Background. We aimed to investigate the distributive characteristics of SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms and their influence on metformin efficacy in Chinese T2DM patients. Methods. The distributions of SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms were determined in 267 T2DM patients and 182 healthy subjects. Subsequently, 53 newly diagnosed patients who received metformin monotherapy were recruited to evaluate metformin efficacy. Results. No significant difference was found between T2DM patients and healthy subjects in SLC22A1 rs594709 and SLC47A1 rs2289669 allele frequencies and genotype frequencies. After metformin treatment, SLC22A1 rs594709 GG genotype patients showed a higher increase in FINS (p = 0.015) and decrease in HOMA-IS (p = 0.001) and QUICKI (p = 0.002) than A allele carriers. SLC47A1 rs2289669 GG genotype patients had a higher decrease in TChol (p = 0.030) and LDL-C (p = 0.049) than A allele carriers. Among SLC22A1 rs594709 AA genotype, patients with SLC47A1 rs2289669 AA genotype showed a higher decrease in FBG (p = 0.015), PINS (p = 0.041), and HOMA-IR (p = 0.014) than G allele carriers. However, among SLC22A1 rs594709 G allele carriers, SLC47A1 rs2289669 AA genotype patients showed a higher decrease in TChol (p = 0.013) than G allele carriers. Conclusion. Our data suggest that SLC22A1 rs594709 and SLC47A1 rs2289669 polymorphisms may influence metformin efficacy together in Chinese T2DM patients.

Objective To analyze the association between serum uric acid (SUA) and metabolic state in obese inpatients and preliminarily explore potential mechanisms of hyperuricemia in obesity. Methods A total of 153 obese inpatients were selected and assigned based on SUA level to the normal uric acid (NC group) or high uric acid (HUA) group. Patients’ sex, age, height, weight, blood pressure, BMI, and prevalence of metabolic syndrome were collected and recorded. SUA, FPG, FIns, HOMA-IR, HOMA-IS, HbA 1c , TGs, TC, LDL-C, and HDL-C levels were tested. Pearson correlation analysis was performed to analyze the correlation between SUA and related metabolic indicators. Logistic regression was performed to analyze independent risk factors of hyperuricemia in obesity. Results In the HUA group, the patients were predominantly males, and BMI, DBP, TGs, FPG, FIns, HOMA-IR, HOMA-IS, and metabolic syndrome were higher than those in the NC group ( P <0.05), while HDL-C was lower than that in the NC group ( P <0.05). There were no significant differences between the groups in TC or LDL-C. Pearson correlation analysis showed that in obese patients, SUA was positively correlated with BMI, FIns, HOMA-IR, HOMA-IS, TGs, andmetabolic syndrome and negatively correlated with age and HDL-C. Logistic regression showed that BMI, hyperinsulinemia, and insulin resistance were independent risk factors of hyperuricemia. Conclusion Development of hyperuricemia in obese populations might be correlated with hyperinsulinemia or insulin resistance.