孟德尔随机化
全基因组关联研究
败血症
表达数量性状基因座
生物
候选基因
遗传关联
计算生物学
生物信息学
基因
遗传学
单核苷酸多态性
免疫学
基因型
遗传变异
作者
Sha Yang,Guo Liang Jiang,Zhuo Kong,Mingke Deng,Jingjing Da,Xin Lin,Shuo Peng,Jiantao Fu,Tāo Luò,Jie Ma,Huan Yin,Lijin Lin,Jian Liu,Yan Zha,Ying Tan,Jiqin Zhang
标识
DOI:10.1186/s12967-023-04835-8
摘要
Abstract Background Gut microbiota alterations have been implicated in sepsis and related infectious diseases, but the causal relationship and underlying mechanisms remain unclear. Methods We 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. Results Our 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. Conclusion Our 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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