Journal of Affective Disorders

BackgroundThe present study analyzes the effects of each containment phase of the first COVID-19 wave on depression levels in a cohort of adults with a history of major depressive disorder (MDD). MethodsThis analysis is part of the Remote Assessment of Disease and Relapse-MDD (RADAR-MDD) study. Individuals included had a diagnosis of DSM-5 major depressive disorder (MDD), at least two episodes of major depression (MDE), one of them in the previous two years. Depression was evaluated with the Patient Health Questionnaire-8 (PHQ-8) and anxiety with the Generalized Anxiety Disorder-7 (GAD-7). A total of 121 participants recruited from Catalonia were registered from November 1, 2019, to October 16, 2020. Levels of depression were explored across the phases (pre-lockdown, lockdown, four post-lockdown phases) of the restrictions imposed by the Spanish/Catalan governments. Then, a mixed model was fitted to estimate how depression varied over the phases. ResultsA small but statistically significant rise in the depressive severity was found during the lockdown and phase 0 (early post-lockdown), as compared with the pre-lockdown phase in this sample with a history of MDD. Those with low pre-lockdown depression experienced an increase in depression levels during the "new normality". We observed a significant decrease in the depression levels during the "new normality" in those with high pre-lockdown depression, compared to the pre-lockdown period. ConclusionThese findings suggest that COVID-19 restrictions impacted on the depression of individuals diagnosed with MDD, depending on their pre-lockdown depression severity. Furthermore, these subjects worsened when the restrictions were harder, during the lockdown and the early post-lockdown.

In Low and Middle Income Countries (LMICs), adolescent depression is one of the leading mental health problems with serious implications, posing a significant public health concern. A comprehensive understanding of adolescent depression and the development of effective intervention strategies require not only an examination of its biological and psychological determinants but also a critical analysis of the social factors influencing its prevalence and impact. This scoping review, guided by Arksey and OMalleys framework, examined the social factors influencing adolescent depression. A total of 48 primary studies were included, identified through a systematic search across five databases and manual exploration of relevant literature from various LMICs. This review identified structural factors including gender, socioeconomic status, ethnicity, and family structure alongside stressors in family, school, and neighborhood settings, such as conflict, harsh parenting, maltreatment, academic pressure, peer rejection, bullying, and neighborhood violence, as key contributors to adolescent depression. Conversely, social support from family, peers and teachers was found to be a protective factor against depression. However, these studies are primarily cross-sectional, with a predominant focus on Asia and limited attention to neighborhood-level factors, often concentrating on school-going adolescents. Furthermore, the studies are largely descriptive and atomized, inadequately exploring the domains and their interplay with social structures in shaping adolescent depression.

BackgroundThe early prediction of adolescent depression recurrence poses a significant challenge in the field. This study aims to investigate and compare the abilities of two psychopathology factors, namely the general psychopathology factor (p) and the specific internalizing factor, in predicting depression recurrence over a 2-year course, as well as identifying remitted depression patients from healthy adolescents. Longitudinal changes of these two factors in different trajectory groups were also tracked to examine their sensitivity to sustained remission and relapse. MethodsWe included 255 baseline-remitted depression patients and a healthy control group (n=255) matched in age, sex, and race, sourced from the Adolescent Brain Cognitive Development Study. The Linear Mixed Model was employed to differentiate between healthy controls and remitted depression patients, predict depression recurrence, and track longitudinal changes over a subsequent 2-year course using the p factor and the specific internalizing factor respectively. ResultsThe p factor not only effectively discriminated between remitted depression patients and healthy controls, but also robustly predicted the depression recurrence over a subsequent 2-year course. The specific internalizing factor could only differentiate remitted depression patients from healthy controls. Additionally, a noteworthy longitudinal decline of the p factor in the sustained-remission group was observed. ConclusionsPsychopathology factors serve as the inherent and enduring measurement of long-term mental health aberrations. Longitudinal results indicate that the p factor is more sensitive to respond to sustained remission than the internalizing factor. The ability of the overall p factor to anticipate depression relapse, unlike the specific internalizing factor, suggests clinical interventions should monitor and mitigate the coincident symptoms across all dimensions to preempt relapse of adolescent depression, rather than an exclusive focus on internalizing symptoms.

