Acta Neuropsychiatrica

BackgroundBipolar disorder (BD) is frequently underdiagnosed, particularly in patients presenting with depressive disorders, leading to delays in appropriate treatment. Artificial intelligence (AI) applied to electronic health records (EHRs) may improve early detection by identifying clinically relevant symptom patterns. ObjectiveTo evaluate the diagnostic performance of a natural language processing (NLP)-based AI model for detecting BD-related features in EHRs of patients with affective diagnoses. MethodsA retrospective diagnostic accuracy study was conducted using 500 EHRs from a psychiatric referral hospital in Bogota, Colombia (2020-2024). The model extracted 18 predefined clinical domains from unstructured text and classified patients into four risk categories. Diagnostic performance was assessed in a validation subset of 100 records using independent psychiatric evaluation as the reference standard. Sensitivity, specificity, positive and negative predictive values, F1-score, and area under the receiver operating characteristic curve (AUC-ROC) were calculated. ResultsThe model achieved high agreement in symptom extraction (mean 91.1%). Sensitivity was 96.4% (95% CI: 87.7%-99.0%) and specificity was 84.4% (95% CI: 71.2%-92.3%), with an F1-score of 0.92 and an AUC-ROC of 0.932 (95% CI: 0.881-0.975). A substantial proportion of patients with depressive diagnoses were identified as having confirmed BD or clinically relevant risk. The model analyzed complete EHRs 120 times faster than human reviewers. ConclusionsNLP-based analysis of EHRs can achieve clinically meaningful performance in identifying BD-related patterns while substantially reducing review time. The model may be useful as a clinical decision support tool for earlier identification of bipolar disorder.

Post-traumatic stress disorder (PTSD) remains a significant psychiatric burden; despite growing biomarker research, no blood-based molecular diagnostic tool has been clinically validated for routine use. In this study, we developed a machine learning classifier for PTSD using peripheral blood leukocyte RNA-seq data from combat-exposed U.S. Marines (GSE64813), diagnosed via the Clinician-Administered PTSD Scale (CAPS) under DSM-IV criteria. Differentially expressed genes (DEGs) were identified and further refined through additional filtering criteria, yielding a 90-gene feature set used to train and compare multiple machine learning models. The support vector machine (SVM) classifier achieved the best performance, with an accuracy of 89% and an AUC of 0.95, outperforming logistic regression and random forest approaches. Furthermore we evaluated our model on independent external datasets to assess generalizability. These findings highlight the promise of transcriptomic signatures as a foundation for objective, blood-based PTSD diagnostics, while emphasizing the critical need for robust cross-dataset generalizability. Code availabilityhttps://www.kaggle.com/code/persianexxx/ptsd-final

Esketamine is a fast-acting antidepressant drug which induces acute psychoactive effects. The most frequent is a dissociative state which seems unrelated to therapeutic efficacy. Other esketamine-induced effects, including psychedelic-like mystical experiences, have been poorly studied in terms of phenomenology and frequency, and may carry specific therapeutic relevance. In this study, we characterised esketamine-induced mystical experiences in relation with clinical outcomes. We conducted a longitudinal observational study and systematically measured acute subjective effects in patients receiving esketamine for treatment-resistant depression after each administration across the induction phase. A total of 45 patients were included, from two independent centres, totalling 352 esketamine administrations. Principal Component Analysis (PCA) supported the validity of the Mystical Experience Questionnaire (MEQ-30) for assessing esketamine-induced subjective effects, with components recovering dimensions previously validated with classic psychedelics. Mystical experiences (MEQ-30 score above 60) occurred in 58% of patients, with high inter- and intra-individual variability in frequency, intensity, and phenomenology across sessions. Higher mean and peak MEQ scores were associated with greater improvement in Montgomery-Asberg Depression Rating Scale scores from pre- to post-treatment, whereas the intensity of dissociative or other non-mystical effects was not. Positive mood and mystical MEQ dimensions in particular predicted therapeutic outcomes. Baseline spirituality also significantly predicted treatment outcomes and peak MEQ scores in the first week of treatment. These findings add to the growing body of evidence suggesting that psychedelic-like mystical experiences may be associated to therapeutic efficacy, not only in classic psychedelic-assisted therapy, but also in esketamine treatment.

