1. Asada K, Tojo Y, Osanai H, Saito A, Hasegawa T, Kumagaya S. {{Reduced Personal Space in Individuals with Autism Spectrum Disorder}}. {PLoS One};2016;11(1):e0146306.
Maintaining an appropriate distance from others is important for establishing effective communication and good interpersonal relations. Autism spectrum disorder (ASD) is a developmental disorder associated with social difficulties, and it is thus worth examining whether individuals with ASD maintain typical or atypical degrees of social distance. Any atypicality of social distancing may impact daily social interactions. We measured the preferred distances when individuals with ASD and typically developing (TD) individuals approached other people (a male experimenter) and objects (a coat rack with clothes) or when other people approached them. Individuals with ASD showed reduced interpersonal distances compared to TD individuals. The same tendency was found when participants judged their preferred distance from objects. In addition, when being approached by other people, both individuals with ASD and TD individuals maintained larger interpersonal distances when there was eye contact, compared to no eye contact. These results suggest that individuals with ASD have a relatively small personal space, and that this atypicality exists not only for persons but also for objects.
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2. Buckingham G, Michelakakis EE, Rajendran G. {{The Influence of Prior Knowledge on Perception and Action: Relationships to Autistic Traits}}. {J Autism Dev Disord};2016 (Jan 28)
Autism is characterised by a range of perceptual and sensorimotor deficits, which might be related to abnormalities in how autistic individuals use prior knowledge. We investigated this proposition in a large non-clinical population in the context of the size-weight illusion, where individual’s expectations about object weight influence their perceptions of heaviness and fingertip forces. Although there was no relationship between autistic traits and the magnitude of the illusion, we observed an inverse relationship between AQ scores and how expectations influenced initial fingertip force application. These findings provide a novel dissociation between how perceptual and sensorimotor processes are related to autistic traits, and suggest that, autistic traits might explain some of the variance surrounding how individuals grip and lift objects.
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3. Cyranoski D. {{Monkeys genetically modified to show autism symptoms}}. {Nature};2016 (Jan 28);529(7587):449.
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4. Funabashi N, Takaoka H, Ozawa K, Tanabe N, Tatsumi K, Saeki N, Higashide T, Uno T, Kobayashi Y. {{Combined ostium secundum type ASD and pulmonary arterial thromboembolism causing pulmonary artery enlargement, pulmonary hypertension and recurrent paradoxical cerebral embolism due to deep venous thrombosis}}. {Int J Cardiol};2016 (Jan 14);207:303-307.
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5. Ghosh A, Mahajan PB, Tripathy PR, Mishra BR, Mahapatra SC, Nanda P. {{Exploring Health Situation of Indian Children with Autism Spectrum Disorder Using Autism Treatment Evaluation Checklist (ATEC) in an Urban Area of Odisha: A Case Study}}. {J Clin Diagn Res};2015 (Dec);9(12):VC05-VC08.
INTRODUCTION: Autism or Autism Spectrum Disorder (ASD) is a complex behavioural disorder in children with uncertain aetiology. Gastrointestinal metabolites have direct impact on brain function with possible role in its causation. Data on burden of Autism in India is sparse. AIM: The aim of the study was to determine the extent of social, communication and behavioural impairment among children suffering from ASD patientsin Odisha. MATERIALS AND METHODS: A cross-sectional study design was used to assess 20 children with ASD in Odisha using an autism treatment evaluation checklist to understand the extent of social, communication and behavioural impairment in them. Of these, 72% children were diagnosed with ASD within 2 to 2.5 years of age and 38.9% patients suffered from diarrhoea together with constipation at the time of the study. RESULT: There was moderate impairment in, subclasses I (Speech/language/ communication), II (sociability), III (sensory/ cognitive awareness) and overall score but mild impairment in subclass IV (i.e., health/ physical/behaviour). Possibly, the training programme of the school had positive impact on the behaviour and the health component. Severity of scores in subclasses was less in older children. There is need for training in order to improve the communication and social interaction domain of these children. CONCLUSION: This study has provided valuable insight into the health situation of children with ASD. The study has been carried out using ATEC checklist. It points towards the need for training in order to improve the communication and social interaction domain of these children. It also reinforces the necessity to carry out further studies to explore possible link of gastrointestinal metabolites in causing ASD and age related changes in ATEC score of these children.
