Acta Neuropsychiatrica

Bipolar disorder (BD) is a chronic psychiatric condition affecting approximately 1-2% of the population, characterized by depressive and manic episodes. BD comprises two main subtypes, defined by the presence of mania (BD-I) or hypomania (BD-II). Commonly used clinical scales, including the Global Assessment of Functioning (GAF), Clinical Global Impressions (CGI), and World Health Organization Disability Assessment Schedule (WHODAS), assess functional impairment at the time of evaluation. However, they may not adequately capture cumulative lifetime illness burden or provide a retrospective measure of clinical severity. Here, we introduce the Index of Number of Events and Severity (INES), a novel instrument designed to quantify longitudinal illness-course severity in BD by integrating cumulative clinical events with illness duration. INES incorporates psychosis and rapid cycling as dichotomous variables and quantifies hospitalizations, suicide attempts, and affective episodes as discrete categories. INES was evaluated in 307 individuals from the MadManic cohort. It correlated moderately with GAF and CGI, while its strongest association was observed with WHODAS (r=0.347). Factor analysis over the four scales supported a two-factor structure, where INES loaded alongside WHODAS, capturing the variability of structured instruments. Linear modelling indicated that traditional scales explained only 14.4% of the variance of INES, suggesting that this scale captures clinical information largely unaccounted by the other instruments. INES was the only to differentiate between BD subtypes, with higher severity observed in individuals with BD-I. These findings support INES as a reproducible tool for capturing cumulative lifetime severity in BD, with potential utility in clinical and genetic studies.

Background: Personality traits are consistently associated with bipolar disorder (BD). However, their features across BD diagnostic subtypes and their modulation by demographic and health-related factors remain largely unexplored. This study aimed to characterize Big Five personality domains in individuals with BD compared to controls, and to examine differences between BD type I (BD-I) and BD type II (BD-II). Methods: We analyzed 833 participants from the MadManic cohort (300 BD subjects and 533 controls) with available Big Five Inventory-2 (BFI-2) data. Linear regression models were used to assess associations between personality traits and BD diagnosis, adjusting for relevant covariates. Additional comparisons were conducted across sex, age, and Body Mass Index (BMI), and between BD-I and BD-II patients. Results: BD was associated with higher Negative Emotionality (NE) and lower Extraversion and Conscientiousness. Conscientiousness was also inversely associated with BMI. Within the BD group, individuals with BD-I exhibited lower NE compared to those with BD-II. Stratified analyses indicated that elevated NE in BD was the most consistent domain across sex, age, and BMI subgroups, whereas differences in Extraversion and Conscientiousness varied depending on subgroup features. Conclusions: BD is characterized by a distinct personality profile marked by elevated NE and reduced Extraversion and Conscientiousness. NE emerged as the most robust domain associated with BD, which may also differentiate between subtypes, with higher levels observed in BD-II than BD-I. These findings highlight the relevance for considering demographic and health-related factors, particularly BMI, when interpreting personality patterns in BD, supporting the role of personality dimensions to examine clinical heterogeneity.

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 Diabetes is common in people with bipolar disorder, particularly men. Both type 2 diabetes and bipolar disorder are associated with evening chronotype, and men of working-age have later chronotypes than women. However, it is not known whether elevated rates of diabetes in bipolar are explained by evening chronotype, nor whether sex differences in chronotype contribute to higher rates of diabetes observed in men with bipolar disorder. Aim To determine whether evening chronotype increases the likelihood of comorbid type 2 diabetes in bipolar disorder, relative to those with no mental health problems. Additionally, to determine whether any effect differs between men and women. Methods Using data from the Our Future Health cohort, we estimated odds ratios for type 2 diabetes by bipolar disorder diagnosis, chronotype, and their interaction, adjusting for relevant covariates. Results A total of 1,136,694 participants (N = 6,846 with bipolar disorder) were included in the adjusted models. Type 2 diabetes was independently associated with bipolar disorder and evening chronotype. There were no significant differences in the interaction effects of chronotype on the odds of type 2 diabetes in bipolar across the whole sample or when stratified by sex. Conclusions The high prevalence of type 2 diabetes in people (and in men, specifically) with bipolar disorder may be independent of evening chronotype.

