European Hair, Eye, and Skin Color: Solving the Puzzle

 

The distinguishing physical features of Europeans began as female features.

 

I’ve published a book through Academica Press. It’s titled: European Hair, Eye, and Skin Color: Solving the Puzzle. It can be ordered at: https://www.academicapress.com/node/549  

 

Here is a summary:

 

 

Europeans are strangely colored, particularly in the north and east. Hair is not only black but also brown, flaxen, golden, or red. Eyes are not only brown but also blue, gray, hazel, or green. Finally, skin is white, almost like that of an albino.

 

That color scheme is strange for several reasons:

 

·        It arose through new alleles at unrelated genes: hair color diversified through a proliferation of new alleles at MC1R, and eye color through a proliferation of new alleles in the HERC2-OCA2 region. Skin color became fair through new alleles at SLC45A2, SLC24A5, and TYRP1. All three changes occurred in parallel at different loci on the genome.

 

·        The new hair and eye color alleles are too numerous and too recent to be due to anything but strong selection. Among Europeans, the various hair colors are produced by new alleles at over 200 loci (SNPs), and the various eye colors by new alleles at over 124. Those alleles arose over a relatively short span of time, certainly less than the 50,000 years that modern humans have been in Europe. Only some kind of selection, and very strong selection at that, could have caused such a proliferation of new alleles over such a short time.

 

·        The selection was aimed primarily at women. Even today, women naturally have a higher incidence of red hair, blonde hair, and green eyes. Hair and eye colors are more evenly distributed among women: the less frequent colors are more common, and the more frequent ones less common. Skin is also fairer in women.

 

·        The new colors are mostly on or near the face, the focus of visual attention. When compared with the original black and brown, they are brighter and “purer” (they occupy thinner slices of the visible spectrum). Brightness and purity are characteristic of colors favored by sexual selection. A third characteristic is novelty: the relative rarity of a color. Novelty improves mating success by attracting attention and interest, but that success is eventually its undoing. As each generation passes, it becomes more common and less novel. Other colors attract more interest, particularly new ones that arise through mutation, with the result that a growing number of color variants accumulate in the gene pool. Such color polymorphisms are a frequent outcome of sexual selection.

 

·        Unlike the hair and the eyes, the skin did not develop a color polymorphism among Europeans, instead becoming unusually pale. The reason may be that sexual selection was guided by a pre-existing dimorphism. In all populations, men are browner and ruddier than women, who by comparison are fairer. Fairer-skinned women were seen as more feminine in traditional cultures and preferred as mates. Sexual selection, if sufficiently strong, would have drained the European gene pool of alleles for dark skin.

 

Sexual selection is not the preferred explanation among writers on this subject. Most lean toward one of two scenarios that involve natural selection:

 

·        Relaxation of selection for dark skin: when modern humans entered Europe, natural selection stopped favoring dark skin because UV protection was less necessary at northern latitudes. Defective alleles for skin pigmentation began to accumulate in the gene pool, and some of them had effects on hair and eye color.

 

That scenario has two weak points:

 

o   Relaxation of selection would take more than a million years to produce the current diversity of hair and eye colors. Yet modern humans have been in Europe for only 50,000 years. In fact, it was only around 20,000 years ago that some Europeans began to acquire pale skin and diverse hair and eye colors, and that phenotype would not become fully established throughout Europe until 10,000 to 5,000 years ago.

o   Skin color is weakly linked to hair color and eye color. Light skin often coexists with dark hair and dark eyes.

 

·        Selection for light skin: natural selection reduced skin pigmentation in order to maintain sufficient production of vitamin D. The hair and the eyes underwent a similar reduction in pigmentation because a change to one pigmentary trait presumably affects the others.

 

That scenario has two weak points:

 

o   Again, skin color is weakly linked to hair color and eye color. Yet the changes to the latter have been as profound as those to skin color. Moreover, the changes to hair and eye color have not been so much a reduction in pigmentation as a non-random creation of new hues that emit more light within narrower slices of the spectrum.

o   Analysis of ancient DNA and present-day DNA indicates that modern humans were dark-skinned for tens of thousands of years after their entry into Europe. Why wasn’t vitamin D a problem then? If we consider the indigenous inhabitants of North and South America, we see that natural selection has created very little latitudinal variation in their skin color, even though they have lived in the Americas for some 12,000 years. Natural selection, by itself, appears to change skin color rather slowly.

 

The current physical features of Europeans seem to have arisen on the steppe-tundra of eastern Europe and western Siberia during the last ice age, between 10,000 and 20,000 years ago, when nomadic humans subsisted almost entirely on meat from reindeer and other migratory game. Long-distance hunting increased the death rate among men and decreased the polygyny rate—only the ablest hunters could provide for more than one woman and her children because women had almost no food autonomy. 

