POS0546 URINARY METABOLOMIC BIOMARKER CANDIDATES FOR SKELETAL MUSCLE WASTING IN PATIENTS WITH RHEUMATOID ARTHRITIS

Abstract

BackgroundRheumatoid arthritis (RA) is an autoimmune disease that affects the joints, leading to chronic synovial inflammation and local tissue destruction. Extra-articular manifestations may also occur, such as changes in body composition. Skeletal muscle wasting is often observed in patients with RA, but methods for assessing loss of muscle mass are expensive and not widely available, limiting their use in clinical practice and their evaluation in longitudinal studies. Metabolomic analysis has shown great potential for identifying changes in the metabolite profile of patients with autoimmune diseases and can advance our understanding of pathogenic mechanisms, early diagnosis, treatment, and follow-up. In this setting, urine metabolomic profiling in patients with RA may be a useful tool to identify skeletal muscle wasting.ObjectivesTo evaluate the urinary metabolomic profile of patients with rheumatoid arthritis and associate it with skeletal muscle loss.MethodsWe recruited patients aged 40–70 years with RA according to the 2010 ACR/EULAR classification criteria. We measured disease activity by the Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP). We determined muscle mass according to DXA-derived appendicular lean mass index (ALMI) by summing the lean mass measurements for both arms and legs and dividing them by height squared (kg/height2). We performed urine metabolomic analysis by nuclear magnetic resonance (NMR) spectroscopy using the BAYESIL and MetaboAnalyst software packages. We performed principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), followed by Spearman’s correlation analysis. We set the significance level at p<0.05 for all analyses. We combined Receiver Operating Characteristic Curve (ROC) and logistic regression analyses to establish a diagnostic model.ResultsWe included 90 patients with RA. Most patients were women (86.7%), with a mean age of 56.5 (SD, 7.3) years and a median DAS28-CRP of 3.0 (IQR, 1.0–3.0). We identified 15 metabolites that showed high variable importance in projection (VIP scores) by MetaboAnalyst. Of these, dimethylglycine (r=0.205; p=0.053), oxoisovalerate (r= −0.203; p=0.055) and isobutyric acid (r= −0.249; p= 0.018) were significantly correlated with ALMI. Based on low muscle mass (ALMI ≤6.0 kg/m2 for women and ≤8.1 kg/m2 for men), we established a diagnostic model with dimethylglycine (Area Under the Curve - AUC=0.65), oxoisovalerate (AUC=0.49) and isobutyric acid (AUC=0.83), with significant sensitivity and specificity.ConclusionIsobutyric acid, oxoisovalerate and dimethylglycine from urine samples were associated with low skeletal muscle mass in patients with RA. These findings suggest that this group of metabolites may be further tested as biomarkers for identification of skeletal muscle wasting.