BackgroundA range of rare chromosomal micro-deletions or -duplications (Copy Number Variants - CNVs) are associated with high risk of neurodevelopmental and mental health conditions (ND-CNVs). There is great individual variability in outcomes, but we lack insights into the contributing social factors, including family functioning. MethodsCaregivers of 598 children and young people (CYP) with a range of 16 ND-CNVs and 222 siblings without ND-CNVs (controls) completed questionnaires on overall family climate (cohesion and conflict) as well as caregiver-CYP relationship warmth and hostility and took part in a research diagnostic interview about CYPs psychiatric symptoms. CYPs intelligence quotient (IQ) was also measured. ResultsComparisons with published data from neurotypical families indicated that families affected by ND-CNVs are characterised by higher family cohesion and conflict as well as lower caregiver-CYP warmth and hostility. Symptoms of oppositional defiant disorder reduced more steeply in CYP with ND-CNVs compared to controls with increasing family cohesion (interaction effect: {beta} = -0.14, p = 4.65 x 10-{superscript 2}). In contrast, they rose more steeply with increasing family conflict (interaction effect: {beta} = 0.18, p = 1.05 x 10-{superscript 2}). Furthermore, symptoms of mood disorder increased more steeply with increased caregiver-CYP hostility in CYP with ND-CNVs (interaction effect: {beta} = 0.15, p = 4.55 x 10-{superscript 2}). ConclusionsRaising a CYP with a rare genetic condition is challenging. Timely access to interventions that support caregivers in fostering a positive family environment may reduce behavioural difficulties in CYP, with subsequent benefits for family functioning.

Background: Hydrogen sulfide (H2S) is an endogenous gasotransmitter synthesised in the central nervous system (CNS) primarily by cystathionine {beta}-synthase (CBS) and cystathionine {gamma}-lyase (CSE). Pre-clinical studies consistently implicates H2S deficiency in the pathophysiology of depression through disruption of synaptic plasticity, neuroinflammation, oxidative stress, and brain-derived neurotrophic factor (BDNF) signalling. Yet, we still lack direct clinical evidence quantifying circulating H2S in patients with Major Depressive Disorder (MDD), particularly from South Asian populations. In this study, we measured serum H2S levels in drug-naive patients with MDD and compared them with healthy controls at a tertiary care center in eastern India. We examined the associations between serum H2S and depression severity as assessed by the 17-item Hamilton Depression Rating Scale (HAM-D-17). This institution-based, cross-sectional analytical study was conducted at North Bengal Medical College and Hospital (NBMCH), West Bengal, India, over 12 months. Fifty drug-naive patients fulfilling DSM-5 criteria for MDD and fifty age- and sex-matched healthy controls were enrolled by consecutive sampling. We quantified serum H2S using the spectrophotometric methylene blue method and depression severity was assessed using HAM-D-17. Statistical analyses included independent-samples t-test, chi-square test, and linear regression. Serum H2S was markedly and significantly lower in MDD patients (0.068 {+/-} 0.044 {micro}mol/L) compared with healthy controls (0.524 {+/-} 0.272 {micro}mol/L; p < 0.001), representing an approximately 7.7-fold reduction. HAM-D-17 scores were significantly higher in MDD patients (28.94 {+/-} 12.78) than in controls (3.96 {+/-} 2.31; p < 0.001). Linear regression across the combined cohort revealed a significant negative association between serum H2S and HAM-D score (R{superscript 2} = 0.287; y = 24.64 - 26.84x; p < 0.001), indicating that higher serum H2S was associated with lower depression severity. Within the MDD group alone, the regression was weak (R{superscript 2} = 0.061), consistent with a floor effect. Within the control group alone, the regression was strong (R{superscript 2} = 0.772). No significant associations were found between serum H2S and any sociodemographic variable in either group. Drug-naive MDD patients exhibited substantially reduced serum H2S levels compared with healthy controls, and lower H2S was associated with greater depression severity. These findings provide direct clinical evidence from an Indian population supporting the H2S deficiency hypothesis of depression and suggest that the CBS/CSE-H2S axis may represent a novel biomarker and therapeutic target in MDD. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/26352330v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1ce64f6org.highwire.dtl.DTLVardef@1465ca2org.highwire.dtl.DTLVardef@6bba64org.highwire.dtl.DTLVardef@9a1411_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundOptical coherence tomography (OCT) is increasingly used to investigate retinal structural changes across neurological and neuropsychiatric conditions. This systematic review and meta-analysis synthesises evidence examining retinal thickness in anxiety, depression, and substance use disorders (SUD) compared with healthy controls. MethodsA pre-registered systematic search (PROSPERO: CRD42024559542) of major databases following PRISMA guidelines was conducted. Case-control studies measuring retinal layer thickness via OCT in adults with DSM or ICD diagnosed anxiety, depression, or SUD were included. Multilevel random-effects models were used to calculate pooled standardised mean differences (SMD) and account for dependencies. ResultsThirty-three studies were included for narrative review, and 25 studies with 145 effect sizes were included for meta-analysis. The primary analysis, which pooled all disorders and effect sizes from available retinal thickness measures, found no significant differences between cases and controls (SMD = -0.20; 95% CI [-0.53, 0.14]; p = .244). Subgroup analyses for anxiety, depression, and SUD also yielded non-significant results (all p > .05). No specific retinal layer was consistently affected, and there was no evidence of an age x diagnosis interaction. Significant heterogeneity (Q = 756.57, p < .001) was present across analyses. ConclusionThis meta-analysis found no significant associations between retinal structural differences and anxiety, depression, or SUD. The field is characterised by high heterogeneity and publication bias, limiting the strength of evidence for the utility of OCT as a reliable biomarker for these conditions. Standardised, large-scale studies are needed with strict controls for confounding factors, including medication, disease stage and ocular parameters, alongside standardised OCT segmentation protocols. Article HighlightsO_LIFirst meta-analysis of OCT retinal thickness in anxiety, depression and SUD. C_LIO_LINo significant retinal thickness differences found between cases and healthy controls. C_LIO_LIAge and sex did not moderate the association between diagnosis and retinal thickness. C_LIO_LIHigh heterogeneity and publication bias limit utility of OCT as a neuropsychiatric biomarker. C_LIO_LIStandardised protocols are needed to clarify retinal changes in psychiatric research. C_LI

