GWAS on the Island of Kosrae Table 4. cont. Thyroid Stimulating Hormone 8 rs4704397 PDE8B C-Reactive Protein 9 rs7553007 rs1892534 rs7310409 rs780094 rs4129267 9 9 9 9 CRP LEPR HNF1A GCKR IL6R Caucasian Kosraen SNP Study Nearest Gene(s) Allele Freq P-value b on 500 k Freq P-value b Phet b Phet Freq A A A A A A 0.48 0.33 0.38 0.39 0.41 0.40 1.3E-11 0.21 same 3.0E-04 0.25 0.60 2.2E-26 6.5E-21 6.8E-17 6.7E-15 2.0E-8 20.20 same 20.17 same 20.15 rs2393791 0.14 same 20.10 rs4537545 0.03 0.13 3E-04 0.99 0.02 20.11 0.06 20.09 0.18 20.16 0.82 7E-4 0.01 20.10 1.00 0.77 0.38 0.82 0.44 0.73 0.36 0.28 0.86 0.03 2 0.12 2 1Frayling et al. (2007) Science 316:889. 2Loos et al. (2008) Nat Genet 40:768. 3Gudbjartsson et al. (2008) Nat Genet 40:609. 4Lettre et al. (2008) Nat Genet 40:584. 5Kathiresan et al. (2008) Nat Genet 40:189. 6Chen et al. (2008) J Clin Invest 118:2620. 7Weedon et al. (2005) Diabetes 54:576. 8Arnaud-Lopez et al. (2008) Am J Hum Genet 82:12. 9Ridker et al. (2008) Am J Hum Genet 82:1185. For SNPs not directly genotyped on the Affymetrix array (n = 9), association results are reported for a proxy on the Affymetrix chip with strong correlation (r2$0.95) to the original SNP in both HapMap Caucasian and Asian populations. The effect size (b) is expressed as the number of standard deviations change in phenotype for each copy of the associated allele. ‘‘Phet b’’ denotes p-values for the test of heterogeneity between the Caucasian and Kosrae effect sizes. SNPs with low frequency in Kosraens (MAF,0.05; n = 6) were omitted from the test of heterogeneity for effect sizes. ‘‘Phet Freq’’denotes p-values for similarity between frequency of the risk allele in Caucasians and Kosraens. SNPs not directly genotyped on the Affymetrix array were omitted from the comparison of allele frequencies. ‘‘2,’’ not analyzed. doi:10.1371/journal.pgen.1000365.t004 arising differences in allele frequency and LD patterns to aid in confirmation and fine mapping of common disease variants. Discussion We describe genome-wide association analyses in a population- based cohort with extensive family structure, and explore the value of genetic studies in a population isolate with high levels of linkage disequilibrium and relative allelic homogeneity [4]. Our goal was to take advantage of the population genetic features of this isolated population while maximizing the power to detect associations. We broke the extended Kosrae pedigree into sibships to create a computationally tractable dataset that uses as many genotyped individuals as possible. Empirical power calculations show that testing for association both within and between sibships gives more power than within-family tests alone. We used permutation testing and genomic control to correct for score inflation. Association to true biological variants was clearly observed for several known lipid loci, including APOE, CETP, HMGCR and APOC3/A5. Our ability to detect multiple loci with known association indicates that our analytic strategy is adequate to identify true disease loci. Suggestive evidence for association was observed for thyroid stimulating factor (TSH) to SNPs in the gene encoding thyroid transcription factor 2 (TTF-2), a strong biological candidate with no previously known association. Associations near APOC3/A5 for triglycerides and near TTF-2 for TSH also highlight the possibility of island-specific variants or differences in LD between Kosraens and Caucasians that may be useful in identifying causal variants common to both populations. Our study tests the hypothesis that reduced genetic diversity, genetic drift and/or natural selection might have resulted in a class of common alleles with large effects on metabolic phenotypes. Reduced diversity is evident in our study and consistent with our earlier observations [4], with 20% of the SNPs (n.109,000) passing technical quality filters having minor allele frequencies ,0.01 in Kosraens. Empirical estimates of study power showed that we have 95% power to observe effects explaining $5% phenotypic variance at p,1026. And yet, no large effects of this sort were detected. This is similar to the pattern observed in other populations, where the majority of common variants have individually modest effects, typically explaining #2% of pheno- typic variance [21,22,35–37]. Our genome-wide data expand on and confirm previous work suggesting that many genes of small effect influence trait variation in both outbred and founder populations such as Kosrae [38]. While our cohort encompasses ,65% of the adult population on Kosrae, limited sample size, coupled with substantial relatedness between study participants, reduces the power of our study in comparison to recently published genome-wide associa- tion studies and meta-analyses for common diseases. It is interesting, given the widespread and reasonable predictions that gene-by-gene and gene-by-environment effects modulate marginal associations, that a comparison of allele frequencies and the direction/magnitude of effects for loci originally identified in Caucasian cohorts shows that a majority with statistically indistinguishable effects in Kosraens. We also note that the set of biologically relevant variants influencing metabolic traits is unlikely to be wholly identical between Kosraens and Caucasians. For example, heritability of total plasma cholesterol is similar in Kosraens and Caucasians, but the population mean is approximately 20 mg/dL lower in Kosraens. Variants specific to Kosraens may underlie the phenotypic difference between populations; these variants may lie in novel genes or genes previously implicated in disease or trait variation. Identification of such variants in Kosraens and other ethnic groups may shed light on biological pathways and aspects of disease biology that might otherwise be overlooked in purely Caucasian studies. PLoS Genetics | www.plosgenetics.org 13 February 2009 | Volume 5 | Issue 2 | e1000365