Looking beyond the data

 

General intelligence (g factor) as a function of alleles associated with educational attainment (Education polygenic score). (Fuerst et al. 2021, p. 165)

Among non-Hispanic European Americans, cognitive ability shows a positive correlation with Amerindian admixture. The reason is to be found in the history of European settlement.

 

 

We know that cognitive ability differs among human populations, but are those differences innate? Or are they purely cultural? The question is difficult to answer because a purely cultural difference can, over time, become innate. If you are better able to meet the demands of your culture, you will probably live longer, have more offspring, and pass on many of your characteristics. Thus, over succeeding generations, those heritable characteristics will become more and more widespread in the gene pool, and they will increasingly determine certain abilities that were initially created by culture.

 

This is a recurring problem when we try to distinguish between cultural and genetic determination. The two often run parallel to each other, and we can seemingly rule out the existence of genetic determination by showing that cultural determination runs in the same direction.

 

But there is another recurring problem in our efforts to distinguish between culture and genetics. We lack the proper tools. For a long time, we could only infer genetic influences by using twin studies or adoption studies. 

 

Things have changed with the advent of a new tool: genomic data. Specifically, we can now:

 

·         Measure ethnic ancestry in mixed populations, as opposed to using self-report or inferring from skin color.

·         Measure the genetic component of cognitive ability, by using genetic variants associated with educational attainment. Although these variants explain only 11-13% of the variance in educational attainment among individuals, they explain a much higher percentage of the variance among populations (Piffer 2019). This is because genetic variants within the same population are exposed to the same pressure of selection and will thus vary in the same direction. They act, so to speak, as “weathervanes” that tell us the strength and direction of selection in that population.

·         Measure skin color, by looking at the relevant genes. We can thus control for the effects of “colorism” in mixed populations, i.e., discrimination in favor of lighter-skinned individuals.

 

In my last post, I described how Bryan Pesta used these tools to understand differences in mean cognitive ability between African Americans and European Americans (Lasker et al. 2019). To that end, his research team looked at cognitive ability among African Americans in relation to European admixture and in relation to genetic variants associated with educational attainment.

 

They made several findings: 1) among African Americans, cognitive ability correlates with European admixture; 2) the correlation is modestly reduced, but not eliminated, when controlled for parental education; 3) controlling for skin color has no effect; and 4) the correlation seems to be largely explained by genetic variants associated with educational attainment.

 

The same data source was then used by Fuerst et al. (2021) to investigate cognitive ability not only in European Americans and African Americans but also in Hispanic Americans. The research team thus looked at cognitive ability in relation to Amerindian admixture, and not just in relation to European and African admixture.

 

Most of their findings are similar to those of the first study:

 

·         Among Hispanic Americans, cognitive ability shows a positive correlation with European admixture and a negative correlation with African admixture and Amerindian admixture.

·         Among Hispanic Americans, the correlations are reduced but not eliminated by controlling for parental education. Controlling for skin color has no effect.

·         The above correlations are partially explained by variants associated with educational attainment, but not by skin color.

·         Among non-Hispanic European Americans, cognitive ability shows a positive correlation with Amerindian admixture.

 

The last correlation may seem curious. Keep in mind that the data came from residents of Pittsburgh and that the native peoples of the Eastern U.S. intermixed mostly with early settlers of British, Dutch, or French origin. There is much less Amerindian admixture among the descendants of later immigrants from southern and eastern Europe. The correlation may thus be due not to Amerindian admixture per se but rather to variation in cognitive ability among Europeans.

 

Until the eleventh century, mean IQ was relatively low throughout Europe, perhaps hovering in the low 90s. It then rose during late medieval and post-medieval times through the expansion of the middle class. There was in fact a broad mental and behavioral change: "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; see also Clark 2007, 2009a, 2009b). More people could better understand probability, cause and effect, and another person’s perspective, whether real or hypothetical (Rinderman 2018, pp. 49, 86-87; Oesterdiekhoff 2012). As the "smart fraction" grew in size, a point was reached when intellectuals were no longer voices crying in the wilderness. They were now numerous enough to form learned societies and collaborate in projects of various sorts (Frost 2019b, pp. 175-176).

