Demirkan A, Amin N, Isaacs A, Jarvelin MR, Whitfield JB, Wichmann HE, Kyvik KO, Rudan I, Gieger C, Hicks AA, Johansson Å, Hottenga JJ, Smith JJ, Wild SH, Pedersen NL, Willemsen G, Mangino M, Hayward C, Uitterlinden AG, Hofman A, Witteman J, Montgomery GW, Pietiläinen KH, Rantanen T, Kaprio J, Döring A, Pramstaller PP, Gyllensten U, de Geus EJ, Penninx BW, Wilson JF, Rivadeneria F, Magnusson PK, Boomsma DI, Spector T, Campbell H, Hoehne B, Martin NG, Oostra BA, McCarthy M, Peltonen-Palotie L, Aulchenko Y, Visscher PM, Ripatti S, Janssens AC, van Duijn CM, ENGAGE CONSORTIUM
Eur. J. Hum. Genet. 19 (7) 813-819 [2011-07-00; online 2011-03-30]
Serum concentrations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TGs) and total cholesterol (TC) are important heritable risk factors for cardiovascular disease. Although genome-wide association studies (GWASs) of circulating lipid levels have identified numerous loci, a substantial portion of the heritability of these traits remains unexplained. Evidence of unexplained genetic variance can be detected by combining multiple independent markers into additive genetic risk scores. Such polygenic scores, constructed using results from the ENGAGE Consortium GWAS on serum lipids, were applied to predict lipid levels in an independent population-based study, the Rotterdam Study-II (RS-II). We additionally tested for evidence of a shared genetic basis for different lipid phenotypes. Finally, the polygenic score approach was used to identify an alternative genome-wide significance threshold before pathway analysis and those results were compared with those based on the classical genome-wide significance threshold. Our study provides evidence suggesting that many loci influencing circulating lipid levels remain undiscovered. Cross-prediction models suggested a small overlap between the polygenic backgrounds involved in determining LDL-C, HDL-C and TG levels. Pathway analysis utilizing the best polygenic score for TC uncovered extra information compared with using only genome-wide significant loci. These results suggest that the genetic architecture of circulating lipids involves a number of undiscovered variants with very small effects, and that increasing GWAS sample sizes will enable the identification of novel variants that regulate lipid levels.