Biological Psychiatry Global Open Science

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.

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.

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.

Previous studies have linked opioid use to altered metabolic profiles, but findings have been inconsistent and mechanisms remain unclear. One potential mechanism involves increased adiposity, leading to chronic low-grade inflammation that elevates metabolic risk. Here, we examined metabolic profiles in individuals with opioid use disorder (OUD) and matched non-OUD controls, focusing on the sequential mediating roles of BMI and inflammation. Data from individuals with OUD (n=281) and non-OUD (n=246) were drawn from a natural history screening protocol from the National Institute on Alcohol Abuse and Alcoholism intramural program. Groups were matched on age, sex, race, ethnicity, socioeconomic status, and education via propensity score matching. Metabolic measures included BMI, blood glucose, hemoglobin A1c (HbA1c), and lipid profiles, with lipid imbalance indexed by the atherogenic index of plasma (AIP). Inflammatory markers included C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). Individuals with OUD had significantly higher BMI (F1,481=12.9, p<0.001), HbA1c (F1,481=10.5, p=0.001), lower high-density lipoprotein cholesterol (HDL-C; F1,481= 46.2, p< 0.001), higher low-density lipoprotein cholesterol (LDL-C; F1, 481=11.9, p< 0.001), and higher AIP (F1,481=20.7, p< 0.001) compared to non-OUD. Inflammatory markers were also elevated in individuals with OUD, including CRP (F1,481=9.4, p=0.002) and ESR (F1,481=7.4, p= 0.007), and statistically mediated group differences in AIP and HbA1c, respectively. Our results are consistent with prior evidence of metabolic dysfunctions in individuals with OUD and suggest inflammation as a contributing mechanism. Targeting metabolic health and inflammation may offer new avenues for improving long-term health outcomes in OUD.

Adult ADHD is increasingly recognized across the lifespan, yet the psychometric equivalence of the Adult ADHD Self-Report Scale (ASRS) remains unverified for older populations. This study examined age-related Differential Item Functioning (DIF) in 600 adults (n = 100 per decade, ages 20-80) who completed the 18-item ASRS. Using a bi-factor Graded Response Model, we extracted latent ADHD trait scores ({omega}H = .895) and assessed DIF via ordinal logistic regression with adaptive age modeling. Five of 18 items exhibited significant uniform DIF. At equivalent latent severity, older adults were less likely to endorse hyperactivity symptoms in Part A (fidgeting, feeling "driven by a motor") but more likely to endorse specific symptoms in Part B (careless mistakes, misplacing items, interrupting). From ages 20 to 80, expected Part A scores decreased by 1.36 points (~0.27 per decade), while Part B scores increased by 1.15 points (~0.23 per decade). These findings indicate a phenotypic redistribution of ADHD symptoms as individuals age. Because the 6-item Part A screener serves as the primary clinical gatekeeper, its concentration of negative DIF suggests standard screening practice may systematically underestimate ADHD severity in older adults. We recommend using the full 18-item ASRS when screening older populations and suggest that developing age-adjusted norms would improve diagnostic accuracy.