 

Western Europe was where the middle class began to expand, and that was where the expansion would have its greatest impact, not only demographically but also behaviorally and cognitively. Gregory Clark (2009a) has shown that the English, even in the lower classes, are largely descended from people who were middle-class several generations earlier. The same is likely true elsewhere in Western Europe. We should therefore see a cognitive gradient between the Western European core and its periphery, as can indeed be seen between northern and southern Italy. When Piffer and Lynn (2022) looked at genomic data from that country, they found a north-south gradient in alleles associated with educational attainment. That difference corresponds to historical differences in economic development. By the 18th century, the South had already fallen behind the North; its middle class had remained small and economic relations were still structured by paternalism and familialism (De Rosa 1979).

 

All of that leads to an interesting corollary: the IQ gap used to be smaller between Europeans and sub-Saharan Africans. On the one hand, European mean IQ had probably remained in the low 90s until late medieval times. On the other hand, mean IQ may have been in the upper 80s among those Black African groups that Europeans had first encountered, particularly the Nubians. By the time of Classical Antiquity they had reached a high level of material culture, social complexity and State formation.

 

A smaller IQ gap would be in line with an observation by Jason Malloy. He noted that blacks were often described in the ancient world as having large penises but not as being less intelligent. Indeed, I have found only two Greco-Roman texts in which the writer disparaged Black Africans as being unintelligent. One of them is of doubtful authenticity, and both come from Late Antiquity (Frost 2019b). By then, blacks in the Roman world were increasingly slaves who came from farther within the African interior. Thereafter, a stereotype of low intelligence is regularly attested in Middle Eastern and European sources.

 

 

References

 

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

 

Clark, G. (2009a). The indicted and the wealthy: surnames, reproductive success, genetic selection and social class in pre-industrial England.  http://www.econ.ucdavis.edu/faculty/gclark/Farewell%20to%20Alms/Clark%20-Surnames.pdf     

 

Clark, G. (2009b). The domestication of man: The social implications of Darwin. ArtefaCTos 2: 64-80. https://www.researchgate.net/publication/277275046_The_Domestication_of_Man_The_Social_Implications_of_Darwin

 

De Rosa, L. (1979). Property Rights, Institutional Change, and Economic Growth in Southern Italy in the XVIIIth and XIXth Centuries. Journal of European Economic History 8(3): 531-551.

 

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

 

Frost, P. (2019b). Why that stereotype and not the other? Evo and Proud, July 28. https://evoandproud.blogspot.com/2019/07/why-that-stereotype-and-not-other.html

 

Frost, P. (2021). Commentary on Fuerst et al: Do Human Populations Differ in Their Mental Characteristics? Mankind Quarterly 62(2). http://doi.org/10.46469/mq.2021.62.2.9   

 

Fuerst, J., E.O.W. Kirkegaard and D. Piffer. (2021). More research needed: There is a robust causal vs. confounding problem for intelligence-associated polygenic scores in context to admixed American populations. Mankind Quarterly 62(1): 151-185. https://www.researchgate.net/profile/John-Fuerst/publication/354767141_More_Research_Needed_There_is_a_Robust_Causal_vs_Confounding_Problem_for_Intelligence-associated_Polygenic_Scores_in_Context_to_Admixed_American_Populations/links/614bc1dfa595d06017e4c017/More-Research-Needed-There-is-a-Robust-Causal-vs-Confounding-Problem-for-Intelligence-associated-Polygenic-Scores-in-Context-to-Admixed-American-Populations.pdf

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global Ancestry and Cognitive Ability. Psych 1(1):431-459. https://doi.org/10.3390/psych1010034  

 

Oesterdiekhoff, G.W. (2012). Was pre-modern man a child? The quintessence of the psychometric and developmental approaches. Intelligence 40, 470–478. https://doi.org/10.1016/j.intell.2012.05.005

 

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

 

Piffer, D., and R. Lynn. (2022). In Italy, North-South Differences in Student Performance Are Mirrored by Differences in Polygenic Scores for Educational Attainment. Mankind Quarterly 62(4), Article 2. https://doi.org/10.46469/mq.2022.62.4.2   

 

Rindermann, H. (2018). Cognitive Capitalism. Human Capital and the Wellbeing of Nations, 1st ed.; Cambridge University Press.