The result: a surplus of women on the mate market; intense rivalry among them for male attention; and strong selection for eye-catching female features. Such features became more frequent with succeeding generations, eventually forming what is now seen as the “European” phenotype.

 

 

Frost, P. (2022). European Hair, Eye, and Skin Color: Solving the Puzzle. Washington: Academica Press, 169 pp., hardcover, ISBN 9781680538724

 

If you wish to buy a less expensive paperback edition, please make your preference known to Academica Press by emailing to:

academicapress.editorial@gmail.com

 

 

 

 

 

Recent cognitive evolution in Europe: a new study of ancient DNA

 

Polygenic scores for alleles associated with educational attainment - Europeans of different time periods (Kuijpers et al. 2022)

 

According to a new study of ancient European DNA, cognitive evolution stagnated after the last ice age and then speeded up with the rise of farming. It stagnated again during Antiquity and then speeded up again sometime between then and now.

 

 

In my last post, I mentioned an ancient DNA study of 99 genomes from sites across Europe and Central Asia. It showed an apparent increase in mean cognitive ability between 4,560 and 1,210 years ago, as measured by alleles associated with educational attainment (Woodley et al. 2017).

 

That finding has been partially replicated by a new study of 827 genomes from ancient European remains and 250 genomes from modern Europeans. It looks like cognitive evolution stagnated after the last ice age and then speeded up with the rise of farming. It stagnated again during Antiquity and then speeded up again sometime between then and now:

 

Interestingly, while the period between the Early Upper Paleolithic and the Neolithic is characterized by stagnation or slight decrease in PRS related to intelligence, the genetic data show a clear increase in the scores for educational attainment, intelligence, and fluid intelligence from the Neolithic onwards, while the traits related with unipolar depression tend to decrease from that era on. The most significant differences can be observed comparing the pre-Neolithic and Neolithic groups, as well as the post-Neolithic and modern groups, whereas the period between the Neolithic and post-Neolithic shows a very constant distribution of PRS scores. (Kuijpers et al. 2022).

 

The authors define the time periods as follows:

 

Early Upper Paleolithic era – before 28,000 years BC

Late Upper Paleolithic era – 28,000 to 11,000 BC

Mesolithic - 11,000 to 5500 BC

Neolithic - 8,500 to 3900 BC

Post-Neolithic - 5000 BC and more recent ages (no end date given)

Modern – circa 1950 AD

 

The Mesolithic, the Neolithic, and the Post-Neolithic overlap a lot with each other. This is because their boundaries are defined by cultural changes that came to different parts of Europe at different times. The Neolithic began when hunting and gathering gave way to farming, which came later to northern Europe. Similarly, the post-Neolithic began with the advent of metallurgy, which likewise came later to northern Europe.

 

Such overlap is problematic for three reasons:

 

·         In some cases, there is uncertainty as to whether the ancient DNA came from the remains of hunter-gatherers or those of farmers.

·         “Hunter-gatherer” is not a homogeneous category. It includes not only small nomadic groups but also the hunter-fisher-gatherers of the Baltic and North Sea, who attained a degree of sedentism, population growth, and social complexity that we normally associate with farmers (Price 1991).

·         The Post-Neolithic is too long to be meaningful. It covers all of recorded history, and then some.

 

The study’s authors could have divided the Post-Neolithic into smaller time periods to give us a better look at changes during historical times. In particular, did cognitive evolution regress during Classical Antiquity? That was the preliminary finding of a team led by Michael Woodley of Menie (2019) in a study of ancient DNA from Greece. They found that mean cognitive ability increased from the Neolithic to the Mycenaean period and then decreased sometime between the latter and the present day. That study was never published, perhaps because the geographic area and the time periods were too small to provide robust results.

 

To get more robust results, we could look at ancient DNA from the entire Greco-Roman world, perhaps divided into three time periods: 5000 to 1000 BC; 1000 to 0 BC; and 0 to 500 AD. Was there a large increase in mean cognitive ability followed by an equally large decrease? Or was there simply a long period of stagnant evolution?

 

In a previous post, I argued that the culture of Classical Antiquity, particularly in its later stages, caused cognitive evolution to regress (Frost 2022). There were several reasons:

 

·         A decline in fertility and family formation, particularly among the upper classes;

·         A corresponding increase in female hypergamy, often by freed slaves, which reduced the reproductive importance of upper-class women;

·         An increase in the foreign slave population, which disrupted cognitive evolution within the local population. Even if there had been demographic overflow from the upper classes, that overflow could not have replaced the lower classes, since those classes were being replaced from external sources.

