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脓毒症诱导肝衰竭中与铁死亡相关基因的筛选及免疫相关性分析。

Screening of ferroptosis-related genes in sepsis-induced liver failure and analysis of immune correlation.

机构信息

Department of Emergency Medicine, Lishui City People's Hospital, Lishui, Zhejiang Province, China.

Department of Infectious Disease, Lishui City People's Hospital, Lishui, Zhejiang Province, China.

出版信息

PeerJ. 2022 Jul 29;10:e13757. doi: 10.7717/peerj.13757. eCollection 2022.

DOI:10.7717/peerj.13757
PMID:35923893
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9341447/
Abstract

PURPOSE

Sepsis-induced liver failure is a kind of liver injury with a high mortality, and ferroptosis plays a key role in this disease. Our research aims to screen ferroptosis-related genes in sepsis-induced liver failure as targeted therapy for patients with liver failure.

METHODS

Using the limma software, we analyzed the differentially expressed genes (DEGs) in the GSE60088 dataset downloaded from the Gene Expression Omnibus (GEO) database. Clusterprofiler was applied for enrichment analysis of DEGs enrichment function. Then, the ferroptosis-related genes of the mice in the FerrDb database were crossed with DEGs. Sepsis mice model were prepared by cecal ligation and perforation (CLP). ALT and AST in the serum of mice were measured using detection kit. The pathological changes of the liver tissues in mice were observed by hematoxylin-eosin (H & E) staining. We detected the apoptosis of mice liver tissues using TUNEL. The expression of Hmox1, Epas1, Sirt1, Slc3a2, Jun, Plin2 and Zfp36 were detected by qRT-PCR.

RESULTS

DEGs analysis showed 136 up-regulated and 45 down-regulated DEGs. Meanwhile, we found that the up-regulated DEGs were enriched in pathways including the cytokine biosynthesis process while the down-regulated DEGs were enriched in pathways such as organic hydroxy compound metabolic process. In this study, seven genes (Hmox1, Epas1, Sirt1, Slc3a2, Jun, Plin2 and Zfp36) were obtained through the intersection of FerrDb database and DEGs. However, immune infiltration analysis revealed that ferroptosis-related genes may promote the development of liver failure through B cells and natural killer (NK) cells. Finally, it was confirmed by the construction of septic liver failure mice model that ferroptosis-related genes of Hmox1, Slc3a2, Jun and Zfp36 were significantly correlated with liver failure and were highly expressed.

CONCLUSION

The identification of ferroptosis-related genes Hmox1, Slc3a2, Jun and Zfp36 in the present study contribute to our understanding of the molecular mechanism of sepsis-induced liver failure, and provide candidate targets for the diagnosis and treatment of the disease.

摘要

目的

脓毒症相关性肝衰竭是一种高死亡率的肝损伤,铁死亡在该疾病中起关键作用。我们的研究旨在筛选脓毒症相关性肝衰竭中的铁死亡相关基因,作为肝衰竭患者的靶向治疗。

方法

使用 limma 软件分析从基因表达综合数据库(GEO)下载的 GSE60088 数据集的差异表达基因(DEGs)。使用 ClusterProfiler 进行 DEGs 富集功能分析。然后,将 FerrDb 数据库中的铁死亡相关基因与 DEGs 进行交叉。通过盲肠结扎穿孔(CLP)制备脓毒症小鼠模型。使用检测试剂盒测量小鼠血清中的 ALT 和 AST。通过苏木精-伊红(H&E)染色观察小鼠肝组织的病理变化。使用 TUNEL 检测小鼠肝组织的凋亡。使用 qRT-PCR 检测 Hmox1、Epas1、Sirt1、Slc3a2、Jun、Plin2 和 Zfp36 的表达。

结果

DEGs 分析显示 136 个上调和 45 个下调 DEGs。同时,我们发现上调的 DEGs 富集在细胞因子生物合成过程等途径中,而下调的 DEGs 富集在有机羟基化合物代谢过程等途径中。在本研究中,通过 FerrDb 数据库和 DEGs 的交集获得了七个基因(Hmox1、Epas1、Sirt1、Slc3a2、Jun、Plin2 和 Zfp36)。然而,免疫浸润分析表明,铁死亡相关基因可能通过 B 细胞和自然杀伤(NK)细胞促进肝衰竭的发展。最后,通过构建脓毒症相关性肝衰竭小鼠模型证实,Hmox1、Slc3a2、Jun 和 Zfp36 的铁死亡相关基因与肝衰竭显著相关,且表达水平较高。

结论

本研究中鉴定的 Hmox1、Slc3a2、Jun 和 Zfp36 等铁死亡相关基因有助于我们理解脓毒症相关性肝衰竭的分子机制,并为该疾病的诊断和治疗提供候选靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/d4a65d337192/peerj-10-13757-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/b503d7960d10/peerj-10-13757-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/e507571516b1/peerj-10-13757-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/c5daa9ddc2c0/peerj-10-13757-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/dd665f4098d5/peerj-10-13757-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/812cd7adedff/peerj-10-13757-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/d4a65d337192/peerj-10-13757-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/b503d7960d10/peerj-10-13757-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/e507571516b1/peerj-10-13757-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/c5daa9ddc2c0/peerj-10-13757-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/dd665f4098d5/peerj-10-13757-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/812cd7adedff/peerj-10-13757-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3af5/9341447/d4a65d337192/peerj-10-13757-g006.jpg

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