Eppur si muove

 

General intelligence (g) varies with ethnicity, as do genetic variants associated with educational attainment (Lasker et al. 2019, p. 445)

 

 

Bryan Pesta was fired from a tenured university position for a study he coauthored in a peer-reviewed journal. No one actually disputed his findings. It was simply taken for granted that they could not be true.

 

 

Three years ago I contributed a paper to a special issue of Psych. One of the other contributors, Bryan J. Pesta, coauthored a paper on “Global Ancestry and Cognitive Ability.” It was one of several recent studies that had used genetic data to understand how populations differ on average in their capacity for intelligence.

 

Pesta and his coauthors looked at data from an existing neurodevelopment study of 9,421 participants from Philadelphia. A little over half of them were European American, and a third were African American. They had all been genotyped and had all taken a battery of cognitive tests.

 

The study produced several findings:

 

·         Almost 15 IQ points separated the African American participants from the European American participants. About three quarters of the difference was due to general intelligence (g).

·         Among the African Americans, general intelligence correlated with the degree of European admixture.

·         The correlation was modestly reduced, but not eliminated, when controlled for parental education. Controlling for skin color had no effect. Although skin color does correlate with European admixture, it evidently has a less direct relationship to general intelligence. This finding therefore eliminates “colorism” (discrimination in favor of lighter-skinned African Americans) as a possible cause.

·         As much as 20-25% of the difference in general intelligence between the African Americans and the European Americans was explained by genetic variants associated with educational attainment. By comparison, the same variants explain only 11-13% of the variance in educational attainment among individuals.

·         Although these genetic variants predicted general intelligence in both groups, the predictive power for the African Americans was only 20% of the predictive power for the European Americans. This finding is consistent with a growing consensus that the genetic architecture of intelligence is different in the two groups. Because the genetic variants have been identified in Europeans or European Americans, they may contribute less to the capacity for intelligence in people of African descent. In addition, other variants may be found only in African populations and thus remain to be identified.

 

For the above findings, Bryan Pesta would be fired from his tenured position at Cleveland State University. The whole affair is described in The Chronicle of Higher Education. At no point did anyone actually dispute his findings. It was simply taken for granted that they could not be true. And that’s that.

 

Please don’t argue that Bryan Pesta unconsciously looked for data that would provide the findings he wanted. The data had already been collected by another research team for a completely different purpose. So put aside The Mismeasure of Man and tell Stephen Jay Gould to go back to sleep.

 

This story isn’t over. People are curious, and curiosity ends up finding a way—despite the barriers we erect. Below is a screen shot of the paper’s access statistics (Hint: The Chronicle’s article came out on October 13).

 

 

References

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global Ancestry and Cognitive Ability. Psych 1(1):431-459. https://doi.org/10.3390/psych1010034  

 

Standifer, C. (2022). Racial Pseudoscience on the Faculty. A professor’s research flew under the radar for years. What finally got him fired? The Chronicle of Higher Education. October 13. https://www.chronicle.com/article/racial-pseudoscience-on-the-faculty?cid2=gen_login_refresh&cid=gen_sign_in

Comparing an incomparable?

 

Stigmata Siciliana (1964), David McLure (Wikicommons)

 

 

What is the mean IQ of sub-Saharan Africans? There’s no clear answer. Current estimates come from an early stage of the Flynn effect and are also distorted by qualitative differences in cognition. Furthermore, mean IQ differs among African groups.

 

 

 

At present, there is little consensus on the mean IQ of sub-Saharan Africans. Estimates have ranged from a low of 66 to a high of 82 (Lynn 2010; Wicherts et al. 2010). Rindermann (2013) put forward a "best guess" of 75, which is inexplicably much lower than the estimated African American mean of 85. Yes, African Americans are about 20% European by ancestry, but that degree of admixture would not cause a 10-point difference. Malnutrition? That might depress IQ scores in some African countries but not most.

 

Noah Carl (2022) has reopened the debate by inferring mean IQ from harmonized test scores and GDP per capita. Sub-Saharan Africa looks somewhat better on the first measure and somewhat worse on the second. Both measures correlate roughly with mean IQ, but the correlation isn’t strong enough to tell us whether the mean is 62, 75, or 82. Moreover, the first measure suffers from the same problem that plagues IQ tests: Africa is just starting to experience the secular increase in mean IQ that the West experienced during the 20th century, i.e., the Flynn effect. By how much should we increase the estimate of mean African IQ to adjust for Africa being at an earlier stage of the Flynn effect?