Neuropsychiatric symptoms are considered the most common feature of long COVID disease. Recent studies have demonstrated structural brain changes and highlighted the importance of neuroinflammation in the development of cognitive deficits as seen in long COVID patients. In addition, peripheral studies have demonstrated heterogeneous molecular subtypes of long COVID pathology. However, it is unknown which peripheral metabolomic alterations occur in patients with neuropsychiatric long COVID syndrome and how these relate to symptom severity. In the present study, we investigated differences in the peripheral serum metabolome profiles of healthy controls and patients with long COVID syndrome with neuropsychiatric symptoms. We found that patients with long COVID showed peripheral alterations in lipid species such as triacylglycerides and acylcarnitines. Furthermore, metabolites altered in patients with long COVID syndrome were also associated with depressive and fatigue symptom burden as well as with differences in cortical thickness in multiple brain regions. Our results demonstrate a metabolic phenotype of long COVID patients that may reflect a dysregulation of lipid metabolism and deficits in mitochondrial energy production as potential contributors to symptom burden and brain structural alterations. These data may serve as a resource and basis for further studies aimed at investigating peripheral molecular alterations in patients with neuropsychiatric long COVID syndrome.

Abstract Background: Glycosylated RNAs (GlycoRNAs) participate in immune recognition and intercellular communication, but their relationship with brain cell-type transcriptional signatures in major depressive disorder (MDD) remains unclear. We examined GlycoRNA-related transcriptional coupling with microglial and other cellular signatures in the dorsolateral prefrontal cortex (DLPFC). Method: Postmortem DLPFC transcriptomic data from 22 controls and 26 MDD patients (GSE102556) were analyzed. GlycoRNA-related pathway enrichment was quantified using gene set variation analysis (GSVA), whereas microglial, neuronal, astrocytic, and oligodendrocytic signatures were derived using single-sample gene set enrichment analysis (ssGSEA). Pearson correlations, linear regression, and generalized estimating equations (GEE) evaluated cell-type-specific associations and diagnostic interactions. Exploratory GEE results underwent false discovery rate (FDR) correction. Results: No differentially expressed genes survived FDR correction, and GlycoRNA-related and cell-type signatures did not differ significantly between groups. In controls, GlycoRNA enrichment was positively associated with the microglial signature (beta = 0.447, FDR-adjusted P = 0.006), with significantly weaker associations for neurons, astrocytes, and oligodendrocytes (all FDR-adjusted P < 0.05). The two-way GlycoRNA x is_microglia interaction was nominally significant (beta = 0.210, P = 0.048), confirming that GlycoRNA transcriptional coupling is substantially stronger for microglia than for the other three cell types combined. The microglial association was numerically attenuated in MDD (beta difference = -0.273, P = 0.167), but diagnostic interactions were nonsignificant. Conclusions: GlycoRNA pathway transcriptional enrichment exhibits preferential microglial association in control DLPFC. Its possible attenuation in MDD remains to be validated. keyword: Major depressive disorder; GlycoRNA; microglia; dorsolateral prefrontal cortex; generalized estimating equation; ssGSEA; bioinformatics

Background: Dissociative identity disorder (DID) is associated with frequent psychiatric comorbidity. Its complex and overlapping symptom profile can complicate recognition of both DID and co-occurring psychiatric conditions, contributing to diagnostic uncertainty. Evidence regarding psychiatric comorbidity is limited and prevalence estimates vary across studies. Aims: This meta-analysis aimed to examine the prevalence of psychiatric comorbidities in DID and factors associated with variation in prevalence estimates. Methods: Eligible studies were identified through PubMed, Scopus, Embase, PsycINFO, and MEDLINE from 1980 to 25 April 2026 (PROSPERO, no. CRD420261335819). Studies reporting psychiatric comorbidity in adults with DID were independently screened by two reviewers. Risk of bias was assessed. Random-effects meta-analyses using logit-transformed prevalence estimates were conducted. Meta-regressions examined moderators, whilst influence and sensitivity analyses assessed robustness. Certainty was evaluated using the GRADE approach. Results: Twenty-four studies (N = 858) contributed to the meta-analysis across 23 psychiatric comorbidities. Among individuals with DID, posttraumatic stress disorder had the highest pooled prevalence (87.44%, 95% CI 71.79-94.96), followed by major depressive disorder (62.64%, 95% CI 33.45-84.84), and borderline personality disorder (47.05%, 95% CI 34.21-60.32). Substantial heterogeneity was noted across most estimates. Meta-regressions identified significant associations with participant characteristics, recruitment, study quality, and diagnostic method. Risk of bias and certainty of evidence were heterogenous. Conclusions: Psychiatric comorbidity in DID is substantial and spans multiple diagnostic categories, although considerable heterogeneity and methodological variation limit confidence in prevalence estimates. Standardised diagnostic assessment, more representative sampling, and longitudinal research are needed to clarify the extent and clinical significance of comorbidity in DID.

