Prediction of electroconvulsive therapy response and remission in major depression: Meta-analysis

Electroconvulsive therapy (ECT) is considered to be the most effective treatment in severe major depression. The identification of reliable predictors of ECT response could contribute to a more targeted patient selection and consequently increased ECT response rates. Aims To investigate the predictive value of age, depression severity, psychotic and melancholic features for ECT response and remission in major depression. Method A meta-analysis was conducted according to the PRISMA statement. A literature search identified recent studies that reported on at least one of the potential predictors. Results Of the 2193 articles screened, 34 have been included for metaanalysis. Presence of psychotic features is a predictor of ECT remission (odds ratio (OR) = 1.47, P = 0.001) and response (OR = 1.69, P < 0.001), as is older age (standardised mean difference (SMD) = 0.26 for remission and 0.35 for response (P < 0.001)). The severity of depression predicts response (SMD = 0.19, P = 0.001), but not remission. Data on melancholic symptoms were inconclusive. Conclusions ECT is particularly effective in patients with depression with psychotic features and in elderly people with depression. More research on both biological and clinical predictors is needed to further evaluate the position of ECT in treatment protocols for major depression

Interrogating Associations Between Polygenic Liabilities and Electroconvulsive Therapy Effectiveness

Background: Electroconvulsive therapy (ECT) is the most effective treatment for severe major depressive episodes (MDEs). Nonetheless, firmly established associations between ECT outcomes and biological variables are currently lacking. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response in psychiatry are seldom reported. Here, we examined whether PRSs for major depressive disorder, schizophrenia (SCZ), cross-disorder, and pharmacological antidepressant response are associated with ECT effectiveness. Methods: A total of 288 patients with MDE from 3 countries were included. The main outcome was a change in the 17-item Hamilton Depression Rating Scale scores from before to after ECT treatment. Secondary outcomes were response and remission. Regression analyses with PRSs as independent variables and several covariates were performed. Explained variance (R 2) at the optimal p-value threshold is reported. Results: In the 266 subjects passing quality control, the PRS-SCZ was positively associated with a larger Hamilton Depression Rating Scale decrease in linear regression (optimal p-value threshold = .05, R 2 = 6.94%, p < .0001), which was consistent across countries: Ireland (R 2 = 8.18%, p = .0013), Belgium (R 2 = 6.83%, p = .016), and the Netherlands (R 2 = 7.92%, p = .0077). The PRS-SCZ was also positively associated with remission (R 2 = 4.63%, p = .0018). Sensitivity and subgroup analyses, including in MDE without psychotic features (R 2 = 4.42%, p = .0024) and unipolar MDE only (R 2 = 9.08%, p < .0001), confirmed the results. The other PRSs were not associated with a change in the Hamilton Depression Rating Scale score at the predefined Bonferroni-corrected significance threshold. Conclusions: A linear association between PRS-SCZ and ECT outcome was uncovered. Although it is too early to adopt PRSs in ECT clinical decision making, these findings strengthen the positioning of PRS-SCZ as relevant to treatment response in psychiatry

White matter changes following electroconvulsive therapy for depression: a multicenter ComBat harmonization approach

ECT is proposed to exert a therapeutic effect on WM microstructure, but the limited power of previous studies made it difficult to highlight consistent patterns of change in diffusion metrics. We initiated a multicenter analysis and sought to address whether changes in WM microstructure occur following ECT. Diffusion tensor imaging (DTI) data (n = 58) from 4 different sites were harmonized before pooling them by using ComBat, a batch-effect correction tool that removes inter-site technical variability, preserves inter-site biological variability, and maximizes statistical power. Downstream statistical analyses aimed to quantify changes in Fractional Anisotropy (FA), Mean Diffusivity (MD), Radial Diffusivity (RD) and Axial Diffusivity (AD), by employing whole-brain, tract-based spatial statistics (TBSS). ECT increased FA in the right splenium of the corpus callosum and the left cortico-spinal tract. AD in the left superior longitudinal fasciculus and the right inferior fronto-occipital fasciculus was raised. Increases in MD and RD could be observed in overlapping white matter structures of both hemispheres. At baseline, responders showed significantly smaller FA values in the left forceps major and smaller AD values in the right uncinate fasciculus compared with non-responders. By harmonizing multicenter data, we demonstrate that ECT modulates altered WM microstructure in important brain circuits that are implicated in the pathophysiology of depression. Furthermore, responders appear to present a more decreased WM integrity at baseline which could point toward a specific subtype of patients, characterized by a more altered neuroplasticity, who are especially sensitive to the potent neuroplastic effects of ECT

