孟德尔随机化
多效性
表达数量性状基因座
计算生物学
生物
基因组学
败血症
遗传学
精密医学
生物信息学
表型
遗传变异
基因
单核苷酸多态性
基因组
免疫学
基因型
作者
Yuanqi Zhao,Zijian Zhou,Xiuyu Cui,Yiwei Yu,Ping Yan,Weidong Zhao
标识
DOI:10.1016/j.intimp.2024.112910
摘要
This research investigated the intricate relationship between ferroptosis and sepsis by utilizing advanced genomic and pharmacological methodologies. Specifically, we obtained expression quantitative trait loci (eQTLs) for 435 genes associated with ferroptosis from the eQTLGen Consortium and detected notable cis-eQTLs for 281 of these genes. Next, we conducted a detailed analysis to assess the impact of these eQTLs on susceptibility to sepsis using Mendelian randomization (MR) with data from a cohort of 10,154 sepsis patients and 452,764 controls sourced from the UK Biobank. MR analysis revealed 16 ferroptosis-related genes that exhibited significant associations with sepsis outcomes. To bolster the robustness of these findings, sensitivity analyses were performed to assess pleiotropy and heterogeneity, thus confirming the reliability of the causal inferences. Furthermore, single-cell RNA sequencing data from sepsis patients offered a detailed examination of gene expression profiles, demonstrating varying levels of ferroptosis marker expression across different cell types. Pathway enrichment analysis utilizing gene set enrichment analysis (GSEA) further revealed the key biological pathways involved in the progression of sepsis. Additionally, the use of computational molecular docking facilitated the prediction of interactions between identified genes and potential therapeutic compounds, highlighting novel drug targets. In conclusion, our integrated approach combining genomics and pharmacology offers valuable insights into the involvement of ferroptosis in sepsis, laying the groundwork for potential therapeutic strategies targeting this cell death pathway to enhance sepsis management.
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