Molecular Autism

ImportanceMotor skill impairments affect up to 87% of children with autism spectrum disorder (ASD) and are associated with greater severity of repetitive behaviors. Yet, most research examining this relationship has treated ASD as a unitary condition. Understanding whether motor-behavior relationships differ by genetic etiology could inform stratified approaches to ASD research and clinical care. ObjectiveTo determine whether the relationship between motor function and restricted and repetitive behaviors (RRBs) differs between children with monogenic forms of ASD (SHANK3, DYRK1A, or SCN2A variants) and children with idiopathic ASD. Design, Setting, and ParticipantsMatched cohort cross-sectional study using data from the Simons Foundation Powering Autism Research for Knowledge (SPARK) database. Children with loss-of-function variants in SHANK3, DYRK1A, or SCN2A were matched to children with idiopathic autism and intellectual disability. Main Outcomes and MeasuresMotor function was assessed using the Developmental Coordination Disorder Questionnaire (DCDQ). Repetitive behaviors were assessed using the Repetitive Behavior Scale-Revised (RBS-R), with subscales categorized as lower-order (stereotyped, self-injurious) or higher-order (compulsive, ritualistic, sameness, restricted interests). The primary analysis compared motor-RRB correlations between groups. ResultsThe sample included 93 children with monogenic autism (SHANK3, n=34; DYRK1A, n=46; SCN2A, n=13) and 787 matched children with idiopathic ASD. In idiopathic ASD, motor function was negatively correlated with RRBs (r = -0.156); in monogenic ASD, this reversed to a positive correlation (r = +0.185; {Delta}r = 0.341, P = 0.002). This reversal was specific to higher-order RRBs (idiopathic r=-0.106; monogenic r=+0.234; {Delta}r=0.339, 95% CI 0.124-0.535, P=0.002) and was not observed for lower-order RRBs ({Delta}r=0.212, P=0.05). All three genes showed positive correlations (SHANK3 r=+0.033; DYRK1A r=+0.262; SCN2A r=+0.623) with no significant heterogeneity (P=0.153). Conclusions and RelevanceThe relationship between motor function and repetitive behaviors differs by genetic etiology, with children with monogenic ASD showing a positive motor-RRB correlation specific to higher-order behaviors, opposite to the negative correlation observed in idiopathic ASD. This reversal was consistent across three molecularly distinct genes. These findings support stratifying autism research and clinical care by genetic etiology. KEY POINTSO_ST_ABSQuestionC_ST_ABSDoes the relationship between motor function and restricted and repetitive behaviors (RRBs) differ between children with autism spectrum disorder (ASD) attributable to SHANK3, DYRK1A, or SCN2A variants and children with idiopathic ASD? FindingsWe conducted a matched cohort cross-sectional study comparing correlations between motor function and RRBs in children with monogenic ASD versus children with idiopathic ASD and intellectual disability. Motor function was negatively correlated with RRBs in children with idiopathic ASD but positively correlated in children with monogenic ASD. MeaningGenetic variants may alter behavioral organization, supporting the value of stratifying populations of individuals with ASD by genetic etiology in both research and clinical care.

Misophonia is the adverse emotional reaction to everyday sounds (e.g., chewing or pen clicking). Since atypical sensory experiences are a key feature of autism, we investigated whether autistic individuals are more liable for experiencing misophonia symptoms. In addition, we explore the contribution of sensory sensitivity to misophonia symptoms in autism. Autistic adults (N=1050) filled out the Amsterdam Misophonia Scale-Revised (AMISOS-R), the Autism Spectrum Quotient (AQ-28), and the Sensory Processing Questionnaire (SPQ). Autistic people reported higher scores on the AMISOS-R compared to population levels, reflecting more misophonia symptoms. In particular autistic females and those with co-occurring disorders scored higher. In addition, we found that autistic traits strongly predicted misophonia symptoms. Hearing or vision sensitivity subscales of the SPQ significantly mediated the effect of autism on misophonia symptoms. The increased level of misophonia symptoms in autism and the mediation analyses suggest that autistic traits and sensory sensitivity are factors to consider for a subset of misophonia sufferers, with possible consequences for their clinical interventions.

