JCPP Advances

Importance: Avoidant/restrictive food intake disorder (ARFID) is a feeding and eating disorder characterized by extremely restricted dietary variety and/or quantity resulting in significant physical health impairment and psychosocial dysfunction. ARFID frequently co-occurs with neurodevelopmental conditions, yet the extent to which this co-occurrence reflects shared genetic or environmental influences remains largely unknown, as few twin or genetic studies of ARFID have been conducted. Objective: To examine the extent to which genetic and environmental influences contribute to the association between a broad ARFID phenotype and neurodevelopmental traits. Design, Setting, and Participants: Population-based twin study using data from the Child and Adolescent Twin Study in Sweden, including 30,374 twins born 1992-2008. Main Outcomes and Measures: A broad ARFID phenotype was identified using a composite measure derived from parent reports and national health registers between ages 6 and 12 years. Parents completed measures of neurodevelopmental traits at age 9 or 12 years, including autism (subdomains: social communication problems and restricted/repetitive behaviors), attention-deficit/hyperactivity disorder (ADHD, subdomains: inattention and impulsivity/hyperactivity), tic disorders, learning disorders, oppositional defiant disorder, conduct disorder, obsessive-compulsive disorder (OCD), sensory perception problems, and sleep problems. Phenotypic associations were estimated using polyserial correlations. Bivariate twin models decomposed variance and covariance into genetic and environmental components. Results: Phenotypic correlations with the broad ARFID phenotype ranged from 0.18 (95% CI: 0.15-0.21) for OCD to 0.36 (95% CI: 0.33-0.38) for autism. Broad genetic correlations (rH; additive plus dominant genetic influences) ranged from 0.27 (95% CI: 0.21-0.33) for conduct disorder to 0.52 (95% CI: 0.44-0.60) for autism-restricted/repetitive behaviors. Genetic factors explained 77% to 95% of all phenotypic correlations. Non-shared environmental correlations were minimal to small, with the largest observed for autism (0.17; 95% CI: 0.08-0.26). Conclusions and Relevance: The broad ARFID phenotype shares substantial genetic influences with a number of neurodevelopmental traits. These findings suggest that the frequent co-occurrence of ARFID with neurodevelopmental traits largely reflects shared genetic influences rather than overlapping environmental influences, supporting the conceptualization of ARFID within a broader neurodevelopmental framework.

ABSTRACT IMPORTANCE Childhood obesity is a growing global health concern associated with adverse physical, psychiatric, and neurodevelopmental outcomes. Although previous neuroimaging studies have linked obesity to widespread alterations in brain structure and function, it remains unclear how well multimodal neuroimaging measures and genetic markers can predict future weight gain and inform early intervention strategies. OBJECTIVE To evaluate the predictive utility of multimodal MRI measures and polygenic risk scores for obesity in estimating proportional body weight at baseline and predicting weight gain over one year in preadolescent children. DESIGN, SETTING, AND PARTICIPANTS This study used data from the Adolescent Brain Cognitive Development (ABCD) Study, a large-scale, multisite longitudinal cohort of children aged 9 to 10 years (N = 11,880). Analyses included baseline data collected between 2016 and 2018, and one-year follow-up data collected between 2018 and 2020 across multiple imaging sites. MAIN OUTCOMES AND MEASURES Elastic net regression models were applied to structural MRI (including diffusion tensor imaging) and resting-state functional MRI data to predict baseline triponderal mass index (TMI), a weight-for-height measure that more accurately reflects adiposity in children than body-mass index (BMI). Longitudinal classification models were developed to predict excess weight gain relative to normative developmental trajectories at one-year follow-up. Models were evaluated with and without the inclusion of polygenic risk scores and other non-imaging covariates. Generalizability was assessed using leave-one-site-out cross-validation. RESULTS Structural MRI measures predicted baseline TMI with an R^2 of 0.21, whereas resting-state functional MRI measures predicted TMI with an R^2 of 0.08. Classification models predicted one-year weight gain with area under the receiver operating characteristic curve (AUC) values of 0.73 for structural MRI and 0.60 for resting-state functional MRI. Including polygenic risk scores and other covariates improved model performance (structural MRI: R^2 = 0.25, AUC = 0.75; resting-state functional MRI: R^2 = 0.15, AUC = 0.69). Leave-one-site-out cross-validation revealed reduced generalizability across imaging sites (structural MRI R^2 = 0.13-0.17; resting-state functional MRI R^2 = 0.02-0.09; structural MRI AUC = 0.73-0.74; resting-state functional MRI AUC = 0.60-0.67). CONCLUSIONS AND RELEVANCE Multimodal MRI measures were associated with proportional body weight and demonstrated modest predictive utility for future weight gain in preadolescent children, explaining up to one fifth of the variance in weight-related outcomes. The addition of genetic and non-imaging variables improved prediction accuracy, underscoring the multifactorial nature of childhood obesity. However, the observed decline in performance under site-wise cross-validation highlights the need to address site-related variability to enhance reproducibility and generalizability in neuroimaging-based predictive models of pediatric obesity.

