Autism Spectrum Disorder Group Research Articles

EEG findings and clinical severity and quality of life in non-epileptic patients with autism spectrum disorders

ABSTRACT Electroencephalogram (EEG) abnormalities could be seen in up to 60% of non-epileptic children with autism spectrum disorder (ASD). They have been used as biomarkers of ASD severity. The objective of our study is to identify EEG abnormalities in children with different degrees of ASD severity based on the Autism Treatment Evaluation Checklist (ATEC). We also want to assess the quality of life for children with ASD. All of the children underwent at least one hour of sleep-deprived EEG. Forty-five children were enrolled, of whom 42 were male. EEG abnormalities were found in 10 (22.2%) children, predominantly in the bilateral frontal areas. There were no differences in EEG findings among the mild, moderate, and severe ASD groups. The severity of ASD was associated with female sex (p-value = 0.013), ASD with attention deficit hyperactivity disorder (ADHD) (p-value = 0.032), ASD children taking medications (p-value = 0.048), and a lower Pediatric Quality of Life Inventory (PedsQL) (p-value <0.001). Social and emotional domains were the most problematic for health-related quality of life in ASD children, according to parent reports of PedsQL. Further studies with a larger sample size will help to clarify the potential associations between EEG abnormalities and the severity of ASD, as well as the impact on quality of life.

Specialization of anterior and posterior hippocampal functional connectivity differs in autism.

Structural and functional differences in the hippocampus have been related to the episodic memory and social impairments observed in autism spectrum disorder (ASD). In neurotypical individuals, hippocampal-cortical functional connectivity systematically varies between anterior and posterior hippocampus, with changes observed during typical development. It remains unknown whether this specialization of anterior-posterior hippocampal connectivity is disrupted in ASD, and whether age-related differences in this specialization exist in ASD. We examined connectivity of the anterior and posterior hippocampus in an ASD (N = 139) and non-autistic comparison group (N = 133) aged 5-21 using resting-state functional magnetic resonance imaging (MRI) data from the Healthy Brain Network (HBN). Consistent with previous results, we observed lower connectivity between the whole hippocampus and medial prefrontal cortex in ASD. Moreover, preferential connectivity of the posterior relative to the anterior hippocampus for memory-sensitive regions in posterior parietal cortex was reduced in ASD, demonstrating a weaker anterior-posterior specialization of hippocampal-cortical connectivity. Finally, connectivity between the posterior hippocampus and precuneus negatively correlated with age in the ASD group but remained stable in the comparison group, suggesting an altered developmental specialization. Together, these differences in hippocampal-cortical connectivity may help us understand the neurobiological basis of the memory and social impairments found in ASD.

Functional Gastrointestinal Symptoms in Children with Autism and ADHD: Profiles of Hair and Salivary Cortisol, Serum Leptin Concentrations and Externalizing/Internalizing Problems.

Functional Gastrointestinal Disorders (FGIDs) present a higher prevalence in individuals with Neurodevelopmental Disorders (NDDs). The Stress System and the Gut-Brain axis (GBA) may mediate these relations. We aimed to assess the prevalence and profile of FGIDs in a clinical sample of children with Autism Spectrum Disorder (ASD) and Attention Deficit/Hyperactivity Disorder (ADHD) compared to typically developing children (TD) as well as to investigate possible relations between stress-related biomarkers and internalizing/externalizing problems in children with NDDS. In total, 120 children, aged between 4 and 12 years old, formed three groups (N = 40, each): ADHD, ASD and TD. Salivary cortisol, hair cortisol and serum leptin were measured. The ASD group had more FGID problems than the TD group (p = 0.001). The ADHD and ASD groups had higher total internalizing/externalizing problems than the TD group (p < 0.0001, p < 0.0001, p = 0.005, respectively). Children with FGIDs showed more total, internalizing and externalizing problems compared to children without FGIDs (p < 0.0001, p < 0.0001, p = 0.041, respectively). The ADHD group showed lower AUCg values (p < 0.0001), while the hair cortisol was higher for the TD group (p < 0.0001). In conclusion, children with NDDs had more FGID symptoms and present higher internalizing and externalizing problems. Children with ADHD and FGIDs had more internalizing problems compared to those without FGIDs. No differences in stress-related biomarkers were shown to differentiate children with NDDs with and without FGIDs. Future prospective studies including a greater number of children may elucidate the biological pathways linking these comorbidities.

