Department of Neurology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Medical Research Center, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Biomed Res Int. 2022 Jun 8;2022:2747043. doi: 10.1155/2022/2747043. eCollection 2022.
108 IS samples and 47 matched controls were obtained from the GEO database. Immune-related genes (IRGs) and their associated drugs were collected from the ImmPort and PharmGBK databases, respectively. Random forest (RF) regression and least absolute shrinkage and selection operator (LASSO) logistic regression were applied to identify immune-related genetic biomarkers (IRGBs) of IS, and accuracy was verified using neural network models. Finally, proportion changes of various immune cells in peripheral blood of IS patients were evaluated using CIBERSORT and xCell and correlation analyses were performed between IRGBs and differentially distributed immune cells.
A total of 537 genes were differentially expressed between IS and control samples. Four immune-related differential expressed genes identified by regression analysis presented strong predictive power (AUC = 0.909) which we suggeseted them as immune-related genetic biomarkers (IRGBs). We also demonstrated six immune-related genes targeted by known drugs. In addition, post-IS immune system presented an increase in the proportion of innate immune cells and a decrease in adaptive immune cells in the peripheral circulation, and IRGBs showing significance were associated with this process.
The study identified , , , and as immune-related genetic biomarkers of IS. Six immune-related DEGs targeted by known drugs were found and provide new candidate drug targets for modulating the post-IS immune system. The innate immune cells and adaptive immune cells are diversified in the post-IS immune system, and IRGBs might play important role during this process.
从 GEO 数据库中获得了 108 例 IS 样本和 47 例匹配对照。分别从 ImmPort 和 PharmGBK 数据库中收集免疫相关基因(IRGs)及其相关药物。应用随机森林(RF)回归和最小绝对值收缩和选择算子(LASSO)逻辑回归来识别 IS 的免疫相关遗传生物标志物(IRGBs),并使用神经网络模型验证准确性。最后,使用 CIBERSORT 和 xCell 评估 IS 患者外周血中各种免疫细胞的比例变化,并对 IRGBs 和差异分布的免疫细胞进行相关性分析。
IS 组与对照组样本之间有 537 个基因存在差异表达。通过回归分析确定的 4 个免疫相关差异表达基因具有很强的预测能力(AUC=0.909),我们将其建议作为免疫相关遗传生物标志物(IRGBs)。我们还证明了 6 个与已知药物靶标相关的免疫相关基因。此外,IS 后免疫系统在外周循环中呈现固有免疫细胞比例增加和适应性免疫细胞比例降低的趋势,具有显著性的 IRGBs与该过程相关。
本研究确定、、、和 为 IS 的免疫相关遗传生物标志物。发现了 6 个与已知药物靶标相关的免疫相关差异表达基因,为调节 IS 后免疫系统提供了新的候选药物靶点。IS 后免疫系统中固有免疫细胞和适应性免疫细胞呈多样化,IRGBs 在该过程中可能发挥重要作用。