Electroencephalographic Abnormalities in Autism Spectrum Disorder: Characteristics and Therapeutic Implications

Short report on a distinct electroencephalogram endophenotype for MTHFR gene variation co-occurring in autism spectrum disorder

Anecdotal reports link a distinct, bilateral, parieto-temporally generated 4.5-Hz rhythm on an electroencephalogram to a methylenetetrahydrofolate reductase gene variant co-occurring in autism spectrum disorder, but the validation of its precision is needed. The electroencephalograms of children with autism spectrum disorder showing the distinct bilateral parieto-temporally generated 4.5-Hz rhythm and their clinical chart report on polymerase chain reaction screening for methylenetetrahydrofolate reductase gene variants, 677C>T and 1298A>C, were retrieved from an outpatient clinic between February 2019 and April 2024. Twenty-five cases were identified. Patients were between 2 and 12 (7 ± 3) years old from Asian (n = 16, 64%), European (n = 5, 20%), African (n = 1, 4%) and mixed (n = 3, 12%) ethnicities. Twenty patients (80%) were positive for 677 C>Theterozygous (n = 3, 15%), 1298A>Cheterozygous (n = 8, 40%) or both (n = 9, 45%). The polymerase chain reaction testing detected neither variant in 5 (20%) patients. Therefore, the electroencephalogram-endophenotype showed 80% precision in identifying methylenetetrahydrofolate reductase gene variant within the sample. This preliminary data support the precision of the proposed distinct, bilateral, parieto-temporally generated 4.5-Hz rhythm in identifying methylenetetrahydrofolate reductase gene variants and its potential clinical applications as a valuable, non-invasive and objective measure within the population.Lay abstractMethylenetetrahydrofolate reductase mutations refer to genetic variations in the methylenetetrahydrofolate reductase enzyme, which plays an important role in folate metabolism. Folate is essential for neural development and signalling. Children with autism spectrum disorder have atypical neural signals compared with control. This study used a non-invasive method to identify a distinct neural signal that may be useful in future screening for methylenetetrahydrofolate reductase mutation in children with autism spectrum disorder. Given that the underlying causes of autism spectrum disorder have multiple genetic factors and often require subjective assessment, this study introduces a potential non-invasive screening method for methylenetetrahydrofolate reductase gene mutation. This method could provide valuable biomarkers for screening and personalised treatments, offering hope for improved risk stratification and bespoke nutritional support and supplements to mitigate the impact on affected individuals and their descendants.

Electroencephalography in Autism Spectrum Disorder

Background/Objectives: Electroencephalography (EEG) has been widely used to differentiate individuals with autism spectrum disorder (ASD) and co-occurring conditions, particularly epilepsy. However, the relationship between EEG abnormalities and core features of ASD remains unclear. This study reviews the potential impact of EEG findings on the development, behavior, sleep, and seizure occurrence in ASD patients. Additionally, it evaluates whether routine EEG testing is warranted for all ASD patients, particularly in the absence of clinical seizures. Methods: A systematic review was conducted that covered literature published between 2014 and 2024. The review focused on EEG abnormalities, both epileptiform and non-epileptiform, in individuals with ASD. Studies were selected based on predefined inclusion criteria, emphasizing the prevalence, type, and clinical relevance of EEG findings. The analysis also included a critical assessment of whether EEG abnormalities correlate with specific ASD symptoms, such as cognitive impairment, speech delay, or behavioral issues. Results: EEG abnormalities were reported in 23-80% of ASD patients, indicating a broad range of findings. Despite their frequent occurrence, the evidence linking these abnormalities to specific clinical symptoms remains inconclusive. Some studies suggest an association between epileptiform patterns and more severe ASD traits, while others do not confirm this. Furthermore, the effectiveness of anticonvulsant treatment in children with EEG abnormalities and no seizures remains uncertain, with limited supporting data. Conclusions: Given the uncertain relationship between EEG findings and ASD symptoms, routine EEG testing for all children with ASD appears unnecessary. EEG should be considered primarily when epilepsy is clinically suspected.

