Bayesian validation of a serum and milk ELISA for antibodies against Mycobacterium avium subspecies paratuberculosis in Greek dairy goats across lactation

Abstract

We validated a commercial (Idexx Pourquier, Montpellier, France) serum and milk indirect ELISA that detects antibodies against Mycobacterium avium ssp. paratuberculosis (MAP) in Greek dairy goats. Each goat was sampled 4 times, starting from kidding and covering early, mid, and late lactation. A total of 1,268 paired milk (or colostrum) and serum samples were collected during the 7-mo lactation period. Bayesian latent class models, which allow for the continuous interpretation of test results, were used to derive the distribution of the serum and milk ELISA response for healthy and MAP-infected individuals at each lactation stage. Both serum and milk ELISA, in all lactation stages, had average and similar overall discriminatory ability as measured by the area under the curve (AUC). For each test, the smallest overlap between the distribution of the healthy and MAP-infected does was in late lactation. At this stage, the AUC was 0.89 (95% credible interval: 0.70; 0.98) and 0.92 (0.74; 0.99) for the milk and serum ELISA, respectively. Both tests had comparable sensitivities and specificities at the recommended cutoffs across lactation. Lowering the cutoffs led to an increase in sensitivity without serious loss in specificity. In conclusion, the milk ELISA was as accurate as the serum ELISA. Therefore, it could serve as the diagnostic tool of choice, especially during the implementation of MAP control programs that require frequent testing, because milk sampling is a noninvasive, rapid, and easy process.

Keywords: Bayesian latent class model; dairy goat; paratuberculosis; serum and milk ELISA.