This paper proposes that geography is a better determinant of human genetic variation than ethnicity (read: race). There are two problems with the paper.
One, they use the proportion of shared alleles as a measure of similarity. Under this measure, three populations A, B, C that share the same alleles will be grouped as similar, even if the alleles occur in very similar frequencies in A and B and different frequencies in C. Sharing of alleles is expected to be influenced by geography: most alleles are pan-human, and few are population specific; racial differentiation consists both in different frequency of pan-human alleles and possession of population specific variants.
Two, their claim that geography is a better predictor than ethnicity is due to the fact that their geographical determinant is complex, consisting of pairwise geographical distances between the 51 populations, whereas their ethnicity determinant is simple, consisting of population placement in one of four clusters. It is not surprising that a complex predictor explains more variance than a simpler alternative, but this has little to do with the superiority of geography over ethnicity as a predictor.
Human Genetics (Online first)
Geography is a better determinant of human genetic differentiation than ethnicity
Andrea Manica et al.
Individuals differ genetically in their susceptibility to particular diseases and their response to drugs. However, personalized treatments are difficult to develop, because disease susceptibility and drug response generally have poorly characterized genetic architecture. It is thus tempting to use the ethnicity of patients to capture some of the variation in allele frequencies at the genes underlying a clinical trait. The success of such a strategy depends on whether human populations can be accurately classified into discrete genetic ethnic groups. Despite the heated discussions and controversies surrounding this issue, there has been essentially no attempt so far to quantify the relative power of ethnic groups and geography at predicting the proportion of shared alleles between human populations. Here, we present the first such quantification using a dataset of 51 populations typed at 377 autosomal microsatellite markers, and show that pair-wise geographic distances across landmasses constitute a far better predictor than ethnicity. Allele-sharing between human populations worldwide decays smoothly with increasing physical distance. We discuss the relevance of these patterns for the expected distribution of variants of medical interest. The distribution patterns of gene coding for simple traits are expected to be highly heterogeneous, as most such genes experienced strong natural selection. However, variants involved in complex traits are expected to behave essentially neutrally, and we expect them to fit closely our predictions based on microsatellites. We conclude that the use of ethnicity alone will often be inadequate as a basis for medical treatment.