Early onset of selective serotonin reuptake inhibitor antidepressant action: systematic review and meta-analysis

Response trajectory to left dorsolateral prefrontal rTMS in major depressive disorder: A systematic review and meta-analysis: Trajectory of rTMS

The depression response trajectory after a course of repetitive transcranial magnetic stimulation(rTMS) remains understudied. We searched for blinded randomized controlled trials(RCTs) that examined conventional rTMS over left dorsolateral prefrontal cortex(DLPFC) for major depressive episodes(MDE). The effect size was calculated as the difference in depression improvement, between active and sham rTMS. We conducted a random-effects dose-response meta-analysis to model the response trajectory from the beginning of rTMS to the post-treatment follow-up phase. The area under curve (AUC) of the first 8-week response trajectory was calculated to compare antidepressant efficacy between different rTMS protocols. We included 40 RCTs(n = 2012). The best-fitting trajectory model exhibited a logarithmic curve(X2=17.7, P < 0.001), showing a gradual ascent with tapering off around the 3-4th week mark and maintaining until week 16. The maximum effect size was 6.1(95 %CI: 1.25-10.96) at week 16. The subgroup analyses showed distinct trajectories across different rTMS protocols. Besides, the comparisons of AUC showed that conventional rTMS protocols with more pulse/session group or more total pulses were associated with greater efficacy than those with fewer pulse/session or fewer total pulses, respectively. A course of conventional left DLPFC rTMS could lead to both acute antidepressant effects and sustained after-effects, which were modeled by different rTMS protocols in MDE.

PET Imaging of the Serotonin 1A Receptor in Major Depressive Disorder: Hierarchical Multivariate Analysis of [11C]WAY100635 Overcomes Outcome Measure Discrepancies

The serotonin 1A receptor has been linked to both the pathophysiology of major depressive disorder (MDD) and the antidepressant action of serotonin reuptake inhibitors. Most PET studies of the serotonin 1A receptor in MDD used the receptor antagonist radioligand, [carbonyl-11C]WAY100635; however the interpretation of the combined results has been contentious owing to reports of higher or lower binding in MDD with different outcome measures. The reasons for these divergent results originate from several sources, including properties of the radiotracer itself, which complicate its quantification and interpretation; as well as from previously reported differences between MDD and healthy volunteers in both reference tissue binding and plasma free fraction, which are typically assumed not to differ. Recently, we have developed two novel hierarchical multivariate methods which we validated for the quantification and analysis of [11C]WAY100635, which show better accuracy and inferential efficiency compared to standard analysis approaches. Importantly, these new methods should theoretically be more resilient to many of the factors thought to have caused the discrepancies observed in previous studies. We sought to apply these methods in the largest [11C]WAY100635 sample to date, consisting of 160 individuals, including 103 MDD patients, of whom 50 were not-recently-medicated and 53 were antidepressant-exposed, as well as 57 healthy volunteers. While the outcome measure discrepancies were substantial using conventional univariate analysis, our multivariate analysis techniques instead yielded highly consistent results across PET outcome measures and across pharmacokinetic models, with all approaches showing higher serotonin 1A autoreceptor binding potential in the raphe nuclei of not-recently-medicated MDD patients relative to both healthy volunteers and antidepressant-exposed MDD patients. Moreover, with the additional precision of estimates afforded by this approach, we can show that while binding is also higher in projection areas in this group, these group differences are approximately half of those in the raphe nuclei, which are statistically distinguishable from one another. These results are consistent with the biological role of the serotonin 1A autoreceptor in the raphe nuclei in regulating serotonin neuron firing and release, and with preclinical and clinical evidence of deficient serotonin activity in MDD due to over expression of autoreceptors resulting from genetic and/or epigenetic effects. These results are also consistent with downregulation of autoreceptors as a mechanism of action of selective serotonin reuptake inhibitors. In summary, the results using multivariate analysis approaches therefore demonstrate both face and convergent validity, and may serve to provide a resolution and consensus interpretation for the disparate results of previous studies examining the serotonin 1A receptor in MDD.

Effectiveness of Shugan Jieyu capsules for psychiatric symptoms of epilepsy: a systematic review and meta-analysis

BACKGROUND

The relationship between epilepsy and depression is bidirectional. One condition exacerbates the other. However, there are no current guidelines for treating depression in epilepsy patients. In some cases, seizures worsen when antidepressants (AD) are prescribed or when they are discontinued due to adverse events. The Shugan Jieyu capsule, composed of Acanthopanax senticosus and Hypericum perforatum, is a widely used herbal medicine for treating depression. This study aimed to explore the effectiveness and safety of Shugan Jieyu capsules (SJC) in relieving depression in patients with epilepsy.

METHODS

We searched English, Korean, Japanese, and Chinese databases in October 2023 to collect all relevant randomized clinical trials (RCTs). The primary outcomes were the depression scale scores and seizure frequency. The secondary outcomes were quality of life (QoL) and adverse events.

RESULTS

Nine RCTs were included in this meta-analysis. Compared with AD, SJC showed significant differences in the improvement of depression (SMD: 3.82, 95% CI: 3.25, 4.39) and reduction in seizure frequency (MD: 0.39 times/month, 95% CI: 0.28, 0.50). SJC showed more beneficial results than antiepileptic drugs (AED) in terms of antidepressant effects (SMD: 1.10, 95% CI: 0.69, 1.51) and QoL (MD: 11.75, 95% CI: 10.55, 12.95). When patients were prescribed AED, the additional administration of SJC improved depression symptoms (SMD: 0.96, 95% CI: 0.28, 1.63). The SJC treatment group had a lower incidence of side effects than the control group. However, the difference was not statistically significant.

CONCLUSIONS

Our results suggest that SJC may be effective in treating depression in patients with epilepsy. Additionally, SJC has the potential to help reduce seizure frequency in epilepsy patients with depression.

Efficacy and safety of zuranolone for the treatment of depression: A systematic review and meta-analysis

Major depressive disorder (MDD) and postpartum depression (PPD) are common and burdensome conditions. This study aims to evaluate the efficacy and safety of zuranolone, a neuroactive steroid γ-aminobutyric acid type A receptors-positive allosteric modulator, in treating MDD and PPD. A comprehensive literature search was conducted until September 2023, identifying seven randomized controlled trials (RCTs). The results demonstrated that zuranolone significantly decreased Hamilton Rating Scale for Depression (HAM-D) scores in patients with PPD or MDD at day 15 (concluding the 14-day course) and day 42-45 (4 weeks after treatment cessation) compared with the placebo, albeit exhibiting a diminishing trend. Moreover, a higher percentage of patients with PPD or MDD achieved HAM-D response and remission with zuranolone treatment compared with placebo at day 15. However, zuranolone did not significantly increase the proportion of MDD patients achieving HAM-D remission at 42/43 days. Adverse events (AEs) such as somnolence, dizziness, and sedation were linked to zuranolone, with a higher but not statistically significant rate of discontinuation due to AEs in the zuranolone group. Overall, our findings support the rapid antidepressant effects of zuranolone in MDD and PPD, along with a relatively favorable safety and tolerability. Large-scale longitudinal RCTs are needed to evaluate the long-term efficacy of zuranolone.

The role of depression and antidepressant treatment in antihypertensive medication adherence and persistence: Utilising electronic health record data

Higher blood pressure levels in patients with depression may be associated with lower adherence to antihypertensive medications (AHMs). Here, we use electronic health record (EHR) data from the Estonian Biobank (EstBB) to investigate the role of lifetime depression in AHM adherence and persistence. We also explore the relationship between antidepressant initiation and intraindividual change in AHM adherence among hypertension (HTN) patients with newly diagnosed depression. Diagnosis and pharmacy refill data were obtained from the National Health Insurance database. Adherence and persistence to AHMs were determined for hypertension (HTN) patients initiating treatment between 2009 and 2017 with a three-year follow-up period. Multivariable regression was used to explore the associations between depression and AHM adherence or persistence, adjusting for sociodemographic, genetic, and health-related factors. A linear mixed-effects model was used to estimate the effect of antidepressant treatment initiation on antihypertensive medication adherence, adjusting for age and sex. We identified 20,724 individuals with newly diagnosed HTN (6294 depression cases and 14,430 controls). Depression was associated with 6% lower probability of AHM adherence (OR = 0.943, 95%CI = 0.909-0.979) and 12% lower odds of AHM persistence (OR = 0.876, 95%CI = 0.821-0.936). Adjusting for sociodemographic, genetic, and health-related factors did not significantly influence these associations. AHM adherence increased 8% six months after initiating antidepressant therapy (N = 132; β = 0.078; 95%CI = 0.025-0.131). Based on the EHR data on EstBB participants, depression is associated with lower AHM adherence and persistence. Additionally, antidepressant therapy may help improve AHM adherence in patients with depression.

