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Background: Although suicide bereavement is associated with suicide and self-harm, evidence regarding mechanisms is lacking. We investigated whether depression and substance use (alcohol and/or other drugs) explain the association between partner suicide bereavement and suicide. Methods: Linkage of nationwide, longitudinal data from Denmark for the period 1980–2016 facilitated a comparison of 22 668 individuals exposed to bereavement by a partner's suicide with 913 402 individuals bereaved by a partner's death due to other causes. Using causal mediation models, we estimated the degree to which depression and substance use (considered separately) mediated the association between suicide bereavement and suicide. Results: Suicide-bereaved partners were found to have a higher risk of suicide (HRadj = 1.59, 95% CI 1.36–1.86) and of depression (ORadj 1.16, 95% CI 1.09–1.25) when compared to other-bereaved partners, but a lower risk of substance use (ORadj 0.83; 95% CI 0.78–0.88). An increased risk of suicide was found among any bereaved individuals with a depression diagnosis recorded post-bereavement (ORadj 3.92, 95% CI 3.55–4.34). Mediation analysis revealed that depression mediated 2% (1.68%; 95% CI 0.23%–3.14%; p = 0.024) of the association between suicide bereavement and suicide in partners when using bereaved controls. Conclusions: Depression is a partial mediator of the association between suicide bereavement and suicide. Efforts to prevent and optimize the treatment of depression in suicide-bereaved people could reduce their suicide risk. Our findings might be conservative because we did not include cases of depression diagnosed in primary care. Further work is needed to understand this and other mediators. [ABSTRACT FROM AUTHOR]

Background: Individuals in a depressive episode and healthy controls exhibit robust differences on affect dynamics captured with ecological momentary assessment (EMA). However, few studies have explored affect dynamics in individuals in remission from depression, and results have been mixed. Methods: A community sample of 18-year-olds (N = 345) completed diagnostic interviews and EMA probing emotions and low interest/motivation 5× daily for 2 weeks. Affect home base, variability, and inertia were compared across currently depressed, remitted, and never-depressed groups. Results: Both depression groups had a higher negative affect (NA) and low interest/motivation home base, lower positive affect (PA) home base, greater variability of NA, PA, and low interest/motivation, and greater NA and low interest/motivation inertia than never-depressed participants. Additionally, the currently depressed group had a higher sad home base specifically, greater variability across most negative emotions and low interest/motivation, and greater low interest/motivation inertia than the remitted group. The currently depressed and remitted groups did not differ in anxious, upset, or PA home base, anxious or PA variability, and inertia of all negative emotions and PA. Conclusions: Findings suggest that a number of abnormalities in emotion and reward functioning persist after a depressive episode resolves, however, the tendency to experience higher levels of sadness, greater range of a variety of negative emotions, and more variable and persistent low interest/motivation are exacerbated during depressive episodes. Conversely, greater intensity and persistence of some negative emotions (anxiety, upset) and blunted positive emotions appear to equally characterize depression in both the symptomatic and remitted state. [ABSTRACT FROM AUTHOR]

Background: Depression is characterized by abnormalities in emotional processing, but the specific drivers of such emotional abnormalities are unknown. Computational work indicates that both surprising outcomes (prediction errors; PEs) and outcomes (values) themselves drive emotional responses, but neither has been consistently linked to affective disturbances in depression. As a result, the computational mechanisms driving emotional abnormalities in depression remain unknown. Methods: Here, in 687 individuals, one-third of whom qualify as depressed via a standard self-report measure (the PHQ-9), we use high-stakes, naturalistic events – the reveal of midterm exam grades – to test whether individuals with heightened depression display a specific reduction in emotional response to positive PEs. Results: Using Bayesian mixed effects models, we find that individuals with heightened depression do not affectively benefit from surprising, good outcomes – that is, they display reduced affective responses to positive PEs. These results were highly specific: effects were not observed to negative PEs, value signals (grades), and were not related to generalized anxiety. This suggests that the computational drivers of abnormalities in emotion in depression may be specifically due to positive PE-based emotional responding. Conclusions: Affective abnormalities are core depression symptoms, but the computational mechanisms underlying such differences are unknown. This work suggests that blunted affective reactions to positive PEs are likely mechanistic drivers of emotional dysregulation in depression. [ABSTRACT FROM AUTHOR]

Background: To evaluate the clinical efficacy of COMPASS, a therapist-supported digital therapeutic for reducing psychological distress (anxiety/depression) in people living with long-term physical health conditions (LTCs). Methods: A two-armed randomized-controlled trial recruiting from LTC charities. Participants with anxiety and/or depression symptoms related to their LTC(s) were randomized (concealed allocation via independent administrator) to COMPASS (access to 11 tailored modules plus five thirty-minute therapist support sessions) or standard charity support (SCS). Assessments were completed online pre-randomization, at 6- and 12-weeks post-randomization. Primary outcome was Patient Health Questionnaire Anxiety and Depression Scale; PHQ-ADS measured at 12-weeks. Analysis used intention-to-treat principles with adjusted mean differences estimated using linear mixed-effects models. Data-analyst was blinded to group allocation. Results: 194 participants were randomized to COMPASS (N = 94) or SCS (N = 100). At 12-weeks, mean level of psychological distress was 6.82 (95% confidence interval; CI 4.55–9.10) points lower (p < 0.001) in the COMPASS arm compared with SCS (standardized mean difference of 0.71 (95% CI 0.48–0.95)). The COMPASS arm also showed moderate significant treatment effects on secondary outcomes including depression, anxiety and illness-related distress and small significant effects on functioning and quality-of-life. Rates of adverse events were comparable across the arms. Deterioration in distress at 12-weeks was observed in 2.2% of the SCS arm, and no participants in the COMPASS arm. Conclusion: Compared with SCS, COMPASS digital therapeutic with minimal therapist input reduces psychological distress at post-treatment (12-weeks). COMPASS offers a potentially scalable implementation model for health services but its translation to these contexts needs further evaluating. Trial Registration: NCT04535778 [ABSTRACT FROM AUTHOR]

Background: Increased autocorrelation (AR) of system-specific measures has been suggested as a predictor for critical transitions in complex systems. Increased AR of mood scores has been reported to anticipate depressive episodes in major depressive disorder, while other studies found AR increases to be associated with depressive episodes themselves. Data on AR in patients with bipolar disorders (BD) is limited and inconclusive. Methods: Patients with BD reported their current mood via daily e-diaries for 12 months. Current affective status (euthymic, prodromal, depressed, (hypo)manic) was assessed in 26 bi-weekly expert interviews. Exploratory analyses tested whether self-reported current mood and AR of the same item could differentiate between prodromal phases or affective episodes and euthymia. Results: A total of 29 depressive and 20 (hypo)manic episodes were observed in 29 participants with BD. Self-reported current mood was significantly decreased during the two weeks prior to a depressive episode (early prodromal, late prodromal), but not changed prior to manic episodes. The AR was neither a significant predictor for the early or late prodromal phase of depression nor for the early prodromal phase of (hypo)mania. Decreased AR was found in the late prodromal phase of (hypo)mania. Increased AR was mainly found during depressive episodes. Conclusions: AR changes might not be better at predicting depressive episodes than simple self-report measures on current mood in patients with BD. Increased AR was mostly found during depressive episodes. Potentially, changes in AR might anticipate (hypo)manic episodes. [ABSTRACT FROM AUTHOR]

