Milk extracellular vesicles reveal insulin resistance status in peripartum dairy cows.

Abstract

The transition from gestation to lactation is a critical period that leads to insulin resistance (IR) in dairy cows. IR detection requires invasive sampling and laborious methods; therefore, novel and non-invasive approaches are essential. Extracellular vesicles (EVs) are nano-sized particles released by cells and are linked to disease pathophysiology. Hence, the present study aimed to explore the potential application of cow milk EVs (MEVs) in detecting IR in dairy cows. An intravenous glucose tolerance test (IVGTT) was performed (n = 12), and the cows were classified as low, moderate, or high IR based on prepartum area under the curve insulin values. MEVs were enriched using double-size exclusion chromatography and physico-chemically characterized. The results revealed that the particle diameter of MEVs was significantly higher (p ≤ 0.05) in the high-IR group compared to other groups. Out of 26 fatty acids (FAs) detected in MEVs, three long-chain FAs differed significantly in abundance (p ≤ 0.05) in high-IR group. Proteomic analysis revealed a correlation of inflammation and the IR-related proteins; Annexin A1 and Rab proteins, to IR severity. Overall, this study identified promising predictors of IR in cows, supporting the development of non-invasive biomarkers for early detection, facilitating improved herd and disease management, and reducing economic losses.