1. AlShawaf AJ, AlNassar SA, AlGhamdi N, Mattei C, Lim SY, Dottori M, Al-Mohanna FA. Autism Spectrum Disorder Induced Pluripotent Stem Cells Display Dysregulated Calcium Signaling During Neural Differentiation. Cells. 2025; 14(17).

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects communication, social interaction, and behavior. Calcium (Ca(2+)) signaling dysregulation has been frequently highlighted in genetic studies as a contributing factor to aberrant developmental processes in ASD. Herein, we used ASD and control induced pluripotent stem cells (iPSCs) to investigate transcriptomic and functional Ca(2+) dynamics at various stages of differentiation to cortical neurons. Idiopathic ASD and control iPSC lines underwent the dual SMAD inhibition differentiation protocol to direct their fate toward cortical neurons. Samples from multiple time points along the course of differentiation were processed for bulk RNA sequencing, spanning the following sequential stages: the iPSC stage, neural induction (NI) stage, neurosphere (NSP) stage, and differentiated cortical neuron (Diff) stage. Our transcriptomic analyses suggested that the numbers of Ca(2+) signaling-relevant differentially expressed genes between ASD and control samples were higher in the iPSC and Diff stages. Accordingly, samples from the iPSC and Diff stages were processed for Ca(2+) imaging studies. Results revealed that iPSC-stage ASD samples displayed elevated maximum Ca(2+) levels in response to ATP compared to controls. By contrast, in the Diff stage, ASD neurons showed reduced maximum Ca(2+) levels in response to ATP but increased maximum Ca(2+) levels in response to KCl and DHPG relative to controls. Considering the distinct functional signaling contexts of these stimuli, this differential profile of receptor- and ionophore-mediated Ca(2+) response suggests that aberrant calcium homeostasis underlies the pathophysiology of ASD neurons. Our data provides functional evidence for Ca(2+) signaling dysregulation during neurogenesis in idiopathic ASD.

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2. Choi G, Lee S, Yoo S, Do JT. MECP2 Dysfunction in Rett Syndrome: Molecular Mechanisms, Multisystem Pathology, and Emerging Therapeutic Strategies. Int J Mol Sci. 2025; 26(17).

Rett syndrome is a severe neurodevelopmental disorder that occurs primarily in females and is caused by mutations in the methyl-CpG-binding protein 2 (MECP2) gene located on the X chromosome. Though MECP2 acts as a representative transcriptional regulator and affects gene expression both directly and indirectly, a complete understanding of this disease and the treatment mechanism has not been established yet. MECP2 plays a particularly important role in synaptic development, neuronal maturation, and epigenetic regulation in the brain. In this study, we summarize the molecular structure of MECP2, mutation-specific pathogenesis, and the role of MECP2 in regulating chromatin remodeling, RNA splicing, and miRNA processing to provide a comprehensive understanding of Rett syndrome. Additionally, we describe abnormal phenotypes manifested in various brain regions and other tissues owing to MECP2 dysfunction. Finally, we discuss current and future therapeutic approaches, including AAV-based gene therapy, RNA editing, X chromosome reactivation, and pharmacological interventions. Understanding the diverse functions and pathological mechanisms of MECP2 provides an important foundation for developing targeted therapies for Rett syndrome.

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3. Chu S, Woodfin S, Bayliss E, Smith M, Fulp A, Mirabelli E, Moore W. Acetaminophen’s Role in Autism and ADHD: A Mitochondrial Perspective. Int J Mol Sci. 2025; 26(17).

One in 36 children were identified with autism in 2020, a 22% increase from 2018 and a 98% increase from 2010. Simultaneously, attention-deficit/hyperactivity disorder (ADHD) diagnoses increased 36% from 2003 to 2016-2019. Despite this surge, their etiologies remain largely unknown. However, numerous studies document higher incidences of mitochondrial abnormalities in affected individuals. Additionally, acetaminophen has been implicated in these disorders in longitudinal studies and murine models. This paper is a compilation of literature aiming to explore a theoretical framework for acetaminophen-induced mitochondrial damage in utero. It focuses on a toxic metabolite of acetaminophen, N-acetyl-p-benzoquinone imine (NAPQ1), and its role in neuroinflammation. Based on our findings, we recommend further research studying fetal mitochondria after maternal acetaminophen usage.

