Consistent superiority of selective serotonin reuptake inhibitors over placebo in reducing depressed mood in patients with major depression

Clinical validation of the self-reported 6-item Hamilton Depression Rating Scale (HAM-D6-SR) among inpatients

BACKGROUND

Brief and valid patient-rated symptom scales represent a valuable addition to clinician-rated scales for assessing depression. Studies on the psychometric properties of the self-rated 6-item Hamilton Depression Rating Scale (HAM-D6-SR) have shown promising results for outpatients with depression. The aim of the present study was to evaluate the psychometric properties of the HAM-D6-SR among inpatients using the clinician-rated 17-item Hamilton Rating Scale for Depression (HAMD17) as the gold standard.

METHODS

Inpatients with unipolar or bipolar depression completed the HAM-D6-SR and were subsequently rated on the HAM-D17 by trained raters, who were blind to the HAM-D6-SR ratings. The pairs of HAM-D6-SR and HAM-D17 ratings were completed twice during admission to evaluate responsiveness over time. Agreement between the HAM-D6-SR and the clinician-rated HAM-D17-derived HAM-D6 was evaluated using the intraclass correlation coefficient (ICC). Responsiveness was evaluated by means of the Spearman's rank correlation coefficient (rho).

RESULTS

A total of 102 participants completed the HAM-D6-SR at least once (median age: 41 years; 66 % females). The ICC for the HAM-D6-SR and the HAM-D17-derived HAM-D6 was 0.60 (95%CI = 0.30-0.76), with the ICC at the item level ranging from 0.13 (Psychomotor retardation) to 0.75 (Depressed mood). The correlation between the changes in the baseline-endpoint total scores on the HAM-D6-SR and HAM-D17-derived HAM-D6 was rho = 0.59 (p < 0.001).

LIMITATIONS

Test-retest reliability and structural validity were not evaluated.

CONCLUSIONS

The HAM-D6-SR holds promise as a valid self-report of core depressive symptoms among inpatients and may aid treatment decisions. However, the validity of self-reported psychomotor retardation was poor.

Investigation of core symptoms and symptom clusters in maintenance hemodialysis patients: A network analysis

PURPOSE

To construct a symptom network of maintenance hemodialysis patients and identify the core symptoms and core symptom clusters. Finally, this study provides a reference for accurate symptom management.

DESIGN AND METHOD

A correlational cross-sectional design. A total of 368 patients who underwent maintenance hemodialysis were enrolled from two hemodialysis centers in Chengdu, Sichuan Province, China. A symptom network was constructed with the R coding language to analyze the centrality index. Symptom clusters were extracted by exploratory factor analysis, and core symptom clusters were preliminarily determined according to the centrality index of the symptom network.

FINDINGS

The most common symptoms in maintenance hemodialysis patients were fatigue, dry skin, and pruritus. In the symptom network, headache had the highest mediation centrality (rB = 2.789) and closeness centrality (rC = 2.218) and the greatest intensity of numbness or tingling in the feet (rS = 1.952). A total of six symptom clusters were extracted, including pain and discomfort symptom clusters, emotional symptom clusters, gastrointestinal symptom clusters, sleep disorder symptom clusters, dry symptom clusters, and sexual dysfunction symptom clusters. The cumulative variance contribution rate was 69.269%.

CONCLUSIONS

Fatigue, dry skin, and pruritus are the sentinel symptoms of maintenance hemodialysis patients, headache is the core symptom and bridge symptom, and pain symptom clusters are the core symptom clusters of MHD patients. Nurses can develop interventions based on core symptoms and symptom clusters to improve the effectiveness of symptom management in maintenance hemodialysis patients.

CLINICAL RELEVANCE

Understanding the core symptoms and symptom groups that plague maintenance hemodialysis patients is critical to providing accurate symptom management. To ensure that maintenance hemodialysis patients receive effective support during treatment, reduce the adverse effects of symptoms, and improve the quality of life of patients.

Investigating the relationship between hippocampus/dentate gyrus volume and hypothalamus metabolism in participants with major depressive disorder

Reduced hippocampal volume occurs in major depressive disorder (MDD), potentially due to elevated glucocorticoids from an overactivated hypothalamus-pituitary-adrenal (HPA) axis. To examine this in humans, hippocampal volume and hypothalamus (HPA axis) metabolism was quantified in participants with MDD before and after antidepressant treatment. 65 participants (n = 24 males, n = 41 females) with MDD were treated in a double-blind, randomized clinical trial of escitalopram. Participants received simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI) before and after treatment. Linear mixed models examined the relationship between hippocampus/dentate gyrus volume and hypothalamus metabolism. Chi-squared tests and multivariable logistic regression examined the association between hippocampus/dentate gyrus volume change direction and hypothalamus activity change direction with treatment. Multiple linear regression compared these changes between remitter and non-remitter groups. Covariates included age, sex, and treatment type. No significant linear association was found between hippocampus/dentate gyrus volume and hypothalamus metabolism. 62% (38 of 61) of participants experienced a decrease in hypothalamus metabolism, 43% (27 of 63) of participants demonstrated an increase in hippocampus size (51% [32 of 63] for the dentate gyrus) following treatment. No significant association was found between change in hypothalamus activity and change in hippocampus/dentate gyrus volume, and this association did not vary by sex, medication, or remission status. As this multimodal study, in a cohort of participants on standardized treatment, did not find an association between hypothalamus metabolism and hippocampal volume, it supports a more complex pathway between hippocampus neurogenesis and hypothalamus metabolism changes in response to treatment.

Symptom clusters in adolescent depression and differential responses of clusters to pharmacologic treatment

OBJECTIVE

Symptoms of depression in adolescents are widely variable, but they are often interactive and clustered. The analysis of interactions and clusters among individual symptoms may help predict treatment outcomes. We aimed to determine clusters of individual symptoms in adolescent depression and their changes in the response to pharmacological treatment.

METHOD

A total of 95 adolescents, aged 12-17 years, with major depressive disorder were included. Participants were treated with escitalopram, and depressive symptoms were assessed at baseline (V1) and 1, 2, 4, 6, and 8 weeks (V6). The severity of depression was assessed using the Children's Depression Rating Scale-Revised. To construct network and clustering structures among symptoms, the Gaussian graphical model and Exploratory Graph Analysis with the tuning parameter to minimize the extended Bayesian information criterion were adopted.

RESULTS

Exploratory Graph Analysis revealed that symptoms of depression comprised four clusters: impaired activity, somatic concerns, subjective mood, and observed affect. The main effect of visit with decreased symptom severity was significant in all four clusters; however, the degree of symptom improvement differed among the four clusters. The effect size of score differences from V1 to V6 was the highest in the subjective mood (Cohen's d = 1.075), and lowest in impaired activity (d = 0.501) clusters.

CONCLUSION

The present study identified four symptom clusters associated with adolescent depression and their differential changes related to antidepressant treatment. This finding suggests that escitalopram was the most effective at improving subjective mood among different clusters. However, other therapeutic modalities may be needed to improve other clusters of symptoms, consequently leading to increased overall improvement of depression in adolescents.

Examining factors related to low performance of predicting remission in participants with major depressive disorder using neuroimaging data and other clinical features

Major depressive disorder (MDD), a prevalent mental health issue, affects more than 8% of the US population, and almost 17% in the young group of 18-25 years old. Since Covid-19, its prevalence has become even more significant. However, the remission (being free of depression) rates of first-line antidepressant treatments on MDD are only about 30%. To improve treatment outcomes, researchers have built various predictive models for treatment responses and yet none of them have been adopted in clinical use. One reason is that most predictive models are based on data from subjective questionnaires, which are less reliable. Neuroimaging data are promising objective prognostic factors, but they are expensive to obtain and hence predictive models using neuroimaging data are limited and such studies were usually in small scale (N<100). In this paper, we proposed an advanced machine learning (ML) pipeline for small training dataset with large number of features. We implemented multiple imputation for missing data and repeated K-fold cross validation (CV) to robustly estimate predictive performances. Different feature selection methods and stacking methods using 6 general ML models including random forest, gradient boosting decision tree, XGBoost, penalized logistic regression, support vector machine (SVM), and neural network were examined to evaluate the model performances. All predictive models were compared using model performance metrics such as accuracy, balanced accuracy, area under ROC curve (AUC), sensitivity and specificity. Our proposed ML pipeline was applied to a training dataset and obtained an accuracy and AUC above 0.80. But such high performance failed while applying our ML pipeline using an external validation dataset from the EMBARC study which is a multi-center study. We further examined the possible reasons especially the site heterogeneity issue.

