Genome-Wide Association Studies of Plasma Lipids

For those who have witnessed the evolution of genetic association studies of plasma lipids since 1983, the field has had its roller-coaster moments. The early high points followed from the application of “restriction fragment length polymorphism” analysis to yield candidate genotypes that were statistically evaluated for association with plasma lipoproteins. After 2 decades, though, the candidate gene approach had produced only negligible replicable associations, notably with genotypes for the canonical APOE isoforms and some others.1 Because of this inconsistency, enthusiasm for candidate gene association studies had essentially been exhausted by 2005. However, in late 2007, association studies experienced a renaissance and have generated important new findings for lipoprotein metabolism.See accompanying article on page 2264 The reasons underlying this resurrection have been widely discussed2 and include both new technology—namely, microarrays to genotype hundreds of thousands of single-nucleotide polymorphisms (SNPs)—plus very large sample sizes, permitting metaanalysis of individual-level or summary data from tens of thousands of individuals. Over the last 3 years, genome-wide association studies (GWASs) have identified robust, replicable statistical associations for numerous complex diseases and traits, including plasma lipids. The basic GWAS design and workflow are shown in the Figure. The study by Waterworth et al in the current issue of Arteriosclerosis, Thrombosis, and Vascular Biology illustrates both strengths and limitations of the GWAS approach.3 Figure. A path for discovery and translation phases of GWASs is shown. Step 1 indicates the study design: population-based or case-control samples for continuous and discrete trait analysis, respectively. After microarray-based genotyping, step 2 indicates the statistical testing approach: generally, linear regression analysis for a quantitative trait and χ2 …