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.

This study aimed to develop a classification model predicting incident bipolar disorder (BD) cases in young adults within a 5-year interval, using sociodemographic and clinical features from a large cohort study. We analyzed 1,091 individuals without BD, aged 18 to 24 years at baseline, and used the XGBoost algorithm with feature selection and oversampling methods. Forty-nine individuals (4.49%) received a BD diagnosis five years later. The best model had an acceptable performance (test AUC: 0.786, 95% CI: 0.686, 0.887) and included ten features: feeling of worthlessness, sadness, current depressive episode, selfreported stress, self-confidence, lifetime cocaine use, socioeconomic status, sex frequency, romantic relationship, and tachylalia. We performed a permutation test with 10,000 permutations that showed the AUC from the built model is significantly better than random classifiers. The results provide insights into BD as a latent phenomenon, as depression is its typical initial manifestation. Future studies could monitor subjects during other developmental stages and investigate risk populations to improve BD characterization. Furthermore, the usage of digital health data, biological, and neuropsychological information and also neuroimaging can help in the rise of new predictive models.

Neuroticism is a subclinical manifestation of the phenome of depression, comprising depressive and anxiety symptoms, and suicidal behaviors. Rumination is positively associated with depression and neuroticism and may mediate the effects of neuroticism on depression. This study aims to determine whether rumination or its components, including brooding or reflection, mediate the effects of neuroticism on depression, or alternatively, whether both neuroticism and rumination are manifestations of the phenome of depression. This study recruited 74 depressed subjects and 44 healthy controls. The depression group was split into groups with high versus low brooding scores. We used partial least squares (PLS) to examine mediation effects. We found that brooding and reflection scores are significantly higher in depressed patients than in controls. Patients with higher brooding scores have increased severity of depression, anxiety, insomnia, neuroticism, and current suicidal ideation as compared with patients with lower brooding scores and controls. There is a strong positive association between rumination, and neuroticism, depression, anxiety, and lifetime and current suicidal behaviors. PLS analysis shows that brooding does not mediate the effects of neuroticism on the depression phenome, because no discriminant validity could be established between neuroticism and brooding, or between neuroticism and brooding and the depression phenome. We were able to extract one validated latent vector from brooding and neuroticism, insomnia, depression, anxiety, and current suicidal behaviors. Overall, this study supports the theory that rumination and neuroticism are manifestations of the phenome of depression, just like affective symptoms, suicidal behaviors, and insomnia.

BackgroundThere is evidence that adverse childhood experiences (ACEs) and negative life events (NLEs) are associated with major depression (MDD). PurposeTo determine whether ACEs affect all features of mild MDD, including suicidal tendencies, brooding, neuroticism, insomnia, cognitive deficits, severity of depression and anxiety, and cognitive deficits, and whether NLEs mediate these effects. Patients and methodsThis study examines a cohort of 118 academic students, namely 74 students who satisfied the DSM-5-TR criteria for MDD and 44 normal control students. We assessed brooding, neuroticism, suicidal ideation and attempts, and the severity of depression, anxiety, insomnia, and the Stroop tests. ResultsOne validated factor could be extracted from brooding, neuroticism, current suicidal behaviors, and the severity of depression, anxiety, and insomnia, labeled the phenome of depression. A large part of the variance in the phenome of depression (55.0%) was explained by the combined effects of self-, relationships, and academic-related NLEs in conjunction with ACEs, including family dysfunction and abuse and neglect (both physical and emotional). The latter ACEs significantly interacted (moderating effect) with NLEs to impact the depression phenome. Although sexual abuse did not have direct effects on the phenome, its effects were mediated by NLEs. We discovered that increased sexual abuse, physical and emotional abuse and neglect, and ACEs related to family dysfunction predicted 22.5% of the variance in NLEs. Up to 18.5% of the variance in the Stroop test scores was explained by sexual abuse and the phenome of depression. The latter mediated the effects of NLEs and abuse, neglect, and family dysfunction on the Stroop test scores. ConclusionComplex intersections between ACEs and NLEs impact the phenome of depression, which comprises neuroticism, brooding, suicidal tendencies, and the severity of insomnia, anxiety, and depression, while sexual abuse together with other ACEs and NLEs may impact cognitive interference inhibition.

