Cargando…
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...
Autores principales: | , , , , , , , , |
---|---|
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 |
_version_ | 1783434166168190976 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6622493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT sasakichiyomi metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT hiraishitomoko metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT okutakuma metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT okumakenji metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT suzumurakenichi metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT hashimotomotomu metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT itohiromu metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT aramoriichiro metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis AT hirayamayoshitaka metabolomicapproachtotheexplorationofbiomarkersassociatedwithdiseaseactivityinrheumatoidarthritis |