Intrinsic cerebral activity at resting state in adults with major depressive disorder: A meta-analysis

Numerous neuroimaging studies have been undertaken to detect cerebral intrinsic activity in major depressive disorder (MDD) with resting state fMRI (rs-fMRI). However, the inconsistent results have hindered our understanding of the exact neuropathology related to MDD. The current meta-analysis used state-of-the-art conjunction analysis techniques to systematically review and summarize all available neuroimaging studies using rsfMRI with amplitude of low frequency fluctuation (ALFF) and/or fractional ALFF (fALFF) on MDD patients and further explored the effect of antidepressants on the intrinsic activity of the brain. The anisotropic effect size version of signed differential mapping (AES-SDM) was applied to investigate changes in ALFF/fALFF in depression. We performed a subgroup analysis and group comparison on medicated and drug nave patients to detect drug effect on MDD patients and conjunction analysis to identify congruent results between the two methods. Meta-regression was used to explore the effects of demographics and clinical characteriStics. Adult MDD patients showed a robust increase in intrinsic activity in the resting state in the anterior cingulate cortex (ACC) in both ALFF (P<0.001) and fALFF (P < 0.01) studies. The subgroup analysis demonstrated that the increased activity in the ACC was prominent in medicated patients only and not seen in drug-nave MDD patients, while medication naive patients showed a specific decreased activity in the cerebellum (P<0.01). Group comparison showed that the intrinsic ACC activity is elevated in medicated MDD patients compared with drug nave MDD patients. Meta-regression analysis demonstrated that the increased ACC activation was positively correlated with illness duration (P<0.001). Our findings suggest that increased activity of the ACC is more likely to be associated with antidepressant treatment, while decreased intrinsic activity of the cerebellum might be a specific biomarker for current MDD. (C) 2017 Elsevier Inc. All rights reserved.