A combination of single nucleotide polymorphisms is associated with the interindividual variability in the blood lipid response to dietary fatty acid consumption in a randomized clinical trial.
Level 2 - randomized trial
Randomized crossover trial
PubMed 33871574 · doi:10.1093/ajcn/nqab064
What was done
In a multicenter randomized crossover trial, 92 participants with elevated waist circumference and low HDL cholesterol completed five 4-week isoenergetic diets: saturated fatty acids (SFAs) from cheese, SFAs from butter, monounsaturated fatty acids (MUFAs), n-6 polyunsaturated fatty acids (PUFAs), and a higher carbohydrate diet. The association between 22 candidate SNPs in lipid and bile acid metabolism genes and changes in LDL cholesterol and triglyceride (TG) concentrations was evaluated using univariate statistics and partial least squares regression.
What was found
Endpoint LDL cholesterol concentrations differed significantly across diets (butter: 3.31 ± 0.04 mmol/L, cheese: 3.18 ± 0.04 mmol/L, higher carbohydrate: 3.11 ± 0.04 mmol/L, MUFA: 3.00 ± 0.04 mmol/L, PUFA: 2.81 ± 0.04 mmol/L; P < 0.001), while endpoint TG concentrations did not (P = 0.117). Both exhibited high interindividual variability (CV of 34.5 ± 2.2% for LDL cholesterol and 55.8 ± 1.8% for TG). Only ABCA1-rs2066714 and APOE isoforms demonstrated consistent significant effects across diets on LDL cholesterol. Multivariate SNP models explained 16.0% to 33.6% of the variability in LDL cholesterol changes and 17.5% to 32.0% of the variability in TG changes across the diets.
Why it matters
The findings demonstrate that multi-SNP panels capture a meaningful proportion of the interindividual variance in blood lipid responses to dietary fat intake, which single-SNP analyses typically fail to explain.
Limits
The sample size was modest (n = 92) and limited to individuals with elevated waist circumference and low HDL cholesterol. The study evaluated only 22 preselected candidate SNPs rather than full genomic variation, and the abstract mentions no external validation cohort for the multivariate models.
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