Interaction between polyphenols intake and PON1 gene variants on markers of cardiovascular disease: a nutrigenetic observational study

Abstract

Background: Paraoxonase 1 (PON1) gene polymorphisms and polyphenols intake have been reported independently associated to lipid profile and susceptibility to atherosclerosis and cardiovascular disease. However, the interaction between these factors remains to be investigated. We performed an observational nutrigenetic study to examine whether the interaction between polyphenols and anthocyanins intake and PON1 genetic variants can modulate biomarkers of cardiovascular health in an Italian healthy population.

Methods: We recruited 443 healthy volunteers who participated in the EC funded ATHENA project (AnThocyanin and polyphenols bioactive for Health Enhancement through Nutritional Advancement). Data collection included detailed demographic, clinical, dietary, lifestyle, biochemical and genetic data. Polyphenols and anthocyanins intake was measured by 24 h dietary recall repeated three times a year in order to get seasonal variations. We tested the interaction between 18 independent tagging SNPs in PON1 gene and polyphenols intake on HDL, LDL, cholesterol, triglycerides and atherogenic index of plasma.

Results: Without considering the genetic background, we could not observe significant differences in the lipid profile between high and low polyphenols and anthocyanins intake. Using a nutrigenetic approach, we identified protective genotypes in four independent polymorphisms that, at Bonferroni level (p ≤ 0.0028), present a significant association with increased HDL level under high polyphenols and anthocyanins intake, compared to risk genotypes (rs854549, Beta = 4.7 per C allele; rs854552, Beta = 5.6 per C allele; rs854571, Beta = 3.92 per T allele; rs854572, Beta = 3.94 per C allele).

Conclusions: We highlight the protective role of genetic variants in PON1 towards cardiovascular risk under high polyphenols and anthocyanins consumption. PON1 variants could represent novel biomarkers to stratify individuals who might benefit from targeted dietary recommendation for health promotion and strategies of preventive medicine.

Keywords: Anthocyanins; Antioxidants; Gene diet interaction; Genetic variants; HDL; Lipid profile; Nutrigenomics; PON1 gene; Polyphenols.

Fig. 1

Participant flow chart

Fig. 2

Phenotypes distribution relative to genotypes at best SNPs according to anthocyanins and polyphenols intakes. rs854549 (a), rs854551 (b), rs854552 (c), rs3917477 (d), rs854571 (e) and rs854572 (f). Y axis reports the residuals calculated for each phenotype (HDL, AIP and cholesterol) adjusted for age, sex, BMI and the first ten principal components. The bars summarize the distribution as mean and standard errors. For each bar, the numbers of individuals per genotype are indicated. P_GxE denotes the SNP x environment interaction analysis comparing high and low intake both for anthocyanins (a–c) and polyphenols (d–f). P indicates the multivariate linear regression analysis comparing genotypes in each environment subgroup (low/high); Beta coefficients refer to minor alleles