FADS genotypes shape plasma polyunsaturated fatty acids independently of dietary intake in breast cancer survivors on aromatase inhibitors.

INTRODUCTION

Alterations in lipid metabolism are common in breast cancer (BRC) survivors on aromatase inhibitor therapy, and may increase the risk of cardiovascular complications. Long-chain n-3 and n-6 plasma fatty acids (PUFA) are substantial components of complex lipids, with important structural and regulatory functions. Their circulating levels are determined by both dietary intake and endogenous metabolism, of which the latter is influenced by polymorphisms in fatty acid desaturase (FADS) genes. This study aimed to assess the association of FADS polymorphisms and plasma n-3 and n-6 PUFA levels in BRC survivors on AI therapy.

METHODS

Fatty acid status was determined by gas chromatography, and FADS polymorphisms (rs174537, rs174576 and rs174602) were genotyped using real-time PCR. Dietary intake of n-3 and n-6 fatty acids was evaluated via three 24-h dietary recalls. Data were analyzed using a multiple linear regression model.

RESULTS

All three polymorphisms were significantly associated with plasma arachidonic acid levels. Minor alleles of rs174537 (TT), rs174576 (AA) and rs174602 (CC) were associated with lower plasma arachidonic acid proportions. Moreover, positive association of rs174537 and rs174576 minor alleles with higher levels of linoleic acid, precursor of arachidonic acid and decreased estimated activities of delta-5 and delta-6 desaturases were observed, pointing out a lower conversion rate along the n-6 pathway. Lower levels of n-3 docosapentaenoic acid were associated with minor allele carriers of rs174576, while no significant differences were found for other n-3 PUFA. Dietary intake of n-3 and n-6 fatty acids did not differ significantly across the three genotypes, except for EPA for the rs174602 groups.

DISCUSSION: These findings demonstrate that FADS genotypes significantly influence plasma PUFA profiles independently of dietary intake in BRC survivors receiving AI therapy. This supports the potential relevance of considering genetic variability in future approaches aimed at optimizing PUFA balance and reducing CVD risk in this vulnerable population.