Autism Spectrum Disorder Research Articles

Predicting neurodevelopmental disorders using machine learning models and electronic health records - status of the field.

Machine learning (ML) is increasingly used to identify patterns that could predict neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). One key source of multilevel data for ML prediction models includes population-based registers and electronic health records. These can contain rich information on individual and familial medical histories and socio-demographics. This review summarizes studies published between 2010-2022 that used ML algorithms to develop predictive models for NDDs using population-based registers and electronic health records. A literature search identified 1191 articles, of which 32 were retained. Of these, 47% developed ASD prediction models and 25% ADHD models. Classical ML methods were used in 82% of studies and in particular tree-based prediction models performed well. The sensitivity of the models was lower than 75% for most studies, while the area under the curve (AUC) was greater than 75%. The most important predictors were patient and familial medical history and sociodemographic factors. Using private in-house datasets makes comparing and validating model generalizability across studies difficult. The ML model development and reporting guidelines were adopted only in a few recently reported studies. More work is needed to harness the power of data for detecting NDDs early.

The role of co-occurring conditions and genetics in the associations of eating disorders with attention-deficit/hyperactivity disorder and autism spectrum disorder.

Eating disorders (EDs) commonly co-occur with other psychiatric and neurodevelopmental disorders including attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD); however, the pattern of family history and genetic overlap among them requires clarification. This study investigated the diagnostic, familial, and genetic associations of EDs with ADHD and ASD. The nationwide population-based cohort study included all individuals born in Denmark, 1981-2008, linked to their siblings and cousins. Cox regression was used to estimate associations between EDs and ADHD or ASD, and mediation analysis was used to assess the effects of intermediate mood or anxiety disorders. Polygenic scores (PGSs) were used to investigate the genetic association between anorexia nervosa (AN) and ADHD or ASD. Significantly increased risk for any ED was observed following an ADHD or ASD diagnosis. Mediation analysis suggested that intermediate mood or anxiety disorders could account for 44%-100% of the association between ADHD or ASD and ED. Individuals with a full sibling or maternal half sibling with ASD had increased risk of AN compared to those with siblings without ASD. A positive association was found between ASD-PGS and AN risk whereas a negative association was found between AN-PGS and ADHD. In this study, positive phenotypic associations between EDs and ADHD or ASD, mediation by mood or anxiety disorder, and genetic associations between ASD-PGS and AN and between AN-PGS and ADHD were observed. These findings could guide future research in the development of new treatments that can mitigate the development of EDs among individuals with ADHD or ASD.

Atypical brain network topology of the triple network and cortico-subcortical network in autism spectrum disorder.

The default mode network (DMN), salience network (SN), and central executive control network (CEN) form the well-known triple network, providing a framework for understanding various neurodevelopmental and psychiatric disorders. However, the topology of this network remains unclear in autism spectrum disorder (ASD). To gain a more profound understanding of ASD, we explored the topology of the triple network in ASD. Additionally, the striatum and thalamus are pivotal centres of information transmission within the brain, and the realization of various brain functions requires the coordination of cortical and subcortical structures. Therefore, we also investigated the topology of the cortico-subcortical network in ASD, which consists of the DMN, SN, CEN, striatum, and thalamus. Resting-state functional magnetic resonance imaging data on 208 ASD patients and 278 typically developing (TD) controls (8-18 years old) were obtained from the Autism Brain Imaging Data Exchange database. We performed graph theory analysis on the triple network and the cortico-subcortical network. The results showed that the triple network's clustering coefficient, lambda, and network local efficiency values were significantly lower in ASD, and the nodal degree and efficiency of the medial prefrontal cortex also decreased. For the cortico-subcortical network, the sigma, clustering coefficient, gamma, and network local efficiency showed the same reduction, and the altered clustering coefficient negatively correlated with ASD manifestations. In addition, the interaction between the DMN and CEN was more robust in ASD patients. These findings enhance our understanding of ASD and suggest that subcortical structures should be more considered in future ASD related studies.

An online survey of perspectives towards the impact of the covid-19 pandemic amongst caregivers of adolescents with ASD.