Objective: Studies assessing the validity of screening measures for avoidant/restrictive food intake disorder (ARFID) remain scarce. We evaluated the diagnostic performance and validity of an online, parent-reported screening approach for ARFID in a population-based sample of children. Methods: Participants were drawn from the ARFID Initiative Sweden (ARIES) cohort and included 65 children aged 6-14 years. Parents completed three screening questionnaires (Pica, ARFID, and Rumination Disorder Interview-ARFID Questionnaire [PARDI-AR-Q], Nine-Item ARFID Screen [NIAS], and Parent Eating Disorder Examination Questionnaire [PEDE-Q]), followed by a diagnostic interview (PARDI). Diagnostic performance indices (sensitivity, specificity, positive predictive value [PPV], and negative predictive value [NPV]) were calculated. Convergent validity was assessed via correlations between questionnaire and interview dimensions. Results: The combined screening algorithm demonstrated perfect sensitivity and NPV, indicating accurate detection of all ARFID cases and exclusion of non-cases. Specificity was high (0.83), and PPVs ranged from 0.91 to 0.95, decreasing to 0.78 under a more conservative operationalization of ARFID Criterion A4 (psychosocial impairment). Diagnostic performance varied across ARFID criteria: PPVs were low for medically anchored Criteria A1-A3 but high for Criterion A4 (psychosocial impairment; PPV=0.95). Correlations between screening measures and corresponding interview dimensions were generally moderate to strong, supporting convergent validity. Children meeting threshold ARFID criteria showed significantly greater symptom severity than subthreshold cases at screening. Discussion: These findings support the use of a multi-instrument, parent-reported screening approach for ARFID in large-scale pediatric research and highlight the centrality of psychosocial impairment, underscoring the need for standardized operationalization of this criterion.

Background: The widespread prevalence of psychopathology, which affects approximately 50% of the global population, often manifests during adolescence. Understanding why some individuals remain resilient while others experience mental health challenges despite similar environmental risks is essential for developing early interventions. However, past efforts have faced challenges with the retrospective definition of resilience. Here, we aim to address these challenges by quantifying resilience to psychopathology at the individual level. Methods: In the Adolescent Brain and Cognitive Development (ABCD) Study(R) (N = 11,868), we utilized gradient-boosted tree regression to predict 2-year follow-up psychopathology from 208 Social Determinants of Health features. We used the "gap score" method--the difference between model-predicted and reported psychopathology--to quantify individual differences in psychopathology resilience and susceptibility, defined as the Resilience-Susceptibility Gap (RS-Gap). We validated the RS-Gap against independent 3-year follow-up clinical and quality-of-life outcomes. Results: Collinearity between gap scores and reported symptoms was high (r=-0.84), requiring further correction. Four bias-correction techniques were implemented and compared. After appropriate bias-correction, greater RS-Gap scores were associated with a higher likelihood of poor academic and social outcomes one year later, suggesting that early adaptation to adversity may carry a latent long-term cost. Conclusions: Dependency between RS-Gap and psychopathology scores is a statistical challenge for gap score resilience methods. Our comparisons demonstrate that correction is mandatory to separate resilience signal from shared variance with psychopathology scores. Findings converged across different bias correction methods, providing a validated framework for using gap scores to identify high-risk developmental trajectories in youth.

