RESUMO
BACKGROUND: Recent analyses in Greenlandic Inuit identified six genetic polymorphisms (rs74771917, rs3168072, rs12577276, rs7115739, rs174602 and rs174570) in the fatty acid desaturase gene cluster (FADS1-FADS2-FADS3) that are associated with multiple metabolic and anthropometric traits. Our objectives were to systematically assess whether dietary polyunsaturated fatty acid (PUFA) intake modifies the associations between genetic variants in the FADS gene cluster and cardiometabolic traits, and to functionally annotate top-ranking candidates to estimate their regulatory potential. METHODS: Data analyses consisted of the following: interaction analyses between the 6 candidate genetic variants and dietary PUFA intake; gene-centric joint analyses to detect interaction signals in the FADS region; haplotype-centric joint tests across 30 haplotype blocks in the FADS region to refine interaction signals; and functional annotation of top-ranking loci from the previous steps. These analyses were undertaken in Swedish adults from the GLACIER Study (N = 5,160); data on genetic variation and eight cardiometabolic traits were used. RESULTS: Interactions were observed between rs174570 and n-6 PUFA intake on fasting glucose (Pint = 0.005) and between rs174602 and n-3 PUFA intake on total cholesterol (Pint = 0.001). Gene-centric analyses demonstrated a statistically significant interaction effect for FADS and n-3 PUFA on triglycerides (Pint = 0.005) considering genetic main effects as random. Haplotype analyses revealed three blocks (Pint < 0.011) that could drive the interaction between FADS and n-3 PUFA on triglycerides; functional annotation of these regions showed that each block harbours a number of highly functional regulatory variants; FADS2 rs5792235 demonstrated the highest functionality score. CONCLUSIONS: The association between FADS variants and triglycerides may be modified by PUFA intake. The intronic FADS2 rs5792235 variant is a potential causal variant in the region, having the highest regulatory potential. However, our results suggest that multiple haplotypes may harbour functional variants in a region, rather than a single causal variant.