Analyzing the effects of high autistic traits on neural markers of learning and memory: An EEG approach analysis

OBJECTIVE

A body of electroencephalographic (EEG) research demonstrates that executive functioning (EF) differences exist in autistic people. Here, we aimed to investigate how and to what extent these EF differences appear in people with high autistic traits in contrast to a low autistic traits comparison.

METHODS

The present study used a series of EEG markers (frontal theta power, frontal beta power, the reward positivity ERP component, and the P300 ERP component) to examine potential differences in EF over the course of gambling and oddball tasks. Qualitative research measures to include the perspectives of the autistic people who took part in the study were also used.

RESULTS

While frontal theta and beta power differed between groups, we observed no significant component or correlational differences. However, it was found that high autistic traits participants perceived their task performance as worse than low autistic traits participants despite task performance being equal across groups.

CONCLUSIONS

EF differences as measured by frontal theta and beta power were observed across groups. Self-perception of task performance may differ in high autistic traits participants when asked to complete tasks under a time constraint.

Investigation of Electroencephalographic Aspects, Adaptive Features, and Clinical Phenotypes in a Group of Children with Autism-A Pilot Study

(1) Background: Autism, as an important global problem that affects many phenotypically different individuals, is associated with electroencephalographic (EEG) abnormalities and adaptability impairment. (2) Materials and Methods: In this retrospective study of a group of 101 autistic children, we aimed to evaluate the presence of EEG abnormalities, adaptive features, and clinical phenotypes via EEG, the Adaptive Behavior Assessment System II (ABAS II) scale, and neurological examination. (3) Results: Our results showed statistically significant associations between the level of adaptability obtained through the ABAS II scale and neurological deficit, specifically in terms of coordination impairment. There were also statistically significant differences between the level of adaptability and clinical phenotypes between autism type groups. (4) Conclusions: This study shows that children with autism are likely to exhibit neurological and adaptive abnormalities. Non-invasive assessment tools, such as EEG recordings, the ABAS II scale, and neurological examination offer valuable support for improved diagnosis and management.

EEG Abnormalities and Phenotypic Correlates in Preschoolers with Autism Spectrum Disorder: A Single-Center Study

Background: The literature suggests the existence of an association between autism spectrum disorders (ASDs) and subclinical electroencephalographic abnormalities (SEAs), which show a heterogeneous prevalence rate (12.5-60.7%) within the pediatric ASD population. The aim of this study was to investigate the EEG findings in a cohort of ASD preschoolers and their correlation with the phenotypic characteristics. Methods: We retrospectively reviewed data on 141 ASD preschoolers evaluated in a tertiary care university hospital over the period 2008-2018. All participants underwent at least one standard polygraphic electroencephalogram (EEG) and a clinical multidisciplinary assessment with standardized instruments. Results: 77 patients (55%) showed SEAs, which were mainly represented by epileptiform discharges (p < 0.00001), especially focal and multifocal (p = 0.010). Abnormal EEG (p = 0.035) and epileptiform discharges (p = 0.014) were associated with seizure onset and were predominant in sleep (p < 0.00001). Patients with abnormal tracing (p = 0.031) and slow abnormalities (p < 0.001) were significantly younger. ASD severity was not found to be correlated with EEG results, which showed a potential, albeit non-significant, association with some psychometric parameters. Very similar results were found when patients were divided according to sex. Conclusions: EEG abnormalities appear to correlate more with ASD internalizing, externalizing and emotional comorbidities, rather than with ASD core symptoms; larger samples are needed to further investigate this association.

A machine learning model based on CHAT-23 for early screening of autism in Chinese children

Introduction

Autism spectrum disorder (ASD) is a neurodevelopmental condition that significantly impacts the mental, emotional, and social development of children. Early screening for ASD typically involves the use of a series of questionnaires. With answers to these questionnaires, healthcare professionals can identify whether a child is at risk for developing ASD and refer them for further evaluation and diagnosis. CHAT-23 is an effective and widely used screening test in China for the early screening of ASD, which contains 23 different kinds of questions.

