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Explaining Race and Genetics: No Need to Despair
Response to Birney, Raff, Rutherford, & Scally
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It is good to have an essay which sets out a point of view clearly, so Ewan Birney’s 24th October blogpost (Ewan Birney, Jennifer Raff, Adam Rutherford, Aylwyn Scally) is welcome. A summary of this sort gives discussions of racial differences a focal point.

Race, genetics and pseudoscience: an explainer

It is not up to me, but I wonder if a more balanced title would have been: Race, genetics and science? Birney et al. give a general introduction to genetic discoveries and then refer to “darker currents” affecting current research:

A small number of researchers, mostly well outside of the scientific mainstream, have seized upon some of the new findings and methods in human genetics, and are part of a social-media cottage-industry that disseminates and amplifies low-quality or distorted science, sometimes in the form of scientific papers, sometimes as internet memes – under the guise of euphemisms such as ‘race realism’ or ‘human biodiversity’. Their arguments, which focus on racial groupings and often on the alleged genetically-based intelligence differences between them, have the semblance of science, with technical-seeming tables, graphs, and charts. But they’re misleading in several important ways. The aim of this article is to provide an accessible guide for scientists, journalists, and the general public for understanding, criticising and pushing back against these arguments.

Strong stuff. These misleading cottage dwellers are low grade people, it seems! So, the Birney et al. paper is not so much an “explainer” as an attack on a position with which they do not agree. No problem with that, but these authors seek to clothe themselves in the robes of righteousness, rarely a good stance in scientific debate.

Birney et al. argue that the standard descriptions of races:

(the) crude categorisations used colloquially (black, white, East Asian etc.) were not reflected in actual patterns of genetic variation, meaning that differences and similarities in DNA between people did not perfectly match the traditional racial terms. The conclusion drawn from this observation is that race is therefore a socially constructed system, where we effectively agree on these terms, rather than their existing as essential or objective biological categories.

The key phrase is “did not perfectly match”. A high re-definition. In fact, many people find that the new genetics is a pretty good match with the continental racial groupings in general use. As witness, the authors concede as much, and also use these terms when making various points in their arguments. There are genetic groupings in different continents. It seems a great leap to say that because the match with genetic research is good, but not perfect, we can reject objective biological categories based on DNA. Many researchers regard DNA classifications as an improvement on the older ones: there is plenty of overlap, but DNA provides finer detail, which increases our understanding of group differences. The authors will have none of this. They argue:

Even though geography has been an important influence on human evolution, and geographical landmasses broadly align with the folk taxonomies of race, patterns of human genetic variation are much more complex, and reflect the long demographic history of humankind.

Forgive me if I give a cheer here: this seems a most welcome concession: if DNA provides descriptions which “broadly align” with the old ones, why not accept this major point of agreement, shake hands, and move on? Apparently, we cannot do so because there is more genetic diversity within Africa than anywhere else. Africans are “just as different from each other as Africans are to non-Africans”.

I probably misunderstood Cavalli-Sforza and his genetic trees, and imagined that these divergent African groups in Africa were all at a significant genetic distance from those Africans who went walkabout out of Africa, and eventually became non-Africans. Can we ignore the finding that some African groups are genetically close and have a common ancestry; and that groups who later splinter away and leave Africa go on to develop differently on other continents? Furthermore, to understand what this diversity implies we should have population totals for each of the genetic African groups, and some evidence that they differ in intelligence. Currently, African country levels of IQ are pretty similar.Tribal differences would be interesting.

the real history of Homo sapiens is more like an overgrown thicket than a stately branching tree. Much of the population structure that we see today in ancestry testing results dates back only to a few thousand years or less. For example, the majority of European genomes are a mixture of at least three major groups within the last 10,000 years: the early hunter-gatherers who first populated the continent, a second wave of ancestry from the Near East associated with the spread of farming; and a third contribution from north Eurasia during the Bronze Age (2000–500 BCE).

So, genetic trees aren’t acceptable. Furthermore, I don’t see why a few thousand years is such a problem. Two thousand years, at one generation per 28 years, is 71 generations. If it is the 10,000 years of agriculture that is the time base, that provides 357 generations for the breeder’s equation to play out. Even 16 generations of very hard selection can bring about big changes in the relative proportions of different alleles. In fact, as luck would have it, a very recent publication shows that if brighter people move to London from coal mining areas and the less bright stay mining coal, then even in the short space of the British Industrial Revolution there will be evidence that those who go walkabout start differing from the local populations they leave behind.

