Prevalence and predictors of recurrence of major depressive disorder in the adult population

Depression-Anxiety Coupling Strength as a predictor of relapse in major depressive disorder: A CAN-BIND wellness monitoring study report

BACKGROUND

A critical challenge in the study and management of major depressive disorder (MDD) is predicting relapse. We examined the temporal correlation/coupling between depression and anxiety (called Depression-Anxiety Coupling Strength, DACS) as a predictor of relapse in patients with MDD.

METHODS

We followed 97 patients with remitted MDD for an average of 394 days. Patients completed weekly self-ratings of depression and anxiety symptoms using the Quick Inventory of Depressive Symptoms (QIDS-SR) and the Generalized Anxiety Disorder 7-item scale (GAD-7). Using these longitudinal ratings we computed DACS as random slopes in a linear mixed effects model reflecting individual-specific degree of correlation between depression and anxiety across time points. We then tested DACS as an independent variable in a Cox proportional hazards model to predict relapse.

RESULTS

A total of 28 patients (29 %) relapsed during the follow-up period. DACS significantly predicted confirmed relapse (hazard ratio [HR] 1.5, 95 % CI [1.01, 2.22], p = 0.043; Concordance 0.79 [SE 0.04]). This effect was independent of baseline depressive or anxiety symptoms or their average levels over the follow-up period, and was identifiable more than one month before relapse onset.

LIMITATIONS

Small sample size, in a single study. Narrow phenotype and comorbidity profiles.

CONCLUSIONS

DACS may offer opportunities for developing novel strategies for personalized monitoring, early detection, and intervention. Future studies should replicate our findings in larger, diverse patient populations, develop individual patient prediction models, and explore the underlying mechanisms that govern the relationship of DACS and relapse.

Childhood maltreatment and association with trajectories of depressive symptoms among older adults: a longitudinal study in China

OBJECTIVES

Childhood maltreatment has long-lasting effects on mental health. Existing evidence suggests that trajectories of depressive symptoms vary among individuals; however, little is known about how childhood maltreatment shapes these trajectory patterns. Therefore, this study investigated the impacts of childhood maltreatment on eight-year depressive trajectories among Chinese older adults.

METHOD

Five waves of longitudinal data from the China Health and Retirement Longitudinal Study were utilized. Growth Mixture Modelling was performed to identify distinct trajectories of depressive symptoms, and multinomial logistic regression was conducted to explore the associations between these trajectories and childhood maltreatment.

RESULTS

Four trajectories of depressive symptoms were identified: the 'no symptoms' class (61.83%), the 'increasing symptoms' class (14.49%), the 'decreasing symptoms' class (16.44%), and the 'chronic symptoms' class (7.24%). Older adults who experienced childhood physical abuse were more likely to be in the 'chronic symptoms' class than in the 'no symptoms' class, whereas emotional neglect did not show a significant association with three problematic trajectories.

CONCLUSION

This study provides empirical evidence that childhood physical abuse increases the likelihood of developing chronic depressive symptoms in later life. To mitigate this risk, it is crucial to institute comprehensive treatment plans that incorporate trauma-informed care principles, employ evidence-based therapies specifically designed to address the long-term effects of abuse, and prioritize regular screening and assessment of mental health among older adults.

Models for depression recognition and efficacy assessment based on clinical and sequencing data

Major depression is a complex psychiatric disorder that includes genetic, neurological, and cognitive factors. Early detection and intervention can prevent progression, and help select the best treatment. Traditional clinical diagnosis tends to be subjective and misdiagnosed. Based on this, this study leverages clinical scale assessments and sequencing data to construct disease prediction models. Firstly, data undergoes preprocessing involving normalization and other requisite procedures. Feature engineering is then applied to curate subsets of features, culminating in the construction of a model through the implementation of machine learning and deep learning algorithms. In this study, 18 features with significant differences between patients and healthy controls were selected. The depression recognition model was constructed by deep learning with an accuracy of 87.26 % and an AUC of 91.56 %, which can effectively distinguish patients with depression from healthy controls. In addition, 33 features selected by recursive feature elimination method were used to construct a prognostic effect model of patients after 2 weeks of treatment, with an accuracy of 75.94 % and an AUC of 83.33 %. The results show that the deep learning algorithm based on clinical and sequencing data has good accuracy and provides an objective and accurate method for the diagnosis and pharmacodynamic prediction of depression. Furthermore, the selected differential features can serve as candidate biomarkers to provide valuable clues for diagnosis and efficacy prediction.

Prevalence and correlates of common mental disorders among participants of the Uganda Genome Resource: Opportunities for psychiatric genetics research

Genetics research has potential to alleviate the burden of mental disorders in low- and middle-income-countries through identification of new mechanistic pathways which can lead to efficacious drugs or new drug targets. However, there is currently limited genetics data from Africa. The Uganda Genome Resource provides opportunity for psychiatric genetics research among underrepresented people from Africa. We aimed at determining the prevalence and correlates of major depressive disorder (MDD), suicidality, post-traumatic stress disorder (PTSD), alcohol abuse, generalised anxiety disorder (GAD) and probable attention-deficit hyperactivity disorder (ADHD) among participants of the Uganda Genome Resource. Standardised tools assessed for each mental disorder. Prevalence of each disorder was calculated with 95% confidence intervals. Multivariate logistic regression models evaluated the association between each mental disorder and associated demographic and clinical factors. Among 985 participants, prevalence of the disorders were: current MDD 19.3%, life-time MDD 23.3%, suicidality 10.6%, PTSD 3.1%, alcohol abuse 5.7%, GAD 12.9% and probable ADHD 9.2%. This is the first study to determine the prevalence of probable ADHD among adult Ugandans from a general population. We found significant association between sex and alcohol abuse (adjusted odds ratio [AOR] = 0.26 [0.14,0.45], p < 0.001) and GAD (AOR = 1.78 [1.09,2.49], p = 0.019) respectively. We also found significant association between body mass index and suicidality (AOR = 0.85 [0.73,0.99], p = 0.041), alcohol abuse (AOR = 0.86 [0.78,0.94], p = 0.003) and GAD (AOR = 0.93 [0.87,0.98], p = 0.008) respectively. We also found a significant association between high blood pressure and life-time MDD (AOR = 2.87 [1.08,7.66], p = 0.035) and probable ADHD (AOR = 1.99 [1.00,3.97], p = 0.050) respectively. We also found a statistically significant association between tobacco smoking and alcohol abuse (AOR = 3.2 [1.56,6.67], p = 0.002). We also found ever been married to be a risk factor for probable ADHD (AOR = 2.12 [0.88,5.14], p = 0.049). The Uganda Genome Resource presents opportunity for psychiatric genetics research among underrepresented people from Africa.

Real-world case series of maintenance theta burst stimulation therapy following response to acute theta burst stimulation therapy for difficult-to-treat depression

OBJECTIVE

Treatment and management for difficult-to-treat depression are challenging, especially in a subset of patients who are at high risk for relapse and recurrence. The conditions that represent this subset are recurrent depressive disorder (RDD) and bipolar disorder (BD). In this context, we aimed to examine the effectiveness of maintenance transcranial magnetic stimulation (TMS) on a real-world clinical basis by retrospectively extracting data from the TMS registry data in Tokyo, Japan.

METHODS

Data on patients diagnosed with treatment-resistant RDD and BD who received maintenance intermittent theta burst stimulation (iTBS) weekly after successful treatment with acute iTBS between March 2020 and October 2023 were extracted from the registry.

RESULTS

All patients (21 cases: 10 cases with RDD and 11 cases with BD) could sustain response, and 19 of them further maintained remission. In this study, maintenance iTBS did not exacerbate depressive symptoms in any of the cases, but may rather have the effect of stabilizing the mental condition and preventing recurrence.

CONCLUSIONS

This case series is of great clinical significance because it is the first study to report on the effectiveness of maintenance iTBS for RDD and BD, with a follow-up of more than 2 years. Further validation with a randomized controlled trial design with a larger sample size is warranted.

Natural history of depression up to 18 years after stroke: a population-based South London Stroke Register study

Background

Current evidence on the long-term natural history of post-stroke depression (PSD) is limited. We aim to determine the prevalence, incidence, duration and recurrence rates of depression to 18-years after stroke and assess differences by onset-time and depression severity.

