Journal of Neurodevelopmental Disorders

Generalization is a key cognitive process that allows humans to flexibly apply prior knowledge to guide new behaviors. Difficulties with generalization and flexibility are observed across neurodevelopmental disorders, especially autism, limiting adaptive function and quality of life. Cognitive-behavioral treatment benefits some but not all autistic individuals. As treatment requires application of learned skills to everyday life, variability in generalization ability may limit intervention success in autism. While cognitive substrates of learning and generalization are well established, their potential for explaining clinical outcomes is not known. Here, we combined a category learning task with computational modelling to distinguish two learning strategies underlying generalization -- prototype abstraction vs. exemplar memorization -- and tested whether individual differences in these learning strategies predicted real-world intervention outcomes in autistic youth. Fifty-four participants completed the category learning task at two pre-intervention timepoints, and then completed Unstuck and On Target:14-22 intervention targeting flexible problem solving, goal setting, and planning. We found that participants who consistently relied on prototype abstraction (N=26) were subsequently more likely to benefit from the intervention, showing improvement in parent- and self-reported flexibility. These findings identify prototype abstraction as a clinically relevant cognitive capacity that may help explain individual differences in intervention response and support the tailoring of interventions. More broadly, they demonstrate the value of linking basic cognitive mechanisms to clinical outcomes and may inform strategies to enhance the effectiveness of cognitive-behavioral interventions for youth with developmental disabilities.

The Autism Spectrum Quotient (AQ-50) is widely used to assess autistic traits, yet its Hungarian version has not been psychometrically evaluated. We assessed the reliability, factor structure, temporal stability, convergent validity, and clinical utility of the Hungarian AQ-50 and a revised translation (AQ-50-HU-R) in two samples (N1 = 1967; N2 = 423), including autistic and non-autistic participants. The AQ-50-HU-R showed high internal consistency and test-retest reliability. A bifactor model provided the best fit ({chi}2[1125] = 1650.433, p < 0.001; CFI = 0.991; TLI = 0.990; RMSEA = 0.033 [90% CI = 0.030-0.037]; SRMR = 0.083), with 71% of common variance attributable to a general autistic traits factor. The total score distinguished clinically verified autistic participants from participants reporting no ASD diagnosis (AUC = 0.906), with a cutoff of 25. Associations with ADOS scores were weak or nonsignificant. The AQ-50-HU-R is best interpreted as a reliable total-score screening measure, supporting referral for comprehensive autism assessment.

Children and adolescents with hearing loss frequently encounter reduced auditory access and delayed language development, factors that may influence the maturation of executive functions. This study examined developmental differences in planning, a core executive function, in 98 children and adolescents with hearing loss or normal hearing aged 7 to18 years using the Tower of London task. Compared to normal hearing peers, participants with hearing loss made more unnecessary moves and rule violations and initiated problem-solving more rapidly, suggesting reduced preplanning efficiency and increased impulsivity. These group differences were most pronounced in adolescents, who showed faster initiation and greater movement inefficiency than age-matched normal hearing participants. Within the hearing loss group, adolescents displayed higher accuracy and longer initiation times than children, reflecting developmental improvements despite persistent gaps relative to hearing peers. Language development age did not alter the main effects. Findings indicate that reduced early auditory and language access may contribute to differences in planning development, highlighting the need for targeted executive functions support in educational and clinical settings for youth with hearing loss.

