Diagnosis Of Autism Spectrum Disorder Research Articles

Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods

Rationale and objectivesTo explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features. MethodsA total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients. ResultsCompared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (P< 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively. ConclusionAutomatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.

Demographic and socioeconomic characteristics of patients diagnosed with autism through the Rapid Interactive screening Test for Autism in Toddlers.

We evaluated the integration of the Rapid Interactive screening Test for Autism in Toddlers (RITA-T) model in a community, comparing autism spectrum disorder (ASD) toddlers' demographic and socioeconomic characteristics. Of 394 ASD toddlers, 323 were screened with RITA-T. Those screened were from more deprived areas, traveled farther and were diagnosed earlier. The model improved the diagnosis of ASD in underserved areas.

Espectro del autismo: cambio de paradigma

Autism is a difference in neurodevelopment that influences how you experience the world and how you interact with others. It is considered a quantitative and gradual difference, a spectrum that, in some cases, will cause a disorder, the so-called Autism Spectrum Disorder (ASD). The diagnosis of ASD is made by behavior. The estimated prevalence has been increasing over time, but the increase in diagnoses is considered to be due to the broadening of criteria and a better understanding of the process rather than an actual increase in prevalence. Currently, there is a false stereotype that associates autism with intellectual disability, but this is a comorbidity that occurs only in a minority of patients. In many cases, there is a lack of understanding, a lack of empathy from others towards the autistic person, which considerably hinders their social integration and adds to their differences. This has the double effect of, on the one hand, making them try to compensate or camouflage their differences in a more or less conscious way, to avoid marginalization, and on the other hand, they suffer from problems of stress, anxiety and frustration that can sometimes end up producing a low quality of life and even mental disorders. The new ideas in neurodiversity tend to show this new vision, this new paradigm, of autistic people being perceived as different, with capacities and strengths that society should be able to value and take advantage of, thus facilitating their integration and making their social difficulties disappear, as they are often caused more by the incomprehension of the neurotypical society than by their differences in neuronal mechanisms.

Enhancing Awareness and Understanding of Autism Spectrum Disorder in Minchinabad A Participatory Action Research Approach

This study investigates the effectiveness of interventions aimed at enhancing awareness of Autism Spectrum Disorder (ASD) in Minchinabad through a participatory action research approach. A total of 100 participants were included in this research. They were Community Leaders, Healthcare Professionals, Religious Leaders, and Educators picked through Convenience Sampling. Initial data collection reveals prevalent misconceptions and barriers surrounding ASD awareness. Among them, 89% of respondents expressed a lack of sufficient awareness and 85% attributed ASD to divine factors. Subsequently, community-led workshops, social media campaigns, and Religious institutions-based awareness activities were implemented to address these challenges. Evaluation indicates a significant improvement in awareness levels. Improvement with 53% acknowledging adequate awareness. However, more than 40% still perceive a stigma associated with seeking an ASD diagnosis. While cultural beliefs persist, such as 60% to 68% believing in the divine causation of ASD. The interventions have contributed to a positive shift in community perceptions. The findings underscore the importance of sustained efforts to promote understanding and acceptance of ASD within the community, emphasizing the need for continued engagement and advocacy for ASD Awareness.

The profile of social communication in Dravet syndrome

Dravet syndrome (DS) presents a multifaceted clinical picture marked by epilepsy, cognitive impairments and behavioral disorders that progresses throughout development. Behavioral disorders include impairments in social relationships and communication, with frequent diagnosis of autism spectrum disorder. This study focused on comprehensively evaluating and comparing social communication profiles among a group of 43 children with Dravet syndrome, 30 children with level 1 autism spectrum disorder, 36 with social (pragmatic) communication disorder, and 18 with intellectual disability. Using validated tools like the Childhood Autism Spectrum Test and Children’s Communication Checklist, distinct patterns of social communication deficits were delineated. Our findings indicate that children with Dravet syndrome experience challenges in social relationships, primarily due to difficulties in use of pragmatic language. Areas such as range of interests and social interaction are less affected compared to those with ASD, emphasizing differing profiles between the conditions. While children with DS and ID may have similar intellectual functioning, the different social communication deficits in DS indicate their role in the DS phenotype beyond ID. These results underscore the unique social communication profile of DS and emphasizes the importance of tailored interventions and deep phenotyping efforts for effective DS management.

