Quantitative proteomics unveils potential plasma biomarkers and provides insights into the pathophysiological mechanisms underlying equine metabolic syndrome - E. M. Espinosa-López; B. Ortiz-Guisado; E. Diez de Castro; A. Durham; E. Aguilera-Tejero; G. Gómez-Baena (BMC Veterinary Research)
Abstract Background Equine Metabolic Syndrome (EMS) is a multifactorial endocrine disorder characterized by obesity, insulin dysregulation (ID), and an increase in the risk of laminitis, a painful condition that can lead to euthanasia in severe cases. Diagnosing EMS is challenging and often relies on clinical history including obesity, difficulty in losing weight, and recurring episodes of laminitis. The gold standard for laboratory support of an EMS diagnosis is the identification of ID, with basal insulin being the simplest and most accessible method, especially in a field setting. However, various factors such as diet, age, stress, season, medications administered, and testing protocols can influence results. Dynamic tests like the oral sugar test (OST) are preferred but present limitations due to low sensitivity and poor repeatability. These diagnostic challenges make EMS difficult to detect in veterinary medicine highlighting the need for an effective method of the early detection of EMS to prevent laminitis and its associated complications. Results Mass spectrometry-based proteomics represents a powerful tool to identify biomarkers and explore molecular pathways related to the underlying pathology. In the current study we established an integrated proteomics pipeline to identify plasma biomarkers for EMS diagnosis. We compared plasma proteomes from healthy horses, non-ID obese horses and animals diagnosed with EMS. This comparison revealed 76 proteins with significant changes (1% FDR) between groups. Conclusions Our study demonstrates that the complement system, the coagulation cascade and extracellular matrix remodelling pathways are altered in EMS. These findings offer new insights into the molecular basis of the development of EMS and led to the nomination of several proteins as potential biomarkers for its early detection.