A University of Queensland researcher is combining genetics and statistics to shed new light on conditions such as coronary heart disease, asthma and diabetes.
Professor David Evans who is Head of the Genomic Medicine program at The University of Queensland Diamantina Institute, based at the Translational Research Institute (TRI), says the new perspective could play an important role in better identification of causative genes.
The method will better assist scientists understanding of the common complex genetic influence on a number of different conditions.
“Traditionally we’ve looked at the relationship between disease and the human genome one gene at a time,” said Professor Evans.
“Whilst this strategy has been relatively successful, typically the effect of a single gene is quite small, meaning that there are many unknown biological pathways involved in the development of disease.”
The new method combines the effect of several genes that are already known to affect a pathway and determines whether this combination of genes is related to the disease.
Looking at several genes together means researchers might be able detect effects on disease previously unable to be identified by examining single genes one at a time.
“The really exciting implication of the work is that because we now have the technology to measure hundreds of thousands of biological molecules, we can use this approach to screen thousands of these biological pathways for their involvement in hundreds of different diseases, using data that is already available in the scientific community,” said Professor Evans.
This new strategy could revolutionise how researchers identify genes involved in disease causation, allowing for hundreds of thousands of biological pathways to be screened quickly and inexpensively.
“The method is extremely simple - it’s just a shift in perspective,” Professor Evans says.
“This is the next logical step in using genetic technologies to understand how diseases develop, and it will hopefully assist in creating improved treatments for these diseases in the future.”
The paper was published in Public Library of Science Genetics.