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4. Fernandez A, Sarn N, Eng C, Wright KM. Altered Primary Somatosensory Neuron Development in a Pten Heterozygous Model for Autism Spectrum Disorder. Autism Res. 2025.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by deficits in social interactions, repetitive behaviors, and hyper- or hyposensitivity to sensory stimuli. The cellular mechanisms underlying the emergence of abnormal sensory sensitivity in ASD are not fully understood. Recent studies in rodent models of ASD identified differences in dorsal root ganglia (DRG) neurons that convey somatosensory information to the central nervous system. However, it is unknown how ASD-associated alterations in DRG neurons emerge during development and if these phenotypes are conserved across ASD models. We examined Pten (phosphatase and tensin homolog) heterozygous mice (Pten(Het)) as a model for syndromic ASD and identified altered responses to sensory stimuli. Transcriptomic and in vivo analysis identified alterations in subtype-specific markers of DRG neurons in Pten(Het) mice, emerging during early DRG development and involving dysregulation of signaling pathways downstream of PTEN. Finally, we show that mice harboring an ASD-associated mutation (Pten(Y69H)) show nearly identical alterations in the expression of somatosensory neuron subtype-specific markers. These results show that precise levels of PTEN are required for proper somatosensory development and provide insight into the molecular and cellular basis of sensory abnormalities in a model for syndromic ASD.

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5. Frye RE, Cohen IL, Sequeira JM, Hill Z, Espinoza A, Brown WT, Mevs C, Marchi E, Flory M, Jenkins EC, Velinov MT, Quadros EV. Transgenerational Effects and Heritability of Folate Receptor Alpha Autoantibodies in Autism Spectrum Disorder. Int J Mol Sci. 2025; 26(17).

Autism Spectrum Disorder (ASD) affects an estimated prevalence of 1 in 31 children but the cause in most cases is unknown. Human and animal studies have linked ASD to Folate Receptor Alpha Autoantibodies (FRAAs). Our previous studies demonstrated that FRAAs are more common, on average, in families with children with ASD. This study reanalyzed data from a previous study which included 82 children diagnosed with ASD, 53 unaffected siblings, 70 mothers, 65 fathers, and 52 typically developing controls who did not have a history of ASD in their family. This study investigates the association of FRAA titers with ASD risk factors and explores the relationship of FRAA titers across generations. Several known risk factors for ASD, including multiplex ASD families, multiple birth pregnancies, and increased maternal and paternal ages at birth, were related to offspring FRAA titers. Multiplex ASD families demonstrated higher FRAA titers. Significant correlation were found between maternal and offspring blocking FRAA titers. FRAA titers increased across generations, although the increase in blocking FRAA titers was only seen in multiplex families. The proband with ASD showed higher blocking but not higher binding, FRAA titers compared to their non-affected siblings. Paternal FRAA titers are associated with several measures of offspring behavior and cognitive development. This research highlights the potential transgenerational transmission of FRAAs and their role in ASD. This supports the notion that heritable non-genetic factors may be important in the etiology of ASD and that FRAAs may demonstrate anticipation (worsening across generations), especially in multiplex families. FRAAs may provide one example of the possibility that susceptibility to autoimmune processes may contribute to disrupted brain development and function in ASD.

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6. Gigonzac TCV, Silva MO, Rodrigues FM, Bernardes AH, da Silva CC, da Cruz AD, Gigonzac MAD. Chromosome 15q Structural Variants Associated with Syndromic Autism Spectrum Disorder: Clinical and Genomic Insights from Three Case Reports in a Brazilian Reference Center. Int J Mol Sci. 2025; 26(17).

