1. Bertoncelli CM, Altamura P, Vieira ER, Bertoncelli D, Solla F. {{Using Artificial Intelligence to Identify Factors Associated with Autism Spectrum Disorder in Adolescents with Cerebral Palsy}}. {Neuropediatrics}. 2019.
Autism spectrum disorder (ASD) is common in adolescents with cerebral palsy (CP) and there is a lack of studies applying artificial intelligence to investigate this field and this population in particular. The aim of this study is to develop and test a predictive learning model to identify factors associated with ASD in adolescents with CP. This was a multicenter controlled cohort study of 102 adolescents with CP (61 males, 41 females; mean age +/- SD [standard deviation] = 16.6 +/- 1.2 years; range: 12-18 years). Data on etiology, diagnosis, spasticity, epilepsy, clinical history, communication abilities, behaviors, intellectual disability, motor skills, and eating and drinking abilities were collected between 2005 and 2015. Statistical analysis included Fisher’s exact test and multiple logistic regressions to identify factors associated with ASD. A predictive learning model was implemented to identify factors associated with ASD. The guidelines of the « transparent reporting of a multivariable prediction model for individual prognosis or diagnosis » (TRIPOD) statement were followed. Type of spasticity (hemiplegia > diplegia > tri/quadriplegia; OR [odds ratio] = 1.76, SE [standard error] = 0.2785, p = 0.04), communication disorders (OR = 7.442, SE = 0.59, p < 0.001), intellectual disability (OR = 2.27, SE = 0.43, p = 0.05), feeding abilities (OR = 0.35, SE = 0.35, p = 0.002), and motor function (OR = 0.59, SE = 0.22, p = 0.01) were significantly associated with ASD. The best average prediction model score for accuracy, specificity, and sensitivity was 75%. Motor skills, feeding abilities, type of spasticity, intellectual disability, and communication disorders were associated with ASD. The prediction model was able to adequately identify adolescents at risk of ASD. Lien vers le texte intégral (Open Access ou abonnement)
2. Bradshaw J, Klin A, Evans L, Klaiman C, Saulnier C, McCracken C. {{Development of attention from birth to 5 months in infants at risk for autism spectrum disorder}}. {Development and psychopathology}. 2019: 1-11.
Social-communication skills emerge within the context of rich social interactions, facilitated by an infant’s capacity to attend to people and objects in the environment. Disruption in this early neurobehavioral process may decrease the frequency and quality of social interactions and learning opportunities, potentially leading to downstream deleterious effects on social development. This study examined early attention in infant siblings of children with autism spectrum disorder (ASD) who are at risk for social and communication delays. Visual and auditory attention was mapped from age 1 week to 5 months in infants at familial risk for ASD (high risk; N = 41) and low-risk typically developing infants (low risk; N = 39). At 12 months, a subset of participants (N = 40) was administered assessments of social communication and nonverbal cognitive skills. Results revealed that high-risk infants performed lower on attention tasks at 2 and 3 months of age compared to low-risk infants. A significant association between overall attention at 3 months and developmental outcome at 12 months was observed for both groups. These results provide evidence for early vulnerabilities in visual attention for infants at risk for ASD during a period of important neurodevelopmental transition (between 2 and 3 months) when attention has significant implications for social communication and cognitive development.
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3. Canfield MA, Langlois PH, Rutenberg GW, Mandell DJ, Hua F, Reilly B, Ruktanonchai DJ, Jackson JF, Hunt P, Freedenberg D, Lee R, Villanacci JF. {{The association between newborn screening analytes and childhood autism in a Texas Medicaid population, 2010-2012}}. {Am J Med Genet B Neuropsychiatr Genet}. 2019.
Autism (or autism spectrum disorder [ASD]) is an often disabling childhood neurologic condition of mostly unknown cause. It is commonly diagnosed at 3 or 4 years of age. We explored whether there was an association of any analytes measured by newborn screening tests with a later diagnosis of ASD. A database was compiled of 3-5 year-old patients with any ASD diagnosis in the Texas Medicaid system in 2010-2012. Two controls (without any ASD diagnosis) were matched to each case by infant sex and birth year/month. All study subjects were linked to their 2007-2009 birth and newborn screening laboratory records, including values for 36 analytes or analyte ratios. We examined the association of analytes/ratios with a later diagnosis of ASD. Among 3,258 cases and 6,838 controls, seven analytes (e.g., 17-hydroxyprogesterone, acylcarnitines) were associated with a later ASD diagnosis. In this exploratory study, an ASD diagnosis was associated with 7 of 36 newborn screening analytes/ratios. These findings should be replicated in other population-based datasets.