 

As for the second measure, GDP per capita, the ability to create wealth is determined not only by cognitive ability but also by other mental traits: future time orientation (also known as time preference), willingness to follow rules and enforce them, feelings of guilt over breaking rules, reluctance to use violence to settle disputes, tendency toward individualism rather than nepotism and familialism, and so on.

 

In a reply to Carl’s article, Emil Kirkegaard (1922) infers mean IQ from the Social Progress Index. But that measure is no less problematic than GDP per capita. Social progress is driven by a basket of mental qualities, of which cognitive ability is only one. Emil himself makes that point:

 

One cannot just impute IQs reliably from non-IQ data in order to get some kind of unbiased estimates of a region's IQ because the regions themselves may under- or overperform on international rankings for whatever reason, [including] legacy of or current communism, nonWEIRDness, low individualism, or any other difference you can imagine.

 

Emil concludes: “There’s no avoiding having to collect more African IQ data.”

 

More data would be nice, but no amount of data will provide us with a mean African IQ that can be usefully compared with the mean IQs of other populations. There are several reasons:

 

·        Again, estimates of African IQ come from an early stage of the Flynn effect. They are not comparable with estimates of IQ that come from a later stage in other populations.

·        The genetic architecture of cognition is not the same. Sub-Saharan Africans seem to have alleles for cognitive ability that do not exist in other populations. To date, such alleles have been identified only in people of European descent.

·       Recent cognitive evolution, particularly in societies near the Niger, has created differences in mean cognitive ability among African groups. It is no more meaningful to talk about a single mean African IQ than it is to talk about a single mean European IQ.

 

Differences in the stage of the Flynn effect

 

IQ data from Western societies are not comparable with IQ data from African societies. The latter are just beginning to experience the rise in mean IQ that took place earlier in the West, specifically the increase of 13.8 points between 1932 and 1978 (Flynn 1984). The Flynn effect seems to be not so much an increase in cognitive ability as an increase in familiarity with the “test paradigm” at school and, more broadly, in society. Flynn (2013) situates the cause in the modernist paradigm: “We freed ourselves from fixation on the concrete and entered a world in which the mass of people began to use logic on abstractions and universalize their moral principles.”

 

Keep in mind that competitive exams began to appear in the West only in the late 19th century, first for entry into the civil service and then more generally for the educational system (Wikpedia 2022). Previously, people entered the civil service through patronage appointments, and education took the form of apprenticeship and imitation of role models. In those days, people were less inclined to formulate questions and look for the answers. The answers were already known, and you had to learn them. In fact, there was a stigma attached to asking too many questions, especially in rapid-fire succession.

 

Differences in the genetic architecture of cognition

 

As a means to estimate cognitive ability, the IQ test is becoming superseded by the educational polygenic score. This measure is based on SNPs that have been shown to be associated with educational attainment. Your polygenic score is higher to the extent that the alleles at those SNPs are associated with higher educational attainment. It is thus a measure of innate cognitive ability. At present, we have identified 1,271 SNPs that are associated with educational attainment and which, together, explain 11-13% of the variance in educational attainment among individuals (Lee et al. 2018). The educational polygenic score has shown good reliability in predicting the IQ of individuals and even better reliability in predicting the mean IQ of populations.

 

Again, we have identified alleles associated with educational attainment only in people of European descent. For this reason, the educational polygenic score is five times worse at predicting the cognitive ability of African Americans (Lasker et al. 2019). The loss of predictive power seems greatest in the domain of language ability, according to two studies:

 

·        Guo et al. (2019, p. 27) found that the educational polygenic score is ten to eighteen times worse at predicting the verbal ability of African Americans, in comparison to White, Asian, and Hispanic White Americans. They attributed this difference to the smaller size of the African American sample, to gene-environment interactions, and to “significantly less than full coverage of African genetic variants related to cognitive ability.”

·        With a sample of school-age African Americans, Rabinowitz et al. (2019) found that the educational polygenic score fails to predict performance on a standardized reading test but does predict pursuit of postsecondary education, getting a criminal record (only among boys), and performance on a standardized math test (only for one of the three cohorts).

