Molecular Autism

Abstract Background & Aims: Language development in autism is heterogeneous and strongly predicts later functioning. The balance between receptive and expressive abilities and their developmental trajectories, however, remains poorly understood. While some autistic children exhibit a relative expressive advantage (ExpAdv), others show receptive advantage (RecAdv) or a balanced profile. Prior studies report inconsistent findings and are often limited by cross-sectional designs and small samples. The present study aimed to (1) describe longitudinal trajectories of receptive and expressive language in autistic and typically developing (TD) children; (2) classify children into ExpAdv, Balanced, and RecAdv profiles across early childhood; and (3) examine the stability and transitions of these profiles over time, including associated clinical features. Methods: We analyzed 1,174 longitudinal time points from 318 autistic children and 294 time points from 108 TD children (1.2-5.8 years) from the Geneva Autism Cohort. Receptive and expressive language were assessed with the Mullen Scales of Early Learning. Receptive-expressive balance was quantified as the ratio of receptive to expressive age equivalent scores, classifying children into ExpAdv, Balanced, and RecAdv profiles using adapted cut-offs. Mixed-effects models examined developmental trajectories, and Sankey diagrams visualized profile transitions. Autism features and adaptive behavior were compared across profiles. Results: Autistic children displayed lower expressive and receptive language than TD peers, with receptive abilities exceeding expressive skills in both groups. Overall, 30-35% of autistic children were classified as ExpAdv at 18-36 months, declining to ~12% by 48-54 months, while Balanced and RecAdv profiles became more prevalent with age. ExpAdv was associated with slower verbal and non-verbal developmental gains. Stability was highest for Balanced and RecAdv profiles (50-60%), whereas ExpAdv often transitioned to Balanced. Autistic children with stable ExpAdv profiles were more often female, less likely to receive early intervention, and showed weaker adaptive communication. Conclusions: Receptive-expressive language profiles in autistic children are dynamic. ExpAdv profile is more frequent in younger autistic children, less stable, and linked to slower verbal and non-verbal development and higher autism severity. Implications: ExpAdv may represent an early marker of autism associated with slower expressive and receptive language growth. Longitudinal monitoring of receptive and expressive skills is essential, as transitions toward Balanced or RecAdv profiles are associated with improved developmental outcomes. Early intervention before age three may facilitate transitions toward Balanced or RecAdv profiles, supporting more favorable language development and long-term outcomes. Keywords: autism; early childhood; longitudinal design; expressive language; receptive language; language profile; early intervention; language gap; discrepant profiles

