Guangzhou University of Chinese Medicine, Guangzhou, China.
Zhongshan Hospital of Traditional Chinese Medicine Affiliated to Guangzhou University of Traditional Chinese Medicine, Zhongshan, China.
Clin Rheumatol. 2024 Dec;43(12):3901-3912. doi: 10.1007/s10067-024-07215-9. Epub 2024 Oct 29.
Gout, a prevalent form of inflammatory arthritis, has a complex etiology where the causal relationship between metabolites and the disease remains underexplored. This study aims to elucidate the impact of genetically determined blood metabolites on gout.
Employing a two-sample bidirectional Mendelian randomization analysis, we examined the association between 1400 blood metabolites and gout. Causal associations were determined using the inverse variance weighted (IVW) method with false discovery rate (FDR) correction. Sensitivity analyses encompassed weighted models, MR-Egger, weighted median, and MR-PRESSO approaches. MR-pleiotropy and Cochran's Q statistic were utilized to evaluate potential heterogeneity and pleiotropy. Additionally, metabolic pathway analyses were conducted to pinpoint relevant pathways.
Of the initial 4 serum metabolites identified, 3 known metabolites-hexanoylglutamine levels, mannose content, and the phosphate to mannose ratio-were found to be causally associated with gout, along with 55 serum metabolites identified as potential predictors of gout (PIVW < 0.05). Furthermore, we discovered 3 metabolic pathways implicated in gouty attacks.
Our findings, derived from Mendelian randomization, indicate that the identified metabolites and pathways may serve as biomarkers for clinical screening and prevention of gout. Additionally, they offer novel insights into the mechanisms of the disease and potential drug targets. Key points • Conducted a comprehensive Mendelian randomization study involving 1400 blood metabolites to explore their genetic impact on gout development and progression • Identified three key metabolites-hexanoylglutamine, mannose, and the phosphate-to-mannose ratio-with causal associations to gout, highlighting their potential use as biomarkers for early detection and risk stratification • Discovered 55 additional serum metabolites as potential predictors of gout, offering new insights into the pathophysiology of the disease and identifying high-risk individuals • Revealed three novel metabolic pathways involved in gout attacks, providing new therapeutic targets for precision medicine in gout treatment.
痛风是一种常见的炎症性关节炎，其病因复杂，代谢物与疾病之间的因果关系仍未得到充分探索。本研究旨在阐明遗传决定的血液代谢物对痛风的影响。
采用两样本双向孟德尔随机化分析，我们研究了 1400 种血液代谢物与痛风之间的关联。使用逆方差加权（IVW）方法并进行错误发现率（FDR）校正来确定因果关系。敏感性分析包括加权模型、MR-Egger、加权中位数和 MR-PRESSO 方法。MR 多效性和 Cochrane's Q 统计量用于评估潜在的异质性和多效性。此外，还进行了代谢途径分析以确定相关途径。
在最初确定的 4 种血清代谢物中，有 3 种已知代谢物——己酰谷氨酰胺水平、甘露糖含量和磷酸与甘露糖的比值——被发现与痛风有因果关系，此外还发现了 55 种可能预测痛风的血清代谢物（PIVW<0.05）。此外，我们发现了 3 个与痛风发作相关的代谢途径。
本研究基于孟德尔随机化，表明所确定的代谢物和途径可能成为痛风临床筛查和预防的生物标志物。此外，这些发现为该疾病的发病机制和潜在药物靶点提供了新的见解。
