European Psychiatry

Importance: Excess mortality associated with mental disorders is well established, but estimates are largely based on specialist psychiatric populations. Whether they characterize mortality in the broader diagnosed population is uncertain. Objective: To characterize heterogeneity in excess mortality by diagnosis, psychiatric care setting, substance use disorder (SUD), and time since diagnosis. Design: Nationwide population-based cohort study with follow-up from January 1, 2011, through December 31, 2023. Setting: Primary and specialist health care and population registers in Finland. Participants: Residents aged 5 to 95 years without a recorded prevalent mental disorder at cohort entry. Exposures: Mental, behavioural, and neurodevelopmental disorders classified using ICD-11, with time-varying psychiatric care setting and SUD status. Main Outcomes and Measures: All-cause mortality, mortality rate ratios (MRRs), and 10-year differences in restricted mean survival time (RMST). Results: Among 5,526,599 individuals (2,784,897 [50.4%] women), 1,463,064 (26.5%) received a mental disorder diagnosis. Excess mortality varied substantially by diagnosis, clinical subgroup, and time since diagnosis. Among those aged 5 to 64 years with any mental disorder, adjusted MRRs across care setting and SUD strata ranged from 1.54 (95% CI, 1.39-1.71) to 8.97 (7.86-10.24). MRRs were highest immediately after first diagnosis and declined during the first 2 to 3 years. At 3 years, MRRs for depressive, anxiety or fear-related, and stress-related disorders among individuals without SUD treated outside specialist psychiatric care ranged from 0.88 (0.79-0.98) to 1.20 (1.12-1.29) in men and from 0.81 (0.73-0.89) to 1.13 (1.04-1.22) in women, whereas MRRs for schizophrenia and other primary psychotic disorders remained 1.84 (1.60-2.12) in men and 1.55 (1.37-1.75) in women. Ten-year survival loss across all mental disorders was 0.53 years (95% CI, 0.53-0.54) in men and 0.34 years (0.33-0.34) in women and was greater for natural than external causes. Conclusions and Relevance: Excess mortality varied markedly by diagnosis, clinical context, and time since diagnosis and was small in some common disorders outside specialist psychiatric care without SUD. Estimates derived from specialist psychiatric populations or averaged across follow-up may therefore provide an incomplete picture of mortality in the broader diagnosed population.

Background: Previous trauma research includes many limitations, such as the scarcity of pretraumatic health measurements and assessment of traumatic experiences with a broad scope across the lifespan. To respond to these gaps, we aimed to develop a new, prospective, population-based trauma dataset from childhood to middle age. Methods: We used the Young Finns Study that is a population-based, multi-generational, prospective study (n = 3596 for the main generation). It has started in 1980 (baseline assessment) and includes follow-ups in 1983, 1986, 1989, 1992, 1997, 2001, 2007, 2011/2012, and 2018-2020. From the 38-year follow-up and ten measurement points of the YFS, we collected all relevant trauma variables, including both free-format and structured questions that both the participants and their parents responded to. By a data-driven case-to-case analysis, we developed a scale to numerically capture variation in the quality of the experiences. Results: Our final dataset captured a total of 7769 traumatic experiences. We also developed the Traumatic Experience Severity Scale (TESS), including six subscales such as shamefulness, rarity, danger to life or health, effects on everyday life, human-made physical threat, and whether the target person was within or outside one's household. We also preprocessed the dataset to be later easily interleaved with other psychological, cardiovascular, and epigenetic variables of the YFS. Conclusions: We believe this new trauma dataset with thousands of experiences across the lifespan provides new opportunities to multidisciplinary, lifelong trauma research.

