Date: Tuesday, November 12, 2019
Session Title: Infection-Related Rheumatic Disease Poster
Session Type: Poster Session (Tuesday)
Session Time: 9:00AM-11:00AM
Background/Purpose: Early diagnosis of inflammatory rheumatic diseases (IRD), as axial Spondyloarthritis (axSpA), Rheumatoid Arthritis (RA) and Systemic Lupus Erythematosus (SLE) represents in our days a major clinical challenge. Increasing evidence has determined that early diagnosis, prompt treatment initiation and early achievement of remission are the main predictors of long-term clinical, functional and radiographic outcomes. Therefore, identification of sensitive markers is important for the early detection and precise therapy for IRD patients. Taking into consideration that metabolomics is a post-genomics technology that offers the closest characterization of the phenotype, this methodology can constitute a key tool for discriminating patients with IRD. This study aims to identify differences in the urinary metabolic profile and develop a feasible clinical approach for axSpA, RA and SLE diagnosis.
Methods: A cross-sectional non-targeted mass spectrometry-based metabolomics study was performed in 111 individuals composed by: axSpA (n=27, according to ASAS criteria), RA (n=22, according to ACR/EULAR criteria for RA) and SLE (n=23, according to ACR classification criteria for SLE) patients and healthy controls (HC; n=39). Patients with co-occurrence of other IRD or having received biotechnological therapies were excluded. Urine samples were analyzed by liquid chromatography high-resolution mass spectrometry (LC-HRMS) and data was subsequently preprocessed with the open-source software MZmine. The resulting matrix was normalized by total area and analyzed by multivariate analysis with the SIMCA software.
Results: Patients with RA were significantly older than controls [RA: 58±12 years old (yo); HC: 43±13yo; axSpA: 36±7yo; SLE: 49±12yo]. RA and SLE groups contained significantly more women (RA: 90%; SLE: 91%; HC: 49%; axSpA: 33%). However, Principal Component Analysis showed that the metabolic profile was not influenced by gender or age. Additionally, metabolic differences were identified between RA and SLE vs HC, but not between axSpA and HC. Importantly, the metabolic profile of SLE and RA patients was significantly different from the one displayed by axSpA patients.
Conclusion: Urine metabolomics demonstrated to be a useful tool to discriminate SLE and RA patients from axSpA patients. Further studies will validate the potential use of urine metabolomic profile for Inflammatory rheumatic diseases diagnosis in clinical practice.
To cite this abstract in AMA style:Morello J, M. Teixeira S, Rodrigues J, Maia S, Sardoo A, Pinheiro Torres R, A. Pereira S, Branco J, Antunes A, Pimentel-Santos F. Diagnosis of Inflammatory Rheumatic Diseases: Preliminary Approach by Urine Metabolomics [abstract]. Arthritis Rheumatol. 2019; 71 (suppl 10). https://acrabstracts.org/abstract/diagnosis-of-inflammatory-rheumatic-diseases-preliminary-approach-by-urine-metabolomics/. Accessed June 1, 2023.
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ACR Meeting Abstracts - https://acrabstracts.org/abstract/diagnosis-of-inflammatory-rheumatic-diseases-preliminary-approach-by-urine-metabolomics/