BackgroundPerinatal mood and anxiety disorders (PMADs) are among the most common and consequential complications of pregnancy. The perinatal period is also characterized by profound hormonal fluctuations and large-scale brain plasticity. However, the mechanisms linking these neurobiological changes to psychiatric risk are poorly understood. Prospective, clinically informed studies are needed to identify quantitative biomarkers and clarify pathways linking perinatal neurobiology to PMADs risk. MethodsThis report describes the design of a prospective, longitudinal cohort study integrating multimodal neuroimaging, biofluid sampling, and deep clinical phenotyping to enable precision characterization of neurobiological trajectories of PMADs risk. Twenty-five individuals at elevated risk for PMADs will be recruited prior to conception and followed across six in-person timepoints spanning the menstrual cycle, pregnancy, and early postpartum, with additional remote follow-ups through the first postpartum year. Data collection includes high-resolution structural MRI, functional brain mapping using multi-echo resting-state fMRI, diffusion MRI, arterial spin labeling, ultra-high field MR-based techniques for measuring glutamate (GluCEST and 1HMRS), biofluid sampling, and comprehensive clinical, behavioral, and cognitive assessments. Structured clinical interviews assess categorical diagnoses while dimensional symptom measures capture heterogeneity and transdiagnostic features of perinatal psychopathology. Longitudinal analyses will model nonlinear trajectories of brain and symptom change across the perinatal period as well as evaluate whether preconception network features and menstrual cycle-related brain changes are associated with subsequent perinatal symptom emergence. DiscussionThis cohort study establishes a longitudinal, multimodal framework for investigating neurobiological changes across the transition to pregnancy in individuals at elevated risk for PMADs. By anchoring pregnancy-related brain changes to preconception and menstrual cycle-related variability within the same individuals, this study is designed to evaluate associations between preconception hormone sensitivity, pregnancy-induced neuroplasticity, and PMADs risk. The resulting dataset will provide a deeply phenotyped longitudinal resource for investigating brain-behavior relationships across the perinatal period. Findings are expected to inform future larger-scale studies aimed at advancing mechanistic understanding of PMADs, improving individualized risk stratification, and supporting development of personalized preventive and neuromodulatory interventions.

BackgroundEarly-life adversity (ELA) is a risk factor for enduring pain in youth and is associated with alterations in brain morphology and function. However, it remains unclear whether ELA-related neurobiological changes contribute to the development of enduring pain in early adolescence. MethodsUsing data from the Adolescent Brain Cognitive Development (ABCD) Study, we examined multimodal magnetic resonance imaging (MRI) markers in children assessed at baseline (ages 9-11 years) and at 2-year follow-up (ages 11-13 years). ELA exposure was defined at baseline to maximise temporal separation between early adversity and later enduring pain. Participants with enduring pain at follow-up (n = 322) were compared to matched pain-free controls (n = 644). Structural MRI, diffusion MRI (fractional anisotropy, mean diffusivity), and resting-state functional connectivity data were analysed. Linear models tested main effects of enduring pain, ELA, and their interaction on brain metrics, controlling for relevant covariates. ResultsELA exposure was associated with smaller caudate and nucleus accumbens volumes, and reduced surface area of the left rostral middle frontal gyrus. No significant effects of enduring pain or ELA-by-enduring pain interaction were observed across grey matter, white matter, or functional connectivity measures. ConclusionsELA was associated with alterations in fronto-striatal regions in late childhood, but these changes were not linked to enduring pain in early adolescence. These findings suggest that ELA-related neurobiological alterations may represent early markers of vulnerability rather than concurrent correlates of enduring pain. Longitudinal follow-up is needed to determine whether these alterations contribute to later chronic pain risk.

Substance use disorders (SUD) are chronic conditions with devastating effects on brain health, functioning, and survival. In this study, we compared brain morphometry of 2,782 individuals with SUD to 1,951 controls and assessed the topographic overlap of these differences with brain connectivity and receptor architecture. Across SUD, we identified a morphometric signature involving frontal, parietal, temporal and limbic systems that overlapped with cortical hub regions and harbored cortical and subcortical disease epicenters. Findings were highly consistent across six substances and numerous robustness and generalizability analyses. Transdiagnostic comparisons showed high spatial overlap of SUD epicenters with those of schizophrenia and bipolar disorder, suggesting shared network-constrained cortical differences. Finally, multivariate mapping revealed that SUD brain differences aligned with two neurotransmitter axes contrasting cannabinoid-opioid and dopaminergic systems. These findings indicate that addiction-related brain differences are shaped by connectome and neurotransmitter architecture, positioning brain network and neurochemical organization as key principles of SUD-related brain alterations.

