From multifunctional genes to more precise use of medicines
A single gene or protein can have several functions for the organism, for example aspects as different as height, vision and heart function or eczema and mental impairments.
The phenomena is known as pleiotropy and it may also contribute to some of the adverse drug reactions we see in patients. Associate Professor Alexander Hauser has received a grant of 6.2 mill DKK from DFF’s Sapere Aude Research Leader program to investigate this further. The four-year project’s title is “Pleiotropic effects — from drug targets to drug actions”.
The concept of pleiotropy is central in genetics and biology, showing how complex and interconnected genetic makeup can be. Alexander Hauser explains the purpose of his project:
“I want to elucidate if protein variability is associated with pleiotropy and want to test if pleiotropy can also explain adverse drug reactions by combining cellular assays, patient data and computational methods. Improved understanding of pleiotropy in clinically important proteins might help to identify better drug targets and open avenues for personalised medicine to prevent treatment delays or unnecessary side effects.”
Proteins are basic drug targets
The most common drug targets are GPCRs, G protein-coupled receptors. Some GPCR-genes are involved in many different processes in the body, and the team will investigate how this may contribute to unwanted side effects, compared to genes with more unique functions. The group of researchers will also investigate how patients with differently regulated drug targets or mutations react in different ways to the same drug. This can help better select treatment options based on the individual’s DNA and to design drugs fit for purpose in the future.
Biobanks often contain genetic data from DNA sequencing of hundreds of thousands of individuals and linking this genetic data with disease history or medication use creates a new opportunity to understand how our genetic variability affect us in health and disease. To utilize this vast amount of data, the researchers will apply sophisticated computational methods to investigate how this data can be used for designing more personalized treatments for individual patients.