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.

IntroductionProspective studies on mental health of students showed that young adults enroled in university are affected by poorer mental health than other working peers or adults, and this condition is responsible for a large proportion of disability-adjusted life-years MethodsWe enrolled 1388 students at the baseline (and 557 completed follow-up after six months) who reported their demographic information and completed self-report questionnaires on depressive, anxiety and obsessive-compulsive symptoms. We applied multiple regression modelling and supervised machine learning to evince associations and predict the risk factors of poorer mental health at baseline and follow-up ResultsApproximately one out of five students reported severe depressive symptoms and/or suicidal ideation. An association of economic worry with depression was evidenced at the beginning of the study (when there was a high frequency of worry OR = 3.11 [1.88 - 5.15]) and during follow-up. Supervised machine learning exhibited high accuracy in predicting the students who maintained well-being (balanced accuracy = 0.85) or absence of suicidal ideation, but its performance was almost null in identifying those whose symptoms worsened. ConclusionsStudents severe mental health problems are reaching worrying percentages, and few demographic factors can be leveraged to predict poor mental health outcomes. Further research including people with lived experience is crucial to assess students needs and improve the prediction of those at risk of developing worse symptoms.

The present study aims to assess the association between sleep quality and the functional and cognitive impairment in subjects that recently converted to bipolar disorder (BD), subjects with past major depressive disorder (MDD) and subjects with recurrent MDD. This was a cross-sectional study corresponding to a second wave of a cohort study with a community sample. The first wave included 585 subjects diagnosed with MDD. Mood episodes were assessed through structured clinical interview. Functional and objective cognitive impairments were measured by the Functional Assessment Short Test (FAST) and Letter-number sequencing from Wechsler Adult Intelligence Scale III, respectively, and Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA) was used for subjective cognition measure. Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI). In PSQI, FAST and COBRA, we found significantly worse scores in the BD and recurrent MDD groups when compared to past MDD group. Our findings also showed a significant association between functioning and subjective cognition with general sleep quality in all observed groups. We reinforce the need to follow-up for maintenance of functional and cognitive impairment, notably with BD patients, who may suffer in addition to damage caused by sleep alterations, also with neuroprogression in the long term.

Neuroticism, a personality trait, can predict major depressive disorder (MDD). The current study aims to determine whether a) neuroticism is a feature of the acute state of MDD, including suicidal behaviors (SB); and b) adverse childhood experiences (ACEs) are associated with neuroticism in MDD. This study included 133 participants, 67 normal controls and 66 MDD patients, and assessed the Big 5 Inventory (BFI), ACEs using the ACE Questionnaire, and the phenome of depression using the Hamilton Depression (HAMD) Rating Scale (HAMD), Beck Depression Inventory (BDI), The State-Trait Anxiety Inventory (STAI) and Columbia Suicide Severity Rating Scale (C-SSRS) scores to assess current SB. Neuroticism was significantly higher in MDD than controls, and it explained 64.9% of the variance in the depression phenome (a latent vector extracted from HAMD, BDI, STAI, and current SB scores). The other BFI domains had much less (extraversion, agreeableness) or no effect (openness, conscientiousness). One latent vector could be extracted from the phenome, lifetime dysthymia, lifetime anxiety disorders and neuroticism scores. Neglect (physical and emotional) and abuse (physical, neglect and sexual) account for approximately 30% of the variance in this latent vector. Partial Least Squares analysis showed that the effects of neglect on the phenome were partially mediated by neuroticism, whereas the effects of abuse were completely mediated by neuroticism. Neuroticism (trait) and the MDD phenome (state) are both manifestations of the same latent core, with neuroticism being a less severe manifestation of major depression, which in fact is a multiplicative manifestation of neuroticism.

