Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning
“Medical imaging data has great potential for better understanding health and disease, aiding earlier diagnosis and improving health outcomes. It is excellent to see UK Biobank data being put to use for cutting edge technology development.” Dr Peter Broomfield, FCC’s Head of Policy and Research
Researchers in the US and UK have conducted the largest-ever study of its kind using abdominal MRI scans in the UK Biobank and deep learning. They are:
Yi Liu , Nicolas Basty, Brandon Whitcher , Jimmy D Bell , Elena P Sorokin , Nick van Bruggen , E Louise Thomas, Madeleine Cule. Calico Life Sciences LLC, South San Francisco, United States; Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom
In a recently published paper they wrote in their abstract:
“Abstract Cardiometabolic diseases are an increasing global health burden.
“While socioeconomic, environmental, behavioural, and genetic risk factors have been identified, a better understanding of the underlying mechanisms is required to develop more effective interventions.
“Magnetic resonance imaging (MRI) has been used to assess organ health, but biobank-scale studies are still in their infancy.
“Using over 38,000 abdominal MRI scans in the UK Biobank, we used deep learning to quantify volume, fat, and iron in seven organs and tissues, and demonstrate that imaging-derived phenotypes reflect health status.
“We show that these traits have a substantial heritable component (8–44%) and identify 93 independent genome-wide significant associations, including four associations with liver traits that have not previously been reported.
“Our work demonstrates the tractability of deep learning to systematically quantify health parameters from high-throughput MRI across a range of organs and tissues, and use the largest-ever study of its kind to generate new insights into the genetic architecture of these traits.”
Dr Peter Broomfield, FCC’s Head of Policy and Research, said:
“Medical imaging data has great potential for better understanding health and disease, aiding earlier diagnosis and improving health outcomes. It is excellent to see UK Biobank data being put to use for cutting edge technology development.”
FCC has worked on developing a value framework for medical imaging datasets in research and product development with NCIMI (the National Consortium for Intelligent Medical Imaging). Read it here.