A novel biomarker Ins60/ApoA for predicting diabetic kidney disease in newly diagnosed type 2 diabetes: a pilot study

一种用于预测新诊断2型糖尿病患者糖尿病肾病的新型生物标志物Ins60/ApoA:一项初步研究

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Abstract

OBJECTIVE: We performed this cross-sectional study to explore potential biomarkers for predicting diabetic kidney disease (DKD) in newly diagnosed type 2 diabetes mellitus (T2DM). METHODS: A total of 623 patients were recruited from Xuzhou First People's Hospital and Nanjing First Hospital based on the electronic case records system. Patients were grouped according to their albuminuria-to-creatinine ratio (ACR) into two categories: ACR < 30 mg/g and ACR ≥ 30 mg/g. Biomarker levels between the two ACR groups were compared using an independent sample t-test. Correlation analysis was determined using Pearson's or Spearman's analysis and binary logistic regression. Receiver operating characteristic (ROC) curve analysis was used to elucidate the predictive effect of biomarkers on DKD. RESULTS: The levels of total cholesterol, glycated hemoglobin (HbA1c), fasting C-peptide, fasting insulin, and prevalence of hypertension were higher, while the levels of red blood cell counts (RBC), hemoglobin, ApoA, and free triiodothyronine were lower in the ACR ≥ 30 mg/g group. Negative correlations were found between ACR ≥ 30 mg/g and RBC, hemoglobin, albumin, and NAFLD (r = -0.094, p = 0.02; r = -0.130, p = 0.001; r = -0.137, p = 0.001; r = -0.097, p = 0.018), while positive correlations were found between high-density lipoprotein, fasting blood glucose, hypertension, and the ratio of 60-min postprandial insulin and serum apolipoprotein(a) (Ins60/ApoA) (r = 0.134, p = 0.001; r = 0.120, p = 0.003; r = 0.131, p = 0.001; r = 0.359, p = 0.001). Furthermore, binary logistic regression showed that lnIns60/ApoA was an independent influence factor for ACR ≥ 30 mg/g. After adjusting for age, gender, hypertension, non-alcoholic fatty liver disease (NAFLD), hemoglobin, albumin, smoking history, alcohol consumption history, and body mass index (BMI), lnIns60/ApoA was an independent influence factor for ACR ≥ 30 mg/g(OR = 2.778, p = 0.015). The area under the ROC curve was 0.741 (95% CI: 0.629-0.854, p = 0.001) for ACR ≥ 30 mg/g. The analysis of ROC curves revealed that an optimal cutoff for ACR was 22.42 mg/g, with a sensitivity of 67.6% and a specificity of 72.1%. CONCLUSION: The ratio of Ins60/ApoA could be used as an alternative biomarker for predicting DKD in newly diagnosed T2DM patients.

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