Background: To address if the long-standing association between maternal infection, depression/anxiety in pregnancy, and offspring neurodevelopmental disorder (NDD) is causal, we conducted two negative-control studies. Methods: Four primary care cohorts of UK children (pregnancy, 1 and 2 years prior to pregnancy, and siblings) born between 1 January 1990 and 31 December 2017 were constructed. NDD included autism/autism spectrum disorder, attention-deficit/hyperactivity disorder, intellectual disability, cerebral palsy, and epilepsy. Maternal exposures included depression/anxiety and/or infection. Maternal (age, smoking status, comorbidities, body mass index, NDD); child (gender, ethnicity, birth year); and area-level (region and level of deprivation) confounders were captured. The NDD incidence rate among (1) children exposed during or outside of pregnancy and (2) siblings discordant for exposure in pregnancy was compared using Cox-regression models, unadjusted and adjusted for confounders. Results: The analysis included 410 461 children of 297 426 mothers and 2 793 018 person-years of follow-up with 8900 NDD cases (incidence rate = 3.2/1000 person years). After adjustments, depression and anxiety consistently associated with NDD (pregnancy-adjusted HR = 1.58, 95% CI 1.46–1.72; 1-year adj. HR = 1.49, 95% CI 1.39–1.60; 2-year adj. HR = 1.62, 95% CI 1.50–1.74); and to a lesser extent, of infection (pregnancy adj. HR = 1.16, 95% CI 1.10–1.22; 1-year adj. HR = 1.20, 95% CI 1.14–1.27; 2-year adj. HR = 1.19, 95% CI 1.12–1.25). NDD risk did not differ among siblings discordant for pregnancy exposure to mental illness HR = 0.97, 95% CI 0.77–1.21 or infection HR = 0.99, 95% CI 0.90–1.08. Conclusions: Maternal risk appears to be unspecific to pregnancy: our study provided no evidence of a specific, and therefore causal, link between in-utero exposure to infection, common mental illness, and later development of NDD. [ABSTRACT FROM AUTHOR]

Background: To investigate the association between pre-trial expectancy, suggestibility, and response to treatment in a trial of escitalopram and investigational drug, COMP360, psilocybin, in the treatment of major depressive disorder (ClinicalTrials.gov registration: NCT03429075). Methods: We used data (n = 55) from our recent double-blind, parallel-group, randomized head-to-head comparison trial of escitalopram and investigational drug, COMP360, psilocybin. Mixed linear models were used to investigate the association between pre-treatment efficacy-related expectations, as well as baseline trait suggestibility and absorption, and therapeutic response to both escitalopram and COMP360 psilocybin. Results: Patients had significantly higher expectancy for psilocybin relative to escitalopram; however, expectancy for escitalopram was associated with improved therapeutic outcomes to escitalopram, expectancy for psilocybin was not predictive of response to psilocybin. Separately, we found that pre-treatment trait suggestibility was associated with therapeutic response in the psilocybin arm, but not in the escitalopram arm. Conclusions: Overall, our results suggest that psychedelic therapy may be less vulnerable to expectancy biases than previously suspected. The relationship between baseline trait suggestibility and response to psilocybin therapy implies that highly suggestible individuals may be primed for response to this treatment. [ABSTRACT FROM AUTHOR]

Background: Internet-based interventions produce comparable effectiveness rates as face-to-face therapy in treating depression. Still, more than half of patients do not respond to treatment. Machine learning (ML) methods could help to overcome these low response rates by predicting therapy outcomes on an individual level and tailoring treatment accordingly. Few studies implemented ML algorithms in internet-based depression treatment using baseline self-report data, but differing results hinder inferences on clinical practicability. This work compares algorithms using features gathered at baseline or early in treatment in their capability to predict non-response to a 6-week online program targeting depression. Methods: Our training and test sample encompassed 1270 and 318 individuals, respectively. We trained random forest algorithms on self-report and process features gathered at baseline and after 2 weeks of treatment. Non-responders were defined as participants not fulfilling the criteria for reliable and clinically significant change on PHQ-9 post-treatment. Our benchmark models were logistic regressions trained on baseline PHQ-9 sum or PHQ-9 early change, using 100 iterations of randomly sampled 80/20 train-test-splits. Results: Best performances were reached by our models involving early treatment characteristics (recall: 0.75–0.76; AUC: 0.71–0.77). Therapeutic alliance and early symptom change constituted the most important predictors. Models trained on baseline data were not significantly better than our benchmark. Conclusions: Fair accuracies were only attainable by involving information from early treatment stages. In-treatment adaptation, instead of a priori selection, might constitute a more feasible approach for improving response when relying on easily accessible self-report features. Implementation trials are needed to determine clinical usefulness. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic disrupted many areas of life, including culturally accepted practices at end-of-life care, funeral rites, and access to social, community, and professional support. This survey investigated the mental health outcomes of Australians bereaved during this time to determine how these factors might have impacted bereavement outcomes. Methods: An online survey indexing pandemic and bereavement experiences, levels of grief, depression, anxiety, and health, work, and social impairment. Latent class analysis (LCA) was used to identify groups of individuals who shared similar symptom patterns. Multinomial regressions identified pandemic-related, loss-related, and sociodemographic correlates of class membership. Results: 1911 Australian adults completed the survey. The LCA identified four classes: low symptoms (46.8%), grief (17.3%), depression/anxiety (17.7%), and grief/depression/anxiety (18.2%). The latter group reported the highest levels of health, work, and social impairment. The death of a child or partner and an inability to care for the deceased due to COVID-19 public health measures were correlated with grief symptoms (with or without depression and anxiety). Preparedness for the person's death and levels of pandemic-related loneliness and social isolation differentiated all four classes. Unemployment was associated with depression/anxiety (with or without grief). Conclusions: COVID-19 had profound impacts for the way we lived and died, with effects that are likely to ricochet through society into the foreseeable future. These lessons learned must inform policymakers and healthcare professionals to improve bereavement care and ensure preparedness during and following future predicted pandemics to prevent negative impacts. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Cross-sectional studies report high levels of depressive symptoms during the COVID-19 pandemic, especially in youth and females. However, longitudinal research comparing depressive symptoms before and during the pandemic is lacking. Little is known about how the pandemic affected individuals with familial history of mental illness. The present study examines the impact of the pandemic on youth depressive symptoms, including offspring of parents with major mood and psychotic disorders. Methods: Between March 2018 and February 2020, we measured depressive symptoms in 412 youth aged 5–25 years. We measured depressive symptoms again in 371 (90%) of these youth between April 2020 and May 2022. Two thirds (249) participants had a biological parent with a major mood or psychotic disorder. We tested the effect of the pandemic by comparing depression symptoms before and after March 2020. We examined age, sex, and family history as potential moderators. Results: We found an overall small increase in youth depressive symptoms (b = 0.07, 95% CI −0.01 to 0.15, p = 0.062). This was driven by an increase in female youth without familial history of mental illness (b = 0.35, 95% CI 0.14 to 0.56, p = 0.001). There was no change in depressive symptoms among offspring of parents with mental illness or males. Conclusions: Our results provide reassurance about the wellbeing of children of parents with mental illness during a period of restricted access to resources outside the family. Rather than increasing symptoms in established risk groups, the pandemic led to a redistribution of depression burden towards segments of the youth population that were previously considered to be low-risk. [ABSTRACT FROM AUTHOR]

Background: There are many barriers to engaging in current psychological treatments, including time, cost, and availability. Ultra-brief treatments overcome some of these barriers by delivering therapeutic information and skills using significantly less time than standard-length treatments. We developed a therapist-guided online ultra-brief treatment for depression and anxiety and compared it to an existing 8-week, 5-lesson therapist-guided standard-length treatment and a waitlist control. Methods: In a randomized controlled trial, adults with self-reported depression or anxiety were randomized (1:1:1) to the ultra-brief treatment, standard-length treatment, or waitlist control. The primary outcomes were depression symptoms and anxiety symptoms assessed at baseline, 5-weeks later, 9-weeks later (primary timepoint), and 3-months later. The trial was prospectively registered. Results: Between 7 February 2022, and 16 August 2022, 242 participants were enrolled in the ultra-brief treatment (n = 85), standard-length treatment (n = 80), and waitlist control (n = 77). Participants were mostly women with an average age of 48.56 years. At 9-weeks post-baseline, participants in the ultra-brief treatment group reported significantly lower depression (between groups d = 0.41) and anxiety (d = 0.53) than the waitlist control. The ultra-brief treatment was non-inferior for anxiety at both 9-weeks and 3-months follow-up. Non-inferiority for depression was observed at 9-weeks. Conclusions: The online ultra-brief treatment resulted in significant reductions in depression and anxiety that were non-inferior to a longer treatment course after 9-weeks. Remotely delivered ultra-brief treatments have the potential to provide accessible and effective care for those who cannot, or would prefer not to, access longer psychological interventions. [ABSTRACT FROM AUTHOR]

