1. Alsaqati M, Heine VM, Harwood AJ. {{Pharmacological intervention to restore connectivity deficits of neuronal networks derived from ASD patient iPSC with a TSC2 mutation}}. {Mol Autism}. 2020; 11(1): 80.
BACKGROUND: Tuberous sclerosis complex (TSC) is a rare genetic multisystemic disorder resulting from autosomal dominant mutations in the TSC1 or TSC2 genes. It is characterised by hyperactivation of the mechanistic target of rapamycin complex 1 (mTORC1) pathway and has severe neurodevelopmental and neurological components including autism, intellectual disability and epilepsy. In human and rodent models, loss of the TSC proteins causes neuronal hyperexcitability and synaptic dysfunction, although the consequences of these changes for the developing central nervous system are currently unclear. METHODS: Here we apply multi-electrode array-based assays to study the effects of TSC2 loss on neuronal network activity using autism spectrum disorder (ASD) patient-derived iPSCs. We examine both temporal synchronisation of neuronal bursting and spatial connectivity between electrodes across the network. RESULTS: We find that ASD patient-derived neurons with a functional loss of TSC2, in addition to possessing neuronal hyperactivity, develop a dysfunctional neuronal network with reduced synchronisation of neuronal bursting and lower spatial connectivity. These deficits of network function are associated with elevated expression of genes for inhibitory GABA signalling and glutamate signalling, indicating a potential abnormality of synaptic inhibitory-excitatory signalling. mTORC1 activity functions within a homeostatic triad of protein kinases, mTOR, AMP-dependent protein Kinase 1 (AMPK) and Unc-51 like Autophagy Activating Kinase 1 (ULK1) that orchestrate the interplay of anabolic cell growth and catabolic autophagy while balancing energy and nutrient homeostasis. The mTOR inhibitor rapamycin suppresses neuronal hyperactivity, but does not increase synchronised network activity, whereas activation of AMPK restores some aspects of network activity. In contrast, the ULK1 activator, LYN-1604, increases the network behaviour, shortens the network burst lengths and reduces the number of uncorrelated spikes. LIMITATIONS: Although a robust and consistent phenotype is observed across multiple independent iPSC cultures, the results are based on one patient. There may be more subtle differences between patients with different TSC2 mutations or differences of polygenic background within their genomes. This may affect the severity of the network deficit or the pharmacological response between TSC2 patients. CONCLUSIONS: Our observations suggest that there is a reduction in the network connectivity of the in vitro neuronal network associated with ASD patients with TSC2 mutation, which may arise via an excitatory/inhibitory imbalance due to increased GABA-signalling at inhibitory synapses. This abnormality can be effectively suppressed via activation of ULK1.
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2. Attia SM, Ahmad SF, Nadeem A, Attia MSM, Ansari MA, As Sobeai HM, Al-Mazroua HA, Alasmari AF, Bakheet SA. {{3-Aminobenzamide alleviates elevated DNA damage and DNA methylation in a BTBR T(+)Itpr3(tf)/J mouse model of autism by enhancing repair gene expression}}. {Pharmacology, biochemistry, and behavior}. 2020: 173057.
Little is known about genetic and epigenetic alterations in autism spectrum disorder. Moreover, the efficiency of DNA repair in autism must be improved to correct these alterations. We examined whether 3-aminobenzamide (3-AB) could reverse these alterations. We conducted experiments to clarify the molecular mechanism underlying these ameliorations. An assessment of genetic and epigenetic alterations by a modified comet assay showed elevated levels of oxidative DNA strand breaks and DNA hypermethylation in BTBR T(+)Itpr3(tf)/J (BTBR) mice used as a model of autism. Oxidative DNA strand breaks and DNA methylation were further quantified fluorometrically, and the results showed similar changes. Conversely, 3-AB treated BTBR mice showed a significant reduction in these alterations compared with untreated mice. The expressions of 43 genes involved in DNA repair were altered in BTBR mice. RT(2) Profiler PCR Array revealed significantly altered expression of seven genes, which was confirmed by RT-PCR analyses. 3-AB treatment relieved these disturbances and significantly improved Ogg1 and Rad1 up-regulation. Moreover, autism-like behaviors were also mitigated in BTBR animals by 3-AB treatment without alterations in locomotor activities. The simultaneous effects of reduced DNA damage and DNA methylation levels as well as the regulation of repair gene expression indicate the potential of 3-AB as a therapeutic agent to decrease the levels of DNA damage and DNA methylation in autistic patients. The current data may help in the development of therapies that ultimately provide a better quality of life for individuals suffering from autism.