A body of research suggests that autistic individuals are less likely to drink alcohol than neurotypicals. However, emerging studies support a link between autism and alcohol use. This complex relationship is also reflected in studies that have examined the genetic overlap between the two traits. However, it is unclear whether there is a direct causal relationship between them. To explore this, we applied a combination of polygenic score and Mendelian randomisation analyses using publicly available genome-wide summary statistics and phenotypic measures of autism and alcohol consumption from UK Biobank. LD score regression analyses did not provide evidence of a genetic correlation between genetic liability for autism and drinks consumed per week (rg=-0.08; CI95%=-0.19, 0.03). Further, findings from polygenic score analyses did not support an association between genetic liability for autism and overall monthly alcohol intake. Univariable Mendelian randomisation analyses showed little evidence for a total effect of autism, attention deficit hyperactivity disorder (ADHD) or depression on overall monthly alcohol consumption. Multivariable Mendelian randomisation analyses also showed little evidence of a direct effect of autism on drinks per week when controlling for ADHD and depression. It is plausible that genetic liability for autism does not directly increase the amount of alcohol consumed but instead operates via commonly co-occurring difficulties in the autistic community. However, our findings may be due to methodological shortcomings, including weak instruments biasing effects towards to the null. Consequently, results should be interpreted with caution and further research conducted to address these issues.

Purpose: In clinical trials, treatment efficacy is commonly assessed by comparing control and treatment groups. However, in large samples, even small and clinically trivial differences may achieve statistical significance. Accordingly, the Minimal Clinically Important Difference (MCID) is used as a threshold to determine whether statistically-significant effects are also clinically meaningful to patients. The objective of this study was to estimate the MCID for the Childhood Autism Rating Scale Second-Edition (CARS2) using the Patient Impression of Change (PIC) as an external anchor. Methods: Single-item PICs are not well suited to characterizing improvement in a multifaceted disorder such as ASD. Accordingly, the 77-item Autism Treatment Evaluation Checklist (ATEC) was used as a multi-item PIC. CARS2 and ATEC were administered concurrently to 62 children with ASD, aged 1.8-7.9 years, with assessments conducted six months apart. Results: The correlation between changes in CARS2 and ATEC total scores was 0.41-0.44 (p<0.0001), supporting the use of ATEC as an anchor measure. Two anchor-based methods yielded MCIDs of 2.39-2.82 CARS2 points. Two distribution-based methods produced MCIDs of 1.33-3.32. Conclusions: Taken together, these approaches suggest that a between-group difference of 2.6 CARS2 points (the midpoint of the anchor-based estimates) may serve as the MCID in children with ASD.

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition defined by differences in social communication and restricted, repetitive behaviours. As diagnostic criteria have broadened, ASD is now recognised across a wider range of individuals, raising key questions about its structure: does ASD have discrete sub-types, or is it better conceptualised as a continuous, possibly multidimensional, condition? We aim to explore whether a multidimensional continuum model more accurately captures the variability within ASD. We analysed a large SPARK phenotypic dataset of medical history and diagnostic surveys (background history, SCQ, RBS-R; n=36,710 individuals). We apply and compare two traditional statistical approaches, Factor Analysis and Gaussian Mixture Models, with a modern machine learning technique, the Variational Autoencoder (VAE). VAEs reconstructed unseen test data with ~4-fold better accuracy than Factor Analysis, and ~8-fold better accuracy than Gaussian Mixture Models. We identified four stable latent factors across 100 independently trained VAEs. These four dimensions provide an individual behavioural profile that can be visualized using radar-plots, offering a compact way to compare profiles at the person level. Through further analysis, we found evidence for 3 overlapping clusters or subtypes of ASD identified within the 4D latent space. This work aims to inform new ways of modelling ASD using a VAE that will be able to discern between a continuum or a clustered output and that go beyond binary diagnosis, instead reflecting the complex range of trait profiles, with implications for personalised diagnosis and intervention.