The COVID-19 pandemic has presented a significant challenge to societal mental health. Yet, it remains unknown which factors influence the mental adaptation from lockdown to subsequent relaxation periods, particularly for vulnerable groups. This study used smartphone-based monitoring to explore how 74 individuals with major depression (MDD) and 77 healthy controls (HCs) responded to the transition from lockdown to relaxation during the first wave of the COVID-19 pandemic (March 21 to November 01, 2020) regarding interpersonal interactions, COVID-19-related fear (fear of participants own health, the health of close relatives, and the pandemics economic impact), and the feeling of isolation. Furthermore, we investigated the effect of a diagnosis of MDD and the experience of childhood maltreatment (CM) on adaptive functioning. During the transition from lockdown to relaxation, we observed an increase in direct contacts and a decrease in indirect contacts and self-perceived isolation in the study population. The diagnosis of MDD and the experience of CM moderated a maintenance of COVID-19-related fear: HCs and participants without the experience of CM showed a decrease in fear, while fear of participants with MDD and with an experience of CM did not change significantly. The finding that elevated COVID-19-related fear was sustained in vulnerable groups after lockdown measures were lifted could help guide psychosocial prevention efforts in future pandemic emergencies.

This study examines the impact of pandemic-related worries on mental health in the Indian general adult population from 2020 to 2022. Using data from the Global COVID-19 Trends and Impact Survey (N = 2,576,174 respondents aged[≥] 18 years in India; an average weekly sample size of around 25,000), it explores the associations between worry variables (namely financial stress, food insecurity, and COVID-19-related health worries) and self-reported symptoms of depression and nervousness. The statistical analysis was conducted using complete cases only (N = 747,996). Our analysis used survey-weighted models, focusing on the three pandemic-related worries as the exposures, while also adjusting for various other covariates, including demographics and calendar time. The study finds significant associations between these worries and mental health outcomes, with financial stress being the most significant factor affecting both depression (adjusted odds ratio: 2.36, 95% confidence interval: [2.27, 2.46]) and nervousness (adjusted odds ratio: 1.91, 95% confidence interval: [1.81, 2.01]) during the first phase of the study period (June 27, 2020, to May 19, 2021). The fully adjusted models also identify additional factors related to mental health, including age, gender, residential status, geographical region, occupation, and education. Moreover, the research highlights that males and urban residents had higher odds ratios for self-reported mental health problems regarding the worry variables than females and rural residents, respectively. Furthermore, the study reveals a rise in the prevalence of self-reported depression and nervousness and their association with COVID-19-related health worries during the lethal second wave of the pandemic in May 2021 compared to the onset of the pandemic. This study shows that social media platforms like Facebook can deploy surveys to a large number of participants globally and can be useful tools in capturing mental health trends and uncovering associations during a public health crisis.

This study was performed to ascertain whether a) a valid precision model and valid Research and Diagnostic Algorithmic Rules (RADAR) scores can be computed in patients experiencing first-episode depression; and b) adverse childhood experiences (ACEs) and negative life events (NLEs) are associated with suicidal behavior (SBs), cognitive impairment, and phenome RADAR scores. This study recruited 90 patients with major depressive disorder (MDD) in an acute phase, of whom 71 showed a first-episode MDD (FEM), and 40 controls. We constructed RADAR scores for ACEs, NLEs encountered the last year, SBs and severity of depression, anxiety, chronic fatigue and physiosomatic symptoms using the Hamilton Depression and Anxiety Rating scales and the Fibro-Fatigue scale. Partial least squares analysis showed that in FEM, one latent vector (labelled the phenome of FEM) could be extracted from depressive, anxiety, fatigue, physiosomatic, melancholia, and insomnia symptoms, SBs, and cognitive impairments. The latter were conceptualized as a latent vector extracted from the Verbal Fluency Test, Mini Mental State Examination, and ratings of memory and judgment, indicating a generalized cognitive decline (G-CoDe). We found that 60.8% of the variance in the FEM phenome was explained by the cumulative effects of NLEs and ACEs, in particular emotional neglect and, to a lesser extent, physical abuse, and by the interaction between ACEs and physical abuse, whereby the latter attenuates the effects of NLEs. In conclusion, not the binary diagnosis of MDD (DSM/ICD) should be used in research and clinical settings but the RADAR scores and plots constructed here.