Methods

Data were from the South London Stroke Register (1995-2019, N = 6641 at registration). Depression was defined using the Hospital Anxiety and Depression scale (scores > 7 = depression) at 3-months, then annually to 18-years after stroke. We compared early- (3-months post-stroke) vs late-onset depression (1-year) and initial mild (HADS scores > 7) vs severe depression (scores > 10).

Findings

3864 patients were assessed for depression at any time-points during the follow-up (male:55.4% (2141), median age: 68.0 (20.4)), with the number ranging from 2293 at 1-year to 145 at 18-years after stroke. Prevalence of PSD ranged from 31.3% (28.9-33.8) to 41.5% (33.6-49.3). The cumulative incidence of depression was 59.4% (95% CI 57.8-60.9), of which 87.9% (86.5-89.2) occurred within 5-years after stroke. Of patients with incident PSD at 3-months after stroke, 46.6% (42.1-51.2) recovered after 1 year. Among those recovered, 66.7% (58.0-74.5) experienced recurrent depression and 94.4% (87.5-98.2) of recurrences occurred within 5-years since recovery. Similar estimates were observed in patients with PSD at 1-year. 34.3% (27.9-41.1) of patients with severe depression had recovered at the next time-point, compared to 56.7% (50.5-62.8) with mild depression. Recurrence rate at 1-year after recovery was higher in patients with severe depression (52.9% (35.1-70.2)) compared to mild depression (23.5% (14.1-35.4)) (difference: 29.4% (7.6-51.2), p = 0.003).

Interpretation

Long-term depressive status may be established by 5-years post-onset. Early- and late-onset depression presented similar natural history, while severe depression had a longer duration and quicker recurrence than mild depression. These estimates were limited to alive patients completing the depression assessment, who tended to have less severe stroke than excluded patients, so may be underestimated and not generalizable to all stroke survivors.

Funding

National Institute for Health and Care Research (NIHR202339).

The Pathophysiological Underpinnings of Gamma-Band Alterations in Psychiatric Disorders

Investigating the biophysiological substrates of psychiatric illnesses is of great interest to our understanding of disorders' etiology, the identification of reliable biomarkers, and potential new therapeutic avenues. Schizophrenia represents a consolidated model of γ alterations arising from the aberrant activity of parvalbumin-positive GABAergic interneurons, whose dysfunction is associated with perineuronal net impairment and neuroinflammation. This model of pathogenesis is supported by molecular, cellular, and functional evidence. Proof for alterations of γ oscillations and their underlying mechanisms has also been reported in bipolar disorder and represents an emerging topic for major depressive disorder. Although evidence from animal models needs to be further elucidated in humans, the pathophysiology of γ-band alteration represents a common denominator for different neuropsychiatric disorders. The purpose of this narrative review is to outline a framework of converging results in psychiatric conditions characterized by γ abnormality, from neurochemical dysfunction to alterations in brain rhythms.

Prevalence of major depressive disorder and its associated factors among adult patients with neurolathyrism in Dawunt District, Ethiopia; 2022: community-based cross-sectional study

INTRODUCTION

Major Depressive Disorder (MDD) is one of the commonest mental disorders affecting more than 250 million people globally. Patients with chronic illnesses had higher risks for developing MDD than the general population. Neurolathyrism is a chronic illness characterized by lifelong incurable spastic paralysis of lower extremities; causing permanent disability. It is highly prevalent in Dawunt district, Ethiopia; with a point prevalence of 2.4%. Despite this, there were no previous studies assessing the prevalence of MDD among patients with neurolathyrism in Ethiopia.

OBJECTIVE

To assess the prevalence of MDD and to identify its associated factors among patients with neurolathyrism in Dawunt district, Ethiopia.

METHODS

A community based cross-sectional study was conducted on 260 samples in Dawunt district from February 01 to March 30/ 2021. Multistage sampling technique was used to select study participants. The patient Health Questionnaire-9 (PHQ-9) depression screening tool was used to diagnose MDD. PHQ-9 is a standardized depression screening tool and a PHQ-9 score of ≥ 10 has a sensitivity and specificity of 88.0% [95% CI (83.0-92.0%)] and 85.0% [95% CI (82.0-88.0%)] for screening MDD. Data were collected by interview; entered to EpiData version 4.2.0; exported to SPSS version 25.0 for analysis; descriptive statistics and binary logistic regression model were used; AOR with 95% CI was used to interpret the associations; and finally results were presented by texts, charts, graphs, and tables.

RESULTS

A total of 256 adult patients with neurolathyrism were participated; and the prevalence of MDD was found to be 38.7%. Being female [AOR = 3.00; 95% CI (1.15, 7.84)], living alone [AOR = 2.77; 95% CI (1.02-7.53)], being on neurolathyrism stage-3 [AOR = 3.22; 95% CI (1.09, 9.54)] or stage-4 [AOR = 4.00; 95% CI (1.28, 12.48)], stigma [AOR = 2.69; 95% CI (1.34, 5.39)], and lack of social/ family support [AOR = 3.61; 95% CI (1.80, 7.24)] were found to have statistically significant association with an increased odds of MDD; while regular exercise and ever formal counselling were found to have statistically significant association with a decreased odds of MDD.

CONCLUSION

The prevalence of MDD among neurolathyrism patients in Dawunt district was high. Lack of social support, stigma, not getting formal counselling, and not involving in regular exercise were modifiable risk factors. Therefore, social support, reducing stigma, formal counselling, and encouraging regular exercise might help to reduce the burden of MDD among neurolathyrism patients.

Trajectories of remitted psychotic depression: identification of predictors of worsening by machine learning

BACKGROUND

Remitted psychotic depression (MDDPsy) has heterogeneity of outcome. The study's aims were to identify subgroups of persons with remitted MDDPsy with distinct trajectories of depression severity during continuation treatment and to detect predictors of membership to the worsening trajectory.

METHOD

One hundred and twenty-six persons aged 18-85 years participated in a 36-week randomized placebo-controlled trial (RCT) that examined the clinical effects of continuing olanzapine once an episode of MDDPsy had remitted with sertraline plus olanzapine. Latent class mixed modeling was used to identify subgroups of participants with distinct trajectories of depression severity during the RCT. Machine learning was used to predict membership to the trajectories based on participant pre-trajectory characteristics.

RESULTS

Seventy-one (56.3%) participants belonged to a subgroup with a stable trajectory of depression scores and 55 (43.7%) belonged to a subgroup with a worsening trajectory. A random forest model with high prediction accuracy (AUC of 0.812) found that the strongest predictors of membership to the worsening subgroup were residual depression symptoms at onset of remission, followed by anxiety score at RCT baseline and age of onset of the first lifetime depressive episode. In a logistic regression model that examined depression score at onset of remission as the only predictor variable, the AUC (0.778) was close to that of the machine learning model.

CONCLUSIONS

Residual depression at onset of remission has high accuracy in predicting membership to worsening outcome of remitted MDDPsy. Research is needed to determine how best to optimize the outcome of psychotic MDDPsy with residual symptoms.

Clinical factors associated with relapse in depression in a sample of UK primary care patients who have been on long-term antidepressant treatment

BACKGROUND

This paper investigates whether age of onset of depression, duration of the last episode, number of episodes, and residual symptoms of depression and anxiety are associated with depression relapse in primary care patients who have been on long-term maintenance antidepressant treatment and no longer meet ICD10 criteria for depression.

METHODS

An observational cohort using data from ANTLER (N = 478), a double-blind placebo-controlled trial. The primary outcome was time to relapse using the retrospective CIS-R. Participants were followed for 12 months.

RESULTS

Primary outcome was available for 468 participants. Time to relapse in those with more than five previous episodes of depression was shorter, hazard ratio (HR) 1.84 (95% confidence interval [CI] 1.23-2.75) compared to people with two episodes; HR 1.57 (95% CI 1.01-2.43) after adjustment. The residual symptoms of depression at baseline were also associated with increased relapse: HR 1.05 (95% CI 1.01-1.09) and HR 1.06 (95% CI 1.01-1.12) in the adjusted model. There was evidence of reduced rate of relapse in older age of onset group: HR 0.86 (95% CI 0.78-0.95); HR attenuated after adjustment HR 0.91 (95% CI 0.81-1.02). There was no evidence of an association between duration of the current episode and residual anxiety symptoms with relapse.

CONCLUSIONS

The number of previous episodes and residual symptoms of depression were associated with increased likelihood of relapse. These factors could inform joint decision making when patients are considering tapering off maintenance antidepressant treatment or considering other treatments to prevent relapse.