Background: Female individuals tend to be diagnosed with autism later. One factor suggested to contribute to diagnostic timing is verbal ability, in which autistic females may show strengths relative to male peers. Social drivers of health (SDOH) predict higher verbal skills, yet access to resources may facilitate diagnosis; thus, SDOH likely contributes to diagnostic timing in complex ways. We use data from two autism cohorts with substantial representation of those assigned female at birth (AFAB) to examine interactions among assigned sex at birth (sex), verbal IQ (VIQ), and SDOH in predicting autism diagnostic timing. Methods: We used multiple linear regression to examine sex assigned at birth and VIQ as predictors of diagnostic timing in an assigned-sex-balanced research sample (N=164, AFAB: 71) and an independent clinical sample (N=641, AFAB: 177). We hypothesized VIQ would positively predict diagnostic age, particularly among AFAB. Available data in the clinical sample also permitted us to explore the contributions of SDOH and inclusion criteria to model fit in this cohort. Results: In the research sample, VIQ, but not sex, positively predicted diagnostic age. In the clinical sample, VIQ and VIQ x SDOH, but not sex, predicted diagnostic age. Fitting the same model in a subsample of the clinical cohort formed by applying exclusion criteria used in the research sample (N=484, AFAB: 110), VIQ x SDOH x Sex became significant. For AFAB, higher VIQ and lower SDOH together were associated with later diagnosis in the clinical subsample, while for AMAB the opposite was true. Conclusions: Autistic youth with strong verbal ability may experience diagnostic delays. SDOH interacts with VIQ in a complex fashion, with lower SDOH generally exacerbating the tendency for VIQ to be associated with later diagnosis across a large clinical sample. However, among autistic youth without complicating medical factors or intellectual disability, this relationship is dependent upon sex.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with symptoms spanning cognitive, social and behavioral domains and leading to lifelong challenges. Autism is heritable but specific genetic and environmental factors that shape its early neurodevelopmental trajectory remain unknown. Despite the clinical variability, neuroimaging findings from Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA)-ASD consortium identified stable and replicable patterns of cortical and subcortical differences that were consistent with those reported by an independent consortium, the Cognitive Genetics Collaborative Research Organization (COCORO) in Japan. Here we developed and evaluated a regional vulnerability index (RVI), a similarity metric that quantifies how closely a persons brain resembles the specific pattern of an individual with autism. RVI-ASD is based on combining the regional effect sizes for regional brain measurements published by the ENIGMA-ASD group with microstructural white matter integrity differences reported by COCORO. RVI-ASD showed significantly higher effect size for case-control differences relative to any individual brain measure (d=0.30 vs. d=0.01-0.21) in individuals with autism, particularly in the adolescent-to-adult sample (N=2,577; Mean age = 16.1; SD=5.0). We next calculated RVI-ASD in the baseline and follow-up (ages 10 and 12) data from normally developing participants of the ABCD study (N=4,201). We tested the longitudinal stability, heritability, genotype-by-age interaction and sensitivity of RVI-ASD to known factors and cognitive measurements. RVI-ASD were stable on the 2-year follow up (ICC=0.76-0.92); showed significant heritability (h{superscript 2}=0.55-0.83, p<10-16) but was not affected by gene-by-age interaction. RVI-ASD showed significant positive correlation with paternal age, while correlation with maternal age was non-significant. Baseline and follow-up RVI-ASD were negatively correlated with cognitive measures including total, fluid and crystallized intelligence (r=-0.09 to -0.11, p<10-6). RVI-ASD scores tracked with core autism phenotypes including poor eye contact and rigid routines (p < .01). In a sub-sample of children with symptoms of autism (N=20), we found that earlier age of symptom onset was strongly correlated with higher White Matter RVI (r = -0.61), linking early behavioral emergence to the neuroanatomical signature. Longitudinal changes in subcortical RVI-ASD are significantly correlated with change in social functioning. The RVI-ASD is a neuroimaging-based biomarker linked to stable and reproducible brain patterns in autism. RVI-ASD allows researchers to study associations with factors associated with the likelihood for autism and cognition across large and inclusive non-clinical samples, thus moving beyond simple case-control models to understand the biological pathways of autism.

Background Autism is characterized by social-communicative difficulties, with sex differences in symptom presentation. Social functioning is inherently dynamic, however, many neuroimaging studies rely on static, time-averaged approaches that obscure time-varying network interactions, potentially limiting our ability to capture the dynamic processes underlying social cognition. The fusiform gyrus (FFG), central to face and social perception, shows differences in functional connectivity in autism, yet is rarely examined dynamically or as a spatially heterogeneous structure. Here, we investigate the dynamic functional connectivity of FFG subregions in terms of their large-scale network configurations as a function of diagnosis and sex. Methods We applied micro co-activation patterns analysis (CAPs) to resting-state fMRI data from 286 autistic individuals (208:78 males:females) and 228 non-autistic individuals (146:82 males:females), aged 6-30 years, from the EU-AIMS LEAP dataset. CAPs were identified using k-means clustering with FFG as the seed, and connectopic mapping positioned each CAP along the principal connectivity gradient. We quantified CAPs occurrence and further examined dwell time, transition probabilities, and spatial extent, along with associations with social functioning. Results Six CAPs mapped onto distinct FFG subregions along a posterior-anterior axis. A significant sex-by-diagnosis interaction emerged for a default mode network (DMN)-related CAP. Non-autistic females exhibited significantly more frequent occurrences, longer dwell times and distinct transition dynamics compared to males, while no sex difference was observed in autism. The spatial extent of this CAP showed a reversal of typical sex effects. Conclusions Autism is associated with an attenuation and reversal of typical sex differences in the functional configuration and spatial extent of FFG-DMN coupling, indicating that neural signatures of social-cognitive functions are sex-specific and dynamic. These findings suggest that sex is a neurobiologically meaningful dimension of heterogeneity in autism, expressed in dynamic network organization.