The coronavirus disease (COVID-19) pandemic has had a negative impact on the health and mental health of adolescents and adolescents with autism spectrum disorders (ASD) and their caregivers, have been disproportionally affected. The purpose of this study was to investigate the impact of COVID-19 on Thai caregivers and adolescents with ASD. This study used an online survey with closed and free text questions to investigate how the pandemic had impacted on social skills development and psychological variables, and perceived needs for support. The survey link was shared to parents via the Yuwaprasart Withayopathum Child and Adolescent Hospital and the social media platforms of known ASD stakeholder networks in Thailand. Binary logistic regression was used to investigate the relationships between sociodemographic characteristics, service use, and social skills problems experienced by adolescents during the pandemic. Content analysis was applied to analyse free-text data. A total of 376 caregivers of adolescents with ASD aged 10-19 years completed the survey, of which 364 were included in the analysis. In total, 38.7% of caregivers reported that during the pandemic the social skills of their adolescent family member had worsened. Most families reported that they were able to continue to access support from healthcare and educational services, albeit in different ways than pre-pandemic, during the acute stages of the pandemic which benefited the maintenance of ASD symptoms and social skills. Factors identified as reducing the odds of a worsening in social skills during the pandemic included; regular access to treatment for adolescents (odds ratio [OR] = 0.55, confidence interval 95% (CI) 0.32-0.98, p = 0.044), caregivers feeling that they had sufficient support from hospitals (OR = 0.46, 95% CI 0.26-0.81, p = 0.007) and older age of adolescents (OR = 0.53, CI 0.29-0.99, p = 0.047). The qualitative free text comments showed that the caregivers felt that greater information on managing adolescent behaviours, opportunities for adolescents to practice social skills, and the provision of greater emotional support and material assistance from healthcare professionals during the pandemic would have helped them to care for the adolescents with ASD. Regular access to services, support from hospitals during the pandemic and older age in adolescence may have helped prevent the worsening of the social skills problems of adolescents with ASD.

Epileptic encephalopathy, autism and cognitive deficit caused by the SYNGAP1 gene mutation

The paper analyzes data from scientific publications and presents a clinical case study of a rare genetic epileptic encephalopathy caused by a mutation in the SYNGAP1 gene. The case study focuses on a 4-year-old girl who has been diagnosed with epileptic encephalopathy due to the mutation. The paper describes the anamnesis of the child’s illness, including family history, neurological, neuropsychological, and speech assessments, as well as the results of genetic testing, electroencephalography, and magnetic resonance imaging (MRI). The findings indicate that the main symptoms of the condition are typically epilepsy, autism spectrum disorder, difficulty with phrasal speech, and mental retardation. Common types of seizures include atypical absence seizures, myoclonic seizures, atonic seizures, and eyelid myoclonia with absences. On the electroencephalogram, there is a slowdown in occipital activity and diffuse, prolonged «peak-polypic-slow-wave» complexes. Pathognomonic neuroimaging changes in the brain are typically absent. Valproic acid, levetiracetam, and ethosuximide have been shown to be the most effective treatments for controlling epileptic seizures. Due to the rarity of this syndrome, the authors have provided a detailed clinical case report from their practice.Conclusion. SYNGAP1-related epileptic encephalopathy has a specific clinical presentation, including characteristic EEG findings and a particular pattern of seizures. The diagnostic approach for children with this condition, autism spectrum disorder, and delayed language development should include video electroencephalography with sleep deprivation, as well as genetic testing if necessary, using next-generation sequencing, to ensure early detection and appropriate treatment planning.

Multi-Informant Universal Mental Health Screening for Preschool-Aged Children by Parents and Educators: A PRISMA Systematic Review.

