Subthreshold stimulation intensity is associated with greater clinical efficacy of intermittent theta-burst stimulation priming for Major Depressive Disorder

BACKGROUND

Intermittent theta-burst stimulation priming (iTBS-P) can improve clinical outcome of patients with Major Depressive Disorder (MDD) who do not show early benefit from 10 Hz stimulation of left dorsolateral prefrontal cortex (DLPFC), also known as high-frequency left-sided (HFL) stimulation. The intensity and pulse number for iTBS-P needed to induce clinical benefit have not been systematically examined.

OBJECTIVE

To study the effect of intensity and pulse number on the clinical efficacy of iTBS-P.

METHODS

We conducted a retrospective review of 71 participants who received at least five sessions of HFL with limited clinical benefit and received iTBS-P augmentation for between 5 and 25 sessions. Intensity of iTBS-P priming stimuli ranged from 75 to 120% of motor threshold (MT) and pulse number ranged from 600 to 1800. Associations among intensity, pulse number, and clinical outcome were analyzed using a mixed methods linear model with change in IDS-SR as the primary outcome variable, priming stimulation intensity (subthreshold or suprathreshold), pulse number (<1200 or >1200 pulses), and gender as fixed factors, and number of iTBS-P treatments and age as continuous covariates.

RESULTS

Subjects who received subthreshold intensity iTBS-P experienced greater reduction in depressive symptoms than those who received suprathreshold iTBS-P (p = 0.011) with no effect of pulse number after controlling for stimulus intensity.

CONCLUSIONS

Subthreshold intensity iTBS-P was associated with greater clinical improvement than suprathreshold stimulation. This finding is consistent with iTBS-P acting through homeostatic plasticity mechanisms.

A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental illness that is diagnosed through questionnaire-based approaches; however, these methods may not lead to an accurate diagnosis. In this regard, many studies have focused on using electroencephalogram (EEG) signals and machine learning techniques to diagnose MDD.

NEW METHOD

This paper proposes a machine learning framework for MDD diagnosis, which uses different types of EEG-derived features. The features are extracted using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis methods. The sequential backward feature selection (SBFS) algorithm is also employed to perform feature selection. Various classifier models are utilized to select the best one for the proposed framework.

RESULTS

The proposed method is validated with a public EEG dataset, including the EEG data of 34 MDD patients and 30 healthy subjects. The evaluation of the proposed framework is conducted using 10-fold cross-validation, providing the metrics such as accuracy (AC), sensitivity (SE), specificity (SP), F1-score (F1), and false discovery rate (FDR). The best performance of the proposed method has provided an average AC of 99%, SE of 98.4%, SP of 99.6%, F1 of 98.9%, and FDR of 0.4% using the support vector machine with RBF kernel (RBFSVM) classifier.

COMPARISON WITH EXISTING METHODS

The obtained results demonstrate that the proposed method outperforms other approaches for MDD classification based on EEG signals.

CONCLUSIONS

According to the obtained results, a highly accurate MDD diagnosis would be provided using the proposed method, while it can be utilized to develop a computer-aided diagnosis (CAD) tool for clinical purposes.

The relation between therapy quality, therapy processes and outcomes and identifying for whom therapy quality matters in CBT and IPT for depression

BACKGROUND

Research on which therapy processes are crucial for whom is necessary to optimize treatment outcomes for major depressive disorder (MDD) but may be impeded by a lack of variation in therapy quality and because of individual differences in therapy response. The present study used a dataset with large variation in therapy quality to investigate the impact of therapy quality on change in therapy processes and outcome. Machine-learning techniques were used to explore individual differences in these relationships.

METHOD

Data come from a multicenter trial that randomized patients with MDD into weekly versus twice weekly sessions of cognitive behavioral therapy (CBT) or interpersonal psychotherapy (IPT). Correlations between quality of therapy, change in therapy processes and depressive symptoms were calculated. Using elastic net regression, a prognostic model was developed that investigated individual differences.

RESULTS

There were no significant correlations between therapy quality and change in therapy process variables or between therapy quality and therapy outcome, except between therapy quality and dysfunctional thinking and IPT skills. Improvement in therapy processes played a larger role in patients whose therapy outcome was poorly predicted by their baseline characteristics.

CONCLUSIONS

In this study, in which therapy quality varied considerably, we found that therapy quality was not related to change in therapy processes or outcome. In addition, this study provides a first demonstration of proposed methods to identify individual responses to change in therapy processes. Results suggested that the importance of certain therapy processes might differ between patients. Future research into the relation between therapy quality, change in therapy processes and outcome should take into account the variation of therapy quality, focus on improved measurement of therapy quality and use a combination of machine learning techniques and experimental lab studies to determine to which extent and for whom therapy quality and change in therapy processes matter.

