Seminars in Pediatric Neurology : Advances in the Diagnosis and Treatment of Autism Spectrum Disorder-1 (Juillet 2020)

vendredi 3 juillet 2020

La revue Seminars in Pediatric Neurology propose en juillet 2020 un premier volume sur les dernières avancées dans le diagnostic et les traitements proposés dans le TSA.

Advances in the Diagnosis and Treatment of Autism Spectrum Disorder-1

1. Frye RE. Introduction to Part 1. Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100802.

Autism spectrum disorder (ASD) is one of the most challenging neurodevelopmental disorders of our era that the Centers for Disease Control and Prevention estimates the prevalence to be about 1 in 59 children in the United States. Over the last two decades, research focusing on ASD has increased, particularly in areas focusing on physiological disruptions such as mitochondrial and redox metabolism abnormalities, immune system dysfunction and environmental health, although research focusing on genetics and behavior still predominate the field. Drug treatment trials have provided few “home runs” with many failures and some promising, but preliminary, results. A series of two issues of Seminars in Pediatric Neurology will provide articles representing the cutting edge of research and clinical care for children with ASD. The first issue will contain three articles on Advances in Diagnostic Methodology and three articles on Cutting Edge Method for Studying Outcomes. The second issue will contain articles on Advances in Early Screening and Diagnosis on the Front Lines and Novel and Cutting-Edge Therapies. I believe the two issues will provide significant insight into new and exciting developments in the field as well as provide a framework for understanding the challenges ahead.

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2. Vargason T, Grivas G, Hollowood-Jones KL, Hahn J. Towards a Multivariate Biomarker-Based Diagnosis of Autism Spectrum Disorder : Review and Discussion of Recent Advancements. Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100803.

An ever-evolving understanding of autism spectrum disorder (ASD) pathophysiology necessitates that diagnostic standards also evolve from being observation-based to include quantifiable clinical measurements. The multisystem nature of ASD motivates the use of multivariate methods of statistical analysis over common univariate approaches for discovering clinical biomarkers relevant to this goal. In addition to characterization of important behavioral patterns for improving current diagnostic instruments, multivariate analyses to date have allowed for thorough investigation of neuroimaging-based, genetic, and metabolic abnormalities in individuals with ASD. This review highlights current research using multivariate statistical analyses to quantify the value of these behavioral and physiological markers for ASD diagnosis. A detailed discussion of a blood-based diagnostic test for ASD using specific metabolite concentrations is also provided. The advancement of ASD biomarker research promises to provide earlier and more accurate diagnoses of the disorder.

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3. Kreiman BL, Boles RG. State of the Art of Genetic Testing for Patients With Autism : A Practical Guide for Clinicians. Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100804.

The explosion in knowledge, technology, and clinical capabilities regarding genetics and genetic testing has expanded greatly in recent years, and these gains have rapidly been applied to individuals with autism spectrum disorder (ASD). However, most clinicians are unaware or confused in regards to whom to test, what tests to order, and how testing might alter management and improve outcomes. This review will address these issues. Research shows that ASD is highly genetic, and while monogenic cases are common, most patients have multiple genes interacting in disease pathogenesis. However, as genetics dictates disease risk, not outcomes, this does not exclude environmental factors. Clinically actionable genetics test results can be found across the phenotypically-heterogeneous ASD spectrum ; thus recommendations are to test everyone. As ASD is also highly genetically heterogeneous, testing should address a wide range of variant types, including both large (historically detected by microarray) and small (detected by sequencing), at least across all genes (exome). Additional specialized testing important in ASD diagnostics includes fragile X, mitochondrial DNA, and pharmacogenetics ; the latter often informative for which drug to order, at which dose. Recently, whole genome sequencing has emerged as a favorite since all of the above testing, and more, can be performed at a lower total cost than individual test orders. Trio (child plus parents) sequencing is often indicated, especially in more “severe” cases in order to find new (de novo) variants not present in either parent. Additionally, Angelman syndrome testing should be considered in appropriate cases. Current testing provides a precise diagnosis in many cases with ASD. Beyond diagnosis, genetic testing can oftentimes help elucidate potentially treatable risk factors that predispose the individual patient to develop disease. In this clinician’s experience (RGB), this information leads to improved outcomes in as many as one-half of cases. Clinical improvement can occur in common associated ASD symptoms (attention, behavior, and anxiety) and/or in general systemtic symptoms (nausea, fatigue, pain), as demonstrated in brief case reports. Practical guidance is provided regarding assisting clinicians to choose the appropriate test(s) and laboratory, as well as how to get testing paid for. Recent cost reductions now allow for most families to benefit from genetic testing.

