鉴定和验证与免疫相关的基因，用于诊断动脉粥样硬化和代谢综合征的进展。
Identification and verification of immune-related genes for diagnosing the progression of atherosclerosis and metabolic syndrome.
机构信息
Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, 137 Liyushan South Road, Urumqi, Tel, 830054, People's Republic of China.
State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Clinical Medical Research Institute, the First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
出版信息
BMC Cardiovasc Disord. 2024 Aug 2;24(1):405. doi: 10.1186/s12872-024-04026-3.
BACKGROUND
Atherosclerosis and metabolic syndrome are the main causes of cardiovascular events, but their underlying mechanisms are not clear. In this study, we focused on identifying genes associated with diagnostic biomarkers and effective therapeutic targets associated with these two diseases.
METHODS
Transcriptional data sets of atherosclerosis and metabolic syndrome were obtained from GEO database. The differentially expressed genes were analyzed by RStudio software, and the function-rich and protein-protein interactions of the common differentially expressed genes were analyzed.Furthermore, the hub gene was screened by Cytoscape software, and the immune infiltration of hub gens was analyzed. Finally, relevant clinical blood samples were collected for qRT-PCR verification of the three most important hub genes.
RESULTS
A total of 1242 differential genes (778 up-regulated genes and 464 down-regulated genes) were screened from GSE28829 data set. A total of 1021 differential genes (492 up-regulated genes and 529 down-regulated genes) were screened from the data set GSE98895. Then 23 up-regulated genes and 11 down-regulated genes were screened by venn diagram. Functional enrichment analysis showed that cytokines and immune activation were involved in the occurrence and development of these two diseases. Through the construction of the Protein-Protein Interaction(PPI) network and Cytoscape software analysis, we finally screened 10 hub genes. The immune infiltration analysis was further improved. The results showed that the infiltration scores of 7 kinds of immune cells in GSE28829 were significantly different among groups (Wilcoxon Test < 0.05), while in GSE98895, the infiltration scores of 4 kinds of immune cells were significantly different between groups (Wilcoxon Test < 0.05). Spearman method was used to analyze the correlation between the expression of 10 key genes and 22 kinds of immune cell infiltration scores in two data sets. The results showed that there were 42 pairs of significant correlations between 10 genes and 22 kinds of immune cells in GSE28829 (|Cor| > 0.3 & P < 0.05). There were 41 pairs of significant correlations between 10 genes and 22 kinds of immune cells in GSE98895 (|Cor| > 0.3 & P < 0.05). Finally, our results identified 10 small molecules with the highest absolute enrichment value, and the three most significant key genes (CX3CR1, TLR5, IL32) were further verified in the data expression matrix and clinical blood samples.
CONCLUSION
We have established a co-expression network between atherosclerotic progression and metabolic syndrome, and identified key genes between the two diseases. Through the method of bioinformatics, we finally obtained 10 hub genes in As and MS, and selected 3 of the most significant genes (CX3CR1, IL32, TLR5) for blood PCR verification. This may be helpful to provide new research ideas for the diagnosis and treatment of AS complicated with MS.
背景
动脉粥样硬化和代谢综合征是心血管事件的主要原因，但它们的潜在机制尚不清楚。在这项研究中，我们专注于鉴定与这两种疾病相关的诊断生物标志物和有效治疗靶点相关的基因。
方法
从 GEO 数据库中获取动脉粥样硬化和代谢综合征的转录组数据集。使用 RStudio 软件分析差异表达基因，并分析常见差异表达基因的功能丰富度和蛋白质-蛋白质相互作用。此外，使用 Cytoscape 软件筛选枢纽基因，并分析枢纽基因的免疫浸润。最后，收集相关临床血液样本进行 qRT-PCR 验证三个最重要的枢纽基因。
结果
从 GSE28829 数据集筛选出共 1242 个差异基因（778 个上调基因和 464 个下调基因）。从 GSE98895 数据集筛选出共 1021 个差异基因（492 个上调基因和 529 个下调基因）。然后通过 venn 图筛选出 23 个上调基因和 11 个下调基因。功能富集分析表明，细胞因子和免疫激活参与了这两种疾病的发生和发展。通过构建蛋白质-蛋白质相互作用（PPI）网络和 Cytoscape 软件分析，我们最终筛选出 10 个枢纽基因。进一步改进了免疫浸润分析。结果表明，在 GSE28829 中，7 种免疫细胞的浸润评分在各组之间存在显著差异（Wilcoxon Test < 0.05），而在 GSE98895 中，4 种免疫细胞的浸润评分在各组之间存在显著差异（Wilcoxon Test < 0.05）。Spearman 方法用于分析两个数据集 10 个关键基因表达与 22 种免疫细胞浸润评分之间的相关性。结果表明，在 GSE28829 中，10 个基因与 22 种免疫细胞之间存在 42 对显著相关性（|Cor| > 0.3 & P < 0.05）。在 GSE98895 中，10 个基因与 22 种免疫细胞之间存在 41 对显著相关性（|Cor| > 0.3 & P < 0.05）。最后，我们确定了具有最高绝对富集值的 10 种小分子，并且在数据表达矩阵和临床血液样本中进一步验证了三个最重要的关键基因（CX3CR1、TLR5、IL32）。
结论
我们建立了动脉粥样硬化进展和代谢综合征之间的共表达网络，并鉴定了两种疾病之间的关键基因。通过生物信息学方法，我们最终获得了 As 和 MS 中的 10 个枢纽基因，并选择了 3 个最显著的基因（CX3CR1、IL32、TLR5）进行血液 PCR 验证。这可能有助于为 AS 合并 MS 的诊断和治疗提供新的研究思路。
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