The novel subtype of major depressive disorder characterized by somatic symptoms is associated with poor treatment efficacy and prognosis: A data-driven cluster analysis of a prospective cohort in China

BACKGROUND

There is not yet a valid and evidence-based system to classify patients with MDD into more homogeneous subtypes based on their clinical features. This study aims to identify symptom-based subtypes of MDD and investigate whether the treatment outcomes of those subtypes would be different.

METHOD

The cohort was established at 12 densely populated cities of China. A total of 1487 patients were enrolled. All participants were 18-65 years old and diagnosed with MDD. Participants were followed up at baseline, weeks 4, 8, and 12, and months 4 and 6. K-means algorithm was used to cluster patients with MDD according to clinical symptoms. The network analysis was adopted to characterize and compare the symptom patterns in the clusters. We also examined the associations between the clusters and the clinical outcomes.

RESULTS

The optimal number of the clusters was determined to be 2. Each cluster's maximum Jaccard Co-efficient was calculated to be >0.5 (cluster1 = 0.53, cluster 2 = 0.67). The symptom "depressed mood" and some other affective symptoms were the most prominent in cluster 1. Somatic symptoms, such as weight loss and general somatic symptoms, had the greatest expected influence in cluster 2. Compared with the response rates of the patients in the "somatic cluster", those of the patients in the "affective cluster" were significantly higher (P < 0.05).

CONCLUSIONS

Patients with MDD might be classified into two symptom-based subtypes featured with affective symptoms or somatic symptoms. The treatment efficacy and prognosis of the subtype featured with somatic symptoms may be worse.

Nitrogen-containing heterocyclic compounds: A ray of hope in depression?

Depression is not similar to daily mood fluctuations and temporary emotional responses to day-to-day activities. Depression is not a passing problem; it is an ongoing problem. It deals with different episodes consisting of several symptoms that last for at least 2 weeks. It can be seen for several weeks, months, or years. At its final stage, or can say, in its worst condition, it can lead to suicide. Antidepressants are used to inhibit the reuptake of the neurotransmitters by some selective receptors, which increase the concentration of specific neurotransmitters around the nerves in the brain. Drugs that are currently being used for the management of various types of depression include selective serotonin reuptake inhibitors, tricyclic antidepressants, atypical antidepressants, serotonin, noradrenaline reuptake inhibitors, etc. In this review, we have outlined different symptoms, causes, and recent advancements in nitrogen-containing heterocyclic drug candidates for the management of depression. This article highlights the various structural features along with the structure-activity relationship (SAR) of nitrogen-containing heterocyclics that play a key role in binding at target sites for potential antidepressant action. The in silico studies were carried out to determine the binding interactions of the target ligands with the receptor site to determine the potential role of substitution patterns at core pharmacophoric features. This article will help medicinal chemists, biochemists, and other interested researchers in identifying the potential pharmacophores as lead compounds for further development of new potent antidepressants.

Orbitofrontal and striatal metabolism, volume, thickness and structural connectivity in relation to social anhedonia in depression: A multimodal study

BACKGROUND

Social anhedonia is common within major depressive disorder (MDD) and associated with worse treatment outcomes. The orbitofrontal cortex (OFC) is implicated in both reward (medial OFC) and punishment (lateral OFC) in social decision making. Therefore, to understand the biology of social anhedonia in MDD, medial/lateral OFC metabolism, volume, and thickness, as well as structural connectivity to the striatum, amygdala, and ventral tegmental area/nucleus accumbens were examined. A positive relationship between social anhedonia and these neurobiological outcomes in the lateral OFC was hypothesized, whereas an inverse relationship was hypothesized for the medial OFC. The association between treatment-induced changes in OFC neurobiology and depression improvement were also examined.

METHODS

85 medication-free participants diagnosed with MDD were assessed with Wisconsin Schizotypy Scales to assess social anhedonia and received pretreatment simultaneous fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI), including structural and diffusion. Participants were then treated in an 8-week randomized placebo-controlled double-blind course of escitalopram. PET/MRI were repeated following treatment. Metabolic rate of glucose uptake was quantified from dynamic FDG-PET frames using Patlak graphical analysis. Structure (volume and cortical thickness) was quantified from structural MRI using Freesurfer. To assess structural connectivity, probabilistic tractography was performed on diffusion MRI and average FA was calculated within the derived tracts. Linear mixed models with Bonferroni correction were used to examine the relationships between variables.

RESULTS

A significantly negative linear relationship between pretreatment social anhedonia score and structural connectivity between the medial OFC and the amygdala (estimated coefficient: -0.006, 95 % CI: -0.0108 - -0.0012, p-value = 0.0154) was observed. However, this finding would not survive multiple comparisons correction. No strong evidence existed to show a significant linear relationship between pretreatment social anhedonia score and metabolism, volume, thickness, or structural connectivity to any of the regions examined. There was also no strong evidence to suggest significant linear relationships between improvement in depression and percent change in these variables.

CONCLUSIONS

Based on these multimodal findings, the OFC likely does not underlie social anhedonia in isolation and therefore should not be the sole target of treatment for social anhedonia. This is consistent with previous reports that other areas of the brain such as the amygdala and the striatum are highly involved in this behavior. Relatedly, amygdala-medial OFC structural connectivity could be a future target. The results of this study are crucial as, to our knowledge, they are the first to relate structure/function of the OFC with social anhedonia severity in MDD. Future work may need to involve a whole brain approach in order to develop therapeutics for social anhedonia.

Modulation of functional networks related to the serotonin neurotransmitter system by citalopram: Evidence from a multimodal neuroimaging study

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) potentiate serotonergic neurotransmission by blocking the serotonin transporter (5-HTT), but the functional brain response to SSRIs involves neural circuits beyond regions with high 5-HTT expression. Currently, it is unclear whether and how changes in 5-HTT availability after SSRI administration modulate brain function of key serotoninergic circuits, including those characterized by high availability of the serotonin 1A receptor (5-HT1AR).

AIM

We investigated the association between 5-HTT availability and 5-HTT- and 5-HT1AR-enriched functional connectivity (FC) after an acute citalopram challenge.

METHODS

We analyzed multimodal data from a dose-response, placebo-controlled, double-blind study, in which 45 healthy women were randomized into three groups receiving placebo, a low (4 mg), or high (16 mg) oral dose of citalopram. Receptor-Enhanced Analysis of functional Connectivity by Targets was used to estimate 5-HTT- and 5-HT1AR-enriched FC from resting-state and task-based fMRI. 5-HTT availability was determined using [123I]FP-CIT single-photon emission computerized tomography.

RESULTS

5-HTT availability was negatively correlated with resting-state 5-HTT-enriched FC, and with task-dependent 5-HT1AR-enriched FC. Our exploratory analyses revealed lower 5-HT1AR-enriched FC in the low-dose group compared to the high-dose group at rest and the placebo group during the emotional face-matching task.

CONCLUSIONS

Taken together, our findings provide evidence for differential links between 5-HTT availability and brain function within 5-HTT and 5-HT1AR pathways and in context- and dose-dependent manner. As such, they support a potential pivotal role of the 5-HT1AR in the effects of citalopram on the brain and add to its potential as a therapeutic avenue for mood and anxiety disturbances.

