Computational inhibition of S100A8 (calgranulin A) as a potential non-invasive biomarker for rheumatoid arthritis.

Abstract

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic joint pain and inflammation, loss of mobility, which affects the quality of life. The etiology of RA is unknown, and there is no isolated cause for the development of this illness. Synovial inflammation, autoantibody generation and bone degradation leading to deformity are classic characteristics of RA. The search for a non-invasive biomarker is crucial for helping patients receive standard therapies leading to faster treatments, as diagnosis depends on invasive biopsies. Therefore, in the present investigation, using transcriptomics and proteomic approaches, potential genes involved in crucial networks in RA were identified. Gene expression datasets of two tissue types i.e. whole blood and synovial tissue were retrieved from the GEO database and used for transcriptomic analyses. Using SWATH-MS analysis, differentially expressed proteins were identified from collected saliva of RA patients. Through bioinformatics analysis, S100A8, also known as Calprotectin (a complex of S100A8/A9) or Calgranulin A, was found to be common among all tissue types. S100A8 was then further quantified in saliva of healthy volunteers and RA patients, where it was found that the protein's level in healthy controls was lowered when compared to RA patients. Through in-silico characterization, potential plant-based inhibitors of S100A8 were also identified, to reduce its pro-inflammatory effects. Thus, it may be important in the pathophysiology of RA and, in the future, might help guide targeted treatment. as well as act as a non-invasive diagnostic biomarker platform.