Home Stretch | Searching systematically in the DNA

In many cases of hereditary disorders, the exact location of the ‘error’ in the DNA remains unclear. This is also true for patients who suffer from a genetic defect that leads to a high level of cholesterol. By using algorithms and models, Biomedical Engineering graduate student Manon Balvers made it possible for a computer to search DNA for variants that cause abnormal cholesterol metabolism.

Hereditary disorders are caused by an abnormality - mutation - in the genes, which are made up of DNA strings that contain our genetic material. An example of such a genetic effect is familial hypercholesterolemia (FH), a condition characterized by a high level of cholesterol in the blood caused by a genetic disorder. As a result, patients develop an elevated risk of cardiovascular disease and cerebral infarction at an early age.

In some cases of a hereditary disorder, it’s possible to detect the cause in a specific DNA mutation, but FH shows a very complex genetic pattern. Over nine hundred mutations capable of disrupting the cholesterol transport have been found already. Nevertheless, there is a group of patients whose genetic defect still remains unclear.


That is why Biomedical Engineering master’s student Manon Balvers - “detective work makes me happy” - sat down at her computer and tried to systematically screen DNA in search of missing defects using a new method. Successfully so, Balvers says enthusiastically. “Bioinformatics - which basically means using computers to solve biological problems - has received more and more attention in the field of genetic research in recent years. With its four letters, DNA lends itself perfectly to a systematic approach to finding variants. But because it is such a new field, bioinformatics is still in an exploratory phase. Researchers all have their own approach and use their own tools to select mutations. I have tried - in cooperation with Amsterdam UMC - to combine some of these methods, and we have already managed to find a considerable number of risk defects with new hypotheses and the use of the most recent algorithms.”

Important non-code

Besides this method, the location of the mutations found by Balvers proved to be interesting as well. DNA is made up of components that encode for the production of proteins, but also of noncoding components, known as introns. These introns are cut out before protein production starts. Scientists who conduct research on hereditary disorders investigate the coding DNA, which is important for the production of proteins. But Balvers’s research - which covered the DNA in its entirety - showed that mutations can also be found in the part that is cut out. “We believe that these introns determine how the DNA component is cut out, and therefore determine the remaining code as well. Research on other hereditary disorders now also focusses on introns. The non-code turns out to be more important than expected.”

The possible defects Balvers was able to find using models and algorithms are now being studied further. Blood was taken from the FH patients in question once again and is now examined for a faulty code conversion. “If these predictions are correct, we will be able to correctly diagnose patients at a very early stage. New tools and algorithms appear at a rapid pace, which will lead to more accuracy.”

Balvers continues: “Of course, we still need to conduct tests with much larger data sets that will eventually lead to standardized protocols, but this certainly is a great first step forward that shows that a systematic approach can be successful. Research on other complex genetic diseases will benefit from this as well.”

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