A population-based investigation of the body-brain link

This lay summary is based on a paper by Gurholt et al (2021), published open access in Translational Psychiatry. 
D.O.I https://doi.org/10.1038/s41398-021-01414-7

Cardiometabolic risk factors – including obesity – are related to mental illness and observed brain structure differences, in addition to the more well-known associations with a higher risk of encountering adverse health outcomes such as heart attack, stroke, non-alcoholic fatty liver disease, and type 2 diabetes. However, we don’t know a lot about the details, such as which brain regions relate to which aspects of cardiometabolic risk factors, nor do we know whether mental illness relates to individual variations in body composition such as body fat distribution. Gurholt and colleagues recently addressed this knowledge gap to understand better how body fat is related to brain structure.

Conventional body fat indicators such as body mass index (BMI) are blunt tools that do not provide detailed information about individual body compositions. Waist-to-hip ratio and waist circumference are better indicators of cardiometabolic risk than BMI because they are better measures of body fat around the abdomen and are not influenced by muscle weight. However, these conventional measures (e.g., BMI) are still unable to provide detailed information on body fat distributions in different types of body tissue. It is important to obtain detailed information on body fat distribution as different distribution patterns may hold different levels of cardiometabolic risk. For example, ectopic fat, stored in locations that should not typically have fatty tissue, such as around the organs and in the liver, cannot be measured on the body’s surface. Yet, it carries a higher cardiometabolic risk than the subcutaneous fat situated right under the skin.

Gurholt and colleagues used magnetic resonance imaging (MRI) to study the relationship between brain regions and conventional body fat indicators (i.e., BMI, waist-to-hip ratio, waist circumference) and specific measures of body fat and muscle tissue from body MRI such as visceral abdominal fat, fat in the liver, and muscle fat infiltration. They used a large sample of nearly 25,000 participants from the UK Biobank (http://www.ukbiobank.ac.uk), a vast dataset containing physical and mental health information about hundreds of thousands of UK participants. In the current study, all participants had provided brain MRIs, and nearly 5,000 participants also had available body MRIs.

What the researchers found was a complex picture with many body-brain relationships. Higher body fat levels were generally associated with reductions in the cerebral and cerebellar cortex – that is, in the outer layer of both the largest part of the brain and the “little brain”. This pattern was similar whether the researchers used the conventional body fat indicators (e.g., BMI) or the more specific body fat measures from body MRI (e.g., liver fat). Furthermore, for a muscle tissue measure from body MRI, the researchers observed a contrasting pattern across the cerebral cortex relative to the pattern observed for the body fat measures. These findings are essential in learning more about the connections between the brain and body fat and muscle tissue. However, because the study used information collected at a single time point, we can’t determine what direction the effects are going: that is, whether the brain is influencing the body, the body is influencing the brain, the connections are reciprocal, or the same genetic mechanisms influence both. The patterns observed by the researchers are likely due to a mixture of all these effects and more. Future work will build on what has been found in the present study to investigate the underlying mechanisms in more detail.

The study by Gurholt and colleagues was the first to use such a large sample size to examine relationships between the brain and conventional indicators of body fat and measures of body composition from body MRI. Their work suggests the existence of many associations of small effect size linking numerous brain regions with body fat and muscle composition. Indeed, their work provides a foundation for understanding the underlying mechanisms that link mental illness with obesity, other cardiometabolic risk factors, and cardiovascular disease, which may form the foundation for developing new prevention strategies for disorders of the body and the brain.

This study is the first body-brain imaging study of the CoMorMent project. Building large samples such as the UK biobank and register data, researchers of the CoMorMent project will soon be able to examine brain imaging data of more than 100,000 individuals and population datasets with genotype information from up to 1.8 million individuals. These unprecedented datasets will form the foundation for novel discoveries of the role of cardiometabolic factors in mental illness.


Published Dec. 7, 2021 12:07 PM - Last modified Dec. 7, 2021 12:07 PM