TY - JOUR
T1 - Variation in the synovial fluid metabolome according to disease activity of rheumatoid arthritis
AU - Ahn, Joong Kyong
AU - Kim, Jungyeon
AU - Cheong, Yu Eun
AU - Kim, Kyoung Heon
AU - Cha, Hoon Suk
N1 - Funding Information:
this work was supported by the Advanced Biomass R&D Center of Korea (2011-0031353), the National Research Foundation of Korea funded by the Ministry of Education (NRF-2013-R1A1A2059103), and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare (HI14C2285), which are funded by the Korean government. Experiments were performed using the facilities of the Institute of Biomedical Science and Food Safety at the Korea University Food Safety Hall.
PY - 2020/5/1
Y1 - 2020/5/1
N2 - Objective Because genetic and environmental factors both contribute to rheumatoid arthritis (RA), metabolomics could be a very useful tool to elucidate the pathophysiology of RA, and to predict response to treatment. This study was carried out to investigate synovial fluid (SF) metabolic perturbation in RA patients according to the degree of disease activity using gas chromatography/time-of-flight mass spectrometry (GC/TOF MS). Methods SF samples were obtained from 48 RA patients. Disease activity was assessed using DAS28-ESR(3). SF metabolomic profiling was performed using GC/TOF-MS, in conjunction with multivariate statistical analyses and pathway analyses. Results Significant discrimination of metabolite profiles between moderate and high disease activity groups was shown by PLS-DA, which provided evidence that SF metabolic profiles predicted disease activity. We found the significant correlation between DAS28-ESR(3) value and the intensities of 12 metabolites. The intensities of glycocyamine and indol-3-lactate positively correlated with DAS28-ESR(3) value. On the other hand, β-alanine, asparagine, citrate, cyano-L-alanine, leucine, nicotinamide, citrulline, methionine, oxoproline, and salicylaldehyde negatively correlated with DAS28-ESR(3) value. We found fifteen pathways that were significantly associated with disease activity in RA and that the higher the disease activity, the more amino acid metabolic processes were affected. Conclusion We found the SF metabolic alterations in RA patients according to disease activity by using GC/TOF MS and identified 12 candidate metabolic biomarkers that may well reflect the disease activity of RA. SF metabolomic approaches based on GC/TOF MS might provide additional information relating to monitoring disease activity in RA.
AB - Objective Because genetic and environmental factors both contribute to rheumatoid arthritis (RA), metabolomics could be a very useful tool to elucidate the pathophysiology of RA, and to predict response to treatment. This study was carried out to investigate synovial fluid (SF) metabolic perturbation in RA patients according to the degree of disease activity using gas chromatography/time-of-flight mass spectrometry (GC/TOF MS). Methods SF samples were obtained from 48 RA patients. Disease activity was assessed using DAS28-ESR(3). SF metabolomic profiling was performed using GC/TOF-MS, in conjunction with multivariate statistical analyses and pathway analyses. Results Significant discrimination of metabolite profiles between moderate and high disease activity groups was shown by PLS-DA, which provided evidence that SF metabolic profiles predicted disease activity. We found the significant correlation between DAS28-ESR(3) value and the intensities of 12 metabolites. The intensities of glycocyamine and indol-3-lactate positively correlated with DAS28-ESR(3) value. On the other hand, β-alanine, asparagine, citrate, cyano-L-alanine, leucine, nicotinamide, citrulline, methionine, oxoproline, and salicylaldehyde negatively correlated with DAS28-ESR(3) value. We found fifteen pathways that were significantly associated with disease activity in RA and that the higher the disease activity, the more amino acid metabolic processes were affected. Conclusion We found the SF metabolic alterations in RA patients according to disease activity by using GC/TOF MS and identified 12 candidate metabolic biomarkers that may well reflect the disease activity of RA. SF metabolomic approaches based on GC/TOF MS might provide additional information relating to monitoring disease activity in RA.
KW - Disease activity
KW - Gas chromatography-mass spectrometry
KW - Metabolomics
KW - Rheumatoid arthritis
KW - Synovial fluid
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M3 - Article
C2 - 31498072
AN - SCOPUS:85085537009
SN - 0392-856X
VL - 38
SP - 500
EP - 507
JO - Clinical and Experimental Rheumatology
JF - Clinical and Experimental Rheumatology
IS - 3
ER -