Reward processing dysfunctions are considered a candidate mechanism underlying anhedonia and apathy in depression. Neuroimaging studies have documented that neurofunctional alterations in mesocorticolimbic circuits may neurally mediate these dysfunctions. However, common and distinct neurofunctional alterations during motivational and hedonic evaluation of monetary and natural rewards in depression have not been systematically examined. Here, we capitalized on pre-registered neuroimaging meta-analyses to (1) establish general reward-related neural alterations in depression, (2) determine common and distinct alterations during the receipt and anticipation of monetary v. natural rewards, and, (3) characterize the differences on the behavioral, network, and molecular level. The pre-registered meta-analysis (https://osf.io/ay3r9) included 633 depressed patients and 644 healthy controls and revealed generally decreased subgenual anterior cingulate cortex and striatal reactivity toward rewards in depression. Subsequent comparative analyses indicated that monetary rewards led to decreased hedonic reactivity in the right ventral caudate while natural rewards led to decreased reactivity in the bilateral putamen in depressed individuals. These regions exhibited distinguishable profiles on the behavioral, network, and molecular level. Further analyses demonstrated that the right thalamus and left putamen showed decreased activation during the anticipation of monetary reward. The present results indicate that distinguishable neurofunctional alterations may neurally mediate reward-processing alterations in depression, in particular, with respect to monetary and natural rewards. Given that natural rewards prevail in everyday life, our findings suggest that reward-type specific interventions are warranted and challenge the generalizability of experimental tasks employing monetary incentives to capture reward dysregulations in everyday life. [ABSTRACT FROM AUTHOR]

Background: Learning from rewarded and punished choices is perturbed in depressed patients, suggesting that abnormal reinforcement learning may be a cognitive mechanism of the illness. However, previous studies have disagreed about whether this behavior is produced by alterations in the rate of learning or sensitivity to experienced outcomes. This previous work has generally assessed learning in response to binary outcomes of one valence, rather than to both rewarding and punishing continuous outcomes. Methods: A novel drifting reward and punishment magnitude reinforcement-learning task was administered to patients with current (n = 40) and remitted depression (n = 39), and healthy volunteers (n = 40) to capture potential differences in learning behavior. Standard questionnaires were administered to measure self-reported depressive symptom severity, trait and state anxiety and level of anhedonic symptoms. Results: Our findings demonstrate that patients with current depression adjust their learning behaviors to a lesser degree in response to trial-by-trial variations in reward and loss magnitudes than the other groups. Computational modeling revealed that this behavioral signature of current depressive state is better accounted for by reduced reward and punishment sensitivity (all p < 0.031), rather than a change in learning rate (p = 0.708). However, between-group differences were not related to self-reported symptom severity or comorbid anxiety disorders in the current depression group. Conclusion: These findings suggest that current depression is associated with reduced outcome sensitivity rather than altered learning rate. Previous findings reported in this domain mainly from binary learning tasks seem to generalize to learning from continuous outcomes. [ABSTRACT FROM AUTHOR]

Background: Research implicates inflammation in the vicious cycle between depression and obesity, yet few longitudinal studies exist. The rapid weight loss induced by bariatric surgery is known to improve depressive symptoms dramatically, but preoperative depression diagnosis may also increase the risk for poor weight loss. Therefore, we investigated longitudinal associations between depression and inflammatory markers and their effect on weight loss and clinical outcomes in bariatric patients. Methods: This longitudinal observational study of 85 patients with obesity undergoing bariatric surgery included 41 cases with depression and 44 controls. Before and 6 months after surgery, we assessed depression by clinical interview and measured serum high-sensitivity C-reactive protein (hsCRP) and inflammatory cytokines, including interleukin (IL)-6 and IL-10. Results: Before surgery, depression diagnosis was associated with significantly higher serum hsCRP, IL-6, and IL-6/10 ratio levels after controlling for confounders. Six months after surgery, patients with pre-existing depression still had significantly higher inflammation despite demonstrating similar weight loss to controls. Hierarchical regression showed higher baseline hsCRP levels predicted poorer weight loss (β = −0.28, p = 0.01) but had no effect on depression severity at follow-up (β = −0.02, p = 0.9). Instead, more severe baseline depressive symptoms and childhood emotional abuse predicted greater depression severity after surgery (β = 0.81, p < 0.001; and β = 0.31, p = 0.001, respectively). Conclusions: Depression was significantly associated with higher inflammation beyond the effect of obesity and other confounders. Higher inflammation at baseline predicted poorer weight loss 6 months after surgery, regardless of depression diagnosis. Increased inflammation, rather than depression, may drive poor weight loss outcomes among bariatric patients. [ABSTRACT FROM AUTHOR]

Background: Twice weekly sessions of cognitive behavioral therapy (CBT) and interpersonal psychotherapy (IPT) for major depressive disorder (MDD) lead to less drop-out and quicker and better response compared to once weekly sessions at posttreatment, but it is unclear whether these effects hold over the long run. Aims: Compare the effects of twice weekly v. weekly sessions of CBT and IPT for depression up to 24 months since the start of treatment. Methods: Using a 2 × 2 factorial design, this multicentre study randomized 200 adults with MDD to once or twice weekly sessions of CBT or IPT over 16–24 weeks, up to a maximum of 20 sessions. Main outcome measures were depression severity, measured with the Beck Depression Inventory-II and the Longitudinal Interval Follow-up Evaluation. Intention-to-treat analyses were conducted. Results: Compared with patients who received once weekly sessions, patients who received twice weekly sessions showed a significant decrease in depressive symptoms up through month 9, but this effect was no longer apparent at month 24. Patients who received CBT showed a significantly larger decrease in depressive symptoms up to month 24 compared to patients who received IPT, but the between-group effect size at month 24 was small. No differential effects between session frequencies or treatment modalities were found in response or relapse rates. Conclusions: Although a higher session frequency leads to better outcomes in the acute phase of treatment, the difference in depression severity dissipated over time and there was no significant difference in relapse. [ABSTRACT FROM AUTHOR]

Background: Electroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, monocenter studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers. The objective of this study was to develop and validate neuroimaging biomarkers for ECT outcome in a multicenter setting. Methods: Multimodal data (i.e. clinical, sMRI and resting-state fMRI) were collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluate which data modalities or combinations thereof could provide the best predictions for treatment remission (HAM-D score ⩽7) using a support vector machine classifier. Results: Remission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82–0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers (N = 109), and remained acceptable when validated using leave-one-site-out cross-validation (0.70–0.73 AUC). Conclusions: These results show that multimodal neuroimaging data can be used to predict remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. Future development of a clinical decision support tool applying these biomarkers may be feasible. [ABSTRACT FROM AUTHOR]

Background: The association between weight and depressive symptoms is well established, but the direction of effects remains unclear. Most studies rely on body mass index (BMI) as the sole weight indicator, with few examining the aetiology of the association between weight indicators and depressive symptoms. Methods: We analysed data from the Twins Early Development Study (TEDS) and UK Adult Twin Registry (TwinsUK) (7658 and 2775 twin pairs, respectively). A phenotypic cross-lagged panel model assessed the directionality between BMI and depressive symptoms at ages 12, 16, and 21 years in TEDS. Bivariate correlations tested the phenotypic association between a range of weight indicators and depressive symptoms in TwinsUK. In both samples, structural equation modelling of twin data investigated genetic and environmental influences between weight indicators and depression. Sensitivity analyses included two-wave phenotypic cross-lagged panel models and the exclusion of those with a BMI <18.5. Results: Within TEDS, the relationship between BMI and depression was bidirectional between ages 12 and 16 with a stronger influence of earlier BMI on later depression. The associations were unidirectional thereafter with depression at 16 influencing BMI at 21. Small genetic correlations were found between BMI and depression at ages 16 and 21, but not at 12. Within TwinsUK, depression was weakly correlated with weight indicators; therefore, it was not possible to generate precise estimates of genetic or environmental correlations. Conclusions: The directionality of the relationship between BMI and depression appears to be developmentally sensitive. Further research with larger genetically informative samples is needed to estimate the aetiological influence on these associations. [ABSTRACT FROM AUTHOR]

Background: Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians. Methods: In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance. Results: Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12. Conclusions: Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies. [ABSTRACT FROM AUTHOR]