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition often associated with genetic syndromes. Structural variants on the long arm of chromosome 15 (15q) are recurrently implicated in syndromic ASD, yet their phenotypic spectrum remains insufficiently characterized in diverse populations. We retrospectively analyzed clinical and molecular data from three patients with ASD treated at a Brazilian public reference center who also presented neurological and systemic comorbidities. Genetic investigations included G-banded karyotyping, chromosomal microarray analysis (CMA), methylation assays, and multiplex ligation-dependent probe amplification (MLPA) when indicated. Variants were classified according to ACMG guidelines and correlated with individual phenotypes. Case 1 showed an 8.4 Mb triplication at 15q11.2-q13.1 encompassing SNRPN, UBE3A, and GABRB3, which are associated with epilepsy, delayed neuropsychomotor development, and dysmorphic traits. Case 2 presented a 418 kb duplication at 15q13.3 involving CHRNA7 and OTUD7A, a variant of uncertain significance correlated with intellectual disability, speech apraxia, and self-injurious behavior. Case 3 demonstrated extensive loss of heterozygosity at 15q11.2-q13.1 and 15q21.3-q26.2, which is compatible with maternal uniparental disomy and Prader-Willi syndrome, manifesting hypotonia, seizures, and global delay. These findings underscore the potential involvement of the 15q region in syndromic ASD and related neurological comorbidities, highlighting the diverse pathogenic mechanisms and the importance of comprehensive genomic profiling for diagnosis, counseling, and individualized care.

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7. Koh MY, Lee AJW, Wong HC, Aishworiya R. Occurrence and Correlates of Vitamin D and Iron Deficiency in Children with Autism Spectrum Disorder. Nutrients. 2025; 17(17).

Background/Objectives: This study aimed to determine the occurrence of vitamin D and iron deficiency in children with autism spectrum disorder (ASD) in Singapore and identify correlates of the presence of these deficiencies, if any. Methods: This is an observational, cross-sectional, retrospective review of children with a diagnosis of autism, aged 1 to 10 years old, seen at a tertiary developmental paediatric centre from January 2018 to December 2022, with blood investigations completed. Autism diagnosis was determined either clinically by a developmental paediatrician using DSM-5 criteria or using the Autism Diagnostic Observation Schedule (ADOS-2). Children with genetic disorders and chronic medical conditions were excluded. Logistic regression was used to evaluate associations with the deficiencies, and the Bonferroni method was applied on post hoc comparisons. Results: The overall sample comprised 241 children (79% males, mean age 4.2 years [SD 2.25]. There were 222 and 236 children who had blood investigations for vitamin D and iron levels performed, respectively. Out of the 222 children whose vitamin D tests were performed, 36.5% had vitamin D insufficiency/deficiency. Iron deficiency occurred in 37.7% for children who had their iron levels tested. There were 122 observations for both iron levels and complete blood count. Out of these, 19 (15.6%) had iron deficiency anaemia. There were no significant correlates for iron deficiency, with picky eating included. Conclusions: Vitamin D and iron deficiencies were common in this sample. Clinicians should consider testing for vitamin D and iron for children with ASD, especially for vitamin D in children of Indian ethnicity and older age.

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8. Lee T, Yu J, Ahn HS, Yeom J, Hyun Y, Kim JY, Hong J, Yoo JY, Kim K, Kim HW. Comparative proteome analysis of dried blood spots for high-risk group screening in children with autism spectrum disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2025: 111499.

