Significance of Cuproptosis-related genes in immunological characterization, diagnosis and clusters classification in Parkinson's disease

被引:1
|
作者
Zhong, Zhe [1 ]
Wang, Huiqing [1 ]
Ye, Min [2 ]
Yan, Fuling [1 ]
机构
[1] Southeast Univ, Affiliated ZhongDa Hosp, Sch Med, Dept Neurol, Nanjing 210009, Peoples R China
[2] Nanjing Med Univ, Affiliated BenQ Hosp, Dept Neurol, Nanjing 210019, Peoples R China
关键词
Parkinson's disease; cuprotosis; immune infiltration; machine learning; predictive model; COPPER; ONSET;
D O I
10.14715/cmb/2023.69.12.20
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Parkinson's disease (PD) is a progressive neurological disorder that affects millions of people throughout the world. Cuproptosis is a newly discovered form of programmed cell death linked to several neurological disorders. Nevertheless, the precise mechanisms of Cuproptosis-related genes (CRGs) in PD remain unknown. This study investigated immune infiltration and CRG expression profiling in patients with Parkinson's disease and healthy controls. Subsequently, we construct a predictive model based on 5 significant CRGs. The performance of the predictive model was validated by nomograms and external datasets. Additionally, we classified PD patients into two clusters based on CRGs and three gene clusters based on differentially expressed genes (DEG) of CRGs clusters. We further evaluated immunological characterization between the different clusters and created the CRGs scores to quantify CRGs patterns. Finally, we investigate the prediction of CRGs drugs and the ceRNA network, providing new insights into the pathogenesis and management of PD.
引用
收藏
页码:124 / 130
页数:7
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