Journal of Affective Disorders

ObjectiveGiven the episodic nature of bipolar disorder (BD) and the variability in mood episode recurrence across individuals, accurate recurrence prediction is critical. The original COBY recurrence risk calculator (RC) was developed in a longitudinal youth cohort to estimate threshold recurrence risk. However, its accuracy for predicting subthreshold recurrences had not been fully evaluated. The objective of this study was to extend the previously developed COBY mood recurrence RC to predict both threshold and subthreshold mood recurrences and evaluate its performance in an independent sample. MethodAdolescents and young adults with BD-I/II (N= 51; BD-I: 38, BD-II: 13; 14-24 years old) were interviewed with standard instruments at intake and during the follow-up on average every 6 months for a median of 54 weeks. We assessed the degree to which the COBY RC predicted mood recurrence (threshold or subthreshold) in this independent sample. Discrimination was measured using the area under the receiver operating characteristic curves (AUC); calibration and variable importance were also assessed. ResultsThe model demonstrated good prediction of any recurrence within the next six months (any threshold recurrence AUC = 0.72, any subthreshold or worse recurrence AUC = 0.77). Calibration analysis demonstrated the model tended to overestimate risk in the external sample, plausibly attributable to differences in recurrence ascertainment strategy (prospective vs retrospective) or the significant difference in prior remission length, a key predictor. Recalibration greatly improved calibration without loss of discrimination. ConclusionThe mood recurrence RC demonstrated good discrimination for both threshold and subthreshold mood recurrences in an independent young adult cohort, consistent with prior youth and adult validations. Validation now spans across developmental stages and different degrees of severity of mood symptoms opening the opportunity for clinical implementation to provide personalized monitoring and early intervention for people with BD.

BackgroundChildhood maltreatment is a major risk factor for depression and may contribute to sex differences in depression prevalence. We examined sex-specific associations between childhood maltreatment and depression and estimated the proportion of depression cases attributable to specific maltreatment subtypes. MethodsWe analyzed baseline data from 159,045 participants (49.4% women; aged 19-72) in the German National Cohort (NAKO). Childhood maltreatment was assessed via the Childhood Trauma Screener; depression via self-reported physicians diagnosis and MINI classification (lifetime) and the PHQ-9 (current). Associations, including sex interactions, were modeled using binary logistic regressions. Mediation analyses and sex-stratified population attributable fractions (PAFs) quantified the contribution of maltreatment to depression. ResultsMaltreatment was associated with increased odds of lifetime (ORphysicians diagnosis=2.45 [2.38,2.53]; ORMINI=2.30 [2.18,2.43]) and current depression (OR=2.90 [2.79,3.02]). Sex interactions were observed for the physicians diagnosis: physical abuse and neglect had stronger associations in women (ORphysical abuse=2.74 [2.59,2.90]; ORphysical neglect=1.36 [1.28,1.44]) than men (ORphysical abuse=2.36 [2.21,2.52]; ORphysical neglect=1.08 [1.00,1.16]), whereas sexual abuse showed stronger associations in men (OR=3.23 [2.91,3.57]) than women (OR=2.61 [2.48,2.75]). Overall, childhood maltreatment accounted for 21.2-26.2% of lifetime and 33.4% of current depression. PAFs were higher in women than men for lifetime (24.5-28.5% vs. 16.0-20.9%) and current depression (36.1% vs. 28.2%). Emotional abuse and neglect contributed the highest PAFs (up to 10.2%). Maltreatment mediated 18.9-30.0% of the association between sex and depression. ConclusionMaltreatment, especially emotional subtypes, account for a substantial proportion of depression in both sexes, with stronger overall associations in women. Sex-specific prevention may help reduce depression prevalence.

BACKGROUNDConvulsive therapies, including electroconvulsive therapy (ECT) and magnetic seizure therapy (MST), are highly effective for treatment-resistant depression, however, their neural mechanisms remain incompletely understood. We tested whether a data-driven framework applying a massive time-series feature library to electroencephalography (EEG) could reveal novel insights into changes in functional brain dynamics following convulsive therapy and provide preliminary markers of response. METHODSResting-state EEG was analysed before and after a course of ECT or MST in 42 patients. Data were pooled and reduced to three principal components (PCs) capturing 78.1% of total variance, then >7,000 time-series features per PC were extracted from each patient using the highly comparative time-series analysis (hctsa) framework. Linear support vector machines (SVMs) classified pre-versus post-treatment EEG for each PC. A separate linear SVM, was also trained on 18 representative baseline features to predict clinical response. RESULTShctsa-based classifiers distinguished pre-from post-treatment EEG for each PC (accuracy 73.8-76.2%, pFDR<0.01). Between 986-1,414 features significantly differentiated post-stimulation from baseline time-series across the three PCs (pFDR<0.05). The most discriminative features indexed linear and non-linear autocorrelation, correlation, multiscale entropy, and spectral properties. The baseline SVM combining 18 features showed modest but statistically reliable prediction of treatment response (balanced accuracy=0.69, area under the curve [AUC]=0.61, p=0.014). Single-feature ROC analyses further identified several top features with AUCs=[~]0.7. CONCLUSIONSData-driven analysis using a diverse time-series feature library can uncover novel EEG signatures of brain changes following convulsive therapy. This holds potential for delineating treatment-related mechanisms and developing predictive biomarkers to support precision psychiatry.