Characteristics of patients who received deep brain stimulation in obsessive-compulsive disorder versus major depressive disorder

OBJECTIVE

Deep brain stimulation (DBS) is cleared for treatment of obsessive-compulsive disorder (OCD) but is an investigational treatment for major depressive disorder (MDD). The aim of this study is to compare the characteristics of patients who received DBS as part of standard care for OCD versus those who received it a part of a research protocol for MDD.

METHODS

The inpatient sample (N = 110) was drawn from the 2012-2014 Nationwide Inpatient Sample (NIS), and included adults with a primary discharge diagnosis of MDD (N = 50) or OCD (N = 60) and primary procedure of DBS. The study compared various patient demographics, clinical, hospital and insurance variables between the 2 groups.

RESULTS

DBS recipients with OCD were younger compared to those with MDD. DBS recipients with MDD tended to be from high-income families compared to those with OCD. DBS patients with MDD were in the South region, while DBS patients with OCD were in the Midwest and South regions of the United States (US). The study did not detect a significant difference in the length of stay and total charges among DBS recipients with OCD versus MDD.

CONCLUSIONS

DBS patients with MDD are typically older with more financial resources compared to those with OCD. DBS is federally cleared for OCD, but not for MDD, demonstrating the need for further investigation to establish DBS as a federally cleared treatment for difficult to treat MDD if well-powered randomized trials further support its use.

Biological correlates of early life stressful events in major depressive disorder

Major depressive disorder (MDD) is the most common psychiatric disorder and responds for important psychosocial consequences. Stressful life events, especially early life stress (ELS), contribute to an increased probability to develop MDD, leading in particular to severe and chronic manifestation and unfavorable treatment outcome. The association between ELS and MDD seems to have biological bases, consisting in dysregulations occurring at different levels. The aim of this narrative review is to propose an overview of the literature ranging from genetic, epigenetic, expression and protein to neuroimaging correlates underlying this relationship. A search on Pubmed of studies assessing biological correlates of ELS in MDD development, focusing on human studies conducted in both peripheral and brain tissues, was performed. Evidence indicated that the hypothalamic-pituitary-adrenal (HPA) axis and the serotonergic, dopaminergic, neurotrophin and oxytocin systems might play a role in the mediation between ELS and MDD. The most consistent results were found for genetic and epigenetic studies and indicated a joint involvement of the systems mentioned. Expression studies are less numerous and point to an involvement of stress-related systems. Concerning protein studies, the main mediators are markers related to the inflammatory and immune systems. Neuroimaging studies aiming at evaluating brain alterations connecting ELS and MDD in relation to biomarkers indicated the hippocampus, the amygdala and the frontal cortex as important anatomical mediators. These findings can build the bases for future research and clinical interventions; indeed, the clarification of biological mechanisms mediating the relationship between ELS and MDD can lead to new and individualized preventive and therapeutic possibilities.

Characterizing the subtype of anhedonia in major depressive disorder: A symptom-specific multimodal MRI study

Anhedonia is a core symptom of major depressive disorder (MDD). Two subtypes of anhedonia: anticipatory anhedonia and consummatory anhedonia has been recognized in MDD patients. However, our knowledge regarding the distinction of anticipatory anhedonia and consummatory anhedonia in MDD remains limited. This study aimed to characterize the anticipatory anhedonia and consummatory anhedonia in first-episode, drug-naïve MDD patients. Resting-state functional MRI and T1-structural MRI were acquired for 38 MDD patients and 65 matched healthy controls (HCs). The ALFF and cortical surface indexes were compared between MDD and HCs. Then the correlations between the ALFF and cortical surface indexes alternations and the scores of anticipatory and consummatory pleasure measured by Temporal Experience of Pleasure Scale were evaluated. The elevated ALFF of left dorsal anterior cingulate cortex (dACC) and the reduced cortical thickness (CT) of left rostral ACC and lateral orbitofrontal cortex (lOFC) were respectively correlated with anticipatory anhedonia and consummatory anhedonia in MDD patients. These findings suggested the dissociated pathophysiological basis and imaging characteristics of anticipatory anhedonia and consummatory anhedonia. The ALFF and CT values of ACC and lOFC might serve as the imaging biomarker of the subtypes of anhedonia in early onset of MDD.

Prefrontal resting-state connectivity and antidepressant response: no associations in the ELECT-TDCS trial

Functional and structural MRI of prefrontal cortex (PFC) may provide putative biomarkers for predicting the treatment response to transcranial direct current stimulation (tDCS) in depression. A recent MRI study from ELECT-TDCS (Escitalopram versus Electrical Direct-Current Theror Depression Study) showed that depression improvement after tDCS was associated with gray matter volumes of PFC subregions. Based thereon, we investigated whether antidepressant effects of tDCS are similarly associated with baseline resting-state functional connectivity (rsFC). A subgroup of 51 patients underwent baseline rsFC-MRI. All patients of ELECT-TDCS were randomized to three treatment arms for 10 weeks (anodal-left, cathodal-right PFC tDCS plus placebo medication; escitalopram 10 mg/day for 3 weeks and 20 mg/day thereafter plus sham tDCS; and placebo medication plus sham tDCS). RsFC was calculated for various PFC regions and analyzed in relation to the individual antidepressant response. There was no significant association between baseline PFC connectivity of essential structural regions, nor any other PFC regions (after correction for multiple comparisons) and patients' individual antidepressant response. This study did not reveal an association between antidepressants effects of tDCS and baseline rsFC, unlike the gray matter volume findings. Thus, the antidepressant effects of tDCS may be differentially related to structural and functional MRI measurements.