“Being Able to Think Outside the Box”: Exploring Counselors' Competency Development Working with Children Diagnosed with Autism Spectrum Disorder and Their Families

Professional counselors can play a critical role in treating symptoms of autism spectrum disorder (ASD) among children and working alongside their families. While ethical mandates and best practices for treatment center on holding clinical competencies and working within one's scope, the exploration of counselors in the field who specialize in the treatment of children diagnosed with ASD has not been previously explored in counseling research. Through a focus group format, we utilized interpretative phenomenological inquiry to investigate how six professional counselors who specialize in treating ASD diagnosis made sense in building clinical expertise. Implications for professional counselors were presented to better serve this ever-increasing client population.

Neuronal Remodelling as a Predictor of Autism Spectrum Disorder Diagnosis

People with Autism Spectrum Disorder (ASD) are a neurodevelopmental symptom group characterized by significant deficits in information connectivity, mainly caused by specific genetic mutations affecting the fluency of the gamma-aminobutyric acid (GABAergic) system. This disruption, to a greater or lesser degree, hinders the interactive process of incoming stimuli with previously stored information, preventing working memory from fulfilling its role of facilitating access to information in permanent memory and later recovery. In addition to the genetic components, environmental processes occurring, above all, in early childhood, related to specific organic and severe psycho-emotional diseases can produce the same effects in the brain system as the genetic karyotypic component through the concept of neuronal remodelling. In this sense, this research aims to empirically show the influence of neuronal remodelling on the GABAergic pathway leading to the traits of autism spectrum behaviour. A total of 175 participants from the three levels of ASD intensity have participated in this study. Data have been analysed through Linear Logistic Regression, which shows that both components, the genetic process and the environmental process, significantly influence the neural connective pathway that relates information, unlike other operationalized covariates, such as gender or age of the participants. Likewise, as shown by the Chi-Square Test, the interactions between genetic and environmental variables showed no differences in their interaction regarding the connectivity level that would explain the different levels of disorder. However, when there is a combination of genetic mutations in the diagnostic karyotype, there are significant differences between the genetic group and the environmental process over the neural network.

MEGACÓLON PSICOGÊNICO EM PACIENTE PORTADOR DO TRANSTORNO DO ESPECTRO AUTISTA: UM RELATO DE CASO

Introduction: Psychogenic megacolon (PM) is a rare dysfunction usually found during childhood. This condition is characterized as an abnormal and irreversible dilation of the intestinal colon of psychogenic etiology, that is, such motility disorder is linked to some emotional disorder. A full understanding of this disorder is still a long way off due to its scarce description in the medical literature, however, authors such as Liu et al (2019) define it as a persistent dilation of the colon in the absence of any underlying organic or physiological causes, highlighting its diagnosis as purely eliminatory due to its symptomatic similarity with congenital megacolon (Hirschprung's disease). Objectives: The following case report aims at a retrospective and cross-sectional study, arising from the analysis of the patient's medical records, in order to lay scientific foundations for future research addressing the thematic axis of MP in conjunction with the development of new, more effective therapeutic proposals for the disease. Methods: The data provided in this study were obtained from the active collection of information from the patient's medical record, analyzed in line with others extracted from an interview with the person responsible, however, a literature review was carried out using data platforms as sources of good origin such as Scielo Platform, Google Scholar and PubMed. Results: The case describes a 3-year-old male patient, diagnosed with autism spectrum disorder (ASD) and with a history of previous hospitalizations related to urinary tract infection (UTI) and médium acute otitis (MAO). In the current history, the patient was admitted due to an acute infectious condition unrelated to MP, however, a distended and painless abdomen was found with increased peristalsis with decreased frequency of bowel movements and the presence of a large fecal cake. via ultrasound, with the diagnosis of megacolon, the clinic was related to the diagnosis of ASD and the patient's difficulty in adapting to the hospital environment, making the hypothesis of MP very likely. Conclusion: The report above describes a highly suggestive picture for MP, while this study seeks to raise the hypothesis of its correlation with ASD, while this neurodevelopmental disorder can influence the bowel habits of those patients historically included within the age group conducive to the manifestation of this disease.

