1. Arafa A, Mahmoud O, Salah H, Abdelmonem AA, Senosy S. Maternal and neonatal risk factors for autism spectrum disorder: A case-control study from Egypt. PLoS One;2022;17(6):e0269803.

BACKGROUND: The prevalence of autism spectrum disorder (ASD) has been increasing steadily in Egypt and worldwide. Detecting risk factors for ASD could help initiate screening and risk prevention approaches. Herein, this study aimed to detect several maternal and neonatal risk factors for ASD in Egypt. METHODS: In this case-control study, mothers of children with ASD who were visiting Beni-Suef University Hospital in Egypt (n = 268) were compared to mothers of children without ASD attending one primary school with a kindergarten (n = 504) regarding their preconception, conception, and postconception characteristics. Data were collected using a self-administered questionnaire. The odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to investigate the possible associations between the collected data and the odds of ASD. RESULTS: In the multivariable-adjusted models, urban residence: OR (95% CI) = 2.33 (1.60-3.38), relative father: 2.63 (1.74-3.96), history of diabetes: 5.98 (1.99-17.97), previous abortion: 2.47 (1.20-13.38), assisted fertility: 4.01 (1.20-13.38), family history of ASD: 7.24 (2.00-26.24), multiple pregnancy: 11.60 (2.54-53.07), exposure to passive smoking during pregnancy: 2.95 (1.86-4.68), vaginal bleeding during pregnancy: 3.10 (1.44-6.67), hypertension with pregnancy: 3.64 (1.06-12.51), preterm labor: 2.64 (1.26-5.57), neonatal convulsions: 14.88 (5.01-44.20), and admission to neonatal intensive care unit 2.13: (1.21-3.74) were associated with the increased odds of ASD. On the other hand, the intake of vitamins during pregnancy: 0.09 (0.06-0.16) and C-section: 0.44 (0.27-0.70) were associated with the decreased odds of ASD. CONCLUSION: This study detected several maternal and neonatal risk factors for ASD in Egyptian children.

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2. Arpi MNT, Simpson TI. SFARI genes and where to find them; modelling Autism Spectrum Disorder specific gene expression dysregulation with RNA-seq data. Sci Rep;2022 (Jun 16);12(1):10158.

Autism Spectrum Disorders (ASD) have a strong, yet heterogeneous, genetic component. Among the various methods that are being developed to help reveal the underlying molecular aetiology of the disease one approach that is gaining popularity is the combination of gene expression and clinical genetic data, often using the SFARI-gene database, which comprises lists of curated genes considered to have causative roles in ASD when mutated in patients. We build a gene co-expression network to study the relationship between ASD-specific transcriptomic data and SFARI genes and then analyse it at different levels of granularity. No significant evidence is found of association between SFARI genes and differential gene expression patterns when comparing ASD samples to a control group, nor statistical enrichment of SFARI genes in gene co-expression network modules that have a strong correlation with ASD diagnosis. However, classification models that incorporate topological information from the whole ASD-specific gene co-expression network can predict novel SFARI candidate genes that share features of existing SFARI genes and have support for roles in ASD in the literature. A statistically significant association is also found between the absolute level of gene expression and SFARI’s genes and Scores, which can confound the analysis if uncorrected. We propose a novel approach to correct for this that is general enough to be applied to other problems affected by continuous sources of bias. It was found that only co-expression network analyses that integrate information from the whole network are able to reveal signatures linked to ASD diagnosis and novel candidate genes for the study of ASD, which individual gene or module analyses fail to do. It was also found that the influence of SFARI genes permeates not only other ASD scoring systems, but also lists of genes believed to be involved in other neurodevelopmental disorders.

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3. Bhakta BB, Coleman KJ, Choi KR. Randomized Study of Survey Recruitment Strategies for Parents of Autistic Children. J Pediatr Health Care;2022 (Jun 12)

INTRODUCTION: This study aimed to compare phone, email, or text message recruitment strategies for engaging parents of autistic children in an online survey. METHOD: In this randomized study, a sample of 1,624 parents of autistic children spectrum disorder (autism) from an integrated health system in Southern California were sent an initial mailed letter and email simultaneously for baseline survey outreach. Then, participants were randomly assigned to one of three follow-up recruitment groups: phone, email, or text message. We compared the efficacy of recruitment strategies in multivariate models. RESULTS: All three follow-up methods were equally effective for eliciting a survey response. Parents of girls were less likely to respond to survey outreach attempts than parents of boys. DISCUSSION: Multiple modalities of survey recruitment, including digital and mobile approaches, effectively recruit parents of children in research.

