Bioinformatics plays a significant role in type 2 diabetes (T2D) research, providing robust support for the diagnosis and treatment strategies of this disease (Kato et al., 2024; Chen R. et al., 2024).This study identified CXCL2 and MLF1 as novel diagnostic biomarkers for diabetic nephropathy through integrated bioinformatics and machine learning approaches, with experimental validation confirming their significant upregulation in patient samples. The gene discussed is MLF1; the disease is type 2 diabetes mellitus.