European Neuropsychopharmacology

Evidence-based psychotherapies are first-line treatments for psychiatric disorders, yet response rates remain suboptimal. Noninvasive brain stimulation (NIBS) may augment psychotherapy by modulating treatment-engaged circuits. We conducted a systematic review and meta-analysis of randomized controlled trials comparing active NIBS plus evidence-based psychotherapy versus sham NIBS plus psychotherapy. Following Cochrane methods, we searched six databases through February 2025, screening 1,017 records. Twenty-eight trials (31 treatment arms; 1,506 participants) met inclusion criteria. Active NIBS combined with psychotherapy produced significantly greater symptom improvement than sham NIBS with psychotherapy (standardized mean difference = -0.38, 95% confidence interval [-0.68, -0.08]), with substantial heterogeneity. Moderator analyses revealed critical implementation parameters: repetitive transcranial magnetic stimulation (rTMS) showed significant benefit while transcranial direct current stimulation did not. Non-concurrent delivery--stimulation before or after psychotherapy sessions--was significantly effective, whereas concurrent administration was not. Among psychotherapy modalities, cognitive behavioral therapy combined with NIBS produced significant benefit. Human-delivered psychotherapy, but not computerized formats, significantly enhanced outcomes. By diagnosis, significant effects were observed only for anxiety disorders. Secondary analyses revealed significant anxiety symptom reduction specific to rTMS. Treatment integrity was under-reported: only 39.3% of studies used fully manualized protocols and 10.7% documented therapist adherence. Non-concurrent rTMS paired with human-delivered, manualized cognitive behavioral therapy emerges as the most effective strategy, particularly for anxiety disorders. These findings provide an evidence-based framework for optimizing combined treatment protocols and highlight the need for standardized psychotherapy fidelity monitoring in future trials.

BackgroundThe Antidepressant Medications: Biology, Exposure & Response (AMBER) research programme was established to investigate the biological mechanisms underlying antidepressant action and variability in treatment response. Generation Scotland holds detailed genomic, clinical, and health information with recontacting consent, making this cohort ideal for investigating these aims. MethodsWe deployed a questionnaire, developed with input from a Lived Experience panel, to the Generation Scotland cohort to gather data on their depressive symptoms, medication history, efficacy, and side effects to develop clinically meaningful phenotypes of antidepressant response. Invitations were sent to 15,117 Generation Scotland participants who were 18 years or older and consented to be recontacted. Between July and November 2025, 1,180 participants with a history of antidepressant treatment for depression completed the questionnaire. ResultsThe sample was predominantly female (78.1%), self-identified as White (98.6%), and older (median age 57 years) than the wider Generation Scotland cohort (median 49 years) and Scottish population (median 41.3 years). Participants reported heterogeneous depressive symptom profiles spanning mood, anxiety, cognitive, sleep, behavioural, and physical domains. One-third of participants (31.1%) had taken three or more different antidepressants. Selective serotonin reuptake inhibitors (SSRIs) were the most common class (89.1%). Using self-reported treatment duration, discontinuation patterns, and efficacy, we developed a stringent classification system to capture treatment response extremes, where 23.8% were classified as responders and 1.5% as non-responders, with the majority unclassified. ConclusionsQuestionnaire data will be linked with electronic health records to validate antidepressant response classifications. Following validation, 25 responders and 25 non-responders will provide biological samples for DNA methylation profiling and generation of patient-derived cell lines. These models will be exposed to SSRIs to identify gene expression signatures and biological pathways distinguishing treatment response, integrating with genomic and clinical data across the AMBER project. These findings will provide a valuable resource for future antidepressant response research. Plain Language SummaryDepression is a common mental health condition affecting millions of people worldwide. Antidepressant medications are the primary medication treatment, but response is highly variable with only about one-third of individuals achieving full symptom remission after their first medication trial. We dont fully understand why some people respond well while others dont. To help answer this question, the Antidepressant Medications: Biology, Exposure & Response (AMBER) research programme was established. This study utilised the Generation Scotland cohort, a large health study in Scotland. Between July and November 2025, we invited 15,117 Generation Scotland participants to complete a detailed questionnaire about their experiences with antidepressant medications. A total of 1,180 participants answered detailed questions about their depression symptoms, which medications they tried, how long they were on a medication, how well the medications worked, and what side effects they experienced. We found that peoples experiences with depression and antidepressants varied considerably. About one-third had tried three or more different antidepressants. Using strict criteria based on treatment duration, effectiveness ratings, and medication changes, we identified 281 people (24%) who responded very well to SSRIs (the most common type of antidepressant) and 18 people (1.5%) who did not respond despite trying multiple SSRIs. A key limitation is that all information was self-reported, so we will validate findings by linking questionnaire responses with medical records. In the future, we will collect blood samples from some participants to study the biological differences between responders and non-responders. This research will help us better understand why antidepressants work for some people but not others, which could lead to more personalised treatment approaches for depression.

