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.