Psilocybin and Other Classic Psychedelics in Depression

Psychedelic drugs such as psilocybin and ketamine are returning to clinical research and intervention across several disorders including the treatment of depression. This chapter focusses on psychedelics that specifically target the 5-HT2A receptor such as psilocybin and DMT. These produce plasma-concentration related psychological effects such as hallucinations and out of body experiences, insightful and emotional breakthroughs as well as mystical-type experiences. When coupled with psychological support, effects can produce a rapid improvement in mood among people with depression that can last for months. In this chapter, we summarise the scientific studies to date that explore the use of psychedelics in depressed individuals, highlighting key clinical, psychological and neuroimaging features of psychedelics that may account for their therapeutic effects. These include alterations in brain entropy that disrupt fixed negative ruminations, a period of post-treatment increased cognitive flexibility, and changes in self-referential psychological processes. Finally, we propose that the brain mechanisms underlying the therapeutic effect of serotonergic psychedelics might be distinct from those underlying classical serotonin reuptake-blocking antidepressants.

SSRIs in the Treatment of Depression: A Pharmacological CUL-DE-SAC?

The widespread adoption of selective serotonin reuptake inhibitors (SSRIs) as first-line pharmacological treatments in the management of clinical depression transformed the landscape of drug therapy for this condition. SSRIs are safer and better tolerated than the tricyclic antidepressants (TCAs) that they replaced. However, they have limitations that may have placed a ceiling on the expectations of first-line pharmacological treatment. Notable problems with SSRIs include induction of anxiety on treatment initiation, delayed onset of significant therapeutic effect, sexual dysfunction, sleep disturbance and overall modest efficacy. The latter is linked with an inability of SSRIs to effectively treat syndromes of anhedonia and cognitive impairment. Combined serotonin and noradrenaline reuptake inhibitors (SNRIs), such as venlafaxine, have produced some limited improvements over SSRIs in efficacy, at the cost of a greater side-effect burden. Attempts to supplement serotonin reuptake activity with actions at serotonin receptor sub-types have not yet yielded substantial benefits; however, vortioxetine may provide more utility in the management of cognitive impairment. Future advances might come from the development of SNRIs, which more closely mimic the actions of effective TCAs. There may also be possible benefits to be derived from combining SSRIs with 5-HT4 receptor agonists and 5-HT7 receptor antagonists.

The Relationship of Early Sleep Improvement With Response to Pharmacotherapy in Unipolar Psychotic Depression

BACKGROUND

Since insomnia and depression are interrelated, improved sleep early in antidepressant pharmacotherapy may predict a positive treatment outcome. We investigated whether early insomnia improvement (EII) predicted treatment outcome in psychotic depression (PD) and examined if there was an interaction effect between EII and treatment type to assess if findings were treatment-specific.

METHODS

This study is a secondary analysis of a randomized trial comparing 7 weeks treatment with the antidepressants venlafaxine, imipramine and venlafaxine plus the antipsychotic quetiapine in PD ( n = 114). Early insomnia improvement, defined as ≥20% reduced insomnia after 2 weeks, was assessed by the Hamilton Rating Scale for Depression (HAM-D-17). Associations between EII and treatment outcome were examined using logistic regressions. Subsequently, we added interaction terms between EII and treatment type to assess interaction effects. The predictive value of EII was compared with early response on overall depression (≥20% reduced HAM-D-17 score after 2 weeks).

RESULTS

EII was associated with response (odds ratio [OR], 7.9; 95% confidence interval [CI], 2.7-23.4; P = <0.001), remission of depression (OR, 6.1; 95% CI, 1.6-22.3; P = 0.009), and remission of psychosis (OR, 4.1; 95% CI, 1.6-10.9; P = 0.004). We found no interaction effects between EII and treatment type on depression outcome. Early insomnia improvement and early response on overall depression had a comparable predictive ability for treatment outcome.

CONCLUSIONS

Early insomnia improvement was associated with a positive outcome in pharmacotherapy of PD, regardless of the medication type. Future studies are needed to confirm our findings and to examine the generalizability of EII as predictor in treatment of depression.

Effects of escitalopram on synaptic density in the healthy human brain: a randomized controlled trial

Selective serotonin reuptake inhibitors (SSRIs) are widely used for treating neuropsychiatric disorders. However, the exact mechanism of action and why effects can take several weeks to manifest is not clear. The hypothesis of neuroplasticity is supported by preclinical studies, but the evidence in humans is limited. Here, we investigate the effects of the SSRI escitalopram on presynaptic density as a proxy for synaptic plasticity. In a double-blind placebo-controlled study (NCT04239339), 32 healthy participants with no history of psychiatric or cognitive disorders were randomized to receive daily oral dosing of either 20 mg escitalopram (n = 17) or a placebo (n = 15). After an intervention period of 3-5 weeks, participants underwent a [11C]UCB-J PET scan (29 with full arterial input function) to quantify synaptic vesicle glycoprotein 2A (SV2A) density in the hippocampus and the neocortex. Whereas we find no statistically significant group difference in SV2A binding after an average of 29 (range: 24-38) days of intervention, our secondary analyses show a time-dependent effect of escitalopram on cerebral SV2A binding with positive associations between [11C]UCB-J binding and duration of escitalopram intervention. Our findings suggest that brain synaptic plasticity evolves over 3-5 weeks in healthy humans following daily intake of escitalopram. This is the first in vivo evidence to support the hypothesis of neuroplasticity as a mechanism of action for SSRIs in humans and it offers a plausible biological explanation for the delayed treatment response commonly observed in patients treated with SSRIs. While replication is warranted, these results have important implications for the design of future clinical studies investigating the neurobiological effects of SSRIs.

Efficacy and safety of zuranolone in Japanese adults with major depressive disorder: A double-blind, randomized, placebo-controlled, phase 2 clinical trial

AIM

To evaluate the efficacy and safety of an oral, once-daily, 14-day treatment course of zuranolone in Japanese patients with major depressive disorder (MDD).

METHODS

This multicenter, randomized, double-blind, placebo-controlled study randomized eligible patients (1:1:1) to receive oral zuranolone 20 mg, zuranolone 30 mg, or placebo once daily for 14 days (treatment-period), followed by two 6-week follow-up periods. The primary endpoint was change from baseline in the 17-item Hamilton Depression Rating Scale (HAMD-17) total score on Day 15.

RESULTS

Overall, 250 patients (enrolled: 07/07/2020-05/26/2021) were randomized to receive placebo (n = 83), zuranolone 20 mg (n = 85), or zuranolone 30 mg (n = 82). The demographic and baseline characteristics were balanced between groups. The adjusted mean (standard error) change from baseline in the HAMD-17 total score on Day 15 was -6.22 (0.62), -8.14 (0.62), and - 8.31 (0.63) in the placebo, zuranolone 20-mg, and zuranolone 30-mg groups, respectively. Significant differences in the adjusted mean (95% confidence interval [CI]) for zuranolone 20 mg versus placebo (-1.92; [-3.65, -0.19]; P = 0.0296) and zuranolone 30 mg versus placebo (-2.09; [-3.83, -0.35]; P = 0.0190) groups were observed on Day 15, and also as early as Day 3. A nonsignificant yet distinct drug-placebo separation was observed during follow-up. Somnolence (placebo [3.7%], zuranolone 20 mg [10.6%], and zuranolone 30 mg [20.7%]) and dizziness (3.7%, 9.4%, and 9.8%, respectively) were more common with zuranolone.

CONCLUSION

Oral zuranolone was safe and demonstrated significant improvements in depressive symptoms, as assessed by HAMD-17 total score change from baseline over 14 days in Japanese patients with MDD.

Major depressive disorder

Major depressive disorder (MDD) is characterized by persistent depressed mood, loss of interest or pleasure in previously enjoyable activities, recurrent thoughts of death, and physical and cognitive symptoms. People with MDD can have reduced quality of life owing to the disorder itself as well as related medical comorbidities, social factors, and impaired functional outcomes. MDD is a complex disorder that cannot be fully explained by any one single established biological or environmental pathway. Instead, MDD seems to be caused by a combination of genetic, environmental, psychological and biological factors. Treatment for MDD commonly involves pharmacological therapy with antidepressant medications, psychotherapy or a combination of both. In people with severe and/or treatment-resistant MDD, other biological therapies, such as electroconvulsive therapy, may also be offered.