Dynamic risk factors of psychiatric readmission for major depressive disorder: A longitudinal study on patients treated with mono-antidepressant

In this comprehensive study, we sought to unravel the risk factors for recurrence in Major Depressive Disorder (MDD), uniquely focusing on patients undergoing mono-antidepressant treatment. By considering psychiatric readmission as a direct indicator of MDD recurrence, we meticulously analyzed the records of 1,456 inpatients from a Chinese mental health center from 2012 to 2020. Our follow-up periods, spanning 90, 180, and 365 days post-discharge, allowed for a nuanced understanding of the recurrence dynamics. We identified four critical risk factors: thyroid function (FT3 and TSH), high-density lipoprotein (HDL) levels, and region of residence. Notably, the study revealed an increasing risk of readmission associated with decreased FT3 and HDL over time, while elevated TSH and residing in another province 's impact diminished. The antidepressant type did not significantly alter readmission risks, providing a unique perspective on MDD management. This research contributes to the field by offering a deeper understanding of how demographic and biochemical factors influence the likelihood of MDD recurrence, guiding more effective treatment approaches.

An investigation of treatment return after psychological therapy for depression and anxiety

BACKGROUND

Some patients return for further psychological treatment in routine services, although it is unclear how common this is, as scarce research is available on this topic.

AIMS

To estimate the treatment return rate and describe the clinical characteristics of patients who return for anxiety and depression treatment.

METHOD

A large dataset (N=21,029) of routinely collected clinical data (2010-2015) from an English psychological therapy service was analysed using descriptive statistics.

RESULTS

The return rate for at least one additional treatment episode within 1-5 years was 13.7%. Furthermore, 14.5% of the total sessions provided by the service were delivered to treatment-returning patients. Of those who returned, 58.0% continued to show clinically significant depression and/or anxiety symptoms at the end of their first treatment, while 32.0% had experienced a demonstrable relapse before their second treatment.

CONCLUSIONS

This study estimates that approximately one in seven patients return to the same service for additional psychological treatment within 1-5 years. Multiple factors may influence the need for additional treatment, and this may have a major impact on service activity. Future research needs to further explore and better determine the characteristics of treatment returners, prioritise enhancement of first treatment recovery, and evaluate relapse prevention interventions.

Association between triglyceride glucose index and depression in hypertensive population

Growing evidence suggests that hypertensive individuals have a greater risk of developing depression, and depression can also increase the incidence of hypertension. In the hypertensive population, the association between triglyceride glucose (TyG) index and depression remains unclear. This study aimed to assess the association between TyG index and depression in hypertensive people through the cross-sectional study of the National Health and Nutrition Examination Survey (2007-2018). To assess the relationship between TyG index and depression in hypertensive population, we conducted weighted multiple logistic regression models and used a generalized additive model to probe for nonlinear correlations. In addition, we employed a recursive algorithm to determine the inflection point and established a two-piece linear regression model. This study enrolled 5897 individuals. In the model adjusted for all covariates, the ORs (95% CI) for the relationship between TyG index and depression in hypertensive population were 1.32 (1.12-1.54). A nonlinear association was found between TyG index and depression, with an inflection point at 8.7. After the inflection point, the ORs (95% CI) were 1.44 (1.15-1.79). Only the interaction with the obese population was statistically significant. Our study highlighted a nonlinear association between TyG index and depression in American hypertensive adults.

Predicting recurrence of major depressive episodes using the Depression Implicit Association Test: A Canadian biomarker integration network in depression (CAN-BIND) report

Identifying clinically relevant predictors of depressive recurrence following treatment for Major Depressive Disorder (MDD) is critical for relapse prevention. Implicit self-depressed associations (SDAs), defined as implicit cognitive associations between elements of depression (e.g., sad, miserable) and oneself, often persist following depressive episodes and may represent a cognitive biomarker for future recurrences. Thus, we examined whether SDAs, and changes in SDAs over time, prospectively predict depressive recurrence among treatment responders in the CAN-BIND Wellness Monitoring for MDD Study, a prospective cohort study conducted across 5 clinical centres. A total of 96 patients with MDD responding to various treatments were followed an average of 1.01 years. Participants completed the Depression Implicit Association Test (DIAT) - a computer-based measure of SDAs - every 8 weeks on a tablet device. Survival analyses indicated that greater SDAs at baseline and increases in SDAs over time predicted shorter time to MDD recurrence, even after accounting for depressive symptom severity. The findings show that SDAs are a robust prognostic indicator of risk for MDD recurrence, and that the DIAT may be a feasible and low-cost clinical screening tool. SDAs also represent a potential mechanism underlying the course of recurrent depression and are a promising target for relapse prevention interventions.

Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity

Recurrence in major depressive disorder (MDD) is common, but neurobiological models capturing vulnerability for recurrences are scarce. Disturbances in multiple resting-state networks have been linked to MDD, but most approaches focus on stable (vs. dynamic) network characteristics. We investigated how the brain's dynamical repertoire changes after patients transition from remission to recurrence of a new depressive episode. Sixty two drug-free, MDD-patients with ≥2 episodes underwent a baseline resting-state fMRI scan when in remission. Over 30-months follow-up, 11 patients with a recurrence and 17 matched-remitted MDD-patients without a recurrence underwent a second fMRI scan. Recurrent patterns of functional connectivity were characterized by applying Leading Eigenvector Dynamics Analysis (LEiDA). Differences between baseline and follow-up were identified for the 11 non-remitted patients, while data from the 17 matched-remitted patients was used as a validation dataset. After the transition into a depressive state, basal ganglia-anterior cingulate cortex (ACC) and visuo-attentional networks were detected significantly more often, whereas default mode network activity was found to have a longer duration. Additionally, the fMRI signal in the basal ganglia-ACC areas underlying the reward network, were significantly less synchronized with the rest of the brain after recurrence (compared to a state of remission). No significant changes were observed in the matched-remitted patients who were scanned twice while in remission. These findings characterize changes that may be associated with the transition from remission to recurrence and provide initial evidence of altered dynamical exploration of the brain's repertoire of functional networks when a recurrent depressive episode occurs.

Comparative analysis of algorithm-guided treatment and predefined duration treatment programmes for depression: exploring cost-effectiveness using routine care data

BACKGROUND

More knowledge on the cost-effectiveness of various depression treatment programmes can promote efficient treatment allocation and improve the quality of depression care.

OBJECTIVE

This study aims to compare the real-world cost-effectiveness of an algorithm-guided programme focused on remission to a predefined duration, patient preference-centred treatment programme focused on response using routine care data.

METHODS

A naturalistic study (n=6295 in the raw dataset) was used to compare the costs and outcomes of two programmes in terms of quality-adjusted life years (QALY) and depression-free days (DFD). Analyses were performed from a healthcare system perspective over a 2-year time horizon. Incremental cost-effectiveness ratios were calculated, and the uncertainty of results was assessed using bootstrapping and sensitivity analysis.

FINDINGS

The algorithm-guided treatment programme per client yielded more DFDs (12) and more QALYs (0.013) at a higher cost (€3070) than the predefined duration treatment programme. The incremental cost-effectiveness ratios (ICERs) were around €256/DFD and €236 154/QALY for the algorithm guided compared with the predefined duration treatment programme. At a threshold value of €50 000/QALY gained, the programme had a probability of <10% of being considered cost-effective. Sensitivity analyses confirmed the robustness of these findings.

CONCLUSIONS

The algorithm-guided programme led to larger health gains than the predefined duration treatment programme, but it was considerably more expensive, and hence not cost-effective at current Dutch thresholds. Depending on the preferences and budgets available, each programme has its own benefits.

CLINICAL IMPLICATION

This study provides valuable information to decision-makers for optimising treatment allocation and enhancing quality of care cost-effectively.

Lithium treatment versus hospitalization in bipolar disorder and major depression patients

BACKGROUND

Preventing hospitalization of major affective disorder patients is a fundamental clinical challenge for which lithium is expected to be helpful.

METHODS

We compared hospitalization rates and morbidity of 260 patients with DSM-5 bipolar or major depressive disorder in the 12 months before starting lithium versus 12 months of its use. We evaluated duration of untreated illness, previous treatments, substance abuse, suicidal status, lithium dose, and use of other medicines for association with new episodes of illness or of symptomatic worsening as well as hospitalization, using bivariate and multivariate analyses.

