1. Abdelhamid N, Thind R, Mohammad H, Thabtah F. Assessing Autistic Traits in Toddlers Using a Data-Driven Approach with DSM-5 Mapping. Bioengineering (Basel, Switzerland). 2023; 10(10).

Autistic spectrum disorder (ASD) is a neurodevelopmental condition that characterises a range of people, from individuals who are not able to speak to others who have good verbal communications. The disorder affects the way people see, think, and behave, including their communications and social interactions. Identifying autistic traits, preferably in the early stages, is fundamental for clinicians in expediting referrals, and hence enabling patients to access to required healthcare services. This article investigates various ASD behavioral features in toddlers and proposes a data process using machine-learning techniques. The aims of this study were to identify early behavioral features that can help detect ASD in toddlers and to map these features to the neurodevelopment behavioral areas of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). To achieve these aims, the proposed data process assesses several behavioral features using feature selection techniques, then constructs a classification model based on the chosen features. The empirical results show that during the screening process of toddlers, cognitive features related to communications, social interactions, and repetitive behaviors were most relevant to ASD. For the machine-learning algorithms, the predictive accuracy of Bayesian network (Bayes Net) and logistic regression (LR) models derived from ASD behavioral data subsets were consistent pinpointing to the suitability of ML techniques in predicting ASD.

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2. Cherchi C, Chiappini E, Chiarini Testa MB, Banfi P, Veneselli E, Cutrera R. Care Issues in Patients with Rett Syndrome: A Parental Perspective. Children (Basel, Switzerland). 2023; 10(10).

BACKGROUND: The purpose of this study is to better understand the way caregivers of patients with Rett syndrome perceive the quality of the health care services they receive and identify its main shortcomings. METHODS: A survey was distributed to all caregivers who are part of AIRETT (the Italian Association of Relatives of Patients with RS). The survey gathered information on the management of relatives of patients with Rett syndrome. RESULTS: The data refers to 52 patients, all females, with a median age of 15 years at the time of the survey. Concerning RS specificity, our data confirm the high complexity of this chronic, multifaceted condition, mainly characterized by the presence of epilepsy, apnea, severe scoliosis, and gastrointestinal symptoms. The specialists more frequently involved in the care of patients were general practitioners or family pediatricians (98%) and neurologists (92%), and more rarely physiatrists (71%). Only 15% of patients were followed by a pulmonologist, despite the fact that respiratory problems were frequent (apneas were present in 81% of patients, and 2% had a tracheostomy). Although 63.5% of patients presented with gastrointestinal symptoms and 2% had a gastrostomy, only 33% were followed by a gastroenterologist. Moreover, although orthopedic issues were present in 78.8% of patients, including severe scoliosis in 22% of them, only 25% were followed by an orthopedist. Furthermore, despite the fact that RS patients are fragile, about one quarter of them were not vaccinated. As far as organizational issues are concerned, several specialized centers are located in various regions throughout the country. As a consequence, the high mobility rate from one center to another resulted in non-homogeneous assistance. CONCLUSIONS: The study shows that caregivers of RS patients take over most obligations and burdens by increasing their perceived level of stress. For the majority of patients, the most frequent complications were not followed by the reference subspecialist, with the only exception of epilepsy. Moreover, improving vaccination strategies for these patients is necessary.

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3. de Miguel L, Ballester P, Egoavil C, Sánchez-Ocaña ML, García-Muñoz AM, Cerdá B, Zafrilla P, Ramos E, Peiró AM. Pharmacogenetics May Prevent Psychotropic Adverse Events in Autism Spectrum Disorder: An Observational Pilot Study. Pharmaceuticals (Basel, Switzerland). 2023; 16(10).

