A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians - PubMed (original) (raw)

A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians

Heejung Shim et al. PLoS One. 2015.

Abstract

We conducted a genome-wide association analysis of 7 subfractions of low density lipoproteins (LDLs) and 3 subfractions of intermediate density lipoproteins (IDLs) measured by gradient gel electrophoresis, and their response to statin treatment, in 1868 individuals of European ancestry from the Pharmacogenomics and Risk of Cardiovascular Disease study. Our analyses identified four previously-implicated loci (SORT1, APOE, LPA, and CETP) as containing variants that are very strongly associated with lipoprotein subfractions (log(10)Bayes Factor > 15). Subsequent conditional analyses suggest that three of these (APOE, LPA and CETP) likely harbor multiple independently associated SNPs. Further, while different variants typically showed different characteristic patterns of association with combinations of subfractions, the two SNPs in CETP show strikingly similar patterns--both in our original data and in a replication cohort--consistent with a common underlying molecular mechanism. Notably, the CETP variants are very strongly associated with LDL subfractions, despite showing no association with total LDLs in our study, illustrating the potential value of the more detailed phenotypic measurements. In contrast with these strong subfraction associations, genetic association analysis of subfraction response to statins showed much weaker signals (none exceeding log(10)Bayes Factor of 6). However, two SNPs (in APOE and LPA) previously-reported to be associated with LDL statin response do show some modest evidence for association in our data, and the subfraction response proles at the LPA SNP are consistent with the LPA association, with response likely being due primarily to resistance of Lp(a) particles to statin therapy. An additional important feature of our analysis is that, unlike most previous analyses of multiple related phenotypes, we analyzed the subfractions jointly, rather than one at a time. Comparisons of our multivariate analyses with standard univariate analyses demonstrate that multivariate analyses can substantially increase power to detect associations. Software implementing our multivariate analysis methods is available at http://stephenslab.uchicago.edu/software.html.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Effects of statin on cholesterol concentrations in LDL subfractions.

Dashed lines show (a) mean absolute change, and (b) mean fractional change, in each study/cohort in each subfraction (see Table 1 for abbrevations); dotted lines show ± one standard deviation; subfractions are in order from lower (left) to higher (right) density lipoprotein.

Fig 2. Effects of associated SNPs on LDL subfractions.

Solid lines show mean (normalized) phenotype for each subfraction (see Table 1 for abbrevations) by genotype class (reference homozygotes: red, heterozygotes: purple, non-reference homozygotes: sky blue; the proportion of individuals is shown next to the genotype; sky blue lines are omitted if the proportion is ≤ 0.01); dotted lines show ±2 standard errors. Results for secondary SNPs are based on residuals from regressing out top SNPs. Grey shading indicates posterior probability of association (either directly or indirectly) for each phenotype (> 0.9: dark grey, > 0.75: light grey, < 0.75: white; raw numbers given at top of figure). Note that, because the minor alleles have opposite effects on total HDL-C at the two SNPs in CETP, the _y_-axis is reversed for the secondary SNP to emphasize the similar shapes of the curves.

Fig 3. Replication of two independent associations in CETP (top SNP rs247616 and secondary SNP rs11076175).

Dashed lines show estimated effect sizes on (normalized) phenotype for each subfraction in our study (red) and JUPITER (blue); dotted lines show ±2 standard errors. Note that, the y-axis is reversed for the secondary SNP as in Fig 2.

Fig 4. Effects of associated SNPs (rs7412 in APOE and rs10455872 in LPA) on treated and untreated measures of LDL subfractions, and on their difference.

Upper panels show the effects of the SNPs on the difference between treated and untreated measures of LDL subfractions. Labels and colors are as in Fig 2. Lower panels show estimated effect size (dashed lines) and ±2 standard errors (dotted lines) in the treated and untreated (normalized) phenotype for each subfraction.

Fig 5. Decomposition of the gain (or loss) from a multivariate analysis of 12 phenotypes vs a univariate analysis of LDL-C into two components: one from using more detailed measurements, and one from using a multivariate analysis.

Plotted are (a) log10 BFav (the BF based on multivariate analysis of all 12 phenotypes) vs log10 BFldl (the BF based on univariate analysis of LDL-C), (b) log10 BFuni (the BF based on univariate analysis of all 12 phenotypes) vs log10 BFldl, and (c) log10 BFav vs log10 BFuni. SNPs are colored according to the nearest gene.

References

1. Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010;466:707–713. 10.1038/nature09270 - DOI - PMC - PubMed
1. Chasman DI, ParNi G, Mora S, Hopewell JC, Peloso G, Clarke R, et al. Forty-three loci associated with plasma lipoprotein size, concentration, and cholesterol content in genome-wide analysis. PLoS Genet. 2009;5(11):e1000730 10.1371/journal.pgen.1000730 - DOI - PMC - PubMed
1. Tukiainen T, Kettunen J, Kangas AJ, Lyytiäainen LP, Soininen P, Sarin AP, et al. Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci. Human Molecular Genetics. 2012. March;21(6):1444–55. 10.1093/hmg/ddr581 - DOI - PubMed
1. Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikinen LP, et al. Genomewide association study identifies multiple loci influencing human serum metabolite levels. Nature Genetics. 2012;44(3):269–76. 10.1038/ng.1073 - DOI - PMC - PubMed
1. Thompson JF, Hyde CL, Wood LS, Paciga SA, Hinds DA, Cox DR, et al. Comprehensive wholegenome and candidate gene analysis for response to statin therapy in the Treating to New Targets (TNT) cohort. Circulation Cardiovascular genetics. 2009. April;2(2):173–81. 10.1161/CIRCGENETICS.108.818062 - DOI - PubMed

A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 Caucasians - PubMed (original) (raw)