Milk fatty acids as biomarkers of metabolic diseases in dairy cows identified through thin layer chromatography and gas chromatographic techniques (Tlc-gc)

In the transition period an excessive mobilization of adipose tissue in high milk production dairy cows predisposes to metabolic diseases as subclinical ketosis. The aim of this research was to identify the association between the concentration of milk fatty acids and the elevated plasmatic value of Non Esterified Fatty Acid (NEFA) for the diagnosis of excessive lipomobilization in dairy cows using Thin Layer Chromatography and Gas Chromatographic Techniques (TLC-GC). Fifty-four multiparous Holstein-Friesian dairy cows in the first phase of lactation were enrolled in the study. Blood samples from the coccygeal vein were collected and Non-Esterified Fatty Acids (NEFA) was evaluated in laboratory of University of Padua. Milk samples (40 mL) were taken at the evening milking from each bovine enrolled in the trial. Animals were divided into two groups on the basis of blood NEFA: healthy animals (NEFA-0) with a value of NEFA ≤ 0.57 mEq/L and sick animals (NEFA-1) with a value of NEFA > 0.57 mEq/L. Milk fatty acids concentrations have been evaluated in 4 lipid classes: Free Fatty Acids (FFA), Cholesterol Esters (CE), Phospholipids (PL), and Triglycerides (TG). Data were analysed using SAS system software (version 9.4; SAS Institute Inc., Cary, NC, USA). The General Linear Model (GLM) analysis was performed for repeated measurements in order to evaluate the differences in the composition of milk fatty acids related to the four lipid fractions in function of two different NEFA blood concentrations (NEFA-0 vs NEFA-1). The results showed the following statistical significance (p ≤ 0.05) in the milk lipid classes: two fatty acids were significant in CE, one fatty acid was significant in FFA, nine fatty acids were significant in TG and one fatty acid was significant in PL. These milk fatty acids, with predictive value for the development of metabolic disorder, could be considered valuable new biomarkers.