Background: Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small-sample studies comparing single responder v. non-responder networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance. Methods: N = 40 518 patients receiving treatment for depression in routine care in England from 2015–2020 were analysed. Cross-sectional networks were constructed using the Patient Health Questionnaire-9 (PHQ-9) for responders and non-responders (N = 20 259 each). To conduct parametric tests investigating the contribution of PHQ-9 sum score mean and variance to connectivity differences, networks were constructed for 160 independent subsamples of responders and non-responders (80 each, n = 250 per sample). Results: The baseline non-responder network was more connected than responders (3.15 v. 2.70, S = 0.44, p < 0.001), but effects were small, requiring n = 750 per group to have 85% power. Parametric analyses revealed baseline network connectivity, PHQ-9 sum score mean, and PHQ-9 sum score variance were correlated (r = 0.20–0.58, all p < 0.001). Both PHQ-9 sum score mean (β = −1.79, s.e. = 0.07, p < 0.001), and PHQ-9 sum score variance (β = −1.67, s.e. = 0.09, p < 0.001) had larger effect sizes for predicting response than connectivity (β = −1.35, s.e. = 0.12, p < 0.001). The association between connectivity and response disappeared when PHQ-9 sum score variance was accounted for (β = −0.28, s.e. = 0.19, p = 0.14). We replicated these results in patients completing longer treatment (8–12 weeks, N = 22 952) and using anxiety symptom networks (N = 70 620). Conclusions: The association between baseline network connectivity and treatment response may be largely due to differences in baseline score variance. [ABSTRACT FROM AUTHOR]

Background: The incidence of adolescent depressive disorder is globally skyrocketing in recent decades, albeit the causes and the decision deficits depression incurs has yet to be well-examined. With an instrumental learning task, the aim of the current study is to investigate the extent to which learning behavior deviates from that observed in healthy adolescent controls and track the underlying mechanistic channel for such a deviation. Methods: We recruited a group of adolescents with major depression and age-matched healthy control subjects to carry out the learning task with either gain or loss outcome and applied a reinforcement learning model that dissociates valence (positive v. negative) of reward prediction error and selection (chosen v. unchosen). Results: The results demonstrated that adolescent depressive patients performed significantly less well than the control group. Learning rates suggested that the optimistic bias that overall characterizes healthy adolescent subjects was absent for the depressive adolescent patients. Moreover, depressed adolescents exhibited an increased pessimistic bias for the counterfactual outcome. Lastly, individual difference analysis suggested that these observed biases, which significantly deviated from that observed in normal controls, were linked with the severity of depressive symoptoms as measured by HAMD scores. Conclusions: By leveraging an incentivized instrumental learning task with computational modeling within a reinforcement learning framework, the current study reveals a mechanistic decision-making deficit in adolescent depressive disorder. These findings, which have implications for the identification of behavioral markers in depression, could support the clinical evaluation, including both diagnosis and prognosis of this disorder. [ABSTRACT FROM AUTHOR]

Background: Electroconvulsive therapy (ECT) is effective for treatment-resistant depression and leads to short-term structural brain changes and decreases in the inflammatory response. However, little is known about how brain structure and inflammation relate to the heterogeneity of treatment response in the months following an index ECT course. Methods: A naturalistic six-month study following an index ECT course included 20 subjects with treatment-resistant depression. Upon conclusion of the index ECT course and again after six months, structural magnetic resonance imaging scans and peripheral inflammation measures [interleukin-6 (IL-6), IL-8, tumor necrosis factor (TNF- α), and C-reactive protein] were obtained. Voxel-based morphometry processed with the CAT-12 Toolbox was used to estimate changes in gray matter volume. Results: Between the end of the index ECT course and the end of follow-up, we found four clusters of significant decreases in gray matter volume (p < 0.01, FWE) and no regions of increased volume. Decreased HAM-D scores were significantly related only to reduced IL-8 level. Decreased volume in one cluster, which included the right insula and Brodmann's Area 22, was related to increased HAM-D scores over six months. IL-8 levels did not mediate or moderate the relationship between volumetric change and depression. Conclusions: Six months after an index ECT course, multiple regions of decreased gray matter volume were observed in a naturalistic setting. The independent relations between brain volume and inflammation to depressive symptoms suggest novel explanations of the heterogeneity of longer-term ECT treatment response. [ABSTRACT FROM AUTHOR]

The onset of the COVID-19 pandemic raised concerns regarding population-wide impacts on mental health. Existing work on the psychological impacts of disaster has identified the potential for multiple response trajectories, with resilience as likely as the development of chronic psychopathology. Early reviews of mental health during the pandemic suggested elevated prevalence rates of multiple forms of psychopathology, but were limited by largely cross-sectional approaches. We conducted a systematic review of studies that prospectively assessed pre- to peri-pandemic changes in symptoms of psychopathology to investigate potential mental health changes associated with the onset of the pandemic (PROSPERO #CRD42021255042). A total of 97 studies were included, covering symptom clusters including obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), fear, anxiety, depression, and general distress. Changes in psychopathology symptoms varied by symptom dimension and sample characteristics. OCD, anxiety, depression, and general distress symptoms tended to increase from pre- to peri-pandemic. An increase in fear was limited to medically vulnerable participants, and findings for PTSD were mixed. Pre-existing mental health diagnoses unexpectedly were not associated with symptom exacerbation, except in the case of OCD. Young people generally showed the most marked symptom increases, although this pattern was reversed in some samples. Women in middle adulthood in particular demonstrated a considerable increase in anxiety and depression. We conclude that mental health responding during the pandemic varied as a function of both symptom cluster and sample characteristics. Variability in responding should therefore be a key consideration guiding future research and intervention. [ABSTRACT FROM AUTHOR]

Background: Theoretical models of neural mechanisms underlying Cognitive Behavior Therapy (CBT) for major depressive disorder (MDD) propose that psychotherapy changes neural functioning of prefrontal cortical structures associated with cognitive-control processes (DeRubeis, Siegle, & Hollon, 2008); however, MDD is persistent and characterized by long-lasting vulnerabilities to recurrence after intervention, suggesting that underlying neural mechanisms of MDD remain despite treatment. It follows that identification of treatment-resistant aberrant neural processes in MDD may inform clinical and research efforts targeting sustained remission. Thus, we sought to identify brain regions showing aberrant neural functioning in MDD that either (1) fail to exhibit substantive change (nonresponse) or (2) exhibit functional changes (response) following CBT. Methods: To identify treatment-resistant neural processes (as well as neural processes exhibiting change after treatment), we collected functional magnetic resonance imaging (fMRI) data of MDD patients (n = 58) before and after CBT as well as never-depressed controls (n = 35) before and after a similar amount of time. We evaluated fMRI data using conjunction analyses, which utilized several contrast-based criteria to characterize brain regions showing both differences between patients and controls at baseline and nonresponse or response to CBT. Results: Findings revealed nonresponse in a cerebellar region and response in prefrontal and parietal regions. Conclusions: Results are consistent with prior theoretical models of CBT's direct effect on cortical regulatory processes but expand on them with identification of additional regions (and associated neural systems) of response and nonresponse to CBT. [ABSTRACT FROM AUTHOR]

Background: The course of Bipolar Disorder (BD) is highly variable, with marked inter and intra-individual differences in symptoms and functioning. In this study, we identified illness trajectories across major clinical domains that could have etiological, prognostic, and therapeutic relevance. Methods: Using the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) study, we performed univariate and multivariate trajectory modeling of depressive symptoms, manic symptoms, and psychosocial functioning. Multinomial regression was performed to identify baseline variables associated with poor outcome trajectories. Results: Depressive symptoms predominated, with most subjects being found in trajectories characterized by various degrees of depressive symptoms and 13% of subjects being classified in a poor outcome 'persistently depressed' trajectory. Most subjects experienced few manic symptoms, although approximately 10% of subjects followed a trajectory of persistently manic symptoms. Trajectory analysis of psychosocial functioning showed impairment in most of the sample, with little improvement during follow up. Multi-trajectory analyses highlighted significant impairment in subjects with persistently mixed and persistently depressed trajectories of illness. In general, poor outcome trajectories were marked by lower educational attainment, higher unemployment and disability, and a greater likelihood of adverse clinical features (rapid cycling and suicide attempts) and comorbid diagnoses (anxiety disorders, PTSD, and substance abuse/dependence disorders). Conclusions: Subjects with BD can be classified into several trajectories of clinically relevant domains that are prognostically relevant and show differing degrees of associations with a broad range of negative clinical risk factors. The highest level of psychosocial disability was found in subjects with chronic mixed and depressive symptoms, who show limited improvement despite guideline-based treatment. [ABSTRACT FROM AUTHOR]

