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Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis

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...

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Autores principales: Sasaki, Chiyomi, Hiraishi, Tomoko, Oku, Takuma, Okuma, Kenji, Suzumura, Kenichi, Hashimoto, Motomu, Ito, Hiromu, Aramori, Ichiro, Hirayama, Yoshitaka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6622493/
https://www.ncbi.nlm.nih.gov/pubmed/31295280
http://dx.doi.org/10.1371/journal.pone.0219400
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author Sasaki, Chiyomi
Hiraishi, Tomoko
Oku, Takuma
Okuma, Kenji
Suzumura, Kenichi
Hashimoto, Motomu
Ito, Hiromu
Aramori, Ichiro
Hirayama, Yoshitaka
author_facet Sasaki, Chiyomi
Hiraishi, Tomoko
Oku, Takuma
Okuma, Kenji
Suzumura, Kenichi
Hashimoto, Motomu
Ito, Hiromu
Aramori, Ichiro
Hirayama, Yoshitaka
author_sort Sasaki, Chiyomi
collection PubMed
description 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.
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spelling pubmed-66224932019-07-25 Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis Sasaki, Chiyomi Hiraishi, Tomoko Oku, Takuma Okuma, Kenji Suzumura, Kenichi Hashimoto, Motomu Ito, Hiromu Aramori, Ichiro Hirayama, Yoshitaka PLoS One Research Article 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. Public Library of Science 2019-07-11 /pmc/articles/PMC6622493/ /pubmed/31295280 http://dx.doi.org/10.1371/journal.pone.0219400 Text en © 2019 Sasaki et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Sasaki, Chiyomi
Hiraishi, Tomoko
Oku, Takuma
Okuma, Kenji
Suzumura, Kenichi
Hashimoto, Motomu
Ito, Hiromu
Aramori, Ichiro
Hirayama, Yoshitaka
Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
title Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
title_full Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
title_fullStr Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
title_full_unstemmed Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
title_short Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
title_sort metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6622493/
https://www.ncbi.nlm.nih.gov/pubmed/31295280
http://dx.doi.org/10.1371/journal.pone.0219400
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