Early Identification of Autism: Early Characteristics, Onset of Symptoms, and Diagnostic Stability

Unraveling the Spectrum: A Comprehensive Review of Autism Spectrum Disorder in India

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by deficits in social interaction, communication difficulties, and repetitive behaviors that profoundly impact the lives of affected individuals and their families. This article provides a comprehensive overview of ASD, focusing on screening, diagnosis, and intervention strategies. Early signs of ASD can manifest in infancy, but parents may not recognize them until their child falls behind in meeting social milestones. This delay in recognition is often due to a lack of awareness, societal stigma, and limited knowledge about developmental and behavioral disorders. Globally, ASD prevalence is increasing potentially due to broader diagnostic criteria, increased awareness, and improved screening practices. Screening for ASD is crucial for early identification and intervention. Various tools are available such as the Modified Checklist for Autism in Toddlers (M-CHATs), Trivandrum Autism Behavioral Checklist (TABC), and the Social Communication Questionnaire (SCQ). Diagnosing ASD involves using established criteria such as the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and specific diagnostic tools like the Autism Diagnostic Observation Schedule (ADOS) and the Indian Scale for the Assessment of Autism (ISAA). Interventions for ASD should be multidisciplinary, involving professionals such as developmental pediatricians, psychologists, psychiatrists, special educators, occupational therapists, physiotherapists, speech therapists, and social workers. Applied behavior analysis (ABA), naturalistic developmental behavioral interventions (NDBIs), and parent-mediated treatment are among the evidence-based approaches. Additionally, speech-language therapy, motor therapy, and sensory integration therapy play vital roles in addressing the diverse needs of individuals with ASD. Medical interventions should be used alongside behavioral and environmental strategies. Early screening, accurate diagnosis, and tailored interventions are essential for improving the lives of individuals with ASD. A multidisciplinary approach and increased awareness are crucial in addressing the growing prevalence of ASD worldwide.

An Open-Label Case Series of Glutathione Use for Symptomatic Management in Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder that has been diagnosed in an increasing number of children around the world. The existing data suggest that early diagnosis and intervention can improve ASD outcomes. The causes of ASD remain complex and unclear, and there are currently no clinical biomarkers for autism spectrum disorder. There is an increasing recognition that ASD might be associated with oxidative stress through several mechanisms including abnormal metabolism (lipid peroxidation) and the toxic buildup of reactive oxygen species (ROS). Glutathione acts as an antioxidant, a free radical scavenger and a detoxifying agent. This open-label pilot study investigates the tolerability and effectiveness of oral supplementation with OpitacTM gluthathione as a treatment for patients with ASD. The various aspects of glutathione OpitacTM glutathione bioavailability were examined when administered by oral routes. The absorption of glutathione from the gastrointestinal tract has been recently investigated. The results of this case series suggest that oral glutathione supplementation may improve oxidative markers, but this does not necessarily translate to the observed clinical improvement of subjects with ASD. The study reports a good safety profile of glutathione use, with stomach upset reported in four out of six subjects. This article discusses the role of the gut microbiome and redox balance in ASD and notes that a high baseline oxidative burden may make some patients poor responders to glutathione supplementation. In conclusion, an imbalance in redox reactions is only one of the many factors contributing to ASD, and further studies are necessary to investigate other factors, such as impaired neurotransmission, immune dysregulation in the brain, and mitochondrial dysfunction.

Prototypical autism: New diagnostic criteria and asymmetrical bifurcation model

The current "autism spectrum" DSM 5 diagnostic criteria and autism standardized diagnostic instruments promote considerable heterogeneity or clinical indecision and may be detrimental to the advancement of fundamental research on autism mechanisms. To increase clinical specificity and reorient research towards core autistic presentations, we propose new diagnostic criteria for prototypical autism during the age of 2- to 5-years. We include autism within other non-dominant, familiarly aggregated phenomena sharing asymmetrical developmental bifurcations, such as twin pregnancy, left handedness, and breech presentation/delivery. Following this model, nature, trajectory, and positive/negative signs structure of autism would result from the polarized problem of whether or not language and information is processed in a socially biased manner. Prototypical autism would follow a canonical developmental trajectory by which a gradual decline in social bias in the processing of incoming information, overtly beginning at the end of the first year, bifurcates into a prototypical autistic presentation in the second half of the second year of life. This bifurcation event is followed by a plateau, in which these atypicalities show maximal stringency and distinctiveness, and then ultimately, in most cases, by partial normalization. During the plateau period, the orientation towards, and processing of, information is considerably modified, with an absence of bias for social information, contrasting with a high level of interest in complex, unbiased information, independently of its social or non-social nature. Integrating autism into asymmetrical developmental bifurcations would explain the absence of deleterious neurological and genetic markers and the presence of familial transmission in canonical autistic presentations.

