2026 年第 3 期 第 21 卷

.2型糖尿病患者尿白蛋白/肌酐比值与氨基酸代谢的相关性分析

Correlation analysis between urinary albumin-to-creatinine ratio and amino acid metabolism in patients with type 2 diabetes mellitus

作者：付苗1蔡梦洁2栗扬阳2杨雪蓉2陶乐维2陈清光2陆灏2侯瑞芳2赵进东1

英文作者：Fu Miao1 Cai Mengjie2 Li Yangyang2 Yang Xuerong2 Tao Lewei2 Chen Qingguang2 Lu Hao2 Hou Ruifang2 Zhao Jindong1

单位：1安徽中医药大学第一附属医院全科医学科，合肥230031；2上海中医药大学附属曙光医院内分泌科，上海201203

英文单位：1Department of General Practice the First Affiliated Hospital of Anhui University of Chinese Medicine Hefei 230031 China; 2Department of Endocrinology Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine Shanghai 201203 China

关键词：2型糖尿病；糖尿病肾病；尿白蛋白/肌酐比值；氨基酸代谢

英文关键词：Type2diabetesmellitus;Diabeticnephropathy;Urinaryalbumin-to-creatinineratio;Aminoacidmetabolism

• 摘要：

• 目的 探究2型糖尿病（T2DM）患者尿白蛋白/肌酐比值（UACR）与氨基酸代谢的关系。方法 选取2021年1—11月上海中医药大学附属曙光医院内分泌科收治的117例T2DM患者作为研究对象。根据UACR检测结果将患者分为正常组（UACR≤30 mg/g，44例）、微量尿白蛋白组（30 mg/g＜UACR≤300 mg/g，41例）、大量尿白蛋白组（UACR＞300 mg/g，32例）。比较3组患者一般资料和生化指标。采用Spearman相关性分析和多因素Logistic回归方法分析UACR水平与氨基酸代谢的关系。采用受试者工作特征（ROC）曲线评估各组氨基酸与UACR水平的关系。结果 3组性别和年龄比较，差异均无统计学意义（χ2=3.011，P=0.222；Z=2.261，P=0.323)；3组病程比较，差异有统计学意义（Z=34.356，P<0.001)。大量尿白蛋白组血肌酐和血尿素氮水平均高于微量尿白蛋白组和正常组，估算肾小球滤过率水平低于微量尿白蛋白组和正常组，差异均有统计学意义（均P＜0.05)。3组患者赖氨酸、脯氨酸、苏氨酸、瓜氨酸、酪氨酸、缬氨酸水平比较，差异均有统计学意义（均P＜0.05)。Spearman相关性分析结果显示，UACR水平与赖氨酸、苏氨酸、酪氨酸、缬氨酸代谢水平呈负相关（r=-0.215、-0.226、-0.363、-0.221，均P＜0.05）。UACR水平与瓜氨酸代谢水平呈正相关（r=0.424，P＜0.001）。多因素Logistic回归分析结果显示高瓜氨酸代谢水平是UACR水平升高的影响因素（P＜0.001）。ROC曲线分析结果显示，瓜氨酸预测UACR升高的曲线下面积为0.782（95%置信区间：0.675~0.890，P＜0.001）,最佳截断值为40.615 μmol/L，敏感度75.0%，特异度82.4%。结论 血清瓜氨酸是T2DM患者UACR升高的敏感标志物，可以较好地预测和评估糖尿病肾病的发生。

• Objective To investigate the relationship between urinary albumin-to-creatinine ratio (UACR) and amino acid metabolism in patients with type 2 diabetes mellitus (T2DM). Methods A total of 117 T2DM patients admitted to the Department of Endocrinology, Shuguang Hospital Affiliated to Shanghai University of Chinese Medicine from January to November 2021 were enrolled as research subjects. According to the UACR test results, the patients were divided into three groups: normal group (UACR≤30 mg/g, 44 cases), microalbuminuria group (30 mg/g<UACR≤300 mg/g, 41 cases), and macroalbuminuria group (UACR>300 mg/g, 32 cases). The general data and biochemical indicators of the three groups were compared. Spearman correlation analysis and multivariate Logistic regression analysis were used to analyze the relationship between UACR level and amino acid metabolism. Receiver operating characteristic (ROC) curve was used to evaluate the relationship between amino acids and UACR levels in each group. Results There were no significant differences in gender and age among the three groups (χ2=3.011, P=0.222; Z=2.261, P=0.323). The difference in disease duration among the three groups was statistically significant (Z=34.356, P<0.001). The levels of serum creatinine and blood urea nitrogen in the macroalbuminuria group were higher than those in the microalbuminuria group and the normal group, while the estimated glomerular filtration rate was lower than that in the microalbuminuria group and the normal group (all P<0.05). There were significant differences in the levels of lysine, proline, threonine, citrulline, tyrosine and valine among the three groups (all P<0.05). Spearman correlation analysis showed that UACR level was negatively correlated with the metabolic levels of lysine, threonine, tyrosine and valine (r=-0.215, -0.226, -0.363, -0.221, all P<0.05), and positively correlated with the metabolic level of citrulline (r=0.424, P<0.001). Multivariate Logistic regression analysis showed that high citrulline metabolic level was an influencing factor for the increase of UACR level (P<0.001). ROC curve analysis showed that the area under the curve of citrulline in predicting the increase of UACR was 0.782 (95% confidence interval: 0.675-0.890, P<0.001), with the optimal cut-off value of 40.615 μmol/L, sensitivity of 75.0% and specificity of 82.4%. Conclusion Serum citrulline is a sensitive marker for the increase of UACR in T2DM patients, which can well predict and evaluate the occurrence of diabetic nephropathy.