Methods

We have collected clinical data from Wuxi, China. All the questions of CHAT-23 are regarded as different kinds of features for building machine learning models. We introduce machine learning methods into ASD screening, using the Max-Relevance and Min-Redundancy (mRMR) feature selection method to analyze the most important questions among all 23 from the collected CHAT-23 questionnaires. Seven mainstream supervised machine learning models were built and experiments were conducted.

Results

Among the seven supervised machine learning models evaluated, the best-performing model achieved a sensitivity of 0.909 and a specificity of 0.922 when the number of features was reduced to 9. This demonstrates the model's ability to accurately identify children for ASD with high precision, even with a more concise set of features.

Discussion

Our study focuses on the health of Chinese children, introducing machine learning methods to provide more accurate and effective early screening tests for autism. This approach not only enhances the early detection of ASD but also helps in refining the CHAT-23 questionnaire by identifying the most relevant questions for the diagnosis process.

Effect of Infra Low Frequency (ILF) neurofeedback training on EEG in children with autism spectrum disorders

Objective

To investigate whether Infra-low frequency Neurofeedback (ILF-NFB) training can improve brain electrical activity in children with autism spectrum disorders ASD.

Method

This single arm pre and post intervention study was carried out at IBMS (Institute of Basic Medical Sciences), Khyber Medical University, Peshawar and Shaheed Zulfiqar Ali Bhutto Medical University (SZABMU), Islamabad from January 2021 to December 2022. A purposive sampling technique was used. Thirty-five ASD children (male=24; female=11; 7-17 years) were provided with 30 sessions of infra low frequency (ILF) neurofeedback training for 15-20 minutes, during 10 weeks. Childhood Autism Rating Scale (CARS) scoring was done and electroencephalogram (EEG) activity was compared before and after ILF-NF training sessions.

Results

Around 62.9% participants had mild-moderate autism and 37.1% had severe autism. Wilcoxon Signed rank test revealed a significant decline in delta (Pre-test=47.31±19.22, Post-test=22.07±6.83; p=<0.001), theta (Pre-test=24.75±16.62, Post-test=12.37±3.59; p=<0.001) and alpha (Pre-test=12.01±9.81, Post-test=4.03±1.61; p=< 0.001) waves. Mann Whitney U test exhibited no significant gender differences in EEG pattern before and after neurofeedback except in theta waves (p=0.03) before the intervention.

Conclusion

Decline in delta, theta, beta and alpha waves propose that ILF-NF training can be effective in improving the EEG activity. ILF-NFB can be perceived as a valuable non-invasive, non-pharmacological intervention for improving EEG pattern via reintegration of brain activity resulting in increased the attention and focus, enhanced mental stability and cognitive engagement.

A comprehensive analysis towards exploring the promises of AI-related approaches in autism research

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that presents challenges in communication, social interaction, repetitive behaviour, and limited interests. Detecting ASD at an early stage is crucial for timely interventions and an improved quality of life. In recent times, Artificial Intelligence (AI) has been increasingly used in ASD research. The rise in ASD diagnoses is due to the growing number of ASD cases and the recognition of the importance of early detection, which leads to better symptom management. This study explores the potential of AI in identifying early indicators of autism, aligning with the United Nations Sustainable Development Goals (SDGs) of Good Health and Well-being (Goal 3) and Peace, Justice, and Strong Institutions (Goal 16). The paper aims to provide a comprehensive overview of the current state-of-the-art AI-based autism classification by reviewing recent publications from the last decade. It covers various modalities such as Eye gaze, Facial Expression, Motor skill, MRI/fMRI, and EEG, and multi-modal approaches primarily grouped into behavioural and biological markers. The paper presents a timeline spanning from the history of ASD to recent developments in the field of AI. Additionally, the paper provides a category-wise detailed analysis of the AI-based application in ASD with a diagrammatic summarization to convey a holistic summary of different modalities. It also reports on the successes and challenges of applying AI for ASD detection while providing publicly available datasets. The paper paves the way for future scope and directions, providing a complete and systematic overview for researchers in the field of ASD.

