Autism Research

RationaleNeurodevelopmental disorders (NDDs) are characterised by significant challenges in communication, social interaction, and adaptive function, often impacting quality of life. Previous studies support genetic influences on the communication abilities of individuals with NDD, but were either limited to single genetic conditions or to small cohorts with a limited selection of communication measures. MethodsWe analysed caregiver-reported communication abilities in 79,518 individuals with NDD from the Simons Searchlight and SPARK registries: 4,439 with a CNV-based or monogenic NDD and 75,079 with autism spectrum disorder (ASD) without a known genetic cause (idiopathic ASD) as controls. For analysis, we a priori selected 10 communication-related measures based on their availability in the study cohorts, coverage of distinct communication aspects, and their frequent use in neurodevelopmental phenotyping, yielding 177,328 data points across all study cohorts. The individuals in the Searchlight registry were divided into a Discovery cohort (the 15 most prevalent genetic NDD conditions) and a Confirmation cohort (all other genetic NDD conditions). A second Confirmation cohort was generated using all individuals with genetic ASD forms from the SPARK registry. We then tested each of the three case cohorts and each genetic condition represented in the Discovery cohort against the ASD control cohort. Developmental trajectories were assessed through testing of participants grouped by age at evaluation. ResultsMeasure-level analyses demonstrated significant associations between genetic status and communication abilities, differences in communication abilities between classes of genetic variants (monogenic vs. CNV-based NDDs), and variability between specific genetic NDD conditions. CNV-based NDDs showed milder communication impairment, outperforming idiopathic ASD controls in 9/10 communication measures, whereas monogenic NDD conditions had more pervasive impairments, especially in verbal communication. Although impaired in verbal communication, five monogenic NDD conditions showed at least suggestive strengths in nonverbal and social communication relative to idiopathic ASD controls (CSNK2A1, CTNNB1, SETBP1, MED13L, and PPP2R5D), specifically in using gestures. Developmental trajectory analyses revealed STXBP1 as the gene group at highest risk of developmental stagnation in communication abilities. ConclusionsThese findings underscore the potential of precision speech-language pathology (SLP) approaches tailored to the specific verbal and nonverbal communication strengths and weaknesses of genetic groups. We also provide evidence for measurable improvements and declines in communication abilities with age at the group level, highlighting the need for developmentally informed care. By integrating genetic insights into clinical practice, precision SLP approaches may enhance communication outcomes and developmental progress and improve quality of life for individuals with genetic NDDs.

PurposeSeveral clinical studies have shown correlations between certain physiological measurements and an autism spectrum disorder (ASD) diagnosis. Such findings, however, have generally not resulted in tangible progress towards practical translation. In fact, most studies have been retrospective in nature and compare biomarker profiles in children with an ASD diagnosis to those who are typically developing. A clinically meaningful test, however, requires an ASD diagnostic center to distinguish children from those with a developmental disorder pre-diagnosis. MethodsThis paper presents, for the first time, a double-blind case/control trial design in which metabolic profiles, collected at two developmental pediatric clinics, were collected from children on a diagnostic waitlist for the purpose of developing a blood-based test for ASD. Besides obtaining blood samples, the children underwent gold-standard clinical evaluations, including the Autism Diagnostic Observation Schedule (ADOS), Mullens Scale of Early Learning (MSEL), and Vineland Adaptive Behavior Scale (VABS). The analysis, together with a complete medical history and physical exam, allowed to confirm or rule-out suspected ASD using DSM-V criteria. The study was based on a cohort of 140 children between the ages 18-60 months, that were referred to a developmental pediatrician because of concerns in their development. Results114 of these children received an ASD diagnosis, while 26 were diagnosed with non-ASD related developmental delays. Based on the measured metabolites, artificial intelligence-based classification algorithms allowed for an over 80% accuracy in predicting whether a sample came from a child diagnosed with ASD or not. ConclusionWhile these results need to be replicated in a larger study, especially involving more children with non-ASD related developmental delays, this is the first work using physiological measurements, coupled with AI, to support ASD diagnoses in a clinically relevant setting.

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.

Typically-developing children progress through three distinct language-comprehension phenotypes. 1) The Command Phenotype, emerging by age 2, is characterized by understanding single words and simple commands. 2) The Modifier Phenotype, observed around age 3, is characterized by understanding adjective-noun combinations. 3) The Syntactic Phenotype, reached by age 4, is characterized by understanding stories and complex syntactic structures. This study examined language-comprehension trajectories in autistic children using parent-submitted longitudinal assessments from 6,736 participants, with a mean observation period of 2.2 {+/-} 1.3 years, spanning ages 1.5-22 years. Autistic children advanced through the same three phenotypes as neurotypical children but showed systematic differences. Increasing autism severity both reduced the likelihood of attaining higher-level phenotypes and lengthened the time required to reach them. The Command Phenotype was retained by 11%, 19%, and 39% of individuals with mild, moderate, and severe autism. Among individuals who advanced, median ages for acquiring the Modifier Phenotype were 3.7, 4.6, and 5.7 years for those with mild, moderate, and severe autism. For the Syntactic Phenotype, median ages were 4.8, 5.9, and 6.5 years across the same groups. These findings provide the first large-scale quantification of language-comprehension trajectories in autism and underscore the importance of early intervention.