RESULTS

Within 12 months before lithium, 40.4 % of patients were hospitalized versus 11.2 % during lithium treatment; other measures of morbidity also improved. Benefits were similar with bipolar and major depressive disorders. Independently associated with hospitalization during lithium treatment were: receiving an antipsychotic with lithium, suicide attempt during lithium treatment, lifetime substance abuse, and psychiatric hospitalization in the year before starting lithium, but not diagnosis.

LIMITATIONS

Participants and observation times were limited. The study was retrospective regarding clinical history, lacked strict control of treatments and was not blinded.

CONCLUSIONS

This naturalistic study adds support to the effectiveness of lithium treatment in preventing hospitalization in patients with episodic major mood disorders.

Alterations of brainstem volume in patients with first-episode and recurrent major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental health condition characterized by recurrent episodes in a substantial proportion of patients. The number of previous episodes is one of the most crucial predictors of depression recurrence. However, the underlying neural mechanisms remain unclear. To date, there have been limited neuroimaging studies investigating morphological changes of the brainstem in patients with first-episode MDD (FMDD) and recurrent MDD (RMDD). This study aimed to examine volumetric changes of individual brainstem regions in relation to the number of previous episodes and disease duration.

METHOD

A total of 111 individuals including 36 FMDD, 25 RMDD, and 50 healthy controls (HCs) underwent T1-weighted structural magnetic resonance imaging scans. A Bayesian segmentation algorithm was used to analyze the volume of each brainstem region, including the medulla oblongata, pons, midbrain, and superior cerebellar peduncle (SCP), as well as the whole brainstem volume. Analyses of variance (ANOVA) were performed to obtain brain regions with significant differences among three groups and then post hoc tests were calculated for inter-group comparisons. Partial correlation analyses were further conducted to identify associations between regional volumes and clinical features.

RESULTS

The ANOVA revealed significant brainstem volumetric differences among three groups in the pons, midbrain, SCP, and the whole brainstem (F = 3.996 ~ 5.886, adjusted p = 0.015 ~ 0.028). As compared with HCs, both groups of MDD patients showed decreased volumes in the pons as well as the entire brainstem (p = 0.002 ~ 0.034), however, only the FMDD group demonstrated a significantly reduced volume in the midbrain (p = 0.003). Specifically, the RMDD group exhibited significantly decreased SCP volume when comparing to both FMDD (p = 0.021) group and HCs (p = 0.008). Correlation analyses revealed that the SCP volumes were negatively associated with the number of depressive episodes (r=-0.36, p < 0.01) and illness duration (r=-0.28, p = 0.035) in patients with MDD.

CONCLUSION

The present findings provided evidence of decreased brainstem volume involving in the pathophysiology of MDD, particularly, volumetric reduction in the SCP might represent a neurobiological marker for RMDD. Further research is needed to confirm our observations and deepen our understanding of the neural mechanisms underlying depression recurrence.

Association between platelet to lymphocyte ratio and depression and symptom severity among adults in the United States: A cross-sectional study

Background

The pathogenesis of depression has not yet been fully understood. The association between platelet to lymphocyte ratio (PLR) and depression has been investigated in previous studies, however, the results were controversial. The objective of the study was to explore the potential relationship between PLR and depression and symptom severity.

Methods

A cross-sectional study was conducted based on the National Health and Nutrition Examination Survey (NHANES) data from 2005 to 2018. Totally 30,032 adults were analyzed, and 2480 reported depression. Depression and symptom severity were assessed with the Patient Health Questionnaire (PHQ-9). PLR was calculated as the ratio of platelets to lymphocytes. Multivariable weighted-logistic regression models and generalized additive model (GAM) were employed to evaluate the linear and nonlinear association between PLR and depression and symptom severity.

Results

There was a negative association for Q3 (odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.68 to 0.99) when comparing participants for Q1 between 10-PLR and depression after fully adjusting the covariates; however, there was no significant association between 10-PLR and symptom severity. GAM showed that 10-PLR was associated with depression and symptom severity in a nonlinear manner. The inflection points were at 12.15. Subgroup analyses showed nonlinear relationships only in specific subgroups. Conclusions: PLR is associated with depression among adults in the United States. U-shaped nonlinear relationships and threshold effects were observed between 10-PLR and depression and symptom severity. Additionally, inflammatory mechanisms vary in different sociodemographic subgroups.

Correlates of depressive mood among graduate-level allied health students: An exploratory study examining trait energy and fatigue

Objective: The objective of this study was to identify factors associated with the occurrence and severity of depressive mood states among graduate-level allied health students. Participants: Students (N = 77) completed this study. Methods: Participants completed a series of self-reported surveys measuring moods, lifestyle behaviors, trait mental and physical energy and fatigue, and objective assessments of Trail-Making Test Part-B, and muscle oxygen consumption. Multiple backwards linear regression models were fitted to identify factors associated with depressive mood states. Results: When accounting for all subjects, increased severity of depressive mood states was associated with worse sleep quality (SQ), increased sitting time (ST), and trait physical fatigue (TPF). When examining subjects reporting depressive mood states, increased severity of depressive mood states was associated with worse SQ, increased ST, decreased mental workload on non-school days, and trait physical energy (TPE). Conclusion: Adjustments in lifestyle factors such as sleep, mental workload, and ST, may ameliorate depressive mood states.

Mentalising and depression: a mini-review on behavior, neural substrates, and treatment options

Major depression is one of the most common mental disorders, affecting millions of people around the globe. In recent years, researchers increasingly investigated social cognition in depression and discovered pronounced alterations. A special focus has been put on mentalising or Theory of Mind, the ability to recognize and understand another person's thoughts and feelings. While there is behavioral evidence for deficits in this ability in patients with depression as well as specialized therapeutic interventions, the neuroscientific substrates are only beginning to be understood. In this mini-review, we take a social neuroscience perspective to analyse the importance of altered mentalising in depression and whether it can help to understand the origins and perpetuation of the disorder. We will put a special focus on treatment options and corresponding neural changes to identify relevant paths for future (neuroscientific) research.

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.

The financial situation before and after first-time psychiatric in-patient diagnosis of schizophrenia spectrum, bipolar, and major depressive disorder

Schizophrenia spectrum, bipolar, and major depressive disorders are severe mental illnesses (SMIs) that not only entail great suffering for those affected but also major societal costs. In this study, I use administrative register data to provide a detailed picture of the financial situation of people with SMI in Sweden during a period of ±10 years around first-time psychiatric in-patient diagnosis of schizophrenia spectrum, bipolar, and major depressive disorders. Receiving a diagnosis was associated with a considerable drop in earnings, which was largely compensated for by social transfers: mainly sickness and disability insurance. However, there were also large and increasing pre-diagnosis earnings gaps, relative to matched comparison groups, especially among those with schizophrenia spectrum disorders. These gaps were to a lesser extent compensated for by social transfers. Consequently, there were permanent and increasing - due to lost earnings growth - income differentials. Hence, findings in previous studies are confirmed: even in an advanced welfare state, people with SMI - especially those with schizophrenia - have an extremely weak position on the labour market and an equally difficult financial situation.

Relationship of insight to neurocognitive function and risk of recurrence in depression: A naturalistic follow-up study

Introduction

Major depressive disorder (MDD) is a highly recurrent mental illness accompanied by impairment of neurocognitive function. Lack of insight may affect patients’ motivation to seek treatment, resulting in poor clinical outcomes. This study explores the relationship of insight to neurocognitive function and the risk of recurrence of depressive episodes in patients with MDD.

Methods

Demographic, clinical variables, and neurocognitive function measured with Intra-Extra Dimensional Set Shift (IED) from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were collected from 277 patients with MDD. Among them, 141 participants completed a follow-up visit within 1–5 years. Insight was measured using the 17-item Hamilton Depression Rating Scale (HAM-D). To explore the factors associated with recurrence, binary logistic regression models were used.

Results

Patients with MDD, without insight, had significantly higher total and factor scores (anxiety/somatization, weight, retardation, and sleep) on the HAM-D and worse performance in the neurocognition task, compared to those with insight. Furthermore, binary logistic regression revealed that insight and retardation can predict recurrence.

Conclusion

Lack of insight is associated with recurrence and impaired cognitive flexibility in patients with MDD.