BackgroundMajor depressive disorder (MDD) is associated with maladaptive self-reported interoception, i.e., abnormal bodily self-experience. Although diminished body trusting predicts suicidal ideation, interoceptive measures have not been considered in depressed inpatients, whose suicide risk regularly peaks post-discharge. This study aims to explore interoceptive characteristics at admission that help identify inpatients at risk for suicidal ideation at discharge, thereby preventing fatal outcomes. MethodsThe observational study included 87 depressed inpatients providing self-ratings at both hospital admission (T0) and discharge (T1) on the following scales: Multidimensional Assessment of Interoceptive Awareness (MAIA-2); Beck Depression Inventory-II (BDI-II). A hierarchical logistic regression analysis estimated the longitudinal association between self-reported interoception (T0) and suicidal ideation (T1). The optimal cutpoints for predicting suicidal ideation were calculated using ROC curve analysis. ResultsSuicidal ideation was found in 17.24% patients at discharge, who reported lower baseline MAIA-2 Trusting scores than non-ideators (p=0.01). Diminished body trusting (OR=0.19), somatic comorbidity (OR=16.77), and baseline suicidal ideation (OR=24.01) significantly predicted suicidal ideation (T1). For body trusting, we estimated an optimal classification of subsequent suicidal ideation for the cutpoint[≤]2.33 (AUC=0.70 [95% CI 0.57, 0.83], sensitivity=0.87, specificity=0.44, positive predictive value=0.25, negative predictive value=0.94). LimitationsDue to the exploratory nature of the study, the findings should be replicated in pre-registered trials with larger sample sizes. ConclusionsDiminished body trusting is, with acceptable sensitivity, a significant predictor for post-treatment suicidal ideation in depressed inpatients. This finding emphasizes the importance of incorporating body-centered approaches into multimodal treatment strategies especially in inpatients under risk to prevent suicidal incidents.

Background and ObjectivesThe goals of depression screening, which is universally recommended in primary care settings in the U.S., are to identify adolescents with depression and connect them to treatment. However, little is known about how depression screening affects the likelihood of being diagnosed with a mental disorder or accessing mental health care over time. MethodsThis longitudinal cohort study used insurance claims data from 57,732 adolescents who had at least one routine well-visit between 2014 and 2017. Using propensity score matching, we compared adolescents who were screened for depression to similar adolescents who were not screened for depression during the well-visit. Diagnostic and treatment-related outcomes were examined over 6-month follow-up and included depression diagnoses, mood-related diagnoses, antidepressant prescriptions, any mental health-related prescriptions, and psychotherapy. We also examined heterogeneity of associations by sex. ResultsCompared to adolescents who were not screened for depression, adolescents screened for depression were 30% more likely to be diagnosed with depression (RR=1.30, 95% CI=1.11-1.52) and 17% more likely to receive a mood-related diagnosis (RR=1.17, 95% CI=1.08-1.27), but were not more likely to be treated with an antidepressant prescription (RR=1.11, 95% CI=0.82-1.51), any mental health prescription (RR=1.15, 95% CI=0.87-1.53), or psychotherapy (RR=1.13, 95% CI=0.98-1.31). In general, associations were stronger among females. ConclusionsAdolescents who were screened for depression during a well-visit were more likely to receive a diagnosis of depression or a mood-related disorder in the six months following screening. Future research should explore methods for increasing access to treatment and treatment uptake following screening. Clinical Trial Registration (if any)N/A Table of Contents SummaryInsurance claims data were used to explore associations between depression screening during routine well-visits and depression diagnoses, psychiatric prescriptions, and psychotherapy among adolescents. Whats Known on This SubjectDepression screening is increasingly viewed as a key strategy for addressing depression among adolescents. To inform clinical guidelines, the United States Preventive Services Task Force has called for research to examine the diagnostic and treatment-related outcomes of depression screening. What This Study AddsIn a sample of 57,732 adolescents, adolescents who were screened for depression during a well-visit were more likely to receive a depression or mood-related diagnosis over 6-month follow-up, but were not more likely to be treated with medication or psychotherapy.

