1. {{Wong et al. Role of p53, Mitochondrial DNA Deletions, and Paternal Age in Autism: A Case-Control Study. Pediatrics. 2016:137(4):e20151888}}. {Pediatrics};2016 (Jul 29)
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2. Asher A. {{Book Review: Visual supports for people with autism: A guide for parents and professionals}}. {Can J Occup Ther};2016 (Jul 27)
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3. Berger NI, Manston L, Ingersoll B. {{Establishing a Scale for Assessing the Social Validity of Skill Building Interventions for Young Children with Autism Spectrum Disorder}}. {J Autism Dev Disord};2016 (Jul 27)
This study evaluated the psychometric properties of the Scale of Treatment Perceptions (STP), a measure of treatment acceptability targeting skill-building interventions for Autism Spectrum Disorder (ASD). This scale utilizes a strength-based approach to intervention assessment, and was established by modifying the Behavior Intervention Rating Scale (Elliott and Von Brock Treuting in J School Psychol 29(1):43-51, 1991. doi: 10.1016/0022-4405(91)90014-I ) and the Treatment Evaluation Inventory (Kazdin in J Appl Behav Anal 13(2):259-273, 1980. doi: 10.1901/jaba.1980.13-259 ) to be appropriate for assessing multiple dimensions of acceptability across skill-building ASD treatments. Overall, the STP demonstrated good psychometric properties: the scale had appropriate internal consistency, demonstrated a stable three-factor structure that was invariant across samples, and discriminated among different skill-building treatments for ASD. This has important implications for dissemination, as perceived acceptability of a treatment relates to treatment utilization and adherence.
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4. Bertorelli TE. {{Hope and doubt in the promise of neuroimaging: The case of autism spectrum disorder}}. {Health (London)};2016 (Jul 29)
Although neuroimaging is currently not a component of the diagnostic process for autism spectrum disorders, some scientists hail these technologies for their promise to one day replace behaviorally based psychiatric diagnostic techniques. This article examines how psychiatrists understand the potential use of neuroimaging technologies within the context of clinical practice. Drawing on 10 semi-structured interviews with child and adolescent psychiatrists, I describe the hope and doubt that comprise their discourse of ambivalence. This analysis demonstrates that the uses and meanings of neuroimaging technologies are rearticulated in ongoing debates in the field of psychiatry regarding the role of the biopsychiatric model in the diagnosis and treatment of mental illness. This study highlights issues surrounding the perceived biopsychiatric focus of neuroimaging technologies within clinical practice, concerns regarding misdirected research attention, and the ways in which understandings of future utility mediate perceptions of technological utility.
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5. Berzhanskaya J, Phillips MA, Shen J, Colonnese MT. {{Sensory hypo-excitability in a rat model of fetal development in Fragile X Syndrome}}. {Sci Rep};2016;6:30769.
Fragile X syndrome (FXS) is characterized by sensory hyper-sensitivity, and animal models suggest that neuronal hyper-excitability contributes to this phenotype. To understand how sensory dysfunction develops in FXS, we used the rat model (FMR-KO) to quantify the maturation of cortical visual responses from the onset of responsiveness prior to eye-opening, through age equivalents of human juveniles. Rather than hyper-excitability, visual responses before eye-opening had reduced spike rates and an absence of early gamma oscillations, a marker for normal thalamic function at this age. Despite early hypo-excitability, the developmental trajectory of visual responses in FMR-KO rats was normal, and showed the expected loss of visually evoked bursting at the same age as wild-type, two days before eye-opening. At later ages, during the third and fourth post-natal weeks, signs of mild hyper-excitability emerged. These included an increase in the visually-evoked firing of regular spiking, presumptive excitatory, neurons, and a reduced firing of fast-spiking, presumptive inhibitory, neurons. Our results show that early network changes in the FMR-KO rat arise at ages equivalent to fetal humans and have consequences for excitability that are opposite those found in adults. This suggests identification and treatment should begin early, and be tailored in an age-appropriate manner.
