Biological Psychiatry Global Open Science

Exposure is considered the most active element of cognitive behavioral therapy (CBT) for pediatric anxiety, and its efficacy is theorized to depend on cognitive control and its supporting neural substrates (e.g., central executive [CEN], salience [SN], and default mode networks [DMN]). However, little work has identified how CBT, or exposure specifically, modulates intrinsic connectivity of these networks. Progress may be limited by heterogeneity in network connectivity in anxiety, which may obscure treatment-related effects in group-averaged analyses. This randomized clinical trial (RCT) leverages person-specific network modeling to test how exposure-focused CBT (EF-CBT) influences resting-state connectivity of cognitive control networks in pediatric anxiety, relative to an active control (relaxation mentorship training; RMT). Youth aged 7-18 years with an anxiety disorder (N = 104) or low/no anxiety (L/NA; N = 37) completed resting-state fMRI scans before being randomized to EF-CBT or RMT. Resting-state connectivity was reassessed following treatment (or commensurate time L/NA youth) in 113 participants. Changes in within-CEN, CEN-SN, and CEN-DMN density were examined using Group Iterative Multiple Model Estimation, which yields sparse, person-specific networks capturing both shared and individual connectivity structure. At baseline, anxious youth exhibited lower density within-CEN, between CEN-SN, and between CEN-DMN than L/NA youth. Treatment effects differed by intervention: EF-CBT selectively increased (i.e., normalized) CEN-SN density, whereas RMT increased within-CEN density. These findings demonstrate dissociable effects of exposure and relaxation on cognitive control network organization in pediatric anxiety. Exposure-focused CBT uniquely strengthens coordination between control and salience systems, consistent with a mechanism supporting top-down control of threat-related signals during exposure. Network-based measures of cognitive control may help identify mechanistic targets for optimizing and personalizing treatment. Clinical Trial NumberNCT02810171.

BackgroundEarly-life adversity can alter emotional and social development and increase vulnerability to later life stress. We investigated how early adverse experiences (EAE) and later adverse experiences (LAE) shape adult emotional contagion (EC) responses in female and male rats. MethodsEAE was induced using the limited bedding and nesting model during the first postnatal week. LAE was induced via footshocks during adolescence. In adulthood, male and female rats underwent an EC test in which observers witnessed a conspecific receiving footshocks. ResultsAdolescence-footshock exposed observers showed cingulate cortex-associated increased immobility, proximity, and attention toward distressed conspecifics during adulthood, compared to adult-exposed and sham animals, both in male and female animals. While EAE did alter maternal care, pup stress physiology, and pup weight, we found evidence that it did not alter immobility during EC. However, female demonstrators paired with EAE observers showed increased immobility, linked to a reduced rate and lower frequency of the observers 50-kHz vocalizations. Mediation analysis revealed that a shift toward lower-frequency 50-kHz vocalizations specifically mediated this effect, suggesting a sex-specific pathway by which early adversity shapes social behavior. ConclusionsEarly and adolescent adversity influenced distinct aspects of emotional contagion: EAE mediated an observer-to-demonstrator emotional transfer during EC, while LAE impacted a demonstrator-to-observer transfer, with no evidence of additive effects. Our results highlight developmentally specific and sex-dependent mechanisms by which early and later adversity alter social-affective responses in adulthood.