INTRODUCTION: Up to 73% of individuals with autism spectrum disorder (ASD) and intellectual disability (ID) currently have prescriptions for psychotropic drugs. This is explained by a higher prevalence of medical and psychiatric chronic comorbidities, which favors polypharmacy, increasing the probability of the appearance of adverse events (AEs). These could be a preventable cause of harm to patients with ASD and an unnecessary waste of healthcare resources. OBJECTIVE: To study the impact of pharmacogenetic markers on the prevention of AE appearance in a population with ASD and ID. METHODS: This is a cross-sectional, observational study (n = 118, 72 participants completed all information) in the ASD population. Sociodemographic and pharmacological data were gathered. The Udvalg for Kliniske Undersøgelser Scale (UKU Scale) was used to identify AEs related to the use of psychotropic medication. Polymorphisms of DOP2, ABCB1, and COMT were genotyped and correlated with the AE to find candidate genes. Furthermore, a review of all medications assessed in a clinical trial for adults with autism was performed to enrich the search for potential pharmacogenetic markers, keeping in mind the usual medications. RESULTS: The majority of the study population were men (75%) with multiple comorbidities and polypharmacy, the most frequently prescribed drugs were antipsychotics (69%); 21% of the participants had four or more AEs related to psychotropic drugs. The most common were « Neurological » and » Psychiatric » (both 41%). Statistical analysis results suggested a significant correlation between the neurological symptoms and the DOP2 genotype, given that they are not equally distributed among its allelic variants. The final review considered 19 manuscripts of medications for adults with ASD, and the confirmed genetic markers for those medications were consulted in databases. CONCLUSION: A possible correlation between neurologic AEs and polymorphisms of DOP2 was observed; therefore, studying this gene could contribute to the safety of this population’s prescriptions. The following studies are underway to maximize statistical power and have a better representation of the population.

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4. Feng M, Xu J. Detection of ASD Children through Deep-Learning Application of fMRI. Children (Basel, Switzerland). 2023; 10(10).

Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable immediate, targeted interventions. This study unveils an advanced convolutional-neural-network (CNN) algorithm that was meticulously engineered to examine resting-state functional magnetic resonance imaging (fMRI) for early ASD detection in pediatric cohorts. The CNN architecture amalgamates convolutional, pooling, batch-normalization, dropout, and fully connected layers, optimized for high-dimensional data interpretation. Rigorous preprocessing yielded 22,176 two-dimensional echo planar samples from 126 subjects (56 ASD, 70 controls) who were sourced from the Autism Brain Imaging Data Exchange (ABIDE I) repository. The model, trained on 17,740 samples across 50 epochs, demonstrated unparalleled diagnostic metrics-accuracy of 99.39%, recall of 98.80%, precision of 99.85%, and an F1 score of 99.32%-and thereby eclipsed extant computational methodologies. Feature map analyses substantiated the model’s hierarchical feature extraction capabilities. This research elucidates a deep learning framework for computer-assisted ASD screening via fMRI, with transformative implications for early diagnosis and intervention.

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5. Giannotti M, Venuti P, De Falco S. Child Attachment Representations and Parenting Stress in Mothers and Fathers of School-Age Children with a Diagnosis of Autism Spectrum Disorder: A Pilot Cross-Sectional Study. Children (Basel, Switzerland). 2023; 10(10).

Mothers and fathers of autistic children (ASD) tend to report elevated levels of parenting stress. Thus, it is critically important to understand which factors contribute to an imbalance between the perceived demands of parenting and the available psychological resources. To date, little is known about the association between child attachment representations and parenting stress. In this study, we first examined group differences in parenting stress levels based on child diagnosis and parents’ gender. Second, we explored the predictive role of child diagnosis, autism severity, and child attachment representations on parenting stress. The study involved 23 school-age children with ASD (IQ > 70), 27 without ASD (7-13 years), and their mothers (n = 50) and fathers (n = 50). Data were collected from 2017 to 2020. Parents completed the Social Responsiveness Scale 2 and the Parenting Stress Index-Short Form, while the children’s attachment representations were assessed using the School-age Assessment of Attachment. Parents of children with ASD reported higher stress compared with controls. No differences were found between mothers and fathers. Implicit attachment representations have been found to be associated with parenting stress only in mothers, while the severity of social impairment showed a significant effect on parenting stress in both parents. These findings revealed the potential benefit of adaptive attachment representations not only for children themselves but also for mothers and the family system, suggesting the bidirectional nature of parent-child relationships in the context of ASD. The uniqueness of maternal and paternal parenting experiences should be considered when parenting stress is addressed.

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6. Gurevitz M, Leisman G. Factors in Infancy That May Predict Autism Spectrum Disorder. Brain sciences. 2023; 13(10).