 

We need a clearer picture. According to the current data, it looks like cognitive evolution simply stagnated during the Post-Neolithic, but I suspect that time period is so broadly defined that it conceals a regression during the centuries before the fifth century collapse and the centuries immediately after.

 

References

 

Frost, P. (2022). When did Europe pull ahead? Evo and Proud, May 16. http://evoandproud.blogspot.com/2022/05/when-did-europe-pull-ahead.html

 

Kuijpers, Y., J. Domínguez-Andrés, O.B. Bakker, M.K. Gupta, M. Grasshoff, C.J. Xu, Joosten LAB, J. Bertranpetit, M.G. Netea, and Y. Li. (2022). Evolutionary Trajectories of Complex Traits in European Populations of Modern Humans. Frontiers in Genetics 13: 833190. https://doi.org/10.3389/fgene.2022.833190

 

Price, T.D. (1991). The Mesolithic of Northern Europe. Annual Review of Anthropology, 20, 211-233. Price, T. D. (1983). The European Mesolithic. American Antiquity 48(4), 761–778. https://doi.org/10.2307/279775  

 

Woodley, M.A., S. Younuskunju, B. Balan, and D. Piffer. (2017). Holocene selection for variants associated with general cognitive ability: comparing ancient and modern genomes. Twin Research and Human Genetics 20: 271-280. https://doi.org/10.1017/thg.2017.37

 

Woodley of Menie, M.A., J. Delhez, M. Peñaherrera-Aguirre, and E.O.W. Kirkegaard. (2019). Cognitive archeogenetics of ancient and modern Greeks. London Conference on Intelligence 

https://www.youtube.com/watch?v=UES_tpDxz9A  

When did Europe pull ahead?

 

Medieval market – Nicole Oresme (15th century) (Wikicommons)

 

In terms of GDP per capita growth, northwest Europe began to surpass the rest of the world during the 14th century: before the conquest of the Americas, the invention of printing, the Atlantic slave trade, and the Protestant Reformation.

 

 

In a recent post, Steve Sailer asks why the European world pulled ahead of the non-European world between 1000 and 1500 AD:

 

[…] much of the non-European world entered a sort of cultural recession well before Europeans directly interfered with them. If you look at, say, Charles Murray’s 2003 book Human Achievement, several major non-European civilizations appear to have lost momentum in making progress in the arts and sciences over roughly the time period of 1000 or maybe 1250 to 1500. (Sailer 2022)

 

For Steve, the reason was the collapse of the Mongol Empire during the 14th century. That century was indeed a turning point for Europe, particularly for England and Holland:

 

These North Sea economies experienced sustained GDP per capita growth for six straight centuries. The North Sea begins to diverge from the rest of Europe long before the 'West' begins its more famous split from 'the rest.'

 

[...] we can pin point the beginning of this 'little divergence' with greater detail. In 1348 Holland's GDP per capita was $876. England's was $777. In less than 60 years time Holland's jumps to $1,245 and England's to 1090. The North Sea's revolutionary divergence started at this time. (Greer 2013b)

 

This process began before the European conquest of the Americas, the invention of printing, the creation of modern finance institutions, the Atlantic slave trade, or the Protestant Reformation. None of these can be proper explanations for this "little divergence." (Greer 2013a; see also Thompson 2012 and Hbd *chick 2013).

 

The divergence began within a part of Europe that was much less affected by the rise and fall of the Mongol Empire. Moreover, if we compare southern Europe with North Africa during the same period, we see the same divergence that we see more generally between Christian Europe and the rest of the world. Yet North Africa was never conquered by the Mongols.

 

It looks like internal causes were responsible for the divergence between Christian Europe and the rest of the world. Those causes seem to have their point of origin in northwest Europe during the long period from 500 to 1500 AD. In that region, the Western Church consolidated a pre-existing pattern of small, nuclear households, weak family ties, and residential mobility, thus strengthening a mindset of individualism and impersonal sociality (Frost 2020; Schulz et al. 2019). Then, from 1000 AD onward, the Western Church strove to pacify social relations (Frost and Harpending 2015). Those two factors—an individualistic mindset operating in a pacified social environment—allowed the market economy to expand into all areas of life and eventually replace kinship as the main organizing principle of society (Frost 2020; Macfarlane 1978; Weber 1930).

 

The expansion of the market economy went hand in hand with the expansion of the middle class. In England, this class began to expand in the twelfth century and would gradually replace the lower classes through downward mobility. By the 1800s, its lineages accounted for most of the English population. English society thus became more middle class in its values: "Thrift, prudence, negotiation, and hard work were becoming values for communities that previously had been spendthrift, impulsive, violent, and leisure loving" (Clark 2007, p. 166). The same process took place elsewhere in Western Europe and more generally throughout Europe to varying degrees and over different timescales (Frost 2019, p. 176).

