Brain Sciences (Jun 2023)

Identification of Cuproptosis Clusters and Integrative Analyses in Parkinson’s Disease

  • Moxuan Zhang,
  • Wenjia Meng,
  • Chong Liu,
  • Huizhi Wang,
  • Renpeng Li,
  • Qiao Wang,
  • Yuan Gao,
  • Siyu Zhou,
  • Tingting Du,
  • Tianshuo Yuan,
  • Lin Shi,
  • Chunlei Han,
  • Fangang Meng

DOI
https://doi.org/10.3390/brainsci13071015
Journal volume & issue
Vol. 13, no. 7
p. 1015

Abstract

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Parkinson’s disease (PD) is the second most common neurodegenerative disease; it mainly occurs in the elderly population. Cuproptosis is a newly discovered form of regulated cell death involved in the progression of various diseases. Combining multiple GEO datasets, we analyzed the expression profile and immunity of cuproptosis-related genes (CRGs) in PD. Dysregulated CRGs and differential immune responses were identified between PD and non-PD substantia nigra. Two CRG clusters were defined in PD. Immune analysis suggested that CRG cluster 1 was characterized by a high immune response. The enrichment analysis showed that CRG cluster 1 was significantly enriched in immune activation pathways, such as the Notch pathway and the JAK-STAT pathway. KIAA0319, AGTR1, and SLC18A2 were selected as core genes based on the LASSO analysis. We built a nomogram that can predict the occurrence of PD based on the core genes. Further analysis found that the core genes were significantly correlated with tyrosine hydroxylase activity. This study systematically evaluated the relationship between cuproptosis and PD and established a predictive model for assessing the risk of cuproptosis subtypes and the outcome of PD patients. This study provides a new understanding of PD-related molecular mechanisms and provides new insights into the treatment of PD.

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