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May 23, 2018

Study indicates need to analyse fat deposits for metabolic diseases

A new body composition study by Swedish digital health company AMRA has revealed the need for examining fat distribution patterns in order to gain better insights into metabolic diseases and develop treatments for them.

A new body composition study by Swedish digital health company AMRA has revealed the need for examining fat distribution patterns in order to gain better insights into metabolic diseases and develop treatments for them.

Results from more than 6,000 subjects showed that coronary heart disease (CHD) and type 2 diabetes (T2D) are associated with specific patterns of distribution.

These findings are expected to aid in future prevention and management of metabolic conditions.

“The study involved a new body composition profiling technique developed by AMRA to precisely analyse different variables to understand the associations and interactions between fat distribution, muscle volumes and metabolic status.”

AMRA CEO Tommy Johansson said: “These ground-breaking results allow a glimpse into the future where precision diagnostics will provide the backbone to personalised medicine.

“By better understanding of muscle and fat volumes, and where fat is located in the body, we hope to help redefine disease risk and suitability for treatment.

“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.”

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For the study, AMRA collaborated with Pfizer, Westminster University, Linköping University and UK Biobank.

The study involved a new body composition profiling technique developed by AMRA to precisely analyse different variables to understand the associations and interactions between fat distribution, muscle volumes and metabolic status.

During the analysis, researchers observed numerous skewed fat distribution patterns/phenotypes, which they said cannot be determined based on a single fat or muscle measurement.

These phenotypes are said to be associated with various metabolic disease profiles with some exhibiting CHD, T2D, or the co-morbidity of the two while others exhibited no metabolic disease.

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