Early and delayed onset of response to antidepressants in individual trajectories of change during treatment of major depression: a secondary analysis of data from the Genome-Based Therapeutic Drugs for Depression (GENDEP) study

Relationship between Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) total scores in older adults with major depressive disorder: An analysis of the OPTIMUM clinical trial

BACKGROUND

The Patient Health Questionnaire (PHQ-9) and Montgomery-Asberg Depression Rating Scale (MADRS) are commonly used scales to measure depression severity in older adults.

METHODS

We utilized data from the Optimizing Outcomes of Treatment-Resistant Depression in Older Adults (OPTIMUM) clinical trial to produce conversion tables relating PHQ-9 and MADRS total scores. We split the sample into training (N = 555) and validation samples (N = 187). Equipercentile linking was performed on the training sample to produce conversion tables for PHQ-9 and MADRS. We compared the original and estimated scores in the validation sample with Bland-Altman analysis. We compared the depression severity level using the original and estimated scores with Chi-square tests.

RESULTS

The Bland-Altman analysis confirmed that differences between the original and estimated scores for at least 95 % of the sample fit within 1.96 standard deviations of the mean difference. Chi-square tests showed a significant difference in the proportion of participants at each depression severity category determined using the original and estimated scores.

LIMITATIONS

The conversion tables should be used with caution when comparing depression severity at the individual level.

CONCLUSIONS

Our conversion tables relating PHQ-9 and MADRS scores can be used to compare treatment outcomes using aggregate data in studies that only used one of these scales.

Update on the assessment of resistance to antidepressant treatment: Rationale for the Antidepressant Treatment History Form: Short Form-2 (ATHF-SF2)

All definitions of treatment-resistant depression (TRD) require that patients have experienced insufficient benefit from one or more adequate antidepressant trials. Thus, identifying "failed, adequate trials" is key to the assessment of TRD. The Antidepressant Treatment History Form (ATHF) was one of the first and most widely used instruments that provided objective criteria in making these assessments. The original ATHF was updated in 2018 to the ATHF-SF, changing to a checklist format for scoring, and including specific pharmacotherapy, brain stimulation, and psychotherapy interventions as potentially adequate antidepressant treatments. The ATHF-SF2, presented here, is based on the consensus of the ATHF workgroup about the novel interventions introduced since the last revision and which should/should not be considered effective treatments for major depressive episodes. This document describes the rationale for these choices and, for each intervention, the minimal criteria for determining the adequacy of treatment administration. The Supplementary Material that accompanies this article provide the Scoring Checklist, Data Collection Forms (current episode and composite of previous episodes), and Instruction Manual for the ATHF-SF2.

Trajectories of improvement with repetitive transcranial magnetic stimulation for treatment-resistant major depression in the BRIGhTMIND trial

Repetitive transcranial magnetic stimulation (rTMS) is an established non-invasive brain stimulation treatment for major depressive disorder, but there is marked inter-individual variability in response. Using latent class growth analysis with session-by-session patient global impression ratings from the recently completed BRIGhTMIND trial, we identified five distinct classes of improvement trajectory during a 20-session treatment course. This included a substantial class of patients noticing delayed onset of improvement. Contrary to prior expectations, members of a class characterised by early and continued improvement showed greatest inter-session variability in stimulated location. By relating target locations and inter-session variability to a well-studied atlas, we estimated an average of 3.0 brain networks were stimulated across the treatment course in this group, compared to 1.1 in a group that reported symptom worsening (p < 0.001, d = 0.893). If confirmed, this would suggest that deliberate targeting of multiple brain networks could be beneficial to rTMS outcomes.

Effectiveness and tolerability of adjunctive transcranial direct current stimulation (tDCS) in management of treatment-resistant depression: A retrospective chart review

Background

There is a limited number of studies from India investigating the role of transcranial direct current stimulation (tDCS) in treatment-resistant depression (TRD). This clinic-based study reports on the effectiveness of tDCS as an add-on treatment in individuals suffering from TRD.

Materials and Methods

Twenty-six right-handed individuals suffering from major depressive disorder who failed to respond to adequate trials of at least two antidepressant drugs in the current episode received tDCS as an augmenting treatment. Twice daily sessions of conventional tDCS were given providing anodal stimulation at the left dorsolateral prefrontal cortex (DLPFC) and cathodal placement at the right DLPFC. A total of 20 sessions were given over 2 weeks. The outcome was assessed based on changes in scores of the Hamilton Rating Scale for Depression (HAMD) and Montgomery-Asberg Depression Rating Scale (MADRS).

Results

There was a significant reduction in outcome assessment after tDCS intervention as compared to baseline, with more than 50% of the participants showing response in both scales, which increased further to approximately 77% by the end of 1 month of the follow-up period.

Conclusion

Twice daily tDCS sessions with anodal stimulation of left DLPFC and cathodal stimulation of right DLPFC is an effective add-on treatment strategy in individuals with TRD.

High-resolution tracking of unconfined zebrafish behavior reveals stimulatory and anxiolytic effects of psilocybin

Serotonergic psychedelics are emerging therapeutics for psychiatric disorders, yet their underlying mechanisms of action in the brain remain largely elusive. Here, we developed a wide-field behavioral tracking system for larval zebrafish and investigated the effects of psilocybin, a psychedelic serotonin receptor agonist. Machine learning analyses of precise body kinematics identified latent behavioral states reflecting spontaneous exploration, visually-driven rapid swimming, and irregular swim patterns following stress exposure. Using this method, we found that acute psilocybin treatment has two behavioral effects: [i] facilitation of spontaneous exploration ("stimulatory") and [ii] prevention of irregular swim patterns following stress exposure ("anxiolytic"). These effects differed from the effect of acute SSRI treatment and were rather similar to the effect of ketamine treatment. Neural activity imaging in the dorsal raphe nucleus suggested that psilocybin inhibits serotonergic neurons by activating local GABAergic neurons, consistent with psychedelic-induced suppression of serotonergic neurons in mammals. These findings pave the way for using larval zebrafish to elucidate neural mechanisms underlying the behavioral effects of serotonergic psychedelics.

When to hold and when to fold: Early prediction of nonresponse to transcranial magnetic stimulation in major depressive disorder

BACKGROUND

Determining when to recommend a change in treatment regimen due to insufficient improvement is a common challenge in therapeutics.

METHODS

In a sample of 7215 patients with major depressive disorder treated with transcranial magnetic stimulation (TMS) and with PHQ-9 scores before, during and after the course, 3 groups were identified based on number of acute course sessions: exactly 36 sessions (N = 3591), more than 36 sessions (N = 975), and less than 36 sessions (N = 2649). Two techniques were used to determine thresholds for percentage change in PHQ-9 scores at assessments after 10, 20, and 30 sessions that optimized prediction of endpoint response status: the Youden index and fixing the false positive rate at 10%. Positive and negative predictive values were calculated to assess the accuracy of identifying final nonresponders and responders, respectively.

RESULTS

There was greater accuracy in predicting final response than nonresponse, especially in the groups that had at least 36 sessions. Substantial proportions of patients with low levels of early improvement were classified as responders at the end of treatment.

LIMITATIONS

The findings should be validated with clinician ratings using a more comprehensive depression severity scale.

CONCLUSIONS

Manifesting clinical improvement early in the TMS course is strongly predictive of final status as a responder, while lack of early improvement is a relatively poor indicator of final nonresponse status. The predictive value of lack of early symptomatic improvement is too low to make reliable recommendations regarding changes in treatment regimen.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Early effects predict trajectories of response to esketamine in treatment-resistant depression

BACKGROUND

The efficacy of esketamine in treatment-resistant depression (TRD) has been confirmed. However, its administration is expensive and restrictive, with limited knowledge on how long the treatment should be continued. Predicting the treatment outcome would benefit patients and alleviate the global treatment cost. We aimed to define distinct trajectories of treatment response and assess their predictability.

METHODS

In this longitudinal study, two independent samples of patients with unipolar or bipolar TRD were treated with esketamine in real-world settings. Depression severity was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) before each esketamine administration. Latent class analyses were used to define trajectories of response.

RESULTS

In the original sample (N = 50), we identified two classes whose trajectories depicted response and non-response, respectively. The model was validated in the confirmatory sample (N = 55). Class membership was influenced by a few baseline characteristics such as concomitant benzodiazepine medication, number of depressive episodes or polarity. On the other hand, after only two esketamine administrations, the MADRS score predicted the 90-day trajectory of response with an accuracy of 80 %.