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

PACS1 syndrome is a rare neurodevelopmental disorder caused by a recurrent de novo missense variant (p.R203W) in the PACS1 protein. However, it remains unclear whether the p.R203W variant acts through a loss-of-function or alternative mechanism. Here, we used isogenic iPSC-derived neurons (iNs) to directly compare the effects of PACS1 p.R203W to complete loss of PACS1 function. Using a combination of proteomic, biochemical and electrophysiological approaches, we identified molecular and functional phenotypes associated with each genotype. While PACS1(+/R203W) and PACS1(-/-) iNs shared phenotypic abnormalities, the overall molecular and functional consequences of the p.R203W variant were distinct from those caused by PACS1 deficiency. Notably, PACS1(+/R203W) presented with unique proteomic and kinase signaling signatures and a shift in stimulus dependent excitability. These findings demonstrate that PACS1 syndrome is not caused by a simple loss of function and instead support a non-loss-of-function mechanism. Lastly, our interactome analysis suggests that the p.R203W variant retains aspects of canonical PACS1 function while acquiring novel molecular interactions that could contribute to PACS1 syndrome pathogenesis. Altogether, these findings provide a framework for future mechanistic studies and therapeutic development in PACS1 syndrome. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/747101v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@d1522corg.highwire.dtl.DTLVardef@69e4dforg.highwire.dtl.DTLVardef@30eebcorg.highwire.dtl.DTLVardef@899b9d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background. GBA2-associated hereditary spastic paraplegia (SPG46) is a rare autosomal recessive neurodegenerative disorder caused by loss-of-function mutations in GBA2, encoding the non-lysosomal glucocerebrosidase 2. GBA2 deficiency leads to glucosylceramide (GlcCer) accumulation and glucosylated cholesterol (GlcChol) depletion, causing cytoskeletal defects in immature neurons. However, the mechanisms linking lipid dysregulation to neuronal dysfunction remain poorly understood. Methods. We modelled GBA2 loss of function by chronic pharmacological inhibition in mouse cerebellar granule neurons (CGNs) and assessed neuronal morphology, synaptic organization, Ca2+ dynamics, mitochondrial function and actin cytoskeleton during maturation. Proteomic profiling was performed in GBA2-inhibited and GlcChol-supplemented neurons. Findings were validated in a zebrafish gba2 crispant model by evaluating motor behavior, cerebellar development, neuronal organization and mitochondrial function, and in patient-derived fibroblasts carrying a homozygous pathogenic GBA2 variant (NM_020944). The role of RAC1 was studied in both neurons and patients' cultured skin fibroblasts, and upon rac1 pharmacological inhibition in zebrafish crispants. Results. Chronic GBA2 inhibition impaired axonal outgrowth in immature CGNs but not neurite complexity in mature neurons, suggesting morphological compensation. Nevertheless, mature neurons displayed enlarged presynaptic terminals, impaired synaptic vesicle clustering and altered Ca2+ responses to potassium and glutamate, the latter associated with NMDA receptor redistribution without changes in total receptor levels. Mitochondrial alterations were observed in CGNs, patient fibroblasts and zebrafish, consistent with defective architecture of the mitochondrial network. Proteomics revealed convergent alterations in actin cytoskeleton, synaptic pathways and cellular metabolism following both GBA2 inhibition and GlcChol supplementation. GlcChol bidirectionally regulated RAC1 function, likely altering its spatial distribution rather than its global activation. Confocal imaging confirmed abnormal RAC1 and F-actin localization in patient fibroblasts. Zebrafish gba2 crispants recapitulated motor deficits, Purkinje cell loss, motor neuron disorganization and mitochondrial abnormalities. Pharmacological Rac1 inhibition rescued motor behavior and neuronal organization, linking cytoskeletal disorganization to the observed phenotype in the zebrafish model. Conclusions. Our findings identify a pathogenic GlcChol-RAC1-actin signalling axis linking lipid imbalance to synaptic disorganization, NMDA receptor redistribution and mitochondrial dysfunction in SPG46. The selective vulnerability of corticospinal neurons, cerebellar granule neurons and Purkinje cells may reflect their dependence on this pathway. Rac1 inhibition rescues disease phenotypes in vivo, highlighting this pathway as a promising therapeutic target.