Background At present, there are no approved pharmacological treatments for people at clinical high risk for psychosis (CHR-P). We sought to assess the acceptability of cannabidiol (CBD): a promising candidate treatment for this population. Methods CHR-P individuals completed a survey which assessed their views on the acceptability of CBD, its expected effectiveness and side effects, and on formulation preferences. Results The sample comprised 55 CHR-P individuals (24.3 years and 69% female). Most (91%) were familiar with CBD, and had previously used cannabis (64%), and around half (42%) had tried over-the-counter CBD. 75% were willing to take CBD as an intervention for mental health problems. Most participants anticipated fewer side effects with CBD than with existing medications, and preferred tablet or capsule formulations over liquids. Discussion CBD is perceived as a highly acceptable treatment among CHR-P individuals.

BackgroundIn 2020, Oregon became the first U.S. state to establish a regulated framework for adults to access psilocybin services using naturally-derived mushroom products. No studies have examined mental health outcomes among individuals receiving psilocybin in this context. AimsTo evaluate changes in self-reported symptoms of depression, anxiety, and well-being 30-days post-psilocybin session under the Oregon state-regulated model , and document session-related adverse events and doses consumed. MethodsThis was a naturalistic study (March 2024-April 2025) among adults [&ge;]21 years participating in a legal psilocybin services program. Online surveys were completed pre-session, 1-day, and 30-days post-session. Primary outcomes were change in depression, anxiety, and well-being symptoms pre-session to 30-days post-session evaluated using linear mixed-effects models (random effect: timepoint; fixed effects: sex, concurrent psychiatric medication use, age, session dose [total psilocybin equivalents, TPE, mg: psilocybin mg + 1.39 * psilocin mg]). Adverse events (e.g., hallucinogen persisting perception disorder [HPPD]) were assessed at 1-day and 30-days post-session. ResultsParticipants (n=88; median age 43 years; 52% male) were predominantly Oregon residents (53.4%), psychedelic-experienced (64.8%), and concurrently using psychiatric medication (46.6%). All outcomes improved significantly at 30-days post-session (p<0.001), including in sensitivity analyses stratified by concurrent psychiatric medication usage (p<0.001 all outcomes, both groups). Two participants (2.3%) reported symptoms consistent with HPPD at 1-day post-session, but none at 30-days. Mean dose was 27.8 mg (SD 8.2) TPE. ConclusionsPsilocybin sessions delivered under the Oregon regulatory model were associated with clinically meaningful improvements in depression, anxiety, and well-being 30-days post-session, supporting therapeutic effectiveness of legal psilocybin services.

