1. Bal VH, Katz T, Bishop SL, Krasileva K. {{Understanding definitions of minimally verbal across instruments: evidence for subgroups within minimally verbal children and adolescents with autism spectrum disorder}}. {J Child Psychol Psychiatry};2016 (Jul 30)
BACKGROUND: Minimally verbal (MV) children with autism spectrum disorder (ASD) are often assumed to be profoundly cognitively impaired and excluded from analyses due to challenges completing standardized testing protocols. A literature aimed at increasing understanding of this subgroup is emerging; however, the many methods used to define MV status make it difficult to compare studies. Understanding how different instruments and definitions used to identify MV children affect sample composition is critical to advance research on this understudied clinical population. METHOD: The MV status of 1,470 school-aged children was defined using five instruments commonly used in ASD research. MV sample composition was compared across instruments. Analyses examined the proportion of overlap across MV subgroups and the extent to which child characteristics varied across MV subgroups defined using different definitions or combinations of measures. RESULTS: A total of 257 children were classified as MV on at least one instrument. Proportion of overlap between definitions ranged from 3% to 100%. The stringency of definition (i.e. few-to-no vs. some words) was associated with differences in cognitive and adaptive functioning; more stringent definitions yielded greater consistency of MV status across instruments. Cognitive abilities ranged from profoundly impaired to average intelligence; 16% had NVIQ >/= 70. Approximately half exhibited verbal skills commensurate with nonverbal cognitive ability, whereas half had verbal abilities significantly lower than their estimated NVIQ. CONCLUSIONS: Future studies of MV children must carefully consider the methods used to identify their sample, acknowledging that definitions including children with ‘some words’ may yield larger samples with a wider range of language and cognitive abilities. Broadly defined MV samples may be particularly important to delineate factors interfering with language development in the subgroup of children whose expressive impairments are considerably below their estimated nonverbal cognitive abilities.
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2. Frampton SE, Wymer SC, Hansen B, Shillingsburg MA. {{The use of matrix training to promote generative language with children with autism}}. {J Appl Behav Anal};2016 (Jul 29)
Matrix training consists of planning instruction by arranging components of desired skills across 2 axes. After training with diagonal targets that each combine 2 unique skill components, responses to nondiagonal targets, consisting of novel combinations of the components, may emerge. A multiple-probe design across participants was used to evaluate matrix training with known nouns (e.g., cat) and verbs (e.g., jumping) with 5 children with autism spectrum disorders (ASD). Following baseline of Matrix 1 and a generalization matrix, diagonal targets within Matrix 1 were trained as noun-verb combinations (e.g., cat jumping). Posttests showed recombinative generalization within Matrix 1 and the generalization matrix for 4 participants. For 1 participant, diagonal training across multiple matrices was provided until correct responding was observed in the generalization matrix. Results support the use of matrix training to promote untrained responses for learners with ASD and offer a systematic way to evaluate the extent of generalization within and across matrices.
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3. Green D, Chandler S, Charman T, Simonoff E, Baird G. {{Brief Report: DSM-5 Sensory Behaviours in Children With and Without an Autism Spectrum Disorder}}. {J Autism Dev Disord};2016 (Jul 30)
Atypical responses to sensory stimuli are a new criterion in DSM-5 for the diagnosis of an autism spectrum disorder (ASD) but are also reported in other developmental disorders. Using the Short Sensory profile (SSP) and Autism Diagnostic Interview-Revised we compared atypical sensory behaviour (hyper- or hypo-reactivity to sensory input or unusual sensory interests) in children aged 10-14 years with (N = 116) or without an ASD but with special educational needs (SEN; N = 72). Atypical sensory behaviour was reported in 92 % of ASD and 67 % of SEN children. Greater sensory dysfunction was associated with increased autism severity (specifically restricted and repetitive behaviours) and behaviour problems (specifically emotional subscore) on teacher and parent Strengths and Difficulties Questionnaires but not with IQ.
