Exploring alternative cytokines as potential biomarkers forinfection in cattle.

Abstract

() is the primary agent of Bovine tuberculosis (bTB) in cattle. It represents both a threat to human health and the cattle industry worldwide. Improving bTB diagnostic performance in cattle represents a key step in eradicating the disease. The interferon-gamma (IFN-γ) release (IGRA) blood assay is routinely used in the diagnosis ofinfection, but additional cytokines might be useful as biomarkers of this infection in cattle. In our study, we evaluated the utility of sixteen immune cytokines as diagnostic biomarkers ofinfection. Fifty-five cattle were used in this study: healthy animals (N = 19), infected (IFN-γ test positive, no post-mortem lesions; N = 17), and affected (IFN-γ test positive, visible post-mortem lesions; N = 19). Heparin blood samples were stimulatedwith bovine purified protein derivative (PPD-B), alongside controls. After 18-24 h of incubation, plasma were collected and levels of 16 key cytokines were measured: IL-1α, IL-4, IL-6, IL-10, IL-17, IL-36Ra, MIP-1α, IP-10, MCP-1, TNF, VEGF-A, IFN-γ, IL-23, IL-27, IL-35, and THBS-1. We observed that bothexposed cattle (both infected and affected) released higher levels of PPD-B specific IFN-γ and IP-10. On the contrary, only cattle belonging to the affected group released higher levels of PPD-B specific IL-4, IL-17, and TNF compared to healthy subjects. Canonical discriminant analyses (CDA) indicated that IP-10, IL-4, IL-17, and TNF could be useful biomarkers for infection status. In particular, our data suggest that the parallel measurement of IFN-γ and IP-10 might improve the diagnosis ofinfection in cattle in terms of sensitivity and specificity, although this should be validated on a larger set of animals. In the CDA analysis, only a modest separation between infected and affected cattle was observed. Nevertheless, our data suggested that IL-4, IL-10, and TNF might improve, at least in part, the differentiation of cattle in diverse stages of TB infection. Overall, the data generated in our study provide a foundation to improve the diagnosis and staging ofin cattle.