MAFT-SO: A novel multi-atlas fusion template based on spatial overlap for ASD diagnosis

Autism spectrum disorder (ASD) is a common neurological condition. Early diagnosis and treatment are essential for enhancing the life quality of individuals with ASD. However, most existing studies either focus solely on the brain networks of subjects within a single atlas or merely employ simple matrix concatenation to represent the fusion of multi-atlas. These approaches neglected the natural spatial overlap that exists between brain regions across multi-atlas and did not fully capture the comprehensive information of brain regions under different atlases. To tackle this weakness, in this paper, we propose a novel multi-atlas fusion template based on spatial overlap degree of brain regions, which aims to obtain a comprehensive representation of brain networks. Specifically, we formally define a measurement of the spatial overlap among brain regions across different atlases, named spatial overlap degree. Then, we fuse the multi-atlas to obtain brain networks of each subject based on spatial overlap. Finally, the GCN is used to perform the final classification. The experimental results on Autism Brain Imaging Data Exchange (ABIDE) demonstrate that our proposed method achieved an accuracy of 0.757. Overall, our method outperforms SOTA methods in ASD/TC classification.

Genetic Testing History in Adults with Autism Spectrum Disorder.

Many genes have been identified in autism spectrum disorder (ASD). Yet little is known about how many adults with ASD receive recommended genetic testing and their outcomes. We investigated the percentage of adults with ASD who received genetic testing using recommended methods in our ASD specialty clinic and the percentage with positive findings. Potentially eligible adults were identified through search of our health system data repository and ASD diagnoses confirmed using review of relevant medical records by consensus of psychiatrists specializing in ASD. Patients were included (N=630) who had at least one visit with a qualifying clinician between 5/1/2010 and 12/15/2020 and demographic data available. Data were collected through manual retrospective review of the electronic health record. Only 41% of the adults with ASD (261/630) had a history of genetic testing documented in the medical record. Genetic testing was declined by patients or families for 11% (72) of records and not recorded in 47% (297). Mean (SD; range) age for the 261 adults with testing documented was 28.5 (5.3; 22-58) years. Sixty-seven (26%) were identified as female, 14 (6%) as Asian, 8 (3%) as Black or African American, 226 (89%) as White, 6 (2%) as other race, and 2 (1%) as Hispanic. 189 (73%) had intellectual disability. Ninety-one percent (236) had the genetic testing method recorded. Only 54% (95% CI: 46%, 61%) of patients had testing using a recommended method (chromosomal array, autism/intellectual disability sequencing panel, or exome sequencing). Few adults had received testing with sequencing technologies. A genetic cause of ASD was found in 28% (95% CI: 19%, 39%) of the 121 adults with results from ASD-related genetic testing recorded. Genetic testing can offer clinical and research insights. Yet it is underutilized in this population of adults with ASD. Nearly half of the adults in our sample lacked documentation of genetic testing. Thus, the percentage of adults with confirmed ASD who had any recommended genetic testing may be even lower than reported. Adults with ASD may benefit from having their genetic testing history reviewed in the clinic and the latest genetic testing performed.

