Davide Piffer
pifferdavide@gmail.com
I recently posted a pretty detailed account of my analysis of the new intelligence GWAS, based on the latest GWAS of intelligence. (Un)surprisingly, the estimates of genotypic intelligence (or actually to be precise, of polygenic selection strength, because genotypic intelligence also includes non-additive components) are almost identical to those from my previous 2013 and 2015 studies. By this, I mean that the factor and polygenic score I had estimated for 26 populations in 2015 are almost identical (r=0.96-0.99) to the factor extracted from the new intelligence GWAS (18 SNPs) and from a factor extracted by pooling together the hits from two educational attainment GWAS published after my 2015 study (9 replicated genomic loci), see my paper for more details. This is called a successful replication. Since the old and new results are almost identical, I report the post-2015 factor scores. Robustness of the findings is supported by Monte Carlo simulation using REAL SNPs (not computer-generated junk), which is the best technique to test the robustness of these findings, since it includes all possible sorts of confounding factors (LD decay, spatial autocorrelation, etc.) in one omnibus test.
Table 1. Factor scores for educational attainment and intelligence
| Population | G Factor score (18 SNPs) | EA factor score (9 SNPs) |
| Afr.Car.Barbados | -1.276 | -1.351 |
| US Blacks | -0.961 | -1.177 |
| Bengali Bangladesh | -0.075 | -0.209 |
| Chinese Dai | 1.35 | 1.017 |
| Utah Whites | 0.844 | 0.471 |
| Chinese, Bejing | 1.109 | 1.511 |
| Chinese, South | 1.208 | 1.382 |
| Colombian | 0.357 | 0.01 |
| Esan, Nigeria | -1.66 | -1.453 |
| Finland | 0.771 | 0.702 |
| British, GB | 0.797 | 0.745 |
| Gujarati Indian, Tx | -0.049 | 0.271 |
| Gambian | -1.358 | -1.397 |
| Iberian, Spain | 0.631 | 0.35 |
| Indian Telegu, UK | -0.074 | 0.049 |
| Japan | 0.878 | 1.342 |
| Vietnam | 1.267 | 1.346 |
| Luhya, Kenya | -1.599 | -1.488 |
| Mende, Sierra Leone | -1.444 | -1.403 |
| Mexican in L.A. | 0.215 | 0.056 |
| Peruvian, Lima | -0.06 | 0.05 |
| Punjabi, Pakistan | 0.066 | 0.24 |
| Puerto Rican | 0.375 | -0.004 |
| Sri Lankan, UK | -0.391 | 0.134 |
| Toscani, Italy | 0.764 | 0.248 |
| Yoruba, Nigeria | -1.684 | -1.443 |
Some may remember I also published factors derived from ALFRED, whose sample is bigger than 1000 Genomes (50-75 populations), but the coverage is much weaker.
I looked up the 18 intelligence GWAS SNPs and the 9 EA quasi-replicated SNPs and could find 4 in ALFRED. Factor analysis was run on them, producing a very interesting factor. For ease of interpretation, I report results ranked from highest to lowest:
| Continent | Population | Factor |
| EastAsia | Tujia | 1.507 |
| East Asia | Mongolian | 1.358 |
| EastAsia | Daur | 1.246 |
| EastAsia | Yi | 1.19 |
| EastAsia | Koreans | 1.127 |
| EastAsia | Miao | 1.078 |
| EastAsia | Japanese | 1.018 |
| EastAsia | Dai | 0.987 |
| EastAsia | Hezhe | 0.98 |
| EastAsia | Han | 0.936 |
| EastAsia | Lahu | 0.877 |
| EastAsia | Tu | 0.828 |
| EastAsia | Xibe | 0.802 |
| Europe | Orcadian | 0.753 |
| EastAsia | She | 0.737 |
| EastAsia | Uyghur | 0.566 |
| Asia | Hazara | 0.506 |
| Asia | Kalash | 0.475 |
| Asia | Oroqen | 0.445 |
| Europe | Italians_N | 0.437 |
| Europe | Italians_C | 0.404 |
| SE Asia | Cambodians, Khmer | 0.34 |
| Siberia | Yakut | 0.311 |
| Europe | Adygei | 0.257 |
| Asia | Druze | 0.254 |
| Europe | French | 0.217 |
| Asia | Burusho | 0.151 |
| EastAsia | Naxi | 0.113 |
| Europe | Russians | 0.073 |
| Asia | Balochi | 0.055 |
| Asia | Palestinian | -0.071 |
| Europe | Basque | -0.088 |
| Asia | Bedouin | -0.156 |
| Europe | Sardinian | -0.225 |
| Asia | Brahui | -0.334 |
| Asia | Pashtun | -0.426 |
| Asia | Sindhi | -0.438 |
| Oceania | Melanesian, Nasioi | -0.533 |
| Oceania | Papuan New Guinean | -0.569 |
| Africa | Mozabite | -0.768 |
| Africa | Mandenka | -1.153 |
| Africa | Yoruba | -1.27 |
| NorthAmerica | Maya, Yucatan | -1.3 |
| NorthAmerica | Pima, Mexico | -1.312 |
| SouthAmerica | Amerindians | -1.366 |
| Africa | Biaka | -1.369 |
| Africa | Bantu Kenya | -1.381 |
| SouthAmerica | Surui | -1.382 |
| Africa | Mbuti | -1.415 |
| Africa | Bantu SA | -1.454 |
| Africa | San | -1.488 |
| SouthAmerica | Karitiana | -1.53 |
We see the that East Asians are at the top. Mongolic tribes from the north, such as Mongolians and the Daur, occupy the top positions. These populations live in really cold climates, and would provide suggestive evidence to the cold winter theory. The Siberian Yakut however, do not fare as well as the East Asians, despite living in cold climates. However, the Yakut are not a Mongolic tribe, but they belong to the Turkic ethnic group.
ALFRED has data from groups not present in 1000 Genomes, such as the Amerindian tribes or the Oceanians.
Let’s have a look at the sub-continental average factor scores:
| Continent | Factor |
| E Asia | 0.959 |
| SE Asia | 0.34 |
| Siberia | 0.311 |
| Europe | 0.293 |
| M East | 0.009 |
| W Asia | -0.002 |
| Oceania | -0.551 |
| North Africa | -0.768 |
| Sub-S. Africa | -1.287 |
| America | -1.378 |
Native Americans and Africans occupy the lowest places, despite being genetically very different. The Native American result is a huge problem for people who want to explain the pattern in term of drift or migrations, because despite being the closest genetically to the East Asians, they are at the opposite of the spectrum in terms of factor scores.
This also suggests that whatever created the East Asian advantage happened after 15kya (the earliest estimate of a migration across the Bering strait into the Americas). It is possible that the extremely low population density in the Americas reduced intraspecific competition, hence selection pressure on higher intelligence was lower.
I calculated the correlation between distance from Eastern Africa (Addis Ababa) and factor scores and this was negative (around -0.45), not supporting the novel environment hypothesis a la Kanazawa.
It seems that what caused different selection pressures on different populations is a mix of cold winters, population size and gene-culture co-evolution.
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