Saturday, April 23, 2016


Summary: Over the past 5 years, a variety of specific genes have been shown to influence IQ. Versions of these genes which lead to higher intelligence are consistently found to be more common in Whites than in Blacks. The difference between Asians and Whites is less clear. The consistency of these findings, which have been replicated across two genetic databases, makes an egalitarian view of racial intelligence differences implausible. This research also suggests that selection, instead of genetic drift, causes racial intelligence differences because IQ-related genes are more racially differentiated than most genes are. In fact, they are more racially differentiated than height related genes are, suggesting that selection for racial intelligence differences was stronger than selection for racial height differences.
When I first started looking into race realism, no one had any idea what specific genes might explain racial differences in intelligence. Happily, that situation is changing. A ground breaking 2015 paper by David Piffer of the Ulster Institute for Social Research looked at population level differences in the frequency of all 9 gene variants which, as of July 2015, had been reliably associated with intelligence. This post will describe that paper.
1. IQ-related Genes
To begin with, let’s look at how these 9 genetic variants, called SNPs, were shown to relate to IQ. These SNPs were studies across 7 studies, each of which is described below:
Reitvald et al (2013) measured two phenotypes. The first, years of education completed, had a discovery sample size of 101,069. The second, a binary variable measuring whether or not the person has completed college, had a sample size of 95,427. Both samples only included Whites. 3 SNPs were found to predict both phenotypes in the discovery and replication samples. These three SNPs explained .022% of educational variance. Each SNP was associated with an extra month of education and a 1.8% increase in the chance of completing college.
Ward (2014) had a sample of 5,979 individuals, who were genotyped and took an English SAT test, while 6,145 were genotyped and took a math SAT. The participants were between 13 and 14 years old. All participants were White and 4 principal components of SNP co-variance were extracted. The top 3 SNPs identified with Rietvald et al (2013) were found to significantly predict SAT scores. Each allele was associated with an average increase of .041 standard deviations in English scores and .028 standard deviations increase in math scores.
Reitvald et al (2014) involved three samples. One contained 107,736 individuals and measured educational attainment. Another contained 24,189 individual and measured general intelligence. A third sample contained 8,652 old individuals for whom dementia and memory was measured. It found three SNPs associated with educational attainment which were also found, in a separate sample, to be associated with intelligence. Each SNP predicted an increase of 0.3 IQ points. However, one of these SNPs was highly correlated with other SNPs in this analysis and was therefore dropped.
Davies et al (2015) utilized three samples (Ns= 53,949, 5,976, and 5,487) which were genotyped and had their general intelligence measured. All participants were White, sex was controlled for, and 4 principal components of SNP co-variance were extracted. 13 SNPs were found to predict cognitive ability at P<.0000001. These SNPs were spread across three chromosome regions. The top three SNPs, one from each region, explained between .19% and 1.27% of intelligence variance in the replication samples. These three SNPs were used in Piffer’s analysis.
Ibrahim-Verbaas (2015) utilized 40 samples. 20 of them were involved in the discovery phase and ranged in size from 5,429 to 32,070. The other 20 were used as replication samples and ranged in size from 1,311 to 21,860. The phenotypes looked at were executive functioning and processing speed. Each sample was entirely made of one race, however, some were all Black and others were all White. One SNP, rs17518584, was found to be a significant and replicated predictor.
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