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Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children's ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child's cognitive abilities at age twelve.

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BACKGROUND: Dopamine receptor D4(DRD4) polymorphisms have been associated with a number of psychiatric disorders, but little is known about the mechanism of these associations. DNA methylation is linked to the regulation of gene expression and plays a vital role in normal cellular function, with abnormal DNA methylation patterns implicated in a range of disorders. Recent evidence suggests DNA methylation can be influenced by cis-acting DNA sequence variation, that is, DNA sequence variation located nearby on the same chromosome. METHODS: To investigate the potential influence of cis-acting genetic elements within DRD4, we analysed DRD4 promoter DNA methylation levels in the transformed lymphoblastoid cell-line DNA of 89 individuals (from 30 family-trios). Five SNPs located +/- 10kb of the promoter region were interrogated for associations with DNA methylation levels. RESULTS: Four significant SNP associations were found with DNA methylation (rs3758653, rs752306, rs11246228 and rs936465). The associations of rs3758653 and rs936465 with DNA methylation were tested and nominally replicated (p-value < 0.05) in post-mortem brain tissue from an independent sample (N = 18). Interestingly, the DNA methylation patterns observed in post-mortem brain tissue were similar to those observed in transformed lymphoblastoid cell line DNA. CONCLUSIONS: The link reported between DNA sequence and DNA methylation offers a possible functional role to seemingly non-functional SNP associations. DRD4 has been implicated in several psychiatric disease phenotypes and our results shed light upon the possible mode of action of SNP associations in this region.

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Environmental factors such as stress influence both the predisposition to and development of alcoholism, as well as have significant implications for alcoholism relapse. One predominant biological response to acute stress is the release of norepinephrine, which activates the peripheral stress response and also the hypothalamic-pituitary-adrenal axis. We aimed to examine the role of two genes of the adrenergic system (SLC6A2 and ADRA2A) in alcoholism by genotyping 21 SNPs in 785 adult alcohol-dependent patients and 1237 controls. Two single nucleotide polymorphisms (SNP) (rs36020 and rs36029) in SLC6A2 were significantly associated with alcoholism [false discovery rate corrected P-value (FDR) P = 0.007]. Two SNPs in ADRA2A (rs521674 and rs602618) were associated with a positive family history of alcoholism (FDR P ≤ 0.05). A combined SNP-set analysis was also carried out to determine the risk of harbouring multiple alcohol risk alleles across SLC6A2 and ADRA2A. Logistic regression analysis revealed that an increase in the number of alcohol risk alleles increased the risk for alcoholism (P = 0.000567, odds ratio = 1.75, 95% confidence interval 1.26-2.44). A three-SNP haplotype consisting of rs187715, rs36020 and rs40147 alleles, AGC, was also found, which was significantly over-represented in cases compared with controls (61% versus 56%). We therefore demonstrate an association of SLC6A2 and ADRA2A with adult alcoholism. These data confirm the relevance of the adrenergic stress system when considering genetic predisposition to alcohol dependence and suggest that SLC6A2 and ADRA2A should be studied in additional alcohol-dependent cohorts.

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Mathematics ability and disability is as heritable as other cognitive abilities and disabilities, however its genetic etiology has received relatively little attention. In our recent genome-wide association study of mathematical ability in 10-year-old children, 10 SNP associations were nominated from scans of pooled DNA and validated in an individually genotyped sample. In this paper, we use a 'SNP set' composite of these 10 SNPs to investigate gene-environment (GE) interaction, examining whether the association between the 10-SNP set and mathematical ability differs as a function of ten environmental measures in the home and school in a sample of 1888 children with complete data. We found two significant GE interactions for environmental measures in the home and the school both in the direction of the diathesis-stress type of GE interaction: The 10-SNP set was more strongly associated with mathematical ability in chaotic homes and when parents are negative.

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BACKGROUND: The Generalist Genes Hypothesis is based upon quantitative genetic findings which indicate that many of the same genes influence diverse cognitive abilities and disabilities across age. In a recent genome-wide association study of mathematical ability in 10-year-old children, 43 SNP associations were nominated from scans of pooled DNA, 10 of which were validated in an individually genotyped sample. The 4927 children in this genotyped sample have also been studied at 7, 9 and 12 years of age on measures of mathematical ability, as well as on other cognitive and learning abilities. RESULTS: Using these data we have explored the Generalist Genes Hypothesis by assessing the association of the available measures of ability at age 10 and other ages with two composite 'SNP-set' scores, formed from the full set of 43 nominated SNPs and the sub-set of 10 SNPs that were previously found to be associated with mathematical ability at age 10. Both SNP sets yielded significant associations with mathematical ability at ages 7, 9 and 12, as well as with reading and general cognitive ability at age 10. CONCLUSIONS: Although effect sizes are small, our results correspond with those of quantitative genetic research in supporting the Generalist Genes Hypothesis. SNP sets identified on the basis of their associations with mathematical ability at age 10 show associations with mathematical ability at earlier and later ages and show associations of similar magnitude with reading and general cognitive ability. With small effect sizes expected in such complex traits, future studies may be able to capitalise on power by searching for 'generalist genes' using longitudinal and multivariate approaches.

