A new calculation offering a more precise assessment of metabolic health has been developed by researchers at the Universities of Leipzig and Gothenburg. The “metabolic BMI,” or metBMI, utilizes artificial intelligence to analyze metabolic measurements, possibly identifying individuals at risk for conditions like diabetes and fatty liver disease who may be missed by traditional Body Mass Index (BMI) screenings. Published January 7, 2026 in Nature Medicine, the study reveals that individuals with a normal BMI can face up to five times greater risk if their metBMI is elevated, highlighting the crucial role of lifestyle and gut bacteria in overall metabolic health.
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07.01.2026 13:45
New BMI Calculation Reveals Hidden Metabolic Imbalance
Researchers from the Universities of Leipzig and Gothenburg have developed a new approach to more accurately determine an individual’s risk for metabolic diseases like diabetes or fatty liver. Instead of relying solely on the traditional Body Mass Index (BMI), the team created an AI-based calculation model based on metabolic measurements – the metabolic BMI (metBMI). The study found that individuals with a normal weight but a high metabolic BMI have a risk of developing metabolic diseases up to five times greater. Lifestyle and environmental factors appear to play a more significant role in metBMI than genetic predisposition.
While the conventional BMI, calculated from height and weight, indicates whether someone is overweight, it doesn’t reveal how healthy or unhealthy body fat actually is. Up to 30% of people are considered normal weight according to BMI, yet already exhibit dangerous metabolic changes. Conversely, some individuals with elevated BMIs show largely normal metabolic profiles. This discrepancy can lead to delayed diagnosis and treatment for those at risk.
For the current research, the international team analyzed data from two large Swedish population studies encompassing nearly 2,000 participants. In addition to standard health and lifestyle information, researchers collected extensive lab values from blood samples and analyzed the gut microbiome. Using this data, they developed a calculation model to predict metabolic BMI. “Our metabolic BMI uncovers a hidden metabolic disorder that isn’t always visible on the scale. Two people with the same BMI can have completely different risk profiles depending on how their metabolism and fat tissue function,” said Dr. Rima Chakaroun, a researcher at the University Hospital of Leipzig and the study’s lead author. She led the research with Prof. Fredrik Bäckhed during a visiting fellowship at the University of Gothenburg.
Connection to Gut Bacteria
The results indicate that an unexpectedly high metabolic BMI (metBMI) is associated with a risk of developing several conditions—including fatty liver, diabetes, visceral fat accumulation, and insulin resistance—that is three to five times higher. Furthermore, individuals with a high metBMI experienced 30% less weight loss following bariatric surgery, procedures performed on the stomach and intestines designed to promote sustainable weight reduction. Comprehensive data for the study was gathered from patients who underwent surgery at the University Hospital of Leipzig.
A key finding of the research was the close relationship between the metabolic profile and the composition of bacteria in the gut. Individuals with higher metBMIs had lower bacterial diversity and a reduced capacity of their gut flora to convert fiber into health-promoting fatty acids, such as butyrate. The study also highlights that genetic factors are less important for metBMI than lifestyle and environmental influences.
The researchers’ metabolic BMI is based on comprehensive measurements of hundreds of small molecules in the blood, reflecting cellular metabolism. From an initial analysis of over 1,000 metabolic products, they identified a reduced panel of just 66 metabolites that retained nearly the same predictive power. These molecules primarily reflect the close interplay between the body’s metabolism and gut bacteria.
Significance for the Future of Medicine
“The traditional BMI often overlooks people who are normal weight but have a high metabolic risk. The metBMI can contribute to a fairer and more accurate assessment of disease risk,” said Dr. Chakaroun. This model could help identify affected individuals earlier, refine the selection process for surgical or medical interventions, and personalize therapeutic decisions. Future plans include refining the models by incorporating dynamic markers of insulin secretion and launching experimental studies on the gut microbiome-metabolite axis. This research offers a more nuanced understanding of metabolic health and could lead to improved preventative care.
Further information about Dr. Rima Chakaroun: She conducted research as a guest scientist at the University of Gothenburg from 2021-2025 with funding from the German Research Foundation (DFG)’s Walter Benjamin Program. She will contribute her expertise in microbiome research to the Leipzig Center of Metabolism (LeiCeM) at the University of Leipzig.
Scientific Contact:
Medical Faculty
Department of Communication and Media Relations
Tel.: +49 341 97 15 790
Mail: presse-mf@medizin.uni-leipzig.de
Original Publication:
Original publication in Nature Medicine: Multi-omic definition of metabolic obesity through adipose tissue-microbiome interactions. DOI: https://doi.org/10.1038/s41591-025-04009-7
More Information:
https://www.uni-leipzig.de/forschung/exzellenz-in-der-forschung/leipzig-center-o… Leipzig Center of Metabolism (LeiCeM) at the University of Leipzig
Images
The newly developed metabolic BMI is based on comprehensive measurements of hundreds of small molecules in the blood, which reflect cellular metabolism. …
Copyright: Image: Colourbox
Dr. Rima Chakaroun
Source: Swen Reichhold
Copyright: University of Leipzig
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