Explaining deep learning-based representations of resting state functional connectivity data: focusing on interpreting nonlinear patterns in autism spectrum disorder

BackgroundResting state Functional Magnetic Resonance Imaging fMRI (rs-fMRI) has been used extensively to study brain function in psychiatric disorders, yielding insights into brain organization. However, the high dimensionality of the rs-fMRI data presents significant challenges for data analysis. Variational autoencoders (VAEs), a type of neural network, have been instrumental in extracting low-dimensional latent representations of resting state functional connectivity (rsFC) patterns, thereby addressing the complex nonlinear structure of rs-fMRI data. Despite these advances, interpreting these latent representations remains a challenge. This paper aims to address this gap by developing explainable VAE models and testing their utility using rs-fMRI data in autism spectrum disorder (ASD).MethodsOne-thousand one hundred and fifty participants (601 healthy controls [HC] and 549 patients with ASD) were included in the analysis. RsFC correlation matrices were extracted from the preprocessed rs-fMRI data using the Power atlas, which includes 264 regions of interest (ROIs). Then VAEs were trained in an unsupervised manner. Lastly, we introduce our latent contribution scores to explain the relationship between estimated representations and the original rs-fMRI brain measures.ResultsWe quantified the latent contribution scores for both the ASD and HC groups at the network level. We found that both ASD and HC groups share the top network connectivitives contributing to all estimated latent components. For example, latent 0 was driven by rsFC within ventral attention network (VAN) in both the ASD and HC. However, we found significant differences in the latent contribution scores between the ASD and HC groups within the VAN for latent 0 and the sensory/somatomotor network for latent 2.ConclusionThis study introduced latent contribution scores to interpret nonlinear patterns identified by VAEs. These scores effectively capture changes in each observed rsFC feature as the estimated latent representation changes, enabling an explainable deep learning model that better understands the underlying neural mechanisms of ASD.

Comparison of urine glycosaminoglycan excretion between children with autism spectrum disorder and typically developed children

BackgroundAbnormalities pertaining to glycosaminoglycan metabolism have been demonstrated in children with autism spectrum disorder. The aim of the present study was to compare urine excretion of sulfated glycosaminoglycans in children with autism spectrum disorder, with neurotypical controls and explore its association with co-occurring symptoms. MethodRandom urine samples were collected from children with autism spectrum disorder (n = 61) between the ages of 2 and 6 years, and age- and sex-matched neurotypical controls. Urine glycosaminoglycan levels were quantified by the dimethylmethylene blue (DMMB) dye-binding assay. ResultsMean glycosaminoglycan/creatinine ratio of children with autism spectrum disorder was 22.279 ± 13.044 mg/mmol while that of neurotypical controls was 19.121 ± 7.319 mg/mmol. Eight patients with autism spectrum disorder (13.11%) exhibited abnormally high glycosaminoglycan excretion. Unstandardized urine glycosaminoglycan levels are significantly higher (p = 0.019) in the autism spectrum disorder group when covariates such as age, urinary creatinine, and height are taken into consideration by ANCOVA. However, the outcome showed a trend towards significance when glycosaminoglycan/creatinine ratio was used in ANCOVA (p = 0.058). In neurotypical subjects, the urine glycosaminoglycan levels appear to decline with age, height, and weight while this trend was not apparent in subjects with autism spectrum disorder. Glycosaminoglycan excretion did not correlate with the presence of co-occurring symptoms of autism spectrum disorder; frequent gastrointestinal symptoms, self-injurious behaviors, food aversions, or parent-reported sleep problems. ConclusionsA subset of children with autism spectrum disorder exhibits higher urine glycosaminoglycan excretion. Further research is needed to explore the molecular basis of this finding.

A Systematic Review on Autism and Hyperserotonemia: State-of-the-Art, Limitations, and Future Directions.

Hyperserotonemia is one of the most studied endophenotypes in autism spectrum disorder (ASD), but there are still no unequivocal results about its causes or biological and behavioral outcomes. This systematic review summarizes the studies investigating the relationship between blood serotonin (5-HT) levels and ASD, comparing diagnostic tools, analytical methods, and clinical outcomes. A literature search on peripheral 5-HT levels and ASD was conducted. In total, 1104 publications were screened, of which 113 entered the present systematic review. Of these, 59 articles reported hyperserotonemia in subjects with ASD, and 26 presented correlations between 5-HT levels and ASD-core clinical outcomes. The 5-HT levels are increased in about half, and correlations between hyperserotonemia and clinical outcomes are detected in a quarter of the studies. The present research highlights a large amount of heterogeneity in this field, ranging from the characterization of ASD and control groups to diagnostic and clinical assessments, from blood sampling procedures to analytical methods, allowing us to delineate critical topics for future studies.