OBJECTIVE: Reliable biomarkers that assist in the diagnosis of autism spectrum disorder (ASD) are limited. This study aimed to identify proteins that can differentiate children with ASD from controls. METHODS: A total of 30 children with ASD and 30 control children participated in the study. Psychological tests and questionnaires to assess cognitive function, adaptive function, autism symptoms, and behavioral problems were administered. Dried blood spots collected from the participants were analyzed using the SWATH LC-MS platform. Core proteins were identified to build a classifying model to predict ASD and control group status. RESULTS: Among the 849 proteins quantified, 33 candidate proteins were identified by combining two different algorithms. Candidate proteins were involved in biological pathways related to the skin, muscle functioning, immune system, and cytoskeleton organization. Of the candidate proteins, we selected 7 core proteins that overlapped between different algorithms. The core proteins, PSME1, four isoforms of TPM3, S100A6, and TBCA, were negatively correlated with the Childhood Autism Rating Scale, Aberrant Behavior Checklist, and Social Responsiveness Scale, and positively correlated with the Full-scale Intellectual Quotient. Furthermore, a logistic regression model with the core proteins predicted the ASD group with an area under the curve (AUC) of 0.956, sensitivity of 0.967, and specificity of 0.867. CONCLUSION: We performed a proteomic analysis of dried blood spot (DBS) from ASD and control group children to explore candidate biomarkers. Our data supports the possibility of using proteins as potential biomarkers for ASD, although further verification is warranted in an independent cohort.

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9. Lewandowska-Pietruszka Z, Figlerowicz M, Mazur-Melewska K. Gut Microbiota and Autism Spectrum Disorders: Neurodevelopmental, Behavioral, and Gastrointestinal Interactions. Nutrients. 2025; 17(17).

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by social communication deficits, repetitive behaviors, and frequent gastrointestinal comorbidities. Emerging research suggests gut microbiota alterations contribute to ASD symptoms and gastrointestinal dysfunction, but detailed microbial profiles and clinical correlations remain underexplored. METHODS: This study analyzed gut microbiota in 45 children aged 2-18 years diagnosed with ASD. Stool samples underwent 16S rRNA gene sequencing. Clinical assessments included ASD diagnostic subtype, adaptive functioning using the Vineland Adaptive Behavior Scale, gastrointestinal symptoms as per the Rome IV criteria, dietary patterns, and demographic variables. Statistical analyses correlated microbiota profiles with clinical features. RESULTS: Gut microbiota composition was significantly influenced by delivery mode, age, sex, and diet. Vaginally delivered children had higher beneficial SCFA-producing bacteria, whereas Cesarean section was linked to increased pathogenic Clostridiales. High-calorie and protein-rich diets correlated with shifts toward pro-inflammatory taxa. Microbial diversity and specific genera correlated with adaptive behavior domains (communication, socialization, motor skills) and severity of gastrointestinal symptoms. Both pro-inflammatory and anti-inflammatory bacteria variably impacted neurodevelopmental outcomes. CONCLUSIONS: Gut microbiota composition in children with ASD is shaped by multifactorial influences and connected to neurobehavioral and gastrointestinal phenotypes. The findings of this study support the potential of microbiota-targeted interventions to ameliorate ASD-associated symptoms and improve quality of life.

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10. Li J, Shum KK. Exploring the Relationships Between Theory of Mind, Social Skills, and Friendship Quality in Adolescents and Adults With and Without Autism Spectrum Disorder Through Structural Equation Modeling. J Autism Dev Disord. 2025.

This study examined friendship quality and theory of mind (ToM) in individuals with autism spectrum disorder (ASD) compared to non-autistic peers, and the influence of ToM, social skills, and problem behaviors on friendships. Participants included adolescents/young adults with ASD (N = 104; Male: 74, M(age) = 18.55 years) and without ASD (N = 192; Male: 101, M(age) = 16.65 years). Data were collected using measures of ToM, autistic traits, social skills, problem behaviors, and friendship quality. Independent samples t-tests and Pearson correlations were used to characterize group differences and variable relationships. Multi-group structural equation modeling (SEM) was employed to examine the roles of social skills and problem behaviors in the relationship between ToM and friendship quality across groups. Individuals with ASD reported lower friendship quality, with less companionship, help, security, and closeness, experienced more conflicts in friendships than their non-autistic peers, and exhibited lower ToM performance. Multi-group SEM indicated significant positive effects of ToM on social skills in both groups, with a stronger effect observed in ASD. Additionally, there was a significant direct effect of ToM on friendship quality, with social skills mediating this relationship in the ASD group. Conversely, the negative direct effect of problem behaviors on friendship quality was significant only in individuals without ASD. The findings provide insights into the social cognitive and behavioral processes that influence friendship quality in individuals with ASD and emphasize the importance of targeted interventions aimed at enhancing social skills and ToM abilities in this population.