Effect of modernized collaborative care for depression on brain-derived neurotrophic factor (BDNF) and depressive symptom clusters: Data from the eIMPACT trial

Brain-derived neurotrophic factor (BDNF) levels are lower in people with depression and are normalized following pharmacological treatment. However, it is unknown if psychological treatments for depression improve BDNF and if change in BDNF is a mediator of intervention effects on depressive symptoms. Therefore, using data from the eIMPACT trial, we sought to determine the effect of modernized collaborative care for depression on 12-month changes in BDNF and cognitive/affective and somatic depressive symptom clusters and to examine whether BDNF changes mediate intervention effects on depressive symptoms. 216 primary care patients with depression from a safety net healthcare system were randomized to 12 months of the eIMPACT intervention (internet cognitive-behavioral therapy [CBT], telephonic CBT, and select antidepressant medications) or usual primary care. Plasma BDNF was measured with commercially available kits, and depressive symptom clusters were assessed by the Patient Health Questionnaire-9. The intervention did not influence BDNF but did improve both the cognitive/affective and somatic clusters over 12 months. Changes in BDNF did not mediate the intervention effect on either cluster. Our findings suggest that modernized collaborative care is an effective treatment for both the cognitive/affective and somatic symptoms of depression and that the mechanism of action is not improvements in BDNF. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02458690.

Practical pathway for the management of depression in the workplace: a Canadian perspective

Major depressive disorder (MDD) and other mental health issues pose a substantial burden on the workforce. Approximately half a million Canadians will not be at work in any week because of a mental health disorder, and more than twice that number will work at a reduced level of productivity (presenteeism). Although it is important to determine whether work plays a role in a mental health condition, at initial presentation, patients should be diagnosed and treated per appropriate clinical guidelines. However, it is also important for patient care to determine the various causes or triggers including work-related factors. Clearly identifying the stressors associated with the mental health disorder can help clinicians to assess functional limitations, develop an appropriate care plan, and interact more effectively with worker's compensation and disability programs, as well as employers. There is currently no widely accepted tool to definitively identify MDD as work-related, but the presence of certain patient and work characteristics may help. This paper seeks to review the evidence specific to depression in the workplace, and provide practical tips to help clinicians to identify and treat work-related MDD, as well as navigate disability issues.

Effectiveness of physical activity interventions for improving depression, anxiety and distress: an overview of systematic reviews

OBJECTIVE

To synthesise the evidence on the effects of physical activity on symptoms of depression, anxiety and psychological distress in adult populations.

DESIGN

Umbrella review.

DATA SOURCES

Twelve electronic databases were searched for eligible studies published from inception to 1 January 2022.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Systematic reviews with meta-analyses of randomised controlled trials designed to increase physical activity in an adult population and that assessed depression, anxiety or psychological distress were eligible. Study selection was undertaken in duplicate by two independent reviewers.

RESULTS

Ninety-seven reviews (1039 trials and 128 119 participants) were included. Populations included healthy adults, people with mental health disorders and people with various chronic diseases. Most reviews (n=77) had a critically low A MeaSurement Tool to Assess systematic Reviews score. Physical activity had medium effects on depression (median effect size=-0.43, IQR=-0.66 to -0.27), anxiety (median effect size=-0.42, IQR=-0.66 to -0.26) and psychological distress (effect size=-0.60, 95% CI -0.78 to -0.42), compared with usual care across all populations. The largest benefits were seen in people with depression, HIV and kidney disease, in pregnant and postpartum women, and in healthy individuals. Higher intensity physical activity was associated with greater improvements in symptoms. Effectiveness of physical activity interventions diminished with longer duration interventions.

CONCLUSION AND RELEVANCE

Physical activity is highly beneficial for improving symptoms of depression, anxiety and distress across a wide range of adult populations, including the general population, people with diagnosed mental health disorders and people with chronic disease. Physical activity should be a mainstay approach in the management of depression, anxiety and psychological distress.

PROSPERO REGISTRATION NUMBER

CRD42021292710.

A Three-Way Interaction of Sex, PER2 rs56013859 Polymorphism, and Family Maltreatment in Depressive Symptoms in Adolescents

The prevalence of depressive symptoms in adolescents is 12-18% and is twice as frequent in females. Sleep problems and thoughts of death are depressive symptoms or co-occurrent phenomena. Family maltreatment is a risk factor for later depressive symptoms and the period circadian regulator (PER) has been studied in relation to neurotransmitters, adaptation to stress, and winter depression. The purpose of this work was to study the relation of the three-way interactions of sex, PER2 rs56013859, and family maltreatment in relation to core depressive symptoms, sleep complaints, and thoughts of death and suicide in self-reports from a cohort of Swedish adolescents in 2012, 2015, and 2018. Cross-sectional and longitudinal analyses with linear and logistic regressions were used to study the relationships to the three outcomes. The three-way interaction was related to core depressive symptoms at both baseline and six years later. In contrast, the model did not show any relation to the other dependent variables. At 13-15 years, a sex-related differential expression was observed: females with the minor allele C:C/C:T exposed to family maltreatment showed higher levels of core depressive symptoms. Six years later, the trend was inverted among carriers of minor alleles.

Effect of modernized collaborative care for depression on depressive symptoms and cardiovascular disease risk biomarkers: eIMPACT randomized controlled trial

Although depression is a risk and prognostic factor for cardiovascular disease (CVD), clinical trials treating depression in patients with CVD have not demonstrated cardiovascular benefits. We proposed a novel explanation for the null results for CVD-related outcomes: the late timing of depression treatment in the natural history of CVD. Our objective was to determine whether successful depression treatment before, versus after, clinical CVD onset reduces CVD risk in depression. We conducted a single-center, parallel-group, assessor-blinded randomized controlled trial. Primary care patients with depression and elevated CVD risk from a safety net healthcare system (N = 216, Mage = 59 years, 78% female, 50% Black, 46% with income <$10,000/year) were randomized to 12 months of the eIMPACT intervention (modernized collaborative care involving internet cognitive-behavioral therapy [CBT], telephonic CBT, and/or select antidepressants) or usual primary care for depression (primary care providers supported by embedded behavioral health clinicians and psychiatrists). Outcomes were depressive symptoms and CVD risk biomarkers at 12 months. Intervention participants, versus usual care participants, exhibited moderate-to-large (Hedges' g = -0.65, p < 0.01) improvements in depressive symptoms. Clinical response data yielded similar results - 43% of intervention participants, versus 17% of usual care participants, had a ≥ 50% reduction in depressive symptoms (OR = 3.73, 95% CI: 1.93-7.21, p < 0.01). However, no treatment group differences were observed for the CVD risk biomarkers - i.e., brachial flow-mediated dilation, high-frequency heart rate variability, interleukin-6, high-sensitivity C-reactive protein, β-thromboglobulin, and platelet factor 4 (Hedges' gs = -0.23 to 0.02, ps ≥ 0.09). Our modernized collaborative care intervention - which harnessed technology to maximize access and minimize resources - produced clinically meaningful improvements in depressive symptoms. However, successful depression treatment did not lower CVD risk biomarkers. Our findings indicate that depression treatment alone may not be sufficient to reduce the excess CVD risk of people with depression and that alternative approaches are needed. In addition, our effective intervention highlights the utility of eHealth interventions and centralized, remote treatment delivery in safety net clinical settings and could inform contemporary integrated care approaches. Trial Registration:ClinicalTrials.gov Identifier: NCT02458690.

Effects of the dopamine depleting agent tetrabenazine in tests evaluating different components of depressive-like behavior in mice: sex-dependent response to antidepressant drugs with SERT and DAT blocker profiles

BACKGROUND

Depression is a disorder twice as common in women than in men. There are sex differences in the symptomatology and treatment response to this disorder. Impairments in behavioral activation (i.e. anergia, fatigue) are often seen in people with depression and are highly resistant to treatment. The role of mesolimbic dopamine (DA) in regulating behavioral activation has been extensively studied in male rodents, but little is known in female rodents.

OBJECTIVE

The present studies assessed potential sex differences in rodent paradigms used to study different components of depressive-like behavior, and in the treatment response to antidepressants with different mechanisms of action.

METHODS

Male and female CD1 mice received Tetrabenazine (TBZ), a VMAT-2 blocker that depletes DA and induces depressive symptoms in humans. Mice were tested on the Forced Swim Test, (FST), the Dark-Light box (DL), the elevated plus maze (EPM), Social Interaction (SI) test, and sucrose preference and consumption using the two bottles test. In addition, bupropion (a DA reuptake inhibitor) or fluoxetine (a serotonin reuptake inhibitor) were used to reverse TBZ-induced anergia.

