Identification of diagnostic genes and drug prediction in metabolic syndrome-associated rheumatoid arthritis by integrated bioinformatics analysis, machine learning, and molecular docking.

Journal: Frontiers in immunology
Published Date:

Abstract

BACKGROUND: Interactions between the immune and metabolic systems may play a crucial role in the pathogenesis of metabolic syndrome-associated rheumatoid arthritis (MetS-RA). The purpose of this study was to discover candidate biomarkers for the diagnosis of RA patients who also had MetS.

Authors

  • Yifan Huang
    Department of Orthopedics, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
  • Songkai Yue
    Department of Orthopedics, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
  • Jinhan Qiao
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
  • Yonghui Dong
    Department of Orthopedics, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
  • Yunke Liu
    Laboratory Department, Guangzhou Tianhe District Maternal and Child Health Care Hospital, Guangzhou, Guangdong Province, PR China.
  • Meng Zhang
    College of Software, Beihang University, Beijing, China.
  • Cheng Zhang
    College of Forestry, Jiangxi Agricultural University, Nanchang, Jiangxi Province, China.
  • Chuanliang Chen
    Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, P. R. China.
  • Yuqin Tang
    Clinical Bioinformatics Experimental Center, People's Hospital of Zhengzhou University, Henan Provincial People's Hospital, Zhengzhou, Henan, China.
  • Jia Zheng
    School of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.