BackgroundSuicidal ideation (SI) fluctuates over time, yet traditional static risk factors poorly align with its dynamics over time. Understanding dynamic symptom patterns may advance knowledge of the temporal interplay between SI and co-occurring symptoms in adults with depressive and anxiety disorders. Materials and methodsWe analyzed six waves (at baseline, and after 2, 4, 6, 9, and 13 years of follow-up) of the Netherlands Study of Depression and Anxiety (NESDA; n = 305, mean age 40.8 years, 62% female) in participants with any SI fluctuation over time. Variables included depressive, anxiety, mastery, and worry symptoms. Dynamic Time Warping (DTW) quantified within-person temporal alignment between SI and other symptoms, and an undirected network and forestplot visualized co-fluctuations. Analyses were stratified by age-groups and sex. ResultsOver the years, SI co-fluctuated most strongly with affective and anhedonic depressive symptoms, including sad mood, low capacity for pleasure, low general interest, pessimism, quality of mood, and decreased appetite. Select anxiety (terrified/afraid) and worry (overwhelming worries) items also aligned with SI, whereas mastery items did not. Patterns were broadly consistent across age and gender subgroups. Networks indicated that SI is part of a cluster of depressogenic symptoms but bridges to acute fear and persistent worry. ConclusionsSI is a dynamic phenomenon closely linked to specific depressive, anxiety, and worry symptoms. Interventions targeting mood instability, anhedonia, and uncontrollable worry, combined with real-time monitoring, may improve personalized suicide prevention. DTW provides a framework to identify long-term temporally proximal symptom patterns.

BackgroundSuicidal ideation (SI) is a major global concern, yet its dynamic interplay with other symptoms remains poorly understood. ObjectiveTo identify symptoms that co-fluctuate with or temporally precede SI to improve warning signal detection and intervention. MethodsLongitudinal data from three Dutch psychiatric cohorts with lifetime internalizing disorders (16 waves from April 2020 until February 2022) were collected during the COVID-19 pandemic. We analyzed depressive, happiness, anxiety, loneliness, worry symptoms, and COVID-19-specific items only in those participants with SI fluctuations. Dynamic Time Warping (DTW) quantified within-person similarity between symptom trajectories and SI, and results were aggregated at group level. FindingsThe 307 participants (mean age 44.8 years; 61.6% female) showed increasing SI over time (p < .001). SI aligned with four depressive symptoms (i.e., sad mood, low self-esteem, low interest, and reduced happiness), two anxiety-related symptoms (i.e., fear of losing control, faintness), feeling abandoned, and overwhelming worrying. In directed DTW analysis, sad mood, hypersomnia, worrying about projects, and numbness/tingling showed significant temporal precedence before SI. ConclusionSI is embedded in a broad symptom network beyond depression. These results underscore the value of time-sensitive, idiographic monitoring using tools like DTW to capture the person-specific temporal pathways through which SI emerges and intensifies. Clinical implicationsThis study suggests a core group of affective, cognitive, and interpersonal symptoms that could serve as informative signals for evaluating changes in SI and may represent actionable targets for intervention. Summary BoxO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LISuicidal ideation (SI) is a dynamic phenomenon, yet traditional research often relies on static, group-level averages that do not capture individual fluctuations. C_LIO_LIWhile SI is linked to depression, it can emerge independently through complex interactions with other affective and interpersonal states C_LI What this study adds?O_LIThis study identifies a set of affective, cognitive, and interpersonal symptoms, sad mood, overwhelming worry, and feelings of abandonment, that significantly co-fluctuate with SI over weeks and months. Additionally four specific "leading" symptoms, sad mood, hypersomnia, worrying about projects, and somatic numbness, were found that precede increases in SI. C_LI How this study might affect research, practice or policy?O_LIThe identified co-fluctuations and precursors serve as informative "(early) warning signals" that can improve individual risk stratification and clinical monitoring and may represent targets for intervention. C_LIO_LIThe results support a shift toward network-based models in suicidology, emphasizing the need for time-sensitive monitoring to capture the complex and dynamic nature of suicidality. C_LI