Objective: The Alimetry Gut-Brain Wellbeing (AGBW) Survey is a validated 10-item scale developed to assess mental health in patients with chronic gastroduodenal symptoms. While the original scale demonstrated strong psychometric properties overall, as part of an ongoing commitment to continuous instrument optimization, this study evaluated a revised, unidirectional version of the scale (AGBW-II) to enhance measurement precision. Methods: The psychometric properties of the revised AGBW-II were evaluated via an anonymous online questionnaire in a sample of 161 patients with chronic gastroduodenal symptoms. Score distributions, factor analysis, reliability, and validity were analyzed and compared with data from the validation study of the original scale (n= 311). Results: The AGBW-II total and subscale scores demonstrated robust reliability and validity, outperforming the original AGBW Survey. Notable improvements in the reliability and validity of the stress subscale were observed following item rewording. Confirmatory factor analysis verified the three-factor model separating the depression, stress, and anxiety subscales, with the AGBW-II showing improved model fit indices. Conclusions: The revised, unidirectional AGBW-II demonstrated improved reliability and validity, while maintaining the underlying psychometric properties of the original scale. Consequently, the AGBW-II provides a reliable, valid, and brief mental health assessment for patients with chronic gastroduodenal symptoms.

Major depressive disorder (MDD) is strongly associated with dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, systemic inflammation, and gut microbiota dysbiosis. Although selective serotonin reuptake inhibitors such as escitalopram are standard treatments, their efficacy is often constrained by partial response and gastrointestinal adverse effects. In this 12-week, randomized, double-blind, placebo-controlled trial, we evaluated the clinical efficacy and microecological mechanisms of adjunctive Lactiplantibacillus plantarum PS128 (PS128; 6*1010CFU/day) in MDD patients on stable escitalopram therapy. Adjunctive PS128 significantly enhanced clinical response compared to placebo, yielding substantial reductions in HAMD-17 and MADRS, alongside a higher remission rate. 16S rRNA sequencing and PICRUSt2 profiling revealed that PS128 enriched key short-chain fatty acid producers (Faecalibacterium, Coprococcus), counteracting the Klebsiella expansion seen in placebo. Functionally, PS128 up-regulated neuroprotective cofactor, B vitamins, biosynthesis and down-regulated the neurotoxic kynurenine pathway. Network analysis demonstrated that PS128 maintained a resilient, integrated microbial co-occurrence topology, whereas the placebo network showed structural segregation. This stabilized ecosystem attenuated peripheral inflammatory signaling and normalized salivary cortisol levels. Overall, adjunctive PS128 augments escitalopram efficacy by enhancing gut network stability, supporting cellular energetics, and modulating neuroendocrine activity, offering a promising multimodal strategy for MDD.

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.

