Persistence of amygdala hyperactivity to subliminal negative emotion processing in the long-term course of depression.

Biased emotion processing has been suggested to underlie the etiology and maintenance of depression. Neuroimaging studies have shown mood-congruent alterations in amygdala activity in patients with acute depression, even during early, automatic stages of emotion processing. However, due to a lack of prospective studies over periods longer than 8 weeks, it is unclear whether these neurofunctional abnormalities represent a persistent correlate of depression even in remission. In this prospective case-control study, we aimed to examine brain functional correlates of automatic emotion processing in the long-term course of depression. In a naturalistic design, n = 57 patients with acute major depressive disorder (MDD) and n = 37 healthy controls (HC) were assessed with functional magnetic resonance imaging (fMRI) at baseline and after 2 years. Patients were divided into two subgroups according to their course of illness during the study period (n = 37 relapse, n = 20 no-relapse). During fMRI, participants underwent an affective priming task that assessed emotion processing of subliminally presented sad and happy compared to neutral face stimuli. A group × time × condition (3 × 2 × 2) ANOVA was performed for the amygdala as region-of-interest (ROI). At baseline, there was a significant group × condition interaction, resulting from amygdala hyperactivity to sad primes in patients with MDD compared to HC, whereas no difference between groups emerged for happy primes. In both patient subgroups, amygdala hyperactivity to sad primes persisted after 2 years, regardless of relapse or remission at follow-up. The results suggest that amygdala hyperactivity during automatic processing of negative stimuli persists during remission and represents a trait rather than a state marker of depression. Enduring neurofunctional abnormalities may reflect a consequence of or a vulnerability to depression.

Long-term effects of electroconvulsive therapy on brain structure in major depression.

BACKGROUND: Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome. METHODS: In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t0), after ECT (t1) and 2 years later (t2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed. RESULTS: Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t0 to t1 and decreases from t1 to t2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t0 to t1 correlate with immediate and delayed symptom increase, while volume decreases from t1 to t2 correlate with long-term depressive outcome (all p ⩽ 0.049). CONCLUSIONS: Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes.

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

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.

Cognitive performance and brain structural connectome alterations in major depressive disorder.

BACKGROUND: Cognitive dysfunction and brain structural connectivity alterations have been observed in major depressive disorder (MDD). However, little is known about their interrelation. The present study follows a network approach to evaluate alterations in cognition-related brain structural networks. METHODS: Cognitive performance of n = 805 healthy and n = 679 acutely depressed or remitted individuals was assessed using 14 cognitive tests aggregated into cognitive factors. The structural connectome was reconstructed from structural and diffusion-weighted magnetic resonance imaging. Associations between global connectivity strength and cognitive factors were established using linear regressions. Network-based statistics were applied to identify subnetworks of connections underlying these global-level associations. In exploratory analyses, effects of depression were assessed by evaluating remission status-related group differences in subnetwork-specific connectivity. Partial correlations were employed to directly test the complete triad of cognitive factors, depressive symptom severity, and subnetwork-specific connectivity strength. RESULTS: All cognitive factors were associated with global connectivity strength. For each cognitive factor, network-based statistics identified a subnetwork of connections, revealing, for example, a subnetwork positively associated with processing speed. Within that subnetwork, acutely depressed patients showed significantly reduced connectivity strength compared to healthy controls. Moreover, connectivity strength in that subnetwork was associated to current depressive symptom severity independent of the previous disease course. CONCLUSIONS: Our study is the first to identify cognition-related structural brain networks in MDD patients, thereby revealing associations between cognitive deficits, depressive symptoms, and reduced structural connectivity. This supports the hypothesis that structural connectome alterations may mediate the association of cognitive deficits and depression severity.

Subcortical shape alterations in major depressive disorder: Findings from the ENIGMA major depressive disorder working group.

Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD-related differences in subcortical regions using shape analysis. In this meta-analysis of subcortical shape from the ENIGMA-MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta-analysis. Relative to CTL, patients with adolescent-onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = -0.164 to -0.180). Relative to first-episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = -0.173 to -0.184). Our results suggest that previously reported MDD-associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.