Objective: Neuropsychiatric presentations are common across neurological and mental health services but they are often inadequately covered by core clinical psychology and clinical neuropsychology training. Consequently, we aimed to identify components for a neuropsychiatry curriculum for clinical psychologists using a Delphi process. Method: We completed a three-round e-Delphi study with 19 experts (clinical psychologists, neuropsychologists, psychiatrists, neurologists, individuals with lived experience of neuropsychiatric disorders). Round 1 collected ratings on 80 syllabus items derived from textbook reviews, conference topics, and a scoping review of neuropsychiatry syllabuses. Items failing to reach consensus were refined, and new topics added via free-text suggestions. Rounds 2 and 3 repeated rating and thematic analysis, culminating in a consensus meeting where items were classified as core or supplementary. Consensus thresholds were set at mean>=2.0, mean distance from the mean<=0.2, and => 75% agreement for final decisions. Results: The process yielded 40 core and 38 supplementary syllabus items. Core topics include autoimmune and neuroinflammatory disorders, delirium, functional neurological disorders, neuropsychiatric sequelae of epilepsy, stroke, traumatic brain injury, dementia, and multidisciplinary working, among others. Supplementary items covered background knowledge of less frequent but still prevalent disorders as well as competencies in interpreting clinical data alongside conceptual and historical issues. The final component list reflects both clinical competencies and emerging areas of practice, emphasising assessment, formulation, psychological interventions, cultural considerations, and medicolegal aspects. Conclusions: The e-Delphi derived curriculum provides a framework for neuropsychiatric competencies for postgraduate psychology training with modification needed for application in diverse healthcare settings.