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3. Engelhard MM, Berchuck SI, Garg J, Henao R, Olson A, Rusincovitch S, Dawson G, Kollins SH. {{Health system utilization before age 1 among children later diagnosed with autism or ADHD}}. {Sci Rep}. 2020; 10(1): 17677.
Children with autism spectrum disorder (ASD) or attention deficit hyperactivity disorder (ADHD) have 2-3 times increased healthcare utilization and annual costs once diagnosed, but little is known about their utilization patterns early in life. Quantifying their early health system utilization could uncover condition-specific health trajectories to facilitate earlier detection and intervention. Patients born 10/1/2006-10/1/2016 with ≥ 2 well-child visits within the Duke University Health System before age 1 were grouped as ASD, ADHD, ASD + ADHD, or No Diagnosis using retrospective billing codes. An additional comparison group was defined by later upper respiratory infection diagnosis. Adjusted odds ratios (AOR) for hospital admissions, procedures, emergency department (ED) visits, and outpatient clinic encounters before age 1 were compared between groups via logistic regression models. Length of hospital encounters were compared between groups via Mann-Whitney U test. In total, 29,929 patients met study criteria (ASD N = 343; ADHD N = 1175; ASD + ADHD N = 140). ASD was associated with increased procedures (AOR = 1.5, p < 0.001), including intubation and ventilation (AOR = 2.4, p < 0.001); and outpatient specialty care, including physical therapy (AOR = 3.5, p < 0.001) and ophthalmology (AOR = 3.1, p < 0.001). ADHD was associated with increased procedures (AOR = 1.41, p < 0.001), including blood transfusion (AOR = 4.7, p < 0.001); hospital admission (AOR = 1.60, p < 0.001); and ED visits (AOR = 1.58, p < 0.001). Median length of stay was increased after birth in ASD (+ 6.5 h, p < 0.001) and ADHD (+ 3.8 h, p < 0.001), and after non-birth admission in ADHD (+ 1.1 d, p < 0.001) and ASD + ADHD (+ 2.4 d, p = 0.003). Each condition was associated with increased health system utilization and distinctive patterns of utilization before age 1. Recognizing these patterns may contribute to earlier detection and intervention. Lien vers le texte intégral (Open Access ou abonnement)
4. Gonzales-Rojas R, Rana AN, Mason P, Renfro C, Annaluru V, Panda S, Lee HY. {{The mouse model of fragile X syndrome exhibits deficits in contagious itch behavior}}. {Sci Rep}. 2020; 10(1): 17679.
Individuals with autism spectrum disorders (ASDs) imitate observed behavior less than age-matched and typically developing peers, resulting in deterred learning ability and social interaction. However, this deficit lacks preclinical assessment tools. A previous study has shown that mice exhibit contagious itch behavior while viewing a scratching demonstrator mouse, as opposed to an ambulating demonstrator mouse, but whether autism mouse models imitate observed scratching behavior remains unknown. Here, we investigated contagious itch behavior in the mouse model of fragile X syndrome (FXS), a common form of inherited intellectual disabilities with a high risk for ASDs. We found that the mouse model of FXS shows deficits in contagious itch behavior. Our findings can be used as a new preclinical assessment tool for measuring imitative deficits in the study of neurodevelopmental disorders including FXS.
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5. Hedger N, Dubey I, Chakrabarti B. {{Social Orienting and Social Seeking Behaviors in ASD. A Meta Analytic Investigation}}. {Neurosci Biobehav Rev}. 2020.
Social motivation accounts of autism spectrum disorder (ASD) posit that individuals with ASD find social stimuli less rewarding than neurotypical (NT) individuals. Behaviorally, this is proposed to manifest in reduced social orienting (individuals with ASD direct less attention towards social stimuli) and reduced social seeking (individuals with ASD invest less effort to receive social stimuli). In two meta-analyses, involving data from over 6000 participants, we review the available behavioral studies that assess social orienting and social seeking behaviors in ASD. We found robust evidence for reduced social orienting in ASD, across a range of paradigms, demographic variables and stimulus contexts. The most robust predictor of this effect was interactive content – effects were larger when the stimulus involved an interaction between people. By contrast, the evidence for reduced social seeking indicated weaker evidence for group differences, observed only under specific experimental conditions. The insights gained from this meta-analysis can inform design of relevant task measures for social reward responsivity and promote directions for further study on the ASD phenotype.