Deficits in inhibitory control are common across a wide range of psychiatric disorders and are closely linked to symptom severity, including emotional dysregulation, anxiety, substance misuse, and self-harm, making them an appealing target for intervention. Cognitive training offers a low-cost, scalable, and non-invasive strategy to strengthen inhibitory control; however, most existing paradigms target only a single facet of inhibition and rarely account for environmental influences, such as affective context. To address these gaps, we developed a computerized inhibitory control training paradigm to simultaneously engage three components of inhibition: preemptive, proactive, and reactive, while embedding trials within positive and negative affective contexts to assess the impact of emotional stimuli. Across two online experiments, participants completed the GAMBIT task in one session (Experiment 1, N = 300) or repeated over three sessions (Experiment 2, N = 65). The task included No-Go trials to train preemptive inhibition, stop-signal trials for reactive inhibition, and stop-signal anticipation trials to train proactive inhibition. Affective images of differing valence were presented as background stimuli to evaluate their impact on inhibitory performance. In Experiment 1, participants showed higher accuracy on No-Go versus reference Go trials ({beta}=1.45, SE=0.09, p<.001), confirming successful manipulation of preemptive inhibition. Reaction times were slower during anticipation trials across two different conditions ({beta}=0.16, SE=0.04, p<.001; {beta} = 0.07, SE = 0.04, p = 0.047), consistent with proactive slowing when anticipating a potential stop signal. Additionally, positive affective images ({beta} = 0.10, SE= 0.009, p < 0.001) further slowed RTs, indicating emotional interference with proactive control. In Experiment 2, the pattern of higher No-Go accuracy was replicated ({beta} = 0.91, SE = 0.11, p < .001) and accuracy generally improved over sessions ({beta} = 0.38, SE = 0.06, p < .001). In anticipation trials, RTs become shorter across sessions (session 2: {beta} = -0.25, SE = 0.06, p < .001; session 3: {beta} = -0.45, SE = 0.06, p < .001), reflecting practice-related gains, and SSRTs decreased over time (F(2,56) = 6.26, p = .004), consistent with enhanced reactive inhibition. Proactive inhibition was modulated by affective images, with both negative ({beta} = 0.04, SE = 0.02, p = .039) and positive ({beta} = 0.16, SE = 0.02, p < .001) affective images associated with slower RTs. Participants also reported reductions in self-assessed temper control by the last session (W = 25.5, p = .007, q = .037, d = -0.51) and usability ratings were high (all means [&ge;] 3.87/5). Together, these findings show that this paradigm recruits multiple forms of inhibitory control and yields training-related improvements in both performance and affective outcomes. This provides preliminary validation of a scalable, fully online inhibitory control training tool targeting multiple dissociable inhibitory processes within affective contexts. The approach holds promise as an accessible transdiagnostic intervention to support symptom improvement across psychiatric disorders, with future work needed to evaluate clinical efficacy in patient populations.

BackgroundWhile commonly accepted depressive subtypes reflect phenotypic differences, there has been minimal progress in identifying discrete pathophysiological pathways, biomarkers or differential therapeutic approaches which effectively guide clinical management. AimsTo test the biological validity and clinical utility of a circadian subtype of depression on the basis of clinical course, differential medication response (self-reported) and genetic risk profile. MethodsCross-sectional data were drawn from the nationwide, genetically-informative Australian Genetics of Depression Study. Participants were classified as having a "circadian" versus "non-circadian" subtype of depression on the basis of meeting criteria for at least three binary circadian features: social jetlag, seasonality, delayed sleep midpoint, evening chronotype, sleep inertia, and hypersomnia. Clinical course characteristics were compared. Associations with response to commonly prescribed antidepressants and polygenic risk scores (PGS) for mental disorders and sleep, circadian, metabolic and inflammatory traits, were investigated using logistic regression models. Results2,604 participants (23%; 80% females; mean age=37.87{+/-}13.62) had a circadian subtype. These cases reported an earlier age of onset (p<0.001), more severe clinical features including hypo/manic-like and psychotic-like experiences, suicidality, psychological distress and somatic complaints (ps<0.001), weight gain during depressive episodes (p<0.001), poorer response to SSRIs (OR=0.88 [0.82, 0.94]) and SNRIs (OR=0.89 [0.83, 0.97]) and more side-effects, compared to those with a non-circadian subtype. Having a circadian subtype was associated with higher PGS for attention-deficit/hyperactivity disorder (OR=1.11 [1.06, 1.17]), major depression (OR=1.11 [1.06, 1.16]), bipolar disorder (OR=1.09 [1.04, 1.14]), body mass index (OR=1.09 [1.05, 1.14]), triglycerides (OR=1.10 [1.06, 1.16]), interleukin-6 (OR=1.08 [1.03, 1.13]), higher insulin resistance (OR=1.08 [1.04, 1.13]), later sleep midpoint (OR=1.15 [1.10, 1.21]), insomnia (OR=1.08 [1.03, 1.13]), and later chronotype (OR=0.68 [0.65, 0.71]). ConclusionThese findings support the face validity and potential clinical utility of circadian subtype of depression as a clinical profile. Pending independent replication, investigation of its biology and predictive utility are warranted.

