Type 2 diabetes (T2D) often develops insidiously, and many individuals with prediabetes (preDM) remain undiagnosed. While current diagnostic methods rely on blood sampling, urine-based proteomic biomarkers offer a promising noninvasive alternative for early risk stratification. Here, we applied label-free nanoLC-MS/MS-based proteomics to identify urinary protein biomarkers associated with prediabetes and to evaluate their potential in predicting progression to T2D. The discovery phase included urine samples from 43 control and 58 preDM participants, with protein quantification performed using two independent software platforms to ensure analytical robustness. Candidate proteins showing consistent differential expression were further validated by enzyme-linked immunosorbent assay (ELISA) in an expanded sample set comprising 91 control and 68 preDM subjects. Two proteins─alpha-1-acid glycoprotein 1 (AGP1) and zinc-α2-glycoprotein (ZAG)─were identified as candidate biomarkers. When combined with age and sex, AGP1 and ZAG showed good discriminative performance (AUCs of 0.936 and 0.926, respectively), comparable to fasting blood glucose (AUC = 0.944). Overall, these findings suggest that AGP1 and ZAG may serve as potential urinary biomarkers reflecting early metabolic alterations associated with prediabetes and progression to T2D, although further validation in independent cohorts is warranted.
Liao et al. (Tue,) studied this question.