Treating depression in clinical practice: new insights on the multidisciplinary use of trazodone

Depression is estimated to be a leading contributor to the global mental health-related burden. The determinants of this huge prevalence lie in the fact that depressive symptoms may be comorbid in a wide variety of disorders, thus complicating and exacerbating their clinical framework. This makes the treatment of depressive symptoms difficult, since many pharmacological interactions should be considered by physicians planning therapy. Hence, depression still represents a challenge for both psychiatrists and other clinicians, in terms of its high rates of relapse and resistance despite well-established protocols. It is also complicated by the well-known latency in its complete response to current antidepressant treatments. In this context, the search for new strategies regarding antidepressant treatment is mandatory. Revising the use of "old" pharmacotherapies by considering their specific features may help to perfecting the treatment of depression, both in its standalone psychiatric manifestation and in the framework of other clinical conditions. Using a nominal group technique approach, the results of a consensus of expert physicians regarding the possible use of trazodone as a valuable strategy for addressing the "real world" unmet needs of depression treatment in different fields (psychiatry, primary care, neurology and geriatrics) is herein provided. This idea is based on the unique characteristics of this drug which delivers a more rapid antidepressant action as compared to other selective serotonin reuptake inhibitors. It also has pharmacodynamic malleability (i.e., the possibility of exerting different effects on depressive symptoms at different dosages) and pharmacokinetic tolerability (i.e., the possibility of being used as an add-on to other antidepressants with scarce interaction and achieving complimentary effects) when used in the milieu of other drugs in treating comorbid depressive symptoms. Moreover, the large number of formulations available permits finite dosage adjustments, and the use of trazodone for specific pathologies, such as dysphagia. Therefore, although additional studies exploring the real-world conditions of antidepressant treatment are warranted, experts agree on the idea that depressive disorder, in both its standalone and its comorbid manifestations, may surely take advantage of the particular characteristics of trazodone, thus attempting to reach the greatest effectiveness in different contexts.

Boosting Serotonin Increases Information Gathering by Reducing Subjective Cognitive Costs

Serotonin is implicated in the valuation of aversive costs, such as delay or physical effort. However, its role in governing sensitivity to cognitive effort, for example, deliberation costs during information gathering, is unclear. We show that treatment with a serotonergic antidepressant in healthy human individuals of either sex enhances a willingness to gather information when trying to maximize reward. Using computational modeling, we show this arises from a diminished sensitivity to subjective deliberation costs during the sampling process. This result is consistent with the notion that serotonin alleviates sensitivity to aversive costs in a domain-general fashion, with implications for its potential contribution to a positive impact on motivational deficits in psychiatric disorders.SIGNIFICANCE STATEMENT Gathering information about the world is essential for successfully navigating it. However, sampling information is costly, and we need to balance between gathering too little and too much information. The neurocomputational mechanisms underlying this arbitration between a putative gain, such as reward, and the associated costs, such as allocation of cognitive resources, remain unclear. In this study, we show that week-long daily treatment with a serotonergic antidepressant enhances a willingness to gather information when trying to maximize reward. Computational modeling indicates this arises from a reduced perception of aversive costs, rendering information gathering less cognitively effortful. This finding points to a candidate mechanism by which serotonergic treatment might help alleviate motivational deficits in a range of mental illnesses.

Suicide prevention and ketamine: insights from computational modeling

Suicide is a pressing public health issue, with over 700,000 individuals dying each year. Ketamine has emerged as a promising treatment for suicidal thoughts and behaviors (STBs), yet the complex mechanisms underlying ketamine's anti-suicidal effect are not fully understood. Computational psychiatry provides a promising framework for exploring the dynamic interactions underlying suicidality and ketamine's therapeutic action, offering insight into potential biomarkers, treatment targets, and the underlying mechanisms of both. This paper provides an overview of current computational theories of suicidality and ketamine's mechanism of action, and discusses various computational modeling approaches that attempt to explain ketamine's anti-suicidal effect. More specifically, the therapeutic potential of ketamine is explored in the context of the mismatch negativity and the predictive coding framework, by considering neurocircuits involved in learning and decision-making, and investigating altered connectivity strengths and receptor densities targeted by ketamine. Theory-driven computational models offer a promising approach to integrate existing knowledge of suicidality and ketamine, and for the extraction of model-derived mechanistic parameters that can be used to identify patient subgroups and personalized treatment approaches. Future computational studies on ketamine's mechanism of action should optimize task design and modeling approaches to ensure parameter reliability, and external factors such as set and setting, as well as psychedelic-assisted therapy should be evaluated for their additional therapeutic value.

Systematic evaluation of a predator stress model of depression in mice using a hierarchical 3D-motion learning framework

Investigation of the neurobiology of depression in humans depends on animal models that attempt to mimic specific features of the human disorder. However, frequently-used paradigms based on social stress cannot be easily applied to female mice which has led to a large sex bias in preclinical studies of depression. Furthermore, most studies focus on one or only a few behavioral assessments, with time and practical considerations prohibiting a comprehensive evaluation. In this study, we demonstrate that predator stress effectively induced depression-like behaviors in both male and female mice. By comparing predator stress and social defeat models, we observed that the former elicited a higher level of behavioral despair and the latter elicited more robust social avoidance. Furthermore, the use of machine learning (ML)-based spontaneous behavioral classification can distinguish mice subjected to one type of stress from another, and from non-stressed mice. We show that related patterns of spontaneous behaviors correspond to depression status as measured by canonical depression-like behaviors, which illustrates that depression-like symptoms can be predicted by ML-classified behavior patterns. Overall, our study confirms that the predator stress induced phenotype in mice is a good reflection of several important aspects of depression in humans and illustrates that ML-supported analysis can simultaneously evaluate multiple behavioral alterations in different animal models of depression, providing a more unbiased and holistic approach for the study of neuropsychiatric disorders.

Modeling the antidepressant treatment response to transcranial magnetic stimulation using an exponential decay function

Recovery from depression often demonstrates a nonlinear pattern of treatment response, where the largest reduction in symptoms is observed early followed by smaller improvements. This study investigated whether this exponential pattern could model the antidepressant response to repetitive transcranial magnetic stimulation (TMS). Symptom ratings from 97 patients treated with TMS for depression were collected at baseline and after every five sessions. A nonlinear mixed-effects model was constructed using an exponential decay function. This model was also applied to group-level data from several published clinical trials of TMS for treatment-resistant depression. These nonlinear models were compared to corresponding linear models. In our clinical sample, response to TMS was well modeled with the exponential decay function, yielding significant estimates for all parameters and demonstrating superior fit compared to a linear model. Similarly, when applied to multiple studies comparing TMS modalities as well as to previously identified treatment response trajectories, the exponential decay models yielded consistently better fits compared to linear models. These results demonstrate that the antidepressant response to TMS follows a nonlinear pattern of improvement that is well modeled with an exponential decay function. This modeling offers a simple and useful framework to inform clinical decisions and future studies.

Circadian rhythm biomarker from wearable device data is related to concurrent antidepressant treatment response

Major depressive disorder (MDD) is associated with circadian rhythm disruption. Yet, no circadian rhythm biomarkers have been clinically validated for assessing antidepressant response. In this study, 40 participants with MDD provided actigraphy data using wearable devices for one week after initiating antidepressant treatment in a randomized, double-blind, placebo-controlled trial. Their depression severity was calculated pretreatment, after one week and eight weeks of treatment. This study assesses the relationship between parametric and nonparametric measures of circadian rhythm and change in depression. Results show significant association between a lower circadian quotient (reflecting less robust rhythmicity) and improvement in depression from baseline following first week of treatment (estimate = 0.11, F = 7.01, P = 0.01). There is insufficient evidence of an association between circadian rhythm measures acquired during the first week of treatment and outcomes after eight weeks of treatment. Despite this lack of association with future treatment outcome, this scalable, cost-effective biomarker may be useful for timely mental health care through remote monitoring of real-time changes in current depression.

