1. Beck KB. Trauma and Social Adversity in Autism: Considerations and Directions for Clinicians and Researchers. Pa J Posit Approaches;2024 (Sep);13(2):23-32.

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2. Bender A, Voytek B, Schaworonkow N. Resting-state alpha and mu rhythms change shape across development but lack diagnostic sensitivity for ADHD and autism. bioRxiv;2025 (Apr 5)

In the human brain, the alpha rhythm in occipital cortex and the mu rhythm in sensorimotor cortex are among the most prominent rhythms, with both rhythms functionally implicated in gating modality-specific information. Separation of these rhythms is non-trivial due to the spatial mixing of these oscillations in sensor space. Using a computationally efficient processing pipeline requiring no manual data cleaning, we isolated alpha and/or mu rhythms from electroencephalography recordings performed on 1605 children aged 5-18. Using the extracted time series for each rhythm, we characterized the waveform shape on a cycle-by-cycle basis and examined whether and how the waveform shape differs across development. We demonstrate that alpha and mu rhythms both exhibit nonsinusoidal waveform shape that changes significantly across development, in addition to the known large changes in oscillatory frequency. This dataset also provided an opportunity to assess oscillatory measures for attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). We found no differences in the resting-state features of these alpha-band rhythms for either ADHD or ASD in comparison to typically developing participants in this dataset. While waveform shape is ignored by traditional Fourier spectral analyses, these nonsinusoidal properties may be informative for building more constrained generative models for different types of alpha-band rhythms, yielding more specific insight into their generation.

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3. Benedicto-Rodríguez G, Bosch F, Juan CG, Bonomini MP, Fernández-Caballero A, Fernandez-Jover E, Ferrández-Vicente JM. Understanding Robot Gesture Perception in Children with Autism Spectrum Disorder during Human-Robot Interaction. Int J Neural Syst;2025 (Apr 16):2550026.

Social robots are increasingly being used in therapeutic contexts, especially as a complement in the therapy of children with Autism Spectrum Disorder (ASD). Because of this, the aim of this study is to understand how children with ASD perceive and interpret the gestures made by the robot Pepper versus human instructor, which can also be influenced by verbal communication. This study analyzes the impact of both conditions (verbal and nonverbal communication) and types of gestures (conversational and emotional) on gesture recognition through the study of the accuracy rate and examines the physiological responses of children with the Empatica E4 device. The results reveal that verbal communication is more accessible to children with ASD and neurotypicals (NT), with emotional gestures being more interpretable than conversational gestures. The Pepper robot was found to generate lower responses of emotional arousal compared to the human instructor in both ASD and neurotypical children. This study highlights the potential of robots like Pepper to support the communication skills of children with ASD, especially in structured and predictable nonverbal gestures. However, the findings also point to challenges, such as the need for more reliable robotic communication methods, and highlight the importance of changing interventions tailored to individual needs.

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4. Bonnycastle K, Nawaz MS, Kind PC, Cousin MA. Convergent depression of activity-dependent bulk endocytosis in rodent models of autism spectrum disorder. Mol Autism;2025 (Apr 16);16(1):26.

BACKGROUND: The key pathological mechanisms underlying autism spectrum disorder (ASD) remain relatively undetermined, potentially due to the heterogenous nature of the condition. Targeted studies of a series of monogenic ASDs have revealed postsynaptic dysfunction as a central conserved mechanism. Presynaptic dysfunction is emerging as an additional disease locus in neurodevelopmental disorders; however, it is unclear whether this dysfunction drives ASD or is an adaptation to the altered brain microenvironment. METHODS: To differentiate between these two competing scenarios, we performed a high content analysis of key stages of the synaptic vesicle lifecycle in primary neuronal cultures derived from a series of preclinical rat models of monogenic ASD. These five independent models (Nrxn1(+/-), Nlgn3(-/y), Syngap(+/-), Syngap(+/Δ-GAP), Pten(+/-)) were specifically selected to have perturbations in a diverse palette of genes that were expressed either at the pre- or post-synapse. Synaptic vesicle exocytosis and cargo trafficking were triggered via two discrete trains of activity and monitored using the genetically-encoded reporter synaptophysin-pHluorin. Activity-dependent bulk endocytosis was assessed during intense neuronal activity using the fluid phase marker tetramethylrhodamine-dextran. RESULTS: Both synaptic vesicle fusion events and cargo trafficking were unaffected in all models investigated under all stimulation protocols. However, a key convergent phenotype across neurons derived from all five models was revealed, a depression in activity-dependent bulk endocytosis. LIMITATIONS: The study is exclusively conducted in primary cultures of hippocampal neurons; therefore, the impact on neurons from other brain regions or altered brain microcircuitry was not assessed. No molecular mechanism has been identified for this depression. CONCLUSION: This suggests that depression of activity-dependent bulk endocytosis is a presynaptic homeostatic mechanism to correct for intrinsic dysfunction in ASD neurons.

