Autism Research

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by core impairments in social communication as well as restricted, repetitive patterns of behavior and/or interests. Individuals with ASD, which includes about 2% of the US population, have challenges with activities of daily living and suffer from comorbid medical and mental health concerns. While aripiprazole and risperidone are indicated for use in autistic youth with interfering irritability, there are no drugs indicated for the core impairments of ASD. As such, there is a significant need for the development of new medication strategies for individuals with ASD. This first-in-human placebo-controlled, double-blind, crossover study investigated the safety (primary objective) and efficacy of oral SB-121, a combination of L. reuteri, Sephadex(R) (dextran microparticles), and maltose administered once daily for 28 days in 15 autistic participants. SB-121 was safe and well tolerated. SB-121-associated directional improvements in adaptive behavior measured by Vineland-3 and social preference as measured with eye tracking were noted. These results provide support for further clinical evaluation of SB-121 as a treatment in autistic patients.

Discovering genes involved in complex human genetic disorders is a major challenge. Many have suggested that machine learning (ML) algorithms using gene networks can be used to supplement traditional genetic association-based approaches to predict or prioritize disease genes. However, questions have been raised about the utility of ML methods for this type of task due to biases within the data, and poor real-world performance. Using autism spectrum disorder (ASD) as a test case, we sought to investigate the question: Can machine learning aid in the discovery of disease genes? We collected thirteen published ASD gene prioritization studies and evaluated their performance using known and novel high-confidence ASD genes. We also investigated their biases towards generic gene annotations, like number of association publications. We found that ML methods which do not incorporate genetics information have limited utility for prioritization of ASD risk genes. These studies perform at a comparable level to generic measures of likelihood for the involvement of genes in any condition, and do not out-perform genetic association studies. Future efforts to discover disease genes should be focused on developing and validating statistical models for genetic association, specifically for association between rare variants and disease, rather than developing complex machine learning methods using complex heterogeneous biological data with unknown reliability.

The increased awareness of autism spectrum disorders (ASD) is accompanied by burgeoning ASD research, and concerted research efforts are trying to elucidate the molecular ASD aetiology. However, much of this research is concentrated in the Global North, with recent reviews of research in Sub-Saharan Africa (SSA) highlighting the significant shortage of ASD publications from this region. The most limited focus area was molecular research with only two molecular studies ever published from SSA, both being from South Africa (SA). We examine the molecular ASD research publications from 2016 to 2021 from all African countries, with a special focus on SA. The SSA publications are compared to Brazil and India, two non-African, low-to-middle-income countries (LMICs), and to the UK and USA, two high-income countries (HICs). There were 228 publications across all regions of interest; only three publications were from SA. Brazil (n=29) and India (n=27) had almost 10 times more publications than SA. The HICs had more publications than the LMICs, with the UK (n=62) and the USA (n=74) having approximately 20 to 25 times more publications than SA, respectively. Given that SA has substantial research capacity as demonstrated by its recent research on SARS-CoV-2, we explore potential reasons for this deficit in molecular ASD publications from SA. We compare mental health research outputs, GDP per capita, research and development expenditure, and the number of psychiatrists and child psychiatrists per 100,000 people across all regions. The UK and the USA had significantly higher numbers for all these indicators, consistent with their higher publication output. Among the LMICs, SA can potentially produce more molecular ASD research, however, there are numerous barriers that need to be addressed to facilitate increased research capacity. These include cultural stigmas, challenges in accessing mental healthcare, shortages of specialists in the public sector, and the unreliability of ASD diagnostic tools across the 11 official SA languages. The unique genetic architecture of African populations presents an untapped reservoir for finding novel genetic loci associated with ASD. Therefore, addressing the disparity in molecular ASD research between the Global North and SSA is integral to global advancements in ASD research.