Probiotics, prebiotics, and synbiotics for patients with autism spectrum disorder: a meta-analysis and umbrella review

Background and objective

The potential impact of gut health on general physical and mental well-being, particularly in relation to brain function, has led to a growing interest in the potential health advantages of prebiotics, probiotics, and synbiotics for the management of ASD. A comprehensive meta-analysis and systematic review was conducted in order to evaluate the effectiveness and protection of many drugs targeted at manipulating the microbiota in the treatment of ASD.

Methods

The present study employed a comprehensive examination of various electronic databases yielded a total of 3,393 records that were deemed possibly pertinent to the study. RCTs encompassed a total of 720 individuals between the ages of 2 and 17, as well as 112 adults and participants ranging from 5 to 55 years old, all of whom had received a diagnosis of ASD.

Results

Overall, 10 studies reported Autism-Related Behavioral Symptoms (ARBS). Regarding the enhancement of autism-related behavioral symptoms, there wasn't a statistically significant difference between the intervention groups (combined standardized mean difference = -0.07, 95% confidence interval: -0.39 to 0.24, Z = 0.46, p = 0.65). We observed that in the patients with ASD treated with probiotic frontopolar's power decreased significantly from baseline to endpoints in beta band (Baseline: 13.09 ± 3.46, vs. endpoint: 10.75 ± 2.42, p = 0.043, respectively) and gamma band (Baseline: 5.80 ± 2.42, vs. endpoint: 4.63 ± 1.39, p = 0.033, respectively). Among all tested biochemical measures, a significant negative correlation was found between frontopolar coherence in the gamma band and TNF-α (r = -0.30, p = 0.04).

Conclusion

The existing body of research provides a comprehensive analysis of the developing evidence that indicates the potential of probiotics, prebiotics, and synbiotics as therapeutic therapies for ASD. Our findings revealed that those there was no significant effect of such therapy on autism-related behavioral symptoms, it has significant effect on the brain connectivity through frontopolar power in beta and gamma bands mediated by chemicals and cytokines, such as TNF-α. The psychobiotics showed no serious side-effects.

Age-Related Changes in Epilepsy Characteristics and Response to Antiepileptic Treatment in Autism Spectrum Disorders

Despite the high prevalence of epilepsy in individuals with autism spectrum disorder (ASD), there is little information regarding whether seizure characteristics and treatment effectiveness change across age. Using an online survey, seizure characteristics, effectiveness of antiepileptic treatments, comorbidities, potential etiologies, and ASD diagnosis were collected from individuals with ASD and seizures. We previously reported overall general patterns of treatment effectiveness but did not examine the effect of seizure characteristics or age on antiepileptic treatment effectiveness. Such information would improve the personalized medicine approach to the treatment of seizures in ASD. Survey data from 570 individuals with ASD and clinical seizures were analyzed. Seizure severity (seizure/week) decreased with age of onset of seizures, plateauing in adolescence, with a greater reduction in generalized tonic-clonic (GTC) seizures with age. Seizure severity was worse in those with genetic disorders, neurodevelopmental regression (NDR) and poor sleep maintenance. Carbamazepine and oxcarbazepine were reported to be more effective when seizures started in later childhood, while surgery and the Atkins/modified Atkins Diet (A/MAD) were reported to be more effective when seizures started early in life. A/MAD and the ketogenic diet were reported to be more effective in those with NDR. Interestingly, atypical Landau-Kleffner syndrome was associated with mitochondrial dysfunction and NDR, suggesting a novel syndrome. These interesting findings need to be verified in independent, prospectively collected cohorts, but nonetheless, these data provide insights into novel relationships that may assist in a better understanding of epilepsy in ASD and provide insight into personalizing epilepsy care in ASD.

Autism with co-occurring epilepsy care pathway in Europe

BACKGROUND

Autism and epilepsy often occur together. Epilepsy and other associated conditions have a substantial impact on the well-being of autistic people and their families, reduce quality of life, and increase premature mortality. Despite this, there is a lack of studies investigating the care pathway of autistic children with co-occurring epilepsy in Europe.

