RESEARCH ARTICLE Metabolite assignment of ultrafiltered synovial fluid extracted from knee joints of reactive arthritis patients using high resolution NMR spectroscopy Durgesh Dubey 1,2 | Smriti Chaurasia 3 | Anupam Guleria 1 | Sandeep Kumar 3 | Dinesh Raj Modi 2 | Ramnath Misra 3 | Dinesh Kumar 1 1 Centre of Biomedical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India 2 Babasaheb Bhimrao Ambedkar University, Lucknow, India 3 Department of Clinical Immunology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India Correspondence Ramnath Misra, Department of Clinical Immunology, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Raibareli Road, Lucknow 226014, India. Email: rnmisra2000@gmail.com Dinesh Kumar, Centre of Biomedical Research (CBMR), Sanjay Gandhi Postgraduate Institute of Medical Sciences, Raibareli Road, Lucknow 226014, India. Email: dineshcbmr@gmail.com Funding information Science and Engineering Research Board, Grant/Award Number: EMR/2016/001756 Abstract Currently, there are no reliable biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Met- abolic profiling of synovial fluid (SF)—obtained from joints affected in ReA— holds great promise in this regard and will further aid monitoring treatment and improving our understanding about disease mechanism. As a first step in this direction, we report here the metabolite specific assignment of 1 H and 13 C reso- nances detected in the NMR spectra of SF samples extracted from human patients with established ReA. The metabolite characterization has been carried out on both normal and ultrafiltered (deproteinized) SF samples of eight ReA patients (n = 8) using high‐resolution (800 MHz) 1 H and 1 H─ 13 C NMR spectroscopy methods such as one‐dimensional 1 H CPMG and two‐dimensional J‐resolved 1 H NMR and homonuclear 1 H─ 1 H TOCSY and heteronuclear 1 H─ 13 C HSQC correla- tion spectra. Compared with normal SF samples, several distinctive 1 H NMR sig- nals were identified and assigned to metabolites in the 1 H NMR spectra of ultrafiltered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared with nonfiltered SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metab- olites will serve to guide future metabolomics studies aiming to identify/evaluate the SF‐based metabolic biomarkers of diagnostic/prognostic potential or seeking biochemical insights into disease mechanisms in a clinical perspective. KEYWORDS biomarkers, metabolomics, NMR, reactive arthritis, rheumatic diseases (RD), rheumatoid arthritis, synovial fluid 1 | INTRODUCTION Differential biomarkers are becoming clinically essential for timely diagnosis and predicting prognosis of rheumatic diseases (RDs) and subsequent treatment Abbreviations: CPMG, Car–Purcell–Meiboom–Gill sequence; DSS, 2, 2‐Dimethyl‐2‐silapentane‐5‐sulfonate; HSQC, heteronuclear single quantum correlation; JRES, J‐resolved; NMR, nuclear magnetic resonance; RA, rheumatoid arthritis; RD, rheumatic disease; ReA, reactive arthritis; TOCSY, total correlation spectroscopy Received: 18 January 2018 Revised: 27 May 2018 Accepted: 6 June 2018 DOI: 10.1002/mrc.4763 30 © 2018 John Wiley & Sons, Ltd. Magn Reson Chem. 2019;57:30–43. wileyonlinelibrary.com/journal/mrc