T. Mark

Genetic correlations between pathogen-specific mastitis and somatic cell count in Danish Holsteins.

The aim of this study was to estimate genetic correlations (r(a)) between 2 lactation average somatic cell count (LASCC) traits and 6 different mastitis traits in 226,482 first-parity Danish Holstein cows that calved between 1998 and 2008. The LASCC traits were defined from 5 to either 170 d (LASCC_170) or 300 d (LASCC_300) after calving, and the mastitis traits were unspecific mastitis (all mastitis treatments, both clinical and subclinical, regardless of the causative pathogen) and mastitis caused by either Streptococcus dysgalactiae, Escherichia coli, coagulase-negative staphylococci (CNS), Staphylococcus aureus, or Streptococcus uberis. Variance components were estimated using bivariate threshold-Gaussian models via Gibbs sampling. The posterior means of r(a) between LASCC_170 and the mastitis traits were greatest for unspecific mastitis (r(a) = 0.71), followed by CNS, Strep. dysgalactiae, Strep. uberis, and E. coli (r(a) = 0.54 to 0.69) and were lowest for Staph. aureus mastitis (r(a) = 0.44). The genetic correlation between LASCC_300 and the mastitis traits were generally smaller (r(a) = 0.47 to 0.69). Caution should be taken when interpreting the results, however, because some posterior density intervals for r(a) were large (between 0.14 and 0.47 units). Phenotypically, Staph. aureus is known to be associated with high SCC and especially with subclinical mastitis through chronic infections, so the low r(a) between Staph. aureus mastitis and LASCC, compared with r(a) for the other pathogens, was not expected. Subclinical cases are usually submitted to dry cow therapy (not included in the present study), not treated at all, or wrongly recorded as clinical cases. Thus, the incidence of Staph. aureus mastitis is likely too low, and the genetic correlation between Staph. aureus mastitis and LASCC may therefore be underestimated in the present study. The results for the remaining pathogens were as expected, smallest for E. coli and larger but similar for Strep. dysgalactiae, Strep. uberis, and CNS. Selection for lower LASCC is expected to decrease the incidence of pathogen-specific mastitis, especially for Strep. uberis, Strep. dysgalactiae, and CNS and, to a lesser extent, for Staph. aureus and E. coli. Data recording should preferably be improved, and economic weights for the pathogen-specific mastitis traits should be estimated before implementing an udder health index that includes pathogen-specific mastitis traits.

Economic values and expected effect of selection index for pathogen-specific mastitis under Danish conditions

The objectives of this study were 1) to estimate costs related to 5 different pathogen-specific mastitis traits (susceptibility to different pathogens causing mastitis in dairy cattle) and unspecific mastitis, and 2) to compare selection differentials for an udder health index consisting of 5 different pathogen-specific mastitis traits and lactation average somatic cell count from 5 to 170 d after first calving (LASCC170) with another index consisting of 1 unspecific mastitis trait and LASCC170. Economic values were estimated for mastitis caused by Staphylococcus aureus, Streptococcus dysgalactiae, Escherichia coli, coagulase-negative staphylococci, and Streptococcus uberis using a stochastic simulation model (SimHerd IV). Mastitis incidences for SimHerd IV were from incidences of mastitis treatments in primiparous Danish Holstein cows calving in 2007. Estimated costs ranged from 149 euro to 570 euro per mastitis case and were highest for contagious pathogens such as Staph. aureus and coagulase-negative staphylococci and lowest for Strep. dysgalactiae and Strep. uberis. The value for unspecific mastitis was 231 euro per case. Selection differentials (in euro) were estimated for 4 different selection indices, including 1) unspecific mastitis, 2) unspecific mastitis and LASCC170, 3) 5 pathogen-specific mastitis traits and unspecific residual mastitis (unspecific mastitis treatments minus mastitis treatments caused by the 5 pathogens), and 4) as index 3 including LASCC170. The breeding goal was identical to selection index 3. Mastitis data from primiparous cows calving from 1998 to 2008 were used to estimate genetic parameters of the mastitis traits using linear models and AI-REML algorithm. These parameters were used for construction of the selection index equations. For the selection indices, information sources were measurements of mastitis treatments and LASCC170 from 50, 80, or 130 daughters of a bull as well as measurements of mastitis treatments from 1,000 progeny of the bulls sire and 1,000 daughters of his maternal grandsire. Differences in selection differentials were marginal among the 4 indices. Without considering LASCC170, the selection differential of an unspecific mastitis index was 0.4 euro (<1%) better than that of a pathogen-specific index. On the other hand, the selection differential of the pathogen-specific index was 0.3 euro (<1%) better than that of an unspecific index when LASCC170 was included in the indices. Reliabilities of the selection indices were 0.62 to 0.67 (80 daughters) and were proportional to the selection differential. Changing the number of daughters to 50 or 130 did not change ranking of the indices. Heritabilities of the pathogen-specific traits were very low (h(2)=0.005-0.021) compared with unspecific mastitis (h(2)=0.062), which may limit the selection differential of the pathogen-specific index.