Journal of Child Psychology and Psychiatry

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.

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

Understanding depressive symptoms dynamics and their determinants is crucial for designing effective mental health support initiatives. This study compared two methods for describing youth depressive symptoms trajectories and investigated associations of early-life factors (maternal education, maternal perinatal depression, domestic violence, physical, emotional, or sexual abuse, bullying victimisation, psychiatric disorder) with trajectory features. Prospective data from 8,264 mostly White European participants (54% female), including self-reported Short Moods and Feelings Questionnaires on ten occasions between 10-25 years, were used. Trajectories were summarised using functional principal component analysis (FPCA) and P-splines linear mixed-effect (PLME) models. Estimated derivatives were used to obtain magnitude and age of peak symptoms and peak symptoms velocity. Both methods performed comparably, but PLME models tended to over-smooth trajectories. Peak symptoms and peak velocity were higher and occurred >1 year earlier in females than males. All early-life factors were associated with higher peak symptoms, and most associated with higher and earlier peak velocity. Abuse and bullying additionally associated with earlier age of peak symptoms. FPCA is a useful alternative for characterising depressive symptoms trajectories and informing time-sensitive preventative measures to reduce impact of depression before symptoms reach their peak. Early-life stressors may accelerate timeline and intensity of symptoms escalation during adolescence. Lay summaryUnderstanding development of depressive symptoms and factors shaping them is crucial for designing effective mental health support initiatives. This study used data from over 8,000 young people regularly followed up from before birth to compare two cutting-edge methods for describing depressive symptoms trajectories and examined how known risk factors for adulthood depression relate to the severity and rate of change of depressive symptoms in adolescence. We found that both methods performed well and that the peaks in depressive symptoms and their rate of change were, on average, higher and occurred over a year earlier in females than males. Our findings additionally suggest that early-life stressors (e.g., abuse, bullying) may accelerate the development of depression, highlighting the importance of early 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.

Background Although an expansive body of evidence exists on children's mental health during the COVID-19 pandemic, it is largely restricted to the early phases and lockdowns. This study examines longitudinal changes in child and youth mental health symptoms across two years of the COVID-19 pandemic, with data collection strategically timed to capture variability in pandemic restrictions. Methods A population-based longitudinal study of 1,261 children and youth aged 4-17 years followed prospectively from January 2021 to December 2022, with five waves of data collected in Ontario, Canada. Latent growth curve modelling was used to estimate trajectories of parent-reported mental health symptoms and identify baseline and time-varying covariates associated with variable trajectories. Findings Mental health symptoms were elevated and stable during lockdowns, followed by significant reductions as pandemic restrictions loosened, particularly for oppositional defiant and inattention/hyperactivity symptoms compared to internalizing symptoms. Children without pre-existing clinician diagnosed physical, mental or neurodevelopmental conditions and those not in lockdown at baseline demonstrated relative increases in mental health symptoms during lockdowns; and girls, compared to boys, demonstrated smaller reductions in internalizing symptoms as restrictions loosened. Concurrent and lagged associations between parental distress and children's mental health symptoms varied across the pandemic. Interpretation Variation in symptom trajectories by mental health domain, gender, pandemic restrictions and pre-existing diagnosed conditions underscores the need for tailored, equity-informed pandemic planning and response. Policies designed to optimize the balance between the need to reduce viral community transmission whilst limiting pandemic lockdowns may mitigate adverse impacts on child and youth mental health. Funding Ontario Ministry of Health

ObjectiveThere is little longitudinal research investigating links between violence exposure and mental disorders among children in low- and middle-income countries (LMICs), despite high rates of violence. We examined cross-sectional and longitudinal violence-mental health associations among children in a large South African birth cohort, the Drakenstein Child Health Study, including direct clinical interviews capturing childrens mental disorders. MethodIn this birth cohort (N=974), we assessed lifetime violence exposure and four subtypes (witnessed community, community victimization, witnessed domestic, domestic victimization) at ages 4.5 and 8-years via caregiver reports. At 8-years, caregivers completed the Child Behaviour Checklist; and psychiatric disorders were assessed using the Mini-International Neuropsychiatric Interview for Children and Adolescents, a self-report measure. We tested for associations using linear/logistic regressions, adjusted for confounders. ResultsMost children (91%) had experienced violence by 8-years. Cross-sectionally, total violence exposure was associated with total (B =0.49 [95% CI 0.32, 0.66]), internalizing (0.32 [0.17, 0.47]), and externalizing problems (0.46 [0.31, 0.61]), and with increased odds of disorder at 8 years (aOR=1.09 [1.05, 1.13]). Longitudinally, total violence exposure up to 4.5-years was associated with total (B=0.27 [0.03, 0.52]), internalizing (0.24 [0.04. 0.44]), and externalizing scores (0.23 [0.008, 0.45]) at 8-years, but not with increased risk of psychiatric disorders. The strongest and most consistent associations were observed for domestic versus community violence subtypes. ConclusionOur strong cross-sectional but weaker longitudinal findings suggest that recent violence exposures may be more critical than early exposures for childrens mental health. Longitudinal exploration of other violence-affected LMIC populations is urgently needed.