Background: Major depressive disorder (MDD) is the leading cause of non-fatal disability in youth and disproportionately affects adolescent females. Structural MRI studies of adolescent depression have yielded inconsistent findings, potentially reflecting symptom heterogeneity and rapid developmental changes in brain morphology. Methods: In this longitudinal study, we examined associations between specific depressive symptoms and structural brain MRI measures in 9,722 youth (53% male, age range = 10.0-17.7, 24,378 observations) from the Adolescent Brain Cognitive Development (ABCD) Study. A four-wave panel graphical vector autoregression (GVAR) model was estimated to separate within-person (contemporaneous and temporal networks) from stable between-person effects. Brain measures included cortical thickness in the insula, cingulate, medial orbitofrontal cortex (mOFC) and fusiform gyrus, as well as hippocampal volume. Depressive symptoms included parent-reported depressed mood, anhedonia, lethargy, and worthlessness. Additionally, sex-differences in network structures were tested. Results: Strong within-domain associations were observed among brain measures and among symptoms, with the largest effects in the symptom domain. Cross-domain (brain-symptom) associations emerged only at the within-person level, where elevated depressed mood was associated with contemporaneous and subsequent reductions in cingulate and fusiform gyrus thickness (partial r = [-0.02 - 0.04]). No cross-domain associations were detected in the between-person networks. Sex-differences emerged only in the within-person networks. Conclusions: Associations between brain structure and depressive symptoms were subtle, symptom-specific, and dynamic rather than reflecting stable individual differences. Longitudinal within-person approaches are therefore important for understanding neurodevelopmental contributions to adolescent depression risk.

BackgroundExercise therapy reduces depressive and anxiety symptoms, but its neural mechanisms are not fully understood. We examined whether and how running therapy reorganizes dynamic brain functional connectivity in affective disorders. MethodsAt baseline, resting-state fMRI was collected from 66 healthy controls and 50 individuals with affective disorders. Co-activation patterns analyses (CAPs) identified recurring whole-brain network states characterized by spatial patterns of regional co-activation/codeactivation patterns and their temporal occurrence rates. We compared CAPs between groups at baseline. Participants with affective disorders then received 16 weeks of running therapy or antidepressant treatment. We examined: (1) treatment-induced changes in brain CAPs and clinical symptoms, (2) brain-symptom associations at baseline versus post-treatment, and (3) associations between network reorganization and symptom improvement. ResultsAt baseline, individuals with affective disorders showed fewer occurrences of the visual-somatomotor-subcortical network state (VS-SCCAP) than controls (F=5.4, P=0.02, {superscript 2}=0.04). Running therapy significantly altered the temporal dynamics of two brain systems: the default mode (DMCAP: {beta} = -0.88, P = 0.006, d =- 0.88) and VS-SCCAP ({beta} = 0.87, P = 0.006, d = 0.85). These reorganizations were accompanied by significant improvements in depressive and anxiety symptoms (IDS: {beta} = -1.23, P < 0.001, d = -1.15; BAI: {beta} = - 0.98, P = 0.008, d = -0.93). DMCAP-symptom coupling changed significantly from baseline to post-treatment ({Delta}RHO=-0.48, Z{approx}-2.0, P<0.05). ConclusionsRunning therapy altered dynamic brain networks in association with clinical symptom improvement. These findings provide neurobiological evidence for exercise-induced therapeutic effects through transient brain-state reorganization, demonstrating the utility of dynamic connectivity approaches for characterizing neural mechanisms in affective disorders.