RESULTS

In the FST, bupropion reversed TBZ effects in both sexes but fluoxetine was only effective in female mice. DA depletion did not affect other aspects of depression such as anxiety, sociability or sucrose consumption, and there was no interaction with bupropion on these parameters. In TBZ treated-females SERT-blockers may be effective at reversing anergia in aversive contexts (FST), and potentiating avoidance of anxiogenic stimuli.

CONCLUSIONS

Pro-dopaminergic antidepressants seem more efficacious at improving anergia in both sexes than SERT-blockers.

A critical evaluation of QIDS-SR-16 using data from a trial of psilocybin therapy versus escitalopram treatment for depression

BACKGROUND

In a recent clinical trial examining the comparative efficacy of psilocybin therapy (PT) versus escitalopram treatment (ET) for major depressive disorder, 14 of 16 major efficacy outcome measures yielded results that favored PT, but the Quick Inventory of Depressive Symptomatology, Self-Report, 16 items (QIDS-SR16) did not.

AIMS

The present study aims to (1) rationally and psychometrically account for discrepant results between outcome measures and (2) to overcome psychometric problems particular to individual measures by re-examining between-condition differences in depressive response using all outcome measures at item-, facet-, and factor-levels of analysis.

METHOD

Four depression measures were compared on the basis of their validity for examining differences in depressive response between PT and ET conditions.

RESULTS/OUTCOMES

Possible reasons for discrepant findings on the QIDS-SR16 include its higher variance, imprecision due to compound items and whole-scale and unidimensional sum-scoring, vagueness in the phrasing of scoring options for items, and its lack of focus on a core depression factor. Reanalyzing the trial data at item-, facet-, and factor-levels yielded results suggestive of PT's superior efficacy in reducing depressed mood, anhedonia, and a core depression factor, along with specific symptoms such as sexual dysfunction.

CONCLUSION/INTERPRETATION

Our results raise concerns about the adequacy of the QIDS-SR16 for measuring depression, as well as the practice of relying on individual scales that tend not to capture the multidimensional structure or core of depression. Using an alternative approach that captures depression more granularly and comprehensively yielded specific insight into areas where PT therapy may be particularly useful to patients and clinicians.

The genetic basis of major depressive disorder

The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.

Associations between specific depressive symptoms and psychosocial functioning in psychotherapy

BACKGROUND

Psychotherapy for depression aims to reduce symptoms and to improve psychosocial functioning. We examined whether some symptoms are more important than others in the association between depression and functioning over the course of psychotherapy treatment.

METHODS

We studied associations between specific symptoms of depression (PHQ-9) and change in social and occupational functioning (SOFAS), both with structural equation models (considering liabilities of depression and each specific symptom) and with logistic regression models (considering the risk for individual patients). The study sample consisted of adult patients (n = 771) from the Finnish Psychotherapy Quality Registry (FPQR) who completed psychotherapy treatment between September 2018 and September 2021.

RESULTS

Based on our results of logistic regression analyses and SEM models, the baseline measures of depression symptoms were not associated with changes in functioning. Changes in depressed mood or hopelessness, problems with sleep, feeling tired, and feeling little interest or pleasure were associated with improved functioning during psychotherapy. The strongest evidence for symptom-specific effects was found for the symptom of depressed mood or hopelessness.

LIMITATIONS

Due to our naturalistic study design containing only two measurement points, we were unable to study the causal relationship between symptoms and functioning.

CONCLUSIONS

Changes in certain symptoms during psychotherapy may affect functioning independently of underlying depression. Knowledge about the dynamics between symptoms and functioning could be used in treatment planning or implementation. Depressed mood or hopelessness appears to have a role in the dynamic relationship between depression and functioning.

The complex clinical response to selective serotonin reuptake inhibitors in depression: a network perspective

The clinical response to selective serotonin reuptake inhibitors (SSRIs) in depression takes weeks to be fully developed and is still not entirely understood. This study aimed to determine the direct and indirect effects of SSRIs relative to a placebo control condition on clinical symptoms of depression. We included data of 8262 adult patients with major depression participating in 28 industry-sponsored US Food and Drug Administration (FDA) registered trials on the efficacy of SSRIs. Clinical symptoms of depression were assessed by the 17 separate items of the Hamilton Depression Rating Scale (HDRS) after 1, 2, 3, 4 and 6 weeks of treatment. Network estimation techniques showed that SSRIs had quick and strong direct effects on the two affective symptoms, i.e., depressed mood and psychic anxiety; direct effects on other symptoms were weak or absent. Substantial indirect effects were found for all four cognitive symptoms, which showed larger reductions in the SSRI condition but mainly in patients reporting larger reductions in depressed mood. Smaller indirect effects were found for two arousal/somatic symptoms via the direct effect on psychic anxiety. Both direct and indirect effects on sleep problems and most arousal/somatic symptoms were weak or absent. In conclusion, our study revealed that SSRIs primarily caused reductions in affective symptoms, which were related to reductions in mainly cognitive symptoms and some specific arousal/somatic symptoms. The results can contribute to disclosing the mechanisms of action of SSRIs, and has the potential to facilitate early detection of responders and non-responders in clinical practice.

Differential symptom cluster responses to repetitive transcranial magnetic stimulation treatment in depression

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) can target specific neural circuits, which may allow for personalized treatment of depression. Treatment outcome is typically determined using sum scores from validated measurement scales; however, this may obscure differential improvements within distinct symptom domains. The objectives for this work were to determine: (1) whether a standard depression measure can be represented using a four symptom cluster model and (2) whether these symptom clusters had a differential response to rTMS treatment.

METHODS

Data were obtained from two multi-centre randomized controlled trials of rTMS delivered to the left dorsolateral prefrontal cortex (DLPFC) for participants with treatment-resistant depression (TRD) conducted in Canada (THREE-D [Conducted between Sept 2013, and Oct 2016] and CARTBIND [Conducted between Apr 2016 and Feb 2018]). The first objective used confirmatory factor analytic techniques, and the second objective used a linear mixed effects model. Trial Registration: NCT01887782, NCT02729792.

FINDINGS

In the total sample of 596 participants with TRD, we found a model consisting of four symptom clusters adequately fit the data. The primary analysis using the THREE-D treatment trial found that symptom clusters demonstrated a differential response to rTMS treatment (F(3,5984) = 31.92, p < 0.001). The anxiety symptom cluster was significantly less responsive to treatment than other symptom clusters (t(6001) = -8.02, p < 0.001). These findings were replicated using data from the CARTBIND trial.

INTERPRETATION

There are distinct symptom clusters experienced by individuals with TRD that have a differential response to rTMS. Future work will determine whether differing rTMS treatment targets have distinct patterns of symptom cluster responses with the eventual goal of personalizing rTMS protocols based on an individual's clinical presentation.

FUNDING

Canadian Institutes of Health Research, Brain Canada.

Involvement of inflammatory responses in the brain to the onset of major depressive disorder due to stress exposure

Major depressive disorder (MDD) is a multifactorial disease affected by several environmental factors. Although several potential onset hypotheses have been identified, the molecular mechanisms underlying the pathogenesis of this disorder remain unclear. Several recent studies have suggested that among many environmental factors, inflammation and immune abnormalities in the brain or the peripheral tissues are associated with the onset of MDDs. Furthermore, several stress-related hypotheses have been proposed to explain the onset of MDDs. Thus, inflammation or immune abnormalities can be considered stress responses that occur within the brain or other tissues and are regarded as one of the mechanisms underlying the stress hypothesis of MDDs. Therefore, we introduce several current advances in inflammation studies in the brain that might be related to the pathophysiology of MDD due to stress exposure in this review.