Background: The Adolescent Brain Cognitive Development (ABCD) Study provides rich longitudinal data on environmental, genetic, and behavioral factors related to substance use initiation. Classical marginal structural models (MSMs) require selecting covariates for propensity models, which is challenging when there are many correlated predictors. Methods: We analyzed longitudinal panel data from 11,868 ABCD participants with repeated observations over time. Interval-level binary outcomes were defined for initiation of alcohol, nicotine, cannabis, and any substance, including only participants at risk before initiation. All predictors were constructed as lagged variables to preserve temporal ordering. We used a two-stage machine learning-based causal framework. First, we performed graph discovery using a Granger-inspired lagged predictive modeling approach with elastic-net logistic regression to identify relationships between past predictors and future outcomes. Stable candidate edges were selected using subject-level bootstrap stability selection. Second, we estimated adjusted effects for stable predictors using double machine learning (DML) with partialling-out and cross-fitting. For each predictor, the lagged variable was treated as the exposure and adjusted for high-dimensional lagged covariates. Cross-fitting with group-based splitting accounted for within-subject dependence. Nuisance functions were estimated using random forests, and cluster-robust standard errors were used for inference. Results: We identified stable predictors across multiple domains, including sleep patterns, family environment, peer relationships, behavioral traits, and genetic risk. Many predictors were shared across substance outcomes, while some were outcome-specific. Effect sizes were modest, typically ranging from -0.01 to 0.02 per standard deviation increase in the predictor. Both risk-increasing and protective associations were observed. Risk factors included sleep disturbance and behavioral risk indicators, while protective factors included parental monitoring and structured environments. Conclusions: This study presents a practical framework for analyzing high-dimensional longitudinal data and identifying time-varying predictors of substance use initiation. The approach combines machine learning for variable selection with causal inference for effect estimation. The results highlight both shared and outcome-specific risk factors and identify modifiable targets, such as family environment and sleep, that may inform prevention strategies.

Early life stress (ELS) events during sensitive postnatal time periods can recalibrate future stress responsiveness and precipitate mental disorders. Neurovascular adaptations can influence cognition, mood, and stress responses. Disruption of blood-brain barrier (BBB) integrity, which is formed by endothelial cells, astrocytes, and pericytes, has been implicated in affective disorders such as depression, which often arise from chronic stress experiences. Despite the BBB undergoing critical maturation stages during development, it remains poorly known how ELS influences brain vascular function, as previously shown for adult stress, and whether it augments BBB vulnerability to subsequent challenges. First, we took advantage of a public two-hit stress RNA-sequencing dataset and filtered for vascular enriched genes in the prefrontal cortex and nucleus accumbens, the two brain regions where BBB integrity is frequently compromised. This analysis revealed BBB-related gene ontology categories modulated by either ELS alone or its combination with adult stress. Then, using a mouse model combining ELS with chronic social defeat stress (CSDS) in adulthood, we found that ELS did not exacerbate CSDS susceptibility; instead, it increased social interactions and the likelihood of a resilient profile in both males and females. Transcriptomic profiling in our cohort further identified distinct sex- and region-specific BBB gene expression patterns associated with ELS and its interaction with CSDS. Additionally, we observed a reduction of corticosterone levels, the primary stress hormone, following CSDS. Altogether, these results indicate that ELS modulates stress responses when facing emotional challenges in adulthood, possibly through long-lasting changes of BBB function via the glucocorticoid system. HighlightsO_LIRNA-seq vascular filtering reveals BBB distinct ontology categories for ELS and AS C_LIO_LIELS increases the likelihood of a high social and resilient profile. C_LIO_LIPericytes gene expression associated to resilience is sex- and region-specific. C_LIO_LICORT response desensitizes after adult CSDS in both sexes. C_LI

