Genome-wide association studies (GWAS) have identified .500 common variants associated with quantitative metabolic
traits, but in aggregate such variants explain at most 20–30% of the heritable component of population variation in these
traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in
.6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes
case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding
sequence and 59 and 39 untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits
(serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both
single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype
associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant
evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found
significant gene-level evidence of association to non-synonymous variants with MAF,1%. Additionally, two potentially
deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094,
a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference
populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated
population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped
samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.