Genetic correlates of social stratification in Great Britain. Published: 21 October 2019

Anyway, can’t we just display racial results using a Principal Components Analysis? Apparently not. The authors caution that data collection might be biased by:

existing cultural, anthropological or political groupings. If samples are collected based on pre-defined groupings, it’s entirely unsurprising that the analyses of these samples will return results that identify such groupings. This does not tell us that such taxonomies are inherent in human biology.

I can see that if geneticists only collect data say, from Protestants and not Catholics, or Sunni and not Shia, or even from Republicans and not Democrats, this could be a problem, but everyone lives in cultural and political groupings, researchers included, so why not take broad samples (like UK Biobank) across the world and then see if religious and political groupings show any genetic discriminators.

The authors are also against refining the concept of “race” to include new findings, and recommend it be dropped altogether, in favour of “populations”. No problem. They can use “populations”. Although different people may prefer different descriptors, if a name-change eases tensions, adopt it.

The authors then go on to make a general point about science:

It is often suggested that geneticists who emphasise the biological invalidity of race are under the thumb of political correctness, forced to suppress their real opinions in order to maintain their positions in the academy. Such accusations are unfounded and betray a lack of understanding of what motivates science.
The charge that thousands of scientists across the world are covering up a real discovery for fear of personal or wider social consequences is absurd.

I don’t know about “thousands of scientists” but researchers working in the field of genetics, particularly regarding intelligence, tell me they have to be careful what they publish. They fear that grants applications, always difficult and time-consuming, will fail if they announce they wish to work on racial differences in ability. As far as Jim Flynn could find, no such studies have been funded. It is a career risk.

The authors continue:

There are countless traits one can measure in humans, but none more controversial than those associated with intelligence, such as IQ. ‘Human biodiversity’ proponents tend to fixate on IQ, and one can speculate about why this is and what conclusions they wish to draw;

Only two paragraphs ago the authors denied unfounded accusations about researcher’s motivations (not how science works) and now they are wondering aloud what motivates researchers to discuss race and IQ!

On a brighter note, the authors accept that intelligence can be tested. They go on to concede that groups evolve to have different characteristics: lactic tolerance, oily fish tolerance and so on, but this, apparently, does not support the notion that races (populations) differ in a similar way. There can be local or regional adaptation but not larger scale adaptation, apparently. We now come to the nub of the paper:

IQ scores are heritable: that is, within populations, genetic variation is related to variation in the trait. But a fundamental truism about heritability is that it tells us nothing about differences between groups. Even analyses that have tried to calculate the proportion of the difference between people in different countries for a much more straightforward trait (height) have faced scientific criticisms.

Lewontin is rattling his chains yet again. I disagree with the claim that heritability tells us nothing about differences between groups. If something is heritable there must be a genetic mechanism which makes it so. If groups show any differences in skulls, faces, brains, body shapes, muscles, fat, bones, skin and hair then it is reasonable to test for genetic causes. It is a strong prior, and it would be odd to say that genetics has an effect on human behaviour, except in the specific case of comparing genetic groups.

As regards GWAS studies, the authors argue that the samples on which the published results are based are too selective: Finns and Sardinians are rejected because they have distinct genetic ancestries compared with other Europeans. They are not European enough. The final results are too European, and leave out interesting variations which might make Europeans more like other groups.

I see this as a feature, not a bug. Try the GWAS both ways, with and without the outlying groups, and compare the results. Once we get more data from other continents, particularly from Africa, then do the same on those results. Researchers (Lee et al. 2018) have already used European polygenic risk scores for intelligence on African samples, and the formula which predicts 11-14% of the intelligence variance in Europeans predicts 1.6% of the variance in Africans. Not much, but not nothing. Doing the same for polygenic height scores also results in a commensurate attenuation. European predictors don’t work well for Africans. (African sample n=1519 which is small). Both genetic groups probably have the same intelligence boosting variants, but not in the same positions on the genome, and not necessarily with the same frequency in their populations.

However, the authors consider they have found a deeper problem:

Simply put, nobody has yet developed techniques that can bypass the genetic clustering and removal of people that do not fit the statistical model mentioned above, while simultaneously taking into account all the differences in language, income, nutrition, education, environment, and culture that may themselves be the cause of differences in any trait observed between different groups.

Not all researchers are so pessimistic. Most researchers assume that environmental and cultural factors play a part in continental differences in intellectual achievements. If genetic studies on large samples come up with a null result for genetic predictors, this would strengthen the view that environmental factors are dominant. A null result would be highly informative, and would have a big impact on the debate about racial differences in intelligence. It is worth increasing the coverage of GWAS studies to the global population, and increasing our understanding of the power and limits of genetic predictors.

