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The purpose of this study is to examine the association between autism spectrum disorder (ASD) severity and having a special education or early intervention plan and the impact of adverse childhood experiences (ACEs) on this association. This study used the 2020-2021 National Survey of Children's Health (NSCH) and included 2,537 children aged 3-17 years old who currently have ASD. Multivariable logistic regression, controlling for demographic and family characteristics and health status, was used to explore the association between autism severity and having an early intervention plan. The analysis was stratified by the number of ACEs to explore their role in the association. Children with moderate or severe ASD were more likely to have a special education or early intervention plan than those with mild ASD in the crude and adjusted models. This association continued to be true for children who experienced 1 ACE (aOR: 2.28, 95%CI: 1.09-4.77) but not true for those who experienced no ACEs (aOR: 1.16, 95%CI: 0.70-1.94) and 2 or more ACEs (aOR: 1.84, 95%CI: 0.92-3.69). Results demonstrate that children with moderate or severe autism were more likely to receive early intervention or special education. This association changed depending on the number of ACEs experiences.

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Autism severity is currently defined and measured based exclusively on the severity levels of the two core symptom domains: social-communication and restricted or repetitive patterns of behaviors and interests. Autistic individuals, however, are often diagnosed with other medical, developmental, and psychological co-occurring conditions. These additional challenges such as intellectual disability, limited expressive and/or receptive language, and anxiety disorders, can have a tremendous impact on the day-to-day lives of autistic individuals, for both their adaptive functioning as well as their sense of wellbeing. Furthermore, the initial presentation of core symptoms and their likelihood of changing over time are influenced by the presence of such co-occurring conditions. In order to truly understand how a person's autism impacts their life, both core symptoms as well as other challenges should be considered. This approach was recently taken by The Lancet Commission on the future of care and clinical research in autism, which proposed the term "profound autism" for a subgroup of individuals presenting with high core symptom severity, co-occurring intellectual disability, and little or no language, who require extensive long-term care. Considering other individual factors such as daily living skills, specific support needs and environmental resources would also enhance the evaluation of disability in autistic individuals. As currently employed in the assessment of intellectual disability, a multidimensional approach to autism could provide a more comprehensive system for classification of impairment. At present, however, there is no formal way to designate the combined effect of these different aspects of autism on a person's life. A comprehensive outlook that acknowledges impairments, capabilities, co-occurring conditions, and environmental factors would be useful for identifying subgroups of individuals as well as for determining individual needs and strengths in clinical assessments. Lay Summary: The severity of a person's autism is currently defined based on the severity of their core autism symptoms: impaired social-communication and the presence of restricted or repetitive patterns of behaviors and interests. But autistic people often face additional challenges such as intellectual disability, epilepsy, and anxiety disorder, that considerably impact their everyday life, wellbeing, and the need for support. A more complete view of autism severity, one that includes core symptoms as well as additional challenges, could help identify meaningful sub-groups of autistic individuals and could be useful in clinical care. Appeared originally in Autism Res 2023; 16:685-696.

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PURPOSE: This study aimed to investigate the relationship between physical fitness, gray matter volume (GMV), and autism severity in children with autism spectrum disorder (ASD). Besides, we sought to diagnose autism severity associated with physical fitness and GMV using machine learning methods. METHODS: Ninety children diagnosed with ASD underwent physical fitness tests, magnetic resonance imaging scans, and autism severity assessments. Diagnosis models were established using extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), and decision tree (DT) algorithms. Hyperparameters were optimized through the grid search cross-validation method. The shapley additive explanation (SHAP) method was employed to explain the diagnosis results. RESULTS: Our study revealed associations between muscular strength in physical fitness and GMV in specific brain regions (left paracentral lobule, bilateral thalamus, left inferior temporal gyrus, and cerebellar vermis I-II) with autism severity in children with ASD. The accuracy (95 % confidence interval) of the XGB, RF, SVM, and DT models were 77.9 % (77.3, 78.6 %), 72.4 % (71.7, 73.2 %), 71.9 % (71.1, 72.6 %), and 66.9 % (66.2, 67.7 %), respectively. SHAP analysis revealed that muscular strength and thalamic GMV significantly influenced the decision-making process of the XGB model. CONCLUSION: Machine learning methods can effectively diagnose autism severity associated with physical fitness and GMV in children with ASD. In this respect, the XGB model demonstrated excellent performance across various indicators, suggesting its potential for diagnosing autism severity.

