University of Cambridge researchers have discovered what appears to be a transformative method of identifying mutations linked to genetic disorders. 

Neurodegenerative disorders such as Huntington’s disease or forms of amyotrophic lateral sclerosis affect around one in 280 people worldwide. Of that number, scientists note that it goes undiagnosed in as many as 90% of cases. 

These diseases are linked to abnormal repetitions within genetic material, which have multiplied far beyond their normal length. This can result in the interruption of cellular function and the triggering of repeat expansion disorders. 

As part of an international effort to form a fast and affordable test for these disorders, scientists at the University of Cambridge have discovered a technique which has been dubbed “RNA origami”. 

The technique works by unfolding ribonucleic acid (RNA) molecules, responsible for genetic transfer, into measurable structures by linking them with DNA. These structures are then analysed by nanopores, tiny sensors capable of telling the difference between healthy and diseased strands.  

“Current techniques were designed for DNA, so they often lose the information in RNA that signals disease. We wanted to fix that,” said Gerardo Patiño-Guillén, postdoctoral pathway fellow at Cavendish Laboratory and lead author of the study. 

Thanks to the promising results, the team are hoping to expand into patient trials, with a spin-out company responsible for further developing the technology. Cambridge Nucleomics, co-founded by senior author and professor of applied physics Ulrich Keyser, is currently developing the method into a diagnostics platform. 

While researchers are cautious whether this new technique will replace the standardised polymerase chain reaction (PCR)-based diagnostic tests, it represents a notable step forward in technological capabilities in providing more detailed information about disease-associated RNA.

“We’re confident about what it can do in controlled samples. The next challenge is proving it works just as well in clinical material”, said Patiño-Guillén.