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.

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.

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

BackgroundThe influence of genetic and environmental factors, especially during early development, is critical in the pathogenesis of autism. Maternal autoantibodies that recognize specific fetal brain proteins can be strong predictors of autism risk. These antibodies cross the placenta and bind to their target antigens, which play critical roles in neurodevelopment, thereby increasing autism risk. This etiologically defined subtype is now referred to as Maternal Autoantibody-Related Autism (MARA). The newly developed MAR-AutismTM test is an indirect multi-ELISA assay designed to detect specific combinations of these maternal antibodies, which strongly predicts increased autism risk. ObjectiveTranslation of the indirect ELISA assays for the eight relevant antibodies (LDH-A, LDH-B, GDA, STIP1, CRMP1, CRMP2, NSE and YBOX) from an academic laboratory to a clinical development laboratory for optimization and determination of the analytical performance of the individual antibody assays. MethodsFeasibility assays were transferred from the academic laboratory and their performance confirmed prior to optimization of all steps from target protein production to preliminary threshold determination. Validation to rigorous standards was conducted. The ELISAs are qualitative assays using an internal continuous response and a cutoff to define positivity and negativity for each analyte. Analytical performance metrics of linearity, sensitivity, specificity, precision, and stability were determined by standard testing methodologies. ResultsThe optimized ELISAs all performed at acceptable standards for analytical performance. All of the assays except one were demonstrated to be linear upon dilution with buffer and with non-reactive plasma, however, recovery was overestimated with buffer diluent. The precision profile results demonstrated that the Lower Limit of Quantification (LOQ) was greater than the Limit of Detection (LOD) and below the preliminary thresholds determined from a general population cohort distribution. Precision studies showed coefficients of variation less than 15% with two minor exceptions. Common interfering substances, apart from whole human IgG, did not affect assay performance. The microtiter assay plates were stable for at least 6 months without significant drift. ConclusionOverall, the individual antibody assays demonstrated high sensitivity, specificity, and robustness sufficient to enable extension to clinical validation. These assays enable evaluation of specific antibody combinations that were previously reported to strongly and specifically correlate with autism risk, particularly in settings of suspected diagnosis or in families with an older sibling with a confirmed autism diagnosis.

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.

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.

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.

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.

Autism shows a consistent sex bias, yet how sex shapes de novo variant (DNV) risk across coding and noncoding sequence remains unclear. We analyzed DNVs in 41,367 parent-child sequenced trios from three autism family-based cohorts and compared DNV characteristics and enrichment patterns in males and females. Importantly, these trios consisted of some trios with individuals with autism and some without autism. We developed a new sex-aware DNV caller and performed intensive, feature-based investigation of each candidate DNV to produce a high-confidence callset. We identified enrichment of missense and loss-of-function (LOF) DNVs both overall and within known autism-related genes (i.e., SFARI genes). Gene-specific enrichment analyses revealed twelve genes that were exome-wide significant and specific to males, for significance, including FOXP1, SMAD6, AUTS2, CCDC168, PIEZO1, EML6, ZNF84, IGSF23, OTOG, SLC6A1, GIGYF1, and FREM3 and four genes that were specific to females, for significance, including TAOK1, MECP2, DDX3X, and TBL1XR1 within a variant class. Direct comparisons of DNVs in males and females revealed GABBR2 as the only gene trending toward enrichment in the direct males with autism comparison to females with autism. Finally, we analyzed promoters and identified a single significant promoter region (p = 3.8x10-13), associated with the WDR74 gene, with the signal driven by DNVs observed in males with autism. Surprisingly, the noncoding RNA gene RNU2-2 lies within this significant WDR74 promoter and accounted for most of the DNVs in the region. RNU2-2 DNVs were present in 0.2% of males with autism, and several are predicted to potentially alter RNA folding. We also observed RNU2-2 DNVs in 0.2% of females with autism, including two DNVs that were recurrent (i.e., shared) with unrelated, affected males. Notably, RNU2-2 DNVs were detected in 0.1% of unaffected males and were not observed in unaffected females. Together, these results suggest that although RNU2-2 does not show a sex bias, it contributes to autism risk, which is intriguing due to a prior study implicating RNU2-2 in a severe neurodevelopmental disorder.

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.

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.

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.