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5. Brueggeman L, Pottschmidt N, Koomar T, Thomas TR, Michaelson JJ. Genomic dissection of sleep archetypes in a large autism cohort. medRxiv;2025 (Apr 6)

Poor sleep is a major concern among individuals with autism and their caregivers. To better characterize the genetic and phenotypic heterogeneity of poor sleep in autism, we recruited 5,686 families from SPARK, a nationwide genetic study of autism, who described their sleep experiences using the Children’s Sleep Health Questionnaire (CSHQ) and other self-report items. The collective experiences from this large sample allowed us to discover eight distinct archetypes of sleep in autism. Membership in some of these archetypes showed significant SNP-heritability (0.50 – 0.65, 95% confidence interval = 0.08 – 1), and polygenic estimates of educational attainment, BMI, and ADHD risk contributed extensively to the genetic signatures of these sleep archetypes. Surprisingly, polygenic estimates of general population sleep phenotypes showed sparser and more modest associations, perhaps suggesting that the genetic drivers of disordered sleep in autism may be distinct from those encountered in the general population. GWAS on archetype membership yielded no genome-wide significant loci, however, the most significant gene for the most severe archetype was the nitric oxide (NO) signaling gene NOS1AP, which was previously linked to sleep disruption in schizophrenia. Finally, the eight sleep archetypes showed specific signatures of treatment response across five major categories of sleep aid, pointing to the potential of treatment plans that are tailored to the nature of the sleep problem. These findings provide critical new insight into the comorbidities, subtypes, and genetic risk factors associated with disordered sleep in autism.

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6. Canaguier J, Mallaret G, Paraschivescu C, Barbosa S, Le Merrer J, Becker J, Glaichenhaus N, Davidovic L. Perinatal exposure to the autism-linked metabolite p-Cresol has limited impact on early development in mice but lasting effects on adult social behavior. Sci Rep;2025 (Apr 15);15(1):12934.

Environmental exposures during pregnancy are increasingly recognized as significant risk factors for the offspring health. Perinatal exposure to environmental toxins, including p-Cresol, may disrupt essential physiological processes during critical developmental windows. The perinatal period is particularly critical for neurodevelopment, making the brain particularly vulnerable to external toxins that can impair neural circuitry and increase the risk of behavioral and neuropsychiatric disorders later in life. p-Cresol, a microbial metabolite produced by the human microbiota and through the bacterial decomposition of organic matter, is also released in exhaust fumes and widely used in chemical manufacturing. Elevated levels of p-Cresol have been consistently observed in patients with autism spectrum disorders (ASD), yet, its developmental toxicity and its impact on ASD-related behaviors remain to be determined. In this study, we exposed pregnant mice (C57BL/6J) to p-Cresol via drinking water from mid-gestation, through lactation, and until weaning, mimicking potential patterns of human exposure during pregnancy and early infancy. Our findings indicated that while perinatal p-Cresol exposure did not affect gestational outcomes, postnatal growth, developmental milestones, or sensorimotor reflexes, it resulted in marked social deficits and stereotyped behaviors in adult males and females offspring-which are core behavioral phenotypes associated with ASD. These results suggest that p-Cresol exposure selectively induces ASD-like behaviors, without broadly impairing early development. Our findings emphasize the need for future epidemiological studies to quantify p-Cresol exposure during pregnancy and early childhood, and to evaluate its potential association with social behavior impairments in children. This research provides a foundation for understanding how environmental factors, such as p-Cresol, may contribute to social impairments and neurodevelopmental disorders in the broader population.

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7. Choi JW, Jang H, Kuiper JR, Bennett DH, Schmidt RJ, Shin HM. Gestational exposures to mixtures of multiple chemical classes and autism spectrum disorder in the MARBLES study. Environ Res;2025 (Apr 16):121646.

BACKGROUND: Previous epidemiologic studies on gestational chemical exposures and autism spectrum disorder (ASD) often lack analysis of chemical mixtures or are limited to investigating certain chemical classes. OBJECTIVE: We examined the impact of multi-class chemical mixtures on ASD risk, using data from the MARBLES (Markers of Autism Risks in Babies-Learning Early Signs) cohort. METHODS: Children were clinically assessed at age 3 and classified as ASD, typical development (TD), or non-TD with other neurodevelopmental concerns. In blood or urine from 105 pregnant mothers, we quantified 42 biomarkers across 5 chemical classes: per- and polyfluoroalkyl substances (PFAS), parabens, phenols, phthalates, and organophosphate esters (OPEs). We only analyzed 30 biomarkers detected in >50% of the sample. After identifying clusters with similar chemical profiles via hierarchical clustering, we applied linear discriminant analysis (LDA) to compute LDA exposure summary scores. In covariate-adjusted models, we used LDA scores to assess co-adjusted, multipollutant associations (relative risk [RR]) with ASD or non-TD, via quasi-Poisson regression. We further examined overall mixture effect and chemical interactions with Bayesian kernel machine regression. RESULTS: We identified four distinct clusters: PFAS (Cluster 1), OPEs (Cluster 2), parabens and triclosan (Cluster 3), and phthalates and bisphenol A (Cluster 4). Relative to TD, LDA scores for each cluster were associated with increased risk of ASD (RR [95% CI]: 1.14 [1.03, 1.25], 1.12 [1.01, 1.24], 1.17 [1.07, 1.29], 1.17 [1.07, 1.28] for Cluster 1-4, respectively), whereas clusters 2 and 4 were associated with non-TD (1.07 [1.07, 1.14] and 1.12 [1.05, 1.19], respectively). Cumulative exposure across the four clusters was linked to increased risk of both ASD and non-TD. Potential interactions within and between clusters were observed. CONCLUSION: This study shows that considering multiple chemical classes resulted in stronger associations with ASD and non-TD risk, compared to when investigated separately in our previous studies.

