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A three-stage genome-wide association study of general cognitive ability: hunting the small effects.

Davis OS, Butcher LM, Docherty SJ, Meaburn EL, Curtis CJ, Simpson MA, Schalkwyk LC, Plomin R - Behav. Genet. (2010)

Bottom Line: Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample.However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association.Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci.

View Article: PubMed Central - PubMed

Affiliation: Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK. Oliver.Davis@iop.kcl.ac.uk.

ABSTRACT
Childhood general cognitive ability (g) is important for a wide range of outcomes in later life, from school achievement to occupational success and life expectancy. Large-scale association studies will be essential in the quest to identify variants that make up the substantial genetic component implicated by quantitative genetic studies. We conducted a three-stage genome-wide association study for general cognitive ability using over 350,000 single nucleotide polymorphisms (SNPs) in the quantitative extremes of a population sample of 7,900 7-year-old children from the UK Twins Early Development Study. Using two DNA pooling stages to enrich true positives, each of around 1,000 children selected from the extremes of the distribution, and a third individual genotyping stage of over 3,000 children to test for quantitative associations across the normal range, we aimed to home in on genes of small effect. Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample. However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association. These replications may take advantage of SNP sets to overcome limitations of statistical power. Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci. Larger samples, denser arrays and multiple replications will be necessary in the hunt for the genetic variants that influence human cognitive ability.

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Related in: MedlinePlus

A SNP set for g at 7 years of age. The SNP set is formed from the nominally associated SNPs from Table 1 by counting the number of alleles associated with high g in each individual. Because rs10997145 is significantly non-additive, it was scored 0, 2 and 2 instead. The points represent mean g scores and the line represents the regression of the g score on the SNP set score. The underlying bar chart shows the number of individuals with each SNP set score. The graph runs from 6 to 16 rather than from 0 to 18, because there were no individuals with SNP set scores of 0 to 5 or 17 to 18
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Fig3: A SNP set for g at 7 years of age. The SNP set is formed from the nominally associated SNPs from Table 1 by counting the number of alleles associated with high g in each individual. Because rs10997145 is significantly non-additive, it was scored 0, 2 and 2 instead. The points represent mean g scores and the line represents the regression of the g score on the SNP set score. The underlying bar chart shows the number of individuals with each SNP set score. The graph runs from 6 to 16 rather than from 0 to 18, because there were no individuals with SNP set scores of 0 to 5 or 17 to 18

Mentions: Bearing in mind these caveats, the enrichment of low P values in the second (and third) stage suggest that at least some of the SNPs we selected are likely to show true association with g. One tool that may assist in exploring and replicating these weak associations is the SNP set. Creating a SNP set involves coding a group of putatively associated SNPs in the same direction by counting the number of high-g-associated alleles carried by each individual at each locus and summing the score across loci. To demonstrate, we created a SNP set using the 9 SNPs from the third stage of the analysis that were associated with g at the nominal significance level of P < 0.05 (Fig. 3). This SNP set correlates r = 0.11 with g, accounting for 1.2% of the variance. Or, to put it another way, each additional high-g associated allele increases g by 0.06 standard deviations or 0.92 IQ points. However, these calculations involve some members of the discovery population, so effect size estimates are likely to be smaller in an independent sample because of the winner’s curse (Lohmueller et al. 2003). A SNP set score may be used for attempted replication in samples that, because of the expected small effect sizes, do not have sufficient power to replicate individual SNP associations. For example, a sample of over 4,500 would be required to replicate the individual SNPs within the SNP set (accounting for a mean 0.136% of the variance) with 80% power at α = 0.05. However, a sample of just over 500 is required to attempt replication of the SNP set. SNP set scores may also be used for behavioural genomic analyses that explore developmental, multivariate and gene-environment issues (Harlaar et al. 2005; Haworth et al. 2007).Fig. 3


A three-stage genome-wide association study of general cognitive ability: hunting the small effects.

Davis OS, Butcher LM, Docherty SJ, Meaburn EL, Curtis CJ, Simpson MA, Schalkwyk LC, Plomin R - Behav. Genet. (2010)

A SNP set for g at 7 years of age. The SNP set is formed from the nominally associated SNPs from Table 1 by counting the number of alleles associated with high g in each individual. Because rs10997145 is significantly non-additive, it was scored 0, 2 and 2 instead. The points represent mean g scores and the line represents the regression of the g score on the SNP set score. The underlying bar chart shows the number of individuals with each SNP set score. The graph runs from 6 to 16 rather than from 0 to 18, because there were no individuals with SNP set scores of 0 to 5 or 17 to 18
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2992848&req=5

Fig3: A SNP set for g at 7 years of age. The SNP set is formed from the nominally associated SNPs from Table 1 by counting the number of alleles associated with high g in each individual. Because rs10997145 is significantly non-additive, it was scored 0, 2 and 2 instead. The points represent mean g scores and the line represents the regression of the g score on the SNP set score. The underlying bar chart shows the number of individuals with each SNP set score. The graph runs from 6 to 16 rather than from 0 to 18, because there were no individuals with SNP set scores of 0 to 5 or 17 to 18
Mentions: Bearing in mind these caveats, the enrichment of low P values in the second (and third) stage suggest that at least some of the SNPs we selected are likely to show true association with g. One tool that may assist in exploring and replicating these weak associations is the SNP set. Creating a SNP set involves coding a group of putatively associated SNPs in the same direction by counting the number of high-g-associated alleles carried by each individual at each locus and summing the score across loci. To demonstrate, we created a SNP set using the 9 SNPs from the third stage of the analysis that were associated with g at the nominal significance level of P < 0.05 (Fig. 3). This SNP set correlates r = 0.11 with g, accounting for 1.2% of the variance. Or, to put it another way, each additional high-g associated allele increases g by 0.06 standard deviations or 0.92 IQ points. However, these calculations involve some members of the discovery population, so effect size estimates are likely to be smaller in an independent sample because of the winner’s curse (Lohmueller et al. 2003). A SNP set score may be used for attempted replication in samples that, because of the expected small effect sizes, do not have sufficient power to replicate individual SNP associations. For example, a sample of over 4,500 would be required to replicate the individual SNPs within the SNP set (accounting for a mean 0.136% of the variance) with 80% power at α = 0.05. However, a sample of just over 500 is required to attempt replication of the SNP set. SNP set scores may also be used for behavioural genomic analyses that explore developmental, multivariate and gene-environment issues (Harlaar et al. 2005; Haworth et al. 2007).Fig. 3

Bottom Line: Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample.However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association.Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci.

View Article: PubMed Central - PubMed

Affiliation: Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, UK. Oliver.Davis@iop.kcl.ac.uk.

ABSTRACT
Childhood general cognitive ability (g) is important for a wide range of outcomes in later life, from school achievement to occupational success and life expectancy. Large-scale association studies will be essential in the quest to identify variants that make up the substantial genetic component implicated by quantitative genetic studies. We conducted a three-stage genome-wide association study for general cognitive ability using over 350,000 single nucleotide polymorphisms (SNPs) in the quantitative extremes of a population sample of 7,900 7-year-old children from the UK Twins Early Development Study. Using two DNA pooling stages to enrich true positives, each of around 1,000 children selected from the extremes of the distribution, and a third individual genotyping stage of over 3,000 children to test for quantitative associations across the normal range, we aimed to home in on genes of small effect. Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample. However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association. These replications may take advantage of SNP sets to overcome limitations of statistical power. Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci. Larger samples, denser arrays and multiple replications will be necessary in the hunt for the genetic variants that influence human cognitive ability.

Show MeSH
Related in: MedlinePlus