The integrated understanding of structural and functional connectomes in depression: A multimodal meta-analysis of
Shu-Xian Xu1, Wen-Feng Deng2, Ying-Ying Qu3
1Brain Function and Psychosomatic Medicine Institute, Second People's Hospital of Huizhou, Huizhou, Guangdong, China; Department of Psychiatry, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, Guangdong, China; Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, China.
Background:
From the perspective of information processing, an integrated understanding of the structural and functional connectomes in depression patients is important, a multimodal meta-analysis is required to detect the robust alterations in graph metrics across studies.
Methods:
Following a systematic search, 952 depression patients and 1447 controls in nine diffusion magnetic resonance imaging (dMRI) and twelve rest state functional MRI (rs-fMRI) studies with high methodological quality met the inclusion criteria and were included in the meta-analysis.
Results:
Regarding the dMRI results, no significant differences of meta-analytic metrics were found; regarding the rs-fMRI results, the modularity and local efficiency were found to be significantly lower in the depression group than in the controls (Hedge's g = -0.330 and -0.349, respectively).
Conclusion:
Our findings suggested a lower modularity and network efficiency in the rs-fMRI network in depression patients, indicating that the pathological imbalances in brain connectomes needs further exploration.
Limitations:
Included number of trials was low and heterogeneity should be noted.
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