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8. Cosart BD, Lawson KA, Williams SR, Lewis KE, Namutebi R, Johnson MB. Parent Perspectives on Water Safety for Children with Autism. J Autism Dev Disord;2025 (Apr 16)

Among children with autism, drowning is the leading cause of death through 14 years old. Attributes such as wandering, sensory issues, impulsivity, and a limited sense of danger could increase risk. In addition, autistic children often have trouble participating in structured group activities like swimming lessons. The purpose of this study is to better understand water safety experiences of parents of children with autism. Parents of autistic children were asked to participate in a focus group about their family’s water safety experiences. Six focus groups and one interview were held. Six major themes were identified from transcripts that were common among participants: autism characteristics influence water safety risk; water safety fears influence family life; it is difficult to find and access water safety and swimming lesson information for children with autism; autism characteristics affect participation in swimming lessons and other aquatic activities; autistic children have unique swimming lesson needs; and instructor preparedness is key to swimming lesson success for autistic children. Water safety needs to be elevated in importance for families of autistic children. Information on drowning risk and prevention should be made more accessible. Barriers to adaptive swimming lessons such as cost, scheduling, and availability need to be addressed. More training opportunities need to be provided to swimming instructors to improve teaching children with complex needs, such as those with autism.

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9. Dastgheib SS, Kaufmann JM, Kowallik AE, Schweinberger SR. Attention to Social and Non-Social Stimuli in a Continuous Performance Test in Autistic and Typically Developed Participants: An ERP Study. J Autism Dev Disord;2025 (Apr 16)

Autism spectrum disorder (ASD) is characterized by a range of symptoms, including restrictive behaviors and deficient social skills. We investigated EEG correlates of social attention, face, and non-face perception by applying a continuous performance test (CPT) with two different sets of stimuli (letters and faces). The CPT required participants to respond to a specific target stimulus (e.g., « X ») only when it followed a specific preceding stimulus (e.g., « O »). Event-related potential (ERP) components, including P100, N170, P200, N250, P300, and continuous negative variation (CNV), were analyzed in 19 young adults with ASD and 19 typically developed (TD) individuals that were matched for intelligence, age, and gender. TD participants had higher accuracies only for the target condition and regardless of stimulus type. No ERP differences between the two groups were found for the CPT with letter stimuli. By contrast, autistic individuals exhibited lower amplitudes of P300 and CNV during face CPT. Results suggest diminished allocation of attentional resources and response preparation towards socially relevant face stimuli.

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10. Feldman D, Prigge M, Alexander A, Zielinski B, Lainhart J, King J. Flexible nonlinear modeling reveals age-related differences in resting-state functional brain connectivity in autistic males from childhood to mid-adulthood. Mol Autism;2025 (Apr 15);16(1):24.

BACKGROUND: Divergent age-related functional brain connectivity in autism spectrum disorder (ASD) has been observed using resting-state fMRI, although the specific findings are inconsistent across studies. Common statistical regression approaches that fit identical models across functional brain networks may contribute to these inconsistencies. Relationships among functional networks have been reported to follow unique nonlinear developmental trajectories, suggesting the need for flexible modeling. Here we apply generalized additive models (GAMs) to flexibly adapt to distinct network trajectories and simultaneously describe divergent age-related changes from childhood into mid-adulthood in ASD. METHODS: 1107 males, aged 5-40, from the ABIDE I & II cross-sectional datasets were analyzed. Functional connectivity was extracted using a network-based template. Connectivity values were harmonized using COMBAT-GAM. Connectivity-age relationships were assessed with thin-plate spline GAMs. Post-hoc analyses defined the age-ranges of divergent aging in ASD. RESULTS: Typically developing (TD) and ASD groups shared 15 brain connections that significantly changed with age (FDR-corrected p < 0.05). Network connectivity exhibited diverse nonlinear age-related trajectories across the functional connectome. Comparing ASD and TD groups, default mode to central executive between-network connectivity followed similar nonlinear paths with no group differences. Contrarily, the ASD group had chronic hypoconnectivity throughout default mode-ventral attentional (salience) and default mode-somatomotor aging trajectories. Within-network somatomotor connectivity was similar between groups in childhood but diverged in adolescence with the ASD group showing decreased within-network connectivity. Network connectivity between the somatomotor network and various other functional networks had fully disrupted age-related pathways in ASD compared to TD, displaying significantly different model curvatures and fits. LIMITATIONS: The present analysis includes only male participants and has a restricted age range, limiting analysis of early development and later life aging, years 40 and beyond. Additionally, our analysis is limited to large-scale network cortical functional parcellation. To parse more specificity of brain region connectivity, a fine-grained functional parcellation including subcortical areas may be warranted. CONCLUSION: Flexible non-linear modeling minimizes statistical assumptions and allows diagnosis-related brain connections to follow independent data-driven age-related pathways. Using GAMs, we describe complex age-related pathways throughout the human connectome and observe distinct periods of divergence in autism.

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11. Hata M, Xu M, Hakuno Y, Yamamoto E, Minagawa Y. Emerging sensitivity to talking mouth in infants with low and elevated likelihood of autism spectrum disorder: A longitudinal study. Infant Behav Dev;2025 (Apr 16);79:102057.

The talker’s mouth provides significant multimodal information that supports language development. Studies have revealed that infants over 6 months of age show increased attention to the mouth of a talking face, which results in vocabulary growth. However, few studies have reported the relationship between early gaze behavior and later language development in infants with an elevated likelihood of autism spectrum disorder (ASD) (EL infants). Since ASD cannot be diagnosed in infancy, these infants provide a valuable opportunity to investigate early developmental differences in visual attention that may be associated with ASD. Therefore, we conducted a longitudinal eye-tracking experiment at ages 6, 9, 12, 18, and 24 months to investigate differences in gaze behavior between infants with a low likelihood of ASD (LL infants) and EL infants. We found that, exclusively in LL infants, the proportion of mouth-looking time significantly increased from 6 months to 9 months of age and remained relatively constant thereafter. In contrast, in EL infants, although the proportion of mouth-looking time gradually increased with age up to 24 months, their attentional change to talking mouth started later than that in LL infants. Furthermore, our results showed a conditionally positive relationship between mouth-looking and expressive vocabulary size in LL infants but not in EL infants. These findings indicate that EL infants may not utilize audiovisual information as valuable cues for language acquisition during infancy and toddlerhood, which may be a factor in their slow language development.