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6. Ling Z, Wang J, Li X, Zhong Y, Qin Y, Xie S, Yang S, Zhang J. {{[Association between mothers’ body mass index before pregnancy or weight gain during pregnancy and autism in children]}}. {Zhonghua Liu Xing Bing Xue Za Zhi};2015 (Sep);36(9):949-952.
OBJECTIVE: To explore the relationship between mothers’ body mass index (BMI) before pregnancy or weight gain during pregnancy and autism in children. METHODS: From 2013 to 2014, the 181 children with autism and 181 healthy children matched by sex and age from same area were included in this study. According to mothers’ BMI before pregnancy, the selected cases were divided into 3 groups: low, normal and high group. Then 3 groups were divided into 3 subgroups based on mother’ s weight gain during pregnancy: low, normal and high group, according to the recommendations of Institute of Medicine. Logistic regression analysis and chi(2) test were conducted with SPSS 18.0 software to analysis the relationship between mothers’ BMI before pregnancy or weight gain during pregnancy and autism in children. RESULTS: The age and sex distributions of case group and control group were consistent (chi(2)=0.434, P>0.05). The mothers’ BMI before pregnancy of case group was higher than that of control group (chi(2)=9.580, P<0.05) ,which was (21.28+/-3.80) kg/m(2) for case group and (19.87+/-2.83) kg/m(2) for control group. The proportion of cases in high BMI group (10.5%) was much higher than that in control group (2.8%) . The risk of children with autism in high BMI group was 3.7 times higher than that in normal BMI group (OR=3.71, 95% CI: 1.34-10.24). In normal BMI group, the proportion of mothers who had excessive weight gain during pregnancy was higher in case group (44.1%) than in control group (33.9%). In high BMI group, the proportion of mothers who had excessive weight gain was higher in case group (52.6%) than in control group (20.0%) . In normal BMI group (chi(2) =8.690, P<0.05) and high BMI group (chi(2)=4.775, P<0.05), the weight gain during pregnancy was associated with autism in children. Logistic regression analysis showed that mothers' BMI before pregnancy (unadjusted OR=1.89, 95% CI: 1.26-2.85, adjusted OR=1.52, 95% CI: 1.19-2.27) and weight gain during pregnancy were the risk factors for autism in children (unadjusted OR=1.63, 95% CI: 1.08-1.25, adjusted OR=1.64, 95% CI: 1.21-2.21). CONCLUSION: Overweight or obesity before pregnancy and excessive weight gain during pregnancy were associated with autism in children, suggesting that women who plan to be pregnant should pay attention to body weight control. Lien vers Pubmed
7. Meng WD, Sun SJ, Yang J, Chu RX, Tu W, Liu Q. {{Elevated Serum Brain-Derived Neurotrophic Factor (BDNF) but not BDNF Gene Val66Met Polymorphism Is Associated with Autism Spectrum Disorders}}. {Mol Neurobiol};2016 (Jan 28)
The aim of our study was to illuminate the potential role of brain-derived neurotrophic factor (BDNF) in autism spectrum disorder (ASD). We measured the circulating levels of BDNF in serum and BDNF gene (Val66Met) polymorphisms, in which two indicators were then compared between ASD and normal controls. A total of 82 drug-naive ASD children and 82 age- and gender-matched normal controls were enrolled in the study. Their serum BDNF levels were detected by the ELISA. BDNF Val66Met polymorphism genotyping was conducted as according to the laboratory’s standard protocol in laboratory. The ASD severity assessment was mainly determined by the score of the Childhood Autism Rating Scale (CARS). ELISA assay showed that the mean serum BDNF level of children with ASD was significantly (P < 0.0001) higher than that of the control cases (17.75 +/- 5.43 vs. 11.49 +/- 2.85 ng/ml; t = 9.236). Besides, the serum BDNF levels and CARS scores (P < 0.0001) were positively related. And, the BDNF genotyping results showed that there was no difference between the ASD cases and the control. Among the children with ASD, the mean serum BDNF level of Met/Met group was lower than other groups. According to the ROC curve generated from our clinical data, the optimal cutoff value of serum BDNF levels, an indicator for diagnosis of ASD, was projected to be 12.50 ng/ml. Thus, it yielded a corresponding sensitivity of 81.7 % and the specificity of 66.9 %. Accordingly, area value under the curve was 0.836 (95 % CI, 0.774-0.897); the positive predictive value (PPV) and the negative predictive value (NPV) were 70.1 and 79.1 %, respectively. These results suggested that rather than Val66Met polymorphism, BDNF was more possible to impact the pathogenesis of ASD.