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information

Early identification of the likelihood of autism spectrum disorder (ASD) using minimal information is crucial for early diagnosis and intervention, which can affect developmental outcomes. To develop and validate a machine learning (ML) model for predicting ASD using a minimal set of features from background and medical information and to evaluate the predictors and the utility of the ML model. For this diagnostic study, a retrospective analysis of the Simons Foundation Powering Autism Research for Knowledge (SPARK) database, version 8 (released June 6, 2022), was conducted, including data from 30 660 participants after adjustments for missing values and class imbalances (15 330 with ASD and 15 330 without ASD). The SPARK database contains participants recruited from 31 university-affiliated research clinicals and online in 26 states in the US. All individuals with a professional ASD diagnosis and their families were eligible to participate. The model performance was validated on independent datasets from SPARK, version 10 (released July 21, 2023), and the Simons Simplex Collection (SSC), consisting of 14 790 participants, followed by phenotypic associations. Twenty-eight basic medical screening and background history items present before 24 months of age. Generalizable ML prediction models were developed for detecting ASD using 4 algorithms (logistic regression, decision tree, random forest, and eXtreme Gradient Boosting [XGBoost]). Performance metrics included accuracy, area under the receiver operating characteristics curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and F1 score, offering a comprehensive assessment of the predictive accuracy of the model. Explainable AI methods were applied to determine the effect of individual features in predicting ASD as secondary outcomes, enhancing the interpretability of the best-performing model. The secondary outcome analyses were further complemented by examining differences in various phenotypic measures using nonparametric statistical methods, providing insights into the ability of the model to differentiate between different presentations of ASD. The study included 19 477 (63.5%) male and 11 183 (36.5%) female participants (mean [SD] age, 106 [62] months). The mean (SD) age was 113 (68) months for the ASD group and 100 (55) months for the non-ASD group. The XGBoost (termed AutMedAI) model demonstrated strong performance with an AUROC score of 0.895, sensitivity of 0.805, specificity of 0.829, and PPV of 0.897. Developmental milestones and eating behavior were the most important predictors. Validation on independent cohorts showed an AUROC of 0.790, indicating good generalizability. In this diagnostic study of ML prediction of ASD, robust model performance was observed to identify autistic individuals with more symptoms and lower cognitive levels. The robustness and ML model generalizability results are promising for further validation and use in clinical and population settings.

Neurological Validation of ASD Diagnostic Criteria Using Frontal Alpha and Theta Asymmetry.

Background/Objectives: Diagnosis of Autism Spectrum Disorder (ASD) relies on the observation of difficulties in social communication and interaction, plus the presence of repetitive and restrictive behaviors. The identification of neurological correlates of these symptoms remains a high priority for clinical research, and has the potential to increase the validity of diagnosis of ASD as well as provide greater understanding of how the autistic brain functions. This study focused on two neurological phenomena that have been previously associated with psychiatric disorders (alpha- and theta-wave asymmetry across the frontal region of the brain), and tested for their association with the major diagnostic criteria for ASD. Methods: A total of 41 male autistic youth underwent assessment with the Autism Diagnostic Observation Schedule (ADOS-2) and 3 min of eyes-closed resting EEG to collect alpha- and theta-wave data from right and left frontal brain sites. Results: Different associations were found for theta versus alpha asymmetry and the ADOS-2 subscales, across different brain regions responsible for a varying range of cognitive functions. In general, theta asymmetry was associated with conversation with others, sharing of enjoyment, and making social overtures, whereas alpha asymmetry was linked with making eye contact, reporting events to others, and engaging in reciprocal social communication. Specific brain regions involved are identified, as well as implications for clinical practice. Conclusions: Specific autism symptoms may be associated with selected brain region activity, providing a neurological basis for diagnosis and treatment.

Barriers to and enablers of the transition from child and adolescent to adult mental health services for autistic young people and/or those with attention deficit hyperactivity disorder: protocol for a scoping review

IntroductionAutistic young people and/or those with attention deficit hyperactivity disorder (ADHD) who have co-occurring mental health conditions experience significant challenges when transitioning from child and adolescent mental health services (CAMHS)...