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12. Huang Z, Li Y, Bucci V, Haran JP. Decoding cancer prognosis with deep learning: the ASD-cancer framework for tumor microenvironment analysis. mSystems;2025 (Apr 16):e0145524.

Deep learning is revolutionizing biomedical research by facilitating the integration of multi-omics data sets while bridging classical bioinformatics with existing knowledge. Building on this powerful potential, Zhang et al. proposed a semi-supervised learning framework called Autoencoder-Based Subtypes Detector for Cancer (ASD-cancer) to improve the multi-omics data analysis (H. Zhang, X. Xiong, M. Cheng, et al., 2024, mSystems 9:e01395-24, https://doi.org/10.1128/msystems.01395-24). By utilizing autoencoders pre-trained on The Cancer Genome Atlas data, the ASD-cancer framework outperforms the baseline model. This approach also makes the framework scalable, enabling it to process new data sets through transfer learning without retraining. This commentary explores the methodological innovations and scalability of ASD-cancer while suggesting future directions, such as the incorporation of additional data layers and the development of adaptive AI models through continuous learning. Notably, integrating large language models into ASD-cancer could enhance its interpretability, providing more profound insights into oncological research and increasing its influence in cancer subtyping and further analysis.

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13. Ju J, Pan Y, Yang X, Li X, Chen J, Wu S, Hou ST. The « don’t eat me » signal CD47 is associated with microglial phagocytosis defects and autism-like behaviors in 16p11.2 deletion mice. Proc Natl Acad Sci U S A;2025 (Apr 22);122(16):e2411080122.

Various pathological characteristics of autism spectrum disorder (ASD) stem from abnormalities in brain resident immune cells, specifically microglia, to prune unnecessary synapses or neural connections during early development. Animal models of ASD exhibit an abundance of synapses in different brain regions, which is strongly linked to the appearance of ASD behaviors. Overexpression of CD47 on neurons acts as a « don’t eat me » signal, safeguarding synapses from inappropriate pruning by microglia. Indeed, CD47 overexpression occurs in 16p11.2 deletion carriers, causing decreased synaptic phagocytosis and the manifestation of ASD characteristics. However, the role of CD47 in synaptic pruning impairment leading to ASD phenotypes in the 16p11.2 deletion mouse model is unclear. Moreover, whether blocking CD47 can alleviate ASD mice’s behavioral deficits remains unknown. Here, we demonstrate a strong link between increased CD47 expression, decreased microglia phagocytosis capacity, and increased impairment in social novelty preference in the 16p11.2 deletion mice. The reduction in microglia phagocytosis caused a rise in excitatory synapses and transmission in the prefrontal cortex of 16p11.2 deletion mice. Importantly, blocking CD47 using a specific CD47 antibody or reducing CD47 expression using a specific short hairpin RNA (shRNA) enhanced the microglia phagocytosis and reduced excitatory transmission. Reduction in CD47 expression improved social novelty preference deficits in 16p11.2 mice. These findings demonstrate that CD47 is associated with the ASD phenotypes in the 16p11.2 deletion mice and could be a promising target for the development of treatment for ASD.

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14. Kannikeswaran N, Roback MG, Burger RK, Barrowman N, Sucha E, Bhatt M. Comparison of Procedural Sedation Outcomes in Children With and Without Autism Spectrum Disorder. Hosp Pediatr;2025 (Apr 16)

OBJECTIVE: Children with autism spectrum disorder (ASD) often have comorbidities predisposing them to higher risk for sedation-related adverse events (AEs). Our objective was to compare sedation-related AEs in children with and without ASD. PATIENTS AND METHODS: We conducted a multicenter study of children aged 3-18 years with and without ASD who underwent sedation outside the operating room from May 1, 2022, to April 30, 2023, using the Pediatric Sedation Research Consortium database. The primary exposure was ASD diagnosis. We compared AEs in children with and without ASD after matching for age, sex, procedure, and American Society of Anesthesiologists classification. RESULTS: Of 64 708 children analyzed, 4421 (6.8%) had an ASD diagnosis. A higher proportion of children with ASD were male (75.4% vs 54.7%), obese (6.0% vs 2.9%), and had a comorbid condition (93.5% vs 40.3%). Matched analysis showed no significant difference in critical AEs (odds ratio [OR], 0.63; 95% CI, 0.23-1.49). However, children with ASD had greater odds of high risk (OR, 1.52; 95% CI, 1.26-1.83) and low-risk AEs (OR, 1.39; 95% CI, 1.25-1.55) compared with children without ASD. Specifically, children with ASD had greater odds of hypoxia (OR, 1.31; 95% CI, 1.10-1.56) and complete (OR, 1.89; 95% CI, 1.27-2.81) or partial (OR, 1.43; 95% CI, 1.25-1.63) airway obstruction. CONCLUSIONS: Children with ASD are at a higher risk for sedation-related airway AEs and significant respiratory interventions, although the incidence of critical AEs was low.

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15. Kasahara S, Yoshimoto T, Oka H, Sato N, Morita T, Niwa SI, Uchida K, Matsudaira K. Correlation between attention deficit/hyperactivity disorder and chronic pain: a survey of adults in Japan. Sci Rep;2025 (Apr 16);15(1):13165.