Autism Spectrum Disorder (ASD) is a heterogenous condition that has no biologically relevant subtypes yet. Here, we utilized a multidimensional approach considering social deficits in ASD alongside negative valence and empathy dysfunction to distinguish ASD from Neurotypicals (NT) and to generate ASD subtypes using machine learning approaches. 114 subjects were analyzed, with 70 being NT and 44 ASD, all male with an IQ greater than 70, with 5 domains of personality (NEO-PI-r) and Reading the Mind the Eyes Test (RMET) scores included in the main classifier. We then used a multitude of behavioral (such as IQ, Broader Autism Phenotype, Autism Quotient, Interpersonal Reactivity Index) and clinical measures such as Autism Diagnostic Interview-Revised (ADI-R) alongside biological methods including DNA methylation of OXTR gene and resting-state functional connectivity (rsFC) to validate the putative subtypes. 30 ASD who received IN-OXT in a randomized, placebo-controlled, within-subject design and 17 new NT were part of the rs-FC analysis. A random forest tree algorithm was used to classify NT and ASD and Shapley Additive Explanation Values were used to describe the model and to cluster ASD subtypes using K-Means clustering. Three subtypes were generated with two of them being highly distinctive in behavioral and brain functional traits. One subtype named NASA (or Negative Affect and Social Aloofness) was characterized by high Neuroticism and Low warmth alongside lower rsFC between networks involved in social cognition, self-awareness, and sensory processing, such as Superior Temporal Sulcus and Sensorimotor Network; or ACC/Insula with visual cortex, Posterior Cingulate Cortex and visual cortex. The second subtype NADR (Neurocognitive and Affect Dysregulation with Resistance to Change) was characterized by higher DNA methylation of OXTR, hyperconnectivity between default mode network, reward areas and inferior frontal and fusiform networks. NADR has more cognitive difficulties and higher ADI-R scores as well as higher Neuroticism, higher personal distress, higher rigidity and lower openness. In a mixed model analysis, we found that IN-OXT in a dose dependent manner impacted NASA subtype by modulating rsFC between PCC and cerebellum and between Brainstem/Cerebellum and Parietal cortex to probably enhance social cognition and to reduce negative valence in this subtype.

AO_SCPLOWBSTRACTC_SCPLOWAutism Spectrum Disorder standardized behavioral assessments provide quantitative measures of symptoms, yet their reliability and consistency have not been systematically evaluated. We present the first large-scale comparative analysis of four widely used assessments. We analyzed behavioral assessments across three autism cohorts using correlations, clustering, and diagnostic agreement analyses. We related behavioral variation to genetic and imaging data to evaluate biomarker associations. Sentence-level embeddings generated by large language models reveal substantial semantic overlap across instruments. Nonetheless, behavioral scores are weakly correlated (0.26 {+/-} 0.21), and diagnostic classification shows only 65-80% agreement between tests. These patterns hold across three datasets comprising N = 1 954. None of the assessments show consistent associations with widely studied MRI or genetic biomarkers. These findings expose critical inconsistencies among widely used autism assessments and underscore the need for more reliable tools to support precision phenotyping, biomarker discovery, and individualized care. Rather than diminishing the utility of behavioral assessment in autism, the inconsistencies identified here highlight a critical opportunity to refine how behavioral phenotypes are defined and operationalized.

Predictive processing has been proposed as an explanatory framework for symptom development in both autism (ASD) and schizophrenia (SSD) spectrum disorders, with ASD being associated with an overweighting of (low-level) sensory evidence whereas SSD is characterized by an overweighting of (high-level) prior beliefs. The goal of the present study was to investigate these hypotheses in subclinical expressions of ASD and SSD in the domain of language processing. To test this, we used an auditory comprehension task designed to directly manipulate the precision of high-level semantic prior beliefs and low-level sensory evidence. We applied hierarchical Bayesian belief updating modeling to quantify this effect and used EEG to examine whether an imbalance in the weighting of prior beliefs and sensory evidence would be characterized by altered processing of semantic precision-weighted prediction errors as indexed by alterations in mean N400 amplitudes. Computational modeling revealed that increasing schizotypal traits were associated with a significant overweighting of prior beliefs, while autistic traits did not show a significant shift. Linear mixed models on the mean N400 amplitudes further indicated that this schizotypy-related overweighting of semantic prior beliefs was reflected in a reduced semantic prediction error signal, indexed by smaller N400 differences between low entropy sentences and both high and low-mismatch sentences. A similar pattern emerged for increasing autistic traits, though the effect was weaker and less distinct, pointing to a subtle overweighting of semantic prior beliefs, only. Overall, our findings provide converging computational and electrophysiological support for an overweighting of semantic prior beliefs with increasing subclinical schizotypy, consistent with predictive processing accounts of SSD, whereas we did not find evidence for an overweighting of sensory evidence with increasing autistic traits, with electrophysiological results instead pointing toward subtle alterations in the weighting of semantic prior beliefs.