METHODS

We analyzed the care pathway for autistic children with associated epilepsy in Italy, Spain, and the United Kingdom from the perspective of caregivers (using a survey aimed at caregivers of autistic children 0-18 years old), the autistic community, and professionals, in order to identify major barriers preventing caregivers and autistic children from receiving timely screening and treatment of possible co-occurring epilepsy.

RESULTS

Across all three countries, an analysis of the current care pathway showed a lack of systematic screening of epilepsy in all autistic children, lack of treatment of co-occurring epilepsy, and inappropriate use of antiepileptic drugs. A major challenge is the lack of evidence-based harmonized guidelines for autism with co-occurring epilepsy in these countries.

CONCLUSIONS

Our findings show both heterogeneity and major gaps in the care pathway for autism with associated epilepsy and the great efforts that caregivers must make for timely screening, diagnosis, and adequate management of epilepsy in autistic children. We call for policy harmonization in Europe in order to improve the experiences and quality of life of autistic people and their families.

Does the Potocki-Lupski Syndrome Convey the Autism Spectrum Disorder Phenotype? Case Report and Scoping Review

Potocki-Lupski Syndrome (PTLS) is a rare condition associated with a duplication of 17p11.2 that may underlie a wide range of congenital abnormalities and heterogeneous behavioral phenotypes. Along with developmental delay and intellectual disability, autism-specific traits are often reported to be the most common among patients with PTLS. To contribute to the discussion of the role of autism spectrum disorder (ASD) in the PTLS phenotype, we present a case of a female adolescent with a de novo dup(17) (p11.2p11.2) without ASD features, focusing on in-depth clinical, behavioral, and electrophysiological (EEG) evaluations. Among EEG features, we found the atypical peak-slow wave patterns and a unique saw-like sharp wave of 13 Hz that was not previously described in any other patient. The power spectral density of the resting state EEG was typical in our patient with only the values of non-linear EEG dynamics: Hjorth complexity and fractal dimension were drastically attenuated compared with the patient's neurotypical peers. Here we also summarize results from previously published reports of PTLS that point to the approximately 21% occurrence of ASD in PTLS that might be biased, taking into account methodological limitations. More consistent among PTLS patients were intellectual disability and speech and language disorders.

EEG Features in Autism Spectrum Disorder: A Retrospective Analysis in a Cohort of Preschool Children

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that can be associated with intellectual disability (ID) and epilepsy (E). The etiology and the pathogenesis of this disorder is in most cases still to be clarified. Several studies have underlined that the EEG recordings in children with these clinical pictures are abnormal, however the precise frequency of these abnormalities and their relationship with the pathogenic mechanisms and in particular with epileptic seizures are still unknown. We retrospectively reviewed 292 routine polysomnographic EEG tracings of preschool children (age < 6 years) who had received a first multidisciplinary diagnosis of ASD according to DSM-5 clinical criteria. Children (mean age: 34.6 months) were diagnosed at IRCCS E. Medea (Bosisio Parini, Italy). We evaluated: the background activity during wakefulness and sleep, the presence and the characteristics (focal or diffuse) of the slow-waves abnormalities and the interictal epileptiform discharges. In 78.0% of cases the EEG recordings were found to be abnormal, particularly during sleep. Paroxysmal slowing and epileptiform abnormalities were found in the 28.4% of the subjects, confirming the high percentage of abnormal polysomnographic EEG recordings in children with ASD. These alterations seem to be more correlated with the characteristics of the underlying pathology than with intellectual disability and epilepsy. In particular, we underline the possible significance of the prevalence of EEG abnormalities during sleep. Moreover, we analyzed the possibility that EEG data reduces the ASD clinical heterogeneity and suggests the exams to be carried out to clarify the etiology of the disorder.

Prevalence of autism spectrum disorder among children referred to special needs clinic in Giza

Background

Little is known about the prevalence of autism spectrum disorder (ASD) among the population with disability in Egypt. Furthermore, the increasing prevalence of ASD and the variability of the ASD manifestations and severity highlight the importance of investigating the ASD comorbidities.

