1. Altschuler MR, Faja S. Brief Report: Test-Retest Reliability of Cognitive, Affective, and Spontaneous Theory of Mind Tasks Among School-Aged Children with Autism Spectrum Disorder. Journal of autism and developmental disorders. 2022; 52(4): 1890-5.

The present study evaluates the test-retest reliability of six theory of mind (ToM) tasks that measured cognitive, affective, and spontaneous ToM in 7 to 11 year-old children with autism spectrum disorder. Our results revealed considerable variation in test-retest reliability depending on the type of ToM task, which ranged from poor to good with the majority of the measures exhibiting moderate reliability. Results inform which common measures of cognitive ToM should be selected versus avoided in future intervention work, suggest our measure of spontaneous ToM should be used more widely in intervention and ToM research more broadly, and indicate more work is needed to develop reliable measures of affective ToM. Implications for research and clinical practice are discussed.

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2. Chaudhary R, Agarwal V, Kaushik AS, Rehman M. Involvement of myocyte enhancer factor 2c in the pathogenesis of autism spectrum disorder. Heliyon. 2021; 7(4): e06854.

Myocyte enhancer factor 2 (MEF2), a family of transcription factor of MADS (minichromosome maintenance 1, agamous, deficiens and serum response factor)-box family needed in the growth and differentiation of a variety of human cells, such as neural, immune, endothelial, and muscles. As per existing literature, MEF2 transcription factors have also been associated with synaptic plasticity, the developmental mechanisms governing memory and learning, and several neurologic conditions, like autism spectrum disorders (ASDs). Recent genomic findings have ascertained a link between MEF2 defects, particularly in the MEF2C isoform and the ASD. In this review, we summarized a concise overview of the general regulation, structure and functional roles of the MEF2C transcription factor. We further outlined the potential role of MEF2C as a risk factor for various neurodevelopmental disorders, such as ASD, MEF2C Haploinsufficiency Syndrome and Fragile X syndrome.

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3. Farhat LC, Brentani H, de Toledo VHC, Shephard E, Mattos P, Baron-Cohen S, Thapar A, Casella E, Polanczyk GV. ADHD and autism symptoms in youth: a network analysis. Journal of child psychology and psychiatry, and allied disciplines. 2022; 63(2): 143-51.

BACKGROUND: Previous research investigating the overlap between attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (henceforth, autism) symptoms in population samples have relied on latent variable modeling in which averaged scores representing dimensions were derived from observed symptoms. There are no studies evaluating how ADHD and autism symptoms interact at the level of individual symptom items. METHODS: We aimed to address this gap by performing a network analysis on data from a school survey of children aged 6-17 years old (N = 7,405). ADHD and autism symptoms were measured via parent-report on the Swanson, Nolan, Pelham-IV questionnaire and the Childhood Autism Spectrum test, respectively. RESULTS: A relatively low interconnectivity between ADHD and autism symptoms was found with only 10.06% of possible connections (edges) between one ADHD and one autism symptoms different than zero. Associations between ADHD and autism symptoms were significantly weaker than those between two symptoms pertaining to the same construct. Select ADHD symptoms, particularly those presenting in social contexts (e.g. ‘talks excessively’, ‘does not wait turn’), showed moderate-to-strong associations with autism symptoms, but some were considered redundant to autism symptoms. CONCLUSIONS: The present findings indicate that individual ADHD and autism symptoms are largely segregated in accordance with diagnostic boundaries corresponding to these conditions in children and adolescents from the community. These findings could improve our clinical conceptualization of ADHD and autism and guide advancements in diagnosis and treatment.

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4. Guan J, Blanchard A, DiGuiseppi CG, Chihuri S, Li G. Homicide Incidents Involving Children with Autism Spectrum Disorder as Victims Reported in the US News Media, 2000-2019. Journal of autism and developmental disorders. 2022; 52(4): 1673-7.

Recent research indicates that children with autism are at increased risk of maltreatment. We examined news media reports on homicide incidents involving children with autism as victims in the United States between 2000 and 2019. Of the 52 victims studied, 47 (90.4%) were male. Age of victims ranged from 2 to 20 years (mean = 10.4 ± 5.3 years). Parents and other caregivers accounted for 63.5% and 13.5% of the perpetrators, respectively. The leading injury mechanism was gunshot wounds (23.1%), followed by drowning (19.2%), and suffocation, strangulation, or asphyxiation (19.2%). The most commonly cited contributing factor (47.1%) was overwhelming stress from caring for the autistic child. These results underscore the importance of supporting services for caregivers of children with autism.