Background: Depression and anxiety symptoms emerge early in life. We examined developmental trajectories of emotional symptoms, starting from early childhood, in three UK birth-cohorts spanning successive generations and diverse socio-ethnic contexts. Methods: Using data from three longitudinal, population-based UK birth-cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC), Millenium Cohort Study (MCS), and Born in Bradford (BiB) we identified group-based trajectories of emotional symptoms using repeated Strengths and Difficulties Questionnaire, Emotional Subscale (SDQ-E) scores from ages 3-14y. Baseline samples comprised children with [≥]1 SDQ-E measure between age 3-14y (NALSPAC=11,025; NMCS=15,446; NBiB=6711). Participants were born three decades apart (ALSPAC: 1990-2, MCS: 2000-2, BiB: 2007-10) in distinct socioeconomic and ethnic contexts. We characterised group membership by: female sex, non-white ethnicity, maternal depression/anxiety and IMD quintile. In ALSPAC we modelled associations between trajectories and depression/anxiety diagnoses in early adulthood (24y and 30y). Results: In all cohorts 49% were female. ALSPAC had few non-white participants (4%) compared to MCS (17%) and BiB (66%). Each cohort had low-, mid- and high-level symptom trajectories. High-level trajectories comprised 6-7% of the population in each cohort. However, in younger cohorts, high-level symptom trajectories started high and persisted from age 3-5y but started low and increased in the oldest cohort. Female sex and maternal depression/anxiety were associated with higher odds of high-level or increasing symptom trajectories across all cohorts. Higher socioeconomic status and belonging to the ethnic majority was protective. Mid- and high-level symptom trajectories had higher odds of depression/anxiety diagnoses in early-adulthood in the older ALSPAC cohort. Conclusions: Developmental trajectories of emotional symptoms across childhood and adolescence are broadly similar across generations and diverse social contexts. However, children born more recently and in more diverse contexts may experience more persistent, severe emotional symptoms from a young age Key words: Longitudinal trajectories; emotional symptoms; SDQ, ALSPAC; MCS; Born in Bradford

Background: EEG provides a scalable method for elucidating neurophysiological characteristics that may distinguish mental health risk early in life, when symptoms are often non-specific, transdiagnostic, and pluripotential. Most prior studies have examined cross-sectional associations between individual EEG metrics and singular outcomes, potentially overlooking integrated patterns of neurophysiological organization. We applied data-driven clustering to infant baseline EEG to derive neurophysiological profiles and examined whether these profiles prospectively differentiated temperament and psychopathology domains in childhood. Methods: Participants were (N = 360; 46% female) from a longitudinal community cohort followed from infancy to age 7 years. Baseline EEG was collected in infancy (Mage = 7.81 months). Neurophysiological profiles were derived from spectral features (band-limited periodic power, peak frequency characteristics, and aperiodic exponent) using Bayesian model averaging of multiple clustering algorithms. Bayesian mixed-effects models tested profile differences in parent-reported temperament (surgency, negative affectivity, regulation/effortful control) across infancy and ages 3, 5, and 7 years, and child internalizing and externalizing symptoms at 5 and 7 years. Results: Consensus clustering identified four infant neurophysiological profiles characterized by: (1) elevated alpha/beta power, (2) low-frequency-dominant power, (3) globally attenuated oscillatory power, and (4) faster frequency-shifted dynamics. The profiles showed graded differentiation across childhood in effortful control (Cluster 1>2>3>4), with strong evidence for higher effortful control in Clusters 1/2 relative to Clusters 3/4 (posterior probabilities > .95). Additional differentiation was observed across surgency, negative affectivity, and psychopathology symptoms. Clusters 3/4 showed higher internalizing and externalizing symptom probabilities relative to Clusters 1/2, particularly Cluster 2, which also showed lower surgency relative to Clusters 1/3/4. Conclusions: Infant EEG-derived neurophysiological profiles prospectively differentiated temperament and psychopathology outcomes in childhood. With ongoing research, data-driven EEG profiling may provide a scalable, biologically informed framework for early mental health risk stratification prior to the consolidation of stable psychiatric diagnoses.

Adolescence is a period of rapid neurodevelopment during which psychiatric symptoms may emerge, yet symptom-specific markers show inconsistent associations with cognition and brain structure and can rarely be generalised longitudinally. Using data from the ABCD Study, we derived a transdiagnostic mental-health burden measure that integrates multiple symptom domains and examined its cognitive and structural brain correlates in early adolescence longitudinally. Adolescents with higher burden showed consistently lower performance in vocabulary, memory, and processing-speed, alongside widespread reductions in whole-brain, cortical, and white-matter volumes at baseline and after 2 years. These effects were strongest in a subgroup with persistent high burden and replicated in cross-sectional analyses. After 4 years, mental-health differences remained robust, although brain-behaviour associations weakened, likely reflecting developmental reorganisation and reduced sample size. Our study demonstrates that global mental-health burden provides a scalable, developmentally appropriate marker of early psychiatric vulnerability that overcomes limitations of symptom-specific approaches.