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4. Cheak-Zamora NC, Teti M, Maurer-Batjer A, O’Connor KV, Randolph JK. {{Sexual and Relationship Interest, Knowledge, and Experiences Among Adolescents and Young Adults with Autism Spectrum Disorder}}. {Archives of sexual behavior}. 2019.
Little research exists to describe sexual and romantic relationships among adolescents and young adults with autism spectrum disorder (ASD) from their perspectives. Sexuality and intimacy are developmentally important and influence health and quality of life for all adolescents and young adults, including those with ASD. This study explored and compared the sex and relationship experiences of 27 adolescents and young adults with ASD (males = 20). Adolescents and young adults participated in semi-structured interviews to explore this topic. Using theme analysis, we uncovered four thematic categories: (1) interest in relationships, (2) ideal partners, (3) realities of adolescent and young adult relationships, and (4) advice about sex and relationships. Although many adolescents and young adults expressed wanting a relationship, few reported having partners. Among those that did, their actual relationships rarely met ideals. Most adolescents and young adults talked with parents and friends but not healthcare providers about sex and relationships. All adolescents and young adults described the need for additional education. Adolescents and young adults express the need for education that covers basic safety and sexual health topics as well as social/relationship skills building and courtship modeling. These findings can inform the design of tailored sexual health intervention. Future research should examine specific issues related to sexuality from the adolescents’ and young adults’ perspectives.
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5. Crawford H, Karakatsani E, Singla G, Oliver C. {{The Persistence of Self-injurious and Aggressive Behavior in Males with Fragile X Syndrome Over 8 Years: A Longitudinal Study of Prevalence and Predictive Risk Markers}}. {J Autism Dev Disord}. 2019.
Self-injurious and aggressive behaviors are common in fragile X syndrome (FXS). However, little is known about the persistence of these behaviors and associated risk markers. We established the prevalence and persistence of self-injurious and aggressive behaviors over eight years in males with FXS, and associations with risk markers. Results showed 77% and 69% persistence rates for self-injurious and aggressive behavior, respectively. Baseline levels of repetitive behavior predicted persistent self-injurious behavior. Chronological age, impulsivity and overactivity were associated with persistent aggressive behavior but only impulsivity predicted persistence. This is the first study to document the persistence of self-injurious and aggressive behavior in FXS over the medium to long term and to identify behavioral risk markers that might facilitate targeted early intervention.
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6. Guimaraes-Souza EM, Joselevitch C, Britto LRG, Chiavegatto S. {{Retinal alterations in a pre-clinical model of an autism spectrum disorder}}. {Mol Autism}. 2019; 10: 19.
Background: Autism spectrum disorders (ASD) affect around 1.5% of people worldwide. Symptoms start around age 2, when children fail to maintain eye contact and to develop speech and other forms of communication. Disturbances in glutamatergic and GABAergic signaling that lead to synaptic changes and alter the balance between excitation and inhibition in the developing brain are consistently found in ASD. One of the hallmarks of these disorders is hypersensitivity to sensory stimuli; however, little is known about its underlying causes. Since the retina is the part of the CNS that converts light into a neuronal signal, we set out to study how it is affected in adolescent mice prenatally exposed to valproic acid (VPA), a useful tool to study ASD endophenotypes. Methods: Pregnant female mice received VPA (600 mg/kg, ip) or saline at gestational day 11. Their male adolescent pups (P29-35) were behaviorally tested for anxiety and social interaction. Proteins known to be related with ASD were quantified and visualized in their retinas by immunoassays, and retinal function was assessed by full-field scotopic electroretinograms (ERGs). Results: Early adolescent mice prenatally exposed to VPA displayed impaired social interest and increased anxiety-like behaviors consistent with an ASD phenotype. The expression of GABA, GAD, synapsin-1, and FMRP proteins were reduced in their retinas, while mGluR5 was increased. The a-wave amplitudes of VPA-exposed were smaller than those of CTR animals, whereas the b-wave and oscillatory potentials were normal. Conclusions: This study establishes that adolescent male mice of the VPA-induced ASD model have alterations in retinal function and protein expression compatible with those found in several brain areas of other autism models. These results support the view that synaptic disturbances with excitatory/inhibitory imbalance early in life are associated with ASD and point to the retina as a window to understand their subjacent mechanisms.