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4. Dekhil O, Ali M, Haweel R, Elnakib Y, Ghazal M, Hajjdiab H, Fraiwan L, Shalaby A, Soliman A, Mahmoud A, Keynton R, Casanova MF, Barnes G, El-Baz A. A Comprehensive Framework for Differentiating Autism Spectrum Disorder From Neurotypicals by Fusing Structural MRI and Resting State Functional MRI. Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100805.

Autism spectrum disorder is a neurodevelopmental disorder characterized by impaired social abilities and communication difficulties. The golden standard for autism diagnosis in research rely on behavioral features, for example, the autism diagnosis observation schedule, the Autism Diagnostic Interview-Revised. In this study we introduce a computer-aided diagnosis system that uses features from structural MRI (sMRI) and resting state functional MRI (fMRI) to help predict an autism diagnosis by clinicians. The proposed system is capable of parcellating brain regions to show which areas are most likely affected by autism related abnormalities and thus help in targeting potential therapeutic interventions. When tested on 18 data sets (n = 1060) from the ABIDE consortium, our system was able to achieve high accuracy (sMRI 0.75-1.00 ; fMRI 0.79-1.00), sensitivity (sMRI 0.73-1.00 ; fMRI 0.78-1.00), and specificity (sMRI 0.78-1.00 ; fMRI 0.79-1.00). The proposed system could be considered an important step toward helping physicians interpret results of neuroimaging studies and personalize treatment options. To the best of our knowledge, this work is the first to combine features from structural and functional MRI, use them for personalized diagnosis and achieve high accuracies on a relatively large population.

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5. Grzadzinski R, Janvier D, Kim SH. Recent Developments in Treatment Outcome Measures for Young Children With Autism Spectrum Disorder (ASD). Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100806.

Significant advancements have been made in early intervention programs for children with Autism spectrum disorder (ASD). However, measuring treatment response for children with ASD is difficult due to the heterogeneity of changes in symptoms, which can be subtle, especially over a short period of time. Here we outline the challenge of evaluating treatment response with currently available measures as well as newly developed or refined measures that may be useful in clinical trials for young children with ASD. Continued development of treatment outcome measures will help the field identify and compare efficacious interventions and tailor treatments for children with ASD.

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6. Amoss RT, Leong T, Evans AN, Ousley O, Herrington JD, Lecavalier L, Goodwin MS, Hofmann SG, Scahill L. A Pilot Study of Cardiovascular Reactivity in Children With Autism Spectrum Disorder. Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100807.

In preparation for a larger case-control study of children with autism spectrum disorder (ASD) and anxiety, we conducted a pilot study using a noninvasive electrocardiographic device to measure cardiovascular reactivity in 10 children (age range 9-14) with ASD. The 45-minute procedure included 6 conditions : baseline rest, an interview about school, interim rest, an unfair computerized ball-toss game followed by a fair version of the game, and a final rest. Data were successfully collected for 95% of all conditions. Omnibus Skillings-Mack tests suggested that heart rate variability variables including mean heart rate, mean RR interval, and root mean square of successive differences showed statistically significant variation across conditions. The procedure appears feasible and may be an informative biomarker of anxiety in ASD.

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7. Bent S, Wahlberg J, Chen Y, Widjaja F, McDonald MG, Hendren RL. Quality of Life Among School-Age Children With Autism : The Oak Hill School Outcomes Study. Seminars in Pediatric Neurology ;2020 (2020/07/01/) ;34:100808.

Prior studies have documented a lower quality of life (QOL) in children with autism spectrum disorder (ASD) compared to typically developing peers, but few studies have examined the trajectory of QOL over time in the same population. We conducted a 2-year cohort study in 29 children attending a specialized school for ASD with quarterly measures of parent-rated QOL as well as parent and teacher measures of behavior and social skills to determine the trajectory of change in QOL and predictors of change. The average change in QOL was constant (no change over time), but there was substantial variation with some students showing significant gains and others showing declines. Exploratory analyses revealed that improvements in behavior and social skills were greater (nonsignificantly) among children with improvements in QOL. Children with improved QOL were also younger and had a lower initial symptom burden. This study suggests that early intervention programs that provide social skills and behavioral management strategies may improve QOL in children with ASD. The study also highlights the need to develop and study novel, qualitative measures of QOL in this population.

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