Ling Yingchun, Hu Lingmin, Chen Jie, Zhao Mingyong, Dai Xinyang
Department of Clinical Laboratory, Shaoxing Seventh People's Hospital, Shaoxing, Zhejiang, China.
Department of Geriatrics, Shaoxing Seventh People's Hospital, Shaoxing, Zhejiang, China.
Clinics (Sao Paulo). 2024 Apr 30;79:100373. doi: 10.1016/j.clinsp.2024.100373. eCollection 2024.
This study explored novel biomarkers that can affect the diagnosis and treatment in Alzheimer's Disease (AD) related to mitochondrial metabolism.
The authors obtained the brain tissue datasets for AD from the Gene Expression Omnibus (GEO) and downloaded the mitochondrial metabolism-related genes set from MitoCarta 3.0 for analysis. Differentially Expressed Genes (DEGs) were screened using the "limma" R package, and the biological functions and pathways were investigated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The LASSO algorithm was used to identify the candidate center genes and validated in the GSE97760 dataset. PMAIP1 with the highest diagnostic value was selected and its effect on the occurrence of AD by biological experiments.
A sum of 364 DEGs and 50 hub genes were ascertained. GO and KEGG enrichment analysis demonstrated that DEGs were preponderantly associated with cell metabolism and apoptosis. Five genes most associated with AD as candidate central genes by LASSO algorithm analysis. Then, the expression level and specificity of candidate central genes were verified by GSE97760 dataset, which confirmed that PMAIP1 had a high diagnostic value. Finally, the regulatory effects of PMAIP1 on apoptosis and mitochondrial function were detected by siRNA, flow cytometry and Western blot. siRNA-PMAIP1 can alleviate mitochondrial dysfunction and inhibit cell apoptosis.
This study identified biomarkers related to mitochondrial metabolism in AD and provided a theoretical basis for the diagnosis of AD. PMAIP1 was a potential candidate gene that may affect mitochondrial function in Hippocampal neuronal cells, and its mechanism deserves further study.
本研究探索了与线粒体代谢相关的、可影响阿尔茨海默病(AD)诊断和治疗的新型生物标志物。
作者从基因表达综合数据库(GEO)获取AD的脑组织数据集,并从MitoCarta 3.0下载线粒体代谢相关基因集进行分析。使用“limma”R包筛选差异表达基因(DEG),并通过基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析研究其生物学功能和通路。采用LASSO算法识别候选核心基因,并在GSE97760数据集中进行验证。选择诊断价值最高的PMAIP1,并通过生物学实验研究其对AD发生的影响。
共确定了364个DEG和50个核心基因。GO和KEGG富集分析表明,DEG主要与细胞代谢和凋亡相关。通过LASSO算法分析确定了5个与AD最相关的基因作为候选核心基因。然后,通过GSE97760数据集验证了候选核心基因的表达水平和特异性,证实PMAIP1具有较高的诊断价值。最后,通过siRNA、流式细胞术和蛋白质免疫印迹法检测PMAIP1对凋亡和线粒体功能的调节作用。siRNA-PMAIP1可减轻线粒体功能障碍并抑制细胞凋亡。
本研究鉴定了AD中线粒体代谢相关的生物标志物,为AD的诊断提供了理论依据。PMAIP1是一个潜在的候选基因,可能影响海马神经元细胞的线粒体功能,其机制值得进一步研究。