Construction of a diagnostic model utilizing m7G regulatory factors for the characterization of diabetic nephropathy and the immune microenvironment.

ABSTRACT: Diabetic nephropathy (DN), a prevalent and severe complication of diabetes, is associated with poor prognosis and limited treatment options. N7-Methylguanosine (m7G) modification plays a crucial role in regulating RNA structure and function, linking it closely to metabolic disorders. However, despite its biological significance, the interplay between m7G methylation and immune status in DN remains largely unexplored. Leveraging data from the GEO database, we conducted consensus clustering of m7G regulators in DN patients to identify distinct molecular subtypes. To construct and validate m7G-related prognostic features and risk scores, we integrated multiple machine learning approaches, including Support Vector Machine-Recursive Feature Elimination, Random Forest, LASSO, Cox regression, and

SUBMITTER: Zhong J 

PROVIDER: S-EPMC11914462 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature