Open AccessMetabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
Author(s) -
Chiyomi Sasaki,
Tomoko Hiraishi,
Teruo Oku,
Kenji Okuma,
Kenichi Suzumura,
Motomu Hashimoto,
Hiromu Ito,
Ichiro Aramori,
Yoshitaka Hirayama
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0219400
Subject(s) - urine , biomarker , rheumatoid arthritis , erythrocyte sedimentation rate , medicine , receiver operating characteristic , metabolomics , area under the curve , metabolome , gastroenterology , metabolite , chemistry , chromatography , biochemistry
We aimed to investigate metabolites associated with the 28-joint disease activity score based on erythrocyte sedimentation rate (DAS28-ESR) in patients with rheumatoid arthritis (RA) using capillary electrophoresis quadrupole time-of-flight mass spectrometry. Plasma and urine samples were collected from 32 patients with active RA (DAS28-ESR≥3.2) and 17 with inactive RA (DAS28-ESR<3.2). We found 15 metabolites in plasma and 20 metabolites in urine which showed a significant but weak positive or negative correlation with DAS28-ESR. When metabolites between active and inactive patients were compared, 9 metabolites in plasma and 15 in urine were found to be significantly different. Consequently, we selected 11 metabolites in plasma and urine as biomarker candidates which significantly correlated positively or negatively with DAS28-ESR, and significantly differed between active and inactive patients. When a multiple logistic regression model was built to discriminate active and inactive cohorts, three variables—histidine and guanidoacetic acid from plasma and hypotaurine from urine—generated a high area under the receiver operating characteristic (ROC) curve value (AUC = 0.8934). Thus, this metabolomics approach appeared to be useful for investigating biomarkers of RA. Combination of plasma and urine analysis may lead to more precise and reliable understanding of the disease condition. We also considered the pathophysiological significance of the found biomarker candidates.