Ketamine affects homeostatic sleep regulation in the absence of the circadian sleep-regulating component in freely moving rats

Pharmacological effects of ketamine may affect homeostatic sleep regulation via slow wave related mechanisms. In the present study effects of ketamine applied at anesthetic dose (80 mg/kg) were tested on neocortical electric activity for 24 h in freely moving rats. Ketamine effects were compared to changes during control (saline) injections and after 6 h gentle handling sleep deprivation (SD). As circadian factors may mask drug effects, an illumination protocol consisting of short light-dark cycles was applied. Ketamine application induced a short hypnotic stage with characteristic slow cortical rhythm followed by a long-lasting hyperactive waking resulting pharmacological SD. Coherence analysis indicated an increased level of local synchronization in broad local field potential frequency ranges during hyperactive waking but not during natural- or SD-evoked waking. Both slow wave sleep and rapid eye movement sleep were replaced after the termination of the ketamine effect. Our results show that both ketamine-induced hypnotic state and hyperactive waking can induce homeostatic sleep pressure with comparable intensity as 6 h SD, but ketamine-induced waking was different compared to the SD-evoked one. Both types of waking stages were different compared to spontaneous waking but all three types of wakefulness can engage the homeostatic sleep regulating machinery to generate sleep pressure dissipated by subsequent sleep. Current-source density analysis of the slow waves showed that cortical transmembrane currents were stronger during ketamine-induced hypnotic stage compared to both sleep replacement after SD and ketamine application, but intracortical activation patterns showed only quantitative differences. These findings may hold some translational value for human medical ketamine applications aiming the treatment of depression-associated sleep problems, which can be alleviated by the homeostatic sleep effect of the drug without the need for an intact circadian regulation.

Connecting Dots between Mitochondrial Dysfunction and Depression

Mitochondria are the prime source of cellular energy, and are also responsible for important processes such as oxidative stress, apoptosis and Ca2+ homeostasis. Depression is a psychiatric disease characterized by alteration in the metabolism, neurotransmission and neuroplasticity. In this manuscript, we summarize the recent evidence linking mitochondrial dysfunction to the pathophysiology of depression. Impaired expression of mitochondria-related genes, damage to mitochondrial membrane proteins and lipids, disruption of the electron transport chain, higher oxidative stress, neuroinflammation and apoptosis are all observed in preclinical models of depression and most of these parameters can be altered in the brain of patients with depression. A deeper knowledge of the depression pathophysiology and the identification of phenotypes and biomarkers with respect to mitochondrial dysfunction are needed to help early diagnosis and the development of new treatment strategies for this devastating disorder.

Effect of fluvoxamine on preventing neuropsychiatric symptoms of post COVID syndrome in mild to moderate patients, a randomized placebo-controlled double-blind clinical trial

BACKGROUND

Shortly after the Coronavirus disease 2019 (COVID-19) pandemic, a considerable number of recovered patients reported persisting symptoms, especially neuropsychological manifestations, which were later named post-COVID syndrome (PCS). Immune dysregulation was suggested as one of the main mechanisms for PCS. Fluvoxamine, a selective serotonin reuptake inhibitor (SSRI) that is mostly used to treat depression, anxiety disorders, and obsessive-compulsive disorder, has been suggested as an anti-COVID drug due to its anti-inflammatory effects, mainly through the sigma-1 receptor. Therefore, we aimed to evaluate fluvoxamine's effect on PCS neuropsychiatric symptoms.

METHOD

In this double-blind randomized clinical trial, we included confirmed mild to moderate COVID-19 outpatients using polymerase chain reaction (PCR) by an infectious disease specialist. The presence of severe COVID-19 symptoms was evaluated by the infectious disease specialist and included dyspnea, SpO2 < 94% on room air, PaO2/FiO2 < 300 mm Hg, a respiratory rate > 30 breaths/min, and lung infiltrates > 50%. Then we performed permuted block randomization and assigned patients 1:1 into two groups to either receive fluvoxamine 100 mg tablet or a placebo daily for 10 days. Eligible patients were evaluated after 12 weeks for the presence of fatigue, as the primary, and other PCS symptoms as secondary outcomes.

RESULTS

We screened a total of 486 patients from March to June 2022. After 12 weeks, 42 patients receiving fluvoxamine and 43 patients receiving Placebo were evaluated for PCS. Patients had a mean age of 38.5 ± 14.1 and 48% of them were women. Fatigue was significantly lower in the fluvoxamine group (p-value 0.026). No significant differences were observed in other symptoms.

CONCLUSION

We concluded that taking fluvoxamine during active COVID-19 can reduce the chance of fatigue but the advantage of fluvoxamine was not observed for other symptoms. Further studies are necessary to confirm these preliminary results.

Association of Medicaid Expansion With Postpartum Depression Treatment in Arkansas

Importance

Postpartum depression affects approximately 1 in every 8 postpartum individuals in the US. Antidepressant medication can effectively treat postpartum depression. However, gaps in postpartum insurance coverage after the end of Medicaid pregnancy coverage at 60 days postpartum may limit treatment uptake and decrease continuity of postpartum depression treatment.

Objective

To examine the association of Medicaid expansion in Arkansas with postpartum antidepressant prescription fills and antidepressant continuation and supply during the first 6 months postpartum.

Design, Setting, and Participants

Cohort study with a difference-in-differences analysis comparing persons with Medicaid and commercially financed childbirth using Arkansas' All-Payer Claims Database (2013-2016). Analysis was completed between July 2021 and June 2022.

Exposures

Medicaid-paid childbirth after January 1, 2014.

Main Outcomes and Measures

Antidepressant medication prescription fills and the number of days of antidepressant supply in the early (first 60 days after childbirth) and the late (61 days to 6 months after childbirth) postpartum periods.

Results

In this cohort study with a difference-in-differences analysis of 60 990 childbirths (mean [SD] birthing parent's age, 27 [5.3] years; 22% Black, 7% Hispanic, 67% White individuals), 72% of births were paid for by Medicaid and 28% were paid for by a commercial payer. Before expansion, 4.2% of people with a Medicaid-paid birth filled an antidepressant prescription in the later postpartum period. Medicaid expansion was associated with a 4.6 percentage point (95% CI, 2.9-6.3) increase in the likelihood, or a relative change of 110%, in this outcome. Before expansion, among people with postpartum depression in the early postpartum period with a Medicaid-paid birth, 32.7% filled an antidepressant prescription in the later postpartum period, and had an average of 23 days of antidepressant prescription supply during the later postpartum period. Among people with early postpartum depression, Medicaid expansion increased the continuity of antidepressant treatment by 20.5 percentage points (95% CI, 14.1-26.9) and the number of days with antidepressant supply in the later postpartum period by 14.1 days (95% CI, 7.2-20.9).

Conclusions and Relevance

Medicaid expansion in Arkansas was associated with an increase in postpartum antidepressant prescription fills, and an increase in antidepressant treatment continuity and medication supply in the period after Medicaid pregnancy-related eligibility ended.

Replication of distinct trajectories of antidepressant response to intravenous ketamine

BACKGROUND

The goal of this study was to replicate previous findings of three distinct treatment response pathways associated with repeated intravenous (IV) ketamine infusions among patients with major depressive disorder (MDD).

METHODS

We conducted growth mixture modeling to estimate latent classes of change in depression (Quick Inventory of Depressive Symptomatology-Self Report, QIDS-SR) across six treatment visits in 298 patients with MDD treated with IV ketamine in an outpatient community clinic. Mean age was 40.36 and patients were primarily male (58.4 %). The sample had relatively severe depression (QIDS-SR = 16.61) at pre-treatment and the majority had not responded to at least two prior medications.

RESULTS

Best-fit indices indicated three trajectory groups to optimally demonstrate non-linear, quadratic changes in depressive symptoms during ketamine treatment. Two groups had severe depression at baseline but diverged into a group of modest improvement over the treatment course (n = 78) and a group of patients with rapid improvement (n = 103). A third group had moderate depression at baseline with moderate improvement during the treatment course (n = 117). Additional planned trajectory comparisons showed that suicidality at entry was higher in the high depression groups and that change in suicidality severity followed that of depression.

LIMITATIONS

This was a retrospective analysis of a naturalistic sample. Patients were unblinded and more heterogenous than those included in most controlled clinical trial samples.

CONCLUSIONS

This replication study in an independent community-based ketamine clinic sample revealed similar response trajectories, with only about a third of depressed patients benefitting substantially from an acute induction course of ketamine infusions.

Systematic review of studies using platelet serotonin content to assess bioeffect of serotonin reuptake inhibitors at the serotonin transporter

RATIONALE

Assessment of the bioeffect of serotonin reuptake inhibitors (SRIs, including both selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs)) at the serotonin transporter (SERT) in patients and healthy controls can have important theoretical and clinical implications.

OBJECTIVES

Bioeffect at SERT has been assessed by neuroimaging of brain SERT occupancy, through in vitro measurements of platelet serotonin (5-HT) uptake, and by measuring platelet 5-HT content pre- and post-initiation of SRI administration. Studies of platelet 5-HT content were reviewed in order to (1) determine the overall apparent bioeffect of SRIs; (2) compare bioeffect across types of SRIs; (3) compare the three approaches to assessing SRI bioeffect; and (4) determine how the findings might inform clinical practice.

METHODS

We performed a systematic review of the published studies that measured platelet 5-HT content to assess SRI bioeffect at the platelet SERT. Studies using neuroimaging and in vitro platelet 5-HT uptake to assess SRI bioeffect were reviewed for comparison purposes.

