Objectives: This study aimed to determine potential serum biomarkers of type 2 diabetes (T2DM) through proteomic data analysis and protein association assessment.

Methods: This study included 80 patients with obesity, 76 patients with newly diagnosed T2DM combined with obesity, and 73 healthy controls. Proteomics analysis was used to investigate changes in protein abundance in the serum across the three groups. Correlations were analyzed using logistic regression, Pearson's correlation, and Spearman's correlation. Group comparisons for non-normally distributed continuous or categorical variables were performed using the Mann-Whitney U test, Kruskal-Wallis test, χ² test, or Fisher's exact probability test, as appropriate. Logistic regression analysis was employed to identify independent predictors, and correlations were evaluated using Pearson or Spearman tests based on data distribution. Receiver operating characteristic (ROC) curve analysis was employed to determine the predictive value of the differential proteins for the diagnosis of obesity and T2DM.

Results: In this study, two-dimensional gel electrophoresis was used to analyze three groups. Several proteins were differentially expressed, with α2-macroglobulin (α2-MG) showing significant up-regulation in the obesity and T2DM + obesity groups compared to the control group. ELISA verification showed higher α2-MG levels in the obesity (2.746±0.391 g/L) and T2DM + obesity (3.261±0.400 g/L) groups than in the control group (1.376±0.229 g/L) (P<0.05). For predicting obesity and T2DM combined with obesity, α2-MG (AUC=0.873 and 0.601 respectively) were significant predictors.

Conclusion: Serum a2-MG levels are elevated in obese individuals and those with T2DM. It shows high sensitivity and specificity for predicting obesity and T2DM, suggesting its potential as a biomarker for T2DM diagnosis. However, further large-scale studies are needed to confirm its clinical utility.

Keywords: biomarkers; mass spectrometry; obesity; proteomics; risk assessment; twodimensional polyacrylamide gel electrophoresis; type 2 diabetes mellitus; α2-Macroglobulin.

Copyright © 2025 Wang, He, Chang and Yan.

目标： 本研究旨在通过蛋白质组数据分析和蛋白质关联评估，确定潜在的2型糖尿病（T2DM）血清生物标志物。

方法： 该研究包括80名肥胖患者、76名新诊断的伴有肥胖症的T2DM患者以及73名健康对照者。使用蛋白质组学分析来调查三个组别之间血液中蛋白质丰度的变化。通过逻辑回归、皮尔逊相关和斯皮尔曼相关进行关联性分析。对于非正态分布的连续变量或分类变量，分别使用Mann-Whitney U检验、Kruskal-Wallis检验、卡方检验（χ²）或Fisher确切概率检验进行组间比较。采用逻辑回归分析确定独立预测因子，并根据数据分布采用皮尔逊或斯皮尔曼检验评估相关性。使用受试者工作特征曲线（ROC）分析来测定差异蛋白质对肥胖症和T2DM诊断的预测价值。

结果： 本研究中，使用二维凝胶电泳分析了三个组别。多个蛋白质表达不同，其中α2-巨球蛋白（α2-MG）在肥胖组和T2DM合并肥胖组中的上调显著高于对照组。酶联免疫吸附测定验证表明，在肥胖患者 (2.746±0.391 g/L) 和 T2DM 合并肥胖患者 (3.261±0.400 g/L) 组中 α2-MG 水平高于对照组 (1.376±0.229 g/L)，差异有统计学意义（P

结论： 血液中 α2-MG 的水平在肥胖人群和 T2DM 患者中升高，对于预测肥胖症和 T2DM 表现出高敏感性和特异性，提示其可能作为 T2DM 诊断的生物标志物。然而，需要进一步的大规模研究来确认其临床应用价值。

关键词： 生物标志物；质谱分析；肥胖症；蛋白质组学；风险评估；二维聚丙烯酰胺凝胶电泳；2型糖尿病；α2-巨球蛋白。