Guangxi university of chinese medicine Nanning, China.
Shaanxi University of Traditional Chinese Medicine Xianyang, China.
Exp Gerontol. 2024 Mar;187:112374. doi: 10.1016/j.exger.2024.112374. Epub 2024 Feb 6.
Ischemic stroke and vascular dementia, as common cerebrovascular diseases, with the former causing irreversible neurological damage and the latter causing cognitive and memory impairment, are closely related and have long received widespread attention. Currently, the potential causative genes of these two diseases have yet to be investigated, and effective early diagnostic tools for the diseases have not yet emerged. In this study, we screened new potential biomarkers and analyzed new therapeutic targets for both diseases from the perspective of immune infiltration. Two gene expression profiles on ischemic stroke and vascular dementia were obtained from the NCBI GEO database, and key genes were identified by LASSO regression and SVM-RFE algorithms, and key genes were analyzed by GO and KEGG enrichment. The CIBERSORT algorithm was applied to the gene expression profile species of the two diseases to quantify the 24 subpopulations of immune cells. Moreover, logistic regression modeling analysis was applied to illustrate the stability of the key genes in the diagnosis. Finally, the key genes were validated using RT-PCR assay. A total of 105 intersecting DEGs genes were obtained in the 2 sets of GEO datasets, and bioinformatics functional analysis of the intersecting DEGs genes showed that GO was mainly involved in the purine ribonucleoside triphosphate metabolic process，respiratory chain complex，DNA-binding transcription factor binding and active transmembrane transporter activity. KEGG is mainly involved in the Oxidative phosphorylation, cAMP signaling pathway. The LASSO regression algorithm and SVM-RFE algorithm finally obtained three genes, GAS2L1, ARHGEF40 and PFKFB3, and the logistic regression prediction model determined that the three genes, GAS2L1 (AUC: 0.882), ARHGEF40 (AUC: 0.867) and PFKFB3 (AUC: 0.869), had good diagnostic performance. Meanwhile, the two disease core genes and immune infiltration were closely related, GAS2L1 and PFKFB3 had the highest positive correlation with macrophage M1 (p < 0.001) and the highest negative correlation with mast cell activation (p = 0.0017); ARHGEF40 had the highest positive correlation with macrophage M1 and B cells naive (p < 0.001), the highest negative correlation with B cell memory highest correlation (p = 0.0047). RT-PCR results showed that the relative mRNA expression levels of GAS2L1, ARHGEF40, and PFKFB3 were significantly elevated in the populations of both disease groups (p < 0.05). Immune infiltration-based models can be used to predict the diagnosis of patients with ischemic stroke and vascular dementia and provide a new perspective on the early diagnosis and treatment of both diseases.
缺血性卒中和血管性痴呆作为常见的脑血管疾病，前者可导致不可逆的神经损伤，后者可导致认知和记忆障碍，两者密切相关，长期以来受到广泛关注。目前，这两种疾病的潜在致病基因尚未被研究，也没有出现有效的早期诊断工具。在这项研究中，我们从免疫浸润的角度筛选了这两种疾病的新的潜在生物标志物，并分析了新的治疗靶点。从 NCBI GEO 数据库中获得了缺血性卒中和血管性痴呆的两个基因表达谱，并通过 LASSO 回归和 SVM-RFE 算法鉴定了关键基因，通过 GO 和 KEGG 富集分析了关键基因。应用 CIBERSORT 算法对两种疾病的基因表达谱物种进行量化，分析 24 种免疫细胞亚群。此外，应用逻辑回归建模分析说明了关键基因在诊断中的稳定性。最后，使用 RT-PCR 检测验证了关键基因。在 2 组 GEO 数据集中共获得了 105 个交集差异表达基因，交集差异表达基因的生物信息学功能分析表明，GO 主要参与嘌呤核糖核苷酸三磷酸代谢过程、呼吸链复合物、DNA 结合转录因子结合和主动跨膜转运体活性。KEGG 主要参与氧化磷酸化、cAMP 信号通路。LASSO 回归算法和 SVM-RFE 算法最终得到三个基因，GAS2L1、ARHGEF40 和 PFKFB3，逻辑回归预测模型确定三个基因 GAS2L1（AUC：0.882）、ARHGEF40（AUC：0.867）和 PFKFB3（AUC：0.869）具有良好的诊断性能。同时，两种疾病的核心基因与免疫浸润密切相关，GAS2L1 和 PFKFB3 与巨噬细胞 M1 的正相关性最高（p<0.001），与肥大细胞激活的负相关性最高（p=0.0017）；ARHGEF40 与巨噬细胞 M1 和初始 B 细胞的正相关性最高（p<0.001），与记忆 B 细胞的最高负相关性（p=0.0047）。RT-PCR 结果显示，两种疾病人群中 GAS2L1、ARHGEF40 和 PFKFB3 的相对 mRNA 表达水平均显著升高（p<0.05）。基于免疫浸润的模型可用于预测缺血性卒中和血管性痴呆患者的诊断，并为两种疾病的早期诊断和治疗提供新的视角。
