1. Benson V, Castelhano MS, Howard PL, Latif N, Rayner K. {{Looking, seeing and believing in autism: Eye movements reveal how subtle cognitive processing differences impact in the social domain}}. {Autism Res};2015 (Nov 28)
Adults with High Functioning Autism Spectrum Disorders (ASD) viewed scenes with people in them, while having their eye movements recorded. The task was to indicate, using a button press, whether the pictures were normal, or in some way weird or odd. Oddities in the pictures were categorized as violations of either perceptual or social norms. Compared to a Typically Developed (TD) control group, the ASD participants were equally able to categorize the scenes as odd or normal, but they took longer to respond. The eye movement patterns showed that the ASD group made more fixations and revisits to the target areas in the odd scenes compared with the TD group. Additionally, when the ASD group first fixated the target areas in the scenes, they failed to initially detect the social oddities. These two findings have clear implications for processing difficulties in ASD for the social domain, where it is important to detect social cues on-line, and where there is little opportunity to go back and recheck possible cues in fast dynamic interactions. Autism Res 2015. (c) 2015 International Society for Autism Research, Wiley Periodicals, Inc.
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2. Farrant K, Uddin LQ. {{Atypical developmental of dorsal and ventral attention networks in autism}}. {Dev Sci};2015 (Nov 27)
Individuals with autism spectrum disorders (ASD) exhibit early and lifelong impairments in attention across multiple domains. While the disorder is known to affect attention processes, very little is currently known about the brain networks underlying attention in ASD, and even less is known about whether these atypicalities persist across the lifespan. We used functional connectivity analysis applied to resting state functional magnetic resonance imaging (fMRI) data to explore the dorsal (DAN) and ventral (VAN) attention networks in two separate age cohorts of children and adults with and without ASD. We find significant developmental differences in functional connectivity of brain regions that are critical for attention in children and adults with ASD. Specifically, children with ASD show hyper-connectivity of regions-of-interest (ROIs) in both attention networks compared with both typically developing (TD) children and adults with ASD. In contrast, adults with ASD show hypo-connectivity of these networks compared with neurotypical adults. These findings are consistent with the notion that consideration of developmental stage is critical in studies of functional connectivity in ASD. This study further illustrates diverging developmental patterns for top-down and bottom-up attention systems in autism.
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3. Grefer M, Flory K, Cornish K, Hatton D, Roberts J. {{The emergence and stability of attention deficit hyperactivity disorder in boys with fragile X syndrome}}. {J Intellect Disabil Res};2015 (Nov 27)
BACKGROUND: Children with fragile X syndrome (FXS) are at high risk for developing a range of behavioural disorders, including attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASD). However, very few studies have investigated the comorbid profile of FXS and ADHD and the possible dissociation from the FXS and ASD profile. The present study examined the relationship of childhood temperament characteristics of the Surgency facet (activity level, impulsivity, approach, shyness, and smiling and laughter) and the severity of ADHD and ASD features at two measurement time points in childhood, preschool (ages 3-4) and at school entry (ages 5-6). METHODS: The study consisted of males with FXS measured at each time point (preschool and school entry), as well as comparison of typically developing (TD) boys at the preschool measurement time point. Parent reported measures of temperament and behavioural symptoms were collected at each time point. Multiple regression analyses were used to analyse obtained data. RESULTS: Elevated activity level scores are associated with ADHD scores at preschool age and elevated shyness and decreased smiling and laughter are strongly associated with ADHD scores upon school entry. Impulsivity emerges as a strong indicator of elevated ADHD scores around school age, but even preschool impulsivity scores demonstrate some predictive value for higher ADHD scores later in school. Finally, no Surgency characteristic was significantly related to ASD scores at any age. CONCLUSIONS: Impulsivity serves as an indicator of elevated ADHD symptoms across development periods in boys with FXS, while activity level is just indicative of higher ADHD scores at the preschool age. The Surgency facet of temperament at either age does not predict strong relationships of comorbid pathologies of ADHD and ASD in FXS. However, Surgency characteristics may serve as informative discriminative factors when studying behavioural outcomes in boys with FXS.
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4. Guy J, Mottron L, Berthiaume C, Bertone A. {{The developmental trajectory of contrast sensitivity in autism spectrum disorder}}. {Autism Res};2015 (Nov 27)
Autism Spectrum Disorder (ASD) is characterized by a detail-driven visual processing strategy, evidence for which has been based largely on cross-sectional studies in small participant groups of limited age ranges. It is therefore unknown when sensitivity to detailed information emerges and develops in ASD. Contrast sensitivity to sinusoidal gratings of different spatial frequencies (0.5, 1, 2, 4, and 8 cycles per degree (cpd)) was measured for 34 participants with ASD and 55 typically developing participants (aged 6-16 years). Cross-sectional, developmental trajectories were constructed to examine within and between group differences across the range of spatial frequencies tested. Developmental trajectories indicated that sensitivity across low (i.e., 0.5 and 1 cpd) and mid (2 and 4 cpd) spatial frequencies varied by chronological age within each group, with mid frequencies developing at a more significant rate than low frequencies. There was no overall difference between groups in terms of the relationship of sensitivity and age across spatial frequencies, yet the ASD group had an overall lower level of sensitivity. Closer examination revealed that the youngest participants with ASD had a reduced sensitivity for mid frequencies. Moreover, the ASD group showed a statistically significant developmental relationship at 8 cpd, which suggests that a trend for increased sensitivity to early detailed information may manifest beyond the ages tested. These findings demonstrate a differential development of contrast sensitivity for spatial frequencies in ASD and underscore the need to better identify what drives such differences in the « building blocks » of visual perception. Autism Res 2015. (c) 2015 International Society for Autism Research, Wiley Periodicals, Inc.