LIMITATIONS

This observational study is not placebo-controlled. Therefore, its results and their generalizability need to be confirmed in experimental settings.

CONCLUSIONS

After the first administrations of esketamine, the MADRS score has a good capacity to predict the most plausible trajectory of response. While thresholds and their predictive values need to be confirmed, this finding suggests that clinicians could base on MADRS scores their decision to discontinue treatment because of poor remaining chances of treatment response.

Factors Affecting Antidepressant Response Trajectories: A Veterans Affairs Augmentation and Switching Treatments for Improving Depression Outcomes Trial Report

Background

In this secondary analysis of the VA Augmentation and Switching Treatments for Improving Depression Outcomes (VAST-D) study we used antidepressant response trajectories to assess the association of treatment and multiple clinical/demographic factors with the probability of response.

Methods

Using data from VAST-D, a multi-site, randomized, single-blind trial with parallel-assignment to one of three treatment interventions in 1522 Veterans whose major depressive disorder was unresponsive to at least one antidepressant trial, we evaluated response patterns using group-based trajectory modeling (GBTM). A weighted multinomial logistic regression analysis with backward elimination and additional exploratory analyses were performed to evaluate the association of multiple clinical/demographic factors with the probability of inclusion into specific trajectories. Additional exploratory analyses were used to identify factors associated with trajectory group membership that could have been missed in the primary analysis.

Results

GBTM showed the best fit for depression symptom change was comprised of six trajectories, with some trajectories demonstrating minimal improvement and others showing a high probability of remission. High baseline depression and anxiety severity scores decreased, and early improvement increased, the likelihood of inclusion into the most responsive trajectory in both the GBTM and exploratory analyses.

Conclusion

While multiple factors influence responsiveness, the probability of inclusion into a specific depression symptom trajectory is most strongly influenced by three factors: baseline depression, baseline anxiety, and the presence of early improvement.

Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study

Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5-4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8-12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.

Self-processing in relation to emotion and reward processing in depression

BACKGROUND

Depression is characterised by a heightened self-focus, which is believed to be associated with differences in emotion and reward processing. However, the precise relationship between these cognitive domains is not well understood. We examined the role of self-reference in emotion and reward processing, separately and in combination, in relation to depression.

METHODS

Adults experiencing varying levels of depression (n = 144) completed self-report depression measures (PHQ-9, BDI-II). We measured self, emotion and reward processing, separately and in combination, using three cognitive tasks.

RESULTS

When self-processing was measured independently of emotion and reward, in a simple associative learning task, there was little association with depression. However, when self and emotion processing occurred in combination in a self-esteem go/no-go task, depression was associated with an increased positive other bias [b = 3.51, 95% confidence interval (CI) 1.24-5.79]. When the self was processed in relation to emotion and reward, in a social evaluation learning task, depression was associated with reduced positive self-biases (b = 0.11, 95% CI 0.05-0.17).

CONCLUSIONS

Depression was associated with enhanced positive implicit associations with others, and reduced positive learning about the self, culminating in reduced self-favouring biases. However, when self, emotion and reward processing occurred independently there was little evidence of an association with depression. Treatments targeting reduced positive self-biases may provide more sensitive targets for therapeutic intervention and potential biomarkers of treatment responses, allowing the development of more effective interventions.

Temporal multi-step predictive modeling of remission in major depressive disorder using early stage treatment data; STAR*D based machine learning approach

BACKGROUND

Artificial intelligence is currently being used to facilitate early disease detection, better understand disease progression, optimize medication/treatment dosages, and uncover promising novel treatments and potential outcomes.

METHODS

Utilizing the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, we built a machine learning model to predict depression remission rates using same clinical data as features for each of the first three antidepressant treatment steps in STAR*D. We only used early treatment data (baseline and first follow up) in each STAR*D step to temporally analyze predictive features of remission at the end of the step.

RESULTS

Our model showed significant prediction performance across the three treatment steps, At step 1, Model accuracy was 66 %; sensitivity-65 %, specificity-67 %, positive predictive value (PPV)-65.5 %, and negative predictive value (NPV)-66.6 %. At step 2, model accuracy was 71.3 %, sensitivity-74.3 %, specificity-69 %, PPV-64.5 %, and NPV-77.9 %. At step 3, accuracy reached 84.6 %; sensitivity-69 %, specificity-88.8 %, PPV-67 %, and NPV-91.1 %. Across all three steps, the early Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) scores were key elements in predicting the final treatment outcome. The model also identified key sociodemographic factors that predicted treatment remission at different steps.

LIMITATIONS

The retrospective design, lack of replication in an independent dataset, and the use of "a complete case analysis" model in our analysis.

CONCLUSIONS

This proof-of-concept study showed that using early treatment data, multi-step temporal prediction of depressive symptom remission results in clinically useful accuracy rates. Whether these predictive models are generalizable deserves further study.

Systematic review and meta-analysis of augmentation and combination treatments for early-stage treatment-resistant depression

BACKGROUND

Major depressive disorder (MDD) is a highly burdensome health condition, for which there are numerous accepted pharmacological and psychological interventions. Adjunctive treatment (augmentation/combination) is recommended for the ~50% of MDD patients who do not adequately respond to first-line treatment. We aimed to evaluate the current evidence for concomitant approaches for people with early-stage treatment-resistant depression (TRD; defined below).

METHODS

We systematically searched Medline and Institute for Scientific Information Web of Science to identify randomised controlled trials of adjunctive treatment of ⩾10 adults with MDD who had not responded to ⩾1 adequate antidepressant. The cochrane risk of bias (RoB) tool was used to assess study quality. Pre-post treatment meta-analyses were performed, allowing for comparison across heterogeneous study designs independent of comparator interventions.

RESULTS

In total, 115 trials investigating 48 treatments were synthesised. The mean intervention duration was 9 weeks (range 5 days to 18 months) with most studies assessed to have low (n = 57) or moderate (n = 51) RoB. The highest effect sizes (ESs) were from cognitive behavioural therapy (ES = 1.58, 95% confidence interval (CI): 1.09-2.07), (es)ketamine (ES = 1.48, 95% CI: 1.23-1.73) and risperidone (ES = 1.42, 95% CI: 1.29-1.61). Only aripiprazole and lithium were examined in ⩾10 studies. Pill placebo (ES = 0.89, 95% CI: 0.81-0.98) had a not inconsiderable ES, and only six treatments' 95% CIs did not overlap with pill placebo's (aripiprazole, (es)ketamine, mirtazapine, olanzapine, quetiapine and risperidone). We report marked heterogeneity between studies for almost all analyses.

CONCLUSIONS

Our findings support cautious optimism for several augmentation strategies; although considering the high prevalence of TRD, evidence remains inadequate for each treatment option.

Symptoms that remain after depression treatment in patients with coronary heart disease

OBJECTIVE

Symptoms which commonly remain after treatment for major depression increase the risk of relapse and recurrence in medically well patients. The same symptoms predict major adverse cardiac events in observational studies of patients with coronary heart disease (CHD). The purpose of this study was to determine the prevalence and predictors of residual depression symptoms in depressed patients with CHD-.

METHODS

Beck Depression Inventory-II data from two randomized clinical trials and an uncontrolled treatment study of depression in patients with CHD were combined to determine the prevalence and predictors of residual symptoms.

RESULTS

Loss of energy, loss of pleasure, loss of interest, fatigue, and difficulty concentrating were the five most common residual symptoms in all three studies. They are also among the most common residual symptoms in medically well patients who are treated for depression. The severity of pre-treatment anxiety predicted the post-treatment persistence of all these symptoms except for loss of energy.

CONCLUSIONS

The most common post-treatment residual symptoms found in this study of patients with coronary heart disease and comorbid major depression are the same as those that have been reported in previous studies of medically-well depressed patients. This suggests that they may be resistant to standard depression treatments across diverse patient populations. More effective treatments for these symptoms are needed.

