Social Communication Behaviors Research Articles

A novel USP51 variant in a patient with autism spectrum disorder and epilepsy

Abstract Background Autism spectrum disorder (ASD) is a highly heritable neurodevelopmental disorder characterized by impaired social communication and repetitive behaviours. The genetic basis of ASD is complex and involves both rare variants with large effect sizes and common variants with small effect sizes. Case presentation This case report describes a 19-year-old male with ASD, intellectual disability, absent speech, and epilepsy. Molecular testing revealed a novel maternally inherited variant in the USP51 gene, which encodes Ubiquitin Specific Peptidase 51, a deubiquitinating enzyme involved in the DNA damage response. Conclusions Based on current knowledge, the variant is predicted to result in a truncated protein and is considered a variant of uncertain significance (VUS). The USP51 gene has been implicated in neurodevelopment, and its role in the developing brain suggests its potential relevance to ASD. Further studies are needed to establish the association of USP51 variants with ASD and elucidate the full phenotypic spectrum associated with these variants.

Beyond Breeding: Re-Interpreting Paradigms in Domestic Dog Aggression Research

Pet dog aggression is a research theme of extreme importance since, today more than ever, caretakers have the motivation and interest to better understand and relate to their dogs. However, most of the literature exploring this theme focuses on biased views of breeding, behaviour profiles and aggression itself. That way, many studies regarding incident predictability end in the same pitfall of standardizing aggression by a single factor, like breed, instead of approaching other important factors beyond genetics and learning. In this essay, we propose a new approach to understand aggression in dogs, taking from non-dichotomous and non-urban-western views. Regarding the animal as complex developing systems, that are always shaping and being shaped by its surrounding environment. With said approach, factors such as skull morphology, size, weight, caretaker relationship and culture, should be further incorporated in research for a deeper understanding of dog aggression as a social communicative behaviour.

A comprehensive narrative review on psychotherapies for patients with autism spectrum disorders

Autism spectrum disorders (ASD) are complex neurodevelopmental conditions characterized by challenges in social interaction, communication, and repetitive behaviors. Psychotherapeutic interventions must tailor to meet the specific needs of individuals with ASD, given their diverse presentation of symptoms and functioning levels. This narrative review explores the range of psychotherapies available for individuals with ASD, examining their methodologies, effectiveness, and suitability. By using targeted search terms such as “autism,” “autistic disorder,” “autism spectrum disorders,” “psychotherapy,” “psychological intervention,” and “psychosocial intervention,” an extensive review of publications in English from 2000 to 2024 was conducted. This review covered several databases, including Embase, PubMed, Web of Science, Scopus, Cochrane Library, and Google Scholar. The review identified ten major psychological interventions for the treatment of individuals with ASD: behavioral therapies, developmental therapies, cognitive behavioral therapy, social skills training, speech-language therapy, occupational therapy, family therapy, mindfulness-based interventions, parent-mediated interventions, and dance movement psychotherapy. The main text elaborates on the effects of each intervention on various aspects of ASD. By providing this comprehensive overview, clinicians can select appropriate therapeutic strategies that cater to the individual profiles of those with ASD, ultimately enhancing therapeutic outcomes and quality of life for this population.

Technology-Based Interventions for Autism Spectrum Disorder: A Systematic Review

Introduction: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. Its prevalence has steadily increased, with the CDC reporting a rise from 1 in 100 children in 2006 to 1 in 44 in the United States by 2021. ASD manifests in a spectrum of symptoms, requiring tailored interventions to address each child's unique needs. Recent advancements in technology have shown promise in aiding children with ASD, particularly through robotics and socially assistive robots (SARs). This systematic review explores the impact of technology-based interventions on children with ASD, assessing their efficacy in enhancing social skills, communication, and behavior regulation. Methodology: This review followed PRISMA guidelines, screening 46,580 articles across databases such as PubMed, Cochrane, Science Direct, Google Scholar, and PsychInfo. After applying inclusion and exclusion criteria, 254 studies were selected for in-depth review. The review focused on technology-based interventions, including robotics and socially assistive robots, with MeSH terms such as "Technology," "Artificial Intelligence," "Autism Spectrum Disorder," and "ASD." Results: Technology-based interventions, particularly SARs, demonstrated significant improvements in social interaction, emotional regulation, and communication for children with ASD. Robots such as LEGO Mindstorms and "Kaspar" were effective in enhancing eye contact, cooperation, and emotional recognition. However, results varied depending on the type of technology used, study design, and participant characteristics. Conclusion: While technology-based interventions hold promise for children with ASD, further research is needed to standardize intervention protocols, dosage, and long-term outcomes. These tools offer a non-invasive, scalable solution for enhancing social and cognitive skills, but variability in study designs limits definitive conclusions. Keywords: Autism Spectrum Disorder, Technology, Robotics, Socially Assistive Robots, Communication, Cognitive Skills, Applied Behavioral Analysis