 

In sum, between 500 and 1500 AD the Western Church created a system of social reproduction that would have far-reaching demographic, behavioral, and economic consequences. To understand that system, one must understand not only the Bible but also the writings of early and medieval Christianity, as well as the pagan Germanic elements it incorporated (Russell 1994). Finally, one must understand the preceding system, and its failings.

 

The pre-Christian world: demographic and cognitive decline

 

Ancient DNA from Greece suggests that mean cognitive ability began to decline at some point during Classical Antiquity (Woodley of Menie et al. 2019). A similar decline probably happened throughout the Mediterranean basin and the Middle East of that time.

There were three main causes:

 

·         A decline in fertility and family formation, particularly among the upper classes (Caldwell 2004; Hopkins 1965; Roetzel 2000, p. 234);

·         A corresponding increase in female hypergamy, often by freed slaves, which reduced the reproductive importance of upper-class women (Perry 2013);

·         An increase in the slave population, particularly foreign slaves (Harris 1999). This ongoing influx disrupted the process of local cognitive evolution. Even if there had been demographic overflow from the upper classes, that overflow could not have replaced the lower classes, since those classes were being replaced from external sources.

 

Christianity and Islam both tried to correct the ruinous demographic state of the ancient world. Islam succeeded in reversing negative population growth but failed to restart cognitive evolution. In some ways, it made such evolution more difficult. Islam increased female hypergamy by permitting male polygamy, thus further reducing the reproductive importance of upper-class women (van den Berghe 1960). Foreign slaves were also imported on a larger-scale than in antiquity, thus further disrupting local cognitive evolution (Lewis 1990). Finally, the upper classes tended to congregate in urban areas, where the death rate was higher.

 

Before the 20th century, population growth had been sluggish in the Muslim world. Wherever Muslims coexisted with Christians, the latter community was often the one that grew at a faster pace. This was the case in the Balkans:

 

By the end of the eighteenth century the Muslim population had entered a period of comparative economic and moral decline. Several explanations have been offered for this development. Certainly the fact that the Muslim population provided the soldiers contributed to its ultimate weakening. Their concentration in towns also made them more susceptible to the ravages of plague and other diseases. Turkish customs, particularly the practice of polygamy, played a part. This process of decay was clearly illustrated in the eighteenth century in the changing demography of the Balkan towns where Christian and national elements formed an increasingly larger proportion of the population (Jelavich and Jelavich, 1977, pp. 6-7)

 

Christianity, especially Western Christianity, succeeded not only in promoting population growth but also in restarting cognitive evolution, specifically by supporting the formation of monogamous families, by discouraging slavery, at least during the long period from 500 to 1500 AD, and eventually by creating the peace, order, and stability that allowed the middle class to expand and become dominant. The rise of Christian Europe actually began before its expansion into the Americas and Asia. The latter was, in fact, a consequence of the former.

 

References

 

Caldwell, J.C. (2004). Fertility control in the classical world: Was there an ancient fertility transition?  Journal of Population Research 21:1. https://doi.org/10.1007/BF03032208  

 

Clark, G. (2007). A Farewell to Alms. A Brief Economic History of the World. Princeton University Press: Princeton.

 

Frost, P. (2019). The Original Industrial Revolution. Did Cold Winters Select for Cognitive Ability? Psych 1(1): 166-181. https://doi.org/10.3390/psych1010012

 

Frost, P. (2020). The large society problem in Northwest Europe and East Asia. Advances in Anthropology 10(3): 214-134. https://doi.org/10.4236/aa.2020.103012   

 

Frost, P. and H. Harpending. (2015). Western Europe, state formation, and genetic pacification. Evolutionary Psychology 13(1): 230-243. https://doi.org/10.1177%2F147470491501300114

 

Greer, T. (2013a). The Rise of the West: Asking the Right Questions. July 7, The Scholar's Stage. https://scholars-stage.org/the-rise-of-the-west-asking-the-right-questions/

Greer, T. (2013b). Another look at the 'Rise of the West' - but with better numbers. November 20, The Scholar's Stage. https://scholars-stage.org/another-look-at-the-rise-of-the-west-but-with-better-numbers/

Harris, W. (1999). Demography, Geography and the Sources of Roman Slaves. Journal of Roman Studies 89, 62-75. https://doi.org/10.2307/300734  

 

Hbd *chick (2013). Going Dutch, November 29. https://hbdchick.wordpress.com/2013/11/29/going-dutch/

 

Hopkins, K. (1965). Contraception in the Roman Empire. Comparative Studies in Society and History 8(1): 124-151. https://doi.org/10.1017/S0010417500003935  

 

Jelavich, C. and B. Jelavich. (1977). The Establishment of the Balkan National States, 1804-1920. Seattle: University of Washington Press.