The relationship between gamma-band neural oscillations and language skills in youth with Autism Spectrum Disorder and their first-degree relatives

BackgroundMost children with Autism Spectrum Disorder (ASD) have co-occurring language impairments and some of these autism-specific language difficulties are also present in their non-autistic first-degree relatives. One of the possible neural mechanisms associated with variability in language functioning is alterations in cortical gamma-band oscillations, hypothesized to be related to neural excitation and inhibition balance.MethodsWe used a high-density 128-channel electroencephalography (EEG) to register brain response to speech stimuli in a large sex-balanced sample of participants: 125 youth with ASD, 121 typically developing (TD) youth, and 40 unaffected siblings (US) of youth with ASD. Language skills were assessed with Clinical Evaluation of Language Fundamentals.ResultsFirst, during speech processing, we identified significantly elevated gamma power in ASD participants compared to TD controls. Second, across all youth, higher gamma power was associated with lower language skills. Finally, the US group demonstrated an intermediate profile in both language and gamma power, with nonverbal IQ mediating the relationship between gamma power and language skills.LimitationsWe only focused on one of the possible neural contributors to variability in language functioning. Also, the US group consisted of a smaller number of participants in comparison to the ASD or TD groups. Finally, due to the timing issue in EEG system we have provided only non-phase-locked analysis.ConclusionsAutistic youth showed elevated gamma power, suggesting higher excitation in the brain in response to speech stimuli and elevated gamma power was related to lower language skills. The US group showed an intermediate pattern of gamma activity, suggesting that the broader autism phenotype extends to neural profiles.

Frequency of Hypocalcemia and Hypomagnesemia in Autistic Spectrum Disordered Children of Bangladesh

Background: Autistic spectrum disorder (ASD) in children is commonly associated with mitochondrial dysfunction and mineral deficiency. Studies have highlighted links between Ca2+ and Mg2+ deficiency and neuronal excitability, along with connections between iron deficiency and behavioral abnormalities in individuals with ASD. Objective: This study was aimed to assess the frequency of hypocalcemia and hypomagnesemia in autistic spectrum-disordered children of Bangladesh. Methods: This cross-sectional study was conducted in the Department of Physiology, Bangabandhu Sheikh Mujib Medical University, Dhaka from March 2014 to January 2015. The study included 100 randomly selected male children, with 50 in a healthy control group (Group A) and 50 diagnosed with autistic spectrum disorder (Group B). Children with ASD were selected from the Parents Forum (DOHS, Mohakhali), while the control group was chosen from schools with typically developing children. Fasting serum levels of various components along with calcium and magnesium were measured, and statistical analysis was conducted using independent sample 't' tests and proportion (Z) tests, with a significance level set at p-value ˂0.05. Results: In this study, out of 50 autistic spectrum disorder cases, the frequencies of hypocalcemia and hypomagnesemia were 74% and 52%, respectively. A comparison with the control group revealed significantly higher frequencies of both hypomagnesemia and hypocalcemia in the ASD group, with p-values &lt;0.001. Conclusions: Among most children with autism spectrum disorder in Bangladesh, hypocalcemia and hypomagnesemia are prevalent. These prevalences are significantly higher than those observed in healthy children. J Rang Med Col. March 2024; Vol. 9, No. 1: 55-58

Investigation of Liver X Receptor Gene Variants and Oxysterol Dysregulation in Autism Spectrum Disorder.