Children develop rapidly in the preschool period, making accurate appraisals of mental health (MH) difficult. The preschool years are a key period for early identification of MH concerns and could benefit from multi-informant, universal MH screening (UMHS). This systematic review aimed to identify multi-informant UMHS measures for preschool-aged children, and to examine their clinical utility, effectiveness, and acceptability. Studies reporting the predictive and incremental validity, effectiveness or acceptability of parent and educator-report UMHS measures for children aged 3-5years were identified through CINAHL, Embase, ERIC, Medline, PsycINFO, Scopus and Web of Science. Studies were excluded if screening was not the primary focus, not universal, single informant, or primarily focussed on Autism Spectrum Disorder. A total of 11 studies using 10 measures was identified. Ten studies screened for broad MH difficulties. Three educator-report and one parent- and educator-report measures had acceptable predictive validity. One study reporting incremental validity found that adding educator-report to parent ratings significantly improved the identification of MH concerns. No studies reported on effectiveness. Three studies that explored acceptability reported strong support for either UMHS in general or specific measures. There are promising results that UMHS can accurately identify child MH concerns in the preschool period using parent and educator reports. However, with few of the examined measures reaching the benchmark standards for predictive validity and only one study examining incremental validity, further research is needed to establish clinical utility. UMHS with preschool populations appears to be acceptable; future studies should further examine multi-informant screening in preschool populations. This systematic review was registered with the International Prospective Register of Systematic Reviews (PROSPERO; https://www.crd.york.ac.uk/prospero ; registration number: CRD 42022383426).

Pineal gland volume in children with intellectual disability.

Pineal gland volume (PGV), which is associated with sleep and circadian rhythm, is known to be changed in some psychiatric disorders such as major depression, mood disorders and schizophrenia. This study aimed to compare the PGV of children with mild and moderate intellectual disability (ID) and healthy children. This multicentre retrospective study included 40 children with ID (patient group), aged 6-12 years and 40 age- and sex-matched healthy children (control group). The children were examined for their sociodemographic characteristics and for PGV using magnetic resonance imaging. The PGV of the patient group was significantly larger than that of the controls (p = 0.023). There was no statistically significant difference in PGV between mild and moderate ID. A moderate and positive correlation was found between Weschler Intelligence Scale for Children-revised (WISC-R) performance score and PGV (p = 0.049, r = 0.313) only in the patient group. In the receiver operating characteristic analysis, the area under the curve was 0.648, and the sensitivity was 70.0%, and the specificity was 60.0%. In conclusion, this study demonstrated that the increased PGV levels were associated with autism spectrum disorder (ASD) and PGV could be a risk factor in the aetiology of ID. Further research with larger sample sizes is needed to clarify this issue.

Early diagnosis of autism spectrum disorders in children: what pediatricians should know

The issue of autism spectrum disorder (ASD) in children is a significant concern at present. In the Russian Federation, there has been a rapid increase in the incidence of ASD and the number of children diagnosed with this condition, making childhood autism a major medical and social issue. Pediatricians need to be trained in the diagnostic criteria for early identification of this disorder. The main diagnostic methods involve monitoring the child’s development, with the district pediatrician playing a crucial role. The knowledge and expertise of the doctor significantly influences the timeliness of diagnosis and the prescription of appropriate interventions, which can lead to positive outcomes and prevent further symptom progression. It is essential for pediatricians to carefully listen to families’ concerns about any developmental or behavioral issues in their children. According to our research, 32% of families did not receive timely assistance. The most common complaint made by parents was delayed speech development and impaired communication. To identify autism spectrum disorders, doctors should regularly assess a child’s neuropsychiatric development and monitor them in various situations to assess their behavior and interaction with others. If any deviations are detected, a questionnaire such as the M-CHAT (a modified list of questions for detecting autism in children) should be used and the patient referred to a psychiatrist for further consultation. Our study highlighted the need for pediatricians to better understand the signs and symptoms of autism spectrum disorders.

Prediction for children with autism spectrum disorder based on digital behavioral features during free play.