Previous meta-analyses on psychotherapy for adult depression have found a larger treatment effect in non-Western trials compared to Western trials (i.e. North America, Europe, and Australia). However, factors contributing to this difference remain unclear. This study investigated different study characteristics between Western and non-Western trials and examined their association with effect size estimates. We systematically searched PubMed, PsycINFO, Embase, and Cochrane Library (01–09–2022). We included randomized-controlled trials (RCTs) that compared psychotherapy with a control condition. The validity of included RCTs was assessed by the Cochrane risk of bias assessment tool (RoB 1). Effect sizes were pooled using the random-effects model. Subgroup analyses and meta-regressions were also conducted. We identified 405 eligible trials, among which 105 trials (117 comparisons, 16 304 participants) were from non-Western countries. We confirmed that non-Western trials had a larger treatment effect (g = 1.10, 95% CI 0.90–1.31) than Western trials (g = 0.57, 95% CI 0.52–0.62). Trials from non-Western countries also had more usual care controls, higher risk of bias, larger sample sizes, lower mean ages, younger adults, more group-based interventions, and other recruitment methods (e.g. systematic screening; p < 0.05). The larger effect sizes found in non-Western trials were related to the presence of wait-list controls, high risk of bias, cognitive-behavioral therapy, and clinician-diagnosed depression (p < 0.05). The larger treatment effects observed in non-Western trials may result from the high heterogeneous study design and relatively low validity. Further research on long-term effects, adolescent groups, and individual-level data are still needed. [ABSTRACT FROM AUTHOR]

Background: Preliminary evidence shows that discordance in stress experience, expression, and physiology (EEP) in adolescents is linked to depression, suicidal ideation (SI), non-suicidal self-injury (NSSI), and brain functioning. This study employs person-centered analysis to probe the relationship between stress responses, psychopathology, and neural patterns in female adolescents who are oversampled for engagement in NSSI. Methods: Adolescent females (N = 109, ages 12–17) underwent a social stress test from which self-report measures of stress experience, observer ratings of stress expression, and physiological metrics of stress (via salivary cortisol) were obtained. Multi-trajectory modeling was employed to identify concordant and discordant stress EEP groups. Depressive symptoms, SI and attempt, NSSI engagement, frontal and limbic activation to emotional stimuli, and resting state fronto-limbic connectivity were examined in the EEP groups derived from the multi-trajectory models. Results: Four groups were identified, three of which demonstrated relatively concordant EEP and one which demonstrated discordant EEP (High Experience-High Expression-Low Physiology). Further, replicating past research, the High Experience-High Expression-Low Physiology discordant group exhibited higher depressive symptoms, SI, suicide attempt, and NSSI episodes (only for sensitivity analyses based on past year) relative to other EEP groups. No significant group differences in brain functioning emerged. Conclusion: Results indicate that within-person, multi-level patterns in stress responding capture risk for dysfunction including depression and self-injurious thoughts and behaviors. Further interrogating of system-level stress functioning may better inform assessment and intervention efforts. [ABSTRACT FROM AUTHOR]

Background: Frequently associated with early psychosis, depressive and manic dimensions may play an important role in its course and outcome. While manic and depressive symptoms can alternate and co-occur, most of the studies in early intervention investigated these symptoms independently. The aim of this study was therefore to explore the co-occurrence of manic and depressive dimensions, their evolution and impact on outcomes. Methods: We prospectively studied first-episode psychosis patients (N = 313) within an early intervention program over 3 years. Based on latent transition analysis, we identified sub-groups of patients with different mood profiles considering both manic and depressive dimensions, and studied their outcomes. Results: Our results revealed six different mood profiles at program entry and after 1.5 years follow-up (absence of mood disturbance, co-occurrence, mild depressive, severe depressive, manic and hypomanic), and four after 3 years (absence of mood disturbance, co-occurrence, mild depressive and hypomanic). Patients with absence of mood disturbance at discharge had better outcomes. All patients with co-occurring symptoms at program entry remained symptomatic at discharge. Patients with mild depressive symptoms were less likely to return to premorbid functional level at discharge than the other subgroups. Patients displaying a depressive component had poorer quality of physical and psychological health at discharge. Conclusions: Our results confirm the major role played by mood dimensions in early psychosis, and show that profiles with co-occurring manic and depressive dimensions are at risk of poorer outcome. An accurate assessment and treatment of these dimensions in people with early psychosis is crucial. [ABSTRACT FROM AUTHOR]

Background: Serum levels of C-reactive protein (CRP) and interleukin-6 (IL-6) have been associated with anxiety and depression in cross-sectional and Mendelian randomisation studies, but results regarding the effect size and direction have been mixed. A recent Mendelian Randomisation (MR) study suggested that CRP may decrease and IL-6 may increase anxiety and depression symptoms. Methods: Among 68 769 participants of the population-based Trøndelag Health Study (HUNT), we performed cross-sectional observational and one-sample MR analyses of serum CRP and two-sample MR analysis of serum IL-6. The main outcomes were symptoms of anxiety and depression assessed using the Hospital Anxiety and Depression Scale (HADS) and life satisfaction assessed using a seven-level ordinal questionnaire where higher scores indicate lower life satisfaction. Results: In cross-sectional observational analyses, a doubling in serum CRP level was associated with 0.27% (95% CI −0.20 to 0.75) difference in HADS depression score (HADS-D), −0.77% (95% CI −1.24 to −0.29) difference in HADS anxiety score (HADS-A) and −0.10% (95% CI −0.41 to 0.21) difference in life satisfaction score. In one-sample MR analyses, a doubling in serum CRP was associated with 2.43% (95% CI −0.11 to 5.03) higher HADS-D, 1.94% (95% CI −0.58 to 4.52) higher HADS-A, and 2.00% (95% CI 0.45 to 3.59) higher life satisfaction score. For IL-6, causal point estimates were in the opposite direction, but imprecise and far from conventional criteria for statistical significance. Conclusions: Our results do not support a major causal role of serum CRP on anxiety and depression symptoms and life satisfaction, but provides weak evidence that serum CRP may modestly increase anxiety and depression symptoms and reduce life satisfaction. Our findings do not support the recent suggestion that serum CRP may lower anxiety and depression symptoms. [ABSTRACT FROM AUTHOR]

Background: Early neurodevelopmental deviations, such as abnormal cortical folding patterns, are candidate biomarkers of major depressive disorder (MDD). We aimed to investigate the association of MDD with the local gyrification index (LGI) in each cortical region at the whole-brain level, and the association of the LGI with clinical characteristics of MDD. Methods: We obtained T1-weighted images from 234 patients with MDD and 215 healthy controls (HCs). The LGI values from 66 cortical regions in the bilateral hemispheres were automatically calculated according to the Desikan–Killiany atlas. We compared the LGI values between the MDD and HC groups using analysis of covariance, including age, sex, and years of education as covariates. The association between the clinical characteristics and LGI values was investigated in the MDD group. Results: Compared with HCs, patients with MDD showed significantly decreased LGI values in the cortical regions, including the bilateral ventrolateral and dorsolateral prefrontal cortices, medial and lateral orbitofrontal cortices, insula, right rostral anterior cingulate cortex, and several temporal and parietal regions, with the largest effect size in the left pars triangularis (Cohen's f 2 = 0.361; p = 1.78 × 10−13). Regarding the association of clinical characteristics with LGIs within the MDD group, recurrence and longer illness duration were associated with increased gyrification in several occipital and temporal regions, which showed no significant difference in LGIs between the MDD and HC groups. Conclusions: These findings suggest that the LGI may be a relatively stable neuroimaging marker associated with MDD predisposition. [ABSTRACT FROM AUTHOR]

Background: Recreational cannabis policies are being considered in many jurisdictions internationally. Given that cannabis use is more prevalent among people with depression, legalisation may lead to more adverse events in this population. Cannabis legalisation in Canada included the legalisation of flower and herbs (phase 1) in October 2018, and the deregulation of cannabis edibles one year later (phase 2). This study investigated disparities in cannabis-related emergency department (ED) visits in depressed and non-depressed individuals in each phase. Methods: Using administrative data, we identified all adults diagnosed with depression 60 months prior to legalisation (n = 929 844). A non-depressed comparison group was identified using propensity score matching. We compared the pre–post policy differences in cannabis-related ED-visits in depressed individuals v. matched (and unmatched) non-depressed individuals. Results: In the matched sample (i.e. comparison with non-depressed people similar to the depressed group), people with depression had approximately four times higher risk of cannabis-related ED-visits relative to the non-depressed over the entire period. Phases 1 and 2 were not associated with any changes in the matched depressed and non-depressed groups. In the unmatched sample (i.e. comparison with the non-depressed general population), the disparity between individuals with and without depression is greater. While phase 1 was associated with an immediate increase in ED-visits among the general population, phase 2 was not associated with any changes in the unmatched depressed and non-depressed groups. Conclusions: Depression is a risk factor for cannabis-related ED-visits. Cannabis legalisation did not further elevate the risk among individuals diagnosed with depression. [ABSTRACT FROM AUTHOR]

