Mapping the risk in our genes

Posted: 15th November 2021

Dr Christina Azodi’s work to uncover how individual genetic differences lead to different health outcomes is being supported for the next three years with a Rising Star Fellowship supported by Helen and Michael Gannon.

Our genetic make-up influences how we each individually look, as well as our risk of developing a range of diseases. But with more than three billion base pairs in human DNA, the exact relationship between a person’s genes and their susceptibility to disease can be enormously difficult to pin down.

This link is clear when a condition is caused by a single genetic change, such as in Huntington’s Disease, for example. However, many common diseases – including diabetes, neurodegenerative diseases and mental health disorders – result from the combined effect of multiple changes affecting multiple genes, along with exposure to environmental factors. For these ‘complex’ disease traits, identifying the connection between genetic differences and the risk of developing a condition remains highly challenging.

Christina’s goal is to use cutting-edge genomic, statistical and data science approaches to devise and apply statistical methods that will improve our ability to map the associations between a person’s genetic make-up and their disease risk.

“Even after more than a decade of work in this field and growing genomic data repositories worldwide, we are still able to explain only about 11% of the variation in complex disease traits observed in humans,” Christina explains.

“It’s so exciting that today we can look deep inside ourselves to investigate the billions of pieces making up our individual DNA. But through these investigations, we are also generating astronomical volumes of biological data that we can potentially harness and learn from – with the right powerful and robust statistical tools.”

“My hope is that my research will help inform how genetic data is used by researchers around the world to understand a broad range of diseases. I am very grateful to the Gannon family for their support of this important work.”

For more information please see: Bioinformatics & cellular genomics