Journal of affective disorders最新文献

Although low-grade inflammatory processes have traditionally been studied in affective disorders, they are increasingly recognized as relevant across diagnostic categories. Genetic predisposition and environmental exposures such as childhood trauma (CT) may influence inflammation and shape vulnerability to psychopathology. Understanding how genetic predisposition for inflammation relates to specific symptom dimensions may clarify biological mechanisms underlying psychopathology. In N = 1790 individuals from the Marburg-Münster Affective Disorders Cohort Study (MACS), including patients with affective, anxiety, and psychotic disorders, as well as healthy controls, five transdiagnostic psychopathological syndrome factors were derived using factor analysis of clinical ratings. Polygenic scores (PGS) for circulating tumor necrosis factor TNF-α, interleukin IL-6, IL-10, and CRP were computed to indicate genetic predisposition to low-grade inflammation. Using network analyses, associations between inflammatory PGS and psychopathological syndrome factors were estimated while adjusting for age, sex, and BMI and including CT as a potential moderator. Six direct PGS-syndrome associations emerged, all with small but stable effect sizes. IL-6 PGS had the broadest connectivity, showing negative associations with increased appetite, paranoid-hallucinatory syndrome, and depression, as well as a positive association with negative syndrome. It also had the highest bridging centrality. IL-10 PGS was connected to negative and paranoid hallucinatory syndromes. These associations were largely independent of diagnosis and CT exposure. Integrating inflammatory genetic predisposition into networks of transdiagnostic symptom dimensions reveals small but consistent links between immune-related genetic risk and psychopathology, highlighting shared and distinct immunological pathways across psychiatric disorders.

Objectives: Major depressive disorder (MDD) is associated with significant impairment in occupational functioning. The Lam Employment Absence and Productivity Scale (LEAPS) is a self-report questionnaire validated for the assessment of work productivity and absenteeism in patients with MDD. Our study objective was to establish a minimal clinically important difference (MCID) for the LEAPS.

Methods: Data from the Canadian Biomarker Integration Network in Depression (CAN-BIND)-1 study was used. CAN-BIND-1 involved participants with MDD treated with escitalopram for 8 weeks (n = 138). Assessments included the LEAPS, Sheehan Disability Scale (SDS), and Quick Inventory of Depressive Symptomatology-Self-Rated (QIDS-SR). The MCID for the LEAPS was calculated using both distribution (value equivalent to half the standard deviation for LEAPS baseline scores) and anchor-based (comparing to the SDS work item) methods.

Results: The LEAPS total score was significantly correlated (p < 0.01) with other measures including SDS work item (r = 0.598), SDS total score (r = 0.609), and QIDS-SR (r = 0.678). Using the distribution-based method, the MCID value for LEAPS total score was 3.0 and MCID for LEAPS productivity subscale score was 1.5. Using the anchor-based method, the MCID value for the LEAPS total score was shown to lie between 2.7 and 3.5 and for the LEAPS productivity subscale score between 0.9 and 1.4.

Conclusions: Establishing an MCID is important for determining clinically relevant change in the LEAPS, both for treatment studies and for individual patients in clinical care. For clinical use, the proposed MCID is 3 points for the LEAPS total score and 2 points for the LEAPS productivity subscale score.