Background: As cannabis policy changes in the United States, secondhand cannabis smoke (SCS) is increasingly common, including within families. However, prevalence of exposure and clinical correlates over time in adolescents are not fully understood. Objectives: (1) To estimate the prevalence of SCS and personal cannabis use in US-based teens exposed to SCS, and (2) examine the cognitive trajectories of adolescents exposed to SCS compared to non-exposed peers. Methods: Data from the Adolescent Brain Cognitive Development (ABCD) Study was used. Participants (n=11,316 of full cohort with follow-up data; n=776 with self-reported family SCS exposure) attended yearly visits from ages 11-17, completing substance use interviews, toxicological testing, and the NIH Toolbox Cognitive battery. Youth with SCS but no personal cannabis use (n=419; 47% female) were matched on prenatal substance exposure, family substance use history, and sociodemographics to non-SCS exposed and non-cannabis-using youth with a 1:2 ratio (Controls n=838). Linear mixed-effects models assessed cognitive performance by SCS*age interactions, accounting for random effects of subject and family. Covariates included sex and alcohol, nicotine, and other substance use. Secondary models analyzed performance by cumulative waves of reported SCS exposure interacting with age. Results: Of the full cohort, 6.9% (n=776) reported exposure to SCS. Of these individuals, 46% endorsed lifetime personal cannabis use by age 17, relative to 20% of non-SCS exposed youth (OR=3.83[95%CI:3.29,4.44]). Within matched participants, SCS*age demonstrated a significant interaction on attention and inhibitory control ({beta}=-0.32, p=.028), with SCS demonstrating reduced improvement over time. More waves of exposure were also associated with worse performance over time ({beta}=-0.39, p=.057). Discussion: Almost half of those who had been exposed to SCS endorsed personal cannabis use. Cognitive findings were domain specific, similar to findings in secondhand tobacco: SCS exposed youth showed restricted improvement in attention and inhibitory control by age 17. Public health and policymakers should make efforts to curb youth SCS exposure, given the potential for risk which has not been fully explored to date.

Recent large-scale studies have enabled new knowledge about genetic underpinnings of morphological and electrophysiological alterations of the retina. Variation in retinal traits, often of neurodevelopmental origin, have been linked to major psychiatric disorders (MPDs). Here, we investigate the genetic overlap between MPDs and key retinal traits to identify underlying molecular mechanisms. We obtained genome-wide associations studies data for bipolar disorder (BD), major depression (MD), schizophrenia (SCZ), and the retinal traits retinal nerve fibre layer thickness (RNFL), ganglion cell inner plexiform layer thickness (GCIPL), and vertical cup-disc ratio (VCDR). We estimated the number of trait-influencing variants shared between traits with MiXeR and identified shared genetic loci with condFDR. Subsequently, we examined the biological pathways of the genes mapped to shared loci. This revealed that GCIPL shared the most genetic variants with MPDs (~60%), followed by RNFL (~40%), and VCDR (~20%). The genetic variants shared between retinal traits and MPDs showed disorder-specific patterns with more pronounced overlaps of SCZ and BD with RNFL, and MD negatively correlated with GCIPL. Gene-pathway analysis highlighted the importance of GABAergic neurotransmission and a two-stage neurodevelopmental process in SCZ, whereas the role of mitochondria and a weaker developmental component were observed in BD. The results also implicated synaptic functioning and gene-expression processes in MD. Furthermore, polygenic analysis suggested that the genetic architecture of retinal traits can distinguish between MPDs. Our findings indicate shared genetic underpinnings between retinal traits and SCZ, BD, and MD, implicating altered neurodevelopment and neurotransmission underlying the retinal link to major psychiatric disorders.

Although the brain was traditionally considered immune-privileged, recent studies show immune factors play key roles in brain function. Dysfunction of these factors is linked to neurodevelopmental disorders, but mechanisms remain unclear. Using a maternal immune activation (MIA) mouse model, we investigated immune-related genes in neurodevelopmental disorder pathogenesis. MIA mice showed increased locomotor activity and disrupted prepulse inhibition. RNA-seq and qPCR analyses revealed persistent increases in major histocompatibility complex class II (MHCII) expression and persistent decreases in GABAergic synapse-related gene expression, particularly glutamate decarboxylase (Gad) expression, in dopaminergic regions. These expressions were negatively correlated, and immunohistochemistry showed MHCII at postsynaptic GABAergic synapses on dopaminergic neurons. Patch-clamp recordings confirmed reduced mIPSC frequency in MIA mice. MHCII knockout mice showed opposite phenotypes, while MHCII overexpression in dopaminergic neurons decreased Gad expression. These results suggest MIA-induced MHCII upregulation enhances pruning of GABAergic synapses on dopaminergic neurons, leading to behavioral deficits.

