Sesardic (2010) makes the point that the fact that genetic variation within a group is of larger than variation between (the average of) the groups does not mean that the groups cannot be distinguished. This point is not, however, sufficient to rehabilitate a biological picture of race. I continue from the previous post to sketch the issues we face once we delve deeper into the relevant scientific knowledge, concepts, methods, and questions for inquiry…
2. Putting point #1 aside, suppose we imagine an original human gene pool that dispersed at some point of time from its origins in Africa around the world and was not subject to subsequent breeding among widely dispersed parts of the pool. Cluster analysis techniques could be used on genetic data to divide humans into, say, N groups. Such clustering techniques are sensitive to assumptions that determine whether groups are of roughly equal size or are a mix of a few large groups. If we looked for groups that had similar within-group genetic variation, most of the N groups would be in Africa. In other words, the traditional subdivisions of human races would have to be reformulated. However, experience using cluster analysis in large agricultural data sets (Cooper and Hammer 1996) suggests that many individuals cannot be consistently be assigned to one group versus another; the grouping changes according to what traits (in our case, variants at genetic loci or SNPs) and how much each group is represented in the data.
3. Suppose we now add migration subsequent to the initial dispersal, but without cross-breeding among the groups. Picking up this last point in #2, if individuals from non-African groups outweigh those from African groups in, say, the United States, then how well could we recover from the U.S. data all the groups delineated in #2? That would be an empirical question, but the experience from agriculture warns us not to be optimistic.
4. Of course, #3 is only a thought-experiment. There has been considerable migration and cross-breeding subsequent to the initial dispersal from the place of human origin in Africa, including but not confined to the recent centuries of cross-Atlantic slavery and master-slave relations. How well could we recover from current individuals the one or more groups (as delineated in #2) that make up the individuals´ ancestry? Again, this is an empirical question. Biomedical researchers do not have to be politically biased to judge that research efforts might be more fruitfully directed along other avenues, such as those indicated by biomedical correlates of socially defined race (i.e., not the groups that would emerge from the cluster analyses in #2).
5. Perhaps, we could ask less than we have in #4. Rather than full recovery of original ancestries, we might seek simply want to predict whether an individual patient has some major biomedically relevant genes that differed, on average, among the original groups. These predictions, necessarily probabilistic, would be limited in value given the recently-emerged consensus that most medically significant traits are associated with many genes of quite small effect (McCarthy et al. 2008). Moreover, given that the groups delineated in #2 would not match the traditional subdivisions of human races or those current in the U.S.—there would be several different groups of African origin—medical practitioners would need to disregard superficial assignments to racial groups. They might just as well test directly for the presence or absence of the biomedically relevant genes.
6. If we put #1-5 aside and imagine a world in which we were able to use genetic information to assign humans to original post-dispersal groups as reliably as in the statistics class we were able to assign individuals to male and female groups. What could we do with that knowledge that there is a difference between the average genetic profiles for groups A and B when there is large within-group variation for most genetic loci (at least, for those that vary within the human species)? Let me accentuate this question with using the IQ test score case Sesardic has paid considerable attention to (2005). Suppose we knew (which we do not) that only a certain small set of genes influenced IQ test scores. What could we do with the knowledge that there is a large difference between the average IQ test score for two groups and this difference is smaller than the within-group variation? (To visualize this situation, imagine one of the axes in the Figure is IQ test score.) I would not use my ability to assign humans to original post-dispersal groups based on genetic profiles as grounds for using an individual´s membership in a group to make educational or employment decisions for the individual. But I will not speak for Sesardic; I do not know what he thinks would follow if a biological view of race were to be rehabilitated along the lines he discusses.
7. There are clearly many issues to be delved deeply into before the relevant science about human genetic variation would support a biological notion of human ancestral groupings. A biological notion of socially and historically varying racial categories lies well outside the scope of “what the best contemporary science tells us about human genetic variation.”
References
Cooper M, Hammer GL (eds) (1996). Plant Adaptation and Crop Improvement. CAB International, Wallingford, UK.
McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JPA, Hirschhorn JN (2008) Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics 9: 356-369.
Sesardic N (2010) Race: A Social Destruction of a Biological Concept. Biology and Philosophy 25:143-162.