Dental experiences related to oral care of children with autism spectrum disorders in Saudi Arabia: A literature review

The burden of autism spectrum disorder (ASD) in Saudi Arabia remains unclear with a dearth of literature, which focus on risk factors, prevalence, or interventions. This study is a review of the published literature related to dental experiences of children with ASD in Saudi Arabia. Twenty-two studies were included in this review, based on the predefined inclusion criteria which examined dental disease prevalence in children with ASD, identified the risk factors and the potential barriers to oral care. Results uncovered a lack of systematically published studies from Saudi Arabia which might have led to the limited development of effective oral health policies in the Kingdom. Identification of research gaps and potential intervention policies are needed to improve the oral health and quality of life of children with ASD in Saudi Arabia.

Deep Neural Network-based Handheld Diagnosis System for Autism Spectrum Disorder

Objective

The aim of the present work was to propose and implement deep neural network (DNN)-based handheld diagnosis system for more accurate diagnosis and severity assessment of individuals with autism spectrum disorder (ASD).

Methods

Initially, the learning of the proposed system for ASD diagnosis was performed by implementing DNN algorithms such as a convolutional neural network (CNN) and long short-term memory (LSTM), and multilayer perceptron (MLP) with DSM-V based acquired dataset. The performance of the DNN algorithms was analyzed based on parameters viz. accuracy, loss, mean squared error (MSE), precision, recall, and area under the curve (AUC) during the training and validation process. Later, the optimum DNN algorithm, among the tested algorithms, was implemented on handheld diagnosis system (HDS) and the performance of HDS was analyzed. The stability of proposed DNN-based HDS was validated with the dataset group of 20 ASD and 20 typically developed (TD) individuals.

Results

It was observed during comparative analysis that LSTM resulted better in ASD diagnosis as compared to other artificial intelligence (AI) algorithms such as CNN and MLP since LSTM showed stabilized results achieving maximum accuracy in less consumption of epochs with minimum MSE and loss. Further, the LSTM based proposed HDS for ASD achieved optimum results with 100% accuracy in reference to DSM-V, which was validated statistically using a group of ASD and TD individuals.

Conclusion

The use of advanced AI algorithms could play an important role in the diagnosis of ASD in today's era. Since the proposed LSTM based HDS for ASD and determination of its severity provided accurate results with maximum accuracy with reference to DSM-V criteria, the proposed HDS could be the best alternative to the manual diagnosis system for diagnosis of ASD.

Informing Developmental Milestone Achievement for Children With Autism: Machine Learning Approach

Background

Care for children with autism spectrum disorder (ASD) can be challenging for families and medical care systems. This is especially true in low- and- middle-income countries such as Bangladesh. To improve family–practitioner communication and developmental monitoring of children with ASD, mCARE (Mobile-Based Care for Children with Autism Spectrum Disorder Using Remote Experience Sampling Method) was developed. Within this study, mCARE was used to track child milestone achievement and family sociodemographic assets to inform mCARE feasibility/scalability and family asset–informed practitioner recommendations.

Objective

The objectives of this paper are threefold. First, it documents how mCARE can be used to monitor child milestone achievement. Second, it demonstrates how advanced machine learning models can inform our understanding of milestone achievement in children with ASD. Third, it describes family/child sociodemographic factors that are associated with earlier milestone achievement in children with ASD (across 5 machine learning models).

Methods

Using mCARE-collected data, this study assessed milestone achievement in 300 children with ASD from Bangladesh. In this study, we used 4 supervised machine learning algorithms (decision tree, logistic regression, K-nearest neighbor [KNN], and artificial neural network [ANN]) and 1 unsupervised machine learning algorithm (K-means clustering) to build models of milestone achievement based on family/child sociodemographic details. For analyses, the sample was randomly divided in half to train the machine learning models and then their accuracy was estimated based on the other half of the sample. Each model was specified for the following milestones: Brushes teeth, Asks to use the toilet, Urinates in the toilet or potty, and Buttons large buttons.