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7. Gurney ME, Nugent RA, Mo X, Sindac JA, Hagen TJ, Fox D, 3rd, O’Donnell JM, Zhang C, Xu Y, Zhang HT, Groppi VE, Bailie M, White RE, Romero DL, Vellekoop AS, Walker JR, Surman MD, Zhu L, Campbell RF. {{Design and Synthesis of Selective Phosphodiesterase 4D (PDE4D) Allosteric Inhibitors for the Treatment of Fragile X Syndrome and Other Brain Disorders}}. {J Med Chem}. 2019.
Novel pyridine- and pyrimidine-based allosteric inhibitors are reported that achieve PDE4D subtype selectivity through recognition of a single amino acid difference on a key regulatory domain, known as UCR2, that opens and closes over the catalytic site for cAMP hydrolysis. The design and optimization of lead compounds was based on iterative analysis of X-ray crystal structures combined with metabolite identification. Selectivity for the activated, dimeric form of PDE4D provided potent memory enhancing effects in a mouse model of novel object recognition with improved tolerability and reduced vascular toxicity over earlier PDE4 inhibitors that lack subtype selectivity. The lead compound, 28 (BPN14770), has entered midstage, human phase 2 clinical trials for the treatment of Fragile X Syndrome.
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8. Hollins S, Lodge KM, Lomax P. {{The case for removing intellectual disability and autism from the Mental Health Act}}. {The British journal of psychiatry : the journal of mental science}. 2019: 1-3.
SummaryIntellectual disability (also known as learning disability in UK health services) and autism are distinct from the serious mental illnesses for which the Mental Health Act is designed to be used. Their inclusion in the definition of mental disorder is discriminatory, resulting in unjust deprivations of liberty. Intellectual disability and autism should be excluded from the Mental Health Act.Declaration of interestNone.
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9. Lake EMR, Finn ES, Noble SM, Vanderwal T, Shen X, Rosenberg MD, Spann MN, Chun MM, Scheinost D, Constable RT. {{The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder}}. {Biol Psychiatry}. 2019.
BACKGROUND: Autism spectrum disorder and attention-deficit/hyperactivity disorder (ADHD) are associated with complex changes as revealed by functional magnetic resonance imaging. To date, neuroimaging-based models are not able to characterize individuals with sufficient sensitivity and specificity. Further, although evidence shows that ADHD traits occur in individuals with autism spectrum disorder, and autism spectrum disorder traits in individuals with ADHD, the neurofunctional basis of the overlap is undefined. METHODS: Using individuals from the Autism Brain Imaging Data Exchange and ADHD-200, we apply a data-driven, subject-level approach, connectome-based predictive modeling, to resting-state functional magnetic resonance imaging data to identify brain-behavior associations that are predictive of symptom severity. We examine cross-diagnostic commonalities and differences. RESULTS: Using leave-one-subject-out and split-half analyses, we define networks that predict Social Responsiveness Scale, Autism Diagnostic Observation Schedule, and ADHD Rating Scale scores and confirm that these networks generalize to novel subjects. Networks share minimal overlap of edges (<2%) but some common regions of high hubness (Brodmann areas 10, 11, and 21, cerebellum, and thalamus). Further, predicted Social Responsiveness Scale scores for individuals with ADHD are linked to ADHD symptoms, supporting the hypothesis that brain organization relevant to autism spectrum disorder severity shares a component associated with attention in ADHD. Predictive connections and high-hubness regions are found within a wide range of brain areas and across conventional networks. CONCLUSIONS: An individual's functional connectivity profile contains information that supports dimensional, nonbinary classification in autism spectrum disorder and ADHD. Furthermore, we can determine disorder-specific and shared neurofunctional pathology using our method. Lien vers le texte intégral (Open Access ou abonnement)
10. Lindahl J, Stollon N, Wu K, Liang A, Changolkar S, Steinway C, Trachtenberg S, Coccia A, Devaney M, Jan S. {{Domains of planning for future long-term care of adults with intellectual and developmental disabilities: Parent and sibling perspectives}}. {J Appl Res Intellect Disabil}. 2019.
