Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Meta-Analysis
. 2012 Nov 2;91(5):823-38.
doi: 10.1016/j.ajhg.2012.08.032. Epub 2012 Oct 11.

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

Folkert W Asselbergs  1 , Yiran Guo, Erik P A van Iperen, Suthesh Sivapalaratnam, Vinicius Tragante, Matthew B Lanktree, Leslie A Lange, Berta Almoguera, Yolande E Appelman, John Barnard, Jens Baumert, Amber L Beitelshees, Tushar R Bhangale, Yii-Der Ida Chen, Tom R Gaunt, Yan Gong, Jemma C Hopewell, Toby Johnson, Marcus E Kleber, Taimour Y Langaee, Mingyao Li, Yun R Li, Kiang Liu, Caitrin W McDonough, Matthijs F L Meijs, Rita P S Middelberg, Kiran Musunuru, Christopher P Nelson, Jeffery R O'Connell, Sandosh Padmanabhan, James S Pankow, Nathan Pankratz, Suzanne Rafelt, Ramakrishnan Rajagopalan, Simon P R Romaine, Nicholas J Schork, Jonathan Shaffer, Haiqing Shen, Erin N Smith, Sam E Tischfield, Peter J van der Most, Jana V van Vliet-Ostaptchouk, Niek Verweij, Kelly A Volcik, Li Zhang, Kent R Bailey, Kristian M Bailey, Florianne Bauer, Jolanda M A Boer, Peter S Braund, Amber Burt, Paul R Burton, Sarah G Buxbaum, Wei Chen, Rhonda M Cooper-Dehoff, L Adrienne Cupples, Jonas S deJong, Christian Delles, David Duggan, Myriam Fornage, Clement E Furlong, Nicole Glazer, John G Gums, Claire Hastie, Michael V Holmes, Thomas Illig, Susan A Kirkland, Mika Kivimaki, Ronald Klein, Barbara E Klein, Charles Kooperberg, Kandice Kottke-Marchant, Meena Kumari, Andrea Z LaCroix, Laya Mallela, Gurunathan Murugesan, Jose Ordovas, Willem H Ouwehand, Wendy S Post, Richa Saxena, Hubert Scharnagl, Pamela J Schreiner, Tina Shah, Denis C Shields, Daichi Shimbo, Sathanur R Srinivasan, Ronald P Stolk, Daniel I Swerdlow, Herman A Taylor Jr, Eric J Topol, Elina Toskala, Joost L van Pelt, Jessica van Setten, Salim Yusuf, John C Whittaker, A H Zwinderman; LifeLines Cohort Study; Sonia S Anand, Anthony J Balmforth, Gerald S Berenson, Connie R Bezzina, Bernhard O Boehm, Eric Boerwinkle, Juan P Casas, Mark J Caulfield, Robert Clarke, John M Connell, Karen J Cruickshanks, Karina W Davidson, Ian N M Day, Paul I W de Bakker, Pieter A Doevendans, Anna F Dominiczak, Alistair S Hall, Catharina A Hartman, Christian Hengstenberg, Hans L Hillege, Marten H Hofker, Steve E Humphries, Gail P Jarvik, Julie A Johnson, Bernhard M Kaess, Sekar Kathiresan, Wolfgang Koenig, Debbie A Lawlor, Winfried März, Olle Melander, Braxton D Mitchell, Grant W Montgomery, Patricia B Munroe, Sarah S Murray, Stephen J Newhouse, N Charlotte Onland-Moret, Neil Poulter, Bruce Psaty, Susan Redline, Stephen S Rich, Jerome I Rotter, Heribert Schunkert, Peter Sever, Alan R Shuldiner, Roy L Silverstein, Alice Stanton, Barbara Thorand, Mieke D Trip, Michael Y Tsai, Pim van der Harst, Ellen van der Schoot, Yvonne T van der Schouw, W M Monique Verschuren, Hugh Watkins, Arthur A M Wilde, Bruce H R Wolffenbuttel, John B Whitfield, G Kees Hovingh, Christie M Ballantyne, Cisca Wijmenga, Muredach P Reilly, Nicholas G Martin, James G Wilson, Daniel J Rader, Nilesh J Samani, Alex P Reiner, Robert A Hegele, John J P Kastelein, Aroon D Hingorani, Philippa J Talmud, Hakon Hakonarson, Clara C Elbers, Brendan J Keating, Fotios Drenos
Collaborators, Affiliations
Meta-Analysis

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

Folkert W Asselbergs et al. Am J Hum Genet. .

Abstract

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 ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼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.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Summary of the Design Used and the Number of Individuals Involved and p Value Thresholds Used in Each Step
Figure 2
Figure 2
Manhattan Plots for HDL-C, LDL-C, TC, and TG Data from the IBC Lipid Meta-analysis Show p Values Based on Those Obtained from the METAL Meta-analysis
Figure 3
Figure 3
Venn Diagram per Phenotype for the Comparison of the Three Models Used Model 1 corrects only for population stratification; model 2 corrects for population stratification, age, and lipid medication; and model 3 corrects for population stratification, age, T2D, smoking, BMI, and lipid medication. Only signals with p < 2.4 × 10−6 are included.
See this image and copyright information in PMC

References

    1. Lopez A.D., Mathers C.D., Ezzati M., Jamison D.T., Murray C.J. Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data. Lancet. 2006;367:1747–1757. - PubMed
    1. Berenson G.S., Srinivasan S.R., Bao W., Newman W.P., 3rd, Tracy R.E., Wattigney W.A. Association between multiple cardiovascular risk factors and atherosclerosis in children and young adults. The Bogalusa Heart Study. N. Engl. J. Med. 1998;338:1650–1656. - PubMed
    1. Arsenault B.J., Boekholdt S.M., Kastelein J.J. Lipid parameters for measuring risk of cardiovascular disease. Nat Rev Cardiol. 2011;8:197–206. - PubMed
    1. Di Angelantonio E., Sarwar N., Perry P., Kaptoge S., Ray K.K., Thompson A., Wood A.M., Lewington S., Sattar N., Packard C.J., Emerging Risk Factors Collaboration Major lipids, apolipoproteins, and risk of vascular disease. JAMA. 2009;302:1993–2000. - PMC - PubMed
    1. Weiss L.A., Pan L., Abney M., Ober C. The sex-specific genetic architecture of quantitative traits in humans. Nat. Genet. 2006;38:218–222. - PubMed

Publication types

Grants and funding