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11. Malik W, Fahiem MA, Farhat T, Alghazo R, Mahmood A, Alhajlah M. An Explainable Deep Learning Framework for Multimodal Autism Diagnosis Using XAI GAMI-Net and Hypernetworks. Diagnostics (Basel). 2025; 15(17).

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by heterogeneous behavioral and neurological patterns, complicating timely and accurate diagnosis. Behavioral datasets are commonly used to diagnose ASD. In clinical practice, it is difficult to identify ASD because of the complexity of the behavioral symptoms, overlap of neurological disorders, and individual heterogeneity. Correct and timely identification is dependent on the presence of skilled professionals to perform thorough neurological examinations. Nevertheless, with developments in deep learning techniques, the diagnostic process can be significantly improved by automatically identifying and automatically classifying patterns of ASD-related behaviors and neuroimaging features. Method: This study introduces a novel multimodal diagnostic paradigm that combines structured behavioral phenotypes and structural magnetic resonance imaging (sMRI) into an interpretable and personalized framework. A Generalized Additive Model with Interactions (GAMI-Net) is used to process behavioral data for transparent embedding of clinical phenotypes. Structural brain characteristics are extracted via a hybrid CNN-GNN model, which retains voxel-level patterns and region-based connectivity through the Harvard-Oxford atlas. The embeddings are then fused using an Autoencoder, compressing cross-modal data into a common latent space. A Hyper Network-based MLP classifier produces subject-specific weights to make the final classification. Results: On the held-out test set drawn from the ABIDE-I dataset, a 20% split with about 247 subjects, the constructed system achieved an accuracy of 99.40%, precision of 100%, recall of 98.84%, an F1-score of 99.42%, and an ROC-AUC of 99.99%. For another test of generalizability, five-fold stratified cross-validation on the entire dataset yielded a mean accuracy of 98.56%, an F1-score of 98.61%, precision of 98.13%, recall of 99.12%, and an ROC-AUC of 99.62%. Conclusions: These results suggest that interpretable and personalized multimodal fusion can be useful in aiding practitioners in performing effective and accurate ASD diagnosis. Nevertheless, as the test was performed on stratified cross-validation and a single held-out split, future research should seek to validate the framework on larger, multi-site datasets and different partitioning schemes to guarantee robustness over heterogeneous populations.

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12. Mirizzi P, Esposito M, Ricciardi O, Bove D, Fadda R, Caffò AO, Mazza M, Valenti M. Food Selectivity in Children with Autism Spectrum Disorder and in Typically Developing Peers: Sensory Processing, Parental Practices, and Gastrointestinal Symptoms. Nutrients. 2025; 17(17).

BACKGROUND/OBJECTIVES: Food selectivity is a prevalent and challenging issue in childhood, particularly in children with autism spectrum disorder (ASD), which may result in restricted dietary patterns and nutrient deficiencies. This study aimed to identify high-risk subgroups of children by combining food selectivity, diet, BMI, gastrointestinal symptoms, sensory processing, and parental feeding practices in children with ASD and in typically developing children (TDC). METHODS: To achieve this aim, we ran a cross-sectional, survey-based study, including 408 children (aged 3 to 12.11 years), with gender-matched groups. Both parents completed a survey on children’s diet, anthropometric curves, gastrointestinal symptoms, and the Brief Autism Mealtime Behavior Inventory (BAMBI), Short Sensory Profile (SSP), and Caregiver’s Feeding Style Questionnaire (CFSQ). Data analysis included comparative tests, correlations, and k-means cluster analysis. RESULTS: Children with ASD exhibited significantly greater sensory processing difficulties, higher food refusal, limited food variety in the diet, and autism-related mealtime characteristics compared with TDC across all age groups. Caregivers of children with ASD reported higher controlling and contingency management feeding practices compared to the parents of the TDC. We found a strong correlation between sensory sensitivities and feeding issues. Notably, Body Mass Index (BMI) was not significantly associated with dietary restriction or gastrointestinal symptoms. Cluster analysis revealed a high-risk sub-phenotype in both groups of children with some differences, characterized by high food selectivity, taste, tactile, and smell sensitivity, gastrointestinal symptoms, and overactive parental practices. CONCLUSIONS: The early identification of this subgroup might foster more tailored, multidisciplinary, and effective assessment and clinical intervention.