Increasing Adiponectin Signaling by Sub-Chronic AdipoRon Treatment Elicits Antidepressant- and Anxiolytic-Like Effects Independent of Changes in Hippocampal Plasticity

(1) Background: Adiponectin is an adipocyte-secreted hormone that has antidepressant- and anxiolytic-like effects in preclinical studies. Here, we investigated the antidepressant- and anxiolytic-like effects of sub-chronic treatment with AdipoRon, an adiponectin receptor agonist, and its potential linkage to changes in hippocampal adult neurogenesis and synaptic plasticity. (2) Methods: Different cohorts of wild-type C57BL/6J and CamKIIα-Cre male mice were treated with sub-chronic (7 days) AdipoRon, followed by behavioral, molecular, and electrophysiological experiments. (3) Results: 7-day AdipoRon treatment elicited antidepressant- and anxiolytic-like effects but did not affect hippocampal neurogenesis. AdipoRon treatment reduced hippocampal brain-derived neurotrophic factor (BDNF) levels, neuronal activation in the ventral dentate gyrus, and long-term potentiation of the perforant path. The knockdown of N-methyl-D-aspartate (NMDA) receptor subunits GluN2A and GluN2B in the ventral hippocampus did not affect the antidepressant- and anxiolytic-like effects of AdipoRon. (4) Conclusions: Increasing adiponectin signaling through sub-chronic AdipoRon treatment results in antidepressant- and anxiolytic-like effects independent of changes in hippocampal structural and synaptic function.

Typical disease courses of patients with unipolar depressive disorder after in-patient treatments-results of a cluster analysis of the INDDEP project

Introduction

Previously established categories for the classification of disease courses of unipolar depressive disorder (relapse, remission, recovery, recurrence) are helpful, but insufficient in describing the naturalistic disease courses over time. The intention of the present study was to identify frequent disease courses of depression by means of a cluster analysis.

Methods

For the longitudinal cluster analysis, 555 datasets of patients who participated in the INDDEP (INpatient and Day clinic treatment of DEPression) study, were used. The present study uses data of patients with at least moderate depressive symptoms (major depression) over a follow-up period of 1 year after their in-patient or day-care treatments using the LIFE (Longitudinal Interval Follow-Up Evaluation)-interview. Eight German psychosomatic hospitals participated in this naturalistic observational study.

Results

Considering only the Calinski-Harabatz index, a 2-cluster solution gives the best statistical results. In combination with other indices and clinical interpretations, the 5-cluster solution seems to be the most interesting. The cluster sizes are large enough and numerically balanced. The KML-cluster analyses revealed five well interpretable disease course clusters over the follow-up period: "sustained treatment response" (N = 202, 36.4% of the patients), "recurrence" (N = 80, 14.4%), "persisting relapse" (N = 115, 20.7%), "temporary relapse" (N = 95, 17.1%), and remission (N = 63, 11.4%).

Conclusion

The disease courses of many patients diagnosed with a unipolar depression do not match with the historically developed categories such as relapse, remission, and recovery. Given this context, the introduction of disease course trajectories seems helpful. These findings may promote the implementation of new therapy options, adapted to the disease courses.

Predicting relapse from the time to remission during the acute treatment of depression: A re-analysis of the STAR*D data

BACKGROUND

Predicting relapse during maintenance treatment for depression is challenging. The objective of this analysis was to investigate the association between the time taken to achieve remission in the acute phase, and the subsequent relapse rate or time to relapse using the Sequenced Treatment Alternatives to Relieve Depression dataset.

METHOD

Data of 1296 outpatients with nonpsychotic depression who entered a 12-month naturalistic follow-up period after achieving remission with citalopram for up to 14 weeks were analyzed. One-way analysis of variance and the Jonckheere-Terpstra trend test were performed to compare the relapse rates and days to relapse during the follow-up period among those who achieved remission at weeks 2, 4, 6, 9, 12, and 14. Remission and relapse were defined as scores of ≤5 and ≥11, respectively, on the 16-Item Quick Inventory of Depressive Symptomatology and Self-Report.

RESULTS

The relapse rates were significantly different among those who achieved remission each week (F_{(5, 1087)} = 4.995, p < 0.001). The lowest and highest relapse rates were observed in those who achieved remission at weeks 4 (25.7 %) and 12 (42.4 %), respectively, with a significant difference (p = 0.006). There was also a significant negative trend between the weeks taken to achieve remission and the days to relapse (z = -6.13, p < 0.001).

CONCLUSIONS

Patients with depression who show a faster response to antidepressant treatment are more likely to maintain remission in the long term. This finding suggests that, to prevent relapse, close attention should be paid to patients who require a relatively long time to achieve remission.

Predicting treatment outcome in depression: an introduction into current concepts and challenges

Improving response and remission rates in major depressive disorder (MDD) remains an important challenge. Matching patients to the treatment they will most likely respond to should be the ultimate goal. Even though numerous studies have investigated patient-specific indicators of treatment efficacy, no (bio)markers or empirical tests for use in clinical practice have resulted as of now. Therefore, clinical decisions regarding the treatment of MDD still have to be made on the basis of questionnaire- or interview-based assessments and general guidelines without the support of a (laboratory) test. We conducted a narrative review of current approaches to characterize and predict outcome to pharmacological treatments in MDD. We particularly focused on findings from newer computational studies using machine learning and on the resulting implementation into clinical decision support systems. The main issues seem to rest upon the unavailability of robust predictive variables and the lacking application of empirical findings and predictive models in clinical practice. We outline several challenges that need to be tackled on different stages of the translational process, from current concepts and definitions to generalizable prediction models and their successful implementation into digital support systems. By bridging the addressed gaps in translational psychiatric research, advances in data quantity and new technologies may enable the next steps toward precision psychiatry.

Early Response to Antidepressant Medications in Adults With Major Depressive Disorder: A Naturalistic Study and Odds of Remission at 14 Weeks

PURPOSE/BACKGROUND

Early response after 2 to 4 weeks of antidepressant therapy has been shown to predict remission by 8 to 12 weeks. Most of the work to date on early response has been done using data from randomized controlled trials.

METHODS/PROCEDURES

This naturalistic study uses archival data from a national tele-mental health company. The positive and negative predictive values as well as sensitivity and specificity were calculated using different drops in baseline Patient Health Questionnaire 9 scores at various periods. Demographic and clinical characteristics were compared between early responders versus those lacking early response. Binary logistic regression analyses determined if early response was predictive of remission, response, and greater than minimal improvement at 14 weeks. For those who do not show early improvement, treatments were investigated using binary logistic regression to see if changes predicted later outcomes.

FINDINGS/RESULTS

Positive predictive values for all endpoints improved with the strength of early response but did not improve much with the time allowed for that response to occur. In contrast, negative predictive values increased substantially with time. Using a definition of 30% drop in Patient Health Questionnaire 9 score at week 4, 56.5% of patients were early responders. Early responders were ~3.2 times more likely to achieve remission than those lacking early response. Of nonresponders by week 4, those prescribed atypical antipsychotics (+SSRI) had significantly reduced odds of response at week 14, whereas those prescribed a norepinephrine and dopamine reuptake inhibitor had increased odds.

IMPLICATIONS/CONCLUSIONS

Early response may be associated with better outcomes at 14 weeks. In those with lack of response by week 4, patients prescribed a norepinephrine and dopamine reuptake inhibitor may achieve superior outcomes.

TCA and SSRI Antidepressants Exert Selection Pressure for Efflux-Dependent Antibiotic Resistance Mechanisms in Escherichia coli

Microbial diversity is reduced in the gut microbiota of animals and humans treated with selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs). The mechanisms driving the changes in microbial composition, while largely unknown, is critical to understand considering that the gut microbiota plays important roles in drug metabolism and brain function. Using Escherichia coli, we show that the SSRI fluoxetine and the TCA amitriptyline exert strong selection pressure for enhanced efflux activity of the AcrAB-TolC pump, a member of the resistance-nodulation-cell division (RND) superfamily of transporters. Sequencing spontaneous fluoxetine- and amitriptyline-resistant mutants revealed mutations in marR and lon, negative regulators of AcrAB-TolC expression. In line with the broad specificity of AcrAB-TolC pumps these mutants conferred resistance to several classes of antibiotics. We show that the converse also occurs, as spontaneous chloramphenicol-resistant mutants displayed cross-resistance to SSRIs and TCAs. Chemical-genomic screens identified deletions in marR and lon, confirming the results observed for the spontaneous resistant mutants. In addition, deletions in 35 genes with no known role in drug resistance were identified that conferred cross-resistance to antibiotics and several displayed enhanced efflux activities. These results indicate that combinations of specific antidepressants and antibiotics may have important effects when both are used simultaneously or successively as they can impose selection for common mechanisms of resistance. Our work suggests that selection for enhanced efflux activities is an important factor to consider in understanding the microbial diversity changes associated with antidepressant treatments. IMPORTANCE Antidepressants are prescribed broadly for psychiatric conditions to alter neuronal levels of synaptic neurotransmitters such as serotonin and norepinephrine. Two categories of antidepressants are selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs); both are among the most prescribed drugs in the United States. While it is well-established that antidepressants inhibit reuptake of neurotransmitters there is evidence that they also impact microbial diversity in the gastrointestinal tract. However, the mechanisms and therefore biological and clinical effects remain obscure. We demonstrate antidepressants may influence microbial diversity through strong selection for mutant bacteria with increased AcrAB-TolC activity, an efflux pump that removes antibiotics from cells. Furthermore, we identify a new group of genes that contribute to cross-resistance between antidepressants and antibiotics, several act by regulating efflux activity, underscoring overlapping mechanisms. Overall, this work provides new insights into bacterial responses to antidepressants important for understanding antidepressant treatment effects.