Background: Childhood adversity (CA) is recognized as a distal risk-factor for suicide attempts (SA) in individuals with psychiatric disorders. However, not all individuals with experiences of CA will engage in SA. Contributing to this relationship may be proximal factors such as impulsivity, inward anger and self-aggression. However, these factors are often conceptually blended and measured in different samples. We sought to clarify association among CA and personality factors in persons with SA. Methods: Participants from two studies comprised individuals with a diagnosed psychiatric disorder and history of SA (n= 139) and individuals with depressive disorder (clinical controls, CC; n= 24). We investigated self-reported levels of CA, impulsivity, inward anger, and self-aggression between the SA and CC (pcorr< .012). We tested the relationship among the factors using regression (pcorr<.017) and mediation model (indirect effects, p<.05) within the SA group. Sensitivity models were run controlling for age, gender, symptom severity, trait anger, and externally oriented aggression. Results: SA group had higher impulsivity (pcorr=.067) in a model controlled for age and gender. Other factors did not differ among groups. Within the SA group the analyses revealed positive association among CA and personality factors (pcorr<.06) in basic and model with age and gender, however the association was not specific for internally (self) oriented factors (coefficient comparison, p<.07). Parallel mediation model indicated that CA had indirect effect on self-aggression through impulsivity (p=.001) and to a lesser extent through inward anger (p=.066). Generally, models controlling for cognitive depression symptoms showed less prominent effects (pcorr>.1). Limitations: The study was cross-sectional and did not include behavioral tasks (state) measures of proximal factors. Conclusions: CA and personality factors showed similar severity levels among the SA and CC groups suggesting they may relate to broader psychopathologies, rather than specifically to SA. The association of CA with anger and aggression was unspecific to internally oriented factors indicating the need for more precise measuring instruments developed specifically for individuals with SA. Overall, the study highlights personality factors as being associated with risk in broader vulnerable populations.

BackgroundDepression is associated with an increased risk of subsequent Parkinsons disease. Neuroimaging studies suggest a neurobiological overlap in mechanisms underlying Parkinsons disease and psychomotor retardation in depression. Our aim was to investigate whether, among individuals with depression, the presence of psychomotor retardation was associated with the development of subsequent Parkinsons disease. MethodsIn a retrospective cohort study, electronic healthcare records from individuals diagnosed with depression at age 40 or over in a large mental health service in London, UK were examined for the presence of psychomotor retardation. Linkage to general hospital records was used to ascertain diagnoses of Parkinsons disease between 2007 and 2023. Cox regression was used to compare the hazard of Parkinsons disease in individuals with depression with and without psychomotor retardation. ResultsAmong 6327 patients with depression, 2402 (38.0%) had psychomotor retardation. The adjusted hazard ratio for development of Parkinsons in those with psychomotor retardation was 1.43 (95% CI 1.02 - 2.01, p = 0.04). Secondary analyses demonstrated a significant difference in psychomotor retardation incidence at least 10 years before Parkinsons diagnosis. ConclusionsPsychomotor retardation in later-life depression is associated with increased risk of subsequent Parkinsons diagnosis over an extended period of time, suggesting that the relationship cannot solely be explained by misdiagnosis. Psychomotor retardation may therefore serve as a marker of prodromal Parkinsons disease. HighlightsO_LIPsychomotor retardation was associated with later Parkinsons disease. C_LIO_LIPsychomotor retardation may present >10 years prior to Parkinsons diagnosis. C_LIO_LIDepression with psychomotor retardation may be a prodrome for Parkinsons disease. C_LI