This cross-sectional epidemiological internet survey assessed whether attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) symptoms are associated with pain chronicity and intensity and explored the relationship between developmental disorder symptoms and pain. Participants were 4028 adults aged 20-64 years who experienced pain, assessed using an 11-point numerical rating scale (NRS), in any body part in the previous 4 weeks. ADHD and ASD symptoms were assessed using the Adult ADHD Self-Report Scale (ASRS) and autism spectrum quotient, respectively. Problems with mental health (PMH) were assessed using the shortened Profile of Mood States. Pathway analyses were performed to examine the association between ADHD symptoms and pain. The chronic pain symptoms (CP) group (N = 1465) scored higher than the non-CP group (N = 2563) for all ASRS variables. ASRS positivity was associated with CP symptoms and increased with increasing NRS score; the CP group showed particularly high positivity (38.3%) with extreme pain. ADHD symptoms were more strongly associated with CP symptoms and intensity than was PMH (0.26 vs. 0.09). ADHD symptoms, but not ASD symptoms, were associated with CP symptoms. ADHD medications reportedly improve coexisting CP; therefore, ADHD screening and treatment may be important for patients with CP, especially those with extreme pain.

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16. Kim KM, Lee CE, Park YM, Han K, Cho IY. Perspectives of South Korean Parents Toward Psychotropic Medication Use Among Autistic Individuals. J Autism Dev Disord;2025 (Apr 16)

This study aimed to understand the status of psychotropic medication use among autistic individuals and how South Korean parents perceive its effects and the associated communication processes. This study involved three research questions investigating the following: general prescription trends of psychotropic medication use among autistic individuals, psychotropic medication use and its effects, and the communication of psychotropic medication use with stakeholders. This study employed a qualitative design and involved individual interviews with 19 parents of autistic individuals. To be included in the study, participants were required to have a child with autism over 18 years of age, currently receiving psychotropic medication. Constant comparative analysis and emergent coding were used to analyze the data. The general prescription trends of psychotropic medication use were grouped according to age based on the initiation of psychotropic medication use, reasons for psychotropic medication use, dose of psychotropic medication use, and experience of psychiatric hospitalization. Overall, parents were skeptical of the effects of psychotropic medications, leading to non-adherence to the prescribed psychotropic medications. Finally, there was a lack of communication among psychiatrists, autistic adults, and other professionals regarding psychotropic medication use. Future practices are warranted to develop educational programs on medication use, including foundational knowledge on medications, correct dosages, and strategies for managing side effects. Furthermore, ongoing communication among stakeholders should be guaranteed based on team approaches while prioritizing the voices of autistic individuals.

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17. Leadbitter K, Gulati S, Shephard E, Hoekstra R. Autism as an international journal: Equity, inclusion and cultural humility for a global authorship and readership. Autism;2025 (Apr 16):13623613251333822.

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18. Lidstone DE. Missed Early Intervention Opportunities for Children With Autism Spectrum Disorder. Autism Res;2025 (Apr 16)

Early intervention (EI) is essential for improving developmental outcomes in children with autism spectrum disorder (ASD). However, participation during the critical neurodevelopmental (0-3 years) period remains a challenge. To identify those factors associated with the participation of preschool children with ASD in EI before age 2, this study uses recent cross-sectional data from the 2021 to 2023 National Survey of Children’s Health (NSCH). Binary logistical regression analysis was conducted to identify factors associated with EI receipt before age 2, including age of ASD diagnosis, socioeconomic status (SES), race, ASD severity, biological sex, birth weight, and diagnosis of early indicators of future developmental delay (DD). The findings revealed that only 15% of preschool children with ASD received EI before age 2. Significant predictors of timely participation in Part C EI included an ASD diagnosis before age 2, higher SES, and lower birth weight. Findings also revealed that 15.5% of children who did not receive timely EI had severe ASD symptoms, highlighting the critical need to improve EI participation for these children. Potential solutions discussed include expanding the definition of DD, increasing the number of states recognizing low birth weight as a Part C EI diagnosis, reducing barriers to Part C EI participation for disadvantaged families, and developing more effective tools to detect ASD and DD earlier in development.

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19. Luo Y, Chen Q, Li F, Yi L, Xu P, Zhang Y. Hierarchical feature extraction on functional brain networks for autism spectrum disorder identification with resting-state fMRI data. Neural Netw;2025 (Apr 12);188:107450.

Autism Spectrum Disorder (ASD) is a pervasive developmental disorder of the central nervous system, primarily manifesting in childhood. It is characterized by atypical and repetitive behaviors. Conventional diagnostic methods mainly rely on questionnaire surveys and behavioral observations, which are prone to misdiagnosis due to their subjective nature. With advancements in medical imaging, MR imaging-based diagnostics have emerged as a more objective alternative. In this paper, we propose a Hierarchical Neural Network model for ASD identification, termed ASD-HNet, which hierarchically extracts features from functional brain networks based on resting-state functional magnetic resonance imaging (rs-fMRI) data. This hierarchical approach enhances the extraction of brain representations, improving diagnostic accuracy and aiding in the identification of brain regions associated with ASD. Specifically, features are extracted at three levels, i.e., the local region of interest (ROI) scale, the community scale, and the global representation scale. At the ROI scale, graph convolution is employed to transfer features between ROIs. At the community scale, functional gradients are introduced, and a K-Means clustering algorithm is applied to group ROIs with similar functional gradients into communities. Features from ROIs within the same community are then extracted to characterize the communities. At the global representation scale, we extract global features from the whole community-scale brain networks to represent the entire brain. We validate the effectiveness of the ASD-HNet model using the publicly available Autism Brain Imaging Data Exchange I (ABIDE-I) dataset, ADHD-200,dataset and ABIDE-II dataset. Extensive experimental results demonstrate that ASD-HNet outperforms existing baseline methods. The code is available at https://github.com/LYQbyte/ASD-HNet.

