Cheng-Mei Wang, Luo Gang, Liu Ping, Ren Wei, Yang Sijin
Beibei Traditional Chinese Medicine Hospital, Chongqing - China.
The Affiliated Hospital of Traditional Chinese Medicine of Southwest Medical University, Luzhou, Sichuan - China.
Arq Bras Cardiol. 2024 Nov;121(12):e20230674. doi: 10.36660/abc.20230674.
Myocardial fibrosis (MF) occurs throughout the onset and progression of cardiovascular disease, and early diagnosis of MF is beneficial for improving cardiac function, but there is a lack of research on early biomarkers of MF.
Utilizing bioinformatics techniques, we identified potential biomarkers for MF.
Datasets related to MF were sourced from the GEO database. After processing the data, differentially expressed genes were screened. Differentially expressed genes were enriched, and subsequently, protein-protein interaction (PPI) was performed to analyze the differential genes. The associated miRNAs and transcription factors were predicted for these core genes. Finally, ROC validation was performed on the core genes to determine their specificity and sensitivity as potential biomarkers. The level of significance adopted was 5% (p < 0.05).
A total of 91 differentially expressed genes were identified, and PPI analysis yielded 31 central genes. Enrichment analysis showed that apoptosis, collagen, extracellular matrix, cell adhesion, and inflammation were involved in MF. One hundred and forty-two potential miRNAs were identified. the transcription factors JUN, NF-κB1, SP1, RELA, serum response factor (SRF), and STAT3 were enriched in most of the core targets. Ultimately, IL11, GADD45B, GDF5, NOX4, IGFBP3, ACTC1, MYOZ2, and ITGB8 had higher diagnostic accuracy and sensitivity in predicting MF based on ROC curve analysis.
Eight genes, IL11, GADD45B, GDF5, NOX4, IGFBP3, ACTC1, MYOZ2, and ITGB8, can serve as candidate biomarkers for MF. Processes such as cellular apoptosis, collagen protein synthesis, extracellular matrix formation, cellular adhesion, and inflammation are implicated in the development of MF.
心肌纤维化（MF）贯穿于心血管疾病的发生和发展过程，早期诊断MF有利于改善心脏功能，但目前缺乏关于MF早期生物标志物的研究。
利用生物信息学技术，我们鉴定了MF的潜在生物标志物。
从GEO数据库获取与MF相关的数据集。对数据进行处理后，筛选差异表达基因。对差异表达基因进行富集分析，随后进行蛋白质-蛋白质相互作用（PPI）分析以分析差异基因。预测这些核心基因相关的miRNA和转录因子。最后，对核心基因进行ROC验证，以确定它们作为潜在生物标志物的特异性和敏感性。采用的显著性水平为5%（p < 0.05）。
共鉴定出91个差异表达基因，PPI分析产生31个核心基因。富集分析表明，细胞凋亡、胶原蛋白、细胞外基质、细胞黏附及炎症参与了MF的发生。鉴定出142个潜在的miRNA。转录因子JUN、NF-κB1、SP1、RELA、血清反应因子（SRF）和STAT3在大多数核心靶点中富集。最终，基于ROC曲线分析，IL11、GADD45B、GDF5、NOX4、IGFBP3、ACTC1、MYOZ2和ITGB8在预测MF方面具有较高的诊断准确性和敏感性。
IL11、GADD45B、GDF5、NOX4、IGFBP3、ACTC1、MYOZ2和ITGB8这8个基因可作为MF的候选生物标志物。细胞凋亡、胶原蛋白合成、细胞外基质形成、细胞黏附及炎症等过程与MF的发生发展有关。