Functional plasticity abnormalities over the lifespan of first-episode patients with major depressive disorder: a resting state fMRI study

Background

Neurodevelopmental and neurodegenerative theories of depression suggest that patients with major depressive disorder (MDD) may follow abnormal developmental, maturational, and aging processes. However, a lack of lifespan studies has precluded verification of these theories. Herein, we analyzed functional magnetic resonance imaging (fMRI) data to comprehensively characterize age-related functional trajectories, as measured by the fractional amplitude of low frequency fluctuations (fALFF), over the course of MDD.

Methods

In total, 235 MDD patients with age-differentiated onsets and 235 age- and sex-matched healthy controls (HC) were included in this study. We determined the pattern of age-related fALFF changes by cross-sectionally establishing the general linear model (GLM) between fALFF and age over a lifespan. Furthermore, the subjects were divided into four age groups to assess age-related neural changes in detail. Inter-group fALFF comparison (MDD vs. HC) was conducted in each age group and Granger causal analysis (GCA) was applied to investigate effective connectivity between regions.

Results

Compared with the HC, no significant quadratic or linear age effects were found in MDD over the entire lifespan, suggesting that depression affects the normal developmental, maturational, and degenerative process. Inter-group differences in fALFF values varied significantly at different ages of onset. This implies that MDD may impact brain functions in a highly dynamic way, with different patterns of alterations at different stages of life. Moreover, the GCA analysis results indicated that MDD followed a distinct pattern of effective connectivity relative to HC, and this may be the neural basis of MDD with age-differentiated onsets.

Conclusions

Our findings provide evidence that normal developmental, maturational, and ageing processes were affected by MDD. Most strikingly, functional plasticity changes in MDD with different ages of onset involved dynamic interactions between neuropathological processes in a tract-specific manner.

Identifying response and predictive biomarkers for Transcranial magnetic stimulation outcomes: protocol and rationale for a mechanistic study of functional neuroimaging and behavioral biomarkers in veterans with Pharmacoresistant depression

BACKGROUND

Although repetitive transcranial magnetic stimulation ('TMS') is becoming a gold standard treatment for pharmacoresistant depression, we lack neural target biomarkers for identifying who is most likely to respond to TMS and why. To address this gap in knowledge we evaluate neural targets defined by activation and functional connectivity of the dorsolateral prefrontal cortex-anchored cognitive control circuit, regions of the default mode network and attention circuit, and interactions with the subgenual anterior cingulate. We evaluate whether these targets and interactions between them change in a dose-dependent manner, whether changes in these neural targets correspond to changes in cognitive behavioral performance, and whether baseline and early change in neural target and cognitive behavioral performance predict subsequent symptom severity, suicidality, and quality of life outcomes. This study is designed as a pragmatic, mechanistic trial partnering with the National Clinical TMS Program of the Veteran's Health Administration.

METHODS

Target enrollment consists of 100 veterans with pharmacoresistant Major Depressive Disorder (MDD). All veterans will receive a clinical course of TMS and will be assessed at 'baseline' pre-TMS commencement, 'first week' after initiation of TMS (targeting five sessions) and 'post-treatment' at the completion of TMS (targeting 30 sessions). Veterans will be assessed using functional magnetic resonance imaging (fMRI), a cognitive behavioral performance battery, and established questionnaires. Multivariate linear mixed models will be used to assess whether neural targets change with TMS as a function of dose (Aim 1), whether extent and change of neural target relates to and predicts extent of behavioral performance (Aim 3), and whether extent of neural target change predicts improvement in symptom severity, suicidality, and quality of life (Aim 3). For all three aims, we will also assess the contribution of baseline moderators such as biological sex and age.

DISCUSSION

To our knowledge, our study will be the first pragmatic, mechanistic observational trial to use fMRI imaging and cognitive-behavioral performance as biomarkers of TMS treatment response in pharmacoresistant MDD. The results of this trial will allow providers to select suitable candidates for TMS treatment and better predict treatment response by assessing circuit connectivity and cognitive-behavioral performance at baseline and during early treatment.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04663481 , December 5th, 2020, retrospectively registered. The first veteran was enrolled October 30th, 2020.