The Effects of Online Self-management Interventions for Patients With Mood Disorders: Protocol for a Systematic Review and Meta-analysis

BACKGROUND

Self-management has become important as a complementary approach to the recovery of patients with mood disorders, and the need for a remote intervention program has been revealed in relation to the COVID-19 pandemic.

OBJECTIVE

The aim of this review is to systematically review the studies for evidence on the effects of online self-management interventions based on cognitive behavioral therapy or psychoeducation for patients with mood disorders and to verify the statistical significance of the effectiveness of the interventions.

METHODS

A comprehensive literature search will be conducted using a search strategy in nine electronic bibliographic databases and will include all randomized controlled trial studies conducted up through December 2021. In addition, unpublished dissertations will be reviewed to minimize publication bias and to include a wider range of research. All steps in selecting the final studies to be included in the review will be performed independently by two researchers, and any discrepancies will be resolved through discussion.

RESULTS

Institutional review board approval was not required because this study was not conducted on people. Systematic literature searches, data extraction, narrative synthesis, meta-analysis, and final writing of the systematic review and meta-analysis are expected to be completed by 2023.

CONCLUSIONS

This systematic review will provide a rationale for the development of web-based or online self-management interventions for the recovery of patients with mood disorders and will be used as a clinically meaningful reference in terms of mental health management.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45528.

Resilience to depression: Implication for psychological vaccination

From the vulnerability perspective, we often ask the question "why someone suffers from depression?" Despite outstanding achievements along this line, we still face high occurrence or recurrence and unsatisfied therapeutic efficacy of depression, suggesting that solely focusing on vulnerability perspective is insufficient to prevent and cure depression. Importantly, although experiencing same adversity, most people do not suffer from depression but manifest certain resilience, which could be used to prevent and cure depression, however, the systematic review is still lack. Here, we propose the concept "resilience to depression" to emphasize resilient diathesis against depression, by asking the question "why someone is exempted from depression?" Research evidence of resilience to depression has been reviewed systematically: positive cognitive style (clear purpose in life, hopefulness, et al.), positive emotion (emotional stability, et al.), adaptive behavior (extraversion, internal self-control, et al.), strong social interaction (gratitude and love, et al.), and neural foundation (dopamine circuit, et al.). Inspired by these evidence, "psychological vaccination" could be achieved by well-known real-world natural-stress vaccination (mild, controllable, and adaptive of stress, with help from parents or leaders) or newly developed "clinical vaccination" (positive activity intervention for current depression, preventive cognitive therapy for remitted depression, et al.), both of which aim to enhance the resilient psychological diathesis against depression, through events or training. Potential neural circuit vaccination was further discussed. This review calls for directing attention to resilient diathesis against depression, which offers a new thinking "psychological vaccination" in both prevention and therapy of depression.

Rethinking the risk for depression using the RDoC: A psychophysiological perspective

Considering that the classical categorical approach to mental disorders does not allow a clear identification of at-risk conditions, the dimensional approach provided by the Research Domain Criteria (RDoC) is useful in the exploration of vulnerability to psychopathology. In the RDoC era, psychophysiological models have an important role in the reconceptualization of mental disorders. Indeed, progress in the study of depression vulnerability has increasingly been informed by psychophysiological models. By adopting an RDoC lens, this narrative review focuses on how psychophysiological models can be used to advance our knowledge of the pathophysiological mechanisms underlying depression vulnerability. Findings from psychophysiological research that explored multiple RDoC domains in populations at-risk for depression are reviewed and discussed. Future directions for the application of psychophysiological research in reaching a more complete understanding of depression vulnerability and, ultimately, improving clinical utility, are presented.

The Role of Lifestyle on Adherence to Treatment in a Sample of Patients with Unipolar and Bipolar Depression

Introduction: Poor adherence to treatment is currently stated to be one of the causes of depression relapse and recurrence. The aim of the present study is to assess potential differences in terms of clinical and lifestyle features related to adherence to treatment in a sample of patients with unipolar and bipolar depression. Methods: One hundred and eight patients with a diagnosis of unipolar or bipolar depressive episode were recruited from January 2021 to October 2022. Adherence to psychopharmacological treatment was assessed using the clinician rating scale. Descriptive and association analyses were performed to compare subgroups based on adherence to treatment. Results: Lower levels of adherence to treatment were associated with fewer years of education, work impairment, manic prevalent polarity lifetime, and greater comorbidity with alcohol and drug abuse. The majority of patients with positive adherence did not report any hospitalization and involuntary commitment lifetime. Conclusions: Patients with a positive treatment adherence showed significant differences in terms of lifestyle and clinical features compared to non-adherent patients. Our results may help to identify patients more likely to have poor medication adherence, which seem to lead to a worse disease course and quality of life.

Predictors of relapse of psychotic depression: Findings from the STOP-PD II randomized clinical trial

Psychotic depression has a high rate of relapse. The study aims were to identify a prediction model of risk of relapse of psychotic depression and examine whether predictors moderated the effect of treatment on relapse. One hundred and twenty-six men and women aged 18-85 years, who experienced sustained remission or near-remission of psychotic depression with sertraline plus olanzapine, participated in a 36-week randomized controlled trial that compared sertraline plus olanzapine with sertraline plus placebo in preventing relapse (NCT01427608). Cox regression analyses were performed to identify significant predictors of relapse and to model the combined role of significant predictors. Concordance statistic was calculated to determine the accuracy of the best fit multivariable models in predicting relapse. Finally, interaction terms were tested for each significant predictor to examine whether they moderated the effect of treatment on risk of relapse. Lifetime number of depressive episodes, severity of residual depressive symptoms at the time of randomization, and psychomotor disturbance both at acute enrollment when participants were depressed and at the time of randomization predicted risk of relapse. Multivariable models had 69-70% accuracy in predicting relapse. Psychomotor disturbance was associated with increased risk of relapse in the sertraline plus olanzapine group compared with sertraline plus placebo, whereas the other predictors did not moderate the effect of treatment on relapse. Future research is needed to determine whether a combination of clinical and biological variables can further increase the accuracy of prediction of relapse of psychotic depression.

Directionality of change in obsessive compulsive disorder and depression over six years of prospective follow-up

Major Depressive Disorder (MDD) is often comorbid with obsessive-compulsive disorder (OCD) yet little is known about the directionality of the association between OCD and depression symptoms. We aim to investigate the effect OCD symptoms has on depression symptoms and vice versa over an extended period of time. This is one of the first longitudinal studies to evaluate the relationship between OCD and depression in a large clinical sample. Participants (n = 324) were treatment-seeking adults with a primary diagnosis of OCD. OCD and depression symptoms were assessed annually over the six-year follow-up period. Random intercepts cross-lagged panel models (RI-CLPM) were conducted to compare unidirectional and bidirectional models over time. The best-fitting and most parsimonious model included paths with OCD symptoms predicting depression symptoms, but not vice versa. OCD symptom severity in a given year predicted next year depression severity. However, depression severity did not predict next-year OCD symptom severity in this sample. Our results suggest that depression severity may be secondary to OCD symptoms and treating OCD should be prioritized over treating depression.

Anti-Inflammatory Treatment Efficacy in Major Depressive Disorder: A Systematic Review of Meta-Analyses

PURPOSE

Immune imbalances in major depressive disorder (MDD) have been targeted by anti-inflammatory treatment approaches in clinical trials to increase responsiveness to therapy. However, even after several meta-analyses, no translation of evidence into clinical practice has taken place. We performed a systematic review to evaluate meta-analytic evidence of randomized controlled trials on the use of anti-inflammatory agents for MDD to summarize efficacy estimates and elucidate shortcomings.

METHODS

Pooled effect estimates and heterogeneity indices were primary outcomes. Characteristics of the included meta-analyses were extracted. Scientific quality of meta-analyses was assessed using the Revised Assessment of Multiple Systematic Reviews (R-AMSTAR).

RESULTS

N=20 meta-analyses met the eligibility criteria. Study characteristics like outcome scales, composition of patient populations, and add-on or monotherapy regimen varied very little for celecoxib studies, varied little for minocycline studies, and were rather variable for omega 3 fatty acids studies. R-AMSTAR scores ranged from 26 to 39 out of 44 points indicating variable quality, where a comprehensive literature search was the strongest and the consideration of scientific quality in the conclusions was the weakest domain across all meta-analyses. For minocycline and celecoxib, superiority was demonstrated with medium to large effect size with substantial heterogeneity and with large to very large effect size with negligible heterogeneity, respectively. For omega 3 fatty acids, superiority was also demonstrated with mainly small and medium effect sizes with substantial heterogeneity. However, for minocycline and omega 3 fatty acids, non-significant meta-analyses were found also.