Opioid use disorder (OUD) is characterized by compulsive drug seeking and impaired executive control arising from maladaptive plasticity within cortico-striatal circuits. While transcriptomic studies have identified coding gene alterations in the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC), the contribution of the noncoding genome remains poorly defined. Here, we performed integrative transcriptomic analysis of postmortem human NAc and DLPFC to systematically identify and characterize long noncoding RNAs (lncRNAs) in OUD. We identified 36,225 lncRNA loci expressed across reward and executive regions, approximately half of which were previously unannotated. OUD was associated with widespread lncRNA dysregulation in NAc and DLPFC, with lncRNA-centered co-expression modules enriched for neuroimmune signaling, phosphorylation-dependent synaptic pathways, and intracellular receptor cascades. Notably, OUD disrupted circadian rhythmicity of lncRNAs to a degree comparable to or exceeding mRNAs, implicating temporal reorganization of noncoding networks in addiction pathology. Integration with single-nucleus transcriptomic data revealed pronounced neuronal and glial cell type specificity among OUD-associated lncRNAs. Together, these findings demonstrate that lncRNAs represent a critical regulatory layer in reward and executive circuits and suggest that spatial, temporal, and cellular remodeling of the noncoding transcriptome contributes to circuit dysfunction in OUD.

BackgroundThe present study examines the link between DNA methylation at the nerve growth factor-induced protein A (NGFI-A) binding domain of the NR3C1 1F promoter and later cognitive functions in children from families living in disadvantaged psychosocial conditions. MethodsParticipants were 132 children who took part in a Swiss Parents as Teachers (PAT) randomized controlled trial (72 in the intervention group, 60 in the control group). DNA methylation was quantified from saliva samples collected at age three using sodium bisulfite next-generation sequencing (NGS). Cognitive functions were assessed at age five using the SON-R 2.5-7 Intelligence Test. Results(a) DNA methylation at age three predicted lower IQ at age five through increased concentration problems; (b) participation in the three-year PAT program predicted lower methylation levels at the end of the intervention; and (c) early life stressors predicted lower IQ through increased methylation and concentration problems with descriptively stronger effects in the control group. ConclusionsThese findings demonstrate a link between early DNA methylation at the NGFI-A binding site of the NR3C1 1F promoter and later cognitive functions in children and highlight the role of early life stressors and the PAT intervention in shaping these associations.

Hypothalamic-pituitary-adrenal axis (HPA axis) dysregulation is a risk factor for poor mental and physical health. Animal studies indicate that DNA methylation may be one mechanism through which stress can influence the function of the HPA axis, however human studies have not identified consistent individual loci. Machine learning can be used to develop methylation profile scores (MPSs), but this method has not yet been applied to HPA axis function. Using a novel machine learning pipeline, we developed an MPS to predict the salivary cortisol response (AUCi) to the Trier Social Stress Test (TSST) from whole blood Illumina Infinium HumanMethylation 450K BeadChip data (N = 84, mean age = 34, 49% female). The MPS was associated with the cortisol response in an independent, cross-tissue cohort (N = 53, mean age = 20, 51% female), both before ({beta} = 0.33, 95% CI [0.09, 0.54]) and after a social stressor ({beta} = 0.3, 95% CI [0.09, 0.47]). Functional characterisation revealed several immune, stress, and disease-related pathways and genes, including tolerance induction to self antigen, chronic myeloid leukemia, NR3C2, and PSMB4 (putatively causal in depression). We have developed and validated a novel epigenetic biomarker for stress reactivity, identifying a set of genomic loci where DNA methylation is associated with the cortisol response. Future research could investigate if HPA axis-related MPSs could be used alongside traditional risk factors to improve clinical risk assessment.