 

Lewis, B. (1990). Race and Slavery in the Middle East. New York: Oxford University Press.

 

Macfarlane, A. (1978). The Origins of English Individualism: The Family, Property and Social Transition. Oxford: Blackwell.

 

Perry, M.J. (2013). Gender, Manumission, and the Roman Freedwoman. Cambridge University Press.

 

Roetzel, C.J. (2000). Sex and the single god: celibacy as social deviancy in the Roman period. In: S.G. Wilson and M. Desjardins (eds). Text and Artefact in the Religions of Mediterranean Antiquity. Essays in Honour of Peter Richardson. Wilfrid Laurier University Press (pp. 231-248).

 

Russell, J.C. (1994). The Germanization of Early Medieval Christianity: A Sociohistorical Approach to Religious Transformation. New York; Oxford: Oxford University Press.

 

Sailer, S. (2022). Why was much of the non-European world stagnating well before 1492? The Unz Review, May 10 https://www.unz.com/isteve/why-was-much-of-the-non-european-world-stagnating-well-before-1492/#new_comments  

 

Schulz, J.F., D. Bahrami-Rad, J.P. Beauchamp, and J. Henrich. (2019). The Church, intensive kinship, and global psychological variation. Science 366(707), 1-12. https://doi.org/10.1126/science.aau5141  

 

Thompson, D. (2012). The Economic History of the Last 2000 Years: Part II, The Atlantic, June 20, http://www.theatlantic.com/business/archive/2012/06/the-economic-history-of-the-world-after-jesus-in-4-slides/258762/  

 

Van den Berghe, P.L. (1960). Hypergamy, Hypergenation, and Miscegenation. Human Relations 13(1):83-91. https://doi.org/10.1177%2F001872676001300106   

 

Weber, M. (1930). The Protestant Ethic and the Spirit of Capitalism. New York: Charles Scribner’s Sons.

 

Woodley of Menie, M.A., J. Delhez, M. Peñaherrera-Aguirre, and E.O.W. Kirkegaard. (2019). Cognitive archeogenetics of ancient and modern Greeks. London Conference on Intelligence. https://www.altcensored.com/watch?v=UES_tpDxz9A  

Selection for fair skin in Europeans and North Asians

 

Selection for fair skin in different human populations (Huang et al. 2021)

Selection for fair skin was about four times stronger among ancestral Europeans than it was among ancestral North Asians or the earlier shared ancestors of both groups. So says a recent genome study.

 

Huang et al. (2021) examined genes that influence skin pigmentation to calculate the strength of selection for lighter skin among the ancestors of today’s Europeans and North Asians. They concluded that selection for lighter skin was strongest among the unique ancestors of present-day Europeans, with a selection pressure of 25.9. It was about four times weaker among the unique ancestors of North Asians (5.61) and the earlier shared ancestors of both groups (6.5). East Asians actually became darker after they split from North Asians, with a negative selection pressure of -5.53.

 

Our estimate shows that the modern European lineage had the largest selective pressure (s4=0.0259/generation) on light pigmentation than the other branches, suggesting that recent natural selection favoured light pigmentation in Europeans. Recent studies using ancient DNA could support our observation of recent directional selection in Europeans (Huang et al. 2021, p. 3)

 

This finding supports earlier findings. Modern humans remained dark-skinned in Europe long after they had spread north into northern latitudes some 45,000 years ago. It was not until 20,000 years ago that alleles for white skin made their appearance (Beleza et al. 2013; Canfield et al. 2014; Norton and Hammer 2007). As a Science correspondent concluded: "The implication is that our European ancestors were brown-skinned for tens of thousands of years" (Gibbons 2007).

 

Those ancestors were initially proto-Eurasians, and it was only later that they differentiated to become respectively Europeans and North Asians. Only then, and only in the European lineage, did skin color begin to lighten at a fast rate. This rapid evolution seems to have been confined to a relatively small area that stretched from the Baltic to central Siberia. Elsewhere, in western and southern Europe, people remained dark-skinned until almost the dawn of history, as shown by DNA dated to 11,000 years ago from England, 8,000 years ago from Luxembourg, and 7,000 years ago from Spain (Brace et al. 2019; Lazaridis et al. 2014; Olalde et al. 2014).

 

The fair skin phenotype, together with a variety of hair and eye colors, would later spread throughout all of Europe, while going extinct east of the Urals. In the latter region it would persist into historic times. At sites in south-central Siberia, dating from the third millennium BC to the fourth century AD, genetic analysis has shown that most of the buried individuals had blue or green eyes, light hair (blond, red, light brown), and light skin (Bouakaze et al. 2009). South Siberian peoples were, in fact, described as having "green eyes" and "red hair" in old Chinese records (Keane 1886, p. 703).

