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Nicholas Wade’s recent book on the biology of human races, A Troublesome Inheritance, has by now been reviewed in many venues. We focus on the book and its conclusions here because it is the most recent attempt to racialize genomics and serves as an excellent example of the problems with such endeavors. The book has a simple structure. The first part argues that scientific orthodoxy can be stifling, and that to break away from it brave purveyors of truth must speak out. The second section argues that there is indeed genetic evidence for the biological basis of race. And the third suggests that, because there are races, we can now pinpoint a reason why different peoples purportedly behave differently. In his Wall Street Journal review of Wade’s curious volume, the libertarian political scientist Charles Murray suggests that the book’s last part would be the target of most criticism, reasoning that:
The orthodoxy’s clerisy will take that route, ransacking these chapters [the final five chapters] for material to accuse Mr. Wade of racism, pseudoscience, reliance on tainted sources, incompetence and evil intent. You can bet on it [italics added]. (Murray 2014)
Our intent here is to examine the science and premises in the first two parts (five chapters) of Wade’s book. We can safely ignore its third part, because it can only be taken seriously if the premises in those first five chapters have scientific validity—and it is clear to us they do not.
Our reading of the first half of A Troublesome Inheritance indicates that Wade has made at least seven mistakes that are routinely committed when genomics and genetic information are used both to examine the biological basis for human races and when they are used as a justification for reifying race as a biological reality. We start with a foundational problem that all scientists face:
1. Misunderstanding the Nature of Hypothesis Testing
This first aspect of the “biology of race” controversy gets at the very core of what science is, and indeed of what the problems really are in understanding human variation. It is commonly accepted that the hypothetico-deductive (hypothesis-testing) approach provides the most sound and productive way to conduct science. In contrast, inductive approaches are to be avoided, because induction can only confirm what one already knows. This latter position might at first sound extreme; for if you have an approach that confirms a scientific phenomenon, why not use it? The answer is simple: science advances through the rejection of false hypotheses, while inductive processes will always give you a positive answer. Hence, with respect to “racial” variation in human populations, the proper approach is to pose hypotheses and subsequently test them.
As we saw in the last chapter, STRUCTURE is one of the methodologies most commonly applied in the analysis of human population genetic information. And unfortunately, it takes an entirely inductive approach, throwing data at an algorithm and asking: “How many units do I have?” Wade cites this method approvingly as the ultimate proof that there are five races of humankind. But while the algorithm itself is an important technical advance, how the results of such analyses bear on definitions of “race” is an entirely separate question because of the inquiry’s inherently inductive nature. As we saw, inductive approaches can do a great job of summarizing and displaying information given prior knowledge of a system, and can thus encourage the formulation of new hypotheses and the refinement of existing ones. But what they cannot do is test those hypotheses.
To make scientific statements about race, then, we need to have hypotheses in hand, arrived at inductively or otherwise. So what useful hypotheses can we offer up with respect to human genetics and the existence of human races? The most obvious one is:
H0 = There are n “races” of a type of organism (A) that correspond to the n geographical divisions (often taken to be Africa, Asia, and Europe) that we see on the planet today.
But simply posing our hypothesis in these terms brings us to the second problem with using biology to “prove” race.
2. Subjectivity in Defining Race (or a Misunderstanding of What a Species Is)
How can we test a hypothesis of the kind we have just presented? First of all, we need a definition of race that is both objective and operationally testable. Without such a definition, we cannot proceed to test the hypothesis. We cannot ask an algorithm to give us an idea of the number of races, because that would be in itself inductive. We do have a good idea of what species themselves are; but the definitions of the subordinate units of race and subspecies are substantially less than objective. In fact, we defy any scientist, journalist, philosopher, or layperson to come up with a meaningful definition of race in this context and in such a way that it might be used to test our hypothesis H0. And if this can’t be done, H0 becomes useless scientifically. However, you might change the hypothesis to:
H1 = There are n species of a type of organism (A, B, and C) corresponding to the geographical divisions (for the sake of argument, Africa, Asia, and Europe) that we see on the planet today.
In this case we do have a testable hypothesis, because we do have an operational definition of species. You might object that this is just semantics. But in fact, objective definitions are hugely important in hypothesis testing. Without objective criteria to test our hypotheses, we simply cannot reject those hypotheses.
