Background Microparticles (MP) come from cell activation and apoptosis. Largely considered as cell waste and debris, now it is known they could represent a mechanism of cell communication. Circulating MP have been reported to be increased in Rheumatoid Arthritis (RA) patients, so it has been postulated they could represent interesting biomarkers damage.
Objectives to analyze different subset of MP in RA patients' plasma samples according to clinical and immunological parameters as well as traditional CV risk factors.
Methods citrated-plasma samples were obtained from 18 healthy controls, 115 RA patients and a group of patients with traditional CV risk factors with no inflammatory/autoimmune disease (diabetes, n=24; dyslipidemia, n=27; and hypertension, n=41), as CV-risk controls. MP were analyzed in platelet-poor plasma by total labelling and different subsets were identified by their surface-specific markers: platelet- (PMP, CD41+), endothelial- (EMP, CD146+), granulocyte- (GMP, CD66b+) and Tang-derived (Tang-MP, CD3+CD31+). Disease activity (DAS28), clinical and immunological parameters as well as traditional CV risk factors (diabetes, hypertension, dyslipidemia, and obesity) were registered from clinical records.
Results Absolute MP number was increased in RA patients compared to HC (p<0.0001) and positively correlated with BMI (r=0.232, p=0.021), Total/HDL cholesterol ratio (r=0.319, p=0.004), triglycerides (r=0.390, p<0.0001) and the number of traditional CV risk factors (r=0.221, p=0.030). Accordingly, all subsets of MP were found increased in RA: PMP (p<0.0001), EMP (p=0.001), GMP (p<0.001) and Tang-MP (p=0.007). Using Principal Component Analysis, we have identified four components (disease activity-, traditional CV-, disease duration- and inflammation-related) that display different associations with MP subsets. Whereas total number of MP was correlated with traditional CV-component (r=0.384, p=0.001), EMP were associated with disease-duration component (r=0.300, p=0.010). GMP and Tang-MP were found to be correlated with disease-activity component (r=0.267, p=0.019 and r=0.294, p=0.003, respectively). Finally, MP analysis in a subpopulation of individuals with traditional CV risk factors revealed that total MP counts were increased compared to HC group (p=0.002) and also positively correlated to traditional CV risk factors (BMI: r=0.287, p=0.039; TC/HDL ratio: r=0.376, p=0.008, and triglycerides: r=0.358, p=0.012), although differences in specific subsets were not found.
Conclusions MP analysis revealed increased cell damage in several subsets in RA patients. Our results clearly indicate that MP counts in RA patients are the result of the interaction between traditional CV risk factors. Whereas the endothelial damage is dependent of the disease duration, the injury on Tang cells only depends on disease activity. Finally, factors that explain increased MP numbers in RA patients are all factors that have been previously reported to be implicated in CV disease susceptibility in RA.
Disclosure of Interest None declared