Results

This study aimed to find a suitable machine learning algorithm for milestone prediction/achievement for children with ASD using family/child sociodemographic characteristics. For Brushes teeth, the 3 supervised machine learning models met or exceeded an accuracy of 95% with logistic regression, KNN, and ANN as the most robust sociodemographic predictors. For Asks to use toilet, 84.00% accuracy was achieved with the KNN and ANN models. For these models, the family sociodemographic predictors of “family expenditure” and “parents’ age” accounted for most of the model variability. The last 2 parameters, Urinates in toilet or potty and Buttons large buttons, had an accuracy of 91.00% and 76.00%, respectively, in ANN. Overall, the ANN had a higher accuracy (above ~80% on average) among the other algorithms for all the parameters. Across the models and milestones, “family expenditure,” “family size/type,” “living places,” and “parent’s age and occupation” were the most influential family/child sociodemographic factors.

Conclusions

mCARE was successfully deployed in a low- and middle-income country (ie, Bangladesh), providing parents and care practitioners a mechanism to share detailed information on child milestones achievement. Using advanced modeling techniques this study demonstrates how family/child sociodemographic elements can inform child milestone achievement. Specifically, families with fewer sociodemographic resources reported later milestone attainment. Developmental science theories highlight how family/systems can directly influence child development and this study provides a clear link between family resources and child developmental progress. Clinical implications for this work could include supporting the larger family system to improve child milestone achievement.

Astroglial cells as neuroendocrine targets in forebrain development: Implications for sex differences in psychiatric disease

Astroglial cells are the most abundant cell type in the mammalian brain. They are implicated in almost every aspect of brain physiology, including maintaining homeostasis, building and maintaining the blood brain barrier, and the development and maturation of neuronal networks. Critically, astroglia also express receptors for gonadal sex hormones, respond rapidly to gonadal hormones, and are able to synthesize hormones. Thus, they are positioned to guide and mediate sexual differentiation of the brain, particularly neuronal networks in typical and pathological conditions. In this review, we describe astroglial involvement in the organization and development of the brain, and consider known sex differences in astroglial responses to understand how astroglial cell-mediated organization may play a role in forebrain sexual dimorphisms in human populations. Finally, we consider how sexually dimorphic astroglial responses and functions in development may lead to sex differences in vulnerability for neuropsychiatric disorders.

The Criterion Validity of the First Year Inventory and the Quantitative-CHecklist for Autism in Toddlers: A Longitudinal Study

Pediatric surveillance through screening procedures is needed to detect warning signs of risk for Autism Spectrum Disorder under 24 months of age and to promote early diagnosis and treatment. The main purpose of this study is to extend the literature regarding the psychometric properties of two screening tools, the First Year Inventory (FYI) and the Quantitative-CHecklist for Autism in Toddler (Q-CHAT), testing their criterion validity. They were administered during a three-wave approach involving the general population. At T1, 657 children were tested with the FYI and 36 of them were found to be at risk. At T2, 545 were tested with the Q-CHAT and 29 of them were found to be at risk. At T3, 12 out of the 36 children with a high score on the FYI and 11 out of the 29 children with a high score on the Q-CHAT were compared to 15 typically developing children. The criterion validity was tested considering the severity of the autistic symptoms, emotional/behavioral problems, and limited global functioning as criteria. Accuracy parameters were also calculated. Furthermore, we investigated which dimension of each questionnaire better predicted the aforementioned criterion. The results corroborated the hypotheses and confirmed the criterion validity of FYI and Q-CHAT.

Referral, Assessment and Use of Screening Measures Related to Autism Spectrum Disorder at a Tertiary Hospital Setting

Children with developmental concerns in Australia continue to experience inequitable healthcare and service-related delays, even when diagnostic risk is identified. This study sought to explore service and demographic pathway factors leading up to autism spectrum disorder (ASD) assessment, including value of screening measures applied at triage. Following a trial of centralised intake for referred young children with suspected ASD, observational, retrospective pathway data was explored using bivariate and regression analyses. The mean age of 159 children referred with autism symptoms was 3.6 years, and 64% were diagnosed with ASD. Service allocation was associated with diagnosis, whilst screening tool results were not. Improved pathways are needed to limit wasted waiting times and direct each child to needs-based services.