 

It seems that Europeans acquired their current appearance very fast, perhaps ten to twenty thousand years ago during the last ice age. Initially confined to northeastern Europe and parts of Siberia, the new phenotype would in time spread to the rest of the continent ... on the eve of recorded history. Only then did all Europeans come to look “European” (Frost 2014; Frost 2020).

 

References

 

Beleza, S., A.M. Santos, B. McEvoy, I. Alves, C. Martinho, E. Cameron, et al. (2013). The timing of pigmentation lightening in Europeans. Molecular Biology and Evolution 30(1): 24-35. https://doi.org/10.1093/molbev/mss207

 

Bouakaze, C., C. Keyser, E. Crubézy, D. Montagnon, and B. Ludes. (2009). Pigment phenotype and biogeographical ancestry from ancient skeletal remains: inferences from multiplexed autosomal SNP analysis. International Journal of Legal Medicine 123(4): 315-325.

https://doi.org/10.1007/s00414-009-0348-5

 

Brace, S., Y. Diekmann, T.J. Booth, Z. Faltyskova, N. Rohland, S. Mallick, et al. (2019). Ancient genomes indicate population replacement in Early Neolithic Britain. Nature Ecology & Evolution 3(5): 765-771. https://doi.org/10.1038/s41559-019-0871-9

 

Canfield, V.A., A. Berg, S. Peckins, S.M. Wentzel, K.C. Ang, S. Oppenheimer, and K.C. Cheng. (2014). Molecular phylogeography of a human autosomal skin color locus under natural selection. G3, 3(11): 2059-2067. https://doi.org/10.1534/g3.113.007484

 

Frost, P. (2014). The puzzle of European hair, eye, and skin color. Advances in Anthropology 4(2): 78-88. http://www.scirp.org/journal/PaperInformation.aspx?PaperID=46104

 

Frost, P. (2020). White Skin Privilege: Modern Myth, Forgotten Past. Evolutionary Studies in Imaginative Culture 4(2): 63-82. https://doi.org/10.26613/esic/4.2.190

https://www.jstor.org/stable/10.26613/esic.4.2.190

 

Gibbons, A. (2007). American Association of Physical Anthropologists Meeting: European skin turned pale only recently, gene suggests. Science 20 April 2007, 316(5823): 364.

https://doi.org/10.1126/science.316.5823.364a

 

Huang, X., S. Wang, L. Jin, and Y. He. (2021). Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation. Biology Open 15 February 2021; 10(2): bio056523. https://doi.org/10.1242/bio.056523

 

Keane, A.H. (1886). Asia with Ethnological Appendix. London: Edward Stanford.

 

Lazaridis, I., N. Patterson, A. Mittnik, G. Renaud, S. Mallick, K. Kirsanow, et al. (2014). Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513(7518): 409-413. https://doi.org/10.1038/nature13673

 

Norton, H.L., and M.F. Hammer. (2007). Sequence variation in the pigmentation candidate gene SLC24A5 and evidence for independent evolution of light skin in European and East Asian populations. Program of the 77th Annual Meeting of the American Association of Physical Anthropologists, p. 179.

 

Olalde, I., M.E. Allentoft, F. Sanchez-Quinto, G. Santpere, C.W.K. Chiang, M. DeGiorgio, et al. (2014). Derived immune and ancestral pigmentation alleles in a 7,000-year-old Mesolithic European. Nature 507 (7491): 225-228. https://doi.org/10.1038/nature12960

 

The mismeasure of genetic differentiation

 

Red Tree, Piet Mondrian (1908-10)

If we look at SNP alleles associated with educational attainment, we see differences between Europeans and sub-Saharan Africans. Is genetic drift the cause? Or natural selection?

 

 

IQ has long been the yardstick of cognitive ability. As such, it describes phenotype, not genotype: it measures how your inborn potential has developed in your environment. Genotype is the inborn component of IQ. It can be inferred from twin studies, family studies, and adoption studies, but those approaches are indirect and far from perfect.

 

To measure genotype directly, we need to identify the alleles that affect the development of cognitive ability. We also need to measure the size of each allele’s effect. Recently, much progress has been made. By using genome-wide association studies (GWAS), researchers have identified many alleles that are associated with educational attainment (EA). EA is not quite the same as IQ—it also includes things like sitting still in class and brownnosing the teacher—but it's a good approximation.

