目的:进行了生物信息学和细胞实验的分析,以验证gasderminD(GSDMD)之间的关系,焦亡的执行蛋白,和阿尔茨海默病(AD)。
方法:训练集GSE33000用于鉴定AD组和对照组的差异表达基因(DEGs),以及GSDMD蛋白高/低表达组。随后,进行加权基因共表达网络分析(WGCNA)和最小绝对收缩和选择算子(LASSO)回归分析,然后选择关键基因进行后续基因本体论(GO)和京都基因和基因组百科全书(KEGG)分析。在训练集GSE33000以及验证集GSE5281和GSE48350中评估并确认了GSDMD和AD之间的关联。免疫荧光(IF)用于检测髓鞘碱性蛋白(MBP),在大鼠少突胶质细胞(OLN-93细胞)中发现的一种独特的蛋白质。将β-淀粉样蛋白1-42(Aβ1-42)的浓度范围(1-15μmol/L)暴露于细胞中,随后对细胞形态进行了观察。此外,进行评估以评估细胞活力,乳酸脱氢酶(LDH)的释放,细胞膜通透性,和GSDMD蛋白表达。
结果:使用GSE33000共筛选了7,492个DEG。随后,WGCNA分析鉴定出19个基因在AD中表现出与临床性状最强的相关性。此外,LASSO回归分析确定了13个关键基因,包括GSDMD,AFF1和ATOH8。此外,根据GO和KEGG分析,研究发现关键基因与细胞炎症相关.此外,训练集和验证集中关键基因的曲线下面积(AUC)值分别为0.95和0.70.重要的是,GSDMD在两个数据集上显示AD中的表达水平升高。细胞中MBP表达的阳性率超过95%。随着Aβ1-42作用的浓度逐渐升高,对细胞的有害影响逐渐加剧,导致细胞存活率逐渐下降,伴随着乳酸脱氢酶释放的增加,细胞膜通透性,和GSDMD蛋白表达。
结论:已观察到GSDMD与AD之间的关联,已经发现Aβ1-42可以诱导OLN-93细胞中GSDMD的显著上调。这表明Aβ1-42具有诱导细胞焦亡的潜力,可以作为AD研究的有价值的细胞焦亡模型。
OBJECTIVE: An analysis of bioinformatics and cell experiments was performed to verify the relationship between gasdermin D (GSDMD), an executive protein of pyroptosis, and Alzheimer\'s disease (AD).
METHODS: The training set GSE33000 was utilized to identify differentially expressed genes (DEGs) in both the AD group and control group, as well as in the GSDMD protein high/low expression group. Subsequently, the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) regression analysis were conducted, followed by the selection of the key genes for the subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The association between GSDMD and AD was assessed and confirmed in the training set GSE33000, as well as in the validation sets GSE5281 and GSE48350. Immunofluorescence (IF) was employed to detect the myelin basic protein (MBP), a distinctive protein found in the rat oligodendrocytes (OLN-93 cells). A range of concentrations (1-15 μmol/L) of β-amyloid 1-42 (Aβ1-42) were exposed to the cells, and the subsequent observations were made regarding cell morphology. Additionally, the assessments were conducted to evaluate the cell viability, the lactate dehydrogenase (LDH) release, the cell membrane permeability, and the GSDMD protein expression.
RESULTS: A total of 7,492 DEGs were screened using GSE33000. Subsequently, WGCNA analysis identified 19 genes that exhibited the strongest correlation with clinical traits in AD. Additionally, LASSO regression analysis identified 13 key genes, including GSDMD, AFF1, and ATOH8. Furthermore, the investigation revealed that the key genes were associated with cellular inflammation based on GO and KEGG analyses. Moreover, the area under the curve (AUC) values for the key genes in the training and validation sets were determined to be 0.95 and 0.70, respectively. Significantly, GSDMD demonstrated elevated levels of expression in AD across both datasets. The positivity of MBP expression in cells exceeded 95%. As the concentration of Aβ1-42 action gradually escalated, the detrimental effects on cells progressively intensified, resulting in a gradual decline in cell survival rate, accompanied by an increase in lactate dehydrogenase release, cell membrane permeability, and GSDMD protein expression.
CONCLUSIONS: The association between GSDMD and AD has been observed, and it has been found that Aβ1-42 can induce a significant upregulation of GSDMD in OLN-93 cells. This suggests that Aβ1-42 has the potential to induce cellular pyroptosis and can serve as a valuable cellular pyroptosis model for the study of AD.