Autism spectrum disorder (ASD) diagnosis: A biochemical investigation into the diagnostic utility of S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH) levels and the SAM/SAH ratio

BackgroundThe balance between SAM and SAH ratios is critical for cellular methylation capacity such that a decrease in this ratio signals decrease the methylation potential, impacting cellular functions. In Autism Spectrum Disorder (ASD), impaired methylation processes are prominent, disrupting essential methyl group transfers crucial for DNA methylation, neurotransmitter synthesis, and detoxification. This disturbance affects gene expression and neural function, contributing to ASD development. This paper aims to explore ASD's pathogenesis by investigating biochemical parameters linked to the methylation cycle. For this purpose, some laboratory parameters are employed to aid in the understanding of potential laboratory abnormalities in ASD in children aged 2 to 8 years. Materials and MethodsThis study included a cohort of 43 children aged 2 to 8 years diagnosed ASD, alongside a control group of 43 age-and gender-matched healthy subjects. The serum of blood samples taken was used to measure biochemical factors. Specimens were processed using ELISA instrumentation and hemogram auto analyzers. The study conducted a statistical comparison between the ASD-diagnosed subjects and healthy controls, focusing on levels of S-adenosyl methionine (SAM), S-adenosyl homocysteine (SAH), Glycine N-methyltransferase (GNMT), and platelet counts. RESULTSThe levels of SAH and platelets were significantly higher in the case group compared to the control group. Conversely, levels of SAM, as well as the SAM/SAH ratio, were found to be significantly lower in the case group than in the control group (p < 0.05). No statistically significant difference was observed in the levels of GNMT when compared (p > 0.05). Receiver Operating Characteristic (ROC) analysis revealed that the diagnostic performance for SAM had an area under the curve (AUC) of 0.876, with a cut-off point determined at 286.9 ng/mL, yielding a sensitivity of 85 % and a specificity of 75 %. For SAH, the AUC was calculated to be 0.671, with a cut-off point set at 0.49 ng/mL, resulting in a sensitivity and specificity of 64 %. The SAM/SAH ratio demonstrated an AUC of 0.806, with the cut-off point established at 576.3, leading to a sensitivity and specificity of 72 %. A significant negative correlation was detected between the scores of the Modified Checklist for Autism in Toddlers (M-CHAT) and both SAM levels and the SAM/SAH ratio. The analysis indicated that an increase of one unit (1 ng/mL) in SAM levels is associated with a decreased autism risk by a factor of 1/0.914 = 1.1 %, whereas an increase of one unit (1 × 103/µL) in platelet count is associated with an increased autism risk by a factor of 1.019 %. Regarding glycine N-methyltransferase, no significant difference was observed between the two groups. ConclusionFollow-up studies with larger samples will be needed to better understand the potential for SAM, SAH, and SAM/SAH as a potential biomarker, at least for a subset of those with ASD. The correlation between these markers and the total score on the M-Chat raises further interest in this possibility. The correlation between these markers and the total score on the M-Chat further supports their utility as clinical biochemical laboratory parameters that could aid in the diagnosis of ASD.

Comorbidity rates of autism spectrum disorder and functional neurological disorders: A systematic review, meta-analysis of proportions and qualitative synthesis.

Autism spectrum disorder (ASD) and functional neurological disorders (FND) are relatively common conditions, and there has been recent interest in the overlap between them. Both conditions share core features of alexithymia, impaired interoception and deficits in attentional focus. To date, relatively little is known about the comorbidity rates between ASD and FND. This is the first meta-analysis and qualitative synthesis on the subject. We found that around 10% of children presenting with functional seizures have a comorbid ASD diagnosis. People with ASD are more likely than the neurotypical population to have functional somatic disorders, and there is also evidence that ASD rates are higher for other FNDs such as functional motor disorders. Since FND comes with risks of unnecessary medical procedures and investigations, it is important to recognize the potential for people with ASD to have an FND comorbidity.

Genetic Diagnostic Yield in Autism Spectrum Disorder (ASD) and Epilepsy Phenotypes in Children with Genetically Defined ASD.