The NR1H2 gene produces the Liver X Receptor Beta (LXRB) protein, which is crucial for brain cholesterol metabolism and neuronal development. However, its involvement in autism spectrum disorder (ASD) remains largely unexplored, aside from animal studies. This study is the first to explore the potential link between autism and rs2695121/rs17373080 single nucleotide polymorphisms (SNPs) in the regulatory regions of NR1H2, known for their association with neuropsychiatric functions. Additionally, we assessed levels of oxysterols (24-Hydroxycholesterol, 25-Hydroxycholesterol, 27-Hydroxycholesterol), crucial ligands of LXR, and lipid profiles. Our cohort comprised 107 children with ASD and 103 healthy children aged 2-18 years. Clinical assessment tools included the Childhood Autism Rating Scale, Autistic Behavior Checklist, and Repetitive Behavior Scale-Revised. Genotyping for SNPs was conducted using PCR-RFLP. Lipid profiles were analyzed with Beckman Coulter kits, while oxysterol levels were determined through liquid chromatography-tandem mass spectrometry. Significantly higher total cholesterol (p = 0.003), LDL (p = 0.008), and triglyceride (p < 0.001) levels were observed in the ASD group. 27-Hydroxycholesterol levels were markedly lower in the ASD group (p ≤ 0.001). ROC analysis indicated the potential of 27-Hydroxycholesterol to discriminate ASD diagnosis. The SNP genotype and allele frequencies were similar in both groups (p > 0.05). Our findings suggest that disturbances in oxysterol metabolism, previously linked to neurodegeneration, may constitute a risk factor for ASD and contribute to its heterogeneous phenotype.

Decreased brain iron deposition based on quantitative susceptibility mapping correlates with reduced neurodevelopmental status in children with autism spectrum disorder.

To investigate potential correlations between the susceptibility values of certain brain regions and the severity of disease or neurodevelopmental status in children with autism spectrum disorder (ASD), 18 ASD children and 15 healthy controls (HCs) were recruited. The neurodevelopmental status was assessed by the Gesell Developmental Schedules (GDS) and the severity of the disease was evaluated by the Autism Behavior Checklist (ABC). Eleven brain regions were selected as regions of interest and the susceptibility values were measured by quantitative susceptibility mapping. To evaluate the diagnostic capacity of susceptibility values in distinguishing ASD and HC, the receiver operating characteristic (ROC) curve was computed. Pearson and Spearman partial correlation analysis were used to depict the correlations between the susceptibility values, the ABC scores, and the GDS scores in the ASD group. ROC curves showed that the susceptibility values of the left and right frontal white matter had a larger area under the curve in the ASD group. The susceptibility value of the right globus pallidus was positively correlated with the GDS-fine motor scale score. These findings indicated that the susceptibility value of the right globus pallidus might be a viable imaging biomarker for evaluating the neurodevelopmental status of ASD children.

Trajectory of depressive symptoms over adolescence in autistic and neurotypical youth

BackgroundAdolescence coincides with a dramatic rise in the onset of psychiatric conditions including depression. Depression symptoms may be particularly prevalent and impairing for youth with autism spectrum disorder (ASD). While prior research suggests adolescence is associated with worsening depression symptoms for typically developing (TD) and autistic youth, it is unclear if they follow a similar course.MethodThe study examined the trajectory of depressive symptoms in autistic and neurotypical youth over a 4-year longitudinal study using linear and logistic mixed effects models. In youth with clinically relevant depressive scores (t-score > 65), moderating factors (i.e., diagnosis, age, puberty, sex) were explored. During Year 1, the sample included 244 youth 10-to-13 years: 140 in the ASD group (36 females) and 104 in the TD group (46 females).ResultsAutistic youth had elevated depression scores compared to TD peers (p < 0.001) and females were higher than males in both groups (p = 0.001). There was significant diagnosis by age (p < 0.001) and diagnosis by pubertal stage (p < 0.05) interactions. In the ASD group, elevated depressive scores presented in early adolescence and decreased during middle adolescence and puberty, whereas the TD group showed the opposite trend with an increase in depression symptoms with advancing development.LimitationsLimitations include an unequal sex distribution (fewer females), non-representative autistic sample (e.g., cognition and race/ethnicity), and potential confound of the COVID-19 pandemic.ConclusionsAutistic youth present with higher rates of depressive symptoms early in development; yet, approaching middle adolescence and puberty, the symptom trajectory in the autistic youth declines coinciding with an increase in the TD youth. While group trajectories are divergent, they lead to similar levels of depression in late adolescence with higher symptoms in females. Findings suggest a period of quiescence in depressive symptomology influenced by biopsychosocial factors impacting affective profiles.