Play is an indispensable and meaningful activity in children's daily life. Research has shown that autistic children often exhibit differences in play development. The core traits of autism, such as distinct patterns in social interaction and communication, focused interests, and repetitive behaviors, frequently manifest in their play. Therefore, play may serve as an insightful measure of these differences. Unlike previous studies focusing on play behaviors only, we explored other behaviors associated with autism during free play, and constructed a clinical prediction model for effectively screening autistic children. Participants, including 123 autistic children and 123 neurotypical children aged 1-6 years, engaged in a 1.5-min free play with fixed toys, which was videotaped. A novel behavior-coding scheme was used to code these videos for 19 autistic behaviors, including play. The coding details of the 19 behaviors were then converted and expanded to 81 digital behavior indicators, including counts, duration, and proportion. The autistic children showed less functional play and imaginative play and reduced social communication and interactions, such as eye contact, facial expressions, and vocalizations, compared to the neurotypical children during free play. Furthermore, 5 behavioral indicators were selected for the prediction model through stepwise logistic regression, including 1 on socially oriented vocalizations and 4 on count and duration of functional play. The receiver operating characteristic (ROC) curve revealed a good prediction performance with an area under the curve (AUC) of 0.826, a sensitivity of 85.4%, and a specificity of 68.3%. Our findings highlight differences in play performance and social communication and interactions during free play among autistic children. Based on these findings, we constructed a good clinical prediction model, which might be a potential digital tool used by clinicians to effectively screen autistic children.

Parental experiences and perspectives of healthcare providers' genetic testing recommendations for their children diagnosed with autism spectrum disorder in the United States.

Although genetic testing is recommended for all children diagnosed with autism spectrum disorder (ASD) in the United States, it remains unclear how many parents have received and followed these recommendations. This study aimed to assess parental experiences and perspectives of healthcare providers' genetic testing recommendations. A total of 1043 parents of children with ASD from Simons Foundation Powering Autism Research for Knowledge completed an online survey. Only about one-third of the parents (34.2%) reported that their children's providers had recommended genetic testing. Factors associated with whether parents received these recommendations included the type of healthcare providers diagnosing ASD, parents' knowledge of genetic testing, the age of their children's diagnosis, and the presence of certain co-occurring medical conditions in their children. Our study also revealed that most parents (76.9%) who received recommendations had pursued genetic testing for their children. Adherence to the recommendations was associated with the characteristics of the parents (i.e., age and employment status) and children (i.e., gender), and their trust in the information from providers. The findings highlight the critical role of healthcare providers in facilitating genetic testing among families of children with ASD. Healthcare providers are recommended to increase their competencies and practice in providing genetic testing recommendations for ASD, assist parents in navigating testing challenges, and support parents through the testing process.

Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina

Background/Objectives: The study of microbiome composition shows positive indications for application in the diagnosis and treatment of many conditions and diseases. One such condition is autism spectrum disorder (ASD). We aimed to analyze gut microbiome samples from children in Bosnia and Herzegovina to identify microbial differences between neurotypical children and those with ASD. Additionally, we developed machine learning classifiers to differentiate between the two groups using microbial abundance and predicted functional pathways. Methods: A total of 60 gut microbiome samples (16S rRNA sequences) were analyzed, with 44 from children with ASD and 16 from neurotypical children. Four machine learning algorithms (Random Forest, Support Vector Classification, Gradient Boosting, and Extremely Randomized Tree Classifier) were applied to create eight classification models based on bacterial abundance at the genus level and KEGG pathways. Model accuracy was evaluated, and an external dataset was introduced to test model generalizability. Results: The highest classification accuracy (80%) was achieved with Random Forest and Extremely Randomized Tree Classifier using genus-level taxa. The Random Forest model also performed well (78%) with KEGG pathways. When tested on an independent dataset, the model maintained high accuracy (79%), confirming its generalizability. Conclusions: This study identified significant microbial differences between neurotypical children and children with ASD. Machine learning classifiers, particularly Random Forest and Extremely Randomized Tree Classifier, achieved strong accuracy. Validation with external data demonstrated that the models could generalize across different datasets, highlighting their potential use.

