Elucidating Osteoarthritis Endotypes in Human Synovial Fluid via Global Metabolomic Profiling
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Authors
Parkey, Audrey
Lynch, Liam
Date of Issue
2024
Type
Presentation
Language
en_US
Subject Keywords
Other Titles
Abstract
Osteoarthritis (OA) poses a challenge to human health by causing progressive joint degradation and associated symptoms. The complex interplay of risk factors such as joint trauma, abnormal joint loading, obesity and advanced age underscore the need to better define OA phenotypes for targeted treatment options. The aim of this study was to identify and characterize metabolic phenotypes of OA. Synovial fluid (SF) samples from the Carroll College IRB-approved biobank were utilized in this study. Ten healthy post-mortem samples were designated as controls, and 12 SF samples from living patients diagnosed with OA were analyzed as the experimental group. Metabolites were extracted from the fluid, and analyzed at Montana State University using liquid chromatography-mass spectrometry (LC-MS). Unsupervised statistical methods were used to identify subgroups of OA patients as possible metabolic phenotypes. Supervised statistical methods were employed to identify key metabolites differentiating between subgroups which were then mapped to metabolic pathways. Our findings reveal distinct groupings of OA patients, identified as Group 1 (G1) and Group 2 (G2). Group 1 exhibited increased joint effusion and decreased metabolism of amino acids like lysine in the SF. Conversely, G2 was characterized by reduced joint effusion and decrease of both amino acid and fatty acid metabolism. The results suggest that treatment based on lysine and fatty acid metabolism profiles could serve as a basis for optimal clinical intervention tailored to individual OA metabolic phenotypes.