Suppr超能文献

炎症细胞因子与脓毒症之间的因果关系:一项孟德尔随机化研究

Causal Relationships Between Inflammatory Cytokines and Sepsis: A Mendelian Randomization Study.

作者信息

Lu Feng, Chen Cuilan, Feng Dongshan, Zhou Zheyi, Qin Jin, Qin Jiang, Yan Yizhen, Zhong Ying, Tang Xuan, Wei Tingqiu

机构信息

Department of Intensive Care Unit (ICU), Liuzhou Hospital of Traditional Chinese Medicine, Liuzhou, China.

Department of Emergency Medicine, Liuzhou Hospital of Traditional Chinese Medicine, Liuzhou, China.

出版信息

Ann Clin Lab Sci. 2025 Jan;55(1):64-71.

Abstract

OBJECTIVE

The complex interplay between inflammatory cytokines and sepsis is not well understood. This study employs Mendelian Randomization (MR) to investigate the causal relationships between various inflammatory cytokines and sepsis, aiming to elucidate the underlying mechanisms and potential therapeutic targets.

METHODS

This study employed a bidirectional MR approach to investigate the causal effects of inflammatory cytokines on sepsis and vice versa. Genetic variants from genome-wide association studies (GWAS) were used as instrumental variables (IVs). Key MR methods included Inverse Variance Weighted (IVW), MR-Egger, and Weighted Median. SNPs were filtered using a p-value threshold of <5e-08, with linkage disequilibrium exclusions (r²<0.001). We analyzed 41 inflammatory cytokines, utilizing leave-one-out analysis and MR-PRESSO to address pleiotropy.

RESULTS

The MR analysis revealed significant causal relationships between specific cytokines and sepsis. CTACK (OR=1.102, =0.031), MIF (OR=1.071, =0.036), and TRAIL (OR=1.053, =0.036) were identified as risk factors, while MIP1-β (OR=0.933, =0.039) and TGF- (OR=0.957, =0.029) emerged as protective factors. Additionally, sepsis increased the risk for IL-2 (OR=1.455, <0.01), IL-6 (OR=1.151, = 0.012), and MCSF (OR=1.272, =0.028), while showing a protective effect on NGF-β (OR=0.78, =0.012) and SCF (OR=0.86, =0.02).

CONCLUSION

This study reveals novel causal relationships between specific inflammatory cytokines and sepsis, suggesting that CTACK, MIF, and TRAIL are risk factors, while MIP1-β and TGF- are protective. Additionally, sepsis influences various cytokines, indicating complex bi-directional interactions. These findings provide valuable insights for developing targeted therapeutic strategies to manage sepsis and inflammatory responses.

摘要

目的

炎症细胞因子与脓毒症之间复杂的相互作用尚未得到充分理解。本研究采用孟德尔随机化(MR)方法来探究各种炎症细胞因子与脓毒症之间的因果关系,旨在阐明潜在机制和潜在治疗靶点。

方法

本研究采用双向MR方法来研究炎症细胞因子对脓毒症的因果效应,反之亦然。来自全基因组关联研究(GWAS)的基因变异被用作工具变量(IVs)。关键的MR方法包括逆方差加权(IVW)、MR-Egger和加权中位数。使用p值阈值<5e-08对单核苷酸多态性(SNPs)进行过滤,并排除连锁不平衡(r²<0.001)。我们分析了41种炎症细胞因子,采用留一法分析和MR-PRESSO来处理多效性。

结果

MR分析揭示了特定细胞因子与脓毒症之间的显著因果关系。黏膜相关上皮趋化因子(CTACK,比值比[OR]=1.102,P=0.031)、巨噬细胞移动抑制因子(MIF,OR=1.071,P=0.036)和肿瘤坏死因子相关凋亡诱导配体(TRAIL,OR=1.053,P=0.036)被确定为危险因素,而巨噬细胞炎性蛋白1-β(MIP1-β,OR=0.933,P=0.039)和转化生长因子-β(TGF-β,OR=0.957,P=0.029)则为保护因素。此外,脓毒症增加了白细胞介素-2(IL-2,OR=1.455,P<0.01)、白细胞介素-6(IL-6,OR=1.151,P=0.012)和巨噬细胞集落刺激因子(MCSF,OR=1.272,P=0.028)的风险,而对神经生长因子-β(NGF-β,OR=0.78,P=0.012)和干细胞因子(SCF,OR=0.86,P=0.02)具有保护作用。

结论

本研究揭示了特定炎症细胞因子与脓毒症之间新的因果关系,表明CTACK、MIF和TRAIL是危险因素,而MIP1-β和TGF-β是保护因素。此外,脓毒症会影响多种细胞因子,表明存在复杂的双向相互作用。这些发现为制定针对性治疗策略以管理脓毒症和炎症反应提供了有价值的见解。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验