Sex differences on the response to antidepressants and psychobiotics following early life stress in rats

Major depressive disorder (MDD) is the most prevalent mood disorder globally. Most antidepressants available for the treatment of MDD increase the concentration of monoamines in the synaptic cleft. However, such drugs have a high latency time to obtain benefits. Thus, new antidepressants with fast action and robust efficacy are very important. This study evaluated the effects of escitalopram, ketamine, and probiotic Bifidobacterium infantis in rats submitted to the maternal deprivation (MD). MD rats received saline, escitalopram, ketamine, or probiotic for 10, 30, or 50 days, depending on the postnatal day (PND):21, 41, and 61. Following behavior, this study examined the integrity of the blood-brain barrier (BBB) and oxidative stress markers. MD induced depressive-like behavior in females with PND21 and males with PND61. All treatments reversed depressive-like behavior in females and escitalopram and ketamine in males. MD induced an increase in the permeability of the BBB, an imbalance between oxidative stress and antioxidant defenses. Treatments regulated the oxidative damage and the integrity of the BBB induced by MD. The treatment with escitalopram, ketamine, or probiotics may prevent behavioral and neurochemical changes associated with MDD, depending on the developmental period and gender.

Suicidal ideation in remitted major depressive disorder predicts recurrence

INTRODUCTION

Each year almost 800.000 people die from suicide, of which up to 87% are affected by major depressive disorder (MDD). Despite the strong association between suicidality and MDD, it remains unknown if suicidal symptoms during remission put remitted recurrent MDD patients (rrMDD) at risk for recurrence.

METHODS

At baseline we compared sociodemographic characteristics and suicidal symptoms in un-medicated rrMDD participants to matched never-depressed controls. We used the HDRS₁₇ and IDS-SR₃₀ to assess suicidal symptoms and depressive symptomatology. Next, we studied the longitudinal association between baseline suicidal symptoms and time to recurrence(s) in rrMDD during a 2.5-year follow-up period using cox regression analyses. Further, we studied with longitudinal data whether suicidal symptoms and depressive symptomatology were cross-sectionally associated using mixed model analysis.

RESULTS

At baseline, rrMDD participants (N = 73) had higher self-reported suicidal symptoms than matched never-depressed controls (N = 45) (χ² = 12.09 p < .002). Self-reported suicidal symptoms were almost four times higher (27.9% versus 6.9%) compared to clinician-rated suicidal symptoms in rrMDD at baseline. Self-reported baseline suicidal symptoms, but not clinician-rated symptoms, predicted earlier MDD-recurrence during follow-up, independent of other residual depressive symptoms (χ² = 7.26, p < .026). Higher suicidal symptoms were longitudinally related to higher depressive symptoms (HDRS₁₇; F = 49.87, p < .001), IDS-SR₃₀; (F = 22.36, p < .001).

CONCLUSION

This study showed that self-reported - but not clinician-rated - suicidal symptoms persist during remission in rrMDD and predict recurrence, independent from residual symptoms. We recommend to monitor both suicidal and depressive symptomatology during remission in rrMDD, preferably also including self-reported questionnaires apart from clinician-rated. It would be beneficial for future research to assess suicidality using questionnaires primarily designed for measuring suicidal ideation.

C-Reactive protein concentrations in reproductive-aged women with major mood disorders

To examine associations between high sensitivity C-reactive protein (CRP) concentrations and depressive symptoms in reproductive-aged women with mood disorders. Women (N = 86) with major depressive or bipolar disorder in a specialized mood disorders program provided plasma samples which were analyzed for CRP concentrations and categorized by tertiles (T1, low; T2, middle; T3 high). Depressive symptoms were assessed with the Inventory of Depressive Symptoms. We hypothesized that CRP concentrations would be significantly associated with the following: (1) depressive symptoms; (2) pregnancy, (3) body mass index, and (4) counts of white blood cells and absolute neutrophils and percentage of segmented neutrophils. The distribution of CRP concentrations was highly skewed with a median of 2.45 mg/L and an interquartile range 0.90 - 8.17 mg/L. Elevated plasma levels of CRP were not associated with depressive symptoms, which did not differ by tertile group either before or after adjusting for BMI, pregnancy status, and their interactions. Women in T3 had 5 times greater odds of pregnancy compared to women in T1 (p = .021). However, women in T2 had 11% greater BMI on average (p = 0.023), and women in T3 had 47% greater BMI compared to those in T1 (p < 0.001). Women in T3 had higher mean white blood cell counts than those in T1 and T2, the percentage of neutrophils was higher in T2 and T3 compared to T1, and women in T3 had higher absolute neutrophil counts compared to T1. CRP concentrations varied widely and were significantly elevated in reproductive-aged women with high BMI and current pregnancy, but not with depressive symptoms in this sample of depressed women.

Efficacy and acceptability of next step treatment strategies in adults with treatment-resistant major depressive disorder: protocol for systematic review and network meta-analysis

INTRODUCTION

For major depression, a one-size-fits-all treatment does not exist. Patients enter a 'trial-and-change' algorithm in which effective therapies are subsequently applied. Unfortunately, an empirically based order of treatments has not yet been determined. There is a magnitude of different treatment strategies while clinical trials only compare a small number of these. Network meta-analyses (NMA) might offer a solution, but so far have been limited in scope and did not account for possible differences in population characteristics that arise with increasing levels of treatment-resistance, potentially violating the transitivity assumption. We; therefore, present a protocol for a systematic review and NMA aiming at summarising and ranking treatments for treatment-resistant depression (TRD) while covering a broad range of therapeutic options and accounting for possible differences in population characteristics at increasing levels of treatment-resistance.

METHODS AND ANALYSIS

Randomised controlled trials will be included that compared next-step pharmacological, neuromodulation or psychological treatments for treatment-resistant depression (TRD; ie, failure to respond to ≥1 adequate antidepressant drug trial(s) in the current episode) to each other or to a control condition. Primary outcomes will be the proportion of patients who responded to (efficacy) and dropped out of (acceptability) the allocated treatment. A random effects NMA will be conducted, synthesising the evidence for each outcome and determining the differential efficacy of treatments. Heterogeneity in treatment nodes will be reduced by considering alternative geometries of the network structure and by conducting a meta-regression examining different levels of TRD. Local and global methods will be applied to evaluate consistency. The Cochrane Risk of Bias 2 tool, Confidence in Network Meta-Analysis and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework will be used to assess risk of bias and certainty.

ETHICS AND DISSEMINATION

This review does not require ethical approval.

Lipid Biomarkers in Depression: Does Antidepressant Therapy Have an Impact?

Studies have revealed mixed results on how antidepressant drugs affect lipid profiles of patients with major depression disorder (MDD). Even less is known about how patients respond to a switch of antidepressant medication with respect to their metabolic profile. For this, effects of a switch in antidepressants medication on lipid markers were studied in MDD patients. 15 participants (females = 86.67%; males = 13.33%; age: 49.45 ± 7.45 years) with MDD and a prescribed switch in their antidepressant medication were recruited at a psychosomatic rehabilitation clinic. Participants were characterized (with questionnaires and blood samples) at admission to the rehabilitation clinic (baseline, T0) and followed up with a blood sample two weeks (T1) later. HDL, LDL, total cholesterol, and triglycerides were determined (T0), and their change analyzed (Wilcoxon test) at follow up (T1). Decrements in HDL (p = 0.041), LDL (p < 0.001), and total cholesterol (p < 0.001) were observed two weeks after a switch in antidepressant medication. Triglycerides showed no difference (p = 0.699). Overall, LDL, HDL, and total cholesterol are affected by a change in antidepressant drugs in patients with MDD. These observations are of clinical relevance for medical practitioners in the planning and management of treatment strategies for MDD patients.