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13. Panvino F, Paparella R, Tarani F, Lombardi C, Ferraguti G, Pisani F, Fiore M, Pancheva R, Ardizzone I, Tarani L. Neurotrophins in Neurodevelopmental Disorders: A Narrative Review of the Literature. Int J Mol Sci. 2025; 26(17).

Neurodevelopmental disorders (NDDs), including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), intellectual disability (ID), and tic disorders, comprise a range of conditions that originate in early childhood and impact cognitive, behavioral, and social functioning. Despite their clinical heterogeneity, they often share common molecular and neurobiological framework. This narrative review aims to examine the role of neurotrophins-particularly the brain-derived neurotrophic factor, nerve growth factor, and related molecules-in the pathophysiology of NDDs, and to explore their potential as biomarkers and therapeutic targets. A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science, including both clinical and preclinical studies. Neurotrophins are critically involved in brain development, influencing neurogenesis, synaptic plasticity, and neuronal survival. Dysregulation in their signaling pathways has been associated with core features of ASD and ADHD and may modulate cognitive outcomes in ID. Emerging evidence also supports a role for neuroimmune interactions and neurotrophic dysfunction in tic disorders. However, findings across studies remain inconsistent due to methodological variability and limited longitudinal data. Future research should aim for standardized methodologies and stratified, longitudinal designs to clarify their role across developmental stages and clinical phenotypes.

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14. Piccolo A, Raciti C, Di Cara M, Portaro S, Muratore R, De Domenico C, Fulgenzi A, Settimo C, Quartarone A, Cucinotta F, Alito A. Motor Coordination Assessment in Autism Spectrum Disorder: A Systematic Review. Diagnostics (Basel). 2025; 15(17).

Background/Objectives: Motor difficulties are commonly reported in autistic individuals, but they are not currently part of the diagnostic criteria. A better understanding of how motor impairments are assessed in this population is critical to inform clinical practice and intervention. This systematic review aims to evaluate the existing literature on motor skill assessment in autistic children and adolescents, focusing specifically on studies that employed standardized and validated clinical motor assessment tools. Methods: Registered on PROSPERO (CRD42025637880), a systematic search was conducted on PubMed, Science Direct, and Web of Science until 31 December 2024. The review includes: (a) studies published in peer-reviewed journals; (b) randomized controlled trials (RCTs) and observational studies; (c) evaluations of motor difficulties using standardized and validated clinical assessments specifically designed to measure motor skills or coordination abilities; (d) participants diagnosed with ASD based on the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV or DSM-5) or the International Classification of Diseases (ICD-9 or ICD-10); and (e) participants aged ≤18 years; Results: Twenty-two studies met the inclusion criteria. Most studies reported significant motor impairments across various domains, including balance, manual dexterity, and coordination. However, there was substantial variability in the severity of motor deficits and in the assessment tools used. Methodological heterogeneity limited direct comparison across studies. Conclusions: Motor impairments are common in autistic children and adolescents; however, current assessment tools show limitations and require adaptations. The findings underscore the need for autism-specific motor assessments to improve diagnostic accuracy and guide personalized interventions.

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15. Shepelev MV, Skobel OI, Glazko TT, Popov DV, Vysotskii DE, Georgiev PG, Maksimenko OG, Kosovsky GY, Silaeva YY. WBSCR Locus: At the Crossroads of Human Behavioral Disorders and Domestication of Animals. Int J Mol Sci. 2025; 26(17).