Major depressive disorder (MDD) involves dysregulated neuroimmune, metabolic, and oxidative stress (NIMETOX) pathways. Recently, it was shown that NIMETOX pathways should be evaluated in MDD patients stratified for metabolic syndrome (MetS). The current study aims to characterize the metabolic hormone and adipokine profiles of Chinese MDD patients stratified for MetS and to delineate their associations with overall severity of depression (OSOD), suicidal ideation (SI), recurrence of illness (ROI), and physiosomatic symptoms. We enrolled 125 MDD inpatients and 40 healthy controls and measured fasting serum insulin, glucose, glucagon, Glucose-dependent Insulinotropic Polypeptide (GIP), Glucagon-Like Peptide-1 (GLP-1), leptin, secretin, Plasminogen Activator Inhibitor-1 (PAI-1), resistin, ghrelin, and adiponectin, as well as the acute-phase inflammatory (API) response using albumin, transferrin (Tf), and monomeric CRP (mCRP). The results revealed a distinct metabolic hormone and adipokine signature in MDD with significantly lower insulin, glucagon, and PAI-1 levels, alongside an elevated API index (after adjusting for age, MetS, and body mass index). A composite GAP index (ghrelin, adiponectin, PAI-1) correlated negatively with OSOD, SI, ROI, physiosomatic symptoms, and adverse childhood experiences (ACEs). Integrative modeling combining the GAP index, API index, and ACEs achieved an area under the receiver operating characteristic (ROC) curve of 0.864 with an accuracy of 80% for discriminating MDD from controls. In conclusion, the findings delineated that many inpatients with severe MDD suffer from suppressed anabolic hormones and lower adipokine levels coupled with a mild, chronic inflammatory response. The deviations in this "hormonal-immune-metabolic" axis are components of the NIMETOX pathways in MDD and are not associated with MetS.

BackgroundThe COVID-19 pandemic, coupled with concurrent social instabilities, has raised concerns about the long-term impact on the population mental health. While existing studies have primarily focused on the acute phase, less is known about how anxiety and depression symptoms have evolved throughout prolonged societal disruption. This study aimed to identify distinct anxiety and depression symptom trajectories and to determine the individual, relational, and societal protective and risk factors that influence anxiety and depression scores among Belgian adults from 2020 to 2024. MethodsWe used longitudinal data from five waves of the COVID-19 Health Surveys and the BELHEALTH study (n = 10,063) among Belgian adults, collected between April 2020 and June 2024. Anxiety and depression were assessed using the Generalized Anxiety Disorder-7 and the Patient Health Questionnaire-9, respectively. Covariates were selected based on the social-ecological framework and included both time-invariant and time-dependent variables. Latent class linear mixed models identified subgroups with distinct trajectories. Multilevel linear mixed effects models examined associations between symptom severity and predictors across individual, relationship, and societal levels. The final model, selected based on the lowest AIC (Akaike Information Criterion), included the full set of covariates. ResultsFour depression and five anxiety trajectories were identified. While most participants maintained stable mild symptoms, 11.3% experienced increasing depression and 8.4% showed increasing anxiety over time. Financial difficulty, female gender, and younger age were overrepresented in moderate and severe symptom trajectories. Protective factors such as social support, satisfying social contact, and life satisfaction were associated with lower symptom severity. Over time, life satisfaction demonstrated an increasing protective effect, while the influence of social contact on reducing symptoms weakened progressively. Risk factors included financial and job-loss worry, loneliness, psychotropic medication use, and high mental health stigma. ConclusionsOur results demonstrate persistent heterogeneity in mental health responses, with a substantial share of the population experiencing worsening symptoms years after the pandemic began. Public mental health strategies must therefore go beyond short-term crisis response, address long-term risks such as financial insecurity, social isolation, and stigma, while fostering individual and collective resilience.

Background: Previous evidence suggests that higher body size is associated with bipolar disorders, however, whether this association is causal remains uncertain. Interpretation is further complicated by heterogeneity across age, variation in clinical presentation, and potentially distinct underlying aetiologies. Aims: To determine whether body size exerts heterogenous causal effects on bipolar disorder subtypes and symptom profiles. Methods: By leveraging genetic instruments that differentiate effects at different life stages, summary-level univariable and multivariable Mendelian randomisation (MR) analyses were used to estimate how age-specific body size relates to adult psychiatric and symptomatic bipolar features; major depressive disorder (MDD), depressive symptom scores, subthreshold mania symptoms, bipolar disorder, bipolar type I and bipolar type II. Genetic instruments derived from genome-wide association studies (GWASs) for adult body mass index (BMI) (n= 681,275), childhood body size (n= 453,169) and mid-to-later life body size (n= 453,169) served as proxies for prepubertal and adult BMI measures. Results: In univariable MR, higher genetically proxied adult BMI increased the odds of MDD (odds ratio (OR) = 1.13, 95% CI 1.09-1.16), subthreshold mania (OR = 1.09, 95% CI 1.0-1.19)), and depressive scores (Beta = 0.07, 95% CI 0.05-0.09). There was little evidence that childhood body size had an effect on any outcome. Robust evidence suggested bipolar disorder and MDD increased adult BMI in our reverse univariable analyses. Using multivariable MR, robust evidence indicated that increased adult body size after accounting for childhood body size increased the odds of MDD, subthreshold mania and depressive scores. Conclusions: Body size may exert different causal effects on bipolar disorder depending on age and symptoms, with detrimental effects occurring during adulthood. Weaker evidence suggested varying effects across bipolar subtypes. Triangulation of findings and higher powered GWASs to detect symptom-specific genetic variants are required to explore whether body size contributes to distinct aetiologies across bipolar patients, informing the identification of novel and personalised treatment targets.