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4. Błeszyński J, Rumińska A, Hamerlińska A, Stefańska-Klar R, Warszawa A. The experience of the COVID-19 pandemic by persons with ASD: Social aspects. PLoS One;2022;17(6):e0267123.

While causing a variety of social restrictions, the COVID-19 pandemic has also precipitated the digitalisation of public services and official procedures, reducing many, until recently necessary, immediate social interactions. This study has been conducted to investigate their perception of the COVID-19 pandemic and its impact on their current and future social interactions. To this end, semi-structured narrative interviews were conducted. Ten adults on the autism spectrum participated in the study. The phenomenological analysis of the narratives focused on categories related to the social functioning of the study participants. The interpretation of the narratives has shown that autistic people can experience a sense of loss due to the lack of direct contact. On the other hand, we also talked to the participants who expressed their satisfaction with the situation of obligatory social distance. The respondents also discussed the subject of changing the form of interaction in some areas of public life to one that is more adjusted to the needs of people with their condition. The study concludes with a suggestion that autistic people might benefit from technological progress in institutions and the availability of the option to prefer online contact for interactions that are not strictly necessary.

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5. Borra D, Magosso E, Castelo-Branco M, Simoes M. A Bayesian-optimized design for an interpretable convolutional neural network to decode and analyze the P300 response in autism. J Neural Eng;2022 (Jun 15)

OBJECTIVE: P300 can be analyzed in autism spectrum disorder (ASD) to derive biomarkers and can be decoded in BCIs to reinforce ASD impaired skills. Convolutional neural networks (CNNs) have been proposed for P300 decoding, outperforming traditional algorithms but they i) do not investigate optimal designs in different training conditions; ii) lack in interpretability. To overcome these limitations, an interpretable CNN (ICNN), that we recently proposed for motor decoding, has been modified and adopted here, with its optimal design searched via Bayesian optimization. APPROACH: The ICNN provides a straightforward interpretation of spectral and spatial features learned to decode P300. The Bayesian-optimized (BO) ICNN design was investigated separately for different training strategies (within-subject, within-session, and cross-subject) and BO models were used for the subsequent analyses. Specifically, transfer learning (TL) potentialities were investigated by assessing how pretrained cross-subject BO models performed on a new subject vs. random-initialized models. Furthermore, within-subject BO-derived models were combined with an Explanation Technique (ICNN+ET) to analyze P300 spectral and spatial features. MAIN RESULTS: The ICNN resulted comparable or even outperformed existing CNNs, at the same time being lighter. Bayesian-optimized ICNN designs differed depending on the training strategy, needing more capacity as the training set variability increased. Furthermore, TL provided higher performance than networks trained from scratch. The ICNN+ET analysis suggested the frequency range [2, 5.8] Hz as the most relevant, and spatial features showed a right-hemispheric parietal asymmetry. The ICNN+ET-derived features, but not ERP-derived features, resulted significantly and highly correlated to ADOS clinical scores. SIGNIFICANCE: This study substantiates the idea that a CNN can be designed both accurate and interpretable for P300 decoding, with an optimized design depending on the training condition. The novel ICNN-based analysis tool was able to better capture ASD neural signatures than traditional ERP analysis, possibly paving the way for identifying novel biomarkers.

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6. Gauld C, Maquet J, Micoulaud-Franchi JA, Dumas G. Popular and Scientific Discourse on Autism: Representational Cross-Cultural Analysis of Epistemic Communities to Inform Policy and Practice. J Med Internet Res;2022 (Jun 15);24(6):e32912.