Cultural factors probably have two-way relationships with genetic effects: for example, cultural restrictions on marriage will limit the gene pool, and sharpen group characteristics. Some of these hypotheses can be tested by simple means: if culture and environment have strong effects, admixture studies will fail to generate accurate predictors. Merely knowing in the American continent for each country, or state/province, or local district, the percentage of the population that are of European origins will not predict anything much about intelligence, scholastic ability and wealth. Admixture studies provide a quick test of the plausibility of genetic hypotheses, and generate good predictors.

The authors make their final substantive point:

The genetic variants that are most strongly associated with IQ in Europeans are no more population-specific than any other trait. To put it bluntly, the same genetic variants associated with purportedly higher IQ in Europeans are also present in Africans, and have not emerged, or been obviously selected for, in recent evolutionary history outside Africa. Moreover, since it is a complex trait, the genetic variation related to IQ is broadly distributed across the genome, rather than being clustered around a few spots, as is the nature of the variation responsible for skin pigmentation. These very different patterns for these two traits mean that the genes responsible for determining skin pigmentation cannot be meaningfully associated with the genes currently known to be linked to IQ. These observations alone rule out some of the cruder racial narratives about the genetics of intelligence: it is virtually inconceivable that the primary determinant of racial categories – that is skin colour – is strongly associated with the genetic architecture that relates to intelligence.

This paragraph contains a number of elements.

First, that the SNPs that boost intelligence in Europeans are also found in Africans. Great. Are they found as frequently?

Second, that there is no evidence that they have emerged in non-Africans. I thought that there was evidence that there had been selection for such variants in Europeans (and some evidence of negative selection in Iceland). A matter of debate, it seems.

Third, the fact that intelligence SNPs are all over the genome, and skin pigmentation SNPs are clustered in a few spots means that “it is virtually inconceivable that the primary determinant of racial categories – that is skin colour – is strongly associated with the genetic architecture that relates to intelligence.” I am surprised at this line of reasoning, which turns on a very restrictive definition of race, another high re-definition. Skin colour is only one aspect of racial differences, though it has some predictive value. A more reasonable approach would be to look at all the characteristics which differ in racial groups, particularly those not visible, such as bone density. On the other hand, if we find no differences in the architecture and size of brains in different racial groups, that would be far more persuasive.

The authors go on to argue that, regarding black/white intelligence differences in the US, “It is our contention that any apparent population differences in IQ scores are more easily explained by cultural and environmental factors than they are by genetics.” It would certainly be good to have more studies outside the US. Brazil, for example, which had a far more relaxed attitude about different race marriages, and far less race-based strife, has racial differences in intelligence and scholastic attainment very much like those found in the US. Equally, the global results show that Africans in the US are higher achievers than Africans in Africa.

The authors mention the Flynn effect, but not that Flynn accepts that the secular rise in intelligence scores has not led to the disappearance of the black/white achievement gap, which he originally expected. For the record, Jim Flynn says hypotheses about the genetic origins of such differences should be tested.

The authors conclude their “explainer” thus:

By understanding both our history and contemporary research, we are emboldened by knowing that genetics has only served to undermine its own racist history.

Despite their polemical conclusion, there are points of agreement. Intelligence is worth testing. It would be good to have a wider representation of races/populations in GWAS studies. Scientists should be judged on the quality of their findings, not their presumed motivations. We should let the science move forward whether we like the results or not.

Of course, there are a number of points of disagreement.

The authors seem to argue that races are too similar genetically to account for the observed racial differences, ergo the differences are environmental; and at other times that races are too different genetically to be pooled together. Races cannot be simultaneously too similar and too different. (Diana Fleischman drew my attention to this contradiction).

They accuse researchers who argue for a genetic component in race differences of being “dark forces” on the fringes, yet say that any accusation that political correctness marginalises this debate is absurd.

They say that no analytic method can disentangle genetic from environmental/cultural factors when comparing racial groups. I don’t find the “argument from complexity” persuasive. If Brazilian findings are similar to United States findings, some of the US-specific cultural arguments can be discounted. If South East Asian post-colonial progress is better than African post-colonial progress then some of the negative effects of colonialism can questioned. If Chinese progress post 1980 has been faster than Indian progress since 1980 then genetic explanations can be investigated, and so on.

We should not despair. We should push on with studying the genetics of intelligence in all human populations. Many cultural differences will be a consequence of genetic differences, and some cultural habits will have genetic effects. A two-way street. The grand aim of all science [is] to cover the greatest number of empirical facts by logical deduction from the smallest possible number of hypotheses or axioms…

A noble aim.

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