Background: Sleep disruption is prevalent in people with neurodevelopmental disorders such as autism but is not clear whether it occurs as an endophenotype or secondary to other behaviours. The ABCD Study is a population-based longitudinal study that monitors the health, demography and lifestyle of over 11,000 children in the US. In this study we leverage these data to investigate whether traits consistent with autism (social responsiveness) are associated with sleep disruption independent of lifestyle and other behavioural measures. Methods: Autistic traits were assessed using the Social Responsiveness Scale at age 11, and sleep disruption and behavioural outcomes were assessed at ages 11 and 13 years using the Sleep Disturbance Scale, and the Child Behaviour Check List, respectively. Demographic, health and lifestyle-related variables were assessed by caregiver questionnaires. Regression models were applied to investigate associations between autistic traits and sleep outcomes. Results: There was a significant cross-sectional association between sleep disturbance and SRS at age 11 years old that was independent of sex, ethnicity, socioeconomic position, physical activity, sedentary behaviour and anxiety/depression ({beta} = 0.12, 95% CI (0.07, 0.17); p < 0.001), that persisted at age 13, and that was modulated by chronotype, with evening types showing a stronger association. Discussion: Social responsiveness assessed in early adolescence (age 11) were associated with sleep disruption independent of multiple confounding factors and were prospectively associated with sleep disruption at age 13 years. These findings contribute to the evidence that disruption of sleep and circadian timing may have a primary role in the neurobiological mechanisms that mediate autistic traits.

Importance Anxiety and depression frequently co occur and show developmentally patterned co-development from childhood to adolescence. Adult psychiatric outcomes vary according to the timing, sequencing, and persistence of early symptoms, yet it remains unclear whether patterns of co development are comparable across high income and low and middle income country contexts. Objective Examine joint developmental trajectories of anxiety and depression from childhood to adolescence and their associations with anxiety and depression diagnoses in young adulthood. Design, Setting and Participants Population based prospective cohort studies in the UK (Avon Longitudinal Study of Parents and Children [ALSPAC], N=9,586) and Brazil (Pelotas 2004 Birth Cohort, N=3,815). Main Outcomes and Measures Trajectories were derived using parallel process latent growth models and latent class growth analyses of anxiety and depression using the Development and Well Being Assessment at early childhood (6-7 years), middle childhood (10-11 years), and adolescence (13-15 years). Diagnoses of anxiety and depression at 18 years were assessed via the Clinical Interview Schedule (ALSPAC) and the Mini International Neuropsychiatric Interview (Pelotas). Results Prevalence of anxiety and depression from early childhood to adolescence was similar across cohorts. Co-development was stronger in ALSPAC, with modest increases in both conditions, whereas in Pelotas, anxiety increased rapidly while depression showed little average change. In both cohorts, four trajectory classes were identified: stable-low (ALSPAC, 41%; Pelotas, 54%), increasing (31%; 28%), decreasing (23%; 15%), and persistent-high anxiety/increasing depression (5%; 3%). Compared with the stable-low class, youth in the increasing and persistent-high classes had elevated odds of depression (ALSPAC: OR=2.0 [95% CI, 1.4-2.8] and 4.2 [2.6-6.7]; Pelotas: 2.2 [1.5-3.3] and 2.9 [1.4-6.0]) and anxiety in young adulthood (ALSPAC: 1.6 [1.2-2.2] and 4.8 [3.2-7.0]; Pelotas: 1.7 [1.2-2.6] and 2.9 [1.5-5.8]). No increased risk was observed in the decreasing class. Conclusions and Relevance Patterns of anxiety and depression co development were comparable across the UK and Brazil, suggesting shared developmental pathways. However, more rapid increases in anxiety among Brazilian youth may reflect context specific risk factors. Persistence or emergence beyond early childhood was critical for identifying later diagnostic risk in both settings, highlighting the importance of early monitoring and intervention.

BackgroundEarly life adversity (ELA) is associated with notable negative consequences across development. Experiences of deprivation may affect neurocognitive development, while experiences of threat may alter emotion processing. Deprivation and threat may also differentially influence reward processing. However, unique consequences of deprivation and threat beyond low family resources are debated. MethodsWe employed an exposure vs. control data analytic approach to isolate deprivation and threat influences from socioeconomic resources. Adolescent Brain Cognitive Development (ABCD(R)) Study youth exposed to neither deprivation nor threat (N=2408-2962) were matched to youth exposed to deprivation-only (N=638-721), threat-only (N=198-232), or threat non-exclusively (threat+: N=382-464) based on family income, parental education, race/ethnicity, sex, and age. Multivariate analyses were used to distinguish each ELA group from their respective control groups in the neurocognitive domain (resting-state connectomic maturation, cognitive task performance, and cortical grey matter thickness at two timepoints) and in the neuroaffective domain (nucleus accumbens and caudate activation to reward anticipation and amygdala and insula activation to fearful faces). ResultsIn the neurocognitive domain, similar latent variables (LVs) differentiated the deprivation and threat+ groups from their respective matched control groups. This LV corresponded to neurocognitive maturation, loading positively on cortical functional maturation and task performance, and negatively on cortical grey matter thickness. This LV was weaker in the deprivation and threat+ groups compared to controls. In the neuroaffective domain, no significant LVs were found. ConclusionBoth threat and deprivation exposure during childhood may delay neurocognitive development in early adolescence beyond their co-occurrence with low socioeconomic resources.