We compared the epilepsy phenotypes in children with genetically defined versus undefined autism spectrum disorder (ASD). A single-center retrospective study was conducted to investigate diagnostic yields of different genetic testing for children with ASD. Patients with at least one testing modality were included and classified as having genetically defined ASD or not based on updated genotype-phenotype correlation. Of the 523 patients included, 79 (15.1%) had results explaining their ASD diagnosis. WES (whole exome sequencing) outperformed CMA (chromosomal microarray) on diagnostic yield (23.0% versus 8.3%). Compared to those with non-diagnostic test(s), children with genetically defined ASD were associated with higher rates for microcephaly, hypotonia, dysmorphic features, and developmental delay/regression. The prevalence of epilepsy was significantly higher in children with genetically defined ASD than those without a genetic diagnosis (35.4% versus 16.4%, p < 0.001, power = 0.97). Furthermore, children with genetically defined ASD had a younger age of epilepsy onset (median 2.2 versus 5.0years, p = 0.002, power = 0.90) and a higher rate of drug-resistant epilepsy although not reaching statistical significance (35.7% versus 21.9%, p = 0.20). Our study has provided further evidence to support WES as first-tier test for children with ASD and that an early genetic diagnosis has the potential to inform further surveillance and management for ASD comorbid conditions including epilepsy.

Age of Autism Spectrum Disorder Diagnosis and Patient-Centered Medical Home Components.

Early diagnosis of autism spectrum disorder (ASD) in children facilitates the provision of services and enhances opportunities for improving functioning via intervention. To date, limited studies have examined whether age of ASD diagnosis is associated with components of care of the patient-centered medical home (PCMH), a model of health care that emphasizes centralized, accessible, and coordinated care. The objective of the current study was to evaluate the associations between components of the PCMH and age of ASD diagnosis while controlling for associated clinical and socio-demographic factors, in a national sample of children 17years and younger with ASD. The present study was a cross-sectional, observational study. Participants were caregivers of 1,193 children ages with ASD from the 2020 National Survey of Children's Health (NSCH). Hierarchical multiple linear regression analysis was run with age of ASD diagnosis as the criterion variable in two regression models. The binary composite medical home proxy variable was investigated as well as the five individual medical home components (usual source of care, personal doctor or nurse, family-centered care, care coordination, able to obtain referrals when needed). In the first regression analysis, the overall PCMH proxy variable was significantly correlated with the age of ASD diagnosis (standardized beta coefficient = -.08; p < .01). Of the five components of the PCMH assessed in the second regression model, only usual source of sick care was significantly associated with the age of ASD diagnosis (standardized beta coefficient = -.11; p < .01). Having a usual source of sick care may be an important factor in receiving an earlier ASD diagnosis for children and adolescents.

Head circumference growth in children with Autism Spectrum Disorder: trend and clinical correlates in the first five years of life.

Macrocephaly is described in almost 15% of children with Autism Spectrum Disorder (ASD). Relationships between head growth trajectories and clinical findings in ASD children show a high degree of variability, highlighting the complex heterogeneity of the disorder. The aim of this study was to measure differences of the early growth trajectory of head circumference (HC) in children with ASD and macrocephaly compared to ASD normocephalic children, examining clinical correlates in the two groups of patients. HC data were collected from birth to 5 years of age in a sample of children with a confirmed diagnosis of ASD. Participants were classified into two groups: ASD macrocephaly (ASD-M, Z-scores ≥1.88 in at least two consecutive HC measurements), and ASD non-macrocephaly (ASD-N). Based on the distribution of HC measurements (Z-scores), five age groups were identified for the longitudinal study. Developmental and behavioral characteristics of the ASD-M children compared to the ASD-N group were compared by using standardized scores. 20,8% of the children sample met criteria for macrocephaly. HC values became indicative of macrocephaly in the ASD-M group at the age range from 1 to 6 months, and persisted thereafter throughout the first five years of age. ASD-M children showed significantly higher developmental quotients of Griffiths III B and D subscales compared to ASD-N group. No significant differences in the severity of ASD symptoms assessed by ADOS-2 were observed between ASD-M and ASD-N groups. In this study HC size from birth to 5 years links to accelerated HC growth rate as early as the first 6 months of age in children with ASD and macrocephaly, preceding the onset and diagnosis of ASD. We found that in early childhood, children with ASD-M may exhibit some advantages in language and social communication and emotional skills without differences in autism severity, when compared with age-matched normocephalic ASD children. Longitudinal analyses are required to catch-up prospectively possible relationships between head size as proxy measure of brain development and neuro-developmental and behavioral features in children with ASD.