Influence and interaction of genetic, cognitive, neuroendocrine and personalistic markers to antidepressant response in Chinese patients with major depression

OBJECTIVE

Despite there is a wide range of antidepressants available, with various mechanisms of actions, the efficacy of current therapeutic options is yet satisfactory. Previous shreds of evidence have indicated that genetics, cognitive, neuroendocrine, as well as personality factors, are all intrinsically linked and contribute to the diversity of treatment outcomes. We, therefore, sought to investigate this hypothesis in this study.

METHOD

Based on 610 samples treated with a selection of serotonin reuptake inhibitor (SSRI), serotonin-norepinephrine reuptake inhibitors (SNRI), noradrenergic and specific serotonergic antidepressant (NaSSA) or tricyclic antidepressant (TCA), we compared the therapeutic effects of these four classes of drugs by survival analyses. Pharmacogenomic and survival analyses were carried out to explore the hereditary factors for curative effect and the accumulation of genetic factors was further discussed through pathway analysis and the global test. We built a machine learning-based prediction model that integrates genetic and non-genetic factors (including cognition, endocrinology, personality intelligence) to distinguish drug efficacy in single class drug situations. The values of the non-genetic makers after 6 weeks' treatment were collected to evaluate the efficacy of the model.

RESULTS

Our results from the 6-week antidepressant therapeutic study indicated that SSRI and SNRI are better treatments than those of TCA and NaSSA in the Chinese population. Among all possible paired single-agent survival analyses, citalopram and venlafaxine were more effective than mirtazapine. Allele C carriers at rs6354 (SLC6A4) and allele G carriers at rs12150214 (SLC6A4) were significantly prone to poorer treatment response to fluoxetine. Besides, the combination of three loci (rs929377-rs6191-rs32897) located in HPA pathway was significantly associated with the treatment outcome of fluoxetine. In female MDD patients, the minor allele of rs6323 and rs1137070 on the MAOA gene likely lead to a worse response to venlafaxine. Furthermore, genetic variants linked to drug efficacy tended to concentrate on the neurotrophin pathway in depressed patients comorbid with anxiety. From multivariate models, more severe cognitive deficits, psychopathic personality and lower levels of operational intelligence, and higher levels of cortisol predicted worse response status with SSRI or SNRI after 6-week treatment. Notably, genetic factors in the multi-dimensional prediction model for both classes of drugs include loci in HTR2A and CRHBP genes.

CONCLUSION

SSRI and SNRI are more suitable for the treatment of Chinese people with depression. SLC6A4 genetic variants, as well as HPA pathway, play an important role in the fluoxetine antidepressant therapeutic response while the polymorphism of MAOA gene involved in the pharmacological action of venlafaxine among female MDD patients. The presence of anxiety in MDD patients was related to the neurotrophin pathway. Genetic, cognitive, neuroendocrine, and personality intelligence factors combined have an ensemble impact on the medication effect of patients with major depression, leading to more precise and personalized medicine for specific groups of people.

Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards

The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.

Is postnatal depression a distinct subtype of major depressive disorder? An exploratory study

Postnatal depression (PND) has an estimated prevalence of 6.5 to 12.9%. In addition to the direct consequences for women, PND also interferes with the maternal-infant interaction, contributing to long-term cognitive and emotional impairments in exposed offspring. It is unclear how PND differs from major depressive disorder (MDD) more generally, and if PND represents a distinct subtype of depression. We explored whether women with a history of PND have specific differences in brain activation associated with sex hormone changes during the late luteal phase of the menstrual cycle, compared to parous women with either a past history of MDD outside of the postnatal period, or an absent history of MDD ('never depressed'). Thirty mothers (history of PND (n = 10), history of MDD (n = 10), and 'never depressed' (n = 10)) underwent blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) acquisition during an emotional faces task. Amygdala activity was analysed using a region of interest (small volume correction) approach. There was a significant reduction in BOLD response to positive emotional faces in the right amygdala in women with a history of PND compared to women with a history of MDD. A similar but non-significant trend was found in the left amygdala in women with a history of PND compared to 'never depressed' women. Our findings support the hypothesis that women with vulnerability to PND represent a distinct subgroup of women with a differential sensitivity to changes in sex hormones. Further, albeit highly tentative, they provide a putative biomarker that could assist in detection of women at-risk to PND.

Strategies for augmentation of high-frequency left-sided repetitive transcranial magnetic stimulation treatment of major depressive disorder

BACKGROUND

Repetitive Transcranial Magnetic Stimulation (rTMS) is an effective intervention for treatment-resistant Major Depressive Disorder (MDD). Early improvement during high-frequency left-sided (HFL) stimulation of the dorsolateral prefrontal cortex (DLPFC) is an important predictor of longer-term outcome, but most patients benefit later in their treatment course. We examined patients without early improvement with HFL to determine whether augmentation with additional stimulation approaches improved treatment outcome.