BackgroundThe prevalences of suicidal ideation (SI) and suicide attempt (SA) are influenced by genetic, behavioral, and environmental factors. Alcohol use disorder (AUD) and adverse childhood experiences (ACEs) may mediate or moderate genetic liability for suicidality. MethodsUsing data from 10,275 participants (43.8% female; 47.2% African-like genetic ancestry [AFR], 52.8% European-like genetic ancestry [EUR]), we tested whether polygenic scores (PGS) for SI and SA predicted lifetime SI or SA. We also evaluated whether alcohol use disorder (AUD) mediated these associations and whether adverse childhood experiences (ACEs) moderated the direct and indirect pathways. ResultsAlthough there were significant direct associations of the SA PGS with SA (AFR: b = 0.36, SE = 0.01; EUR: b = 0.17, SE = 0.01; both ps < 2e-16), the SI PGS did not predict SI (p > 0.55). AUD mediated SA genetic risk (average causal mediation effect (ACME): AFR = 0.01, 95% CI [0.01-0.01]; EUR = 0.02, 95% CI [0.01-0.02]; both ps < 2e-16). Moderation analyses indicated that indirect effects were attenuated by ACEs score ({Delta}ACME: AFR = 0.02, p < 2e-16; EUR = 0.01, p = 0.03). There was neither mediation nor moderated mediation for SI. ConclusionsGenetic liability to SA operates partly through AUD, particularly among individuals with lower childhood adversity. Under higher adversity, alternative pathways to SA likely predominate. These findings highlight the need to consider distinct etiological pathways to the development of suicidality and the relevance of AUD as a modifiable target for suicide prevention among individuals at high genetic liability.

BackgroundTo clarify the working mechanisms of psychotherapy for obsessive-compulsive disorder (OCD), we studied the neural effects of two psychotherapies: cognitive behavioral therapy with exposure and response prevention (CBT-ERP) and inference-based cognitive behavioral therapy (I-CBT). MethodsFifty-five individuals with OCD completed an emotional processing task during fMRI before and after 20 weekly psychotherapy sessions, using general fear and OCD-related visual stimuli. Forty-two healthy controls performed the task once. We used Bayesian region-of-interest analyses to assess changes in brain activation in prefrontal, limbic, sensory, subcortical, and visual areas, and their association with symptom improvement. ResultsAfter treatment, the CBT-ERP group (N=28) showed strong credible evidence for decreased activation across all brain regions during fear (but not OCD) versus neutral stimuli, especially in treatment responders. Conversely, the I-CBT group (N=27) showed increased activation during fear versus neutral stimuli in the precentral gyrus and lateral occipital cortex (LOC), which correlated with symptom improvement. A similar but weaker pattern was observed for OCD-related stimuli. Across all ROIs, baseline fear-related activity was associated with symptom improvement in CBT-ERP, while lower baseline activity was associated with improvement in I-CBT in, amongst others, the precentral gyrus and dorsolateral prefrontal cortex. Lower baseline LOC activation during OCD-related stimuli was linked to symptom improvement after both psychotherapies. ConclusionsThe results support CBT-ERPs mechanism of fear reduction and I-CBTs mechanism of sensory engagement. Visual brain activity during emotional processing may predict treatment response across psychotherapies.

BackgroundPersonalized pharmacotherapy requires systematic consideration of genetic factors influencing drug efficacy and safety. The accumulation of large-scale whole-exome sequencing (WES) data provides an opportunity to assess population frequencies of clinically significant pharmacogenetic variants; however, the diagnostic applicability of exome data for pharmacogenomics remains insufficiently studied. Materials and MethodsA retrospective analysis of 6,102 anonymized sequencing datasets obtained between 2020 and 2025 was performed using the DNBSEQ-G400 (MGI) platform and Agilent SureSelect Human All Exon v6/v7/v8 enrichment kits. SNV and indel detection, CNV analysis, high-resolution HLA typing, and diplotype assignment for key pharmacogenes were conducted. Pharmacogenomic annotations were derived from PharmGKB (levels of evidence 1A-2B), CPIC, and PharmVar. Additionally, WES limitations and the feasibility of imputing non-coding pharmacogenetic variants were evaluated. ResultsPopulation frequencies of alleles and metabolic phenotypes were determined for 13 Very Important Pharmacogenes (VIPs), along with the distribution of HLA class I and II alleles. The highest allelic and phenotypic variability was observed in CYP family genes, particularly CYP2D6, CYP2C19, and CYP2B6. A total of 663 pharmacogenomic annotations were identified, predominantly related to drug metabolism (50.38%) and toxicity (29.56%), including psychotropic agents, anticoagulants, statins, opioid analgesics, antineoplastic agents, and immunosuppressants. At least 32 drugs require pharmacogenetic testing based on variants located in non-coding regions, as well as accurate CYP2D6 copy number determination. Linkage disequilibrium analysis demonstrated the inability to reliably impute most non-coding pharmacogenetic variants from WES data. ConclusionThese findings represent one of the largest reference assessments to date of pharmacogenetically significant variant and HLA allele frequencies in the Russian population. The results confirm the utility of WES for population pharmacogenomic screening while simultaneously highlighting its fundamental limitations and the need for alternative genetic diagnostic methods in selected cases.

