Causal relationship between serum metabolites and juvenile idiopathic arthritis: a mendelian randomization study

• DOI: 10.1186/s12969-024-00986-0
• Publication Date: 2024-05-09T11:02:09Z
• Authors: Han Zhang; Xiao Ma; Wanlu Liu; Ze Wang; Zian Zhang; GuanHong Chen; Yingze Zhang; Tianrui Wang; Tengbo Yu; Yongtao Zhang
• Keywords: Serum; 0303 health sciences; Diseases of the musculoskeletal system; Juvenile idiopathic arthritis; Mendelian Randomization Analysis; Pediatrics; Polymorphism, Single Nucleotide; RJ1-570; Arthritis, Juvenile; Causality; 03 medical and health sciences; RC925-935; Metabolites; Mendelian randomization; Humans; Child; Kynurenine; Research Article; Genome-Wide Association Study

Abstract 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.

Conclusion 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.