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A Mathematical Explanation For Precision Of Trinucleotide Hereditary Diseases

Scientists at the Weizmann Institute have proposed a mechanism which explains the precision of prognoses for trinucleotide repeat diseases. The study, published on November 23 in the journal PLoS Computational Biology, may lead researchers in the direction of a possible prevention or cure.

Based on the literature on some twenty known trinucleotide repeat diseases and their knowledge of the mechanisms governing somatic mutation, the team has proposed a mechanism that explains the precise relations between the patient's age of onset and the number of repeats in the diseased gene in the patient's genome. Using computer simulations and mathematical analysis of the mechanism the scientists have characterized the way in which the disease progresses.

Trinucleotide hereditary diseases are known as “time bomb” diseases, as people who live with them have a predictable onset of suffering and eventual death in adulthood. These diseases are caused by an unusual genetic mutation: A three-letter piece of gene code is repeated over and over in one gene. Scientists can predict by how many times the sequence repeats in a patient's gene both the age at which the disease will appear and how quickly the disease will progress.

The basic assumption has been that the protein fragment containing the amino acid (glutamine) encoded in the repeating triplet slowly builds up in the cells until eventually reaching toxic levels. This theory, unfortunately, fails to explain some of the clinical data.

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The Weizmann Institute scientists, led by Ehud Shapiro, show that the answer lies in somatic mutations – changes in the number of DNA repeats that build up in our cells throughout our lives. The longer the DNA sequence, the greater the chance of additional mutation. The scientists realized that the genes carrying the disease code might be accumulating more and more DNA repeats over time, until some critical threshold is crossed.

These findings suggest that a cure for all might be found in a drug or treatment that slows down the expansion process, if researchers are successful in using this new model.

Andrew Hyde | alfa
Further information: 10.1371/

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