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5. Heavner K, Newschaffer C, Hertz-Picciotto I, Bennett D, Burstyn I. {{Pooling Bio-Specimens in the Presence of Measurement Error and Non-Linearity in Dose-Response: Simulation Study in the Context of a Birth Cohort Investigating Risk Factors for Autism Spectrum Disorders}}. {Int J Environ Res Public Health};2015;12(11):14780-14799.
We sought to determine the potential effects of pooling on power, false positive rate (FPR), and bias of the estimated associations between hypothetical environmental exposures and dichotomous autism spectrum disorders (ASD) status. Simulated birth cohorts in which ASD outcome was assumed to have been ascertained with uncertainty were created. We investigated the impact on the power of the analysis (using logistic regression) to detect true associations with exposure (X(1)) and the FPR for a non-causal correlate of exposure (X(2), r = 0.7) for a dichotomized ASD measure when the pool size, sample size, degree of measurement error variance in exposure, strength of the true association, and shape of the exposure-response curve varied. We found that there was minimal change (bias) in the measures of association for the main effect (X(1)). There is some loss of power but there is less chance of detecting a false positive result for pooled compared to individual level models. The number of pools had more effect on the power and FPR than the overall sample size. This study supports the use of pooling to reduce laboratory costs while maintaining statistical efficiency in scenarios similar to the simulated prospective risk-enriched ASD cohort.
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6. Luo SX, Shinall JA, Peterson BS, Gerber AJ. {{Semantic mapping reveals distinct patterns in descriptions of social relations in adults with autism spectrum disorder}}. {Autism Res};2015 (Nov 27)
Adults with autism spectrum disorder (ASD) may describe other individuals differently compared with typical adults. In this study, we first asked participants to describe closely related individuals such as parents and close friends with 10 positive and 10 negative characteristics. We then used standard natural language processing methods to digitize and visualize these descriptions. The complex patterns of these descriptive sentences exhibited a difference in semantic space between individuals with ASD and control participants. Machine learning algorithms were able to automatically detect and discriminate between these two groups. Furthermore, we showed that these descriptive sentences from adults with ASD exhibited fewer connections as defined by word-word co-occurrences in descriptions, and these connections in words formed a less « small-world » like network. Autism Res 2015. (c) 2015 International Society for Autism Research, Wiley Periodicals, Inc.
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7. Nicholas DB, Zwaigenbaum L, Ing S, MacCulloch R, Roberts W, McKeever P, McMorris CA. {{« Live It to Understand It »: The Experiences of Mothers of Children With Autism Spectrum Disorder}}. {Qual Health Res};2015 (Nov 26)
Mothers of children with an autism spectrum disorder (ASD) variably experience challenges in their caregiving role. This ethnographic study examined the caregiving experiences of mothers of a young person with ASD (aged Lien vers le texte intégral (Open Access ou abonnement)
8. Nuttall JR. {{The plausibility of maternal toxicant exposure and nutritional status as contributing factors to the risk of autism spectrum disorders}}. {Nutr Neurosci};2015 (Nov 27)
Recent research suggests the maternal environment may be especially important for the risk of developing autism spectrum disorders (ASD). In particular maternal infections, micronutrient deficiencies, obesity, and toxicant exposures are likely to interact with genetic risk factors to disrupt fetal brain development. Objectives The goal of this paper is to investigate the plausibility of maternal toxicant exposure and nutritional status as causal factors in the development of ASD. Methods This paper reviews current research investigating the hypothesis that maternal toxicant exposure and prenatal micronutrient intake are important modifiable risk factors for ASD. Results Zinc, copper, iron, and vitamin B9 are identified as specific micronutrients with relevance to the etiology of ASD. Specific toxicants induce a maternal inflammatory response leading to fetal micronutrient deficiencies that disrupt early brain development. Importantly, maternal micronutrient supplementation is associated with reduced risk of ASD. Furthermore, animal studies show that micronutrient supplementation can prevent the teratogenicity and developmental neurotoxicity of specific toxicants. Discussion These findings lead to the hypothesis that maternal infection, obesity, and toxicant exposures (e.g. valproic acid, endocrine disrupting plasticizers, ethanol, and heavy metals) are all environmental risk factors for ASD that lead to fetal micronutrient deficiencies resulting from a maternal inflammatory response. It could be possible to use markers of inflammation and micronutrient status to identify women that would benefit from micronutrient supplementation or dietary interventions to reduce the risk of ASD. However, more research is needed to demonstrate a causal role of fetal micronutrient deficiencies and clarify the underlying mechanisms that contribute to ASD.