Changes in brain function during negative emotion processing in the long-term course of depression.

BACKGROUND: Relapses in major depression are frequent and are associated with a high burden of disease. Although short-term studies suggest a normalisation of depression-associated brain functional alterations directly after treatment, long-term investigations are sparse. AIMS: To examine brain function during negative emotion processing in association with course of illness over a 2-year span. METHOD: In this prospective case-control study, 72 in-patients with current depression and 42 healthy controls were investigated during a negative emotional face processing paradigm, at baseline and after 2 years. According to their course of illness during the study interval, patients were divided into subgroups (n = 25 no-relapse, n = 47 relapse). The differential changes in brain activity were investigated by a group × time analysis of covariance for the amygdala, hippocampus, insula and at whole-brain level. RESULTS: A significant relapse × time interaction emerged within the amygdala (PTFCE-FWE = 0.011), insula (PTFCE-FWE = 0.001) and at the whole-brain level mainly in the temporal and prefrontal cortex (PTFCE-FWE = 0.027), resulting from activity increases within the no-relapse group, whereas in the relapse group, activity decreased during the study interval. At baseline, the no-relapse group showed amygdala, hippocampus and insula hypoactivity compared with healthy controls and the relapse group. CONCLUSIONS: This study reveals course of illness-associated activity changes in emotion processing areas. Patients in full remission show a normalisation of their baseline hypo-responsiveness to the activation level of healthy controls after 2 years. Brain function during emotion processing could further serve as a potential predictive marker for future relapse.

White matter fiber microstructure is associated with prior hospitalizations rather than acute symptomatology in major depressive disorder.

BACKGROUND: Eighty percent of all patients suffering from major depressive disorder (MDD) relapse at least once in their lifetime. Thus, understanding the neurobiological underpinnings of the course of MDD is of utmost importance. A detrimental course of illness in MDD was most consistently associated with superior longitudinal fasciculus (SLF) fiber integrity. As similar associations were, however, found between SLF fiber integrity and acute symptomatology, this study attempts to disentangle associations attributed to current depression from long-term course of illness. METHODS: A total of 531 patients suffering from acute (N = 250) or remitted (N = 281) MDD from the FOR2107-cohort were analyzed in this cross-sectional study using tract-based spatial statistics for diffusion tensor imaging. First, the effects of disease state (acute v. remitted), current symptom severity (BDI-score) and course of illness (number of hospitalizations) on fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity were analyzed separately. Second, disease state and BDI-scores were analyzed in conjunction with the number of hospitalizations to disentangle their effects. RESULTS: Disease state (pFWE < 0.042) and number of hospitalizations (pFWE< 0.032) were associated with decreased FA and increased MD and RD in the bilateral SLF. A trend was found for the BDI-score (pFWE > 0.067). When analyzed simultaneously only the effect of course of illness remained significant (pFWE < 0.040) mapping to the right SLF. CONCLUSIONS: Decreased FA and increased MD and RD values in the SLF are associated with more hospitalizations when controlling for current psychopathology. SLF fiber integrity could reflect cumulative illness burden at a neurobiological level and should be targeted in future longitudinal analyses.

Variation of HbA1c affects cognition and white matter microstructure in healthy, young adults.

The metabolic serum marker HbA1c has been associated with both impaired cognitive performance and altered white matter integrity in patients suffering from diabetes mellitus. However, it remains unclear if higher levels of HbA1c might also affect brain structure and function in healthy subjects. With the present study we therefore aimed to investigate the relationship between HbA1c levels and cognitive performance as well as white matter microstructure in healthy, young adults. To address this question, associations between HbA1c and cognitive measures (NIH Cognition Toolbox) as well as DTI-derived imaging measures of white matter microstructure were investigated in a publicly available sample of healthy, young adults as part of the Humane Connectome Project (n = 1206, mean age = 28.8 years, 45.5% male). We found that HbA1c levels (range 4.1-6.3%) were significantly inversely correlated with measures of cognitive performance. Higher HbA1c levels were associated with significant and widespread reductions in fractional anisotropy (FA) controlling for age, sex, body mass index, ethnicity, and education. FA reductions were furthermore found to covary with measures of cognitive performance. The same pattern of results could be observed in analyses restricted to participants with HBA1c levels below 5.7%. The present study demonstrates that low-grade HbA1c variation below diagnostic threshold for diabetes is related to both cognitive performance and white matter integrity in healthy, young adults. These findings highlight the detrimental impact of metabolic risk factors on brain physiology and underscore the importance of intensified preventive measures independent of the currently applied diagnostic HbA1c cutoff scores.