Postmortem investigations in autism have identified anomalies in neural cytoarchitecture across limbic, cerebellar, and neocortical networks. These anomalies include narrow cell mini-columns and variable neuron density. However, difficulty obtaining sufficient post-mortem samples has often prevented investigations from converging on reproducible measures. Recent advances in processing magnetic resonance diffusion weighted images (DWI) make in vivo characterization of neuronal cytoarchitecture a potential alternative to post-mortem studies. Using extensive DWI data from the Adolescent Brain Cognitive Developmentsm (ABCD(R)) study 142 individuals with an Autism diagnosis were compared with 8971 controls using a restriction spectrum imaging (RSI) framework that characterized total neurite density (TND), its component restricted normalized directional diffusion (RND), and restricted normalized isotropic diffusion (RNI). A significant decrease in TND was observed in Autism in the right cerebellar cortex ({beta}=-0.005, SE =0.0015, p=0.0267), with significant decreases in RNI and significant increases in RND found diffusely throughout posterior and anterior aspects of the brain, respectively. Furthermore, these regions remained significant in post-hoc analysis when the ASD sample was compared against a subset of 1404 individuals with other psychiatric conditions (pulled from the original 8971). These findings highlight the importance of characterizing neuron cytoarchitecture in Autism and the significance of their incorporation as physiological covariates in future studies. Lay abstractChildren with autism have differences in neuron structure unique from the general population and populations with attention, anxiety, and depression disorders. Brain imaging data on over 11,000 children was acquired at ages 9 and 11 years-of-age. Estimates of neuron density were derived from brain imaging data using recently validated techniques and comparative groups were composed using parent reported diagnosis of autism and other common psychiatric disorders. Consistent macro-structural changes in brain have been difficult to replicate and micro-structural changes have been historically difficult to acquire with other methodologies. We identified regional differences in the density of neuron cell bodies, neuron branching, and total neuron density in those with a reported diagnosis of ASD. Findings were consistent when compared against those with other psychiatric disorders in post-hoc analysis. These findings demonstrate the viability and importance of investigating in vivo changes to neurons in those with autism to advance our current understanding of related physiology.

BackgroundThe 40Hz auditory steady-state response (ASSR) is a measure of gamma-band neural synchrony sensitive to excitation-inhibition (E/I) balance. Disruptions to E/I balance have been implicated in autism spectrum disorder (ASD), making ASSR an efficient tool for investigating neural synchrony development in this population. Whether age-related differences in 40Hz ASSR are detectable across development in ASD remains understudied. Phelan-McDermid syndrome (PMS), a rare genetic disorder with a phenotype overlapping with autism, caused by SHANK3 disruption, provides a genetically defined model for further investigating E/I-related neural synchrony disruptions. MethodsWe examined 40Hz inter-trial phase coherence (ITPC) as an index of neural synchrony across a wide age range (2-37 years) in 127 participants from four groups: TD (n=43), ASD without intellectual disability (w/o ID; n=37), ASD with intellectual disability (w/ID; n=24), and PMS (n=23). Given the distinct age and cognitive profiles of ASD subgroups in this sample, analyses were conducted in separate models: TD vs. ASD w/o ID across all ages, and TD vs. ASD w/ID vs. PMS restricted to participants under 18. ResultsFor the first time in a cross-sectional sample spanning a large age range, we show that 40Hz ITPC increases significantly with age in TD individuals, while this developmental trajectory is absent in ASD without intellectual disability. Among children and adolescents under 18, 40Hz ITPC did not differ across TD, ASD w/ID, and PMS, and IQ did not predict ITPC in clinical groups. A post-hoc analysis revealed higher ITPC in TD males than females, with no sex differences in ASD or PMS. ConclusionsWe demonstrate that gamma-band ITPC trajectories diverge between TD and ASD, specifically in adulthood, with no such difference detectable in childhood. No significant group differences were found among TD, ASD w/ID, and PMS individuals under 18. These findings highlight the importance of age as a critical variable when measuring ASSR, and underscore the need for lifespan studies, particularly in genetically defined conditions such as PMS, to determine whether similar divergence emerges in adulthood.