The global increase in the prevalence of ASD (Autism Spectrum Disorder) is of great medical importance, but the reasons for this increase are still unknown. This study sought to identify possible early contributing factors in children who were later diagnosed with ASD. In this retrospective cohort study, postnatal records of 1105 children diagnosed with ASD were analyzed to determine if any signs of ASD could be found in a large database of births and well-baby care programs. We compared the recordings of typically developing children and analyzed the differences statistically. Rapid increases in weight, height, and head circumference during early infancy predict the development of ASD. In addition, low birth weight, older maternal age, and increased weight and height percentiles at six months of age together predict the development of ASD. At two years of age, these four parameters, in addition to impaired motor development, can also predict the development of ASD. These results suggest that the recent increase in ASD prevalence is associated with the « obesity epidemic » and with recommendations of supine sleeping to prevent Sudden Infant Death Syndrome, associated with atypical neural network development in the brain.

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7. Hirst K, Zamzow RM, Stichter JP, Beversdorf DQ. A Pilot Feasibility Study Assessing the Combined Effects of Early Behavioral Intervention and Propranolol on Autism Spectrum Disorder (ASD). Children (Basel, Switzerland). 2023; 10(10).

Autism spectrum disorder (ASD), a neurodevelopmental disorder typified by differences in social communication as well as restricted and repetitive behaviors, is often responsive to early behavioral intervention. However, there is limited information on whether such intervention can be augmented with pharmacological approaches. We conducted a double-blinded, placebo-controlled feasibility trial to examine the effects of the β-adrenergic antagonist propranolol combined with early intensive behavioral intervention (EIBI) for children with ASD. Nine participants with ASD, ages three to ten, undergoing EIBI were enrolled and randomized to a 12-week course of propranolol or placebo. Blinded assessments were conducted at baseline, 6 weeks, and 12 weeks. The primary outcome measures focusing on social interaction were the General Social Outcome Measure-2 (GSOM-2) and Social Responsiveness Scale-Second Edition (SRS-2). Five participants completed the 12-week visit. The sample size was insufficient to evaluate the treatment efficacy. However, side effects were infrequent, and participants were largely able to fully participate in the procedures. Conducting a larger clinical trial to investigate propranolol’s effects on core ASD features within the context of behavioral therapy will be beneficial, as this will advance and individualize combined therapeutic approaches to ASD intervention. This initial study helps to understand feasibility constraints on performing such a study.

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8. Hours CM, Gil S, Gressens P. Molecular and Cellular Insights: A Focus on Glycans and the HNK1 Epitope in Autism Spectrum Disorder. International journal of molecular sciences. 2023; 24(20).

Autism Spectrum Disorder (ASD) is a synaptic disorder with a GABA/glutamate imbalance in the perineuronal nets and structural abnormalities such as increased dendritic spines and decreased long distance connections. Specific pregnancy disorders significantly increase the risk for an ASD phenotype such as preeclampsia, preterm birth, hypoxia phenomena, and spontaneous miscarriages. They are associated with defects in the glycosylation-immune placental processes implicated in neurogenesis. Some glycans epitopes expressed in the placenta, and specifically in the extra-villous trophoblast also have predominant functions in dendritic process and synapse function. Among these, the most important are CD57 or HNK1, CD22, CD24, CD33 and CD45. They modulate the innate immune cells at the maternal-fetal interface and they promote foeto-maternal tolerance. There are many glycan-based pathways of immunosuppression. N-glycosylation pathway dysregulation has been found to be associated with autoimmune-like phenotypes and maternal-autoantibody-related (MAR) autism have been found to be associated with central, systemic and peripheric autoimmune processes. Essential molecular pathways associated with the glycan-epitopes expression have been found to be specifically dysregulated in ASD, notably the Slit/Robo, Wnt, and mTOR/RAGE signaling pathways. These modifications have important effects on major transcriptional pathways with important genetic expression consequences. These modifications lead to defects in neuronal progenitors and in the nervous system’s implementation specifically, with further molecular defects in the GABA/glutamate system. Glycosylation placental processes are crucial effectors for proper maternofetal immunity and endocrine/paracrine pathways formation. Glycans/ galectins expression regulate immunity and neurulation processes with a direct link with gene expression. These need to be clearly elucidated in ASD pathophysiology.

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9. László K, Vörös D, Correia P, Fazekas CL, Török B, Plangár I, Zelena D. Vasopressin as Possible Treatment Option in Autism Spectrum Disorder. Biomedicines. 2023; 11(10).