Importance Prenatal alcohol exposure (PAE) is associated with lasting cognitive and neurodevelopmental deficits and can quadruple risk for depression later in life. However, it remains unknown whether there are specific trimesters when PAE is more strongly associated with longitudinal trajectories of internalizing symptoms - an indicator of depression risk - across childhood and adolescence. Objective To investigate how PAE timing and dosage are associated with internalizing symptom trajectories from ages 4 to 16.5 years. Design, Setting and Participants We analyzed prospective data from the Avon Longitudinal Study of Parents and Children (ALSPAC), an ongoing longitudinal birth cohort from the United Kingdom. Internalizing symptom trajectories were estimated for 6,409 participants. Primary analyses were conducted on 2,254 participants with complete data on PAE in all three trimesters, covariates, and trajectories. Main Outcomes and Measures We used growth mixture modelling to identify latent trajectories of depressive symptoms measured using the internalizing symptom scale from the Strengths and Difficulties Questionnaire (SDQ) at seven occasions between ages 4 to 16.5 years. Prospective alcohol consumption during each trimester were categorized into three PAE dosages: unexposed (0 drinks/week), low (1-7 drinks/week) and high (7+ drinks/week). Results We identified five distinct depressive symptom trajectories: stable low (75.9% of participants), moderate childhood peak (11.2%), progressive increase (5.57%), high early childhood (4.73%), and early adolescent peak (2.61%). PAE in the second (relative risk [RR]=2.08, 95% CI=1.15-3.76) and third trimesters (RR=1.83, 95% CI=1.05-3.21), as well as total PAE burden across pregnancy (RR=1.33, 95% CI=1.06-1.68) increased risk for the progressive increase trajectory, versus the stable low trajectory. High PAE in the second (RR=2.71, 95% CI=1.41-5.21) and third (RR=2.27, 95% CI=1.27-4.05) trimesters drove elevated risk for this trajectory. PAE in the first trimester or at low dosages showed no associations with depressive symptom trajectories. Negative control analyses of paternal drinking also found no associations. Conclusions and Relevance Our results highlight the second and third trimesters as potential sensitive periods for the impact of PAE on rising depressive symptoms from childhood to adolescence. Ultimately, these findings could inform the design of prevention programs, and facilitate targeted interventions to youth at elevated risk for depression.

Purpose. Perinatal loss is associated with a high risk of persistent psychological distress, including prolonged grief, depression, anxiety, and post-traumatic stress symptoms. Cognitive processes such as rumination may play a crucial role in maintaining and amplifying distress following loss, yet their specific contribution in perinatal bereavement remains underexplored. Methods. The CARING (Cognitive Analysis and Rumination INvestigation in perinatal Grief) study employed a cross-sectional design involving 298 parents who experienced perinatal loss within the previous five years. Participants completed an anonymous online survey including measures of depressive rumination (Ruminative Response Scale, RRS), angry rumination (Anger Rumination Scale, ARS), perinatal grief (Perinatal Grief Scale, PGS), general psychopathology (SCL-90), and post-traumatic stress symptoms (NSESSS). Non-parametric analyses were conducted to examine associations between rumination patterns and psychological outcomes. Results. Higher levels of rumination were significantly associated with greater perinatal grief, depressive and anxiety symptoms, and post-traumatic stress. Depressive rumination showed consistently stronger associations with all outcomes compared to angry rumination. Participants presenting both depressive and angry rumination exhibited the highest levels of grief intensity, psychological distress, and PTSD symptoms, suggesting a graded relationship between rumination patterns and severity of distress. Rumination levels were not significantly associated with gestational age at loss or with having received psychological support. Conclusions. Rumination, particularly in its depressive form, appears to function as a transdiagnostic cognitive vulnerability factor in perinatal bereavement. These findings highlight rumination as a potential target for early screening and tailored psychological interventions aimed at reducing long-term distress following perinatal loss.