Aim of work

This analysis was to compare the prevalence of autism with that of other disabilities among children visiting the clinic for special needs and to explore possible comorbid disorders in this sample of Egyptian ASD participants.

Methods

The study included individuals who visited the clinic for special needs in Giza, affiliated to the National Research Centre, for nearly 4 years (2019 to 2022). They were subjected to full clinical evaluation. Autistic children were further subjected to scales for confirming diagnosis and severity evaluation.

Results

The results revealed that a total of 3555 individuals were referred to the clinic. The percentage of children who were diagnosed as having ASD was 22.5% (N = 803; age: 4.5 ± 2.4 years). The most common associated comorbidities with ASD were language and intellectual deficits (80.25%, 58.7%). Hearing impairment was the least common (0.75%). The scores of the childhood autism rating scale were higher in the groups with the comorbid disorders (p = 0.03 or < 0.0001).

Conclusion

The prevalence of ASD among children with disability varied from other countries. Comorbid disorders have led to increasing the severity of ASD. We emphasize that accurate and early diagnosis of autism is the key for proper management of cases.

An Overview of Pediatric Approaches to Child with Developmental Delay Especially if There is Suspicion of ASD in First Few Years of Life

To be a pediatrician means that one encounters many serious childhood health problems and one finds many ways to help families cope with these problems. Symptoms in children can be discrete, and the responsibility of the pediatrician to distinguish normal development from pathological. We are facing a new era in the developmental assessment of children. A cluster of neurodevelopmental disorders includes ASD (autism spectrum disorder) and ADHD (attention deficit hyperactivity disorder). Parents often do not recognize the problem on time. Generally, their first concern is speech delay, leading to the suspicion of hearing problems. Therefore, it is very important to obtain objective anamnestic information and for the child to undergo a careful physical examination, a neurophysiological assessment, and metabolic and genetic testing. The etiology usually is multifactorial: genetic, epigenetic, and non-genetic factors act in combination through various paths. Most children seem to have typical neurodevelopment during first their year. It was found that approximately one-third of children with ASD lose some skills during the preschool period, usually speech related, but sometimes also non-verbal communication, social or play skills. In conclusion we must say that it is very important to recognize the early signs of ASD and any kind of other developmental delay and to start with early intervention. Clinical pediatricians tend to correlate clinical manifestations and biological underpinnings related to neurodevelopmental disorder, especially ASD. Therefore, better treatment possibilities are needed.

Exome sequencing in a child with neurodevelopmental disorder and epilepsy: Variant analysis of the AHNAK2 gene

Background

The AHNAK2 gene encodes a large nucleoprotein expressed in several tissues, including brain, squamous epithelia, smooth muscle, and neuropil. Its role in calcium signaling has been suggested and to date, clear evidence about its involvement in the pathogenesis of clinical disorders is still lacking.

Methods

Here, we report a female 24‐year‐old patient diagnosed with a cardio‐facio‐cutaneous‐like phenotype (CFC‐like), characterized by epilepsy, psychomotor development delay, atopic dermatitis, congenital heart disease, hypotonia, and facial dysmorphism, who is compound heterozygote for two missense mutations in the AHNAK2 gene detected by exome sequencing.

Results

This patient had no detectable variant in any of the genes known to be associated with the cardio‐facio‐cutaneous syndrome. Moreover, the mode of inheritance does not appear to be autosomal dominant, as it is in typical CFC syndrome. We have performed in silico assessment of mutation severity separately for each missense mutation, but this analysis excludes a severe effect on protein function. Protein structure predictions indicate the mutations are located in flexible regions possibly involved in molecular interactions.

Conclusion

We discuss an alternative interpretation on the potential involvement of the two missense mutations in the AHNAK2 gene on the expression of CFC‐like phenotype in this patient based on inter‐allelic complementation.