Attention and sensory integration for gait in young adults with autism spectrum disorder

IntroductionAltered sensorimotor function is a common feature of autism spectrum disorder (ASD). As a result, spatiotemporal walking patterns are typically affected. Attentional processes relevant for locomotion may be altered in people with ASD. This study assessed the extent to which gait alterations observed under sensory challenging conditions are due to reduced attention-related processes in young adults with ASD. MethodsTwenty-one adults with ASD and 21 age- and sex-matched neurotypical participants walked at a self-selected pace on a 10-m walkway under 12 sensory/attention conditions: hard or carpet flooring; well-lit or dim lighting; no attention task, an auditory choice-reaction time information-processing task, or a simple reaction time information-processing task. Gait data were collected with a 12-marker motion capture set and a trunk accelerometer. Spatiotemporal characteristics of gait were derived and compared between the two groups across gait conditions. ResultsFloor/light conditions impacted gait speed, average step length, average stance time, average step width, and step width variability similarly in both groups (p<0.05). The information processing tasks impacted average step length, gait speed, and step length variability (p<0.05). Group differences were found in step length metrics: the ASD group had decreased average step length during the simple reaction time information-processing task and neurotypical participants did not (p=0.039); the ASD group had increased variability on carpet compared to hard floor and the neurotypical group had no change in variability due to floor (p=0.015). SignificanceThese results suggest that attentional set-shifting and somatosensory inputs may play an important role in ASD-related gait alterations. Step length metrics appear to be sensitive to group differences between ASD and neurotypical adults during sensory challenging conditions.

Using virtual reality to enhance attention for autistic spectrum disorder with eye tracking

Attention deficit disorder is a frequently observed symptom in individuals with autism spectrum disorder (ASD). This condition can present significant obstacles for those affected, manifesting in challenges such as sustained focus, task completion, and the management of distractions. These issues can impede learning, social interactions, and daily functioning. This complexity of symptoms underscores the need for tailored approaches in both educational and therapeutic settings to support individuals with ASD effectively. In this study, we have expanded upon our initial virtual reality (VR) prototype, originally created for attention therapy, to conduct a detailed statistical analysis. Our objective was to precisely identify and measure any significant differences in attention-related outcomes between sessions and groups. Our study found that heart rate (HR) and electrodermal activity (EDA) were more responsive to attention shifts than temperature. The ‘Noise’ and ‘Score’ strategies significantly affected eye openness, with the ASD group showing more responsiveness. The control group had smaller pupil sizes, and the ASD group’s pupil size increased notably when switching strategies in Session 1. Distraction log data showed that both ‘Noise’ and ‘Object Opacity’ strategies influenced attention patterns, with the ‘Red Vignette’ strategy showing a significant effect only in the ASD group. The responsiveness of HR and EDA to attention shifts and the changes in pupil size could serve as valuable physiological markers to monitor and guide these interventions. These findings further support evidence that VR has positive implications for helping those with ASD, allowing for more tailored personalized interventions with meaningful impact.

An Exploratory Characterization of Speech- and Fine-Motor Coordination in Verbal Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder often associated with difficulties in speech production and fine-motor tasks. Thus, there is a need to develop objective measures to assess and understand speech production and other fine-motor challenges in individuals with ASD. In addition, recent research suggests that difficulties with speech production and fine-motor tasks may contribute to language difficulties in ASD. In this paper, we explore the utility of an off-body recording platform, from which we administer a speech- and fine-motor protocol to verbal children with ASD and neurotypical controls. We utilize a correlation-based analysis technique to develop proxy measures of motor coordination from signals derived from recordings of speech- and fine-motor behaviors. Eigenvalues of the resulting correlation matrix are inputs to Gaussian Mixture Models to discriminate between highly-verbal children with ASD and neurotypical controls. These eigenvalues also characterize the complexity (underlying dimensionality) of representative signals of speech- and fine-motor movement dynamics, and form the feature basis to estimate scores on an expressive vocabulary measure. Based on a pilot dataset (15 ASD and 15 controls), features derived from an oral story reading task are used in discriminating between the two groups with AUCs > 0.80, and highlight lower complexity of coordination in children with ASD. Features derived from handwriting and maze tracing tasks led to AUCs of 0.86 and 0.91, however features derived from ocular tasks did not aid in discrimination between the ASD and neurotypical groups. In addition, features derived from free speech and sustained vowel tasks are strongly correlated with expressive vocabulary scores. These results indicate the promise of a correlation-based analysis in elucidating motor differences between individuals with ASD and neurotypical controls.