Depression is a common and clinically significant mental health condition among university students, particularly those experiencing academic failure and course repetition, and is associated with adverse effects on cognitive functioning, emotional regulation, and academic performance. This study evaluated the efficacy of an internet-based cognitive behavioural therapy (iCBT) intervention, MoodGYM, in reducing depressive symptoms among repeating undergraduate students at the University of Zambia Ridgeway Campus. A quasi-experimental quantitative study design was employed. Seventy-five repeating undergraduate students with depressive symptoms were enrolled, with 33 assigned to the MoodGYM intervention group and 42 to a control group. Depressive symptom severity was assessed using the Beck Depression Inventory (BDI) at baseline and after an eight-week intervention period. Statistical analyses included within-group and between-group comparisons, difference-in-differences estimation, and fixed-effects regression modelling. At baseline, participants exhibited predominantly moderate to severe depressive symptoms, with no statistically significant differences between the intervention and control groups. Following the eight-week intervention, the MoodGYM group demonstrated a statistically and clinically significant reduction in depressive symptoms, with median BDI scores decreasing from 22 to 16 (p < 0.001), representing a large effect size (Cohens d = 1.02). In contrast, the control group showed persistence or worsening of depressive symptoms over the same period. Difference-in-differences analysis confirmed a robust intervention effect, with an approximately 10-point greater reduction in depression scores among MoodGYM participants compared with controls (p < 0.001). These findings indicate that MoodGYM is an effective internet-based intervention for reducing depressive symptoms among repeating undergraduate students and offers a feasible and scalable approach to addressing student mental health needs in low-resource university settings.

Very preterm infants (<30 weeks gestation) are at elevated risk for neurodevelopmental and social-behavioral challenges. DNA methylation (DNAm) may provide a biological link between preterm birth and later behavioral outcomes. We examined associations between DNAm profiles at neonatal intensive care unit (NICU) discharge and at age 5 with Social Responsiveness Scale (SRS) scores which measure social communication, social interaction, and repetitive behaviors at age 5, including sex-specific effects, in the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study. Epigenome-wide buccal DNAm was profiled at NICU discharge (n=218) and at 5 years (n=188). We identified 38 neonatal and 6 age-5 CpG sites associated with SRS scores (all q<0.05) using epigenome-wide association studies (EWAS) at each time point. Several CpGs mapped to genes involved in neurodevelopment including TCF4, KLC4, CAP2, PTDSS1, ADAM12, SENP1, CHN2, SH3D19, and ITGA1, with sex-specific effects observed for CpGs in CAMTA1 and GABBR1. Enriched pathways included neurodevelopment, cytoskeletal regulation, stress-response, and metabolic processes. DNAm patterns during early life, particularly the neonatal period, were associated with social-behavioral development in very preterm children. Findings in key genes such as TCF4 and CAMTA1 highlight potential epigenetic mechanisms linking early-life biology to later behavioral challenges.

