Christopher Cole is a DPhil student in the Genomic Medicine and Statistics programme at the University of Oxford. Born in London and raised in Ottawa, Chris has always been passionate about bringing genomics from bench to bedside. He began his career in this field by obtaining an Honours BSc in Biomedical Science with a specialisation in Biostatistics from the University of Ottawa.
Chris balanced academics with research during his undergraduate, publishing several first author articles and working with mentors in different areas of statistics and genetics. His main area of research was developing polygenic risk scores to predict and dissect the heritability of common diseases, though he also spent time examining the methodological basis of identifying important mutations in cohort studies. Chris has additionally worked on understanding nicotine metabolism in African American smokers, using natural language processing to categorise biomedical literature, and retrospectively inferring how genetic variation has evolved across the globe with coalescent particle filters. All of this work has been motivated by a pervading belief that there is a disconnect between the information available in the genome and that which is currently used in the fight against complex disease.
Years of declining cost and increasing availability have created the possibility of using whole genome sequencing to truly personalise medicine. Currently, care involving clinical genetics mainly focuses on sequence variation in regions which directly code for proteins. This makes interpreting the effect of a mutation relatively straightforward. However, a wealth of information is contained within the remainder of the genome, which in part serves to control and regulate gene expression and degradation. Understanding how variants in these regulatory regions may affect disease risk and prognosis is a central issue in the field of genetics.
Christopher’s current research focuses on using artificial intelligence models to understand the pathways leading to gene expression and stability. Working with his advisor Dr. Gerton Lunter he aims to address this issue by making tools to predict gene expression from an individual’s particular sequence and understand the pathways which regulate it. At each step of his career, Chris has learnt to create better and more accurate models of biology, a pursuit fostered by collaboration. AI has become a cornerstone of Canadian entrepreneurship, and Toronto especially has become a hub of innovation. Chris spent the summer after being awarded a CCSF scholarship collaborating with the Morris group at the Vector Institute in Toronto, bridging the expertise offered by both Canada and the United Kingdom. AI holds the promise to help us learn about biology, and to fight disease, but to harness its potential requires communication. Between individuals, research groups, and countries, sharing expertise is crucial for bringing the power and promise of genomics to a medical reality.
Outside of work, Chris is an avid hiker, coffee enthusiast and home baker (though the last is a work in progress).
