Scientists make Johne’s disease diagnosis breakthrough

A novel approach to diagnosing Johne’s disease could have a transformative impact on the fortunes of UK farmers, researchers have said.

A preliminary study by scientists from MI:RNA Diagnostics and Scotland’s Rural College (SRUC) discovered that MicroRNA (miRNA) profiling, analysed via advanced predictive modelling, can detect the disease earlier and more reliably than current diagnostic methods.

The chronic condition, which affects cattle and other ruminants, is said to cost the UK agricultural economy £10 million each year, but researchers believe this “promising” new diagnostic approach will reduce the number of animals lost.

Prevalence

Due to the presence of “silent” carriers, Johne’s disease is said to frequently go undiagnosed, with a prevalence of up to 50% within UK herds.

It is estimated to cost UK farmers £200 per cow annually, which can be up to half of their profit each year.

MiRNAs control the production of proteins within cells and are vital to gene regulation.

Researchers investigated expression levels (gene activity) within these biomarkers in samples from infected and uninfected cattle and analysed the data using advanced statistical and machine learning (AI) methods.

Detect patterns

The machine learning is said to be able to analyse results quickly and detect patterns in the data that traditional diagnosis methods miss, as well as provide predictive modelling for infections.

The scientists said this diagnostic approach could also be used to identify other diseases within animals, but increased sample sizes will be required in further studies to improve the precision of their diagnoses and further validate their findings.

MI:RNA Diagnostics founder and chief executive Eve Hanks said: “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.”

SRUC’s Spiridoula Athanasiadou said the study “demonstrates potential for added benefits of the new tool,” adding: “Upscaling is important for wider implementation and further development.”