Link between patterns of fat distribution and metabolic diseases

Specific patterns of fat distribution are linked to the presence of Coronary Heart Disease (CHD) and Type 2 Diabetes (T2D), according to a new study published in Obesity. AMRA has announced the results of a body composition study of over 6,000 subjects, stressing the need to measure and investigate several fat compartments in order to understand and develop treatments for multiple metabolic diseases.

The Obesity study was co-authored in collaboration between AMRA, Pfizer, Westminster University, Linköping University, and UK Biobank. The 6,000 subjects analysed are part of the UK Biobank Imaging Study, a major national and international health resource. In 2015, UK Biobank announced that AMRA would perform the automated analysis of MRI images for precise fat and muscle measurements. AMRA has now developed the technique of body composition profiling, which allows for precise analysis of multiple variables to describe the complex associations and interactions between fat distribution, muscle volumes, and metabolic status.

“Our vision is that, in the future, our research and technology will be used to assist in the improved prevention, diagnosis, and treatment of a wide range of diseases.”

Regardless of normal, overweight, or obese BMI class, AMRA’s body composition profiling of the subjects revealed a number of skewed fat distribution patterns, or phenotypes, that cannot be described when looking at a single fat or muscle measurement. These phenotypes are associated with different metabolic disease profiles: some exhibit no metabolic disease, while others exhibit CHD, T2D, or the co-morbidity of the two.

Dr Olof Dahlqvist Leinhard, senior author of the study, commented, “by using a multivariable approach and an intuitive visualization of body composition, we’ve been able to identify a wide range of body composition profiles that could provide the link to increased risk of metabolic diseases.”

Tommy Johanson, Chief Executive Officer of AMRA, added, “Our vision is that, in the future, our research and technology will be used to assist in the improved prevention, diagnosis, and treatment of a wide range of diseases.”