Worldwide differentiation at disease related SNPs

the objective:

To address the strength of the CDCV model on a worldwide scale and to evaluate the effects of local positive selection on worldwide risk allele frequencies, we present allele frequencies and levels of population differentiation across 53 populations for 25 SNPs which show replicated association with the following common complex human diseases: Crohn’s disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity [17, 26-42]

the conclusion:

disease-associated SNPs do not show more population differentiation than random SNPs

I'm not so sure why one would expect a different result if you're looking at a set of polymorphisms related to risk to a bunch of different "diseases" (am I the only one getting tired of this term?). Also, I wonder, how exactly did they pick the 25 SNPs? Do the diseases in question differ in prevalence between worldwide populations? They may answer these in the paper, but my cursory reading of the paper did not find answers.
Also, I remember someone blogging about this paper a while back, because one of the figures looked very familiar. I thought it was someone at GNXP, but I can't find it... anyone know??

Worldwide population differentiation at disease-associated SNPs.
Myles S, Davison D, Barrett J, Stoneking M, Timpson N.
BMC Med Genomics. 2008 Jun 4;1(1):22. [Epub ahead of print]

Abstract: BACKGROUND: Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs). METHODS: We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohns disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals. RESULTS: On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations. CONCLUSIONS: Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.