A Glimpse Into the Sexual Dimorphisms in Major Depressive Disorder Through Epigenetic Studies

Depression is an umbrella term used to describe a mood disorder with a broad spectrum of symptoms including a persistent feeling of sadness, loss of interest, and deficits in social behavior. Epigenetic research bridges the environmental and genetic landscape and has the potential to exponentially improve our understanding of such a complex disorder. Depression is also a sexually dimorphic disorder and variations exist within epigenetic modification sites between sexes. These sex-specific mediators may impact behavioral symptomology and could serve as therapeutic targets for treatments to improve behavioral deficits. This mini review will focus on the social behavior perspective of depression and specifically explore the sexually different epigenetic modifications on depression.

Antidepressant effects of curcumin-coated iron oxide nanoparticles in a rat model of depression

The antidepressant effect of curcumin-coated iron oxide nanoparticles (Cur-IONPs) was investigated in the current study using depression rat model induced by reserpine. IONPs were synthesized by curcumin as a reducing agent producing Cur-IONPs. Rats were divided into control, depression rat model, and depressed rats treated with Cur-IONPs. After treatment rat behavior was evaluated using forced swimming test (FST). Serotonin (5-HT), norepinephrine (NE), dopamine (DA), monoamine oxidase (MAO), acetylcholinesterase (AchE), Na+, K+, ATPase, lipid peroxidation (MDA), reduced glutathione (GSH), glutathione-s-transferase (GST) and nitric oxide (NO) were measured in the cortex and hippocampus. In depressed rats, FST showed increased immobilization time and reduced swimming time. This was associated with a significant decrease in 5-HT, NE, DA and GSH and a significant increase in MDA and NO levels and GST, MAO, AchE and Na+, K+, ATPase activities in the cortex and hippocampus. Treatment with Cur-NONPs for two weeks increased the swimming time reduced the immobility time, and elevated 5-HT, NE and DA levels. Cur-IONPs attenuated the oxidative stress induced by reserpine and restored the MAO, AchE and Na+, K+, ATPase. The present green method used curcumin in the IONPs synthesis and has several merits; obtaining nanoform of iron oxide, increasing the bioavailability of curcumin and reducing the oxidative stress induced by iron. The present antidepressant effect of Cur-IONPs could be attributed to the ability of Cur-IONPs to restore monoamine neurotransmitter levels by increasing their synthesis and reducing their metabolism. In addition, the antioxidant activity of curcumin prevented oxidative stress in the depressed rats.

2-Phenyl-3-(phenylselanyl)benzofuran elicits acute antidepressant-like action in male Swiss mice mediated by modulation of the dopaminergic system and reveals therapeutic efficacy in both sexes

RATIONALE

Depression is a psychiatric disorder that constitutes one of the leading causes of disability worldwide. 2-Phenyl-3-(phenylselanyl)benzofuran (SeBZF1) has been studied as a potential antidepressant drug, but its pharmacological action needs more investigation.

OBJECTIVES AND METHODS

Our aim was to extend information about the antidepressant-like action of SeBZF1 using the mouse tail suspension test (TST). Initial experiments investigated the mechanisms involved in the acute antidepressant-like action of SeBZF1 in male Swiss mice. For this purpose, males received noradrenergic or dopaminergic receptor antagonists before acute SeBZF1 administration (50 mg/kg, per oral). In parallel, effects of combined treatment with SeBZF1 and bupropion at sub-effective doses (1 and 3 mg/kg, respectively) were tested. The next experiments were designed to determine the acute effects of SeBZF1 in females through a dose-response curve (5-50 mg/kg). Lastly, the efficacy of a 7-day repeated treatment with SeBZF1 (1 and 5 mg/kg) in mice of both sexes and its safety were evaluated. TST and the open-field test (OFT) were employed in all behavioral experiments.

RESULTS

Pre-administration of dopaminergic antagonists (SCH23390, a selective D₁R antagonist; sulpiride, a selective D₂/D₃R antagonist; and haloperidol, a non-selective antagonist), but not of adrenergic α₁, α₂, and β-R antagonists, blocked the acute antidepressant-like effects of SeBZF1 in males. Co-administration of sub-effective doses of SeBZF1 and bupropion reduced the depressive phenotype. In addition, acute treatment with SeBZF1 at 50 mg/kg produced a reduction of female immobility. Finally, repeated treatment with SeBZF1 (1 and 5 mg/kg) was effective in causing antidepressant-like effects in both sexes. Locomotor activity, plasma transaminases, and urea levels remained unaltered after SeBZF1 exposure.

CONCLUSION

Our findings provide evidence of the involvement of the dopaminergic system in the acutely antidepressant-like action of SeBZF1 in male mice and reveal the compound efficacy when acute or repeatedly administered in both sexes.

Acute Diallyl Disulfide Administration Prevents and Reveres Lipopolysaccharide-Induced Depression-Like Behaviors in Mice via Regulating Neuroinflammation and Oxido-Nitrosative Stress

Neuroinflammation and oxidative stress play critical roles in pathogenesis of depression. Diallyl disulfide (DADS), an active compound in garlic oil, has been shown to exhibit obvious anti-inflammatory and anti-oxidative activities. Preliminary evidence indicates that depression is associated with high levels of pro-inflammatory cytokines and oxidative markers, suggesting that inhibition of neuroinflammatory response and oxidative stress may be beneficial for depression interruption. Here, we investigated the antidepressant effect of DADS as well as it mechanisms in a depression-like model induced by lipopolysaccharide (LPS). Similarly to imipramine (10 mg/kg), a clinical antidepressant, DADS (40 or 80 mg/kg), which was administered 1 h before LPS treatment (pre-LPS) or 1.5 h and 23.5 h after LPS treatment (post-LPS), prevented and reversed LPS (100 μg/kg)-induced increase in immobility time in the tail suspension test (TST) and forced swim test (FST) in mice. Mechanistic studies revealed that DADS pre-treatment or post-treatment at the dose of 40 and 80 mg/kg prevented and reversed (i) LPS-induced increases in interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and nitric oxide (NO) levels in the hippocampus and prefrontal cortex, (ii) LPS-induced increases in contents of malondialdehyde (MDA), a parameter reflecting high levels of oxidative stress, and (iii) LPS-induced decreases in contents of GSH, a marker reflecting weakened anti-oxidative ability, in the hippocampus and prefrontal cortex in mice. These results indicate that DADS is comparable to imipramine in effectively ameliorating LPS-induced depression-like behaviors in mice, providing a potential value for DADS in prevention and/or therapy of depression.

Prediction of short-term antidepressant response using probabilistic graphical models with replication across multiple drugs and treatment settings

Heterogeneity in the clinical presentation of major depressive disorder and response to antidepressants limits clinicians' ability to accurately predict a specific patient's eventual response to therapy. Validated depressive symptom profiles may be an important tool for identifying poor outcomes early in the course of treatment. To derive these symptom profiles, we first examined data from 947 depressed subjects treated with selective serotonin reuptake inhibitors (SSRIs) to delineate the heterogeneity of antidepressant response using probabilistic graphical models (PGMs). We then used unsupervised machine learning to identify specific depressive symptoms and thresholds of improvement that were predictive of antidepressant response by 4 weeks for a patient to achieve remission, response, or nonresponse by 8 weeks. Four depressive symptoms (depressed mood, guilt feelings and delusion, work and activities and psychic anxiety) and specific thresholds of change in each at 4 weeks predicted eventual outcome at 8 weeks to SSRI therapy with an average accuracy of 77% (p = 5.5E-08). The same four symptoms and prognostic thresholds derived from patients treated with SSRIs correctly predicted outcomes in 72% (p = 1.25E-05) of 1996 patients treated with other antidepressants in both inpatient and outpatient settings in independent publicly-available datasets. These predictive accuracies were higher than the accuracy of 53% for predicting SSRI response achieved using approaches that (i) incorporated only baseline clinical and sociodemographic factors, or (ii) used 4-week nonresponse status to predict likely outcomes at 8 weeks. The present findings suggest that PGMs providing interpretable predictions have the potential to enhance clinical treatment of depression and reduce the time burden associated with trials of ineffective antidepressants. Prospective trials examining this approach are forthcoming.