BackgroundMajor depressive disorder (MDD) involves immune-metabolic dysregulation, psychosocial adversity, and multidomain cognitive disturbances, yet single cognitive indices often show small and inconsistent effects. We derived a multivariate Cambridge Neuropsychological Test Automated Battery (CANTAB)-based cognitive phenotype ("cognitype") and tested whether it adds explanatory value beyond adverse childhood experiences (ACEs) and an acute-phase protein (APP) index in acute-phase MDD. MethodsEighty-seven acute-phase MDD patients and 40 healthy controls completed CANTAB testing; key outcomes from DMS, RVP, OTS, and ERT were summarized as a cognitype score (PC1). ACEs were assessed, and peripheral inflammatory markers were combined into an APP index. Logistic and multiple regression models tested discrimination between MDD and controls and prediction of multidimensional phenome features (affective, physio-somatic, vegetative, recurrence-related, personality, and suicidality domains). ResultsIndividual CANTAB outcomes showed limited between-group differences after FDR correction, but multivariable models integrating cognitive measures with ACEs and APP robustly discriminated MDD from controls (AUC up to 0.907). The cognitype independently predicted multiple phenome domains when modeled alongside ACEs and APP, and their combined effects explained [~]40-55% of variance across symptom dimensions. ConclusionA data-driven cognitype derived from core CANTAB tasks captures clinically meaningful cognitive variation in acute-phase MDD and contributes significant predictive value beyond psychosocial adversity and inflammatory activation. Integrating cognition, ACEs, and inflammation improves characterization of symptom heterogeneity and supports precision approaches targeting neurocognitive-immune-environmental mechanisms.

Perinatal depression (PD) is common and disabling, yet its longitudinal comorbidity patterns and predictability remain poorly understood. This study leveraged 8,804 women with delivery records in the All of Us cohort, including 438 with clinically diagnosed postpartum depression (PPD), to characterize multimorbidity trajectories and develop integrated prediction models. Comorbidities were grouped into 38 conditions across psychiatric, autoimmune, metabolic, neurological/pain, and reproductive/gynecological categories and examined both cross-sectionally and in monthly time bins from 250 months before to 500 months after delivery. Latent class analysis identified three pre- and post-delivery multimorbidity profiles and transitions between classes, while polygenic risk scores for depression and obstetric, clinical and socioeconomic variables were combined in machine learning models to predict PPD, post-delivery class membership, and symptom worsening among initially low-burden women. PPD cases showed higher odds of several psychiatric, autoimmune, and metabolic conditions and a tendency toward greater post-delivery comorbidity accumulation, particularly among women who were healthy pre-pregnancy. Multimorbidity profiles based on latent classes captured clinically meaningful risk gradients, and transition analyses revealed that incident PPD in previously healthy women marked a shift toward more symptomatic post-delivery profiles. Machine learning models achieved moderate discrimination for PPD and comorbidity outcomes and highlighted the importance of genetic liability, obstetric complications, and socioeconomic disadvantage, but low positive predictive values limit clinical implementation. These findings position PPD as a critical event in womens psychiatric, cardiometabolic, and pain-related health trajectories and support life-course, multimorbidity-informed screening and prevention strategies that extend beyond the traditional postpartum period.

Children exposed to severe childhood maltreatment often develop complex mental health disorders where standard treatments show limited efficacy. Current residential approaches combine psychopharmacological with behavioural interventions, yet the feasibility and clinical-neurobiological outcomes of intensive, medication-free psychotherapy have not been investigated in this population. Our prospective study followed severely traumatized children (aged 6-13 years) with documented histories of changes and failures in placement.They completed an intensive 6-8 months inpatient treatment program (5 individual psychotherapy and 3 group therapy sessions per week with high caregiver-patient ratio) grounded in a novel, multimodal, attachment-based therapeutic framework. Medication was discontinued prior to treatment. The intervention group was compared to healthy controls and waitlist controls receiving treatment as usual. Participants in the intervention group achieved high remission rates for dysregulated behaviour (Child Behaviour Checklist (CBCL) >60% post treatment, 50% on follow-up) and trauma-related symptoms (Parent Report of Post-traumatic Stress Symptoms (PROPS) >65% post treatment, >60% on follow-up). Within-group effect sizes for Total Problems Score, Externalising behaviour (both CBCL), Hyperactivity (Strengths and Difficulties Questionnaire) and trauma symptoms (PROPS) each exceeded Cohen's d = 1.0 and were maintained at 6-month follow-up. Resting-state fMRI identified significant functional reorganization in visual processing networks. Atypical correlation patterns between visual network activity and symptom severity resolved following treatment, yielding patterns comparable to those of healthy controls. These pilot findings provide initial evidence of the feasibility and effectiveness of intensive, medication-free, attachment-based inpatient treatment to promote clinical remission and neurobiological normalization in severely traumatized children.