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4. Kovarski K, Thillay A, Houy-Durand E, Roux S, Bidet-Caulet A, Bonnet-Brilhault F, Batty M. {{Brief Report: Early VEPs to Pattern-Reversal in Adolescents and Adults with Autism}}. {J Autism Dev Disord};2016 (Jul 30)
Autism spectrum disorder (ASD) is characterized by atypical visual perception both in the social and nonsocial domain. In order to measure a reliable visual response, visual evoked potentials were recorded during a passive pattern-reversal stimulation in adolescents and adults with and without ASD. While the present results show the same age-related changes in both autistic and non-autistic groups, they reveal a smaller P100 amplitude in the ASD group compared to controls. These results confirm that early visual responses are affected in ASD even with a simple, non social and passive stimulation and suggest that they should be considered in order to better understand higher-level processes.
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5. Lingren T, Chen P, Bochenek J, Doshi-Velez F, Manning-Courtney P, Bickel J, Wildenger Welchons L, Reinhold J, Bing N, Ni Y, Barbaresi W, Mentch F, Basford M, Denny J, Vazquez L, Perry C, Namjou B, Qiu H, Connolly J, Abrams D, Holm IA, Cobb BA, Lingren N, Solti I, Hakonarson H, Kohane IS, Harley J, Savova G. {{Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder}}. {PLoS One};2016;11(7):e0159621.
OBJECTIVE: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD. METHODS: We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children’s Hospital (BCH) (N = 150) and Cincinnati Children’s Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups. RESULTS: The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children’s Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters. CONCLUSIONS: In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD.
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6. Pan PY, Yeh CB. {{The comorbidity of disruptive mood dysregulation disorder in autism spectrum disorder}}. {Psychiatry Res};2016 (Jul 30);241:108-109.
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7. Strati F, Cavalieri D, Albanese D, De Felice C, Donati C, Hayek J, Jousson O, Leoncini S, Pindo M, Renzi D, Rizzetto L, Stefanini I, Calabro A, De Filippo C. {{Altered gut microbiota in Rett syndrome}}. {Microbiome};2016;4(1):41.
BACKGROUND: The human gut microbiota directly affects human health, and its alteration can lead to gastrointestinal abnormalities and inflammation. Rett syndrome (RTT), a progressive neurological disorder mainly caused by mutations in MeCP2 gene, is commonly associated with gastrointestinal dysfunctions and constipation, suggesting a link between RTT’s gastrointestinal abnormalities and the gut microbiota. The aim of this study was to evaluate the bacterial and fungal gut microbiota in a cohort of RTT subjects integrating clinical, metabolomics and metagenomics data to understand if changes in the gut microbiota of RTT subjects could be associated with gastrointestinal abnormalities and inflammatory status. RESULTS: Our findings revealed the occurrence of an intestinal sub-inflammatory status in RTT subjects as measured by the elevated values of faecal calprotectin and erythrocyte sedimentation rate. We showed that, overall, RTT subjects harbour bacterial and fungal microbiota altered in terms of relative abundances from those of healthy controls, with a reduced microbial richness and dominated by microbial taxa belonging to Bifidobacterium, several Clostridia (among which Anaerostipes, Clostridium XIVa, Clostridium XIVb) as well as Erysipelotrichaceae, Actinomyces, Lactobacillus, Enterococcus, Eggerthella, Escherichia/Shigella and the fungal genus Candida. We further observed that alterations of the gut microbiota do not depend on the constipation status of RTT subjects and that this dysbiotic microbiota produced altered short chain fatty acids profiles. CONCLUSIONS: We demonstrated for the first time that RTT is associated with a dysbiosis of both the bacterial and fungal component of the gut microbiota, suggesting that impairments of MeCP2 functioning favour the establishment of a microbial community adapted to the costive gastrointestinal niche of RTT subjects. The altered production of short chain fatty acids associated with this microbiota might reinforce the constipation status of RTT subjects and contribute to RTT gastrointestinal physiopathology.