Background Alcohol use disorder (AUD) is highly prevalent in schizophrenia, yet the neurobiological basis of this vulnerability remains poorly understood. Neurodevelopmental models suggest that pre-existing brain dysconnectivity may increase vulnerability to AUD. We therefore tested whether schizophrenia-like neurodevelopmental pathology alters how alcohol-related experience is incorporated into large-scale brain networks. Methods Resting-state functional connectivity was assessed in male Sprague-Dawley rats (n = 18-21/group) with neonatal ventral hippocampal lesions (NVHL), a neurodevelopmental model of schizophrenia, and sham-operated controls, with or without voluntary adolescent alcohol exposure. Functional connectivity was assessed using seed-to-voxel and seed-to-seed analyses within a cortico-striato-limbic network. We additionally examined whether individual alcohol intake during adolescence predicted adult functional connectivity according to neurodevelopmental status. Results NVHL and adolescent alcohol exposure independently produced predominantly hypoconnected cortico-striato-limbic networks. However, alcohol exposure did not exacerbate NVHL-associated dysconnectivity but instead induced a distinct network reorganization characterized by functional hyperconnectivity. Although alcohol intake was comparable between groups, dose-dependent relationships between adolescent alcohol consumption and adult functional connectivity were observed in sham animals but were absent or markedly attenuated in NVHL rats. These effects were primarily centered on prelimbic cortex connectivity with the amygdala, hippocampus, and dorsal striatum, highlighting this circuitry as a major locus of altered experience-dependent remodeling. Conclusions These findings suggest that vulnerability to AUD associated with schizophrenia-like neurodevelopment may arise less from additive network dysfunction than from an altered capacity of large-scale brain networks for experience-dependent functional remodeling. Schizophrenia-like neurodevelopmental pathology may therefore change how alcohol-related experience is translated into persistent brain network organization.

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

Objective: This study examined the prevalence of psychotic experiences (PE) and how early onset and persistence of PE contribute to risk and severity of mental disorders in adolescents at familial high-risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP) and adolescents from a population-based control group (PBC). Methods: This is the second follow-up of a nationwide cohort study including 522 children at FHR-SZ (N=202), FHR-BP (N=120), and PBC (N=200). Participants were assessed at ages 7, 11, and 15 using a semi-structured interview to evaluate PE and mental disorders. Results: At age 15, adolescents at FHR-SZ reported more PE than PBC over the past six months (current) and the past four years, while adolescents at FHR-BP only reported more current PE. PE reported at two or three timepoints (persistent PE) predicted any Axis I disorder in mid-adolescence, corresponding to three- (OR 2.9, 95% CI [1.5-5.7]) and 21-fold (OR 21.4, 95% CI [2.8-162.3]) increased risks, respectively. Persistent PE also predicted multimorbidity, with three- (OR 2.8, 95% CI [1.0-7.6]) and four-fold (OR 4.1, 95% CI [1.2-14.1]) increased risks, respectively. This was after adjustment for sex, early mental disorders, and familial risk. Conclusions: This study demonstrates a strong link between persistent PE and mid-adolescence mental disorders. Our findings emphasize PE as important risk markers for mental disorders during mid-adolescence and highlight the importance of monitoring children with PE before age 7 who develop persistent symptoms.