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20. Nawghare P, Prasad J. Hybrid CNN and random forest model with late fusion for detection of autism spectrum disorder in Toddlers. MethodsX;2025 (Jun);14:103278.

Accurate and early diagnosis of Autism Spectrum Disorder (ASD) in toddlers is crucial for effective intervention. Traditional models have shown limited success, while deep learning approaches achieve higher accuracies. Our study proposes a hybrid model combining VGG16, a pre-trained deep CNN, with an RF classifier to leverage high-level image feature extraction using the ACD image dataset on Kaggle alongside robust decision-making on the ACD Questionnaire dataset. The proposed model achieves an accuracy of 88.34 %, outperforming both standalone deep learning models like VGG16, EfficientNetB0, and AlexNet-based models as well as conventional ML models. This improvement demonstrates the effectiveness of combining feature-rich deep learning outputs with RF’s ensemble-based classification. Our findings suggest that this hybrid approach is highly suitable for ASD classification tasks, enhancing the reliability of predictions in clinical settings. This research not only establishes the model as an option for ASD diagnosis but also underscores the potential of hybrid architectures that fuse deep learning with machine learning. Future research will focus on integrating multi-modal data (e.g., genetic and socio-demographic) and further testing on diverse datasets to improve generalizability. The study contributes to the growing body of evidence supporting advanced ML techniques in healthcare diagnostics, especially in neurodevelopmental disorders like ASD.

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21. Olson HA, Johnson KT, Nishith S, D’Mello AM. Incorporating special interests to investigate the language system in autism: A feasibility pilot fMRI study. bioRxiv;2025 (Apr 5)

Most autistic individuals have sustained, focused interests in particular topics or activities. In some cases, these special interests have been shown to motivate communicative behaviors, a domain in which many autistic individuals experience challenges. We conducted a pilot study with 15 autistic children (ages 8.18 – 13.27 years, mean(SD)= 11.17(1.62), 3 female/11 male/1 nonbinary), comparing brain responses elicited by short narratives tailored to individuals’ special interests to responses elicited by generic, non-tailored narratives. Using functional magnetic resonance imaging (fMRI), we found that autistic children did not show typical language responses to generic narratives. However, they did show heightened responses to the narratives that incorporated their special interests relative to the generic narratives in language regions and in regions associated with reward and self-reference. Brain responses for personalized narratives were also more consistent across children than responses for the generic narratives. These results suggest that personalizing stimuli by incorporating special interests might be a promising approach for neuroimaging in autistic participants. LAY SUMMARY: In a pilot sample of autistic children, we found that listening to short narratives tailored to each child’s special interest elicited higher responses in the brain than listening to non-personalized narratives. Brain responses across children were also more similar for the special interest narratives. Thus, personalizing stimuli to special interests may be a promising approach for neuroimaging studies of autism.

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22. Prabhakaran N, Jestine S, Chandran S, Shiva L, Moncy AM. Gastrointestinal Manifestations and Associated Comorbidities in Children with Autism Spectrum Disorder: A Cross-sectional Analysis from South India. Indian J Psychol Med;2025 (Apr 16):02537176251331152.

BACKGROUND: Gastrointestinal (GI) symptoms are frequently reported in children with autism spectrum disorder (ASD) and may significantly impact behavior, sleep, adaptive functioning, and the severity of autism. This study aims to explore the relationship between GI symptoms and these factors in children with ASD. METHODS: We investigated 96 children and adolescents with ASD aged 3-18 years attending an autism clinic in South India. Parents were interviewed using a semi-structured proforma that gathered information on GI symptoms, sociodemographic details, medical history, and treatment history. Behavioral problems were assessed using the Strengths and Difficulties Questionnaire-2 (SDQ-2), ASD severity was measured using the Indian Scale for Assessment of Autism (ISAA), and sleep issues were evaluated using the Children’s Sleep Habits Questionnaire (CSHQ) for autism. Statistical analyses were conducted to determine the predictive value of assessment scores on GI symptoms in two groups: (a) those with mild to moderate ASD and (b) participants aged less than or equal to six years versus more than six years. RESULTS: Constipation and dietary problems were the most commonly reported (82.29%), followed by dyspepsia and reflux (44.79%), pica (36.46%), abdominal pain (26.04%), and diarrhea (14.58%). Holding all other predictor variables constant, constipation increased by 20% (odds ratio [OR] = 1.201) for unit increases in speech-language communication scores. Abdominal pain decreased by 24.5% (OR = 0.755) for unit increases in peer problems scores. Excessive flatulence decreased by 64.2% (OR = 0.358) for unit increases in conduct problems score. Finally, pica was found to increase by 23.2% (OR = 1.232) for unit increases in the sensory patterns score. CONCLUSIONS: The GI symptoms can negatively impact sleep and behavior in children with ASD, spotlighting the importance of routine GI screening in this population. Clinicians should be particularly vigilant in cases where symptoms suggest a higher likelihood of GI issues to enhance the quality of care for children with ASD.

