AI Summary & Key Takeaways
AI InsightTherefore, these polymorphisms may be used as a predictive marker for diabetic dyslipidemia in high-risk patients
📌 3 Key Takeaways
Abstract
Objective: The polymorphisms/mutations of genes encoding proteins and enzymes involved in lipoprotein metabolism play important roles in the development of diabetic dyslipidemia. The aim of our study was to investigate the effects of LPL (rs320), LIPC (rs2070895), SCARB1 (rs5888), LCAT (rs2292318), CETP (rs708272), ADIPOQ (rs1501299), RETN (rs3745367), PON1 (rs662), and MNSOD (rs4880) gene polymorphisms on lipid metabolism and diabetic dyslipidemia.Methods: This case-control study included 217 patients with diabetic dyslipidemia and 212 healthy age- and gender-matched individuals. Genomic DNA isolation was performed from blood samples, and genotype analysis was performed using melting curve analysis on a LightCycler®480 Instrument. The chi-square test was used to compare genotype distribution and allele frequencies between the groups.Results: Significant associations were observed between LPL (rs320) (p<0.001), LIPC (rs2070895) (p<0.001), SCARB1 (rs5888) (p<0.001), LCAT (rs2292318) (p<0.001), CETP (rs708272) (p<0.001), ADIPOQ (rs1501299) (p=0.01), RETN (rs3745367) (p<0.001), and MNSOD (rs4880) (p<0.001) polymorphisms and diabetic dyslipidemia. However, no association was observed between PON1 (rs662) polymorphisms and diabetic dyslipidemia (p=0.611).Conclusion: LPL (rs320), LIPC (rs2070895), SCARB1 (rs5888), LCAT (rs2292318), CETP (rs708272), ADIPOQ (rs1501299), RETN (rs3745367), and MNSOD (rs4880) polymorphisms play an important role in basic molecular metabolism in diabetic dyslipidemia. Therefore, these polymorphisms may be used as a predictive marker for diabetic dyslipidemia in high-risk patients