 

When modern humans began to spread out of Africa some 60,000 years ago, those left behind began to pursue their own trajectory of cognitive evolution. The evolutionary change seems to have been greatest in the domain of language, i.e., the ability to express oneself in speech and writing. Polygenic scores cannot predict innate reading ability because too many of the relevant alleles are exclusive to the African gene pool and remain unidentified. Other relevant alleles may simply be more important or less important in other gene pools.

 

Although the educational polygenic score is based on alleles identified in Europeans, it can still be used for rough predictions of cognitive ability among people of African descent. Lasker et al. (2019, pp. 444-445) were able to increase its predictive power for African Americans by almost a factor of three, i.e., an increase from 20% to 54% of its predictive power for European Americans. They achieved this improvement by using alleles from a much smaller subset of SNPs that are less sensitive to decay of linkage disequilibrium.

 

Differences among African groups in the trajectory of cognitive evolution

 

Within the larger African trajectory of cognitive evolution, various African populations have pursued their own sub-trajectories. This has been especially true for populations in West Africa over the past millennium and a half. Their educational polygenic scores vary as you go from west to east, being lowest among the Mende (Sierra Leone) and progressively higher among Gambians, the Esan (Nigeria), and the Yoruba (Nigeria). The Yoruba have almost the same educational polygenic score as that of African Americans, who nonetheless are about 20% admixed with Europeans (Piffer 2021, see Figure 7).

 

Before European contact, West African societies were more complex in the north and the east, i.e., in the Sahel and the Nigerian forest. Those areas saw the creation of towns, the formation of states, and an increasing use of metallurgy and luxury goods from the fourth century onward. The increase in social complexity seems to have been driven by the development of trade along the Niger, which served as the main trading route between the coast and the interior (Frost 2022).

 

In West Africa, cognitive evolution seems to have gone the farthest among the Igbo of the Niger delta. We have no educational polygenic data on them, but their record of academic achievement in Nigeria, the UK, and elsewhere indicates an unusually high level of cognitive ability (Chisala 2015).

 

Conclusion

 

We should get more data, while recognizing the limits of what the data may tell us. IQ tests will always be problematic, and future research should focus on educational polygenic scores. In particular, we need to identify relevant alleles in non-European populations. Some of those alleles may be population-specific, and others may be universal but more important in some populations than in others. Finally, Africa is not a monolith. Different African populations have pursued different trajectories of cognitive evolution.

 

 

References

 

Carl, N. (2022). How useful are national IQs? Noah’s Newsletter, July 13. https://noahcarl.substack.com/p/how-useful-are-national-iqs  

 

Chisala, C. (2015). The IQ gap is no longer a black and white issue. The Unz Review, June 25.

http://www.unz.com/article/the-iq-gap-is-no-longer-a-black-and-white-issue/   

 

Flynn, J.R. (1984). The mean IQ of Americans: Massive gains 1932–1978. Psychological Bulletin 95(1):29–51. https://psycnet.apa.org/doi/10.1037/0033-2909.95.1.29  

 

Flynn, J.R. (2013). The “Flynn Effect” and Flynn’s paradox. Intelligence 41: 851-857. http://dx.doi.org/10.1016%2Fj.intell.2013.06.014   

 

Frost, P. (2021). Polygenic scores and Black Americans. Evo and Proud, April 27. https://evoandproud.blogspot.com/2021/04/polygenic-scores-and-black-americans.html   

 

Frost, P. (2022). Recent cognitive evolution in West Africa: the Niger’s role. Evo and Proud, April 30. https://evoandproud.blogspot.com/2022/04/recent-cognitive-evolution-in-west.html  

 

Guo, G., Lin, M.J., and K.M. Harris. (2019). Socioeconomic and Genomic Roots of Verbal Ability. bioRxiv, 544411. https://www.biorxiv.org/content/10.1101/544411v1  

 

Kirkegaard, E.O.W. (2022). African IQs without African IQs: it’s complicated. Just Emil Kirkegaard Things. August 7. https://kirkegaard.substack.com/p/african-iqs-without-african-iqs-its?utm_source=substack&utm_medium=email  

 

Lasker, J., B.J. Pesta, J.G.R. Fuerst, and E.O.W. Kirkegaard. (2019). Global ancestry and cognitive ability. Psych 1(1). https://doi.org/10.3390/psych1010034  

 