BACKGROUND: Social media provide a window onto the circulation of ideas in everyday folk psychiatry, revealing the themes and issues discussed both by the public and by various scientific communities. OBJECTIVE: This study explores the trends in health information about autism spectrum disorder within popular and scientific communities through the systematic semantic exploration of big data gathered from Twitter and PubMed. METHODS: First, we performed a natural language processing by text-mining analysis and with unsupervised (machine learning) topic modeling on a sample of the last 10,000 tweets in English posted with the term #autism (January 2021). We built a network of words to visualize the main dimensions representing these data. Second, we performed precisely the same analysis with all the articles using the term « autism » in PubMed without time restriction. Lastly, we compared the results of the 2 databases. RESULTS: We retrieved 121,556 terms related to autism in 10,000 tweets and 5.7×109 terms in 57,121 biomedical scientific articles. The 4 main dimensions extracted from Twitter were as follows: integration and social support, understanding and mental health, child welfare, and daily challenges and difficulties. The 4 main dimensions extracted from PubMed were as follows: diagnostic and skills, research challenges, clinical and therapeutical challenges, and neuropsychology and behavior. CONCLUSIONS: This study provides the first systematic and rigorous comparison between 2 corpora of interests, in terms of lay representations and scientific research, regarding the significant increase in information available on autism spectrum disorder and of the difficulty to connect fragments of knowledge from the general population. The results suggest a clear distinction between the focus of topics used in the social media and that of scientific communities. This distinction highlights the importance of knowledge mobilization and exchange to better align research priorities with personal concerns and to address dimensions of well-being, adaptation, and resilience. Health care professionals and researchers can use these dimensions as a framework in their consultations to engage in discussions on issues that matter to beneficiaries and develop clinical approaches and research policies in line with these interests. Finally, our study can inform policy makers on the health and social needs and concerns of individuals with autism and their caregivers, especially to define health indicators based on important issues for beneficiaries.

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7. Holtman SJ, Winans KS, Hoch JD. Utility of Diagnostic Classification for Children 0-5 to Assess Features of Autism: Comparing In-person and COVID-19 Telehealth Evaluations. J Autism Dev Disord;2022 (Jun 16)

Logistic regression was used to examine the use of Autism Spectrum diagnostic categories from pre-COVID-19 in-person evaluations and COVID-19 telehealth evaluations at a specialist community mental health clinic. The diagnostic classification for children 0-5 (DC: 0-5) affords a wider range of diagnoses that allowed for inferences of clinician certainty of diagnosis. Use of full criteria diagnoses was significantly lower from telehealth evaluations during the pandemic, and was less certain for younger children, some non-English speakers, and children reporting Native American/Alaska Native race. Higher Child Behavior Checklist (CBCL) ASD subscale scores, lower CBCL total scores, and global developmental delay diagnoses predicted greater use of full ASD diagnoses. Findings suggest factors that could identify children appropriate for telehealth evaluations.

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8. Jackson SZ, Pinto-Martin JA, Deatrick JA, Boyd R, Souders MC. High Depressive Symptoms, Low Family Functioning, and Low Self-Efficacy in Mothers of Children With Autism Spectrum Disorder Compared to Two Control Groups. J Am Psychiatr Nurses Assoc;2022 (Jun 16):10783903221104147.

BACKGROUND: Parents of children with autism spectrum disorder (ASD) face unique challenges in raising their children, and they are at higher risk for depression compared to parents of children with typical development (TD) and other disabilities. AIMS: (1) To compare prevalence of depressive symptoms among mothers of children with ASD (n = 101), Down syndrome (DS, n = 101), and TD (n = 43) and (2) to describe the relationships among depression, self-efficacy, and family functioning, and describe the mediating role of maternal child care self-efficacy between depressive symptoms and child behavior. METHODS: In this cross-sectional study, mothers completed the Social Communication Questionnaire, Aberrant Behavior Checklist, Patient Health Questionnaire-9 (PHQ-9), Family Assessment Device General Functioning Scale, and Maternal Self-Efficacy Scale. RESULTS: Mothers of children with ASD had significantly higher mean PHQ-9 scores (p < .001), higher proportion of positive depression screening (p < .001), and lower family functioning (p < .001). Better family functioning is associated with less depression, better self-efficacy, and less severe ASD symptoms and behaviors. Self-efficacy mediated the relationship between depression and child ASD symptoms, and problematic behavior. CONCLUSIONS: The rates of reported history of depression and low family functioning in mothers of children with ASD are twice the rate in mothers of children with DS and TD. Maternal child care self-efficacy is protective against maternal depression, even in the presence of severe child problematic behaviors and ASD symptoms. Interventions that increase child care self-efficacy and family functioning may be helpful in addressing depression in mothers of children with ASD.

