Serum branched-chain amino acid to histidine ratio: a novel metabolomic biomarker of knee osteoarthritis

骨关节炎 医学 代谢组学 生物标志物 内科学 代谢物 混淆 临床意义 体质指数 胃肠病学 生物信息学 病理 生物化学 生物 替代医学
作者
Guangju Zhai,Rui Wang‐Sattler,Deborah Hart,Nigel Arden,Alan J. Hakim,Thomas Illig,Tim D. Spector
出处
期刊:Annals of the Rheumatic Diseases [BMJ]
卷期号:69 (6): 1227-1231 被引量:179
标识
DOI:10.1136/ard.2009.120857
摘要

Objective There is a pressing need to develop reliable molecular biomarkers in osteoarthritis. The aim of the study was to identify novel serum biomarkers for osteoarthritis using a metabolomics approach. Methods A two-stage study design was utilised. 123 knee osteoarthritis cases and 299 controls were selected from the TwinsUK cohort as a discovery sample. 76 knee osteoarthritis cases and 100 controls from the Chingford Study were used as replication. Knee osteoarthritis was defined as either radiographic, medically diagnosed or total knee joint replacement due to primary osteoarthritis. All the subjects were unrelated white women. Their serum samples were assessed for targeted metabolite profiling by electrospray ionisation tandem mass spectrometry using the AbsoluteIDQ kit. 163 serum metabolites were assessed and their concentrations obtained. The ratios of metabolite concentrations as proxies for enzymatic reaction rates were calculated and tested for the association with knee osteoarthritis. Significance was assessed after adjustment for multiple testing (Bonferroni method) and potential confounders. Results In the discovery stage, the authors identified 14 ratios significantly associated with knee osteoarthritis with p≤1.9×10 −6 . Two of these 14 ratios were successfully confirmed in the replication stage—the ratios of valine to histidine and xleucine to histidine, with p=0.002. The significance remained after adjustment for age and body mass index. Conclusion This is the first serum-based metabolomic study of osteoarthritis in humans. The branched-chain amino acids to histidine ratio has potential clinical use as an osteoarthritis biomarker and shows the clinical potential of metabolomics.
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