Delayed onset of canonical babbling and first words is often reported in infants later diagnosed with autism spectrum disorder. Identifying the neural mechanisms underlying language acquisition in autism is therefore critical to inform early diagnosis, prognosis, and intervention strategies. In this study, we investigated two speech processing mechanisms previously identified as atypical in children and adults with autism: the neural ability to track syllables; and statistical learning, the capacity to detect speech regularities beneath surface variability. We recorded 83 longitudinal high-density EEGs from 44 infants (2.5-22.6 months) at high (HL) and low (LL) likelihood for autism and assessed their verbal outcomes at 20 months. Neural entrainment was measured at syllable and word frequencies during exposure to a multi-speaker stream of concatenated tri-syllabic words, followed by a word recognition test using ERP recording. Our findings revealed reduced tracking abilities at the syllabic level in HL infants, a measure that correlated with verbal outcomes. While HL infants did not exhibit deficits in statistical learning itself, they displayed reduced novelty orientation during the word recognition test, indicated by a reduced late ERP. By contrast, multi-talker variability temporarily disrupted word segmentation around 12 months in LL infants, but not in HL infants, potentially reflecting decreased sensitivity to human voices variability in the HL group. These results emphasize the importance of longitudinal protocols employing online, implicit measures to track the hierarchical stages of speech processing in both HL and LL infants.

Autism spectrum disorder (ASD) is frequently accompanied by sensory and motor abnormalities, including impaired balance, postural control, and spatial orientation, that are often attributed largely to altered central circuitry. Emerging evidence, however, suggests that peripheral sensory dysfunction can also shape ASD related behavioral phenotypes. Here, we tested whether loss of the ASD associated gene Cntnap2/Caspr2 alters vestibular signaling in Cntnap2-/- mice. Developmental transcriptomic analysis showed that Cntnap2 is expressed in vestibular sensory organs and increases during the first postnatal month, coincident with vestibular pathway maturation. Vestibular sensory evoked potentials revealed reduced response amplitudes and prolonged latencies in Cntnap2-/- mice, indicating impaired peripheral afferent responses to transient linear acceleration. Cntnap2-/- mice also showed delayed contact righting, reduced ocular counter roll, and increased hindlimb slips and compensatory tail excursions during balance beam walking, whereas rotational vestibulo-ocular reflex gain and phase were preserved. These vestibular and balance abnormalities were accompanied by reduced novel arm preference in the Y maze and severe impairment of Barnes maze acquisition, consistent with impaired spatial learning. Together, these findings identify Cntnap2/Caspr2 as a regulator of vestibular sensory signaling and support a model in which disrupted peripheral vestibular input, likely acting together with central effects of Cntnap2 loss, contributes to sensorimotor and spatial cognitive phenotypes relevant to ASD.

Atypical processing of emotional faces has been proposed as a characteristic of Autism Spectrum Disorder (ASD), but functional neuroimaging research has yielded inconsistent findings. Prior work is limited in generalizability due to methodological heterogeneity, imbalanced or small sample sizes, and underrepresentation of females. The present study examined functional brain activation during the Hariri Emotional Face-Matching Task (EFMT) in a large, sex-balanced sample of both typically developing and ASD participants (n=295, 8-18 years old) from the multi-site Autism Center of Excellence GENDAAR project. Using an ROI-driven approach, we targeted the right FFA, right OFA, right pSTS, and bilateral amygdala, we investigated whether ASD diagnosis was associated with atypical regional activation when viewing emotional faces, and if these differences were generalizable across sexes. Results revealed a group-by-sex interaction in the right FFA, driven by divergence of ASD males from the ASD female and typically developing participants. Generally, ASD females did not diverge greatly from typically developing populations. These findings suggest that atypical face processing is present, but meaningfully modulated by sex, underscoring the importance of sex-balanced, well-powered developmental samples in autism.