Consumption and ocurrence of antidepressants (SSRIs) in pre- and post-COVID-19 pandemic, their environmental impact and innovative removal methods: A review

Selective serotonin reuptake inhibitors (SSRIs) are pharmaceuticals whose consumption has increased significantly. They are prescribed as first-line treatment in mental disorders such as depression, obsessive-compulsive disorder, phobias, and anxiety; also, they are indicated as adjuvants in diseases such as fibromyalgia and bulimia nervosa. In addition to being linked to the illegal market to be consumed as recreational drugs. The relevance of this review lies in the fact that worldwide consumption has increased significantly during the COVID-19 pandemic, due to the depression and anxiety that originated in the population. As a consequence of this increase in consumption, concentrations of SSRIs in the environment have increased, and these have become a relevant issue for toxicologists due to the effects that they could generate in different organisms, both aquatic and terrestrial. For this reason, the objective of this article was to do a critical evaluation of the existing data on the characteristics and physicochemical properties of SSRIs, consumption data during the COVID-19 pandemic, its occurrence in the environment and the reports of toxic effects that have been generated in different organisms; we also conclude with an updated review of different methods that have been used for their removal. With this analysis, it can be concluded that, despite SSRIs are pharmaceutical products widely studied since their launching to the market, still currently under investigation to clarify their mechanisms of action to understand the different effects on the organisms, adverse reactions, as well as possible toxicological effects on non-target organisms. On the other hand, it has been proven that although it is already possible to eliminate a significant percentage of SSRIs in the laboratory, due to their physicochemical characteristics and their behavior in complex mixtures in the environment, they have not yet been eradicated, showing a persistence in the soil, subsoil and surface waters of the entire planet that may represent a future risk.

Effectiveness of Pharmacotherapy for Depression after Adult Traumatic Brain Injury: an Umbrella Review

Symptoms of depression are common following traumatic brain injury (TBI), impacting survivors' ability to return to work, participate in leisure activities, and placing strain on relationships. Depression symptoms post TBI are often managed with pharmacotherapy, however, there is little research evidence to guide clinical practice. There have been a number of recent systematic reviews examining pharmacotherapy for post TBI depression. The aim of this umbrella review was to synthesize systematic reviews and meta-analyses of the effectiveness of pharmacotherapy for the management of post TBI depression in adults. Eligible reviews examined any pharmacotherapy against any comparators, for the treatment of depression in adults who had sustained TBI. Seven databases were searched, with additional searching of online journals, Research Gate, Google Scholar and the TRIP Medical Database to identify published and unpublished systematic reviews and meta-analyses in English up to May 2020. A systematic review of primary studies available between March 2018 and May 2020 was also conducted. Evidence quality was assessed using Joanna Briggs Institute Critical Appraisal Instruments. The results are presented as a narrative synthesis. Twenty-two systematic reviews were identified, of which ten reviews contained a meta-analysis. No new primary studies were identified in the systematic review. There was insufficient high quality and methodologically rigorous evidence to recommend prescribing any specific drug or drug class for post TBI depression. The findings do show, however, that depression post TBI is responsive to pharmacotherapy in at least some individuals. Recommendations for primary studies, systematic reviews and advice for prescribers is provided. Review Registration PROSPERO (CRD42020184915).

Impact of chosen cutoff on response rate differences between selective serotonin reuptake inhibitors and placebo

Response defined as a 50% reduction in the sum score of the Hamilton Depression Rating Scale (HDRS-17-sum) is often used to assess the efficacy of antidepressants. Critics have, however, argued that dichotomising ratings with a cutoff close to the median may lead to scores clustering on either side, the result being inflation of miniscule drug-placebo differences. Using pooled patient-level data sets from trials of three selective serotonin reuptake inhibitors (SSRIs) (citalopram, paroxetine and sertraline) (n = 7909), and from similar trials of duloxetine (n = 3478), we thus assessed the impact of different cutoffs on response rates. Response criteria were based on (i) HDRS-17-sum, (ii) the sum score of the HDRS-6 subscale (HDRS-6-sum) and (iii) the depressed mood item. The separation between SSRI and placebo with respect to response rates increased when HDRS-17-sum was replaced by HDRS-6-sum or depressed mood as effect parameter and was markedly dependent on SSRI dose. With the exception of extreme cutoff values, differences in response rates were largely similar regardless of where the cutoff was placed, and also not markedly changed by the exclusion of subjects close to the selected cutoff (e.g., ±10%). The observation of similar response rate differences between active drugs and placebo for different cutoffs was corroborated by the analysis of duloxetine data. In conclusion, the suggestion that using a cutoff close to the median when defining response has markedly overestimated the separation between antidepressants and placebo may be discarded.

Integrative omics analysis identifies differential biological pathways that are associated with regional grey matter volume changes in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is accompanied by alterations in grey matter volume. However, the biological processes associated with regional structural perturbations remain elusive.

METHODS

We applied integrative omics analysis to investigate specialized transcriptome signatures and translational determinants associated with regional grey matter variations in 2737 MDD patients relative to 3098 controls by summarizing the results from gene co-expression network analysis of Allen human brain transcriptome profiles in six donors, enrichment analysis of gene-sets and cellular structure from rodents and mediation analysis of BrainSpan proteome profile in six donors.

RESULTS

We found convergent alterations of grey matter volume in MDD were associated with transcriptome profiles enriched for synaptic transmission, metabolism, immune processes and transmembrane transport. Genes with abnormal expression in post-mortem tissue in MDD were also associated with transcriptome signatures. Further gene co-expression network and enrichment analysis of MDD-related genes in these signatures revealed the modules with higher neuronal expression were enriched in the medial temporal cortex and temporo-parietal junction with genes differentially associated with neuronal development and metabolism. Also, the modules with higher non-neuronal (e.g. astrocyte and oligodendrocyte) expression were concentrated in the rostral and dorsal anterior cingulate cortex and were separately associated with immune response and transmembrane transport. Moreover, proteins as the gene expression products mediated the association between transcriptome signatures and brain volume changes in the visual and dorsolateral prefrontal cortex.

CONCLUSIONS

Our multidimensional analyses offer a novel approach to detect specific biological pathways that capture regional structural variations in MDD, which suggests structural endophenotypes associated with MDD.

Estimates of the minimal important difference to evaluate the clinical significance of antidepressants in the acute treatment of moderate-to-severe depression

The efficacy of antidepressants in the acute treatment of moderate-to-severe depression remains a controversial issue. The minimal important difference (MID) is relevant to judge the clinical significance of treatment effects. In this analysis paper, we discuss estimates of the MID for common depression outcome measures.For the Hamilton Depression Rating Scale 17-item Version (HDRS-17), according to both anchor-based and distribution-based approaches, MID estimates range from 3 to 8 points, and the most accurate values are likely between 3 and 5 points. For the 6-item version (HDRS-6), MID estimates range between 2 and 4 points. For both the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Beck Depression Inventory II (BDI-II), MID estimates range between 3 and 9 points, with estimates of 3-6 points likely being the most accurate. Quality of life appears to be more important to patients than core depression symptoms. We thus also evaluated the Short-Form 36 (SF-36) mental component score, a popular mental-health-related quality of life measure. Its MID estimate is likely about 5 points. By contrast, the average treatment effects of antidepressants on the HDRS-17, HDRS-6, MADRS, BDI-II and SF-36 are 2 points, 1.5 points, 3 points, 2 points and 3-5 points, respectively.In conclusion, the efficacy of antidepressants in the acute treatment of moderate-to-severe depression consistently fails to exceed the lower bound of the MID estimates for common depression outcome measures. The clinical significance of antidepressants thus remains uncertain and we call for more research on quality of life measures, which are the patients' most valued outcome domains.

Selective serotonin reuptake inhibitors and suicidal behaviour: a population-based cohort study

There is concern that selective serotonin reuptake inhibitor (SSRI) treatment may increase the risk of suicide attempts or deaths, particularly among children and adolescents. However, debate remains regarding the nature of the relationship. Using nationwide Swedish registers, we identified all individuals aged 6-59 years with an incident SSRI dispensation (N = 538,577) from 2006 to 2013. To account for selection into treatment, we used a within-individual design to compare the risk of suicide attempts or deaths (suicidal behaviour) in time periods before and after SSRI-treatment initiation. Within-individual incidence rate ratios (IRRs) of suicidal behaviour were estimated. The 30 days before SSRI-treatment initiation was associated with the highest risk of suicidal behaviour compared with the 30 days 1 year before SSRI initiation (IRR = 7.35, 95% CI 6.60-8.18). Compared with the 30 days before SSRI initiation, treatment periods after initiation had a reduced risk-the IRR in the 30 days after initiation was 0.62 (95% CI 0.58-0.65). The risk then declined over treatment time. These patterns were similar across age strata, and when stratifying on history of suicide attempts. Initiation with escitalopram was associated with the greatest risk reduction, though CIs for the IRRs of the different SSRI types were overlapping. The results do not suggest that SSRI-treatment increases the risk for suicidal behaviour in either youths or adults; rather, it may reduce the risk. Further research with different study designs and in different populations is warranted.