BackgroundMajor depressive disorder (MDD), a leading cause of disability worldwide, exhibits substantial heterogeneity in treatment outcomes. Patients who do not respond to standard antidepressant therapy account for the majority of MDDs disease burden. Risk factors have been implicated in treatment response, including genes impacting on how antidepressants are metabolised. Yet, despite its clinical importance, risk factors for treatment-resistant depression (TRD) remain unexplored in low- and middle-income countries (LMIC). We used data from the DIVERGE study on MDD to investigate the risk factors of TRD in Pakistan. MethodsDIVERGE is a genetic epidemiological study that recruited adult MDD patients ([&ge;]18 years) between Sep 27,2021 to Jun 30, 2025, from psychiatric care facilities across Pakistan. Detailed phenotypic information was collected by trained interviewers and blood samples taken. Infinium Global Diversity Array with Enhanced PGx-8 from Illumina was used for genotyping followed by DRAGEN calling to infer metaboliser phenotypes for Cytochrome P450 (CYP) enzyme genes. We defined TRD as minimal to no improvement after [&ge;]12 weeks of adherent antidepressant therapy. We conducted multi-level logistic regression to test the association of demographic, clinical and pharmacogenetic variables with TRD. FindingsAmong 3,677 eligible patients, polypharmacy was rampant; 86% were prescribed another psychotropic drug along with an antidepressant. Psychological therapies were uncommon (6%) while 49% of patients had previously visited to a religious leader/faith healer in relation to their mental health problems. TRD was experienced by 34% (95%CI: 32-36%) patients. The TRD group was characterised by more psychotic symptoms and suicidal behaviour (OR=1.39, 95%CI=1.04-1.84, p=0.02; OR=1.03, 95%CI=1.01-1.05, p=0.005). Social support (OR=0.55, 95%CI=0.44-0.69, p=1.4x10-7) and parents being first cousins (OR=0.81, 95%CI=0.69-0.96, p=0.01) were associated with lower odds of TRD. In 1,085 patients with CYP enzyme data, poor (OR=1.85, 95%CI=1.11-3.07, p=0.01) and ultra-rapid (OR=3.11, 95%CI=1.59-6.12, p=0.0009) metabolizers for CYP2C19 had increased risk of TRD compared with normal metabolisers. InterpretationThere was an excessive use of polypharmacy in the treatment of depression while psychological therapies were uncommon highlighting the need for more evidence-based practice. This first large study of MDD from Pakistan uncovered the importance of culture-specific forms of social support in preventing TRD, highlighting opportunities for interventions in low-income settings. Pharmacogenetic markers can be leveraged to predict TRD.

Background Somatic and psychological symptoms like depression, anxiety, and trauma-related stress often co-occur, especially in young adults, a group facing major life transitions and increased vulnerability. These overlapping symptoms pose diagnostic challenges that traditional disorder-specific models capture poorly. Transdiagnostic and dimensional approaches may offer a more meaningful framework. However, population-based data on symptom patterns in young adults remains sparse. This study investigated the patterns of psychological and somatic symptoms among young adults from Switzerland and compares these results to findings from populations with different stress exposure histories: Ukrainians who fled to Switzerland, and Ukrainians living in different regions in Ukraine during the war. Methods We analyzed cross-sectional baseline data collected in spring 2024 as part of the Mental Health Assessment of the Population (MAP) studies, where we enrolled randomly selected young adults aged 18-24 from Switzerland, Ukrainian refugees in Switzerland, and Ukrainians residing in regions with different degrees of proximity to active war zones. We assessed somatic (PHQ-15) and psychological symptoms (PHQ-9, GAD-7, PCL-5) and explored symptom patterns using descriptive statistics, correlations, and k-means clustering. Results Psychological symptom severity showed highly consistent moderate-to-strong correlations with somatic symptoms (range: 0.53-0.69), across all young adult subgroups and disorders. Rather than identifying disorder-specific patterns, symptoms clustered by overall symptom severity, emerging in three clusters: (1) high symptom burden, (2) moderate symptom burden, and (3) low symptom burden clusters with elevated somatic, depressive, anxiety, and PTSD symptoms. The cluster structure was remarkably stable across Swiss, Ukrainian, and refugee subsamples, despite markedly different stress exposure histories. Conclusion Our results support a symptom-based, dimensional approach to understanding mental health in young adults and to better capture the complexity and co-occurrence of psychological and somatic symptoms in this age group. These findings further suggest that prevention and early detection strategies should more systematically integrate both psychological and somatic symptomatology.