But then you might say, “I will objectively define a race as being a group differentiated from other closely related entities.” This is slightly better, but it is still subjective and untestable, because “differentiated” is an extremely vague term. Putting numbers on it does not necessarily help; for example, if you refine your definition by saying that “a race is a group of organisms that are 50 percent divergent from the next most closely related group of things,” you still have two problems. The first is that the 50 percent figure is entirely arbitrary, and others might think this “magic” number is not so magical. Most scientists will agree that genetic or morphological cohesion, reproductive isolation, or both lie at the core of what a species is. But there is no consensus as to what degree of divergence is significant as entities go their own separate ways in nature. For one group the magic number might be 5 percent, so that if it achieves over a 5 percent divergence level the probability is high that it will end up with complete divergence—hence becoming a new species. But for another group of organisms, the magic number might well be 95 percent.
A second problem is that whatever percent divergence you might choose, it must mean something biologically. The species definition that most taxonomists use requires 100 percent divergence in relevant traits. The question is an either/or one, and there is no subjectivity to it. The biological meaning of that 100 percent is that your entity is no longer meaningfully reproducing or significantly swapping genes with its closest relatives. It is on its own separate and historically established evolutionary trajectory. Percent divergence might mean something if researchers could pin down a magic threshold; but as we have seen, this is a very slippery concept indeed.
Yet this is how Wade described the process of species formation in a broadcast interview on CNN in June 2014: “Since evolution happens all the time, it’s a continuous, unstoppable process that as a population splits, the two halves will continue to evolve, but now independently. So, over time they will accumulate differences between each other and eventually they’ll become new species.”
While we know from experience that radio interviews can be harrowing, and that it is difficult to explain things completely in short sound bites, this description of species formation is quite close to the portrayal he provides in his book. And what is particularly enlightening is that, directly before offering this definition, Wade had said: “Regionality underlines the fact of race because the populations on each continent have been evolving independently since we left our African homeland about 50,000 years ago.”
The subjective perception of species, population evolution, and regionality expressed here leads to unwarranted conclusions about the existence of any entity below the level of the species Homo sapiens. This appears to reflect a failure on Wade’s part to grasp the subtleties of taxonomic science. And this misapprehension has led to the third error we see in his reasoning.
3. A Misunderstanding of the Rigors of Taxonomic Science
Understanding our origins, and indeed the biology of all organisms on the planet, is really a problem of taxonomy. This vital branch of natural history is sometimes derided as “stamp collecting,” but this claim could hardly be farther from the truth. Taxonomy is a well-developed and highly scientific endeavor that has been around in some form ever since humans began to name things. The science of taxonomy combines simple but rigorous hypothesis-testing approaches with objective definitions of species. It is true that competent taxonomists occasionally use the terms “subspecies” and “race” in their descriptions, but only as conveniences to imply future hypotheses to be tested.
Why is this “name game” so important for a discussion of race? We point to the following example from the pseudoscientific and white nationalist “journal” the Occidental Quarterly. This publication claims to have an academic and intellectual approach to the issues it addresses, but whiteness and nationalism almost always become the focus. The racist way the journal has approached the science of genetic and genomic bearings on race has been likened to some of the more extreme material that regularly appears in Breitbart News. In 2008, Andrew Hamilton (a pseudonym) published an article entitled “Taxonomic Approaches to Race.” He started with a quote from the journalist Natalie Angier, who has written about Craig Venter, one of the scientists who led the release of the first draft of the human genome sequence. Angier characterized Venter—correctly—as implying that “there is only one race—the human race.” Hamilton then continued by declaring, “The mawkish sentiment reported by Natalie Angier is incorrect. In biology, race is a synonym for subspecies” (Hamilton 2008, 11).
He went on to point out that race designations pervade the study of the natural world in organisms like insects, rabbits, cats, dogs, mice, horses, etc. But then he defined race as “a recognizably distinct division…distinguished from other groups by its unique clustering of genetically transmitted anatomical, physiological, psychological, and behavioral traits” (Hamilton 2008, 12). Well, thank you, Mr. Hamilton (or whatever your real name is) for clarifying that you feel race and subspecies are synonyms and that clusters are an important concept in naming races. But only one of these statements is correct (race equals subspecies); and much more importantly, the other (clusters are a test of taxonomic unit existence) is flat-out wrong, as we have seen.
Hamilton’s declaration raises two important factors that we have pointed to throughout this book. Subspecies (races) are indeed recognized ranks; but as we hope to have shown, a subspecies rank is a placeholder, a hypothesis of species existence. Once this hypothesis is rejected, we are obliged to leave it and move on to other more testable and more interesting hypotheses. And in the human case, this hypothesis has repeatedly been tested—and rejected. We have discussed the clustering approach to organizing populations at length and have shown that it has severe shortcomings in testing hypotheses about the existence of taxonomic units. At best, the clusters are hypotheses that themselves need to be tested.