Objective: This study examined the prevalence of psychotic experiences (PE) and how early onset and persistence of PE contribute to risk and severity of mental disorders in adolescents at familial high-risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP) and adolescents from a population-based control group (PBC). Methods: This is the second follow-up of a nationwide cohort study including 522 children at FHR-SZ (N=202), FHR-BP (N=120), and PBC (N=200). Participants were assessed at ages 7, 11, and 15 using a semi-structured interview to evaluate PE and mental disorders. Results: At age 15, adolescents at FHR-SZ reported more PE than PBC over the past six months (current) and the past four years, while adolescents at FHR-BP only reported more current PE. PE reported at two or three timepoints (persistent PE) predicted any Axis I disorder in mid-adolescence, corresponding to three- (OR 2.9, 95% CI [1.5-5.7]) and 21-fold (OR 21.4, 95% CI [2.8-162.3]) increased risks, respectively. Persistent PE also predicted multimorbidity, with three- (OR 2.8, 95% CI [1.0-7.6]) and four-fold (OR 4.1, 95% CI [1.2-14.1]) increased risks, respectively. This was after adjustment for sex, early mental disorders, and familial risk. Conclusions: This study demonstrates a strong link between persistent PE and mid-adolescence mental disorders. Our findings emphasize PE as important risk markers for mental disorders during mid-adolescence and highlight the importance of monitoring children with PE before age 7 who develop persistent symptoms.

Suicidal behavior results from complex behavioral and biological changes. Previous cross-sectional studies indicate that proinflammatory immunobiological factors are often increased in close temporal proximity to a suicide attempt. Suicidal individuals may also exhibit a biological trait vulnerability to stress and inflammation, due to persistent epigenetic modifications. We enrolled 130 individuals with major depressive disorder (MDD), 83 with suicidal behavior at intake, and followed them for 12 months with up to eight clinical assessments. Quantification of plasma inflammatory markers and metabolites was performed by high-sensitivity electrochemiluminescence and Ultra High-Performance-Liquid-Mass Spectrometry (UPLC-MS), respectively. Epigenetic changes were identified using Illumina EPIC arrays. We identified 15 genes with altered DNA-methylation associated with suicidal behavior and attempts at baseline. Childhood trauma predicted lifetime suicide attempts and was associated with altered methylation of seven genes. Increased neutrophils and lower plasma serotonin at baseline predicted future suicide attempts over the following year (neutrophil estimate = 0.42, P = 0.016; serotonin OR = 0.58, 95% CI: 0.39-1.13). Utilizing biomarkers from baseline and epigenetic data from the genes with highest predictive values (STBD1 ,PRDM8, and TRIM15), we achieved an area under the curve (AUC) of 0.84 for suicide attempts over the year. Suicidal behavior in MDD was associated with specific epigenetic signatures. Several of the identified genes, such as MAD1L1, have been implicated in psychiatric disease, suicidal behavior and the immune response. These findings support the usefulness of epigenetic and immunometabolic blood markers for identifying suicidal individuals in clinical settings, potentially enhancing preventative efforts.

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition defined by differences in social communication and restricted, repetitive behaviours. As diagnostic criteria have broadened, ASD is now recognised across a wider range of individuals, raising key questions about its structure: does ASD have discrete sub-types, or is it better conceptualised as a continuous, possibly multidimensional, condition? We aim to explore whether a multidimensional continuum model more accurately captures the variability within ASD. We analysed a large SPARK phenotypic dataset of medical history and diagnostic surveys (background history, SCQ, RBS-R; n=36,710 individuals). We apply and compare two traditional statistical approaches, Factor Analysis and Gaussian Mixture Models, with a modern machine learning technique, the Variational Autoencoder (VAE). VAEs reconstructed unseen test data with ~4-fold better accuracy than Factor Analysis, and ~8-fold better accuracy than Gaussian Mixture Models. We identified four stable latent factors across 100 independently trained VAEs. These four dimensions provide an individual behavioural profile that can be visualized using radar-plots, offering a compact way to compare profiles at the person level. Through further analysis, we found evidence for 3 overlapping clusters or subtypes of ASD identified within the 4D latent space. This work aims to inform new ways of modelling ASD using a VAE that will be able to discern between a continuum or a clustered output and that go beyond binary diagnosis, instead reflecting the complex range of trait profiles, with implications for personalised diagnosis and intervention.