Neuroimaging has revealed that major depression is underpinned by dysfunctional brain networks, with symptom variability stemming from altered interactions within and between brain regions. While the effect of depression severity is well-studied, the effect of depression duration (chronicity) is relatively neglected, despite its clinical significance. This study examined how severity, chronicity, and their interaction affect brain network connectivity and grey matter volume. Forty-six patients (31 females, mean age 40.5) were assessed using whole-brain network modeling and voxel-based morphometry (VBM). Severity was measured via the Hamilton Depression Rating Scale, and chronicity was defined as an episode lasting over 24 months. The key finding was that chronicity moderated the impact of severity on functional connectivity between the Central Executive Network (CEN) and the precuneus (part of the Default Mode Network, DMN). Chronic versus non-chronic patients showed opposite patterns. Non-chronic patients showed stronger CEN-Default Mode Precuneus connectivity at low severity and weaker at high severity; chronic patients showed the reverse. This study reveals a novel impact of chronicity on CEN-DMN interactions, a neglected moderator of brain-symptom severity correlations in depression.

BackgroundWorldwide, common mental disorders such as anxiety and depression are major contributors to disability. However, the role of diet as a risk factor for anxiety and depression remains underexplored. Therefore, we investigated the associations between food groups and major depressive disorder (MDD) and anxiety disorders, following a harmonized protocol to enable integration of studies. MethodsWe analysed data from 1,634 participants in the Netherlands Study of Depression and Anxiety to examine cross-sectional associations between 14 dietary exposures--derived from a 238-item Food Frequency Questionnaire (fruit, vegetables, legumes, whole grains, nuts and seeds, milk, red meat, processed meat, sweet drinks, fibre, calcium, omega-3 fatty acids, polyunsaturated fatty acids, and trans fats)--and anxiety and depressive disorders in the past month (assessed with the Composite International Diagnostic Interview). Secondary outcomes were depressive symptoms (Quick Inventory of Depressive Symptomatology score [&ge;]13 vs. <13) and anxiety symptoms (Beck Anxiety Index score [&ge;]16 vs. <16). Logistic regression analyses were conducted for each dietary exposure, with depression and anxiety measures as outcomes. Results8.7% had MDD and 14.4% had an anxiety disorder in the past month. Higher vegetable intake was associated with lower odds of depression and anxiety disorders. Additionally, higher intakes of omega-3 fatty acids, red meat, whole grains, and fibre were associated with lower odds of depression and anxiety, whereas higher intake of trans fats was associated with increased odds of these disorders. Other dietary exposures were not significantly related to depression or anxiety. DiscussionCertain dietary exposures, particularly vegetables, as well as omega-3 fatty acids, red meat, whole grains, and fibre, were associated with depression and anxiety outcomes. These findings may contribute to integration of results in Global Burden of Diseases initiatives on exploring dietary risk factors of depression and anxiety.

BackgroundDepression is a mood disorder frequently associated with episodic memory impairment. However, it remains unclear whether functional brain activity differs between depressed and non-depressed individuals during encoding or retrieval of autobiographical or non-autobiographical memories. Clarifying these differences is important for refining theoretical models of memory impairment in depression and, potentially, for developing targeted interventions. MethodsWe conducted three coordinate-based meta-analyses examining encoding and retrieval of autobiographical and non-autobiographical memory in control participants and individuals with current, remitted, or subthreshold depression, or those at risk for depression. Studies were identified via database searches and analysed using Seed-based d Mapping. ResultsWe included coordinates from 21 fMRI studies. During encoding, depression was associated with reduced activity in the thalamus, the caudate, the salience network, the frontoparietal executive control network, and motor-related areas (ten studies, N = 506). During non-autobiographical retrieval, depression was associated with higher activity in the right inferior frontal gyrus (six studies, N = 332). During autobiographical retrieval, depression was associated with reduced activity in the right insula and fusiform gyrus, alongside increased activity in the left anterior cingulate cortex and the left middle frontal gyrus (ten studies, N = 423). Between-study heterogeneity was low and no evidence for publication bias was found. DiscussionOur results indicate that depression may be associated with impaired salience integration during encoding and autobiographical retrieval. In contrast, during non-autobiographical retrieval, increased frontal activity suggests a more vigilant or self-monitoring retrieval mode. Functional brain activity changes in depression therefore appear stage- and content-specific.