BackgroundExternalizing liability is a strong risk factor for early substance initiation, but the neurobiological pathways linking polygenic risk to initiation remain incompletely characterized. MethodsUsing the ABCD Study, we implemented a four-stage framework linking an externalizing polygenic risk score (extPRS) to baseline multimodal neuroimaging-derived phenotypes (IDPs) and longitudinal substance initiation (alcohol [primary], nicotine, cannabis, and any substance). First, we screened extPRS-IDP associations using covariate-adjusted linear models (age, sex, ancestry principal components, site/scanner variables; modality-specific covariates where applicable) and controlled multiple testing using false discovery rate (FDR) procedures. Second, we estimated direct extPRS associations with time-to-initiation using Cox proportional hazards models. Third, we fit joint Cox models including extPRS and each discovery-significant IDP, retaining outcome-IDP associations after within-outcome FDR correction. Fourth, we conducted mediation analyses for prioritized outcome-IDP pairs using an extPRS [-&gt;] IDP mediator model and an initiation model including both extPRS and IDP, estimating indirect (ACME) and direct (ADE) effects via bootstrap with multiple-testing control. ResultsAmong 10,608 participants, higher extPRS was associated with earlier initiation across outcomes, with the largest effects observed for nicotine and cannabis and a modest but significant effect for alcohol. Stage 1 identified thousands of extPRS-associated IDPs that were highly concordant across robustness specifications. Stage 3 prioritized outcome-specific IDPs associated with initiation beyond extPRS, with the number of retained IDPs varying across sensitivity settings (site-clustered vs. HC3 standard errors; SES covariates on/off) but showing a replicated core set across models. In Stage 4, mediation analyses showed that indirect effects of extPRS through IDPs were small in magnitude (ACME {approx} 10-4) and accounted for less than 2% of the total effect, while direct effects (ADE {approx} 0.02-0.05) remained strong across outcomes. FDR-significant mediation signals were observed only for alcohol and any-substance initiation, whereas no mediation effects survived multiple testing correction for cannabis or nicotine. Across outcomes, direct genetic effects were substantially larger than mediated effects, indicating that genetic liability operates primarily through direct pathways rather than through baseline brain measures. ConclusionsExternalizing polygenic liability is broadly associated with substance initiation, with robust and consistent direct effects across substances. Although specific frontal structural and microstructural phenotypes show statistically significant mediation signals, their contribution is small, suggesting that baseline brain measures explain only a limited proportion of genetic risk. This framework provides a scalable approach to prioritize neurobiological pathways linking genetic liability to early substance initiation while highlighting the dominant role of direct genetic effects.

Objective: While ADHD symptoms often decline from childhood into adulthood, the underlying neurobiological mechanisms, such as altered brain maturation or neural reorganization, remain incompletely understood. This study investigated how grey matter development relates to ADHD symptom trajectories into adulthood. Method: We analyzed data of individuals with ADHD and controls from the longitudinal Dutch NeuroIMAGE cohort, utilizing dimensional ADHD symptom scores (Conners Parent Rating Scale) from three waves and T1-weighted structural MRI scans from the final two waves. Using General Linear Models with permutation-based inference, we examined: 1) cross-sectional associations between ADHD symptoms and vertex-wise cortical thickness and surface area, and subcortical volumes at Wave 1 (n = 765, mean age = 16.95 years); and 2) longitudinal associations between symptom progression and brain morphometric changes (Wave 0 to 1: n = 644, mean age = 11.55-17.24 years; Wave 1 to 2: n = 149, mean age = 16.45-20.11 years). Results: Cross-sectionally, at Wave 1, more ADHD symptoms were related to widespread reductions in surface area, most prominently in the frontal cortex, and smaller volumes of the cerebellum, amygdala, and hippocampus. Longitudinally, symptom improvement from Wave 1 to Wave 2 was associated with stronger reductions in surface area, particularly in prefrontal and occipital regions, and with more pronounced cortical thinning across multiple brain regions. Conclusion: These findings suggest an association between symptom trajectories and structural brain changes, indicating that clinical improvement in ADHD behaviors might coincide with ongoing neural refinement during the transition to adulthood.