BackgroundThe Michigan Freshman Study on Stress and Resilience aims to identify factors that predict the emergence of depression and/or anxiety symptoms in college freshmen. We previously showed that a combination of psychiatric instruments (Affect Score) strongly predicts who will develop such symptoms during the freshman year. Here, we ask: a) Can we replicate the predictive power of the Affect Score in an independent cohort? and b) Can the neuroendocrine profile during the Trier Social Stress Test (TSST) serve as an additional predictor? MethodsA new cohort of subjects (N= 357) was used for Affect Score replication. The TSST study involved 337 subjects (Females 184, Males 153). Self-report questionnaires at the start of the year were used to derive the Affect Score. GAD-7 and PHQ-9 were used to monitor anxiety and depression, respectively. TSST measures involved plasma ACTH and Cortisol and heart rate monitoring. ResultsThe Affect Score proved to be a highly replicable predictor of future depression and anxiety. In the TSST, subjects not currently depressed but who developed depression at another timepoint during the year showed a higher and delayed peak of the CORT response. Female subjects not currently anxious but who developed anxiety at another timepoint had an elevated CORT response throughout the TSST. This hyperresponsiveness was not correlated with Affect Score and was an independent predictor of anxiety. Present addressMichigan Neuroscience Institute, University of Michigan, A. Alfred Taubman Biomedical Science Research Building, Rm 2009, Ann Arbor, MI, 48109-9901, USA Author ContributionsHK performed research, analyzed data, wrote the paper; CAT designed research, performed research, wrote the paper; VM-W designed research, performed research; LG, FL, AO, KA and LW performed research; CS coded and analyzed data; JFL designed research; SJW Jr designed research; HA designed research, wrote the paper. FundingThis work was supported by the Office of Naval Research (ONR) Grant N00014-09-1-0598, N00014-12-1-0366 and N00014-19-1-2149, the Pritzker Neuropsychiatric Disorders Research Consortium Fund, LLC and the Hope for Depression Research Foundation. This project was also supported by Grant Number P30DK020572 (MDRC) from the National Institute of Diabetes and Digestive and Kidney Diseases. Competing interestsThe authors declare no competing interests. ConclusionsThe Affect Score is a powerful predictor of depression and anxiety in college freshmen. The combination of Affect Score and TSST is strongly predictive of anxiety in females.

Background: Major depressive disorder (MDD) is the leading cause of non-fatal disability in youth and disproportionately affects adolescent females. Structural MRI studies of adolescent depression have yielded inconsistent findings, potentially reflecting symptom heterogeneity and rapid developmental changes in brain morphology. Methods: In this longitudinal study, we examined associations between specific depressive symptoms and structural brain MRI measures in 9,722 youth (53% male, age range = 10.0-17.7, 24,378 observations) from the Adolescent Brain Cognitive Development (ABCD) Study. A four-wave panel graphical vector autoregression (GVAR) model was estimated to separate within-person (contemporaneous and temporal networks) from stable between-person effects. Brain measures included cortical thickness in the insula, cingulate, medial orbitofrontal cortex (mOFC) and fusiform gyrus, as well as hippocampal volume. Depressive symptoms included parent-reported depressed mood, anhedonia, lethargy, and worthlessness. Additionally, sex-differences in network structures were tested. Results: Strong within-domain associations were observed among brain measures and among symptoms, with the largest effects in the symptom domain. Cross-domain (brain-symptom) associations emerged only at the within-person level, where elevated depressed mood was associated with contemporaneous and subsequent reductions in cingulate and fusiform gyrus thickness (partial r = [-0.02 - 0.04]). No cross-domain associations were detected in the between-person networks. Sex-differences emerged only in the within-person networks. Conclusions: Associations between brain structure and depressive symptoms were subtle, symptom-specific, and dynamic rather than reflecting stable individual differences. Longitudinal within-person approaches are therefore important for understanding neurodevelopmental contributions to adolescent depression risk.

