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Dataset for: Metabolite assignment of Ultra-Filtered Synovial Fluid extracted from knee joints of Reactive Arthritis patients using High-Resolution NMR spectroscopy

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posted on 2018-08-07, 06:28 authored by Durgesh Dubey, Smriti Chaurasia, Anupam Guleria, Sandeep Kumar, Dinesh Raj Modi, Ramnath Misra, Dinesh Kumar
Currently, there are no reliable clinical biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Metabolic 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 1H and 13C resonances 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 as well as on ultra-filtered (deproteinized) SF samples of eight ReA patients (n=8) using high resolution (800 MHz) 1H and 1H-13C NMR spectroscopy methods such as one-dimensional (1D) 1H CPMG and two-dimensional (2D) J-resolved1H NMR and homonuclear 1H-1H TOCSY and heteronuclear1H-13C HSQC correlation spectra. Compared to normal SF samples, several distinctive 1H NMR signals were identified and assigned to metabolites in the 1H NMR spectra of ultra-filtered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared to normal (un-filtered) SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metabolites 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.

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