ObjectiveAutism shows a male-biased diagnostic sex ratio. Given the heritability of autism, genetic factors likely contribute to this ratio. This study systematically reviews sex differences in additive common genetic effects related to autism and autistic traits. MethodsOriginal research was collected from PubMed, Web of Science, APA PsycInfo and Scopus (2008 - July 2025) following PRISMA guidelines. Genome wide association studies (GWASs) on autism, and related downstream analyses, including polygenic scores (PGS), Single-Nucleotide Polymorphism (SNP) heritability, and genetic correlations were included when sex-stratified results were reported. Risk of bias was assessed, followed by a best-evidence synthesis. ResultsOf 6,053 records screened, 21 studies were eligible. In clinical populations, results on mean PGS differences were inconclusive. In subgroups without intellectual disability, strong evidence indicated higher mean PGS in females. In general population samples, weak evidence supported this pattern. PGS associations with autistic traits showed inconsistent results, although stronger associations were reported for sensory sensitivity in males with weak evidence. SNP heritability findings were inconclusive. Genetic correlations between the sexes were significantly different from 1 (rg = 0.80 (SE = 0.09), but evidence was considered weak. DiscussionFindings suggest an axis of heterogeneity around intellectual disability. Inconsistent findings largely resulted in inconclusive evidence. Results highlight a lack of sex-stratified reporting and were limited by sample makeup such as male- and European ancestry dominated cohorts. Future sex-balanced and stratified GWAS and downstream analyses with complete reporting of female and male data are needed to clarify potential genetic sex differences in autism.

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental condition marked by pronounced heterogeneity in brain structure, which limits the development of targeted interventions. Morphological brain networks (MBNs) enable mapping of coordinated structural features across brain regions at the individual level. However, the specific organization of such networks in ASD and their potential relationships with underlying neurotransmitter systems remain largely unexplored. AimsTo characterize alterations in cortical thickness-based MBNs among adolescent males with ASD and to test whether these network changes spatially correspond to normative PET-derived neurotransmitter receptor/transporter maps. MethodsIn this case-control study, T1-weighted MRI data from 424 adolescent males (207 ASD, 217 typically developing) in the Autism Brain Imaging Data Exchange were analyzed. MBNs were constructed using interregional cortical thickness similarity quantified by Jensen-Shannon divergence. Graph-theoretical metrics were computed and group differences were assessed with permutation tests controlling for age and IQ. Spatial correlations between the left lateral orbitofrontal morphological similarity and atlas-based neurotransmitter maps were investigated using the JuSpace toolbox. ResultsAdolescent males with ASD showed increased normalized clustering coefficient (t=2.40, p=0.020, FDR corrected) and reduced nodal measures in the left lateral orbitofrontal cortex (OFC) including degree centrality, PageRank centrality, and betweenness centrality (all p<0.001, FDR corrected). Morphological similarity analysis revealed decreased OFC-based similarity with 65 brain regions. Furthermore, the OFC-related morphological similarity was associated with the spatial distributions of neurotransmitter systems, with GABAa, 5-HT1a, and -opioid receptors remaining significant after FDR correction. ConclusionsThese findings highlight the left lateral OFC as a structural key hub in adolescent males with ASD, linking left lateral OFC-based morphological similarity to neurotransmitter systems and providing a potential neurobiological basis for targeted interventions in this population. 1. What is already known on this topicStructural brain alterations and heterogeneity in autism spectrum disorder (ASD) are well established, but little is known about how individual brain networks relate to neurochemical systems that may guide treatment targets. 2. What this study addsThis study adds to existing knowledge by identifying the left lateral orbitofrontal cortex (OFC) as a disrupted structural hub in adolescent males with ASD and demonstrating its morphological similarity alterations are linked to GABAa, 5-HT1a, and -opioid receptor systems. 3. How this study might affect research, practice or policyBy establishing spatial correspondence between left lateral OFC morphological similarity and GABAa, 5-HT1a, and -opioid receptor systems, this work may provide potential neurobiological markers and targets for circuit-based interventions in adolescent males with ASD.

