背景:青少年特发性关节炎(JIA)是一种当16岁以下的个体发展为持续六周以上的关节炎时发生的疾病,原因不明。JIA的发展可能与血清代谢物有关。然而,JIA发病机制与血清代谢物之间的关联尚不清楚,研究结果存在差异。
方法:在这项研究中,使用遗传变异数据和全基因组关联研究评估了人类JIA与486种血清代谢物之间的关联.因果关系的识别是通过应用单变量孟德尔随机化(MR)分析来完成的。各种统计方法,包括逆方差加权和MR-Egger,用于实现这一目标。为了确保MR分析的结果是可信的,进行了一些评估。为保证所得结果的准确性,使用了一系列技术,包括CochranQ测试,检查MR-Egger截距,实施留一审战略,和连锁不平衡分数的回归分析。为了确定与JIA相关的特定代谢途径,我们的主要目标是使用京都基因和基因组百科全书进行途径富集分析.
结果:两个样本汇总数据MR分析和敏感性分析显示,五种代谢物与JIA有显著的因果关系。包括两个危险因素-犬尿氨酸(比值比[OR]:16.39,95%置信区间[CI]:2.07-129.63,p=5.11×10-6)和亚油酸酯(OR:16.48,95%CI:1.32-206.22,p=0.030)-和三个保护因素-3-脱氢肉碱(OR:0.32,95%CI:0.14-0.72,p=0.0072,乙酰丙酸酯(4-氧代戊酸酯)(OR:0.40,95%CI:0.20-0.80,p=0.010),和X-14,208(苯丙氨酰基丝氨酸)(OR:0.68,95%CI:0.51-0.92,p=0.010)。此外,七种代谢途径,包括α-亚麻酸代谢和泛酸和CoA生物合成,可能与JIA的发病和进展有关。
结论:五种血清代谢物,包括犬尿氨酸和3-脱氢肉碱,可能与JIA有因果关系。这些结果为制定有效的JIA预防和筛查策略提供了理论框架。
BACKGROUND: Juvenile Idiopathic Arthritis (JIA) is a condition that occurs when individuals under the age of 16 develop arthritis that lasts for more than six weeks, and the cause is unknown. The development of JIA may be linked to serum metabolites. Nevertheless, the association between JIA pathogenesis and serum metabolites is unclear, and there are discrepancies in the findings across studies.
METHODS: In this research, the association between JIA in humans and 486 serum metabolites was assessed using genetic variation data and genome-wide association
study. The identification of causal relationships was accomplished through the application of univariate Mendelian randomization (MR) analysis. Various statistical methods, including inverse variance weighted and MR-Egger, were applied to achieve this objective. To ensure that the findings from the MR analysis were trustworthy, a number of assessments were carried out. To ensure the accuracy of the obtained results, a range of techniques were utilised including the Cochran Q test, examination of the MR-Egger intercept, implementation of the leave-one-out strategy, and regression analysis of linkage disequilibrium scores. In order to identify the specific metabolic pathways associated with JIA, our primary objective was to perform pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes.
RESULTS: Two-sample summary data MR analyses and sensitivity analyses showed that five metabolites were significantly causally associated with JIA, including two risk factors-kynurenine (odds ratio [OR]: 16.39, 95% confidence interval [CI]: 2.07-129.63, p = 5.11 × 10- 6) and linolenate (OR: 16.48, 95% CI: 1.32-206.22, p = 0.030)-and three protective factors-3-dehydrocarnitine (OR: 0.32, 95% CI: 0.14-0.72, p = 0.007), levulinate (4-oxovalerate) (OR: 0.40, 95% CI: 0.20-0.80, p = 0.010), and X-14,208 (phenylalanylserine) (OR: 0.68, 95% CI: 0.51-0.92, p = 0.010). Furthermore, seven metabolic pathways, including α-linolenic acid metabolism and pantothenate and CoA biosynthesis, are potentially associated with the onset and progression of JIA.
CONCLUSIONS: Five serum metabolites, including kynurenine and 3-dehydrocarnitine, may be causally associated with JIA. These results provide a theoretical framework for developing effective JIA prevention and screening strategies.