Neuroinflammation induces anxiety- and depressive-like behavior by modulating neuronal plasticity in the basolateral amygdala

Increasing evidence indicates that excessive inflammatory responses play a crucial role in the pathophysiology of psychiatric diseases, including depression and anxiety disorders. The dysfunctional neural plasticity in amygdala has long been proposed as the vital cause for the progression of psychiatric disorders. However, the effect of neuroinflammation on the functional changes of the amygdala remains largely unknown. Here, by using a mouse model of inflammation induced by lipopolysaccharide (LPS) injection, we investigated the effect of LPS-induced neuroinflammation on the synaptic and non-synaptic plasticity in basolateral amygdala (BLA) projection neurons (PNs) and their contribution to the LPS-induced anxiety- and depressive-like behavior. The results showed that LPS treatment led to the activation of microglia and production of proinflammatory cytokines in the BLA. Furthermore, LPS treatment increased excitatory but not inhibitory synaptic transmission due to the enhanced presynaptic glutamate release, thus leading to the shift of excitatory/inhibitory balance towards excitatory. In addition, the intrinsic neuronal excitability of BLA PNs was also increased by LPS treatment through the loss of expression and function of small-conductance, calcium-activated potassium channel. Chronic fluoxetine pretreatment significantly prevented these neurophysiological changes induced by LPS, and alleviated anxiety and depressive-like behavior, indicating that LPS-induced neuronal dysregulation of BLA PNs may contribute to the development of psychiatry disorders. Collectively, these findings provide evidence that dysregulation of synaptic and non-synaptic transmission in the BLA PNs may account for neuroinflammation-induced anxiety- and depressive-like behavior.

Risk of mortality associated with concomitant antidepressant and benzodiazepine therapy among patients with depression: a population-based cohort study

BACKGROUND

With antidepressants (ADs) having minimal therapeutic effects during the initial weeks of treatment, benzodiazepines (BZDs) are concomitantly used to alleviate depressive symptoms of insomnia or anxiety. However, with mortality risks associated with this concomitant use yet to be examined, it remains unclear as to whether this concomitant therapy offers any benefits in treating depression.

METHODS

We conducted a population-based cohort study using South Korea's nationwide healthcare database from 2002 to 2017. Of 2.6 million patients with depression, we identified 612,729 patients with incident depression and newly prescribed ADs or BZDs, by excluding those with a record of diagnosis or prescription within the 2 years prior to their incident diagnosis. We classified our study cohort into two discrete groups depending on the type of AD treatment received within 6 months of incident diagnosis-AD monotherapy and AD plus BZD (AD+BZD) therapy. We matched our study cohort in a 1:1 ratio using propensity scores to balance baseline characteristics and obtain comparability among groups. The primary outcome was all-cause mortality, and patients were followed until the earliest of outcome occurrence or end of the study period. We conducted multivariable Cox proportional hazards regression analysis to estimate adjusted hazards ratios (HRs) with 95% confidence intervals (CIs) for the risk of mortality associated with AD+BZD therapy versus AD monotherapy.

RESULTS

The propensity score-matched cohort had 519,780 patients with 259,890 patients in each group, where all baseline characteristics were well-balanced between the two groups. Compared to AD monotherapy, AD+BZD therapy was associated with an increased risk of all-cause mortality (adjusted HR, 1.04; 95% CI, 1.02 to 1.06).

CONCLUSIONS

Concomitantly initiating BZDs with ADs was associated with a moderately increased risk of mortality. Clinicians should therefore exercise caution when deciding to co-prescribe BZDs with ADs in treating depression, as associated risks were observed.

Using prefrontal and midline right frontal EEG-derived theta cordance and depressive symptoms to predict the differential response or remission to antidepressant treatment in major depressive disorder

There is a growing need for optimizing treatment selection and response prediction in individuals with major depressive disorder (MDD). Prior investigations have shown that changes in electroencephalographic (EEG)-based measures precede symptom improvement and could serve as biomarkers of treatment outcome. One such method is cordance, a computation of regional brain activity based on a combination of absolute and relative resting EEG activity. Specifically, early reduction in prefrontal (PF) and midline right frontal (MRF) theta (4-8Hz) cordance has been shown to predict response to various antidepressants, though replication is required. Thus, this study examined early changes (baseline to week 1) in PF and MRF cordance in 47 MDD patients undergoing antidepressant treatment. Early changes in cordance and in Montgomery Åsberg Depression Rating Scale (MADRS) scores were assessed alone, and in combination, to predict eventual (by week 12) treatment response and remission. Models combining early changes in theta cordance (PF and MRF) and depressive symptoms were most predictive of response to treatment at week 12; remission models (cordance, MADRS, and their combination) were weaker, though provided modest prediction values. These results suggest that antidepressant response may be optimally predicted by combining both EEG and symptom-based measures after one week of treatment.

Genetic Markers for Later Remission in Response to Early Improvement of Antidepressants

Planning subsequent treatment strategies based on early responses rather than waiting for delayed antidepressant action can be helpful. We identified genetic markers for later non-remission in patients exhibiting poor early improvement using whole-exome sequencing data of depressive patients treated in a naturalistic manner. Among 1000 patients, early improvement at 2 weeks (reduction in Hamilton Depression Rating Scale [HAM-D] score ≥ 20%) and remission at 12 weeks (HAM-D score ≤ 7) were evaluated. Gene- and variant-level analyses were conducted to compare patients who did not exhibit early improvement and did not eventually achieve remission (n = 126) with those who exhibited early improvement and achieved remission (n = 385). Genes predicting final non-remission in patients who exhibited poor early improvement (COMT, PRNP, BRPF3, SLC25A40, and CGREF1 in males; PPFIBPI, LZTS3, MEPCE, MAP1A, and PFAS in females; ST3GAL5 in the total population) were determined. Among the significant genes, variants in the PRNP (rs1800014), COMT (rs6267), BRPF3 (rs200565609), and SLC25A40 genes (rs3213633) were identified. However, interpretations should be made cautiously, as complex pharmacotherapy involves various genes and pathways. Early detection of poor early improvement and final non-remission based on genetic risk would be helpful for decision-making in a clinical setting.

The Psychopharmacology Algorithm Project at the Harvard South Shore Program: An Update on Unipolar Nonpsychotic Depression

BACKGROUND

The Psychopharmacology Algorithm Project at the Harvard South Shore Program presents evidence-based recommendations considering efficacy, tolerability, safety, and cost. Two previous algorithms for unipolar nonpsychotic depression were published in 1993 and 1998. New studies over the last 20 years suggest that another update is needed.

METHODS

The references reviewed for the previous algorithms were reevaluated, and a new literature search was conducted to identify studies that would either support or alter the previous recommendations. Other guidelines and algorithms were consulted. We considered exceptions to the main algorithm, as for pregnant women and patients with anxious distress, mixed features, or common medical and psychiatric comorbidities.

SUMMARY

For inpatients with severe melancholic depression and acute safety concerns, electroconvulsive therapy (or ketamine if ECT refused or ineffective) may be the first-line treatment. In the absence of an urgent indication, we recommend trialing venlafaxine, mirtazapine, or a tricyclic antidepressant. These may be augmented if necessary with lithium or T3 (triiodothyronine). For inpatients with non-melancholic depression and most depressed outpatients, sertraline, escitalopram, and bupropion are reasonable first choices. If no response, the prescriber (in collaboration with the patient) has many choices for the second trial in this algorithm because there is no clear preference based on evidence, and there are many individual patient considerations to take into account. If no response to the second medication trial, the patient is considered to have a medication treatment-resistant depression. If the patient meets criteria for the atypical features specifier, a monoamine oxidase inhibitor could be considered. If not, reconsider (for the third trial) some of the same options suggested for the second trial. Some other choices can also considered at this stage. If the patient has comorbidities such as chronic pain, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, or posttraumatic stress disorder, the depression could be secondary; evidence-based treatments for those disorders would then be recommended.

