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PISA test documents at a German school (source: Theo Müller). PISA and IQ tests are informing us about differences in intellectual capacity by country. Meanwhile, genetic studies are informing us about genomic differences by country. Davide Piffer has been tapping into these two pools of data to explore the links between genes and intellectual capacity.
Between individuals and populations, intellectual capacity seems to differ through small differences at many genes. This is hardly surprising. Intelligence is a complex trait that involves many different genes interacting with each other and with the environment. If one gene changes, the immediate effect may be beneficial, but there will be side effects at other genes, and most of those side effects will likely be harmful. The bigger the effect at any one gene, the greater the likelihood of negative side effects elsewhere.
So evolution has proceeded through tinkering. A small effect here, a small effect there, but nothing that will rock the boat.
We must therefore pool data from many genes to understand the evolution of complex traits like intelligence. This is what Davide Piffer (2013) has done in a recent study. He began with seven genes (SNPs) whose different alleles are associated with differences in intellectual capacity, as measured by PISA or IQ tests. Then, for fifty human populations, he looked up the prevalences of the alleles that seem to increase intellectual capacity. Finally, for each population, he calculated their average prevalence at all seven genes.
The average prevalence was 39% among East Asians, 36% among Europeans, 32% among Amerindians, 24% among Melanesians and Papuan-New Guineans, and 16% among sub-Saharan Africans. The lowest scores were among San Bushmen (6%) and Mbuti Pygmies (5%). A related finding is that all but one of the alleles seem to be derived. In other words, they are specific to humans and not shared with ancestral primates.
Since these alleles have only small effects on intellectual capacity, there might be other causes for the above geographic pattern. For instance, as modern humans spread out of Africa, older alleles would have gradually given way to newer ones simply through founder effects and other random events. On the other hand, these derived alleles do not reach their highest prevalence in populations that are farthest removed from Africa, like the native inhabitants of the Americas and Oceania. The highest prevalences are actually reached less far away, in Europe and East Asia. Furthermore, the African/non-African difference is much greater for these alleles than for derived alleles in general. Derived alleles typically have a prevalence of 42% among sub-Saharan Africans and 56-57% among East Asians and Europeans (Watkins et al., 2001). This difference is tiny in comparison to the one for alleles that seem to increase intellectual capacity.
Principal component analysis
In this study and in a subsequent one (Piffer, 2014), principal component analysis has shown that a single factor explains much of the variability in the data (45%). Moreover, this one factor correlates highly with average IQ scores (r=0.9) and PISA scores (r=0.8) for each population. A common neural property thus seems to be the target of the various derived alleles. Could it be the elusive g factor?
The existence of such a large factor is further proof that we are dealing with some kind of selection pressure, and not random genetic changes like founder effects. It doesn’t follow, however, that the “unexplained variability” is without significance. Selection for intellectual capacity, like selection for any complex trait, may follow different paths in different cultural contexts. Moreover, there may be tradeoffs between different kinds of mental ability, and these tradeoffs may likewise vary according to the cultural context.
A final caveat
These seven genes are a small subset of the many genes that affect intellectual capacity. They thus provide only a rough picture of how this trait varies within the human species. Nonetheless, this picture is probably not far from reality.
Piffer, D. (2013). Factor analysis of population allele frequencies as a simple, novel method of detecting signals of recent polygenic selection: The example of educational attainment and IQ, Interdisciplinary Bio Central, provisional manuscript
Piffer, D. (2014). Simple statistical tools to detect signals of recent polygenic selection, Interdisciplinary Bio Central, 6, article 1
Watkins, W.S., C.E. Ricker, M.J. Bamshad, M.L. Carroll, S.V. Nguyen, M. A. Batzer, H.C. Harpending, A.R. Rogers, and L.B. Jorde. (2001). Patterns of ancestral human diversity: An analysis of Alu-insertion and restriction-site polymorphisms, American Journal of Human Genetics, 68, 738-752.