鉴定免疫相关关键基因作为儿童脓毒症潜在诊断生物标志物
Identification of Immune-Related Key Genes as Potential Diagnostic Biomarkers of Sepsis in Children.
作者信息
Wang Huabin, Huang Junbin, Yi Wenfang, Li Jiahong, He Nannan, Kang Liangliang, He Zhijie, Chen Chun
机构信息
Division of Hematology/Oncology, Department of Pediatrics, the Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, People's Republic of China.
Department of Pediatric Intensive Care Unit, the Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, 518107, People's Republic of China.
出版信息
J Inflamm Res. 2022 Apr 14;15:2441-2459. doi: 10.2147/JIR.S359908. eCollection 2022.
OBJECTIVE
The pathogenesis of sepsis is still unclear due to its complexity, especially in children. This study aimed to analyse the immune microenvironment and regulatory networks related to sepsis in children at the molecular level and to identify key immune-related genes to provide a new basis for the early diagnosis of sepsis.
METHODS
The GSE145227 and GSE26440 datasets were downloaded from the Gene Expression Omnibus. The analyses included differentially expressed genes (DEGs), functional enrichment, immune cell infiltration, the competing endogenous RNA (ceRNA) interaction network, weighted gene coexpression network analysis (WGCNA), protein-protein interaction (PPI) network, key gene screening, correlation of sepsis molecular subtypes/immune infiltration with key gene expression, the diagnostic capabilities of key genes, and networks describing the interaction of key genes with transcription factors and small-molecule compounds. Finally, real-time quantitative PCR (RT-qPCR) was performed to verify the expression of key genes.
RESULTS
A total of 236 immune-related DEGs, most of which were enriched in immune-related biological functions, were found. Further analysis of immune cell infiltration showed that M0 macrophages and neutrophils infiltrated more in the sepsis group, while fewer activated memory CD4 T cells, resting memory CD4 T cells, and CD8 T cells did. The interaction network of ceRNA was successfully constructed. Six key genes (FYN, FBL, ATM, WDR75, FOXO1 and ITK) were identified by WGCNA and PPI analysis. We found strong associations between key genes and constructed septic molecular subtypes or immune cell infiltration. Receiver operating characteristic analysis showed that the area under the curve values of the key genes for diagnosis were all greater than 0.84. Subsequently, we successfully constructed an interaction network of key genes and transcription factors/small-molecule compounds. Finally, the key genes in the samples were verified by RT-qPCR.
CONCLUSION
Our results offer new insights into the pathogenesis of sepsis in children and provide new potential diagnostic biomarkers for the disease.
目的
由于脓毒症发病机制复杂，其发病机制仍不明确，尤其是在儿童中。本研究旨在从分子水平分析儿童脓毒症相关的免疫微环境和调控网络，并鉴定关键免疫相关基因，为脓毒症的早期诊断提供新依据。
方法
从基因表达综合数据库下载GSE145227和GSE26440数据集。分析包括差异表达基因（DEG）、功能富集、免疫细胞浸润、竞争性内源RNA（ceRNA）相互作用网络、加权基因共表达网络分析（WGCNA）、蛋白质-蛋白质相互作用（PPI）网络、关键基因筛选、脓毒症分子亚型/免疫浸润与关键基因表达的相关性、关键基因的诊断能力以及描述关键基因与转录因子和小分子化合物相互作用的网络。最后，进行实时定量PCR（RT-qPCR）验证关键基因的表达。
结果
共发现236个免疫相关的差异表达基因，其中大部分富集于免疫相关生物学功能。对免疫细胞浸润的进一步分析表明，脓毒症组中M0巨噬细胞和中性粒细胞浸润较多，而活化记忆CD4 T细胞、静息记忆CD4 T细胞和CD8 T细胞浸润较少。成功构建了ceRNA相互作用网络。通过WGCNA和PPI分析鉴定出6个关键基因（FYN、FBL、ATM、WDR75、FOXO1和ITK）。我们发现关键基因与构建的脓毒症分子亚型或免疫细胞浸润之间存在强关联。受试者工作特征分析表明，关键基因诊断的曲线下面积值均大于0.84。随后，我们成功构建了关键基因与转录因子/小分子化合物的相互作用网络。最后，通过RT-qPCR验证了样本中的关键基因。
结论
我们的结果为儿童脓毒症的发病机制提供了新见解，并为该疾病提供了新的潜在诊断生物标志物。
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