Obesity genomics: assessing the transferability of susceptibility loci across diverse populations

Abstract

The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single nucleotide polymorphism (SNP) and locus-wide comparisons. SNPs in FTO and near MC4R, obesity-susceptibility loci first identified in Europeans, replicate widely across other ancestries. SNP-to-SNP comparisons suggest that more than half of the 36 body mass index-associated loci are shared across European and East Asian ancestry populations, whereas locus-wide analyses suggest that the transferability might be even more extensive. Furthermore, by taking advantage of differences in haplotype structure, populations of different ancestries can help to narrow down loci, thereby pinpointing causal genes for functional follow-up. Larger-scale genetic association studies in ancestrally diverse populations will be needed for in-depth and locus-wide analyses aimed at determining, with greater confidence, the transferability of loci and allowing fine-mapping. Understanding similarities and differences in genetic susceptibility across populations of diverse ancestries might eventually contribute to a more targeted prevention and customized treatment of obesity.

Figure 1

Obesity-susceptibility loci discovered through genome-wide association studies (GWAS) for body mass index (blue), three waves of GWAS for waist circumference and waist-to-hip ratio (pink) and two waves of GWAS for extreme and early onset of obesity (green). Each Venn diagram represents the loci from one paper, except for papers that discovered only one locus, that is, the fat mass and obesity associated gene FTO [14,15,33] and the near-MC4R loci [16,36], for which no Venn diagram was drawn. An additional three BMI-associated loci (TOMM40-APOE-APOC1, SREBF2, and NTRK2) were identified using the gene-centric ITMAT-Broad-Candidate Gene Association Resource (IBC) array [21]; these are not depicted. Figure modified and updated from Loos [11].

Figure 2

Effect sizes for (a) the 32 BMI-associated SNPs identified in European ancestry populations and (b) the five BMI-associated SNPs identified in East Asian ancestry populations. The lighter shaded bars represent the effect sizes (and 95% confidence interval (CI)) in European ancestry populations [19] (in both (a) and (b)), the darker shaded bars represent the effect sizes (and 95% CI) in East Asian ancestry populations [38,39]. Data were obtained and adapted from Wen et al. [39] and are presented in Table 1. Asterisks indicate SNPs that reached genome-wide significance in GWAS meta-analyses of East Asian ancestry populations [39]. SD, standard deviation.

Figure 3

SNP-to-SNP comparison of (a) effects on BMI, (b) frequency of BMI-increasing alleles, and (c) explained BMI variance in East Asian ancestry populations (y-axis) and European ancestry populations (x-axis) of the 32 BMI-associated loci identified in European ancestry populations (blue diamonds) and five BMI-loci additionally identified in East Asian ancestry populations (green squares). Data were obtained and adapted from Wen et al. [39] and are presented in Table 1. SD, standard deviation.

Figure 4

Regional plots of (a,b) the GP2/GPRC5B and (c,d) the CDKAL1 loci in East Asian ancestry populations [39]and European ancestry populations, respectively [19]. SNPs are plotted by position on the chromosome against association with BMI (-log10 P-value). Recombination rates (from HapMap) are plotted in blue to reflect the local LD structure. The SNPs surrounding the most significant SNP (in purple) are color coded to reflect their LD with this SNP (r² values from the HapMap CHB/JPT and CEU data, respectively).