Coinfection of pulmonary lophomoniasis, tuberculosis, and hydatid cyst in a pediatric autism patient: a case report and literature review

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental condition marked by difficulties in social interaction, communication, and repetitive behaviors or restricted interests. Although research on the link between ASD and parasitic diseases is limited, immune deficiency and inflammation may contribute to the development of parasitic infections.Case reportWe admitted a 14-year-old boy to the hospital who had a known history of ASD because he was presenting with respiratory symptoms, including cough and hemoptysis. During his time in the hospital, after conducting a series of tests and evaluations, we made a critical diagnosis of co-infection of lophomonas, tuberculosis, and hydatid cyst. In response to this diagnosis, we initiated a treatment plan that involved administering appropriate antibiotics as well as preparing for surgical intervention.ConclusionThis case report highlights the complexities and challenges of managing such a rare combination of co-infections with TB, pulmonary hydatid disease and lophomonas in a pediatric patient with underlying developmental considerations such as ASD.

Proposed Hypothesis of TWEAK/Fn14 Receptor Modulation in Autism Spectrum Disorder.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with a complex, multiple etiology that is marked by impaired social interaction, communication, and repetitive behaviour. There is presently no pharmaceutical treatment for the core symptoms of ASD, even though the prevalence of ASD is increasing worldwide. Treatment of autism spectrum disorder involves the interaction of numerous signalling pathways, such as the Wnt/beta-catenin pathway, probiotics and kynurenine pathway, PPAR pathway, PI3K-AKT-mTOR pathway, Hedgehog signaling pathway, etc. The scientific literature has revealed TWEAK/Fn14 to not be explored in the autism spectrum disorder. In vitro and in vivo, TWEAK can control a wide range of cellular responses. Recent research has revealed that TWEAK and Fn14 are expressed in the Central Nervous System (CNS) and upregulated in perivascular endothelial cells, astrocytes, neurons, and microglia in response to various stimuli, including cerebral ischemia. This upregulation is followed by cell death and an increase in Blood-brain Barrier (BBB) permeability. The study has revealed that Aurintricarboxylic Acid (ATA) acts as an agent that suppresses TWEAK/Fn14 signaling. Similarly, from the discussion, it has been emphasized that the proposed molecular TWEAK/Fn14 signalling pathway can be considered as a therapeutic approach in the management of autism spectrum disorder.

Genome Sequencing Identifies 13 Novel Candidate Risk Genes for Autism Spectrum Disorder in a Qatari Cohort.

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social communication, restricted interests, and repetitive behaviors. Despite considerable research efforts, the genetic complexity of ASD remains poorly understood, complicating diagnosis and treatment, especially in the Arab population, with its genetic diversity linked to migration, tribal structures, and high consanguinity. To address the scarcity of ASD genetic data in the Middle East, we conducted genome sequencing (GS) on 50 ASD subjects and their unaffected parents. Our analysis revealed 37 single-nucleotide variants from 36 candidate genes and over 200 CGG repeats in the FMR1 gene in one subject. The identified variants were classified as uncertain, likely pathogenic, or pathogenic based on in-silico algorithms and ACMG criteria. Notably, 52% of the identified variants were homozygous, indicating a recessive genetic architecture to ASD in this population. This finding underscores the significant impact of high consanguinity within the Qatari population, which could be utilized in genetic counseling/screening program in Qatar. We also discovered single nucleotide variants in 13 novel genes not previously associated with ASD: ARSF, BAHD1, CHST7, CUL2, FRMPD3, KCNC4, LFNG, RGS4, RNF133, SCRN2, SLC12A8, USP24, and ZNF746. Our investigation categorized the candidate genes into seven groups, highlighting their roles in cognitive development, including the ubiquitin pathway, transcription factors, solute carriers, kinases, glutamate receptors, chromatin remodelers, and ion channels.