IntroductionThere is a growing body of research showing that the menstrual cycle can affect mood, although research in those with an existing depressive disorder is still scarce. Studies estimate that 60% of women with depression experience premenstrual exacerbation (PME) of their depressive symptoms. AimsWith the TIDE study, we aim to 1) examine the feasibility of daily symptom tracking for two consecutive menstrual cycles to track PME, 2) estimate the prevalence of PME in depression in a clinical cohort and 3) examine whether PME is associated with other hormone-related mood symptoms (i.e., hormonal contraceptive side effects, peripartum depression). MethodsWe aim to recruit 60 female participants aged 18 to 45, who are in treatment for a depressive episode and who have a regular natural menstrual cycle. Participants will participate in questionnaires at baseline, inquiring about demographic characteristics and previous experiences with hormonal contraceptives and pregnancy. Participants will complete retrospective menstruation questionnaires on days 1 and 10 of each menstrual cycle, as well as daily diaries for two consecutive menstrual cycles, inquiring about menstruation and mood symptoms. After completion of the diaries, participants will receive a symptom report, as well as a study evaluation questionnaire. Results and conclusionWe expect that providing the menstrual cycle overview of symptom severity will lead to increased symptom course insights in participants with PME, and that participants with PME will find it clinically relevant and significant to gain insight into symptom trajectories across the menstrual cycle. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/26352210v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@1d6545eorg.highwire.dtl.DTLVardef@3ceb57org.highwire.dtl.DTLVardef@17ea0faorg.highwire.dtl.DTLVardef@7aa9f6_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundEarly adolescence is a common period of onset for depressive symptoms. In part, this may reflect a developmental manifestation of individuals genetic propensities as they undergo physiological and hormonal changes and interact with new environments. Many commonly proposed mechanisms assume direct effects of an individuals own genes on emerging variation in their depressive symptomatology. However, estimates of genetic influence based on analyses in unrelated individuals capture not only direct genetic effects but also genetic effects from parents and other biologically related family members. AimIn data from the Norwegian Mother, Father and Child Cohort (MoBa), we used linear mixed models to distinguish developmentally-stable and adolescence-specific direct and parental indirect genetic effects. We examined effects of polygenic scores for major depressive disorder (MDD), ADHD, anxiety disorders, and educational attainment (EA) on depressive symptoms, which were assessed by maternal reports at ages 8 and 14. ResultsChildrens own MDD polygenic scores showed adolescence-specific effects on depressive symptoms ({beta}PGS*wave=0.041, [95% CI: 0.017, 0.065]). Developmentally-stable direct effects from childrens polygenic scores for MDD ({beta}=0.016, [0.006, 0.039]), ADHD ({beta}=0.024, [0.008, 0.041]) and EA ({beta}=-0.02, [-0.038, -0.002]) were also evident. The only evidence of indirect genetic effects was a stable effect of maternal EA polygenic scores ({beta}=0.04, [0.024, 0.054]). ConclusionDirect genetic effects linked to genetic liability to MDD accounted for emerging variation in depressive symptoms in adolescence. These results imply that specific etiological mechanisms related to MDD may become particularly relevant for depressive symptoms during early adolescence compared to at earlier ages.

Background Complementary and Alternative Medicine (CAM) contributes significantly to the utilization of healthcare services in mental health care in sub-Saharan Africa. However, there is limited evidence on the utilization of CAM in the particular setting of post-conflict northern Uganda. This study sought to establish the prevalence, forms, and socio-demographic determinants of CAM use among patients attending the Mental Health Unit at Gulu Regional Referral Hospital (GRRH). Methods This is a cross-sectional study conducted in a hospital setting from June to August 2025. Convenience sampling was employed to recruit 407 participants. A structured questionnaire was employed for data collection. Data analysis was done using STATA software version 18.0. Descriptive statistics were calculated, and bivariate analysis with Prevalence Ratios (PR) with 95% confidence intervals was employed to determine factors that are significantly associated with the use of CAM. Results The lifetime prevalence of CAM use was 63.4% (258/407), with 41.3% (168/407) using CAM currently. The most frequent CAM practices used were herbal medicine (50.4%), spiritual practices (33.7%), and traditional medicine (19.8%). For current users, spiritual practices were most frequent (88.7%). The reasons for using CAM were recommendations from others (84.8%) and cultural or religious beliefs (63.4%). Predictors of CAM use were primary education (PR = 1.36, p = 0.017), living in an urban area (PR = 1.23, p = 0.007), separated (PR = 1.39, p = 0.050), and having a mental health disorder for six or more months (PR range = 1.55-1.72). Catholics (PR = 0.72, p = 0.0007) and Protestants (PR = 0.76, p = 0.011) were less likely to use CAM than Born Again Christians. Conclusion The level of CAM use among patients accessing mental health services in GRRH of northern Uganda is significantly high, while the reporting of CAM use to healthcare providers is remarkably low. This is a challenge that requires urgent attention. Recommendations include integrating the use of CAM into medical practice, developing national policy guidelines on CAM, working in collaboration with traditional/spiritual healers, and conducting public education campaigns.

