Association of allelic combinations in selenoprotein and redox related genes with markers of lipid metabolism and oxidative stress - multimarkers analysis in a cross-sectional study

Abstract

Background: Selenium (Se) and selenoproteins have been shown to be involved in lipid metabolism mainly due to their ability to modulate redox homeostasis in adipose tissue. The underlying mechanisms are yet to be evaluated. In the light of few data related to the association between polymorphic variants of selenoprotein encoding genes and metabolic syndrome or obesity in humans, the role of selenoprotein polymorphisms in lipid metabolism remains unclear. The aim of this study was to investigate the impact of allelic combination within selenoprotein and redox related genes on the markers of lipid metabolism and oxidative stress.

Methods: The study comprised 441 healthy individuals from Poland, in the 18-74 year age group. Allelic combinations were investigated within the polymorphic variants of four selenoprotein encoding genes (GPX1 rs1050450, GPX4 rs713041, SELENOP rs3877899 and SELENOF rs5859) and the redox related gene (SOD2 rs4880). The impact of the most common allelic GPX1-GPX4-SELENOP-SELENOF-SOD2 combinations was assessed on the following markers: triglycerides (TG), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), glutathione peroxidase activities (GPX1, GPX3), lipid peroxidation (as TBARS), ceruloplasmin (Cp) and superoxide dismutase 1 (SOD1).

Results: Multivariable analysis revealed significant associations between three allelic combinations and markers of lipid metabolism, including HDL-C and TC/HDL-C ratio (AAAAa), LDL-C (aaAaa), and triglycerides (aaaaA), whereas two allelic combinations (aAaAA, aaaAA) were associated with GPX3 activity.

Conclusion: This study confirms the possible implication of selenoproteins in lipid metabolism and warrants further research on specific allele combinations within selenoprotein and redox related genes in order to identify functional genetic combinations linked to metabolic phenotype.

Keywords: Energy metabolism; Genetic polymorphisms; Lipid metabolism; Selenium; Selenoproteins.