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9. O’Reilly M, Lester JN, Muskett T. {{Discourse/Conversation Analysis and Autism Spectrum Disorder}}. {J Autism Dev Disord};2015 (Nov 28)
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10. Stepniak B, Kastner A, Poggi G, Mitjans M, Begemann M, Hartmann A, Van der Auwera S, Sananbenesi F, Krueger-Burg D, Matuszko G, Brosi C, Homuth G, Volzke H, Benseler F, Bagni C, Fischer U, Dityatev A, Grabe HJ, Rujescu D, Fischer A, Ehrenreich H. {{Accumulated common variants in the broader fragile X gene family modulate autistic phenotypes}}. {EMBO Mol Med};2015;7(12):1565-1579.
Fragile X syndrome (FXS) is mostly caused by a CGG triplet expansion in the fragile X mental retardation 1 gene (FMR1). Up to 60% of affected males fulfill criteria for autism spectrum disorder (ASD), making FXS the most frequent monogenetic cause of syndromic ASD. It is unknown, however, whether normal variants (independent of mutations) in the fragile X gene family (FMR1, FXR1, FXR2) and in FMR2 modulate autistic features. Here, we report an accumulation model of 8 SNPs in these genes, associated with autistic traits in a discovery sample of male patients with schizophrenia (N = 692) and three independent replicate samples: patients with schizophrenia (N = 626), patients with other psychiatric diagnoses (N = 111) and a general population sample (N = 2005). For first mechanistic insight, we contrasted microRNA expression in peripheral blood mononuclear cells of selected extreme group subjects with high- versus low-risk constellation regarding the accumulation model. Thereby, the brain-expressed miR-181 species emerged as potential « umbrella regulator », with several seed matches across the fragile X gene family and FMR2. To conclude, normal variation in these genes contributes to the continuum of autistic phenotypes.
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11. Woodman AC, Mailick MR, Greenberg JS. {{Trajectories of internalizing and externalizing symptoms among adults with autism spectrum disorders}}. {Dev Psychopathol};2015 (Nov 27):1-17.
Individuals with autism spectrum disorder (ASD) experience higher rates of psychopathology than their typically developing peers or peers with other intellectual or developmental disabilities. Little is known about the developmental course of psychiatric symptoms such as internalizing and externalizing behaviors in this population. Individual characteristics and aspects of the family environment may explain variability in outcomes for adults with ASD. The present study extends our current understanding of psychopathology among individuals with ASD by examining group-based trajectories of internalizing and externalizing symptoms in adulthood. Overall, the results showed that symptoms became less severe over time. Distinct patterns of change in psychopathology were observed and associated with differential profiles of psychotropic medication use, comorbid mental health diagnoses, and residential placement. The likelihood of following each developmental trajectory was estimated based on characteristics of the adults with ASD (gender, adaptive behavior, and autistic symptoms) and maternal expressed emotion (criticism and warmth). Maternal criticism and warmth were identified as key risk and protective factors, respectively, with important implications for future research and intervention for individuals with ASD.
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12. Zwaigenbaum L, Bryson SE, Brian J, Smith IM, Roberts W, Szatmari P, Roncadin C, Garon N, Vaillancourt T. {{Stability of diagnostic assessment for autism spectrum disorder between 18 and 36 months in a high-risk cohort}}. {Autism Res};2015 (Nov 27)
Children with autism spectrum disorder (ASD) are diagnosed, on average, around the age of 4 years. However, previous research has shown that the diagnosis can be made as early as 2 years, and that if the child is seen a year or more later, it is highly likely that the diagnosis will be confirmed. In this study, to examine whether diagnoses made as early as 18 months of age are also « stable, » we followed a group of younger siblings of children with ASD (who are known to be at higher risk). We also examined whether the age of ASD diagnosis within this high-risk group was related to the severity of children’s ASD symptoms or developmental delays. Participants (n = 381) were seen at three ages: 18 months, 24 months, and 3 years. ASD symptoms, general development, and adaptive functioning were assessed at each time point. Twenty-three children were diagnosed with ASD at 18 months and a total of 61 at 24 months. Of these diagnoses, 19/23 (82.6%) and 56/61 (91.8%), respectively, were confirmed independently at 3 years. However, 45 children were diagnosed with ASD at 3 years who had not been identified at earlier visits. Children diagnosed at 18 months, in comparison to those diagnosed at 24 months, had less advanced language and adaptive skills at 18 months. Children not diagnosed with ASD until 3 years, compared with those diagnosed earlier, had more advanced language and adaptive skills, and milder ASD symptoms. Autism Res 2015. (c) 2015 International Society for Autism Research, Wiley Periodicals, Inc.