Neurobiological mechanisms underlying child maltreatment perpetration remain poorly understood, and the role of immune dysregulation has rarely been examined. Here, we tested whether peripheral inflammatory signatures are linked to brain structural alterations in mothers who have perpetrated maltreatment, and whether such alterations mediate this link to perpetration. In this cross-sectional study integrating structural MRI and inflammatory proteomics, 16 mothers with histories of maltreatment perpetration and 145 age-matched control mothers underwent brain imaging; a subgroup (n = 52; 11 maltreatment, 41 control) also completed plasma proteomic profiling using the Olink Target 96 Inflammation panel. Whole-brain voxel-based morphometry revealed significantly reduced gray matter volume (GMV) in the right middle/inferior temporal gyri, a region implicated in social cognition and contextual interpretation, in the maltreatment group. Proteomic analysis identified 16 inflammation-related proteins differentially expressed between groups; among these, nine were significantly associated with GMV in this temporal region. Lower GMV was associated with higher levels of pro-inflammatory proteins (CCL20, IL-17C) and with lower levels of immune-regulatory and metabolic proteins (CXCL1, CXCL6, SIRT2, STAMBP, MCP-2, MCP-4, 4E-BP1). Mediation analyses revealed that both protein sets were indirectly associated with perpetration through this regional GMV, with opposing patterns of direct association. These findings suggest that peripheral immune imbalance, characterized by elevated inflammatory signaling and diminished immune-regulatory capacity, is linked to structural vulnerability in a temporal cortical region involved in social cognition, specifically in perpetrating mothers. This neuroimmune pathway may contribute to maladaptive interpretation of child signals during caregiving and represents a potential target for biomarker-informed preventive intervention.

Autism development involves multiple genetic and early-life environmental factors. Studying the placenta's gene expression profile may reveal key mechanistic pathways in autism development. Here, using a nested case-cohort design within an Australian population-derived prebirth cohort study (n=1074), we identified 1,644 differentially expressed genes (DEGs; FDR<0.05) in the placenta of children with autism diagnosis (n=43), compared to those without (n=120). The top enriched pathways related to mitochondrial translation, oxidative stress, RNA processing and transcription regulation. CYP1A1, the most important xenobiotic-metabolising enzyme of the placenta, was the top downregulated DEG in the placenta of children with autism, while immuno-regulatory human leukocyte antigen (HLA)-related genes were among the top upregulated DEGs. A machine learning-based approach predicted autism from the transcriptomic data with a median sensitivity of 0.57 (2.5th-97.5th centiles: 0.29, 0.76) and median specificity of 0.92 (2.5th-97.5th centiles: 0.78, 0.98). Weighted Gene Correlation Network Analysis identified eight affected placental gene modules, with the largest five modules being enriched primarily for mitochondrial bioenergetics, oxidative phosphorylation and RNA processing pathways. This placental transcriptomic signature of impaired mitochondrial function and gene transcription regulation among infants subsequently diagnosed with autism has profound implications for understanding both risk factors and prediction, suggesting the possibility of identifying modifiable prenatal pathways to improve autism outcomes.

IntroductionDown syndrome (DS), arising from Trisomy 21, is the most common genetic condition associated with intellectual disability. While smaller total brain volumes have been consistently observed in DS, no longitudinal neuroimaging studies have examined volumetric brain development in DS during infancy, a period of rapid neural growth when interventions may have the greatest impact. MethodHigh-resolution T1- and T2-weighted images were acquired during natural sleep in a multisite longitudinal cohort of 44 infants with DS and 39 control infants without DS at ages 6 and 12 months. Neuroimaging data were harmonized to reduce batch effects, and a novel deep-learning, repeated-measures segmentation approach was applied to optimize neuroanatomical segmentations. Total intracranial volume (ICV) and bilateral absolute subcortical volumes (amygdala, caudate, hippocampus, pallidum, putamen, thalamus) were first directly compared in infants with and without DS at 6 and 12 months. Hierarchical linear modeling (HLM) evaluated longitudinal group differences for each structure, accounting for sex, gestational age, and laterality. Subcortical group differences estimated by HLM were also compared to group differences in total ICV. ResultsICV in infants with DS was lower than controls at 6 months (12.6%; p<.001) and 12 months (16.3%; p<.001). Subcortical structures displayed a range of lower volumes (6.9%-13.1%; ps[&le;].003) in infants with DS, although the caudate and putamen were exceptions. Caudate volumes were on average lower in DS but not significantly different from controls, while putamen volumes were on average higher in DS but not significantly different from controls, except for the right putamen, which was significantly larger (5.3%; p=.018) at 6 months. In HLM, ICV and all subcortical structures showed slower growth in DS from 6 to 12 months, except for the amygdala and putamen, which displayed similar growth rates to controls. DS-associated reductions in subcortical volumes were similar in magnitude to ICV, although 12-month caudate and 6- and 12-month putamen volumes were enlarged relative to ICV. ConclusionInfants with DS exhibited substantially reduced ICV and widespread reductions in subcortical volumes and growth from 6-12 months. Across a range of volumetric differences, findings were most distinct in the basal ganglia, for which volume reductions were attenuated in the caudate, while the putamen was uniquely enlarged with comparable growth to controls. These observations support early regional specificity in the neural impact of Trisomy 21 and underscore the utility of infant neuroimaging to inform biologically based interventions and clinical trial readiness in DS.