RESULTS

Clinical doses of SRIs typically resulted in 70-90% reductions in platelet 5-HT content. The observed bioeffect at the platelet SERT appeared similar among different SSRIs and SNRIs. The bioeffect estimations based on platelet 5-HT content were consistent with those obtained using neuroimaging to assess brain SERT occupancy and those based on the in vitro measurement of platelet 5-HT uptake.

CONCLUSIONS

In general, excellent agreement was seen in the apparent SRI bioeffect (70-90% inhibition) among the platelet 5-HT content studies and across the three bioeffect approaches. Theoretical and practical clinical implications are discussed.

A National Retrospective Study of Antidepressants' Effects on Overdose and Self-Harm Among Adults Treated With Opioid Analgesics

OBJECTIVE

Because individuals with a history of depression who are receiving opioids are at higher risk for adverse events, the authors examined whether antidepressant treatment reduces risk for overdose and self-harm among individuals with a history of depression who receive opioids.

METHODS

Commercial insurance claims of individuals with a history of depression receiving opioids from 2007 to 2017 were used to quantify the association between antidepressant fills and adverse events among individuals after initiation of opioid treatment; the authors accounted for selection into treatment and used discrete-time, proportional hazards survival models.

RESULTS

Among 283,374 adults with a history of depression treatment, 8,203 experienced 47,486 adverse events from 2007 to 2017 in the 12 months after initiation of opioid treatment. Approximately half (N=144,052, 50.8%) filled an antidepressant prescription at least once in the 12 months after the opioid episode began. Individuals receiving antidepressants for at least 6 weeks had a reduced risk for any adverse event (adjusted odds ratio [AOR]=0.79, 95% confidence interval [CI]=0.65-0.97) as well as a reduced risk for opioid overdoses (AOR=0.78, 95% CI=0.64-0.96), overdoses from nonopioid controlled substances (AOR=0.76, 95% CI=0.62-0.94), overdoses from other substances (AOR=0.79, 95% CI=0.65-0.97), and other self-harm events (AOR=0.82, 95% CI=0.67-1.00).

CONCLUSIONS

Individuals with a history of depression who received opioid analgesics had a significantly lower risk for overdose and self-harm after they had been taking antidepressants for at least 6 weeks. Universal screening for mood disorders among individuals receiving opioids, and promptly providing evidence-based depression treatment when appropriate, may reduce adverse events.

A unified model of ketamine's dissociative and psychedelic properties

Ketamine is an N-methyl-d-aspartate antagonist which is increasingly being researched and used as a treatment for depression. In low doses, it can cause a transitory modification in consciousness which was classically labelled as 'dissociation'. However, ketamine is also commonly classified as an atypical psychedelic and it has been recently reported that ego dissolution experiences during ketamine administration are associated with greater antidepressant response. Neuroimaging studies have highlighted several similarities between the effects of ketamine and those of serotonergic psychedelics in the brain; however, no unified account has been proposed for ketamine's multi-level effects - from molecular to network and psychological levels. Here, we propose that the fast, albeit transient, antidepressant effects observed after ketamine infusions are mainly driven by its acute modulation of reward circuits and sub-acute increase in neuroplasticity, while its dissociative and psychedelic properties are driven by dose- and context-dependent disruption of large-scale functional networks. Computationally, as nodes of the salience network (SN) represent high-level priors about the body ('minimal' self) and nodes of the default-mode network (DMN) represent the highest-level priors about narrative self-experience ('biographical' self), we propose that transitory SN desegregation and disintegration accounts for ketamine's 'dissociative' state, while transitory DMN desegregation and disintegration accounts for ketamine's 'psychedelic' state. In psychedelic-assisted psychotherapy, a relaxation of the highest-level beliefs with psychotherapeutic support may allow a revision of pathological self-representation models, for which neuroplasticity plays a permissive role. Our account provides a multi-level rationale for using the psychedelic properties of ketamine to increase its long-term benefits.

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.

Selective serotonin reuptake inhibitors: New hope in the fight against COVID-19

The emerging COVID-19 pandemic led to a dramatic increase in global mortality and morbidity rates. As in most infections, fatal complications of coronavirus affliction are triggered by an untrammeled host inflammatory response. Cytokine storms created by high levels of interleukin and other cytokines elucidate the pathology of severe COVID-19. In this respect, repurposing drugs that are already available and might exhibit anti-inflammatory effects have received significant attention. With the in vitro and clinical investigation of several studies on the effect of antidepressants on COVID-19 prognosis, previous data suggest that selective serotonin reuptake inhibitors (SSRIs) might be the new hope for the early treatment of severely afflicted patients. SSRIs' low cost and availability make them potentially eligible for COVID-19 repurposing. This review summarizes current achievements and literature about the connection between SSRIs administration and COVID-19 prognosis.

Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response

BACKGROUND

Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response.

METHODS

The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response.

RESULTS

Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups.

CONCLUSIONS

Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.

Serotonin modulates asymmetric learning from reward and punishment in healthy human volunteers

Instrumental learning is driven by a history of outcome success and failure. Here, we examined the impact of serotonin on learning from positive and negative outcomes. Healthy human volunteers were assessed twice, once after acute (single-dose), and once after prolonged (week-long) daily administration of the SSRI citalopram or placebo. Using computational modelling, we show that prolonged boosting of serotonin enhances learning from punishment and reduces learning from reward. This valence-dependent learning asymmetry increases subjects’ tendency to avoid actions as a function of cumulative failure without leading to detrimental, or advantageous, outcomes. By contrast, no significant modulation of learning was observed following acute SSRI administration. However, differences between the effects of acute and prolonged administration were not significant. Overall, these findings may help explain how serotonergic agents impact on mood disorders.

Two factors can drive learning: punishment of failures and reward of successes. Serotonin induces a valence-dependent learning asymmetry, as revealed by prolonged administering of SSRIs to healthy participants in a gambling task.

Protocol for the Ketamine for Postoperative Avoidance of Depressive Symptoms (K-PASS) feasibility study: A randomized clinical trial

Background: Postoperative depressive symptoms are associated with pain, readmissions, death, and other undesirable outcomes. Ketamine produces rapid but transient antidepressant effects in the perioperative setting. Longer infusions confer lasting antidepressant activity in patients with treatment-resistant depression, but it is unknown whether a similar approach may produce a lasting antidepressant effect after surgery. This protocol describes a pilot study that will assess the feasibility of conducting a larger scale randomized clinical trial addressing this knowledge gap. Methods: This single-center, double-blind, placebo-controlled pilot trial involves the enrollment of 32 patients aged 18 years or older with a history of depression scheduled for surgery with planned intensive care unit admission. On the first day following surgery and extubation, participants will be randomized to an intravenous eight-hour infusion of either ketamine (0.5 mg kg -1 over 10 minutes followed by a continuous rate of 0.3 mg kg -1 h -1) or an equal volume of normal saline. Depressive symptoms will be quantified using the Montgomery-Asberg Depression Rating Scale preoperatively and serially up to 14 days after the infusion. To detect ketamine-induced changes on overnight sleep architecture, a wireless headband will be used to record electroencephalograms preoperatively, during the study infusion, and after infusion. The primary feasibility endpoints will include the fraction of patients approached who enroll, the fraction of randomized patients who complete the study infusion, and the fraction of randomized patients who complete outcome data collection. Conclusions: This pilot study will evaluate the feasibility of a future large comparative effectiveness trial of ketamine to reduce depressive symptoms in postsurgical patients. Registration: K-PASS is registered on ClinicalTrials.gov: NCT05233566; registered February 10, 2022.

Resting-State fMRI in Predicting Response to Treatment With SSRIs in First-Episode, Drug-Naive Patients With Major Depressive Disorder

Objective

For major depressive disorder (MDD), there has been a lack of neuroimaging markers of efficacy of pharmacological treatment. In this study, we aimed to explore the neuroimaging mechanisms in patients with first-episode MDD and identify markers that predict the efficacy of 5-hydroxytryptamine reuptake inhibitors (SSRIs) with the use of resting-state brain imaging technology.

Methods

A total of 101 patients with first-episode MDD and 53 normal controls were finally included in this study. Based on the reduction rate of the score of Hamilton Depression Rating Scale (HAMD-17) during the 2-week SSRI treatment, 31 patients were assigned into the unresponsive group and 32 were assigned into the responsive group. The brain function was compared between patients with MDD and normal controls, and the diagnostic value of brain function was analyzed. With brain regions showing differences between patients with MDD and normal controls as a mask, and the brain function between the responsive and unresponsive groups were compared. Correlations between brain function the HAMD-17 score reduction rate during the 2-week SSRI treatment were analyzed.