Attempts to extract early biomarkers and expedite detection of Autism Spectrum Disorder (ASD) have been centered on postnatal measures of babies at familial risk. Here, we suggest that it might be possible to do these tasks already at birth relying on ultrasound and biological measurements routinely collected from pregnant mothers and fetuses during gestation and birth. We performed a gradient boosting decision tree classification analysis in parallel with statistical tests on a population of babies with typical development or later diagnosed with ASD. By focusing on minimization of the false positive rate, the cross-validated specificity of the classifier reached to 96% with a sensitivity of 41% and a positive predictive value of 77%. Extracted biomarkers included sex, maternal familial history of auto-immune diseases, maternal immunization to CMV, IgG CMV level, timing of fetal rotation on head, femoral length in the 3rd trimester, white cells in the 3rd trimester, fetal heart rate during labour, newborn feeding and newborn’s temperature difference between birth and one day after. Statistical models revealed that 38% of babies later diagnosed with ASD had significantly larger fetal cephalic perimeter than age matched neurotypical babies, suggesting an in-utero origin of the bigger brains of toddlers with ASD. Results pave the way to use pregnancy follow-up measurements to provide an early prognosis of ASD and implement pre-symptomatic behavioral interventions to attenuate efficiently ASD developmental sequels.Competing Interest StatementDr. S. Alain reported being a Scientific Expert for GSK, Shire, Sanofi, MSD, Merck, Biotest, BioMerieux and Hologic, and IP France Solstice study (Takeda). Dr. Y. Ben-Ari reported being the CEO and shareholder of BA Biomedical, a company dedicated to the use of artificial intelligence in biomedical research, and Neurochlore, a company dedicated to treat autism. He is also the president of the IBEN foundation, a non-for-profit foundation dedicated to study the early pathogenesis of brain disorders. Dr. S. Hantz reported receiving a congress fee, travel and accommodation by MSD vaccines, a congress fee from Diasorin, and a remuneration as speaker for "Expert days in virology" from Roche Diagnostics. Dr. E. Lemonnier reported being a shareholder of Neurochlore. Dr. H. Rabiei reported his salary paid by Neurochlore. No other disclosures were reported.View Full Text

BackgroundAutism Spectrum Disorder (ASD) is characterized by sensory disruptions, including auditory processing differences, which can significantly impact social, emotional, and cognitive development. This study investigates auditory brainstem development in Autistic children and adults using auditory brainstem responses (ABRs) and acoustic startle responses (ASRs), two key measures of auditory processing. We hypothesize that early hypo-responsivity in children, measured with ABRs, may lead to compensatory neural adaptations, resulting in hyper-reactivity in adulthood, measured by ASRs. MethodsThe study included 40 Autistic children, 57 non-Autistic children, 20 Autistic adults, and 21 non-Autistic adults. Participants underwent peripheral hearing screening, ABR testing at slow and fast click-rates, and ASR measurements. ABR wave and ASR latencies and amplitudes were analyzed. Statistical analyses included mixed-model ANOVAs and Spearmans correlations to examine group differences and associations with age. ResultsAutistic children exhibited increased ABR wave latencies and reduced amplitudes, indicating slower neurotransmission and reduced neural responsivity in the ascending auditory pathway. In contrast, Autistic adults showed normalized ABR latencies but increased ASR magnitude, suggesting hyper-reactivity to auditory stimuli. Age-related correlations revealed that ABR latencies increased with age in non-Autistic participants, while ASR magnitude was negatively correlated with age in non-Autistic participants. The associations were significantly different between groups. ConclusionThe findings support the hypothesis that Autistic children experience auditory brainstem hypo-responsivity, which may normalize in adulthood but lead to maladaptive hyper-reactivity. These results highlight the role of early auditory disruptions in shaping long-term sensory processing and reactivity in Autism, emphasizing the need for further research into the neural mechanisms underlying these differences.

BackgroundIndividuals with Autism Spectrum Disorder (ASD) show atypical auditory perception. The N100 event-related potential (ERP) reflects early auditory encoding, predictive coding, and sensory gain. Therefore, this study examined N100 responses to speech stimuli as a neural marker of auditory processing differences in ASD. MethodsEvent-related potentials (ERPs) were recorded using OpenBCI in 12 boys diagnosed with Level 1 ASD (requiring minimal support) and 15 typically developing (TD) peers. Participants passively listened to Romanian sentences systematically varied in pitch (normal, high, low), distance-based intensity (0.5, 1, 2 meters; 65, 59, 53 dB), and spatial presentation (binaural, left, right). N100 amplitudes and latencies were analyzed using Python and SPSS. ResultsASD group indicated significantly reduced N100 amplitudes for normal-pitch stimuli (p = .030, {superscript 2} = .175) and binaural presentation (p = .030, {superscript 2} = .175). Marginal reductions were also observed for low pitch (p = .096, {superscript 2} = .120), speech presented from a 0.5-meter distance (p = .058, {superscript 2} = .147), and unilateral conditions (ps = .066-.077, {superscript 2}s = .130-.142). No group differences emerged for N100 latency. These findings suggest attenuated early auditory responses in ASD to both typical and spatially complex speech cues. ConclusionsResults support predictive coding models proposing reduced sensory precision in ASD. The consistent amplitude attenuation, including near-significant findings, points to subtle but pervasive impairments in early auditory encoding. The use of ecologically valid speech stimuli and portable EEG underscores the translational potential of N100 as a biomarker for early identification and intervention in autism.