METHODS

139 participants received HFL in a measurement-based care paradigm. Participants who achieved < 20% improvement by treatment 10 could continue with HFL (N = 17) or receive one of two augmentation strategies: bilateral stimulation (BL; HFL followed by low-frequency stimulation of right DLPFC) (N = 69) or intermittent theta-burst priming of left DLPFC (iTBS-P) (N = 17) for their remaining treatment sessions. The primary outcome was the percent reduction in depressive symptoms at treatment 30.

RESULTS

Participants who achieved < 20% improvement by treatment 10 and continued with HFL showed limited benefit. iTBS-P participants had significantly greater improvement, while those receiving BL trended toward improved outcomes. Ten sessions of either augmentation strategy appeared necessary to determine the likelihood of benefit.

CONCLUSIONS

Augmentation of early non-response to HFL appears to improve rTMS outcomes, with a novel iTBS-P strategy surpassing both continued HFL or BL treatment in participants with < 20% improvement after 10 treatments. These findings suggest that measurement-based care with addition of augmented stimulation for those not showing early improvement may yield superior rTMS treatment outcomes.

Effects of Baihui electroacupuncture in a rat model of depression

Background

This study aimed to investigate the effect of electroacupuncture (EA) on behavior in a rat model of chronic unpredictable mild stress (CUMS) and to explore the underlying molecular mechanisms.

Methods

A total of 45 adult male Sprague-Dawley rats were randomly divided into three groups: the control, CUMS, and CUMS plus EA groups. Rats in the CUMS and EA groups were subjected to a 3-week CUMS condition, while rats in the EA group received EA at the Baihui (GV 20) acupoint (2 Hz, 0.6 mA) for 10 min once daily before being subjected to the CUMS condition. The sucrose preference test (SPT) was used as a measure to infer activation of the pleasure response to depression-like behaviour. After the behavioral test, 5-bromodeoxyuridine (BrdU) was intraperitoneally injected (100 mg/kg) and brain samples were collected 24 h later for the detection of hippocampal BrdU. Cell proliferation was determined according to the proportion of BrdU-positive cells. Brain-derived neurotrophic factor (BDNF) expression was detected.

Results

The severity of anhedonia, BDNF⁺ cells, and BrdU⁺ neurons in DG significantly decreased in CUMS rats, and was accompanied by a reduced BDNF and BrdU⁺ expression (P<0.05). After EA, the low levels of BDNF⁺ cells and BrdU⁺ expression and the depression-like behavior increased markedly (P<0.05).

Conclusions

EA contributes to neuroprotection against CUMS by enhancing BDNF expression and improving hippocampal neurogenesis.

Working memory moderates the relation between the brain-derived neurotropic factor (BDNF) and psychotherapy outcome for depression

BACKGROUND

Insight into patient characteristics that predict response to treatment for major depressive disorder (MDD) may help to personalize treatment and improve outcomes. One mechanism that has been linked to the success of treatment for MDD is brain-derived neurotropic factor (BDNF). BDNF is implicated in learning and memory and may play a role in the effects of psychotherapy that involves changing cognitions and behaviors. In addition, only in individuals with low BDNF, low working memory capacity has been associated with increased symptoms of depression. However, the role of BDNF and working memory capacity in psychotherapy outcome is unclear. The aim of this study was to investigate the role of BDNF and its interaction with working memory capacity in psychotherapy outcomes for MDD.

METHOD

Adult patients with MDD were randomized to weekly or twice weekly sessions of cognitive behavioral therapy or interpersonal psychotherapy. BDNF Val66Met polymorphism (rs6265) (n = 138) was defined and serum BDNF was quantified before (n = 138) and after psychotherapy (n = 82).

RESULTS

Baseline serum BDNF and the Val66Met polymorphism were not associated with outcome and associations did not differ between treatment conditions. Working memory capacity significantly moderated the relation between baseline serum BDNF and outcome: high serum BDNF at baseline was related to less depressive symptoms following psychotherapy in the presence of high working memory capacity, but not low working memory capacity.

DISCUSSION

These findings, if replicated, might indicate that while BDNF may not be related to psychotherapy outcomes in general, they may play a role in the presence of specific learning processes such as working memory capacity.

The effects of childhood trauma on the onset, severity and improvement of depression: The role of dysfunctional attitudes and cortisol levels

BACKGROUND

Childhood trauma is an important early social risk factor for the development of the major depressive disorder (MDD). Both childhood trauma and depression are associated with dysfunctional attitudes and dysregulation in stress hormones. We aimed to clarify the path from childhood trauma to depression and identify potential predictors of antidepressant treatment outcomes.

OBJECTIVES

One hundred and thirty-nine MDD patients and 112 healthy controls were included at baseline. Depressive symptoms were assessed with both self-reported and expert-rated scales. Childhood trauma and dysfunctional attitudes were evaluated and blood cortisol levels were assayed. Patients received an open-label antidepressant trial with paroxetine and their depressive symptoms were monitored by the Hamilton Depression Rating Scale (HAMD) during 6 months of treatment. After 6 months, 94 patients received the same assessments as the baseline.

