Journal of affective disorders最新文献

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

Methods: Participants were adults with moderately severe or severe depressive symptoms who were enrolled in psilocybin-assisted CBT (PA-CBT). Treatment consisted of two psilocybin doses (10 mg and 25 mg separated by one month) interspersed with 12 psychotherapy sessions in 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 at 3-months post-treatment.

Results: Sixteen participants 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 showed at least moderate (≥ 25%) improvement by 3 months, and 9 had fully remitted. Pre-to-post treatment improvement in depressive symptoms and psychosocial functioning were sustained at a 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 cognitions.

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 psilocybin-assisted therapy that contains more minimal psychotherapy.

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 PBDEs 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: Major depressive disorder (MDD) and bipolar depression (BD) are common mood disorders with overlapping clinical features, posing significant challenges for accurate diagnosis and effective treatment. Electroencephalography (EEG) microstates reflect transient, quasi-stable patterns of brain activity that index fast, large-scale neural network dynamics and may provide novel insights into the neural abnormalities associated with mood disorders.

Methods: In this study, 210 participants (78 MDD, 45 BD, and 87 healthy controls) completed demographic, clinical, and microstate assessments. Resting-state EEG microstate features were analyzed and used in machine learning models to classify MDD versus BD, MDD versus HCs, and BD versus HCs.

Results: MDD patients showed higher microstate C metrics, lower microstate D metrics, increased transition probabilities from B to C, and reduced transition probabilities between B and D, suggesting enhanced sequential activation from the occipital visual cortex to the default mode network but disrupted sequential activation from the visual cortex to the executive control network. BD patients primarily showed significantly longer microstate B duration, indicating excessive visual network activity. Microstate-based machine learning models showed moderate to good discriminative performance, with Area Under the Curve (AUC) values of 83.4% (MDD versus BD), 86.0% (MDD versus HCs), and 93.3% (BD versus HCs).

Limitations: The modest sample size may restrict generalizability, and refined methodological approaches could further enhance classification performance.

Conclusions: These findings provide preliminary insight into neural alterations in MDD and BD, suggest potential diagnostic relevance of EEG microstates, and may inform future hypothesis-driven research on disorder-specific interventions.

This study examined whether sociodemographic and higher-risk psychiatric characteristics predicted whether college students sought a referral to mental health care through the American Foundation for Suicide Prevention's Interactive Screening Program (ISP). Using data from 63,407 college students across 58 institutions of higher education from 2009 to 2024, natural language processing (NLP) methods were used to classify student-counselor online message exchanges to determine whether students sought a referral to care, with robust agreement between human coders and the NLP model. Logistic regression models were used to examine the relationships between seeking a referral and higher-risk psychiatric and sociodemographic characteristics of ISP participants. Students were more likely to seek a referral if they had a PHQ-9 score ≥ 10 (aOR: 1.55, 95% CI: 1.44-1.66), were not currently in therapy (aOR: 2.02, 95% CI: 1.80-2.28), reported recent self-harm (aOR: 1.13, 95% CI: 1.00-1.26), recent suicidal ideation (aOR: 1.22, 95% CI: 1.12-1.33), a lifetime suicide attempt (aOR: 1.10, 95% CI: 1.00-1.22), and were aged 25+ (aOR: 1.38, 95% CI: 1.29-1.47). Participants identifying as genderqueer (aOR: 0.70, 95% CI: 0.53-0.91), Hispanic/Latin(x) (aOR: 0.86, 95% CI: 0.78-0.96), and "other" race and ethnicity (aOR: 0.79, 95% CI: 0.63-0.97) were less likely to seek referrals. Findings underscore the ISP's effectiveness in connecting students with significant mental health challenges to care and ability to bridge gaps in care by facilitating connections to appropriate resources. However, disparities in referral-seeking among genderqueer, Hispanic/Latin(x), and participants of "other" races and ethnicities highlight the need for further work to address factors that might discourage help-seeking.