Autism spectrum disorder (ASD) is rather common, presenting with prevalent early problems in social communication and accompanied by repetitive behavior. As vasopressin was implicated not only in salt-water homeostasis and stress-axis regulation, but also in social behavior, its role in the development of ASD might be suggested. In this review, we summarized a wide range of problems associated with ASD to which vasopressin might contribute, from social skills to communication, motor function problems, autonomous nervous system alterations as well as sleep disturbances, and altered sensory information processing. Beside functional connections between vasopressin and ASD, we draw attention to the anatomical background, highlighting several brain areas, including the paraventricular nucleus of the hypothalamus, medial preoptic area, lateral septum, bed nucleus of stria terminalis, amygdala, hippocampus, olfactory bulb and even the cerebellum, either producing vasopressin or containing vasopressinergic receptors (presumably V(1a)). Sex differences in the vasopressinergic system might underline the male prevalence of ASD. Moreover, vasopressin might contribute to the effectiveness of available off-label therapies as well as serve as a possible target for intervention. In this sense, vasopressin, but paradoxically also V(1a) receptor antagonist, were found to be effective in some clinical trials. We concluded that although vasopressin might be an effective candidate for ASD treatment, we might assume that only a subgroup (e.g., with stress-axis disturbances), a certain sex (most probably males) and a certain brain area (targeting by means of virus vectors) would benefit from this therapy.

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10. Maric DM, Vojvodic D, Maric DL, Velikic G, Radomir M, Sokolovac I, Stefik D, Ivkovic N, Susnjevic S, Puletic M, Dulic O, Abazovic D. Cytokine Dynamics in Autism: Analysis of BMAC Therapy Outcomes. International journal of molecular sciences. 2023; 24(20).

Autism spectrum disorder (ASD) has recently been linked to neuroinflammation and an aberrant immune response within the central nervous system. The intricate relationship between immune response and ASD remains elusive, with a gap in understanding the connection between specific immune mechanisms and neural manifestations in autism. In this study, we employed a comprehensive statistical approach, fusing both overarching and granular methods to examine the concentration of 16 cytokines in the cerebrospinal fluid (CSF) across each autologous bone marrow aspirate concentrate (BMAC) intrathecal administration in 63 male and 17 female autism patients. Following a six-month period post the third administration, patients were stratified into three categories based on clinical improvement: Group 1- no/mild (28 subjects), Group 2-moderate (16 subjects), and Group 3-major improvement (15 subjects). Our integrated analysis revealed pronounced disparities in CSF cytokine patterns and clinical outcomes in autism subjects pre- and post-BMAC transplantation. Crucially, our results suggest that these cytokine profiles hold promise as predictive markers, pinpointing ASD individuals who might not exhibit notable clinical amelioration post-BMAC therapy.

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11. Márquez-García AV, Ng BK, Iarocci G, Moreno S, Vakorin VA, Doesburg SM. Atypical Associations between Functional Connectivity during Pragmatic and Semantic Language Processing and Cognitive Abilities in Children with Autism. Brain sciences. 2023; 13(10).

Autism Spectrum Disorder (ASD) is characterized by both atypical functional brain connectivity and cognitive challenges across multiple cognitive domains. The relationship between task-dependent brain connectivity and cognitive abilities, however, remains poorly understood. In this study, children with ASD and their typically developing (TD) peers engaged in semantic and pragmatic language tasks while their task-dependent brain connectivity was mapped and compared. A multivariate statistical approach revealed associations between connectivity and psychometric assessments of relevant cognitive abilities. While both groups exhibited brain-behavior correlations, the nature of these associations diverged, particularly in the directionality of overall correlations across various psychometric categories. Specifically, greater disparities in functional connectivity between the groups were linked to larger differences in Autism Questionnaire, BRIEF, MSCS, and SRS-2 scores but smaller differences in WASI, pragmatic language, and Theory of Mind scores. Our findings suggest that children with ASD utilize distinct neural communication patterns for language processing. Although networks recruited by children with ASD may appear less efficient than those typically engaged, they could serve as compensatory mechanisms for potential disruptions in conventional brain networks.

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12. Morales-Marín ME, Castro Martínez XH, Centeno Cruz F, Barajas-Olmos F, Náfate López O, Gómez Cotero AG, Orozco L, Nicolini Sánchez H. Differential DNA Methylation from Autistic Children Enriches Evidence for Genes Associated with ASD and New Candidate Genes. Brain sciences. 2023; 13(10).