Brief assessments reduce clinician and patient burden and increase utilization. Recently, five core depression symptoms (low mood, poor concentration, low self-worth, loss of interest, low energy) have been shown to be particularly sensitive to treatment effects in adults. How these core depressive symptom domains perform for screening or diagnostic purposes in youth is unknown. To address this question, we extracted five analogous symptom items from four widely used symptom assessment tools for children and adolescents (Child Behavior Checklist [CBCL], Youth Self Report [YSR], Parent General Behavior Inventory [P-GBI], and Adolescent General Behavior Inventory [A-GBI]) to create 5-item short forms. We evaluated their psychometric properties and diagnostic utility in a large (N=1185), racially diverse sample (48% Black youth) across community and academic outpatient mental health settings, with diagnoses established through LEAD consensus. All short forms correlated highly with full-length measures (r=.74-.92) and demonstrated comparable inter-item correlations (r =.19-.46). The short forms did not differ meaningfully from the full measures in correlations with psychiatric diagnoses, demographics, or diagnostic interviews. Area under the curve (AUC) values for identifying depression and any mood disorder diagnosis (determined by semi-structured diagnostic interviews) were fair to good (AUC=0.60-0.79), which were not worse than full measures, except for the P-GBI. The CBCL-5, YSR-5, P-GBI-5, and A-GBI-5 may be useful brief depression assessments in youth. How these five symptom domains perform as outcome measures in treatment deserves study.

Non-suicidal self-injury (NSSI) is highly prevalent and exhibits substantial fluctuations among adolescents with mood disorders, yet the heterogeneity and differential treatment responses accompanied by such fluctuations remain unclear. The current study employed ecological momentary assessment (EMA) and latent profile analysis to identify latent subtypes of NSSI ideation via temporal features, and constructed machine-learning models to validate the predictive value of dynamic features for post-treatment self-injury risk. Thirty-five Chinese female adolescents with mood disorders and co-occurring NSSI (Mage = 14.4 years) receiving inpatient psychiatric treatment completed baseline assessments and 5 daily surveys of NSSI ideation throughout the course of treatment. Two subtypes were identified: the high-mean paroxysmal subtype (54.3%) and the low-mean sporadic subtype (45.7%). The high-mean paroxysmal subtype exhibited significantly more severe clinical symptoms, more emotional abuse experiences, lower self-esteem, higher impulsivity and greater difficulties in emotion regulation. The temporal-feature-based model outperformed the baseline-feature-based model in predicting self-injury risk. These findings underscore the dynamic nature and heterogeneity of NSSI ideation among adolescents with mood disorders, and offering implications for tailoring interventions to distinct youth subgroups.

The present study examined the relationship between the DSM-5 diagnostic criteria for gambling disorder (GD) and gambling severity via an item response theory (IRT) analysis in two large German population survey data sets (Buth et al. (2022, 2024)). IRT-based person fit analyses may reveal atypical response patterns (e.g. endorsing criteria linked to higher levels of disorder severity, but not criteria linked to lower levels). We examined the link of such atypical response patterns and mental health as measured by the MHI-5, employing a 2-parameter-logistic (2PL) IRT model and a linear mixed model with random intercepts. Results largely replicated previously reported item severity rankings across both samples: GD criteria such as loss chasing and a preoccupation with gambling were generally linked to lower severity levels, whereas criteria such as withdrawal symptoms or job/family problems where generally linked to higher severity levels. Modelling revealed a reduced assessment sensitivity in lower gambling severity ranges. Furthermore, person fit analyses suggest that atypical symptom patterns may be linked to poorer mental health (MHI-5). Implications for the interpretability of total scores of endorsed criteria and the validity of diagnostic practices determining eligibility for treatment and financial compensation are discussed.

