Urine metabolic profile in rheumatoid arthritis development

Marianne Schrader de Oliveira, Barbara Bartikoski, Jordana de Souza Silva, Rafaela Cavalheiro do Espirito Santo, Stephen Young, Ricardo Xavier

Research output: Contribution to journalAbstractpeer-review

102 Downloads (Pure)


Background: Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by increased mortality and associated with metabolic disorders including dyslipidaemia, insulin resistance and cachexia. Since the metabolomic profile is known to vary in response to different inflammatory conditions, metabolome analysis could substantially contribute to diagnosis and prognosis.

Objectives: To analyse the urine metabolic profile and assess its correlation with body composition parameters and disease activity of RA patients.

Methods: Seventy-nine RA patients, according to ACR/EULAR 2010 classification criteria, aged between 40 and 70 years, were recruited and followed for 12 months. Disease activity, body composition, fatigue and urine metabolome were measured. Body composition was assessed by total body dual-energy x-ray absorptiometry (DXA) for measurement of appendicular lean mass index (ALMI). Disease activity was assessed by Disease Activity Score-28 with erythrocyte sedimentation rate (DAS28ESR). Fatigue as assessed by the Functional Assessment of Chronic Illness Therapy (FACIT). Nuclear Magnetic Resonance spectroscopy (NMR) measurements were performed to evaluate the profile of metabolic changes during the 12mo follow-up, resulting in the identification of 48 metabolites in urine collected at the baseline and after one year. Frequency analysis, Pearson Correlation and Multivariate data analysis with orthogonal projections to latent structures (OPLS) method were performed and a statistical significance was considered as p<0.05.

Results: The study population was characterized by the majority of women (86.7%), mean age 56 years old, mean disease duration of 8 years, around 80% with positive anti-CPP and RF. There was a significant increase of citric acid, creatinine, L-serine and urea during the follow-up, metabolites that are involved in the muscular-related metabolism. There was no substantial variation in the DAS28-ESR (baseline: 3,8, after 12 months: 4,0) and there was no significant correlation between changes in the metabolome pattern and DAS28-ESR score (p>0.05). Fatigue was negatively correlated with L-serine/creatinine (r: - 0,4, p<0.001). Appendicular lean mass index (ALMI) also showed a positive difference which correlated with the increase of urea and creatinine (r: 0,3, p<0.019).

Conclusion: This prospective metabolomic analysis indicated that the RA might be associated with amino acid metabolism alterations probably related to inflammation injury to muscle and fatigue. These findings suggest that urine metabolome analysis may be an interesting approach to study and monitor the systemic impact of RA
Original languageEnglish
Pages (from-to)2129-2130
Number of pages2
JournalAnnals of the Rheumatic Diseases
Issue numberSuppl 2
Publication statusPublished - 27 Jun 2019
EventEULAR Annual Congress - Paris, Paris, France
Duration: 12 Jun 201915 Jun 2019


Dive into the research topics of 'Urine metabolic profile in rheumatoid arthritis development'. Together they form a unique fingerprint.

Cite this