Integrated bioinformatics and machine learning reveal pan-apoptosis and immune infiltration signatures in diabetic nephropathy
Through comprehensive bioinformatics approaches, this study identified CD44, CRIP1, CEBPB, TNFRSF1B, CAV1, IGF1, GZMB and LY96 as potential diagnostic biomarkers for DN, providing new insights into disease diagnosis.
Authors
- Yu‐Li Shen (ORCID: https://orcid.org/0000-0003-4895-7066)
- Zhicong Xiang (ORCID: https://orcid.org/0000-0003-3389-1826)
- Hequn Zou (ORCID: https://orcid.org/0000-0001-6422-6090)
- Baoyi Ni
- Yu Liu (ORCID: https://orcid.org/0000-0003-0946-7961)
- Xiaofei Shao (ORCID: https://orcid.org/0000-0001-8477-3569)
- W Lu
Institutions
- Heilongjiang University of Chinese Medicine (CN)
- Third Affiliated Hospital of Southern Medical University (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- Shenzhen University Health Science Center (CN)
- Shenzhen Luohu People's Hospital (CN)
- Shenzhen Second People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2025-12-17
- DOI
- https://doi.org/10.3389/fimmu.2025.1659065
- Citations
- 2
- Primary Topic
- Chronic Kidney Disease and Diabetes
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- National Natural Science Foundation of China