Rare pathogenic variants in many genes contribute to neurodevelopmental disorders (NDDs), including intellectual disability and/or global developmental delay (ID), autism spectrum disorder (ASD), epilepsy (EP), and cerebral palsy (CP). These conditions frequently co-occur and share genetic etiologies, yet the broader phenotypic eYects and the extent of shared versus distinct genetic influences remain unclear. Here, we adopt a cross-disorder framework to examine NDD genes across four diagnostic categories, characterize gene-associated phenotypic profiles, and identify convergent pathways that help refine how pathogenic variants in these genes shapes clinical outcomes. Using a discovery cohort of 8,973 probands with disease-causing variants in 263 NDD genes, we performed phenotype-based gene clustering and identified six distinct gene clusters. These clusters reveal structured patterns of genetic overlap, showing that subsets of NDD genes preferentially contribute to specific disorder combinations of ID, ASD, EP, and CP. The largest gene cluster was characterized by ID, whereas the other five included one enriched for ASD and ID, two for EP and ID and two for CP and ID, each with significantly diYering frequencies. In an independent validation cohort of 19,704 probands, five of the six clusters were replicated. Gene Ontology enrichment analyses revealed distinct biological processes in each cluster, suggesting that coherent molecular mechanisms underlie the diYering NDD diagnostic profiles. Together these findings demonstrate that NDD genes fall into coherent clusters that consistently map onto characteristic phenotype profiles, providing a framework to inform future therapeutic strategies and support early prognostication for individuals with pathogenic variants in NDD genes.

Externalising and internalising symptoms span multiple psychiatric diagnoses. Although similar measures assess these traits in autistic and non-autistic populations, it remains unclear whether their polygenic influences and biological mechanisms align. This study compared genetic contributions to these symptoms in autistic individuals (SPARK, N=3,486) and the general population (ABCD, N=4,637; external datasets: Neff=523,150 externalising; Neff=132,260 internalising). Regression models tested associations between polygenic scores, demographics, and symptom outcomes. Genetic correlations were computed with 12 global and 2,159 regional brain phenotypes, and with 461 cell types across 31 superclusters. In both cohorts, higher symptoms correlated with lower maternal education, lower household income and polygenic scores for depression. The strongest associations were observed for externalising symptoms in the general population, showing negative correlations with cortical expansion and enrichment in hypothalamic and histaminergic neurons. These findings suggest shared genetic architectures but different neurobiological correlates of externalising and internalising symptoms across autism and the general population.

Autism spectrum disorder (ASD) is increasingly conceptualized as a disorder of large-scale functional brain network organization rather than isolated regional abnormalities. Graph-theoretical analysis provides a principled framework for characterizing such distributed network reconfiguration. Here, we investigated global, nodal, and system-level functional network topology in ASD using a large, multi-site resting-state fMRI dataset. Resting-state fMRI data from 996 participants (428 ASD, 568 healthy controls) were obtained from the ABIDE I and II data repositories. Whole-brain weighted resting state functional networks were constructed using Pearson correlation. To improve robustness and reduce threshold-selection bias, graph-theoretical metrics were computed across a range of network sparsity thresholds and summarized using an area-under-the-curve (AUC) approach. At the global level, ASD was associated with reduced assortativity, and local efficiency, along with altered normalized characteristic path length ({lambda}), indicating local information processing and subtle deviations in network integration relative to an optimal small-world topology. Nodal analyses revealed non-random, region-specific alterations predominantly affecting higher-order associative systems. Increased nodal centrality and hub-like properties were observed in frontal and parietal regions within the frontoparietal control and dorsal attention networks, whereas reduced nodal efficiency and centrality were primarily localized to limbic and anterior temporal regions, including the temporal pole. System-level analyses, controlling for age, sex, and acquisition site, further demonstrated network-specific topological reorganization across multiple functional systems. Clinical correlation analyses identified modest but significant associations between nodal topology and core ASD symptom severity, particularly within default mode, limbic, and attention networks. Together, these findings indicate that ASD is characterized by subtle yet reproducible multi-scale reorganization of functional brain network topology, supporting a systems-level account of ASD neurobiology and highlighting the clinical relevance of large-scale network architecture.