Background: The extent to which digital media use by adolescents contributes to poor mental health, or vice-versa, remains unclear. The purpose of the present study is to clarify the strength and direction of associations between adolescent internet use and the development of depression symptoms using a longitudinal modeling approach. We also examine whether associations differ for boys and girls. Methods: Data are drawn from (N = 1547) participants followed for the Quebec longitudinal Study of Child Development (QLSCD 1998–2020). Youth self-reported internet use in terms of the average hours of use per week at the ages of 13, 15, and 17. Youth also self-reported depression symptoms at the same ages. Results: After testing sex-invariance, random intercepts cross-lagged panel models stratified by sex, revealed that internet use by girls was associated with significant within-person (time-varying) change in depression symptoms. Girl's internet use at age 13 was associated with increased depression symptoms at age 15 (ß = 0.12) and internet use at age 15 increased depression at age 17 (ß = 0.10). For boys, internet use was not associated with significant time varying change in depression symptoms. Conclusions: The present findings support the hypothesis that internet use by adolescents can represent a significant risk factor for the development of depressive symptoms, particularly in girls. [ABSTRACT FROM AUTHOR]

Background: Mental health and functional difficulties are highly comorbid across neurological disorders, but supportive care options are limited. This randomised controlled trial assessed the efficacy of a novel transdiagnostic internet-delivered psychological intervention for adults with neurological disorders. Methods: 221 participants with a confirmed diagnosis of epilepsy, multiple sclerosis, Parkinson's disease, or an acquired brain injury were allocated to either an immediate treatment group (n = 115) or treatment-as-usual waitlist control (n = 106). The intervention, the Wellbeing Neuro Course, was delivered online via the eCentreClinic website. The Course includes six lessons, based on cognitive behavioural therapy, delivered over 10 weeks with support from a psychologist via email and telephone. Primary outcomes were symptoms of depression (PHQ-9), anxiety (GAD-7) and disability (WHODAS 2.0). Results: 215 participants commenced the trial (treatment n = 111; control n = 104) and were included in intention-to-treat analysis. At post-treatment, we observed significant between-group differences in depression (PHQ-9; difference = 3.07 [95% CI 2.04–4.11], g = 0.62), anxiety (GAD-7; difference = 1.87 [0.92–2.81], g = 0.41) and disability (WHODAS 2.0 difference = 3.08 [1.09–5.06], g = 0.31), that favoured treatment (all ps < 0.001). Treatment-related effects were maintained at 3-month follow-up. Findings were achieved with minimal clinician time (average of 95.7 min [s.d. = 59.3] per participant), highlighting the public health potential of this approach to care. No adverse treatment events were reported. Conclusions: Internet-delivered psychological interventions could be a suitable model of accessible supportive care for patients with neurological disorders. [ABSTRACT FROM AUTHOR]

Background: Studies have reported mixed findings regarding the impact of the coronavirus disease 2019 (COVID-19) pandemic on pregnant women and birth outcomes. This study used a quasi-experimental design to account for potential confounding by sociodemographic characteristics. Methods: Data were drawn from 16 prenatal cohorts participating in the Environmental influences on Child Health Outcomes (ECHO) program. Women exposed to the pandemic (delivered between 12 March 2020 and 30 May 2021) (n = 501) were propensity-score matched on maternal age, race and ethnicity, and child assigned sex at birth with 501 women who delivered before 11 March 2020. Participants reported on perceived stress, depressive symptoms, sedentary behavior, and emotional support during pregnancy. Infant gestational age (GA) at birth and birthweight were gathered from medical record abstraction or maternal report. Results: After adjusting for propensity matching and covariates (maternal education, public assistance, employment status, prepregnancy body mass index), results showed a small effect of pandemic exposure on shorter GA at birth, but no effect on birthweight adjusted for GA. Women who were pregnant during the pandemic reported higher levels of prenatal stress and depressive symptoms, but neither mediated the association between pandemic exposure and GA. Sedentary behavior and emotional support were each associated with prenatal stress and depressive symptoms in opposite directions, but no moderation effects were revealed. Conclusions: There was no strong evidence for an association between pandemic exposure and adverse birth outcomes. Furthermore, results highlight the importance of reducing maternal sedentary behavior and encouraging emotional support for optimizing maternal health regardless of pandemic conditions. [ABSTRACT FROM AUTHOR]

Background: Mental disorders, including depression, obsessive compulsive disorder (OCD), and schizophrenia, share a common neuropathy of disturbed large-scale coordinated brain maturation. However, high-interindividual heterogeneity hinders the identification of shared and distinct patterns of brain network abnormalities across mental disorders. This study aimed to identify shared and distinct patterns of altered structural covariance across mental disorders. Methods: Subject-level structural covariance aberrance in patients with mental disorders was investigated using individualized differential structural covariance network. This method inferred structural covariance aberrance at the individual level by measuring the degree of structural covariance in patients deviating from matched healthy controls (HCs). T1-weighted anatomical images of 513 participants (105, 98, 190 participants with depression, OCD and schizophrenia, respectively, and 130 age- and sex-matched HCs) were acquired and analyzed. Results: Patients with mental disorders exhibited notable heterogeneity in terms of altered edges, which were otherwise obscured by group-level analysis. The three disorders shared high difference variability in edges attached to the frontal network and the subcortical-cerebellum network, and they also exhibited disease-specific variability distributions. Despite notable variability, patients with the same disorder shared disease-specific groups of altered edges. Specifically, depression was characterized by altered edges attached to the subcortical-cerebellum network; OCD, by altered edges linking the subcortical-cerebellum and motor networks; and schizophrenia, by altered edges related to the frontal network. Conclusions: These results have potential implications for understanding heterogeneity and facilitating personalized diagnosis and interventions for mental disorders. [ABSTRACT FROM AUTHOR]

Background: Individuals with depression have an increased dementia risk, which might be due to modifiable risk factors for dementia. This study investigated the extent to which the increased risk for dementia in depression is explained by modifiable dementia risk factors. Methods: We used data from the English Longitudinal Study of Ageing (2008–2009 to 2018–2019), a prospective cohort study. A total of 7460 individuals were included [mean(standard deviation) age, 65.7 ± 9.4 years; 3915(54.7%) were women]. Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression Scale-8 (score ≥3) or self-reported doctor's diagnosis. Ten modifiable risk factors for dementia were combined in the 'LIfestyle for BRAin health' (LIBRA) score. Dementia was determined by physician diagnosis, self-reported Alzheimer's disease or the shortened version of the Informant Questionnaire on Cognitive Decline in the Elderly (average score ≥3.38). Structural equation modelling was used to test mediation of LIBRA score. Results: During 61 311 person-years, 306 individuals (4.1%) developed dementia. Participants aged 50–70 years with depressive symptoms had higher LIBRA scores [difference(s.e.) = 1.15(0.10)] and a 3.59 times increased dementia risk [HR(95% CI) = 3.59(2.20–5.84)], adjusted for age, sex, education, wealth and clustering at the household level. In total, 10.4% of the dementia risk was mediated by differences in LIBRA score [indirect effect: HR = 1.14(1.03–1.26)], while 89.6% was attributed to a direct effect of depressive symptoms on dementia risk [direct effect: HR = 3.14(2.20–5.84)]. Conclusions: Modifiable dementia risk factors can be important targets for the prevention of dementia in individuals with depressive symptoms during midlife. Yet, effect sizes are small and other aetiological pathways likely exist. [ABSTRACT FROM AUTHOR]

