|MAGOMBEDZE, G - Imperial College|
|SHIRI, T - University Of Warwick|
|EDA, S - University Of Tennessee|
Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/9/2017
Publication Date: 3/20/2017
Citation: Magombedze, G., Shiri, T., Eda, S., Stabel, J.R. 2017. Inferring biomarkers for Mycobacterium avium subsp. paratuberculosis infection and disease progression using experimental data. Scientific Reports. 7:44765. https://doi.org/10.1038/srep44765.
Interpretive Summary: Johne's disease is a chronic, debilitating intestinal disorder in cattle characterized by diarrhea, reduced feed intake, weight loss and death. Cattle usually become infected as young calves by ingesting feces containing the causative bacteria. However, symptoms of disease do not usually present themselves until the animals reach 3 to 5 years of age or even older. During this time the animal is infected and may be shedding the organism in its feces without showing any clinical signs of disease. In addition to reduced milk production by these animals, they also present a potential infective threat to the rest of the herd. Host immune responses to Johne’s disease are dynamic and change during the progression of disease from a latent, asymptomatic stage to a more advanced stage demonstrating symptoms listed above. Modeling the immune responses of the host during infection will help us understand how the disease progresses. This paper develops a model to explain the dynamics of the infection process in young calves and identifies specific biomarkers during infection that modulate the immune response. Understanding the host immune response to this pathogen will help us develop control measures to prevent the spread of infection.
Technical Abstract: Available diagnostic assays for Mycobacterium avium subsp paratuberculosis (MAP) have poor sensitivities and cannot detect early stages of the infection, therefore, there is need to find new diagnostic markers for early infection detection and disease stages. We analyzed longitudinal IFN- gamma, ELISA-antibody and fecal shedding experimental sensitivity scores for MAP infection detection and disease progression. We used both statistical methods and dynamic mathematical models to (i) evaluate the empirical assays (ii) infer and explain biological mechanisms that affect the time evolution of the biomarkers, and (iii) predict disease stages of 57 animals that were naturally infected with MAP. This analysis confirms that fecal test is the best marker for disease progression and illustrates that Th1/Th2 assays are important for infection detection, but cannot reliably predict persistent infections. Our simulated results show that a macrophage-based assay is a good diagnostic marker for MAP persistent infections and predictor of disease specific stages.