Association of disease course and brain structural alterations in major depressive disorder.

INTRODUCTION: The investigation of disease course-associated brain structural alterations in Major Depressive Disorder (MDD) have resulted in heterogeneous findings, possibly due to low reliability of single clinical variables used for defining disease course. The present study employed a principal component analysis (PCA) on multiple clinical variables to investigate effects of cumulative lifetime illness burden on brain structure in a large and heterogeneous sample of MDD patients. METHODS: Gray matter volumes (GMV) was estimated in n = 681 MDD patients (mean age: 35.87 years; SD = 12.89; 66.6% female) using voxel-based-morphometry. Five clinical variables were included in a PCA to obtain components reflecting disease course to associate resulting components with GMVs. RESULTS: The PCA yielded two main components: Hospitalization reflected by patients' frequency and duration of inpatient treatment and Duration of Illness reflected by the frequency and duration of depressive episodes. Hospitalization revealed negative associations with bilateral dorsolateral prefrontal cortex (DLPFC) and left insula volumes. Duration of Illness showed significant negative associations with left hippocampus and right DLPFC volumes. Results in the DLPFC and hippocampus remained significant after additional control for depressive symptom severity, psychopharmacotherapy, psychiatric comorbidities, and remission status. CONCLUSION: This study shows that a more severe and chronic lifetime disease course in MDD is associated with reduced volume in brain regions relevant for executive and cognitive functions and emotion regulation in a large sample of patients representing the broad heterogeneity of MDD disease course. These findings were only partly influenced by other clinical characteristics (e.g., remission status, psychopharmacological treatment).

Accounting for symptom heterogeneity can improve neuroimaging models of antidepressant response after electroconvulsive therapy.

Depression symptom heterogeneity limits the identifiability of treatment-response biomarkers. Whether improvement along dimensions of depressive symptoms relates to separable neural networks remains poorly understood. We build on work describing three latent symptom dimensions within the 17-item Hamilton Depression Rating Scale (HDRS) and use data-driven methods to relate multivariate patterns of patient clinical, demographic, and brain structural changes over electroconvulsive therapy (ECT) to dimensional changes in depressive symptoms. We included 110 ECT patients from Global ECT-MRI Research Collaboration (GEMRIC) sites who underwent structural MRI and HDRS assessments before and after treatment. Cross validated random forest regression models predicted change along symptom dimensions. HDRS symptoms clustered into dimensions of somatic disturbances (SoD), core mood and anhedonia (CMA), and insomnia. The coefficient of determination between predicted and actual changes were 22%, 39%, and 39% (all p < .01) for SoD, CMA, and insomnia, respectively. CMA and insomnia change were predicted more accurately than HDRS-6 and HDRS-17 changes (p < .05). Pretreatment symptoms, body-mass index, and age were important predictors. Important imaging predictors included the right transverse temporal gyrus and left frontal pole for the SoD dimension; right transverse temporal gyrus and right rostral middle frontal gyrus for the CMA dimension; and right superior parietal lobule and left accumbens for the insomnia dimension. Our findings support that recovery along depressive symptom dimensions is predicted more accurately than HDRS total scores and are related to unique and overlapping patterns of clinical and demographic data and volumetric changes in brain regions related to depression and near ECT electrodes.

Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity.

BACKGROUND: MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. METHODS: We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. RESULTS: The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. CONCLUSIONS: Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder.