BackgroundAutism spectrum disorder (ASD) is frequently associated with speech and language difficulties, yet empirical data from Central Asian countries remain scarce. This study examined the association between a diagnosis of childhood autism (ICD-10: F84.0) and the presence of speech development difficulties in a clinical sample from Tajikistan MethodA retrospective cross-sectional study was conducted using clinical records of 85 patients (36 with F84.0; 49 with other psychiatric diagnoses) at the Insight Mental Health Center in Dushanbe, Tajikistan (December 2025-January 2026). Speech difficulties were identified through systematic review of clinical notes. Between-group comparisons were performed using Pearsons {chi}2 test, odds ratios (OR), relative risk (RR), and effect size measures ({varphi} coefficient, Cohens h). ResultsSpeech difficulties were present in 72.2% of the autism group versus 36.7% of the comparison group. The association was statistically significant ({chi}2 = 10.47, p <.01). Children with autism had substantially higher odds of speech difficulties (OR = 4.48, 95% CI [1.76, 11.38]), with a large effect size (Cohens h = 0.73). ConclusionsAutism diagnosis was significantly associated with elevated rates of speech difficulties in this Tajik clinical sample. Practical implicationsThese findings support the systematic inclusion of speech-language assessment and intervention within autism care protocols, particularly in Central Asian healthcare settings where such integration remains limited. HighlightsO_LISpeech difficulties were identified in 72.2% of children with autism (F84.0) in a Tajik clinical sample. C_LIO_LIChildren with autism were 4.5 times more likely to present with speech difficulties than those with other diagnoses (OR = 4.48, 95% CI [1.76, 11.38]). C_LIO_LIThe most prevalent speech pattern was complete absence of expressive speech (nonverbal presentation). C_LIO_LIFindings support the integration of speech-language assessment into standard autism care protocols in Central Asia. C_LIO_LIThis is one of the first empirical reports on autism and speech profiles from Tajikistan. C_LI

Functional brain networks are altered in Autism Spectrum Disorder (ASD), with differences in thalamocortical connectivity detectable as early as infancy. ASD shows distinct sex differences, not only in diagnostic rates, but also in brain and behavioral manifestations of the condition. Although common variants account for much of the genetic liability for ASD, little is known about the impact of ASD-associated genetic variation on functional brain connectivity and behavioral outcomes in early life or how this may differ between males and females. Here, we utilize functional MRI (fMRI), genetic, and behavioral data from the Developing Human Connectome Project (dHCP) to investigate sex differences in the association between ASD polygenic scores (PGS), thalamocortical functional connectivity (37-44 weeks postmenstrual age), and behavioral outcomes (18 months) in European term-born infants. We show that across the full sample, higher ASD PGS is associated with weaker thalamic connectivity with posterior parietal cortex, as well as greater ASD-related and ADHD symptoms and slower motor development. Sex differences in the relationship between ASD PGS and thalamic connectivity largely encompassed sensorimotor, posterior parietal, temporal, and insular cortices. Further, in female infants, thalamic connectivity patterns associated with greater genetic liability for ASD were related to poorer motor development. These findings suggest genetic predisposition for ASD shapes early thalamocortical functional connectivity in a sex-specific manner and negatively impacts behavioral development in early toddlerhood.