T1w/T2w ratio maps identify children with autism spectrum disorder and the relationships between myelin-related changes and symptoms

BackgroundModern neuroimaging methods have revealed that autistic symptoms are associated with abnormalities in brain morphology, connectivity, and activity patterns. However, the changes in brain microstructure underlying the neurobiological and behavioral deficits of autism remain largely unknown. Methodswe characterized the associated abnormalities in intracortical myelination pattern by constructing cortical T1-weighted/T2-weighted ratio maps. Voxel-wise comparisons of cortical myelination were conducted between 150 children with autism spectrum disorder (ASD) and 139 typically developing (TD) children. Group differences in cortical T1-weighted/T2-weighted ratio and gray matter volume were then examined for associations with autistic symptoms. A convolutional neural network (CNN) model was also constructed to examine the utility of these regional abnormalities in cortical myelination for ASD diagnosis. ResultsCompared to TD children, the ASD group exhibited widespread reductions in cortical myelination within regions related to default mode, salience, and executive control networks such as the inferior frontal gyrus, bilateral insula, left fusiform gyrus, bilateral hippocampus, right calcarine sulcus, bilateral precentral, and left posterior cingulate gyrus. Moreover, greater myelination deficits in most of these regions were associated with more severe autistic symptoms. In addition, children with ASD exhibited reduced myelination in regions with greater gray matter volume, including left insula, left cerebellum_4_5, left posterior cingulate gyrus, and right calcarine sulcus. Notably, the CNN model based on brain regions with abnormal myelination demonstrated high diagnostic efficacy for ASD. ConclusionsOur findings suggest that microstructural abnormalities in myelination contribute to autistic symptoms and so are potentially promising therapeutic targets as well as biomarkers for ASD diagnosis.

The implication of sleep disturbances on daily executive functioning and learning problems in children with autism without intellectual disability

BackgroundIndividuals with autism spectrum disorder (ASD) often have sleep disturbances, executive functioning difficulties, and learning problems. The aim of this study was twofold. First, to examine the quality of sleep in children with ASD without intellectual disability and typically developing (TD) children. Second, to explore the implication of sleep disturbances in the association between daily executive functioning and learning problems in children with ASD without intellectual disability. MethodThe sample included 47 children with autism without intellectual disability and 32 TD children. Parent-reported questionnaires were used to assess participants' sleep disturbances, daily executive functions, and learning problems. All statistical analyses performed were adjusted for age, IQ, and medication. ResultsAs expected, the prevalence of sleep disturbances was significantly higher in the ASD group than in the TD group. Regarding the second aim of the study, the total score of sleep disturbances was significantly associated with learning problems and the metacognition subdomain of executive functioning in children with autism without intellectual disability. In turn, executive functions and learning problems were also significantly associated. Finally, sleep disturbances were found to mediate the relationship between global executive functioning and learning problems in children with ASD without intellectual disability. ConclusionsThe findings suggest that sleep disturbances are common in children with autism, and that they play a mediating role in the association between executive functions and learning problems. Therefore, sleep should be a crucial aspect of interventions to improve the learning and academic performance of school-aged children with ASD without intellectual disability.

Motor proficiency of persons with attention deficit hyperactivity disorder or autism spectrum disorder diagnosed in adulthood

Purpose To compare (1) motor proficiency of persons diagnosed in adulthood with attention deficit hyperactivity disorder (ADHD) or autism spectrum disorder (ASD) with normative values of motor proficiency, and (2) motor proficiency between persons with ADHD and those with ASD diagnosed in adulthood. Methods A total of 153 adults (median age 32 years, 36% women) participated in this cross-sectional study. Fifty-three persons with predominately inattentive presentation (ADHD-I), 67 persons with combined presentation (ADHD-C), and 33 persons with ASD performed the Bruininks-Oseretsky Test of Motor Proficiency (BOT-2). One-sample binominal tests were used to compare motor proficiency against standardized norms of BOT-2 for young adults. One-way ANOVAs and Kruskal-Wallis tests were used to compare test outcomes between the groups. Results The total sample showed significantly impaired motor proficiency in comparison to norms in all test domains (p < 0.001–0.006), except for fine motor skills. The ASD group showed significantly poorer body coordination compared with the ADHD-I and ADHD-C groups, with a moderate effect size (p = 0.003–0.02, η2 = 0.061). Conclusions Motor proficiency is impaired in most persons with ADHD or ASD diagnosed in adulthood, suggesting that motor assessment should be included in clinical examinations of adults with suspected neurodevelopment disorders.

