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Abstract Objecitve Endoplasmic reticulum (ER) stress can activate the unfolded protein response (UPR), and sustained activation of UPR is closely associated with inflammation and neuronal dysfunction, ultimately leading to neurodegeneration. This study aims to identify potential targets related to ER stress, aiming to provide new insights into the treatment of Alzheimer's disease (AD). Methods We conducted differential expression analysis of the GSE4757 dataset in the Gene Expression Omnibus (GEO) database using the GEO2R tool and performed Venn analysis to identify differentially expressed genes (DEGs) related to ER stress. Subsequently, we annotated the functions of DEGs in GSE4757 and ER stress genes, constructed a protein-protein interaction network using Cytoscape, and identified hub genes. Results The GSE4757 dataset contained a total of 407 DEGs, with 33 genes overlapping with those related to ER stress. The biological processes involved in these genes mainly include mesenchymal morphogenesis, muscle growth, and ossification regulation. KEGG analysis revealed that these genes mainly participate in cellular pathways such as the basal cell carcinoma signaling pathway, breast cancer, and pertussis signaling pathway. We also constructed a protein-protein interaction network of overlapping genes and identified four hub genes related to ER stress in AD by Cytoscape. Conclusion We used bioinformatics to study the potential role of ER stress related genes in AD, analyzed the functions of hub genes and their involvement in biological processes, and revealed new targets for intervening in ER stress, thereby providing a new direction for treating AD.
Liu et al. (Tue,) studied this question.