relevant articles were obtained by searching on PubMed and Web of Science. RESULTS: Following exclusion criteria of inappropriate studies, seventeen papers with 392 individual depressivepatients were included. Those articles contained repetitive transcranial magnetic stimulation (rTMS) treatment, pharmacotherapy, cognitive behavioral therapy (CBT), electroconvulsive therapy (ECT) and transcutaneous vagus nerve stimulation in patients with depression. Meta-analysis revealed that clinical response to all treatments could be predicted by baseline default mode network connectivity in patients with depression. The rTMS treatment had larger effect size compared to other treatment strategies. Furthermore, subgroup meta-analysis showed that the baseline connectivity of perigenual anterior cingulate cortex (pgACC) and ventral medial prefrontal cortex could predict symptoms improvement of rTMS treatment. LIMITATIONS: More resting-state connectivity studies of CBT and ECT treatment are needed. CONCLUSIONS: This study highlighted crucial role of DMN, especially the pgACC, in understanding the underlying treatment mechanism of depression.
Authors: Gwen van der Wijk; Jacqueline K Harris; Stefanie Hassel; Andrew D Davis; Mojdeh Zamyadi; Stephen R Arnott; Roumen Milev; Raymond W Lam; Benicio N Frey; Geoffrey B Hall; Daniel J Müller; Susan Rotzinger; Sidney H Kennedy; Stephen C Strother; Glenda M MacQueen; Andrea B Protzner Journal: Cereb Cortex Date: 2022-03-04 Impact factor: 4.861