Background: Metabolomic studies of depression have yielded heterogeneous findings, potentially because metabolic correlates differ across symptoms and metabolic states. We examined symptom-specific metabolomic associations and whether body mass index (BMI) modifies these relationships. Methods: We analyzed 83,717 Estonian Biobank participants (70.6% female) with 249 Nightingale metabolite measures and 14 lifetime depressive symptoms. Logistic regression models progressively adjusted for sociodemographic, lifestyle, medication, and BMI factors. BMI-related attenuation and metabolite x BMI interactions were evaluated, followed by self-organizing map analyses of broader metabolic context. Results: Before BMI adjustment, 660 metabolite-symptom associations were Bonferroni-significant; 136 were significant after BMI adjustment, including 105 retained associations. Weight-related associations showed the strongest BMI dependence: none of 199 weight-gain associations and 2 of 115 weight-loss associations were retained. Among 691 preselected metabolite-symptom pairs, 211 (30.5%) showed significant metabolite x BMI interactions after false discovery rate correction. Six systemic metabolic profiles were identified, but only 3 of 211 BMI-sensitive pairs showed additional profile-dependent heterogeneity. Conclusions: Circulating metabolic correlates of depressive symptoms are heterogeneous and strongly dependent on symptom phenotype and BMI-related metabolic context. These findings suggest that metabolic biomarkers in depression should be interpreted in relation to both symptom presentation and metabolic state rather than as uniform correlates of the disorder.

Background: Substance use is common among individuals with depression. Transcranial magnetic stimulation (TMS) is an effective treatment for depression, but current clinical guidelines have discouraged TMS treatment for individuals with depression and co-occurring substance use given concerns for limited efficacy. However, limited data exists on whether substance use affects response to TMS. Methods: Using electronic health record data from patients who received a standard course of TMS for major depressive disorder at an academic medical center, we investigated associations between substance use frequency and response to TMS, defined as change in Patient Health Questionnaire-9 (PHQ-9) scores. Substance use frequency was extracted for alcohol, cannabis, nicotine, stimulants, benzodiazepines, opioids, inhalants, psychedelics, and other drugs. We performed ANCOVA and multiple regression analyses to predict change in PHQ-9 score based on substance use frequency, controlling for pre-TMS PHQ-9 score, age, sex, and number of TMS sessions received. Results: We extracted data from 219 TMS courses. Alcohol was the substance used most commonly (34.2%), followed by prescription benzodiazepines (28.3%), and prescription stimulants (21.0%). Across all substance categories, substance use was not associated with change in PHQ-9 score (all p > 0.05, Cohens d=0.00 to 0.30). In multiple regression models to compare individual levels of substance use frequency (e.g., daily use vs. no use), level of substance use was not associated with change in PHQ-9 score (all p > 0.05). The range of plausible effects of substance use frequency on PHQ-9 change was generally below the minimal clinically important difference for PHQ-9, suggesting substance use was unlikely to have a meaningful clinical effect on antidepressant response to TMS. Conclusions: Low to moderate substance use does not have a clinically significant effect on antidepressant response to TMS. Low-level substance use should not exclude individuals with depression from receiving TMS.

Aim: The Patient Safety Screener-3 (PSS-3) is a brief suicide-risk screening tool. Item 1 of this scale assesses depressive mood but is not included in the total score. We examined the association of item 1 with depressive symptom severity and characterized the suicide-related risk captured by PSS-3 total positivity. Methods: We conducted a nationwide cross-sectional survey among resident physicians in Japan. Associations between PSS-3 item 1 endorsement and Patient Health Questionnaire-9 (PHQ-9) scores were evaluated using the Wilcoxon rank-sum test. Diagnostic performance of item 1 was evaluated using PHQ-9 positivity ([&ge;]10) as reference standard. We also compared Short-form Scale for Suicide Ideation (SIS-6) scores according to PSS-3 total positivity and PHQ-9 item 9 positivity. Results: A total of 1,844 participants were included. PSS-3 item 1 was endorsed by 443 physicians (24.0%), and 47 (2.5%) met the criteria for PSS-3 total positivity. Item 1 showed 79.3% sensitivity and 79.5% specificity for PHQ-9 positivity. SIS-6 scores were higher in the PSS-3 total-positive group than in the total-negative group (median [IQR], 6 [5-9] vs 0 [0-1]; p<0.001). The SIS-6 showed a higher area under the receiver operating characteristic curve (AUC) and Youden index using PSS-3 total positivity (AUC, 0.961; optimal cutoff, 3) than PHQ-9 item 9 positivity (AUC, 0.907; optimal cutoff, 2). Discussion: PSS-3 may support brief, simultaneous screening for depressive symptoms and suicide-related risk. Compared with PHQ-9 item 9, PSS-3 may capture a more severe spectrum of suicide-related risk. PSS-3 may facilitate identification of individuals requiring further mental health assessment.