Family Involvement During Comprehensive Developmental Evaluations: Perspectives of Diverse Mothers.

Early diagnosis and social support postdiagnosis (i.e., family involvement) can lead to improved outcomes for children with autism spectrum disorder (ASD) and other developmental disorders. Children of minority ethnic and racial groups are typically diagnosed later in childhood compared with White children, contributing to disparities in outcomes. Research has not yet explored family involvement during comprehensive developmental evaluations nor accounted for cross-cultural differences in family roles and involvement. This qualitative study sought to characterize the nature and impact of family involvement during the developmental evaluation process among racially and ethnically marginalized mothers of children with developmental delays and possible ASD. Mothers (N = 27) of children who had a positive autism screen during their 18- or 24-month well-child visit but did not receive an ASD diagnosis after comprehensive developmental evaluation participated in individual semi-structured interviews exploring experiences with developmental screening, related services, and family involvement/social support. Qualitative data were transcribed, coded, and analyzed using applied thematic analysis. Data were stratified by partner status (i.e., partnered vs. nonpartnered) to examine differences in support and family involvement across varying family compositions. Three qualitative themes emerged: (1) mothers sought family involvement when making decisions about pursuing developmental evaluations, (2) family involvement affected mothers' navigation of logistical challenges, and (3) mothers involved family members for emotional support. Differences by partner status emerged in themes 1 and 2. Findings highlight benefits of and potential approaches to harnessing family involvement to support parents' navigation of the developmental evaluation process and ultimately improve child outcomes.

Developmental trajectory and sex differences in auditory processing in a PTEN-deletion model of autism spectrum disorders

Autism Spectrum Disorders (ASD) encompass a wide array of debilitating symptoms, including severe sensory deficits and abnormal language development. Sensory deficits early in development may lead to broader symptomatology in adolescents and adults. The mechanistic links between ASD risk genes, sensory processing and language impairment are unclear. There is also a sex bias in ASD diagnosis and symptomatology. The current study aims to identify the developmental trajectory and genotype- and sex-dependent differences in auditory sensitivity and temporal processing in a Pten-deletion (phosphatase and tensin homolog missing on chromosome 10) mouse model of ASD. Auditory temporal processing is crucial for speech recognition and language development and deficits will cause language impairments. However, very little is known about the development of temporal processing in ASD animal models, and if there are sex differences. To address this major gap, we recorded epidural electroencephalography (EEG) signals from the frontal (FC) and auditory (AC) cortex in developing and adult Nse-cre PTEN mice, in which Pten is deleted in specific cortical layers (layers III-V) (PTEN conditional knock-out (cKO). We quantified resting EEG spectral power distribution, auditory event related potentials (ERP) and temporal processing from awake and freely moving male and female mice. Temporal processing is measured using a gap-in-noise-ASSR (auditory steady state response) stimulus paradigm. The experimental manipulation of gap duration and modulation depth allows us to measure cortical entrainment to rapid gaps in sounds. Temporal processing was quantified using inter-trial phase clustering (ITPC) values that account for phase consistency across trials. The results show genotype differences in resting power distribution in PTEN cKO mice throughout development. Male and female cKO mice have significantly increased beta power but decreased high frequency oscillations in the AC and FC. Both male and female PTEN cKO mice show diminished ITPC in their gap-ASSR responses in the AC and FC compared to control mice. Overall, deficits become more prominent in adult (p60) mice, with cKO mice having significantly increased sound evoked power and decreased ITPC compared to controls. While both male and female cKO mice demonstrated severe temporal processing deficits across development, female cKO mice showed increased hypersensitivity compared to males, reflected as increased N1 and P2 amplitudes. These data identify a number of novel sensory processing deficits in a PTEN-ASD mouse model that are present from an early age. Abnormal temporal processing and hypersensitive responses may contribute to abnormal development of language function in ASD.