Background: In the past 10 years an increasing number of randomised trials have examined the effects of transdiagnostic treatments of patients with depression or anxiety. We conducted the first comprehensive meta-analysis of the outcomes of this emerging field. Methods: We used the searches in PubMed, PsychINFO, Embase and the Cochrane library of an existing database of randomised trials of psychological interventions for depression to identify studies comparing a transdiagnostic treatment of patients with depression or anxiety with a control group (deadline 1 January 2022). We conducted random-effects meta-analyses and examined the effects on depression and anxiety at the short and longer term. Results: We included 45 randomised controlled trials with 51 comparisons between a psychotherapy and a control group and 5530 participants. Thirty-five (78%) studies were conducted in the last 10 years. The overall effect size was g = 0.54 (95% CI 0.40–0.69; NNT = 5.87), with high heterogeneity (I 2 = 78; 95% CI 71–83), and a broad PI (−0.31–1.39). The effects remained significant in a series of sensitivity analyses, including exclusion of outliers, adjustment for publication bias, for studies with low risk of bias, and in multilevel analyses. The results were comparable for depression and anxiety separately. At 6 months after randomisation the main effects were still significant, but not at 12 months, although the number of studies was small. Conclusions: Transdiagnostic treatments of patients with depression or anxiety are increasingly examined and are probably effective at the short term. [ABSTRACT FROM AUTHOR]

Background: Studies investigating the long-term effect of attention bias modification (ABM) in clinical samples are lacking. This study investigates the 6-months follow-up effect of ABM on depressive symptoms in participant with major depressive disorder with and without comorbid disorders. Methods: We conducted a double-blind randomized sham-controlled trial in 101 participants between 19 November 2019, and 17 August 2021. Follow-up ended 3 April 2022. Participants were allocated to ABM or sham condition twice daily for 14 consecutive days. Primary outcomes were the total score on the Beck Depression Inventory-II (BDI-II) at 6 months, mean Brief State Rumination Inventory (BSRI) score post-treatment and reduction in BSRI post-treatment. Secondary outcome was change in attentional bias (AB). The trial was preregistered in ClinicalTrials.gov (#NCT 04137367). Results: A total of 118 patients aged 18–65 years were assessed for eligibility, and 101 were randomized and subjected to intention-to-treat analyses. At 6 months, ABM had no effect on depression and anxiety compared to a sham condition. While rumination decreased during the intervention, there was no effect of condition on rumination and AB. Predictor analysis did not reveal differences between participants with ongoing major depressive episode or comorbid anxiety. Conclusion: Compared to sham training, there was no effect of ABM on depressive symptoms at 6-months follow-up. Since the intervention failed at modifying AB, it is unclear whether changes in AB are related to long-term outcomes. [ABSTRACT FROM AUTHOR]

Background: Enhanced post-awakening cortisol may serve as a biological marker for individuals with major depressive disorder. However, studies comparing post-awakening cortisol between patients with major depressive disorder (MDD) and healthy controls have produced conflicting findings. The aim of this study was to investigate whether this inconsistency could be due to the effects of childhood trauma. Methods: A total of N = 112 patients with MDD and healthy controls were divided into four groups according to the presence of childhood trauma. Saliva samples were collected at awakening and 15, 30, 45, and 60 min later. The total cortisol output and the cortisol awakening response (CAR) were calculated. Results: The total post-awakening cortisol output was significantly higher in patients with MDD as compared to healthy controls, but only in those individuals reporting childhood trauma. The four groups did not differ regarding the CAR. Conclusions: Elevated post-awakening cortisol in MDD may be confined to those with a history of early life stress. Tailoring and/or augmenting of currently available treatments may be required to meet the specific needs of this population. [ABSTRACT FROM AUTHOR]

Background: Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks. Methods: Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks. Results: In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity. Conclusions: Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis. Registration: ClinicalTrials.gov NCT02332291 [ABSTRACT FROM AUTHOR]

Background: The current study used data from an ethnically diverse population from South London to examine ethnic differences in physical and mental multimorbidity among working age (18–64 years) adults in the context of depression and anxiety. Method: The study included 44 506 patients who had previously attended Improving Access to Psychological Therapies services in the London Borough of Lambeth. Multinomial logistic regression examined cross-sectional associations between ethnicity with physical and mental multimorbidity. Patterns of multimorbidity were identified using hierarchical cluster analysis. Results: Within 44 056 working age adults with a history of depression or anxiety from South London there were notable ethnic differences in physical multimorbidity. Adults of Black Caribbean ethnicity were more likely to have physical multimorbidity [adjusted relative risk ratio (aRRR) = 1.25, 95% confidence interval (CI) 1.15–1.36] compared to adults of White ethnicity. Relative to adults of White ethnicity, adults of Asian ethnicity were more likely to have physical multimorbidity at higher thresholds only (e.g. 4 + conditions; aRRR = 1.53, 95% CI 1.17–2.00). Three physical (atopic, cardiometabolic, mixed) and three mental (alcohol/substance use, common/severe mental illnesses, personality disorder) multimorbidity clusters emerged. Ethnic minority groups with multimorbidity had a higher probability of belonging to the cardiometabolic cluster. Conclusion: In an ethnically diverse population with a history of common mental health disorders, we found substantial between- and within-ethnicity variation in rates of physical, but not mental, multimorbidity. The findings emphasised the value of more granular definitions of ethnicity when examining the burden of physical and mental multimorbidity. [ABSTRACT FROM AUTHOR]

Background: Research suggests that there have been inequalities in the impact of the coronavirus disease 2019 (COVID-19) pandemic and related non-pharmaceutical interventions on population mental health. We explored generational, sex, and socioeconomic inequalities during the first year of the pandemic using nationally representative cohorts from the UK. Methods: We analysed data from 26772 participants from five longitudinal cohorts representing generations born between 1946 and 2000, collected in May 2020, September–October 2020, and February–March 2021 across all five cohorts. We used a multilevel growth curve modelling approach to investigate generational, sex, and socioeconomic differences in levels of anxiety and depressive symptomatology, loneliness, and life satisfaction (LS) over time. Results: Younger generations had worse levels of mental and social wellbeing throughout the first year of the pandemic. Whereas these generational inequalities narrowed between the first and last observation periods for LS [−0.33 (95% CI −0.51 to −0.15)], they became larger for anxiety [0.22 (0.10, 0.33)]. Generational inequalities in depression and loneliness did not change between the first and last observation periods, but initial depression levels of the youngest cohort were worse than expected if the generational inequalities had not accelerated. Women and those experiencing financial difficulties had worse initial mental and social wellbeing levels than men and those financially living comfortably, respectively, and these gaps did not substantially differ between the first and last observation periods. Conclusions: By March 2021, mental and social wellbeing inequalities persisted in the UK adult population. Pre-existing generational inequalities may have been exacerbated with the pandemic onset. Policies aimed at protecting vulnerable groups are needed. [ABSTRACT FROM AUTHOR]

Background: Adding short-term psychodynamic psychotherapy (STPP) to antidepressants increases treatment efficacy, but it is unclear which patients benefit specifically. This study examined efficacy moderators of combined treatment (STPP + antidepressants) v. antidepressants for adults with depression. Methods: For this systematic review and meta-analysis (PROSPERO registration number: CRD42017056029), we searched PubMed, PsycINFO, Embase.com, and the Cochrane Library from inception to 1 January 2022. We included randomized clinical trials comparing combined treatment (antidepressants + individual outpatient STPP) v. antidepressants in the acute-phase treatment of depression in adults. Individual participant data were requested and analyzed combinedly using mixed-effects models (adding Cochrane risk of bias items as covariates) and an exploratory machine learning technique. The primary outcome was post-treatment depression symptom level. Results: Data were obtained for all seven trials identified (100%, n = 482, combined: n = 238, antidepressants: n = 244). Adding STPP to antidepressants was more efficacious for patients with high rather than low baseline depression levels [ B = −0.49, 95% confidence interval (CI) −0.61 to −0.37, p < 0.0001] and for patients with a depressive episode duration of >2 years rather than <1 year (B = −0.68, 95% CI −1.31 to −0.05, p = 0.03) and than 1–2 years (B = −0.86, 95% CI −1.66 to −0.06, p = 0.04). Heterogeneity was low. Effects were replicated in analyses controlling for risk of bias. Conclusions: To our knowledge, this is the first study that examines moderators across trials assessing the addition of STPP to antidepressants. These findings need validation but suggest that depression severity and episode duration are factors to consider when adding STPP to antidepressants and might contribute to personalizing treatment selection for depression. [ABSTRACT FROM AUTHOR]

