Adaptations to Climate Table 3. Coefficients and p-Values (in Parentheses) for Pigmentation Candidate SNPs. Method Gene SNP Latitude Summer PC1 Summer PC2 Winter PC1 Winter PC2 Summer SWRF Winter SWRF Bayesian geographic analysisa ASIP rs6058017 0.52 (0.88) OCA2 rs1800404 0 (0) OCA2 rs1800410 0.12 (0.07) SLC24A5 rs1426654 0 (0) SLC45A2 rs16891982 0 (0) TYR rs1042602 0.08 (0.25) Spearman rank correlationa ASIP rs6058017 0.23 (0.58) OCA2 rs1800404 0.7 (0) OCA2 rs1800410 0.03 (0.92) SLC24A5 rs1426654 0.59 (0.01) SLC45A2 rs16891982 0.59 (0.01) TYR rs1042602 0.53 (0.01) 0.31 (0.72) 0 (0) 0.97 (0.93) 0 (0) 0.46 (0.94) 0.11 (0.25) 0.02 (0.9) 0.49 (0.08) 0.33 (0.16) 0.7 (0) 0.65 (0.04) 0.64 (0.04) 0.58 (0.8) 0.95 (0.1) 0.03 (0.03) 0.8 (0.4) 1 (0) 0.37 (0.85) 0.18 (0.54) 0.3 (0.19) 0.42 (0.09) 0.02 (1) 0.06 (0.9) 0.05 (0.79) 0.18 (0.43) 0 (0) 0.01 (0) 0 (0) 0 (0) 0.18 (0.42) 0.2 (0.62) 0.61 (0) 0.25 (0.41) 0.4 (0.16) 0.42 (0.14) 0.34 (0.24) 0 (0.02) 0.73 (0.68) 0.15 (0.19) 0.96 (0.1) 0 (0.01) 0.36 (0.65) 0.45 (0) 0.07 (0.64) 0.04 (0.75) 0.05 (0.74) 0.21 (0.22) 0.15 (0.4) 0.35 (0.81) 0.08 (0.19) 0.23 (0.3) 0 (0) 1 (0) 0.07 (0.17) 0.01 (0.92) 0.41 (0.13) 0.37 (0.1) 0.61 (0.04) 0.55 (0.05) 0.59 (0.04) 0.94 (0.12) 1 (0) 0.06 (0.09) 0.91 (0.18) 1 (0) 0.84 (0.41) 0.41 (0.13) 0.64 (0) 0.09 (1) 0.44 (0.11) 0.52 (0.02) 0.44 (0.1) aBayesian geographic analysis coefficients range from zero to one, whereas Spearman coefficients range from negative one to one. For both statistics, empirical p-values are two-tailed. Bolded values represent significance with p 0.01. doi:10.1371/journal.pgen.0040032.t003 short-wave radiation ﬂux than the causative SNP. Similarly, with the Bayesian geographic analysis, several SNPs show a signal that is as strong as that carried by the causative SNP. These results suggest that, while there is strong signal at the SLC24A5 gene (with as high as 60% SNPs with p , 0.05), there is not sufﬁcient resolution in the SNP-based signal to distinguish the causative SNP from other correlated SNPs. Discussion Our goal was to test the hypothesis that climate, and in particular cold and heat stress, exerted strong selective pressures on the biological processes underlying common metabolic disorders in humans. To select a group of genes likely to have experienced similar selective pressures, we exploited the knowledge-base gleaned from studies of the metabolic syndrome and its phenotypes coupled with a bioinformatics approach based on network theory. Common variation in these genes was systematically captured by genotyping tag SNPs in a worldwide population panel and the data were analyzed to characterize the spatial patterns of variation. Based on the assumption that selection varies according to measurable aspects of climate, we show that the spatial distribution of allele frequencies in genes involved in metabolic processes is signiﬁcantly different from that of unconstrained SNPs. Although we cannot exclude the possibility that other environmental variables correlated with climate drove part of the signals of spatially varying selection, our results argue for a role of climate adaptations in the biological processes underlying the metabolic syndrome and its phenotypes. The ﬁnding that variation in candidate genes for common metabolic disorders was selected because it increased tolerance to climatic extremes is supported by the link between a number of non-disease metabolic traits and the phenotypes of the metabolic syndrome. For example, variation in energy balance is likely to be related to obesity risk, through variation in food intake, body mass index, and basal metabolic rate. Basal metabolic rate has been shown to vary among species [70] as well as among human populations [26,27,71] as a function of environmental temperature, and this variation is thought to be related to the need for increased heat production to maintain homeostasis in colder climates [27]. Blood glucose levels are increased in individuals with T2D, which might increase survival in cold temperatures [72]. Elevated levels of sugar and sugar derivatives in the blood have been found in some cold-adapted species [1]. Changes in blood serum triglycerides and HDL cholesterol [73,74] with acclimation to cold environments have been documented in humans. Optimal sodium retention may differ among climates and variation in sodium retention is likely to affect hypertension risk. In hot, humid environ- ments, high sodium retention may be necessary, whereas high sodium retention may be deleterious in cooler environments [20]. Therefore, because of the partial overlap between common metabolic disorders and cold-adaptive phenotypes, the subset of SNPs with strong signals of spatially varying selection detected in this study can be considered strong candidates for the genetic susceptibility to the metabolic syndrome. Consistent with the idea of a link between the genetic susceptibility to metabolic disorders and adaptations to climate, many of the SNPs with strong signals in our analysis were also associated with metabolic phenotypes. As a general observation, this may not be surprising: genes were included in the analysis because of prior evidence of association with metabolic disorders. However, the speciﬁc patterns observed at SNPs in which signals of spatially varying selection coincided with evidence of association with speciﬁc pheno- types were not dictated by our study design. For example, several of the SNPs showing strong patterns with winter PC1, which summarizes mainly winter temperatures and latitude, are also known to play a role speciﬁcally in cold tolerance. Perhaps the best case is the nonsynonymous 109R allele in LEPR; this allele increases in frequency with decreasing winter temperatures and is associated with increased respi- ratory quotient (CO2 released:O2) [75], consistent with a role in non-shivering thermogenesis [75,76]. This derived allele was also reported to be associated with lower BMI, lower abdominal sagittal diameter, and lower systolic and diastolic blood pressure [75,76]. In addition, Wauters et al. [77] found an association for the LEPR 109R allele with fasting insulin levels and insulin response in women with impaired glucose tolerance, suggesting a role in the pathogenesis of T2D. PLoS Genetics | www.plosgenetics.org 0007 February 2008 | Volume 4 | Issue 2 | e32