Researchers at the Huntsman Cancer Institute (HCI) have developed a new way to interpret genetic test results. The merit is also from Bayer's Theorem, a mathematical equation dating back to 1763. The researchers used it as a basis for developing the new evaluation method.
Genetic tests are used in a wide range of areas. They range from fetal DNA tests for prenatal diagnosis to cancer treatments. Test results can help to get more precise diagnoses and develop tailor-made treatments for the individual patient. Depending on what a genetic test says, treatment for the same disease can change significantly.
One of today's big challenges is to understand which genetic variations count and which can be ignored. Over the years, in fact, thousands of VUS have accumulated, or genetic variations whose meaning is unclear. Most of these are almost certainly harmless, but many others could be decisive for the development of a disease.
In order to reduce the subjectivity of certain interpretations, the team developed an algorithm that analyzes the results of genetic tests. The tool serves to determine the risk rate that a patient develops a certain disease. To test its effectiveness, they tested it according to 18 rules recommended by the American College of Genetics and Genomics (ACMG). The results were positive and the new tool proved that it could make the diagnosis more precise.