Diagnostic biomarker panels of osteoarthritis: UPLC-QToF/MS-based serum metabolic profiling

PeerJ

article

Xinxin Lin¹  Shiqi He¹  Suyu Wu¹  Tianwen Zhang²  Sisi Gong³  Tang Minjie⁴  Yao Gao¹ 

[1]The School of Medical Technology and Engineering, Fujian Medical University

[2]Fujian Fishery Resources Monitoring Center

[3]Department of Laboratory Medicine, the Second Affiliated Hospital of Fujian Medical University

[4]Department of Laboratory Medicine, the First Affiliated Hospital of Fujian Medical University

关键词: Osteoarthritis;    Biomarker;    UPLC-QToF/MS;    Early diagnosis;    Metabolic pathway analysis;   

DOI  :  10.7717/peerj.14563

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Osteoarthritis (OA) is the most common joint disease in the world, characterized by pain and loss of joint function, which has led to a serious reduction in the quality of patients’ lives. In this work, ultrahigh performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC-QToF/MS) in conjunction with multivariate pattern recognition methods and an univariate statistical analysis scheme were applied to explore the serum metabolic signatures within OA group (n = 31), HC (healthy controls) group (n = 57) and non-OA group (n = 19) for early diagnosis and differential diagnosis of OA. Based on logistic regression analysis and receiver operating characteristic (ROC) curve analysis, seven metabolites, including phosphatidylcholine (18:0/22:6), p-cresol sulfate and so on, were identified as critical metabolites for the diagnosis of OA and HC and yielded an area under the curve (AUC) of 0.978. The other panel of unknown m/z 239.091, phosphatidylcholine (18:0/18:0) and phenylalanine were found to distinguish OA from non-OA and achieved an AUC of 0.888. These potential biomarkers are mainly involved in lipid metabolism, glucose metabolism and amino acid metabolism. It is expected to reveal new insight into OA pathogenesis from changed metabolic pathways.

【 授权许可】

CC BY