Objective To measure the accuracy of clinical coding, clinician review, and a locally deployed large language model (LLM) in identifying alcohol, drug, and self-harm involvement in emergency department (ED) attendances, and quantify prevalence. Design Two-phase diagnostic accuracy study. In a validation week, the identification strategies were assessed against a conflict-adjudicated reference standard (n=2,256); the LLM was then applied to n=105,096 annual attendances at the same site. Setting UK Type 1 Emergency Department treating patients [&ge;]16yrs. Main outcome measures Prevalence quantification compared with the reference standard; sensitivity, specificity, and balanced accuracy of each strategy; monthly identification rates and adjusted annual prevalence. Results The reference standard identified 12.1% of attendances as involving alcohol, drugs, or self-harm (coding 6.0%; clinician 10.0%, LLM 15.6%). LLM balanced accuracy matched or outperformed clinician review in all three domains (alcohol 0.942 v 0.930, p=0.635; drug 0.959 v 0.791, p<0.001; self-harm 0.982 v 0.908, p=0.004). Coding recorded 1.07 domains per identified patient against 1.32 in the reference standard. Adjusted annual prevalence corresponded to 12,890 domain involvements per year not identifiable in coded data. Subdomain classification found at least 81.6% of self-harm attendances required medical assessment for injury or overdose before psychiatric review. Conclusions Clinical coding identified fewer than half of presentations involving alcohol, drugs, and self-harm and rarely captured co-occurring domains; under-recording was present across a full year. A locally deployed LLM generated more complete structured data from existing clinical text within NHS infrastructure, at a scale which is not feasible for manual review.

Neighbourhood deprivation is one of the few potential policy-modifiable risk factors for psychiatric and neurological disorders, but the neurobiological pathways underlying these associations remain unclear. We investigated these relationships across three cohorts spanning the life span: the Healthy Brain and Child Development (HBCD) Study (n = 84, aged 0 to 4 weeks postnatal), the Adolescent Brain Cognitive Development (ABCD) Study (n = 4,792, aged 9 to 10 years), and the UK Biobank (UKB; approximately 500,000 adults, aged 44 to 87 years). Neighbourhood deprivation was associated with elevated disease risk, and individual lifestyle factors accounted for only a small fraction of this burden, indicating that the much larger residual effect reflects broader contextual characteristics of deprived environments rather than individual behaviours alone. Across all cohorts, greater deprivation consistently predicted lower cortical and subcortical brain volume, with effects detectable in early development and substantially stronger in adulthood. Across disorders, regional brain volume emerged as a consistent neuroanatomical mediator linking neighbourhood deprivation to neuropsychiatric disease. We further showed that deprivation preferentially affects brain regions intrinsically vulnerable to neuropsychiatric disorders. Spatial decoding analyses implicated dopaminergic and serotonergic neurotransmitter systems together with specific excitatory and inhibitory neuronal classes. Importantly, both the deprivation effects and their neuroanatomical mediation patterns were replicated across independent populations. Our study delivers a translational framework linking neighbourhood deprivation to brain health, which could inform public health policies and preventive interventions.

Background: Cognitive impairment is the leading cause of disability in schizophrenia with limited treatments. A major barrier to treatment development is the absence of reproducible, mechanistically grounded neural targets. Cross-sectional studies have identified dorsomedial prefrontal cortex (DMPFC)-somatomotor connectivity as a neural marker of cognitive performance on the Auditory Continuous performance task (ACPT), a measure of attention. To test the stability of this marker, we tested the relationship between DMPFC-somatomotor connectivity and ACPT performance in a longitudinal psychosis sample. Methods: Individuals with early psychosis (n=251) and matched controls (n=90) were enrolled and underwent resting-state neuroimaging and neurocognitive assessment. A subset completed longitudinal assessments over 2-4 years. We calculated DMPFC-somatomotor resting-state functional connectivity using a previously identified DMPFC region and a seed in the somatomotor cortex. We performed linear mixed effects models to predict ACPT performance based on connectivity, time, psychosis type, and their interaction. Results: In the psychosis sample, time (p=.0037) and affective psychosis diagnosis (p<.0001) predicted better ACPT performance. In a model predicting ACPT performance, we observed a significant interaction effect of DMPFC-somatomotor connectivity*psychosis subtype (p=.0079) such that DMPFC-somatomotor connectivity predicted ACPT performance only in individuals with non-affective psychosis (p=.0051). We then tested the specificity of this connectivity-cognitive performance relationship. In a model predicting DMPFC-somatomotor connectivity, only ACPT performance (p=.017), but not fluid cognition, was a significant predictor. Conclusions: DMPFC-somatomotor connectivity is longitudinally associated with cognitive performance in early psychosis. This relationship is strongest in nonaffective psychosis, suggesting a novel, reliable target for intervention for cognitive deficits in early psychosis.