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23. Şanlidağ B, Donbaloğlu F, Sari Yanartaş M, Şekeroğlu B, Yilmaz A, Köken Ö Y. High-frequency oscillations in autism spectrum disorder: are they related to clinical severity?. Cereb Cortex;2025 (Apr 1);35(4)

High-frequency oscillations are oscillatory high-frequency (>80 Hz) signals that can be physiological or pathological. Physiological high-frequency oscillations related to sleep spindles have been reported. In addition, some reports indicate that high-frequency oscillations are a marker for the prediction of seizures. Our aim was to explore the presence of high-frequency oscillations in children with autism spectrum disorder and their relationship with clinical symptoms. Fifty-two children with autism spectrum disorder and 49 healthy children were enrolled in the study. EEG records were evaluated via the open-source Python library magnetoencephalography and electroencephalography (MNE)-high-frequency oscillation for the detection of scalp high-frequency oscillations and sleep spindles detected by open-source YASA. SPSS version 22 used for statistical analysis. The duration of sleep spindle was shorter, and the frequency was significantly greater, in children with autism spectrum disorder than in healthy controls. High-frequency oscillations unrelated to sleep spindle were more common in children with autism spectrum disorder (P < 0.01). Younger children with autism spectrum disorder had particularly more high-frequency oscillations unrelated to sleep spindle (P < 0.01). Within the autism spectrum disorder group of patients, high-frequency oscillations unrelated to sleep spindle were significantly greater in subgroups with moderate-severe social interaction problems (P < 0.01), moderate-severe restricted interest (P = 0.018), and severe linguistic delays (P = 0.006). High-frequency oscillations might be a candidate marker for autism spectrum disorder that might be used in clinical settings that warrants further studies.

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24. Sessiz R, Ayan G, Sezer B, Tosun İ. Evaluation of oral health and dental hygiene habits in adolescents with intellectual and developmental disabilities: a longitudinal pilot study. Quintessence Int;2025 (Apr 16);0(0):0.

OBJECTIVES: Adolescents with intellectual and developmental disabilities (IDDs) are at increased risk of oral diseases due to physical limitations, poor oral health awareness, and inadequate dental hygiene practices. The aim of this study was to evaluate the oral health status of adolescents with IDDs and to analyze changes in their dental hygiene habits following subsequent visits and oral hygiene education. METHOD AND MATERIALS: This pilot longitudinal observational study involved students with mild to moderate IDDs from a special needs school. Oral health was assessed using the Decayed, Missing, and Filled Teeth (DMFT) index, International Caries Detection and Assessment System (ICDAS-II), Basic Erosive Wear Examination (BEWE), Developmental Defects of Enamel (DDE), and Simplified Oral Hygiene (OHI-S) indices. Participants received oral hygiene training, and their brushing techniques were evaluated using the Oral Hygiene Skills Survey. Data on brushing frequency, skills, toothpaste use, and OHI-S scores were collected at baseline and at 1-, 3-, and 6-month follow-ups. RESULTS: Twenty-three participants aged 14-19 were evaluated, showing high DMFT scores (mean 10.91 ± 6.06), advanced caries in 78.3%, and enamel defects and erosive tooth wear in 65.2%. Significant improvements were observed in toothbrushing frequency (P = .008), with reductions in OHI-S scores (P = .001) and enhanced brushing skills (P = .016) during follow-ups. CONCLUSION: The findings indicate a high prevalence of dental caries, enamel defects, and erosive tooth wear among adolescents with IDDs. Despite poor baseline oral hygiene practices, regular follow-ups and oral hygiene education significantly improved oral hygiene habits and outcomes.

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25. Seymour RA, Rippon G, Gooding-Williams G, Wang H, Kessler K. The Neural Oscillatory Basis of Perspective-Taking in Autistic and Non-Autistic Adolescents Using Magnetoencephalography. Eur J Neurosci;2025 (Apr);61(8):e70109.

Taking another’s perspective is a high-level mental skill underlying many aspects of social cognition. Perspective-taking is usually an embodied egocentric process whereby people mentally rotate themselves away from their physical location into the other’s orientation. This is accompanied by increased theta-band (3-7 Hz) brain oscillations within a widespread fronto-parietal cortical network including the temporoparietal junction. Individuals with autism spectrum conditions (ASC) have been reported to experience challenges with high-level perspective-taking, particularly when adopting embodied strategies. To investigate the potential neurophysiological basis of these autism-related individual differences, we used magnetoencephalography in combination with a well-replicated perspective-taking paradigm in a group of 18 autistic and 17 age-matched non-autistic adolescents. Findings revealed that increasing the angle between self and other perspective resulted in prolonged reaction times for the autistic group during perspective-taking. This was accompanied by reduced theta power across a wide network of regions typically active during social cognitive tasks. On the other hand, the autistic group showed greater alpha power decreases in visual cortex compared with the non-autistic group across all perspective-taking conditions. These divergent theta and alpha power effects, coupled with steeper response time slopes, suggest that autistic individuals may rely more on alternative cognitive strategies, such as mental object rotation, rather than an egocentric embodied approach. Finally, no group differences were found when participants were asked to track, rather than take, another’s viewpoint, suggesting that autism-related individual differences are specific to high-level perspective-taking.

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26. Shil A, Arava N, Levi N, Levine L, Golan H, Meiri G, Michaelovski A, Tsadaka Y, Aran A, Menashe I. An integrative scoring approach for prioritization of rare autism spectrum disorder candidate variants from whole exome sequencing data. Sci Rep;2025 (Apr 15);15(1):13024.