Soluble form of Lingo2, an autism spectrum disorder-associated molecule, functions as an excitatory synapse organizer in neurons

Autism Spectrum Disorder (ASD) is a developmental disorder characterized by impaired social communication and repetitive behaviors. In recent years, a pharmacological mouse model of ASD involving maternal administration of valproic acid (VPA) has become widely used. Newborn pups in this model show an abnormal balance between excitatory and inhibitory (E/I) signaling in neurons and exhibit ASD-like behavior. However, the molecular basis of this model and its implications for the pathogenesis of ASD in humans remain unknown. Using quantitative secretome analysis, we found that the level of leucine-rich repeat and immunoglobulin domain-containing protein 2 (Lingo2) was upregulated in the conditioned medium of VPA model neurons. This upregulation was associated with excitatory synaptic organizer activity. The secreted form of the extracellular domain of Lingo2 (sLingo2) is produced by the transmembrane metalloprotease ADAM10 through proteolytic processing. sLingo2 was found to induce the formation of excitatory synapses in both mouse and human neurons, and treatment with sLingo2 resulted in an increased frequency of miniature excitatory postsynaptic currents in human neurons. These findings suggest that sLingo2 is an excitatory synapse organizer involved in ASD, and further understanding of the mechanisms by which sLingo2 induces excitatory synaptogenesis is expected to advance our understanding of the pathogenesis of ASD.

Transforming lives in autism spectrum disorder treatment through acupuncture: A case report

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication, restricted and repetitive behaviors, and narrow interests. Given the high prevalence of ASD and the lack of specific pharmacological treatments, there is a pressing need for alternative therapeutic approaches. Acupuncture has shown promise in improving the clinical symptoms of ASD. This report presents the case of a 6-year-old girl diagnosed with ASD, intellectual developmental disorder, attention deficit hyperactivity disorder, and articulation disorder. She underwent Liu’s pediatric neurological rehabilitation acupuncture therapy (PNRAT) for over 2 years. The treatment involved specific scalp acupuncture techniques targeting cognitive and linguistic rehabilitation. After the treatment course, the patient showed significant improvements in cognitive, linguistic, social, and behavioral symptoms, transitioning from limited verbal communication and marked social difficulties to thriving in a mainstream school setting. This case highlights the potential of Liu’s PNRAT as an effective intervention for ASD. The observed improvements suggest that acupuncture may offer valuable therapeutic benefits for children with ASD, contributing to the growing interest in its potential as an adjunct therapy. Further research is needed to optimize treatment protocols and explore synergies with conventional therapies.

Feasibility and Acceptability of a Self-Guided Digital Family Skills Management Intervention for Children Newly Diagnosed With Type 1 Diabetes: Pilot Randomized Controlled Trial.

Family dynamics play an important role in determining the glycemic outcomes of type 1 diabetes (T1D) in children. The time interval immediately following T1D diagnosis is particularly stressful for families, and interventions to support families in adjusting their family practices to support adjustment to and management of T1D in the months following diagnosis may improve glycemic outcomes. Self-guided digital interventions offer a sustainable model for interventions to support caregivers in learning evidence-based family management skills for adjustment to and management of T1D. We hypothesized that a self-guided, web-based, family skills management program (addressing caregiver social support as well as family problem-solving, communication, and supportive behavior change strategies) initiated at the time of T1D diagnosis would improve glycemic outcomes in children with T1D. In this study, we report on the feasibility and acceptability of this program. We prospectively evaluated a sample of 37 children newly diagnosed with T1D recruited from a pediatric endocrinology clinic. Parent participants were asked to complete web-based modules addressing social support, family problem-solving, communication, and supportive behavior change strategies. Module completion was analyzed for percentage completion, patterns of completion, and differences in completion rates by coparenting status. Qualitative open-ended feedback was collected at the completion of each module. A total of 31 (84%) of the 37 participants initiated the web-based program. Of those 31 participants, 25 (81%) completed some content and 15 (48%) completed all 5 modules. Completion rates were higher when coparenting partners engaged in the intervention together (P=.04). Of the 18 participants given a choice about the spacing of content delivery, 15 (83%) chose to have all sessions delivered at once and 3 (17%) chose to space sessions out at 2-week intervals. Qualitative feedback supported the acceptability of the program for delivery soon after T1D diagnosis. Families reported on positive benefits, including requesting future access to the program and describing helpful changes in personal or family processes for managing T1D. In this study, we found that a self-guided digital family support intervention initiated at the time of a child's T1D diagnosis was largely feasible and acceptable. Overall, rates of participation and module completion were similar to or higher than other self-guided digital prevention interventions for mental and physical health outcomes. Self-guided digital programs addressing family management skills may help prevent challenges common with T1D management and can decrease cost, increase access, and add flexibility compared to traditional interventions. ClinicalTrials.gov NCT03720912; https://clinicaltrials.gov/study/NCT03720912.

