An index of population structure (Fst) is used to test the null hypothesis that the genetic factor extracted from GWAS hits represents differences between populations due to migrations and drift. Employing the 1000 Genomes data, a regression of average IQ distances on the general intelligence genetic factor and Fst distances shows that the former is the only significant predictor of IQ distances(Beta= 0.82), whereas the population structure has no independent predictive power (Beta=-0.05). This result suggests that the null hypothesis can be rejected.

Factor analysis of allele frequencies was used to identify signals of polygenic selection on human intelligence. Four SNPs which reached genome-wide significance in previous meta-analyses were used. Allele frequencies for 26 population were obtained from 1000 Genomes. The resulting factor scores were highly correlated to average national IQ (r=0.92). A regression of IQ differences between subcontinental groups on the 4 SNPs g factor and an index of genome-wide genetic distances showed the former was an independent and significant predictor (Beta= 1.14), whereas genome-wide distances lost all predictive power. This finding suggests that the relationship between the 4 SNPs g factor and IQ is due to natural selection on a specific phenotype and not the result of a spurious correlation arising from genome-wide evolutionary processes such as random drift or migrations. A regression of IQs on genetic factor scores of developed countries was used to estimate the predicted genotypic IQs of developing countries. The residuals (difference between predicted and actual scores) were negatively correlated to per capita GDP and Human Development Index, implying that countries with low socioeconomic conditions have not yet reached their full intellectual potential.