\n<\/p>\n
How do scientists talk about race? For quite some time a
\nsmall group of geneticists have been engaged in deep conversations about how
\nbest to convey the complexities of, and the relationship between race, DNA, and
\nhuman variation to the general public. We come from different backgrounds\u2014Ewan
\nis the director of the European Bioinformatics Institute, Adam is a geneticist
\nand science writer, Aylwyn is a human evolutionary geneticist, and I am an
\nanthropological geneticist\u2014and nationalities, but are united in our agreement
\nthat patterns of human genetic variation do not support the biological division
\nof people into races.<\/p>\n
Over the course of a year, we worked together on a statement
\nthat best reflects our consensus view of human genetic variation, race, and
\neven the fraught topic of race and IQ. We wanted to correct the misconceptions
\nthat many people have about these topics, and directly confront a number of untrue
\nideas promoted by a small group of pseudo-scientists who refer to themselves as
\n\u201crace realists\u201d or proponents of \u201chuman biological diversity\u201d (HBD). <\/p>\n
The result is a (rather lengthy) statement which Ewan has posted in its entirety here<\/a>. I want to summarize its main points here with excerpts, but I encourage everyone to go read the whole thing. We intend for this statement to contribute to the ongoing conversation between scientists, social scientists, scholars in the humanities, the media, and the public.<\/p>\n (Also please note that I kept the original British spellings The biological race concept emerges from a particular Research in the 20th century found Describing race as a social construct does not undermine its Human population structure is not race<\/strong><\/p>\n Some people claim that the Geneticists use a variety of tools Traits, IQ, and genetic diversity<\/strong><\/p>\n \u2018Human biodiversity\u2019 proponents Such tales, and the claims about (Most genome-wide association studies This, in turn, can confuse people IQ scores are heritable: that is, Not only that, the genetic However, there are some strong Finally, multiple lines of evidence The history of our species is complex and convoluted, and our genomes reflect that. As we delve deeper into the DNA of the people of the world, the science of genetics becomes even more complex too. But we see no scientifically sound evidence that contemporary genetics can be used to recapitulate biological or historical concepts for race. It is our duty and wish that this understanding is spread far and wide. <\/p>\n Ewan Birney<\/p>\n European Molecular Biology Jennifer Raff<\/p>\n Department of Anthropology, Adam Rutherford<\/p>\n Genetics, Evolution & Aylwyn Scally<\/p>\n Department of Genetics, University The authors wish to thank Stuart Ritchi<\/a>e for his valuable contributions to our discussion.<\/em><\/p>\n<\/p>\n **Note: comments for this post are not enabled**<\/p>\n
\nin excerpts that I quoted from the statement). <\/p>\n
\nhistory<\/strong><\/p>\n
\nthat the crude categorisations used colloquially (black, white, East Asian
\netc.) were not reflected in actual patterns of genetic variation, meaning that
\ndifferences and similarities in DNA between people did not perfectly match the
\ntraditional racial terms. The conclusion drawn from this observation is that
\nrace is therefore a socially constructed system, where we effectively agree on
\nthese terms, rather than their existing as essential or objective biological
\ncategories. <\/p>\n
\nexistence, nor its importance; it merely points out that there is no
\nfundamental biological basis for race.<\/p>\n
\nexquisitely detailed picture of human variation that we can now obtain by
\nsequencing whole genomes contradicts this. Recent studies, they argue, actually
\nshow that the older notions of races as biological categories (some dating back
\nto the 18th<\/sup> century) were basically correct in the first place. As
\nevidence for this they often point to the images produced by analyses in
\nstudies that seem to show natural clustering of humans into broadly continental
\ngroups based on their DNA. But these claims misinterpret and misrepresent the
\nmethods and results of this type of research. Populations do show both genetic
\nand physical differences, but the analyses that are cited as evidence for the
\nconcept of race as a biological category actually undermine it.<\/p>\n
\nto visualise the subtle and complex patterns of genetic variation between
\npeople, and to mathematically cluster them together based on relatedness. Such
\nmethods are helpful for exploring data, but have also been the source of wider
\nconfusion. For example, Principal Component Analysis (PCA) plots often show
\ndistinct, colourful clusters of dots that appear to separate groups of people
\nfrom different parts of the world. In some cases, these clusters even seem to
\ncorrespond to traditional racial groupings (e.g. \u2018Africans\u2019, \u2018Europeans\u2019 and
\n\u2018Asians\u2019). It is images such as these which are often deployed as genetic
\nevidence for the existence of separate races. But these methods can be misleading
\nin ways which non-experts \u2013 and even some specialists \u2013 are unaware of. For
\nexample, some of the observed genetic clustering is a reflection of the samples
\nthat were included in the study and how they were collected, rather than any
\ninherent genetic structure. DNA sample collection typically follows existing
\ncultural, anthropological or political groupings. If samples are collected
\nbased on pre-defined groupings, it\u2019s entirely unsurprising that the analyses of
\nthese samples will return results that identify such groupings. This does not
\ntell us that such taxonomies are inherent in human biology.<\/p>\n
\nsometimes assert that alleged
\ndifferences in the mean value of IQ when measured in different populations \u2013
\nsuch as the claim that IQ in some sub-Saharan African countries is measurably
\nlower than in European countries \u2013 are caused by genetic variation, and thus
\nare inherent. The purported genetic differences involved are usually attributed
\nto recent natural selection and adaptation to different environments or
\nconditions. Often there are associated stories about the causes of this
\nselection, for example that early humans outside Africa faced a more
\nchallenging struggle for survival, or that via historical persecution and
\nrestriction of professional endeavours, Ashkenazi Jews harbour genes selected
\nfor intellectual and financial success.<\/p>\n
\nthe genetic basis for population differences, are not scientifically supported.