Progress in pharmacological treatment development for neurodevelopmental disorders is hindered by a misalignment between targeted mechanisms, outcome measures, and trial designs. This study was initiated as a post-trial access pathway for bumetanide and later expanded with treatment-naive participants. Within this framework, we implemented a parent-cocreated sensory outcome measure set (PROMset) in an unmasked, multiple-baseline single-case experimental design with randomized baseline periods of 2-12 weeks, followed by 6 months of bumetanide treatment (up to 1.5 mg twice daily). Participants (7-19 years) had atypical sensory reactivity and a diagnosis of ASD, ADHD, epilepsy, or TSC. The primary outcome was a PROMset comprising seven PROMIS item banks assessing anxiety, depressive symptoms, sleep disturbance, fatigue, sleep-related impairment, cognitive function, and peer relationships. Secondary outcomes included SSP, SRS-2, RBS-R, and ABC. Of 113 enrolled participants (mean age 13.2 [SD 2.7], 64% male), 102 completed the trial and 95 had analyzable PROMsets. At baseline, PROMset scores showed substantial impairment across domains (mean deviation =9.0 T-score points, p<.001) and correlated with sensory reactivity (SSP; r=-0.40, p<.001). Individual-level analyses showed improvement in 24-41% of participants per PROM domain, most frequently in anxiety and depressive symptoms (41% and 38%; mean across-case Cohen's d=-1). Overall, 83% improved on at least one domain. Group-level analyses showed improvement across all secondary outcomes (p<.001), with superiority over historic placebo for RBS-R and SSP. Integrating PROMsets with individualized trial designs can reveal clinically meaningful changes, supporting a more sensitive and patient-centered framework for treatment evaluation in heterogeneous populations.

BackgroundMajor depressive disorder (MDD) severely impairs individual health and creates heavy societal burdens. Diagnostic and therapeutic research remains hindered by MDDs marked heterogeneity and the absence of valid biomarkers. As a neuro-immune, metabolic, and oxidative stress (NIMETOX) disorder, MDD exhibits metabolomic signatures as a final common pathway in the Chinese population. ObjectivesTo identify lipidomic profile differences between MDD patients and healthy controls and examine associations between lipidomic alterations and clinical phenotypes. MethodsWe recruited 125 MDD patients and 40 healthy controls, and measured serum lipidomic profiles using liquid chromatography-mass spectrometry. A rigorously controlled multistage machine learning pipeline with leakage-prevention measures was utilized to examine disparities between MDD and control groups and to predict phenome features. ResultsWe identified 43 differentially abundant lipids between the MDD and control groups. Subsequent factor analysis clustered the 43 lipids into 3 functional modules, namely the increased ceramide/GM3/LNAPE (CERLNAPE) module, the decreased mitochondrial fatty acid oxidation/acetyl-flux (CARSM) module, and the reduced lysophospholipid/ether-lysolipid (LYSOPE) module. The three lipidomic modules correlated with six previously reported metabolomic functional domains, establishing an integrated metabolomics-lipidomics architecture in MDD. A substantial portion of the variance in the overall severity of depression (74.0%), physiosomatic symptoms (58.5%), suicidal ideation (11.1%), and recurrence of illness (36.6%) was associated with the integrated metabolomics-lipidomics architecture. ConclusionThe MDD lipotype indicates a unified metabolic network linked to the NIMETOX pathophysiology of MDD. Lipidomics provides a robust foundation for subtyping and precision psychiatry. Ceramide, acetyl carnitine, lipotoxicity, and plasmalogens are potential drug targets to treat MDD.