A mood state-specific interaction between kynurenine metabolism and inflammation is present in bipolar disorder

Objectives: Cytokines are thought to contribute to the pathogenesis of psychiatric symptoms by kynurenine pathway activation. Kynurenine metabolites affect neurotransmission and can cause neurotoxicity. We measured inflammatory markers in patients with bipolar disorder (BD) and studied their relation to kynurenine metabolites and mood. Methods: Patients with BD suffering from an acute mood episode were assigned to the depressive (n = 35) or (hypo)manic (n = 32) subgroup. Plasma levels of inflammatory markers [cytokines, C-reactive protein] and kynurenine metabolites [tryptophan (TRP), kynurenine (KYN), 3-hydroxykynurenine (3-HK), quinolinic acid (QA), kynurenic acid (KYNA)] were measured on 6 time points during 8 months follow-up. Biological marker levels in patients were compared to controls (n = 35) and correlated to scores on mood scales. Spearman correlations and linear mixed models were used for statistical analysis. Results: Twenty patients of the manic subgroup, 29 of the depressive subgroup, and 30 controls completed the study. The manic subgroup had a rapid remission of mood symptoms, but in the depressive subgroup subsyndromal symptoms persisted. No differences in inflammation were found between groups. A strong correlation between tumor necrosis factor-α and KYN, KYN/TRP, 3-HK and QA (ρ > 0.60) was specific for the manic group, but only at baseline (during mania). The depressive subgroup had a lower neuroprotective ratio (KYNA/3-HK, P =.0004) and a strong association between interferon-y and kynurenine pathway activation (P <.0001). KYNA was low in both patient groups versus controls throughout the whole follow-up (P =.0008). Conclusions: Mania and chronic depressive symptoms in BD are accompanied by a strong interaction between inflammation and a potentially neurotoxic kynurenine metabolism

Electroconvulsive therapy-induced volumetric brain changes converge on a common causal circuit in depression

Abstract: Neurostimulation is a mainstream treatment option for major depression. Neuromodulation techniques apply repetitive magnetic or electrical stimulation to some neural target but significantly differ in their invasiveness, spatial selectivity, mechanism of action, and efficacy. Despite these differences, recent analyses of transcranial magnetic stimulation (TMS) and deep brain stimulation (DBS)-treated individuals converged on a common neural network that might have a causal role in treatment response. We set out to investigate if the neuronal underpinnings of electroconvulsive therapy (ECT) are similarly associated with this causal depression network (CDN). Our aim here is to provide a comprehensive analysis in three cohorts of patients segregated by electrode placement (N = 246 with right unilateral, 79 with bitemporal, and 61 with mixed) who underwent ECT. We conducted a data-driven, unsupervised multivariate neuroimaging analysis Principal Component Analysis (PCA) of the cortical and subcortical volume changes and electric field (EF) distribution to explore changes within the CDN associated with antidepressant outcomes. Despite the different treatment modalities (ECT vs TMS and DBS) and methodological approaches (structural vs functional networks), we found a highly similar pattern of change within the CDN in the three cohorts of patients (spatial similarity across 85 regions: r = 0.65, 0.58, 0.40, df = 83). Most importantly, the expression of this pattern correlated with clinical outcomes (t = -2.35, p = 0.019). This evidence further supports that treatment interventions converge on a CDN in depression. Optimizing modulation of this network could serve to improve the outcome of neurostimulation in depression