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6. Bilder DA, Bakian AV, Stevenson DA, Carbone PS, Cunniff C, Goodman AB, McMahon WM, Fisher NP, Viskochil D. {{Brief Report: The Prevalence of Neurofibromatosis Type 1 among Children with Autism Spectrum Disorder Identified by the Autism and Developmental Disabilities Monitoring Network}}. {J Autism Dev Disord};2016 (Jul 27)
Neurofibromatosis type 1 (NF1) is an inherited neurocutaneous disorder associated with neurodevelopmental disorders including autism spectrum disorder (ASD). The frequency of ASD/NF1 co-occurrence has been subject to debate since the 1980s. This relationship was investigated in a large population-based sample of 8-year-old children identified with ASD (N = 12,271) by the Centers for Disease Control and Prevention’s Autism and Developmental Disabilities Monitoring (ADDM) Network. Twenty-two (1-in-558) children with ASD had diagnosed NF1, exceeding NF1 general population estimates by four to five fold. Children with ASD/NF1 versus ASD without NF1 were significantly less likely to receive a community-based ASD diagnosis (p = 0.04) and understand non-verbal communication (p = 0.001). These findings underscore the importance of including social-communication ability among relevant developmental concerns in children with NF1.
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7. Brennan JR, Wagley N, Kovelman I, Bowyer SM, Richard AE, Lajiness-O’Neill R. {{Magnetoencephalography shows atypical sensitivity to linguistic sound sequences in autism spectrum disorder}}. {Neuroreport};2016 (Jul 27)
Neuroscientific evidence points toward atypical auditory processing in individuals with autism spectrum disorders (ASD), and yet, the consequences of this for receptive language remain unclear. Using magnetoencephalography and a passive listening task, we test for cascading effects on speech sound processing. Children with ASD and age-matched control participants (8-12 years old) listened to nonce linguistic stimuli that either did or did not conform to the phonological rules that govern consonant sequences in English (e.g. legal ‘vimp’ vs. illegal ‘vimk’). Beamformer source analysis was used to isolate evoked responses (0.1-30 Hz) to these stimuli in the left and the right auditory cortex. Right auditory responses from participants with ASD, but not control participants, showed an attenuated response to illegal sequences relative to legal sequences that emerged around 330 ms after the onset of the critical phoneme. These results suggest that phonological processing is impacted in ASD, perhaps because of cascading effects from disrupted initial acoustic processing.
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8. 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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9. Garcia-Villamisar D, Dattilo J, Muela C. {{Effects of therapeutic recreation on adults with ASD and ID: a preliminary randomized control trial}}. {J Intellect Disabil Res};2016 (Jul 28)
BACKGROUND: The purpose of this research was to examine effects of a therapeutic recreation (TR) program designed to increase executive function (EF), social skills, adaptive behaviours and well-being of adults with autism spectrum disorder (ASD) and intellectual disability (ID). METHOD: A preliminary pre-test, post-test randomized control group experimental design was used to measure effects of a 40-week TR program designed to increase EF (TR-EF). The TR-EF used instructional electronically based games delivered during 200 1-h sessions (5/week). RESULTS: Participants (experimental group, n = 19; wait-list group, n = 18) were evaluated at baseline and 10 months later. There was a positive and direct impact of the program on several EF and indirect effect on social skills, adaptive behaviour and personal well-being. CONCLUSIONS: Findings provide support for inclusion of EF enrichment as a way to enhance effects of TR interventions for adults with ASD and ID. Preliminary results of this study can be considered in planning TR services in the future. In addition to TR-EF program primary effects on EF, there were indirect benefits on adaptive behaviours, personal well-being and social skills.
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10. Gonzalez-Gadea ML, Sigman M, Rattazzi A, Lavin C, Rivera-Rei A, Marino J, Manes F, Ibanez A. {{Neural markers of social and monetary rewards in children with Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder}}. {Sci Rep};2016;6:30588.
Recent theories of decision making propose a shared value-related brain mechanism for encoding monetary and social rewards. We tested this model in children with Attention-Deficit/Hyperactivity Disorder (ADHD), children with Autism Spectrum Disorder (ASD) and control children. We monitored participants’ brain dynamics using high density-electroencephalography while they played a monetary and social reward tasks. Control children exhibited a feedback Error-Related Negativity (fERN) modulation and Anterior Cingulate Cortex (ACC) source activation during both tasks. Remarkably, although cooperation resulted in greater losses for the participants, the betrayal options generated greater fERN responses. ADHD subjects exhibited an absence of fERN modulation and reduced ACC activation during both tasks. ASD subjects exhibited normal fERN modulation during monetary choices and inverted fERN/ACC responses in social options than did controls. These results suggest that in neurotypicals, monetary losses and observed disloyal social decisions induced similar activity in the brain value system. In ADHD children, difficulties in reward processing affected early brain signatures of monetary and social decisions. Conversely, ASD children showed intact neural markers of value-related monetary mechanisms, but no brain modulation by prosociality in the social task. These results offer insight into the typical and atypical developments of neural correlates of monetary and social reward processing.
