Screening and analysis of programmed cell death related genes and targeted drugs in sepsis.

IF 2.7 3区 生物学
Juanjuan Song, Kairui Ren, Yi Wang, Dexin Zhang, Lin Sun, Zhiqiang Tang, Lili Zhang, Ying Deng
{"title":"Screening and analysis of programmed cell death related genes and targeted drugs in sepsis.","authors":"Juanjuan Song, Kairui Ren, Yi Wang, Dexin Zhang, Lin Sun, Zhiqiang Tang, Lili Zhang, Ying Deng","doi":"10.1186/s41065-025-00403-w","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>This study employed bioinformatics techniques to identify diagnostic genes associated with programmed cell death (PCD) and to explore potential therapeutic agents for the treatment of sepsis.</p><p><strong>Methods: </strong>Gene expression profiles from sepsis patients were analyzed to identify differentially expressed genes (DEGs) and hub genes through Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to elucidate the functions of the DEGs. PCD-related genes were cross-referenced with the identified DEGs. Diagnostic genes were selected using Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) methodologies. Single-cell RNA sequencing was utilized to assess gene expression in blood cells, while CIBERSORT was employed to evaluate immune cell infiltration. A transcription factor (TF)-microRNA (miRNA)-hub gene network was constructed, and potential therapeutic compounds were predicted using the Drug Gene Interaction Database (DGIdb). Mendelian Randomization (MR) methods were applied to analyze genome-wide association study (GWAS) data for S100A9, TXN, and GSTO1.</p><p><strong>Results: </strong>The analysis revealed 2156 PCD-related genes, 714 DEGs, and 1198 hub genes, with 88 genes enriched in immune and cell death pathways. Five pivotal PCD-related genes (IRAK3, S100A9, TXN, NFATC2, and GSTO1) were identified, leading to the construction of a network comprising six transcription factors and 171 microRNAs. Additionally, seven drugs targeting S100A9, TXN, and NFATC2 were identified. MR analysis suggested that a decrease in GSTO1 levels is associated with an increased risk of sepsis, and that sepsis influences the levels of S100A9, TXN, and GSTO1.</p><p><strong>Conclusions: </strong>Through bioinformatics approaches, this study successfully identified five genes (IRAK3, S100A9, TXN, NFATC2, and GSTO1) associated with programmed cell death in the context of sepsis. This research identified seven candidate drugs for sepsis treatment and established a methodological framework for predicting biomarkers and drug targets that could be applicable to other diseases.</p>","PeriodicalId":12862,"journal":{"name":"Hereditas","volume":"162 1","pages":"40"},"PeriodicalIF":2.7000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11921706/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hereditas","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s41065-025-00403-w","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: This study employed bioinformatics techniques to identify diagnostic genes associated with programmed cell death (PCD) and to explore potential therapeutic agents for the treatment of sepsis.

Methods: Gene expression profiles from sepsis patients were analyzed to identify differentially expressed genes (DEGs) and hub genes through Weighted Gene Co-expression Network Analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted to elucidate the functions of the DEGs. PCD-related genes were cross-referenced with the identified DEGs. Diagnostic genes were selected using Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest (RF) methodologies. Single-cell RNA sequencing was utilized to assess gene expression in blood cells, while CIBERSORT was employed to evaluate immune cell infiltration. A transcription factor (TF)-microRNA (miRNA)-hub gene network was constructed, and potential therapeutic compounds were predicted using the Drug Gene Interaction Database (DGIdb). Mendelian Randomization (MR) methods were applied to analyze genome-wide association study (GWAS) data for S100A9, TXN, and GSTO1.

Results: The analysis revealed 2156 PCD-related genes, 714 DEGs, and 1198 hub genes, with 88 genes enriched in immune and cell death pathways. Five pivotal PCD-related genes (IRAK3, S100A9, TXN, NFATC2, and GSTO1) were identified, leading to the construction of a network comprising six transcription factors and 171 microRNAs. Additionally, seven drugs targeting S100A9, TXN, and NFATC2 were identified. MR analysis suggested that a decrease in GSTO1 levels is associated with an increased risk of sepsis, and that sepsis influences the levels of S100A9, TXN, and GSTO1.

Conclusions: Through bioinformatics approaches, this study successfully identified five genes (IRAK3, S100A9, TXN, NFATC2, and GSTO1) associated with programmed cell death in the context of sepsis. This research identified seven candidate drugs for sepsis treatment and established a methodological framework for predicting biomarkers and drug targets that could be applicable to other diseases.

求助全文
约1分钟内获得全文 求助全文
来源期刊
Hereditas
Hereditas Biochemistry, Genetics and Molecular Biology-Genetics
CiteScore
3.80
自引率
3.70%
发文量
0
期刊介绍: For almost a century, Hereditas has published original cutting-edge research and reviews. As the Official journal of the Mendelian Society of Lund, the journal welcomes research from across all areas of genetics and genomics. Topics of interest include human and medical genetics, animal and plant genetics, microbial genetics, agriculture and bioinformatics.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信