1. Alshihri AA, Al-Askar MH, Aldossary MS. {{Correction to: Barriers to Professional Dental Care among Children with Autism Spectrum Disorder}}. {J Autism Dev Disord}. 2020.
In the original publication of the article, the author’s affiliation was processed incorrectly without the name of department. The correct affiliation of the author « Mohammed S. Aldossary » is given below.
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2. Brueggeman L, Koomar T, Michaelson JJ. {{Author Correction: Forecasting risk gene discovery in autism with machine learning and genome-scale data}}. {Sci Rep}. 2020; 10(1): 20994.
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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3. Hirayama A, Wakusawa K, Fujioka T, Iwata K, Usui N, Kurita D, Kameno Y, Wakuda T, Takagai S, Hirai T, Nara T, Ito H, Nagano Y, Oowada S, Tsujii M, Tsuchiya KJ, Matsuzaki H. {{Simultaneous evaluation of antioxidative serum profiles facilitates the diagnostic screening of autism spectrum disorder in under-6-year-old children}}. {Sci Rep}. 2020; 10(1): 20602.
This case-control study aimed to assess oxidative stress alterations in autism spectrum disorder (ASD). We used the MULTIS method, an electron spin resonance-based technique measuring multiple free radical scavenging activities simultaneously, in combination with conventional oxidative stress markers to investigate the ability of this MULTIS approach as a non-behavioural diagnostic tool for children with ASD. Serum samples of 39 children with ASD and 58 age-matched children with typical development were analysed. The ASD group showed decreased hydroxyl radical ((•)OH) and singlet oxygen scavenging activity with increased serum coenzyme Q10 oxidation rate, indicating a prooxidative tendency in ASD. By contrast, scavenging activities against superoxide (O(2)(•-)) and alkoxyl radical (RO(•)) were increased in the ASD group suggesting antioxidative shifts. In the subgroup analysis of 6-year-olds or younger, the combination of (•)OH, O(2)(•-), and RO(•) scavenging activities predicted ASD with high odds ratio (50.4), positive likelihood (12.6), and percentage of correct classification (87.0%). Our results indicate that oxidative stress in children with ASD is not simply elevated but rather shows a compensatory shift. MULTIS measurements may serve as a very powerful non-behavioural tool for the diagnosis of ASD in children.
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4. Jin X, Simmons SK, Guo A, Shetty AS, Ko M, Nguyen L, Jokhi V, Robinson E, Oyler P, Curry N, Deangeli G, Lodato S, Levin JZ, Regev A, Zhang F, Arlotta P. {{In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes}}. {Science (New York, NY)}. 2020; 370(6520).
The number of disease risk genes and loci identified through human genetic studies far outstrips the capacity to systematically study their functions. We applied a scalable genetic screening approach, in vivo Perturb-Seq, to functionally evaluate 35 autism spectrum disorder/neurodevelopmental delay (ASD/ND) de novo loss-of-function risk genes. Using CRISPR-Cas9, we introduced frameshift mutations in these risk genes in pools, within the developing mouse brain in utero, followed by single-cell RNA-sequencing of perturbed cells in the postnatal brain. We identified cell type-specific and evolutionarily conserved gene modules from both neuronal and glial cell classes. Recurrent gene modules and cell types are affected across this cohort of perturbations, representing key cellular effects across sets of ASD/ND risk genes. In vivo Perturb-Seq allows us to investigate how diverse mutations affect cell types and states in the developing organism.
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5. Long J, Lu F, Guo X, Pang Y, Yang S, Chen H, He B. {{Parcellation of the thalamus by using a dual-segment method based on resting-state functional connectivity: an application on autism spectrum disorder}}. {Neurosci Lett}. 2020: 135518.
BACKGROUND: Evidence suggests thalamus is a key « information relay » center and all cortical areas receive inputs from the thalamus and each of the main nuclei of thalamus connects a single one or a few cortical areas. The traditional « winner-takes-all » thalamus parcellation method was then proposed based on this assumption. However, this method is based on the structural segments of the cortex which is not suitable for the functional parcellation of the thalamus. METHOD: Here we proposed a dual-segment method for thalamus functional parcellation based on the resting-state fMRI data. The traditional « winner-takes-all » and the proposed dual-segment methods were both applied to the dataset of 76 healthy controls (HCs) and 34 subjects with autism spectrum disorder. RESULTS: The results showed that the thalamus was subdivided into two sub-regions by using the dual-segment method: one is located in the dorsomedial part of thalamus which connects the high-level cognitive cortical regions; the other is located in the ventrolateral part of thalamus which connects the low-level sensory cortical areas. The functional connectivity strength between thalamus sub-regions and the corresponding cortical regions based on the dual-segment method was higher than that of results from the traditional « winner-takes-all » method. The thalamo-cortical functional connectivity based on our proposed method also showed higher classification ability to distinguish subjects with autism spectrum disorder from HCs. CONCLUSION: Our study will provide a new method for functional thalamus parcellation which might help understand the sub-regions functions of thalamus in neuroscience studies.
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6. Ma X, Wang XH, Lihua L. {{Identifying individuals with autism spectrum disorder based on the principal components of whole-brain phase synchrony}}. {Neurosci Lett}. 2020: 135519.