Sleep problems and sensory over-responsivity (SOR) are common, co-occurring, and early-emerging features of Autism Spectrum Disorder (ASD). Yet, the early neural mechanisms underlying this relationship remain unclear. Here, we used resting-state fMRI data from the Infant Brain Imaging Study (IBIS) to examine how brain connectivity at 6 months may relate to parent-reported measures of sleep-onset problems and SOR in infants at varying familial likelihood for ASD. The right anterior insula was used in seed-based analyses to investigate Salience Network (SN) connectivity to cortical and cerebellar regions of interest previously implicated in sleep disruption, sensory processing challenges, and ASD. Infants at high (HL) and low (LL) likelihood for ASD displayed divergent patterns of SN connectivity with sensorimotor cortex, as well as cerebellar regions involved in sensorimotor processing and higher-order functions. Furthermore, stronger SN connectivity with sensorimotor cortices and cerebellar regions was associated with worse sleep-onset problems and SOR in HL infants. In contrast, stronger SN-cerebellar connectivity was related to fewer sleep-onset problems and SOR in LL infants. Our findings indicate that altered SN connectivity may result in over-attribution of attention to sensory stimuli and highlight aberrant sensory prediction learning, which may underlie worse sleep problems and higher SOR in HL infants.

Attention Deficit Hyperactivity Disorder (ADHD) affects 5-7% of children worldwide, yet diagnosis continues to rely on clinical-behavioral assessments. The theta/beta ratio (TBR) derived from electroencephalography (EEG) has long been proposed as a complementary neurobiological marker of ADHD, based on reports of elevated TBR in affected children. However, accumulating evidence has raised concerns about the robustness and generalisability of these findings, pointing to a strong sensitivity to methodological choices. Here, we used multiverse analyses to systematically quantify how researcher degrees of freedom shape conclusions about associations between TBR and ADHD. Across two large, independent datasets (Healthy Brain Network: N=1,499; validation sample: N=381), we evaluated 576 of theoretically plausible analytical specifications, varying recording conditions, reference scheme, frequency band definitions, treatment of aperiodic (1/f) activity, regions of interest, sample inclusion criteria and covariate specifications. Across the multiverse, we found that group differences in TBR were highly contingent on analytical choices, with no evidence for robust main effects of diagnosis, indicating no reliable differences between healthy controls, ADHD-inattentive, and ADHD-combined subtypes. Instead, significant effects emerged primarily as interactions with age and individual alpha frequency (IAF), particularly when TBR was derived from aperiodic-uncorrected power or from the aperiodic signal itself. These findings suggest that previously reported TBR effects are driven largely by variations in the 1/f-slope and IAF rather than reflecting genuine differences in oscillatory activity. These interaction patterns replicated across both independent samples and were observed using both categorical and dimensional definitions of ADHD. Together, these findings indicate that previously reported TBR effects are largely driven by variability in aperiodic activity and IAF rather than stable differences in oscillatory theta-beta dynamics. Our results challenge the interpretation of TBR as a reliable standalone biomarker for ADHD and underscore the importance of multiverse approaches for evaluating candidate neurobiological markers in heterogeneous clinical populations.

Very preterm infants (<30 weeks gestation) are at elevated risk for neurodevelopmental and social-behavioral challenges. DNA methylation (DNAm) may provide a biological link between preterm birth and later behavioral outcomes. We examined associations between DNAm profiles at neonatal intensive care unit (NICU) discharge and at age 5 with Social Responsiveness Scale (SRS) scores which measure social communication, social interaction, and repetitive behaviors at age 5, including sex-specific effects, in the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study. Epigenome-wide buccal DNAm was profiled at NICU discharge (n=218) and at 5 years (n=188). We identified 38 neonatal and 6 age-5 CpG sites associated with SRS scores (all q<0.05) using epigenome-wide association studies (EWAS) at each time point. Several CpGs mapped to genes involved in neurodevelopment including TCF4, KLC4, CAP2, PTDSS1, ADAM12, SENP1, CHN2, SH3D19, and ITGA1, with sex-specific effects observed for CpGs in CAMTA1 and GABBR1. Enriched pathways included neurodevelopment, cytoskeletal regulation, stress-response, and metabolic processes. DNAm patterns during early life, particularly the neonatal period, were associated with social-behavioral development in very preterm children. Findings in key genes such as TCF4 and CAMTA1 highlight potential epigenetic mechanisms linking early-life biology to later behavioral challenges.

