Beyond BMI to estimate disease risk
People with the same body-mass index (BMI) can have different distributions of body fat, which could affect heart and metabolic disease risk. To look for associations between fat distribution and disease risk, CGM PI, Amit Khera, and colleagues used deep learning models to analyze whole-body MRI images of more than 40,000 people from the UK Biobank and quantify fat volumes at three anatomical locations. Using these data, they found an association between deep belly fat and increased risk of type 2 diabetes and coronary artery disease in people with the same BMI, as well as a link between hip and thigh fat and reduced disease risk. The study shows how fat distribution can affect disease risk independent of BMI.
Read more in Nature Communications and a tweetorial from Saaket.
The Center for Genomic Medicine (CGM) comprises one of the largest and most vibrant hubs of genomic medicine research in the world. The CGM includes 46 faculty collaborating to define the ‘genomic medicine cycle’ – which envisages a genomics community seeking to advance research from basic genomics research to ultimately using genome information for diagnostics and targeted therapeutics. All of our investigators are faculty at Harvard Medical School, and many members of our community are also investigators at the Broad Institute of Harvard and MIT.