CONCLUSION

Even in our synthesized approach, no clear recommendations could be derived on the use of anti-inflammatory treatment for MDD due to several critical aspects like heterogeneity, diversity of patient populations, treatment regimen, and outcomes, and limited scientific quality. However, we observed clear inter-substance differences with meta-analytic evidence being strongest for celecoxib and weakest for omega 3 fatty acids.

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

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

EISI: Extended inter-spike interval for mental health patients clustering based on mental health services and medications utilisation

Mental health is vital in all human life stages, and managing mental healthcare service resources is crucial for providers. This paper presents a new method, called Extended Inter-Spike Interval (EISI), on identifying the patients with a similar utilisation of mental health services and medications. The EISI measures the distance between the utilisation patterns of the patients. Then, the pairwise distances are given to a developed split-and-merge Partitioning Around Medoids (PAM) clustering algorithm to identify the patients with similar utilisation patterns. To evaluate the proposed method, we use two years (2013-2014) of the 10% publicly available sample of the Australian Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) administrative data. Results show that mental health patients can be grouped into ten clusters with distinct and interpretable utilisations patterns. The largest cluster comprises individuals who only visit general practitioners and take psycholeptics medications for a short time. The smallest group contains occasional visits with general practitioners and regularly utilises psycholeptics and psychoanaleptics medications over long periods. The proposed method provides insights on whom to target and how to structure services for different groups of individuals with mental health conditions.

Transitions in depression: if, how, and when depressive symptoms return during and after discontinuing antidepressants

Purpose

The aim of the current study is to provide insight into if, how, and when meaningful changes occur in individual patients who discontinue antidepressant medication. Agreement between macro-level quantitative symptom data, qualitative ratings, and micro-level Ecological Momentary Assessments is examined.

Methods

During and shortly after antidepressant discontinuation, depressive symptoms and ‘feeling down’ were measured in 56 participants, using the SCL-90 depression subscale weekly (macro-level) for 6 months, and 5 Ecological Momentary Assessments daily (micro-level) for 4 months (30.404 quantitative measurements in total). Qualitative information was also obtained, providing additional information to verify that changes were clinically meaningful.

Results

At the macro-level, an increase in depressive symptoms was found in 58.9% of participants that (a) was statistically reliable, (b) persisted for 3 weeks and/or required intervention, and (c) was clinically meaningful to patients. Of these increases, 30.3% happened suddenly, 42.4% gradually, and for 27.3% criteria were inconclusive. Quantitative and qualitative criteria showed a very high agreement (Cohen’s κ = 0.85) regarding if a participant experienced a recurrence of depression, but a moderate agreement (Cohen’s κ = 0.49) regarding how that change occurred. At the micro-level, 41.1% of participants experienced only sudden increases in depressed mood, 12.5% only gradual, 30.4% experienced both types of increase, and 16.1% neither.

Conclusion

Meaningful change is common in patients discontinuing antidepressants, and there is substantial heterogeneity in how and when these changes occur. Depressive symptom change at the macro-level is not the same as depressive symptom change at the micro-level.

Evaluation of DNA methylation in BDNF, SLC6A4, NR3C1 and FKBP5 before and after treatment with selective serotonin-reuptake inhibitor in major depressive disorder

Aim: To identify the DNA methylation status of related genes in major depressive disorder following selective serotonin-reuptake inhibitor treatment. Materials & methods: 45 patients with major depressive disorder and 45 healthy volunteers were considered experimental and control groups, respectively. High-resolution melting real-time PCR was implemented to evaluate DNA methylation. Results: After 100 days of selective serotonin-reuptake inhibitor treatment, methylation of promoter CpG sites of BDNF, NR3C1, FKBP5 and SLC6A4 was significantly reduced. Compared with before treatment, patients' Hamilton Depression Rating Scale scores were significantly reduced after selective serotonin-reuptake inhibitor treatment (p ≤ 0.0001). Conclusion: Based on the proven effect of antidepressants on DNA methylation and gene expression, these medications can improve the treatment process and reduce depression scores after treatment.

Long-term outcomes at 24- and 36-month follow-up in the intervention arm of the randomized controlled trial of Prompt Mental Health Care

BACKGROUND

Whether long-term symptom improvement is maintained after treatment in services such as the Norwegian Prompt Mental Health Care (PMHC) and the English Improving Access to Psychological Therapies is not yet known. In this prospective study, we investigate whether improvements observed at 6-month follow-up are maintained at 24- and 36-month follow-up among clients who received PMHC.

METHOD

Data from the treatment arm of the randomized controlled trial of PMHC were used (n = 459). The main outcomes were (reliable) recovery rate and symptoms of depression (PHQ-9) and anxiety (GAD-7). Primary outcome data at 24- and 36-months follow-up were available for 47% and 39% of participants, respectively. Secondary outcomes were work participation, functional status, health-related quality of life, and positive mental well-being. Sensitivity analyses with regard to missing data assumptions were conducted for the primary continuous outcomes.

RESULTS

Improvements were maintained at 24- and 36-month follow-up for symptoms of depression and anxiety, (reliable) recovery rate, and health-related quality of life. Small linear improvements since 6-month follow-up were observed for work participation, functional status, and positive mental well-being. Sensitivity analyses did not substantially alter the findings for symptoms of depression and anxiety mentioned above.

CONCLUSIONS

Our findings support the long-term effectiveness of PMHC, but results should be interpreted with caution due to lacking follow-up data at 24- and 36-month in the control group, and substantial attrition.

Brain structural correlates of recurrence following the first episode in patients with major depressive disorder

Former prospective studies showed that the occurrence of relapse in Major Depressive Disorder (MDD) is associated with volume loss in the insula, hippocampus and dorsolateral prefrontal cortex (DLPFC). However, these studies were confounded by the patient's lifetime disease history, as the number of previous episodes predict future recurrence. In order to analyze neural correlates of recurrence irrespective of prior disease course, this study prospectively examined changes in brain structure in patients with first-episode depression (FED) over 2 years. N = 63 FED patients and n = 63 healthy controls (HC) underwent structural magnetic resonance imaging at baseline and after 2 years. According to their disease course during the follow-up interval, patients were grouped into n = 21 FED patients with recurrence (FEDrec) during follow-up and n = 42 FED patients with stable remission (FEDrem). Gray matter volume changes were analysed using group by time interaction analyses of covariance for the DLPFC, hippocampus and insula. Significant group by time interactions in the DLPFC and insula emerged. Pairwise comparisons showed that FEDrec had greater volume decline in the DLPFC and insula from baseline to follow-up compared with FEDrem and HC. No group by time interactions in the hippocampus were found. Cross-sectional analyses at baseline and follow-up revealed no differences between groups. This longitudinal study provides evidence for neural alterations in the DLPFC and insula related to a detrimental course in MDD. These effects of recurrence are already detectable at initial stages of MDD and seem to occur without any prior disease history, emphasizing the importance of early interventions preventing depressive recurrence.

Prevalence of depressive disorders and associated demographic characteristics in Shandong: An epidemiological investigation

BACKGROUND

Depression is characterized by debilitating symptoms and high recurrence rates, and there are relatively few large-scale epidemiological surveys of depressive disorders conducted in Shandong since 2005. Data from the largest Epidemiological Survey of Mental Disorders conducted in 2015 in Shandong were collected to investigate the prevalence of depressive disorders and associated demographic characteristics in general adult population.

METHODS

A multi-stage stratified cluster sampling method was adopted to select residents and a two-stage screening and assessment process was used to define the prevalence and characteristics of depressive disorders. Respondents were initially screened using the General Health Questionnaire followed by a structured clinical interview using the DSM-IV criteria.

RESULTS

Among 27,489 respondents who completed the survey, 1277 respondents met the diagnostic criteria for depressive disorders. The adjusted prevalence in the last month was 4.86%, among which the prevalence of major depressive disorder, dysthymia, and unspecified depressive disorder were 2.32%, 1.78%, and 0.75%, respectively. 40.35% of depression patients had moderate or severe functional impairment and only 10.65% of patients had visited a psychiatric service. Univariate and multivariate analyses revealed that age, gender, occupation, education, marital status, and urban/rural living were associated with the prevalence.

