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

ABSTRACT: 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.

SUBMITTER: Sasaki C

PROVIDER: S-EPMC6622493 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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

Sasaki Chiyomi C Hiraishi Tomoko T Oku Takuma T Okuma Kenji K Suzumura Kenichi K Hashimoto Motomu M Ito Hiromu H Aramori Ichiro I Hirayama Yoshitaka Y

PloS one 20190711 7

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 n ...[more]

PMID: 31295280

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Project description:ObjectiveTo evaluate rheumatoid arthritis (RA) disease activity and risk of RA-associated interstitial lung disease (RA-ILD).MethodsWe investigated disease activity and risk of RA-ILD using the Brigham RA Sequential Study (BRASS, 2003-2016). All patients were diagnosed as having RA according to accepted criteria. Disease Activity Scores in 28 joints (DAS28) and covariate data were measured prospectively at annual study visits. Diagnosis of RA-ILD was determined by review of images from clinically indicated chest computed tomography scans. We analyzed patients without RA-ILD at baseline. We used Cox regression to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for RA-ILD, using annually updated DAS28 data, with adjustment for known RA-ILD risk factors (age, sex, smoking status, RA duration, and serologic status). We performed alternative analyses that did not censor at the time of missing DAS28 data and included adjustment for use of methotrexate, use of glucocorticoids, presence of bone erosions, and presence of rheumatoid nodules.ResultsAmong 1,419 participants, the mean ± SD age was 55.8 ± 14.2 years, and 68.6% were seropositive for either cyclic citrullinated peptide or rheumatoid factor. We identified 85 incident cases of RA-ILD during a mean ± SD follow-up duration of 8.9 ± 4.2 years per patient. The moderate/high disease activity group had a multivariable HR of 2.22 (95% CI 1.28-3.82) for RA-ILD compared to the remission/low disease activity group. Risk of RA-ILD increased across disease activity categories: multivariable HR 1.00 (reference) for remission, 1.41 (95% CI 0.61-3.28) for low disease activity, 2.08 (95% CI 1.06-4.05) for moderate disease activity, and 3.48 (95% CI 1.64-7.38) for high disease activity (P for trend = 0.001). For each unit increase in the DAS28, the risk of RA-ILD increased by 35% (95% CI 14-60%). Results were similar in analyses that included follow-up for missing DAS28 data and with adjustment for use of methotrexate, use of glucocorticoids, presence of bone erosions, or presence of rheumatoid nodules.ConclusionActive articular RA was associated with an increased risk of developing RA-ILD. These results suggest that decreasing systemic inflammation may alter the natural history of RA-ILD development.

Project description:BackgroundRheumatoid arthritis (RA) is a chronic, autoimmune disorder characterized by joint inflammation and pain. In patients with RA, metabolomic approaches, i.e., high-throughput profiling of small-molecule metabolites, on plasma or serum has thus far enabled the discovery of biomarkers for clinical subgroups, risk factors, and predictors of treatment response. Despite these recent advancements, the identification of blood metabolites that reflect quantitative disease activity remains an important challenge in precision medicine for RA. Herein, we use global plasma metabolomic profiling analyses to detect metabolites associated with, and predictive of, quantitative disease activity in patients with RA.MethodsUltra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was performed on a discovery cohort consisting of 128 plasma samples from 64 RA patients and on a validation cohort of 12 samples from 12 patients. The resulting metabolomic profiles were analyzed with two different strategies to find metabolites associated with RA disease activity defined by the Disease Activity Score-28 using C-reactive protein (DAS28-CRP). More specifically, mixed-effects regression models were used to identify metabolites differentially abundant between two disease activity groups ("lower", DAS28-CRP ≤ 3.2; and "higher", DAS28-CRP > 3.2) and to identify metabolites significantly associated with DAS28-CRP scores. A generalized linear model (GLM) was then constructed for estimating DAS28-CRP using plasma metabolite abundances. Finally, for associating metabolites with CRP (an indicator of inflammation), metabolites differentially abundant between two patient groups ("low-CRP", CRP ≤ 3.0 mg/L; "high-CRP", CRP > 3.0 mg/L) were investigated.ResultsWe identified 33 metabolites differentially abundant between the lower and higher disease activity groups (P < 0.05). Additionally, we identified 51 metabolites associated with DAS28-CRP (P < 0.05). A GLM based upon these 51 metabolites resulted in higher prediction accuracy (mean absolute error [MAE] ± SD: 1.51 ± 1.77) compared to a GLM without feature selection (MAE ± SD: 2.02 ± 2.21). The predictive value of this feature set was further demonstrated on a validation cohort of twelve plasma samples, wherein we observed a stronger correlation between predicted and actual DAS28-CRP (with feature selection: Spearman's ρ = 0.69, 95% CI: [0.18, 0.90]; without feature selection: Spearman's ρ = 0.18, 95% CI: [-0.44, 0.68]). Lastly, among all identified metabolites, the abundances of eight were significantly associated with the CRP patient groups while controlling for potential confounders (P < 0.05).ConclusionsWe demonstrate for the first time the prediction of quantitative disease activity in RA using plasma metabolomes. The metabolites identified herein provide insight into circulating pro-/anti-inflammatory metabolic signatures that reflect disease activity and inflammatory status in RA patients.

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

Publications

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

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