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://doi.org/10.1038/s41588-018-0147-3

 

Lynn, R. (2010). The average IQ of sub-Saharan Africans assessed by the Progressive Matrices: A reply to Wicherts, Dolan, Carlson & van der Maas. Learning and Individual Differences 20(3): 152-154. https://doi.org/10.1016/j.lindif.2010.03.009   

 

Piffer, D. (2021). Divergent selection on height and cognitive ability: evidence from Fst and polygenic scores. OpenPsych. https://openpsych.net/files/submissions/14_Divergent_selection_on_height_and_cognitive_ability_evidence_from_Fst_and_13c3ICJ.pdf     

 

Rabinowitz, J.A., S.I.C. Kuo, W. Felder, R.J. Musci, A. Bettencourt, K. Benke, ... and A. Kouzis. (2019). Associations between an educational attainment polygenic score with educational attainment in an African American sample. Genes, Brain and Behavior, e12558. https://doi.org/10.1111/gbb.12558   

 

Rindermann, H. (2013). African cognitive ability: Research, results, divergences and recommendations. Personality and Individual Differences 55: 229-233. https://doi.org/10.1016/j.paid.2012.06.022   

 

Wicherts, J.M., C.V. Dolan, and H.L.J. van der Maas. (2010). A systematic literature review of the average IQ of sub-Saharan Africans. Intelligence 38: 1-20. https://doi.org/10.1016/j.intell.2009.05.002   

 

Wikipedia. (2022). Imperial examination – Influence - West. https://en.wikipedia.org/wiki/Imperial_examination#West  

Vitamin D scarcity and natural selection

 

In humans who are dark-skinned or who live above the Arctic Circle, natural selection has favored those who use vitamin D more efficiently or have workarounds of one sort or another for vitamin D scarcity. Yakut family, Wikicommons (Uyban)

 

 

Vitamin D is less easily obtained by some people than by others. It is less available to those who are dark-skinned or who live above the Arctic Circle. Because less UV light enters the skin for biosynthesis, natural selection has favored individuals who use this vitamin more efficiently or have workarounds of one sort or another (Frost 2009; Frost 2012; Frost 2018).

 

Vitamin D levels are thus naturally lower in Arctic and dark-skinned humans. Some variation exists even among Europeans, with levels being lower in darker-skinned southern Europeans than in lighter-skinned northern Europeans (Snellman et al. 2009; van der Wielen et al. 1995).

 

Unfortunately, vitamin D deficiency is diagnosed on the basis of norms developed for light-skinned people from temperate latitudes. Inuit and African Americans are thus diagnosed as “deficient” and offered vitamin supplementation, which has the effect of bathing their body tissues in concentrations of vitamin D that they and their ancestors have not experienced for tens of thousands of years, if not longer.

 

If  Arctic and darker-skinned humans naturally have lower levels of vitamin D, their optimal range of levels will likewise be lower, and toxic effects may occur at levels that lie within the optimal range of Europeans. You may have been told that this cannot happen because toxicity occurs only if you ingest huge amounts of this vitamin. Actually, toxicity begins at relatively low levels. In light-skinned humans from the temperate zone, the optimal range seems to extend only from 40 nmol/L to 100 nmol/L:

 

·         The total mortality rate is about 50% greater in men whose vitamin D levels are either below 46 nmol/L or above 98 nmol/L (Michaelsson et al. 2010).

·         The risk of prostate cancer is significantly greater below 40 nmol/L and above 60 nmol/L (Tuohimaa 2008; Tuohimaa et al. 2009).

·         Mortality for 7 types of cancer (endometrial, esophageal, gastric, kidney, non-Hodgkin's lymphoma, pancreatic, ovarian) is significantly greater below 45 nmol/L and above 124 nmol/L (Helzlsouer et al. 2010).

·         The risk of pancreatic cancer is significantly greater above 100 nmol/L (Stolzenberg-Solomon et al. 2010).

·         The risk of cardiovascular disease is significantly greater below 50 nmol/L and above 62.5 nmol/L, and mortality from all causes is significantly greater above 122.5 nmol/L (Davis 2009).

 

Perhaps most worrisome, studies on mice indicate a U-shaped response curve for the aging process, with premature aging associated with both too little and too much vitamin D (Tuohimaa 2009; Tuohimaa et al. 2009).