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6. Hong JS, Singh V, Kalb L. {{Attention Deficit Hyperactivity Disorder Symptoms in Young Children with Autism Spectrum Disorder}}. {Autism Res}. 2020.
The purpose of the current study was to examine the prevalence of attention deficit hyperactivity disorder (ADHD) symptoms among young children with autism spectrum disorder (ASD), child and parent-related demographic and clinical correlates of ADHD symptoms, and the relationships between co-occurring mental health problems and ADHD symptoms. Data for this cross-sectional study came from 979 toddlers and preschoolers, ages 1.5-5 years, with ASD. The primary outcome, ADHD symptoms, was measured using the Child Behavior Check List 1.5-5 (CBCL). Additional information from the medical record included demographics, parenting stress, and Autism Diagnostic Observation Schedule Second Edition. Descriptive and bivariate (ANOVA, Chi-Square) statistics and multivariate, multinomial regression analyses were used to examine demographic and clinical differences between low, moderate, and high ADHD symptom groups, as defined by 2 ADHD-related subscales. There were 418 (43%) children in the low ADHD symptom group, 294 (30%) in the moderate ADHD symptom group, and 267 (27%) in the high ADHD symptom group. Those with high ADHD symptoms were less likely to be Black or Hispanic and less likely to have parents with a graduate-level education compared to those with low ADHD symptoms. Parenting stress and all CBCL DSM-oriented subscales were positively associated with increasing ADHD symptoms. Among young children with ASD, ADHD symptoms were highly prevalent. The presence of ADHD symptoms was associated with increasing parenting stress and greater levels of other psychopathologies. These data suggest that young children with ASD should be evaluated for ADHD, and mental health as a whole. LAY SUMMARY: We investigated attention deficit hyperactivity disorder (ADHD) symptoms in toddlers and preschoolers with autism spectrum disorder (ASD) from a large sample with diverse race and socioeconomic background. In our study, we found that ADHD symptoms are highly prevalent in young children with ASD and are associated with increasing parenting stress and greater level of other psychopathologies, both internalizing and externalizing problems.
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7. Kaliukhovich DA, Manyakov NV, Bangerter A, Ness S, Skalkin A, Goodwin MS, Dawson G, Hendren RL, Leventhal B, Hudac CM, Bradshaw J, Shic F, Pandina G. {{Social attention to activities in children and adults with autism spectrum disorder: effects of context and age}}. {Mol Autism}. 2020; 11(1): 79.
BACKGROUND: Diminished visual monitoring of faces and activities of others is an early feature of autism spectrum disorder (ASD). It is uncertain whether deficits in activity monitoring, identified using a homogeneous set of stimuli, persist throughout the lifespan in ASD, and thus, whether they could serve as a biological indicator (« biomarker ») of ASD. We investigated differences in visual attention during activity monitoring in children and adult participants with autism compared to a control group of participants without autism. METHODS: Eye movements of participants with autism (n = 122; mean age [SD] = 14.5 [8.0] years) and typically developing (TD) controls (n = 40, age = 16.4 [13.3] years) were recorded while they viewed a series of videos depicting two female actors conversing while interacting with their hands over a shared task. Actors either continuously focused their gaze on each other’s face (mutual gaze) or on the shared activity area (shared focus). Mean percentage looking time was computed for the activity area, actors’ heads, and their bodies. RESULTS: Compared to TD participants, participants with ASD looked longer at the activity area (mean % looking time: 58.5% vs. 53.8%, p < 0.005) but less at the heads (15.2% vs. 23.7%, p < 0.0001). Additionally, within-group differences in looking time were observed between the mutual gaze and shared focus conditions in both participants without ASD (activity: Δ = - 6.4%, p < 0.004; heads: Δ = + 3.5%, p < 0.02) and participants with ASD (bodies: Δ = + 1.6%, p < 0.002). LIMITATIONS: The TD participants were not as well characterized as the participants with ASD. Inclusion criteria regarding the cognitive ability [intelligence quotient (IQ) > 60] limited the ability to include individuals with substantial intellectual disability. CONCLUSIONS: Differences in attention to faces could constitute a feature discriminative between individuals with and without ASD across the lifespan, whereas between-group differences in looking at activities may shift with development. These findings may have applications in the search for underlying biological indicators specific to ASD. Trial registration ClinicalTrials.gov identifier NCT02668991.
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8. Li X, Liu G, Chen W, Bi Z, Liang H. {{Network analysis of autistic disease comorbidities in Chinese children based on ICD-10 codes}}. {BMC medical informatics and decision making}. 2020; 20(1): 268.