Purpose: Mother or newborn admission to intensive care units (maternal ICU [MICU] or neonatal ICU [NICU]) is one of the most significant sources of psychological stress during the postpartum period. This cross-sectional observational study aimed to evaluate the effect of intensive care exposure on maternal anxiety, depression, and mother-infant attachment.

Methods: Mothers were allocated to four groups according to ICU admission: MICU only (n = 28), NICU only (n = 69), combined MICU + NICU (n = 46), and control (n = 64). All assessments were conducted within the first postpartum week, prior to discharge. Psychological health was assessed using the Beck Anxiety Inventory (BAI), Beck Depression Inventory-II (BDI-II), and Edinburgh Postnatal Depression Scale (EPDS). Mother-infant attachment was assessed using the Maternal Attachment Inventory (MAI). Group comparisons were performed using the Kruskal-Wallis test.

Results: A total of 207 mothers were included. All ICU-exposed groups had significantly higher anxiety, depression, and postpartum depression scores and significantly lower maternal attachment scores compared with controls (all p < 0.001). In the combined MICU + NICU group, all mothers had high anxiety, most had depression, and the majority met criteria for postpartum depression and scored in the lowest MAI scores. This group also had the lowest breastfeeding rate.

Conclusions: Maternal or neonatal ICU admission was strongly associated with substantial postpartum psychological morbidity, with an additive effect observed in the combined MICU + NICU group. Maternal critical illness may be associated with disrupted early maternal-infant bonding in addition to the effects of neonatal illness.

Background: Major depressive disorder (MDD) is a leading cause of global disability and poses a substantial public health burden. However, current diagnostic approaches largely rely on subjective assessments and lack the ability to integrate heterogeneous clinical and sociodemographic information. Recent advances in large language models (LLMs) offer new opportunities to support MDD diagnosis through reasoning over complex data, yet their clinical applicability is constrained by challenges related to interpretability, hallucinations, and reliance on synthetic data.

Methods: We propose MDD-Thinker, an LLM-based diagnostic system that integrates supervised fine-tuning (SFT) and reinforcement learning (RL) to enhance reasoning and interpretability under the evaluated conditions. Using the UK Biobank dataset, we constructed 40,000 structured reasoning samples and incorporated an additional 10,000 records from publicly available mental health datasets. MDD-Thinker was trained on these heterogeneous textual data and evaluated against conventional machine learning models, deep learning methods, and representative LLM baselines in terms of diagnostic performance and interpretability.

Results: MDD-Thinker achieved high performance in MDD diagnosis, with an accuracy of 0.8268 and an F1-score of 0.8081, showing better performance than conventional machine learning models, deep learning approaches, and representative LLM baselines on the evaluated dataset. Beyond predictive accuracy, it consistently produced structured reasoning paths that were clinically coherent, enabling transparent interpretation of diagnostic decisions in the evaluated experiments. The integration of SFT and RL contributed to notable improvements in both diagnostic reliability and reasoning quality.

Conclusion: MDD-Thinker demonstrates the potential of reasoning-enhanced LLMs for large-scale MDD diagnosis under the evaluated settings. By jointly optimizing accuracy, interpretability, and efficiency, the proposed system provides a scalable and explainable approach for intelligent psychiatric assessment within the scope of the study, highlighting the potential of reasoning-oriented LLMs in mental health care.

Objective: To assess the impact of cardiorespiratory fitness (CRF) and muscle strength on depression and individual depression symptoms.

Methods: Mendelian randomisation (MR) analysis was conducted in up to 341,326 participants of European ancestry from UK Biobank (aged 37-73 years). Genetic variants from previous genome-wide association studies (GWAS) of CRF and grip strength (to proxy overall muscle strength) were utilised to instrument exposures. A broad depression phenotype based on self-report and hospital records, as well as individual measures of depression symptoms from the Patient Health Questionnaire-9 (PHQ-9) were used as outcomes. Analysis was repeated stratifying by sex and using summary statistics from a major depressive disorder (MDD) GWAS.