Impact of the COVID-19 pandemic on children and adolescents with autism spectrum disorder and their caregivers

Objective: To analyze the impact of the COVID-19 pandemic and social distancing on children and adolescents with autism spectrum disorder (ASD) and their caregivers. Methods: Observational, descriptive, and cross-sectional study conducted with parents/caregivers of children with ASD through an online questionnaire with 39 questions. Data were collected from October 2020 to January 2021, referring to the critical period of the pandemic in Ceará, from March to June 2020. Results: Of the 122 research participants (children/adolescents aged 2 to 18 years, average of 6.7 years), 87.7% interrupted multidisciplinary treatments during isolation. Most caregivers (86.8%) had more difficulties managing the children's free time. Behavioral problems became more intense for 61.5% and more frequent for 59.8% of participants. Difficulties in managing meals were reported by 39.3% of participants, and 97.1% stated that problems in managing autonomy were amplified. Behavioral regressions and worsening symptoms occurred in 81.1% of cases. Children and adolescents with pre-pandemic behavioral problems showed a significantly greater increase in the intensity (OR = 3.87, p = 0.05) and frequency (OR = 3.42, p = 0.05) of behavioral problems. In contrast, being an only child proved to be a protective factor against the negative impacts of isolation, with a significant reduction in the intensification (OR = 0.16, p < 0.05) and frequency (OR = 0.08, p < 0.01) of behavioral problems. Conclusion: The COVID-19 pandemic and social distancing negatively altered behavior, eating, and self-care patterns in children and adolescents with ASD, making this period more challenging for their caregivers.

Towards a Satisfactory Future—Multiprofessional Rehabilitation for Young Persons with ADHD or ASD

There is a lack of knowledge about what kind of support should be offered in adulthood for persons with attention-deficit/hyperactivity disorder (ADHD) or autism spectrum disorder (ASD) to promote inclusive participation in meaningful life domains. The core components of multiprofessional rehabilitation intervention for young adults are explored from the perspective of multiprofessional teams. This qualitative study adopts a pragmatic perspective on the core components of rehabilitation. Twenty-six professionals participated in vignette-based focus group interviews (n = 5), and thematic reflexive analysis was used to abductively analyze the data. A total of ten core components were identified. Nine of them were aggregated into three categories: (1) rehabilitation readiness (two core components), (2) adaptive progress in personal goals (four core components), and (3) rehabilitation continuum (three core components). The overarching tenth core component is focusing on the personal goals of daily life, work, studies, and social interaction. A collaborative relationship between the client and professional is essential to ensure adaptive progress and to foster clients’ self-determination. The focus should be on strengths and solutions instead of deficits and challenges. To establish rehabilitation continuum, it is essential to collaborate within the clients’ networks and to promote awareness and inclusive opportunities for working and studying for people with ADHD and ASD.

Development of personalized profiles of students with autism spectrum disorder for interactive interventions with robots to enhance language and social skills

The inclusion of students with autism spectrum disorder (ASD) in mainstream education (primary and secondary, in the range of 4-5 to 8-10 years old) is a complex task that has long challenged both educators and health professionals. However, the correct use of digital technologies such as personalization settings and interaction with robots has clearly shown how these new technologies can benefit ASD students. However, it is essential to characterize the profile, problems, and needs of each student, since it is not possible to generalize an accessible approach for all users. The work presented shows the creation and validation, through pilot tests, of an instrument that outlines the main needs of a student with ASD, based on behavioral variables. In a later phase, instructional sequences will be designed and adapted through digital tablets and interaction with a robot to improve specific aspects identified in the initial profile. The results demonstrate the method’s ability to assess and prioritize profiles satisfactorily which helps create a design adjusted to each student. The first pilot tests have been well received by ASD students, who have shown increased interest in the contents and methods used in this approach. Motivation levels and engagement have also increased, and social interactions with their peers have improved.

Ligand distances as key predictors of pathogenicity and function in NMDA receptors.