RESULTS

At baseline, the influence of childhood trauma on depression diagnosis was mediated by dysfunctional attitudes. In patients with MDD, the influence of childhood trauma on depression severity was mediated by both dysfunctional attitudes and cortisol levels. Baseline childhood trauma predicted the antidepressant treatment outcome during early treatment phase and baseline cortisol levels predicted the antidepressant treatment outcome at later treatment phase. After 6-month antidepressant treatment, a significant remission by time effect was found on dysfunctional attitudes and depression severity but not on cortisol levels.

CONCLUSION

Effect of childhood trauma on depression onset was mediated by dysfunctional attitudes. The relationship between childhood trauma and depressive symptoms was mediated by dysfunctional attitudes and cortisol levels in MDD patients. Baseline childhood trauma and cortisol levels may be moderators for antidepressant treatment response at different treatment phase.

SNRIs achieve faster antidepressant effects than SSRIs by elevating the concentrations of dopamine in the forebrain

Major depressive disorder (MDD) is a severe mental disorder with a high disability rate worldwide. Selective serotonin reuptake inhibitors (SSRIs) and serotonin and norepinephrine reuptake inhibitors (SNRIs) are the most common agents for antidepressant use. SSRIs and SNRIs are believed to achieve antidepressant effects through the activation of serotonergic or noradrenergic systems. However, whether the dopaminergic system is involved remains unclear. In our study, a genetically encoded dopamine sensor and in vivo fiber photometry recordings were used to measure the dopamine concentrations in the medial prefrontal cortex (mPFC) and nucleus accumbens (NAc) after acute intraperitoneal injection of SSRIs or SNRIs. Combined with the behavioral tests, we found that SNRIs increased dopamine concentrations in both the mPFC and the NAc and showed faster antidepressant effects than SSRIs. To verify the enhanced dopamine levels induce the faster antidepressant effects of SNRIs, we employed dopamine receptor antagonists to specifically block the dopaminergic function. The results showed that the faster antidepressant effects of SNRIs were weakened by the dopamine receptor antagonists. Altogether, our study reveals that SNRIs achieve faster antidepressant effects than SSRIs by elevating the dopamine concentrations in the mPFC and the NAc. Our work proposes further mechanisms for the first-line antidepressants, which provides more basis for clinical treatments. This article is part of the special issue on Stress, Addiction and Plasticity.

Major depressive disorder assessment via enhanced k-nearest neighbor method and EEG signals

The aim of this paper is to introduce a novel method using short-term EEG signals to separate depressed patients from healthy controls. Five common frequency bands (delta, theta, alpha, beta and gamma) were extracted from the signals as linear features, as well as, wavelet packet decomposition to break down signals into certain frequency bands. Afterwards, two entropy measures, namely sample entropy and approximate entropy were applied on the wavelet packet coefficients as nonlinear features, and significant features were selected via genetic algorithm (GA). Three machine-learning algorithms were used for classification; including support vector machine (SVM), multilayer perceptron (MLP) a novel enhanced K-nearest neighbors (E-KNN), which uses GA to optimize the feature-space distances and provides a feature importance index. The highest accuracy obtained by using frequency-based features was from gamma oscillations which resulted in 91.38%. Performance of nonlinear features were better compared to the frequency-based features and the results showed 94.28% accuracy. The combination of the features showed 98.44% accuracy with the new proposed E-KNN classifier.

Transition and Dynamic Reconfiguration of Whole-Brain Network in Major Depressive Disorder

Major depressive disorder (MDD) has been characterized by abnormal brain activity and interactions across the whole-brain functional networks. However, the underlying alteration of brain dynamics remains unclear. Here, we aim to investigate in detail the temporal dynamics of brain activity for MDD, and to characterize the spatiotemporal specificity of whole-brain networks and transitions across them. We developed a hidden Markov model (HMM) analysis for resting-state functional magnetic resonance imaging (fMRI) from two independent cohorts with MDD. In particular, one cohort included 127 MDD patients and 117 gender- and age-matched healthy controls, and the other included 44 MDD patients and 33 controls. We identified brain states characterized by the engagement of distinct functional networks that recurred over time and assessed the dynamical configuration of whole-brain networks and the patterns of activation of states that characterized the MDD groups. Furthermore, we analyzed the community structure of transitions across states to investigate the specificity and abnormality of transitions for MDD. Based on our identification of 12 HMM states, we found that the temporal reconfiguration of states in MDD was associated with the high-order cognition network (DMN), subcortical network (SUB), and sensory and motor networks (SMN). Further, we found that the specific module of transitions was closely related to MDD, which were characterized by two HMM states with opposite activations in DMN, SMN, and subcortical areas. Notably, our results provide novel insights into the dynamical circuit configuration of whole-brain networks for MDD and suggest that brain dynamics should remain a prime target for further MDD research.