Results: There was no clear evidence for association between CRF and any depression outcome. There was robust evidence suggesting greater grip was associated with lower odds of broad depression (OR per 0.1 kg increase in weight adjusted grip: 0.86, 95% CI:0.80,0.93), as well as the PHQ-9 items appetite changes (OR:0.56, 95% CI:0.49,0.65), and anhedonia (OR:0.79, 95% CI:0.69,0.90), a core symptom of depression. There was also some evidence for associations between greater grip and lower odds of depressed mood (OR:0.85, 95% CI:0.74,0.97), psychomotor changes (OR:0.79, 95% CI:0.64,0.97), fatigue (OR:0.83, 95% CI:0.74,0.93) and concentration problems (OR:0.85, 95% CI:0.74,0.98) in the MR-inverse variance weighted analysis. Effects were mostly driven by stronger associations in females and results replicated in the two-sample MR for MDD.

Conclusion: Muscle strength may represent an important modifiable factor for preventing and treating depression and several specific symptoms, including core symptoms such as anhedonia.

Introduction: Sexual minority college students experience elevated discrimination and microaggressions, as well as increased levels of defeat and suicidal ideation (SI). These experiences are believed to be highly variable, but little research has investigated the occurrences of these experiences on a momentary basis in sexual minority college students reporting SI.

Methods: We investigated concurrent and prospective relationships between discrimination (Everyday Discrimination Scale), microaggressions (Sexual Orientation Microaggression Inventory), and defeat in sexual minority college students reporting SI via ambulatory surveys. We hypothesized discrimination and microaggressions would be concurrently and prospectively associated with defeat. Further, due to the importance of examining reverse directional effects when establishing temporal associations, reverse directional models were also examined.

Results: Participants were N = 49 sexual minority college students reporting SI with an average age of 19.27 years who were primarily White, Black, or multi-racial, and bisexual or pansexual, cisgender women. Participants completed M = 41.39 ambulatory responses (SD = 11.85). Results indicate discrimination and microaggressions were concurrently and prospectively associated with defeat. Defeat also prospectively predicted discrimination and microaggressions. There was a significant autoregressive effect of defeat.

Conclusions: Findings suggest discrimination, microaggressions, and defeat may be appropriate intervention targets for sexual minority college students who have experienced recent SI. Further research should investigate these relationships in other minority groups and develop interventions to disrupt self-perpetuating defeat in these individuals.

Objective: Previous studies reported higher suicide mortality in severe autoimmune diseases (SADs). However, few studies have comprehensively assessed the suicide mortality and accidental mortality across different types of SADs and their associations with comorbid psychiatric disorders.

Methods: We utilised the nationwide database of Taiwan from 2003 to 2017, linked with the National Death Registry, to identify 1,164,960 individuals, including 232,992 patients with SADs and 931,968 matched controls. Cox-regression was used to estimate the risks of suicide and accidental mortalities. Subgroup analyses were conducted based on sex, ten specific SAD types, and eight psychiatric comorbidities.

Results: Patients with SAD had a 1.54-fold increased risk of suicide mortality (hazard ratio [HR]: 1.54, 95% confidence interval [CI]: 1.36-1.74) compared to controls. Specifically, individuals with systemic lupus erythematosus (2.04; 1.47-2.83), rheumatoid arthritis (1.57; 1.25-1.96), and Sjögren's syndrome (2.32; 1.69-3.18) exhibited higher suicide mortality compared to the controls. The suicide mortality was further higher among SAD individuals with psychiatric comorbidities, including schizophrenia (2.82; 1.94-4.10), major depressive disorder (4.44; 3.79-5.20), and substance use disorder (2.59; 1.74-3.87). Among female patients, comorbid major depressive disorder (5.15; 4.16-6.39), alcohol use disorder (5.17; 2.61-10.24), and substance use disorder (4.50; 2.53-7.99) showed approximately 5-fold increased risk of suicide mortality compared to the controls.

Conclusion: These findings suggest that patients with SADs are at significantly higher risk of suicide, particularly when psychiatric disorders are present. Routine mental health screening and integrated care may be critical in reducing suicide risk in this vulnerable population.