Genetic variants in the genes GRIN1, GRIN2A, GRIN2B, and GRIN2D, which encode subunits of the N-methyl-D-aspartate receptor (NMDAR), have been associated with severe and heterogeneous neurologic and neurodevelopmental disorders, including early onset epilepsy, developmental and epileptic encephalopathy, intellectual disability, and autism spectrum disorders. Missense variants in these genes can result in gain or loss of the NMDAR function, requiring opposite therapeutic treatments. Computational methods that predict pathogenicity and molecular functional effects of missense variants are therefore crucial for therapeutic applications. We assembled 223 missense variants from patients, 631 control variants from the general population, and 160 missense variants characterized by electrophysiological readouts that show whether they can enhance or reduce the function of the receptor. This includes new functional data from 33 variants reported here, for the first time. By mapping these variants onto the NMDAR protein structures, we found that pathogenic/benign variants and variants that increase/decrease the channel function were distributed unevenly on the protein structure, with spatial proximity to ligands bound to the agonist and antagonist binding sites being a key predictive feature for both variant pathogenicity and molecular functional consequences. Leveraging distances from ligands, we developed two machine-learning based predictors for NMDA variants: a pathogenicity predictor which outperforms currently available predictors and the first molecular function (increase/decrease) predictor. Our findings can have direct application to patient care by improving diagnostic yield for genetic neurodevelopmental disorders and by guiding personalized treatment informed by the knowledge of the molecular disease mechanism.

Report of one case with de novo mutation in TLK2 and literature review.

TLK2 variants were identified as the cause for several neurodevelopmental disorders by impacting brain development. The incidence of mutation in TLK2 is low, which has common clinical features with other rare diseases. Herein, we reported a 5-year-old boy with TLK2 heterozygous mutation who presented distinctive facial features, gastrointestinal diseases, short stature, language delay, autism spectrum disorder, heart diseases, abnormal genitourinary system and skeletal abnormality. Moreover, we reviewed previous reported patients and our case in order to investigate more information on genotype-phenotype correlation and identify significant clinical characteristics for better diagnosis.

Visual attention modulates mu suppression during biological motion perception in autistic individuals.

There has been a lot of controversy regarding mirror neuron function in autism spectrum disorder (ASD), in particular during the observation of biological motions (BM). Here, we directly explored the link between visual attention and brain activity in terms of mu suppression, by simultaneously recording eye-tracking and EEGs during BM tasks. Nineteen autistic children (15 boys, mean age = 11.57 ± 4.28 years) and 19 age-matched neurotypical (NT) children (15 boys, mean age = 11.68 ± 5.22 years) participated in the study. Each participant's eye movement and EEG were simultaneously recorded while watching four BM stimuli (walking, cartwheeling, free-throwing and underarm throwing) and a scrambled condition. Mu (8-13 Hz) suppression index (SI) for central regions was calculated. Fixation counts and percent of fixation time were calculated as indices of eye movements. EEG results revealed significant mu suppressions in the central region in both groups for all BM actions. Eye-tracking results showed that NT children had greater fixation counts and a higher percentage of fixation time than autistic children, indicating greater overall visual attention to BM. Notably, correlational analyses for both groups further revealed that individuals' fixation time and fixation counts were negatively correlated with the mu suppression index for all actions, indicating a strong association between visual attention and mu SI in the central region. Our findings suggest a critical role of visual attention in interpreting mu suppression during action perception in autism.

Investigating frank autism: clinician initial impressions and autism characteristics.