PTSD is defined by a core of inter-connected symptom clusters. It is currently unclear whether this pattern of interconnections remains stable across the lifespan or differs across key developmental periods. Synthesising seven international trauma-exposed samples (N=5,470), we compared network interrelationships among core self-reported and/or caregiver-reported PTSD symptom clusters (re-experiencing, avoidance and arousal) in preschoolers, school-aged children, adolescents, and adults. For self-report from school-age to adulthood, within-cluster connectivity (associations among symptoms within the same cluster) was consistently stronger than between-cluster connectivity (associations among symptoms from different clusters) across all age groups. This was especially true for the re-experiencing symptom cluster. These inter-relationships appeared stable across with lifecourse with no significant age-related differences. In contrast, caregiver reports from preschool to adolescence, showed stronger within-cluster connectivity among arousal symptoms but these only emerged in school-aged children and adolescents. Longitudinal analyses across approximately the first year post-trauma of self-report symptoms indicated that adults overall symptom connectivity increased over time, whereas school-aged childrens and adolescents networks became sparser. These findings suggest that while PTSD network architecture is broadly stable across different age groups, reporter discrepancies and temporal dynamics warrant close attention, especially with regards to less visible, internalised symptoms such as re-experiencing.

Childhood obesity remains a pressing global health challenge, yet the impact of dynamic adiposity changes during active developmental window retains poorly understood. Leveraging longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study (N=8519 at baseline; N=1873 at 4-year follow-up), our study reveals distinct neurodevelopmental implications of central fat dynamics during adolescence. At baseline, central fat indices (body roundness index, BRI / waist-to-height ratio, WHtR) outperformed BMI in predicting cognitive deficits, showing robust associations with impaired inhibitory control and episodic memory. The prediction effect was partially mediated by cortical changes in prefrontal and temporal regions. Longitudinally, the rate of fat accumulation ({Delta}) emerged as a critical predictor: faster adiposity accrual predicted attenuated cortical thinning (i.e., slower development) in parietal lobes and poorer executive function at follow-up, while baseline adiposity showed no significant effects on the follow-up brain morphology or cognitive development. Notably, subgroup analyses uncovered that obese adolescents with central fat reduction exhibited accelerated cortical thinning in posterior cingulate (change difference p=0.006-0.029) alongside rapid improvement in inhibitory control (Flanker slope difference p<0.05), whereas those with persistent adiposity showed delayed thinning in the postcentral gyrus. The study reveals that central fat (BRI/WHtR) is closely linked to neurocognitive risks, and longitudinal fat accumulation?rather than baseline adiposity?drives cortical alteration. Notably, fat reduction activated adaptive neural change in obese adolescents, underscoring the importance of weigh regulation during neurodevelopment.

A growing number of studies point to a key role of the amygdala in Autism Spectrum Disorders (ASD). The amygdala is involved in several processes in ASD including emotional valence, facial recognition, regulation of social learning, empathy, and anxiety. Brain imaging and postmortem studies demonstrate altered amygdala development in children with ASD, associated with impairment in social behavior and anxiety. There is limited information regarding the molecular pathology of the amygdala in children with ASD. We conducted RNAseq profiling on postmortem amygdala samples from male children (4-14 yrs old) with ASD (n=8) and normotypic male children (n=6). Furthermore, we conducted drug repurposing analysis to identify compounds predicted to reverse the transcriptomic signatures identified in order to identify potential therapeutic targets for development of early intervention treatments. Full transcriptome gene expression profiling implicated molecular pathways involved in neuroimmune signaling, glycogen and carbohydrate metabolism, matrix metalloproteases, neurodevelopment, estrogen receptor signaling, and synaptic signaling. Targeted pathway analysis of the top 10% of differentially expressed genes implicated pathways involved in extracellular matrix organization, immune signaling, and synaptic signaling. Our drug repurposing analysis identified sleep modifying compounds and anti-inflammatory compounds including COX2 and GSK3 inhibitors amongst the top predicted therapeutic compound classifications. PDGF receptor tyrosine kinase inhibitors were identified as a top potential therapeutic mechanism of action. Our results point to alterations in immune signaling, extracellular matrix organization, and synaptic signaling in the amygdala of children with ASD. Furthermore, our results identified a number of potential therapeutic drug targets for development of early intervention strategies.