Bayesian optimization of one-dimensional convolutional neural networks (1D CNN) for early diagnosis of Autistic Spectrum Disorder

Autistic Spectrum Disorder (ASD) is a challenging neurological development disorder, which involves poor social interaction, communication, and repetitive behaviours. If autism is identified early enough it can be treated with better outcomes but present diagnostic tests are dependent on subjective opinion, consume a lot of time, and are vague. This study is aimed at optimizing one-dimensional convolutional neural networks (1D CNN) to improve the precision and speed of early ASD diagnosis. Four ASD datasets representing different age groups — toddlers, children, adolescents, and adults were modelled using one-dimensional convolutional neural networks (1D CNN). These datasets are accessible to the public on the UCI Machine Learning Repository and Kaggle, they consist of behavioural features relevant to ASD diagnosis. Each dataset underwent feature selection, categorical encoding, and missing value handling. Then, baseline 1D CNN with predefined hyperparameters was modelled on each of the datasets. Subsequently, the baseline models were optimized using the Tree-structured Parzen Estimator (TPE). An interactive web-based ASD diagnostic tool was developed, where user inputs are processed through age-specific pre-trained optimized models to determine ASD probability. The optimized 1D CNN models significantly outperformed the baseline models across all age groups and achieved scores of 100% in accuracy, precision, recall, F1-score, MCC, and AUC ROC. This implies that the optimized models can reliably identify people in various age groups who have and do not have ASD. The development of an interactive web-based diagnostic tool extends the practical utility of the models, making them accessible for clinical and at-home use.

ASD or OCD? An evidence‐based differentiation of repetitive behaviors

While distinct diagnoses, the behavioral presentation of ritualistic/repetitive behaviors seen in obsessive compulsive disorder (OCD) and autism spectrum disorder (ASD) can present similarly. This results in difficulty with accurate diagnosis and implementation of evidence‐based treatments. OCD is characterized by prolonged and recurrent unwanted thoughts, known as obsessions, which cause a feeling of intense anxiety or distress. As a result, people with OCD perform repetitive behaviors known as compulsions to help alleviate distress. ASD is characterized as a developmental disorder causing persistent challenges associated with social communication, restricted and repetitive behaviors (RRB), and impairment in functioning. While the definitions are distinct, accurate conceptualization is not always clear. The picture can become even more complex with comorbidities. To parse these behaviors apart, we can consider the course of the behavior and assess the function. With better ability to differentiate, we can have a clearer picture of how to support the youth and family.

Characterization and phylogenetic analysis of vomeronasal receptors in the female muskrat (Ondatra zibethicus)

