SAT0058 Biomarkers of Endothelial Dysfuncton in Rheumatoid Arthritis Compared with Diabetes Mellitus Type 2, Obesity and Healthy Controls. (23rd January 2014)

• Record Type: Journal Article
• Authors: Soto, J. J.; Viveros, M. E.; Gutierrez, S.; Hernandez, S. E.; Rivera, A.; Cardiel, M. H.
• Is Part Of: Annals of the rheumatic diseases. Volume 72:Supplement 3(2013)
• Page Start: A599
• Page End: A599
• Publication Date: 2014-01-23
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2013-eular.1784
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Rheumatoid Arthritis (RA) is characterized by increased cardiovascular (CV) morbimortality due to higher prevalence of traditional CV risk factors such as diabetes, dyslipidemia, hypertension, sedentarism, increased body mass index (BMI) that is often undertreated 1 . RA is considered a state of accelerated atherosclerosis, which has been recognized as a dynamic inflammatory process that begins with endothelial activation/dysfunction. Diabetes Mellitus Type 2 (DM2) is the prototype of disease with a high degree of endothelial dysfunction, atherosclerosis and CV risk. CV risk could be similar in RA and DM2. 2, 3 Objectives: To determine the degree of endothelial dysfunction in RA patients compared to DM2 patients with and without glycemic control, obese patients and healthy subjects. Methods: Descriptive, prolective, transversal, observational clinical study, with 5 groups: 1) AR, 2) UDM: Uncontrolled DM2, 3) CDM: Controlled DM2, 4) Obesity, 5) Control Group. All matched with group 1 for age (±2 years), gender, period of clinical diagnosis. Complete medical history, Carotid Intima-Media Thickness, blood cell count, erythrosedimentation rate, C-reactive Protein, fasting & 2 hours postprandial glucose, fasting insulin, urea, creatinine, ureic nitrogen, uric acid, glycosylated haemoglobin (HbA1c%), Triglycerides (TG), total cholesterol (TC), C-HDL, C-LDL, C-VLDL, urianalysis, micro-albuminuria. Endothelial dysfunction biomarkers (ELISA): TNF-α, IL-6, vWF, PAI-1. Descriptive statistical analyses:mean & standard deviation. Kolmogorov-Smirnov test to determine distribution type. Comparison between groups (parametric distribution): ANOVA; non-parametric distribution: Kruskal-Wallis. Spearman´s correlation coefficient to associate biomarkers with cardiovascular risk variables. Results: 190 participants in five groups, main results showed. Conclusions: Patients with RA share traditional factors of CV risk with diabetic patients (obesity, arterial hypertension, low levels of C-HDL), present non-traditional risk factors that are characteristic of their inflammatory status (SGS, CRP, TNF-α, IL-6) and also appear to present a prothrombotic status (PAI-1, vWF) that is greater than that of DM2 patients. This confers an increased risk of accelerated atherosclerosis upon the RA patients. It is therefore imperative that these patients are managed appropriately in a comprehensive manner. References: Liao KP, Solomon DH. Rheumatology 2012; 2: 123-129. Van Halm VP et al. Ann Rheum Dis 2009; 68: 1395-1400. Stamatelopoulos SK et al. Arterioscler Thromb Vasc Biol 2009: 5:1-7. Acknowledgements: The research team is grateful to Bristol Myers Squibb for the provision of funding with which to conduct this study. Disclosure of Interest: None Declared