journal articles
ALZHEIMER’S DISEASE AND AGING ASSOCIATION: IDENTIFICATION AND VALIDATION OF RELATED GENES
T. Liu, K. Hou, J. Li, T. Han, S. Liu, . Wei
J Prev Alz Dis 2024;1(11):196-213
BACKGROUND: Aging is considered a key risk factor for Alzheimer’s disease (AD). This study aimed to identify and validate potential aging-related genes associated with AD using bioinformatics analysis.
METHODS: Datasets GSE36980 and GSE5281 were selected to screen differentially expressed genes (DEGs), and the immune cell correlation analysis and GSEA analysis of DEGs were performed. The intersection with senescence genes was taken as differentially expressed senescence-related genes (DESRGs), and the GSE44770 dataset was used for further validation. The potential biological functions and signaling pathways were determined by GO and KEGG, and the hub genes were identified by 12 algorithms in Cytohubba. The expression of 10 hub genes in different brain regions was determined and single-cell sequencing analysis was performed, and diagnostic genes were further screened by gene expression and receiver operating characteristic (ROC) curve. Finally, a miRNA-gene network of diagnostic genes was constructed and targeted drug prediction was performed.
RESULTS: A total of 2137 DEGs were screened from the GSE36980 and GSE5281 datasets, and 278 SRGs were identified from the CellAge database. The overlapping DEGs and SRGs constituted 29 DESRGs, including 14 senescence suppressor genes and 15 senescence inducible genes. The top 10 hub genes, including MDH1, CKB, PSMD14, SMARCA4, PEBP1, DDB2, ITPKB, ATF7IP, YAP1, and EWSR1 were screened. Furthermore, four diagnostic genes were identified: PMSD14, PEBP1, ITPKB, and ATF7IP. The ROC analysis showed that the respective area under the curves (AUCs) of PMSD14, PEBP1, ITPKB, and ATF7IP were 0.732, 0.701, 0.747, and 0.703 in the GSE36980 dataset and 0.870, 0.817, 0.902, and 0.834 in the GSE5281 dataset. In the GSE44770 dataset, PMSD14 (AUC, 0.838) and ITPKB (AUC, 0.952) had very high diagnostic values in the early stage of AD. Finally, based on these diagnostic genes, we found that the drug Abemaciclib is a targeted drug for the treatment of age-related AD. Flutamide can aggravate aging-related AD.
CONCLUSION: The results of this study suggest that cellular SRGs might play an important role in AD. PMSD14, PEBP1, ITPKB, and ATF7IP have the potential as specific biomarkers for the early diagnosis of AD.
CITATION:
T. Liu ; K. Hou ; J. Li ; T. Han ; S. Liu ; J. Wei ; (2023): Alzheimer’s Disease and Aging Association: Identification and Validation of Related Genes. The Journal of Prevention of Alzheimer’s Disease (JPAD). http://dx.doi.org/10.14283/jpad.2023.101