Objective: Biopsychosocial models recognize multiple determinants of post-trauma mental disorders, but their relative and interactive effects remain unclear. We quantified the independent contribution of traumatic event severity, preexisting vulnerability, social support, and coping capacity, and tested mediation pathways. Methods: In a Brazilian clinical sample reporting traumatic or stressful events (N = 612), constructs were operationalized as composite scores and a dichotomous clinical outcome was derived from intake assessments. Logistic regression (n = 594) and structural equation modeling evaluated prediction and mediation. Results: Vulnerability was the strongest risk factor (OR = 1.46, p < .001) and social support the main protective factor (OR = 0.60, p < .001). Traumatic event severity remained an independent predictor (OR = 1.39, p < .001), whereas coping capacity was not significant (OR = 0.94, p = .410). Discrimination was good (AUC = 0.80). Mediation indicated vulnerability reduced social support and coping capacity, with a significant indirect effect via social support. Conclusions: Findings support a multifactorial model centered on a triad of vulnerability, social support, and traumatic exposure. Risk is shaped primarily by preexisting vulnerability and relational context, alongside a direct trauma effect, providing a clinically relevant framework for assessment and intervention.

BackgroundRett Syndrome (RTT) is a severe neurodevelopmental disorder affecting approximately 1 in 10,000 live female births worldwide. The Rett Syndrome Behaviour Questionnaire (RSBQ), remains one of the most widely used standardized behavioral assessment tools for RTT. However, the RSBQ was originally validated only in British English, limiting its applicability for Spanish-speaking caregivers and clinical centers across Latin America and Spain. ObjectiveThe primary aim of this study was to develop and validate the comprehension of the Spanish translation of the RSBQ to ensure cultural and linguistic equivalence, enhance data reliability, and facilitate earlier, more accurate clinical assessments among Spanish-speaking RTT populations. MethodsSurveys were administered in two phases to Spanish-speaking caregivers between November 2023 and September 2025. Phase I consisted of 12 guided survey administrations with participants being able to ask clarifying questions and offer linguistic modifications of RSBQ questions. Phase II consisted of independent online administration of the refined Spanish RSBQ and a retest at least 7 days later. Participants were recruited through direct outreach and supported virtually during questionnaire completion. ResultsFollowing data cleaning and quality control, a total of 51 caregivers successfully completed both surveys. The Spanish RSBQ demonstrated high caregiver comprehension and strong engagement across multiple Latin American countries, including Argentina, Mexico, and Peru. Responses were highly correlated between test and retest timepoints, and no question showed biased response distributions. A slight effect of response interval on test-retest correlation was observed, potentially indicating the impact of natural disease progression confounding retest evaluation for long (>80 day) intervals; however this effect did not impact the overall linguistic validation results as analysis of only <21 day test-retest responders confirmed the findings. ConclusionsThis linguistic validation study represents the first formal step toward the clinical validation of the Spanish RSBQ, enabling broader inclusion of Spanish-speaking populations in RTT research. The collaborative, bilingual data collection strategy proved both feasible and effective, paving the way for multinational trials and expanding therapeutic accessibility through localized, patient-centered innovation.

Objective: Major depressive episodes frequently show limited response to first-line treatments, motivating the search for objective biomarkers. EEG/ECG-based support tools aggregating electrophysiological predictors may guide treatment selection. We examined whether antidepressant treatments concordant with an EEG/ECG-biomarker report were associated with higher response rates. Methods: We retrospectively analyzed adults with ICD-10 depressive disorder or bipolar depression treated with electroconvulsive therapy (ECT), repetitive transcranial magnetic stimulation (rTMS), (es)ketamine, or selective serotonin reuptake inhibitors (SSRIs) between 2022 and 2024. Resting-state EEG with simultaneous ECG generated individualized biomarker reports with modality-specific response likelihoods. Treatment chosen by clinical teams was classified as concordant or non-concordant; response was derived from routinely collected clinical scales. Results: Among 153 patients (ECT n=53, rTMS n=48, (es)ketamine n=36, SSRIs n=16), response rates were higher for concordant vs non-concordant treatments: ECT 70% vs 50%, rTMS 30% vs 13%, (es)ketamine 31% vs 10%, and SSRIs 100% vs 11%. Overall, 46% (42/92) of concordant vs. 26% (14/54) of non-concordant patients responded (absolute difference +20 percentage points; relative increase {approx}77%; number needed to treat {approx}5). Conclusion: Concordance with EEG/ECG biomarkers correlated with higher treatment response, warranting confirmation in prospective trials. Significance: EEG/ECG-based decision support may enhance antidepressant treatment response in everyday clinical practice.