Low-frequency variants (LFVs), defined by minor allele frequencies (MAF) of 1-5%, occupy the gap between common and rare variants in both frequency and effect size. The conventional genome-wide association study (GWAS) significance threshold (5x10-) is overly conservative for LFVs, which account for more than 25% of variants in GWAS. This limitation may obscure meaningful associations in highly heritable yet genetically complex disorders such as autism spectrum disorder (ASD). We hypothesize that the scarcity of significant LFVs in ASD GWAS reflects statistical constraints rather than a true lack of association. To address this, we derived a MAF-specific genome-wide significance threshold using linkage disequilibrium-informed simulations applied to ASD GWAS summary statistics, identifying 2.03x10- as optimal. Applying this threshold revealed three novel LFVs mapping to zinc finger proteins (ZNF420, ZNF781) and known ASD-related genes (KMT2E, PRKDC, MCM4). Enrichment analyses suggested their function in nervous system development and gene regulation. Our findings highlight the contribution of LFVs to ASD risk and underscore the importance of frequency-aware association strategies.

Autism spectrum disorder (ASD; MIM 209850) is reported to vary globally from 0.01% in East Asian populations to 4.36% in certain Australian cohorts. Despite high heritability estimates (61-94%), the genetic architecture underlying ASD susceptibility remains poorly characterized across diverse populations, as most genomic studies have initially focused on individuals of European ancestry. To investigate ancestry-specific genetic contributions to ASD, we analyzed whole-genome sequencing data from three independent ASD cohorts. We identified admixed ASD probands (n = 1 033) and ancestry-matched controls (n = 1 033) and performed admixture mapping (AM). AM using five continental reference populations (European, African, East Asian, South Asian, and Native American) identified five ancestry-specific ASD-susceptibility loci, including one African-related locus at 1p21.2 near S1PR1 and four Native American-associated loci at chromosome 11q13.4. Three of these latter loci were contiguous and encompassed genes previously implicated in ASD, notably SHANK2 and DHCR7, with fine-mapping identifying a significantly associated variant between the two genes (rs77695321; P = 1.52 x 10-). The fourth Native American-associated signal at 11q13.4 overlapped the folate receptor genes FOLR1 and FOLR3, with fine-mapping identifying a genome-wide significant variant (rs7950807; P = 5.21 x 10-). A secondary admixture mapping analysis restricted to Latin American individuals, incorporating 6 487 Brazilian controls, identified 16 additional ancestry-specific loci across seven genomic regions.

BackgroundThe present study examines the link between DNA methylation at the nerve growth factor-induced protein A (NGFI-A) binding domain of the NR3C1 1F promoter and later cognitive functions in children from families living in disadvantaged psychosocial conditions. MethodsParticipants were 132 children who took part in a Swiss Parents as Teachers (PAT) randomized controlled trial (72 in the intervention group, 60 in the control group). DNA methylation was quantified from saliva samples collected at age three using sodium bisulfite next-generation sequencing (NGS). Cognitive functions were assessed at age five using the SON-R 2.5-7 Intelligence Test. Results(a) DNA methylation at age three predicted lower IQ at age five through increased concentration problems; (b) participation in the three-year PAT program predicted lower methylation levels at the end of the intervention; and (c) early life stressors predicted lower IQ through increased methylation and concentration problems with descriptively stronger effects in the control group. ConclusionsThese findings demonstrate a link between early DNA methylation at the NGFI-A binding site of the NR3C1 1F promoter and later cognitive functions in children and highlight the role of early life stressors and the PAT intervention in shaping these associations.

