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Large-scale candidate gene analysis of HDL particle features
Authors:Kaess Bernhard M  Tomaszewski Maciej  Braund Peter S  Stark Klaus  Rafelt Suzanne  Fischer Marcus  Hardwick Robert  Nelson Christopher P  Debiec Radoslaw  Huber Fritz  Kremer Werner  Kalbitzer Hans Robert  Rose Lynda M  Chasman Daniel I  Hopewell Jemma  Clarke Robert  Burton Paul R  Tobin Martin D  Hengstenberg Christian  Samani Nilesh J
Institution:Department of Cardiovascular Science, University of Leicester, Leicester, United Kingdom.
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.
Keywords:
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