A small but significant proportion of children have unexplained difficulties acquiring language and/or reading skills, in the absence of any obvious causes. These problems have major impacts on education, mental health and social well-being. It is well established that a child's genetic make-up plays a major role in susceptibility to language and reading problems. Now advances in genomics make it possible to zero in on some of the risk genes. This subproject targets common language- and reading-related disorders that are likely to involve multiple different genes, and approaches impairment as one extreme of a continuum in ability in the general population. Making use of individual differences in performance, we apply quantitative genetic methods, in a similar manner to that used to study genetics of human height or body mass index.

Specific Language Impairment

In collaboration with Dianne Newbury and colleagues (University of Oxford, UK) we are studying a set of families from the United Kingdom, collected by the Specific Language Impairment Consortium (SLIC). Each family contains at least one child with poor language skills, but every available sibling is assessed with standardized measures for receptive and expressive language, nonsense word repetition (a robust heritable marker of language impairment), as well as indices of general cognition. We are analyzing the SLIC families with ~700,000 common genetic variants from different parts of the genome. In this high-density genome-wide association screen, statistical tests establish whether inheritance of any particular marker is significantly correlated with language-related performance. These data will be integrated with our other studies of language impairment and related disorders, coupled with those of collaborators worldwide.

Reading disability

We work with a sample of roughly 800 twins and their siblings that were collected by the Colorado Learning Disabilities Research Center. We are performing genome-wide screens for associations with single nucleotide polymorphisms and copy number variants, using Illumina arrays and multivariate statistical approaches, to identify genetic effects on cognitive traits such as phonological awareness and orthographic coding.