Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology

被引:15
|
作者
Yang, Sha [1 ]
Guo, Jing [1 ]
Kong, Zhuo [3 ]
Deng, Mei [3 ]
Da, Jingjing [4 ]
Lin, Xin [3 ]
Peng, Shuo [3 ]
Fu, Junwu [3 ]
Luo, Tao [3 ]
Ma, Jun [3 ]
Yin, Hao [3 ]
Liu, Lin [5 ]
Liu, Jian [1 ,3 ]
Zha, Yan [4 ]
Tan, Ying [5 ]
Zhang, Jiqin [2 ]
机构
[1] Guizhou Univ, Med Coll, Guiyang 550025, Guizhou, Peoples R China
[2] Guizhou Prov Peoples Hosp, Dept Anesthesiol, Guiyang, Peoples R China
[3] Guizhou Prov Peoples Hosp, Dept Neurosurg, Guiyang, Peoples R China
[4] Guizhou Prov Peoples Hosp, Dept Nephrol, Guiyang, Peoples R China
[5] Guizhou Prov Peoples Hosp, Dept Resp & Crit Care Med, Guiyang, Peoples R China
基金
中国国家自然科学基金;
关键词
Mendelian randomization; Sepsis; Gut microbiota; Single-cell RNA-seq; Network pharmacology; Transcriptomics; GENE-EXPRESSION; T-CELLS; ACTIVATION; MIGRATION; REVEALS; PLCG2; SATB1;
D O I
10.1186/s12967-023-04835-8
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
BackgroundGut microbiota alterations have been implicated in sepsis and related infectious diseases, but the causal relationship and underlying mechanisms remain unclear.MethodsWe evaluated the association between gut microbiota composition and sepsis using two-sample Mendelian randomization (MR) analysis based on published genome-wide association study (GWAS) summary statistics. Sensitivity analyses were conducted to validate the robustness of the results. Reverse MR analysis and integration of GWAS and expression quantitative trait loci (eQTL) data were performed to identify potential genes and therapeutic targets.ResultsOur analysis identified 11 causal bacterial taxa associated with sepsis, with increased abundance of six taxa showing positive causal relationships. Ten taxa had causal effects on the 28-day survival outcome of septic patients, with increased abundance of six taxa showing positive associations. Sensitivity analyses confirmed the robustness of these associations. Reverse MR analysis did not provide evidence of reverse causality. Integration of GWAS and eQTL data revealed 76 genes passing the summary data-based Mendelian randomization (SMR) test. Differential expression of these genes was observed between sepsis patients and healthy individuals. These genes represent potential therapeutic targets for sepsis. Molecular docking analysis predicted potential drug-target interactions, further supporting their therapeutic potential.ConclusionOur study provides insights for the development of personalized treatment strategies for sepsis and offers preliminary candidate targets and drugs for future drug development.
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页数:22
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