The best predictor of a suicide attempt is a previous attempt, apart from psychiatric diagnoses also associated. Some studies found other indicators of great risk for suicide reattempts. Machine Learning algorithms offer the potential for systematic detection of features that carry greater risk for an event. This study sought to develop a classification algorithm distinguishing between Single Suicide Attempters (SSA) and Multiple Suicide Attempters (MSA) in a Spanish multicentre national cohort to explore prediction of subsequent attempts in suicidal patients. Two models including the same sociodemographic and clinical variables grouped in more specific (Model I) or broad (Model II) categories were developed to explore risk factors for suicide reattempts. A Least Absolute Shrinkage and Regression Operator logistic regression with a 10-fold cross-validation was adopted. 1443 adult patients from the SURVIVE cohort were included (582 SSA and 861 MSA). Both Model I (AUC = 0.696; BAC = 0.644) and Model II (AUC = 0.678; BAC = 0.621) outperformed naïve majority-class classification for SSA and MSA. Bipolar disorder type II, binge-eating disorder, and schizophrenia variables weighted heavier on Model I for suicide reattempt-related; while eating disorder diagnosis, Africa as birthplace, affective disorder diagnosis, being employed, schizophrenia-spectrum disorder and substance use disorder diagnoses were the most important suicide reattempt-related of Model II. Affective disorders, eating disorders and schizophrenia-spectrum disorders emerged as the most important variables in predicting reattempts. Both models showed similar sensitivity and specificity when discriminating between SSA and MSA. Identifying specific risk factors for reattempts could have a significant impact on tailoring prevention strategies and interventions.

Loneliness in youth is linked to poor mental and physical health, yet the effectiveness of interventions remains unclear. Given its distinct developmental presentation, this meta-analysis synthesises interventions targeting loneliness in individuals aged 4-18 to inform age-appropriate strategies. It examines the effects of interventions on loneliness and includes a narrative synthesis of intervention and sample characteristics. We conducted a systematic literature review and meta-analysis of quantitative studies up to March 2024, focusing on interventions where loneliness was the primary target in school-aged youth. Nineteen studies were included in the SLR, of which 18 were included in the meta-analysis (6 RCTs, 6 multi-cohort, and 6 single-cohort studies). RCTs showed a small, non-significant reduction in loneliness (Hedges' g = -0.20, 95% CI [-0.42, 0.02], p = .07), with social and emotional skills training interventions being most effective. Multi-cohort studies showed a negligible effect (Hedges' g = -0.01, 95% CI [-0.08, 0.07], p = .84). Single-cohort studies indicated a moderate, non-significant effect (Hedges' g = -0.55, 95% CI [-1.29, 0.18], p = .14). Interventions targeting loneliness show promise in reducing loneliness, particularly when they incorporate social and emotional learning. Future research should integrate qualitative approaches and consider loneliness within broader mental health and well-being frameworks to support the development of more comprehensive, youth-centred interventions.

Background: Depressive episodes are associated with a higher risk for the onset of bipolar disorder (BD). This study investigates the contribution of specific depressive symptoms using a multi-method approach in persons at-risk for bipolar disorders.

Methods: In the Early-BipoLife study, N = 1083 participants at risk for BD were examined over two years (baseline, 6, 12, 18, and 24 months). Out of 1083 participants, N = 57 (5.3%) transitioned to BD and/or were prescribed with a mood stabilizing medication (lithium, lamotrigine, valproic acid, carbamazepine, quetiapine). At baseline, N = 880 participants met the diagnostic criteria for lifetime major depression (lifetime MD) (SCID). Depressive symptoms were recorded using diagnostic interviews (EPIbipolar, SCID), a clinician rating (ICD-C) and a self-rating (QIDS-SR16). Binary logistic regressions were calculated to assess the prospective association between depressive symptoms and transition/prescription of a mood stabilizing medication.

Results: Compared to 'no lifetime MD', 'lifetime MD' were at higher risk for transition and/or prescription of a mood stabilizing medication (OR = 2.87, 95%CI: 1.03-8.04). A higher QIDS-SR16 symptom load was associated with transition and/or prescription of a mood stabilizing medication (OR = 1.07, 95%CI: 1.01-1.13). Consistently and across methods, it was shown that suicidality at baseline predicted transition to BD and/or prescription of a mood stabilizing medication. Further baseline symptoms assessed by the clinicians (IDS-C), such as decreased or increased appetite and quality of mood were also predictive for this outcome.

Conclusion: Depressive symptom load and suicidality were robust predictors for BD. Clinician judgment can provide important information for early detection of BD.

