Akhbari Pouya, Karamchandani Urvi, Jaggard Matthew K J, Graça Goncalo, Bhattacharya Rajarshi, Lindon John C, Williams Horace R T, Gupte Chinmay M
Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, UK.
School of Medicine, Imperial College London, London, UK.
Bone Joint Res. 2020 May 16;9(3):108-119. doi: 10.1302/2046-3758.93.BJR-2019-0167.R1. eCollection 2020 Mar.
Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes.
A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines using the MEDLINE, Embase, PubMed, and Cochrane databases. Studies included were case series, case control series, and cohort studies looking specifically at HSF.
The primary analysis, which pooled the results from 17 published studies and four meeting abstracts, identified over 200 metabolites. Seven of these studies (six published studies, one meeting abstract) had asymptomatic control groups and collectively suggested 26 putative biomarkers in osteoarthritis, inflammatory arthropathies, and trauma. These can broadly be categorized into amino acids plus related metabolites, fatty acids, ketones, and sugars.
The role of metabolic profiling in orthopaedics is fast evolving with many metabolites already identified in a variety of pathologies. However, these results need to be interpreted with caution due to the presence of multiple confounding factors in many of the studies. Future research should include largescale epidemiological metabolic profiling studies incorporating various confounding factors with appropriate statistical analysis to account for multiple testing of the data. 2020;9(3):108-119.
代谢谱分析是一种自上而下的分析方法，着眼于代谢物，代谢物是各种细胞途径的中间产物或终产物。我们的主要目标是对已发表的文献进行系统综述，以识别通过代谢谱分析技术分类的人滑液（HSF）中的代谢物。次要目标是识别可能代表骨科疾病过程潜在生物标志物的任何代谢物。
根据系统评价和Meta分析的首选报告项目（PRISMA）指南，使用MEDLINE、Embase、PubMed和Cochrane数据库进行系统综述。纳入的研究包括病例系列、病例对照系列和专门针对HSF的队列研究。
初步分析汇总了17项已发表研究和4篇会议摘要的结果，识别出200多种代谢物。其中7项研究（6项已发表研究，1篇会议摘要）有无症状对照组，并共同提出了骨关节炎、炎性关节病和创伤中的26种假定生物标志物。这些大致可分为氨基酸及其相关代谢物、脂肪酸、酮和糖。
代谢谱分析在骨科中的作用正在迅速发展，已在多种病理中识别出许多代谢物。然而，由于许多研究中存在多种混杂因素，这些结果需要谨慎解释。未来的研究应包括大规模流行病学代谢谱分析研究，纳入各种混杂因素并进行适当的统计分析，以考虑数据的多重检验。2020年；9（3）：108 - 119。