The genomic approach to the existence of races in human beings has usually involved collecting the frequencies of variants at many locations in the human genome from increasingly larger numbers of people. Of course, nobody would put much stock in a test of a hypothesis that involved only two individuals from each of the geographic regions suspected of diverging. For, as we have seen, if one examines too few individuals there is a danger of overdiagnosing the number of entities (i.e., of finding purely random evidence for differentiation). Similarly, examining too few populations will also result in overdiagnosis. Consider the following scenario: populations of a cosmopolitan organism are examined for their genetic variability by sequencing the genomes of individuals from Africa and Oceania. Not surprisingly, some genetic differences are detected and found to be significant, in that some are unique to the individuals from Africa while others are unique to individuals from Oceania. A big hoopla could be made, and species existence could be claimed; but this would be poor science, because the severity of the test is so low as to make it meaningless. Why? Because the organism might also exist in Europe, the Americas, and East Asia. By leaving out the populations “in between,” one would miss the connectedness of the two populations initially sequenced. This phenomenon in widely distributed populations led the human biologist Frank Livingstone many years ago to conclude that “there are no human races, there are only clines” (Livingstone 1962, 279).
Wade understands this. Here is how he describes a genome-level polymorphism study and how it can be interpreted in a taxonomic context. He first uses the Rosenberg et al. (2002) study that we discussed in the last chapter to suggest that there are five clusters of people on the planet. As we saw, this important study used genomic information (nearly four hundred markers) from one thousand people, and employed the STRUCTURE clustering approach. The one thousand subjects “clustered naturally into five groups, corresponding to the five continental races.” Wade apparently feels it is unimportant that this study was soon criticized by several researchers who objected that intermediate populations needed to be examined to exclude potential clinal variation. He then describes the Rosenberg group’s next study of 2005, which increased the number of markers to nearly one thousand and yielded similar results (Ramachandran et al. 2005). And he suggests that the addition of more data in this case addressed the “cline” criticism. But while more data always help, the critical addition in this case would not be more genetic markers but more individuals from different geographic areas. These were not forthcoming, but Wade nevertheless uses the expanded genomic information (i.e., the doubling of the number of markers) to state categorically that “they found the clusters are real.” [italics added].
More importantly for our argument about taxonomy, Wade goes on to discuss the inclusion of new information (using a newer genetic survey technology than the one used in the Rosenberg group’s studies) to address the problem. In this newer study, one thousand different individuals were surveyed, but from fifty-one well-defined geographic areas. And instead of five, the researchers involved clustered their subjects into seven major groups. What is more, when even more subjects were added to Rosenberg and colleagues’ data set, as was done by Sarah Tishkoff and her colleagues, fourteen clusters were inferred (Bryc et al. 2010). You might smell a rat here. But here is how Wade handles this new information:
It might be reasonable to elevate the Indian and Middle Eastern groups (the two new ones) to the level of major races, making seven in all. But then many more subpopulations could be declared races, so to keep things simple, the five-race continent based scheme seems the most practical for most purposes. (Wade 2015, 177).
Any self-respecting taxonomist would avoid the kind of language Wade uses here. It is unscientific and circular. He is saying that just because inferences about the number of races vary, we cannot say that races do not exist. This is a variation on the argument that while people disagree on the number of shapes, shapes still exist—which simply trivializes the definitions we use in science generally and in taxonomy specifically.
There are six to seven billion human beings on the planet, and the best test of any hypothesis about human genomes and populations would include them all. Of course, this is not possible at present and probably never will be. But if it were possible, and the clustering were performed as in the two studies we have just referred to, we wonder how many groups might fall out. We suspect that, depending on the markers used, it might be as many as the entire number of nuclear families there are on the planet. Certainly, the patterns that would emerge from such a global analysis would not be anywhere near a clear demonstration of any definition of race that one could generate. Clustering alone is obviously inadequate for addressing problems of this kind in taxonomy and systematics. Which brings us to the fourth mistake made by proponents of a biological basis for race.
