Xiong Tao, Han Shen, Pu Lei, Zhang Tian-Chen, Zhan Xu, Fu Tao, Dai Ying-Hai, Li Ya-Xiong
Cardiovascular Surgery, Yan'an Affiliated Hospital of Kunming Medical University, Kunming Medical University, Kunming, China.
Key Laboratory of Cardiovascular Disease of Yunnan Province, Yan'an Affiliated Hospital of Kunming Medical University, Kunming Medical University, Kunming, China.
Front Cardiovasc Med. 2022 Feb 28;9:832591. doi: 10.3389/fcvm.2022.832591. eCollection 2022.
The 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.
The 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.
A 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.
FN1 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.
本研究旨在确定主动脉瓣钙化（AVC）的潜在诊断标志物，并研究免疫细胞浸润在该疾病中的作用。
从基因表达综合数据库获取AVC数据集。使用R软件进行差异表达基因（DEG）的鉴定和功能相关性分析。为探索与AVC相关的枢纽基因，构建了蛋白质-蛋白质相互作用网络。然后使用最小绝对收缩和选择算子、逻辑回归、支持向量机-递归特征消除算法以及枢纽基因筛选并验证AVC的诊断标志物。使用CIBERSORT评估免疫细胞向AVC组织的浸润情况，并分析诊断标志物与浸润免疫细胞之间的相关性。最后，利用连通性图谱数据库预测可能用作治疗AVC的前瞻性药物的候选小分子药物。
共筛选出337个DEG。分析表明，发现的DEG大多与动脉粥样硬化和动脉粥样硬化性心血管疾病相关。与对照组相比，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中具有不同的活性。发现纤连蛋白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过程可能由未成熟B细胞、记忆B细胞、浆细胞、活化的自然杀伤细胞、单核细胞和M0巨噬细胞介导。此外，FN1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、单核细胞和活化的自然杀伤细胞相关。使用育亨宾酸（迄今为止发现的最有前景的小分子）可能会逆转AVC。
FN1可作为AVC的诊断标志物。研究表明，免疫细胞浸润在AVC的发生和发展中起重要作用，这可能有助于改善AVC的诊断和治疗。