Background: Altered white matter brain connectivity has been linked to depression. The aim of this study was to investigate the association of markers of white matter connectivity with prevalence, incidence and course of depressive symptoms. Methods: Markers of white matter connectivity (node degree, clustering coefficient, local efficiency, characteristic path length, and global efficiency) were assessed at baseline by 3 T MRI in the population-based Maastricht Study (n = 4866; mean ± standard deviation age 59.6 ± 8.5 years, 49.0% women; 17 406 person-years of follow-up). Depressive symptoms (9-item Patient Health Questionnaire; PHQ-9) were assessed at baseline and annually over seven years of follow-up. Major depressive disorder (MDD) was assessed with the Mini-International Neuropsychiatric Interview at baseline only. We used negative binominal, logistic and Cox regression analyses, and adjusted for demographic, cardiovascular, and lifestyle risk factors. Results: A lower global average node degree at baseline was associated with the prevalence and persistence of clinically relevant depressive symptoms [PHQ-9 ⩾ 10; OR (95% confidence interval) per standard deviation = 1.21 (1.05–1.39) and OR = 1.21 (1.02–1.44), respectively], after full adjustment. On the contrary, no associations were found of global average node degree with the MDD at baseline [OR 1.12 (0.94–1.32) nor incidence or remission of clinically relevant depressive symptoms [HR = 1.05 (0.95–1.17) and OR 1.08 (0.83–1.41), respectively]. Other connectivity measures of white matter organization were not associated with depression. Conclusions: Our findings suggest that fewer white matter connections may contribute to prevalent depressive symptoms and its persistence but not to incident depression. Future studies are needed to replicate our findings. [ABSTRACT FROM AUTHOR]

Background: Repetitive negative thinking (RNT), a cognitive process that encompasses past (rumination) and future (worry) directed thoughts focusing on negative experiences and the self, is a transdiagnostic construct that is especially relevant for major depressive disorder (MDD). Severe RNT often occurs in individuals with severe levels of MDD, which makes it challenging to disambiguate the neural circuitry underlying RNT from depression severity. Methods: We used a propensity score, i.e., a conditional probability of having high RNT given observed covariates to match high and low RNT individuals who are similar in the severity of depression, anxiety, and demographic characteristics. Of 148 MDD individuals, we matched high and low RNT groups (n = 50/group) and used a data-driven whole-brain voxel-to-voxel connectivity pattern analysis to investigate the resting-state functional connectivity differences between the groups. Results: There was an association between RNT and connectivity in the bilateral superior temporal sulcus (STS), an important region for speech processing including inner speech. High relative to low RNT individuals showed greater connectivity between right STS and bilateral anterior insular cortex (AI), and between bilateral STS and left dorsolateral prefrontal cortex (DLPFC). Greater connectivity in those regions was specifically related to RNT but not to depression severity. Conclusions: RNT intensity is directly related to connectivity between STS and AI/DLPFC. This might be a mechanism underlying the role of RNT in perceptive, cognitive, speech, and emotional processing. Future investigations will need to determine whether modifying these connectivities could be a treatment target to reduce RNT. [ABSTRACT FROM AUTHOR]

Background: The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors. Method: Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change. Results: Prospective symptom analyses showed small decreases in depression (PHQ-9: −0.43 points) and anxiety [generalised anxiety disorder scale – 7 items (GAD)-7: −0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status. Conclusions: We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity. [ABSTRACT FROM AUTHOR]

Adolescents' sense of self has important implications for their mental health. Despite more than two decades of work, scholars have yet to amass evidence across studies to elucidate the role of selfhood in the mental health of adolescents. Underpinned by the conceptual model of selfhood, this meta-analytic review investigated the strength of associations of different facets of selfhood and their associated traits with depression and anxiety, moderating factors that attenuate or exacerbate these associations, and their causal influences. Using mixed-effects modeling, which included 558 effect sizes from 298 studies and 274 370 adolescents from 39 countries, our findings revealed that adolescents' self-esteem/self-concept [ r = −0.518, p < 0.0001; (95% CI −0.49 to −0.547)] and self-compassion [ r = −0.455, p < 0.0001; (95% CI −0.568 to −0.343)] demonstrating largest effect sizes in their associations with depression. Self-esteem/self-concept, self-compassion, self-awareness, self-efficacy, and self-regulation had similar moderate negative associations with anxiety. Meta-regressions revealed that adolescent age and type of informants (parents v. adolescents) were important moderators. Findings on causal influences indicated bidirectional causations, particularly low self-esteem/self-concept, self-awareness and self-efficacy drive higher depression and vice-versa. In contrast, the different self traits did not demonstrate specific causal direction with anxiety. These results pinpoint self traits that are pivotal in relating to adolescent mental health functioning. We discussed the theoretical implications of our findings in terms of how they advance theory of selfhood for adolescent mental health, and the practical implications of building selfhood as cultivating psychological skills for mental health. [ABSTRACT FROM AUTHOR]

Background: Depression is an important, potentially modifiable dementia risk factor. However, it is not known whether effective treatment of depression through psychological therapies is associated with reduced dementia incidence. The aim of this study was to investigate associations between reduction in depressive symptoms following psychological therapy and the subsequent incidence of dementia. Methods: National psychological therapy data were linked with hospital records of dementia diagnosis for 119808 people aged 65+. Participants received a course of psychological therapy treatment in Improving Access to Psychological Therapies (IAPT) services between 2012 and 2019. Cox proportional hazards models were run to test associations between improvement in depression following psychological therapy and incidence of dementia diagnosis up to eight years later. Results: Improvements in depression following treatment were associated with reduced rates of dementia diagnosis up to 8 years later (HR = 0.88, 95% CI 0.83–0.94), after adjustment for key covariates. Strongest effects were observed for vascular dementia (HR = 0.86, 95% CI 0.77–0.97) compared with Alzheimer's disease (HR = 0.91, 95% CI 0.83–1.00). Conclusions: Reliable improvement in depression across psychological therapy was associated with reduced incidence of future dementia. Results are consistent with at least two possibilities. Firstly, psychological interventions to improve symptoms of depression may have the potential to contribute to dementia risk reduction efforts. Secondly, psychological therapies may be less effective in people with underlying dementia pathology or they may be more likely to drop out of therapy (reverse causality). Tackling the under-representation of older people in psychological therapies and optimizing therapy outcomes is an important goal for future research. [ABSTRACT FROM AUTHOR]

Background: Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis. Methods: T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges. Results: As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms. Conclusions: In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression. [ABSTRACT FROM AUTHOR]

Background: Vulnerability theories propose that suboptimal levels of lipid markers and proinflammatory proteins predict future heightened depression. Scar models posit the reverse association. However, most studies that tested relationships between non-specific immune/endocrine markers and depression did not separate temporal inferences between people and within-person and how different immunometabolism markers related to unique depression symptoms. We thus used cross-lagged prospective network analyses (CLPN) to investigate this topic. Methods: Community midlife women (n = 2224) completed the Center for Epidemiologic Studies-Depression scale and provided biomarker samples across five time-points spanning 9 years. CLPN identified significant relations (edges) among components (nodes) of depression (depressed mood, somatic symptoms, interpersonal issues), lipid markers [insulin, fasting glucose, triglycerides, low-density lipoprotein-cholesterol (LDL), high-density lipoprotein-cholesterol (HDL)], and proinflammatory proteins [C-reactive protein (CRP), fibrinogen], within and across time-points. All models adjusted for age, estradiol, follicle-stimulating hormone, and menopausal status. Results: In within-person temporal networks, higher CRP and HDL predicted all three depression components (d = 0.131–2.112). Increased LDL preceded higher depressed mood and interpersonal issues (v. somatic symptoms) (d = 0.251–0.327). Elevated triglycerides predicted more somatic symptoms (v. depressed mood and interpersonal problems) (d = 0.131). More interpersonal problems forecasted elevated fibrinogen and LDL levels (d = 0.129–0.331), and stronger somatic symptoms preceded higher fibrinogen levels (d = 0.188). Conclusions: Results supported both vulnerability and scar models. Long-term dysregulated immunometabolism systems, social disengagement, and related patterns are possible mechanistic accounts. Cognitive-behavioral therapies that optimize nutrition and physical activity may effectively target depression. [ABSTRACT FROM AUTHOR]