Gambling on putative biomarkers of osteoarthritis and osteochondrosis by equine synovial fluid proteomics.

Osteoarthritis (OA) and osteochondrosis (OC) are two of the main challenges in orthopedics, whose definitive diagnosis is usually based on radiographic/arthroscopic evidences. Their early diagnosis should allow preventive or timely therapeutic actions, which are generally precluded from the poor relationships occurring between symptomatologic and radiographic evidences. These limitations should be overcome by improving the knowledge on articular tissue metabolism and on molecular factors regulating its normal homeostasis, also identifying novel OA and OC biomarkers suitable for their earlier diagnoses, whenever clinical/pathological inflammatory scenarios between these joint diseases seem somewhat related. To identify proteins involved in their aetiology and progression, we undertook a differential proteomic analysis of equine synovial fluid (SF), which compared the protein pattern of OA or OC patients with that of healthy individuals. Deregulated proteins in OA and OC included components related to inflammatory state, coagulation pathways, oxidative stress and matrix damage, which were suggestive of pathological alterations in articular homeostasis, plasma-SF exchange, joint nutritional status and vessel permeability. Some proteins seemed commonly deregulated in both pathologies indicating that, regardless of the stimulus, common pathways are affected and/or the animal joint uses the molecular mechanisms to restore its homeostasis. On the other hand, the increased number of deregulated proteins observed in OA with respect to OC, together with their nature, confirmed the high inflammatory character of this disease. Some deregulated proteins in OA found a verification by analyzing the SF of injured arthritic joints following autologous conditioned serum treatment, an emergent therapy that provides positive results for both human and equine OA. Being the horse involved in occupational/sporting activities and considered as an excellent animal model for human joint diseases, our data provide suggestive information for biomedical extrapolations, allowing to overcome the limitations in joint size and workload that are typical of other small animal models.