Uncovering glycolysis-driven molecular subtypes in diabetic nephropathy: a WGCNA and machine learning approach for diagnostic precision.

Journal: Biology direct
PMID: 39838413

Abstract

INTRODUCTION: Diabetic nephropathy (DN) is a common diabetes-related complication with unclear underlying pathological mechanisms. Although recent studies have linked glycolysis to various pathological states, its role in DN remains largely underexplored.

Authors

  • Chenglong Fan
    Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China.
  • Guanglin Yang
    Department of Urology, Affiliated Cancer Hospital of Guangxi Medical University, Nanning 530021, China. Electronic address: ygl199503@163.com.
  • Cheng Li
    College of Food and Bioengineering, Henan University of Science and Technology, Luoyang, China.
  • Jiwen Cheng
    Department of Urology, Institute of Urology and Nephrology, First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China. chengjiwen1977@foxmail.com.
  • Shaohua Chen
    Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, 530021, Guangxi, China.
  • Hua Mi
    Department of Urology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, China. mihua2019@163.com.

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