Parental Beliefs and Feelings about Autism Spectrum Disorder in Iran

BACKGROUND

This study provides information on beliefs that parents of children with autism hold in Iran. The main focus is on their beliefs about the cause and the way that this condition is explained based on the first signs that made them be concerned for their children.

METHOD

To attain the aims of this study, 43 parents of children with ASD (27 mothers and 16 fathers) were recruited and interviewed in two sessions in their home. A mixed method approach was used to understand Iranian parents' reaction to receive diagnosis for their children.

RESULTS

Based on findings for the identification, description, and treatment of ASD in Iran, it is argued that since Iranian parents had their special justification regarding their experience with ASD, early child development and interventions must be understood within cultural context. Culturally informed research on ASD is vital to boost awareness of the importance of understanding parental concerns and their need for educational and psychological services in countries in which autism is less known, undiagnosed, misdiagnosed, or even stigmatized. Understanding the difference in ASD meaning across cultures urges stakeholders such as service providers and policymakers to accept and appreciate cultural and individual diversities in the present century.

Sex: A Significant Risk Factor for Neurodevelopmental and Neurodegenerative Disorders

Males and females sometimes significantly differ in their propensity to develop neurological disorders. Females suffer more from mood disorders such as depression and anxiety, whereas males are more susceptible to deficits in the dopamine system including Parkinson's disease (PD), attention-deficit hyperactivity disorder (ADHD) and autism. Despite this, biological sex is rarely considered when making treatment decisions in neurological disorders. A better understanding of the molecular mechanism(s) underlying sex differences in the healthy and diseased brain will help to devise diagnostic and therapeutic strategies optimal for each sex. Thus, the aim of this review is to discuss the available evidence on sex differences in neuropsychiatric and neurodegenerative disorders regarding prevalence, progression, symptoms and response to therapy. We also discuss the sex-related factors such as gonadal sex hormones and sex chromosome genes and how these might help to explain some of the clinically observed sex differences in these disorders. In particular, we highlight the emerging role of the Y-chromosome gene, SRY, in the male brain and its potential role as a male-specific risk factor for disorders such as PD, autism, and ADHD in many individuals.

MAOA Influences the Trajectory of Attentional Development

Attention is vital to success in all aspects of life (Meck and Benson, 2002; Erickson et al., 2015), hence it is important to identify biomarkers of later attentional problems early enough to intervene. Our objective was to determine if any of 11 genes (APOE, BDNF, HTR4, CHRNA4, COMT, DRD4, IGF2, MAOA, SLC5A7, SLC6A3, and SNAP25) predicted the trajectory of attentional development within the same group of children between infancy and childhood. We recruited follow up participants from children who participated as infants in visual attention studies and used a similar task at both time points. Using multilevel modeling, we associated changes in the participant’s position in the distribution of scores in infancy to his/her position in childhood with genetic markers on each of 11 genes. While all 11 genes predicted reaction time (RT) residual scores, only Monoamine oxidase A (MAOA) had a significant interaction including time point. We conclude that the MAOA single nucleotide polymorphism (SNP) rs1137070 is useful in predicting which girls are likely to develop slower RTs on an attention task between infancy and childhood. This early identification is likely to be helpful in early intervention.

The motivation for very early intervention for infants at high risk for autism spectrum disorders

The first Autism Research Matrix (IACC, 2003) listed the identification of behavioural and biological markers of risk for autism as a top priority. This emphasis was based on the hypothesis that intervention with infants at-risk, at an early age when the brain is developing and before core autism symptoms have emerged, could significantly alter the developmental trajectory of children at risk for the disorder and impact long-range outcome. Research has provided support for specific models of early autism intervention (e.g., Early Start Denver Model) for improving outcomes in young children with autism, based on both behavioural and brain activity measures. Although great strides have been made in ability to identify risk markers for autism in younger infant/toddler samples, how and when to intervene during the prodromal state remains a critical question. Emerging evidence suggests that abnormal brain circuitry in autism precedes altered social behaviours; thus, an intervention designed to promote early social engagement and reciprocity potentially could steer brain development back toward the normal trajectory and remit or reduce the expression of symptoms.