Psychotic-like experiences (PLEs) are common in youth and predict later mental health problems. Bullying victimization is a robust environmental risk factor for psychopathology including PLEs, but whether its association with PLEs reflects shared genetic liability, individual-specific putatively causal effects, or reciprocal processes is unclear. We analyzed seven waves of longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study, examining associations across the sample in addition to leveraging within-family comparisons among twin and sibling pairs who were concordant or discordant for exposure to bullying victimization. Using linear mixed-effects and cross-lagged models, we found that youth reporting bullying victimization were more likely to endorse significantly distressing PLEs than non-victimized youth (caregiver-reported odds ratio=2.35; youth-reported odds ratio=4.10). Longitudinal analyses revealed bidirectional associations: prior bullying predicted subsequent increases in distressing PLEs, and prior PLEs predicted elevated risk of later bullying victimization. Genetically-informed within-family analyses indicated that both shared genetic influences and individual-specific factors contributed to these associations; critically, bullied youth exhibited higher odds of distressing PLEs than their non-exposed siblings (youth-reported odds ratio=6.67; 95%CI:4.96-8.96), consistent with an individual-specific effect of victimization. Together, these findings suggest that bullying and PLEs are linked through reciprocal developmental processes that are not fully explained by familial confounding. More broadly, our results highlight bullying prevention as a plausible leverage point for reducing early psychosis-spectrum risk and illustrate the value of integrating within-family designs to help disentangle genetic and environmental contributions to mental health outcomes in adolescence. Significance StatementUnderstanding how early adversity shapes mental health trajectories is important for science and public policy. Using nationally representative, longitudinal twin and sibling data, analyses show that bullying victimization and psychotic-like experiences in youth are linked through reciprocal processes that cannot be fully explained by shared genetics or family background. Bullied youth were more likely to endorse distressing psychotic-like experiences than their own non-bullied siblings, providing rare evidence for individual-specific effects of bullying victimization. Early psychotic-like experiences also increased subsequent risk of being bullied, suggesting a potential feedback loop that may compound risk. These findings demonstrate how social environments and mental health dynamically interact and point to bullying prevention as a population-level strategy with potential to reduce early psychopathology risk.

ImportanceEating disorders (EDs) are heritable, yet the developmental pathways through which genetic liability manifests in early life remain unclear. ObjectiveTo investigate the associations between genetic liability for anorexia nervosa (AN) and binge eating (BE) and disordered eating behaviors (DEB) across childhood, and to identify the mediating roles of metabolic and psychosocial traits. Design, Setting, and ParticipantsThis longitudinal observational study used genomic and behavioral data from the Adolescent Brain Cognitive Development SM (ABCD(R)) Study, a multisite, population-based cohort of children recruited between 2016 and 2018 at ages 9 to 10 years from 21 research centers across the United States. A three-wave temporal design was employed, utilizing data from baseline (T0), Year 1 (T1), and Year 2 (T2) follow-ups. Primary analyses focused on 5,618 participants of genetically inferred European (EUR) ancestry, with exploratory analyses conducted in a diverse sample of 9,132 participants. ExposuresPolygenic scores (PGS) for AN and BE were calculated using summary statistics from the most recent genome-wide association studies. Mediators included BMI, ADHD, anxiety/depression, and social problems from the Child Behavioral Checklist assessed at Year 1 follow-up (T1). Main Outcomes and MeasuresParent reported DEB symptoms via the Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS). For longitudinal association analyses, DEB were pooled across T0, T1 and T2 to assess the relationship between genetic liability and childhood symptom severity. For mediation analyses, DEB at T2 follow-up were used to ensure a clear temporal sequence between mediators at T1 and the outcomes. ResultsAmong 5,618 EUR participants (mean [SD] age, 9.91 [0.62] years; 47% female), longitudinal association models revealed that higher AN-PGS was associated with increased AN symptoms, while BE-PGS was associated with increased BE and AN symptoms. These patterns were largely consistent in exploratory cross-ancestry analyses. Mediation analyses showed that BMI mediated genetic risks across sexes, while ADHD and anxiety/depression symptoms emerged as additional mediators in females. Conclusions and RelevanceGenetic liabilities to AN and BE contribute to childhood DEB through sex-dependent pathways, highlighting the developmental continuity of ED risk from childhood. Integrating genetic profiles with behavioral markers may facilitate early identification and support multifaceted interventions. Key points QuestionDo genetic risks for anorexia nervosa (AN) and binge eating (BE) contribute to childhood disordered eating behaviors, and what mechanisms mediate these effects? FindingsIn this longitudinal study of 5,618 children of European ancestry, AN polygenic scores (AN-PGS) were associated with early AN symptoms, while BE-PGS showed transdiagnostic associations with both AN and BE symptoms. These links were mediated by BMI and psychosocial traits, including sex-specific pathways through ADHD and anxiety/depression symptoms in females. MeaningOur findings suggest that genetic liability to eating disorders manifests early in life through distinct metabolic and psychosocial pathways, highlighting a window for sex-specific targeted prevention.