This document describes the Statistical Analysis Plan (SAP) for PETRA, a randomised controlled trial in people with generalised anxiety disorder comparing pregabalin plus an antidepressant and standard care, with placebo plus an antidepressant and standard care, with respect to the primary outcome of the GAD-7 score at week 12.

A body of research suggests that autistic individuals are less likely to drink alcohol than neurotypicals. However, emerging studies support a link between autism and alcohol use. This complex relationship is also reflected in studies that have examined the genetic overlap between the two traits. However, it is unclear whether there is a direct causal relationship between them. To explore this, we applied a combination of polygenic score and Mendelian randomisation analyses using publicly available genome-wide summary statistics and phenotypic measures of autism and alcohol consumption from UK Biobank. LD score regression analyses did not provide evidence of a genetic correlation between genetic liability for autism and drinks consumed per week (rg=-0.08; CI95%=-0.19, 0.03). Further, findings from polygenic score analyses did not support an association between genetic liability for autism and overall monthly alcohol intake. Univariable Mendelian randomisation analyses showed little evidence for a total effect of autism, attention deficit hyperactivity disorder (ADHD) or depression on overall monthly alcohol consumption. Multivariable Mendelian randomisation analyses also showed little evidence of a direct effect of autism on drinks per week when controlling for ADHD and depression. It is plausible that genetic liability for autism does not directly increase the amount of alcohol consumed but instead operates via commonly co-occurring difficulties in the autistic community. However, our findings may be due to methodological shortcomings, including weak instruments biasing effects towards to the null. Consequently, results should be interpreted with caution and further research conducted to address these issues.

Major depressive disorder (MDD) has been associated with accelerated structural brain aging, yet whether this reflects a pre-existing neurobiological vulnerability, a dynamic acute state effect, or an accumulating biological residual remains unresolved. Across two longitudinal cohorts (N=3220), including a unique sample of 78 initially healthy individuals who transitioned into their first depressive episode during the study course, we systematically tested all three hypotheses. Patients with diagnosed MDD showed elevated MRI-derived brain age relative to healthy controls (1.4 and 2.5 years across cohorts). For the vulnerability hypothesis, individuals scanned prior to their first episode showed no baseline elevation, despite already demonstrating subclinical elevations in self-reported symptom severity, indicating that advanced brain age does not precede illness onset. For the state hypothesis, we found no acceleration of brain aging following the first depressive episode, and longitudinal brain age trajectories were independent of acute clinical symptom severity. Finally, neither episode duration nor recurrence scaled with brain age. Accelerated brain aging in depression is therefore neither an antecedent vulnerability nor an acute state marker of the first episode, but rather a stable biological feature of a long term illness course.

Background: Bipolar disorder is associated with persistent social, cognitive, and functional impairment during euthymia, yet the neural mechanisms underlying these deficits remain unclear. Alterations to self-referential processing are a candidate mechanism, but existing electrophysiological studies rely on emotionally valenced paradigms that potentially confound self-processing with emotional biases. Methods: We analysed electroencephalography from 28 patients with bipolar disorder (type I or II) and 28 age- and sex-matched healthy controls during an emotionally neutral colour judgment task with self-related (preference) and non-self-related (similarity) conditions. Late positive potentials, temporal generalisation decoding, and frequency band decoding (theta, alpha, beta) were used to characterise the temporal dynamics and oscillatory correlates of self versus non-self processing. Results: Controls showed higher overall event-related potential amplitudes and greater self versus non-self differentiation than patients (condition by group interaction, 337 to 946 ms). Broadband temporal generalisation decoding revealed extensive cross-temporal generalisation of the self versus non-self representation in controls, spanning most of the trial, but no significant generalisation in patients. Frequency analyses showed that alpha and beta carried self versus non-self information in both groups, with broader extent in controls, and that anterior theta carried this information in patients but not controls. Exploratory correlations linked decoding measures to rumination and anxiety but not to manic symptoms. Conclusions: The neural representation distinguishing self-referential from externally guided processing was both smaller in amplitude and less temporally sustained in bipolar disorder. Reduced persistence is not detectable by conventional amplitude analyses, and may bear on the self-related and social cognitive difficulties reported in this population.