BACKGROUND: Autism is a lifelong disability associated with several comorbidities that confound diagnosis and treatment. A better understanding of these comorbidities would facilitate diagnosis and improve treatments. Our aim was to improve the detection of comorbid diseases associated with autism. METHODS: We used an FP-growth algorithm to retrospectively infer disease associations using 1488 patients with autism treated at the Guangzhou Women and Children’s Medical Center. The disease network was established using Cytoscape 3.7. The rules were internally validated by 10-fold cross-validation. All rules were further verified using the Columbia Open Health Data (COHD) and by literature search. RESULTS: We found 148 comorbid diseases including intellectual disability, developmental speech disorder, and epilepsy. The network comprised of 76 nodes and 178 directed links. 158 links were confirmed by literature search and 105 links were validated by COHD. Furthermore, we identified 14 links not previously reported. CONCLUSION: We demonstrate that the FP-growth algorithm can detect comorbid disease patterns, including novel ones, in patients with autism.
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9. Malucelli ERS, Antoniuk SA, Carvalho NO. {{The effectiveness of early parental coaching in the autism spectrum disorder}}. {J Pediatr (Rio J)}. 2020.
OBJECTIVE: Analysis of the effectiveness of early Parental Coaching in the Autism Spectrum Disorder. METHOD: Randomized, controlled and blinded clinical trial to analyze parent-child interaction videos. RESULTS: The sample consisted of 18 children being followed up at the Autism Outpatient Clinic of a Neuropediatric Center in southern Brazil diagnosed with Autism Spectrum Disorder, between 29 and 42 months of age, randomly allocated to two groups: the Study Group (SG; n = 9), which received Parental Coaching performed by a professional certified by the ESDM (Early Start Denver Model); and the Control Group (CG; n = 9), which was in a routine follow-up, without treatment and training of parents by a trained professional. The parents of the SG were willing to attend weekly meetings and to apply the instructional techniques at home with their children. It took 12 weeks and an average of 2 h per meeting. CONCLUSIONS: The learning rate for comprehensive development skills in the ESDM checklist, such as receptive communication, expressive communication, social capacity, imitation, cognition, games, fine motor skills, gross motor skills, behavior, and personal independence was significantly higher in the SG, as well as the strategies and the quality of interaction between parents and children. Thus, Parental Coaching presents as a possibility of early intervention in children with Autism Spectrum Disorder.
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10. McLennan JD, Bahadur A, Cobigo V, Hrycko S, Fulford C. {{Cross-sector service use patterns among children with developmental disabilities in a district in Canada}}. {J Appl Res Intellect Disabil}. 2020.
BACKGROUND: There is a lack of information about cross-sector service use by children with developmental disabilities despite their need for services from multiple sectors. METHODS: Responses to service use questions from a parent-completed survey on school-aged children who attended clinics specific for those with developmental disabilities at a Canadian children’s hospital were examined. RESULTS: School meetings were the most common of three professional meeting types attended in the last 12 months (64.9%) for the sample of 205 children. Recreational services were the most common of five service types received in the same time period (79.0%). Using ordinal logistic regression models, a higher number of behavioural difficulties was the only variable consistently related to indices of more meeting types (school, physician, other) attended and more service types received (recreation, respite, etc.). CONCLUSIONS: The service relationship with behavioural problems, and not socio-demographic variables, is consistent with a needs-based oriented delivery system.
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11. Moreau CA, Urchs SGW, Kuldeep K, Orban P, Schramm C, Dumas G, Labbe A, Huguet G, Douard E, Quirion PO, Lin A, Kushan L, Grot S, Luck D, Mendrek A, Potvin S, Stip E, Bourgeron T, Evans AC, Bearden CE, Bellec P, Jacquemont S. {{Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia}}. {Nat Commun}. 2020; 11(1): 5272.
16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. Here we report an analysis of resting-state FC using magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We characterize CNV FC-signatures and use them to identify dimensions contributing to complex idiopathic conditions. CNVs have large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions play a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibit worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.
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12. Morgan J. {{Catherine Lord: changing futures for people with autism}}. {Lancet Psychiatry}. 2020; 7(11): 938.
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13. Ohta H, Aoki YY, Itahashi T, Kanai C, Fujino J, Nakamura M, Kato N, Hashimoto RI. {{White matter alterations in autism spectrum disorder and attention-deficit/hyperactivity disorder in relation to sensory profile}}. {Mol Autism}. 2020; 11(1): 77.