BackgroundAdolescence and early adulthood are periods of increased mortality risk, and young people with neurodisability may be particularly vulnerable, yet evidence on mortality during the transition from paediatric to adult services is limited. ObjectivesTo estimate all-cause and cause-specific mortality risk from ages 11 to 22 years in young people with and without neurodisability in England. MethodsWe used the Education and Child Health Insights from Linked Data (ECHILD) database to follow pupils aged 11 in 2008-15 from the start of secondary school to age 22. Neurodisability was identified from education and hospital records. Gender-specific cumulative mortality risk and relative differences, overall and by neurodisability subtype, were estimated using Kaplan-Meier curves and Cox proportional hazards models. We repeated analyses for deaths due to medical or injury-related causes. ResultsAmong 3,601,180 young people, 143,864 (4.0%) had neurodisability. By age 22, 5,565 (0.15%) had died; 24% of whom had neurodisability. Among females, cumulative mortality risk was 1.6% (95% Confidence Interval [CI] 1.4-1.8%) in those with neurodisability versus 0.14% (95% CI 0.13-0.15%) in peers (Hazard Ratio [HR] 13.9, 95% CI 12.6-15.4). Among males, cumulative risk was 1.3% (95% CI 1.2-1.4%) in those with neurodisability versus 0.28% (95% CI 0.27-0.29%) in peers (HR 5.3, 95% CI 4.9-5.8). Among young people with neurodisability, most deaths were due to medical causes, with cumulative risks of 1.5% (95% CI 1.3-1.6%; HR 25.9, 95% CI 23.0-29.1) in females and 1.1% (95% CI 0.96-1.2%; HR 14.7, 95% CI 13.3-16.3) in males. Mortality risk was highest in those with cerebral palsy, developmental delay, epilepsy, congenital anomalies, and learning disability, and lowest among autistic young people. ConclusionsYoung people with neurodisability, particularly females, face substantially elevated mortality risk, largely from medical causes. Variation by neurodisability subtype and gender highlights the need for tailored care during transition to adulthood. SynopsisStudy question: What are the all-cause and cause-specific mortality risks among young people aged 11 to 22 years with neurodisability compared with their peers in England? Whats already known: Young people with neurodisability face increased mortality risk, but evidence on risk during the transition from paediatric to adult services is limited. What this study adds: In a national cohort of 3.6 million pupils followed from age 11 to 22, 4% had neurodisability. These young people had substantially higher mortality than peers, particularly females, with most deaths due to medical causes. Mortality risk varied by neurodisability subtype. These findings quantify the magnitude of excess mortality in young people with neurodisability and highlight the need for targeted support during the transition to adulthood.

CTNNB1 syndrome is a rare neurodevelopmental disorder caused by pathogenic variants in the CTNNB1 gene. Although its core clinical manifestations have been increasingly recognised, longitudinal data on cognitive, behavioural and motor trajectories remain limited, and the craniofacial phenotype has not previously been quantitatively characterised. This study provides longitudinal evidence on the cognitive, clinical and psychological profile of individuals with CTNNB1 syndrome, together with a detailed three-dimensional morphometric analysis of facial morphology. Cognitive, clinical, psychological and neuropsychological data were collected at two time points (T0 and T1), separated by a one-year interval, using a comprehensive and standardised assessment protocol. Longitudinal analyses indicated stability across most domains, with no evidence of systematic regression. A significant improvement in gross motor functioning was observed, particularly among younger participants. Linear mixed-effects models showed that age moderated developmental change, with younger individuals exhibiting greater gains over time in gross motor skills and adaptive behaviour compared to older participants. Three-dimensional facial morphometric analyses revealed a distinctive and statistically significant craniofacial pattern associated with CTNNB1 syndrome, independent of age and facial size. This phenotype was characterised by midfacial narrowing, reduced midface projection and mandibular retrusion. Importantly, facial shape variation was significantly associated with externalising behavioural problems and clinically relevant behavioural difficulties, suggesting a link between craniofacial morphology and behavioural severity. This study represents the first integrated longitudinal characterisation of CTNNB1 syndrome combining neurodevelopmental follow-up with quantitative craniofacial phenotyping. The findings indicate slow but progressive improvement in specific clinical domains during childhood and adolescence, alongside relative stability in global adaptive functioning, and highlight three-dimensional facial morphology as a sensitive structural biomarker for phenotypic stratification and clinical monitoring in CTNNB1 syndrome. Lay summaryThis study is the first to describe how children with CTNNB1 syndrome, a rare genetic condition that leads to global developmental delays, develop over time. We also performed advanced facial analysis to look for common facial features among patients.