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8. Modabbernia A, Mollon J, Boffetta P, Reichenberg A. {{Impaired Gas Exchange at Birth and Risk of Intellectual Disability and Autism: A Meta-analysis}}. {J Autism Dev Disord};2016 (Jan 28)
We conducted meta-analyses of 67 studies on the association between neonatal proxies of impaired gas exchange and intellectual disability (ID) or autism spectrum disorders (ASD). Neonatal acidosis was associated with an odds ratio (OR) of 3.55 [95 % confidence interval (95 % CI) 2.23-5.49] for ID and an OR of 1.10 (95 % CI 0.91-1.31) for ASD. Children with a 5-min Apgar score of <7 had an OR of 5.39 (95 % CI 3.84-7.55) for ID and an OR of 1.67 (95 % CI 1.34-2.09) for ASD. O2 treatment was associated with an OR of 4.32 (95 % CI 3.23-5.78) for ID and an OR of 2.02 (95 % CI 1.45 to 2.83) for ASD. Our meta-analysis demonstrates an increased risk of ID and (to a lesser extent) ASD in children with neonatal hypoxia. Moreover, our findings raise the possibility that concomitant ID might account for the observed association between the gas exchange proxies and ASD.
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9. Ofe EE, Plumb AM, Plexico LW, Haak NJ. {{School-Based Speech-Language Pathologists’ Knowledge and Perceptions of Autism Spectrum Disorder and Bullying}}. {Lang Speech Hear Serv Sch};2016 (Jan 1);47(1):59-76.
Purpose: The purpose of the current investigation was to examine speech-language pathologists’ (SLPs’) knowledge and perceptions of bullying, with an emphasis on autism spectrum disorder (ASD). Method: A 46-item, web-based survey was used to address the purposes of this investigation. Participants were recruited through e-mail and electronic mailing lists for American Speech-Language-Hearing Association (ASHA) special interest divisions 1 (Language, Learning, and Education) and 16 (School-Based Issues). Also, an embedded link to the survey was posted on the ASHA Community website and ASHA Facebook page. Results: Participants demonstrated knowledge of many aspects of bullying research; however, they demonstrated weaknesses in others. All respondents agreed that SLPs should intervene in moments of bullying, but not all indicated that they feel comfortable intervening. Few participants indicated that their school district implemented antibullying campaigns specific to children with special needs, such as ASD. Conclusions: As recognized experts in working with children with communication deficits, including individuals with ASD, SLPs have the opportunity to play a key role in antibullying efforts. Results revealed, however, that school-based SLPs may benefit from more information on bullying in order to understand the nature, context, and extent of this issue, as well as ways in which to respond to bullying when it is observed.
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10. Pitzianti M, D’Agati E, Pontis M, Baratta A, Casarelli L, Spiridigliozzi S, Curatolo P, Pasini A. {{Comorbidity of ADHD and High-functioning Autism: A Pilot Study on the Utility of the Overflow Movements Measure}}. {J Psychiatr Pract};2016 (Jan);22(1):22-30.
OBJECTIVES: Children with attention-deficit/hyperactivity disorder (ADHD) and high-functioning autism (HFA) commonly show neurological soft signs (NSS) and impairment in executive functioning (EF). Many children with HFA may experience ADHD-like symptoms, and the 2 disorders may be comorbid. Evaluating NSS and EF in drug-naive subjects with ADHD, HFA, and ADHD+HFA compared with healthy children may be critical in understanding and differentiating the biological substrates and cognitive phenotypes associated with these disorders. The goal of this study was to evaluate possible differences among these groups in motor and EF and the effects of comorbidity. METHODS: Thirty-eight drug-naive patients (13 with ADHD, 13 with HFA, 12 with ADHD+HFA) and 13 healthy controls (HC) were evaluated on measures of planning, verbal working memory, and response inhibition. Evaluation of NSS involved 3 primary variables: overflow movements (OM), dysrhythmia, and speed of timed activities. RESULTS: The group with ADHD and the group with HFA both showed impairment on measures of planning, response inhibition, and verbal working memory compared with the HC group. Moreover, the group with ADHD showed a greater number of NSS compared with the HC group, whereas the group with HFA showed greater dysrhythmia and slowness compared with the HC group. The group with ADHD+HFA showed deficits of planning and response inhibition and a greater number of NSS compared with the HC group. The group with ADHD+HFA showed greater impairment of planning compared with the other clinical groups and greater dysrhythmia compared with the group with ADHD. CONCLUSION: According to our data, the OM measure revealed a gradient in which ADHD was at one extreme (more OM) and HFA at the other extreme (less OM), whereas ADHD+HFA showed a number of OM that fell in the middle between the numbers for the ADHD and HFA groups.