Major depressive disorder (MDD) is associated to affected brain wiring. Little is known whether these changes are stable over time and hence might represent a biological predisposition, or whether these are state markers of current disease severity and recovery after a depressive episode. Human white matter network ("connectome") analysis via network science is a suitable tool to investigate the association between affected brain connectivity and MDD. This study examines structural connectome topology in 464 MDD patients (mean age: 36.6 years) and 432 healthy controls (35.6 years). MDD patients were stratified categorially by current disease status (acute vs. partial remission vs. full remission) based on DSM-IV criteria. Current symptom severity was assessed continuously via the Hamilton Depression Rating Scale (HAMD). Connectome matrices were created via a combination of T1-weighted magnetic resonance imaging (MRI) and tractography methods based on diffusion-weighted imaging. Global tract-based metrics were not found to show significant differences between disease status groups, suggesting conserved global brain connectivity in MDD. In contrast, reduced global fractional anisotropy (FA) was observed specifically in acute depressed patients compared to fully remitted patients and healthy controls. Within the MDD patients, FA in a subnetwork including frontal, temporal, insular, and parietal nodes was negatively associated with HAMD, an effect remaining when correcting for lifetime disease severity. Therefore, our findings provide new evidence of MDD to be associated with structural, yet dynamic, state-dependent connectome alterations, which covary with current disease severity and remission status after a depressive episode.

Cortical surface area alterations shaped by genetic load for neuroticism.

Neuroticism has been shown to act as an important risk factor for major depressive disorder (MDD). Genetic and neuroimaging research has independently revealed biological correlates of neurotic personality including cortical alterations in brain regions of high relevance for affective disorders. Here we investigated the influence of a polygenic score for neuroticism (PGS) on cortical brain structure in a joint discovery sample of n = 746 healthy controls (HC) and n = 268 MDD patients. Findings were validated in an independent replication sample (n = 341 HC and n = 263 MDD). Subgroup analyses stratified for case-control status and analyses of associations between neurotic phenotype and cortical measures were carried out. PGS for neuroticism was significantly associated with a decreased cortical surface area of the inferior parietal cortex, the precuneus, the rostral cingulate cortex and the inferior frontal gyrus in the discovery sample. Similar associations between PGS and surface area of the inferior parietal cortex and the precuneus were demonstrated in the replication sample. Subgroup analyses revealed negative associations in the latter regions between PGS and surface area in both HC and MDD subjects. Neurotic phenotype was negatively correlated with surface area in similar cortical regions including the inferior parietal cortex and the precuneus. No significant associations between PGS and cortical thickness were detected. The morphometric overlap of associations between both PGS and neurotic phenotype in similar cortical regions closely related to internally focused cognition points to the potential relevance of genetically shaped cortical alterations in the development of neuroticism.

Social support and hippocampal volume are negatively associated in adults with previous experience of childhood maltreatment.

Background: Childhood maltreatment has been associated with reduced hippocampal volume in healthy individuals, whereas social support, a protective factor, has been positively associated with hippocampal volumes. In this study, we investigated how social support is associated with hippocampal volume in healthy people with previous experience of childhood maltreatment. Methods: We separated a sample of 446 healthy participants into 2 groups using the Childhood Trauma Questionnaire: 265 people without maltreatment and 181 people with maltreatment. We measured perceived social support using a short version of the Social Support Questionnaire. We examined hippocampal volume using automated segmentation (Freesurfer). We conducted a social support × group analysis of covariance on hippocampal volumes controlling for age, sex, total intracranial volume, site and verbal intelligence. Results: Our analysis revealed significantly lower left hippocampal volume in people with maltreatment (left F1,432 = 5.686, p = 0.018; right F1,433 = 3.371, p = 0.07), but no main effect of social support emerged. However, we did find a significant social support × group interaction for left hippocampal volume (left F1,432 = 5.712, p = 0.017; right F1,433 = 3.480, p = 0.06). In people without maltreatment, we observed a trend toward a positive association between social support and hippocampal volume. In contrast, social support was negatively associated with hippocampal volume in people with maltreatment. Limitations: Because of the correlative nature of our study, we could not infer causal relationships between social support, maltreatment and hippocampal volume. Conclusion: Our results point to a complex dynamic between environmental risk, protective factors and brain structure - in line with previous evidence - suggesting a detrimental effect of maltreatment on hippocampal development.