Associations Between Joint Attention, Supported Joint Engagement and Language in TD Children and Children with ASD: Potential Sources of Individual and Group Differences in Language Outcomes

ABSTRACT Joint Attention (JA) and Supported Joint Engagement (Supported JE) have each been reported to predict later language development in typically developing (TD) children and children with Autism Spectrum Disorder (ASD). In this longitudinal study including 33 TD children (20 months at V1) and 30 children with ASD (33 months at V1), the contributions of JA and Supported JE to later language, assessed via standardized tests and spontaneous speech, were directly compared. Frequency and durations of JA and Supported JE episodes were coded from 30-minute interactions with caregivers; subsequent language skills were assessed two years later. JA duration in the ASD group significantly predicted later standardized and spontaneous language, most strongly in the low-verbal ASD subgroup. Supported JE measures did not positively predict later language in either group. These findings suggest that JA played a larger role with children with ASD with low-verbal abilities, but not with children with ASD with high-verbal abilities nor with the TD children. The current study adds to existing literature by providing further support for studying children with ASD as two subgroups based on their verbal abilities (high vs low), as well as directly comparing the effects of JA and Supported JE on later language development in such groups. Implications for further research are discussed.

Neurofeedback training of executive function in autism spectrum disorder: distinct effects on brain activity levels and compensatory connectivity changes

BackgroundDeficits in executive function (EF) are consistently reported in autism spectrum disorders (ASD). Tailored cognitive training tools, such as neurofeedback, focused on executive function enhancement might have a significant impact on the daily life functioning of individuals with ASD. We report the first real-time fMRI neurofeedback (rt-fMRI NF) study targeting the left dorsolateral prefrontal cortex (DLPFC) in ASD.MethodsThirteen individuals with autism without intellectual disability and seventeen neurotypical individuals completed a rt-fMRI working memory NF paradigm, consisting of subvocal backward recitation of self-generated numeric sequences. We performed a region-of-interest analysis of the DLPFC, whole-brain comparisons between groups and, DLPFC-based functional connectivity.ResultsThe ASD and control groups were able to modulate DLPFC activity in 84% and 98% of the runs. Activity in the target region was persistently lower in the ASD group, particularly in runs without neurofeedback. Moreover, the ASD group showed lower activity in premotor/motor areas during pre-neurofeedback run than controls, but not in transfer runs, where it was seemingly balanced by higher connectivity between the DLPFC and the motor cortex. Group comparison in the transfer run also showed significant differences in DLPFC-based connectivity between groups, including higher connectivity with areas integrated into the multidemand network (MDN) and the visual cortex.ConclusionsNeurofeedback seems to induce a higher between-group similarity of the whole-brain activity levels (including the target ROI) which might be promoted by changes in connectivity between the DLPFC and both high and low-level areas, including motor, visual and MDN regions.

The Metabolic Insight into Autism Spectrum Disorder: Evaluating Adiponectin's Impact on Severity and Therapy

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with a complex interplay of genetic and environmental factors. Recent research has suggested a significant link between metabolic alterations and ASD pathology, particularly focusing on adiponectin, a hormone related to glucose regulation and fatty acid breakdown. Anomalies in adiponectin levels have been associated with cognitive impairment and the severity of ASD. Objective: This study aims to evaluate the potential of the ADIPOQ gene as a biomarker for dementia in individuals with ASD, exploring its correlation with cognitive decline and metabolic dysregulation. Methods: A total of 108 EDTA blood samples from ASD patients and 32 from healthy controls were collected after obtaining written informed consent. The inclusion criteria included individuals aged over 40 with Type II Diabetes Mellitus and confirmed cases of diabetes and dementia. Exclusion criteria comprised the absence of clinical history, refusal of consent, and secondary autism. Adiponectin levels were quantified using ELISA, and cognitive function was assessed via MMSE scores over a six-month follow-up period. Data analysis was conducted using GraphPad Prism 9.0 with ANOVA for statistical significance. Results: The study found a significant decrease in adiponectin levels among ASD patients (5.17±1.04 µg/mL) compared to healthy controls (11.37±4.14 µg/mL, p=0.014). MMSE scores were notably lower in the ASD group (10.26±2.56) than in controls (23.1±3.12, p=0.006). A marked underexpression of ADIPOQ gene (fold change of 4.9) was observed in patients with dementia. Conclusion: The ADIPOQ gene shows potential as a biomarker for the early detection of dementia in ASD, offering avenues for personalized medical interventions and preventative healthcare measures. Recognizing its role could lead to improved therapeutic strategies and a reduction in the healthcare burden due to neurodegenerative diseases associated with ASD.