Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.

Journal: Current medical science
PMID:

Abstract

OBJECTIVE: This study aims to investigate the exosome-derived metabolomicsĀ profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).

Authors

  • Zhong-Yu Wang
    Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, 210008, China.
  • Wen-Jing Liu
    Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, 210008, China.
  • Qing-Yang Jin
    Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, 210008, China.
  • Xiao-Shan Zhang
    Inner Mongolia Medical University, Department of Analgesic, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot, North Street, Inner Mongolia, 010050, China.
  • Xiao-Jie Chu
    Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Xuzhou Medical University, Nanjing, 210008, China.
  • Adeel Khan
    State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing, China.
  • Shou-Bin Zhan
    Department of Laboratory Medicine, Nanjing Drum Tower Hospital Clinical College of Jiangsu University, Nanjing, 210008, China. shoubin_zhan2021@163.com.
  • Han Shen
    School of Life Sciences and Biopharmaceutics, Guangdong Pharmaceutical University, Guangzhou, 51006, PR China. Electronic address: shenhanbc@163.com.
  • Ping Yang
    Key Laboratory of Grain and Oil Processing and Food Safety of Sichuan Province, College of Food and Bioengineering, Xihua University Chengdu 610039 China xingyage1@163.com.