Given its recurrent nature and burden, major depressive disorder (MDD) warrants reliable methods of relapse prediction.

To determine whether actigraphy-derived parameters, measured over 1 to 2 years, are associated with relapse.

This was an observational cohort study with data collection from July 2016 to January 2019. The setting was multicentric. A referred sample of participants from outpatient psychiatric and primary care clinics across Canada were followed up for 1 to 2 years. Participants had a diagnosis of MDD and Montgomery-Åsberg Depression Rating Scale (MADRS) score less than or equal to 14 at baseline.

Actigraphy-derived parameters measured over 1 to 2 years.

The primary outcome was relapse, defined as any of the following: MADRS score greater than or equal to 22 for 2 consecutive weeks, psychiatric hospitalization, emergence of suicidal intent or behavior, or antidepressant treatment escalation-all adjudicated by an independent panel. Continuous actigraphy data were averaged every 2 weeks.

From a referred sample of 102 adults, 93 participants (mean [SD] age, 39.1 [12.7] years; 58 female [62%]) contributed approximately 32 000 complete actigraphy days (median, 46 weeks). In Cox models adjusted for age, sex, season, and baseline MADRS score, baseline lower sleep regularity (hazard ratio [HR], 0.46; 95% CI, 0.28-0.74; P = .002), lower relative amplitude (RA; HR, 0.45; 95% CI, 0.29-0.70; P < .001), lower sleep efficiency (HR, 0.57; 95% CI, 0.38-0.85; P = .005), higher wake after sleep onset (HR, 1.77; 95% CI, 1.12-2.80; P = .01), and higher nighttime activity (HR, 1.86; 95% CI, 1.32-2.62; P < .001) were associated with relapse. In time-varying models, greater composite phase deviation (HR, 1.76; 95% CI, 1.04-2.98; P = .04) and lower RA (HR, 0.45; 95% CI, 0.21-0.97; P = .046) were associated with relapse, with RA remaining significant even after adjusting for concurrent MADRS scores (HR, 0.60; 95% CI, 0.36-0.98; P = .04). Actigraphy significantly differentiated individuals experiencing relapse from those with an ultrastable (MADRS score <14 throughout) and unstable (transient MADRS score, 14-22 without relapse) clinical course.

Actigraphy measures of sleep phase variability and daily activity amplitude were associated with depressive relapse, supporting actigraphy as a potential scalable biomarker to identify high-risk individuals and enable timely, personalized relapse prevention in MDD.

Psychiatric comorbidities increase the risk of migraine disease progression. These post hoc analyses explored whether self-reported psychiatric comorbidities at screening had an impact on the short- and long-term efficacy of eptinezumab in the DELIVER trial.

DELIVER was a multinational trial that evaluated eptinezumab in adults with migraine with 2-4 prior preventive treatment failures. Participants were initially randomized to intravenous eptinezumab 100 mg, 300 mg, or placebo every 12 weeks. Participants receiving placebo during the 24-week double-blind placebo-controlled period were switched to eptinezumab 100 mg or 300 mg for the 48-week dose-blinded extension, while those initially randomized to eptinezumab continued their assigned dose. Subgroups included participants self-reporting a psychiatric condition at screening, within which participants self-reporting a depressive condition at screening were also analyzed. Outcomes were changes from baseline in monthly migraine days (MMDs), ≥ 50% migraine responder rates (MRRs), and participants who improved per Patient Global Impression of Change (PGIC; much or very improved). As post hoc analyses, no p-values were generated.

Of the total population, 122/890 (13.7%) self-reported ≥ 1 psychiatric comorbidity, including 68/890 (7.6%) who self-reported depression. The mean change from baseline in MMDs over Weeks 1-12 in the psychiatric comorbidity subgroup was - 4.6 with eptinezumab versus - 0.9 with placebo, with similar mean changes observed in those with comorbid depression (eptinezumab, - 4.7; placebo, 0.0). In the psychiatric comorbidity subgroup, ≥ 50% MRRs over Weeks 1-12 were higher with eptinezumab (42%; odds ratio [OR] vs placebo = 25.3) than with placebo (3%), as were the proportions of participants with PGIC improvement (eptinezumab, 60%, OR = 6.7; placebo, 19%). During the extension period, participants switching from placebo to eptinezumab reported similar improvements to the eptinezumab-eptinezumab group, with similar outcomes in the subgroups with psychiatric comorbidities.

Psychiatric comorbidities, including depressive conditions, did not appear to impact the short- or long-term efficacy of eptinezumab in participants with migraine for whom 2-4 prior preventive treatments had failed.

EudraCT (2019-004497-25); ClinicalTrials.gov (NCT04418765).