 

Vitamin D metabolism and gene-culture coevolution among the Inuit

 

To what extent has the safe range of vitamin D been shifted downward in Arctic and dark-skinned humans? To answer that question, we need to understand gene-culture coevolution. When humans enter a new environment, they adapt by pushing the bounds of phenotypic plasticity—they do the most with what they have already. There is then natural selection for genetic variants that can stabilize this new pattern of adaptation and make it more innate. A new phenotype thus ends up becoming a new genotype.

 

Traditionally, Inuit coped with vitamin D scarcity through a high-meat/low-cereal diet and through extended breastfeeding of children for two years or longer. This diet not only provided vitamin D but also helped the body use this vitamin more efficiently, specifically by means of β-casein in breast milk, unknown substances in meat, and absence of phytic acid (Frost 2018). 

 

Those cultural adaptations were followed by physiological adaptations: receptors that bind more tightly to the vitamin D molecule; a lower set-point for calcium-regulated release of parathyroid hormone; and conversion of vitamin D at a higher rate from its common form to its most active form. Inuit breast milk might also be richer in β-casein (Frost 2018).

 

That gene-culture coevolution has been notably demonstrated by a genome study of the Greenland Inuit, whose marine diet has apparently selected for genetic variants that help their bodies digest and use polyunsaturated fatty acids (Fumagalli et al. 2015).

 

Research on indigenous northern Eurasian peoples

 

Before 2020, the Inuit were the only non-European population for whom we had research on cultural and physiological adaptations to vitamin D scarcity (Frost 2012; Frost 2018). Two studies have since been published on this subject with regard to indigenous peoples in northern Eurasia.

 

Research by Khrunin et al. (2020)

 

This research team looked for signals of natural selection in the genomes of eight northern populations: Russians from the Archangelsk and Vologda regions; Izhemski Komi; Priluzski Komi; Veps; Khanty; Mansi; and Nenets. The strongest signal came from two genes: SLC37A2 and PKNOX2. The first gene is expressed when vitamin D₃ is present in peripheral blood cells. The authors go on to note:

 

Deficit of vitamin D is often observed in northern populations, where exposure to sunlight is limited for many months. Hypothetically, mutations in the VDR-controlled SLC37A2 gene may help northern populations adjust to vitamin D levels. At the same time, the same mutations could have effects on alcohol tolerance in these populations through the PKNOX2 gene, located on the opposite strand of DNA in the same locus. 

 

The second gene, PKNOX2, is associated with alcohol addiction in mice and humans. The authors add that this finding “is of special interest in the context of the well-known alcohol addiction that occurs widely in indigenous populations of Northern Eurasia.”

 

Could vulnerability to alcoholism be a side-effect of adaptation to vitamin D scarcity? The hypothesis is interesting, although I lean more toward another explanation. Some populations, like those around the Mediterranean, have had a long history of drinking fermented beverages instead of water, which might be contaminated with bacteria that cause dysentery and other diseases. Consequently, natural selection has favored individuals who have higher levels of alcohol dehydrogenase and other physiological adaptations that make alcohol less toxic. Conversely, other populations, like northern Eurasians, have consumed fermented beverages for a shorter time, and their bodies are less adapted to alcohol (Nabhan 2004, pp. 27-30; Ridley 2000).

 

Research by Malyarchuk (2020)

 

This is a study of a single polymorphic gene, GC, in several indigenous peoples of northeastern Siberia (Eskimos, Chukchi, Koryaks), central Siberia (Evens, Evenks, Yakuts), southern Siberia (Tuvinians, Shorts, Altaians, Buryats), and western Siberia (Kets, Khanty, Mansi, Selkups, Nenets, Nganasans). The GC gene produces a protein that is the main carrier of vitamin D in the body.

 

One GC variant, specifically the T variant at rs4588, is much less frequent in northeast and central Siberians (5.4%, 3.1%) than in southern and western Siberians (28.6%, 27.5%). Conversely, the G variant is much more frequent in the northeast and center (32.1%, 46.9%) than in the south and west (16.1%, 12.5%). I initially thought the reason was a higher level of European admixture in southern and western Siberia. But there is little European admixture in East Asians, and they resemble southern and western Siberians in having the same high frequency of the T variant (26.1%).