 

In the most recent study of this sort, Lee et al. (2018) identified 1,271 single-nucleotide polymorphisms (SNPs) that are significantly associated with high EA in a sample of over one million people of European ancestry. Together, the SNPs can explain 11-13% of the variance in EA among individuals. This new yardstick is called the "polygenic score."

 

The polygenic score is more accurate for populations than for individuals. If we compare the mean polygenic score of a population and its mean IQ, the correlation is 90% (Piffer 2019). This high correlation is due to the logic of sampling: to estimate the mean cognitive ability of a population, we don't have to identify all of the relevant SNPs, just a large enough sample.

 

Like mean IQ, the mean polygenic score differs among human populations. It seems to have increased during the northward spread of modern humans out of Africa and into the temperate zone of Europe and Asia, with East Asians having the highest scores. This geographic pattern is in line with IQ data. The mean polygenic score is also very high among Ashkenazi Jews and Finns, again in line with IQ data (Piffer 2019).

 

 

Kevin Bird’s paper

 

The above findings have been disputed by the American researcher Kevin Bird in a recent paper. Although Europeans and sub-Saharan Africans have different alleles at genes associated with educational attainment, he argues that these differences correspond to small differences in cognitive ability. In fact, they are more consistent with genetic drift than with natural selection.

 

To prove his argument, he performed two analyses of the data: an Fst and a test for polygenic selection. In my opinion, both analyses have serious problems.

 

The Fst

 

This is the most common measure of genetic differentiation. If the Fst is low, differentiation is trivial and consistent with genetic drift. If it is high, differentiation is significant and consistent with natural selection.

 

For SNPs associated with EA, Kevin Bird reports an Fst of 0.111. Is that low or high? When Sewall Wright (1978, pp. 82-85) created this measure, he defined four categories of differentiation:

 

0 to 0.05 - little genetic differentiation

0.05 to 0.15 - moderate genetic differentiation

0.15 to 0.25 - great genetic differentiation

0.25 to 1 - very great genetic differentiation

 

Those categories are widely cited in the literature. A search in Google Scholar for "moderate genetic differentiation" and "0.05 - 0.15" shows over two hundred papers.

 

So does an Fst of 0.111 mean moderate genetic differentiation? Not according to Kevin Bird, who sees nothing at all below a benchmark of 0.118. That benchmark may be valid, but it cannot be easily verified and does not appear elsewhere in the literature. Nor does Kevin explain why it is better than the ones put forward by Sewall Wright. In fact, he makes no reference to them.

 

One may also question the Fst of 0.111. For the data source, the reader is referred to Lee et al. (2018), but that study was done only with European subjects. Moreover, Kevin Bird used 1,259 SNPs to calculate that Fst, even though he found only 685 SNPs that had data on both Africans and Europeans.

 

The Fst of 0.111 seems to be the diversification of those SNPs in Europeans. That value is what would be expected, but it says nothing about diversification between Europeans and sub-Saharan Africans.

 

The polygenic selection analysis

 

The other analysis is more on subject. Kevin Bird compared European data with African data as follows:

 

1. First, he looked through the 1000 Genomes Project for SNP data on Europeans and sub-Saharan Africans. He found data on five European-descended populations (Utah residents, Tuscans, Finns, British, Iberians) and five African populations (Yoruba, Luhya, Gambians, Mende, Esan). The two datasets had information on 685 of the 1,271 SNPs associated with educational attainment.

 

2. For each SNP, he noted the allele frequencies in Europeans and the allele frequencies in sub-Saharan Africans.

 

3. He calculated the differences in allele frequencies between the two groups. He then weighted the differences for the allele's effect size (its estimated positive or negative effect on educational attainment). For each allele, he used two different estimates of effect size: one from between-family data and the other from within-family data.

 

4. Alongside this list of weighted alleles, he created a second list to simulate genetic drift by randomly flipping the sign of effect size for 10,000 permutations.

 

5. When effect size was calculated from between-family data, the two lists clearly differed from each other. When it was calculated from within-family data, the overall difference was much smaller and easily explained by genetic drift.

 

Bird (2021) prefers the second dataset to the first, whereas Piffer (2019) prefers the first. Who is right? All things being equal, data should come from within families. There is less statistical noise because siblings have similar upbringings. With less noise, group differences can more easily be identified.

 

Yet, here, we have the opposite. We see a significant difference between Europeans and Africans in the between-family data, but not in the within-family data. Why? The reason is that the between-family data came from over a million subjects whereas the within-family data came from 20,000 sibling pairs. Being smaller, the second dataset had a lot more noise. Sure, there should have been less noise, all things being equal. But some things weren't.