The Centrality of Depression and Anxiety Symptoms in Major Depressive Disorder Determined Using a Network Analysis

BACKGROUND

Comorbid anxiety symptoms are highly prevalent and closely linked with poorer treatment outcomes, chronicity, and hospitalization in major depressive disorder (MDD). Our study aimed to estimate the network of depression and anxiety symptoms that was developed based on a sample of MDD patients.

METHODS

We constructed a network of the 21 Beck Depression Inventory (BDI) symptoms and 21 Beck Anxiety Inventory (BAI) symptoms in 223 patients with MDD who were beginning psychiatric treatment. In addition, each of the depression and anxiety symptoms was considered to be an ordered categorical variable ranging in value from 0 to 3.

RESULTS

The three depression symptoms including loss of energy, loss of interest, and worthlessness and the seven anxiety symptoms including faintness or lightheadedness, feeling of choking, feeling scared, fear of the worst happening, nervousness, inability to relax, and feeling shaky were identified as the ten most central nodes within a network of depression and anxiety symptoms. The inter-connection between irritability and nervousness was a strong trans-diagnostic edge within the network of depression and anxiety symptoms.

LIMITATIONS

Because our study was designed in a cross-sectional manner, the networks were estimated undirectionally.

CONCLUSIONS

Our findings show that depression symptoms are not more central than anxiety symptoms within an estimated network structure of symptoms in patients with MDD. Moreover, the inter-connection between irritability and nervousness may suggests a probable trans-diagnostic association in MDD symptomatology.

Early life stress and glutamate neurotransmission in major depressive disorder

Early life stress (ELS) and glutamate neurotransmission have been implicated in the pathophysiology of major depressive disorder (MDD). In non-human primates, ELS was positively correlated with cortical Glx (i.e., glutamate + glutamine). However, the relationship between ELS and cortical glutamate in adult patients with MDD is not fully known. Using ¹H Magnetic Resonance Spectroscopy (MRS), we conducted exploratory analyses measuring occipital cortical glutamate and glutamine levels in 36 medication-free patients with MDD. In a subsample (n=11), we measured dynamic glutamate/glutamine cycling (V_cycle) using advanced ¹³C MRS methods. ELS history was assessed using Early-life Trauma Inventory (ETI). Exploratory analyses suggest a relationship between ETI and glutamine as reflected by a significant positive correlation between ETI scores and occipital glutamine (r_s=0.39, p=0.017) but not glutamate. Post-hoc analyses showed that the association with glutamine was driven by the ETI emotional abuse (ETI-EA) subscale (r_s=0.39, p=0.02). V_cycle correlation with ETI was at trend level (r_s=0.55, p=0.087) and significantly correlated with ETI-EA (r_s=0.67, p=0.03). In this small sample of patients with MDD, those with childhood emotional abuse appear to have increased occipital glutamate neurotransmission as reflected by increased glutamate/glutamine cycling and glutamine level. Future studies would be needed to confirm this pilot evidence and to examine whether ELS effects on glutamate neurotransmission underlie the relationship between ELS and psychopathology.

Reduced serum VGF levels are linked with suicide risk in Chinese Han patients with major depressive disorder

BACKGROUND

VGF (nonacronymic) is a neuropeptide that plays an important role in the pathogenesis of major depressive disorder (MDD). However, no studies have yet investigated VGF levels in patients with MDD who are at risk of suicide. The purpose of the present study was to determine whether serum VGF levels are related to suicide risk in patients with MMD.

METHODS

A total of 107 patients with MDD and 40 normal control participated in the present study. The risk of suicide was assessed using the Nurses Global Assessment of Suicide Risk (NGASR). On this basis, 60 patients were assigned to a high-risk group (NGASR≥9) and 47 were assigned to a low-risk group (NGASR< 9). The severity of depression was measured using the 17-item Hamilton Depression Rating Scale (HDRS). Levels of serum VGF were determined using a double antibody sandwich enzyme-linked immunosorbent assay.

RESULTS

Serum VGF levels in the high-risk group (883.34 ± 139.67 pg/mL) were significantly lower than in the low-risk group (1020.56 ± 131.76 pg/mL) and in the control group (1107.00 ± 155.38 pg/mL) (F = 31.90, p < 0.001). In patients with MDD, suicide risk was significantly negatively correlated with VGF levels (r = - 0.55, p = 0.001).

CONCLUSIONS

Reduced serum VGF levels are related to risk of suicide in patients with MDD, so VGF may be a biomarker of suicide risk in MDD.

L-Carnosine combination therapy for major depressive disorder: A randomized, double-blind, placebo-controlled trial

BACKGROUND

Evidence for antidepressant effects of L-Carnosine was shown in some experimental studies. In this study we tried to evaluate the efficacy and tolerability of L-Carnosine combination therapy in treatment of patients with major depressive disorder (MDD).

