Discovering Potential Biomarkers for Osteoarthritis, Gouty Arthritis, and Rheumatoid Arthritis

Abstract

In the United States alone, 24% of adults have arthritis, which include many different types. The three most common forms of arthritis are osteoarthritis (OA), gouty arthritis (gout), and rheumatoid arthritis (RA). Despite having different pathologies, the main symptoms of all types include pain, aching, stiffness, and swelling of joints. There are no cures for OA, gout, or RA, so treatment is based on symptom management, with more targeted and beneficial treatment being introduced early into disease progression. The diagnostic process for all three disease states is complex, and there is a need to find effective diagnostic markers for early detection. This research examines the use of metabolomics to analyze metabolite levels and intermediates in metabolic pathways in order to find potential biomarkers indicative of their respective disease and provide early and more concise diagnosis. In our experiment, we will extract metabolites from synovial fluid samples and analyze them using Liquid Chromatography-Mass Spectrometry to identify possible biomarkers that would help early diagnosis of arthritis. After metabolite extraction, the raw data will be analyzed using the online data analysis site Metaboanalyst. Using Metaboanalyst. We will construct multiple statistical plots to compare osteoarthritis, gouty arthritis, and rheumatoid arthritis on a molecular level. Our goal is to find unique metabolic pathways affected by each type of arthritis, and to confirm potential biomarkers that could help diagnose each type of arthritis earlier. We hypothesize that rheumatoid arthritis will appear the most different due to the role the immune system plays, but ultimately, we expect to see unique metabolites and affected metabolic pathways in each type of arthritis.