Relationship of Major Depression with Body Mass Index and Salivary Cortisol

Introduction Depression is one of the most incapacitating psychiatric diseases that disturb life of millions of people round the globe. Its major causes include stressful life events, bereavement, social abuses or certain biological and genetic factors with complex causal mechanisms. Higher salivary cortisol levels for a long period lead to dyslipidemias which increase body mass index (BMI), elevate adiposity and waist-to-hip ratio (WHR). Such individuals with high quartiles of BMI have considerably higher risk of major depressive disorder. The aim of this study was to establish a correlation between major depression, BMI and salivary cortisol. Methods This cross-sectional analysis was accomplished in the Physiology Department, Sheikh Zayed Federal Postgraduate Medical Institute, Lahore as well as in Punjab Institute of Mental Health, Lahore, Pakistan, over a period of six months. A total of 60 participants aged between 18 and 60 years were included in this study; they were divided equally into two groups as normal healthy individuals with no physical or mental illness and severely depressed groups. The patients were categorized as cases of severe depression on outdoor clinical assessment and further confirmed by ICD-10. Patient's BMI was estimated by measuring height in meters (m) and weight in kilograms (kg), and then dividing weight with square height. Early morning saliva samples were collected. Estimation of cortisol levels in saliva was done through ELISA. SPSS version 20.0 (IBM Corp., Armonk, NY) was used to analyze the data and p ≤ 0.05 was considered statistically significant. Results The mean BMI in normal healthy group was 22.02 ± 4.21, while the mean BMI in severely depressive group was 24.64 ± 3.58. The difference was statistically significant (p = 0.012). The mean salivary cortisol level was significantly raised in patients with major depression (2.23 ± 1.69 nmol/L) in contrast to healthy normal individuals (1.46 ± 0.91 nmol/L), with p-value = 0.031. Conclusion BMI and depression has a very noteworthy correlation and there is a remarkable link between raised salivary cortisol, greater BMI and development of major depression.

AP-1 controls the p11-dependent antidepressant response

Selective serotonin reuptake inhibitors (SSRIs) are the most widely prescribed drugs for mood disorders. While the mechanism of SSRI action is still unknown, SSRIs are thought to exert therapeutic effects by elevating extracellular serotonin levels in the brain, and remodel the structural and functional alterations dysregulated during depression. To determine their precise mode of action, we tested whether such neuroadaptive processes are modulated by regulation of specific gene expression programs. Here we identify a transcriptional program regulated by activator protein-1 (AP-1) complex, formed by c-Fos and c-Jun that is selectively activated prior to the onset of the chronic SSRI response. The AP-1 transcriptional program modulates the expression of key neuronal remodeling genes, including S100a10 (p11), linking neuronal plasticity to the antidepressant response. We find that AP-1 function is required for the antidepressant effect in vivo. Furthermore, we demonstrate how neurochemical pathways of BDNF and FGF2, through the MAPK, PI3K, and JNK cascades, regulate AP-1 function to mediate the beneficial effects of the antidepressant response. Here we put forth a sequential molecular network to track the antidepressant response and provide a new avenue that could be used to accelerate or potentiate antidepressant responses by triggering neuroplasticity.

Whose depression deteriorates during acute phase antidepressant treatment?

BACKGROUND

Few studies have investigated the proportion of patients with depression who experience worsening of depression symptoms during adequate antidepressant treatment. The current study aimed to investigate the proportion and predictors of worsening depression during antidepressant treatment in a multi-center randomized trial involving patients with major depression.

METHODS

We defined the deterioration of depression using depression symptom severity evaluated by total Patient Health Questionnaire (PHQ-9) score increases from week 0 to week 9 during acute phase antidepressant treatment. Patients' baseline demographic and clinical data, change in PHQ-9 scores from week 0 to week 3, and side effects at week 3 were evaluated as potential predictors of subsequent deterioration of depression.

RESULTS

Of 1,647 patients, 99 (6.0%) exhibited deterioration of depression, and this proportion was smaller when reliable change index criteria were applied. Logistic regression analysis revealed that the following factors were significantly associated with deterioration of depression: younger age at onset of first episode of major depressive disorder, current older age, and greater increase in PHQ-9 scores between week 0 and week 3.

LIMITATIONS

The time of the primary endpoint might not have been sufficiently long. The present study did not include a placebo arm, and potentially relevant predictors might not have been comprehensively investigated.

CONCLUSIONS

A small proportion of patients may experience deterioration of depression during acute phase antidepressant treatment. Age at onset at first depressive episode, current age, and early negative response to antidepressants may be useful predictors of subsequent worsening of depression.

[Angedonia in the structure of affective disorders: therapeutic opportunities]

Anhedonia is one of the core features of depression. The article considers the place of anhedonia in the structure of affective disorders, its influence on the prognosis and effectiveness of therapy. The authors stress that various manifestations of anhedonia must be considered in correlation with the basic ability to feel pleasure. Therapy of anhedonia is not always effective. According to literature, agomelatin occupies a leading position among the drugs that reduce anhedonia.

Body mass index (BMI) in major depressive disorder and its effects on depressive symptomatology and antidepressant response

BACKGROUND

Obesity is one of the most prevalent somatic comorbidities of Major Depressive Disorder (MDD). We aimed to investigate the relationship between body mass index (BMI) and MDD, the symptomatology of the disorder as well as the outcome of antidepressant treatment.

METHODS

Early medication change (EMC) trial participants with BMI measurement (n = 811) were categorized according to WHO-criteria in normal or low weight (BMI < 25), overweight (25-< 30), and obese (≥30). Depression severity and BMI was assessed in weekly intervals up to 8 weeks. BMI at baseline and course of BMI during the study were investigated in linear regression models as possible moderators of therapy response. Possible moderators such as plasma concentrations of applied drugs, sex, comorbidities or age were controlled.

RESULTS

388 (48%) patients showed normal weight, 251 (31%) were overweight and 172 (21%) obese. Linear regression analyses revealed an association between BMI and antidepressant therapy outcome: Overweight patients showed the best response to antidepressant treatment. BMI at baseline was significantly correlated with improvement in neurovegetative and cognitive symptoms of depression. Furthermore, weight gain during the study was associated with better therapy response, independent of symptom complex. Other moderators including serum concentrations of drugs were not able to explain the differences between the BMI groups.

LIMITATIONS

Secondary exploratory analysis. No investigation of visceral fat.

CONCLUSION

We showed for the first time that patients with higher initial increase in BMI showed larger decrease in depression severity during study. The underlying mechanisms are unclear and require further investigation.

Treatment response classes in major depressive disorder identified by model-based clustering and validated by clinical prediction models

The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response.

Effect of antidepressant switching between nortriptyline and escitalopram after a failed first antidepressant treatment among patients with major depressive disorder

BACKGROUND

For patients with major depressive disorder (MDD) experiencing side-effects or non-response to their first antidepressant, little is known regarding the effect of switching between a tricyclic antidepressant (TCA) and a selective serotonin reuptake inhibitor (SSRI).AimsTo compare the switch between the TCA nortriptyline and the SSRI escitalopram.

METHOD

Among 811 adults with MDD treated with nortriptyline or escitalopram for up to 12 weeks, 108 individuals switched from nortriptyline to escitalopram or vice versa because of side-effects or non-response (trial registration: EudraCT No.2004-001723-38 (https://eudract.ema.europa.eu/) and ISRCTN No.03693000 (http://www.controlled-trials.com)). Patients were followed for up to 26 weeks after switching and response was measured with the Montgomery-Åsberg Depression Rating scale (MADRS). We performed adjusted mixed-effects linear regression models with full information maximum likelihood estimation reporting β-coefficients with 95% CIs.

RESULTS

Switching antidepressants resulted in a significant decrease in MADRS scores. This was present for switchers from escitalopram to nortriptyline (n = 36, β = -0.38, 95% CI -0.51 to -0.25, P&lt;0.001) and from nortriptyline to escitalopram (n = 72, β = -0.34, 95% CI -0.41 to -0.26, P&lt;0.001). Both switching options resulted in significant improvement among individuals who switched because of non-response or side-effects. The results were supported by analyses on other rating scales and symptom dimensions.

CONCLUSIONS

These results suggest that switching from a TCA to an SSRI or vice versa after non-response or side-effects to the first antidepressant may be a viable approach to achieve response among patients with MDD.Declarations of interestK.J.A. holds an Alberta Centennial Addiction and Mental Health Research Chair, funded by the Government of Alberta. K.J.A. has been a member of various advisory boards, received consultancy fees and honoraria, and has received research grants from various companies including Johnson and Johnson Pharmaceuticals Research and Development and Bristol-Myers Squibb Pharmaceuticals Limited. D.S. has served on advisory boards for, and received unrestricted grants from, Lundbeck and AstraZeneca. A.F. and P.M. have received honoraria for participating in expert panels for Lundbeck and GlaxoSmithKline.

Trajectories of Response to Dorsolateral Prefrontal rTMS in Major Depression: A THREE-D Study

OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for refractory major depressive disorder, yet no studies have characterized trajectories of rTMS response. The aim of this study was to characterize response trajectories for patients with major depression undergoing left dorsolateral prefrontal cortex rTMS and to determine associated baseline clinical characteristics.

