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    Phenotype refinement for comorbid Attention Deficit Hyperactivity Disorder and reading disability

    Access Status
    Fulltext not available
    Authors
    Sheikhi, A.
    Martin, Neilson
    Hay, David
    Piek, Jan
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Sheikhi, Abdullah R. and Martin, Neilson and Hay, David and Piek, Jan P. 2012. Phenotype refinement for comorbid Attention Deficit Hyperactivity Disorder and reading disability. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics. 162 (1): pp. 44-54.
    Source Title
    American Journal of Medical Genetics
    DOI
    10.1002/ajmg.b.32119
    ISSN
    01487299
    URI
    http://hdl.handle.net/20.500.11937/29454
    Collection
    • Curtin Research Publications
    Abstract

    Comorbidity between Attention Deficit Hyperactivity Disorder (ADHD) and reading disability (RD) is common; however, the heritability of this comorbidity is not well understood. This may be due to the complexity and heterogeneity of ADHD and RD phenotypes. Using alternative ADHD–RD sub-phenotypes instead of those arising from the DSM-IV may lead to greater success in the search for comorbid ADHD–RD susceptibility genes. Therefore, this study aims to refine ADHD–RD phenotypes into homogenous informative sub-phenotypes using latent class analysis (LCA). LCA was performed on 2,610 Australian twin families (6,535 individuals) in order to generate probabilistic genetically distinct classes that define ADHD–RD subtypes, including comorbidity, based on related symptom clusters. The LCA separated the phenotypes for ADHD and RD into nine classes. One class was unaffected; three classes demonstrated the three DSM-IV subtypes of ADHD, three subtypes showed different severities of RD, and two classes expressed a combination of RD and ADHD subtypes. LCA proved effective in refining the phenotypes of ADHD alone, RD alone, and ADHD–RD comorbidity, and its ability to classify them into homogenous groups based on clusters of symptoms, suggesting that the latent classes may be robust enough to use in molecular genetic studies.

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