Objectives: Guided by the diathesis-stress model of mental disorders, the current study tested how two forms of diathesis (ADHD and Medical Health Risk) and two forms of external stressors (social health risk and relational health risk) predicted depression diagnosis in American children and adolescents.

Method: Secondary data for 65,652 children and adolescents (Weighted N = 48,352,311) aged 6-17 were extracted from the combined 2022-2023 National Survey of Children's Health (NSCH). In addition to ADHD and depression diagnosis, the 2022-2023 NSCH constructed the Whole Child Risk Index (WCRI), which includes three domains: (1) Medical Health Risk (MHR) index, which captures the presence of chronic physical health conditions and functional impairment; (2) Social Health Risk (SHR) index, which captures the exposure to family social and economic disadvantages, and (3) Relational Health Risk (RHR) index, which captures the exposure to adverse childhood experiences and relationship challenges with parents. Each index falls on a 0-4-point scale from no risk to four risks.

Results: 12.4% had an ADHD diagnosis, 5.4% had a depression diagnosis, 28% had MHR, 27% had SHR, and 40% had RHR. The logistic regression model showed that ADHD, MHR, SHR, RHR and four diathesis-stress interactions increased the likelihood of depression diagnosis with outstanding model fit and prediction accuracy (McFadden's R-Squared = 0.31; AUC = 0.89). Noticeably, MHR (McFadden's R-Squared = 0.25; AUC = 0.86) outperformed ADHD, SHR and RHR in model fit and prediction accuracy.

Conclusion: The findings support the diathesis-stress interaction hypothesis, but the practical significance of the interactions is negligible.

Implication: Because of its substantial role in depression diagnosis, integrating mental health care into existing medical care can enhance child and adolescent healthcare practice.

Background: Irregular main-meal consumption frequency may disrupt metabolic and behavioral regulation, factors increasingly linked to affective disorders. However, evidence from nationally representative populations is limited.

Methods: We analyzed data from 21,568 adults in the 2014-2022 Korea National Health and Nutrition Examination Survey. Depressive symptoms were assessed with the PHQ-9. Multivariable logistic regression and restricted cubic spline analyses were conducted, adjusting for sociodemographic, lifestyle, and nutritional factors. Moderation and subgroup analyses examined dietary diversity, breakfast skipping, and lifestyle variables.

Results: Irregular main-meal consumption frequency was associated with higher odds of depressive symptoms (adjusted OR for highest vs. lowest irregularity = 1.55, 95% CI 1.42-1.69, p < 0.001). The association was strongest in those with the lowest dietary diversity, while greater variety buffered adverse effects. Frequent breakfast skipping heightened susceptibility. No higher-order interactions were observed. Subgroup analyses showed stronger associations in men, smokers, and late-night eaters, though these require cautious interpretation.

Limitations: Cross-sectional design, self-reported diet, and unmeasured confounders (stress, medication, sleep) may limit causal inference.

Conclusions: Irregular main-meal consumption frequency was associated with depressive symptoms, moderated by dietary diversity and breakfast habits, highlighting meal pattern regularity as a modifiable nutritional target for prevention.

Background: Sleep disturbances are common in older adults and increase the risk of depression. Although several longitudinal studies have examined this relationship, few have focused on subjective sleep quality and its changes in large ageing cohorts.

Methods: A total of 11,050 non-depressed participants from wave 4 (2008-2009) of the English Longitudinal Study of Ageing were followed. Sleep quality was self-reported and categorized as good, intermediate, or poor. Depressive symptoms was assessed using the CESD8 scale. Cox proportional hazards models estimated the hazard ratios (HRs) for depressive symptoms, adjusting for demographic, health, and lifestyle factors.