Understanding depressive symptoms dynamics and their determinants is crucial for designing effective mental health support initiatives. This study compared two methods for describing youth depressive symptoms trajectories and investigated associations of early-life factors (maternal education, maternal perinatal depression, domestic violence, physical, emotional, or sexual abuse, bullying victimisation, psychiatric disorder) with trajectory features. Prospective data from 8,264 mostly White European participants (54% female), including self-reported Short Moods and Feelings Questionnaires on ten occasions between 10-25 years, were used. Trajectories were summarised using functional principal component analysis (FPCA) and P-splines linear mixed-effect (PLME) models. Estimated derivatives were used to obtain magnitude and age of peak symptoms and peak symptoms velocity. Both methods performed comparably, but PLME models tended to over-smooth trajectories. Peak symptoms and peak velocity were higher and occurred >1 year earlier in females than males. All early-life factors were associated with higher peak symptoms, and most associated with higher and earlier peak velocity. Abuse and bullying additionally associated with earlier age of peak symptoms. FPCA is a useful alternative for characterising depressive symptoms trajectories and informing time-sensitive preventative measures to reduce impact of depression before symptoms reach their peak. Early-life stressors may accelerate timeline and intensity of symptoms escalation during adolescence. Lay summaryUnderstanding development of depressive symptoms and factors shaping them is crucial for designing effective mental health support initiatives. This study used data from over 8,000 young people regularly followed up from before birth to compare two cutting-edge methods for describing depressive symptoms trajectories and examined how known risk factors for adulthood depression relate to the severity and rate of change of depressive symptoms in adolescence. We found that both methods performed well and that the peaks in depressive symptoms and their rate of change were, on average, higher and occurred over a year earlier in females than males. Our findings additionally suggest that early-life stressors (e.g., abuse, bullying) may accelerate the development of depression, highlighting the importance of early prevention.

Background: Bipolar disorder (BD) is increasingly conceptualized as a heterogeneous condition with a neurodevelopmental phenotype (NDP) identifying a subgroup with early neurodevelopmental vulnerability and poorer clinical outcomes. Sensory processing (SP) abnormalities are a core feature of neurodevelopmental disorders but remain poorly characterized in BD and may reflect underlying neurodevelopmental liability. We examined whether NDP load is associated with specific SP alterations in euthymic BD patients and whether NDP-based stratification explains SP variability better than conventional BD subtype (BD 1/2). Methods: We assessed 102 euthymic BD patients and 45 healthy controls (HC) using the Adolescent/Adult Sensory Profile (AASP). NDP load (0-3) was computed from nine clinical variables grouped into neonatal, comorbidity, and neurodevelopmental clusters; a median split defined BD without NDP (BD) and BD with NDP (BD-ND). Associations between NDP load and AASP quadrants were analyzed using Spearman correlations with FDR correction. Group differences (BD, BD-ND, HC) were assessed using Welch ANOVA and post-hoc tests. Nested and multivariable linear regressions examined whether NDP classification explained SP variance beyond BD subtype, adjusting for age, sex, anxiety, and residual mood symptoms. Results: Higher NDP load correlated with greater low registration (rho=0.35, p<0.001, q=0.004), sensory sensitivity (rho=0.30, p=0.001, q=0.004), and sensation avoiding (rho=0.23, p=0.014, q=0.040), but not sensation seeking. BD-ND showed higher low registration, sensory sensitivity, and sensation avoiding than BD and HC (all qs<0.01). NDP classification explained more SP variance than BD subtype; with robust associations after adjustment. Conclusions: Sensory processing alterations in BD are dimensionally associated with neurodevelopmental load and more accurately captured by NDP-based stratification than diagnostic subtype. SP alterations may represent a transdiagnostic marker of neurodevelopmental liability within BD, supporting biologically informed stratification approaches.