ObjectivesNeuropsychiatric symptoms (NPS) are prevalent in individuals of cognitive impairement (CI). However, the similarities and disparatenesses in whole-brain dynamics between individuals of CI and NPS are controversy. Electroencephalography (EEG) microstates reflect the whole-brain dynamics. This study aimed to investigate the differential EEG microstates parameters between CI and NPS and to construct related diagnostic model. Methods/designThis study was a cross-sectional study. Clinical and EEG data were collected, and an EEG microstate analysis were performed. The Least absolute shrinkage and selection operation (LASSO) regression model was used to identify significant differential EEG microstates parameters between CI and NPS and to construct a diagnostic model. The model performance was tested by the receiver operating characteristic curve (ROC). ResultsThis study enrolled 78 participants. A total of 36 EEG microstates parameters were identified and included in the differential analysis. In the LASSO regression model, 4 significant differential EEG microstates parameters were selected, including the duration of class C, TPAB, TPBA, and TPDC. The ROC results showed that the diagnostic model for distinguishing NPS patients from CI patients achieved an area under the curve (AUC) of 0.905(95% CI: 0.784-1.000), with a sensitivity of 100.0% and a specificity of 76.9%. ConclusionsThe diagnostic model based on EEG microstate parameters showed a good performance for differentiating NPS patients from CI patients.

ObjectiveTo characterize the familial patterns of misophonia and other commonly co-occurring neuropsychiatric conditions. MethodsWe examined cross-sectional survey responses from 101 probands with misophonia and their biological parents enrolled in a genetics study. ResultsProbands had a mean age of 24.6 {+/-} 11.6 years (8-64 years), were predominantly female (88%), and had high rates of co-occurring neuropsychiatric conditions, including anxiety (70%), depression (38%), ADHD (31%), and OCD (25%). Among probands, 39% had a first-degree relative with misophonia, and 48% had at least one any-degree relative with misophonia. In addition, many probands had at least one first-degree relative with anxiety (65%), depression (57%), ADHD (40%), OCD (20%), and autism (13%). Comparing rates of neuropsychiatric conditions reported by parents, mothers had significantly higher rates of misophonia (29% maternal vs. 9% paternal, p = 0.001) and anxiety (44% maternal vs. 26% paternal, p = 0.02) than fathers. ConclusionThese findings provide new insight into the familial patterns of misophonia and co-occurring neuropsychiatric conditions. Future research on underlying genetic and environmental factors is needed to shed light on the observed shared predispositions for misophonia and other neuropsychiatric conditions in families.

BackgroundMajor depressive disorder (MDD), a leading cause of disability worldwide, exhibits substantial heterogeneity in treatment outcomes. Patients who do not respond to standard antidepressant therapy account for the majority of MDDs disease burden. Risk factors have been implicated in treatment response, including genes impacting on how antidepressants are metabolised. Yet, despite its clinical importance, risk factors for treatment-resistant depression (TRD) remain unexplored in low- and middle-income countries (LMIC). We used data from the DIVERGE study on MDD to investigate the risk factors of TRD in Pakistan. MethodsDIVERGE is a genetic epidemiological study that recruited adult MDD patients ([&ge;]18 years) between Sep 27,2021 to Jun 30, 2025, from psychiatric care facilities across Pakistan. Detailed phenotypic information was collected by trained interviewers and blood samples taken. Infinium Global Diversity Array with Enhanced PGx-8 from Illumina was used for genotyping followed by DRAGEN calling to infer metaboliser phenotypes for Cytochrome P450 (CYP) enzyme genes. We defined TRD as minimal to no improvement after [&ge;]12 weeks of adherent antidepressant therapy. We conducted multi-level logistic regression to test the association of demographic, clinical and pharmacogenetic variables with TRD. FindingsAmong 3,677 eligible patients, polypharmacy was rampant; 86% were prescribed another psychotropic drug along with an antidepressant. Psychological therapies were uncommon (6%) while 49% of patients had previously visited to a religious leader/faith healer in relation to their mental health problems. TRD was experienced by 34% (95%CI: 32-36%) patients. The TRD group was characterised by more psychotic symptoms and suicidal behaviour (OR=1.39, 95%CI=1.04-1.84, p=0.02; OR=1.03, 95%CI=1.01-1.05, p=0.005). Social support (OR=0.55, 95%CI=0.44-0.69, p=1.4x10-7) and parents being first cousins (OR=0.81, 95%CI=0.69-0.96, p=0.01) were associated with lower odds of TRD. In 1,085 patients with CYP enzyme data, poor (OR=1.85, 95%CI=1.11-3.07, p=0.01) and ultra-rapid (OR=3.11, 95%CI=1.59-6.12, p=0.0009) metabolizers for CYP2C19 had increased risk of TRD compared with normal metabolisers. InterpretationThere was an excessive use of polypharmacy in the treatment of depression while psychological therapies were uncommon highlighting the need for more evidence-based practice. This first large study of MDD from Pakistan uncovered the importance of culture-specific forms of social support in preventing TRD, highlighting opportunities for interventions in low-income settings. Pharmacogenetic markers can be leveraged to predict TRD.

