Intelligence in childhood, as measured by psychometric cognitive tests, is a strong predictor of many important life outcomes, including educational attainment, income, health and lifespan. Results from twin, family and adoption studies are consistent with general intelligence being highly heritable and genetically stable throughout the life course. No robustly associated genetic loci or variants for childhood intelligence have been reported. Here, we report the first genome-wide association study (GWAS) on childhood intelligence (age range 6-18 years) from 17?989 individuals in six discovery and three replication samples. Although no individual single-nucleotide polymorphisms (SNPs) were detected with genome-wide significance, we show that the aggregate effects of common SNPs explain 22-46% of phenotypic variation in childhood intelligence in the three largest cohorts (P=3.9 × 10(-15), 0.014 and 0.028). FNBP1L, previously reported to be the most significantly associated gene for adult intelligence, was also significantly associated with childhood intelligence (P=0.003). Polygenic prediction analyses resulted in a significant correlation between predictor and outcome in all replication cohorts. The proportion of childhood intelligence explained by the predictor reached 1.2% (P=6 × 10(-5)), 3.5% (P=10(-3)) and 0.5% (P=6 × 10(-5)) in three independent validation cohorts. Given the sample sizes, these genetic prediction results are consistent with expectations if the genetic architecture of childhood intelligence is like that of body mass index or height. Our study provides molecular support for the heritability and polygenic nature of childhood intelligence. Larger sample sizes will be required to detect individual variants with genome-wide significance.Molecular Psychiatry advance online publication, 29 January 2013; doi:10.1038/mp.2012.184.

Topiramate is an antiepileptic drug that has marked treatment-limiting side effects on specific aspects of cognitive performance in both patients and healthy volunteers. Because these severe side effects occur only in certain individuals, identifying genetic or environmental variables that influence cognitive response would be of great utility in determining whether to administer this drug to a patient. We gave an acute 100 mg oral dose of topiramate to 158 healthy volunteers and measured how the drug changed their performance on a diverse battery of cognitive tests. We found a wide range of responses to topiramate, and we demonstrated that not all tests in the battery were equally affected. There was no correlation between the effect of topiramate and either education level or baseline cognitive performance. Of interest, there was an up to 55-fold variation in the topiramate plasma levels of the participants. Our genome-wide association study (GWAS) of cognitive response did not reveal any genome-wide significant associations; the study was powered to find variants explaining at least 25% of the variation in cognitive response. Combining the results of this GWAS with a retrospective study of cognitive complaints in 290 epilepsy patients who received topiramate as part of their treatment also did not result in a significant association. Our results support the need for additional genetic studies of topiramate that use larger sample sizes.

Increased values of multiple adiposity-related anthropometric traits are important risk factors for many common complex diseases. We performed a genome-wide association (GWA) study for four quantitative traits related to body size and adiposity (BMI, weight, waist circumference, and height) in a cohort of 1,792 adult Filipino women from the Cebu Longitudinal Health and Nutrition Survey (CLHNS). This is the first GWA study of anthropometric traits in Filipinos, a population experiencing a rapid transition into a more obesogenic environment. In addition to identifying suggestive evidence of additional single-nucleotide polymorphism (SNP) association signals (P < 10(-5)), we replicated (P < 0.05, same direction of additive effect) associations previously reported in European populations of both BMI and weight with MC4R and FTO, of BMI with BDNF, and of height with EFEMP1, ZBTB38, and NPPC, but none with waist circumference. We also replicated loci reported in Japanese or Korean populations as associated with BMI (OTOL1) and height (HIST1H1PS2, C14orf145, GPC5). A difference in local linkage disequilibrium (LD) between European and Asian populations suggests a narrowed association region for BDNF, while still including a proposed functional nonsynonymous amino acid substitution variant (rs6265, Val66Met). Finally, we observed significant evidence (P < 0.0042) for age-by-genotype interactions influencing BMI for rs17782313 (MC4R) and rs9939609 (FTO), and for a study year-by-genotype interaction for rs4923461 (BDNF). Our results show that several genetic risk factors are associated with anthropometric traits in Filipinos and provide further insight into the effects of BDNF, FTO, and MC4R on BMI.

Admixture mapping is a recently developed method for identifying genetic risk factors involved in complex traits or diseases showing prevalence differences between major continental groups. Type 2 diabetes (T2D) is at least twice as prevalent in Native American populations as in populations of European ancestry, so admixture mapping is well suited to study the genetic basis of this complex disease. We have characterized the admixture proportions in a sample of 286 unrelated T2D patients and 275 controls from Mexico City and we discuss the implications of the results for admixture mapping studies. Admixture proportions were estimated using 69 autosomal ancestry-informative markers (AIMs). Maternal and paternal contributions were estimated from geographically informative mtDNA and Y-specific polymorphisms. The average proportions of Native American, European and, West African admixture were estimated as 65, 30, and 5%, respectively. The contributions of Native American ancestors to maternal and paternal lineages were estimated as 90 and 40%, respectively. In a logistic model with higher educational status as dependent variable, the odds ratio for higher educational status associated with an increase from 0 to 1 in European admixture proportions was 9.4 (95%, credible interval 3.8-22.6). This association of socioeconomic status with individual admixture proportion shows that genetic stratification in this population is paralleled, and possibly maintained, by socioeconomic stratification. The effective number of generations back to unadmixed ancestors was 6.7 (95% CI 5.7-8.0), from which we can estimate that genome-wide admixture mapping will require typing about 1,400 evenly distributed AIMs to localize genes underlying disease risk between populations of European and Native American ancestry. Sample sizes of about 2,000 cases will be required to detect any locus that contributes an ancestry risk ratio of at least 1.5.