Nature Mental Health

Mood fluctuations in major depressive disorder are difficult to anticipate. The biological neural rhythms that organize mood dynamics over days to weeks remain unknown. In individuals implanted with a chronic neural sensing and stimulation device for treatment-resistant depression, we collected years-long intracranial neural recordings alongside daily mood ratings. Both mood and limbic neural activity fluctuated cyclically with multiday (multidien) periodicities of 2-34 days. An individual's daily phase position within mood cycles tracked depression severity, distinguishing whether symptoms were rising, peaking, or resolving. Neural rhythms led mood cycles and forecast an individual's mood trajectory up to 30 days in advance, outperforming models based on raw neural activity. Electrical stimulation reshaped these rhythms, shifting individuals away from the peak-depression phase of their multidien cycle. Our results identify multidien rhythms as an organizing principle of mood in depression and a forecastable, modifiable target for chronotherapeutic neuromodulation.

Background: Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental condition lacking mechanistically grounded interventions. Here, we tested whether transcranial photobiomodulation (tPBM) can restore neural homeostasis in ADHD patients. Methods: In a randomized, double-blind, sham-controlled crossover design, 28 young adults with ADHD completed a two-week intervention, receiving active (150 mW) and sham (0 mW) stimulation over the right prefrontal cortex for 16 minutes with concurrent electroencephalography (EEG) recording, alongside 29 healthy controls providing a normative reference. Results: Behaviorally, tPBM improved working memory K scores in the ADHD group, with performance closer to typical levels. Across sensor and source levels, tPBM progressively increased relative alpha power, steepened the aperiodic exponent, and enhanced neural complexity, as indexed by multiscale entropy, with widespread effects spanning frontoparietal and attention systems, extending to sensory and default-mode regions, collectively indicating a shift toward normative neural dynamics. Notably, these changes--consistent with rebalanced excitation/inhibition dynamics--predict behavioral improvements in working memory. Conclusions: Together, our findings identify tPBM as a candidate approach for restoring excitation/inhibition balance and normalizing large-scale neural dynamics in ADHD patients, providing a mechanistic foundation for its therapeutic potential.

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.

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.

Lesion Network Mapping (LNM) is a framework used for identifying symptom-related brain circuits by projecting lesion locations onto a normative connectome. Recent methodological investigations have raised concerns about the biological interpretation and specificity of the circuits derived using this method, with published LNM maps often showing high similarity across clinically unrelated conditions. Specificity testing has subsequently been put forward as the decisive step to ensure specificity to the symptom in question, accompanied by the argument that this step was not evaluated in the original methodological investigation. Yet, sensitivity testing, specificity testing, case-control LNM, permutation of group labels, and symptom-based LNM involve related operations on connectivity matrix C. We expand on specificity testing in LNM, clarify its relationship to other LNM steps and variants, and examine the persistent repetition among LNM specificity networks across studies. These considerations advance our understanding of the disease-specificity limitation of LNM and encourage the development of new methodological approaches for identifying brain circuits underlying psychiatric and neurological disorders.

Adolescent substance use is a major public health concern due to increased risk of future physical and mental health conditions. Fronto-striatal functioning - particularly regarding inhibition and reward processing - may increase vulnerability to high-risk substance use. However, it remains unclear if these neurobiological differences precede substance use or are consequences of it. The ongoing Adolescent Brain Cognitive Development (ABCD) Study follows over 10000 youth, offering an unprecedented opportunity to longitudinally examine substance use patterns throughout development. We utilized family-clustered time-varying Cox proportional hazard models to prospectively examine main and interaction effects of right Inferior Frontal Gyrus (IFG) inhibitory control and bilateral nucleus accumbens (NAc) reward response, alongside early life adversity and peer substance use as predictors of alcohol and cannabis onset in the ABCD Study. We identified a significant crossover interaction such that left NAc activity had a slight positive association with first full alcoholic drink in the context of higher right IFG activity but a negative association in the context of lower right IFG activity. However, peer alcohol and cannabis use emerged as the strongest predictors of outcomes. Alcohol onset was also more common in females, and early life adversity was associated only with cannabis onset. Findings indicate that interactions between inhibition- and reward-related brain regions may impact risk for early substance use onset, but these effects may be modest relative to socioenvironmental factors. Additionally, divergent alcohol and cannabis findings suggest that risk profiles are substance specific. Peer-focused strategies should be considered in preventive efforts.

