Modeling of environmental effects in genome-wide association studies identifies SLC2A2 and HP as novel loci influencing serum cholesterol levels

Abstract

Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWAS in order to identify novel loci affecting total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. The Swedish (SE) EUROSPAN cohort (N(SE) = 656) was screened for candidate genes and the non-Swedish (NS) EUROSPAN cohorts (N(NS) = 3,282) were used for replication. In total, 3 SNPs were associated in the Swedish sample and were replicated in the non-Swedish cohorts. While SNP rs1532624 was a replication of the previously published association between CETP and HDL cholesterol, the other two were novel findings. For the latter SNPs, the p-value for association was substantially improved by inclusion of environmental covariates: SNP rs5400 (p(SE,unadjusted) = 3.6 x 10(-5), p(SE,adjusted) = 2.2 x 10(-6), p(NS,unadjusted) = 0.047) in the SLC2A2 (Glucose transporter type 2) and rs2000999 (p(SE,unadjusted) = 1.1 x 10(-3), p(SE,adjusted) = 3.8 x 10(-4), p(NS,unadjusted) = 0.035) in the HP gene (Haptoglobin-related protein precursor). Both showed evidence of association with total cholesterol. These results demonstrate that inclusion of important environmental factors in the analysis model can reveal new genetic susceptibility loci.

Figure 1. Manhattan plot of genome-wide effects on total cholesterol levels in the Swedish discovery cohort.

Results for two GWAS analysis models are presented. The unadjusted model (dark blue and light blue circles) included only sex and age as covariates. The adjusted model (red and orange squares) additionally contained food intake and physical activity as predictors. The dashed line indicates the local Bonferroni-adjusted α error = 1.6×10⁻⁷.

Figure 2. Manhattan plot of genome-wide effects on LDL cholesterol levels in the Swedish discovery cohort.

Results for two GWAS analysis models are presented. The unadjusted model (dark blue and light blue circles) included only sex and age as covariates. The adjusted model (red and orange squares) additionally contained food intake and physical activity as predictors. The dashed line indicates the local Bonferroni-adjusted α error = 1.6×10⁻⁷.

Figure 3. Manhattan plot of genome-wide effects on HDL cholesterol levels in the Swedish discovery cohort.

Results for two GWAS analysis models are presented. The unadjusted model (dark blue and light blue circles) included only sex and age as covariates. The adjusted model (red and orange squares) additionally contained food intake and physical activity as predictors. The dashed line indicates the local Bonferroni-adjusted α error = 1.6×10⁻⁷.

Figure 4. Manhattan plot of genome-wide effects on triglyceride levels in the Swedish discovery cohort.

Results for two GWAS analysis models are presented. The unadjusted model (dark blue and light blue circles) included only sex and age as covariates. The adjusted model (red and orange squares) additionally contained food intake and physical activity as predictors. The dashed line indicates the local Bonferroni-adjusted α error = 1.6×10⁻⁷.