Metabotropic glutamate 2/3 receptors (mGluR2/3) have been implicated in depression, anxiety, learning, and memory. However, their causal role in reward-related behaviors remains unclear. Here, we examined the effects of intraperitoneal administration of LY341495, a selective mGluR2/3 antagonist, on reward-related behaviors in mice. In a head-fixed temporal conditioning task, mice received a 10% sucrose solution every 10 seconds. After training, mice exhibited anticipatory licking and pupil dilation aligned with expected reward delivery, indicating successful reward prediction. LY341495 dose-dependently reduced licking behavior without disrupting temporal prediction, as normalization analyses revealed reduced gain but preserved timing. LY341495 also induced overall pupil dilation and attenuated reward-proximity pupillary responses. To determine whether reduced licking reflected general motor impairment, we assessed spontaneous locomotion in a freely moving open-field task. LY341495 did not affect locomotor activity or excretion, suggesting intact general motor and autonomic function. To further evaluate orofacial motor function, we measured ultrasonic vocalizations (USVs) during a social interaction task. LY341495 did not significantly alter USVs, indicating preserved mouth-related motor function independent of licking. In contrast, LY341495 dose-dependently reduced food intake in a freely moving feeding task. Moreover, social preference testing revealed that LY341495 reduced social interaction, suggesting impaired processing of non-food rewards. Together, these findings demonstrate that mGluR2/3 signaling regulates reward-seeking behaviors independently of general locomotor or orofacial motor function. These results provide new insights into glutamatergic mechanisms underlying reward processing and may have clinical implications for obesity, eating disorders, and psychiatric conditions involving motivational dysfunction.

Adolescent binge drinking is a strong predictor of alcohol use disorder and related mental health outcomes in adulthood, which may be due to disruptions in myelination during this dynamic period of brain development. White matter expansion in frontal regions during adolescence is essential for mature decision-making and stress regulation, yet the cellular mechanisms by which alcohol disrupts this process remain poorly understood. We used multi-label immunofluorescence and confocal microscopy to visualize proteins in oligodendrocyte lineage cells and myelin ensheathment of axons in the anterior cingulate cortex (Cg1) and corpus callosum (CC) following four weeks of episodic voluntary binge drinking using the Drinking-in-the-Dark model in adolescent male and female C57BL/6NJ mice beginning on postnatal day 28. Contrary to our initial hypothesis that alcohol targets early-stage oligodendrocyte precursor cells (OPCs), binge drinking selectively depleted mature oligodendrocytes expressing aspartoacylase (ASPA) in the Cg1 and CC of male mice, but not females. This enzyme is essential for lipid biosynthesis and myelin production, and this cell-specific loss was accompanied by significant hypomyelination of axons only in males. These findings identify a later maturational stage of oligodendroglial development as a sex-dependent target of alcohol, advancing our mechanistic understanding of prefrontal myelin deficits in adolescent drinking. Furthermore, ASPA emerges as a potential therapeutic target for alcohol use disorder and demyelinating diseases, with differential vulnerability across sex carrying important implications for adult neurodevelopmental outcomes.

Early-childhood temperament is associated with mental health outcomes decades later. Temperament reflects early-emerging individual differences in emotional and behavioral tendencies. These differences are relatively stable across development and shaped by both genetic and environmental influences. However, the consequences of departures from expected developmental trajectories remain largely unexplored. Using data from more than 50,000 children in the Norwegian Mother, Father and Child Cohort Study, we modeled longitudinal temperament trajectories at 1.5, 3, and 5 years of age and quantified deviations from expected development. Multivariate pattern analysis revealed latent dimensions linking these deviations to clinical diagnoses, with ADHD as the most prominent outcome. Time-to-event analysis showed that these dimensions were associated with a higher hazard of ADHD diagnosis across childhood and adolescence. Finally, genetic analyses identified loci jointly associated with temperament trajectories and ADHD, revealing age-dependent genetic effects. Together, these findings show that deviations from temperament trajectories in early childhood capture transdiagnostic vulnerability across development. Early temperament monitoring may thus serve as an indicator of later mental health risk.