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Intelligence profiles in autism have been characterized by great variability. The questions of how autistic children's intelligence changes over time, and what factors influence these changes deserve study as part of efforts to document child autism profiles, but also because the relationship between intellectual functioning and children's background characteristics is poorly understood, particularly in a longitudinal context. A total of 39 autistic children and 39 age-matched neurotypical children (5-9 years old) completed two IQ assessments at preschool age and up to 4 years later. Repeated-measures analyses assessed longitudinal changes in the children's verbal (VIQ), performance (PIQ), and full-scale IQ (FSIQ) at group level. We further sought to identify clusters with distinct profiles in each group by adopting an unsupervised K-means clustering approach, and detect possible between-subgroup differences in terms of children's socioeconomic status and autism severity. The largest cluster in the autistic group was composed of children whose PIQ significantly dropped at follow-up, while the second largest cluster improved in all quotients; the smallest cluster, wherein children had more highly educated mothers than the rest of the clusters, was characterized by large improvement in VIQ. For the neurotypical children, there was a two-cluster division; the majority of them improved in the three quotients, while very few dropped in PIQ at follow-up. The relation between socioeconomic status and IQ changes was significant for both groups. The findings demonstrate both the complexity of intelligence changes in autism and the need to view this complexity through the lens of the children's socioeconomic diversity.

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The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. The robot HUMANE, installed with computer vision and linked with recognition technology, detected the direction of eye gaze of children. Children aged 3-8 (M = 5.52; N = 199) participated, 87 of whom had been confirmed with autism, 55 of whom were suspected to have autism, and 57 of whom were not considered to cause any concern for having autism. Before a session, a human experimenter instructed HUMANE to narrate a story to a child. HUMANE prompted the child to return his/her eye gaze to the robot if the child looked away, and praised the child when it re-established its eye gaze quickly after a prompt. The reliability of eye gaze detection was checked across all pairs of human raters and HUMANE and reached 0.90, indicating excellent interrater agreement. Using the pre-specified reference standard (Autism Spectrum Quotient), the sensitivity and specificity of the index tests (i.e., the number of robot prompts and duration of inattentiveness) reached 0.88 or above and the Diagnostic Odds Ratios were beyond 190. These results show that social robots may detect atypical eye patterns, suggesting a potential future for screening autism using social robots.

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PURPOSE: Only a few studies examined the longitudinal pattern of parent-teacher reports on autism severity and comorbidities in autism spectrum disorder (ASD) and yielded conflicting results. The study's aims were to compare parents and teachers' perception of autism, attention deficit hyperactivity disorder (ADHD) and anxiety symptoms severity in children with ASD, at the start (T1) and end (T2) of the school year, to assess changes in their perception over time and to examine correlations between their reports. METHODS: The study included 73 participants, (M = 61), aged 2:10 - 7:6 years (M = 4:10, SD = 1:0), who attended ASD special education classes and were receiving intensive interventions. Parents and teachers completed measures of autism severity and ADHD and anxiety symptoms at T1 and T2. RESULTS: Teachers, in comparison to parents, rated more severe social-communication impairments and inattention symptoms at T1, but not at T2. A significant improvement in teachers' ratings of autism and inattention symptoms severity was documented at T2. At both time points, parents reported more severe anxiety symptoms. Significant correlations between parents' and teachers' reports were noted for autism severity at T1 and T2, but not for inattention and anxiety symptoms severity. CONCLUSION: The study emphasizes the contribution of multiple perspectives for better collaboration between home and school environments. Obtaining accurate information from parents and teachers at the start of the school year may help to identify factors needed for better adjustment at school and to better address difficulties at home.

