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使用孟德尔随机化分析鉴定与慢性鼻-鼻窦炎相关的循环代谢物。

Identification of circulating metabolites associated with chronic rhinosinusitis using Mendelian randomization analysis.

作者信息

Jiang Fan, Tu Junhao, Luo Wenqi, Jia Yizhen, Luo Qing, Ye Jing

机构信息

Nanchang University, Jiangxi Medical College, The First Affiliated Hospital, Department of Otorhinolaryngology, Head and Neck Surgery, Nanchang, Jiangxi Province, China.

Nanchang University, Jiangxi Medical College, The First Affiliated Hospital, Department of Otorhinolaryngology, Head and Neck Surgery, Nanchang, Jiangxi Province, China; Nanchang University, Jiangxi Medical College, The First Affiliated Hospital, Department of Allergy, Nanchang, Jiangxi Province, China.

出版信息

Braz J Otorhinolaryngol. 2025 Apr 25;91(4):101626. doi: 10.1016/j.bjorl.2025.101626.

DOI:10.1016/j.bjorl.2025.101626
PMID:40286593
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12056403/
Abstract

OBJECTIVE

This study aims to employ Mendelian Randomization (MR) analysis to investigate causal relationships between serum metabolites and CRS, identifying key pathogenic and protective factors and analyzing their mechanisms of action.

METHODS

Utilizing data from the Genome-Wide Association Studies (GWAS) database, employing two-sample MR analysis to investigate the potential causal relationship between 233 circulating metabolites with the occurrence of CRS. Inverse Variance Weighted (IVW) model, MR-Egger method, Weighted Median, and Weighted model were employed. Sensitivity analyses were conducted with Bonferroni correction. This research aims to elucidate the impact of metabolites on the development and progression of CRS, providing valuable insights into the underlying mechanisms.

RESULTS

Following MR analysis, two metabolites were significantly associated with CRS: Tyrosine (OR = 1.223; 95% CI 1.115-1.341; p = 1.96E-05) and Creatinine (OR = 1.208; 95% CI 1.103-1.322; p = 4.11E-05). These two key risk factors may be further studied for their pathogenesis and could be targeted for modulation in the treatment of CRS. However, there are several protective factors also worth exploring, among which the correlation is more significant: Ratio of conjugated linoleic acid to total fatty acids (OR = 0.809; 95% CI 0.708‒0.923; p = 1.73E-03), Albumin (OR = 0.787; 95% CI 0.670‒0.926; p = 3.76E-03),Conjugated linoleic acid (OR = 0.664; 95% CI 0.491‒0.898; p = 7.85E-03), Diacylglycerol (OR = 0.804; 95% CI 0.654‒0.989; p = 3.87E-02), Apolipoprotein A-I (OR = 0.915; 95% CI 0.845‒0.991; p = 2.89E-02).

CONCLUSION

In our MR study, we discovered 28 circulating metabolites linked to CRS. Importantly, tyrosine and creatinine were identified as the most significant contributors to the pathogenesis of CRS, highlighting their potential as therapeutic targets. Additionally, several protective factors may offer new avenues for preventive strategies and therapeutic interventions. These findings underscore the clinical relevance of targeting these metabolites to modulate CRS progression and improve patient outcomes.

LEVEL OF EVIDENCE

Level 2*..

摘要

目的

本研究旨在采用孟德尔随机化(MR)分析来研究血清代谢物与慢性鼻窦炎(CRS)之间的因果关系,确定关键的致病和保护因素,并分析其作用机制。

方法

利用全基因组关联研究(GWAS)数据库的数据,采用两样本MR分析来研究233种循环代谢物与CRS发生之间的潜在因果关系。采用逆方差加权(IVW)模型、MR-Egger方法、加权中位数和加权模型。进行了Bonferroni校正的敏感性分析。本研究旨在阐明代谢物对CRS发生和发展的影响,为潜在机制提供有价值的见解。

结果

经过MR分析,两种代谢物与CRS显著相关:酪氨酸(OR = 1.223;95%CI 1.115 - 1.341;p = 1.96E - 05)和肌酐(OR = 1.208;95%CI 1.103 - 1.322;p = 4.11E - 05)。这两个关键风险因素的发病机制可能需要进一步研究,并且在CRS治疗中可能成为调节靶点。然而,也有几个保护因素值得探索,其中相关性更显著的有:共轭亚油酸与总脂肪酸的比值(OR = 0.809;95%CI 0.708 - 0.923;p = 1.73E - 03)、白蛋白(OR = 0.787;95%CI 0.670 - 0.926;p = 3.76E - 03)、共轭亚油酸(OR = 0.664;95%CI 0.491 - 0.898;p = 7.85E - 03)、二酰甘油(OR = 0.804;95%CI 0.654 - 0.989;p = 3.87E - 02)、载脂蛋白A-I(OR = 0.915;95%CI 0.845 - 0.991;p = 2.89E - 02)。

结论

在我们的MR研究中,我们发现了28种与CRS相关的循环代谢物。重要的是,酪氨酸和肌酐被确定为CRS发病机制中最显著的因素,突出了它们作为治疗靶点的潜力。此外,几个保护因素可能为预防策略和治疗干预提供新途径。这些发现强调了针对这些代谢物来调节CRS进展和改善患者预后的临床相关性。

证据水平

2*级。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/6f053b1f4c23/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/409a6f578509/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/ad38fc6fcda9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/d3fda5eb9bb2/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/d91b4ae62ec1/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/6f053b1f4c23/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/409a6f578509/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/ad38fc6fcda9/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/d3fda5eb9bb2/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/d91b4ae62ec1/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/adbb/12056403/6f053b1f4c23/gr5.jpg

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S100a9 might act as a modulator of the Toll-like receptor 4 transduction pathway in chronic rhinosinusitis with nasal polyps.
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