Results

Compared to normal controls, patients with MDD showed increased ReHo in the left parahippocampal gyrus and right parahippocampal gyrus, decreased ReHo in the right middle occipital gyrus, and decreased functional connectivity between the right and left parahippocampal gyri, right middle occipital gyrus and middle temporal gyrus. Receiver operator characteristic (ROC) curve analysis showed that the area under the curve (AUC) was 0.544 (95% CI: 0.445–0.644) for ReHo and 0.822 (95% CI: 0.734–0.909) for functional connectivity. Logistic regression pooling of the differences in ReHo mean time series with the functional connectivity mean time series was performed for the ROC curve analysis, which showed an AUC of 0.832 (95% CI: 0.752–0.911). Compared to the responsive group, the unresponsive group showed elevated ReHo in the right parahippocampal gyrus and lower functional connectivity in the middle temporal gyrus. We also found that the ReHo value was negatively correlated with the HAMD-17 score reduction after 2 weeks of SSRI treatment.

Conclusion

Altered resting-state brain function in some regions might be a neurobiological marker for the diagnosis of MDD, and ReHo values are expected to be predictors of patient response to treatment with SSRIs.

Clinical Trial Registration

[http://www.chictr.org.cn/], identifier [ChiCTR1900028722].

Biomarkers for Deep Brain Stimulation in Animal Models of Depression

OBJECTIVES

Despite recent advances in depression treatment, many patients still do not respond to serial conventional therapies and are considered "treatment resistant." Deep brain stimulation (DBS) has therapeutic potential in this context. This comprehensive review of recent studies of DBS for depression in animal models identifies potential biomarkers for improving therapeutic efficacy and predictability of conventional DBS to aid future development of closed-loop control of DBS systems.

MATERIALS AND METHODS

A systematic search was performed in Pubmed, EMBASE, and Cochrane Review using relevant keywords. Overall, 56 animal studies satisfied the inclusion criteria.

RESULTS

Outcomes were divided into biochemical/physiological, electrophysiological, and behavioral categories. Promising biomarkers include biochemical assays (in particular, microdialysis and electrochemical measurements), which provide real-time results in awake animals. Electrophysiological tests, showing changes at both the target site and downstream structures, also revealed characteristic changes at several anatomic targets (such as the medial prefrontal cortex and locus coeruleus). However, the substantial range of models and DBS targets limits the ability to draw generalizable conclusions in animal behavioral models.

CONCLUSIONS

Overall, DBS is a promising therapeutic modality for treatment-resistant depression. Different outcomes have been used to assess its efficacy in animal studies. From the review, electrophysiological and biochemical markers appear to offer the greatest potential as biomarkers for depression. However, to develop closed-loop DBS for depression, additional preclinical and clinical studies with a focus on identifying reliable, safe, and effective biomarkers are warranted.

Dose-response effects of selective serotonin reuptake inhibitor monotherapy for the treatment of depression: systematic review of reviews and meta-narrative synthesis

Objective

To assess and clarify the relations between selective serotonin reuptake inhibitor (SSRI) dose efficacy, acceptability (early treatment discontinuation (dropouts)), and tolerability (reported adverse drug effects), and critically evaluate methods previously used to examine SSRI dose-response effects for the treatment of depression in adults.

Design

Systematic review of reviews and meta-narrative synthesis.

Data sources

Embase, Medline, PsycINFO, Scopus, and the Cochrane Collaboration library, from 1975 to December 2021. Reference lists of national depression treatment guidelines were systemically searched by hand.

Eligibility criteria for selecting studies

Reviews assessing SSRI monotherapy dose-response effects for the treatment of depression in adults (age ≥18 years) reporting efficacy, acceptability, or tolerability. Reviews meeting inclusion criteria had a high degree of heterogeneity, due to methodological diversity; therefore, a meta-narrative synthesis approach was applied. Standard daily doses were defined as 20 mg citalopram, fluoxetine, paroxetine; 50 mg sertraline; and 10 mg escitalopram. Risk of bias was assessed using the Risk of Bias in Systematic Reviews tool, in line with Cochrane recommendations.

Results

The search identified 9138 records; 387 full text reports were assessed for eligibility, 42 of which matched the inclusion criteria. The majority, 83% (n=35), of reviews included data for studies with a duration of ≤12 weeks (ie, the acute phase of depression treatment). Of 39 reviews assessing efficacy, the majority (n=26) indicated that individual SSRIs and SSRI class demonstrated flat dose-response effects; standard doses were optimal for efficacy. Acceptability or tolerability were assessed in 28 reviews. Higher than standard daily doses were associated with higher dropout rates and a greater incidence of adverse drug effects (eg, nausea, sexual dysfunction, fatigue, anxiety). Despite a range of methods being reported, there was an overall consensus regarding SSRI dose related efficacy, dropouts, and adverse drug effects.

Conclusion

Standard daily doses of SSRIs for the treatment of depression in adults provide a favourable balance between efficacy, acceptability, and tolerability. Patients are encouraged to talk to their prescriber or community pharmacist if they experience adverse effects or have any concerns about their drug treatments.

Probabilistic Reinforcement Learning and Anhedonia

Despite the prominence of anhedonic symptoms associated with diverse neuropsychiatric conditions, there are currently no approved therapeutics designed to attenuate the loss of responsivity to previously rewarding stimuli. However, the search for improved treatment options for anhedonia has been reinvigorated by a recent reconceptualization of the very construct of anhedonia, including within the Research Domain Criteria (RDoC) initiative. This chapter will focus on the RDoC Positive Valence Systems construct of reward learning generally and sub-construct of probabilistic reinforcement learning specifically. The general framework emphasizes objective measurement of a subject's responsivity to reward via reinforcement learning under asymmetrical probabilistic contingencies as a means to quantify reward learning. Indeed, blunted reward responsiveness and reward learning are central features of anhedonia and have been repeatedly described in major depression. Moreover, these probabilistic reinforcement techniques can also reveal neurobiological mechanisms to aid development of innovative treatment approaches. In this chapter, we describe how investigating reward learning can improve our understanding of anhedonia via the four RDoC-recommended tasks that have been used to probe sensitivity to probabilistic reinforcement contingencies and how such task performance is disrupted in various neuropsychiatric conditions. We also illustrate how reverse translational approaches of probabilistic reinforcement assays in laboratory animals can inform understanding of pharmacological and physiological mechanisms. Next, we briefly summarize the neurobiology of probabilistic reinforcement learning, with a focus on the prefrontal cortex, anterior cingulate cortex, striatum, and amygdala. Finally, we discuss treatment implications and future directions in this burgeoning area.

Risk of hospitalized depression and intentional self-harm with brand and authorized generic sertraline

BACKGROUND

Recent suggestions of therapeutic inequivalence of brand and generic sertraline have raised concerns about disproportionately higher adverse events among generic users.

OBJECTIVE

To assess the impact of confounding in a comparison of the risks of worsening depression and intentional self-harm (ISH) between users of brand name sertraline and its pharmaceutically equivalent authorized generic (AG).

METHODS

Using a retrospective new-user cohort design, we identified patients with a diagnosis code for depression aged ≥12 years who were continuously enrolled in a Sentinel Data Partner health plan for ≥180 days before their first sertraline dispensing between June 30, 2006 and September 30, 2015. New use was defined as no evidence of sertraline dispensing in the 180 days before index date. We matched each brand name user to up to 10 AG users using propensity scores (PS) and conducted case-centered logistic regression to assess the risks of hospitalized depression and ISH.

RESULTS

Before PS matching, brand name users were significantly less likely to be hospitalized for depression [Hazard Ratio (HR) = 0.70 (95% confidence interval (CI): 0.53-0.94)]. However, in the matched analysis, we observed no statistical difference between brand and AG users [HR = 0.84 (95% CI: 0.59-1.21)]. The risk of ISH did not significantly differ between the exposure groups in unmatched (HR = 0.99 (95% CI: 0.60-1.62) and matched analyses [HR = 0.91 (95% CI: 0.49-1.70).

CONCLUSION

In depressed patients receiving brand versus AG sertraline, patient characteristics confounded the association with hospitalization. Baseline differences were ameliorated by PS matching resulting in no statistical difference between brand and AG sertraline users.

