Screening COPD-Related Biomarkers and Traditional Chinese Medicine Prediction Based on Bioinformatics and Machine Learning.

Journal: International journal of chronic obstructive pulmonary disease
PMID: 39346628

Abstract

PURPOSE: To employ bioinformatics and machine learning to predict the characteristics of immune cells and genes associated with the inflammatory response and ferroptosis in chronic obstructive pulmonary disease (COPD) patients and to aid in the development of targeted traditional Chinese medicine (TCM). Mendelian randomization analysis elucidates the causal relationships among immune cells, genes, and COPD, offering novel insights for the early diagnosis, prevention, and treatment of COPD. This approach also provides a fresh perspective on the use of traditional Chinese medicine for treating COPD.

Authors

  • Zhenghua Cao
    Changchun University of Traditional Chinese Medicine, Changchun, Jilin, People's Republic of China.
  • Shengkun Zhao
    Changchun University of Traditional Chinese Medicine, Changchun, Jilin, People's Republic of China.
  • Shaodan Hu
    Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin, People's Republic of China.
  • Tong Wu
    National Clinical Research Center for Obstetrical and Gynecological Diseases Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology Wuhan China.
  • Feng Sun
    Department of Neurology, Brain Hospital Affiliated to Nanjing Medical University, Nanjing 210029, China.
  • L I Shi
    Affiliated Hospital of Changchun University of Traditional Chinese Medicine, Changchun, Jilin, People's Republic of China.

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