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9. Kar K. A computational probe into the behavioral and neural markers of atypical facial emotion processing in autism. J Neurosci;2022 (May 23)

Despite ample behavioral evidence of atypical facial emotion processing in individuals with autism spectrum disorder (ASD), the neural underpinnings of such behavioral heterogeneities remain unclear. Here, I have used brain-tissue mapped artificial neural network (ANN) models of primate vision to probe candidate neural and behavior markers of atypical facial emotion recognition in ASD at an image-by-image level. Interestingly, the ANNs’ image-level behavioral patterns better matched the neurotypical subjects’ behavior than those measured in ASD. This behavioral mismatch was most remarkable when the ANN behavior was decoded from units that correspond to the primate inferior temporal (IT) cortex. ANN-IT responses also explained a significant fraction of the image-level behavioral predictivity associated with neural activity in the human amygdala (from epileptic patients without ASD)- strongly suggesting that the previously reported facial emotion intensity encodes in the human amygdala could be primarily driven by projections from the IT cortex. In sum, these results identify primate IT activity as a candidate neural marker and demonstrate how ANN models of vision can be used to generate neural circuit-level hypotheses and guide future human and non-human primate studies in autism.Significance Statement:Moving beyond standard parametric approaches that predict behavior with high-level categorical descriptors of a stimulus (e.g., level of happiness/fear in a face image), in this study, I demonstrate how an image-level probe, utilizing current deep-learning based artificial neural network (ANN) models, allows identification of more diagnostic stimuli for autism spectrum disorder enabling the design of more powerful experiments. This study predicts that inferior temporal (IT) cortex activity is a key candidate neural marker of atypical facial emotion processing in people with ASD. Importantly, the results strongly suggest that ASD-related atypical facial emotion intensity encodes in the human amygdala could be primarily driven by projections from the IT cortex.

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10. Lane AE, Heathcock J. Sensorimotor Surveillance in the First Year of Life: Imperatives for Physical and Occupational Therapy Practice. A Commentary on « Posture Matters: Object Manipulation during the Transition to Arms-Free Sitting in Infants at Elevated vs. Typical Likelihood for Autism Spectrum Disorder ». Phys Occup Ther Pediatr;2022;42(4):366-368.

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11. Paula VAC, Faker K, Bendo CB, Tostes MA. Responsiveness of the B-ECOHIS to detect changes in OHRQoL following dental treatment of children with autism spectrum disorder. Braz Oral Res;2022;36:e079.

The Brazilian Early Childhood Oral Health Impact Scale (B-ECOHIS) is an oral health-related quality of life (OHRQoL) questionnaire. This paper aims to investigate the responsiveness of the B-ECOHIS to dental treatment in individuals diagnosed with autism spectrum disorder (ASD) and determine if dental treatment has an impact on OHRQoL. The survey targeted 27 ASD individuals aged 4 to 14 years attending the Acolher Project of the University Federal Fluminense. This project provides children and adolescents with disabilities with oral health services. A group of randomly selected caregivers self-completed the B-ECOHIS before and 14 days after their children’s dental treatment. The dental treatment included meticulous screening, preventive treatment, and restorative treatment. Responsiveness was assessed by investigating the effect size (ES) and standardized response mean (SRM). Wilcoxon test was used to evaluate internal responsiveness (distribution-based approach). The B-ECOHIS showed significant changes in the total score (p<0.001) and in all domains. The ES of the total B-ECOHIS after treatment was 1.28 and ranged between 0.70 and 1.14 for the domains. The SRM for each of the domains was large, except for the symptom domain. The B-ECOHIS is sensitive and responsive to ASD individuals undergoing dental treatment. Individuals with ASD showed improvement in their OHRQoL score after dental treatment.