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DNA methylation plays a vital role in normal cellular function, with aberrant methylation signatures being implicated in a growing number of human pathologies and complex human traits. Methods based on the modification of genomic DNA with sodium bisulfite are considered the 'gold-standard' for DNA methylation profiling on genomic DNA; however they require large amounts of DNA and may be prohibitively expensive when used on the large sample sizes necessary to detect small effects. DNA pooling approaches are already widely used in large-scale studies of DNA sequence and gene expression. In this paper, we describe the application of this economical DNA pooling technique to the study of DNA methylation profiles. This method generates accurate quantitative assessments of group DNA methylation averages, reducing the time, cost and amount of DNA starting material required for large-scale epigenetic investigation of disease phenotypes.

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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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BACKGROUND: DNA methylation plays a vital role in normal cellular function, with aberrant methylation signatures being implicated in a growing number of human pathologies and complex human traits. Methods based on the modification of genomic DNA with sodium bisulfite are considered the 'gold-standard' for DNA methylation profiling on genomic DNA; however, they require relatively large amounts of DNA and may be prohibitively expensive when used on the large sample sizes necessary to detect small effects. We propose that a high-throughput DNA pooling approach will facilitate the use of emerging methylomic profiling techniques in large samples. RESULTS: Compared with data generated from 89 individual samples, our analysis of 205 CpG sites spanning nine independent regions of the genome demonstrates that DNA pools can be used to provide an accurate and reliable quantitative estimate of average group DNA methylation. Comparison of data generated from the pooled DNA samples with results averaged across the individual samples comprising each pool revealed highly significant correlations for individual CpG sites across all nine regions, with an average overall correlation across all regions and pools of 0.95 (95% bootstrapped confidence intervals: 0.94 to 0.96). CONCLUSION: In this study we demonstrate the validity of using pooled DNA samples to accurately assess group DNA methylation averages. Such an approach can be readily applied to the assessment of disease phenotypes reducing the time, cost and amount of DNA starting material required for large-scale epigenetic analyses.

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BACKGROUND: Over the last decade, associations between Body Mass Index (BMI) and a variety of candidate genes have been reported, but samples have almost all been limited to adults. The purpose of the present study was to test the developmental origins of some of these associations in a large longitudinal sample of children. METHODS: For 10 single-nucleotide polymorphisms (SNPs) in candidate genes reported to be associated with BMI in adults, we examined associations with BMI in a sample of 5000 children (2500 twin pairs) with BMI data at 4, 7 and 10 years. Association analyses were performed using the Quantitative Transmission Disequilibrium Test and we corrected for multiple testing using the False Discovery Rate. RESULTS: Despite having 80% power to detect associations that account for as little as 0.2% of the variance of BMI, none of the 10 SNPs were significantly associated with BMI at any age, although two SNPs showed trends in the expected direction. CONCLUSION: The lack of association for these ten previously reported associations, despite our large sample size, is typical of associations between candidate genes and complex traits. However, some of the reported SNP associations with BMI might emerge as we continue to follow the sample into adolescence and adulthood. This report highlights the importance of developmentally appropriate candidate genes.

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BACKGROUND: Genetic influences underpinning complex traits are thought to involve multiple quantitative trait loci (QTLs) of small effect size. Detection of such QTL associations requires systematic screening of large numbers of DNA markers within large sample populations. Using pooled DNA on SNP microarrays to screen for allelic frequency differences between groups such as cases and controls (called SNP Microarray and Pooling, or SNP-MaP) has been validated as an efficient solution on both 10 k and 100 k platforms. We demonstrate that this approach can be effectively applied to the truly genomewide Affymetrix GeneChip Mapping 500 K Array. RESULTS: In comparisons between five independent DNA pools (N ~200 per pool) on separate Affymetrix GeneChip Mapping 500 K Array sets, we show that, for SNPs with minor allele frequencies > 0.05, the reliability of the rank order of estimated allele frequencies, assessed as the average correlation between allele frequency estimates across the DNA pools, was 0.948 (average mean difference across the five pools = 0.069). Similarly, validity of the SNP-MaP approach was demonstrated by a rank-order correlation of 0.937 (average mean difference = 0.095) between the average DNA pool allele frequency estimates and the allele frequencies of an independent (CEPH) sample of 60 unrelated individually genotyped subjects. CONCLUSION: We conclude that SNP-MaP can be extended for use on the Affymetrix GeneChip Mapping 500 K Array, providing a cost-effective, reliable and valid initial screen of 500 K SNP microarrays in genomewide association scans.

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