| Autor: |
Bin Nie, Yefen Duan, Xuelong Xie, Lihua Qiu, Shaorui Shi, Zhili Fan, Xuxiang Zheng, Ling Jiang |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Frontiers in Aging Neuroscience, Vol 15 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1663-4365 |
| DOI: |
10.3389/fnagi.2023.1204530 |
| Popis: |
ObjectivesThis study aimed to make a systematic analysis of cuproptosis-related genes (CRGs) in immunological characterization and predictive drugs in Alzheimer’s disease (AD) through bioinformatics and biological experiments.MethodsThe molecular clusters related to CRGs and associated immune cell infiltrations in AD were investigated. The diagnostic models were constructed for AD and different AD subtypes. Moreover, drug prediction and molecular docking were also performed. Subsequently, a molecular dynamics (MD) simulation was conducted to further verify the findings. Finally, RT-qPCR validation was performed.ResultsThe characterization of 12 AD-related CRGs was evaluated in AD, and a diagnostic model for AD showed a satisfying discrimination power based on five CRGs by LASSO regression analysis. The dysregulated CRGs and activated immune responses partially differed between patients with AD and healthy subjects. Furthermore, two molecular subtypes (clusters A and B) with different immune infiltration characteristics in AD were identified. Similarly, a diagnostic model for different AD subtypes was built with nine CRGs, which achieved a good performance. Molecular docking revealed the optimum conformation of CHEMBL261454 and its target gene CSNK1D, which was further validated by MD simulation. The RT-qPCR results were consistent with those of the comprehensive analysis.ConclusionThis study systematically elucidated the complex relationship between cuproptosis and AD, providing novel molecular targets for treatment and diagnosis biomarkers of AD. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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