Temperament and sensory features of children with autism

This study sought to characterize temperament traits in a sample of children with autism spectrum disorder (ASD), ages 3-7 years old, and to determine the potential association between temperament and sensory features in ASD. Individual differences in sensory processing may form the basis for aspects of temperament and personality, and aberrations in sensory processing may inform why some temperamental traits are characteristic of specific clinical populations. Nine dimensions of temperament from the Behavioral Style Questionnaire (McDevitt and Carey in Manual for the behavioral style questionnaire, Behavioral-Developmental Initiatives, Scottsdale, AZ, 1996) were compared among groups of children with ASD (n = 54), developmentally delayed (DD; n = 33), and the original normative sample of typically developing children (McDevitt and Carey in J Child Psychol Psychiatr 19(3):245-253, 1978; n = 350) using an ANOVA to determine the extent to which groups differed in their temperament profiles. The hypothesized overlap between three sensory constructs (hyperresponsiveness, hyporesponsiveness, and seeking) and the nine dimensions of temperament was analyzed in children with ASD using regression analyses. The ASD group displayed temperament scores distinct from norms for typically developing children on most dimensions of temperament (activity, rhythmicity, adaptability, approach, distractibility, intensity, persistence, and threshold) but differed from the DD group on only two dimensions (approach and distractibility). Analyses of associations between sensory constructs and temperament dimensions found that sensory hyporesponsiveness was associated with slowness to adapt, low reactivity, and low distractibility; a combination of increased sensory features (across all three patterns) was associated with increased withdrawal and more negative mood. Although most dimensions of temperament distinguished children with ASD as a group, not all dimensions appear equally associated with sensory response patterns. Shared mechanisms underlying sensory responsiveness, temperament, and social withdrawal may be fruitful to explore in future studies.

Frequency and pattern of documented diagnostic features and the age of autism identification

OBJECTIVE

The DSM-IV-TR specifies 12 behavioral features that can occur in hundreds of possible combinations to meet diagnostic criteria for autism spectrum disorder (ASD). This paper describes the frequency and variability with which the 12 behavioral features are documented in a population-based cohort of 8-year-old children under surveillance for ASD, and examines whether documentation of certain features, alone or in combination with other features, is associated with earlier age of community identification of ASD.

METHOD

Statistical analysis of behavioral features documented for a population-based sample of 2,757 children, 8 years old, with ASD in 11 geographically-defined areas in the US participating in the Autism and Developmental Disabilities Monitoring Network in 2006.

RESULTS

The median age at ASD identification was inversely associated with the number of documented behavioral features, decreasing from 8.2 years for children with only seven behavioral features to 3.8 years for children with all 12. Documented impairments in nonverbal communication, pretend play, inflexible routines, and repetitive motor behaviors were associated with earlier identification, whereas impairments in peer relations, conversational ability, and idiosyncratic speech were associated with later identification.

CONCLUSIONS

The age dependence of some of the behavioral features leading to an autism diagnosis, as well as the inverse association between age at identification and number of behavioral features documented, have implications for efforts to improve early identification. Progress in achieving early identification and provision of services for children with autism may be limited for those with fewer ASD behavioral features, as well as features likely to be detected at later ages.

Predictors of diagnosis of child psychiatric disorder in adult-infant social-communicative interaction at 12 months

To establish which social interactive behaviours predict later psychiatric diagnosis, we examined 180 videos of a parent-infant interaction when children were aged one year, from within the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Sixty of the videos involved infants who were later diagnosed with a psychiatric disorder at seven years, and 120 were a randomly selected sex-matched control group. Interactive behaviours for both the caregiver and the one year old infant were coded from the videos according to eight holistic categories of interpersonal engagement: Well-being, Contingent Responsiveness, Cooperativeness, Involvement, Activity, Playfulness, Fussiness, and Speech. Lower levels of adult activity and speech in interaction at one year significantly predicted overall diagnosis of child psychiatric disorder.

Office screening and early identification of children with autism

Autism spectrum disorders (ASDs), also called pervasive developmental disorders in the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revised), constitute a group of neurodevelopmental disorders that coalesce around a common theme of impairments in social functioning, communication abilities, and repetitive or rigid behaviors. The ASDs considered here include autism/autistic disorder, Asperger disorder/Asperger syndrome (AS), and pervasive developmental disorder not otherwise specified. This article focuses on autism/autistic disorder screening and its early identification, with a brief mention for AS screening, as there are limited tools and no recommendation for universal screening for AS.