Impact of self adaptive-elephant herding optimization towards neural network for facial emotion recognition

FACIAL expression is one of the most efficient, universal and fundamental indicators to identify their emotions and intentions in humans. Various experiments have already been performed on automatic Facial Emotion Recognition (FER) owing to useful significance in medical diagnosis, stress monitoring for drivers, sociable robots, and other human-computer interface devices. Here, this proposed framework consists of two processes namely; “(i) proposed feature extraction and (ii) classification”. Here, a major novelty relies in the initial phase (i.e. feature extraction phase), where the Proposed Local Vector Pattern (Proposed- LVP) based features are extracted. In addition to the proposed-LVP, the other Discrete Wavelet Transform (DWT) and Gray Level Co-occurrence Matrix (GLCM) based features are also extracted. Besides, the Principal Component Analysis (PCA) method is used for reducing the dimension of the features. Further, they are subjected to classification process, where Optimized Neural Network (NN) is used. More particularly, a new Improved Elephant Herding Optimization (EHO) model termed as Self Adaptive-EHO (SA-EHO) is used to train the NN model via selecting the optimal weights. At last, the proposed work performance is computed over the other traditional systems with respect to the positive measures like “accuracy, sensitivity, specificity and precision”; negative measures like “False Positive Rate (FPR), False Negative Rate (FNR) and False Discovery Rate (FDR)”; other measures like “Negative Predictive Value (NPV), F1-score and Matthew’s Correlation Coefficient (MCC)”, respectively.

Association between EEG Paroxysmal Abnormalities and Levels of Plasma Amino Acids and Urinary Organic Acids in Children with Autism Spectrum Disorder

Abnormalities in the plasma amino acid and/or urinary organic acid profile have been reported in autism spectrum disorder (ASD). An imbalance between excitatory and inhibitory neuronal activity has been proposed as a mechanism to explain dysfunctional brain networks in ASD, as also suggested by the increased risk of epilepsy in this disorder. This study explored the possible association between presence of EEG paroxysmal abnormalities and the metabolic profile of plasma amino acids and urinary organic acids in children with ASD. In a sample of 55 children with ASD (81.8% male, mean age 53.67 months), EEGs were recorded, and 24 plasma amino acids and 56 urinary organic acids analyzed. EEG epileptiform discharges were found in 36 (65%) children. A LASSO regression, adjusted by age and sex, was applied to evaluate the association of plasma amino acids and urinary organic acids profiles with the presence of EEG epileptiform discharges. Plasma levels of threonine (THR) (coefficient = -0.02, p = 0.04) and urinary concentration of 3-Hydroxy-3-Methylglutaric acid (HMGA) (coefficient = 0.04, p = 0.02) were found to be associated with the presence of epileptiform discharges. These results suggest that altered redox mechanisms might be linked to epileptiform brain activity in ASD.

A review of the pharmacotherapeutic considerations for managing epilepsy in people with autism

INTRODUCTION

Autism, like other neurodevelopmental disorders (NDDs), has a strong association with epilepsy. There are known common genetic pathways in both autism and epilepsy. There are also specific genetic syndromes associated with both complex epilepsy and the autism phenotype.

AREAS COVERED

This review explores the evidence for common genetic etiologies and pathophysiological pathways in relation to both epilepsy and autism. Autism with comorbid epilepsy are associated with a high prevalence of medical and psychiatric comorbidities. This paper discusses how this influences assessment, treatment, and outcomes. The evidence for the treatment of specific seizure types in the context of NDDs is also examined alongside clinical commentary.

EXPERT OPINION

Despite the strong association, there is a limited evidence base to support the efficacy and tolerability of anti-seizure medications specifically in autism, with no Level 1 evidence or National Guidance available. Autism and epilepsy should be approached under a NDD model with cautious introduction and titration of anti-seizure medication. Alongside this, there is evidence to support a move toward precision medicine in specific genetic syndromes such as Tuberous Sclerosis Complex and other genetic seizure disorders. The first-line treatments that should be considered for focal seizures include carbamazepine, lamotrigine, and levetiracetam.