Background Alcohol use disorder (AUD) is highly prevalent in schizophrenia, yet the neurobiological basis of this vulnerability remains poorly understood. Neurodevelopmental models suggest that pre-existing brain dysconnectivity may increase vulnerability to AUD. We therefore tested whether schizophrenia-like neurodevelopmental pathology alters how alcohol-related experience is incorporated into large-scale brain networks. Methods Resting-state functional connectivity was assessed in male Sprague-Dawley rats (n = 18-21/group) with neonatal ventral hippocampal lesions (NVHL), a neurodevelopmental model of schizophrenia, and sham-operated controls, with or without voluntary adolescent alcohol exposure. Functional connectivity was assessed using seed-to-voxel and seed-to-seed analyses within a cortico-striato-limbic network. We additionally examined whether individual alcohol intake during adolescence predicted adult functional connectivity according to neurodevelopmental status. Results NVHL and adolescent alcohol exposure independently produced predominantly hypoconnected cortico-striato-limbic networks. However, alcohol exposure did not exacerbate NVHL-associated dysconnectivity but instead induced a distinct network reorganization characterized by functional hyperconnectivity. Although alcohol intake was comparable between groups, dose-dependent relationships between adolescent alcohol consumption and adult functional connectivity were observed in sham animals but were absent or markedly attenuated in NVHL rats. These effects were primarily centered on prelimbic cortex connectivity with the amygdala, hippocampus, and dorsal striatum, highlighting this circuitry as a major locus of altered experience-dependent remodeling. Conclusions These findings suggest that vulnerability to AUD associated with schizophrenia-like neurodevelopment may arise less from additive network dysfunction than from an altered capacity of large-scale brain networks for experience-dependent functional remodeling. Schizophrenia-like neurodevelopmental pathology may therefore change how alcohol-related experience is translated into persistent brain network organization.

Background: As cannabis policy changes in the United States, secondhand cannabis smoke (SCS) is increasingly common, including within families. However, prevalence of exposure and clinical correlates over time in adolescents are not fully understood. Objectives: (1) To estimate the prevalence of SCS and personal cannabis use in US-based teens exposed to SCS, and (2) examine the cognitive trajectories of adolescents exposed to SCS compared to non-exposed peers. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study was used. Participants (n=11,316 of full cohort with follow-up data; n=776 with self-reported family SCS exposure) attended yearly visits from ages 11-17, completing substance use interviews, toxicological testing, and the NIH Toolbox Cognitive battery. Youth with SCS but no personal cannabis use (n=419; 47% female) were matched on prenatal substance exposure, family substance use history, and sociodemographics to non-SCS exposed and non-cannabis-using youth with a 1:2 ratio (Controls n=838). Linear mixed-effects models assessed cognitive performance by SCS*age interactions, accounting for random effects of subject and family. Covariates included sex and alcohol, nicotine, and other substance use. Secondary models analyzed performance by cumulative waves of reported SCS exposure interacting with age. Results: Of the full cohort, 6.9% (n=776) reported exposure to SCS. Of these individuals, 46% endorsed lifetime personal cannabis use by age 17, relative to 20% of non-SCS exposed youth (OR=3.83[95%CI:3.29,4.44]). Within matched participants, SCS*age demonstrated a significant interaction on attention and inhibitory control ({beta}=-0.32, p=.028), with SCS demonstrating reduced improvement over time. More waves of exposure were also associated with worse performance over time ({beta}=-0.39, p=.057). Discussion: Almost half of those who had been exposed to SCS endorsed personal cannabis use. Cognitive findings were domain specific, similar to findings in secondhand tobacco: SCS exposed youth showed restricted improvement in attention and inhibitory control by age 17. Public health and policymakers should make efforts to curb youth SCS exposure, given the potential for risk which has not been fully explored to date.