"Frank autism," recognizable through the first minutes of an interaction, describes a behavioral presentation of a subset of autistic individuals that is closely tied to social communication challenges, and may be linked to so-called "prototypical autism." To date, there is no research on frank autism presentations of autistic adolescents and young adults, nor individuals diagnosed with autism spectrum disorder (ASD) in childhood who do not meet diagnostic criteria during or after adolescence (loss of autism diagnosis, LAD). In addition, there are currently no data on the factors that drive frank autism impressions in these adolescent groups. This study quantifies initial impressions of autistic characteristics in 24 autistic, 24 LAD and 26 neurotypical (NT) individuals ages 12 to 39 years. Graduate student and expert clinicians completed five-minute impressions, rated confidence in their own impressions, and scored the atypicality of behaviors associated with impressions; impressions were compared with current gold-standard diagnostic outcomes. Overall, clinicians' impressions within the first five minutes generally matched current gold-standard diagnostic status (clinical best estimate), were highly correlated with ADOS-2 CSS, and were driven primarily by prosodic and facial cues. However, this brief observation did not detect autism in all cases. While clinicians noted some subclinical atypicalities in the LAD group, impressions of the LAD and NT groups were similar. The brief observations in this study were conducted during clinical research, including some semi-structured assessments. While results suggest overall concordance between initial impressions and diagnoses following more thorough evaluation, findings may not generalize to less structured, informal contexts. In addition, our sample was demographically homogeneous and comprised only speaking autistic participants. They were also unmatched for sex, with more females in the non-autistic group. Future studies should recruit samples that are diverse in demographic variables and ability level to replicate these findings and explore their implications. Results provide insights into the behavioral characteristics that contribute to the diagnosis of adolescents and young adults and may help inform diagnostic decision making in the wake of an increase in the demand for autism evaluations later than childhood. They also substantiate claims of an absence of apparent autistic characteristics in individuals who have lost the diagnosis.

The Study of the State of Monoaminergic Systems in the Brain Structures of the Offsprings of Female BALB/C Mice at Different Stages of Formation of Autism Spectrum Disorders

The study of the status of norepinephrine-, dopamine- and serotonergic neurotransmitter systems of BALB/C mice brain structures on 15 and 64 days of postnatal development (PD) in the model of autistic disturbances induced by injection of of sodium valproate (SV, 400 mg/kg, s/c) to pregnant females was carried out using the HPLC/ED method. The level of both catechol- and indolamines in the brain structures of control group mice at the age of 15 days was significantly lower than in adult animals at the age of 64 days. Prenatal administration of SV caused a decrease in all parameters of monoaminergic neurotransmission in the striatum of offspring at the age of 15 days, but had no effect in other brain structures studied. Subsequently, the level of dopamine increased and by the 64th day of PD did not differ from the parameters of the control group. The parameters of the serotonergic system changed in a similar pattern, with the content of serotonin and the serotonin metabolite 5-OIAA in the striatum increasing gradually and reaching maximum values by the 64th day of PR. Our data allows to assume that the administration of SV to pregnant females affects the activity of the dopamine and serotonergic systems of the brain of the offspring, causing a decrease in their activity in the striatum by the 15th day of pregnancy, followed by restoration to control values by the 64th day, which we previously observed in male pups. Thus, the patterns of dynamic changes in the neurochemical profile do not differ between males and females.

O PAPEL DO PROFISSIONAL DE ENFERMAGEM NA ATENÇÃO A CRIANÇAS E ADOLESCENTES COM TRANSTORNO DO ESPECTRO AUTISTA: UMA REVISÃO SISTEMÁTICA

Among the professionals involved in the health care of children with Autism Spectrum Disorder (ASD), nurses stand out as the first to establish contact, maintaining significant proximity with this patient. However, the theme of nursing care aimed at childhood autism is still little disseminated in the scientific community and in the practice of nursing professionals, especially when the focus is the mental health of children and adolescents with ASD. The objective of this study is to investigate the fundamental role of nursing professionals in the care of children and adolescents with Autism Spectrum Disorder (ASD), with an emphasis on promoting the mental health of both these individuals and those who live directly with them. To this end, a qualitative and descriptive research was carried out based on a systematic bibliographic review using the descriptors “Autism Spectrum Disorder”, “Nursing”, “Mental health”, "Child", "Adolescent" in the scientific platforms Google Scholar, PUBMED, LILACS, SCIELO and MEDLINE. A total of 1,098 articles were identified, of which 1,090 were obtained from the Google Scholar database, 4 from MEDLINE, 3 from SCIELO, 1 from PUBMED and none from LILACS. Of this total, 28 were considered eligible after applying the inclusion and exclusion criteria. A huge gap was found in Brazilian research regarding the promotion of mental health of children and adolescents with ASD by nursing professionals. Therefore, it is considered urgent to conduct scientific studies that offer nurses more knowledge about ASD, helping them to develop a critical, analytical and humanized perspective.