Vomeronasal receptors (VRs) play a crucial role in recognizing pheromones, which are essential for social chemical communication. The male muskrat (Ondatra zibethicus) secretes musk, which contains pheromones as a reproductive signal, and the female can recognize it through the VNO to mediate social communication behavior. This study aimed to identify the genomic information of VRs (OzVRs) in the female muskrat and elucidate their physicochemical properties and evolutionary relationship. Six predominantly expressed OzVR genes were identified using the RACE technique, and a comprehensive analysis was conducted on their gene structure, subcellular distribution, functional predictions, and mRNA levels, revealed that all OzVRs were transmembrane proteins. Phylogenetic analysis clustered OzVR genes into two clades (V1Rs: OzV1R21, OzV1R81, OzV1R105; V2Rs: OzV2R33, OzV2R44, OzV2R60). Physiochemically, OzV1Rs were basic proteins, while OzV2Rs exhibited weakly acidic character. Among them, OzV1R81 and OzV2R44 were identified as hydrophobicitystable proteins, with the remainder categorized as hydrophobicity-unstable proteins. Promoters analysis revealed the involvement of transcription factors and complexes, including Ahr::Arnt, Runx1, Arnt, and TFAP2A, in regulating the expression of the OzVR genes. Conserved domain and motif analyses demonstrated a high conservation of the VRs superfamily in rodents, with many conserved domains linked to pheromone binding. Functional predictions confirmed that OzVRs were associated with pheromones detection. Finally, the expression patterns of OzVR genes in different tissues and seasons indicated that OzVRs have the highest level of expression in the vomeronasal organ, and OzV1Rs notably higher in the breeding season than that in the non-breeding season, however the expression levels of OzV2Rs were higher in the non-breeding season. This study provided insights into the phylogenetic relationships, gene structure, physicochemical properties, promoter binding sites, functions and gene expression patterns of OzVRs, offering a theoretical reference for further examination of VR gene functions and a foundation for understanding chemical signaling mechanisms in the muskrat.

Exploring the Mechanisms of Neuronal Protection by Glial Cell Line-Derived Neurotrophic Factor in Autism Spectrum Disorder.

A complicated neurological disease known as autism spectrum disorder (ASD) is typified by issues with social interaction, communication, and repetitive behavior. The neural protective mechanisms in ASD are thought to be influenced by genetic variables, including the expression of neurotrophic genes such as glial cell line-derived neurotrophic factor (GDNF). The aim was to examine the relationship between neuronal protection and cognitive functioning by crosslinking GDNF gene expression and serum levels in individuals with relation to Mini-Mental State Examination (MMSE) scores in ASD patients. After getting study approval and informed consent of patients, this case-control study experimental study was conducted for six months between July 2023 and December 2023. The blood samples (5 ml each) were drawn from the study population (n = 140), including 100 ASD patients with a disease course of30 months based on patients' reports data and 40 healthy controls from four major clinical and hospital settings in Lahore, Karachi, and Bahawalpur from Pakistan. The analytical procedures included nucleic acid extraction, primer design and optimization, and GDNF-targeted real-time quantitative polymerase chain reaction expression analysis. To measure cognitive and behavioral deficits, enzyme-linked immunosorbent assay-based serum GDNF levels (pg/ml) and MMSE scores were compared, concluding the neuronal protection potential of GDNF. In patients with ASD, lower serum levels of GDNF (9.371 ± 2.388 pg/ml) were linked to more severe behavioral and cognitive deficits confirmed by MMSE scores (13.6 ± 3.5) of ASD patients in comparison with the control group (27.1 ± 2.1). Healthy individuals showed higher relative gene fold expression (11.71) compared to the ASD patients (5.51). There is a notable decrease in GDNF gene expression in people with ASD, which raises the possibility that GDNF is important for both cognitive performance and neuronal protection in these people. GDNF may be a useful biomarker for identifying ASD and comprehending its molecular causes, opening the door for focused treatment approaches.

Sexuality and Gender Issues in Autistic Youth: A Series of 6 Cases and a Literature Review

Autism Spectrum Disorder (ASD) involves challenges in social communication and repetitive behaviors, impacting daily functioning. Individuals with ASD face unique difficulties regarding sexuality, often experiencing mismatches between sexual development and social maturity, leading to potential inappropriate behaviors. Social competence deficits may limit their understanding of sexuality, increasing risks of offending or victimization. Gender differences in sexual behavior are evident, with males showing earlier and more frequent sexual activity, while females demonstrate greater flexibility in sexual orientation. This paper presents six clinical cases highlighting the diverse experiences of sexuality and gender identity in autistic individuals, offering insights into the complex interactions between ASD, gender, and sexual behavior.