In this study, we systematically review and synthesize the evidence on the association between central serous chorioretinopathy (CSC) and personality types, and quantify the relationship between Type A behaviour and CSC. We systematically searched 12 literature databases on 5 October 2025 for studies in which personality types were evaluated in patients with CSC. Data extraction and risk-of-bias assessment followed standardized protocols. Studies were reviewed qualitatively. Random-effects meta-analysis was performed for the association between Type A behaviour and CSC. Twelve studies of 2176 participants (949 patients with CSC, 1227 controls) were included. Across studies, patients with CSC exhibited personality profiles marked by time urgency, competitiveness, emotional tension and maladaptive affect regulation, including higher neuroticism-anxiety, aggression-hostility and alexithymia scores. A significant association was found between Type A behaviour and CSC (pooled OR 3.43; 95% CI 1.94-6.07; p = 0.00002) in the four studies that evaluated this relationship. Sensitivity analysis confirmed robustness of the association. In conclusion, certain personality traits, particularly Type A behaviour, are associated with CSC. The relationship between personality and CSC appears biologically plausible given the role of stress-related hypothalamic-pituitary-adrenal axis activation and elevated cortisol levels, both recognized in CSC pathophysiology. However, complex biopsychosocial interactions without a direct causal pathway may also be the case. Understanding psychological predispositions may contribute to a more comprehensive view of CSC risk and care. Further longitudinal and mechanistic studies are warranted.

The study evaluated the effectiveness of a resilience training for dental students as a preventive measure for mental health and stress management, with consideration for its long-term integration into dental education.

A 2-day online resilience training was tailored to address specific stressors experienced by dental students in Munich, Germany. Data were collected via online questionnaires from both participants (pre and posttraining) and nonparticipant controls over a 6-month period. Outcomes included resilience development, health behaviour, perceived stress and life satisfaction, utilising an online questionnaire. Statistical analysis (t-tests and mixed ANOVA) was performed using IBM SPSS Statistics.

Training participants showed significantly increased resilience F(1.54) = 4.93, p = 0.031, η² = 0.084 (medium effect), reduced subjective stress and higher overall satisfaction. Qualitative feedback indicated enhanced social support, though the effect on physical health behaviour remained inconclusive. Differences in resilience and satisfaction were observed between preclinical and clinical students, and between sexes.

This resilience training demonstrated preventive benefits for dental students' mental health. Limitations include selection bias, self-reported measures, lack of long-term data and confounding societal influences. Integrating such training into dental curricula may be a valuable strategy with potential for broader application in other institutions as well.

Primary immune thrombocytopenia (ITP) is an autoimmune bleeding disorder with complex immunopathogenesis. Its major symptoms, such as bleeding tendency and fatigue, may predispose patients to depression and anxiety. Although psychiatric comorbidities are increasingly recognized in ITP management, whether ITP causally contributes to these conditions remains unclear.

We conducted a two-sample Mendelian randomization (MR) study to investigate the potential genetically causal links between ITP and depression/anxiety. To ensure robustness, complementary MR approaches were performed, including pleiotropy-robust methods (MR-Corr and MRMix), multivariable MR adjusting for inflammatory biomarkers (C-reactive protein and interleukin-6), the robust adjusted profile score (RAPS) model, reverse MR, and colocalization analysis.

MR analysis revealed a positive causal effect of ITP on depression (OR = 1.007, 95% CI: 1.001-1.013; p = 0.014), whereas no genetic predisposition of ITP on anxiety was observed. Multivariable and pleiotropy-robust sensitivity analyses supported the stability and consistency of the ITP-depression association, indicating that the result was unlikely driven by pleiotropy, instrument weakness, or inflammatory confounding.

These findings provided novel genetic evidence supporting ITP-associated mental health issues and highlighted the importance of integrated psycho-hematological interventions for ITP in clinical practice. Future research was needed to elucidate the biological underpinning between ITP and psychiatric disorders, which might provide more options for ITP patients to improve life quality.

The Centiloid scale is the standard for amyloid (Aβ) PET quantification in research and clinical settings. However, variability between tracers and scanners remains a challenge.

This study introduces DeepSUVR, a deep learning method to correct Centiloid quantification, by penalizing implausible longitudinal trajectories during training. The model was trained using data from 2,129 participants (7,149 Aβ positron emission tomography [PET] scans) in the Australian Imaging, Biomarkers and Lifestyle Study of ageing (AIBL)/Alzheimer's Disease Neuroimaging Initiative (ADNI) and validated using 15,807 Aβ PET scans from 10,543 participants across 10 external datasets.