Elevated body weight modulates subcortical volume change and associated clinical response following electroconvulsive therapy.

Background: Obesity is a frequent somatic comorbidity of major depression, and it has been associated with worse clinical outcomes and brain structural abnormalities. Converging evidence suggests that electroconvulsive therapy (ECT) induces both clinical improvements and increased subcortical grey matter volume in patients with depression. However, it remains unknown whether increased body weight modulates the clinical response and structural neuroplasticity that occur with ECT. Methods: To address this question, we conducted a longitudinal investigation of structural MRI data from the Global ECT-MRI Research Collaboration (GEMRIC) in 223 patients who were experiencing a major depressive episode (10 scanning sites). Structural MRI data were acquired before and after ECT, and we assessed change in subcortical grey matter volume using FreeSurfer and Quarc. Results: Higher body mass index (BMI) was associated with a significantly lower increase in subcortical grey matter volume following ECT. We observed significant negative associations between BMI and change in subcortical grey matter volume, with pronounced effects in the thalamus and putamen, where obese participants showed increases in grey matter volume that were 43.3% and 49.6%, respectively, of the increases found in participants with normal weight. As well, BMI significantly moderated the association between subcortical grey matter volume change and clinical response to ECT. We observed no significant association between BMI and clinical response to ECT. Limitations: Because only baseline BMI values were available, we were unable to study BMI changes during ECT and their potential association with clinical and grey matter volume change. Conclusion: Future studies should take into account the relevance of body weight as a modulator of structural neuroplasticity during ECT treatment and aim to further explore the functional relevance of this novel finding.

Sleep duration is associated with white matter microstructure and cognitive performance in healthy adults.

Reduced sleep duration and sleep deprivation have been associated with cognitive impairment as well as decreased white matter integrity as reported by experimental studies. However, it is largely unknown whether differences in sleep duration and sleep quality might affect microstructural white matter and cognition. Therefore, the present study aims to examine the cross-sectional relationship between sleep duration, sleep quality, and cognitive performance in a naturalistic study design, by focusing on the association with white matter integrity in a large sample of healthy, young adults. To address this, 1,065 participants, taken from the publicly available sample of the Human Connectome Project, underwent diffusion tensor imaging. Moreover, broad cognitive performance measures (NIH Cognition Toolbox) and sleep duration and quality (Pittsburgh Sleep Quality Index) were assessed. The results revealed a significant positive association between sleep duration and overall cognitive performance. Shorter sleep duration significantly correlated with fractional anisotropy (FA) reductions in the left superior longitudinal fasciculus (SLF). In turn, FA in this tract was related to measures of cognitive performance and was shown to significantly mediate the association of sleep duration and cognition. For cognition only, associations shift to a negative association of sleep duration and cognition for participants sleeping more than 8 hr a day. Investigations into subjective sleep quality showed no such associations. The present study showed that real-world differences in sleep duration, but not subjective sleep quality are related to cognitive performance measures and white matter integrity in the SLF in healthy, young adults.

The role of BDNF methylation and Val66 Met in amygdala reactivity during emotion processing.