Transforming the future of nursing care: Artificial intelligence in pediatrics autism nursing care

The advent of artificial intelligence (AI) is revolutionizing various fields, including healthcare. AI's impact is increasingly evident in managing and caring for autistic pediatric patients [1]. The integration of AI into pediatrics autism nursing care is revolutionizing the approach to diagnosis, treatment, and ongoing management of children with autism spectrum disorder (ASD). Through their capacity to process and analyze vast amounts of data, AI technologies offer new possibilities for enhancing the precision, efficiency, and personalization of care for children with autism. ASD presents unique challenges that require specialized, often intensive, care strategies. According to Zhao et al., (2024), integrating AI into nursing care for children with autism offers promising opportunities to enhance diagnostics, personalize treatment plans, and improve overall patient outcomes [2]. This commentary explores how AI is transforming pediatric autism nursing care and the vital role nurses play in this evolving landscape. ASD is a developmental disorder characterized by challenges with social interaction, communication, and repetitive behaviors. Symptoms and their severity vary widely among individuals, making ASD a spectrum disorder. Research indicates that early diagnosis and intervention are crucial for improving outcomes, yet these can be difficult due to the complex and varied presentation of the disorder [3].

Study protocol of a randomized control trial on the effectiveness of improvisational music therapy for autistic children.

Music therapy is the clinical use of musical interventions to improve mental and physical health across multiple domains, including social communication. Autistic children, who have difficulties in social communication and often increased anxiety, tend to show a strong preference for music, because it can be structured and systematic, and therefore more predictable than social interaction. This makes music therapy a promising medium for therapeutic support and intervention. Previous clinical trials of music therapy compared to traditional therapy for autistic children have shown encouraging but nevertheless mixed results. The primary aim is to conduct a randomised controlled trial (RCT) of improvisational music therapy for autistic children and test its effectiveness in at improving social communication and wellbeing, and to reduce anxiety. The RCT will be conducted with 200 autistic children in the UK aged 7 to 11 years old. Participants will be randomly assigned to either improvisational music therapy or support as usual. The trial will be an assessor-blind, pragmatic two-arm cluster RCT comparing the impact of 12-weeks of improvisational music therapy in addition to support as usual, vs. support as usual for autistic children. Researchers who are blind to which arm the children are in will conduct assessments and obtain data via caregiver reports. The primary outcome will be the absolute change in the total score of the Brief Observation of Social Communication Change (BOSCC) assessed at baseline, T1 (13weeks) and T2 (39weeks) follow-ups. The BOSCC consists of specific items that were developed to identify changes in social-communication behaviours. Secondary outcome measures include: (1) Parent reported anxiety scale for youth with ASD (Note that we do not use the term 'ASD' or Autism Spectrum Disorder, because many autistic people feel it is stigmatising. Instead, we use the term 'autism')(PRAS-ASD) (2) Young Child Outcome Rating Scale, for wellbeing (YCORS), (3) Strengths and Difficulties Questionnaire (SDQ); and (4) Vineland Adaptive Behaviour Scale (VABS). (5) The Children's Communication Checklist-2 (CCC-2) will be completed to evaluate pragmatic speech with fluent speakers only; (6) The Music Engagement Scale (MES); and (7) Assessment of the Quality of Relationship (AQR) will be used to evaluate the child-therapist relationships using video-analysis of music therapy sessions. Additional data will be collected by administering the Wechsler Abbreviated Scale of Intelligence (WASI-II), Music at Home Questionnaire (M@H), and children's versions of the Empathy Quotient (EQ) and Systemizing Quotient (SQ). Audio and video data from the therapy sessions will be collected and analysed (using both human and computer-based feature-coding, e.g., machine learning and AI-driven methods) to identify how music and non-musical interactions foster change throughout the therapy. This study aims to observe if the interactions, engagement, and therapeutic modalities fostered during music therapy sessions can translate to non-musical contexts and improve autistic children's social communication skills, identifying possible mediating factors contributing to the effectiveness of music therapy, potentially informing policy making and governance. This randomised control trial is registered with the NIH U.S. National Library of Medicine: https://clinicaltrials.gov/search?term=NCT06016621 , clinicalTrials.gov Identifier: NCT0601662, Registration Date 19th August 2023.