Background: Higher Body Mass Index (BMI) is an established risk factor of sleep disturbance. It is not known if the effect is homogeneous across the lifecourse or if there is a particular time point in life that might be best to target. Methods: Two-sample Mendelian randomization (MR) was used to investigated the effect of childhood adiposity (adjusting on adulthood adiposity and obstructive sleep apnea (OSA)) on insomnia, morning chronotype, sleep duration, daytime sleepiness and daytime napping. Similarly, total, and direct effect of adulthood adiposity on these outcomes was explored. We used summary statistics from a genome-wide association study (GWAS) of UK Biobank for childhood and adulthood adiposity (n=453,169) and large-scale consortia of OSA (Million Veteran Program) (n=410,268), insomnia, and chronotype (23andMe) (n=1,978,022 and n=248,1000, respectively). Results: Two-sample univariable MR analysis provided no evidence of an effect of genetically predicted childhood adiposity on later life insomnia (Odds ratio (OR)= 0.94, 95% Confidence interval (CI)= 0.87, 1.03). Whereas, multivariable MR (adjusted for adulthood adiposity) analysis provide strong evidence of direct protective effect of genetically predicted childhood adiposity on later life insomnia (OR= 0.70, CI= 0.64, 0.77). Further, both in univariable and multivariable MR, a strong positive effect of increased childhood body size on morning chronotype was observed (OR= 1.16, CI= 1.01, 1.33 and OR= 1.36, CI= 1.15, 1.62, respectively) after accounting for adulthood body size. In both analysis the estimate did not change considerably after aditionally adjusting for OSA. However, childhood and adulthood adiposity found to be associated with OSA and OSA with insomnia. In both univariable and multivariable analysis, increased body size in adulthood increased the risk of having insomnia and a morning chronotype. Conclusions: The findings suggest that higher body size in childhood is not a risk factor for later life insomnia, whereas higher body size in adulthood was. Further, if healthy body size is maintained in adulthood, high childhood adiposity may decrease the risk of insomnia and increase the risk of being a morning person in later life. Keywords: childhood, adulthood, obesity, insomnia, morning chronotype, medelian randomization

Background: Multiple sclerosis (MS) is a chronic, immune-mediated disease of the central nervous system marked by demyelination and neurodegeneration. Beyond physical symptoms, MS is often linked to clinically relevant sleep disturbances. The variability and unpredictability of symptoms and disease progression can also fuel fear of relapse (FoR), undermining well-being and potentially increasing morbidity through inflammatory processes. Understanding biopsychosocial risk factors, including childhood maltreatment (CM) and sleep, in relation to FoR remains an important gap in MS management and research. Methods: Data from N = 48 participants were collected via an online survey. We used the Pittsburgh Sleep Quality Index (PSQI), the Fear-of-Relapse Scale (FoR), and the Childhood Trauma Questionnaire (CTQ) to assess the variables of interest. In addition, time points of exposure to different CM subtypes were assessed. Linear regression analyses were conducted to examine associations within the proposed negative triad. Results: A significant negative association between overall sleep quality and FoR was observed. In the total cohort, the interaction between CM and sleep was not a significant predictor of FoR. However, exploratory analysis revealed a significant interaction between CM and sleep among male participants, whereas the same interaction was not significant among female participants. Conclusion: A history of CM and impaired sleep quality introduce new stressors in managing one's own illness that have received little attention to date. However, the present study found that these factors were at least partly influential on the FoR. The results underscore the translational need for additional support services to enhance prevention and personalized care.

Despite its strong link to neuropsychiatric conditions, frustration remains critically understudied in humans and animals alike. Therefore, there is an urgent need to develop tools to understand and therapeutically target frustration-related functions. Interestingly, humans and rats respond similarly during frustrative nonreward by increasing barpress durations. We previously validated barpress duration in rat operant tasks as a reliable measure of frustration-related behavior; however, it is wellknown that in addition to duration of responding, emotional states such as frustration alter other aspects of responding such as force of pressing. One-dimensional, static measures such as maximum force could miss rich information contained within operant data. Thus, the objective of this study is to apply machine learning (ML) to force/time profiles to discriminate frustration-related barpresses from non-frustration-related barpresses. Results showed an AUROC for FR1 (i.e., non-frustrated) vs. extinction (frustrated condition) for individual barpresses of 0.65 that improved to 0.84 with a chunk size of 10. The model generalized well to progressive ratio responding, a different kind of frustration procedure. We conclude that force/time profiling does provide utility beyond one dimensional measures of duration or force separately, meaning that we can indeed infer the internal state of frustration from behavior using ML techniques. Importantly, this project will also serve as proof-of-concept for applying ML to predict other internal states from barpress data.

