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

Jingying Zhong,

Pengli Xu,

Xuanyi Li

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 17, 2025

Diabetic nephropathy (DN), a prevalent and severe complication of diabetes, is associated with poor prognosis limited treatment options. N7-Methylguanosine (m7G) modification plays crucial role in regulating RNA structure function, linking it closely to metabolic disorders. However, despite its biological significance, the interplay between m7G methylation immune status DN remains largely unexplored. Leveraging data from GEO database, we conducted consensus clustering regulators patients identify distinct molecular subtypes. To construct validate m7G-related prognostic features risk scores, integrated multiple machine learning approaches, including Support Vector Machine-Recursive Feature Elimination, Random Forest, LASSO, Cox regression, ROC curves analysis. In addition, employed GSVA, ssGSEA, CIBERSORT, Gene Set Enrichment Analysis investigate pathways landscape, providing deeper insights into DN. Based on expression levels 18 regulatory factors, identified nine key regulators. Through techniques, four significant (METTL1, CYFIP2, EIF3D, NUDT4). Consensus classified these genes two clusters. characterize subtypes, infiltration analysis, differential enrichment uncovering differences Additionally, developed an scoring model using PCA algorithm. The was further validated through vivo experiments, reinforcing their potential disease progression. METTL1, NUDT4 may serve as diagnostic biomarkers for DN, new mechanisms landscape.

Language: Английский

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

Jingying Zhong,

Pengli Xu,

Xuanyi Li

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 17, 2025

Diabetic nephropathy (DN), a prevalent and severe complication of diabetes, is associated with poor prognosis limited treatment options. N7-Methylguanosine (m7G) modification plays crucial role in regulating RNA structure function, linking it closely to metabolic disorders. However, despite its biological significance, the interplay between m7G methylation immune status DN remains largely unexplored. Leveraging data from GEO database, we conducted consensus clustering regulators patients identify distinct molecular subtypes. To construct validate m7G-related prognostic features risk scores, integrated multiple machine learning approaches, including Support Vector Machine-Recursive Feature Elimination, Random Forest, LASSO, Cox regression, ROC curves analysis. In addition, employed GSVA, ssGSEA, CIBERSORT, Gene Set Enrichment Analysis investigate pathways landscape, providing deeper insights into DN. Based on expression levels 18 regulatory factors, identified nine key regulators. Through techniques, four significant (METTL1, CYFIP2, EIF3D, NUDT4). Consensus classified these genes two clusters. characterize subtypes, infiltration analysis, differential enrichment uncovering differences Additionally, developed an scoring model using PCA algorithm. The was further validated through vivo experiments, reinforcing their potential disease progression. METTL1, NUDT4 may serve as diagnostic biomarkers for DN, new mechanisms landscape.

Language: Английский

Citations

1