Unveiling the role of IGF1R in autism spectrum disorder: a multi-omics approach to decipher common pathogenic mechanisms in the IGF signaling pathway.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition marked by impairments in social interaction, communication, and repetitive behaviors. Emerging evidence suggests that the insulin-like growth factor (IGF) signaling pathway plays a critical role in ASD pathogenesis; however, the precise pathogenic mechanisms remain elusive. This study utilizes multi-omics approaches to investigate the pathogenic mechanisms of ASD susceptibility genes within the IGF pathway. Whole-exome sequencing (WES) revealed a significant enrichment of rare variants in key IGF signaling components, particularly the IGF receptor 1 (IGF1R), in a cohort of Chinese Han individuals diagnosed with ASD, as well as in ASD patients from the SFARI SPARK WES database. Subsequent single-cell RNA sequencing (scRNA-seq) of cortical tissues from children with ASD demonstrated elevated expression of IGF receptors in parvalbumin (PV) interneurons, suggesting a substantial impact on their development. Notably, IGF1R appears to mediate the effects of IGF2R on these neurons. Additionally, transcriptomic analysis of brain organoids derived from ASD patients indicated a significant association between IGF1R and ASD. Protein-protein interaction (PPI) and gene regulatory network (GRN) analyses further identified ASD susceptibility genes that interact with and regulate IGF1R expression. In conclusion, IGF1R emerges as a central node within the IGF signaling pathway, representing a potential common pathogenic mechanism and therapeutic target for ASD. These findings highlight the need for further investigation into the modulation of this pathway as a strategy for ASD intervention.

Harmonizing Insights: LR-FFT Feature Extraction for Alzheimer’s and Autism Spectrum Disorder Detection in EEG Signals

Alzheimer’s Disease (AD) and Autism Spectrum Disorder (ASD) represent two distinct but equally impactful challenges in the field of neurology and cognitive health. AD is a degenerative neurological condition characterized by its progressive nature, typically affecting individuals in later stages of life. The hallmark features include cognitive impairment, mem- ory deterioration, and alterations in behavior. In contrast, ASD is a developmental disorder typically diagnosed in childhood, marked by difficulties in social interaction, communication, and repetitive behaviors. This paper explores the potential of the time-frequency feature extraction model known as the Left-Right Fast Fourier Transform (LR-FFT) in the context of these two disorders. While AD and ASD differ significantly in their onset, presentation, and demographic affected, both necessitate early and accurate diagnosis to enable timely intervention and tailored treatment strategies. Our research yields promising results, with classification accuracies reaching 88.26% for AD and 99.86% for ASD, demonstrating the LR-FFT’s potential to enhance diagnostic accuracy. By contributing to improved differentiation between these complex neurological conditions, this work aims to advance our understanding and management of AD and ASD, ultimately benefiting patients, their families, and healthcare practitioners.

Widespread Associations between Behavioral Metrics and Brain Microstructure in ASD.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and repetitive behaviors. A diagnosis of ASD is provided by a clinician following cognitive and behavioral evaluations, but there is currently no biomarker associating these metrics with neurological changes. Our lab has previously found that g-ratio, the proportion of axon width to myelin diameter, and axonal conduction velocity, which is associated with the capacity of an axon to carry information, are both decreased in ASD individuals. By associating these differences with performance on cognitive and behavioral tests, we can evaluate which tests most reveal changes in the brain. Analyzing 273 participants (148 with ASD) ages 8-to-17 (49% female) through an NIH-sponsored Autism Centers of Excellence (ACE) network (Grant#: MH100028), we observe widespread associations between behavioral and cognitive evaluations of autism and between behavioral and microstructural metrics. Analyzing data from all participants, conduction velocity but not g-ratio was significantly associated with many behavioral metrics. However, this pattern was reversed when looking solely at ASD participants. This reversal may suggest that the mechanism underlying differences between autistic and non-autistic individuals may be distinct from the mechanism underlying ASD behavioral severity. Two additional machine learning cluster analyses applied to neuroimaging data reinforce the association between neuroimaging and behavioral metrics and suggest that age-related maturation of brain metrics may drive changes in ASD behavior. By associating neuroimaging metrics with ASD, it may be possible to measure and identify individuals at high risk of ASD before behavioral tests can detect them.