Introduction: Autism spectrum disorder, or autism, is a common neurodevelopmental condition characterized by socio-communicative problems together with restrictive and repetitive behaviors. Typically, the latter is manifested as deficits in behavioral flexibility, i.e. changing routine behaviors to adapt to environmental changes. Despite noticeable difficulties with flexible behavior in autism, there is to date not adequate knowledge about the intricacies of such challenges and neurobiological processes that may subserve them. This study aims to investigate both cognitive and motor flexibility in autistic compared with neurotypical adults using a novel combination of detailed methods for brain imaging and behavioral investigations in relation to probabilistic reversal learning (PRL) paradigms. In addition, the experiences of autistic adults on flexible behavior in education and everyday activities will be explored. Methods and analysis: Differences in cognitive flexibility between autistic (n[&ge;]20) and neurotypical (n[&ge;]20) adults (18-35 years) will be investigated in terms of brain activations, measured by functional magnetic resonance imaging (fMRI), during two-choice PRL performance (cognitive task). In addition, group differences in microcirculation as measured by arterial spin labelling (ASL) will be evaluated. Group differences in motor flexibility will be investigated as expressed in movement planning and execution (spatio-temporal parameters), measured by a robotic manipulandum platform (KinArm End-Point Robot), during two-choice PRL performance (motor task). Semi-structured interviews will be conducted individually with autistic participants (n=15). Questions concern own experiences of cognitive and motor behavior, and strategies used to support flexibility in these behaviors. Data from this qualitative approach will be analyzed by thematic analysis. Ethics and dissemination: Ethical approval has been obtained from the Swedish Ethical Review Authority (ref:2025-07939-01) and the study will be conducted in accordance with the Declaration of Helsinki, the European Union General Data Protection Regulation (GDPR) and national guidelines for the storing of personal data. The different investigations included are well-established, non-invasive and safe. Study outcomes will be published in peer-reviewed international scientific journals (open access), presented at national and international conferences, and to any interested audience/stakeholders.

In Brazil, autistic children and their families face significant challenges in accessing evidence-based interventions, especially via the national public health service. Here, we report the protocol for a hybrid effectiveness-implementation trial, which will investigate the large-scale implementation of Paediatric Autism Communication Therapy (PACT) as well as its real-world effectiveness in Brazilian public health services for autistic children. Eligible professionals from public health services across the five regions of Brazil will be trained in PACT. They will deliver the intervention, which consists of 14 sessions delivered over 6 months, to dyads of autistic children and their caregivers in their regular clinical practice for the trial period of 18 months. We will use elements of three implementation science frameworks to systematically study factors that influence the implementation of PACT in this setting. To study effectiveness dyads will be randomised to receive PACT immediately or following a 6-month waitlist, stratified by healthcare service. Effectiveness outcomes (parent-child interaction, child adaptive social communication skills, caregiver well-being) will be collected pre- and post-PACT/waitlist and compared between groups. This trial will provide the first evidence on the effectiveness of PACT implemented in a public health system and the barriers and facilitators to such large-scale implementation.

Although romantic partners tend to resemble each other on many characteristics, the geographical processes underlying partner similarities remain poorly understood. Using Finnish nationwide registry data from cohabiting or married partners (N = 1,500,204 couples; partnerships were formed between 1990-2023), we examined regional differences in partner similarity in mental disorders, educational attainment, and adolescent school performance. We also analysed geographical variation in partner similarity within three major cities. Accounting for local demographic composition of potential partners attenuated the partner similarity from r=0.43 to r=0.34 for highest obtained educational attainment, but increased partner similarity in any mental disorders from r=.40 to r=.42. In urban municipalities partners were more similar in educational attainment, but less in mental disorders, compared to more rural regions. We found no clear within-city variation in partner similarity. These findings highlight the role regional demographic composition plays in partnership formation and suggest different partnering dynamics depending on societal organization.