\nIn reality for most traits, including IQ, it is not only unclear that genetic
\nvariation explains differences between populations, it is also unlikely. To
\nunderstand why requires a bit of background.<\/p>\n
\nfor detecting variants associated with complex traits such as IQ, known as
\nGWAS) have been carried out in populations sampled from across Europe, and have
\nancestries consistent with this sampling. In many cases though, only certain
\nsubsets of people are included in these analyses \u2013 for good scientific reasons.
\nFor example, samples of \u201cEuropean\u201d populations used in genetic studies often
\nhave excluded up to as many as 30% of self-identified Europeans. This is
\nbecause some individuals introduce hard-to-model complications into the data,
\nforming distinct sub-clusters or complicating the genetic model. For example,
\nFinns and Sardinians are often excluded as they have quite distinct genetic
\nancestries compared to many other Europeans, as are some people in India, north
\nAfrica, Latino\/Hispanics, and many individuals with complex ancestries, despite
\nconfident self-identification within their ethnic group. Researchers therefore
\noften exclude them from the set of people used in a particular GWAS analyses,
\non the basis that their unique population histories can invalidate the
\nstatistical models used in these techniques.<\/p>\n
\nwho read the studies and observe distinct and seemingly \u2018natural\u2019 population
\nclusters emerge. If they aren\u2019t familiar with the practice of removing these
\nindividuals with more complex ancestries (or don\u2019t read the detailed methods,
\nwhich are often tucked away in elusive supplementary sections of a published
\npaper), they could easily be misled into thinking that the populations in these
\nanalyses are much more distinct than they are in reality. The resulting biases
\nare poorly understood, and the terminology involved can be confusing to
\nnon-specialists. Furthermore, while it is clear to GWAS researchers that the results
\nof their analyses tend to be specific to the population studied and their
\npredictions cannot be reliably extended to other populations with very
\ndifferent ancestry, this is not widely recognised or understood by
\nnon-specialists.<\/p>\n
\nwithin populations, genetic variation is related to variation in the trait. But
\na fundamental truism about heritability is that it tells us nothing about
\ndifferences between<\/em>
\ngroups. Even analyses that have tried to calculate the proportion of the
\ndifference between people in different countries for a much more
\nstraightforward trait (height) have faced scientific criticisms. Simply put,
\nnobody has yet developed techniques that can bypass the genetic clustering and
\nremoval of people that do not fit the statistical model mentioned above, while
\nsimultaneously taking into account all the differences in language, income,
\nnutrition, education, environment, and culture that may themselves be the cause
\nof differences in any trait observed between different groups. This applies to
\nany trait you could care to look at \u2013 height, specific behaviours, disease
\nsusceptibility, intelligence.<\/p>\n
\nknowledge we gain from studying our mainly-European pools of participants
\nbecomes highly unreliable when it is applied to those with different
\nancestries. Although it is a common trope to argue that we will have the answer
\nto the question of the genetic basis of group differences in traits \u201cin the
\nnext five years\u201d, or \u201cin the next decade\u201d, the advances in genomics reveal that
\nthe question is far more complex than we could have imagined, even just a few
\nyears ago. Consequently, anyone who tells you that there\u2019s good evidence on how
\nmuch genetics explain group differences (rather than individual differences) is
\nfooling you \u2013 or fooling themselves.<\/p>\n
\nhints towards the answer. The genetic variants that are most strongly
\nassociated with IQ in Europeans are no more population-specific than any other
\ntrait. To put it bluntly, the same genetic variants associated with purportedly higher IQ in
\nEuropeans are also present in Africans, and have not emerged, or been obviously
\nselected for, in recent evolutionary history outside Africa. Moreover, since it
\nis a complex trait, the genetic variation related to IQ is broadly distributed
\nacross the genome, rather than being clustered around a few spots, as is the
\nnature of the variation responsible for skin pigmentation. These very different
\npatterns for these two traits mean that the genes responsible for determining
\nskin pigmentation cannot be meaningfully associated with the genes currently
\nknown to be linked to IQ. These observations alone rule out some of the cruder
\nracial narratives about the genetics of intelligence: it is virtually inconceivable
\nthat the primary determinant of racial categories \u2013 that is skin colour \u2013 is
\nstrongly associated with the genetic architecture that relates to
\nintelligence. <\/p>\n
\nindicate that there are complex environmental effects (as might reasonably be
\nexpected) on measures of IQ and educational attainment. Many socioeconomic and
\ncultural factors are entangled with ancestry in the countries where these
\nstudies are often performed \u2013 particularly in the USA, where structural racism
\nhas historically and continues to hugely contribute to economic and social
\ndisparities. We cannot use populations in these countries to help answer the
\nquestion of why IQ scores are claimed to be lower in other countries with entirely different
\nsocial, economic, and cultural histories, nor to answer the role of genetics
\nfor alleged differences
\nin IQ measures between groups inside a country with strong societal differences
\nlinked to ancestry (for example, the USA). Thus, confident assertions that
\ncurrent GWAS show us that \u2018race\u2019 is associated with cognitive function are
\nsimply wrong. It is our contention that any apparent population differences in IQ scores
\nare more easily explained by cultural and environmental factors than they are
\nby genetics.<\/p>\n<\/div>\n<\/div>\n
\nLaboratory, European Bioinformatics Institute<\/p>\n
\nUniversity of Kansas.<\/p>\n
\nEnvironment, University College London<\/p>\n
\nof Cambridge<\/p>\n