An integrated bioinformatics and machine learning approach to identifying biomarkers connecting parkinson's disease with purine metabolism-related genes.

Journal: BMC neurology
PMID: 40240887

Abstract

BACKGROUND: Parkinson's disease (PD), a prevalent neurodegenerative disorder in the aging population, poses significant challenges in unraveling its pathogenesis and progression. A key area of investigation is the disruption of oncological metabolic networks in PD, where diseased cells display distinct metabolic profiles compared to healthy counterparts. Of particular interest are Purine Metabolism Genes (PMGs), which play a pivotal role in nucleic acid synthesis.

Authors

  • Yao Wang
    Department of Gastrointestinal Surgery, Zhongshan People's Hospital, Zhongshan, Guangdong, China.
  • Dongchuan Wu
    Dongying City Traditional Chinese Medicine Hospital, Dongying, People's Republic of China.
  • Man Zheng
    Dongying People's Hospital (Dongying Hospital of Shandong Provincial Hospital Group), Dongying, 257091, Shandong, People's Republic of China.
  • Tiantian Yang
    College of Engineering, Huaqiao University, Quanzhou, China.

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