Arthritis, a diverse group of inflammatory joint disorders, poses great challenges in early diagnosis and targeted treatment. Timely intervention is imperative, yet conventional diagnostic methods are not able to detect subtle early symptoms. Hence, there is an urgent need for specific biomarkers that discriminate between different arthritis forms and for early diagnosis. The pursuit of such precise diagnostic tools has prompted a growing interest in extracellular vesicles (EVs). EVs, released by cells in a regulated fashion, are detectable in body fluids, including synovial fluid (SF), which fills the joint space. They provide insights into the intricate molecular landscapes of arthritis, and this has stimulated the search for minimally invasive EV-based diagnostics. As such, the analysis of EVs in SF has become a focus for identifying EV-based biomarkers for joint disease endotyping, prognosis, and progression. EVs are composed of a lipid bilayer and a wide variety of different cargo types, of which proteins and RNAs are widely investigated. In contrast, membrane lipids of EVs, especially the abundance, presence, or absence of specific lipids and their contribution to the biological activity of EVs, are largely overlooked in EV research. Furthermore, the identification of specific combinations of different EV components acting in concert in EVs can fuel the definition of composite biomarkers. We here provide a state-of-the-art overview of the knowledge on SF-derived EVs with emphasis on lipid analysis and we give an example of the added value of integrated proteomics and lipidomics analysis in the search for composite EV-associated biomarkers.