Escitalopram modulates learning content-specific neuroplasticity of functional brain networks

Learning-induced neuroplastic changes, further modulated by content and setting, are mirrored in brain functional connectivity (FC). In animal models, selective serotonin reuptake inhibitors (SSRIs) have been shown to facilitate neuroplasticity. This is especially prominent during emotional relearning, such as fear extinction, which may translate to clinical improvements in patients. To investigate a comparable modulation of neuroplasticity in humans, 99 healthy subjects underwent three weeks of emotional (matching faces) or non-emotional learning (matching Chinese characters to unrelated German nouns). Shuffled pairings of the original content were subsequently relearned for the same time. During relearning, subjects received either a daily dose of the SSRI escitalopram or placebo. Resting-state functional magnetic resonance imaging was performed before and after the (re-)learning phases. FC changes in a network comprising Broca's area, the medial prefrontal cortex, the right inferior temporal and left lingual gyrus were modulated by escitalopram intake. More specifically, it increased the bidirectional connectivity between medial prefrontal cortex and lingual gyrus for non-emotional and the connectivity from medial prefrontal cortex to Broca's area for emotional relearning. The context dependence of these effects together with behavioral correlations supports the assumption that SSRIs in clinical practice improve neuroplasticity rather than psychiatric symptoms per se. Beyond expanding the complexities of learning, these findings emphasize the influence of external factors on human neuroplasticity.

Safety concerns on the abuse potential of esketamine: Multidimensional analysis of a new anti-depressive drug on the market

Prominent features of esketamine (e.g., similar mechanism of action as ketamine and target population) require to be vigilant regarding its benefits/risks balance and its risks of abuse in real-life settings. The aim of this study was to review all available pharmacological and clinical data to assess the abuse potential of esketamine shortly after its marketing. This multidimensional study is a quantitative and qualitative analysis of complementary data sources, ranging from preauthorization data (i.e., fundamental pharmacology and clinical trials) to real-life settings data (i.e., pharmacovigilance databases and web forums). According to esketamine pharmacology, its psychoactive effects play a role both in its therapeutic effect and its abuse potential. Only one out of the three short-term efficacy trials found a significant difference between esketamine and placebo in treatment-resistant depression. Beside adverse events that may be sought for abuse purpose (e.g., dissociation, sedation, euphoric mood, hallucination, feeling drunk, and derealization), clinical signs related to substance use disorder (e.g., tolerance, withdrawal syndrome, and drug dependence) and misuse (e.g., off-label use) were also identified in pharmacovigilance databases. Analysis of pharmacovigilance narratives and web forums showed that esketamine psychoactive effects are appreciated by some patients, while they are badly experienced by others. Strict compliance with the market authorization, close monitoring of patients by psychiatrists, and surveillance of any signs of misuse, abuse, or dependence must be part of any treatment course.

Changes in antidepressant therapy should be considered early in patients with inadequate response to a first-line agent

Deciding when and how to change treatment in patients with major depressive disorder who have inadequate response to initial antidepressant therapy is an important everyday clinical question. Here, we ask whether an early change of approach is superior to a delayed change. We consider the recommendations provided by recent guidelines, examine the evidence behind this guidance and suggest a decision tree to clarify treatment options and timing. Both the early and late-change strategies may have their place in clinical practice. However, we take the view that an earlier than currently usual change in antidepressant treatment should be considered more frequently in cases of non-response. Specific studies are needed to identify and to better understand predictors of early and late response.

Optimizing prediction of response to antidepressant medications using machine learning and integrated genetic, clinical, and demographic data

Major depressive disorder (MDD) is complex and multifactorial, posing a major challenge of tailoring the optimal medication for each patient. Current practice for MDD treatment mainly relies on trial and error, with an estimated 42-53% response rates for antidepressant use. Here, we sought to generate an accurate predictor of response to a panel of antidepressants and optimize treatment selection using a data-driven approach analyzing combinations of genetic, clinical, and demographic factors. We analyzed the response patterns of patients to three antidepressant medications in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, and employed state-of-the-art machine learning (ML) tools to generate a predictive algorithm. To validate our results, we assessed the algorithm's capacity to predict individualized antidepressant responses on a separate set of 530 patients in STAR*D, consisting of 271 patients in a validation set and 259 patients in the final test set. This assessment yielded an average balanced accuracy rate of 72.3% (SD 8.1) and 70.1% (SD 6.8) across the different medications in the validation and test set, respectively (p < 0.01 for all models). To further validate our design scheme, we obtained data from the Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) of patients treated with citalopram, and applied the algorithm's citalopram model. This external validation yielded highly similar results for STAR*D and PGRN-AMPS test sets, with a balanced accuracy of 60.5% and 61.3%, respectively (both p's < 0.01). These findings support the feasibility of using ML algorithms applied to large datasets with genetic, clinical, and demographic features to improve accuracy in antidepressant prescription.

Radiation Oncology Program Directors' Attitudes Toward Twenty-Seven Discrete Palliative Care Skills

Background: We evaluated radiation oncology residency program directors' attitudes toward discrete palliative care skills in effort to determine which skills should be prioritized in radiation oncology resident training. Design: We identified 93 U.S. radiation oncology residency program directors and sent them a survey through e-mail. The survey assessed views of 27 discrete palliative care skills in eight domains and was adapted from the American Society of Clinical Oncology/American Academy of Hospice and Palliative Medicine Guidance Statement defining high-quality primary palliative care in medical oncology. Using a nine-point scale, respondents rated each skill on three constructs: (1) importance to high-quality cancer care, (2) relevance of the skill to radiation oncology practice, and (3) importance to radiation oncology residency education. Skills were categorized as "Include" (median score ≥7 for all constructs), "Exclude" (median score ≤3 for all constructs), or "Uncertain" (all other skills) using a composite score of all constructs. Results: Twenty-nine program directors (response rate 31%) completed the survey. Of the 27 skills, 100% were rated as highly important to high-quality cancer care, 70% were rated as highly relevant to radiation oncology practice, and 81% were rated as highly important to resident education (median score ≥7). Using the composite score, 70% of skills were categorized as "Include." The domains of Caregiver Support (100%), End-of-Life Care (66%), and Spiritual/Cultural Assessment and Management (33%) had the highest proportions of skills rated as "Uncertain." Conclusions: The surveyed radiation oncology residency program directors generally value palliative care skills within radiation oncology.

Efficacy of Vortioxetine Monotherapy for Posttraumatic Stress Disorder: A Randomized, Placebo-Controlled Trial

PURPOSE/BACKGROUND

There are few efficacious pharmacological treatments for posttraumatic stress disorder (PTSD) and many patients fail to benefit from existing treatments. Vortioxetine, a recently developed antidepressant, acts as a serotonin modulator through inhibition of the serotonin transporter and actions at multiple types of serotonin receptors. Its unique pharmacodynamic profile suggests it may have efficacy for the treatment of PTSD.

METHODS/PROCEDURES

We conducted a 12-week placebo-controlled, randomized clinical trial of vortioxetine (flexibly dosed from 10 to 20 mg/d) versus placebo in adults with PTSD. The primary outcome was change from baseline in the past-month version of the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5), analyzed using a mixed-model repeated-measures analysis of variance.

FINDINGS/RESULTS

Forty-one patients were randomized, and 32 (78%) completed the 12 weeks of treatment. The mean reduction in CAPS-5 scores at week 12 did not significantly differ between the 2 arms; the effect size for the difference in changes between vortioxetine and placebo on CAPS-5 total scores at week 12 was Cohen d = 0.29. However, at week 8, the drug-placebo difference was d = 0.78, which met the multivariate criteria for statistical significance, P = 0.014.

IMPLICATIONS/CONCLUSIONS

In this study of 41 patients, vortioxetine did not demonstrate superiority over placebo for adults with PTSD. Future PTSD trials may benefit from stratifying the randomization based on number of years since the index traumatic event and a history of failure to respond to treatment.

The effects of KaiXinSan on depression and its association with lipid profiles: A randomized, double-blinded, placebo-controlled trial

BACKGROUND

Traditional Chinese medicine (TCM) KaiXinSan (KXS) has been used to treat depressed patients for a long time, but its potential underlying mechanisms have not been fully understood.

HYPOTHESIS

KXS could mitigate symptoms of patients with atypical depression at least partly via regulating lipid equilibrium.

METHODS

Patients meeting DSM-IV criteria for mild or moderate depression were assigned into placebo (N = 68) or KXS 3.2 g/day (N = 66) groups in a randomized, double-blinded, placebo-controlled, parallel clinical trial to investigate the anti-depressive efficacy of KXS and its association with serum lipid profile.

