Development of a predictive model for bovine leukemia virus proviral load

Abstract

Background: There is currently no commercially available method in Canada to identify bovine leukemia virus (BLV)-positive cows with high proviral load (PVL). Objectives: First, develop a model to predict PVL using common, commercially available, cost-effective diagnostic tests. Second, investigate the relationship between lymphocyte count and PVL in BLV-positive cows. Animals: A total of 339 BLV-positive and 62 BLV-seronegative cows on 15 dairy farms. Methods: Cross-sectional study. Blood and milk samples were collected from all lactating BLV-positive cows on each farm and 5 to 10 BLV-seronegative cows depending on herd size. Blood and milk samples were tested for anti-BLV antibodies using enzyme-linked immunosorbent assay (ELISA). Complete blood counts were performed on blood samples, and standard components analyses were obtained for milk samples. Proviral load was determined by quantitative polymerase chain reaction for each cow. Results: The inverse of lymphocyte count, the square of the inverse of lymphocyte count, and milk ELISA percent positivity were positively associated with increasing PVL in BLV-positive cows. For BLV-positive cows, lymphocyte count >5.2 × 109/L predicted a high PVL (BLV:Bovine DNA of >1 in blood) with a sensitivity of 92.4% and a specificity of 79.8%. For BLV-positive cows, white blood cell count >10.8 × 109/L predicted a high PVL, with a sensitivity of 85.5% and a specificity of 83.6%. Conclusions and Clinical Importance: Based on these results, producers can implement commonly available diagnostic tests to identify cows with high probability of having high PVL, which may help in designing effective disease control strategies for BLV-positive herds.