Autism spectrum disorder (ASD) is increasingly conceptualized as a condition rooted in altered prenatal neurodevelopment, yet in vivo evidence from fetal brain imaging remains limited. Using retrospective fetal MRI and surface-based morphometry, we investigated cortical development in 15 fetuses later diagnosed with ASD (77%; mean gestational age [GA] = 26.7 weeks) without major structural brain abnormalities and compared them with 60 typically developing controls (57% male; mean GA = 28.4 weeks). Fetuses later diagnosed with ASD showed significantly reduced whole-brain inner cortical plate surface area compared with controls ({beta} = -0.08 {+/-} 0.02 SE, p = 0.002, partial {superscript 2} = 0.13), corresponding to an estimated [~]7.7% reduction (predicted at GA = 28.1 weeks). Lobar mixed-effects analyses demonstrated broadly distributed reductions across all cortical lobes (FDR-corrected p = <0.001-0.024; Cohens d = -0.06 to -0.10), with modest regional heterogeneity indicating relatively greater frontal and insular involvement (groupxlobe: F = 19.31, p = 0.002, {superscript 2} = 0.08). Surface area findings remained directionally stable across sensitivity analyses, including restriction to neurodevelopmentally confirmed controls and models accounting for image quality variability, although effect sizes were attenuated after quality adjustment. Normative modeling further demonstrated subtle negative deviations from typical prenatal cortical surface area trajectories in ASD (mean Z = -0.27, p = 0.018). These findings suggest that aspects of cortical morphogenesis may diverge prenatally in individuals later diagnosed with ASD and suggest the feasibility of fetal MRI-based surface morphometry for studying early neurodevelopmental variation associated with ASD risk.

Meiotic recombination is an important means of increasing genetic diversity by generating novel haplotypes in a population. Recombination separates linked loci extremely slowly in some regions, therefore genetic variants in high linkage disequilibrium may become co-adapted. Reciprocal recombination that separates co-adapted variants may generate a deleterious de novo haplotype that contributes to disease. We developed statistical methods to detect genomic regions of recombination excess in two different family-based study designs. We identified recombination in the Simons Simplex Collection in 273 simplex families with one child with autism spectrum disorder (ASD) and at least two unaffected children, in which recombinations can be mapped to the proband and contrasted with the recombination counts in unaffected siblings; and in 1,802 families with two children, where the number of recombinations identified can be contrasted with the expectation from a reference recombination map. Both strategies revealed a tail of low p-values for loci of interest that contrasted with the rest of the distribution. Permutation and bootstrap tests did not identify genome-wide primary findings in either cohort, but the most significant three-child cohort locus of recombination excess (between cadherin genes CDH4 and CDH26) replicated in the two-child cohort (p=0.01). While this replication strategy was not defined a priori, five of the most recombination enriched bins identified candidate ASD genes (p=0.02; WWOX, ADAMTS16, INSR, ADARB2, and HS6ST1). Since the six identified loci were not identified as regions of high de novo copy number variation in the study cohort and no CNVs were detected in any of the recombinant probands in the identified regions, they represent candidates for reciprocal recombinations generating unfavourable haplotypes for these genes. This study highlights a previously unidentified source of clinical genetic variability contributing to the molecular aetiology of ASD. AUTHOR SUMMARYAutism spectrum disorder (ASD) is a constellation of neurodevelopmental disabilities characterised by deficits in social communication and repetitive patterns of behaviour. While ASD is highly heritable, its genetic basis is complex and poorly understood. While some highly penetrant types of genetic variation have been identified, most people with ASD carry a large number of variants that each contribute a small amount to their overall phenotype. In addition to mutations in individual genes, changes in the configuration of genes along a chromosome may contribute to ASD. Here, we describe a method for identifying regions where such new configurations have occurred through recombination and attempt to find regions where such changes are more common in autistic children than in their non-autistic siblings. We explore recombination as a source of genetic variation contributing to autism, which has potential to inform clinicians in providing services to autistic people and their families.