BACKGROUND: Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have high rates of co-occurrence and share atypical behavioral characteristics, including sensory symptoms. The present diffusion tensor imaging (DTI) study was conducted to examine whether and how white matter alterations are observed in adult populations with developmental disorders (DD) and to determine how brain-sensory relationships are either shared between or distinct to ASD and ADHD. METHODS: We collected DTI data from adult population with DD (a primary diagnosis of ASD: n = 105, ADHD: n = 55) as well as age- and sex-matched typically developing (TD) participants (n = 58). Voxel-wise fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity (RD) were analyzed using tract-based spatial statistics. The severities of sensory symptoms were assessed using the Adolescent/Adult Sensory Profile (AASP). RESULTS: Categorical analyses identified voxel clusters showing significant effects of DD on FA and RD in the posterior portion of the corpus callosum and its extension in the right hemisphere. Furthermore, regression analyses using the AASP scores revealed that slopes in relationships of FA or RD with the degree of sensory symptoms were parallel between the two DDs in large parts of the affected corpus callosum regions. A small but significant cluster did exist showing difference in association between an AASP subscale score and RD across ASD and ADHD. LIMITATIONS: Wide age range of the participants may be oversimplified. CONCLUSIONS: These results indicate that white matter alteration and their relationships to sensory symptoms are largely shared between ASD and ADHD, with localized abnormalities showing significant between-diagnosis differences within DD.
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14. Yin W, Mostafa S, Wu FX. {{Diagnosis of Autism Spectrum Disorder Based on Functional Brain Networks with Deep Learning}}. {Journal of computational biology : a journal of computational molecular cell biology}. 2020.
Autism spectrum disorder (ASD) is a neurological and developmental disorder. Traditional diagnosis of ASD is typically performed through the observation of behaviors and interview of a patient. However, these diagnosis methods are time-consuming and can be misleading sometimes. Integrating machine learning algorithms with neuroimages, a diagnosis method, can possibly be established to detect ASD subjects from typical control subjects. In this study, we develop deep learning methods for diagnosis of ASD from functional brain networks constructed with brain functional magnetic resonance imaging (fMRI) data. The entire Autism Brain Imaging Data Exchange 1 (ABIDE 1) data set is utilized to investigate the performance of our proposed methods. First, we construct the brain networks from brain fMRI images and define the raw features based on such brain networks. Second, we employ an autoencoder (AE) to learn the advanced features from the raw features. Third, we train a deep neural network (DNN) with the advanced features, which achieves the classification accuracy of 76.2% and the receiving operating characteristic curve (AUC) of 79.7%. As a comparison, we also apply the same advanced features to train several traditional machine learning algorithms to benchmark the classification performance. Finally, we combine the DNN with the pretrained AE and train it with the raw features, which achieves the classification accuracy of 79.2% and the AUC of 82.4%. These results show that our proposed deep learning methods outperform the state-of-the-art methods.
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15. You Y, Correas A, Jao Keehn RJ, Wagner LC, Rosen BQ, Beaton LE, Gao Y, Brocklehurst WT, Fishman I, Müller RA, Marinkovic K. {{MEG Theta during Lexico-Semantic and Executive Processing Is Altered in High-Functioning Adolescents with Autism}}. {Cereb Cortex}. 2020.
Neuroimaging studies have revealed atypical activation during language and executive tasks in individuals with autism spectrum disorders (ASD). However, the spatiotemporal stages of processing associated with these dysfunctions remain poorly understood. Using an anatomically constrained magnetoencephalography approach, we examined event-related theta oscillations during a double-duty lexical decision task that combined demands on lexico-semantic processing and executive functions. Relative to typically developing peers, high-functioning adolescents with ASD had lower performance accuracy on trials engaging selective semantic retrieval and cognitive control. They showed an early overall theta increase in the left fusiform cortex followed by greater activity in the left-lateralized temporal (starting at ~250 ms) and frontal cortical areas (after ~450 ms) known to contribute to language processing. During response preparation and execution, the ASD group exhibited elevated theta in the anterior cingulate cortex, indicative of greater engagement of cognitive control. Simultaneously increased activity in the ipsilateral motor cortex may reflect a less lateralized and suboptimally organized motor circuitry. Spanning early sensory-specific and late response selection stages, the higher event-related theta responsivity in ASD may indicate compensatory recruitment to offset inefficient lexico-semantic retrieval under cognitively demanding conditions. Together, these findings provide further support for atypical language and executive functions in high-functioning ASD.