IntroductionCognitive impairments are common in depression and often persist beyond mood resolution. However, the relationship between cognitive performance, its neurological underpinnings, and future depression risk is unclear, limiting strategies for primary and secondary prevention. Our objective was to determine whether cognition associates with subsequent depression, including both relapse and first-episode occurrences. Methods2094 UK Biobank participants with previous ICD-10-defined depression currently in remission (RD) (mean(SD) age: 52.4(7.25) years) were age- and sex-matched to 2094 participants without depression history or current antidepressant use. Cognitive scores were compared between groups at the composite (z-score), domain, and task levels. MRI-derived phenotypes assessed brain network structure and functional connectivity. Longitudinal associations with future depression were assessed using logistic regression models controlling for key confounders. ResultsParticipants with RD had a higher risk of future depression (30%) than controls (8.5%). Composite cognitive performance in controls was inversely associated with future depression risk (risk estimated marginal means: 0.48% at -1SD, 0.37% at mean, 0.28% at +1SD). In RD, this relationship was reversed (1.56% at -1SD, 1.80% at mean, 2.08% at +1SD). Executive functioning, processing speed, and reasoning task scores all contributed. Higher grey matter in default mode network regions was associated with better concurrent cognitive performance across all participants, but not with future depression risk. Other MRI findings were limited. ConclusionRD carried a threefold higher risk of future depression than controls. Cognitive performance was a risk marker for future depression in both groups but in opposing directions. Neuroimaging metrics provided little predictive value. What is already known on this topicNeurocognitive impairments are common in depression, even after low mood has resolved and outside of comorbid neurodegenerative processes. However, the specific relationship between cognitive performance and risk of future depression is unclear, including how this relates to previous history of depression. What this study addsCognitive performance is a differential risk marker for future depression in those with previous depression compared to matched controls: without previous history of depression, poorer cognitive scores confer the highest risk; in remitted depression, higher levels of cognitive performance are associated with greater risk of depressive relapse. How this study might affect research, practice or policyFurther research should explore targeting interventions based on specific cognitive profiles, especially in high-risk populations such as those with previous episodes of depression.

Importance: The menopausal transition is associated with an increased risk of depression. Prior depression is a well-established risk factor, but studies do not distinguish between prior reproductive and non-reproductive depression. Objective: To compare the associations of reproductive (i.e., premenstrual mood disorder and perinatal depression) and non-reproductive (i.e., not related to hormonal transitions) histories of depression with depressive symptoms during the menopausal transition. Design: Cross-sectional analysis of questionnaire data from the Multidisciplinary Menopausal Outpatient Care Project (MOPP) collected between February 2023 and October 2025. Setting: Menopause outpatient clinics Amsterdam, the Netherlands, including a specialized multidisciplinary menopause clinic. Participants: In total 364 individuals were approached; 244 enrolled at baseline. After exclusions for age <40 (n=3), premature ovarian insufficiency (n=2), premenopausal status (n=1), age >58 with final menstruation >10 years earlier (n=12), bipolar disorder (n=5), and missing survey data (n=41), 180 participants were included. Exposures: Premenstrual mood disorder measured with Premenstrual Symptom Screening Tool, perinatal depression with Edinburgh Postnatal Depression Scale Lifetime version, and reported prior non-reproductive depression in medical records. Main outcome and measures: Depressive symptom severity measured with Inventory of Depressive Symptomatology-Self Rated. We used univariable and multivariable linear regressions; multivariable models accounted for overlap between exposures. Results: Among 180 participants (median age 51; 61% perimenopausal and 39% postmenopausal), premenstrual mood disorder showed the strongest association with depressive symptom severity (B = 9.0, 95% CI 5.1-12.9, p < 0.001), followed by perinatal depression (B = 7.8, 95% CI 3.4-12.1, p < 0.001) and prior non-reproductive depression (B = 4.7, 95% CI 0.7-8.7, p = 0.021). In multivariable analysis, only premenstrual mood disorder (B = 7.2, 95% CI 2.4-12.1, p = 0.0037) and perinatal depression (B = 5.7, 95% CI 1.2-10.1, p = 0.013) remained associated with depressive symptom severity. Conclusions and Relevance: Prior reproductive depression, but not prior non-reproductive depression, was associated with greater depressive symptom severity during the menopausal transition. A history of premenstrual mood disorder and/or perinatal depression may therefore help identify individuals at increased vulnerability to depressive symptoms during this period. Future studies should replicate these findings in population-based samples.