The Autism Spectrum Quotient (AQ-50) is widely used to assess autistic traits, yet its Hungarian version has not been psychometrically evaluated. We assessed the reliability, factor structure, temporal stability, convergent validity, and clinical utility of the Hungarian AQ-50 and a revised translation (AQ-50-HU-R) in two samples (N1 = 1967; N2 = 423), including autistic and non-autistic participants. The AQ-50-HU-R showed high internal consistency and test-retest reliability. A bifactor model provided the best fit ({chi}2[1125] = 1650.433, p < 0.001; CFI = 0.991; TLI = 0.990; RMSEA = 0.033 [90% CI = 0.030-0.037]; SRMR = 0.083), with 71% of common variance attributable to a general autistic traits factor. The total score distinguished clinically verified autistic participants from participants reporting no ASD diagnosis (AUC = 0.906), with a cutoff of 25. Associations with ADOS scores were weak or nonsignificant. The AQ-50-HU-R is best interpreted as a reliable total-score screening measure, supporting referral for comprehensive autism assessment.

This study investigated bidirectional associations between maternal sleep and depressive symptoms from preconception to postpartum, and whether infant sleep mediated or moderated these associations. We used data from the Generation R Next Study (N=2,294). Maternal sleep (specifically general sleep disturbance, latency, quality, duration, and midpoint) and depressive symptoms were prospectively assessed at five timepoints from preconception to 12-month postpartum. Sleep was self-assessed with the General Sleep Disturbance Scale and Munich Chronotype Questionnaire; depressive symptoms with the Adult Self Report depression/anxiety subscale and Edinburgh Postnatal Depression Scale. Infant sleep (specifically night awakenings, nocturnal sleep duration, and latency) was parent-reported at 1-month postpartum using the Brief Infant Sleep Questionnaire. Bidirectional associations were examined using Autoregressive Latent Trajectory Models with Structured Residuals. The role of infant sleep was examined using mediation and moderation analyses. We found that maternal sleep and depressive symptoms were both stable over time. For sleep quality and disturbance, bidirectional associations suggested slightly stronger effects from depression to sleep (sleep quality:{beta}depression[-&gt;]sleep quality=0.11, 95%CI:0.07 - 0.14; general sleep disturbance:{beta}depression[-&gt;]sleep disturbance=0.14, 95%CI:0.10 - 0.18) than from sleep to depression ({beta}sleep quality/disturbance[-&gt;]depression=0.07 for both, 95%CIs:0.03 - 0.11). For latency, effects were comparable in both directions ({beta}depression[-&gt;]sleep latency=0.06, 95%CI:0.03 - 0.09; {beta}sleep latency[-&gt;]depression=0.05, 95%CI:0.01 - 0.09). The association between depressive symptoms and sleep latency was both mediated (9.7%) and moderated (p<0.05) by infant sleep latency. In conclusion, general maternal sleep disturbance, sleep quality, and sleep latency showed bidirectional associations with depressive symptoms from preconception/early pregnancy onwards. Infant sleep latency may represent a potential modifiable factor within this cycle.

Background The prevalence and pattern of secondary causes of first-onset psychosis (FEP) in Asian populations are understudied. Our objectives are to investigate the prevalence and pattern of secondary causes of FEP presenting in an acute medical setting in a metropolitan, Chinese-predominant population, and to investigate the prevalence and pattern of undiagnosed conditions presenting as psychosis. Method This is a retrospective observational study. We reviewed medical records of patients referred to the consultation psychiatry team at a tertiary acute teaching hospital in Hong Kong from January 2015 to Apr 2025. The inclusion criteria of the study are 1) age 18-64 at the time of the assessment, and 2) FEP confirmed by the consultation liaison team. Patients diagnosed with delirium were excluded. Result Among the 384 patients included in the study (mean age = 40.0 {+/-}13.7 years, 69% female), secondary causes of psychosis were found in 9.6% (n=37) of the cohort. Substance use is the most common secondary cause found (n=11, 2.9% of all FEPs) overall. Among those with secondary psychoses, patients' underlying conditions were revealed only by the workup in relation to the FEP in 16 of them, of which definitive or probable autoimmune encephalitis (n=5) and early-onset dementia (n=4) were the most common conditions uncovered. Conclusion The prevalence of secondary psychoses in our FEP cohort is lower than published international figures. Clinicians need to be aware of the suspicious clinical features suggestive of autoimmune encephalitis and early-onset dementia in FEP patients with otherwise unremarkable past history and toxicology test.