Background: Attention problems are common transdiagnostic symptoms of psychiatric illness. Although environmental exposures and experiences influence attention during adolescent development, the underlying neural pathways by which they do so is unclear. Methods: We measured attention problems, attention-related brain networks, and multidimensional environmental experiences (the exposome) using data from the ABCD Study (N = 11,878). We tested whether the exposome is associated with 9-10-year-olds attention-related brain network strength and current and future attention problems. We further examined cross-sectional indirect pathways linking the exposome, brain network strength, and attention problems. Results: The exposome predicted youths current and future self-, caregiver-, and teacher-reported attention problems as well as their current attention-related brain network strength. This brain network signature of sustained attention also predicted attention problems from all three reporters. Indirect effects models revealed that the exposome was associated with current reported attention problems both directly and indirectly though this brain signature. Conversely, predictive brain network strength was related to attention problems both directly and indirectly through the exposome. Conclusion: Interactions between environmental exposures, experiences, and brain network organization are associated with attention problems in early adolescence. These findings support a bidirectional framework linking the environment and functional brain networks in the development of attention problems.

Objective: Autistic individuals may face elevated risk for PTSD, yet the degree to which this risk differs by sex remains unknown. We examined the association between autism and incident PTSD, characterized sex differences in risk, identified high-risk subgroups, and described post-diagnosis clinical trajectories. Method: We conducted a population-based matched cohort study using Swedish national registers. Individuals born 1990 through 2010 were followed from age 6 years through December 31, 2017. Autistic individuals (N=42,862) were matched 1:10 to controls (N=412,251) on sex and birth year. Cox proportional hazards regression estimated hazard ratios (HRs) for incident PTSD. Among those who developed PTSD, we compared care utilization, hospitalization rates, and persistence of care contacts. Results: During mean follow-up of 5.1 years, 401 autistic individuals (0.9%) and 903 controls (0.2%) developed PTSD (incidence rates: 18.3 vs 4.2 per 10,000 person-years). Autism was associated with 4.4-fold increased PTSD risk (HR=4.37; 95% CI, 3.93-4.86). Risk was higher among females (HR=4.79) than males (HR=3.39; P interaction=.006). Among autistic individuals, comorbid ADHD conferred additional risk (HR=1.38; 95% CI, 1.14-1.68). Ten-year cumulative incidence reached 6.0% among autistic females with ADHD. Autistic individuals with PTSD had higher care utilization (mean visits: 5.0 vs 3.9; P<.001), more psychiatric hospitalizations (27.9% vs 19.8%; P=.002), and more persistent courses (24.8% vs 12.3% with contacts in all 3 post-diagnosis years; P=.001). Conclusion: Autism is associated with substantially elevated PTSD risk, particularly among females with comorbid ADHD. When PTSD occurs, autistic individuals experience more severe and persistent clinical courses, supporting targeted screening and sustained follow-up.