The etiology of Autism Spectrum Disorders (ASD) is a result of the interaction between genes and the environment. The study of epigenetic factors that affect gene expression, such as DNA methylation, has become an important area of research in ASD. In recent years, there has been an increasing body of evidence pointing to epigenetic mechanisms that influence brain development, as in the case of ASD, when gene methylation dysregulation is present. Our analysis revealed 853 differentially methylated CpG in ASD patients, affecting 509 genes across the genome. Enrichment analysis showed five related diseases, including autistic disorder and mental disorders, which are particularly significant. In this work, we identified 64 genes that were previously reported in the SFARI gene database, classified according to their impact index. Additionally, we identified new genes that have not been previously reported as candidates with differences in the methylation patterns of Mexican children with ASD.

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13. Nenadić I, Meller T, Evermann U, Pfarr JK, Federspiel A, Walther S, Grezellschak S, Abu-Akel A. Modelling the overlap and divergence of autistic and schizotypal traits on hippocampal subfield volumes and regional cerebral blood flow. Molecular psychiatry. 2023.

Psychiatric disorders show high co-morbidity, including co-morbid expressions of subclinical psychopathology across multiple disease spectra. Given the limitations of classical case-control designs in elucidating this overlap, new approaches are needed to identify biological underpinnings of spectra and their interaction. We assessed autistic-like traits (using the Autism Quotient, AQ) and schizotypy – as models of subclinical expressions of disease phenotypes and examined their association with volumes and regional cerebral blood flow (rCBF) of anterior, mid- and posterior hippocampus segments from structural MRI scans in 318 and arterial spin labelling (ASL) in 346 nonclinical subjects, which overlapped with the structural imaging sample (N = 298). We demonstrate significant interactive effects of positive schizotypy and AQ social skills as well as of positive schizotypy and AQ imagination on hippocampal subfield volume variation. Moreover, we show that AQ attention switching modulated hippocampal head rCBF, while positive schizotypy by AQ attention to detail interactions modulated hippocampal tail rCBF. In addition, we show significant correlation of hippocampal volume and rCBF in both region-of-interest and voxel-wise analyses, which were robust after removal of variance related to schizotypy and autistic traits. These findings provide empirical evidence for both the modulation of hippocampal subfield structure and function through subclinical traits, and in particular how only the interaction of phenotype facets leads to significant reductions or variations in these parameters. This makes a case for considering the synergistic impact of different (subclinical) disease spectra on transdiagnostic biological parameters in psychiatry.

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14. Olaguez-Gonzalez JM, Chairez I, Breton-Deval L, Alfaro-Ponce M. Machine Learning Algorithms Applied to Predict Autism Spectrum Disorder Based on Gut Microbiome Composition. Biomedicines. 2023; 11(10).

The application of machine learning (ML) techniques stands as a reliable method for aiding in the diagnosis of complex diseases. Recent studies have related the composition of the gut microbiota to the presence of autism spectrum disorder (ASD), but until now, the results have been mostly contradictory. This work proposes using machine learning to study the gut microbiome composition and its role in the early diagnosis of ASD. We applied support vector machines (SVMs), artificial neural networks (ANNs), and random forest (RF) algorithms to classify subjects as neurotypical (NT) or having ASD, using published data on gut microbiome composition. Naive Bayes, k-nearest neighbors, ensemble learning, logistic regression, linear regression, and decision trees were also trained and validated; however, the ones presented showed the best performance and interpretability. All the ML methods were developed using the SAS Viya software platform. The microbiome’s composition was determined using 16S rRNA sequencing technology. The application of ML yielded a classification accuracy as high as 90%, with a sensitivity of 96.97% and specificity reaching 85.29%. In the case of the ANN model, no errors occurred when classifying NT subjects from the first dataset, indicating a significant classification outcome compared to traditional tests and data-based approaches. This approach was repeated with two datasets, one from the USA and the other from China, resulting in similar findings. The main predictors in the obtained models differ between the analyzed datasets. The most important predictors identified from the analyzed datasets are Bacteroides, Lachnospira, Anaerobutyricum, and Ruminococcus torques. Notably, among the predictors in each model, there is the presence of bacteria that are usually considered insignificant in the microbiome’s composition due to their low relative abundance. This outcome reinforces the conventional understanding of the microbiome’s influence on ASD development, where an imbalance in the composition of the microbiota can lead to disrupted host-microbiota homeostasis. Considering that several previous studies focused on the most abundant genera and neglected smaller (and frequently not statistically significant) microbial communities, the impact of such communities has been poorly analyzed. The ML-based models suggest that more research should focus on these less abundant microbes. A novel hypothesis explains the contradictory results in this field and advocates for more in-depth research to be conducted on variables that may not exhibit statistical significance. The obtained results seem to contribute to an explanation of the contradictory findings regarding ASD and its relation with gut microbiota composition. While some research correlates higher ratios of Bacillota/Bacteroidota, others find the opposite. These discrepancies are closely linked to the minority organisms in the microbiome’s composition, which may differ between populations but share similar metabolic functions. Therefore, the ratios of Bacillota/Bacteroidota regarding ASD may not be determinants in the manifestation of ASD.