ObjectiveSocial difficulties are transdiagnostic in childhood, but their heterogeneity is poorly characterised and rarely treated as a primary neurodevelopmental phenotype. This matters because childhood and adolescence are sensitive periods for peer relationships and brain development. We used data-driven modelling and non-linear mapping to derive social profiles and test their clinical, cognitive, and neural correlates. MethodsParticipants were 992 children aged 5-18 years from CALM (Mage = 9.6). Social items from the SDQ, CCC-2, and Conners-3 were modelled using a regularised partial correlation network to derive core social dimensions. A self-organising map captured graded social profiles. Simulated archetypes, SVM-based island identification, and permutation testing defined profile regions and centroid-distance scores. Profiles were related to referral, diagnosis, cognition, BRIEF indices, and T1-derived MIND network structure in an MRI subsample (n = 431). ResultsWe identified four profiles: social engagement, friendship difficulties, social withdrawal, and peer victimisation. Profile expression tracked variation in referral and diagnostic pathways. Social withdrawal showed the clearest disadvantage across cognitive domains, whereas social engagement was associated with fewer executive function difficulties across BRIEF indices. MIND strength components covaried with profile expression (a significant PLS latent variable, p = 0.02), with covariance strongest for social withdrawal and peer victimisation. ConclusionsChildhood social functioning organises graded signatures that relate to clinically relevant pathways, cognitive and executive outcomes, and brain structure. Profiling social signatures provides a scalable framework for identifying social need beyond diagnostic categories, motivating studies to test directionality and improve developmental outcomes.

BackgroundSubstance use initiation in adolescence is influenced by both genetic and environmental factors; however, large-scale genetic studies often treat initiation as a binary outcome and underuse longitudinal timing information. MethodsWe conducted time-to-event (survival) genome-wide association analyses (GWAS) of initiation for four outcomes--alcohol, nicotine, cannabis, and any substance use--using longitudinal follow-up data from the Adolescent Brain Cognitive Development (ABCD) Study. We performed ancestry-stratified GWAS within European (EUR), African (AFR), and Hispanic (HISP) groups, applying consistent quality control and covariate adjustment. Summary statistics were harmonized across ancestries and meta-analyzed using inverse-variance weighted fixed-effects and DerSimonian-Laird random-effects models. We evaluated genomic inflation and heterogeneity (Cochrans Q and I2), identified independent lead variants at genome-wide and suggestive significance thresholds, and assessed cross-trait overlap of associated loci. ResultsIn the multi-ancestry meta-analysis, we observed suggestive association signals across traits (minimum p-values: alcohol [~] 1 x 10-7, any [~] 1 x 10-7, cannabis [~] 5 x 10-8, nicotine [~] 1 x 10-8). Nicotine initiation showed one genome-wide significant variant in both fixed- and random-effects meta-analyses (p < 5 x 10-8). Across traits, suggestive loci demonstrated limited overlap, with the strongest concordance between alcohol and any substance use, consistent with shared liability. Heterogeneity statistics indicated that some loci exhibited cross-ancestry variation in effect estimates. ConclusionsSurvival GWAS leveraging initiation timing can identify genetic signals that may be missed by binary designs and enables principled multi-ancestry synthesis. Our results highlight both shared and trait-specific genetic contributions to early substance initiation and provide a foundation for downstream functional annotation and integrative modeling with environmental risk factors. These findings demonstrate the value of incorporating developmental timing into genetic discovery and provide a framework for integrating longitudinal risk modeling with genomic analyses.

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.