DeepSUVR increased correlation between tracers, and reduced variability in the Aß-negatives. It showed significantly stronger association with cognition, visual reads, neuropathology, and increased longitudinal consistency between studies. DeepSUVR also increased the effect size for detecting small treatment related slowing of amyloid accumulation in the A4 study.

DeepSUVR substantially advances Aβ PET quantification, outperforming all standard approaches, which is particularly important for clinical decision making and to detect subtle or early changes in Aβ.

Novel artificial intelligence (AI)-method that penalizes biologically implausible longitudinal trajectories, enabling the model to learn standardized uptake value ratios (SUVR) correction factors without requiring longitudinal data at inference time. Improves Centiloid consistency across tracers and studies, significantly enhancing cross-sectional and longitudinal amyloid positron emission tomography (PET) quantification. DeepSUVR-derived Centiloids show stronger associations with cognition, visual reads, and neuropathology. Longitudinal variability is reduced three- to five-fold, enabling more reliable tracking of amyloid accumulation and better detection of treatment effects. Novel reference and target masks derived from DeepSUVR replicate most of the model's performance, offering a practical alternative for integration into existing pipelines.

Inpatient treatment aimed at weight restoration and psychiatric stabilization is often required for individuals with anorexia nervosa (AN). This study aimed to identify distinct trajectories of change in body mass index (BMI) and depressive symptoms during inpatient treatment, examine clinical predictors and outcomes, and test reciprocal associations between BMI and depressive symptom changes.

Weekly BMI and depressive symptom data were collected from 156 inpatients with AN (mean treatment duration = 11.6 weeks). Growth mixture modeling identified trajectory classes. Baseline clinical variables were examined as predictors, and discharge outcomes were compared across classes. A joint Bayesian growth model was used to examine longitudinal associations between BMI and depressive symptoms.

Three BMI trajectories were identified: steady increase (58.3%; higher baseline BMI with consistent gains), gradual weight gain (28.9%; low baseline BMI with steady gains), and rapid response (12.8%; low baseline BMI with early rapid gain followed by slowing or decline). Two depressive symptom trajectories emerged: severe-stable and moderate-improving. The severe-stable group was predicted by higher trauma-related comorbidity (OR 11.11, p = 0.009) and eating psychopathology (OR 3.23, p < 0.001). Depressive symptom class was associated with initial BMI but not BMI change, while BMI classes predicted the curvature of depressive symptom trajectories. No credible week-to-week associations emerged between BMI and depressive symptom changes.

Findings highlight substantial heterogeneity in treatment response. Rapid early weight gain in patients with extremely low BMI and high severity may not indicate sustained improvement. Persistent depressive symptoms, especially in those with trauma histories, underscore the need for trauma-informed care alongside weight restoration.

[This corrects the article DOI: 10.3389/fpsyt.2025.1595131.].

Eating disorders (EDs), particularly Anorexia Nervosa (AN), remain one of the most severe and treatment-resistant eating disorders, with high relapse rates and limited pharmacological options. While second-generation antipsychotics and antidepressants are commonly prescribed as adjuncts to nutritional rehabilitation, their real-world impact on weight restoration and psychopathological symptom severity remains unclear.

We conducted a prospective, naturalistic observational study of 127 inpatients diagnosed with restrictive anorexia nervosa (AN-r), binge-purge anorexia nervosa (AN-bp), or bulimia nervosa (BN). BMI and weekly psychopathological symptom burden were systematically monitored throughout a ten-week inpatient treatment program. Psychopharmacological treatments were recorded in real time, and the Average Morbidity Index (AMI), adapted from the Life Chart Methodology, was computed weekly as a prospective measure of clinical severity. Generalized Linear Models assessed the associations between specific drug classes and changes in BMI and AMI.

Patients treated with mood stabilizers (e.g., Carbamazepine, Lithium) showed a smaller BMI increase compared to other groups (Coef. = -0.96 to -1.70; p< 0.05), suggesting a potential weight-stabilizing effect. Diazepam use was associated with greater weight gain (Coef. = +2.06; p = 0.02) but no clear benefit on AMI. Several antidepressants (e.g., Sertraline, Escitalopram) correlated with higher AMI scores, indicating less improvement in psychopathological symptom burden. Atypical antipsychotics (e.g., Olanzapine, Aripiprazole) were linked to greater reductions in AMI.

Prospective monitoring of BMI and AMI revealed differential associations between psychopharmacological agents and both nutritional and symptomatic trajectories in an inpatient ED cohort predominantly composed of patients with AN. Mood stabilizers were associated with smaller BMI increases, while several antidepressants corresponded to less improvement in psychopathological symptom burden. Atypical antipsychotics showed the strongest prospective reductions in AMI. These findings highlight the value of prospective, real-world monitoring to inform pharmacological strategies in treatment-resistant eating disorders.