BACKGROUND AND OBJECTIVE

Studies have shown that Caveolin gene polymorphisms (CAV-1) are involved in chronic diseases, such as metabolic syndrome. Moreover, the dietary insulin index (DII) and dietary insulin load (DIL) have been shown to potentially elicit favorable effects on cardiovascular disease (CVD) risk. Therefore, this study sought to investigate the effect of DII DIL and CAV-1 interaction on CVD risk factors.

METHODS

This cross-sectional study consisted of 333 overweight and obese women aged 18-48 years. Dietary intakes, DII, and DIL were evaluated using the 147-item food frequency questionnaire (FFQ). Serum profiles were measured by standard protocols. The CAV-1 rs 3,807,992 and anthropometric data were measured by the PCR-RFLP method and bioelectrical impedance analysis (BIA), respectively. Participants were also divided into three groups based on DII, DIL score, and rs3807992 genotype.

RESULTS

This comparative cross-sectional study was conducted on 333 women classified as overweight or obese. Participants with A allele for the caveolin genotype and higher DII score showed significant interactions with high-density lipoprotein (HDL) (P for AA = 0.006 and P for AG = 0.019) and CRI-I (P for AA < 0.001 and P for AG = 0.024). In participants with AA genotype and greater DII score, interactions were observed in weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol, CRI-II, fat-free mass (FFM), and skeletal muscle mass (SMM) (P < 0.079). Those with higher DIL scores and AA genotype had higher weight (P = 0.033), FFM (P = 0.022), and SMM (P = 0.024). In addition, DIL interactions for waist/hip ratio (WHR), waist circumference (WC), triglyceride (TG), CRI-I, and body fat mass (BFM) among individuals with AA genotype, while an HDL interaction was observed in individuals with AG and AA (P < 0.066).

CONCLUSION

The findings of the present study indicate that people who carry the caveolin rs3807992 (A) allele and have greater DII and DIL scores are at higher risk for several cardiovascular disease and metabolic syndrome biomarkers. These results highlight that diet, gene variants, and their interaction, should be considered in the risk evaluation of developing CVD.