Amygdala connectivity predicts response to ketamine treatment among anxious-depressed patients

A brain region known as the amygdala can play a key role in predicting symptom improvement after ketamine treatment in patients with treatment-resistant anxiety depression, according to new research published in the journal Journal of Affective Disorders.

Study author Bin Zhang from the Affiliated Brain Hospital of Guangzhou Medical University said: “Since the antidepressant effects of ketamine in patients with anxious depression are still unclear, it is necessary to investigate potential biomarkers that predict the antidepressant efficacy of ketamine in patients with anxiety.” anxiety depression.” .

Previous studies indicated that functional connectivity differences in the amygdala are associated with an improvement in depression after ketamine treatment in depressed patients, but their role in anxious depressed patients is uncertain. Therefore, we examined the relationship between the improvement of depression after ketamine treatment and the functional connectivity of the amygdala in anxious depressed patients.”

For their study, the researchers examined neuroimaging data from 31 patients with anxious depression and 18 patients with non-anxiety depression.

The researchers only included participants who were diagnosed with major depression without comorbid comorbid psychotic symptoms, had a score greater than 17 on the Hamilton Rating Scale for Depression, had previously failed to improve after at least two antidepressant treatments, completed fMRI brain scans, and underwent magnetic resonance imaging (MRI) brain scans. Functional magnetic. He underwent six infusions of ketamine.

Among patients with anxious depression, approximately 60% (20 patients) showed a clinically significant reduction in depressive symptoms after a sixth infusion of ketamine. The remaining 11 patients with anxious depression were classified as non-responders.

The researchers found that before the ketamine injection, those who responded to treatment tended to have greater functional connectivity between the left lateral amygdala and the left parietal amygdala than non-responders. In addition, connectivity between the two brain regions was significantly reduced after treatment among the responders.

Patients with anxious depression also tended to have lower connectivity between the right medial amgydala and the right middle temporal gyrus than patients with non-anxiety depression, which predicted treatment response.

“Consistent with the critical role the amygdala plays in regulating emotions, particularly in negative emotions, our study showed that functional amygdala was associated with depression improvement of ketamine injections in patients with anxious depression,” Zhang told PsyPost.

“The most surprising finding in the current study is that baseline hyperconnectivity of the primary amygdala found in responders relative to non-responders was significantly reduced at day 13 compared to baseline after six infusions of ketamine. It may indicate a possible neuronal underpinning through which ketamine exerts its effect.” Antidepressant in patients with anxiety depression.

The findings provide new insights into the mechanisms underlying ketamine’s antidepressant effects. But as with any study, the new research has limitations. The researchers note that their sample size was relatively small. Future research should be conducted with larger samples to validate the results.

“Although the findings from our study may indicate that functional connectivity of the amygdala is an important predictor of treatment response to ketamine injections in patients with anxious depression, further validation is required,” Zhang said. Moreover, additional studies exploring the potential antidepressant mechanisms of ketamine may help treat anxious depressed patients.

The study, “Functional connectivity differences in the amygdala are associated with the antidepressant efficacy of ketamine in patients with anxious depression,” authored by Shiqi Yuan, Shen Lu, Xiaoyu Chen, Mingqia Wang, Yirou Hu, Yanling Zhou, Yuping Ning, and Ben Zhang.

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