Finding genes and variants for lipid levels after genome-wide association analysis

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Abstract
We review the main findings from genome-wide association studies (GWAS) for levels of HDL-cholesterol, LDL-cholesterol and triglycerides, including approaches to identify the functional variant(s) or gene(s). We discuss study design and challenges related to whole genome or exome sequencing to identify novel genes and variants. GWAS have detected approximately 100 loci associated with one or more lipid trait. Fine mapping of several loci for LDL-cholesterol demonstrated that the trait variance explained may double when the functional variants responsible for the association signals are identified. Experimental follow-up of three loci identified by GWAS has identified functional genes GALNT2, TRIB1, and SORT1, and a functional variant at SORT1. The goal of genetic studies for lipid levels is to improve treatment and ultimately reduce the prevalence of heart disease. Many signals identified by GWAS have modest effect sizes, useful for identifying novel biologically relevant genes, but less useful for personalized medicine. Whole genome or exome sequencing studies may fill this gap by identifying rare variants of larger effect associated with lipid levels and heart disease.

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