New study reveals link between specific fat distributions and metabolic diseases
Biomedical Sciences 24 May 2018
While increased visceral fat, liver fat, and muscle fat infiltration have separately been linked to a number of conditions, such as cardiovascular disease, Type 2 diabetes, and hepatocellular carcinoma in previous research, this study stressed the importance of a multivariable approach, linking different metabolic diseases to different fat distributions.
Over 6,000 participants from the UK Biobank, a major national and international health resource, took part in the study and their body composition profiles were calculated including thigh muscle volume, liver fat and muscle fat infiltration, among other factors, determined by using magnetic resonance imaging.
Regardless of normal, overweight, or obese BMI class, AMRA’s body composition profiling of the subjects revealed a number of skewed fat distribution patterns that cannot be described when looking at a single fat or muscle measurement.
These patterns are associated with different metabolic disease profiles: some exhibit no metabolic disease, while others exhibit Coronary Heart Disease, Type 2 Diabetes, or the presence of the two. Specifically, higher visceral fat and muscle fat was associated with Coronary Heart Disease and Type 2 Diabetes while higher liver fat was associated with Type 2 Diabetes and lower liver fat with Coronary Heart Disease. These associations remained significant when adjusting for sex, age, BMI, alcohol, smoking, and physical activity.
Dr Louise Thompson, who was part of the research project, said: “For many years Jimmy Bell and myself have been involved in the development and implementation of MRI scanning techniques that will allow us to understand the impact of lifestyle, genetics and the environment on body fat content and distribution in both health and disease.
“Our close involvement with the UK Biobank imaging study and longstanding collaboration with AMRA have enabled us to scale up this research to provide remarkable new insights into the interplay between disease risk and body composition phenotypes.”
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