Sensory processing dysfunction not only affects most individuals with autism spectrum disorder (ASD), but at least 5% of children without ASD also experience dysfunctional sensory processing. Our understanding of the relationship between sensory dysfunction and resting state brain activity is still emerging. This study compared long-range resting state functional connectivity of neural oscillatory behavior in children aged 8-12 years with autism spectrum disorder (ASD; N=18), those with sensory processing dysfunction (SPD; N=18) who do not meet ASD criteria, and typically developing control participants (TDC; N=24) using magnetoencephalography (MEG). Functional connectivity analyses were performed in the alpha and beta frequency bands, which are known to be implicated in sensory information processing. Group differences in functional connectivity and associations between sensory abilities and functional connectivity were examined. Distinct patterns of functional connectivity differences between ASD and SPD groups were found only in the beta band, but not in the alpha band. In both alpha and beta bands, ASD and SPD cohorts differed from the TDC cohort. Somatosensory cortical beta-band functional connectivity was associated with tactile processing abilities, while higher-order auditory cortical alpha-band functional connectivity was associated with auditory processing abilities. These findings demonstrate distinct long-range neural synchrony alterations in SPD and ASD that are associated with sensory processing abilities. Neural synchrony measures could serve as potential sensitive biomarkers for ASD and SPD.

Cannabidiol (CBD), a non-intoxicating compound derived from the cannabis plant, has garnered increasing attention as a potential pharmacological therapeutic for autism. We conducted a randomized, double-blind, placebo-controlled, crossover trial to understand whether oral CBD oil containing terpenes can improve outcomes in autistic children. Twenty-nine children (18 male), aged 5 to 12 years (M=9.62 years, SD=2.05), diagnosed with autism spectrum disorder, completed the study. Participants received weight-based dosing of CBD oil (10 mg/kg/day) or matched placebo oil over two 12-week intervention periods (crossover), separated by an 8-week washout period. Outcome measures included the Social Responsiveness Scale-2 (SRS-2; primary outcome), PROMIS Social Relating, Anxiety, and Sleep, Developmental Behaviour Checklist-2 (DBC-2), Vineland-3, and Autism Parenting Stress Index (APSI; secondary outcomes). There was no significant effect observed for the primary outcome measure (SRS-2) for CBD oil relative to placebo oil after 12 weeks ({beta}=-11.15, SE=7.19, p=.125). Significant improvements were observed in secondary measures of social functioning, including DBC-2 Social Relating ({beta}=-2.35, SE=0.92, p(adj)=.024), as well as reduced anxiety on the DBC-2 subscale ({beta}=-3.20, SE=0.94, p(adj)=.002), and lower parental stress (APSI; {beta}=-4.63, SE=2.26, p(adj)=.044). No differences were detected on Vineland-3 adaptive functioning (ABC: {beta}=2.06, SE=2.67, p(adj)=1.000), and domain scores were not significant. Safety and tolerability data indicated that two children experienced gastrointestinal discomfort while taking CBD. Findings from this pilot trial suggest that while CBD combined with terpenes did not improve the primary outcome of social responsiveness, it may hold potential in addressing certain autism-related difficulties, particularly anxiety and social relating. Further research with larger sample sizes is needed to fully evaluate the efficacy and safety of CBD for autistic children. Lay SummaryThis pilot, exploratory study examined whether taking CBD oil could improve social outcomes for autistic children. While no significant changes were seen in overall social responsiveness, CBD led to improvements in specific social behaviours, reduced anxiety, and lowered parental stress. The treatment was generally well tolerated, though a few children experienced mild side effects. These findings suggest potential benefits of CBD for some autism-related symptoms, but larger studies are needed to confirm effectiveness.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by heterogeneity in presentation. In recent decades, ASD prevalence has risen globally, yet data from non-Western and middle-income countries, including Russia, remain scarce. Official statistics report a prevalence of 0.41 per 1000 (0.041%), far below global estimates of 32.2 per 1000 (3.2%), indicating underdiagnosis. This study provides the first population-based estimate of ASD prevalence among Russian elementary school children and examines barriers to diagnosis and treatment. The study followed a two-phase epidemiological approach. ASD identification used standardized instruments (SCQ, ADOS-2, ADI-R). The target population included all students in grades 1-3 (n = 34 847), stratified into mainstream, special education, and resource classes. ASD prevalence was estimated using Bayesian regression correcting for screening misclassification. The estimated ASD prevalence was 22.2 per 1000 children (95% CIs: 18.6-36.0), substantially exceeding what is reported based on the RF administrative data. The diagnostic phase had a 25.6% participation rate. ASD was more frequently identified in students from special education and resource classes than in general education settings. A Bayesian sensitivity analysis confirmed the robustness of prevalence estimates across plausible values for sensitivity and specificity. These findings suggest that ASD prevalence in Russia is considerably underestimated via administrative data. Systemic barriers--including limited access to diagnostic services and stigma surrounding psychiatric labels--may hinder ASD identification. Addressing these challenges is essential for improving early detection and service provision in Russia and similar contexts.