Affective and somatic symptom clusters in depression and their relationship to treatment outcomes in the STAR*D sample

BACKGROUND

The heterogenous nature of depression continues to stymie efforts to identify biomarkers or predict treatment response. Efforts leveraging large datasets to define more uniform subtypes of depression or subgroups of depressed patients have considered only small subsets of symptoms. We aimed to understand how inclusion of more diverse complaints would impact data-emergent symptom and patient clusters.

METHODS

We applied principal components analysis to baselineInventory of Depressive Symptomatology data from 1491 patients with major depressive disorder to derive naturally co-occurring symptom subsets before utilizing k-means clustering to divide patients into groups based on standardized residuals of each symptom subset score. We evaluated the clinical utility of our approach by comparing how cluster membership impacted response to citalopram.

RESULTS

Prinicpal components analysis identified nine naturally co-occurring symptom subsets: core affective symptoms, appetite/weight loss, anxiety, somatic symptoms, insomnia, negative intrusive thoughts, leaden paralysis/mood quality, diurnal mood variation, and irritability. Cluster analysis identified two patient groups, differing significantly in 7 of 9 c symptom subsets. Patients distinguished by the prominence of somatic versus core affective symptoms exhibited less reduction in depression severity with citalopram treatment.

LIMITATIONS

Results depend not only on raw data, but also parameter selection, and interpretation. Replication is indicated.

CONCLUSIONS

Findings are consistent with previous reports linking somatic symptoms to treatment resistance and demonstrating that SSRIs are most effective in treating affective symptoms. A novel distinction between physical somatic symptoms and psychic anxiety highlights the utility of assessing a broad spectrum of symptoms when exploring heterogeneity in depression and the need for treatments targeting physical somatic symptoms specifically.

Pharmacogenomics-Guided Pharmacotherapy in Patients with Major Depressive Disorder or Bipolar Disorder Affected by Treatment-Resistant Depressive Episodes: A Long-Term Follow-up Study

Treatment-resistant depression (TRD) reduces affected patients’ quality of life and leads to important social health care costs. Pharmacogenomics-guided treatment (PGT) may be effective in the cure of TRD. The main aim of this study was to evaluate the clinical changes after PGT in patients with TRD (two or more recent failed psychopharmacological trials) affected by bipolar disorder (BD) or major depressive disorder (MDD) compared to a control group with treatment as usual (TAU). We based the PGT on assessing different gene polymorphisms involved in the pharmacodynamics and pharmacokinetics of drugs. We analyzed, with a repeated-measure ANOVA, the changes between the baseline and a 6 month follow-up of the efficacy index assessed through the Clinical Global Impression (CGI) scale, and depressive symptoms through the Hamilton Depression Rating Scale (HDRS). The PGT sample included 53 patients (26 BD and 27 MDD), and the TAU group included 52 patients (31 BD and 21 MDD). We found a significant within-subject effect of treatment time on symptoms and efficacy index for the whole sample, with significant improvements in the efficacy index (F = 8.544; partial η² = 0.077, p < 0.004) and clinical global impression of severity of illness (F = 6.818; partial η² = 0.062, p < 0.01) in the PGT vs. the TAU group. We also found a significantly better follow-up response (χ² = 5.479; p = 0.019) and remission (χ² = 10.351; p = 0.001) rates in the PGT vs. the TAU group. PGT may be an important option for the long-term treatment of patients with TRD affected by mood disorders, providing information that can better define drug treatment strategies and increase therapeutic improvement.

Evaluating the efficacy and moderators of algorithm-guided antidepressant treatments of major depressive disorder

BACKGROUND

In spite of numerous options, the most efficacious treatment for major depressive disorder (MDD) remains elusive. Algorithm-guided treatments (AGTs) are proposed to address inadequate remission and optimize treatment delivery. This study aimed to evaluate the clinical benefit of AGTs for MDD, and to explore specific moderators of treatment outcomes for individual patients.

METHODS

The study recruited 987 patients with MDD across eight hospitals who were randomly assigned to AGT with escitalopram (AGT-E), AGT with mirtazapine (AGT-M), or treatment-as-usual (TAU). The outcomes were symptom remission, response rate, early improvement rate, subsymptom clusters improvement over time, the mean time to first remission, relapse rate at 6-months posttreatment follow-up, quality of life (QOL), and adverse events.

RESUTLS

No significant differences were observed across groups in outcome, except that TAU showed significantly poorer QOL, higher relapse rates at 6-months posttreatment follow-up, and marginally significantly worse maximal burden of adverse events than the AGT groups. After 6 weeks of treatment initiation, remission rate did not significantly increase with extended treatment. AGT-M outperformed the TAU and AGT-E in treating sleep symptoms. AGT-E was less effective than AGT-M and TAU in patients with severe depression and somatic symptoms (DSSS). The superiority of TAU over AGTs was observed in recurrent MDD patients.

CONCLUSION

Although the superiority of AGTs over TAU was limited by failure of alternative subsequent treatment, AGTs outperformed in QOL and relapse rate. Types of disease episode and DSSS were regarded as specific moderators in treatment of depression. These findings might contribute to future research on targeted antidepressant treatment.

Use of central nervous system drugs in combination with selective serotonin reuptake inhibitor treatment: A Bayesian screening study for risk of suicidal behavior

BACKGROUND

Using other central nervous system (CNS) medications in combination with selective serotonin reuptake inhibitor (SSRI) treatment is common. Despite this, there is limited evidence on the impact on suicidal behavior of combining specific medications. We aim to provide evidence on signals for suicidal behavior risk when initiating CNS drugs during and outside of SSRI treatment.

MATERIALS AND METHODS

Using a linkage of Swedish national registers, we identified a national cohort of SSRI users aged 6-59 years residing in Sweden 2006-2013. We used a two-stage Bayesian Poisson model to estimate the incidence rate ratio (IRR) of suicidal behavior in periods up to 90 days before and after a CNS drug initiation during SSRI treatment, while accounting for multiple testing. For comparison, and to assess whether there were interactions between SSRIs and other CNS drugs, we also estimated the IRR of initiating the CNS drug without SSRI treatment.

RESULTS

We identified 53 common CNS drugs initiated during SSRI treatment, dispensed to 262,721 individuals. We found 20 CNS drugs with statistically significant IRRs. Of these, two showed a greater risk of suicidal behavior after versus before initiating the CNS drug (alprazolam, IRR = 1.39; flunitrazepam, IRR = 1.83). We found several novel signals of drugs that were statistically significantly associated with a reduction in the suicidal behavior risk. We did not find evidence of harmful interactions between SSRIs and the selected CNS drugs.

CONCLUSION

Several of the detected signals for reduced risk correspond to drugs where there is previous evidence of benefit for antidepressant augmentation (e.g., olanzapine, quetiapine, lithium, buspirone, and mirtazapine). Novel signals of reduced suicidal behavior risk, including for lamotrigine, valproic acid, risperidone, and melatonin, warrant further investigation.

Expectancy effects on serotonin and dopamine transporters during SSRI treatment of social anxiety disorder: a randomized clinical trial

It has been extensively debated whether selective serotonin reuptake inhibitors (SSRIs) are more efficacious than placebo in affective disorders, and it is not fully understood how SSRIs exert their beneficial effects. Along with serotonin transporter blockade, altered dopamine signaling and psychological factors may contribute. In this randomized clinical trial of participants with social anxiety disorder (SAD) we investigated how manipulation of verbally-induced expectancies, vital for placebo response, affect brain monoamine transporters and symptom improvement during SSRI treatment. Twenty-seven participants with SAD (17 men, 10 women), were randomized, to 9 weeks of overt or covert treatment with escitalopram 20 mg. The overt group received correct treatment information whereas the covert group was treated deceptively with escitalopram, described as an active placebo in a cover story. Before and after treatment, patients underwent positron emission tomography (PET) assessments with the [11C]DASB and [11C]PE2I radiotracers, probing brain serotonin (SERT) and dopamine (DAT) transporters. SAD symptoms were measured by the Liebowitz Social Anxiety Scale. Overt was superior to covert SSRI treatment, resulting in almost a fourfold higher rate of responders. PET results showed that SERT occupancy after treatment was unrelated to anxiety reduction and equally high in both groups. In contrast, DAT binding decreased in the right putamen, pallidum, and the left thalamus with overt SSRI treatment, and increased with covert treatment, resulting in significant group differences. DAT binding potential changes in these regions correlated negatively with symptom improvement. Findings support that the anxiolytic effects of SSRIs involve psychological factors contingent on dopaminergic neurotransmission while serotonin transporter blockade alone is insufficient for clinical response.