Results: Among 8425 eligible participants, intermediate sleep quality was associated with a 45% lower risk of depressive symptoms (HR = 0.55, 95% CI: 0.43-0.69), and good quality with a 69% lower risk (HR = 0.31, 95% CI: 0.24-0.40). These associations remained significant in sensitivity analyses limited to individuals with normal sleep duration. Stronger protective effects were observed in those aged 60-80 years. Moreover, participants who maintained or improved their sleep quality over time had significantly lower depressive symptoms risks than those whose sleep worsened (HR = 0.64 and HR = 0.58).

Conclusion: Better self-reported sleep quality was independently associated with a lower risk of depressive symptoms in older adults. While causality cannot be inferred, these findings highlight sleep quality as a potentially modifiable target for depression prevention in ageing populations.

Background: Synergistic health risks may arise from co-exposure to polybrominated diphenyl ethers (PBDEs) and metals, yet evidence on their joint associations with depression in adults is limited.

Objectives: We examined individual and joint effects of PBDEs and metals on depression risk in adults.

Methods: Data were drawn from the National Health and Nutrition Examination Survey (NHANES, 2005-2016), and 5872 adults were included in the analysis. Associations between individual PBDEs, five metals (cadmium, lead, mercury, calcium, and iron), and depression were assessed using multivariable logistic regression and Restricted Cubic Splines (RCS). Mixture effects were assessed using Weighted Quantile Sum (WQS) regression and Bayesian Kernel Machine Regression (BKMR).

Results: Higher cadmium exposure was linked to increased depression risk (adjusted odds ratio [adj. OR] = 2.55, 95% confidence interval [CI]: 1.84-3.54), whereas mercury was inversely associated (adj. OR = 0.60, 95% CI: 0.45-0.79). Most PBDE congeners showed no linear associations, though BDE28 exhibited an inverted U-shaped dose-response. The PBDE mixture alone was not associated with depression risk. In contrast, the joint PBDE-metal mixture was linked to significantly increased depression risk in both WQS and BKMR models, with BDE209, cadmium, and calcium as predominant contributors. In addition, stronger associations were observed among women, non-Hispanic Whites, and individuals with lower body mass index (BMI).

Conclusions: Co-exposure to PBDEs and metals was correlated with higher depression risk in U.S. adults, with susceptible subgroups identified by gender, race, and BMI. These findings underscore the importance of considering joint pollutant effects on mental health and prevention strategies.

Background: Psilocybin-assisted therapy has emerged as a promising treatment for major depressive disorder, but little attention has been paid to the psychotherapy that adjoins psilocybin. Providing an adjunctive psychotherapy that is manualized and evidence-based may make psilocybin treatment more acceptable, effective, and disseminable. We examined the acceptability, feasibility, and clinical outcomes of psilocybin paired with cognitive behavioral therapy (CBT) for major depressive disorder.

Methods: Participants were adults with major depressive disorder who presented with at least moderately severe depressive symptoms. All participants underwent psilocybin-assisted CBT (PA-CBT), which consisted of two psilocybin doses (10 mg and 25 mg separated by one month) interspersed with 12 psychotherapy sessions over four months. Participants' depressive symptoms, psychosocial functioning, and cognitive-affective responses were collected at the study's baseline, at the completion of PA-CBT, and three months post-treatment.

Results: Sixteen participants were enrolled, and all were retained through the 7-month study. PA-CBT was rated as highly acceptable by participants and study clinicians, with no serious adverse events reported. Based on independent assessments, 13 of 16 participants showed at least moderate (≥ 25%) improvement in depressive symptoms by the end of treatment, and 9 had fully remitted. Pre-to-post treatment improvements in depressive symptoms and psychosocial functioning were sustained at the 3-month follow-up (Hedges' gs = 1.9-2.7). Changes in depressive severity during the treatment were associated with improvements in emotion regulation and positive and negative cognitive schemas.

Conclusions: CBT appears to be a feasible, well-accepted, and beneficial adjunct to psilocybin treatment. Future randomized trials are needed to compare the efficacy of PA-CBT with other psilocybin-assisted therapy modalities.