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15. Papadopoulos A, Fouska S, Tafiadis D, Trimmis N, Plotas P, Siafaka V. Psychometric Properties of the Greek Version of the Autism Parenting Stress Index (APSI) among Parents of Children with Autism Spectrum Disorder. Diagnostics (Basel, Switzerland). 2023; 13(20).

(1) Background: This study aimed to validate the Greek version of the Autism Parenting Stress Index (APSI) among parents of children with ASD. (2) Methods: The translated version was administered to 113 parents (Male: 12, Female: 101, 39.24 years old, SD 6.70, age range, 25-58) of children diagnosed with ASD and 127 parents (Male: 24, Female: 103, 41.08 years old, SD 6.22, age range: 27-56) of typically developing children. (3) Results: Significant differences between the APSI total scores and three domains between groups were observed. Although the initial factor structure could not be replicated, the APSI’s internal consistency was excellent (a = 0.914), with a high positive item-total correlation (0.900-0.917). The APSI’s test-retest reliability was excellent, showing an ICC equal to 0.922 [95%, CI: 0.900-0.940]. The APSI’s total score cut-off point was equal to 12.00 (AUC 0.845, p < 0.001) with a sensitivity of 0.839 and 1-specificity of 0.220. A principal component analysis of the 13 items, using varimax rotations, identified three factors, which explained approximately 45.8% of the overall variance. (4) Conclusions: The Greek version of the APSI exhibited discriminant validity for measuring parents of children with ASD. Greek health professionals can use it to assess the stress experienced by parents of children with ASD.

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16. Sadeh H, Meiri G, Zigdon D, Ilan M, Faroy M, Michaelovski A, Sadaka Y, Dinstein I, Menashe I. Adherence to treatment and parents’ perspective about effectiveness of melatonin in children with autism spectrum disorder and sleep disturbances. Child and adolescent psychiatry and mental health. 2023; 17(1): 123.

OBJECTIVE: Melatonin is considered an effective pharmacological treatment for the sleep disturbances that are reported in > 50% of children with autism spectrum disorder (ASD). However, real-life data about the long-term course and effectiveness of melatonin treatment in children with ASD is lacking. METHODS: In this retrospective cohort study, we assessed the adherence to melatonin treatment and parents’ perspective of its effect on sleep quality and daytime behavior in children with ASD via a parental phone survey of children in the Azrieli National Center for Autism and Neurodevelopment Research (ANCAN) database. Cox regression analysis was used to assess the effect of key demographic and clinical characteristics on treatment adherence. RESULTS: Melatonin was recommended for ~ 8% of children in the ANCAN database. These children were characterized by more severe symptoms of autism. The median adherence time for melatonin treatment exceeded 88 months, with the most common reason for discontinuation being a lack of effectiveness (14%). Mild side-effects were reported in 14% of children, and 86%, 54%, and 45% experienced improvements in sleep onset, sleep duration and night awakenings, respectively. Notably, melatonin also improved the daytime behaviors of > 28% of the children. Adherence to treatment was independently associated with improvements in night awakenings and educational functioning (aHR = 0.142, 95%CI = 0.036-0.565; and aHR = 0.195, 95%CI = 0.047-0.806, respectively). CONCLUSIONS: Based on parents’ report, melatonin is a safe and effective treatment that improves both sleep difficulties and daily behavior of children with ASD.

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17. Sidulova M, Park CH. Conditional Variational Autoencoder for Functional Connectivity Analysis of Autism Spectrum Disorder Functional Magnetic Resonance Imaging Data: A Comparative Study. Bioengineering (Basel, Switzerland). 2023; 10(10).