Objective: To evaluate the psychometric properties, factor structure, validity, and age- and sex-specific norms of the 21- and 10-item parent-report Child Mania Rating Scale (CMRS-P) in a nationally representative U.S. sample of youth aged 6-18 years. Method: Parents of 2,229 youth aged 6-18 years [weighted M(SD)=12.0(3.3) years; 45.9% female] completed the CMRS-P and related measures between July 2025 and March 2026. Data were weighted to represent U.S. demographics. A clinical comparison sample included parents of 522 youth seeking outpatient mental health services. Complete-case analyses evaluated reliability, factor structure, item response theory, measurement equivalence, retest stability, and convergent and discriminant validity. GAMLSS estimated age- and sex-specific norms. Results: Weighted mean scores were 8.5(SD=9.0) for CMRS-P-21 and 4.0(4.3) for CMRS-P-10. Internal consistency was high ({omega}=.97/.93), and forms correlated .95. A general severity factor explained most reliable variance ({omega}H=.94). Three items differed in response thresholds across samples, with an average impact below one point on expected total scores. Both forms correlated strongly with attention problems, suicidality, depression, externalizing symptoms, and emotion dysregulation (r=.51-.63 for CMRS-P-21) and negligibly with pubertal status. Reliable-change thresholds were 14.5 (CMRS-P-21) and 6.8 (CMRS-P-10) points. Weighted GAMLSS CMRS-P-21 95th percentiles declined with age in males (30-23) and increased in females (22-30), with wide bootstrap intervals at age extremes; the female trend was not replicated without weights. Conclusions: Findings support both CMRS-P forms for assessing youth manic symptoms. The first nationally representative U.S. norms provide age- and sex-adjusted benchmarks for interpreting scores and informing further clinical assessment.

Introduction: Cognitive impairment and disturbed rest-activity patterns often persist between episodes of major depressive disorder (MDD) and bipolar disorder (BD). Whether these deficits are disorder-specific or transdiagnostic remains unclear, as does the existence of a link between rest-activity phenotypes and cognitive performance. Methods: Using the All of Us Research Program, we derived normative deviation scores across four cognitive domains (sustained attention, inhibitory control, reward-based impulsivity, social cognition) from non-clinical controls (NCC), then compared deviations in MDD and BD. MDD was adequately powered to regress deviation scores on four 90-day Fitbit-derived phenotypes (step count, sleep duration, wakefulness after sleep onset, sleep timing variability); the same analysis was run on NCC as a sensitivity check. Results: Samples were substantially larger than prior works (MDD 5,087-6,536; BD 545-739; NCC 40,589-51,491). Relative to NCC, MDD and BD exhibited worse sustained attention (Delta Glass = -0.081 vs. -0.187) and higher impulsivity (Delta Glass = 0.092 vs. 0.240), with deficits more pronounced in BD. No wearable phenotype was significantly associated with cognitive performance in MDD (R2< 0.01); NCC associations, though significant, were of negligible magnitude (R2 <= 1.2%). Discussion: Inter-episode cognitive impairment was domain-selective rather than global, with a gradient BD > MDD. Despite adequate power, wearable rest-activity phenotypes were not associated with cognition in MDD. Whether this extends to BD, where deficits were largest, could not be tested due to limited power. Community-dwelling samples likely underestimate impairment relative to clinical cohorts.

Background: Major depressive disorder (MDD) is a severe mental illness associated with severe clinical consequences and substantial societal burden. It's characterized by immune-inflammatory dysregulation and immune sensitization. Objective: To determine whether in vitro ketamine attenuates phytohemagglutinin (PHA)/lipopolysaccharide (LPS)-induced immune sensitization in patients with MDD and healthy controls (HCs). Methods: Whole blood from 18 patients with MDD and 18 HCs was stimulated with PHA/LPS and exposed to ketamine (0.3 M, 0.6 M, and 6 M) for 72 hours. Cytokines, chemokines, growth factors, and composite immune profiles, including M1/M2 macrophages, T helper (Th)1/2/17, the immune-inflammatory response system (IRS), and compensatory immunoregulatory system (CIRS), were synthesized and determined. Results: Under PHA and LPS stimulation in vitro, the MDD group exhibited markedly elevated immune profiles, including M1, M2, Th1, Th2, Th17, IRS, CIRS, chemokines, and growth factors, consistent with immune sensitization. Significant group-by-treatment interactions were observed for Th1-Th2, M2, growth factors, IL-12(p70), M1, and chemokines. Ketamine produced minimal changes in HCs but broader suppression in MDD, particularly at the highest concentration, without normalizing the sensitized immune phenotype. Among the immune markers with no notable group-by-treatment interactions, ketamine exerted diagnosis-independent effects, decreasing MIP-1{beta}, IL-1&{beta}, Th1, TNF-{beta} IRS, IFN-{gamma}, and IL-2 compared to the control condition. Conclusions: Ketamine exhibited two distinct immunoregulatory patterns: selective, disease-dependent attenuation of sensitized immune pathways and broader, diagnosis-independent suppression of the stimulated immune response, predominantly at higher concentrations. However, these effects were insufficient to normalize the immune-sensitized phenotype of MDD.

