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Asselbergs, F.W.* ; Guo, Y.R.* ; van Iperen, E.P.A.* ; Sivapalaratnam, S.* ; Tragante, V.* ; Lanktree, M.B.* ; Lange, L.A.* ; Almoguera, B.* ; Appelman, Y.E.* ; Barnard, J.* ; Baumert, J.J. ; Beitelshees, A.L.* ; Bhangale, T.R.* ; Chen, Y.D.I.* ; Gaunt, T.R.* ; Gong, Y.* ; Hopewell, J.C.* ; Johnson, T.* ; Kleber, M.E.* ; Langaee, T.Y.* ; Li, M.Y* ; Li, Y.R.* ; Liu, K.A.* ; McDonough, C.W.* ; Meijs, M.E.* ; Middelberg, R.P.S.* ; Musunuru, K.* ; Nelson, C.P.* ; O'Connell, J.R.* ; Padmanabhan, S.* ; Pankow, J.S.* ; Pankratz, N.* ; Rafelt, S.* ; Rajagopalan, R.* ; Romaine, S.P.R.* ; Schork, N.J.* ; Shaffer, J.* ; Shen, H.Q.* ; Smith, E.N.* ; Tischfield, S.E.* ; van der Most, P.J.* ; van Vliet-Ostaptchouk, J.V.* ; Verweij, N.* ; Volcik, K.A.* ; Zhang, L.* ; Bailey, K.R.* ; Bailey, K.M.* ; Bauer, F.* ; Boer, J.M.A.* ; Braund, P.S.* ; Burt, A.* ; Burton, P.R.* ; Buxbaum, S.G.* ; Chen, W.* ; Cooper-DeHoff, R.M.* ; Cupples, L.A.* ; deJong, J.S.* ; Delles, C.* ; Duggan, D.* ; Fornage, M.* ; Furlong, C.E.* ; Glazer, N.* ; Gums, J.G.* ; Hastie, C.* ; Holmes, M.V.* ; Illig, T. ; Kirkland, S.A.* ; Kivimaki, M.* ; Klein, R.* ; Klein, B.E.* ; Kooperberg, C.* ; Kottke-Marchant, K.* ; Kumari, M.* ; LaCroix, A.Z.* ; Mallela, L.* ; Murugesan, G.* ; Ordovas, J.* ; Ouwehand, W.H.* ; Post, W.S.* ; Saxena, R.* ; Scharnagl, H.* ; Schreiner, P.J.* ; Shah, T.* ; Shields, D.C.* ; Shimbo, D.* ; Srinivasan, S.R.* ; Stolk, R.P.* ; Swerdlow, D.I.* ; Taylor, H.A.* ; Topo, E.J.* ; Toskala, E.* ; van Pelt, J.L.* ; van Setten, J.* ; Yusuf, S.* ; Whittaker, J.C.* ; Zwinderman, A.H.* ; Anand, S.S.* ; Balmforth, A.J.* ; Berenson, G.S.* ; Bezzina, C.R.* ; Boehm, B.O.* ; Boerwinkle, E.* ; Casas, J.P.* ; Caulfield, M.J.* ; Clarke, R.* ; Connell, J.M.* ; Cruickshanks, K.J.* ; Davidson, K.W.* ; Day, I.N.M.* ; de Bakker, P.I.W.* ; Doevendans, P.A.* ; Dominiczak, A.E.* ; Hall, A.S.* ; Hartman, C.A.* ; Hengstenberg, C.* ; Hillege, H.L.* ; Hofker, M.H.* ; Humphries, S.E.* ; Jarvik, G.P.* ; Johnson, J.A.* ; Kaess, B.M.* ; Kathiresan, S.* ; Koenig, W.* ; Lawlor, D.A.* ; Maerz, W.* ; Melander, O.* ; Mitchell, B.D.* ; Montgomery, G.W.* ; Munroe, P.B.* ; Murray, S.S.* ; Newhouse, S.J.* ; Onland-Moret, N.C.* ; Poulter, N.* ; Psaty, B.* ; Redline, S.* ; Rich, S.S.* ; Rotter, J.I.* ; Schunkert, H.* ; Sever, P.* ; Shuldiner, A.R.* ; Silverstein, R.L.* ; Stanton, A.* ; Thorand, B. ; Trip, M.D.* ; Tsai, M.Y.* ; van der Harst, P.* ; van der Schoot, E.* ; van der Schouw, Y.T.* ; Verschuren, W.M.M.* ; Watkins, H.* ; Wilde, A.A.M.* ; Wolffenbuttel, B.H.R.* ; Whitfield, J.B.* ; Hovingh, G.K.* ; Ballantyne, C.M.* ; Wijmenga, C.* ; Reilly, M.P.* ; Martin, N.G.* ; Wilson, J.G.* ; Rader, D.J.* ; Samani, N.J.* ; Reiner, A.P.* ; Hegele, R.A.* ; Kastelein, J.J.P.* ; Hingorani, A.D.* ; Talmud, P.J.* ; Hakonarson, H.* ; Elbers, C.C.* ; Keating, B.J.* ; Drenos, F.*

Large-scale gene-centric meta-analysis across 32 studies identifies multiple lipid loci.

Am. J. Hum. Genet. 91, 823-838 (2012)
DOI PMC
Open Access Green as soon as Postprint is submitted to ZB.
Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering similar to 2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Genome-wide Association ; Density-lipoprotein Cholesterol ; Coronary-heart-disease ; Familial Hypercholesterolemia ; Apolipoprotein B-100 ; Missing Heritability ; Plasma Triglycerides ; Quantitative Traits ; Statistical-model ; Complex Traits
Reviewing status