Bioinformatics analysis and experimental validation of differentially expressed genes related to Alzheimer's disease

Hai Shuqin; Luo Jun; Zhu Xi; Miao Jiaodan; Liu Hua; Pu Tao; Gao Li; Gong Jiaojiao; He Liu; Wang Lu

doi:10.11986/j.issn.1673-873X.2025.09.05

Abstract：Objective To analyze and screen three gene chip datasets related to Alzheimer's disease(AD)using bioinformat-ics methods and identify potential biomarkers associated with the disease through bioinformatics analysis and clinical sample verification,providing a reference for the diagnosis and treatment of AD.Methods Differential analysis of the GSE97760,GSE63060,and GSE63061 datasets was performed using the GEO2R online analysis tool.GO/KEGG enrichment analysis was conducted using the DAVID online database.A protein-protein interaction(PPI)network was constructed using the STRING database,and RT-qPCR was used to validate clinical samples.Additionally,AD patients who visited the Depart-ment of Neurology of the Third People's Hospital of Chengdu from 2022 to 2024 were selected for the study.Relevant infor-mation,including patient name,gender,age,medical history,and Montreal Cognitive Assessment(MoCA)scores,was collected through electronic medical records and on-site survey questionnaires.Twenty AD patients diagnosed clinically were randomly selected as the AD group,and 20 volunteers without cognitive impairment were selected as the control group.The expression levels of EIF3E,RPL39,RPS3A,RPS24,RPL31,TOMM7,RPL26,RPL7,RPL17,and EEF1B2 in peripher-al blood of patients in both groups were observed.Results Differential analysis identified 27 common differentially ex-pressed genes across the three datasets.GO enrichment and KEGG pathway analysis were performed,followed by construc-tion of a PPI network,which revealed 10 core genes:EIF3E,RPL39,RPS3A,RPS24,RPL31,TOMM7,RPL26,RPL7,RPL17,and EEF1B2.Functional analysis showed that these genes were mainly involved in processes such as cytoplasmic translation,rRNA processing,biogenesis of ribosomal subunits,and translation initiation.Detection of the mRNA relative expression levels of the 10 core genes showed that RPS3A,RPL26,RPL39,TOMM7,and EEF1B2 were upregulated,but the changes were not statistically significant(P＞0.05).RPL31,RPL7,and RPS24 were significantly upregulated(P＜0.05).EIF3E expression was downregulated,but the changes were not statistically significant(P＞0.05),and RPL17 ex-pression was significantly downregulated(P＜0.05).Conclusion Through bioinformatics analysis,this study identified core genes related to AD and validated them experimentally.These genes may play important roles in the pathogenesis of AD.These findings provide new insights for further research on AD and offer potential novel biomarkers for its clinical diag-nosis and treatment.