 

The G variant may have become more frequent in northeast and central Siberians as an adaptation to vitamin D scarcity. As one goes farther north, the skin produces less vitamin D because less UV light enters the skin. More research is needed, however, on two other factors: (1) amount of vitamin D from dietary sources; and (2) skin pigmentation. It may be that southern Siberians are somewhat darker-skinned than northern Siberians, although that isn’t my impression. These points are made by Malyarchuk (2020) in the Results and Discussion section. Researchers should study:

 

… the gene-environment interactions by taking into account the vitamin D status of the indigenous population, ethnicity, influence of environmental conditions (the level of natural ambient light and seasonal patterns), and specifics of nutrition. The influence of such factors on the distribution of GC polymorphism variants is evidenced by the data obtained in this work on the high prevalence of haplotypes encoding the Gc1F isoform in northeast Asia under condition of low intensity of solar radiation. In addition, an important factor contributing to vitamin D deficiency may be a relatively high level of melanin in the skin of representatives of the Arctic peoples, which prevents the penetration of ultraviolet rays into the skin and thereby hinders the synthesis of vitamin D₃

 

References

 

Davis, C.D. (2009). Vitamin D and health: can too much be harmful? American Journal of Lifestyle Medicine 3(5): 407-408. https://doi.org/10.1177/1559827609338154

 

Frost, P. (2009). Black-White differences in cancer risk and the vitamin-D hypothesis. Journal of the National Medical Association 101: 1310-1313.

https://doi.org/10.1016/s0027-9684(15)31151-2

 

Frost, P. (2012). Vitamin D deficiency among northern Native Peoples: a real or apparent problem? International Journal of Circumpolar Health 71(S2): 18001

https://doi.org/10.3402/IJCH.v71i0.18001

 

Frost, P. (2018). To supplement or not to supplement: are Inuit getting enough vitamin D? Études Inuit Studies 40(2): 271-291.

https://doi.org/10.7202/1055442ar

 

Frost, P. (2020). Ethnic differences in vitamin-D metabolism. E Scholarly Community Encyclopedia.

https://encyclopedia.pub/3033

 

Fumagalli, M., I. Moltke, N. Grarup, F. Racimo, P. Bjerregaard, M.E. Jørgensen et al. (2015). Greenlandic Inuit show genetic signatures of diet and climate adaptation. Science 349(6254): 1343-1347. https://doi.org/10.1126/science.aab2319

 

Helzlsouer, K.J. and Steering Committee of Vitamin D Pooling Project of Rarer Cancers (2010).  Abstract PL04-05: Vitamin D: panacea or a Pandora’s box for prevention? Cancer Prevention Research 3(1 Suppl 1): PL04-05. https://doi.org/10.1158/1940-6207.PREV-09-PL04-05

 

Khrunin, A.V., G.V. Khvorykh, A.N. Fedorov, and S.A. Limborska (2020). Genomic landscape of the signals of positive natural selection in populations of Northern Eurasia: A view from Northern Russia. PLoS ONE 15(2): e0228778. https://doi.org/10.1371/journal.pone.0228778

 

Malyarchuk, B.A. (2020). Polymorphism of GC gene, encoding vitamin D binding protein, in aboriginal populations of Siberia. Ecological Genetics 18(2): 243-250.

https://doi.org/10.17816/ecogen18634

 

Michaëlsson, K., J.A. Baron, G. Snellman, R. Gedeborg, L. Byberg, J. Sundström et al. (2010). Plasma vitamin D and mortality in older men: a community-based prospective cohort study. American Journal of Clinical Nutrition 92(4): 841-848. https://doi.org/10.3945/ajcn.2010.29749 

 

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Ridley, M. (2000).Genome: The Autobiography of a Species in 23 Chapters. New York: HarperCollins.

 

Snellman, G., H. Melhus, R. Gedeborg, et al. (2009). Seasonal genetic influence on serum 25-hydroxyvitamin D levels: a twin study. PLoS ONE 4(11): e7747. https://doi.org/10.1371/journal.pone.0007747

 

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(2010). Circulating 25-hydroxyvitamin D and risk of pancreatic cancer, Cohort Consortium Vitamin D Pooling Project of Rarer Cancers. American Journal of Epidemiology 172(1): 81-93.

https://doi.org/10.1093/aje/kwq120

 

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