Discerning clinically relevant autism spectrum disorder (ASD) candidate variants from whole-exome sequencing (WES) data is complex, time-consuming, and labor-intensive. To this end, we developed AutScore, an integrative prioritization algorithm of ASD candidate variants from WES data and assessed its performance to detect clinically relevant variants. We studied WES data from 581 ASD probands, and their parents registered in the Azrieli National Center database for Autism and Neurodevelopment Research. We focused on rare allele frequency (< 1%) and high-quality proband-specific variants affecting genes associated with ASD or other neurodevelopmental disorders (NDDs). We developed AutScore and AutScore.r and assigned each variant based on their pathogenicity, clinical relevance, gene-disease association, and inheritance patterns. Finally, we compared the performance of both AutScore versions with the rating of clinical experts and the NDD variant prioritization algorithm, AutoCaSc. Overall, 1161 rare variants distributed in 687 genes in 441 ASD probands were evaluated by AutScore with scores ranging from - 4 to 25, with a mean ± SD of 5.89 ± 4.18. AutScore.r cut-off of ≥ 0.335 performs better than AutoCaSc and AutScore in detecting clinically relevant ASD variants, with a detection accuracy rate of 85% and an overall diagnostic yield of 10.3%. Five variants with AutScore.r of ≥ 0.335 were distributed in five novel ASD candidate genes. AutScore.r is an effective automated ranking system for ASD candidate variants that could be implemented in ASD clinical genetics pipelines.

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27. Smith CM, Weimann K, Widick M, Merritt T, Christensen H, Siegel M, Pan Z, Gabriels RL. Best practices for physiological data collection in youth with autism and co-occurring mental health diagnoses: Implications for human-animal intervention research. MethodsX;2025 (Jun);14:103284.

The purpose of this paper is to serve as a catalyst for the human-animal interaction research field to improve scientific rigor and accelerate the knowledge of field-based physiological responses during equine-assisted services in youth with autism spectrum disorder. This paper outlines the best practices for collecting and analyzing electrocardiogram and electrodermal activity in youth with autism spectrum disorder, utilized during a 10-week therapeutic horseback riding intervention.•Motivation strategies such as device choice, reward systems, and a visual schedule should be implemented to improve participant compliance. In addition, devices should be secured to the participant following implementation of appropriate desensitization techniques.•Time-domain heart rate variability analyses are more appropriate during therapeutic horseback riding data collection compared to frequency-domain approaches. For electrodermal activity, tonic responses should be assessed as opposed to phasic analyses.•An effective data monitoring team including the Data Collection Research Personnel, Site Principal Investigator, Physiologist, and Therapeutic Riding Center Intervention Lead are key to increasing the quality of usable data in equine-assisted service research environments.

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28. Xiao S, Li J. Publisher Correction: Impact of imitation abilities on social communication in autistic children: evidence from an Early Start Denver Model intervention study. Mol Autism;2025 (Apr 15);16(1):25.

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29. Ye QY, Zhou BR, Zhang Y, Hu CC, Gu YZ, Li XY, Li HP, Xu Q, Jia FY, Zhang L, Xu X. [Analysis of the intervention effects of skill training for parents with autism child on toddlers with autism spectrum disorder]. Zhonghua Er Ke Za Zhi;2025 (Apr 16);63(5):491-497.

Objective: To explore the intervention effects of the skill training for parents with autism child (STPAC) on toddlers with autism spectrum disorder (ASD). Methods: A multicenter non-randomized concurrent controlled study design was conducted. Thirty children with ASD aged 15-30 months, first diagnosed at the Children’s Hospital of Fudan University, the First Hospital of Jilin University, and Chengdu Women’s and Children’s Central Hospital from 2019 to 2020, were enrolled in the STPAC group. Thirty children with ASD who visited the same hospitals during the same period but refused the STPAC intervention were selected as the control group. The STPAC group received an 8-week intervention (3 h/week) followed by quarterly follow-ups for 1 year, while the control group voluntarily chose community-based routine interventions. The Griffiths development scales-Chinese (GDS-C) was used to assess the developmental levels, and the communication and symbolic behavior scales developmental profile infant-toddler checklist (CSBS-DP-ITC) was completed by the primary caregivers to evaluate social, language and symbolic behavior. The independent samples t-tests or Mann-Whitney U tests, etc.was used for inter-group comparison. The paired t-tests or Wilcoxon signed-rank tests, etc. was used for inter-group pre-post intervention comparison. Results: The STPAC group included 30 children (22 males and 8 females, aged (23.9±2.2) months), and the control group included 30 children (20 males and 10 females, aged (24.2±2.6) months). Before the intervention, there were no statistically differences in GDS-C development quotient (DQ) and CSBS-DP-ITC scores between groups (all P>0.05). After 1-year intervention, GDS-C DQ in personal-social, hearing-language, hand-eye coordination, performance domains of STPAC group and GDS-C DQ in personal-social, hearing-language domains of control group were all increased (all P<0.01). After 1-year intervention, CSBS-DP-ITC scores of both groups were all improved in socia, language, symbolic behavior, and total scores (all P<0.001). GDS-C DQ changes before and after 1 year of intervention in hearing-language, hand-eye coordination, performance domains of the STPAC group were all higher the those of control group (34(15, 48 vs. 10(-4, 39), 11±20 vs. -1±19, 23±25 vs. 8±22, all P<0.05). CSBS-DP-ITC scores changes before and after 1 year of intervention in social and total scores of the STPAC group were both higher the those of control group (10(5, 30) vs. 3(1, 7), 26±17 vs. 11±8, both P<0.001). Conclusion: Compared with the community routine interventions, the STPAC better improves the language, hand-eye coordination, visual-spatial, social communication, and play skills in ASD toddlers.

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