BackgroundMajor depressive disorder (MDD) and generalised anxiety disorder (GAD) are common psychiatric disorders. Previous studies showed shared genetic and environmental factors, but no studies have compared their overlap and differences from gene-environment interaction perspective. Current studies neglect the high rate of comorbidity between them and have overly broad case definitions, which may inflate the shared risk. In this study, we strictly defined the inclusion criteria to define three groups: MDD-only, GAD-only, and comorbid group, to investigate similarities and differences in gene-environment interactions across these groups. Methods and materialsWe analysed data from 396,443 participants in the UK Biobank (UKB), after applying exclusion criteria. We divided case group into three groups: MDD-only, GAD-only and comorbid group. 36 environmental variables across the three dimensions (socio-demographic, early life experiences and lifestyle) were included in this study and the PHESANT package was used to find significant environmental variables associated with three phenotypes. Logistic regression models were established with significant environmental variables and polygenic risk scores (PRS) of depression and anxiety as independent variables to test for PRS x environment interaction effects. Finally, the Genome-wide Gene-environment Interaction Association Studies (GWEIS) were performed using fastGWA-GE to identify susceptibility loci interacting with the significant environmental variables, and their biological annotations were conducted by FUMA and MAGMA. ResultsIn this study, 396,443 participants (53.9% female) were included, the MDD-only (n = 58,582), GAD-only (n = 12,063), comorbid (n = 26,119) and control groups (n = 299,679) differed significantly across all sociodemographic variables (P<0.001). Environmental screening identified 19 variables shared by all three groups, along with 2 environmental variables unique to MDD-only, 1 environmental variable unique to the GAD-only. In the GWEIS analyses, SNPs interacted with 5 stressful life events passed the Bonferroni correction to affect MDD-only; 8 SNP-environment interactions passed the Bonferroni correction to significantly affect GAD-only, including childhood maltreatment and recent stress; and 3 environmental variables, including recent stress and adoption, significantly interacted with the SNPs to influence comorbid phenotype. Same SNP and financial crisis interaction pattern was found in all three groups, but the susceptibility SNPs that significantly interacted with financial crisis were different. MR results showed childhood maltreatment causally increased the risk of MDD-only, GAD-only and their comorbidity. ConclusionFindings indicate MDD-only and GAD-only have more distinct socio-demographic, environmental factors and gene-environment interaction patterns after excluding comorbid cases. There are also difference in socio-demographic and gene-environment interaction patterns when comparing MDD with and without comorbidity. It may provide potential biological evidence for heterogeneity within diseases and clinical intervention for subtypes.

BackgroundAlthough existing research has suggested an association between insecure attachment styles and mental health difficulties, these studies often have small sample sizes, use cross-sectional designs, and measure attachment as a discrete variable at a single point. It is also unclear whether these associations persist into late adolescence. In this prospective study we aimed to determine whether insecure attachment style in early childhood is associated with depression and self-harm at 18 years. MethodsWe used data from the Avon Longitudinal Study of Parents and Children cohort. Mothers completed attachment related questionnaires when their child was 18, 30, and 42 months old. Offspring depression and lifetime self-harm was assessed at 18 years using the Clinical Interview Schedule-Revised. Attachment was derived as a latent variable in a structural equation modelling framework. Logistic regression was performed on participants with complete attachment data (n=7032) to examine the association between attachment style and depression and self-harm, with adjustment for potential confounders. Differential dropout was accounted for using multiple imputation. ResultsWe found some evidence for an association between attachment quality and depression and self-harm. In the fully adjusted imputed model, a one standard deviation increase in insecure attachment was associated with a 13% increase in the odds of depression at age 18 (OR=1.13; 95%CI=1.00 to 1.27) and a 14% increase in the odds of self-harm at age 18 (OR=1.14; 95%CI=1.02 to 1.25). ConclusionsOur findings strengthen the evidence suggesting that an insecure attachment style assessed in early childhood is associated with mental health difficulties in late adolescence. If this association is causal, policies to support parenting or attachment-based interventions to improve attachment quality could help reduce mental health difficulties in adolescence/young adulthood.