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition shaped by contributions from hundreds of genes, many of which remain poorly characterized. This largely uncharacterized genomic landscape may therefore hold critical insight into how diverse molecular disruptions converge on shared social phenotypes. Here, we investigated KIAA0232 (mouse orthologue D5Ertd579e), an uncharacterized locus lacking known functional domains, using a global null knockout mouse model. While loss of D5Ertd579e did not overtly disrupt cortical progenitor dynamics, laminar organization, or gross brain morphology, D5Ertd579e null mutants exhibited selective behavioral deficits in vocalization, sociability, and novelty preference, while anxiety- and memory-related behaviors remained preserved. These behavioral phenotypes were accompanied by attenuated long-term plasticity, despite normal basal synaptic transmission. Together, our findings indicate that D5Ertd579e loss selectively alters neurodevelopment, preferentially impacting neural systems involved in social and motivational processing while preserving hippocampal-dependent networks. We propose that D5Ertd579e functions as a regionally specific regulator of neurodevelopment, whose disruption may contribute to ASD through distinct genetic pathways. More broadly, this study underscores the importance of interrogating uncharacterized loci to refine mechanistic models of the social brain in ASD.

BackgroundAutism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) share substantial clinical and physiological overlap. While naturalistic and sensory-driven paradigms increasingly capture evoked neurophysiological responses, the intrinsic baseline physiology of these conditions remains poorly defined. We aimed to characterize resting-state autonomic arousal and oculomotor stability across the ASD-ADHD spectrum using both continuous (RDoC) and categorical (DSM-5) analytical frameworks. MethodsWe analyzed resting-state eye-tracking data from a large pediatric cohort (N = 2,640) from the Healthy Brain Network. During an unconstrained baseline, we extracted Pupil Relative Volatility (Coefficient of Variation [CV]) to index intrinsic autonomic arousal, and the Bivariate Contour Ellipse Area (BCEA) to index spatial gaze instability. Data were evaluated using continuous dimensional regressions against the Social Responsiveness Scale (SRS) and SWAN inventories, followed by 2x2 factorial ANCOVAs based on clinical diagnoses. Sensitivity analyses accounted for clinical collinearity, spatial outliers, and psychostimulant medication. ResultsDimensional models revealed that Pupil CV was significantly and uniquely associated with continuous autistic traits (q = 0.0043, joint model), exhibiting a strong statistical suppression effect when controlling for ADHD trait covariance. However, this pupillary biomarker lost significance in binary categorical models. Conversely, spatial gaze instability (BCEA) demonstrated robust categorical threshold effects; isolated ASD and ADHD diagnoses significantly impaired baseline gaze stability. Furthermore, comorbid ASD+ADHD produced a distinct, sub-additive interaction for BCEA (q = 0.005) that remained robust to extreme spatial outliers. Both physiological phenotypes were independent of active psychostimulant use. LimitationsWhile this study included a large and diverse group of children, the eye-tracking data were collected during a brief resting period -- watching a simple cross on a screen -- which may not capture how children behave in everyday, real-world situations. Because holding still for eye-tracking can be difficult, particularly for children with more severe symptoms, some data were lost; however, we statistically accounted for how much data each child contributed. Finally, while we confirmed that ADHD medication taken on the day of testing did not explain our findings, complete medication records were not available for every participant in this large observational study. ConclusionsPupillary dynamics and oculomotor stability associate with the ASD-ADHD spectrum through differing analytical patterns during resting states. Baseline autonomic volatility is more strongly captured by dimensional models of autistic trait severity, whereas baseline gaze instability is more clearly differentiated across categorical diagnostic groups, exhibiting a sub-additive interaction in comorbidity. Integrating both dimensional and categorical frameworks provides a more comprehensive understanding of these physiological variations, establishing a necessary foundation for future naturalistic and sensory-evoked research.