Social interaction between the domesticated animal and the domesticator is one of the key features of the « domestication syndrome ». Recent research has identified genes in the WBSCR (Williams-Beuren syndrome control region) locus as significant contributors to social behavior in dogs. Large chromosomal deletions and duplications in the human WBSCR locus lead to the development of WBS (Williams-Beuren syndrome) and WBSCR duplication syndrome, respectively. Hypersociability is one of the key symptoms of WBS, while the duplication syndrome is manifested as an autism spectrum disorder (ASD). The data from both humans and dogs highlight the WBSCR locus as one of the key genetic determinants of social behavior in mammals. Several genes in the WBSCR are candidates for the regulation of social behavior in mammals including GTF2I, GTF2IRD, AUTS2 and GALNT17. Here, we discuss the role of WBSCR locus in the regulation of social behavior in mammals including the recent data that highlight the importance of 3D genome alterations in this genomic region for both domestication of animals and development of neurobehavioral disorders in humans. In addition, we bring attention to the role of the poorly characterized GALNT17 gene as a putative player in the development of ASD symptoms and in the regulation of social behavior in animals. We provide a brief summary of its known functions and propose the future research directions aimed at the elucidation of Galnt17 involvement in the regulation of central nervous system (CNS) functions.

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16. Shoesmith E, Stevens H, Gibsone S, Miles C, Beal H, Jennings K, Ratschen E. Maximising the Potential Benefit of Living with Companion Dogs for Autistic Children and Their Families: A Mixed-Methods Survey of the Impact of a Novel ‘Family Dog Service’. Animals (Basel). 2025; 15(17).

Background: Assistance dogs can support children with autism by improving emotional regulation and social functioning, but access is limited. The Family Dog Service was developed to help families of autistic children gain similar benefits through companion dogs. It offers tailored support for selecting, training, and integrating a dog into the home. This study explored parent perspectives on the service and perceived impacts of companion dogs. Methods: A cross-sectional online survey was conducted among UK residents who attended Family Dog Service workshops. The survey included demographic data, mental health and wellbeing measures, and questions about human-animal interactions. Quantitative data were analysed descriptively; qualitative responses underwent thematic analysis. Results: Of 118 participants, 101 (85.6%) owned a dog, while 17 (14.4%) were considering acquisition. Most owners reported improvements in their child’s mood (75.2%; n = 76) and reduced anxiety-related behaviours (70.3%, n = 71) following dog acquisition. Nearly half (49.5%, n = 50) rated the child-dog relationship as ‘very’ or ‘extremely’ positive within the first month, increasing to 86.1% (n = 87) by the time of data collection. Families also reported enhanced dynamics and reduced caregiver stress. Despite some challenges, the service was valued for its autism-specific guidance and ongoing support. Conclusions: The Family Dog Service may offer a practical, accessible alternative to assistance dogs, supporting autistic children’s wellbeing and strengthening family relationships through positive interactions between children and their dogs.

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17. Wang X, Pei C, He J, Xu J. A deep learning model for diagnosing autism using brain time series. Neuroscience. 2025; 583: 120-35.

The early identification of autism is especially critical as it can significantly enhance the effectiveness of intervention strategies. However, the recognition task remains challenging due to the subtle differences between ASD patients and neurotypical individuals. The presented approach leverages a hybrid model that combines Long Short-Term Memory (LSTM) networks with an Attention mechanism, enabling the extraction of both long-term and short-term features for more accurate autism diagnosis. Additionally, we integrate a residual block with channel Attention to enhance feature fusion and mitigate the risk of network degradation. Innovatively, we introduce a sliding window-based data preprocessing method alongside a voting strategy and validate the framework using subject-level 5-fold cross-validation to ensure generalizability across data splits. Our model was evaluated on the Region of Interest (ROI) time series dataset from the Autism Brain Imaging Data Exchange (ABIDE), achieving 73.1 % accuracy on the DOS brain atlas and 81.1 % on the HO brain atlas-outperforming baseline models. Moreover, we constructed brain functional connectivity topological structures for both ASD patients and healthy individuals, providing valuable resources for future autism research.

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