Adaptation to repetitive sensory inputs promotes efficient neural processing by attenuating responses to redundant information and reallocating resources to novel stimuli. Reduced adaptation has been proposed to contribute to atypical sensory reactivity in autism, but the physiological mechanisms underlying tactile adaptation remain poorly understood. Here, we examined short-term adaptation to repetitive vibrotactile stimulation in autistic and neurotypical adults using high-density electrophysiological recordings. Fifty participants (18-44 years; 25 autistic; 25 neurotypical), received sequences of four brief vibrations to the index fingertip while viewing silent videos. Neural responses were analyzed for an early negative deflection (N1, [~]100 milliseconds) indexing basic stimulus recognition, and a later positive deflection (P2, [~]200-300 milliseconds) indexing higher-order contextual and attentional processing. Adaptation was quantified as changes in response magnitude across the four vibrations. The N1 did not differ between groups, showing minimal change across repetitions, indicating comparable processing of basic tactile features. In contrast, the P2 was significantly larger overall in the autistic group. Across both groups, responses to the first vibration in each sequence were greater than responses to subsequent vibrations, reflecting re-sensitization following the inter-sequence interval. Autistic participants exhibited consistently amplified P2 responses to initial vibrations, suggesting heightened re-sensitization rather than impaired within-sequence adaptation. Associations between neural responses and clinical measures of autistic traits and tactile sensitivity were modest. These findings indicate that autistic adults show amplified higher-order neural responses to tactile input alongside preserved short-term adaptation. Heightened re-sensitization to repeated touch may reflect shortened refractory periods, contributing to sensory hyper-reactivity and increased perceptual load.

BackgroundAutism traits emerge between the ages of 1 and 2. It is not known if experiences which increase the likelihood of childhood autism are related to early trait emergence, or if other exposures are more important. Identifying factors linked to toddler autism traits in the general population may improve our understanding of the mechanisms underlying atypical neurodevelopment. MethodsClinical, socio-demographic, and parental information was collected at birth from 536 toddlers in London, UK (gestational age at birth, sex, maternal body mass index, age, parental education level, parental first language, parental history of neurodevelopmental disorders) and at 18 months (parent cohabiting status, two measures of social deprivation, three measures of maternal parenting style, and a measure of maternal postnatal depression). General neurodevelopment was assessed with the Bayley Scales of Infant and Toddler Development, 3rd Edition (BSID-III), and autism traits were assessed using the Quantitative Checklist for Autism in Toddlers (Q-CHAT). Multivariable models were used to identify associations between variables and Q-CHAT. A model including BSID-III was used to identify factors associated with Q-CHAT independent of general neurodevelopment. Models were also evaluated addressing variable collinearity with principal component analysis (PCA). ResultsA multivariable model explained 20% of Q-CHAT variance, with four individually significant variables (two measures of parenting style and two measures of socio-economic deprivation). After adding general neurodevelopment into the model 36% of Q-CHAT variance was explained, with three individually significant variables (two measures of parenting style and one measure of language development). After addressing variable collinearity with PCA, parenting style and social deprivation were positively correlated with Q-CHAT score via a single principal component, independently of general neurodevelopment. Neither sex nor family history of autism were associated with Q-CHAT score. LimitationsThe Q-CHAT is parent rated and is therefore a subjective opinion rather than a clinical assessment. We measured Q-CHAT at a single timepoint, and to date no participant has been followed up in later childhood, so we are focused purely on emerging traits rather than clinical autism diagnoses. ConclusionsAutism traits are common at age 18 months, and greater emergence is specifically related to exposure to early life adversity.