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5. Haque MM, Rabbani M, Dipal DD, Zarif MII, Iqbal A, Schwichtenberg A, Bansal N, Soron TR, Ahmed SI, Ahamed SI. Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach. JMIR medical informatics. 2021; 9(6): e29242.

BACKGROUND: Care for children with autism spectrum disorder (ASD) can be challenging for families and medical care systems. This is especially true in low- and- middle-income countries such as Bangladesh. To improve family-practitioner communication and developmental monitoring of children with ASD, mCARE (Mobile-Based Care for Children with Autism Spectrum Disorder Using Remote Experience Sampling Method) was developed. Within this study, mCARE was used to track child milestone achievement and family sociodemographic assets to inform mCARE feasibility/scalability and family asset-informed practitioner recommendations. OBJECTIVE: The objectives of this paper are threefold. First, it documents how mCARE can be used to monitor child milestone achievement. Second, it demonstrates how advanced machine learning models can inform our understanding of milestone achievement in children with ASD. Third, it describes family/child sociodemographic factors that are associated with earlier milestone achievement in children with ASD (across 5 machine learning models). METHODS: Using mCARE-collected data, this study assessed milestone achievement in 300 children with ASD from Bangladesh. In this study, we used 4 supervised machine learning algorithms (decision tree, logistic regression, K-nearest neighbor [KNN], and artificial neural network [ANN]) and 1 unsupervised machine learning algorithm (K-means clustering) to build models of milestone achievement based on family/child sociodemographic details. For analyses, the sample was randomly divided in half to train the machine learning models and then their accuracy was estimated based on the other half of the sample. Each model was specified for the following milestones: Brushes teeth, Asks to use the toilet, Urinates in the toilet or potty, and Buttons large buttons. RESULTS: This study aimed to find a suitable machine learning algorithm for milestone prediction/achievement for children with ASD using family/child sociodemographic characteristics. For Brushes teeth, the 3 supervised machine learning models met or exceeded an accuracy of 95% with logistic regression, KNN, and ANN as the most robust sociodemographic predictors. For Asks to use toilet, 84.00% accuracy was achieved with the KNN and ANN models. For these models, the family sociodemographic predictors of « family expenditure » and « parents’ age » accounted for most of the model variability. The last 2 parameters, Urinates in toilet or potty and Buttons large buttons, had an accuracy of 91.00% and 76.00%, respectively, in ANN. Overall, the ANN had a higher accuracy (above ~80% on average) among the other algorithms for all the parameters. Across the models and milestones, « family expenditure, » « family size/type, » « living places, » and « parent’s age and occupation » were the most influential family/child sociodemographic factors. CONCLUSIONS: mCARE was successfully deployed in a low- and middle-income country (ie, Bangladesh), providing parents and care practitioners a mechanism to share detailed information on child milestones achievement. Using advanced modeling techniques this study demonstrates how family/child sociodemographic elements can inform child milestone achievement. Specifically, families with fewer sociodemographic resources reported later milestone attainment. Developmental science theories highlight how family/systems can directly influence child development and this study provides a clear link between family resources and child developmental progress. Clinical implications for this work could include supporting the larger family system to improve child milestone achievement.

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6. Korneder J, Louie WG, Pawluk CM, Abbas I, Brys M, Rooney F. Robot-mediated interventions for teaching children with ASD: a new intraverbal skill. Assistive technology : the official journal of RESNA. 2021: 1-10.

Socially assistive robots (SAR) have the potential to impact therapies for Autism Spectrum Disorder (ASD) by supporting clinicians in increasing learning opportunities presented to individuals. Recent research on robot-mediated intervention (RMI) delivery has predominantly addressed social deficits in ASD with positive outcomes. Current literature has minimal focus on teaching children with ASD a skill not known apriori by the individual. Furthermore, it is unclear how to integrate robots in clinical settings because current RMIs do not adhere to Applied Behavior Analysis (ABA) protocols. In this work, we investigated whether an RMI could be utilized to teach children with ASD a completely new language and communication skill they could not exhibit at baseline. We utilized a standard ABA assessment tool to first identify appropriate skills to teach children with ASD. We then developed, implemented, and evaluated an RMI intervention that followed standard clinical operating procedures in ABA and targets participants’ unique skill deficits. We examined the effects of the RMI training on teaching wh-question answering. All sessions were conducted with the SAR as the primary therapist using evidenced-based ABA human teaching protocols. All participants acquired the wh-questions answering skill within seven sessions, which is in line with their typical acquisition rates.

