AMRA Medical Announces Its Technology Has the Ability to Predict the Occurrence of Coronary Heart Disease and Type 2 Diabetes

A new publication in Obesity journal contains groundbreaking data fromAMRA Medical on its ability to predict the occurrence of disease in individual patients based on real-world evidence from the UK Biobank. Individualised data can be used to create virtual control groups and deeply enrich the patient populations selected in a clinical trial.

AMRA utilized medical data from 10,019 participants in the UK Biobank imaging sub-study. Advanced imaging analysis techniques were applied to the magnetic resonance imaging (MRI) data and body composition profiles, containing visceral and abdominal subcutaneous adipose tissue, muscle fat infiltration, and liver fat were analyzed for each participant. Algorithms were applied to calculate individualized Coronary Heart Disease (CHD) and Type 2 Diabetes (T2D) propensities, or natural inclination, towards these diseases. In addition, the research explored how, in the clinically relevant areas of obesity and non-alcoholic fatty liver disease (NAFLD), metabolic disease phenotypes can be identified to describe an individual’s inclination towards CHD and T2D.

AMRA Medical’s CEO, Eric Converse, sees virtual control groups and sub-phenotyping as key milestones for clinical trial optimization and the company’s precision medicine growth: “Individualized phenotyping and disease prediction are the Holy Grail in medicine. A person’s body weight, waist circumference and general appearance may seem ideal. However, our research shows that AMRA analytics taken from a simple MRI scan tells you so much more about what’s going on inside the body and what disease propensities may be lurking. Quite simply – ‘don’t judge a body by its cover.’”

UK Biobank’s Principal Investigator, Professor Rory Collins agrees:
“UK Biobank’s success has allowed us to ask a lot more of our half a million volunteer participants – including inviting them to have full body scans. We have scanned almost 40,000 people and aim for 100,000. It is clear that these pictures are providing incredibly important information to a wide range of scientists who are getting on with the business of improving health. This new work, linking fat distribution and heart health, is based on just 10,000 images. Imagine the power of ten times that number of scans, which we will have in a few years’ time, to improve diagnosis and treatment of disease. We are very grateful to our participants for giving up their time to help create this exciting resource.”

Read the paper: Sub‐phenotyping Metabolic Disorders Using Body Composition: An Individualized, Nonparametric Approach Utilizing Large Data Sets