New research demonstrates correlations between high adiposity body fat distribution patterns on magnetic resonance imaging (MRI) and neurological impacts ranging from extensive gray matter atrophy to accelerated brain aging.
For the study, recently published in Radiology, researchers reviewed brain, cardiac and abdominal MRI data for 25,997 participants (mean age of 55). Employing latent profile analysis (LPA) to help assess body fat distribution patterns, the study authors identified six body fat distribution profiles.
The researchers found that the pancreatic predominant profile with elevated pancreatic proton density fat fraction and the skinny fat profile with an elevated weight-to-muscle ratio (and the highest adiposity burden among the different profiles) were associated with significantly higher volume of white matter hyperintensity and more pronounced gray matter atrophy in comparison to the other body fat distribution profiles.
The pancreatic predominant profile and skinny fat profiles were also correlated with the lowest global cognitive scores, according to the study authors.
“ … Our findings highlight the pancreatic-predominant adiposity and skinny-fat patterns as high-risk phenotypes for brain abnormalities. The association between pancreatic adiposity and structural brain alterations provides, to our knowledge, the first comparative evidence across adiposity patterns supporting pancreatic ectopic fat as a potential marker of neurodegeneration,” noted lead study author Miao Yu, M.D., who is affiliated with the Department of Radiology at the Affiliated Hospital of Xuzhou Medical University in Xuzhou, China, and colleagues.
The study authors also determined that those with the pancreatic predominant profile had more than double the risk for stroke and the development of multiple sclerosis (MS).
Three Key Takeaways
• Fat distribution matters more than BMI alone. Pancreatic-predominant adiposity and “skinny-fat” phenotypes on MRI were strongly associated with greater white matter hyperintensity burden, more pronounced gray matter atrophy, and lower global cognitive scores, highlighting the limitations of BMI as a standalone risk metric.
• Pancreatic ectopic fat as a potential neurodegenerative marker. Elevated pancreatic proton density fat fraction emerged as a high-risk imaging phenotype, with more than double the risk of stroke and multiple sclerosis, supporting pancreatic fat as a possible biomarker of adverse brain health.
• Distinct neuropsychiatric risks in skinny-fat individuals. Despite moderate BMI, the skinny-fat profile was linked to increased risks of stroke, anxiety, and depression, underscoring the clinical relevance of MRI-based adiposity phenotyping for neurologic risk stratification.
Those with the skinny-fat profile had a 55 percent higher risk for anxiety disorders, an 89 percent higher risk for depressive episodes and a 70 percent higher risk of stroke, according to the researchers.
“ … Male participants with the skinny-fat profile, despite having a moderate BMI, exhibited elevated neurologic risk, challenging the conventional view that BMI is the primary determinant of brain health. This observation aligns with the concept of metabolically obese normal-weight individuals, who face elevated neurologic risk despite normal BMI, thereby underscoring the limitations of BMI as a standalone metric without consideration of fat distribution,” pointed out Yu and colleagues.
(Editor’s note: For related content, see “Emerging MRI Research Suggests Link Between Muscle Mass, Belly Fat and Brain Aging,” “SNMMI: What Tau PET Findings May Reveal About Modifiable Factors for Alzheimer’s Disease” and “MRI Study Demonstrates Link Between MASLD and Accelerated Brain Aging.”)
In regard to study limitations, the authors emphasized that casual relationships should not be inferred from statistical correlations between fat distribution and structural features in the brain drawn from a cross-sectional study. The researchers also noted that skewing of the cohort to an older population thwarts extrapolation of the study findings to a broader population. They also acknowledged the lack of whole-body assessment and no assessment of differentiation between white, brown and beige adipose tissue.