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: A 2025 systematic review concluded there was "strong evidence of a likely relationship" between prenatal acetaminophen exposure and neurodevelopmental disorders, informing a federal health advisory, based on qualitative synthesis without quantitative pooling or bias correction. We reanalysed the same studies to test whether this association withstands standard meta-analytic and bias-correction methods. Methods: We used 24 of 46 studies from a 2025 Navigation Guide systematic review (PubMed search through 25 February 2025) that reported a ratio measure (hazard ratio, odds ratio, relative risk, or incidence rate ratio). Estimates were collapsed to one per study, outcome group, and design, yielding 30 study-level estimates (sample sizes, 307-2,480,797) for attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and other neurodevelopmental disorders. We applied random-effects meta-analysis, eight publication-bias-correction methods, a credibility-ceiling sensitivity analysis, and five quality-filtered subsets, then repeated all analyses after harmonising odds and hazard ratios onto a common risk-ratio scale. Results: The ASD association attenuated from 1.14 (95% CI, 1.01-1.28) to 1.08 (95% CI, 0.97-1.19; P=.17) once each study was weighted once rather than by its number of sub-analyses, before any bias correction. The ADHD association remained positive under most bias-correction methods (range, 1.02-1.31), but its 95% CI crossed 1.00 under a 15% credibility ceiling. The other-NDD association reversed direction under one method (ratio, 0.98; 95% CI, 0.65-1.19) and showed no right-skew on p-curve testing (P=.71). Conclusions: The claim of "strong evidence" for an acetaminophen-neurodevelopmental-disorder association was not supported by this reanalysis. A modest ADHD association persisted, while ASD and other-NDD estimates moved toward the null.

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.

Psychosis has long been conceptualized as a disorder of disrupted hierarchical integration across distributed brain systems, yet it remains unclear whether alterations in macroscale cortical hierarchy are already present before illness onset and are associated with subsequent transition to psychosis. Using connectome gradient mapping, we characterized baseline cortical hierarchical architecture along the unimodal-to-transmodal axis in 580 participants from the NAPLS-3 cohort, including converters (CHR-C, n = 56), non-converters (CHR-NC, n = 434), and healthy controls (HC, n = 90). Group differences were assessed at regional, network, and global levels. Group comparisons revealed that CHR-C individuals, relative to the other two groups, exhibited bidirectional alterations selectively along the sensorimotor-to-association gradient, with reduced values in the visual network alongside elevated values in the default mode network, indicating greater separation between sensory and transmodal systems along the gradient. At the global level, CHR-C showed increased explained variance, range, and variation of this gradient, collectively indicating hierarchical expansion. Notably, greater explained variance of this gradient was associated with a shorter time to conversion to psychosis, while increased gradient range and variation were associated with higher positive symptom severity across CHR individuals. These findings indicate that expansion of the sensorimotor-to-association connectome hierarchy is already present before psychosis onset in individuals who subsequently convert to psychosis. This altered hierarchical organization may reflect greater decoupling between sensory and transmodal systems and may characterize neurobiological changes associated with progression from a clinical high-risk state to psychotic illness.

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 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: 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.

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: 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.

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.

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.

Schizophrenia (SCZ) frequently co-occurs with substance use disorders (SUDs), yet the genetic basis of this comorbidity remains unclear. Using the latest European-ancestry genome-wide association studies (GWAS) for SCZ, cannabis use disorder (CanUD), opioid use disorder (OUD), problematic alcohol use (PAU), tobacco use disorder (TUD), and a general addiction factor (AF), together with two SCZ and one SUD case-control samples with individual-level genotype data, we applied multiple complementary genomic approaches to characterize their shared genetic architecture. Significant positive genome-wide genetic correlations were observed across all SCZ-SUD pairs. Local genetic correlation analyses identified multiple genomic regions contributing to this shared architecture, with both positive and negative correlations, and evidence of genomic regions shared across multiple SCZ-SUD pairs. Polygenic overlap analyses indicated substantial sharing (25-50%) of trait-associated variants between SCZ and SUDs. Genomic structural equation modelling supported a common latent factor underlying SCZ and all SUDs, accounting for approximately 23% of SCZ variance. Cross-trait polygenic risk score (PRS) analyses showed bidirectional associations between SCZ and SUD genetic liability. Mendelian randomization analyses provided evidence for a bidirectional causal relationship between SCZ and CanUD. Horizontal pleiotropy analyses identified numerous loci with concordant and discordant effects across traits, including loci shared among multiple SCZ-SUD pairs. Gene mapping and enrichment analyses indicated pathways related to neuroplasticity, synaptic transmission, immune system, metabolism and proteolysis, including both shared and SCZ-SUD specific biological processes. Overall, these findings suggest that part of SCZ liability reflects genetic susceptibility to SUDs with potential implications for patient stratification and clinical management.