%0 Artículo (Article) %A Molano-González, Nicolas %I Academic Press %D 2019 %G Inglés (English) %T Cluster analysis of autoimmune rheumatic diseases based on autoantibodies. New insights for polyautoimmunity %U https://repository.urosario.edu.co/handle/10336/22263 %U https://doi.org/10.1016/j.jaut.2018.11.002 %X Autoimmune diseases (ADs) are a chronic and clinically heterogeneous group of diseases characterized by share common immunopathogenic mechanisms and risk factors (i.e., the autoimmune tautology), which explain the fact that one AD may coexist with others (i.e., polyautoimmunity - PolyA). In the present exploratory study, a mixed-cluster analysis of the most common autoimmune rheumatic diseases (ARDs) was done. A total of 187 consecutive women with established systemic lupus erythematosus (n = 70), rheumatoid arthritis (n = 51), systemic sclerosis (n = 35) and Sjögren's syndrome (n = 31) were included. A comprehensive clinical, autoantibody and cytokine assessment was simultaneously done. Total PolyA was registered in 142 (75.9%) patients. Six clusters were obtained, built mainly on autoantibodies: PolyA-I to -VI. The PolyA-III cluster showed the highest frequency of overt PolyA (p = 0.01), and the PolyA-I, -III, and -IV clusters exhibited the highest positivity for IL-12/23p40 (p = 0.015). These results provide new insights into the pathophysiology of PolyA and warrant prospective validation to enable development of a more accurate taxonomy of ARDs. © 2018 The Authors