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11. Hollocks MJ, Pickles A, Howlin P, Simonoff E. {{Dual Cognitive and Biological Correlates of Anxiety in Autism Spectrum Disorders}}. {J Autism Dev Disord};2016 (Jul 27)
Young people with autism spectrum disorder (ASD) have a high prevalence (~40 %) of anxiety disorders compared to their non-ASD peers. It is unclear whether cognitive and biological processes associated with anxiety in ASD are analogous to anxiety in typically developing (TD) populations. In this study 55 boys with ASD (34 with a co-occurring anxiety disorder, 21 without) and 28 male controls, aged 10-16 years and with a full-scale IQ >/= 70, completed a series of clinical, cognitive (attention bias/interpretation bias) and biological measures (salivary cortisol/HR response to social stress) associated with anxiety in TD populations. Structural equation modelling was used to reveal that that both attentional biases and physiological responsiveness were significant, but unrelated, predictors of anxiety in ASD.
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12. Kiely B, Vettam S, Adesman A. {{Utilization of genetic testing among children with developmental disabilities in the United States}}. {Appl Clin Genet};2016;9:93-100.
PURPOSE: Several professional societies recommend that genetic testing be routinely included in the etiologic workup of children with developmental disabilities. The aim of this study was to determine the rate at which genetic testing is performed in this population, based on data from a nationally representative survey. METHODS: Data were analyzed from the Survey of Pathways to Diagnosis and Services, a telephone-based survey of parents and guardians of US school-age children with current or past developmental conditions. This study included 3,371 respondents who indicated that their child had an autism spectrum disorder (ASD), intellectual disability (ID), and/or developmental delay (DD) at the time of survey administration. History of genetic testing was assessed based on report by the parent/s. Children were divided into the following five mutually exclusive condition groups: ASD with ID; ASD with DD, without ID; ASD only, without ID or DD; ID without ASD; and DD only, without ID or ASD. Logistic regression was used to assess the demographic correlates of genetic testing, to compare the rates of genetic testing across groups, and to examine associations between genetic testing and use of other health-care services. RESULTS: Overall, 32% of this sample had a history of genetic testing, including 34% of all children with ASD and 43% of those with ID. After adjusting for demographics, children with ASD + ID were more than seven times as likely as those with ASD only, and more than twice as likely as those who had ID without ASD, to have undergone genetic testing. Prior specialist care (developmental pediatrician or neurologist) and access to all needed providers within the previous year were associated with higher odds of genetic testing. CONCLUSION: The majority of children in this nationally representative sample did not undergo recommended genetic testing. Research is needed to identify barriers to the use of genetic testing in this population.
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13. 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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14. Malaia E, Bates E, Seitzman B, Coppess K. {{Altered brain network dynamics in youths with autism spectrum disorder}}. {Exp Brain Res};2016 (Jul 27)
The heterogeneity of behavioral manifestation of autism spectrum disorders (ASDs) requires a model which incorporates understanding of dynamic differences in neural processing between ASD and typically developing (TD) populations. We use network approach to characterization of spatiotemporal dynamics of EEG data in TD and ASD youths. EEG recorded during both wakeful rest (resting state) and a social-visual task was analyzed using cross-correlation analysis of the 32-channel time series to produce weighted, undirected graphs corresponding to functional brain networks. The stability of these networks was assessed by novel use of the L1-norm for matrix entries (edit distance). There were a significantly larger number of stable networks observed in the resting condition compared to the task condition in both populations. In resting state, stable networks persisted for a significantly longer time in children with ASD than in TD children; networks in ASD children also had larger diameter, indicative of long-range connectivity. The resulting analysis combines key features of microstate and network analyses of EEG.
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15. Taylor JL, Gotham KO. {{Cumulative life events, traumatic experiences, and psychiatric symptomatology in transition-aged youth with autism spectrum disorder}}. {J Neurodev Disord};2016;8:28.