METHODS

This was a secondary analysis of a randomized noninferiority trial (N=388) comparing conventional 10-Hz rTMS and intermittent theta burst stimulation (iTBS) rTMS. Participants were adult outpatients who had a primary diagnosis of major depressive disorder, had a score ≥18 on the 17-item Hamilton Depression Rating Scale (HAM-D), and did not respond to one to three adequate antidepressant trials. Treatment was either conventional 10-Hz rTMS or iTBS rTMS applied to the dorsolateral prefrontal cortex, 5 days/week over 4-6 weeks (20-30 sessions). Group-based trajectory modeling was applied to identify HAM-D response trajectories, and regression techniques were used to identify associated characteristics.

RESULTS

Four trajectories were identified: nonresponse (N=43, 11%); rapid response (N=73, 19%); higher baseline symptoms, linear response (N=118, 30%); and lower baseline symptoms, linear response (N=154, 40%). Significant differences in response and remission rates between trajectories were detectable by week 1. There was no association between treatment protocol and response trajectory. Higher baseline scores on the HAM-D and the Quick Inventory of Depression Symptomatology-Self-Report (QIDS-SR) were associated with the nonresponse trajectory, and older age, lower QIDS-SR score, and lack of benzodiazepine use were associated with the rapid response trajectory.

CONCLUSIONS

Major depression shows distinct response trajectories to rTMS, which are associated with baseline clinical characteristics but not treatment protocol. These response trajectories with differential response to rTMS raise the possibility of developing individualized treatment protocols.

FCPR16, a novel phosphodiesterase 4 inhibitor, produces an antidepressant-like effect in mice exposed to chronic unpredictable mild stress

The canonical phosphodiesterase 4 (PDE4) inhibitors produce antidepressant-like effects in a variety of animal models. However, severe side effects, particularly vomiting and nausea, limit their clinical application. FCPR16 is a novel PDE4 inhibitor with less vomiting potential. However, whether it will exert an antidepressant-like effect remains unclear. Here, we aimed to evaluate the effect of FCPR16 in mice subjected to chronic unpredictable mild stress (CUMS). Our results showed that FCPR16 produced antidepressant-like effects in multiple behavioral tests, including a forced swimming test, tail suspension test, sucrose preference test and novelty suppression feeding test. Simultaneously, data indicated that FCPR16 enhanced the levels of several proteins, including cAMP, brain derived neurotrophic factor, exchange protein directly activated by cAMP 2 (EPAC-2), synapsin1, postsynaptic density protein 95, phosphorylated cAMP response element binding protein and extracellular regulated protein kinases 1/2, which were downregulated by CUMS in both the cerebral cortex and hippocampus. The number of DCX⁺ cells in the hippocampus of CUMS mice was increased after FCPR16 treatment. Moreover, treatment with FCPR16 resulted in decreased expression of pro-inflammatory cytokines (TNF-α, IL-6, and IL-1β) and increased expression of anti-inflammatory cytokines (IL-10) in mice challenged with CUMS. Consistently, the mRNA levels of microglial M1 markers (iNOS and TNF-α) were downregulated, while M2 markers (Arginase 1 and CD206) were upregulated in CUMS-exposed mice after FCPR16 treatment. Immunofluorescence analysis showed that FCPR16 inhibited the activation of microglial cells and increased the number of CD206⁺ in CUMS-exposed mice. Collectively, these results suggested that FCPR16 is a potential compound with effects against depressive-like behaviors, and the antidepressant-like effect of FCPR16 is possibly mediated through activation of the cAMP-mediated signaling pathways and inhibition of neuroinflammation in both the cerebral cortex and hippocampus.

Sex differences in depression: Insights from clinical and preclinical studies

Depression represents a global mental health concern, and disproportionally affects women as they are twice more likely to be diagnosed than men. In this review, we provide a summary of evidence to support the notion that differences in depression between men and women span multiple facets of the disease, including epidemiology, symptomology, treatment, and pathophysiology. Through a lens of biological sex, we overview depression-related transcriptional patterns, changes in neuroanatomy and neuroplasticity, and immune signatures. We acknowledge the unique physiological and behavioral demands of pregnancy and motherhood by devoting special attention to depression occurring in the peripartum period. Specifically, we discuss issues surrounding the presentation, time course, treatment, and neurobiology of peripartum depression. We write this review with the intention of highlighting the encouraging advancements in our understanding of sex differences in depression, while underscoring the gaps that remain. A more systematic consideration of biological sex as a variable in depression research will be critical in the discovery and development of pharmacotherapies that are efficacious for both men and women.

SiNiSan Ameliorates the Depression-Like Behavior of Rats That Experienced Maternal Separation Through 5-HT1A Receptor/CREB/BDNF Pathway

Background: Early adverse life stress is an important dangerous factor in the development of psychiatric disorders, particularly depression. Available clinical antidepressant agents, such as fluoxetine, [a selective serotonin reuptake inhibitor (SSRI)], are unsatisfactory because of their side effects. SiNiSan (SNS) is a classic Chinese medicine prescription regarded to disperse stagnated liver qi to relieve qi stagnation. Therefore, this study was designed to detect the effects and molecular mechanism of SNS treatment in rats subjected to maternal separation (MS). Method: Male neonatal Wistar rats were divided into six groups including control + ddH₂O, MS + ddH₂O, MS + fluoxetine (5 g/kg), MS + SNS -low dose (2.5 g/kg), MS + SNS -medium dose (5 g/kg), MS + SNS -high dose (10 g/kg). The volume of drugs and ddH2O in each group are according to the weight of rats every day (10 mL/kg). Each group comprised 16 pups with 8 young and 8 adult pups. Except for the control group, all MS groups were separated from their mothers for 4 h/day from 9:00 to 13:00 during postnatal days (PNDs) 1 to 21. After MS, the six groups were intragastrically administered with ddH2O, fluoxetine, and different doses of SNS until PND 28 (for young pups) and PND 56 (for adult pups). The pups were weighed every day, and depression-like behavior was assessed by sucrose preference test, open field test, and forced swimming test. Serotonin 1A (5-HT1A) receptor, phosphorylated protein kinase A (p-PKA) substrate, cAMP response element-binding protein (CREB), p-CREB and brain-derived neurotrophic factor (BDNF) in the hippocampus were examined by Western blot, and in situ 5-HT1A receptor expression was measured by IHC. Results: Young and adult MS rats exhibited depression-like behavior. However, the depression-like behavior was ameliorated by SNS in both age groups. The levels of 5-HT1A receptor, p-CREB, and BDNF in the hippocampus were reduced in young and adult MS rats. SNS treatment significantly up-regulated the expression of 5-HT1A receptor, p-CREB, and BDNF in the hippocampus of adult MS rats. However, few significant effects on the protein expression were observed in the young MS rats. Conclusion: MS in infancy could develop depression-like behavior in young and adult. SNS treatment may perform antidepressant effects on young and adult MS rats through the BDNF/PKA/CREB pathway.

[Psychiatric pharmacotherapy of older individuals with severe mental illness]

BACKGROUND

Chronic schizophrenia, depression, and bipolar disorders, among other chronic psychiatric disorders with onset at youth or early adulthood are often referred to as severe mental illness (SMI). Aging with SMI is associated with various psychosocial, physiological, and medical problems with potential impact on psychiatric pharmacotherapy.

OBJECTIVES

Determination and discussion of problems and special features of the psychopharmacological treatment of older persons with SMI and presentation of treatment recommendations for the distinct diagnoses.

MATERIALS AND METHODS

International literature and guidelines were searched. In addition, the basic literature and expert opinions are discussed.

RESULTS

General problems that influence the psychiatric pharmacotherapy of older persons with SMI include nonadherence, nonresponse, polypharmacy, and distinct pharmacokinetic changes with aging and somatic comorbidity. Psychotropic drugs may exhibit cardiovascular, metabolic, and neuropsychiatric risks, among others. The literature regarding effectiveness of psychotropic drugs, drug groups, or combination of drugs in older patients with SMI is scarce to nonexistent.

CONCLUSIONS

Drug treatment of older persons with SMI should be part of an overall treatment plan that also has to include social and psychotherapeutic components that address the specific problems of this population. Most importantly, psychiatric pharmacotherapy should consider these risks and the treatment should be tailored to a patient's individual risk profile. Due to a general lack of evidence in this special population, treatment strategies of standard guidelines should be adjusted with special consideration to physiological changes of age.