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11. Robins DL, Adamson LB, Barton M, Connell JE, Jr., Dumont-Mathieu T, Dworkin PH, Fein D, Greenstein MA, Hsu HW, Kerns C, Newschaffer C, Plumb J, Shattuck P, Turchi R, Vivanti G. {{Universal Autism Screening for Toddlers: Recommendations at Odds}}. {J Autism Dev Disord};2016 (Jan 28)
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12. Sabatos-DeVito M, Schipul SE, Bulluck JC, Belger A, Baranek GT. {{Eye Tracking Reveals Impaired Attentional Disengagement Associated with Sensory Response Patterns in Children with Autism}}. {J Autism Dev Disord};2016 (Jan 27)
This study used a gap-overlap paradigm to examine the impact of distractor salience and temporal overlap on the ability to disengage and orient attention in 50 children (4-13 years) with ASD, DD and TD, and associations between attention and sensory response patterns. Results revealed impaired disengagement and orienting accuracy in ASD. Disengagement was impaired across all groups during temporal overlap for dynamic stimuli compared to static, but only ASD showed slower disengagement from multimodal relative to unimodal dynamic stimuli. Attentional disengagement had differential associations with distinct sensory response patterns in ASD and DD. Atypical sensory processing and temporal binding appear to be intertwined with development of disengagement in ASD, but longitudinal studies are needed to unravel causal pathways.
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13. Yang DY, Beam D, Pelphrey KA, Abdullahi S, Jou RJ. {{Cortical morphological markers in children with autism: a structural magnetic resonance imaging study of thickness, area, volume, and gyrification}}. {Mol Autism};2016;7:11.
BACKGROUND: Individuals with autism spectrum disorder (ASD) have been characterized by altered cerebral cortical structures; however, the field has yet to identify consistent markers and prior studies have included mostly adolescents and adults. While there are multiple cortical morphological measures, including cortical thickness, surface area, cortical volume, and cortical gyrification, few single studies have examined all these measures. The current study analyzed all of the four measures and focused on pre-adolescent children with ASD. METHODS: We employed the FreeSurfer pipeline to examine surface-based morphometry in 60 high-functioning boys with ASD (mean age = 8.35 years, range = 4-12 years) and 41 gender-, age-, and IQ-matched typically developing (TD) peers (mean age = 8.83 years), while testing for age-by-diagnosis interaction and between-group differences. RESULTS: During childhood and in specific regions, ASD participants exhibited a lack of normative age-related cortical thinning and volumetric reduction and an abnormal age-related increase in gyrification. Regarding surface area, ASD and TD exhibited statistically comparable age-related development during childhood. Across childhood, ASD relative to TD participants tended to have higher mean levels of gyrification in specific regions. Within ASD, those with higher Social Responsiveness Scale total raw scores tended to have greater age-related increase in gyrification in specific regions during childhood. CONCLUSIONS: ASD is characterized by cortical neuroanatomical abnormalities that are age-, measure-, statistical model-, and region-dependent. The current study is the first to examine the development of all four cortical measures in one of the largest pre-adolescent samples. Strikingly, Neurosynth-based quantitative reverse inference of the surviving clusters suggests that many of the regions identified above are related to social perception, language, self-referential, and action observation networks-those frequently found to be functionally altered in individuals with ASD. The comprehensive, multilevel analyses across a wide range of cortical measures help fill a knowledge gap and present a complex but rich picture of neuroanatomical developmental differences in children with ASD.