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Autism Spectrum Disorder (ASD) is a heterogeneous condition that includes a broad range of characteristics and associated comorbidities; however, the biology underlying the variability in phenotypes is not well understood. As ASD impacts approximately 1 in 100 children globally, there is an urgent need to better understand the biological mechanisms that contribute to features of ASD. In this study, we leveraged rich phenotypic and diagnostic information related to ASD in 2001 individuals aged 4 to 17 years from the Simons Simplex Collection to derive phenotypically driven subgroups and investigate their respective metabolomes. We performed hierarchical clustering on 40 phenotypes spanning four ASD clinical domains, resulting in three subgroups with distinct phenotype patterns. Using global plasma metabolomic profiling generated by ultrahigh-performance liquid chromatography mass spectrometry, we characterized the metabolome of individuals in each subgroup to interrogate underlying biology related to the subgroups. Subgroup 1 included children with the least maladaptive behavioral traits (N = 862); global decreases in lipid metabolites and concomitant increases in amino acid and nucleotide pathways were observed for children in this subgroup. Subgroup 2 included children with the highest degree of challenges across all phenotype domains (N = 631), and their metabolome profiles demonstrated aberrant metabolism of membrane lipids and increases in lipid oxidation products. Subgroup 3 included children with maladaptive behaviors and co-occurring conditions that showed the highest IQ scores (N = 508); these individuals had increases in sphingolipid metabolites and fatty acid byproducts. Overall, these findings indicated distinct metabolic patterns within ASD subgroups, which may reflect the biological mechanisms giving rise to specific patterns of ASD characteristics. Our results may have important clinical applications relevant to personalized medicine approaches towards managing ASD symptoms.

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Autism severity is currently defined and measured based exclusively on the severity levels of the two core symptom domains: social-communication and restricted or repetitive patterns of behaviors and interests. Autistic individuals, however, are often diagnosed with other medical, developmental, and psychological co-occurring conditions. These additional challenges such as intellectual disability, limited expressive and/or receptive language, and anxiety disorders, can have a tremendous impact on the day-to-day lives of autistic individuals, for both their adaptive functioning as well as their sense of wellbeing. Furthermore, the initial presentation of core symptoms and their likelihood of changing over time are influenced by the presence of such co-occurring conditions. In order to truly understand how a person's autism impacts their life, both core symptoms as well as other challenges should be considered. This approach was recently taken byThe Lancet Commission on the future of care and clinical research in autism, which proposed the term "profound autism" for a subgroup of individuals presenting with high core symptom severity, co-occurring intellectual disability, and little or no language, who require extensive long-term care. Considering other individual factors such as daily living skills, specific support needs and environmental resources would also enhance the evaluation of disability in autistic individuals. As currently employed in the assessment of intellectual disability, a multidimensional approach to autism could provide a more comprehensive system for classification of impairment. At present, however, there is no formal way to designate the combined effect of these different aspects of autism on a person's life. A comprehensive outlook that acknowledges impairments, capabilities, co-occurring conditions, and environmental factors would be useful for identifying subgroups of individuals as well as for determining individual needs and strengths in clinical assessments.

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Corpus callosum (CC) is the largest commissural white matter bundle in the brain, responsible for the integration of information between hemispheres. Reduction in the size of the CC structure has been predominantly reported in children with autism spectrum disorder (ASD) compared to typically developing children (TD). However, most of these studies are based on high-functioning individuals with ASD but not on an inclusive sample of individuals with ASD with varying abilities. Our current study aimed to examine the CC morphometry between children with ASD and TD in the Indian population. We also compared CC morphometry in autistic children with autism severity, verbal IQ (VIQ) and full-scale IQ (FSIQ). T1-weighted structural images were acquired using a 3T MRI scanner to examine the CC measures in 62 ASD and 17 TD children. The length and height of the CC and the width of genu were decreased in children with ASD compared to TD. There was no significant difference in CC measures based on autism severity, VIQ or FSIQ among children with ASD. To our knowledge, this is the first neuroimaging study to include a significant number (n = 56) of low-functioning ASD children. Our findings suggest the atypical interhemispheric connectivity of CC in ASD.