Depression and treatment-resistant depression (TRD) are significant public health issues, but the associated network-level neurobiological mechanisms remain poorly understood. This study used magnetoencephalography (MEG) to identify altered resting-state connectivity within the default mode (DMN), executive control (ECN), salience (SN), dorsal attention (DAN), motor (MN), and visual (VN) networks as potential biomarkers of depression and treatment resistance. The study recruited 168 participants (80 healthy volunteers (HVs) and 88 currently experiencing a major depressive episode (74 with TRD and 14 without TRD (noTRD))). Data Integration Analysis for Biomarker Discovery using Latent Variable Approaches for Omics Studies (DIABLO) was used to differentiate the depression, TRD, and HV subgroups and identify neural markers of depression and treatment resistance. For differentiating the depression and HV groups, the triple network model (area under the receiver operating curve (AUROC): 0.759-0.787) - which includes the DMN, ECN, and SN - outperformed the six-network model (AUROC: 0.747-0.762) across different bandwidths. For differentiating the TRD and HV groups, the triple network model demonstrated reasonable prediction across different bandwidths (AUROC: 0.737-0.807); potential within-network connectivity differences distinguished those with TRD from HVs, especially DMN within-network connectivity between the inferior parietal lobule and precuneus in the beta band (FDR-corrected p<.05). Hyperconnectivity within the SN (superior parietal lobule and frontal operculum in the alpha band) and DMN (inferior parietal lobule and lateral prefrontal cortex in the beta band) was associated with number of treatment failures (ps<.05). These findings highlight key brain regions and connectivity patterns, advancing our understanding of neural mechanisms underlying depression and treatment resistance.

Background: Genetic and observational studies have identified metabolic factors potentially contributing to the risk of Major Depression (MD). However, studies to date have concentrated on common genetic variants, many of which are in linkage disequilibrium. This makes it difficult to localise variants to a single gene. To overcome this, we used short read whole-genome sequenced datasets (srWGS) to conduct a targeted rare variant association analysis of the FADS region, which has previously been implicated in metabolic effects on MD. Methods: Using srWGS data from 740,373 individuals from All of Us (AoU) and the UK Biobank (UKB) we tested for associations between rare variants in the FADS region and MD. Additionally we conducted association tests between rare FADS variants and five blood-based metabolites implicated by previous studies of MD. Finally, we applied Mendelian randomisation to identify causal effects of metabolites on MD using rare-variants. Results: We found FADS rare variants were significantly associated with all tested metabolites, but not with MD. Using Wald-Ratio MR we found a putative causal effect of Docosahexaenoic acid (DHA) on MD using a rare-variant instrument in the FADS2 gene. Conclusion: Our study represents the largest rare-variant analysis of MD to date. However, the lack of associations between FADS rare-variants and MD suggests our analysis is underpowered, or that genetic effects on MD are conferred substantially by higher frequency variants. Rare-variant MR suggested a causal effect of DHA on MD, and implicates the FADS2 gene.

In Ethiopia, khat (Catha edulis) leaves, containing amphetamine-like alkaloids, are chewed for their psycho-stimulating effects. Khat use has been associated with psychosis. In a psychosis etiology framework, we investigated whether season, fluctuations of khat availability and khat use are associated with khat-induced psychotic experiences and whether trauma load moderates this association. In Southwestern Ethiopia, a cohort of 685 men aged 18-40 years were interviewed twice, during dry and after rainy season (low vs. high khat availability). Khat use was assessed by urine immunoassay and self-report. Trauma load and psychotic experiences were assessed by trained local interviewers. Khat use increased after the rainy season (p < 0.0001). Khat use and seasonality predicted khat-induced psychotic experiences. Main findings comprise increased odds of psychotic experiences among immunoassay-positive individuals with high trauma load. A potential additional interaction with recent trauma emerged. Findings support sensitization-related mechanisms but require replication in larger samples with longer follow-up.

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.