BACKGROUND: Research shows that adults with intellectual and developmental disabilities (IDD) increasingly outlive caregivers, who often struggle to plan for the future and have little support and knowledge surrounding long-term care planning. METHODS: The study team conducted interviews with parents and siblings of adults with IDD and performed qualitative coding using a modified grounded theory to explore domains of future planning and identify barriers and facilitators. RESULTS: Themes from the interviews revealed seven major domains of future planning that should be considered by caregivers of adults with IDD. These domains are housing, legal planning, identification of primary caregiver(s), financial planning, day-to-day care, medical management and transportation. Approaches to planning within each domain varied greatly. CONCLUSIONS: The study team dentified the domain of « identification of primary caregiver(s) » as potentially the most important step for caregivers when planning for the future, but also observed that the domains identified are significantly interrelated and should be considered together.
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11. Mehra C, Absoud M. {{Commentary on… the overlapping and distinct resting functional connectivity between autism spectrum disorder and attention-deficit hyperactivity disorder}}. {The British journal of psychiatry : the journal of mental science}. 2019: 1-2.
SummaryAltered neural connectivity in neurodevelopmental disorders is likely subtle, meaning that neuroimaging literature studying development has produced heterogeneous findings. A recent study, published in this issue, illustrates the translational potential of functional connectivity magnetic resonance imaging findings as a biomarker for attention-deficit hyperactivity disorder and autism spectrum disorder. Importantly, it highlights the overlap between disorders, emphasising the need for transdiagnostic and dimensional approaches in neurodevelopment.Declaration of interestNone.
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12. Port RG, Dipiero MA, Ku M, Liu S, Blaskey L, Kuschner ES, Edgar JC, Roberts TPL, Berman JI. {{Children with Autism Spectrum Disorder Demonstrate Regionally Specific Altered Resting-State Phase-Amplitude Coupling}}. {Brain Connect}. 2019.
Studies suggest that individuals with autism spectrum disorder (ASD) exhibit altered electrophysiological alpha to gamma phase-amplitude coupling (PAC). Preliminary reports with small samples report conflicting findings regarding the directionality of the alpha to gamma PAC alterations in ASD. The present study examined resting-state activity throughout the brain in a relatively large sample of 119 children with ASD and 47 typically developing children. Children with ASD demonstrated regionally specific abnormalities in alpha to low-gamma PAC, with increased alpha to low-gamma PAC for a central midline source and decreased PAC at lateral sources. Group differences in local gamma-band power did not account for the regional group differences in alpha to low-gamma PAC. Moreover, local alpha power did not significantly modulate alpha to low-gamma PAC estimates. Finally, PAC estimates were correlated with Social Responsiveness Scale (SRS) indicating clinical relevance of the PAC metric. In conclusion, alpha to low-gamma PAC alterations in ASD demonstrate a heterogeneous spatial profile consistent with previous studies and were related to symptom severity.
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13. Roncati AL, Souza AC, Paradigma N, Miguel CF. {{Exposure to a specific prompt topography predicts its relative efficiency when teaching intraverbal behavior to children with autism spectrum disorder}}. {Journal of applied behavior analysis}. 2019.
Comparisons of the relative efficiency of different prompt topographies (visual or auditory), when teaching intraverbal behavior to children with disabilities, have yielded idiosyncratic results. Recent research has shown that previous exposure to a specific prompt type may affect its efficiency when teaching intraverbal behavior to preschool children. The current study was an attempt to replicate these results with 3 children diagnosed with autism spectrum disorder. For all participants, increased exposure to one prompt topography was sufficient to make it relatively more efficient as measured by number of trials to criterion. These results suggest that previous history with a prompt type may predict its efficiency.
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14. Siracusano M, Riccioni A, Baratta A, Baldi M, Curatolo P, Mazzone L. {{Autistic symptoms in Greig cephalopolysyndactyly syndrome: a family case report}}. {Journal of medical case reports}. 2019; 13(1): 100.
