A review of applications of metabolomics in osteoarthritis
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REVIEW ARTICLE
A review of applications of metabolomics in osteoarthritis Jie-Ting Li 1 & Ni Zeng 1 & Zhi-Peng Yan 1 & Tao Liao 1 & Guo-Xin Ni 2 Received: 23 October 2020 / Revised: 10 November 2020 / Accepted: 15 November 2020 # International League of Associations for Rheumatology (ILAR) 2020
Abstract Osteoarthritis (OA) represents the most prevalent and disabling arthritis worldwide due to its heterogeneous and progressive articular degradation. However, effective and timely diagnosis and fundamental treatment for this disorder are lacking. Metabolomics, a growing field in life science research in recent years, has the potential to detect many metabolites and thus explains the underlying pathophysiological processes. Hence, new specific metabolic markers and related metabolic pathways can be identified for OA. In this review, we aimed to provide an overview of studies related to the metabolomics of OA in animal models and humans to describe the metabolic changes and related pathways for OA. The present metabolomics studies reveal that the pathogenesis of OA may be significantly related to perturbations of amino acid metabolism. These altered amino acids (e.g., branched-chain amino acids, arginine, and alanine), as well as phospholipids, were identified as potential biomarkers to distinguish patients with OA from healthy individuals. Keywords Biomarkers . Metabolic pathways . Metabolomics . Osteoarthritis
Introduction Osteoarthritis (OA) represents the most prevalent and disabling arthritis worldwide, affecting several diarthrodial joints, but primarily the knees and hips. Its worldwide incidence rate is approximately 1/10 in male and 1/5 in female over 60 years of age [1]. Our understanding concerning the etiology of OA continues to grow. Many factors, including age, obesity, gender, genetics, and joint injury, have shown to contribute to the development of OA, among which increasing age and obesity are the principal factors [2]. OA is now considered a heterogeneous chronic disease involving multiple joint tissues. It is mainly characterized by the degradation of articular cartilage, subchondral bone sclerosis, osteophyte formation, variable degrees of synovitis, and ligament degeneration, eventually leading to disability in the end state of the disease [3]. The high rates of morbidity and disability associated with OA have led to a reduced quality of life and a great economic burden on society. The economic burden of OA has been estimated to be between
1.0 and 2.5% of the gross domestic product for Western countries [4]. Despite this challenge, there are no effective early diagnostics or main therapeutics for this disease [5]. These statistics could be improved if the understanding of the diagnostic biomarkers and metabolic alterations in OA were clearer [6]. As an emerging field in life science research and a member of the “-omics” family of sciences, metabolomics provides a powerful approach to identify small molecules for several disorders [7]. By measuring and mathematically modeling changes in the leve
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