Numerous studies have shown that adults with depression have distinct oculomotor alterations during saccade tasks, but whether similar alterations occur in adolescents is largely unknown. The purpose of this study was to test if eye-tracking during a structured saccade task could distinguish a group of adolescents with depression from healthy controls. We hypothesized that, due to overlapping circuitry between depression pathology and the oculomotor system, adolescents with depression would show alterations in fixation, saccade, and pupil behaviour. 51 adolescents with depression and 66 age-matched healthy controls completed the Interleaved Pro- and Anti-Saccade Task (IPAST) and several self-reported questionnaires for psychiatric symptoms. Oculomotor outcomes included fixation acquisition, fixation breaks, correct rate, saccadic reaction time, rate of correct express-latency pro-saccades, rate of express- and regular-latency anti-saccade errors, baseline pupil size, as well as pupil constriction and dilation sizes following task instruction. In comparison to healthy controls, adolescents with depression displayed impairments acquiring fixation (p<.001), made more fixation breaks in pro- (p=.023) and anti-saccade trials (p=.005), more anti-saccade errors (p=.013), more express-latency saccades overall (ps=.016), had a smaller pupil constriction in pro-saccade trials (p=.047) and had a smaller pupil dilation in pro- (p=.011) and anti-saccade trials (p=.041). No differences were found for saccadic reaction time, rate of correct pro-saccades, rate of regular-latency anti-saccade errors, pupil constriction size during anti-saccade trials, or baseline pupil size. Patients had psychiatric comorbidities and were using psychotropic medication. While this reflected clinical reality, these factors may have influenced oculomotor behaviour. Adolescents with depression had altered fixation, saccade, and pupil behaviour during IPAST. Given that many cases of adolescent depression remain undetected, accessible and objective screening approaches are highly needed. This oculomotor phenotype may be used in the development of such a screening tool to detect those at risk.

Depression is a heterogeneous disorder, often diagnosed based on symptom co-occurrence. However, individuals may present with markedly different symptom profiles, potentially reflecting distinct underlying mechanisms. Identifying common patterns of symptoms using data-driven approaches could help clarify the heterogeneity of depression. Furthermore, examining the sociodemographic and lifestyle characteristics, health status, and polygenic scores of individuals with specific symptom profiles may offer insights into underlying risk factors. Unsupervised machine learning models were applied to large-scale data from the UK Biobank. Independent groups of individuals were assessed at two time points (the Mental Health Questionnaire: Q1; and the Mental Well-being Questionnaire: Q2) and reporting on historical or current episodes of depression. Two machine learning models, multivariate Bernoulli-mixtures and agglomerative hierarchical clustering, were used to identify common sets of symptoms and cluster individuals by symptom similarity. Consistency of results was examined between Q1 and Q2 and between clustering models. Associations between cluster membership probabilities and sociodemographic and lifestyle factors (sex, age, body mass index, smoking status, ethnicity, and deprivation), eight health conditions, and polygenic scores for bipolar disorder, schizophrenia, and attention-deficit/hyperactivity disorder (ADHD) were examined using regression models. Symptom clusters were highly consistent across Q1 and Q2 (mean correlation > 0.81) and between machine learning models (Rand Index > 0.83). Clusters aligned with the existing clinical subtypes, atypical and melancholic depression, alongside other potentially novel clusters reflecting a range of different symptom profiles. Atypical clusters (hypersomnia with weight gain) appeared in both Q1 and Q2 and were associated with younger age and higher body mass index. Distinct clusters combining insomnia, weight gain, and having thoughts of death were associated with asthma, suggesting potential inflammatory dysregulation. Further clusters were characterised by psychomotor changes and showed strong associations with Parkinsons disease, both before and after the mental health questionnaire was conducted. These findings highlight robust and clinically meaningful symptom subtypes within depression and support the use of data-driven approaches to improve diagnostic refinement and inform personalised treatment strategies.

Objective: Posttraumatic stress disorder (PTSD) after a traumatic birth is a serious but overlooked maternal morbidity, affecting ~20% of women following medically complicated deliveries. PTSD can undermine maternal caregiving. Rapid screening tools suited to busy obstetric settings are lacking. We developed and evaluated a brief screener, derived from the 20-item PTSD Checklist for DSM-5 (PCL-5), to identify PTSD related to childbirth. Study Design: We enrolled 107 women with traumatic childbirth. Participants completed the PCL-5 and the gold-standard clinician diagnostic interview for PTSD (CAPS-5); depression was measured with the Edinburgh Postnatal Depression Scale (EPDS). Bootstrap resampling with LASSO regression identified PCL-5 items most associated with PTSD. Firth logistic regression models estimated diagnostic accuracy. Sensitivity, specificity, area under the ROC curve (AUC), and Youden's J statistic determined performance and optimal cut-off. Results: A six-item version of the PCL-5 (PCL-5 R6), statistically derived from the full scale, showed excellent discrimination for PTSD compared with clinician evaluation (AUC = 0.95; 95% CI, 0.89-1.00). A cut-off score of 7 yielded high sensitivity (0.96) and good specificity (0.83), with an overall diagnostic efficiency of 0.86, detecting most PTSD cases while minimizing false positives. The PCL-5 R6 correlated moderately with the EPDS (rho = 0.53), showing that a depression screen alone cannot reliably detect PTSD. Conclusions: A short, 6-item PCL-5 provides a valid, efficient tool for detecting childbirth PTSD. Its brevity and accuracy make it practical for integration into routine postpartum care, enabling timely mental health screening.