Mutations in SCN2A, which encodes the voltage-gated sodium channel Nav1.2, are associated with a wide spectrum of neurodevelopmental and neuropsychiatric disorders, including epilepsy, autism spectrum disorder (ASD), and schizophrenia. Although dysfunction of SCN2A-dependent neural circuits has been implicated in these disorders, the circuit mechanisms underlying social behavioral abnormalities remain poorly understood. Here, we investigated the neural circuit basis of social behavioral deficits associated with Scn2a dysfunction, focusing on the nucleus accumbens (NAc), a key hub in cortico-limbic circuits that regulates emotional and motivational behaviors. Using conditional genetic and chemogenetic approaches in mice, we examined the roles of dorsal telencephalic excitatory neurons, including those in the cerebral cortex, hippocampus, and amygdala, as well as parvalbumin-positive fast-spiking interneurons (PV FSIs) in the NAc. Mice with Scn2a haploinsufficiency in dorsal telencephalic excitatory neurons (Scn2afl/+/Emx1-Cre) exhibited reduced sociability in the three-chamber social interaction test. Similarly, chemogenetic inhibition of NAc PV FSIs decreased sociability without affecting locomotor activity or anxiety-like behavior. Scn2afl/+/Emx1-Cre mice also showed a trend toward reduced prepulse inhibition of the acoustic startle response. Notably, dopamine release into the NAc in the Scn2afl/+/Emx1-Cre and systemic Scn2a heterozygous knockout (Scn2a+/-) mice was largely comparable to that in control mice. Together, these findings indicate that reduced activity of dorsal telencephalic excitatory neurons or NAc PV FSIs is sufficient to impair sociability independently of mesolimbic dopamine hypofunction. Our results highlight a potential role of cortico-accumbal circuits in social behavioral deficits associated with SCN2A dysfunction.

Internet gaming disorder (IGD) presents a significant public health challenge, yet its complex biopsychosocial mechanisms and dynamic risk trajectories remain poorly understood due to a scarcity of comprehensive longitudinal and multimodal cohorts. To address this critical gap, we established the Chinese College Student Gamers Cohort (CCSGC), a prospective, multimodal longitudinal study of 793 first-year undergraduates primarily playing Honor of Kings from 2022 Sept. The CCSGC integrates semi-annual psychosocial questionnaires, annual neuroimaging (EEG/fMRI), and biospecimen collection over multiple years. Baseline data revealed individuals with IGD (n=211) exhibited significantly higher gaming craving, psychological distress (depression, anxiety), impulsivity, and maladaptive motivational features compared to non-IGD gamers (regular players (RP) n=400; casual players (CP) n=182). Longitudinal analyses across four waves indicated bidirectional temporal associations between IGD severity and mental symptoms, and a stabilization of IGD incidence after an initial decrease. Furthermore, specific neurophysiological (e.g., N400 amplitude to game cues) and neuroimaging (e.g., superior parietal activation) markers were identified that correlated with IGD severity and predicted one-year outcomes in gaming disorder or social functioning. The CCSGC provides an invaluable resource for dissecting the heterogeneity, comorbidity, and intricate biopsychosocial mechanisms of IGD, holding significant potential to advance risk prediction, early identification, and targeted intervention strategies.

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.

Social isolation refers to an extreme form of social deprivation that has enduring effects on the brain and behavior. Adolescents show selective vulnerability to such heightened social stress, displaying aberrant behavior and psychiatric ailments. The post-weaning social isolation rodent model has been widely used to recapitulate such behavioral anomalies and delineate their mechanistic bases. Here, we aim to identify how prolonged social isolation during adolescence affects neuroimmune responses in both sexes and the implications for behavioral outcomes, particularly aggression. While males subjected to adolescent isolation were hyper-aggressive with pathological signs, females showed reduced social exploration and inactivity. Cytokine profiling in core brain regions implicated in aggression revealed reduced interleukin 6 (IL6) levels, specifically in the hypothalamus, in both sexes. Other proinflammatory cytokines, including interferon-gamma and interleukin-1beta, were unaltered. IL6-responsive genes, SOCS3 and TIMP1, were also downregulated in the hypothalamus of both socially isolated males and females. The hypothalamus is crucial for stress responsiveness and the expression of excessive aggression. Despite behavioral dimorphism, reduced IL6 levels in both sexes may indicate differences in downstream signaling and roles beyond classical immune responses. Our findings suggest that hypothalamic IL6 may be a key mediator of adolescent social isolation, which is associated with aberrant behavior, including aggression.