Effects of 34 risk loci for type 2 diabetes or hyperglycemia on lipoprotein subclasses and their composition in 6,580 nondiabetic Finnish men

Abstract

Objective: We investigated the effects of 34 genetic risk variants for hyperglycemia/type 2 diabetes on lipoprotein subclasses and particle composition in a large population-based cohort.

Research design and methods: The study included 6,580 nondiabetic Finnish men from the population-based Metabolic Syndrome in Men (METSIM) study (aged 57 ± 7 years; BMI 26.8 ± 3.7 kg/m(2)). Genotyping of 34 single nucleotide polymorphism (SNPs) for hyperglycemia/type 2 diabetes was performed. Proton nuclear magnetic resonance spectroscopy was used to measure particle concentrations of 14 lipoprotein subclasses and their composition in native serum samples.

Results: The glucose-increasing allele of rs780094 in GCKR was significantly associated with low concentrations of VLDL particles (independently of their size) and small LDL and was nominally associated with low concentrations of intermediate-density lipoprotein, all LDL subclasses, and high concentrations of very large and large HDL particles. The glucose-increasing allele of rs174550 in FADS1 was significantly associated with high concentrations of very large and large HDL particles and nominally associated with low concentrations of all VLDL particles. SNPs rs10923931 in NOTCH2 and rs757210 in HNF1B genes showed nominal or significant associations with several lipoprotein traits. The genetic risk score of 34 SNPs was not associated with any of the lipoprotein subclasses.

Conclusions: Four of the 34 risk loci for type 2 diabetes or hyperglycemia (GCKR, FADS1, NOTCH2, and HNF1B) were significantly associated with lipoprotein traits. A GCKR variant predominantly affected the concentration of VLDL, and the FADS1 variant affected very large and large HDL particles. Only a limited number of risk loci for hyperglycemia/type 2 diabetes significantly affect lipoprotein metabolism.

FIG. 1.

Significances (A) and effect sizes (B) of associations between 34 SNP and 60 lipoprotein traits in nondiabetic men. P values (presented as −log10) were calculated by linear regression adjusted for age, BMI, statin treatment, and smoking, using log-transformed variables. Unstandardized effect sizes (presented as percentage from the mean) per type 2 diabetes/hyperglycemia risk allele were calculated from the same model, using untransformed variables. P, particle concentration.

FIG. 2.

Effects of GCKR rs780094 (A), FADS1 rs174550 (B), NOTCH2 rs10923931 (C), and HNF1B rs7501939 (D) on lipoprotein subclasses and their components in nondiabetic men. Bars represent percentage change to the mean of the trait per copy of a minor allele and were calculated by linear regression adjusted for age, BMI, statin treatment, and smoking. *Significant association after Bonferroni correction (P < 2.3 × 10⁻⁵) or FDR correction for multiple testing (P_FDR < 0.05). ^•Nominally significant associations (P < 0.05). P, particle concentration.

FIG. 3.

Quantile-quantile (Q-Q) plot of the association results between 34 hyperglycemia and type 2 diabetes risk SNPs and 60 lipoprotein traits (observed −log₁₀ P values against theoretical expected −log₁₀ P values). The diagonal black line represents theoretical expected values and the gray dashed lines their 95% CI. Blue dots, all P values; red dots, P values for two leading SNPs (GCKR rs780094 and FADS1 rs174550) excluded; green dots, P values for four SNPs showing significant (P_FDR < 0.05) associations (in GCKR, FADS1, HNF1B, NOTCH2) excluded.