Pediatric bipolar disorder is challenging to diagnose accurately due to symptom heterogeneity. More standardized and data-driven approaches are needed to enhance diagnostic reliability. We evaluated a clinical decision tool (nomogram), statistical methods (logistic regression, LASSO), machine learning (support vector machine, random forest, k-nearest neighbors, extreme gradient boosting), and deep learning model (multilayer perceptron) for pediatric bipolar disorder prediction across two datasets collected in academic (N=550) and community (N=511) clinical settings. We compared three modeling strategies: cross-dataset validation, cross-dataset with interaction terms, and mixed-dataset. We assessed model performance using discrimination ability, calibration, and predictor importance ranking. In the baseline cross-dataset approach, all models showed good internal discrimination in the academic dataset; but external discrimination in the community dataset substantially declined. Interaction-enhanced models slightly improved internal discrimination but not external performance or calibration. Recalibration prominently improved cross-dataset calibration without compromising discrimination, indicating that transportability problems were largely driven by probability scaling. Models trained on mixed datasets exhibited much stronger external discrimination and calibration. Across models and training strategies, family risk and PGBI-10M were consistently ranked as the most important predictors. Predictive models for pediatric bipolar disorder showed strong internal performance but limited cross-setting generalizability due to dataset shift and miscalibration. Increasing model complexity did not improve external performance, whereas training on pooled data substantially improved both discrimination and calibration. Findings suggest that sampling diversity, rather than model complexity, is more valuable for developing clinically useful and generalizable psychiatric prediction models, underscoring the importance of open and collaborative datasets.

Background: Bipolar disorder (BD) is increasingly conceptualized as a heterogeneous condition with a neurodevelopmental phenotype (NDP) identifying a subgroup with early neurodevelopmental vulnerability and poorer clinical outcomes. Sensory processing (SP) abnormalities are a core feature of neurodevelopmental disorders but remain poorly characterized in BD and may reflect underlying neurodevelopmental liability. We examined whether NDP load is associated with specific SP alterations in euthymic BD patients and whether NDP-based stratification explains SP variability better than conventional BD subtype (BD 1/2). Methods: We assessed 102 euthymic BD patients and 45 healthy controls (HC) using the Adolescent/Adult Sensory Profile (AASP). NDP load (0-3) was computed from nine clinical variables grouped into neonatal, comorbidity, and neurodevelopmental clusters; a median split defined BD without NDP (BD) and BD with NDP (BD-ND). Associations between NDP load and AASP quadrants were analyzed using Spearman correlations with FDR correction. Group differences (BD, BD-ND, HC) were assessed using Welch ANOVA and post-hoc tests. Nested and multivariable linear regressions examined whether NDP classification explained SP variance beyond BD subtype, adjusting for age, sex, anxiety, and residual mood symptoms. Results: Higher NDP load correlated with greater low registration (rho=0.35, p<0.001, q=0.004), sensory sensitivity (rho=0.30, p=0.001, q=0.004), and sensation avoiding (rho=0.23, p=0.014, q=0.040), but not sensation seeking. BD-ND showed higher low registration, sensory sensitivity, and sensation avoiding than BD and HC (all qs<0.01). NDP classification explained more SP variance than BD subtype; with robust associations after adjustment. Conclusions: Sensory processing alterations in BD are dimensionally associated with neurodevelopmental load and more accurately captured by NDP-based stratification than diagnostic subtype. SP alterations may represent a transdiagnostic marker of neurodevelopmental liability within BD, supporting biologically informed stratification approaches.