RESULTS

The HAMD score and SDS score at 8 weeks were significantly improved in KXS-treated patients the N-BACK accuracy rate was also increased after 8 weeks of KXS treatment compared with baseline. These results indicated that KXS not only improved the specific symptoms of depression, but also had a beneficial effect on cognitive function related working memory. More importantly, KXS treatment improved patients' lipid profile by reducing the ratios of LDL/HDL and ApoB/ApoA1 (p < 0.05), as well as ApoC3 level. Moreover, subgroup analysis found that HAMD score was significantly higher in patients with high lipid profile than in those with normal lipid profile, and lipid improvement after 8 weeks of KXS treatment was more obvious in depressed patients with high lipid profile than with normal lipid profile.

CONCLUSION

KXS could mitigate symptoms of patients with minor and modest depression at least partly via regulating lipid equilibrium. Its might shed light that KXS may likely contributes to depressed patients with other cardio-metabolic diseases.

The darkness and the light: diurnal rodent models for seasonal affective disorder

The development of animal models is a critical step for exploring the underlying pathophysiological mechanisms of major affective disorders and for evaluating potential therapeutic approaches. Although most neuropsychiatric research is performed on nocturnal rodents, differences in how diurnal and nocturnal animals respond to changing photoperiods, combined with a possible link between circadian rhythm disruption and affective disorders, has led to a call for the development of diurnal animal models. The need for diurnal models is most clear for seasonal affective disorder (SAD), a widespread recurrent depressive disorder that is linked to exposure to short photoperiods. Here, we briefly review what is known regarding the etiology of SAD and then examine progress in developing appropriate diurnal rodent models. Although circadian disruption is often invoked as a key contributor to SAD, a mechanistic understanding of how misalignment between endogenous circadian physiology and daily environmental rhythms affects mood is lacking. Diurnal rodents show promise as models of SAD, as changes in affective-like behaviors are induced in response to short photoperiods or dim-light conditions, and symptoms can be ameliorated by brief exposure to intervals of bright light coincident with activity onset. One exciting avenue of research involves the orexinergic system, which regulates functions that are disturbed in SAD, including sleep cycles, the reward system, feeding behavior, monoaminergic neurotransmission and hippocampal neurogenesis. However, although diurnal models make intuitive sense for the study of SAD and are more likely to mimic circadian disruption, their utility is currently hampered by a lack of genomic resources needed for the molecular interrogation of potential mechanisms.

An analog of psychedelics restores functional neural circuits disrupted by unpredictable stress

Psychological stress affects a wide spectrum of brain functions and poses risks for many mental disorders. However, effective therapeutics to alleviate or revert its deleterious effects are lacking. A recently synthesized psychedelic analog tabernanthalog (TBG) has demonstrated anti-addictive and antidepressant potential. Whether TBG can rescue stress-induced affective, sensory, and cognitive deficits, and how it may achieve such effects by modulating neural circuits, remain unknown. Here we show that in mice exposed to unpredictable mild stress (UMS), administration of a single dose of TBG decreases their anxiety level and rescues deficits in sensory processing as well as in cognitive flexibility. Post-stress TBG treatment promotes the regrowth of excitatory neuron dendritic spines lost during UMS, decreases the baseline neuronal activity, and enhances whisking-modulation of neuronal activity in the somatosensory cortex. Moreover, calcium imaging in head-fixed mice performing a whisker-dependent texture discrimination task shows that novel textures elicit responses from a greater proportion of neurons in the somatosensory cortex than do familiar textures. Such differential response is diminished by UMS and is restored by TBG. Together, our study reveals the effects of UMS on cortical neuronal circuit activity patterns and demonstrate that TBG combats the detrimental effects of stress by modulating basal and stimulus-dependent neural activity in cortical networks.

Cortical Thickness Predicts Response Following 2 Weeks of SSRI Regimen in First-Episode, Drug-Naive Major Depressive Disorder: An MRI Study

OBJECTIVE

Major depression disorder (MDD) is a harmful disorder, and the pathological mechanism remains unclear. The primary pharmacotherapy regimen for MDD is selective serotonin reuptake inhibitors (SSRIs), but fewer than 40% of patients with MDD are in remission following initial treatment. Neuroimaging biomarkers of treatment efficacy can be used to guide personalized treatment in MDD. This study aims to determine if cortical thickness can be used as a predictor for SSRIs.

METHODS

A total of 126 first-episode, drug-naive MDD patients (MDDs) and 71 healthy controls (HCs) were enrolled in our study. Demographic data were collected according to the self-made case report form (CRF) at the baseline of all subjects. Magnetic resonance imaging (MRI) scanning was performed for all the participants at baseline, and all imaging was processed using the DPABISurf software. All MDDs were treated with SSRIs, and symptoms were assessed at both the baseline and 2 weeks using the 17-item Hamilton Rating Scale (HAMD-17). According to HAMD-17 total score improvement from baseline to the end of 2 weeks, the MDDs were divided into the non-responder group (defined as ≤ 20% HAMD-17 reduction) and responder group (defined as ≥50% HAMD-17 reduction). The receiver operating characteristic (ROC) curve was used to analyze the diagnostic value of MDDs' and HCs' cortical thickness for MDD. Correlation analysis was performed for the responder group and the non-responder group separately to identify the relationship between cortical thickness and SSRI treatment efficacy. To analyze whether cortical thickness was sufficient to differentiate responders and non-responders at baseline, we used ROC curve analysis.

RESULTS

Significant decreases were found in the cortical thickness of the right supplementary motor area (SMA) in MDDs at the baseline (corrected by the Monte Carlo permutation correction, cluster-wise significant threshold at p < 0.025 and vertex-wise threshold at p = 0.001), area under the curve (AUC) = 0.732 [95% confidence interval (CI) = 0.233-0.399]. In the responder group, the cortical thickness of the right SMA was significantly thinner than in the non-responder group at baseline. There was a negative correlation (r = -0.373, p = 0.044) between the cortical thickness of SMA (0 weeks) and HAMD-17 reductive rate (2 weeks) in the responder group. The results of ROC curve analyses of the responder and non-responder groups were AUC = 0.885 (95% CI = 0.803-0.968), sensitivity = 73.5%, and specificity = 96.6%, and the cutoff value was 0.701.

CONCLUSION

Lower cortical thickness of the right SMA in MDD patients at the baseline may be a neuroimaging biomarker for MDD diagnosis, and a greater extent of thinner cortical thickness in the right SMA at baseline may predict improved SSRI treatment response. Our study shows the potential of cortical thickness as a possible biomarker that predicts a patient's clinical treatment response to SSRIs in MDD.

Cognitive neuropsychological theory of antidepressant action: a modern-day approach to depression and its treatment

Depression is a leading cause of disability worldwide and improving its treatment is a core research priority for future programmes. A change in the view of psychological and biological processes, from seeing them as separate to complementing one another, has introduced new perspectives on pathological mechanisms of depression and treatment mode of action. This review presents a theoretical model that incorporated this novel approach, the cognitive neuropsychological hypothesis of antidepressant action. This model proposes that antidepressant treatments decrease the negative bias in the processing of emotionally salient information early in the course of antidepressant treatment, which leads to the clinically significant mood improvement later in treatment. The paper discusses the role of negative affective biases in the development of depression and response to antidepressant treatments. It also discusses whether the model can be applied to other antidepressant interventions and its potential translational value, including treatment choice, prediction of response and drug development.

Treatment-Resistant Depression in a Real-World Setting: First Interim Analysis of Characteristics, Healthcare Resource Use, and Utility Values of the FondaMental Cohort

Background: Major depressive disorder (MDD) is among the most common psychiatric disorders. One-third of patients are usually unresponsive to several lines of treatment. This study aimed to describe the FondaMental French cohort of patients with treatment-resistant depression (TRD) and to estimate utility and healthcare resource use outcomes. Methods: Patients with TRD were evaluated prospectively over four years (baseline, 6, 12, 18, 24, 36 and 48 months) in a real-world clinical setting. Interim analyses focused on the first two consecutive years. Four MDD-related states (major depressive episode (MDE), response, remission, recovery) were defined based on the MADRS (Montgomery–Åsberg depression rating scale) and other clinical events. Health status was assessed with the EuroQol 5 Dimensions 5 Level (EQ-5D-5L) questionnaire. Utility values were estimated as preference measures that the patients assigned to their overall health status. Results: This study was based on 252 patients with TRD. The mean utility value by health state was 0.41, 0.63, 0.80, and 0.90, for MDE, response, remission, and recovery, respectively. At baseline, 59% of patients had an MADRS score of at least 28. Their baseline average utility value was lower compared to the other patients (0.43 versus 0.58, p < 0.001). This significant difference persisted at the following visits. The rate of patients in MDEs having at least one hospitalisation for depression or other reasons than depression was generally higher than that in the other health states. Conclusion: This study documented patterns in healthcare resource consumption, quality of life, and other characteristics in patients with TRD, both globally and by health state and depression severity.