 

 

Doing the comparison again but better

 

I suspect Kevin Bird still prefers within-family data. Fine. Let's repeat the comparison with a much larger sample of sibling pairs. There would then be less noise and probably a significant difference between African and European alleles in their effect on educational attainment. Kevin seems to anticipate this eventuality:

 

While the results presented here are more consistent with neutral evolution rather than divergent natural selection, it is not possible to rule out that data sets with more power could present different results. Additionally, although within-family effect sizes are recommended over between-family effect sizes, if the within-family effect sizes are re-estimated for SNPs ascertained by a between-family GWAS, there is still likely to be some level of confounding from population structure. (Bird 2021, p. 7)

 

He elaborates on the last point:

 

[...] the [polygenic] scores might be biased by a variety of factors, including the nonrandom ways that society is geographically structured [...]. For instance, Black people in the US, for reasons unrelated to genetics, live in areas with poorer air quality and more exposure to environmental toxins (Bird 2021, p. 8)

 

Yet, as he notes further on, these SNP alleles were identified only in European subjects, and their effects on educational attainment were estimated only from European data. So how could different alleles among Europeans be spuriously associated with differences in educational attainment among Europeans because of socioeconomic deprivation among Black Americans? Where and when do the latter come into this presumably spurious association?

 

Kevin Bird is right to point out that the allele effects were calculated from European data and may be less applicable to people of other origins. In fact, there is growing evidence that the genetic architecture of cognition is different in sub-Saharan Africans (Frost 2019). By ignoring that factor, however, we introduce even more noise into the data and muddle even more any differences that may exist between Africans and Europeans. The data may indeed be of low quality, but that shortcoming would, if anything, obscure group differences. Again, Kevin is making a coherent point within an incoherent argument.

 

 

Other ways?

 

There are other ways to distinguish between genetic drift and natural selection. One way is to measure the ratio of nonsynonymous alleles to synonymous alleles. If a trait has little functional value and is thus vulnerable to genetic drift, nonsynonymous alleles will tend to proliferate and become as numerous as synonymous alleles (Tomoko 1995). Of course, if nonsynonymous alleles greatly outnumber synonymous alleles, there may be natural selection for diversity (Rana et al. 1999).

 

An SNP, by its very nature, has alleles that differ from each other by only one base substitution, and this fact limits our ability to distinguish between genetic drift and natural selection. It would thus be interesting to identify genetic polymorphisms that are associated with educational attainment but have several nucleotides.

 

If such a polymorphism is undergoing genetic drift, the most frequent alleles will be the ancestral allele and those that differ from it by one base substitution. The less frequent ones will be those that differ by two or more base substitutions. In short, the frequency of an allele will be inversely related to the number of base substitutions that separate it from the ancestral allele.

 

The picture is different with natural selection. The most frequent alleles will not necessarily be the ones that differ the least from the ancestral allele. If allele frequency is graphed as a function of base substitutions, the result will not be a smoothly decreasing exponential curve. The most successful allele may differ from the ancestral one by several base substitutions.

 

 

References

 

Bird, K.A. (2021). No support for the hereditarian hypothesis of the Black-White achievement gap using polygenic scores and tests for divergent selection. American Journal of Physical Anthropology. Feb. 1-12, DOI: 10.1002/ajpa.24216.

https://www.gwern.net/docs/genetics/selection/2021-bird.pdf

 

Frost, P. (2019). Differences in the genetic architecture of cognition? Evo and Proud, September 25

https://evoandproud.blogspot.com/2019/09/differences-in-genetic-architecture-of.html

 

Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, et al. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics 50(8): 1112-1121.

https://academicworks.medicine.hofstra.edu/cgi/viewcontent.cgi?article=5038&context=articles  

 

Tomoko, O. (1995). Synonymous and nonsynonymous substitutions in mammalian genes and the nearly neutral theory. Journal of Molecular Evolution 40 (1): 56-63

 

Piffer, D. (2019). Evidence for Recent Polygenic Selection on Educational Attainment and Intelligence Inferred from Gwas Hits: A Replication of Previous Findings Using Recent Data. Psych 1(1): 55-75. https://doi.org/10.3390/psych1010005   

 

Rana, B.K., D. Hewett-Emmett, L. Jin, B.H.J. Chang, N. Sambuughin, M. Lin, et al. (1999). High polymorphism at the human melanocortin 1 receptor locus. Genetics 151(4): 1547-1557.

https://www.researchgate.net/profile/M-Ramsay/publication/13190390_High_Polymorphism_at_the_Human_Melanocortin_1_Receptor_Locus/links/596b13eeaca2728ca6821b9e/High-Polymorphism-at-the-Human-Melanocortin-1-Receptor-Locus.pdf

 

Wright S. (1978). Evolution and Genetics of Populations, Volume 4. University of Chicago, Chicago, IL.