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Objective: Motor impairments are prevalent in children with autism spectrum disorder (ASD) and persistent across age. Our current study was designed to investigate motor deficits in Chinese toddlers with ASD and to explore the relationships between motor deficits and social communication skills. Methods: For this cross-sectional study, we recruited a total of 210 Chinese toddlers with ASD aged between 18 and 36 months in the study during December 2017 to December 2020. Griffiths Developmental Scales-Chinese (GDS-C), Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) and Communication and Symbolic Behavior Scales Developmental Profile-Infant-Toddler Checklist (CSBS-DP-ITC) were administered in these toddlers to evaluate their development, social communicative skills, and autism severity. We compared the developmental and social communicational profiles of ASD toddlers in different gross and fine motor subgroups, and explored potential associated factors. The univariate generalized linear model tested the relationship of fine and gross motor skills and social communicative skills. Results: The prevalence of gross and fine motor deficits were 59.5 and 82.5%, respectively, which are almost equivalent in boys and girls. The motor impairments tended to be more severe with age in toddlers. After adjusting for age, sex, non-verbal development quotient (DQ) and restricted, repetitive behaviors, severer gross motor impairments were significantly related to higher comparison score of ADOS-2 and higher social composite score of CSBS-DP-ITC, without interactions with other variables. Meanwhile, lower fine motor skills were associated with more deficits of social communication and higher severity of ASD, also depending on non-verbal DQ. In the lower non-verbal DQ subgroup, both fine motor deficits and restricted repetitive behaviors (RRBs) might have effects on autism symptomology. Conclusion: Motor impairments are common in Chinese toddlers with ASD. Toddlers with weaker gross and fine motor skills have greater deficits in social communicative skills. Gross motor impairment might be an independent predictor of the severity of autism and social communication skills, while the effect of fine motor deficits might be affected by non-verbal DQ and RRBs of toddlers with ASD. We provide further justification for the inclusion of motor impairments in the early intervention for toddlers with ASD.

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The present study assessed the prevalence of clinically significant maladaptive behaviors and associated factors among young male children diagnosed with autism. A cross-sectional study including mothers of 88 male children with autism aged 2 to 5 y old was conducted in the year 2019. Using the Child Behavior Checklist (CBCL), mothers rated their child's maladaptive behaviors. CBCL overall scores in the clinically relevant range were found in 76 (86.4%) children with autism (87.5% and 42% children had clinically significant internalizing and externalizing problems, respectively). Withdrawn (94.3%), attention problems (60.2%), and sleep problems (53.4%) were the predominant CBCL syndrome scales. Sociodemographic factors like autism severity and caffeine consumption were found to be significantly associated with maladaptive behaviors. There is an urgent need for designing effective behavioral management strategies incorporating various risk factors to enhance the quality of life among these vulnerable children.

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Background: The transition to adolescence can be challenging for children with autism spectrum disorder (ASD). The present study explored child and family variables that predict functional outcomes of adolescents with ASD in emotional/behavioral difficulties, socialization, daily living skills, and the transition to secondary education. Method: Forty-five individuals with ASD, without intellectual disability, were assessed during childhood (aged 7-11) and almost five years later. Child measures (executive functions, theory of mind, autism symptom severity) and parent measures (parenting stress, social support, coping strategies) were collected. Results: In adolescence, the predictive power of childhood executive functions was important for academic and behavioral/emotional indicators whereas theory of mind mainly predicted adaptive and behavior/emotional outcomes. ASD symptoms had predictive value in all outcome domains. Parental educational level, social support and parenting distress predicted socialization, while the engagement coping strategy had a significant role in daily living skills. Conclusions: The findings raise several clinical considerations related to assessment and intervention in autism. Executive functions and theory of mind programs could help to improve behavior/emotional, adaptive outcomes, and adjustment to school. In addition, the study indicates the need for family-centered interventions based on positive parenting practices and principles of behavioral analysis along with parental support, stress management and coping strategies.(AU)