Although language acquisition delays are frequently observed in children with autism spectrum disorder (autism), our current understanding of the neurobiological mechanisms underlying language development in autism is sparse. Previous studies have found resting-state electroencephalography (EEG) power to be associated with language abilities in autistic children. However, longitudinal studies examining resting-state EEG phase coherence in relation to language development in preschool-aged children with autism are limited. This study aimed to characterize age- and group-related changes in whole-brain coherence in neurotypical children and in autistic children with and without language delay. Resting-state EEG and language data were collected at 2, 3, and 4 years of age. Peak phase coherence within the alpha band (6-11 Hz) was calculated at each timepoint and differences in the developmental trajectory of peak alpha coherence (PAC) were analyzed. In neurotypical children, PAC increased between 2 and 4 years of age. In contrast, PAC did not significantly change with age in children with autism. However, when examining autistic children based on language delay status, PAC increased with age in autistic children without language delay, but not in children with language delay. Exploratory analysis revealed evidence for an interaction between PAC and age, suggesting that the direction of the association between PAC and VDQ varied across age. Overall, these results support previous findings of altered oscillatory connectivity in autism and suggest that differences become apparent early in development. Importantly, phase coherence may not only differentiate diagnostic groups but also capture meaningful variability within the autism group. Future research should further investigate the use of EEG coherence as a biomarker of language development in autism.

The behavioral features of autism spectrum disorders (ASD) span multiple domains, yet the relationships among them remain incompletely characterized. Using phenotypic data from the Simons Foundation Powering Autism Research (SPARK), the largest autism cohort to date (N = 197,187), we characterized associations among motor (DCDQ), repetitive behavior (RBS-R), social-communication (SCQ), and psychopathology (CBCL) measures. Broad positive correlations were observed across all domain pairs, with the strongest effects for RBS-R sensory and obsessive/repetitive features. Covariate-adjusted {surd}{Delta}R2 analyses, controlling for age, sex, and nonverbal IQ, revealed heterogeneous but structured association profiles, with the largest unique contributions observed for CBCL thought problems, social problems, and internalizing outcomes. Principal component analysis (PCA) confirmed that these dimensions dominated a shared covariance structure. Split-half replication and out-of-sample ridge regression both demonstrated strong reproducibility of these profiles. Adjustment for anxiety/depressive symptoms attenuated many associations, particularly those involving sensory and repetitive predictors, though substantial cross-domain structure remained, revealing a reproducible behavioral fingerprint linking motor, sensory-repetitive, social-communicative, and cognitive dimensions in ASD, one that is internally consistent across analytic approaches and only partially explained by co-occurring anxiety and depression.

Abstract Background Gene dosage disorders impact cognition and psychopathology, but outcomes vary widely amongst carriers of the same variant. Recent work has sought to better predict proband outcomes using measures of corresponding traits in family members. However, family-based models have not yet been prospectively quantified across several traits in different genetic disorders, nor evaluated for the precision they afford: both crucial issues for clinical implementation. Methods In a first test case for these questions, we apply regression analyses to quantify and compare family-based prediction of 12 traits (including IQ, autism- and ADHD-related traits) in 433 individuals from families including a proband with XXY or XYY syndrome (N=93 and 58, respectively). Results The 12 traits vary substantially in their proband-family associations (0.001<|r|<0.55) - with differences emerging between XXY and XYY syndrome. Only two traits also show significant and similar proband-family associations in both aneuploidies, with the greatest concordance found for IQ. A family-based model for IQ prediction in male sex chromosome trisomies significantly reduces error vs. a group mean IQ model (F = 7.4, p = 0.006), but only in 65% of probands, and with mean error reduction of ~2 IQ points. Conclusions Family-based prediction of neuropsychiatric traits in genetic syndromes likely requires trait- and syndrome- specific models. Family models can significantly improve outcome prediction for IQ, but to variable degrees across individuals and with a small mean improvement. By mapping and quantifying these limits, our work helps draft a roadmap for refinement of family-based prediction of proband outcomes in gene dosage disorders.

