Language and traits of autism spectrum conditions: evidence of limited phenotypic and etiological overlap

Language difficulties have historically been viewed as integral to autism spectrum conditions (ASC), leading molecular genetic studies to consider whether ASC and language difficulties have overlapping genetic bases. The extent of genetic, and also environmental, overlap between ASC and language is, however, unclear. We hence conducted a twin study of the concurrent association between autistic traits and receptive language abilities. Internet-based language tests were completed by ∼3,000 pairs of twins, while autistic traits were assessed via parent ratings. Twin model fitting explored the association between these measures in the full sample, while DeFries-Fulker analysis tested these associations at the extremes of the sample. Phenotypic associations between language ability and autistic traits were modest and negative. The degree of genetic overlap was also negative, indicating that genetic influences on autistic traits lowered language scores in the full sample (mean genetic correlation = −0.13). Genetic overlap was also low at the extremes of the sample (mean genetic correlation = 0.14), indicating that genetic influences on quantitatively defined language difficulties were largely distinct from those on extreme autistic traits. Variation in language ability and autistic traits were also associated with largely different nonshared environmental influences. Language and autistic traits are influenced by largely distinct etiological factors. This has implications for molecular genetic studies of ASC and understanding the etiology of ASC. Additionally, these findings lend support to forthcoming DSM-5 changes to ASC diagnostic criteria that will see language difficulties separated from the core ASC communication symptoms, and instead listed as a clinical specifier. © 2014 Wiley Periodicals, Inc

Early identification of young children at risk for poor academic achievement: preliminary development of a parent-report prediction tool

<p>Abstract</p> <p>Background</p> <p>Early school success is clearly related to later health. A prediction index that uses parent report to assess children's risk for poor academic achievement could potentially direct targeted service delivery to improve child outcomes.</p> <p>Methods</p> <p>We obtained risk factors through literature review and used the National Longitudinal Survey of Youth 1979 Child Files to examine the predictive associations of these factors with academic achievement scores.</p> <p>Results</p> <p>Twenty predictors were identified including four strong predictors (maternal education, child gender, family income, and low birth weight). Significantly, 12 predictors explained 17-24% of score variance.</p> <p>Conclusions</p> <p>Parent-reported factors provide predictive accuracy for academic achievement.</p

Visual-motor integration and reading Chinese in children with/without dyslexia

This is a post-peer-review, pre-copyedit version of an article published in Reading and Writing. The final authenticated version is available online at: https://link.springer.com/article/10.1007/s11145-018-9876-zNational Natural Science Foundation of China; Beijing Advanced Innovation Center for Imaging Technology; Scientific Foundation of Institute of Psychology; Chinese Academy of Sciences