4. Misunderstanding the Meaning of Clustering and Evolutionary Trees
Wade’s “evidence” for the biological basis of races is based purely on clustering. But clustering is only one way genetic data (or any other kind of discrete data) can be analyzed to test hypotheses. Perhaps a better approach is to use a branching diagram based on reconstructing the evolutionary events that led to the branches. Significantly, Wade does not present this kind of information or analysis in his book, possibly because researchers have for a long time realized that branching diagrams cannot represent the patterns of evolution of individuals that belong to the same species—something that directly reflects the difficulty and artificiality of sorting individuals into races. Branching diagrams can be very useful when used on single genes, and are extremely informative when used on clonal molecules like the maternally inherited mitochondrial DNA and the paternally inherited Y chromosome. But to our knowledge, no properly conceived attempt to build evolutionary trees with many recombining genetic regions, such as those on our autosomes, has ever resulted in a tree with any significant resolution.
The bottom line here, then, is that any attempt to arrive at a hierarchical structuring of humans using phylogenetic trees based on the entire genome will give us an unrecognizable and unresolved bush. But if that is the case, why do clustering methods appear to recover “structure”? We suggest that part of the reason relates to the next mistake in our list, the one that is made in doing genetic studies of geographically separated human populations by cherry-picking, or the phenomenon we prefer to call the “Stephen Colbert effect.”
5. Cherry-picking AIMs: The Stephen Colbert Effect
Most of the early clustering studies used around one thousand genetic markers. More recent studies up the ante into the hundreds of thousands. These markers are chosen because they are believed to be informative about human ancestry, which as we have already noted is why they are known as “ancestral informative markers,” or AIMs. These markers are established using what we like to call the “white swan” principle. People of different geographic origins have their genomes scanned, and when a variant appears at high frequency for a particular geographic location, that variant is said to be a marker for people from the geographic region concerned.
It is safe to say that this procedure introduces a bias into how the data are interpreted. This bias is so extreme that, when Stephen Colbert was presented with a genetic survey of his genome on the PBS show Faces of America, he was told he is 100 percent Caucasian. Some of the other guests were given similar results: Yo-Yo Ma was told he is 100 percent Asian. But some individuals were shocked by their results, among them Eva Longoria, who was given figures that deviated considerably from her prior view of her ancestry.
What was going on? Well, currently there are nearly thirty million places along the chromosomes of humans (out of three billion total) at which humans may vary. But any two randomly chosen humans will typically vary at only about three million bases. So if the typical ancestry study uses three hundred thousand markers (not too far from the actual number examined by commercial laboratories nowadays), it will only be looking at 10 percent of the potential differences between any two genomes, or about 0.1 percent of the entire genome. At best, then, these studies scan less than 1 percent of a human genome. What about the other 99 percent? Much of this remainder is not variable; but that part of it which is variable is African in origin. This means that 99 percent of the total variation in any human genome should be considered African. And what that in turn means is that Stephen Colbert is actually 99 percent African, and at most 1 percent Caucasian.
An argument commonly used to contradict this observation is known as the “Mount Everest paradox.” The argument goes as follows: The elevation of Mount Everest differs from the surface of the ocean by an incredibly small fraction (about 0.0008) of the earth’s diameter. But anyone standing at the foot of Mount Everest can tell the difference, and it is huge. Again, though, this is a trivial and unscientific argument. One could just as easily argue that, to a bacterium, a golf ball looks like Mount Everest (indeed, a similar 0.0002 percentage diameter-wise is involved). But any golfer can tell you how hard it is to find a golf ball in the rough. It is not the changes or differences that matter, but rather what the differences mean, and whether there is any objective way to interpret them. Some researchers prefer to interpret this information in the context of ancestry, which brings us to the sixth major mistake Wade makes.
6. Conflating Racially Based Genetic Differences with Explanation of Ancestry
The broad availability of genetic testing has made it something of a routine among people who are interested in their ancestry. But what do those ancestry tests actually tell us? They basically inform us about the chunks of DNA in our genomes and where that DNA might have originated. This is, of course, about individuals, and more specifically about genes; but very unfortunately, ancestry testing has become a proxy for race determination. This is particularly unfortunate, because everyone’s genome is a mosaic of ancestries, even including chunks of DNA that might show ancestry from other species. And it is particularly misleading when it comes to our understanding of race in humans, because there are no definitions as to how many genomic variants (and even more complicated, which variants) might make a difference. Because ancestry can be traced unbroken all the way to the nuclear-family level, we strongly suggest that the ancestry approach is not informative in any way relative to the hypotheses we proposed in the first part of this piece. Like race, ancestry is clinal with respect to any purported higher level and simply connects us with one another. So what, in the end, do those genetic ancestry tests tell us? Perhaps the best way to view the whole ancestry business is to use a term that has recently appeared in the literature to describe commercially available ancestry tests: “recreational genomics.” Such recreational approaches offer little, if anything, to science. It is even arguable whether they offer much to those engaged in the recreation.
