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脓毒症患者28天死亡与血清代谢物相关性的孟德尔随机化研究
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Abstract:
目的：本研究旨在使用孟德尔随机化(Mendelian randomization, MR)的方法探究脓毒症患者28天死亡率与血浆代谢物之间的相关性。方法：脓毒症患者28天死亡相关数据来源于UK Biobank (486,484例)，代谢物数据来自加拿大老龄化纵向研究(CLSA)队列(8091名个体的1091种代谢物和309种代谢物比率)，均可从全基因组关联研究(GWAS)获取。使用R软件，采用逆方差加权法、MR-Egger回归、简单众数法、加权中位数法和加权众数等方法进行MR分析，并对结果进行异质性、多效性、敏感性分析。结果：本研究利用孟德尔随机化方法，对1400种代谢物与脓毒症28天死亡之间的因果关系进行了分析。通过IVW、MR-Egger、加权中位数、简单模式和加权模式五种方法的综合评估，共发现12种与脓毒症28天死亡显著相关的代谢物。其中，2-甲氧基间苯二酚硫酸盐(2-methoxyresorcinol sulfate)、1-(1-烯基棕榈酸酰基)-2-GPC (1-(1-enyl-palmitoyl)-2-oleoyl-gpc (p-16:0/18:1))和1-亚油酸酰基-2-花生四烯酸酰基-GPC (1-linoleoyl-2-arachidonoyl-GPC (18:2/20:4n6))被发现具有保护作用，而棕榈酰基鞘氨醇磷脂(Hydroxypalmitoyl sphingomyelin)则表现为危险因素。结论：研究发现多种代谢物显著关联于脓毒症的死亡风险，为其作为潜在生物标志物和治疗靶点提供了重要参考。这些发现可能为未来脓毒症的诊断与治疗策略优化提供新的研究方向和理论依据。
Aim: The aim of this study was to investigate the correlation between 28-day mortality in sepsis patients and plasma metabolites using the method of Mendelian randomization (MR). Methods: The 28-day mortality data of sepsis patients were obtained from the UK Biobank (486,484 cases), and the metabolite data were from the Canadian Longitudinal Study on Aging (CLSA) cohort (8091 individuals with 1091 metabolites and 309 metabolite ratios), which could be obtained from genome-wide association studies (GWAS). Perform MR analysis using methods such as Inverse Variance Weighted (IVW), MR-Egger regression, Simple Mode, Weighted Median, and Weighted Mode, and conduct heterogeneity, pleiotropy, and sensitivity analyses on the results. Results: Using MR, this study analyzed the causal relationships between 1400 metabolites and 28-day mortality in sepsis. A comprehensive evaluation using five methods—IVW, MR-Egger, Weighted Median, Simple Mode, and Weighted Mode—identified 12 metabolites significantly associated with 28-day mortality in sepsis. Among these, 2-methoxyresorcinol sulfate, 1-(1-enyl-palmitoyl)-2-oleoyl-GPC (p-16:0/18:1), and 1-linoleoyl-2-arachidonoyl-GPC (18:2/20:4n6) were found to have protective effects, while hydroxypalmitoyl sphingomyelin was identified as a risk factor. Conclusions: This study identified several metabolites significantly associated with sepsis-related mortality risk, providing critical insights into their potential as biomarkers and therapeutic targets. These findings may contribute to future research on optimizing diagnostic and therapeutic strategies for sepsis, offering new directions for clinical practice and precision medicine.
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