Autism spectrum disorder (ASD) is a brain disorder that develops during an early stage of childhood. Previous neuroimaging-based diagnostic models for ASD were based on static functional connectivity (FC). The nonlinear complexity of brain connectivity remains unexplored for ASD diagnosis. This study aimed to build intelligent discriminative models for ASD based on phase synchrony (PS). To this end, data from 49 patients with ASD and 41 healthy controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) project. PS between brain regions was determined using Hilbert transform. Principal component analysis (PCA) and support vector machines (SVMs) were used to build the discriminative models. PS-based models (AUC = 0.81) outperformed static FC-based models (AUC = 0.71). Furthermore, embedded functional biomarkers were discovered. Moreover, significant correlations were found between PCA-PS and the clinical severity of ASD. Together, intelligent discriminative models based on PS were established for ASD identification. The performance of the diagnostic models suggested the potential benefits of PS for clinical applications. The discriminative patterns indicated that PCA-PS features could be additional biomarkers for ASD research. Furthermore, the significant relationships between the PCA-PS features and clinical scores implied their potential use for personalized medication strategies.
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7. McLean KJ, Hoekstra AM, Bishop L. {{United States Medicaid home and community-based services for people with intellectual and developmental disabilities: A scoping review}}. {J Appl Res Intellect Disabil}. 2020.
Emerging research tests the impact of United States Medicaid home and community-based (HCBS) waiver policy on outcomes for people with intellectual and developmental disabilities; however, this body of work has yet to be synthesized. We conducted a scoping review to establish what is known about the impact of Medicaid HCBS policy on the lives of people with intellectual and developmental disabilities. Seven studies met final inclusion criteria. Their findings contribute to preliminary evidence that Medicaid HCBS waivers provide economic benefit at the state and federal level, reduce unmet healthcare needs, increase the likelihood that parents will be able to continue working, and reduce racial disparities in access to care. Additional work should compare HCBS waiver programmes, and their causal pathways, as well as draw international comparisons to similar programming, to determine essential infrastructure needed for a successful HCBS programme.
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8. Patrini M. {{Is family therapy effective for people with autism spectrum disorder and their families? A Cochrane Review summary with commentary}}. {Dev Med Child Neurol}. 2020.
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9. Shillington A, Capal JK. {{Genetic testing in patients with nonsyndromic autism spectrum disorder and EEG abnormalities with or without epilepsy: Is exome trio-based testing the best clinical approach?}}. {Epilepsy Behav}. 2020: 107564.
OBJECTIVES: The association between autism spectrum disorder (ASD) and epilepsy is well-known. Abnormalities on electroencephalography (EEG) studies have been reported in patients with ASD without a history of seizures, and these patients have lower functional scores on adaptive measures than patients with ASD with normal EEG studies. The purpose of the study was to evaluate the genetic test approach in children with ASD and abnormal EEGs. METHODS: Data were collected from medical records at Cincinnati Children’s Hospital Medical Center (CCHMC) of a previously published cohort of patients with well-characterized ASD based on evaluation by Developmental Pediatrics. Patients were subdivided into two groups: ASD without epilepsy, but with abnormal EEG results, and ASD with epilepsy. EEG data were abstracted from reports. In this follow-up study, we analyzed genetic testing data, namely the proportion of this cohort that received genetic testing, and the specific type of genetic testing that was ordered to analyze if there were any differences between groups. RESULTS: Analysis was performed on 173 patients with ASD. Ninety-five patients had a diagnosis of epilepsy. Seventy-eight patients did not have a diagnosis of epilepsy but did have abnormal EEGs. In both groups, approximately three quarters of all subjects received routine neurodevelopmental genetic testing (77% versus 72% p = 0.15) without significant differences between groups. The ASD + epilepsy group was more likely to receive additional second-tier genetic testing outside of a routine neurodevelopmental workup (35% versus 15% p = 0.007). The ASD + epilepsy group was more likely to receive phenotype specific panels, most often an epilepsy gene panel of less than 250 genes (15% versus 3% p = 0.008). However, the ASD + epilepsy group was less likely to receive a genetic diagnosis from testing than the ASD + abnormal EEG group (9% versus 33%, p = 0.047). CONCLUSIONS: Patients with ASD along with a formal epilepsy diagnosis received more genetic testing; but had an overall lower diagnostic rate than patients with ASD with abnormal EEGs but without a formal epilepsy diagnosis. Patients in this cohort without a diagnosis of epilepsy were more likely to get broad trio-based exome testing instead of targeted epilepsy gene panel testing. A higher diagnostic rate was found in patients when a broad genetic test strategy was implemented.
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10. West R, Silverman MJ. {{Social Skills Instruments for Children with Autism Spectrum Disorder: A Critical Interpretive Synthesis}}. {Journal of music therapy}. 2020.
Identifying and critically analyzing the most frequently used social skills psychometric instruments (SSPI) for children with autism spectrum disorder (ASD) can inform future music therapy research and clinical practice. Therefore, the initial purpose of this critical interpretive synthesis was to identify the SSPI most frequently used as dependent measures in the Journal of Autism and Developmental Disorders (JADD) for children with ASD from 2012 to 2018. Results indicated that the Social Responsiveness Scale (n = 35), Autism Diagnostic Observation Schedule (n = 19), and Vineland Adaptive Behavior Scales (n = 15) were the most frequently used instruments. Congruent with critical interpretive synthesis methodology, we then identified the psychometric properties and advantages and disadvantages of the 9 most commonly used instruments. To compare these results with the existing music therapy literature, we also identified nonmusical SSPI used as dependent measures in music therapy research for children with ASD in studies published between 2012 and 2018. In comparing the data sets, music therapy researchers used 5 of the 9 SSPI we identified from our JADD review. Understanding frequently used SSPI has applications for consultation and communication with other professionals as well as how future music therapy research is conducted. Implications for clinical practice, limitations of the study, and suggestions for future research are provided.