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12. Peiris H, Wickramarachchi DC, Samarasinghe P, Vance P, Dahanayake D, Kulasekara V, Nadeeshani M. Diagnosing autism in low-income countries: Clinical record-based analysis in Sri Lanka. Autism Res;2022 (Jun 16)

Use of autism diagnosing standards in low-income countries (LICs) are restricted due to the high price and unavailability of trained health professionals. Furthermore, these standards are heavily skewed towards developed countries and LICs are underrepresented. Due to such constraints, many LICs use their own ways of assessing autism. This is the first retrospective study to analyze such local practices in Sri Lanka. The study was conducted at Ward 19B of Lady Ridgeway Hospital (LRH) using the clinical forms filled for diagnosing ASD. In this study, 356 records were analyzed, from which 79.5% were boys and the median age was 33 months. For each child, the clinical form together with the Childhood Autism Rating Scale (CARS) value were recorded. In this study, a Clinically Derived Autism Score (CDAS) is obtained from the clinical forms. Scatter plot and Pearson product moment correlation coefficient were used to benchmark CDAS with CARS, and it was found CDAS to be positively and moderately correlated with CARS. In identifying the significant variables, a logistic regression model was built based on clinically observed data and it evidenced that « Eye Contact, » « Interaction with Others, » « Pointing, » « Flapping of Hands, » « Request for Needs, » « Rotate Wheels, » and « Line up Things » variables as the most significant variables in diagnosing autism. Based on these significant predictors, the classification tree was built. The pruned tree depicts a set of rules, which could be used in similar clinical environments to screen for autism. LAY SUMMARY: Screening and diagnosing autism in low-income countries such as Sri Lanka has always been a challenge due to limited resources and not being able to afford global standards. Due to these challenges, locally developed clinical forms have been used. This study is the first to analyze a clinical record set for autism in Sri Lanka to benchmark the local clinic form with a global standard. Furthermore, this study identifies the most significant diagnostic symptoms for children and based on these significant features, a simple set of IF-THEN rules are derived which could be used for screening autism in a similar clinical environment by health officials in the absence of consultants.

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13. Qiu S, Qiu Y, Li Y, Cong X. Genetics of autism spectrum disorder: an umbrella review of systematic reviews and meta-analyses. Transl Psychiatry;2022 (Jun 15);12(1):249.

Autism spectrum disorder (ASD) is a class of neurodevelopmental conditions with a large epidemiological and societal impact worldwide. To date, numerous studies have investigated the associations between genetic variants and ASD risk. To provide a robust synthesis of published evidence of candidate gene studies for ASD, we performed an umbrella review (UR) of meta-analyses of genetic studies for ASD (PROSPERO registration number: CRD42021221868). We systematically searched eight English and Chinese databases from inception to March 31, 2022. Reviewing of eligibility, data extraction, and quality assessment were performed by two authors. In total, 28 of 5062 retrieved articles were analyzed, which investigated a combined 41 single nucleotide polymorphisms (SNPs) of nine candidate genes. Overall, 12 significant SNPs of CNTNAP2, MTHFR, OXTR, SLC25A12, and VDR were identified, of which associations with suggestive evidence included the C677T polymorphism of MTHFR (under allelic, dominant, and heterozygote models) and the rs731236 polymorphism of VDR (under allelic and homozygote models). Associations with weak evidence included the rs2710102 polymorphism of CNTNAP2 (under allelic, homozygote, and recessive models), the rs7794745 polymorphism of CNTNAP2 (under dominant and heterozygote models), the C677T polymorphism of MTHFR (under homozygote model), and the rs731236 polymorphism of VDR (under dominant and recessive models). Our UR summarizes research evidence on the genetics of ASD and provides a broad and detailed overview of risk genes for ASD. The rs2710102 and rs7794745 polymorphisms of CNTNAP2, C677T polymorphism of MTHFR, and rs731236 polymorphism of VDR may confer ASD risks. This study will provide clinicians and healthcare decision-makers with evidence-based information about the most salient candidate genes relevant to ASD and recommendations for future treatment, prevention, and research.

