Please use this identifier to cite or link to this item:
|Title:||Large-scale candidate gene analysis of HDL particle features.|
|Authors:||Kaess, Bernhard M.|
Braund, Peter S.
Nelson, Christopher P.
Kalbitzer, Hans Robert
Rose, Lynda M.
Chasman, Daniel I.
Burton, Paul R.
Tobin, Martin D.
Samani, Nilesh J.
|Publisher:||Public Library of Science|
|Citation:||PLoS One, 2011, 6 (1), e14529.|
|Abstract:||Background: HDL cholesterol (HDL-C) is an established marker of cardiovascular risk with significant genetic determination. However, HDL particles are not homogenous, and refined HDL phenotyping may improve insight into regulation of HDL metabolism. We therefore assessed HDL particles by NMR spectroscopy and conducted a large-scale candidate gene association analysis. Methodology/Principal Findings: We measured plasma HDL-C and determined mean HDL particle size and particle number by NMR spectroscopy in 2024 individuals from 512 British Caucasian families. Genotypes were 49,094 SNPs in >2,100 cardiometabolic candidate genes/loci as represented on the HumanCVD BeadChip version 2. False discovery rates (FDR) were calculated to account for multiple testing. Analyses on classical HDL-C revealed significant associations (FDR<0.05) only for CETP (cholesteryl ester transfer protein; lead SNP rs3764261: p = 5.6*10−15) and SGCD (sarcoglycan delta; rs6877118: p = 8.6*10−6). In contrast, analysis with HDL mean particle size yielded additional associations in LIPC (hepatic lipase; rs261332: p = 6.1*10−9), PLTP (phospholipid transfer protein, rs4810479: p = 1.7*10−8) and FBLN5 (fibulin-5; rs2246416: p = 6.2*10−6). The associations of SGCD and Fibulin-5 with HDL particle size could not be replicated in PROCARDIS (n = 3,078) and/or the Women's Genome Health Study (n = 23,170). Conclusions: We show that refined HDL phenotyping by NMR spectroscopy can detect known genes of HDL metabolism better than analyses on HDL-C.|
|Rights:||Copyright: © 2011 Kaess et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.|
|Appears in Collections:||Published Articles, Dept. of Health Sciences|
Files in This Item:
|journal.pone.0014529.pdf||Published (publisher PDF)||1.18 MB||Adobe PDF||View/Open|
Items in LRA are protected by copyright, with all rights reserved, unless otherwise indicated.