ObjectivesElectroconvulsive Therapy (ECT) is an effective treatment for bipolar disorder, particularly in severe acute cases or for illness resistant to pharmacotherapy. However, the risk of relapse following ECT is high, necessitating intervention to reduce this risk. Based on findings from ECT studies in unipolar depression and its well-known mood-stabilizing properties, it is likely that lithium treatment may reduce the risk of relapse of bipolar disorder following ECT. Therefore, we conducted a target trial emulation using data from Danish nationwide registers to investigate whether lithium protects against relapse following ECT treatment of bipolar disorder. MethodsPatients discharged from their first psychiatric admission with a primary diagnosis of bipolar disorder between January 1, 2006, and June 1, 2024, who received at least six ECT treatments, were included. Follow-up began two weeks after discharge and continued until relapse, death, one year, or January 1, 2025. Patients were considered allocated to lithium treatment if they redeemed a prescription for lithium within the first two weeks after discharge from the index admission (ECT treatment). The outcome was time to relapse, defined by either psychiatric hospital admission or suicide. Cox proportional hazards regression, adjusted for potential confounders, was used to compare the outcome between patients allocated and not allocated to lithium treatment. ResultsAmong the 574 eligible patients (mean age 41.5 years, 61.3% women), 214 (37.3%) were allocated to lithium treatment and 360 (62.7%) were not allocated to lithium treatment. During follow-up, 56 patients (26.2%) in the lithium group and 135 patients (37.5%) in the non-lithium group experienced a relapse. Lithium treatment was associated with a substantially reduced risk of relapse (adjusted hazard rate ratio, 0.60, 95% CI=0.43-0.84). ConclusionLithium treatment after ECT may reduce the risk of relapse in patients with bipolar disorder. These findings should be followed up by a randomized controlled trial.

BackgroundAntidepressants exert their therapeutic effects through ameliorating negative emotional biases that underpin depression. However, therapeutic gains may depend upon restructuring how emotional information is processed. This can be achieved through Cognitive Bias Modification (CBM), a technique for positively shifting recognition of emotional facial expressions. Here, we examined how CBM modifies emotional processing circuits in individuals with depression who were taking Selective Serotonin Reuptake Inhibitors (SSRIs). MethodsA double-blind Randomised Controlled Trial was conducted in 84 participants with depression who had recently started SSRI medication. Participants received five sessions of active or sham CBM over one week before fMRI scanning where they viewed emotional faces (happy, fearful, sad). ResultsAcross all emotional expressions, greater Blood Oxygen Level Dependent (BOLD) signal was observed in the inferior occipital gyrus for the active compared to sham CBM. Emotional-specific effects were observed in the medial Prefrontal Cortex (mPFC), with reduced BOLD signal in the active (compared to sham) group for viewing happy vs. fearful faces. Changes in BOLD signal were also associated with individual differences in response to CBM. Enhanced functional connectivity between mPFC and right Dorsolateral Prefrontal Cortex (rDLPFC) predicted improvement in depressive symptoms four weeks later. ConclusionsThese results indicate that CBM modifies the neural circuits involved in emotion processing in people with depression currently taking antidepressants. Converting these changes in emotional perception to improved depressive symptoms was related to changing mPFC-rDLPFC connectivity. Future trials are needed to test CBMs clinical utility as a simple, affordable and accessible adjunct therapy for depression.

BackgroundIntermittent theta burst stimulation (iTBS) and H-coil repetitive transcranial magnetic stimulation (rTMS) are FDA-cleared treatments for major depression; yet their comparative effectiveness in treatment-resistant depression (TRD) has not been evaluated in randomized trials. This pilot randomized trial was designed to obtain preliminary comparative estimates and to explore whether baseline cognitive functioning relates to early remission. MethodsTwenty-eight adults with TRD were randomized to six weeks of iTBS delivered to the dorsolateral prefrontal cortex (DLPFC) using a figure-8 coil (n=15) or H-coil rTMS delivered to the dorsomedial prefrontal cortex (DMPFC) using a H7-coil (n=13). The primary outcome was change in 17-item Hamilton Depression Rating Scale (HRSD-17) score from baseline to week 6, analyzed with ANCOVA. Additional outcomes included response, remission, and symptom trajectories through week 18. Exploratory analyses examined the association between baseline cognitive functioning, such as executive functions and memory, and remission. ResultsTwenty-five participants completed all 30 sessions. Adjusted week-6 HRSD-17 scores did not differ between groups (mean difference -0.40, 95% CI -5.23 to 4.43; p=.865). Response rates were 40.0% for iTBS and 50.0% for H-coil (p>.60), and remission rates were identical across groups (20.0%). Remitters showed higher baseline executive functioning than non-remitters in exploratory analyses, although these associations were not confirmed in adjusted models. ConclusionIn this pilot trial, iTBS and H7-coil rTMS showed symptom improvement, with no clear between-group pattern. Exploratory findings suggest a potential signal involving executive functioning that warrants further investigation. These results inform the feasibility and design of larger comparative trials. Trial registrationClinicalTrials.gov (NCT05902312)