The functional connectivity of the middle frontal cortex predicts ketamine's outcome in major depressive disorder

Fan Zhang; Chengyu Wang; Xiaofeng Lan; Weicheng Li; Ling Fu; Yanxiang Ye; Haiyan Liu; Kai Wu; Yanling Zhou; Yuping Ning

doi:10.3389/fnins.2022.956056

The functional connectivity of the middle frontal cortex predicts ketamine's outcome in major depressive disorder

Front Neurosci. 2022 Sep 15:16:956056. doi: 10.3389/fnins.2022.956056. eCollection 2022.

Authors

Fan Zhang^{1

2

3}, Chengyu Wang^{2

3}, Xiaofeng Lan^{2

3}, Weicheng Li^{1

2

3}, Ling Fu^{1

2

3}, Yanxiang Ye^{2

3}, Haiyan Liu^{2

3}, Kai Wu⁴, Yanling Zhou^{2

3}, Yuping Ning^{1

2

3}

Affiliations

¹ The First School of Clinical Medicine, Southern Medical University, Guangzhou, China.
² The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
³ Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
⁴ School of Biomedical Sciences and Engineering, South China University of Technology, Guangzho, China.

Abstract

Background: Ketamine, a robust antidepressant, has promising potential in the treatment of major depressive disorder (MDD). However, it does not work for all MDD patients, and the mechanism underlying its anti-depressive effects is unclear. Researchers have explored the mechanisms of ketamine action in MDD patients through MRI, a technique that measures brain activity intuitively. Notably, many MRI results were inconsistent because they selected different brain regions as seeds, particularly with respect to functional connectivity (FC) analysis. To eliminate the influence of prior seeds as much as possible, we used the significantly different results in degree centrality (DC) analysis as seeds to explore the FC changes in MDD patients to identify an imaging biomarker of ketamine's effect.

Methods: Forty-four MDD patients and 45 healthy controls (HCs) were included in the study. Patients, aged 18-65, received six intravenous ketamine injections over 12 days. Depressive symptoms were estimated and MRI scans were performed at baseline and the day after the sixth infusion. We estimated FC differences between responders, non-responders and HCs using the region that showed significant differences between responders and non-responders in DC analysis as the seed. The correlation between the MADRS changes and zFC values was performed, and the potential of zFC values to be a neuroimaging biomarker was explored using the receiver operating characteristic curve.

Result: Compared with non-responders, responders had significantly decreased DC values in the right middle frontal gyrus (MFG). In the analysis of FC using the region that showed significant differences in DC as a seed, there was a significant difference in the region of the right supplementary motor area (SMA) among responders, non-responders, and HCs. This region also overlapped with the bilateral median cingulate gyrus. In post hoc analysis, responders had higher FC than non-responders and HCs, and non-responders had lower FC than HCs. Importantly, the FC between the MFG and SMA (overlapping bilateral median cingulate gyrus) was correlated with the improvement of symptoms, which was estimated by the Mongomery-Asberg Depression Scale (MADRS). FC has the potential to be an imaging biomarker that can predict the ketamine effect in MDD patients according to the receiver operating characteristic curve analysis.

Conclusion: Our results revealed that FC between the SMG and SMA and mACC was highly correlated with depressive symptoms and has the potential to be a neuroimaging biomarker to predict the effect of ketamine in MDD.

Keywords: biomarker; default mode network; degree centrality (DC); functional connectivity; ketamine; major depressive disorder.