Antecedentes: el presente estudio exploró variables del niño y familiares que predicen el funcionamiento conductual/ emocional, adaptativo y transición a la Secundaria de adolescentes con trastorno del espectro autista (TEA). Método: se evaluó a 45 individuos con TEA sin discapacidad intelectual en la infancia y casi 5 años después, recogiendo información del niño (funciones ejecutivas, teoría de la mente, y síntomas de autismo), y de padres (estrés, apoyo social, estrategias de afrontamiento). Resultados: las funciones ejecutivas predijeron adaptación académica y dificultades en la adolescencia, mientras que la teoría de la mente predijo resultados en socialización y habilidades de la vida diaria. Los síntomas de autismo tuvieron valor predictivo en los cuatro dominios de resultados. El nivel educativo, el estrés de los padres y el apoyo social predijeron la socialización, mientras que la implicación predijo las habilidades de la vida diaria. Conclusiones: los hallazgos tienen connotaciones para la evaluación e intervención en autismo. Los programas en funciones ejecutivas y en teoría de la mente mejorarían resultados conductuales/emocionales, adaptativos y ajuste escolar. Además, el estudio señala la necesidad de incluir en las intervenciones con familias principios de paternidad positiva y de análisis conductual, junto con apoyo parental, manejo del estrés y estrategias de afrontamiento.(AU)

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Background Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders characterized by defective social communication and interaction with a repetitive pattern of monotonous or stereotyped behavior. Although the exact etiology of ASD is unknown, many factors may be implicated in the development of ASD. We aimed to determine the correlation between specific parental factors and Autism Treatment Evaluation Checklist (ATEC) scores. Methods This cross-sectional study was conducted at the Prince Nasser Bin Abdulaziz Center for Autism, Autism Center for Excellence, and Academy of Special Education for Autism in Riyadh, Saudi Arabia. We enrolled children diagnosed with ASD and their parents from these centers. Data were collected through self-administered questionnaires to the patients' parents. Results All included children were <18 years old. In total, 71 (92.2%) children were male and six (7.8%) were female. Further, 77 (100%) patients were diagnosed with autistic disorder. Children of consanguineous parents, underweight mothers and obese fathers, mothers with a history of depression during pregnancy, and mothers aged ≥31 years during pregnancy tend to have a higher mean ATEC score. The health domain was the most significantly correlated with ATEC scores, with a Pearson correlation of 0.880. In linear regression analysis, only maternal depression during pregnancy was significantly correlated with ATEC scores. Conclusion Our patients had a mean ATEC score of 86.2. The health domain was the most significantly correlated with ATEC scores, with a Pearson correlation of 0.880. Linear regression analysis revealed that consanguinity, parental chronic disease, parental allergy, smoking, drug use during pregnancy, paternal and maternal body mass index (BMI), and sibling number were not significantly correlated with ATEC scores (P=0.701, 0.693, 0.133, 0.874, 0.982, 0.255, 0.778, and 0.502, respectively). However, maternal depression during pregnancy was significantly correlated with ATEC scores (P=0.055).