Previous studies have reported that some children with Autism Spectrum Disorder (ASD) below the age of 3-years-old exhibit increased extra-axial cerebrospinal fluid (EA-CSF) volumes, suggesting that transient early CSF circulation abnormalities may characterize a unique etiology in a sub-group of ASD children. Specifically, this sub-group was proposed to exhibit an EA-CSF to total brain volume (TBV) ratio >0.14. It is unknown whether such findings may correspond to an early radiological diagnosis of Benign external hydrocephalus (BEH), which is defined as an enlargement of CSF volumes within the subarachnoid space (SAS) during the first two years of life. Here we examined a retrospective clinical sample extracted from the National Autism Database of Israel. In 2020, [~]14% of ASD children in the database (n= 102) had completed clinical brain MRI scans at different ages before or after ASD diagnosis. Scans of 83 ASD children fulfilled quality control criteria and were compared to those of 53 age and sex matched typicality developing (TD) children who were referred to the same clinical center for similar clinical reasons. EA-CSF volume and total brain volume (TBV) were quantified from T2-weighted scans using manual labeling and compared across groups. The results revealed that ASD children scanned before the age of 2-years-old (i.e., before ASD diagnosis) exhibited significantly larger EA-CSF volumes when compared to controls (t(49)=2.89, p=0.006, Cohens d=0.82). No significant differences were apparent across groups at older ages. Of those scanned before the age of 2-years-old, [~]16% of the ASD children, and none of the control children, exhibited EA-CSF/TBV ratios >0.14, thereby replicating previous findings from prospective research samples. In addition, retrospective examination of the neuroradiology assessments revealed a BEH prevalence of 33% in the ASD children scanned before the age of 2-years-old, with 80% of these children exhibiting EA-CSF/TBV ratios >0.11. These findings reveal a clear relationship between quantitative EA-CSF volume analyses and qualitative BEH radiological findings, which characterize a considerable sub-group of ASD children. Accumulating evidence, therefore, suggests that BEH diagnosis in conjunction with a high EA-CSF/TBV ratio by the age of 2-years-old may be indicative of a specific ASD etiology that warrants further research and may offer unique opportunities for intervention.

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication and restricted, repetitive behaviors emerging in early childhood. Given rising diagnostic rates and substantial lifelong impacts, accurate global prevalence estimates are essential for health policy, resource planning, and early intervention. This systematic review and meta-analysis synthesized global observational evidence to estimate ASD prevalence across world regions and examine factors influencing heterogeneity. MethodsFollowing PRISMA guidelines, searches were conducted in PubMed, Scopus, Web of Science, Embase, and Google Scholar for observational and registry-based studies published from 2004-2025. Twenty-two studies met inclusion criteria. Random-effects models (REML) estimated pooled global and regional prevalence. Heterogeneity was assessed using Q, I{superscript 2}, {tau}{superscript 2}, Baujat plots, and influence diagnostics. Subgroup analyses and meta-regressions evaluated moderators including geographic region, mean age, and prevalence per 1,000. Sensitivity analyses assessed model robustness. ResultsThe pooled global prevalence of ASD was 1.8% (95% CI: 0.8-3.7%). Substantial heterogeneity existed across studies (Q p <.001; {tau} = 1.64), with prediction intervals ranging from 0.05% to 37.8%. Regional estimates ranged from 0.65% in the Middle East to 3.4% in North America, though subgroup differences were not statistically significant. Meta-regression suggested significant moderation by mean age and prevalence per 1,000 (R{superscript 2} = 59.35%), although sensitivity analyses revealed that these effects were largely driven by one influential study. Publication bias was minimal. ConclusionGlobal ASD prevalence remains around 1%-2%, consistent with contemporary epidemiological data; however, considerable heterogeneity indicates that methodological and contextual factors likely drive observed regional differences. Standardized diagnostic criteria, enhanced surveillance, and early detection systems are needed to improve global prevalence accuracy and inform public health planning.