It is often argued that we need to speak about races if we wish to study the movements of people around the planet and determine their evolutionary histories. But this is entirely false, because our knowledge of mtDNA and Y chromosomes, supplemented by the archaeological and fossil records, already provides an excellent picture of how humans migrated in the past. We are not impeded at all in these endeavors by the lack of formally defined biological races, because we use clinal markers that follow individual haplotypes. No a priori definition of race is needed to interpret the results of such tree-based analyses. It is also argued that ancestry is an important component in medicine; and the leap is then made to the claim that knowledge of a person’s race is essential to the maintenance of his or her health. However, medicine is already benefiting from individualized genomics; and because, as we pointed out in our book Race? Debunking a Scientific Myth, race and ancestry have in the past proven poor clinical tools, we see few cogent reasons to consider race a major factor in medicine. Perhaps ancestry will prove to be important; but the concept of race in medicine is clearly barking up the wrong tree.
7. Conflating Variation and Allele Frequency Differences with Adaptation (and Hence Elements of the Human Condition)
Adaptation and allele frequencies are the focus of Wade’s last five chapters and were extensively discussed in our Race? Debunking a Scientific Myth. Wade seems to believe that we need a notion of races to explain why some of us look different from others. Yet nearly all the (remarkably few) “adaptations” that can be identified—for example, the diverse responses to high-altitude living and to living under intense solar radiation—tend to be intensely local in their occurrence and are not at all usefully illuminated by any concept of major “races.”
Charles Murray placed his bet—that attacks on Wade’s book would be made along more sociological than scientific lines—based on his allegation that scientists would fear breaking away from tyrannical orthodoxy. Wade addresses this tyranny issue in the first few pages of A Troublesome Inheritance. He is concerned that unorthodox thinking tends to get stifled by convention such that progress, both scientific and social, is impeded. We could not disagree more with Murray and Wade on this matter, but in this book we have deliberately refrained from going anywhere near that kind of argument. To us, the most important thing is that when the science Wade cites is placed under real scrutiny, the thesis of his book fails miserably, and Mr. Murray loses his bet.
Wade’s insistence that science advances by departure from orthodoxy might be called the “Indiana Jones fallacy.” And it is especially important to understand quite how destructive this fallacy is, because in line with what appears to be a growing distrust of science in many corners of society, all the authors of positive reviews of Wade’s book (Murray’s included) have harped on the far-reaching importance of Wade’s own departure from despotic scientific orthodoxy. As scientists, we recognize how gratifying it would be if every published scientific paper was earthshaking and unorthodox. This would make scientific progress excitingly rapid and unbounded. But the sad truth is that much of science is rather boring and procedural—just as rigor demands.
Even the hypothesis that there are genetic differences among people from different geographic regions—classifiable or not—is entirely mundane. Of course there are differences among us, as there are among members of any widespread species. We do not need to spend millions of dollars sequencing genomes to know this. The real questions are whether the differences are in any way significant; whether they are interpretable in a rigorous scientific context; and whether the classification of people into races does anything useful to help us understand them. The answers here are clear. While the differences are there, they are superficial—for the most part they are simply epiphenomena of the last few tens of millennia of human evolution—and they do not sort out well at all on larger scales. And, as to whether racial classifications help us to understand anything at all, the answer is a resounding “No!”
This last point may seem at first glance a bit counterintuitive, because as we noted at the beginning of this book, it is often possible to visually sort a certain proportion of your fellow citizens by general geographic origin. And indeed, for almost all the past fifty thousand years or so during which Homo sapiens has been widely present throughout the Old World, our hunting-gathering precursors were sparsely spread out across vast landscapes and constantly buffeted by rapidly changing climatic and environmental conditions. This provided optimal circumstances for regional differentiation and the incorporation of minor genetic novelties into local populations; and it explains why, for example, Africans generally tend to resemble each other more closely than they do Eastern Asians or Europeans. But throughout, all of us remained members of one single, inter-breeding species; and we guarantee that the edges between populations were never sharp. What is more, over the ten thousand years that have elapsed since the adoption of a more settled way of life, demographic circumstances have changed entirely, as populations have mingled on large and small scales and often over vast distances. This, above all, is why it is hopeless to look for the boundaries that are necessarily there if we are to usefully recognize races or to pretend that the enterprise of looking for them is in any way scientific. The central tendencies may be there, but the boundaries are not. Which, of course, means that race is a totally inadequate way of characterizing diverse humankind, or even of helping us to understand humanity’s glorious variety.