A BREAKTHROUGH in early detection of a common disease in cows could save farmers in the UK millions of pounds.
Johne’s disease costs an estimated £200 per cow per year, which can amount to a whopping 50% of a farmer’s annual profit.
However, a unique diagnostics approach from pioneering scientists at MI:RNA could transform the way the disease, which costs the UK agricultural economy £10m annually, is managed.
An inflammatory condition which primarily affects sheep and cattle, Johne’s disease spreads easily through herds impacting the health, welfare and productivity of livestock, with a prevalence of up to 50% within herds in the UK.
The limitations of current diagnostic tests exacerbate the difficulty of managing Johne’s disease, which often goes undiagnosed due to “silent” carriers of the disease.
Traditionally, screening and removal of animals affected by the disease was common practice to manage Johne’s disease.
However, a new and promising approach for developing novel and reliable diagnostics will allow the disease to be identified earlier, reducing the number of cows lost to the disease, and paving the way for new treatments.
MicroRNAs (miRNAs), which control the proteins that cells produce, are found in most eukaryotes (organisms with cells containing a nucleus) and play critical roles in gene regulation.
MicroRNAs are valuable biomarkers, which capture what happens in cells, due to their stability and ease of detection in fluids.
Studies show that miRNA expression levels (the levels of gene activity) change during bacterial infections, including early-stage Mycobacterium avium subspecies paratuberculosis (MAP).
Diagnostic accuracy, which is the ability to distinguish between healthy samples and samples with the disease, can be enhanced with advanced statistical and machine learning (AI) methods.
These tools analyse data quickly, detect patterns missed by traditional methods, and provide predictions about infections.
A preliminary study by MI:RNA Diagnostics and SRUC scientists investigated the use of miRNAs profiling for diagnosing Johne’s disease by measuring miRNAs expression in samples from MAP-infected and uninfected cattle.
The data was analysed using machine learning to develop an optimal method of disease diagnosis.
The study found that miRNA profiling, along with advanced predictive modelling, has the potential to be utilised as a test for diagnosing Johne’s disease in cattle.
Due to the small sample size of the study, future efforts will increase the sample size to further validate findings and improve precision.
There is also the possibility of differentiating between animals with alternative pathogens through MI:RNA Diagnostics methods.
Eve Hanks, founder and CEO at MI:RNA Diagnostics, said: “Animal health is more important than ever, with Johne’s disease costing farmers tens of millions around the UK each year.
“For MI:RNA this is a key area of research and development. Biomarker science combined with our AI-powered modelling, means that we can significantly improve animal health, reduce financial strain on farmers, while also reducing greenhouse gas output as a result.
“We believe miRNAs can assist with progressing future diagnostic testing and understanding diseases more effectively.”
Professor Spiridoula Athanasiadou, SRUC, said: “SRUC has been at the forefront of Johne’s disease control via the Premium Cattle Health Scheme for over 25 years and is in support of research that feeds into practice.
“At SRUC we value our ongoing collaboration with MI:RNA Diagnostics, which has generated data that demonstrates potential for added benefits of the new tool.
“Upscaling is important for wider implementation and further development.”
