Researchers examined over a thousand healthy adults using body and brain MRI. This approach allows for quantifying muscle mass and different types of fat, while estimating the biological age of the brain through artificial intelligence algorithms. The data comes from a study presented at the annual meeting of the
Radiological Society of North America.
The results indicate that individuals with high muscle mass and low visceral fat have a younger estimated brain age. In contrast, subcutaneous fat, located just under the skin, does not show a significant link with brain aging. This finding highlights the importance of distinguishing between types of fat to assess health risks.
Illustration image from Unsplash
The analysis combines MRI scans and artificial intelligence tools to precisely measure muscle and fat volumes. The participants, with an average age of 55, underwent magnetic resonance imaging exams at several centers. The researchers used T1 sequences to clearly visualize tissues, allowing the AI to calculate brain age from the brain's structure.
This discovery opens perspectives for targeted interventions, such as muscle preservation and reduction of deep abdominal fat. According to experts, health programs could integrate these biomarkers to monitor treatment effectiveness. The goal is to develop approaches that simultaneously improve physical condition and brain function.
Medications like GLP-1 could be adjusted to minimize muscle loss while targeting visceral fat. The researchers note that these treatments, often prescribed for weight loss, need to be optimized to avoid adverse effects on muscle mass. Future studies could use MRI to assess the impact of these therapies on the body and brain.
Taking care of one's body therefore directly contributes to maintaining a healthy brain. This connection between body shape and brain youth offers new avenues for preventing neurodegenerative diseases. Balanced lifestyle habits, combining physical activity and appropriate nutrition, seem promising for supporting overall well-being.
Colored brain figure showing an example of segmented regional volumes obtained from 3D T1 volumetric MRI scans used for brain age calculations by artificial intelligence.
Credit: Cyrus Raji, M.D., Ph.D., and RSNA Visceral fat vs subcutaneous fat: why the difference?
Visceral fat is stored deep in the abdomen, around internal organs like the liver and intestines. Unlike subcutaneous fat, which is located just under the skin, it is more metabolically active and can release inflammatory substances. These substances can circulate in the blood and affect various systems, including the brain, contributing to health problems.
Subcutaneous fat, on the other hand, is often considered less harmful because it primarily serves as an energy reserve and thermal insulator. Although an excess may be linked to aesthetic or joint problems, its impact on metabolic and brain health seems less direct. Studies show that it is visceral fat that is associated with an increased risk of cardiovascular diseases and cognitive disorders.
This distinction explains why reducing visceral fat is a priority for improving overall health. Factors such as diet, physical exercise, and stress influence the accumulation of this type of fat. For example, regular activity that combines strength training and cardio can help decrease visceral fat while preserving muscle mass.
Understanding these differences allows for targeting interventions to optimize benefits for the body and brain. By focusing on reducing visceral fat, one can not only improve body shape but also support healthy brain functions, thereby reducing long-term risks.
Brain age: a measure of brain health
Brain age is an estimation of the biological age of the brain, calculated from images obtained by structural magnetic resonance imaging. Unlike chronological age, which simply corresponds to the number of years since birth, brain age reflects the health status and functioning of brain tissues. Artificial intelligence algorithms analyze parameters like the volume of different brain regions to determine this age.
This measure allows for identifying deviations from the expected age, which may indicate an increased risk of developing certain conditions, such as Alzheimer's disease. For example, a brain that appears older than the person's actual age could signal accelerated aging processes. Researchers use this information to study factors that influence brain health over time.
Thus, brain age serves as a diagnostic and monitoring tool in medical research. It helps assess the effectiveness of interventions aimed at slowing cognitive decline. By linking this measure to other body biomarkers, such as muscle and fat composition, we can better understand the interactions between the body and the brain.
This approach paves the way for personalized strategies to promote healthy aging. By regularly monitoring brain age, it becomes possible to adapt lifestyles and treatments to maintain optimal brain function throughout life.