🧠 neurology

Elevated HbA1c is associated with advanced brain age in severe obesity

In a study of adults with severe obesity, elevated HbA1c levels were significantly associated with accelerated brain aging, whereas other cardiometabolic risk factors such as BMI, hypertension, and hyperlipidemia showed no such association.

Original authors: Juhasz, J., DeFeis, B., Britton, M. K., Hoogerwoerd, H., Worwag, K., Johnson, K. J., Uribe, A., Williamson, J. B., Porges, E. C., Cohen, R. A.

Published 2026-06-06

📖 3 min read☕ Coffee break read

CC BY 4.0

Original authors: Juhasz, J., DeFeis, B., Britton, M. K., Hoogerwoerd, H., Worwag, K., Johnson, K. J., Uribe, A., Williamson, J. B., Porges, E. C., Cohen, R. A.

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Imagine your brain has a "biological clock" that ticks at its own pace, separate from the calendar on your wall. Scientists can now look at an MRI scan of your brain and use a smart computer program to guess how old your brain feels biologically. This is called "brain age."

If your brain feels 10 years older than your actual age, that's a big red flag. It's like driving a car that has only 50,000 miles on the odometer but the engine is already sputtering like it has 150,000 miles. This "gap" between your real age and your brain's age is linked to memory problems and a shorter lifespan.

The Big Question
The researchers wanted to know: In people who carry a lot of extra weight (severe obesity), does having high blood sugar make this brain clock tick faster? We already know that things like high blood pressure, high cholesterol, and high blood sugar are bad for the heart and brain in the general population, but this specific group hadn't been studied much.

The Experiment
The team took MRI scans of 97 adults with severe obesity (ranging from a BMI of 35 to 73). They used two different "smart calculators" (called ENIGMA and Pyment models) to estimate each person's brain age. Then, they checked the participants' blood sugar levels (HbA1c), body weight, blood pressure, and cholesterol to see which one was the biggest culprit for making the brain age faster.

What They Found
The results were like finding a specific key that fits a lock:

The Sugar Connection: The study found a clear link between high blood sugar and an "older" brain. Think of HbA1c as a measure of how much sugar is stuck in your blood over time. The higher the sugar, the older the brain looked on the scans. It was as if high sugar was rusting the gears of the brain's clock, making it run faster than it should.
The Weight Surprise: Surprisingly, the actual amount of extra weight (BMI) didn't seem to make the brain age faster in this group. Neither did high blood pressure or high cholesterol.
- Why? The researchers suggest this might be because everyone in the study was already quite heavy. It's like trying to see if adding more water to a bucket that is already full makes a difference; since everyone started with a "full bucket" of weight, the differences in weight didn't stand out. But the sugar levels varied enough to show a clear effect.

The "Prediabetic" and "Diabetic" Clues
When the researchers broke the group down, the effect was even stronger for those with "prediabetes" or full-blown diabetes. In these groups, the brain age gap was even wider, suggesting that once blood sugar crosses a certain threshold, the "rusting" of the brain accelerates noticeably.

The Bottom Line
In simple terms, for people with severe obesity, high blood sugar is the main driver making their brains age faster than their actual years. While carrying extra weight is a major health concern, this specific study suggests that in this group, it's the sugar in the blood—not the weight itself—that is most strongly linked to an "older" brain. The other factors like blood pressure and cholesterol didn't show a direct link to brain aging in this particular group, likely because the study focused on a specific range of body weights where those factors were less variable.

Technical Summary: Elevated HbA1c is Associated with Advanced Brain Age in Severe Obesity

Problem Statement
Brain-predicted age, derived from structural MRI data via machine learning, serves as a biomarker for biological brain aging. A larger brain age gap (BAG)—the difference between predicted and chronological age—signifies advanced brain aging and correlates with cognitive decline and mortality. While cardiometabolic risk factors such as elevated blood glucose, body mass index (BMI), blood pressure, and cholesterol are known to increase the risk of cognitive impairment and dementia in the general aging population, their specific relationship with BAG in individuals with severe obesity remains poorly characterized. This gap is critical given the high prevalence of cardiometabolic comorbidities within the severe obesity population.

Methodology
The study analyzed T1-weighted MRI data from 97 adults with severe obesity (BMI range: 35–73 kg/m²). Brain age was estimated using two distinct machine-learning models: the ENIGMA consortium model and the Pyment model. The primary objective was to examine associations between BAG and four cardiometabolic variables: HbA1c, BMI, hypertension, and hyperlipidemia.

Statistical analysis employed multiple linear regression and MM-estimation robust regression to mitigate the influence of outliers. All models were adjusted for potential confounders, including age, sex, and race. Furthermore, post hoc analyses stratified the sample based on clinical HbA1c cutoffs to evaluate associations within normoglycemic, prediabetic, and diabetic subgroups.

Key Results

HbA1c Association: In linear regression models, higher HbA1c levels were significantly associated with greater BAG across both models (ENIGMA: $B = 1.58, p = .014$ ; Pyment: $B = 0.93, p = .013$ ). In robust regression models, this association remained significant for the ENIGMA model ( $B = 1.70, p = .002$ ) but did not reach statistical significance for the Pyment model ( $B = 0.71, p = .13$ ).
Other Cardiometabolic Factors: Contrary to the findings for HbA1c, BMI, hypertension, and hyperlipidemia showed no significant association with BAG in either linear or robust regression models.
Stratified Analysis: When stratified by glycemic status, elevated HbA1c was associated with greater BAGENIGMA ( $B = 2.15, p = .01$ ) and BAGPyment ( $B = 1.21, p = .04$ ) in individuals at or above prediabetic levels. In the diabetic subgroup, HbA1c was associated with greater BAGENIGMA ( $B = 2.49, p = .047$ ).

Conclusions and Significance
The study concludes that elevated HbA1c is associated with accelerated brain aging in individuals with severe obesity. The authors suggest that the lack of association between BAG and other factors like BMI, hypertension, and hyperlipidemia may reflect the restricted BMI range inherent to a sample consisting exclusively of individuals with severe obesity, rather than a true absence of biological effect. The paper posits that glycemic control, as indicated by HbA1c, may be a more sensitive marker of advanced brain aging in this specific population than other cardiometabolic metrics.

Technical Summary: Elevated HbA1c is Associated with Advanced Brain Age in Severe Obesity

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