BACKGROUND: Co-occurring mood and anxiety symptomatology is commonly observed among youth with autism spectrum disorders (ASD) during adolescence and adulthood. Yet, little is known about the factors that might predispose youth with ASD to mood and anxiety problems. In this study, we focus on the role of cumulative stressful life events and trauma in co-occurring psychopathology among youth with ASD who are preparing to exit high school. Specifically, we examined the distribution of cumulative life events and traumatic experiences and their relations with mood and anxiety symptomatology. METHODS: Participants included 36 youth with ASD, all of whom were in their last year of high school. Cumulative life events and trauma were assessed by parent report. Mood and anxiety symptomatology was determined using a variety of methods (structured interview, questionnaire, self- and informant report). Frequencies were used to examine the distributions of cumulative life events (count of total events) and trauma (coded into any trauma vs. no trauma), as well as mood and anxiety symptomatology (categorized into clinical-level, sub-threshold, or none for each). Bivariate relations between life events/trauma and mood/anxiety symptomatology were assessed using analysis of variance and chi-square. Ordinal logistic regression models were used to test whether significant bivariate relations remained after controlling for the sex of the youth with ASD and his/her IQ. RESULTS: Over 50 % of youth had experienced at least one trauma. Nearly one half had clinical-level mood or anxiety symptomatology. There was a statistically significant relation between absence/presence of trauma and mood symptomatology; nearly 90 % of the youth with clinical-level mood symptoms had at least one trauma, compared to 40 % of those with no mood symptomatology. CONCLUSIONS: Our findings suggest that contextual factors such as trauma might be important for the development of mood symptomatology in individuals with ASD. Although this idea is well-accepted in typically developing populations, contextual factors are rarely studied in investigations of psychopathology or transition outcomes in ASD. Given the high rates of psychiatric comorbidities in this population, future research should continue to identify the range of possible factors-both behavioral and contextual-that might influence the emergence of these disorders.
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16. Tye C, Johnson KA, Kelly SP, Asherson P, Kuntsi J, Ashwood KL, Azadi B, Bolton P, McLoughlin G. {{Response time variability under slow- and fast-incentive conditions in children with ASD, ADHD and ASD+ADHD}}. {J Child Psychol Psychiatry};2016 (Jul 28)
BACKGROUND: Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) show significant behavioural and genetic overlap. Both ADHD and ASD are characterised by poor performance on a range of cognitive tasks. In particular, increased response time variability (RTV) is a promising indicator of risk for both ADHD and ASD. However, it is not clear whether different indices of RTV and changes to RTV according to task conditions are able to discriminate between the two disorders. METHODS: Children with ASD (n = 19), ADHD (n = 18), ASD + ADHD (n = 29) and typically developing controls (TDC; n = 26) performed a four-choice RT task with slow-baseline and fast-incentive conditions. Performance was characterised by mean RT (MRT), standard deviation of RT (SD-RT), coefficient of variation (CV) and ex-Gaussian distribution measures of Mu, Sigma and Tau. RESULTS: In the slow-baseline condition, categorical diagnoses and trait measures converged to indicate that children with ADHD-only and ASD + ADHD demonstrated increased MRT, SD-RT, CV and Tau compared to TDC and ASD-only. Importantly, greater improvement in MRT, SD-RT and Tau was demonstrated in ADHD and ASD + ADHD from slow-baseline to fast-incentive conditions compared to TDC and ASD-only. CONCLUSIONS: Slower and more variable RTs are markers of ADHD compared to ASD and typically developing controls during slow and less rewarding conditions. Energetic factors and rewards improve task performance to a greater extent in children with ADHD compared to children with ASD. These findings suggest that RTV can be distinguished in ASD, ADHD and ASD + ADHD based on the indices of variability used and the conditions in which they are elicited. Further work identifying neural processes underlying increased RTV is warranted, in order to elucidate disorder-specific and disorder-convergent aetiological pathways.
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17. Wiener RC, Vohra R, Sambamoorthi U, Madhavan SS. {{Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum Disorder, Developmental Disability and/or Mental Health Conditions: National Survey of CSHCN, 2009-2010}}. {Matern Child Health J};2016 (Jul 27)
Objective The purpose of this study is to examine the burdens of caregivers on perception of the need and receipt of preventive dental care for a subset of children with special health care needs-children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009-2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers’ financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N = 16,323). Results Overall, 16.3 % of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0 % of caregivers who reported financial burden, 20.3 % who reported employment burden, and 10.8 % who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1, 16.5, 17.7 % respectively) compared to caregivers without financial, employment, or time burdens (9.0, 9.6 %, 11.0 % respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95 % CI 1.02, 1.86] and employment burden (adjusted multinomial odds ratio, 1.45 [95 % CI 1.02, 2.06] were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC.
