Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

ABSTRACT

This study aimed to compare the accuracy of IFN-τ stimulated gene abundance (ISGs) in peripheral blood mononuclear cells (PBMCs), CL blood perfusion by Doppler ultrasound (Doppler-US), plasma concentration of P4 on Day 21 and pregnancy-associated glycoproteins (PAGs) test on Day 25 after timed-artificial insemination (TAI) for early pregnancy diagnosis in dairy cows and heifers. Holstein cows (n = 140) and heifers (n = 32) were subjected to a hormonal synchronization protocol and TAI on Day 0. On Day 21 post-TAI, blood samples were collected for PBMC isolation and plasma concentration of P4. The CL blood perfusion was evaluated by Doppler-US. Plasma samples collected on Day 25 were assayed for PAGs. The abundance of ISGs (ISG15 and RSAD2) in PBMCs was determined by RT-qPCR. Pregnancy was confirmed on Days 32 and 60 post-TAI by B-mode ultrasonography. Statistical analyses were performed by ANOVA using the MIXED procedure and GLIMMIX in SAS software. The pregnancy biomarkers were used to categorize the females as having undergone late luteolysis (LL); early embryonic mortality (EEM); late embryonic mortality (LEM); or late pregnancy loss (LPL). The abundance of ISGs, CL blood perfusion by Doppler-US, and concentrations of P4 on Day 21, and PAGs test on Day 25 were significant (P < 0.05) predictors of early pregnancy in dairy cows and heifers. Dairy cows had a greater (P = 0.01) occurrence of LL than heifers, but there was no difference (P > 0.1) for EEM, LEM, and LPL in heifers compared to cows. Cows with postpartum reproductive issues had a greater (P = 0.008) rate of LEM and a lesser (P = 0.01) rate of LPL compared to cows without reproductive issues. In summary, the CL blood perfusion by Doppler-US had the highest accuracy and the least number of false negatives, suggesting it is the best predictor of pregnancy on Day 21 post-TAI. The PAGs test was the most reliable indicator of pregnancy status on Day 25 post-TAI in dairy heifers and cows. The application of machine learning, specifically the MARS algorithm, shows promise in enhancing the accuracy of predicting early pregnancies in cows.