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本文引用的文献

1
Metabolomics and Machine Learning Identify Metabolic Differences and Potential Biomarkers for Frequent Versus Infrequent Gout Flares.代谢组学和机器学习鉴定频繁与非频繁痛风发作的代谢差异和潜在生物标志物。
Arthritis Rheumatol. 2023 Dec;75(12):2252-2264. doi: 10.1002/art.42635. Epub 2023 Nov 9.
2
Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases.血浆代谢组学基因组图谱优先考虑与人类疾病相关的代谢物。
Nat Genet. 2023 Jan;55(1):44-53. doi: 10.1038/s41588-022-01270-1. Epub 2023 Jan 12.
3
Mannose ameliorates experimental colitis by protecting intestinal barrier integrity.甘露糖通过保护肠道屏障完整性来改善实验性结肠炎。
Nat Commun. 2022 Aug 16;13(1):4804. doi: 10.1038/s41467-022-32505-8.
4
Immunosuppression by piperine as a regulator of the NLRP3 inflammasome through MAPK/NF-κB in monosodium urate-induced rat gouty arthritis.胡椒碱通过丝裂原活化蛋白激酶/核因子κB对尿酸钠诱导的大鼠痛风性关节炎中NLRP3炎性小体的调节作用实现免疫抑制。
Vet World. 2022 Feb;15(2):288-298. doi: 10.14202/vetworld.2022.288-298. Epub 2022 Feb 11.
5
Extracellular Phosphate, Inflammation and Cytotoxicity.细胞外磷酸盐、炎症和细胞毒性。
Adv Exp Med Biol. 2022;1362:15-25. doi: 10.1007/978-3-030-91623-7_3.
6
Gut Microbiota and Psychiatric Disorders: A Two-Sample Mendelian Randomization Study.肠道微生物群与精神疾病:一项两样本孟德尔随机化研究。
Front Microbiol. 2022 Feb 4;12:737197. doi: 10.3389/fmicb.2021.737197. eCollection 2021.
7
Standardization and validation of phytometabolites by UHPLC and high-performance thin layer chromatography for rapid quality assessment of ancient ayurvedic medicine, Mahayograj Guggul.采用 UHPLC 和高效薄层色谱法对植物代谢产物进行标准化和验证,快速评估古老的阿育吠陀药物 Mahayograj Guggul 的质量。
J Sep Sci. 2022 May;45(10):1616-1635. doi: 10.1002/jssc.202100935. Epub 2022 Feb 25.
8
Mendelian Randomization.孟德尔随机化
Cold Spring Harb Perspect Med. 2022 May 17;12(4):a041302. doi: 10.1101/cshperspect.a041302.
9
Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model.混合回归模型联合逆方差加权法和 Egger 回归在孟德尔随机化中的应用。
PLoS Genet. 2021 Nov 18;17(11):e1009922. doi: 10.1371/journal.pgen.1009922. eCollection 2021 Nov.
10
Serum lipidomics reveals distinct metabolic profiles for asymptomatic hyperuricemic and gout patients.血清脂质组学揭示无症状高尿酸血症和痛风患者的不同代谢特征。
Rheumatology (Oxford). 2022 May 30;61(6):2644-2651. doi: 10.1093/rheumatology/keab743.

代谢物与痛风之间的关系:一项孟德尔随机化研究。

The relationship between metabolites and gout: a Mendelian randomization study.

作者信息

Ding Zhixiang, Wu Liting, Xu Ting, Zhang Cui, Liang Yi, Li Jia, Zhuang Wenfang

机构信息

Medical Laboratory, Shidong Hospital Affiliated to University of Shanghai for Science and Technology Shanghai 200438, China.

出版信息

Am J Clin Exp Immunol. 2024 Aug 25;13(4):177-186. doi: 10.62347/UTEW4812. eCollection 2024.

DOI:10.62347/UTEW4812
PMID:39310120
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11411155/
Abstract

BACKGROUND

Gout is closely tied to metabolism, yet there is limited evidence on how metabolites may cause or prevent the condition.

METHODS

This study utilized a two-sample Mendelian randomization (MR) analysis to evaluate the causal relationship between 1,400 serum metabolites and gout. We primarily employed the inverse variance-weighted (IVW) method to estimate causal effects, supplemented by MR-Egger regression, weighted median, simple mode, and weighted mode for comprehensive evaluations. Additionally, we conducted tests for pleiotropy and heterogeneity.

RESULTS

After a rigorous selection process, we identified eight known metabolites and four unknown metabolites associated with gout. Among the eight known metabolites, Glucuronide of piperine metabolite C17H21NO3 and the Phosphate to mannose ratio were positively associated with an increased risk of gout. Conversely, levels of 5 alpha-androstan-3 beta, 17 alpha-diol disulfate, Pantoate, N-carbamoylalanine, Sphingomyelin (d18:0/20:0, d16:0/22:0), Hydroxypalmitoyl sphingomyelin (d18:1/16:0(OH)), and Mannose were linked to a decreased risk of gout.

CONCLUSION

This study identified eight metabolites from 1,400 blood samples significantly linked to gout risk. Integrating genomics and metabolomics offers valuable insights for gout screening and prevention, indicating that specific blood metabolites can help identify individuals at higher risk.

摘要

背景

痛风与新陈代谢密切相关,但关于代谢物如何导致或预防该病症的证据有限。

方法

本研究采用两样本孟德尔随机化(MR)分析来评估1400种血清代谢物与痛风之间的因果关系。我们主要采用逆方差加权(IVW)方法来估计因果效应,并辅以MR-Egger回归、加权中位数、简单模式和加权模式进行综合评估。此外,我们还进行了多效性和异质性检验。

结果

经过严格筛选,我们确定了8种已知代谢物和4种与痛风相关的未知代谢物。在这8种已知代谢物中,胡椒碱代谢物C17H21NO3的葡糖醛酸苷和磷酸与甘露糖的比率与痛风风险增加呈正相关。相反,5α-雄甾烷-3β,17α-二醇二硫酸盐、泛酸盐、N-氨甲酰丙氨酸、鞘磷脂(d18:0/20:0,d16:0/22:0)、羟基棕榈酰鞘磷脂(d18:1/16:0(OH))和甘露糖的水平与痛风风险降低有关。

结论

本研究从1400份血样中鉴定出8种与痛风风险显著相关的代谢物。整合基因组学和代谢组学为痛风筛查和预防提供了有价值的见解,表明特定的血液代谢物有助于识别高风险个体。