Influence of IL1B, IL6 and IL10 gene variants and plasma fatty acid interaction on metabolic syndrome risk in a cross-sectional population-based study

Background & aims: Metabolic syndrome (MetS) is a cluster of interrelated risk factors for type 2 diabetes mellitus, and cardiovascular disease, with underlying inflammatory pathophysiology. Genetic variations and diet are well-known risk factor for MetS, but the interaction between these two factors is less explored. The aim of the study was to evaluate the influence of interaction between SNP of inflammatory genes (encoding interleukin (IL)-6, IL-beta and IL-10) and plasma fatty acids on the odds of MetS, in a population-based cross-sectional study. Methods: Among participants of the Health Survey - Sao Paulo, 301 adults (19-59 y) from whom a blood sample was collected were included. Individuals with and without MetS were compared according to their plasma inflammatory biomarkers, fatty acid profile, and genotype frequency of the IL1B (rs16944, rs1143623, rs1143627, rs1143634 and rs1143643), IL6 (rs1800795, rs1800796 and rs1800797) and IL10 (rs1554286, rs1800871, rs1800872, rs1800890 and rs3024490) genes SNP. The influence of gene fatty acids interaction on MetS risk was investigated. Results: IL6 gene SNP rs1800795 G allele was associated with higher odds for MetS (OR = 1.88; p = 0.017). Gene fatty acid interaction was found between the IL1B gene SNP rs116944 and stearic acid (p inter = 0.043), and between rs1143634 and EPA (p inter = 0.017). For the IL10 gene SNP rs1800896, an interaction was found for arachidonic acid (p inter = 0.007) and estimated D5D activity (p inter = 0.019). Conclusion: The 1L6 gene SNP rs1800795 G allele is associated with increased odds for MetS. Plasma fatty acid profile interacts with the IL1B and IL10 gene variants to modulate the odds for MetS. This and other interactions of risk factors can account for the unexplained heritability of MetS, and their elucidation can lead to new strategies for genome-customized prevention of MetS. (C) 2017 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.