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. 2014 Nov;55(11):2416-22.
doi: 10.1194/jlr.P052522. Epub 2014 Sep 15.

Adiposity significantly modifies genetic risk for dyslipidemia

Affiliations

Adiposity significantly modifies genetic risk for dyslipidemia

Christopher B Cole et al. J Lipid Res. 2014 Nov.

Abstract

Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (P(Interaction) = 2.87 × 10(-4)) and HDLc (P(Interaction) = 1.05 × 10(-3)). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRSLDL cholesterol × adiposity interaction was not significant. Sexual dimorphism was evident for the GRSHDL on HDLc in obese (P(Interaction) = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability.

Keywords: genetic risk score; lipoproteins; obesity; single nucleotide polymorphism; statistical interaction.

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Figures

Fig. 1.
Fig. 1.
TG residuals compared with GRS stratified by lean versus obese status. Significantly differently slope coefficients with 95% CIs are displayed, demonstrating a significant interaction between obesity status and a GRS. The rate of increased TG residuals for an increased predisposition is displayed for obese (broken line) and lean (solid line) individuals. Increased risk in obese individuals corresponds to an increased expression of lipid levels above what would normally be expected. This dimorphic effect was dependent on three SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL, not before observed to have adiposity-dependent dimorphic effects.
Fig. 2.
Fig. 2.
HDLc residuals compared with GRS stratified by lean versus obese status. Significantly differing slope coefficients with 95% CIs are displayed for obese and lean populations. Lean individuals exhibit a greater response to a larger number of HDLc-raising alleles. The dimorphic effect in HDL is due to SNPs tagging cholesteryl ester transfer protein (CETP), endothelial lipase (LIPG), GalNAc-transferase (GALNT2), and phospholipid transfer protein (PLTP), loci not previously noted to exhibit adiposity-dependent dimorphism.
Fig. 3.
Fig. 3.
Regression coefficients for HDLc (mM) for male versus female subjects stratified by lean versus obese status. Data are shown for males and females stratified by adiposity, and bars represent SE. In the lean population, women and men display a similar response to GRSHDLc. In contrast, obese men demonstrate an attenuated effect of GRSHDLc as compared with obese women. One locus was found to be exhibit sexually dimorphic effects in each of obese (rs4846914 tagging GALNT2) and lean (rs605066 tagging CITED2) populations as shown in Table 4.

References

    1. Teslovich T. M., Musunuru K., Smith A. V., Edmondson A. C., Stylianou I. M., Koseki M., Pirruccello J. P., Ripatti S., Chasman D. I., Willer C. J., et al. 2010. Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 466: 707–713. - PMC - PubMed
    1. Willer C. J., Schmidt E. M., Sengupta S., Peloso G. M., Gustafsson S., Kanoni S., Ganna A., Chen J., Buchkovich M. L., Mora S., et al. 2013. Discovery and refinement of loci associated with lipid levels. Nat. Genet. 45: 1274–1283. - PMC - PubMed
    1. Johansen C. T., Wang J., Lanktree M. B., McIntyre A. D., Ban M. R., Martins R. A., Kennedy B. A., Hassell R. G., Visser M. E., Schwartz S. M., et al. 2011. An increased burden of common and rare lipid-associated risk alleles contributes to the phenotypic spectrum of hypertriglyceridemia. Arterioscler. Thromb. Vasc. Biol. 31: 1916–1926. - PMC - PubMed
    1. Namboodiri K. K., Kaplan E. B., Heuch I., Elston R. C., Green P. P., Rao D. C., Laskarzewski P., Glueck C. J., Rifkind B. M. 1985. The Collaborative Lipid Research Clinics Family Study: biological and cultural determinants of familial resemblance for plasma lipids and lipoproteins. Genet. Epidemiol. 2: 227–254. - PubMed
    1. Yu Y., Wyszynski D. F., Waterworth D. M., Wilton S. D., Barter P. J., Kesaniemi Y. A., Mahley R. W., McPherson R., Waeber G., Bersot T. P., et al. 2005. Multiple QTLs influencing triglyceride and HDL and total cholesterol levels identified in families with atherogenic dyslipidemia. J. Lipid Res. 46: 2202–2213. - PubMed

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