Interaction between the dietary indices (DQI, DPI, HEI) and PPAR-γ gene variants on cardiovascular risk factors in a patient with type 2 diabetes mellitus

Interaction between the dietary indices (DQI, DPI, HEI) and PPAR-γ gene variants on cardiovascular risk factors in a patient with type 2 diabetes mellitus
Faezeh Abaj,¹ Gity Sotoudeh ,² Elmira Karimi ,³ Masoumeh Rafiee ,⁴ Fariba Koohdani ,^5,*
1. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
2. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS)
3. Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS)
4. Department of Clinical Nutrition, School of Nutrition and Food Science, Isfahan University of Medical Sciences (IUMS)
5. c. Department of Cellular, Molecular Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS)
Introduction: Cardiovascular disease is one of the major complications in patients with type 2 diabetes mellitus (T2DM). Dietary indices including DQI, DPI, and HEI and genetic variants of PPAR-γ Pro12Ala polymorphism could also affect lipid profile concentrations, inflammatory markers, ghrelin, and leptin hormones. Therefore, we decided to study the interaction between PPAR-γ Pro12Ala polymorphism and dietary indices (DQI, DPI, HEI) on cardiovascular disease risk factors in patients with T2DM
Methods: This cross-sectional study was conducted on 393 diabetic patients. PPAR-γ Pro12Ala polymorphism was genotyped by polymerase chain reaction-restriction length polymorphism (PCR-RFLP). Biochemical markers including total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride (TG), superoxide dismutase (SOD), C-reactive protein (CRP), total antioxidant capacity (TAC), pentraxin-3 (PTX3), isoprostane F2 α (PGF2α) were measured by standard protocol. FFQ was used for estimating food intakes and dietary indices (DQI, DPI, HEI) were calculated
Results: There was no significant relationship between PPAR-γ Pro12Ala polymorphism and cardiovascular disease risk factors. The rs1801282-DQI interactions were significant on WC in both crude and adjusted models (P Interaction = 0.02 and P Interaction = 0.01). Thus, C-allele carriers in the higher tertile of DQI had higher WC measurements compared to GG homozygous. Further, an interaction was observed between PPAR rs1801282 polymorphism and DQI on serum IL-18 level (P interaction= 0.03). Besides, a significant rs1801282-DPI interaction was shown on HDL concentration (P Interaction= 0.04) in the adjusted model, carriers of the G allele who were in the highest tertile of DPI, had lower HDL. Moreover, there were significant rs1801282-HEI interactions on ghrelin (P Interaction = 0.04) in the crude model and leptin plasma levels (P Interaction= 0.02) in the adjusted model. Individuals with (CC, CG) genotypes in the higher tertile of HEI, had lower leptin and ghrelin concentration.
Conclusion: Higher dietary indices (DQI, DPI, HEI) may affect the relationship between PPAR-γ Pro12Ala polymorphism and waist circumference and ghrelin, leptin, HDL-c, IL-18 concentration in patients with T2DM.
Keywords: PPAR-γ; Gene-environment interaction; Personalized diet; Cardio-metabolic disease