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7. LeGrand KJ, Weil LW, Lord C, Luyster RJ. Identifying Childhood Expressive Language Features That Best Predict Adult Language and Communication Outcome in Individuals With Autism Spectrum Disorder. Journal of speech, language, and hearing research : JSLHR. 2021; 64(6): 1977-91.

Purpose Several studies have reported that « useful speech » at 5 years of age predicts outcomes in individuals with autism spectrum disorder (ASD), but this skill has been vaguely defined. This study investigates which specific aspects of expressive language in children with ASD best predict adult language and communication outcomes. Method Language samples from 29 children (ages 47-72 months) enrolled in a longitudinal project (e.g., Lord et al., 2006) were transcribed and coded for spoken language features. Hierarchical linear regression was used to compare the following childhood variables as predictors of adult language and communication outcomes: noun diversity, verb diversity, mean length of utterance, and proportion of utterances that were socially motivated. Results Childhood verb diversity was a value-added predictor of all four adult outcome measures (i.e., verbal IQ, Autism Diagnostic Observation Schedule Communication + Social Interaction Algorithm totals, Peabody Picture Vocabulary Test scores, and Vineland Adaptive Behavior Scales Communication Domain scores), while noun diversity and proportion of utterances that were socially motivated were not value-added predictors of any adult outcome measures. In a second set of regression analyses, mean length of utterance was substituted for verb diversity and was a value-added predictor of two out of four adult outcome measures (i.e., verbal IQ and Vineland Adaptive Behavior Scales Communication Domain scores). The pattern of findings for the other predictors remained the same as in the previous analyses. Conclusion These results have implications for our understanding of early language in ASD and for clinical decision making in early childhood.

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8. Morová M, Kršková L. Autistic-like traits in laboratory rodents exposed to phthalic acid esters during early development – an animal model of autism?. Physiological research. 2021; 70(3): 345-61.

Phthalates are chemical substances that are widely used to provide flexibility and durability to plastic materials. They leach from products in which they are mixed and reach living organisms. Results from experimental studies suggest that exposure to phthalates can have a negative impact on an individual’s neuronal system and behavior. In this regard, exposure during early ontogenesis seems to be particularly dangerous due to the extensive growth and development of body structures and functions. Disruption during this critical time can result in alterations of behavior and the emergence of neurodevelopmental disorders, such as autism spectrum disorder (ASD). Various animal models have been used to elucidate the pathogenesis of this disease. They are fundamental for research, and although the translation of results to humans is difficult, new animal models are being developed. The aim of this review is to summarize laboratory rodent studies in which early developmental phthalate exposure resulted in brain alterations and autistic-like behavioral traits. We also discuss the possibility of using early developmental phthalate exposure in rodents to create a new animal model of autism.

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9. Oliveira JS, Franco FO, Revers MC, Silva AF, Portolese J, Brentani H, Machado-Lima A, Nunes FLS. Computer-aided autism diagnosis based on visual attention models using eye tracking. Scientific reports. 2021; 11(1): 10131.

An advantage of using eye tracking for diagnosis is that it is non-invasive and can be performed in individuals with different functional levels and ages. Computer/aided diagnosis using eye tracking data is commonly based on eye fixation points in some regions of interest (ROI) in an image. However, besides the need for every ROI demarcation in each image or video frame used in the experiment, the diversity of visual features contained in each ROI may compromise the characterization of visual attention in each group (case or control) and consequent diagnosis accuracy. Although some approaches use eye tracking signals for aiding diagnosis, it is still a challenge to identify frames of interest when videos are used as stimuli and to select relevant characteristics extracted from the videos. This is mainly observed in applications for autism spectrum disorder (ASD) diagnosis. To address these issues, the present paper proposes: (1) a computational method, integrating concepts of Visual Attention Model, Image Processing and Artificial Intelligence techniques for learning a model for each group (case and control) using eye tracking data, and (2) a supervised classifier that, using the learned models, performs the diagnosis. Although this approach is not disorder-specific, it was tested in the context of ASD diagnosis, obtaining an average of precision, recall and specificity of 90%, 69% and 93%, respectively.

