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. 2010 Nov;38(8):1083-95.
doi: 10.1007/s10802-010-9429-7.

The genetic association between ADHD symptoms and reading difficulties: the role of inattentiveness and IQ

Yannis Paloyelis  1 , Fruhling Rijsdijk, Alexis C Wood, Philip Asherson, Jonna Kuntsi
Affiliations

The genetic association between ADHD symptoms and reading difficulties: the role of inattentiveness and IQ

Yannis Paloyelis et al. J Abnorm Child Psychol. 2010 Nov.

Abstract

Previous studies have documented the primarily genetic aetiology for the stronger phenotypic covariance between reading disability and ADHD inattention symptoms, compared to hyperactivity-impulsivity symptoms. In this study, we examined to what extent this covariation could be attributed to "generalist genes" shared with general cognitive ability or to "specialist" genes which may specifically underlie processes linking inattention symptoms and reading difficulties. We used multivariate structural equation modeling on IQ, parent and teacher ADHD ratings and parent ratings on reading difficulties from a general population sample of 1312 twins aged 7.9-10.9 years. The covariance between reading difficulties and ADHD inattention symptoms was largely driven by genetic (45%) and child-specific environment (21%) factors not shared with IQ and hyperactivity-impulsivity; only 11% of the covariance was due to genetic effects common with IQ. Aetiological influences shared among all phenotypes explained 47% of the variance in reading difficulties. The current study, using a general population sample, extends previous findings by showing, first, that the shared genetic variability between reading difficulties and ADHD inattention symptoms is largely independent from genes contributing to general cognitive ability and, second, that child-specific environment factors, independent from IQ, also contribute to the covariation between reading difficulties and inattention symptoms.

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Figures

Fig. 1
Fig. 1
Multivariate Cholesky triangular decomposition with unstandardized parameter estimates. The best-fitting ACE(IQ)-AE model is presented (for twin one only)
Fig. 2
Fig. 2
Correlated factors solution of the best fitting ACE(IQ)-AE multivariate Cholesky decomposition model presented in Fig. 1 (for twin one only). Path estimates presented as square roots are the unstandardized parameter estimates (the basis of the square root provides the standardized estimate). Bidirectional arrows between latent genetic (A1–A4) and child-specific environment (E1–E4) factors show the genetic (rg) and child-specific environment (re) correlations between them, respectively. Dotted arrows denote non-significant estimates
Fig. 3
Fig. 3
Illustration of the multivariate independent pathways (a) and common pathway (b) ACE(IQ)-AE models which were compared to the multivariate Cholesky model presented in Fig. 1
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