Epigenetic alterations of the brain-derived neurotrophic factor (BDNF) gene have been associated with psychiatric disorders in humans and with differences in amygdala BDNF mRNA levels in rodents. This human study aimed to investigate the relationship between the functional BDNF-Val66 Met polymorphism, its surrounding DNA methylation in BDNF exon IX, amygdala reactivity to emotional faces, and personality traits. Healthy controls (HC, n = 189) underwent functional MRI during an emotional face-matching task. Harm avoidance, novelty seeking and reward dependence were measured using the Tridimensional Personality Questionnaire (TPQ). Individual BDNF methylation profiles were ascertained and associated with several BDNF single nucleotide polymorphisms surrounding the BDNF-Val66 Met, amygdala reactivity, novelty seeking and harm avoidance. Higher BDNF methylation was associated with higher amygdala reactivity (x = 34, y = 0, z = -26, t(166) = 3.00, TFCE = 42.39, p(FWE) = .045), whereby the BDNF-Val66 Met genotype per se did not show any significant association with brain function. Furthermore, novelty seeking was negatively associated with BDNF methylation (r = -.19, p = .015) and amygdala reactivity (r = -.17, p = .028), while harm avoidance showed a trend for a positive association with BDNF methylation (r = .14, p = .066). The study provides first insights into the relationship among BDNF methylation, BDNF genotype, amygdala reactivity and personality traits in humans, highlighting the multidimensional relations among genetics, epigenetics, and neuronal functions. The present study suggests a possible involvement of epigenetic BDNF modifications in psychiatric disorders and related brain functions, whereby high BDNF methylation might reduce BDNF mRNA expression and upregulate amygdala reactivity.

Brain structural effects of treatments for depression and biomarkers of response: a systematic review of neuroimaging studies.

Antidepressive pharmacotherapy (AD), electroconvulsive therapy (ECT) and cognitive behavioural therapy (CBT) are effective treatments for major depressive disorder. With our review, we aim to provide a systematic overview of neuroimaging studies that investigate the effects of AD, ECT and CBT on brain grey matter volume (GMV) and biomarkers associated with response. After a systematic database research on PubMed, we included 50 studies using magnetic resonance imaging and investigating (1) changes in GMV, (2) pre-treatment GMV biomarkers associated with response, or (3) the accuracy of predictions of response to AD, ECT or CBT based on baseline GMV data. The strongest evidence for brain structural changes was found for ECT, showing volume increases within the temporal lobe and subcortical structures - such as the hippocampus-amygdala complex, anterior cingulate cortex (ACC) and striatum. For AD, the evidence is heterogeneous as only 4 of 11 studies reported significant changes in GMV. The results are not sufficient in order to draw conclusions about the structural brain effects of CBT. The findings show consistently that higher pre-treatment ACC volume is associated with response to AD, ECT and CBT. An association of higher pre-treatment hippocampal volume and response has only been reported for AD. Machine learning approaches based on pre-treatment whole brain patterns reach accuracies of 64-90% for predictions of AD or ECT response on the individual patient level. The findings underline the potential of brain biomarkers for the implementation in clinical practice as an additive feature within the process of treatment selection.

Influence of electroconvulsive therapy on white matter structure in a diffusion tensor imaging study.

BACKGROUND: Electroconvulsive therapy (ECT) is a fast-acting intervention for major depressive disorder. Previous studies indicated neurotrophic effects following ECT that might contribute to changes in white matter brain structure. We investigated the influence of ECT in a non-randomized prospective study focusing on white matter changes over time. METHODS: Twenty-nine severely depressed patients receiving ECT in addition to inpatient treatment, 69 severely depressed patients with inpatient treatment (NON-ECT) and 52 healthy controls (HC) took part in a non-randomized prospective study. Participants were scanned twice, approximately 6 weeks apart, using diffusion tensor imaging, applying tract-based spatial statistics. Additional correlational analyses were conducted in the ECT subsample to investigate the effects of seizure duration and therapeutic response. RESULTS: Mean diffusivity (MD) increased after ECT in the right hemisphere, which was an ECT-group-specific effect. Seizure duration was associated with decreased fractional anisotropy (FA) following ECT. Longitudinal changes in ECT were not associated with therapy response. However, within the ECT group only, baseline FA was positively and MD negatively associated with post-ECT symptomatology. CONCLUSION: Our data suggest that ECT changes white matter integrity, possibly reflecting increased permeability of the blood-brain barrier, resulting in disturbed communication of fibers. Further, baseline diffusion metrics were associated with therapy response. Coherent fiber structure could be a prerequisite for a generalized seizure and inhibitory brain signaling necessary to successfully inhibit increased seizure activity.

Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort.

BACKGROUND: Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age. METHODS: Within the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer. RESULTS: CM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions. CONCLUSIONS: Severity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.