Table_7_Bioinformatics and Machine Learning Methods to Identify FN1 as a Novel Biomarker of Aortic Valve Calcification.XLSX

AimThe purpose of this study was to identify potential diagnostic markers for aortic valve calcification (AVC) and to investigate the function of immune cell infiltration in this disease.MethodsThe AVC data sets were obtained from the Gene Expression Omnibus. The identification of differentially expressed genes (DEGs) and the performance of functional correlation analysis were carried out using the R software. To explore hub genes related to AVC, a protein–protein interaction network was created. Diagnostic markers for AVC were then screened and verified using the least absolute shrinkage and selection operator, logistic regression, support vector machine-recursive feature elimination algorithms, and hub genes. The infiltration of immune cells into AVC tissues was evaluated using CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. Finally, the Connectivity Map database was used to forecast the candidate small molecule drugs that might be used as prospective medications to treat AVC.ResultsA total of 337 DEGs were screened. The DEGs that were discovered were mostly related with atherosclerosis and arteriosclerotic cardiovascular disease, according to the analyses. Gene sets involved in the chemokine signaling pathway and cytokine–cytokine receptor interaction were differently active in AVC compared with control. As the diagnostic marker for AVC, fibronectin 1 (FN1) (area the curve = 0.958) was discovered. Immune cell infiltration analysis revealed that the AVC process may be mediated by naïve B cells, memory B cells, plasma cells, activated natural killer cells, monocytes, and macrophages M0. Additionally, FN1 expression was associated with memory B cells, M0 macrophages, activated mast cells, resting mast cells, monocytes, and activated natural killer cells. AVC may be reversed with the use of yohimbic acid, the most promising small molecule discovered so far.ConclusionFN1 can be used as a diagnostic marker for AVC. It has been shown that immune cell infiltration is important in the onset and progression of AVC, which may benefit in the improvement of AVC diagnosis and treatment.

本研究旨在识别主动脉瓣钙化（AVC）的潜在诊断标志物，并探讨免疫细胞浸润在该疾病中的功能。研究方法：本研究从基因表达综合数据库中获取了AVC数据集。利用R软件进行了差异表达基因（DEGs）的识别和功能相关性分析。为了探索与AVC相关的枢纽基因，构建了蛋白质-蛋白质相互作用网络。随后，通过最小绝对收缩和选择算子、逻辑回归、支持向量机递归特征消除算法和枢纽基因筛选并验证了AVC的诊断标志物。使用CIBERSORT评估了免疫细胞在AVC组织中的浸润，并分析了诊断标志物与浸润性免疫细胞之间的相关性。最后，利用连通性图谱数据库预测了可能作为治疗AVC潜在药物的候选小分子药物。研究结果：共筛选出337个DEGs。根据分析，所发现的DEGs主要与动脉粥样硬化及动脉硬化性心血管疾病相关。与对照相比，参与趋化因子信号通路和细胞因子-细胞因子受体相互作用的基因集在AVC中活性不同。发现纤维连接蛋白1（FN1）（曲线下面积=0.958）可作为AVC的诊断标志物。免疫细胞浸润分析显示，AVC过程可能由原始B细胞、记忆B细胞、浆细胞、活化天然杀伤细胞、单核细胞和M0巨噬细胞介导。此外，FN1的表达与记忆B细胞、M0巨噬细胞、活化肥大细胞、静息肥大细胞、单核细胞和活化天然杀伤细胞相关。使用迄今为止发现的具有最大潜力的化合物——愈创木酸，可能有助于逆转AVC。结论：FN1可作为AVC的诊断标志物。研究表明，免疫细胞浸润在AVC的发生和发展中起着重要作用，这可能在改善AVC的诊断和治疗方面带来益处。