LIMITATIONS

The key limitation is that this is a cross-sectional survey therefore cannot draw any causal relationship between risk factors and disease progression.

CONCLUSIONS

Findings from this largest epidemiological study reveal current prevalence of depressive disorders and associated demographic factors and offers opportunities for policy makers and health-care professionals to improve mental health provision in Shandong.

Cost-Utility Analysis of Pharmacogenetic Testing Based on CYP2C19 or CYP2D6 in Major Depressive Disorder: Assessing the Drivers of Different Cost-Effectiveness Levels from an Italian Societal Perspective

Background and Objectives

Major depressive disorder (MDD) is a common and severe psychiatric disorder that has enormous economical and societal costs. As pharmacogenetics is one of the key tools of precision psychiatry, we analyze the cost–utility of test screening of CYP2C19 and CYP2D6 for patients suffering from major depressive disorder (MDD) and try to understand the main drivers that influence the cost–utility.

Methods

We developed two pharmacoeconomic nonhomogeneous Markov models to test the cost–utility, from an Italian societal perspective, of pharmacogenetic testing genetic to characterize the metabolizing profiles of cytochrome P450 (CYP) 2C19 and CYP2D6 in a hypothetical case study of patients suffering from major depressive disorder (MDD). The model considers different scenarios of adjustment of antidepressant treatment according to the patient’s metabolizing profile or treatment over a period of 18 weeks. The uncertainty of model parameters is tested through both a probabilistic sensitivity analysis and a one-way deterministic sensitivity analysis, and these results are used in a post-hoc analysis to understand the main drivers of three alternative cost-effectiveness levels (“poor,” “standard,” and “high”). These drivers are first evaluated from an exploratory multidimensional perspective and next from a predictive perspective as the probability that a patient belongs to a specific cost-effectiveness level is estimated on the basis of a restricted set of parameters used in the original pharmacoeconomic model.

Results

The models for CYP2C19 and CYP2D6 indicate that screening has an incremental cost-effectiveness ratio of 60,000€ and 47,000€ per quality-adjusted life year (QALY), respectively. The probabilistic sensitivity analysis shows that the treatments are cost-effective for a 75,000€ willingness to pay (WTP) threshold in 58% and 63% of the Monte Carlo replications, respectively. The post-hoc analysis highlights the factors that allow us to clearly discriminates poor cost-effectiveness from high cost-effectiveness scenarios and demonstrates that it is possible to predict with reasonable accuracy the cost-effectiveness of a genetic test and the associated therapeutic pattern.

Conclusions

Our findings suggest that screenings for both CYP2C19 and CYP2D6 enzymes for patients with MDD are cost-effective for a WTP threshold of 75,000€ per QALY, and provide relevant suggestions about the most important aspects to be further explored in clinical studies aimed at addressing the cost-effectiveness of genetic testing for patients diagnosed with MDD.

Predicting relapse or recurrence of depression: systematic review of prognostic models

BACKGROUND

Relapse and recurrence of depression are common, contributing to the overall burden of depression globally. Accurate prediction of relapse or recurrence while patients are well would allow the identification of high-risk individuals and may effectively guide the allocation of interventions to prevent relapse and recurrence.

AIMS

To review prognostic models developed to predict the risk of relapse, recurrence, sustained remission, or recovery in adults with remitted major depressive disorder.

METHOD

We searched the Cochrane Library (current issue); Ovid MEDLINE (1946 onwards); Ovid Embase (1980 onwards); Ovid PsycINFO (1806 onwards); and Web of Science (1900 onwards) up to May 2021. We included development and external validation studies of multivariable prognostic models. We assessed risk of bias of included studies using the Prediction model risk of bias assessment tool (PROBAST).

RESULTS

We identified 12 eligible prognostic model studies (11 unique prognostic models): 8 model development-only studies, 3 model development and external validation studies and 1 external validation-only study. Multiple estimates of performance measures were not available and meta-analysis was therefore not necessary. Eleven out of the 12 included studies were assessed as being at high overall risk of bias and none examined clinical utility.

CONCLUSIONS

Due to high risk of bias of the included studies, poor predictive performance and limited external validation of the models identified, presently available clinical prediction models for relapse and recurrence of depression are not yet sufficiently developed for deploying in clinical settings. There is a need for improved prognosis research in this clinical area and future studies should conform to best practice methodological and reporting guidelines.

Factors associated with sick leave duration in patients suffering from major depressive disorder initiating antidepressant treatment: a real-world evidence study in Germany and Spain

OBJECTIVE

To describe MDD patients starting antidepressant (AD) treatment by pharmacological approach and identify factors associated with a longer sick leave (SL) duration.

METHODS

Retrospective study on IQVIA German Disease Analyser (specialists) and Spanish Longitudinal Patient Database (general practitioners and specialists). MDD patients initiating AD treatment between July 2016-June 2018 were grouped by therapeutic approach (AD monotherapy vs. combination/switch/add-on) and their characteristics were analysed descriptively. Multiple logistic regression models were run to evaluate factors affecting SL duration (i.e., >30 days).

RESULTS

One thousand six hundred and eighty-five patients (monotherapy: 58%; combination/switch/add-on: 42%) met inclusion criteria for Germany, and 1817 for Spain (monotherapy: 83%; combination/switch/add-on: 17%). AD treatment influenced SL duration: combination/switch/add-on patients had a 2-fold and a 4-fold risk of having >30 days of SL than monotherapy patients, respectively in Germany and Spain. Patients with a gap of time between MDD diagnosis and AD treatment initiation had a higher likelihood of experiencing a longer SL both in Germany and Spain (38% higher likelihood and 6-fold risk of having >30 days of SL, respectively).

CONCLUSIONS

A careful and timely selection of AD treatment approach at the time of MDD diagnosis may improve functional recovery and help to reduce SL, minimising the socio-economic burden of the disease.Key pointsThe major depressive disorder has a substantial impact on work absenteeism.The present study aimed to describe MDD patients starting antidepressant (AD) treatment depending on the pharmacological approach and to identify factors associated with longer sick leave (SL) duration.Patients receiving AD monotherapy had a lower likelihood of having more than 30 days of sick leave than those receiving AD combination/switch/add-on.Patients for whom a gap of time between MDD diagnosis and initiation of AD treatment was observed, showed a higher likelihood of having more than 30 days of sick leave.Because findings from this analysis relied on secondary data, the authors would like to claim the urgency of conducting prospective observational studies that further investigate the effect that different AD therapeutic approaches and timely initiation of treatment might exert on patients' recovery.

Low predictive power of clinical features for relapse prediction after antidepressant discontinuation in a naturalistic setting

The risk of relapse after antidepressant medication (ADM) discontinuation is high. Predictors of relapse could guide clinical decision-making, but are yet to be established. We assessed demographic and clinical variables in a longitudinal observational study before antidepressant discontinuation. State-dependent variables were re-assessed either after discontinuation or before discontinuation after a waiting period. Relapse was assessed during 6 months after discontinuation. We applied logistic general linear models in combination with least absolute shrinkage and selection operator and elastic nets to avoid overfitting in order to identify predictors of relapse and estimated their generalisability using cross-validation. The final sample included 104 patients (age: 34.86 (11.1), 77% female) and 57 healthy controls (age: 34.12 (10.6), 70% female). 36% of the patients experienced a relapse. Treatment by a general practitioner increased the risk of relapse. Although within-sample statistical analyses suggested reasonable sensitivity and specificity, out-of-sample prediction of relapse was at chance level. Residual symptoms increased with discontinuation, but did not relate to relapse. Demographic and standard clinical variables appear to carry little predictive power and therefore are of limited use for patients and clinicians in guiding clinical decision-making.

Augmenting neurocognitive remediation therapy to Preventive Cognitive Therapy for partially remitted depressed patients: protocol of a pragmatic multicentre randomised controlled trial

INTRODUCTION

Major depressive disorder (MDD) affects 163 million people globally every year. Individuals who experience subsyndromal depressive symptoms during remission (ie, partial remission of MDD) are especially at risk for a return to a depressive episode within an average of 4 months. Simultaneously, partial remission of MDD is associated with work and (psycho)social impairment and a lower quality of life. Brief psychological interventions such as preventive cognitive therapy (PCT) can reduce depressive symptoms or relapse for patients in partial remission, although achieving full remission with treatment is still a clinical challenge. Treatment might be more effective if cognitive functioning of patients is targeted as well since cognitive problems are the most persisting symptom in partial remission and predict poor treatment response and worse functioning. Studies show that cognitive functioning of patients with (remitted) MDD can be improved by online neurocognitive remediation therapy (oNCRT). Augmenting oNCRT to PCT might improve treatment effects for these patients by strengthening their cognitive functioning alongside a psychological intervention.