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.

BackgroundLight plays a critical role in mental health, as the primary input to the circadian system, which regulates mood, energy, and the sleep-wake cycle. Altered light sensitivity is a potential mechanism in circadian-associated mental disorders. MethodsActigraphy-derived sleep, physical activity, and circadian rhythm correlates of the pupillary light reflex were explored in young people with emerging mental disorders. Participants were 27 healthy controls (Mean age=25.67 {+/-} 2.83, 52% female) and 155 young people from the Neurobiology Youth Follow-up Study (Mean age=25.48 {+/-} 5.65; 60% female), recruited from an early intervention mental health service. 32% of the latter group were re-assessed over 12 months. Pupil constriction, average and maximal constriction velocity, and constriction latency were recorded by the PLR-3000 monocular pupillometer in response to dim ([~]10 lux) and bright ([~]1500 lux) pulses. ResultsCompared to healthy controls, young people with emerging mental disorders had a smaller change in pupil diameter (p=0.037) and a slower maximal constriction velocity (p=0.018) in response to dim light. In the full sample, decreased dim light sensitivity was correlated with later timing of actigraphy-derived sleep midpoint. Within the clinical cases, increased genetic risk for bipolar disorder was correlated with increased dim light sensitivity, and higher insomnia clinical scores were correlated with decreased dim light sensitivity. Pupillometry measures were stable across time and seasons. ConclusionAltered light sensitivity may be associated with the emergence of mood disorder in young people and with altered sleep-wake timing.

Digital therapeutics for mental health often face low patient engagement, which limits their clinical impact. Interventions that deliver treatment using a video game medium may improve engagement and therapeutic efficacy, but the putative emergence of gaming-related problems remains a concern among clinical stakeholders. We examined whether long-term engagement with Meliora, a video game therapeutic for adult major depressive disorder, was associated with changes in gaming-related problems in a three-arm randomized controlled trial. The intention-to-treat cohort (n = 1,001) had a mean age of 33.4 years (SD 9.3) and 64% were female. The Gaming Addiction Scale (GAS-7) scores decreased from baseline (week 0) to post-intervention (week 12) in the Meliora arm (p = 8.1x10-4) and in the treatment-as-usual arm (p = 6.0x10-6), with no significant change observed in the Sham arm (p = 0.39). Changes in GAS-7 scores were not associated with intervention use hours (Meliora: p = 0.17; Sham: p = 0.28) or with experienced immersion (Meliora: p = 0.93; Sham: p = 0.19). Deterioration analysis found worsening rates from baseline to post-intervention low and comparable across study arms. Analyses in the per-protocol completer cohort ([&ge;]24 h use) corroborated these findings, indicating that even higher use did not lead to increases in gaming-related problems. These results provide evidence that long-term use of a video game therapeutic does not increase gaming-related problems when risks are properly mitigated, suggesting that video games may provide a safe medium for digital therapeutics. Author summaryMany patients use digital therapeutics insufficiently or drop out early, which limits their effectiveness and applicability in healthcare. Video game therapeutics deliver the treatment using an interactive video game as a medium to improve both engagement and therapeutic efficacy. However, extended use of video game therapeutics could inadvertently increase gaming-related problems. We examined whether long-term use of Meliora, a video game therapeutic for adults living with depression, was associated with increased gaming-related problems. We found that using Meliora or a highly similar Sham device did not increase gaming-related problems. Changes in gaming-related problems were not associated with the amount of time participants used the interventions, suggesting that typical use patterns are safe. We also found no relationship between experienced immersion and changes in gaming-related problems, suggesting that subjective immersion is distinct from problematic gaming. This study provides the first clinical evidence that extended engagement with a video game therapeutic does not increase gaming-related problems. These findings suggest that video games can be a safe medium for digital therapeutics in healthcare.