Department of Critical Care Medicine, the Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
School of Medicine, Shaoxing University, Shaoxing, China.
Environ Toxicol. 2024 Jun;39(6):3341-3355. doi: 10.1002/tox.24198. Epub 2024 Mar 5.
Sepsis remains a crucial global health issue characterized by high mortality rates and a lack of specific treatments. This study aimed to elucidate the molecular mechanisms underlying sepsis and to identify potential therapeutic targets and compounds.
High-throughput sequencing data from the GEO database (GSE26440 as the training set and GSE13904 and GSE32707 as the validation sets), weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, alongside a combination of PPI and machine learning methods (LASSO and SVM) were utilized.
WGCNA identified the black module as positively correlated, and the green module as negatively correlated with sepsis. Further intersections of these module genes with age-related genes yielded 57 sepsis-related genes. GO and KEGG pathway enrichment analysis, PPI, LASSO, and SVM selected six hub aging-related genes: BCL6, FOS, ETS1, ETS2, MAPK14, and MYC. A diagnostic model was constructed based on these six core genes, presenting commendable performance in both the training and validation sets. Notably, ETS1 demonstrated significant differential expression between mild and severe sepsis, indicating its potential as a biomarker of severity. Furthermore, immune infiltration analysis of these six core genes revealed their correlation with most immune cells and immune-related pathways. Additionally, compounds were identified in the traditional Chinese medicine Danshen, which upon further analysis, revealed 354 potential target proteins. GO and KEGG enrichment analysis of these targets indicated a primary enrichment in inflammation and immune-related pathways. A Venn diagram intersects these target proteins, and our aforementioned six core genes yielded three common genes, suggesting the potential efficacy of Danshen in sepsis treatment through these genes.
This study highlights the pivotal roles of age-related genes in the molecular mechanisms of sepsis, offers potential biomarkers, and identifies promising therapeutic compounds, laying a robust foundation for future studies on the treatment of sepsis.
脓毒症仍然是一个严重的全球健康问题，其特点是死亡率高，缺乏特定的治疗方法。本研究旨在阐明脓毒症的分子机制，并确定潜在的治疗靶点和化合物。
利用 GEO 数据库（GSE26440 作为训练集，GSE13904 和 GSE32707 作为验证集）中的高通量测序数据，进行加权基因共表达网络分析（WGCNA）、基因本体论（GO）和京都基因与基因组百科全书（KEGG）通路富集分析，以及 PPI 和机器学习方法（LASSO 和 SVM）的组合。
WGCNA 鉴定出黑色模块与脓毒症呈正相关，绿色模块与脓毒症呈负相关。进一步将这些模块基因与年龄相关基因进行交集，得到 57 个与脓毒症相关的基因。GO 和 KEGG 通路富集分析、PPI、LASSO 和 SVM 选择了六个关键的与衰老相关的基因：BCL6、FOS、ETS1、ETS2、MAPK14 和 MYC。基于这六个核心基因构建了一个诊断模型，在训练集和验证集均表现出良好的性能。值得注意的是，ETS1 在轻度和重度脓毒症之间表现出显著的差异表达，表明其作为严重程度标志物的潜力。此外，对这六个核心基因的免疫浸润分析显示，它们与大多数免疫细胞和免疫相关通路相关。此外，还在传统中药丹参中发现了化合物，进一步分析表明，丹参中有 354 个潜在的靶蛋白。这些靶蛋白的 GO 和 KEGG 富集分析表明，它们主要富集在炎症和免疫相关通路中。一个 Venn 图将这些靶蛋白与我们之前提到的六个核心基因相交，得到三个共同的基因，这表明丹参通过这些基因治疗脓毒症的潜在疗效。
本研究强调了年龄相关基因在脓毒症分子机制中的关键作用，提供了潜在的生物标志物，并鉴定了有前途的治疗化合物，为脓毒症治疗的进一步研究奠定了坚实的基础。