Determining maximal achievable effect sizes of antidepressant therapies in placebo-controlled trials

OBJECTIVE

Antidepressants outperform placebo with an effect size of around 0.30. It has been suggested that effect sizes as high as 0.875 are necessary for a minimal clinically important difference. Whether such effect sizes are achievable in placebo-controlled trials is unknown. Therefore, we aimed to assess what effect sizes are theoretically achievable in placebo-controlled trials of antidepressants.

METHODS

Patient-level analyses comparing Hamilton Depression Rating Scale (HDRS-17) outcomes for simulated antidepressant therapies to placebo-treated participants (n = 2201) from clinical trials of selective serotonin reuptake inhibitors.

RESULTS

An optimally effective antidepressant, where all treated participants achieve HDRS-17 scores comparable to those displayed by healthy volunteers (remission-type model), had a maximum effect size of 1.75, with a mean difference of 11.6 points on the HDRS-17. In simulations where patients received an additional 50% symptom reduction over that obtained with placebo (improvement-type model), the maximum effect size was 1.08 with a mean HDRS-17 difference of 7.2. When adjusting for normal rates of treatment discontinuation, maximum effect sizes were 1.10 (remission-type model) and 0.76 (improvement-type model) with HDRS-17 mean differences of 8.8 and 5.6, respectively.

CONCLUSIONS

Three methodological issues (i) a large and variable placebo response, (ii) a high rate of dropout and (iii) HDRS-17-ratings significantly larger than zero in healthy volunteers, reduce the degree of treatment-placebo separation achievable in depression trials. Assuming that those who discontinue treatment have only partial response, even a highly effective antidepressant would have difficulties surpassing such effect size cut-offs as have been suggested to signify a minimal clinically important difference.

Antipsychotic-placebo separation on the PANSS-6 subscale as compared to the PANSS-30: a pooled participant-level analysis

In order for measurement-based care to be implemented, there is a need for brief rating instruments that can be administered in a short amount of time, but that are still sufficiently informative. Here, we assessed the drug-placebo sensitivity of the six-item subscale (PANSS-6) of the 30-item Positive and Negative Syndrome Scale (PANSS-30) using a large collection of patient-level data (n = 6685) from randomized controlled trials of risperidone and paliperidone. When analyzing the data by study, we found no material difference in mean effect sizes (ES) between the two measures (PANSS-30 ES = 0.45, PANSS-6 ES = 0.44; p = 0.642). Stratifying the pooled population according to several putative effect moderators (e.g., age, formulation, dose, or diagnosis) generally yielded no meaningful ES differences between the two measures. Similarly, early improvement (≥20% improvement at week 1) on the PANSS-6 predicted subsequent response (≥40% improvement at endpoint) as well as the analog prediction using PANSS-30. Finally, cross-sectional symptom remission assessed via the PANSS-6 showed very good agreement (sensitivity = 100%, specificity = 98%) with cross-sectional symptom remission defined by the Remission in Schizophrenia Working Group.

Impact of Fluoxetine on Behavioral Invigoration of Appetitive and Aversively Motivated Responses: Interaction With Dopamine Depletion

Impaired behavioral activation and effort-related motivational dysfunctions like fatigue and anergia are debilitating treatment-resistant symptoms of depression. Depressed people show a bias towards the selection of low effort activities. To determine if the broadly used antidepressant fluoxetine can improve behavioral activation and reverse dopamine (DA) depletion-induced anergia, male CD1 mice were evaluated for vigorous escape behaviors in an aversive context (forced swim test, FST), and also with an exercise preference choice task [running wheel (RW)-T-maze choice task]. In the FST, fluoxetine increased active behaviors (swimming, climbing) while reducing passive ones (immobility). However, fluoxetine was not effective at reducing anergia induced by the DA-depleting agent tetrabenazine, further decreasing vigorous climbing and increasing immobility. In the T-maze, fluoxetine alone produced the same pattern of effects as tetrabenazine. Moreover, fluoxetine did not reverse tetrabenazine-induced suppression of RW time but it reduced sucrose intake duration. This pattern of effects produced by fluoxetine in DA-depleted mice was dissimilar from devaluing food reinforcement by pre-feeding or making the food bitter since in both cases sucrose intake time was reduced but animals compensated by increasing time in the RW. Thus, fluoxetine improved escape in an aversive context but decreased relative preference for active reinforcement. Moreover, fluoxetine did not reverse the anergic effects of DA depletion. These results have implications for the use of fluoxetine for treating motivational symptoms such as anergia in depressed patients.

Network dynamics of depressive symptoms in antidepressant medication treatment: secondary analysis of eight clinical trials

Depression can be viewed as a network of depressive symptoms that tend to reinforce each other via feedback loops. Specific symptoms of depression may be differently responsive to antidepressant treatment, and some symptoms may be more important than others in the overall improvement of depression associated with treatment. We pooled prospective data from eight industry-sponsored placebo-controlled trials for paroxetine, fluoxetine and imipramine (total n = 3559) to examine whether improvements in specific depressive symptoms were more strongly related to improvements in other depressive symptoms among patients on active antidepressant treatment as compared to placebo. Depressive symptoms were assessed with the 17-item Hamilton Depression Rating Scale. Data on treatment was dichotomized into active treatment (receiving any antidepressant agent) vs. placebo. Time-lagged longitudinal analyses suggested that improvement in three symptoms-depressed mood, insomnia, and suicidality-had a broader overall impact on subsequent improvement in other depressive symptoms in the antidepressant condition compared to placebo (i.e., greater out-strength). Moreover, improvements in depressed mood and insomnia were more likely to follow the improvements in other symptoms in the antidepressant condition compared to placebo (i.e., greater in-strength). These results from clinical trial data suggest that depressed mood, insomnia, and suicidality may be particularly important in accounting for the remission and recovery in response to antidepressant treatment.

Replication of machine learning methods to predict treatment outcome with antidepressant medications in patients with major depressive disorder from STAR*D and CAN-BIND-1

Objectives

Antidepressants are first-line treatments for major depressive disorder (MDD), but 40–60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict treatment outcomes based on clinical symptoms and episode features. We sought to independently replicate recent machine learning methodology predicting antidepressant outcomes using the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, and then externally validate these methods to train models using data from the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) dataset.

Methods

We replicated methodology from Nie et al (2018) using common algorithms based on linear regressions and decision trees to predict treatment-resistant depression (TRD, defined as failing to respond to 2 or more antidepressants) in the STAR*D dataset. We then trained and externally validated models using the clinical features found in both datasets to predict response (≥50% reduction on the Quick Inventory for Depressive Symptomatology, Self-Rated [QIDS-SR]) and remission (endpoint QIDS-SR score ≤5) in the CAN-BIND-1 dataset. We evaluated additional models to investigate how different outcomes and features may affect prediction performance.

Results

Our replicated models predicted TRD in the STAR*D dataset with slightly better balanced accuracy than Nie et al (70%-73% versus 64%-71%, respectively). Prediction performance on our external methodology validation on the CAN-BIND-1 dataset varied depending on outcome; performance was worse for response (best balanced accuracy 65%) compared to remission (77%). Using the smaller set of features found in both datasets generally improved prediction performance when evaluated on the STAR*D dataset.

Conclusion

We successfully replicated prior work predicting antidepressant treatment outcomes using machine learning methods and clinical data. We found similar prediction performance using these methods on an external database, although prediction of remission was better than prediction of response. Future work is needed to improve prediction performance to be clinically useful.