Tourette syndrome (TS) is a neurodevelopmental disorder of childhood onset characterised by vocal and motor tics and is associated with cortical-striatal-thalamic-cortical circuit [CSTC] dysfunction. TS often follows a developmental time course in which tics become increasingly more controlled during adolescence. However, many individuals continue to have debilitating tics into adulthood. This indicates that there may be important differences between adults with TS for whom the clinical phenotype is more stable, and children and adolescents with the disorder who may be undergoing developmental neuroplastic changes linked to the reduction of their tics. Previous studies have used transcranial magnetic stimulation (TMS) to investigate changes in cortical motor excitability in individuals with TS, including measurement of resting motor threshold (RMT). However, the findings from these studies have been mixed, have varied between adult and child samples, and have often been based on small sample sizes. Here we report a multi-centre, mega-analytic, study in which RMT data collected from children and adults with TS at multiple research centres was pooled for analysis. Results confirmed that mean RMT was significantly increased in individuals with TS compared to neurotypical controls. However, this result can be explained by the more important findings that: (a) RMT for adults with TS did not differ from that of neurotypical adults; and (b) the rate that RMT decreases with age during childhood and adolescence is reduced in individuals with TS compared to controls. Thus, while neurotypical individuals reach an adult RMT level by ~12-13 years of age, individuals with TS are substantially delayed in doing so, and do not reach an adult RMT level until much later, at ~24 years of age. We conclude therefore that differences in measures of cortical excitability between children and adolescents with TS and chronologically age-matched neurotypical controls may likely reflect a developmental delay in the maturation of functional brain networks in individuals with TS, which may normalise with age.

Excessive screen use is associated with childhood behavioral problems, but whether associations differ between typically developing (TD) children and those with autism spectrum disorder (ASD) is unclear. Our cross-sectional study included 108 children aged 5-9 years (61 TD, 47 ASD). ASD was diagnosed using standardized clinical instruments. Measures included parent-reported screen time (excluding TV/DVD), cognitive ability (K-ABC), and behavioral problems (Vineland-II). Screen time and externalizing problems were associated in the TD group (Spearmans {rho} = 0.361, p < 0.01), but not in the ASD group. In the regression model, screen time ({beta} = 0.40, t = 2.60, p < 0.05), ASD status ({beta} = 0.70, t = 8.30, p < 0.001), and their interaction ({beta} = -0.34, t = -2.06, p < 0.05) significantly predicted externalizing problems. Considering the diversity within the autism spectrum, future studies with larger sample sizes should consider individual heterogeneity when examining the association between behavioral outcomes and screen time.

Objective: To understand if sociodemographic and neuropsychiatric characteristics of people diagnosed with autism in the United Kingdom (UK) and Sweden have changed since 2010. Design: Cross-context population-based cohort studies. Setting: UK primary care records from 2010-2023 and Swedish population-wide register linkages from 2010-2021 Participants: 24,537,039 individuals age 16 or over, registered with general practices in the UK, including 141,119 with an autism diagnosis. 9,096,874 people age 16 or over in the Swedish Total Population Register, including over 100,817 with an autism diagnosis. Main outcome measures: Annual age-standardised incidence and prevalence of adult autism diagnoses within different sociodemographic groups. Annual age-standardised proportion of adults with new autism diagnoses, lifetime autism diagnoses, and no autism diagnoses, with prior records of other neuropsychiatric conditions or medications. Results: Incident adult autism diagnoses were consistently higher in Sweden than the UK, however incidence increased rapidly in the UK after 2020. Incident diagnoses increased fastest for 16-25-year-olds and females in both nations, as well as people in White ethnic groups in the UK and people with Swedish-born parents in Sweden. For example, in the UK in 2023 the age-standardised incidence of autism diagnoses among 16-65 years olds was 11 diagnoses per 10,000 person-years (95%CI: 10.7, 11.3) in the White ethnic group and 2.2 diagnoses per 10,000 person-years (95%CI: 1.9, 2.5) in the South Asian ethnic group. Over time there has been a consistent decline in the proportion of autistic adults with a prior diagnosis of epilepsy, psychosis and intellectual disability and an increase in the proportion with a prior diagnosis of ADHD, anxiety, depression and several other mental illnesses. For example, in the UK between 2010 and 2023 the age-standardised proportions of newly diagnosed autistic adults with prior records of epilepsy decreased from 10% (95%CI: 7.6, 13) to 4% (95%CI: 3.6, 4.5), while the proportion with records of anxiety increased from 28.7% (95%CI: 24.4, 33.6) to 58.3% (95%CI: 56.6, 60.1). Mental health conditions were generally more common in females and the reduction over time in intellectual disability was greater in females than males. Conclusions: The socio-demographic and neuro-psychiatric characteristics of individuals diagnosed as autistic have changed dramatically since 2010, a phenomenon observed both in the UK and Sweden. The extent to which these changes indicate nuanced recognition of autism or broadening of diagnostic practice needs investigation.