Early life environmental factors associated with autism spectrum disorder symptoms in children at age 2 years: A birth cohort study

LAY ABSTRACT

Mounting evidence indicates the contribution of early life environmental factors in autism spectrum disorder. We aim to report the prospective associations between early life environmental factors and autism spectrum disorder symptoms in children at the age of 2 years in a population-derived birth cohort, the Barwon Infant Study. Autism spectrum disorder symptoms at the age of 2 years strongly predicted autism spectrum disorder diagnosis by the age of 4 years (area under curve = 0.93; 95% CI (0.82, 1.00)). After adjusting for child's sex and age at the time of behavioural assessment, markers of socioeconomic disadvantage, such as lower household income and lone parental status; maternal health factors, including younger maternal age, maternal pre-pregnancy body mass index, higher gestational weight gain and prenatal maternal stress; maternal lifestyle factors, such as prenatal alcohol and environmental air pollutant exposures, including particulate matter < 2.5 μm at birth, child secondhand tobacco smoke at 12 months, dampness/mould and home heating with oil, kerosene or diesel heaters at 2 years postnatal. Lower socioeconomic indexes for area, later birth order, higher maternal prenatal depression and maternal smoking frequency had a dose-response relationship with autism spectrum disorder symptoms. Future studies on environmental factors and autism spectrum disorder should consider the reasons for the socioeconomic disparity and the combined impact of multiple environmental factors through common mechanistic pathways.

Adaptive Behavior, Emotional/Behavioral Problems and Parental Stress in Children With Autism Spectrum Disorder

Background: The aim of our study was to compare adaptive skills, emotional/behavioral problems, and parental stress among children with different severity levels of Autism Spectrum Disorder (ASD) symptoms. Methods: This study included a sample of 88 subjects with ASD (mean age = 6.00 ± 2.70). All subjects underwent standardized neuropsychological tests for the assessment of symptoms of the autism spectrum (Autism Diagnostic Observation Schedule-Second Edition), adaptive level (The Vineland Adaptive Behavior Scales, Survey Interview, 2nd edition), behavioral and emotional problems (Child Behavior CheckList CBCL), and parental stress (Parental Stress Index Short Form-PSI-SF). Non-parametric statistical methods (Kruskal-Wallis test and Mann-Whitney U-test for post hoc analysis) and linear regression analysis were used in this study. Results: Children who had higher severity levels of ASD symptoms had less adaptive functioning; younger children showed more severe symptoms of ASD; older children had better communication skills. The presence of greater adaptive difficulties was related to a greater presence of internalizing problems. An increase in parental stress levels was related to an higher severity of ASD symptoms, fewer adaptive skills, and a greater presence of internalizing and externalizing problems. Conclusion: This study suggests that the adaptive behavior should be considered in order to planning a habilitation intervention in children with autism. It is also important to monitor emotional/behavioral problems and parental stress levels in order to provide parenting support and improve the family quality of life.

Autism spectrum disorders and epilepsy in children: A commentary on the occurrence of autism in epilepsy; how it can present differently and the challenges associated with diagnosis

Autism occurs more frequently in epilepsy, but is often not diagnosed. This could be due to a focus on medical issues, or because it presents differently from classic autism in its timing, phenotype, fluctuating profiles, and high level of comorbidity. Without a diagnosis, these children miss out on interventions that could modify outcome and their families and local teams will struggle to understand and support them. They also become a hidden group that does not participate in or benefit from research. This paper examined the issues and challenges of diagnosing autism in a population with a high-risk of epilepsy, drawing on more than 20 years' experience of a specialist multi-disciplinary Developmental Epilepsy Clinic (DEC).

On the Playing Field to Improve: A Goal for Autism

In recent years, there has been a renewed attention to lifestyle-based interventions in people with autism spectrum disorder. The positive effects of physical exercise programs have been well documented both in healthy people and in people with disabilities in the fields of psychological well-being, cognitive outcome and medical health. There is much less evidence about the opportunity to attempt a team-group sport for people with autism. Although researchers seem to suggest an overall positive effect, playing team sports for people with autism spectrum disorder (ASD) means dealing with difficulties in social interactions and limitations in motor functions. This narrative review aims to report studies about the effects, improvements and difficulties that people with autism have to face when they play the world’s most popular team sport: soccer.