Genome-wide quantitative trait locus association scan of general cognitive ability using pooled DNA and 500K single nucleotide polymorphism microarrays

Abstract

General cognitive ability (g), which refers to what cognitive abilities have in common, is an important target for molecular genetic research because multivariate quantitative genetic analyses have shown that the same set of genes affects diverse cognitive abilities as well as learning disabilities. In this first autosomal genome-wide association scan of g, we used a two-stage quantitative trait locus (QTL) design with pooled DNA to screen more than 500,000 single nucleotide polymorphisms (SNPs) on microarrays, selecting from a sample of 7000 7-year-old children. In stage 1, we screened for allele frequency differences between groups pooled for low and high g. In stage 2, 47 SNPs nominated in stage 1 were tested by individually genotyping an independent sample of 3195 individuals, representative of the entire distribution of g scores in the full 7000 7-year-old children. Six SNPs yielded significant associations across the normal distribution of g, although only one SNP remained significant after a false discovery rate of 0.05 was imposed. However, none of these SNPs accounted for more than 0.4% of the variance of g, despite 95% power to detect associations of that size. It is likely that QTL effect sizes, even for highly heritable traits such as cognitive abilities and disabilities, are much smaller than previously assumed. Nonetheless, an aggregated 'SNP set' of the six SNPs correlated 0.11 (P < 0.00000003) with g. This shows that future SNP sets that will incorporate many more SNPs could be useful for predicting genetic risk and for investigating functional systems of effects from genes to brain to behavior.

Figure 1

A histogram illustrating the distribution of absolute allele frequency differences between low and high g groups derived through pooled DNA on microarrays.The y-axis indicates the number of SNPs with differences corresponding to those on the x-axis. The figure shows that the vast majority of allele frequency differences are small and that the mean allele frequency between low and high g groups is about 0.025. The x-axis is elongated to accommodate outliers, which are a logical source of candidate SNPs to follow up; the extreme end of this scale is magnified for clarity and detail (inset). The total number of SNPs is less than the total number of autosomal SNPs because SNPs represented by fewer than six out of 10 replicates were removed.

Figure 2

A scatter plot showing the 47 top-ranked SNPs (crosses) against the background of unselected SNPs comparing allele frequencies for the low g group (x-axis) and the high g group (y-axis).The figure also displays the density of SNPs as a function of low g vs. high g allele frequency differences; density of SNP clusters increases as the heat map changes from light (sparse clusters) through to dark (dense clusters). Allele frequency differences are small, with the majority of small differences occurring for SNPs with minor allele frequencies of 0.10–0.25, which reflects the overrepresentation of SNPs with these allele frequencies on the Affymetrix microarray. The correlation between low and high g allele frequencies was 0.993, indicating high reliability across the two groups.

Figure 3

Genotype-by-phenotype plots illustrating the effect of genotype (x-axis) on standardized g scores (y-axis).The six significantly associated SNPs using individuals genotyping are labeled a–e.

Figure 4

A histogram illustrating the distribution of SNP-set scores.The x-axis scale runs from 0 to 12 because each of the genotypes for the six SNPs is coded using an additive model with 0, 1 or 2 ‘increaser’ alleles. For each SNP, scores of 2 indicate that the individual is homozygous for the allele conferring higher g scores. These scores are summed at each locus for each individual to create an SNP-set score. The y-axis indicates the number of individuals with a particular SNP-set score. The majority of individuals score between 5 and 8 because the SNPs were chosen on the basis of high minor allele frequency and thus high heterozygosity.

Figure 5

A genotype-by-phenotype plot illustrating the relationship between SNP-set scores and standardized g.The correlation between the SNP-set scores and the g scores is 0.105 (P < 0.00000003, n = 2676). The association is approximately linear, which indicates additivity of the genotypic values in the SNP set.