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10. Pascariello G, Cimino G, Calvi E, Bernardi N, Grigolato M, Garyfallidis P, Fabbricatore D, Pezzola E, Lombardi CM, Metra M, Vizzardi E. Cardiogenic Shock due to COVID-19-Related Myocarditis in a 19-Year-Old Autistic Patient. Journal of medical cases. 2020; 11(7): 207-10.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is mainly responsible for respiratory involvement but cardiac complications are also reported. Nevertheless, potential life-threatening conditions in young people have not been described. A 19-year-old male autistic patient was admitted with fever and cough. The chest radiography showed viral pneumonia and the nasopharyngeal swab detected SARS-CoV-2. He rapidly developed hypotension, oliguria and increased myocardial injury markers and was treated with adrenaline, antiviral drugs and mechanical ventilation. Echocardiography revealed diffuse myocardial hypo-akinesia and decreased left ventricular ejection fraction (LVEF). After several days of treatment, the patient was weaned off mechanical ventilation, LVEF recovered to 50% and laboratory tests showed a decrease of markers of myocardial injury. Coronavirus disease 2019 (COVID-19) can therefore severely affect myocardium with life-threatening complications and even young people can be involved.

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11. Samra N, Toubiana S, Yttervik H, Tzur-Gilat A, Morani I, Itzkovich C, Giladi L, Abu Jabal K, Cao JZ, Godley LA, Mory A, Baris Feldman H, Tveten K, Selig S, Weiss K. RBL2 bi-allelic truncating variants cause severe motor and cognitive impairment without evidence for abnormalities in DNA methylation or telomeric function. Journal of human genetics. 2021; 66(11): 1101-12.

RBL2/p130, a member of the retinoblastoma family of proteins, is a key regulator of cell division and propagates irreversible senescence. RBL2/p130 is also involved in neuronal differentiation and survival, and eliminating Rbl2 in certain mouse strains leads to embryonic lethality accompanied by an abnormal central nervous system (CNS) phenotype. Conflicting reports exist regarding a role of RBL2/p130 in transcriptional regulation of DNA methyltransferases (DNMTs), as well as the control of telomere length. Here we describe the phenotype of three patients carrying bi-allelic RBL2-truncating variants. All presented with infantile hypotonia, severe developmental delay and microcephaly. Malignancies were not reported in carriers or patients. Previous studies carried out on mice and human cultured cells, associated RBL2 loss to DNA methylation and telomere length dysregulation. Here, we investigated whether patient cells lacking RBL2 display related abnormalities. The study of primary patient fibroblasts did not detect abnormalities in expression of DNMTs. Furthermore, methylation levels of whole genome DNA, and specifically of pericentromeric repeats and subtelomeric regions, were unperturbed. RBL2-null fibroblasts show no evidence for abnormal elongation by telomeric recombination. Finally, gradual telomere shortening, and normal onset of senescence were observed following continuous culturing of RBL2-mutated fibroblasts. Thus, this study resolves uncertainties regarding a potential non-redundant role for RBL2 in DNA methylation and telomere length regulation, and indicates that loss of function variants in RBL2 cause a severe autosomal recessive neurodevelopmental disorder in humans.

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12. Wang HV, Forestier S, Corces VG. Exposure to sevoflurane results in changes of transcription factor occupancy in sperm and inheritance of autism†. Biology of reproduction. 2021; 105(3): 705-19.

One in 54 children in the United States is diagnosed with autism spectrum disorder. De novo germline and somatic mutations cannot account for all cases of autism spectrum disorder, suggesting that epigenetic alterations triggered by environmental exposures may be responsible for a subset of autism spectrum disorder cases. Human and animal studies have shown that exposure of the developing brain to general anesthetic agents can trigger neurodegeneration and neurobehavioral abnormalities, but the effects of general anesthetics on the germline have not been explored in detail. We exposed pregnant mice to sevoflurane during the time of embryonic development when the germ cells undergo epigenetic reprogramming and found that more than 38% of the directly exposed F1 animals exhibit impairments in anxiety and social interactions. Strikingly, 44-47% of the F2 and F3 animals, which were not directly exposed to sevoflurane, show the same behavioral problems. We performed ATAC-seq and identified more than 1200 differentially accessible sites in the sperm of F1 animals, 69 of which are also present in the sperm of F2 animals. These sites are located in regulatory regions of genes strongly associated with autism spectrum disorder, including Arid1b, Ntrk2, and Stmn2. These findings suggest that epimutations caused by exposing germ cells to sevoflurane can lead to autism spectrum disorder in the offspring, and this effect can be transmitted through the male germline inter- and transgenerationally.

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