Search

Background: Ketamine is a highly effective antidepressant for patients with treatment-resistant major depressive disorder (MDD). Resting-state functional magnetic resonance imaging studies show disruptions of functional connectivity (FC) between limbic regions and resting-state networks (RSNs) in MDD, including the default mode network, central executive network (CEN), and salience network (SN). Here, we investigated whether serial ketamine treatments change FC between limbic structures and RSNs., Methods: Patients with MDD (n = 44) were scanned at baseline (time 1 [T1]) and 24 hours after the first (T2) and fourth (T3) infusions of ketamine. Healthy control subjects (n = 50) were scanned at baseline, with a subgroup (n = 17) being rescanned at 2 weeks. Limbic regions included the amygdala and hippocampus, and RSNs included the default mode network, CEN, and SN., Results: Ketamine increased right amygdala FC to the right CEN (p = .05), decreased amygdala FC to the left CEN (p = .005) at T2 versus T1 (p = .015), which then increased at T3 versus T2 (p = .002), and decreased left amygdala FC to the SN (p = .016). Decreased left amygdala to SN FC at T2 predicted improvements in anxiety at T3 (p = .006). Ketamine increased right hippocampus FC to the left CEN (p = .001), and this change at T2 predicted decreased anhedonia at T3 (p = .005)., Conclusions: Ketamine modulates FC between limbic regions and RSNs implicated in MDD. Increases in FC between limbic regions and the CEN suggest that ketamine may be involved in restoring top-down control of emotion processing. FC decreases between the left amygdala and SN suggest that ketamine may ameliorate MDD-related dysconnectivity in these circuits. Early FC changes between limbic regions and RSNs may be predictive of clinical improvements., (Copyright © 2020 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Subcallosal cingulate (SCC) activity is associated with treatment response in major depressive disorder (MDD). Using electroconvulsive therapy (ECT) as a treatment model in this exploratory study, we addressed whether pretreatment SCC structural connectivity with corticolimbic-striatal circuitry relates to therapeutic outcome and whether these connectivity patterns change with treatment., Methods: Diffusion magnetic resonance imaging scans were acquired in 43 patients with MDD (mean [SD] age = 41 [13] years; men/women: 18/25) before and within 1 week of completing an ECT index series and in 31 healthy control subjects scanned twice (mean [SD] age = 38 [11] years; men/women: 17/18). Probabilistic tractography from subject-specific anatomically defined SCC seed regions to the ventral striatum (VS), anterior cingulate cortex (ACC), and bilateral medial prefrontal cortex (mPFC) was used to estimate structural connectivity in the target network., Results: SCC-mPFC connectivity was lower in responders (>50% symptom improvement) than nonresponders both before (p < .014) (difference 37%-96% left and right hemispheres) and after (p = .023) (difference 100% right hemisphere) treatment. SCC-mPFC connectivity in responders was also decreased compared with control subjects both at baseline (p = .012) and after ECT (p = .006), whereas nonresponders had SCC-right mPFC connectivity similar to that of control subjects. Subjects with MDD also showed decreased SCC-ACC connectivity compared with control subjects (baseline: p < .003, after ECT: p = .001), although SCC-ACC connectivity did not distinguish responders from nonresponders. Bilateral SCC-VS connectivity decreased (11%) with ECT (p = .021) regardless of treatment response., Conclusions: While SCC-ACC connectivity may be a hallmark of MDD compared with control subjects, lower pretreatment SCC-mPFC connectivity in ECT responders (compared with nonresponders and control subjects) suggests that connectivity in this pathway may serve as a potential biomarker of therapeutic outcome and be relevant for treatment selection., (Copyright © 2020 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Current diagnostic strategy for bipolar disorders relies on symptomological classification. Yet, responses to both pharmacological and psychotherapeutic treatments vary widely, suggesting that underlying neuropathological differences are not well defined by current nosology. Classifying patients with bipolar disorder based on emotion regulation network (ERN) activation may account for some of the heterogeneity within the disorder., Methods: Euthymic participants diagnosed with bipolar I disorder (n = 86) and healthy subjects (n = 80) underwent functional magnetic resonance imaging scans while engaged in emotional reappraisal of negative stimuli. After determining average regional activations in key network regions, we applied agglomerative hierarchical clustering to identify subtypes of bipolar disorder. Next, we examined relations among neural subtypes, demographic variables, and mood symptoms., Results: Analyses revealed two primary neural subtypes of euthymic bipolar I disorder participants. The first subtype, ERN cluster 1, was characterized by increased amygdala activation and slightly increased ventrolateral prefrontal and subgenual cingulate activation, whereas ERN cluster 2 was defined by decreased amygdala activation with wider-spread prefrontal activation. Cluster 1 was associated with a higher number of hospitalizations for depression (odds ratio = 1.30, 95% confidence interval = 1.02-1.64) and later onset of manic episodes (odds ratio = 1.06, 95% confidence interval = 1.00-21.13) than cluster 2. ERN clusters of healthy subjects differed from bipolar disorder clusters and were defined by differential activation of the prefrontal cortex. ERN clusters of healthy subjects, which differed from bipolar disorder clusters, were defined by differential activation of the prefrontal cortex., Conclusions: Emotion regulation circuitry can distinguish neurobiological subtypes of bipolar disorder in the euthymic state. These subtypes, which are differentially associated with indices of illness severity and subsyndromal affective symptoms, may help to inform relapse risk and more personalized treatment approaches., (Copyright © 2020 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: Electroconvulsive therapy (ECT) is an effective treatment for severe depression and is shown to increase hippocampal volume and modulate hippocampal functional connectivity. Whether variations in hippocampal structural connectivity occur with ECT and relate to clinical response is unknown., Methods: Patients with major depression (n = 36, 20 women, age 41.49 ± 13.57 years) underwent diffusion magnetic resonance imaging at baseline and after ECT. Control subjects (n = 32, 17 women, age 39.34 ± 12.27 years) underwent scanning twice. Functionally defined seeds in the left and right anterior hippocampus and probabilistic tractography were used to extract tract volume and diffusion metrics (fractional anisotropy and axial, radial, and mean diffusivity). Statistical analyses determined effects of ECT and time-by-response group interactions (>50% change in symptoms before and after ECT defined response). Differences between baseline measures across diagnostic groups and in association with treatment outcome were also examined., Results: Significant effects of ECT (all p < .01) and time-by-response group interactions (all p < .04) were observed for axial, radial, and mean diffusivity for right, but not left, hippocampal pathways. Follow-up analyses showed that ECT-related changes occurred in responders only (all p < .01) as well as in relation to change in mood examined continuously (all p < .004). Baseline measures did not relate to symptom change or differ between patients and control subjects. All measures remained stable across time in control subjects. No significant effects were observed for fractional anisotropy and volume., Conclusions: Structural connectivity of hippocampal neural circuits changed with ECT and distinguished treatment responders. The findings suggested neurotrophic, glial, or inflammatory response mechanisms affecting axonal integrity., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)