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This study examined the presence of neurodevelopmental regression and its effects on the clinical manifestations and the severity of autism spectrum disorder (ASD) in a group of children with autism compared with those without neurodevelopmental regression at the time of initial classification and subsequently. Methods and Subjects: ASD patients were classified into two subgroups, neurodevelopmental regressive (AMR) and non-regressive (ANMR), using a questionnaire based on the Autism Diagnostic Interview-Revised test. The severity of ASD and neurodevelopment were assessed with the Childhood Autism Rating Scale Test-2, Strengths and Difficulties Questionnaire, and Pervasive Developmental Disorders Behavior Inventory Parent Ratings (PDDBI) and with the Battelle Developmental Inventory tests at the beginning of the study and after 24 months of follow-up. Fifty-two patients aged 2-6 years with ASD were included. Nineteen were classified with AMR, and 33 were classified with ANMR. Results: The AMR subgroup presented greater severity of autistic symptoms and higher autism scores. Additionally, they showed lower overall neurodevelopment. The AMR subgroup at 24 months had poorer scores on the Battelle Developmental Inventory test in the following areas: Total personal/social (p < 0.03), Total Motor (p < 0.04), Expressive (p < 0.01), and Battelle Total (p < 0.04). On the PDDBI test, the AMR subgroup had scores indicating significantly more severe ASD symptoms in the variables: ritual score (p < 0.038), social approach behaviors (p < 0.048), expressive language (p < 0.002), and autism score (p < 0.003). Conclusions: ASD patients exhibited a set of different neurological phenotypes. The AMR and ANMR subgroups presented different clinical manifestations and prognoses in terms of the severity of autistic symptoms and neurodevelopment.

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LAY ABSTRACT: There is some evidence that using therapy dogs for children with autism spectrum disorder generally results in improved social communication skills and reduced behavioral problems. However, well-controlled studies that examine its effectiveness are scarce. This study examined the effectiveness of a "Dog Training Intervention." The study included 73 participants diagnosed with autism spectrum disorder (61 males, 12 females) with age range of 2:10-7:6 years (M = 4:10 ± 1:0) who attend autism spectrum disorder-specific special education schools. The study population was divided into two groups. Each group received the dog training intervention during one part of the school year (first half or second half) in addition to the standard interventions provided by the special education school settings. The dog training intervention was given twice weekly for 4 months within the school setting. The group that received the dog training intervention first showed a significant increase in adaptive social and communication skills in comparison to the second group that did not receive the intervention in this period. This improvement was maintained after the dog training intervention. The second group, which received intervention at the second half of the year, showed improvement in communication and socialization adaptive skills only during the period in which they received the dog training intervention. The positive impact on social communication adaptive skills of the dog training intervention among young children with autism spectrum disorder suggests that dogs may serve as an effective model for establishing social interaction. Dog training intervention appears to be an effective adjunct treatment to the interventions provided in special education schools for young children with autism spectrum disorder.

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LAY ABSTRACT: Raising a child with autism has been linked to mental health difficulties. Poor parental mental health is likely influenced by various factors - including child-, parent-, and family/socioeconomic characteristics. However, little is known about what influences and promotes well-being (as opposed to mental health) among parents of young, newly diagnosed autistic children who may be particularly vulnerable. We examined child-, parent-, and family/socioeconomic factors associated with each of mental health and well-being in a sample of 136 parents of pre-school-aged children. Parental mental health was linked to both child- (i.e. autism symptom severity) and parent-related factors (i.e. personality traits reflecting a tendency to experience negative emotions). By contrast, in additional to mental health difficulties, which were linked to well-being, only other parent-related characteristics (and not child characteristics) were related to well-being. These included personality traits reflecting a tendency to be more extraverted/sociable, and also mindfulness. Other child-related and family/socioeconomic context factors (including household income, parental education level) were not linked to parental mental health or well-being in this sample. These results support the idea that poorer mental health and well-being are not simply the opposite of one another. That is, while these two factors were related, they were linked to different personal characteristics. Perhaps most importantly, the link between well-being and mindfulness - a personal characteristic that parents can improve - suggests mindfulness-based interventions may be helpful in directly supporting parental well-being in the context of raising a young child with autism.

