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Multivariate genome-wide association study (GWAS) of reading and mathematics disabilities/abilities: A quantitative trait locus (QTL) perspective

Robert Plomin

Ian Craig, Cathryn Lewis, Leonard Schalkwyk.

Learning difficulties are the most common and heritable problems in childhood and can have considerable impact on later life. Identifying the genes responsible for this heritable influence will make it possible to predict problems before the school years so that early educational interventions can be devised to prevent these problems from blighting children's lives.

The proposed QTL and multivariate perspectives can facilitate finding genes associated with these important developmental difficulties. The QTL perspective is important because it points to the need to assess quantitative dimensions rather than qualitative diagnoses. Stated more provocatively, a QTL perspective suggests that for common disorders such as learning disabilities there are no aetiologically distinct disorders, just the quantitative extreme of the same genetic factors responsible for variation throughout the normal distribution. If the QTL hypothesis is correct, a quantitative trait strategy will be more powerful for identifying SNP associations than will a case-control strategy based on dichotomous diagnoses.

A multivariate QTL GWAS is proposed that will use quantitative trait data from a battery of reading and mathematics measures from 4000 12-year-old twins participating in the UK Twins Early Development Study (TEDS). The QTL perspective follows from quantitative genetic research that suggests that reading and mathematics disabilities are the quantitative extremes of the same genes that affect normal variation in reading and mathematics abilities. The multivariate perspective follows from quantitative genetic research that suggests that the same set of genes affects reading and mathematics abilities and disabilities. Both the QTL and multivariate features of the proposed research will increase power to identify SNPs associated with reading and mathematics.

The other twin from each of the 4000 twin pairs will provide a replication sample perfectly matched for age and other demographic characteristics and assessed with exactly the same measures for the purpose of replicating SNPs identified in the WTCCC GWAS. At the replication stage, the design will have 80% power to replicate SNP associations that account for 0.25% of the total variance of the quantitative trait.

The rich TEDS dataset will make it possible to use these SNPs in 'behavioural genomic' analyses to investigate developmental, multivariate and gene-environment interplay issues.