MRI Study Identifies Two Hidden Fat Patterns Tied to Accelerated Brain Aging

A new study published in Radiology, the flagship journal of the Radiological Society of North America (RSNA), reveals that the effect of obesity on brain health may depend as much on where fat is stored in the body as on how much fat is present overall.

Researchers from The Affiliated Hospital of Xuzhou Medical University in China used MRI data from 25,997 participants in the UK Biobank to examine how specific fat distribution patterns relate to brain aging, cognitive decline, and risk of neurological disease. They identified two previously unrecognized fat profiles that appear to carry heightened risks: a “pancreatic predominant” type, marked by high fat accumulation in the pancreas, and a “skinny fat” type, characterized by a high fat burden despite relatively average body weight.

According to study coauthor Kai Liu, M.D., Ph.D., associate professor of radiology, the team leveraged MRI’s ability to quantify fat in internal organs to develop a data-driven classification system. This approach revealed two distinct phenotypes that had not been fully described before but are now shown to correlate with adverse neurological outcomes.

Individuals with the pancreatic predominant profile exhibited a proton density fat fraction—an MRI-based marker of tissue fat—of around 30 percent in the pancreas. This level is two to three times higher than other fat distribution categories and can be up to six times higher than in lean individuals. Interestingly, these individuals did not have significantly elevated liver fat, highlighting pancreatic fat as a potentially overlooked risk marker. Liu noted that while radiologists frequently identify fatty liver, the presence of excess pancreatic fat may present a greater risk to brain health and should be recognized as a distinct and clinically relevant finding.

The second pattern, described as “skinny fat,” was observed in individuals who carried high fat across much of the body, especially in the abdomen, but had relatively low fat in the liver and pancreas. These individuals did not typically meet the standard image of obesity; in fact, their average BMI ranked only fourth among the categories examined. However, they had disproportionately high fat-to-muscle ratios, particularly in men, which may help explain their elevated health risks.

Both fat distribution types were significantly associated with gray matter atrophy, signs of accelerated brain aging, and cognitive decline. The study found these effects in both men and women, although with some sex-specific variations. While the research centered on neurological impacts, the team noted that further studies are needed to understand how these fat distribution patterns might affect cardiovascular and metabolic health as well.

Dr. Liu emphasized that these findings could help healthcare providers offer more personalized risk assessments and interventions. Body mass index and general fat measurements may not fully capture a patient’s true risk if fat is stored in areas that pose more direct threats to brain health.

“Brain health is not just a matter of how much fat you have,” Liu said, “but also where it goes.”