Researchers develop new diagnostic tool for Huntington’s disease

Hd Shutterstock Kateryna Kon

Researchers have developed an algorithm that could be used to improve diagnosis of Huntington’s and other neurodegenerative diseases. The study, led by Prof Vincent Dion (UK DRI at Cardiff) is published in the journal NAR Genomics and Bioinformatics.

Huntington’s is a progressive, neurodegenerative disease caused by a mutation in the HTT gene, where a segment of the DNA sequence (CAG) is repeated multiple times, resulting in the production of an abnormally long version of the Huntingtin protein. The elongated protein is cut into small, toxic fragments which clump together and build up in the brain, causing cells to die.

The number of repeats in a person’s HTT gene impacts the age at which their disease starts – the more repeats, the earlier the onset of disease. Current technology allows researchers to sequence the DNA of people who have this type of gene mutation, but it is difficult to quantify exactly how many times the segment is repeated.

Prof Vincent Dion explained:

“We have essentially been using the same diagnostic methods for a very long time now, and consequently, trying to predict exactly when someone will develop the disease is not possible at the moment.”

Prof Dion and team developed an algorithm, known as Repeat Detector, that accurately counts the number of repeats present in the DNA of individuals with Huntington’s and other expanded repeat disorders. The algorithm is applied to data produced from genetic sequencing.

The advantage of our algorithm is that we can apply it to lots of different disease loci, meaning it can be used to measure the number of DNA repeats in nearly 40 different diseases, and it can be used across different sequencing platforms too, so it’s very versatile. Prof Vincent Dion, Group Leader at the UK DRI at Cardiff

Importantly, the algorithm can also identify interruptions in the repeat tract – for example, in Huntington’s disease, 95% of patients will have a CAA interruption in their HTT gene, after the CAG repeat.

Prof Dion explained:

“If someone doesn’t have an interruption, they will have an earlier age of disease onset than you would expect based on the number of repeats in their gene, and conversely if they have multiple interruptions, this shifts the disease onset to later than you would expect based on their repeat size.

Classic diagnostic tests are totally blind to this, and other algorithms can only identify an interruption if you know that one is present. With Repeat Detector, you can set it up so it identifies that there is an interruption, and exactly what kind of interruption is present.”

Repeat Detector is freely available for others to use. Currently, it can be applied to pre-clinical work, and the team plan to use it to test the safety of gene editing – where technology is used to remove the large, repeated sequences. The researchers hope the algorithm could be used to improve diagnosis in the clinic in future.

To find out more about Prof Vincent Dion’s work, visit his UK DRI profile. To stay up to date on the latest research news and Institute updates, sign up to receive our monthly newsletter, ‘Inside Eye on UK DRI'.

Reference: Taylor A, Barros D, Gobet N, Schuepbach T, McAllister B, Aeschbach L, Randall E, Trofimenko E, Heuchan E, Barszcz P, Ciosi M, Morgan J, Hafford-Tear N, Davidson A, Massey T, Monckton D, Jones L, network RH, Xenarios I, Dion V. Repeat Detector: versatile sizing of expanded tandem repeats and identification of interrupted alleles from targeted DNA sequencing. NAR Genom Bioinform. 2022 Dec 5;4(4):lqac089.

Article published: 9 December 2022
Banner image: Shutterstock/Kateryna Kon