Structural and Pharmacological Network Focused on MiRNAs Involved in Rheumatoid Arthritis: A Systematic Review

Background: Rheumatoid Arthritis (RA) is a chronic autoimmune disease that has a prevalence of over one percent of the world population, causing substantial pain, joint deformity, and functional disability in patients. The identification and measurement of miRNAs are relatively easy to perform. Future studies will corroborate if miRNAs can fulfill their roles as biomarkers with either predictive or diagnostic evaluation of treatment potential and provide actual clinical utility. Methods: In the last decade, various advances have been made regarding the identification of the origin and exact functions of miRNAs, allowing us to have a potential use both in the research and clinical fields. Objective: This systematic review aimed to collect, analyze, and improve the current understanding of RA-related miRNAs and their applicability in therapeutics. A bibliographic search of the miRNAs involved in RA was carried out, and through the use of databases, their target genes and small molecules that had some relationship with their expression were searched. The analysis of these data was done through structural network analysis. Results: During the network analysis, miR-30a, miR-30c, let-7a, miR-144, miR-17-5p, miR-124, miR -23b, miR-23, miR-15a, miR-16 were the most connected, which could be used as possible biomarkers or be candidates for further analysis due to their interaction with other miRNAs and genes. Conclusion: Additionally, this is the first systematic review, in which we proposed that small compounds like toxicants and drugs could have a potential role within RA because they regulate the expression of miRNAs involved in this pathology. Some of these compounds are commonly found as environmental contaminants, and others as drugs. These ideas open a new panorama of understanding RA, proposing possible causes or treatments against this pathology. Therefore, these small molecules would give us some indication of a relationship with RA, thereby helping in seeking causes, treatment, or prevention of this disease. Conclusion: This is the first time it is intended to use structural network analysis to determine possible biomarkers of AR for diagnosis and prognosis through the expression of these miRNAs and their relationship with compounds of daily life.