Do side effects of antidepressants impact efficacy estimates based on the Hamilton Depression Rating Scale? A pooled patient-level analysis

The Hamilton Depression Rating Scale (HDRS-17) measures symptoms that may overlap with common antidepressant side effects (e.g., sexual dysfunction), thus making it possible that side effects of antidepressant treatment are erroneously rated as symptoms of depression, and vice versa. This study uses patient-level data from previously conducted antidepressant treatment trials to assess whether side effect ratings co-vary with HDRS-17 ratings. Data from all HDRS-17-rated, industry-sponsored pre- and post-marketing trials (n = 4647) comparing the serotonin and noradrenaline reuptake inhibitor, duloxetine, to placebo and/or to a selective serotonin reuptake inhibitor were pooled; three studies, which utilised sub-therapeutic doses, did not have symptom-level ratings available and could not be included. Severity was assessed for side effects related to sleep, somatic anxiety, gastrointestinal function, and sexual dysfunction. Analysis of covariance was used to assess the relation between these side effects and ratings of relevant HDRS-17-derived outcome parameters. Side effects related to sleep, somatic anxiety and sexual dysfunction significantly and exclusively associated with higher scores on HDRS-17 items measuring the corresponding domains. Side effects related to gastrointestinal function associated with higher HDRS-17 item scores on all assessed domains. Treatment outcome was significantly related to side effect severity when assessed using HDRS-17-sum (beta 0.32 (0.074), p < 0.001), but not when the HDRS-6-sum-score (beta 0.035 (0.043), p = 0.415) or the depressed mood item (beta 0.007 (0.012), p = .527) were used as effect parameters. That some HDRS-17 items co-vary with common antidepressant side effects suggests some of these adverse events are counted twice, potentially leading to an underestimation of antidepressant efficacy.

The Maudsley 3-item Visual Analogue Scale (M3VAS): Validation of a scale measuring core symptoms of depression

AIMS

Low mood and anhedonia are the core symptoms of major depressive disorder (MDD). However, there is no established visual analogue scale that measures pervasiveness of both symptoms. We aimed to validate the Maudsley 3-item Visual Analogue Scale (M3VAS) as a measure of core depressive symptoms and suicidality.

METHODS

This is a cross-sectional secondary analysis combining data from two randomised controlled trials covering a broad range of depression severity from euthymia to severe depression. We validated the M3VAS by testing: 1) latent construct domains using factor analysis; 2) internal consistency using Cronbach's alpha; and 3) convergent validity by correlating M3VAS scores against scores on the Quick Inventory of Depressive Symptomatology-16 item (QIDS-SR-16), which is validated for use in clinical trials.

RESULTS

Of 180 patients in the combined cohort, 177 (98.3%) provided complete data on the M3VAS and QIDS-SR-16. The mean (SD) age was 41.6 (13.0) years and 59.3% were female. Using factor analysis, one eigenvalue above 1 was produced (2.39) that explained 79.6% of the variance, indicating a one-factor model. Cronbach's alpha was 0.87, demonstrating good internal consistency. Total M3VAS scores correlated strongly (r = 0.72, p<0.001) with QIDS-SR-16 scores, indicating good convergent validity.

LIMITATIONS

This was a cross-sectional study and was not validated against a clinician-rated assessment for depression.

CONCLUSION

The M3VAS is a simple, valid instrument for the assessment of core depressive symptoms and suicidality across the depression spectrum. Future studies should test the longitudinal validity of the M3VAS in detecting changes in core depressive symptoms and suicidality over time.

Sleep deprivation as treatment for depression: Systematic review and meta-analysis

OBJECTIVE

To systematically review evidence on the efficacy and safety of sleep deprivation (SD) as a treatment option for patients with unipolar or bipolar depression.

METHODS

A systematic review according to PRISMA guidelines was conducted. The certainty of evidence was assessed using the GRADE approach. Controlled trials were included in efficacy analysis, case series for evaluating complications and qualitative studies for patients' experiences.

RESULTS

Eight controlled studies (368 patients), one qualitative study and seven case series (825 patients) were included. One week after treatment start, SD combined with standard treatment did not reduce depressive symptoms compared with standard treatment (standardized mean difference, SMD = -0.29, [95% confidence interval, CI: -0.84 to 0.25], p = 0.29). When excluding a study in elderly patients in a post hoc analysis, the difference was statistically significant (SMD = -0.54 ([95% CI: -0.86 to -0.22], p < 0.001)) but it diminished two weeks after treatment start. No superiority of SD was found compared with antidepressants, but SD may be superior to exercise in certain settings. It is uncertain whether SD affects quality of sleep, quality of life, everyday functioning or length of stay. Apart from switch to mania (ranging between 2.7% and 10.7%), no other serious complications were reported.

CONCLUSION

Sleep deprivation has been studied in a wide range of settings resulting in divergent results for the short-term efficacy on depressive symptoms. Post hoc analyses indicated that there may be a significant but transient effect in certain populations. Further studies should focus on identifying subgroups of responders as well as examining feasibility in routine clinical care.

Longitudinal associations between specific symptoms of depression: Network analysis in a prospective cohort study

BACKGROUND

Network perspective to mental disorders suggests that depression develops due to interrelated associations between individual symptoms rather than due to a common cause. However, it is unclear whether long-term longitudinal associations between specific symptoms of depression demonstrate coherent patterns. We examined the temporal sequences and changes in depressive symptoms over time, and whether some symptoms are more central than others in inducing changes in the rest of the symptoms over time. We also compared the network structure of depressive symptoms between people who were and were not taking medication for depression or anxiety.

METHODS

Data were from the Survey of Health, Aging and Retirement in Europe, with five follow-ups conducted between 2004 and 2017. Participants who had data on depressive symptoms from at least two study waves were analyzed (n = 72,971). Depressive symptoms were self-reported using the 12-item EURO-D scale.

RESULTS

All individual symptoms were longitudinally associated with each other. Changes in sad or depressed mood, diminished interest, and suicidal ideation were the most strongly associated with changes in other symptoms. There were no consistent differences in symptom associations between individuals taking versus not taking psychotropic medication.

LIMITATIONS

Depressive symptoms were self-reported and measured every two years, which may dilute some short-term temporal sequences of the symptoms.

CONCLUSIONS

Our findings demonstrate differences between depressive symptoms in their long-term associations with other depressive symptoms in the general population. Changes in sad or depressed mood, diminished interest, and suicidal ideation have the strongest associations with changes in the rest of the symptoms.

Using network analysis to examine links between individual depressive symptoms, inflammatory markers, and covariates

BACKGROUND

Studies investigating the link between depressive symptoms and inflammation have yielded inconsistent results, which may be due to two factors. First, studies differed regarding the specific inflammatory markers studied and covariates accounted for. Second, specific depressive symptoms may be differentially related to inflammation. We address both challenges using network psychometrics.

METHODS

We estimated seven regularized Mixed Graphical Models in the Netherlands Study of Depression and Anxiety (NESDA) data (N = 2321) to explore shared variances among (1) depression severity, modeled via depression sum-score, nine DSM-5 symptoms, or 28 individual depressive symptoms; (2) inflammatory markers C-reactive protein (CRP), interleukin 6 (IL-6), and tumor necrosis factor α (TNF-α); (3) before and after adjusting for sex, age, body mass index (BMI), exercise, smoking, alcohol, and chronic diseases.

RESULTS

The depression sum-score was related to both IL-6 and CRP before, and only to IL-6 after covariate adjustment. When modeling the DSM-5 symptoms and CRP in a conceptual replication of Jokela et al., CRP was associated with 'sleep problems', 'energy level', and 'weight/appetite changes'; only the first two links survived covariate adjustment. In a conservative model with all 38 variables, symptoms and markers were unrelated. Following recent psychometric work, we re-estimated the full model without regularization: the depressive symptoms 'insomnia', 'hypersomnia', and 'aches and pain' showed unique positive relations to all inflammatory markers.

CONCLUSIONS

We found evidence for differential relations between markers, depressive symptoms, and covariates. Associations between symptoms and markers were attenuated after covariate adjustment; BMI and sex consistently showed strong relations with inflammatory markers.