METHODS AND ANALYSIS

This study will examine the effectiveness of augmenting oNCRT to PCT in a pragmatic national multicentre superiority randomised controlled trial. We will include 115 adults partially remitted from MDD with subsyndromal depressive symptoms defined as a Hamilton Depression Rating Scale score between 8 and 15. Participants will be randomly allocated to PCT with oNCRT, or PCT only. Primary outcome measure is the effect on depressive symptomatology over 1 year. Secondary outcomes include time to relapse, cognitive functioning, quality of life and healthcare costs. This first dual approach study of augmenting oNCRT to PCT might facilitate full remission in partially remitted individuals as well as prevent relapse over time.

ETHICS AND DISSEMINATION

Ethical approval was obtained by Academic Medical Center, Amsterdam. Outcomes will be made publicly available.

TRIAL REGISTRATION NUMBER

NL9582.

General Transcription Factor IIF Polypeptide 2: A Novel Therapeutic Target for Depression Identified Using an Integrated Bioinformatic Analysis

Depression currently affects 4% of the world’s population; it is associated with disability in 11% of the global population. Moreover, there are limited resources to treat depression effectively. Therefore, we aimed to identify a promising novel therapeutic target for depression using bioinformatic analysis. The GSE54568, GSE54570, GSE87610, and GSE92538 gene expression data profiles were retrieved from the Gene Expression Omnibus (GEO) database. We prepared the four GEO profiles for differential analysis, protein–protein interaction (PPI) network construction, and weighted gene co-expression network analysis (WGCNA). Gene Ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes metabolic pathway analyses were conducted to determine the key functions of the corresponding genes. Additionally, we performed correlation analyses of the hub genes with transcription factors, immune genes, and N6-methyladenosine (m6A) genes to reveal the functional landscape of the core genes associated with depression. Compared with the control samples, the depression samples contained 110 differentially expressed genes (DEGs), which comprised 56 downregulated and 54 upregulated DEGs. Moreover, using the WGCNA and PPI clustering analysis, the blue module and cluster 1 were found to be significantly correlated with depression. GTF2F2 was the only common gene identified using the differential analysis and WGCNA; thus, it was used as the hub gene. According to the enrichment analyses, GTF2F2 was predominantly involved in the cell cycle and JAK-STAT, PI3K-Akt, and p53 signaling pathways. Furthermore, differential and correlation analyses revealed that 9 transcription factors, 12 immune genes, and 2 m6A genes were associated with GTF2F2 in depression samples. GTF2F2 may serve as a promising diagnostic biomarker and treatment target of depression, and this study provides a novel perspective and valuable information to explore the molecular mechanism of depression.

Static and treatment-responsive brain biomarkers of depression relapse vulnerability following prophylactic psychotherapy: Evidence from a randomized control trial

•

A prospective study of neural biomarkers of relapse in remitted depressed patients.

•

Assessed neural response to dysphoric mood-induction before and after psychotherapy.

•

Relapse over a 2-year follow-up linked to dysphoria-evoked sensory inhibition.

•

Relapse risk was lower when dorsolateral prefrontal reactivity decreased over time.

•

Depression prophylaxis may involve reducing dysphoria-evoked sensory inhibition.

Background

Neural reactivity to dysphoric mood induction indexes the tendency for distress to promote cognitive reactivity and sensory avoidance. Linking these responses to illness prognosis following recovery from Major Depressive Disorder informs our understanding of depression vulnerability and provides engagement targets for prophylactic interventions.

Methods

A prospective fMRI neuroimaging design investigated the relationship between dysphoric reactivity and relapse following prophylactic intervention. Remitted depressed outpatients (N = 85) were randomized to 8 weeks of Cognitive Therapy with a Well-Being focus or Mindfulness Based Cognitive Therapy. Participants were assessed before and after therapy and followed for 2 years to assess relapse status. Neural reactivity common to both assessment points identified static biomarkers of relapse, whereas reactivity change identified dynamic biomarkers.

Results

Dysphoric mood induction evoked prefrontal activation and sensory deactivation. Controlling for past episodes, concurrent symptoms and medication status, somatosensory deactivation was associated with depression recurrence in a static pattern that was unaffected by prophylactic treatment, HR 0.04, 95% CI [0.01, 0.14], p < .001. Treatment-related prophylaxis was linked to reduced activation of the left lateral prefrontal cortex (LPFC), HR 3.73, 95% CI [1.33, 10.46], p = .013. Contralaterally, the right LPFC showed dysphoria-evoked inhibitory connectivity with the right somatosensory biomarker

Conclusions

These findings support a two-factor model of depression relapse vulnerability, in which: enduring patterns of dysphoria-evoked sensory deactivation contribute to episode return, but vulnerability may be mitigated by targeting prefrontal regions responsive to clinical intervention. Emotion regulation during illness remission may be enhanced by reducing prefrontal cognitive processes in favor of sensory representation and integration.

Intensity of Treatment as Usual and Its Impact on the Effects of Face-to-Face and Internet-Based Psychotherapy for Depression: A Preregistered Meta-Analysis of Randomized Controlled Trials

INTRODUCTION

Treatment as usual (TAU) is the most frequently used control group in randomized trials of psychotherapy for depression. Concerns have been raised that the heterogeneity of treatments in TAU leads to biased estimates of psychotherapy efficacy and to an unclear difference between TAU and control groups like waiting list (WL).

OBJECTIVE

We investigated the impact of control group intensity (i.e., amount and degree to which elements of common depression treatments are provided) on the effects of face-to-face and internet-based psychotherapy for depression.

METHODS

We conducted a preregistered meta-analysis (www.osf.io/4mzyd). We included trials comparing psychotherapy with TAU or WL in patients with symptoms of unipolar depression. Six indicators were used to assess control group intensity.

PRIMARY OUTCOME

Standardized mean difference (SMD) of psychotherapy and control in depressive symptoms at treatment termination.

RESULTS

We included 89 trials randomizing 14,474 patients to 113 psychotherapy conditions and 89 control groups (TAU in 42 trials, WL in 47 trials). Control group intensity predicted trial results in preregistered (one-sided ps < 0.042) and exploratory analyses. Psychotherapy effects were significantly smaller (one-sided p = 0.002) in trials with higher intensity TAU (SMD = 0.324, CI 0.209 to 0.439) than in trials with lower intensity TAU (SMD = 0.628, CI 0.455 to 0.801). Psychotherapy effects against lower intensity TAU did not differ from effects against WL (two-sided p = 0.663).

CONCLUSIONS

Our results suggest that variation in TAU intensity impacts the outcome of trials. More scrutiny in the design of control groups for clinical trials is recommended.

Gender differences in clinical and biochemical parameters of patients consecutively hospitalized for unipolar depression

Major Depressive Disorder (MDD) is a medical illness twice as common in women than in men lifetime. Purpose of this study is to identify gender differences in clinical and biochemical parameters in subjects affected by MDD to implement individualized treatment strategies. We recruited 234 patients (112 males and 122 females) consecutively hospitalized for MDD in Milan (Italy). Data were obtained through a screening of the clinical charts and blood analyses. Univariate analyses, binary logistic regressions and a final logistic regression model were performed. The final logistic regression model showed that female patients (compared to males) had lower plasmatic levels of hemoglobin (p = 0.020) and uric acid (p = 0.002), higher levels of cholesterol (p < 0.001), had been treated with a lower number of antidepressants (p = 0.011), presented lower red blood cells (p < 0.001) and showed more frequently comorbidity with hypothyroidism (p = 0.036). Univariate analyses identified also that women had an earlier age at onset (p = 0.043), were less likely to have comorbidity with diabetes (p = 0.002) and were less frequently treated with a psychiatric polytherapy (p < 0.001). Finally, female patients had achieved more frequently remission in the last depressive episode (p = 0.001) and were more likely to have family history for psychiatric disorders (p < 0.001) than males. Female patients globally have a better response to treatments, but they seem to be more vulnerable to specific metabolic abnormalities as showed by more frequent hypercholesterolemia and lower plasma levels of uric acid. These results have to be confirmed by further studies.