Generative models, such as Variational Autoencoders (VAEs), are increasingly employed for atypical pattern detection in brain imaging. During training, these models learn to capture the underlying patterns within « normal » brain images and generate new samples from those patterns. Neurodivergent states can be observed by measuring the dissimilarity between the generated/reconstructed images and the input images. This paper leverages VAEs to conduct Functional Connectivity (FC) analysis from functional Magnetic Resonance Imaging (fMRI) scans of individuals with Autism Spectrum Disorder (ASD), aiming to uncover atypical interconnectivity between brain regions. In the first part of our study, we compare multiple VAE architectures-Conditional VAE, Recurrent VAE, and a hybrid of CNN parallel with RNN VAE-aiming to establish the effectiveness of VAEs in application FC analysis. Given the nature of the disorder, ASD exhibits a higher prevalence among males than females. Therefore, in the second part of this paper, we investigate if introducing phenotypic data could improve the performance of VAEs and, consequently, FC analysis. We compare our results with the findings from previous studies in the literature. The results showed that CNN-based VAE architecture is more effective for this application than the other models.

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18. Tizabi Y, Bennani S, El Kouhen N, Getachew B, Aschner M. Interaction of Heavy Metal Lead with Gut Microbiota: Implications for Autism Spectrum Disorder. Biomolecules. 2023; 13(10).

Autism Spectrum Disorder (ASD), a neurodevelopmental disorder characterized by persistent deficits in social interaction and communication, manifests in early childhood and is followed by restricted and stereotyped behaviors, interests, or activities in adolescence and adulthood (DSM-V). Although genetics and environmental factors have been implicated, the exact causes of ASD have yet to be fully characterized. New evidence suggests that dysbiosis or perturbation in gut microbiota (GM) and exposure to lead (Pb) may play important roles in ASD etiology. Pb is a toxic heavy metal that has been linked to a wide range of negative health outcomes, including anemia, encephalopathy, gastroenteric diseases, and, more importantly, cognitive and behavioral problems inherent to ASD. Pb exposure can disrupt GM, which is essential for maintaining overall health. GM, consisting of trillions of microorganisms, has been shown to play a crucial role in the development of various physiological and psychological functions. GM interacts with the brain in a bidirectional manner referred to as the « Gut-Brain Axis (GBA) ». In this review, following a general overview of ASD and GM, the interaction of Pb with GM in the context of ASD is emphasized. The potential exploitation of this interaction for therapeutic purposes is also touched upon.

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19. Zaffanello M, Piacentini G, Nosetti L, Zoccante L. Sleep Disordered Breathing in Children with Autism Spectrum Disorder: An In-Depth Review of Correlations and Complexities. Children (Basel, Switzerland). 2023; 10(10).

Sleep-disordered breathing is a significant problem affecting the pediatric population. These conditions can affect sleep quality and children’s overall health and well-being. Difficulties in social interaction, communication, and repetitive behavioral patterns characterize autism spectrum disorder. Sleep disturbances are common in children with ASD. This literature review aims to gather and analyze available studies on the relationship between SDB and children with autism spectrum disorder. We comprehensively searched the literature using major search engines (PubMed, Scopus, and Web of Science). After removing duplicates, we extracted a total of 96 records. We selected 19 studies for inclusion after a thorough title and abstract screening process. Seven articles were ultimately incorporated into this analysis. The research findings presented herein emphasize the substantial influence of sleep-disordered breathing on pediatric individuals diagnosed with autism spectrum disorder (ASD). These findings reveal a high incidence of SDB in children with ASD, emphasizing the importance of early diagnosis and specialized treatment. Obesity in this population further complicates matters, requiring focused weight management strategies. Surgical interventions, such as adenotonsillectomy, have shown promise in improving behavioral issues in children with ASD affected by OSA, regardless of their obesity status. However, more comprehensive studies are necessary to investigate the benefits of A&T treatment, specifically in children with ASD and OSA. The complex relationship between ASD, SDB, and other factors, such as joint hypermobility and muscle hypotonia, suggests a need for multidisciplinary treatment approaches. Physiotherapy can play a critical role in addressing these intricate health issues. Early sleep assessments and tailored weight management strategies are essential for timely diagnosis and intervention in children with ASD. Policy initiatives should support these efforts to enhance the overall well-being of this population. Further research is crucial to understand the complex causes of sleep disturbances in children with ASD and to develop effective interventions considering the multifaceted nature of these conditions.

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