ImportanceStereotypical motor movements (SMMs) are a form of restricted and repetitive behavior (RRB), which is a core symptom of Autism Spectrum Disorder (ASD). Current quantification of SMM severity is extremely limited, with studies relying on coarse and subjective caregiver reports or laborious manual annotation of short video recordings. ObjectiveTo demonstrate the utility of a new open-source AI algorithm that can analyze extensive video recordings of children and automatically identify segments with heterogeneous SMMs, thereby enabling their direct and objective quantification. Design, setting, and participantsThis retrospective cohort study analyzed video recordings from 319 behavioral assessments of 241 children with ASD, 1.4 to 8 years old, who participated in research at the Azrieli National Centre for Autism and Neurodevelopment Research in Israel. Behavioral assessments included cognitive, language, and autism diagnostic observation schedule, 2nd edition (ADOS-2) assessments. ExposuresEach assessment was recorded with 2-4 cameras, yielding 580 hours of video footage. We manually annotated 7,352 video segments containing heterogeneous SMMs performed by different children (21.14 hours of video). Main outcomes and measuresWe used a pose-estimation algorithm (OpenPose) to extract skeletal representations of all individuals in each video frame and trained an object-detection algorithm (YOLOv5) to identify and track the child in each movie. We then used the skeletal representation of the child to train an SMM recognition algorithm using a PoseConv3D model. We used data from 220 children for training and data from the remaining 21 children for testing. ResultsThe algorithm accurately detected 92.53% of manually annotated SMMs in our test data with 66.82% precision. Overall number and duration of algorithm identified SMMs per child were highly correlated with manually annotated number and duration of SMMs (r=0.8 and r=0.88, p<0.001 respectively). Conclusion and relevanceThese findings demonstrate the ability of the algorithm to capture a highly diverse range of SMMs and quantify them with high accuracy, enabling objective and direct estimation of SMM severity in individual children with ASD. We openly share the "ASDPose" dataset and "ASDMotion" algorithm for further use by the research community. Key PointsO_ST_ABSQuestionC_ST_ABSIs it possible to train a deep learning algorithm to accurately identify and quantify stereotypical motor movements (SMMs) in video recordings of children with autism? FindingsThe ASDMotion algorithm was trained and tested with the largest video dataset of ASD children curated to date, comprised of 319 behavioral assessment recordings from 241 ASD children. The algorithm successfully detected 92.53% of manually identified SMMs with 66.82% precision, achieving highly accurate quantification of SMMs per child that were strongly correlated (r[&ge;]0.8) with quantification by manual annotation. MeaningThis study demonstrates the utility of ASDMotion for objective and direct quantification of SMM severity in children with ASD, offering a new freely available, open-source algorithm and dataset that enable transformative basic and clinical ASD research.

Individuals diagnosed with Autism Spectrum Disorder (ASD) generally have altered responses to social reward, which the "social motivation" hypothesis posits as the primary contributor to their social deficits. Aberrant perception of rewarding faces is considered to be one of the most significant markers of this hypothesis. The orbitofrontal cortex (OFC) plays an important role in modulating reward and arousal responses to happy faces but few studies have investigated whether young autistic children with limited cognitive or language ability have altered neural and behavioral responses to reward related tasks. We therefore conducted an eye-tracking task where autistic (n = 36) and typically developing (n = 36) young children (aged 2.5-6 years) viewed the faces of happy children or of simplified faces (emoticons), combined with OFC activation measurement using functional near infrared spectroscopy (fNIRS), to compare ASD and typically developing (TD) children. Results revealed no differences between the two groups for time spent viewing happy faces although TD children spent more time looking at the eyes of real faces and at the mouths of emoticons whereas children with ASD did not. Children with ASD showed a greater pupil diameter (PD) and OFC activation compared to TD children during presentation of happy faces. Indeed, greater PD and OFC responses were predictive of greater adaptive behavior difficulties and severity of symptoms. Our results therefore demonstrate different gaze patterns and greater arousal and brain reward system responses to happy faces in young children with ASD which are incongruent with social motivation hypothesis. Availability of dataOur ethics approval does not permit public archiving of individual anonymized raw data. Those who wish to access the raw data should contact the corresponding author. Access will be granted to named individuals who adhere to the ethical procedures governing the reuse of sensitive data. They must complete a formal data sharing agreement to obtain the data. The data that support the main group different finding figures related anonymized data of this study are openly available via the Open Science Framework (OSF) Repository https://osf.io/sxkhc/?view_only=6eb51e64a9b54fce909b5ff6eacdc668 Ethics approval statementThe study was conducted in accordance with the principles of the Declaration of Helsinki. It was approved by the Local Ethics Committee (number 202165). Research Highlights[bullet] The present study examined whether altered social reward processing in ASD is caused by reduced behavioral and neural responses to rewarding stimuli. [bullet]Typically developing children showed a preference for viewing specific informative facial features (such as child eyes or emoticon mouths), children with autism did not. [bullet]Children with autism enhanced arousal (pupil dilation) and brain reward (orbitofrontal cortex) responses to happy child faces. [bullet]Altered, gaze patterns, arousal and brain reward responses were highly predictive of adaptive behavior abilities and autistic symptom severity.