Obesity is a significant public health concern. Early-onset obesity in the context of rare disease can reflect genetically-mediated pathology or elevated susceptibility through indirect mechanisms. Mapping the diverse characteristics and needs of young people with obesity in the rare disease population is a first step toward mechanistic and translational research. We carried out a retrospective comparative analysis of demographic, genotypic, phenotypic and health service utilisation data for young people with obesity (cases: n=500) and without obesity (controls: n=11,444) from the UK 100,000 Genomes Project rare disease cohort. Cases and controls were recruited prior to genomic diagnosis, across clinical disorder categories. We observed significant association between socioeconomic deprivation and obesity risk. Young people with obesity had significantly higher utilisations of acute care and mental health services, indicating an overall higher health burden. A curated panel of 519 candidate obesity-associated genes demonstrated aggregate association with obesity, although no single gene reached significance. Phenotypic comparison between cases and controls highlighted increased multi-organ and neurological system involvement, highlighting the overlap between neurodevelopmental and obesity risks. Within the case group, we conducted cluster analysis to identify early-onset obesity groups with different phenotypic profiles, potentially arising from different causal pathways - this identified six obesity subgroups of interest, with differing involvement of neurodevelopmental and other systems. Our study confirms that obesity co-occurs with a wide range of factors within the rare disease population, and is associated with significant physical and mental health needs, requiring holistic lifelong care.

Background and Objectives: Deep sequencing of brain tissue in the research setting has established that mosaic variants are a major cause of malformations of cortical development (MCDs) and epilepsy. However, genetic testing in the clinical setting primarily detects germline variants using clinically accessible samples. We aimed to determine the diagnostic yield and clinical utility of deep sequencing in the clinical setting to identify pathogenic mosaic variants for this population. Methods: We performed a retrospective cohort analysis of individuals at Boston Children's Hospital with MCDs with or without epilepsy who received clinical deep sequencing between September 2017 and February 2026. Demographic, clinical, and genetic testing data were abstracted from the medical record. For individuals without systemic features, we classified brain tissue as an affected tissue sample. For individuals with systemic features, we classified brain or relevant non-brain tissue as affected. The primary outcome was the diagnostic yield of clinical deep sequencing performed using affected vs unaffected tissue samples. The secondary outcome was the clinical utility of genetic diagnoses. Results: Our cohort included 37 individuals (19/37 (51%) female, 18/37 (49%) male) with MCDs, of whom 35/37 (95%) had epilepsy (25 with brain tissue samples available from epilepsy surgery) and 8/37 (22%) had systemic features. Most (35/37 (95%)) had dysplasia phenotypes on MRI and 12/27 (44%) with pathology available had Focal Cortical Dysplasia Type I or II. The diagnostic yield was 53% (17/32; 16 mosaic and 1 germline variant) when clinical deep sequencing was performed using an affected tissue sample vs 0% (0/6) using an unaffected tissue sample (p=0.016). Of the diagnosed cases, 13/17 (76%) had testing performed on brain tissue (1 with systemic features) and 4/17 (24%) on non-brain tissue (3 buccal and 1 duodenal tissue, all with systemic features). All but one diagnosis involved the mTOR pathway. All diagnoses had clinical utility. Discussion: Clinical deep sequencing, when performed using an affected tissue sample, has high diagnostic yield and clinical utility for individuals with MCDs, especially dysplasia phenotypes, and epilepsy. Our findings support implementation of clinical deep sequencing for this population, especially as the genetic diagnoses have implications for emerging precision therapies.