Shandong University of Traditional Chinese Medicine, Jinan, 250014, China.
Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, 250014, China.
Sci Rep. 2023 Mar 1;13(1):3488. doi: 10.1038/s41598-023-30666-0.
Heart failure is the final destination of most cardiovascular diseases, and its complex molecular mechanisms remain largely uncertain. This study aimed to systematically investigate the underlying molecular mechanisms and diagnostic and therapeutic targets of heart failure using bioinformatics. We obtained 8 healthy samples and 8 heart failure samples from GSE8331 and GSE76701. After removing the batch effect, we performed a differential analysis on it and obtained 185 differentially expressed ID. The results of enrichment analysis showed that the molecular mechanisms of heart failure were mostly related to immune, inflammation, and metabolism-related pathways. Immune cell infiltration analysis showed that the degree of infiltration of Tgd cells and Neurons was significantly enriched in heart failure samples, whereas pDCs and NKTs were in healthy tissue samples. We obtained Hub genes including EGR1, EGR2, FOS and FOSB by PPI network analysis. We established a 4-gene diagnostic model with Hub gene, and validated it in GSE21610 and GSE57338, and evaluated the discriminative ability of Hub gene by ROC curve. The 4-gene diagnostic model has an AUC value of 0.775 in GSE21610 and 0.877 in GSE57338. In conclusion, we explored the underlying molecular mechanisms of heart failure and the immune cell infiltration environment of failing myocardium by performing bioinformatic analysis of the GEO dataset. In addition, we identified EGR1, EGR2, FOS and FOSB as potential diagnostic biomarkers and therapeutic targets for heart failure. More importantly, a diagnostic model of heart failure based on these 4 genes was developed, which leads to a new understanding of the pathogenesis of heart failure and may be an interesting target for future in-depth research.
心力衰竭是大多数心血管疾病的最终归宿，其复杂的分子机制在很大程度上仍不确定。本研究旨在使用生物信息学系统地研究心力衰竭的潜在分子机制以及诊断和治疗靶点。我们从 GSE8331 和 GSE76701 中获得了 8 个健康样本和 8 个心力衰竭样本。在去除批次效应后，我们对其进行了差异分析，得到了 185 个差异表达 ID。富集分析的结果表明，心力衰竭的分子机制主要与免疫、炎症和代谢相关途径有关。免疫细胞浸润分析表明，Tgd 细胞和神经元的浸润程度在心力衰竭样本中显著富集，而 pDCs 和 NKTs 在健康组织样本中富集。我们通过 PPI 网络分析获得了包括 EGR1、EGR2、FOS 和 FOSB 在内的 Hub 基因。我们建立了一个包含 Hub 基因的 4 基因诊断模型，并在 GSE21610 和 GSE57338 中进行了验证，并用 ROC 曲线评估了 Hub 基因的判别能力。该 4 基因诊断模型在 GSE21610 中的 AUC 值为 0.775，在 GSE57338 中的 AUC 值为 0.877。总之，我们通过对 GEO 数据集进行生物信息学分析，探讨了心力衰竭的潜在分子机制和衰竭心肌的免疫细胞浸润环境。此外，我们确定了 EGR1、EGR2、FOS 和 FOSB 作为心力衰竭的潜在诊断生物标志物和治疗靶点。更重要的是，基于这 4 个基因开发了心力衰竭的诊断模型，这为心力衰竭的发病机制提供了新的认识，可能成为未来深入研究的一个有趣目标。