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OBJECTIVE: Real-world functioning is a complex construct influenced by different factors. The impact of social cognition and autism spectrum disorder (ASD) symptoms on different aspects of the life of people with schizophrenia has been demonstrated independently, but it is unclear how these factors are related to functioning when considered concurrently. We hypothesized that ASD symptoms could play a major role in predicting real-world functioning in schizophrenia. METHODS: Existent databases from two studies (SCOPE Phase 3 and SCOPE Phase 5), in which a total of 361 patients (mean age 41.7 years; 117 females) were assessed with measures of symptom severity, neuro- and socio-cognitive abilities, functional capacity, social skills, and informant-reported real-world functioning outcomes, were analyzed. RESULTS: Active social avoidance, social skills, ASD symptoms, and emotion processing emerged as predictors of real-world interpersonal relationships. Cognitive performance, positive symptoms, and functional capacity emerged as predictors of real-world participation in daily activities. Cognitive performance, emotion processing, positive symptoms severity, and social skills emerged as predictors of real-world work outcomes. CONCLUSION: Among other demographic, clinical, and functional capacity variables, increased ASD symptoms emerged as a significant predictor of poorer social relationships and may therefore represent a key factor in predicting real-world social functioning in schizophrenia.

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BACKGROUND: Children with Autism Spectrum Disorder (ASD) of different levels of symptom severity may exhibit a wide range of behaviours and characteristics. There is a limited nutrition-related study on children with ASD of different severity in Malaysia. AIMS: This cross-sectional study aims to determine the association between sociodemographic factors, parental factors, and lifestyle factors with autism severity in children with ASD. METHODS AND PROCEDURES: A total of 224 children with ASD were included in this study. Their mothers completed a self-administered questionnaire on sociodemographic characteristics, autism severity, parenting style, parental feeding practices, parenting stress, child's sleep habits and eating behaviours. OUTCOMES AND RESULTS: As high as 78.1 % of the children with ASD demonstrated a high level of autism severity. Multiple linear regression showed that father's employment status (B = 6.970, 95 % CI = 3.172, 10.768, p < 0.001) and perceived child weight (B = 3.338, 95 % CI = 1.350, 5.327, p = 0.001) predicted autism severity. CONCLUSIONS AND IMPLICATIONS: Children with ASD in this study had a high level of autism severity. Regular anthropometric measurements by healthcare professionals should be conducted at the autism intervention centres. It is important to have multidisciplinary collaboration in future research to develop customised guidelines for parents with autistic children.

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Autism spectrum disorder (ASD) is associated with various molecular mechanisms including copy number variants (CNVs). We investigated possible associations between CNVs and ASD clinical correlates. We evaluated pertinent physical characteristics and phenotypic measures such as cognitive level, severity of ASD symptoms and comorbid conditions in ASD patients consecutively recruited over the study period. Children with causative (C-CNVs), non-causative (NC-CNVs) and without CNVs (W-CNVs) were compared. Out of 109 patients, 31 imbalances (16 duplications and 15 deletions) were detected in 25 subjects. Seven (6.4%) had C-CNVs and 18 (16.5%) had NC-CNVs. Paired post hoc comparisons with Bonferroni adjustment showed that dysmorphisms and microcephaly were significantly more frequent in the C-CNVs group. Patients with C-CNVs had more severe autistic core symptoms, while comorbid internalizing behavioral symptoms were more represented among participants with NC-CNVs. No significant differences were observed for distribution of macrocephaly, intellectual disability, epilepsy, isolated electroencephalogram abnormalities and studied neuroimaging characteristics among groups. Recurrent and rare C-CNVs highlighting genes relevant to neurodevelopment had a statistically higher occurrence in children with more severe ASD symptoms and further developmental abnormalities. This study documents the importance of measuring the physical and neurobehavioural correlates of ASD phenotypes to unravel the underlying molecular mechanisms in patient subgroups.

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BACKGROUND: Previous research has examined the relationship between advanced parental age at conception and the incidence of autism, and has noted strong relationships between advanced parental age and other developmental disabilities. AIM: The purpose of this study was to confirm that and extend that knowledge to the association between advanced parental age and severity of autism symptoms as measured by a parental report of ASD symptom severity. METHODS: The current study included 252 participants between the ages of 2-17 years and their parents. RESULTS: Child's gender and paternal age were found to be significant predictors of autism severity with males and children with older fathers at conception showing the highest severity. Interestingly, maternal age was not found to be a significant predictor of autism risk or severity of symptoms in this sample. CONCLUSION: Possible explanations for these findings are discussed, as well as future directions for research in this area.

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