Abstract Parental depression and early child neurodevelopment are closely interconnected, yet few population-based studies have examined both maternal and paternal depression in relation to early neurodevelopmental risk. This study aimed to examine the association between child neurodevelopmental risk and parental depression in the French national birth cohort Etude Longitudinale Francaise depuis l'Enfance (ELFE). We conducted a cross-sectional analysis of 12,953 children and their parents who participated in the 2-year follow-up. Child neurodevelopmental risk was assessed at age 2 years using the Modified Checklist for Autism in Toddlers and categorized as low, intermediate, or high risk. Parental depression was assessed using the Kessler Psychological Distress Scale and defined as maternal depression, paternal depression, or depression in at least one parent. Multivariable logistic regression models were adjusted for sociodemographic, pregnancy-related, and child characteristics. Compared with low child neurodevelopmental risk, intermediate risk was associated with higher odds of maternal depression and depression in at least one parent. High child neurodevelopmental risk was associated with substantially higher odds of maternal depression and depression in at least one parent. Associations with paternal depression were weaker and were no longer statistically significant after adjustment. These findings suggest that parental depression, particularly maternal depression, is associated with early child neurodevelopmental risk from the stage of initial developmental concerns. They support an integrated, family-centred approach combining early identification of child developmental vulnerability with attention to parental mental health.

Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) exhibit high clinical overlap, but categorical diagnostic boundaries obscure their shared, dynamic physiological vulnerabilities during real-world sensory processing. Methods: We analyzed multimodal eye-tracking synchrony in a large transdiagnostic pediatric cohort (N = 2,026) during naturalistic viewing of four distinct media paradigms. A novel 2D complex correlation framework captured gaze inter-subject correlation (ISC) magnitude and spatiotemporal phase divergence, while 1D pupil ISC measured autonomic arousal synchrony. Linear models evaluated dimensional (RDoC) and categorical (2x2 ANCOVA) diagnostic frameworks alongside rigorous medication and severity controls. Results: Dimensional models revealed a domain-general vulnerability: autistic traits independently predicted widespread reductions across gaze synchrony in all media contexts, and pupillary synchrony in narrative-driven contexts, whereas continuous ADHD traits showed minimal independent effects. In contrast, severe spatiotemporal misalignment (phase divergence) did not scale dimensionally but emerged strictly at clinical boundaries, reflecting highly idiosyncratic spatial locking in isolated ASD. Furthermore, categorical models demonstrated a robust, non-additive interaction: the clinical co-occurrence of ADHD paradoxically buffered against this severe spatiotemporal decoupling. Crucially, this protective phenotype was localized strictly to character-driven social narratives and remained highly significant after rigorously adjusting for daily stimulant medication, outlier instability, and baseline autism trait severity. Conclusions: These findings validate model-free physiological synchrony as a candidate transdiagnostic biomarker. Rather than compounding impairment, comorbid ASD and ADHD reflect competing, non-additive neurocognitive strategies that yield distinct, context-dependent visual phenotypes.

The past decade has seen tremendous progress in the identification of genes associated with complex neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia. Expression patterns of these genes in single cell data strongly implicate excitatory and inhibitory neurons; however, there are limited data on the brain regions involved - a critical question for neurobiology. Spatial transcriptomics provide an opportunity to perform systematic multiregional analyses to provide insights into this question. Here, we have generated a spatial transcriptomics dataset encompassing the diverse anatomical territories of the adult mouse brain sagittal midsection. We compare neuropsychiatric gene enrichment by applying Gene Fraction Enrichment Score (GFES), a novel statistic method that controls for differing neuronal proportions across regions. ASD-associated genes identified by exome sequencing were most enriched in the thalamus followed by the cortex. Schizophrenia genes from genome-wide association studies were also enriched in the thalamus, along with the hippocampus and cortex. These findings add to the evidence that the thalamus plays a major role in neuropsychiatric disorders whilst supporting roles for the cortex and hippocampus. The results highlight shared and distinct patterns for pleiotropic brain disorders that could elucidate common underlying mechanisms and circuitry.