Children with developmental language disorder (DLD) have persistent language learning difficulties and often perform poorly on pseudoword repetition, a task that probes phonological, memory, and speech-motor processes that support vocabulary acquisition. Research on the neural basis of pseudoword repetition in DLD is limited. We used whole-brain functional MRI (fMRI) to examine pseudoword repetition and repetition-based learning in 46 children with DLD (ages 10-15 years) and 71 age-matched children with typical language development. During scanning, children heard and repeated pseudowords paired with visual referents, allowing us to track learning-related changes in neural activity across repetitions. Repeated pseudoword production yielded comparable behavioural learning across groups, with faster productions by later repetitions. Post-scan, form-referent recognition was comparable across groups, whereas pseudoword repetition accuracy was lower in DLD. Pseudoword repetition engaged a distributed neural network, including inferior frontal cortex bilaterally (greater on the left), premotor and sensorimotor cortex, and posterior temporal and occipital regions. Group differences emerged primarily in regions where activity was task negative (i.e., below baseline or deactivated): lateral occipito-parietal cortex (posterior angular gyrus), medial parieto-occipital cortex (retrosplenial), and right posterior cingulate cortex. Learning-related decreases in activity were similar across groups, but region-of-interest analyses showed reduced leftward lateralisation of activity in inferior frontal gyrus in DLD. These findings suggest weaker disengagement of the default mode network during a linguistically demanding task in DLD. Although repetition-based pseudoword learning recruited similar neural mechanisms in both groups, these mechanisms may operate less efficiently in DLD, alongside reduced hemispheric specialisation in inferior frontal cortex. HighlightsO_LISimilar repetition-related neural attenuation across groups during pseudoword learning. C_LIO_LIReduced default-mode network suppression during pseudoword repetition in DLD. C_LIO_LIReduced left-hemisphere specialisation of inferior frontal cortex in DLD. C_LIO_LIRepetition-based learning in DLD supported by less efficient neural networks. C_LI

The etiology of autism is influenced by genetic and non-genetic factors, with observational studies suggesting associations between early maternal health diagnoses and offspring autism. However, these associations may partly reflect shared familial genetic liability rather than direct causal effects. Using comprehensive national health registers and individual-level genetic data from the iPSYCH cohort (N=117,542), we examined whether maternal health diagnoses are associated with offspring polygenic scores (PGS) for autism. Such associations between maternal health and offspring autism would indicate shared genetic factors and the possibility of genetic confounding in the observational associations. We also tested such associations with PGSs for other neuropsychiatric and neurodevelopmental conditions that are genetically correlated with autism, but with better-powered PGS (due to larger GWAS sample sizes and likely more polygenic genetic architecture), as well as height, a negative control. Several maternal diagnoses were nominally associated with autism PGS in the child, including, e.g., certain obstetric complications, asthma, and obesity. After adjustment for multiple testing, the only statistically significant results included those between maternal diagnoses, predominantly psychiatric, and other neuropsychiatric and neurodevelopmental PGSs in the child. Sensitivity analyses confirmed the robustness of our results across exposure windows, diagnostic settings, and socioeconomic adjustments. These findings indicate that maternal diagnoses associated with autism partially reflect shared genetic liabilities between mothers and their children. However, such genetic effects, as captured by child PGS do not fully explain the observed associations, suggesting additional factors, including e.g., non-genetic familial factors, rare variants, and indirect effects.

Wellbeing is commonly defined as the combination of feeling good and functioning well and typically conceptualized as two related but distinct components. Hedonic wellbeing emphasizes pleasure, happiness, and life satisfaction, while eudaimonic wellbeing focuses on meaning, personal growth, flourishing, and the realization of ones potential. The Mental Health Continuum-Short Form was developed as a comprehensive measure of wellbeing and includes three subscales assessing emotional, social, and psychological wellbeing. Although the Mental Health Continuum total score is often interpreted as an indicator of overall wellbeing, the underlying genetic structure of its three subscales and its genetic overlap with other commonly used wellbeing measures remains unclear. Using data from 5,212 individuals from the Netherlands Twin Register (72% female, mean age 36.4), we fitted multivariate twin models to examine the genetic architecture of the Mental Health Continuum and its associations with other wellbeing measures (quality of life, life satisfaction, subjective happiness, and flourishing). Results indicate that, at the genetic level, the Mental Health Continuum is best explained by its three distinct subscales rather than by a latent factor. When considering the Mental Health Continuum together with the other wellbeing measures, we found moderate to high genetic correlations (r = 0.52 - 0.83), indicating substantial overlap in the genetics underlying the wellbeing constructs. However, we did not find evidence for a single common genetic factor underlying all constructs. These findings highlight the multidimensional structure of wellbeing, but the moderate to high genetic correlations across measures suggest that it is important to align the level of measurement (phenotypic vs genetic) with the research question.