BACKGROUND: Greig cephalopolysyndactyly syndrome is a rare multiple congenital anomaly syndrome characterized by the triad of polysyndactyly (preaxial or mixed preaxial and postaxial), macrocephaly, and ocular hypertelorism. Little is known about the neuropsychological phenotype and the developmental features of this syndrome. CASE PRESENTATION: We describe the clinical features of a 7-year-old Italian white boy affected by Greig cephalopolysyndactyly syndrome in comorbidity with autism spectrum disorder and the case of his 45-year-old white father, carrying the same point deletion (c.3677del) in the GLI3 gene and showing subclinical autistic symptoms. We performed a neuropsychiatric assessment of cognitive, adaptive, socio-communicative, and behavioral skills of the child. Concurrently, the father underwent his first psychiatric evaluation of cognitive skills and autistic symptoms. CONCLUSIONS: We report the first clinical description of an association between autistic symptoms and Greig cephalopolysyndactyly syndrome in two members of the same family with the same genetic point deletion. Further research is required in order to draw an accurate conclusion regarding the association between Greig cephalopolysyndactyly syndrome and autism.
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15. Tariq Q, Fleming SL, Schwartz JN, Dunlap K, Corbin C, Washington P, Kalantarian H, Khan NZ, Darmstadt GL, Wall DP. {{Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study}}. {Journal of medical Internet research}. 2019; 21(4): e13822.
BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. In our previous work, we demonstrated the efficacy of machine learning classifiers to accelerate the process by collecting home videos of US-based children, identifying a reduced subset of behavioral features that are scored by untrained raters using a machine learning classifier to determine children’s « risk scores » for autism. We achieved an accuracy of 92% (95% CI 88%-97%) on US videos using a classifier built on five features. OBJECTIVE: Using videos of Bangladeshi children collected from Dhaka Shishu Children’s Hospital, we aim to scale our pipeline to another culture and other developmental delays, including speech and language conditions. METHODS: Although our previously published and validated pipeline and set of classifiers perform reasonably well on Bangladeshi videos (75% accuracy, 95% CI 71%-78%), this work improves on that accuracy through the development and application of a powerful new technique for adaptive aggregation of crowdsourced labels. We enhance both the utility and performance of our model by building two classification layers: The first layer distinguishes between typical and atypical behavior, and the second layer distinguishes between ASD and non-ASD. In each of the layers, we use a unique rater weighting scheme to aggregate classification scores from different raters based on their expertise. We also determine Shapley values for the most important features in the classifier to understand how the classifiers’ process aligns with clinical intuition. RESULTS: Using these techniques, we achieved an accuracy (area under the curve [AUC]) of 76% (SD 3%) and sensitivity of 76% (SD 4%) for identifying atypical children from among developmentally delayed children, and an accuracy (AUC) of 85% (SD 5%) and sensitivity of 76% (SD 6%) for identifying children with ASD from those predicted to have other developmental delays. CONCLUSIONS: These results show promise for using a mobile video-based and machine learning-directed approach for early and remote detection of autism in Bangladeshi children. This strategy could provide important resources for developmental health in developing countries with few clinical resources for diagnosis, helping children get access to care at an early age. Future research aimed at extending the application of this approach to identify a range of other conditions and determine the population-level burden of developmental disabilities and impairments will be of high value.
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16. Tiede G, Walton KM. {{Meta-analysis of naturalistic developmental behavioral interventions for young children with autism spectrum disorder}}. {Autism}. 2019: 1362361319836371.
Naturalistic developmental behavioral intervention is an emerging class of interventions for young children with autism spectrum disorder. The present article is a meta-analysis of outcomes of group-design studies ( n = 27) testing interventions using naturalistic developmental behavioral intervention strategies. Small, significant positive effects of naturalistic developmental behavioral intervention were found for expressive language ( g = 0.32), reduction in symptoms of autism spectrum disorder ( g = -0.38), and play skills ( g = 0.23). Larger effects were found for social engagement ( g = 0.65) and overall cognitive development ( g = 0.48). A marginal effect was found for joint attention ( g = 0.14) and receptive language ( g = 0.28). For joint attention, improvement was moderated by hours of professional involvement. Evidence of publication and reporting bias was present for language outcomes. This meta-analysis grows the evidence base for naturalistic developmental behavioral interventions, particularly in the key areas of social engagement and cognition.