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14. Rabelo LN, Queiroz JPG, Castro CCM, Silva SP, Campos LD, Silva LC, Nascimento EB, Martínez-Cerdeño V, Fiuza FP. Layer-Specific Changes in the Prefrontal Glia/Neuron Ratio Characterizes Patches of Gene Expression Disorganization in Children with Autism. J Autism Dev Disord;2022 (Jun 15)

Autism spectrum disorder (ASD) is manifested by abnormal cell numbers and patches of gene expression disruption in higher-order brain regions. Here, we investigated whether layer-specific changes in glia/neuron ratios (GNR) characterize patches in the dorsolateral prefrontal cortex (DL-PFC) of children with ASD. We analyzed high-resolution digital images of postmortem human brains from 11 ASD and 11 non-ASD children obtained from the Autism Study of the Allen Human Brain Atlas. We found the GNR is overall reduced in the ASD DL-PFC. Moreover, layers II-III belonging to patches presented a lower GNR in comparison with layers V-VI. We here provide a new insight into how brain cells are arranged within patches that contributes to elucidate how neurodevelopmental programs are altered in ASD.

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15. Sari NP, Jansen PW, Blanken LME, Ruigrok ANV, Prinzie P, Tiemeier H, Baron-Cohen S, van IMH, White T. Maternal age, autistic-like traits and mentalizing as predictors of child autistic-like traits in a population-based cohort. Mol Autism;2022 (Jun 15);13(1):26.

BACKGROUND: Many empirical studies suggest that higher maternal age increases the likelihood of having an autistic child. However, little is known about factors that may explain this relationship or if higher maternal age is related to the number of autistic-like traits in offspring. One possibility is that mothers who have a higher number of autistic-like traits, including greater challenges performing mentalizing skills, are delayed in finding a partner. The goal of our study is to assess the relationship between maternal age, mentalizing skills and autistic-like traits as independent predictors of the number of autistic-like traits in offspring. METHODS: In a population-based study in the Netherlands, information on maternal age was collected during pre- and perinatal enrolment. Maternal mentalizing skills and autistic-like traits were assessed using the Reading the Mind in the Eyes Test and the Autism Spectrum Quotient, respectively. Autistic-like traits in children were assessed with the Social Responsiveness Scale. A total of 5718 mother/child dyads had complete data (M(agechild) = 13.5 years; 50.2% girls). RESULTS: The relationship between maternal age and autistic-like traits in offspring best fits a U-shaped curve. Furthermore, higher levels of autistic features in mothers are linked to higher levels of autistic-like traits in their children. Lower mentalizing performance in mothers is linked to higher levels of autistic-like traits in their children. LIMITATIONS: We were able to collect data on both autistic-like traits and the mentalizing skills test in a large population of mothers, but we did not collect these data in a large number of the fathers. CONCLUSIONS: The relationships between older and younger mothers may have comparable underlying mechanisms, but it is also possible that the tails of the U-shaped curve are influenced by disparate mechanisms.

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16. Solgi M, Feryn A, Chavez AE, Wilson L, King M, Scholz J, Fombonne E, Zuckerman KE. Parents’ Concerns Are Associated with Early Intervention Evaluation and Eligibility Outcomes. J Dev Behav Pediatr;2022 (Apr 1);43(3):e145-e152.

OBJECTIVE: To test the association of parents’ concerns with early intervention (EI) developmental services outcomes including evaluation, eligibility, and enrollment in services. METHOD: We collected survey data on parents’ concerns and EI service use data from a sample of 428 children referred to EI from 2016 to 2018 in 6 Oregon primary care clinics serving lower-income families as part of a developmental and autism spectrum disorder screening intervention. We assessed EI service use trajectories and associations of the presence of parent concern, age of child at the time of parents’ concerns, number of concerns, and type of provider concern, with EI evaluation, EI eligibility, and enrollment in EI services, using bivariate testing and multivariable logistic regression. RESULTS: Only 22.9% of children referred to EI were enrolled in services 6 months later. Children whose parents had developmental and/or behavioral concerns were more likely to receive an EI evaluation and were also more likely to be eligible for services, compared with children whose parents had no concerns. There was no association between age, number of concerns, and type of concern with EI evaluation, eligibility, or services enrollment. CONCLUSION: Although only a minority of children referred to EI enrolled in services, the presence of parent concern is strongly associated with EI services evaluation and eligibility outcomes. Study results suggest that providers should assess the presence of parent concern when deciding on EI referrals and provide more support to parents who are not concerned at all.

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