METHODS

Fifty-eight patients with MDD (DSM-V) and Hamilton Depression Rating Scale (HAM-D) score ≥ 19 were randomized to receive either 400 mg twice daily L-Carnosine or placebo in addition to citalopram (maximum dosage of 40 mg/day) for six weeks in a randomized double-blind, and placebo-controlled study. Patients were assessed using the HAM-D scale at baseline and weeks 2, 4, and 6.

RESULTS

Fifty-two patients completed the trial. General linear model repeated measure showed significant difference for time × treatment on HAM-D score [F = 3.17, df = 2.39, p-value = 0.03]. Significantly greater improvement was detected in HAM-D score of the L-Carnosine group compared with the placebo group from baseline to weeks 2, 4 and 6 [Ps = 0.013, 0.028 and 0.023; respectively]. Patients in the L-Carnosine group experienced significantly greater response and remission rate than the placebo group [Ps = 0.023 and 0.012; respectively]. There was no significant difference between the two groups in baseline parameters and frequency of side effects.

LIMITATIONS

Short follow-up period and small population size were two important limitations of this study.

CONCLUSIONS

L-Carnosine combination therapy with citalopram can effectively improve symptoms of patients with major depressive disorder. Rapid-onset antidepressant effects of L-Carnosine were also shown which need further investigation.

The association between marital transitions and the onset of major depressive disorder in a south asian general population

BACKGROUND

Marriage in general is associated with better mental health in high-income industrialized countries, but it is unknown to what extent this is also the case in South Asia.

METHODS

The Chitwan Valley Family Study (CVFS) in Nepal is a 24-year family panel study with a recent representative survey to investigate the association between sociodemographic changes and mental health (N = 10,516). We investigated timing of marital transitions and timing of onset of MDD in both male and female respondents, controlling for key confounders.

RESULTS

In this setting the transition to marriage is associated with increased odds of subsequent MDD first onset (median OR=2.28). For female respondents, divorce (OR=2.68), early widowed (OR=11.25), and even getting married significantly increased the odds of subsequent MDD onset (OR=3.03). For male respondents, only becoming widowed increased the odds of subsequent MDD (OR=16.32), but marriage did not reduce the odds of MDD.

LIMITATIONS

Limitations of the study include large-scale protocol that may have resulted in underreporting of MDD and the exclusion of sub-threshold cases that may otherwise have qualified as a case in a clinical setting.

CONCLUSIONS

In the Nepalese general population, marital transitions increase the odds of subsequent depression, especially among the female population. Results provide basic but essential vital health data that can guide clinicians to proactively plan sustainable healthcare both within South Asia and among many South Asians living in other places.

Abnormal functional connectivity strength in first-episode, drug-naïve adult patients with major depressive disorder

BACKGROUND

The pathogenesis of major depressive disorder (MDD) is complicated and equivocal. Previous studies have found an incidence of abnormal changes of neural networks, with plentiful evidence pointing the finger of suspicion firmly at the default mode network (DMN) and cortico-limbic networks. The aim of the present study was to use the approach of functional connectivity strength (FCS) to directly investigate the features of spontaneous brain activity in the case of first-episode, drug-naïve adult patients with MDD at rest.

METHODS

Resting-state functional magnetic resonance imaging (MRI) scans were performed on 23 first-episode drug-naïve major depressive disorder (MDD) patients and 20 healthy controls (HCs). In this study, using graph-theory approaches(FCS), we computed the characteristics of brain connectivity. Simultaneously, we used a series of validated test procedures to evaluate the patients' cognitive function. Subsequently, the results were compared with the peak of FCS value and a correlation analysis was conducted.

RESULTS

Compared with the HCs group, MDD patients showed significantly decreased FCS in bilateral posterior cingulate cortex (PCC)/precuneus and bilateral prefrontal cortex(PFC) and increased FCS in right posterior central gyrus, left thalamus and left temporal lobe. These brain regions belongs to the default-mode network and cortico-limbic networks. Finally, the correlation analyses showed the negative correlation of the FCS values in the left posterior cingulate cortex (PCC)/precuneus and Hamilton Anxiety Rating Scale (HAMA, r = -0.472, p = .023), Stroop Color Word Test-A(SCWT-A, r = -0.451, p = .031), Stroop Color Word Test-B(SCWT-B, r = -0.588, p = .003).Meanwhile, there was negative correlation between the FCS values in the left thalamus and SCWT-A(r = -0.473, p = .023), SCWT-B(r = -0.465, p = .025), SCWTC(r = -0.524, p = .010).In addition, the FCS values in the right PCC has negative correlation with Montgomery Asberg Depression Rating Scale (MADRS) (r = -0.433, p = .039).

CONCLUSIONS

DMN is an important node of MDD. FCS within the default mode network and cortico-limbic networks in patients with major depressive disorder has been changed in the early stage of MDD. FCS can provide favourable and additional evidence in the investigation of brain pathophysiology and therapy in depression.