Importance: Individuals with psychiatric disorders face elevated cardiometabolic risk which is linked to increased mortality. The extent to which this reflects shared pathogenesis or the downstream effects of illness and treatment remains poorly understood. Objective: To characterize the direct pleiotropic effects of psychiatric genetic liability on circulating metabolites and aggregate cardiometabolic risk, independent of psychiatric diagnosis and psychotropic medication use. Design: Cohort study. Setting: Mass General Brigham Biobank (MGBB). Participants: MGBB participants with metabolomic profiling, genomic data, and linked electronic health records. Exposures: Genetic liability to nine psychiatric disorders quantified using polygenic risk scores (PRS): attention deficit/hyperactivity disorder (ADHD), anorexia nervosa (ANO), anxiety disorder (ANX), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), PTSD, schizophrenia (SCZ), and substance use disorder (SUD). Main Outcomes and Measures: 249 circulating metabolites and four metabolomic risk scores (MRS) for type 2 diabetes, myocardial infarction, ischemic stroke, and vascular dementia. PRS-metabolite associations were estimated using nested models adjusting for lifetime psychiatric diagnosis and psychotropic medication use. Results: Across 25,290 participants, we identified 604 significant PRS-metabolite associations (Bonferroni p< 1.36 x 10-4), of which 89% persisted after adjustment for lifetime diagnosis and medication use, suggesting that the direct genetic effects on metabolism are largely independent of illness or treatment. PRS for MDD, PTSD, and ADHD showed the most extensive dysregulation, with a transdiagnostic pattern of elevated lipids and systemic inflammation, specifically triglycerides ({beta} = 0.04 to 0.05, all p< 4.4 x10-13) and glycoprotein acetyls ({beta} = 0.05, all p< 2.2 x10-16). Notably, PRS for SCZ and BD showed minimal metabolite dysregulation despite having the strongest association with their target diagnoses. PRS for MDD, PTSD, ADHD, and SUD were associated with increased MRS across cardiometabolic conditions ({beta} = 0.03 to 0.08, all p< 2.1 x10-4). Sensitivity analyses controlling for BMI or excluding participants without any psychiatric history (N: 21,305 and 11,150, respectively) showed a similar pattern. Conclusions and Relevance: Psychiatric genetic liability is associated with systemic metabolic dysregulation independent of illness onset or treatment, supporting a partially pleiotropic basis for psychiatric-cardiometabolic comorbidity.

Background: Long COVID is a syndrome characterized by symptoms and conditions across all biological systems. This breadth of Long COVID phenotypes impedes efforts to identify the mechanistic pathways of Long COVID. Low serotonin may play a role in long-term sequelae of COVID-19, and selective serotonin reuptake inhibitors (SSRIs) may prevent these sequelae. Evaluation of the relationship between SSRIs and distinct categories of symptoms and conditions associated with Long COVID can highlight the mechanistic pathways that drive these relationships. Methods: We evaluated electronic health record data from a retrospective cohort of patients in the National Clinical Cohort Collaborative with comorbid depression and COVID-19 between October 2021 and February 2024. We estimated the relationship between SSRI prescription (versus no SSRI prescription) during acute COVID-19 and the one-year cumulative incidence of Long COVID-related conditions and symptoms across 14 human phenotype ontology categories. We applied Super Learner and targeted maximum likelihood estimation to estimate risk ratios while adjusting for confounders of interest and correcting for false discoveries from repeated testing. Results: We evaluated EHR data from 542,938 patients. We found that patients who were prescribed SSRIs during COVID-19 had a significantly lower risk of symptoms and conditions related to gastrointestinal factors (adjusted risk ratio (aRR) 0.95, 95% CI 0.92, 0.97), general health (aRR 0.91, 95% CI 0.88, 0.95), headaches (aRR 0.96, 95% CI 0.92, 0.99) and skin (aRR 0.92, 95% CI 0.87, 0.98). Discussion: We found that the prescription of SSRIs during acute COVID-19 was associated with a significantly lower risk of post-COVID sequelae related to gastrointestinal, headache-related, skin-related, and general symptoms and conditions, compared with no SSRI prescription. These findings highlight the role of serotonin in Long COVID and specific sequelae that may be reduced by SSRIs.