The cerebellum rapidly integrates with cerebral networks during infancy and shows consistent structural and functional alterations in Autism Spectrum Disorder (ASD), suggesting that early cerebellar development may be consequential for later behavioral and psychiatric outcomes. Yet, little is known about the effect of ASD genetic liability on cerebello-cerebral functional connectivity in infancy or whether effects may differ by biological sex. Here, we leveraged neonatal functional magnetic resonance imaging, genetic, and behavioral follow-up data from the Developing Human Connectome Project (dHCP) to examine the relationship between ASD polygenic scores (PGS) and functional connectivity of cerebellar regions associated with sensorimotor and social-cognitive functions in 198 term-born neonates (mean age: 9.7 days). We report widespread sex differences in neonatal cerebello-cerebral connectivity that are regionally specific across cerebellar subdivisions. Across the full sample, elevated ASD PGS predicted alterations in cerebello-cerebral connectivity, with hemisphere-dependent differences in sensorimotor cerebellar connectivity with temporal cortex, and hyperconnectivity between the right social-cognitive seed and posterior cingulate. Notably, elevated ASD PGS predicted opposing patterns of cerebello-cerebral connectivity in males and females, including male hyperconnectivity between the right sensorimotor cerebellum and default mode areas, and female hyperconnectivity between the right social-cognitive seed and sensorimotor cortex. Connectivity associated with elevated ASD PGS showed nominal, sex-specific associations with 18-month language ability, attention problems, and emotional reactivity. Our findings show that ASD PGS influences the functional configuration of the cerebellum at birth and suggest that underlying cerebellar connectivity profiles associated with ASD may partially underlie distinct behavioral presentations in males and females.

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.

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.

Here, we test the hypothesis that early sustained exposure to complex bilingual environments can positively affect reading development by altering structural interhemispheric connectivity via the corpus callosum (CC). Interhemispheric connectivity has been shown to be inefficient in dyslexia, but also to support compensatory pathways when genetic risk for reading difficulties is present, by enabling the preserved right hemisphere to support a dysfunctional left hemisphere. Mediation models were conducted on children aged 9-10 years (with a 2-year follow-up assessment) from the Adolescent Brain Cognitive Development database (N>10,000). Polygenic scores (PGS) for dyslexia and cognitive performance and continuous bilingualism indices were used as predictors, with reading aloud as the outcome. Bilingualism showed a positive effect on reading partially mediated by the anterior CC, independently of overall brain size. In contrast, genetic predispositions to reading difficulties influenced reading primarily through overall brain size rather than CC connectivity specifically. These two pathways were independent, suggesting that bilingual experience and genetic risk operate through distinct neuroanatomical mechanisms. These findings suggest that recurrent early exposure to complex bilingual environments may shape the brains structural connectivity toward a more balanced and integrated bilateral frontal organisation. The results highlight potential brain compensatory pathways induced by environmental experiences that may support more efficient reading development and mitigate risks for developmental dyslexia.

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.

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.

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.

AimAutistic children have a high but varied prevalence of internalizing and externalizing problems. This study aimed to identify the subtypes of internalizing and externalizing problems among autistic preschool children in Japan, examine their temporal stability, and investigate differences in participation in daily life and family outcomes across these subtypes. MethodsA prospective cohort study was conducted with 275 caregivers of autistic children aged 51-75 months. Internalizing and externalizing problems were assessed using the Strengths and Difficulties Questionnaire. ResultsLatent transition analysis identified five subtypes: Low-symptom, High-emotional, Externalizing, Comorbid, and Peer-difficulty groups. Membership in the High-emotional and Externalizing groups was relatively stable over time, whereas the Peer-difficulty group showed frequent transitions to subtypes with higher levels of internalizing or externalizing problems. Significant differences in participation in daily life and family outcomes were observed across subtypes, but these patterns were inconsistent with a simple gradient of symptom levels. ConclusionsThe novel findings that the temporal stability of subtype membership varied and that differences in participation in daily life and family outcomes were observed across the subtypes suggest that the heterogeneity of internalizing and externalizing problems may be associated with variations in childrens participation in daily life and family outcomes over time. Plain Language SummaryAutistic preschool children often experience emotional and behavioral difficulties, but the way these difficulties manifest varies widely across individuals. This study aimed to identify the patterns of these difficulties, examine how they change over time, and investigate how participation in daily life and family outcomes differ across autistic preschool children. We conducted a study with 275 caregivers of autistic children aged 4-6 years in Japan. From caregiver reports of childrens emotional and behavioral difficulties, five distinct patterns were identified: a group with mainly emotional difficulties, a group with mainly behavioral difficulties, a group with both types of difficulties, a group with relatively low levels of difficulties, and a group characterized primarily by peer-related difficulties. Our findings suggest that different patterns of emotional and behavioral difficulties are associated with differences in childrens participation in daily life and family outcomes. These differences could not be explained simply by the overall severity of difficulties but rather reflect distinct patterns based on the type of difficulty. The results indicate that autistic children face diverse difficulties that change over time.