BackgroundA growing body of literature suggests etiological overlap between Ehlers-Danlos syndrome (EDS)/hypermobility spectrum disorders (HSD) and some cases of autism, although this relationship is poorly delineated. In addition, immune, autonomic, and endocrine dysregulation are reported in both conditions and may be relevant to their respective etiologies.\n\nAimsTo study symptom overlap in these two comorbid spectrum conditions.\n\nMethods and ProceduresWe surveyed 702 adults aged 25+ years on a variety of EDS/HSD-related health topics, comparing individuals with EDS/HSD, autism, and unaffected controls.\n\nOutcomes and ResultsThe autism group reported similar though less severe symptomology as the EDS/HSD group, especially in areas of immune/autonomic/endocrine dysregulation, connective tissue abnormalities (i.e., skin, bruising/bleeding), and chronic pain. EDS/HSD mothers with autistic children reported more immune symptoms than EDS/HSD mothers without, suggesting the maternal immune system could play a heritable role in these conditions (p = 0.0119).\n\nConclusions and ImplicationsThese data suggest that EDS/HSD and autism share aspects of immune/autonomic/endocrine dysregulation, pain, and some tissue fragility, which is typically more severe in the former. This overlap, as well as documented comorbidity, suggests some forms of autism may be hereditary connective tissue disorders (HCTD).

The Lancet Commission on the Future of Care and Clinical Research in Autism proposed the construct of "profound autism" as a recognizable subtype of autism. Supporters argue that this classification is necessary to ensure that autistic persons with severe impairment receive appropriate research attention and policy support, whereas critics contend that the construct lacks scientific validity and may reflect social or political considerations more than biological distinction. To inform this debate, we evaluate whether the proposed "profound autism" category represents a distinct genetic phenotype using multiple molecular data types collected in a large cohort. Across genomic, transcriptomic, and regulatory analyses, we find no evidence supporting "profound autism" as a biologically distinct phenotypic group. Instead, differences emerge primarily in inferred gene regulatory networks distinguishing nonspeaking from speaking autistic children, suggesting potential regulatory mechanisms contributing to speech ability. These findings suggest that future research into severe impairment may be more productive if focused on specific traits--such as speech impairment--rather than attempting to define a distinct biological subtype within the multidimensional phenomenon of autism.

MotivationAltered auditory processing likely contributes to core social and attentional impairments in autism spectrum disorder (ASD). The auditory steady-state response (ASSR)-- a neural measure of auditory processing and cortical excitatory-inhibitory balance--has yielded mixed results in ASD. This study uses high density electroencephalography (EEG) to evaluate ASSR in ASD and unaffected siblings to clarify neural mechanisms underlying auditory deficits in autism. MethodsHigh-density 70-channel EEG was recorded in children (8-12 years, IQ >80) with ASD (n=53), typically developing (TD) peers (n=35), and unaffected biological siblings (n=26) during 500-ms binaural click trains (27- and 40-Hz) in an active oddball task. ResultsNo group differences were observed in frequency-following responses (FFR) to 27- or 40-Hz stimuli, although higher 40-Hz power was associated with older age and better behavioral performance in ASD. The broad-band response from 180-250 ms was reduced in ASD for both stimulation frequencies--particularly in the low-frequency (<8 Hz) range--and significantly correlated with IQ and age. Siblings showed intermediate broad-band responses. DiscussionWhile FFRs appeared intact in ASD, we observed reduced broad-band response in the transition period to the steady state FFR, which was specific to low (<8-Hz) frequencies--potentially reflecting reduced synchronization at timescales that correspond with slower, syllabic rhythms ([~]4-8 Hz) occurring in natural speech. Intermediate responses in first-degree relatives suggest that this is related to genetic vulnerability for ASD and highlights its clinical relevance. These findings suggest intact sensory processing in ASD alongside possible top-down auditory feedback deficits, which may serve as heritable neurophysiological markers. Lay AbstractChildren with autism may process sounds differently, which could contribute to challenges with attention and communication. Here, electroencephalography (EEG) measured how the brain responds to rapidly repeating sounds and found that, while basic sound processing was intact, children with autism showed significantly reduced low-frequency responses that may reflect difficulty tracking speech rhythm. Interestingly, unaffected siblings showed an intermediate response, suggesting this may be a heritable marker of neural differences in autism.