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MGB researchers just developed a new risk calculator for obesity. Here’s why that’s a game changer.
The new tool could help predict obesity-related health risks earlier and reshape prevention strategies, researchers say.
Researchers from Mass General Brigham have developed a new genetic risk calculator designed to predict not just who may develop obesity or Type 2 diabetes, but how those conditions could affect long-term health.
Drawing on one of the largest datasets ever used for this type of research, the new calculator can identify people at risk of obesity or Type 2 diabetes potentially decades before the conditions develop.
The findings, published in the research journal “Cell Metabolism,” mark a significant step forward in using genetics to forecast the trajectory of complex metabolic diseases — disorders affecting the body’s ability to break down food — MGB announced in a statement Thursday.
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At the center of the research is a tool known as a polygenic risk score, which aggregates multiple genetic variants to estimate a person’s likelihood of developing a disease, MGB officials said.
While such scores already exist, the MGB team set out to go further: predicting the downstream health consequences of obesity and Type 2 diabetes, not just the diagnoses themselves, said co-first author Min Seo Kim in a statement.
“In the future, this genomic approach could complement established clinical risk factors to inform patient care and preventative strategies,” Kim said.
How does it work?
Unlike traditional models that rely heavily on measures like body mass index, the new calculator incorporates genetic signals tied to 20 metabolic traits, including fat distribution, insulin function, and glucose regulation, co-senior author Akl Fahed told Boston.com.
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“We use mathematical modeling to aggregate all that data and create that score,” he said. “Once we created that score, we went and tested it in different populations, so we partnered with different biobanks all over the world.”
Researchers analyzed genome-wide association studies spanning more than 8.5 million participants globally — among the largest datasets ever used for this type of research, according to the MGB statement.
The scale of the data is a key differentiator, said Fahed, who is also an interventional cardiologist with the MGB Heart and Vascular Institute. That breadth allowed the model to outperform previous risk scores across multiple populations, he added.
“This is using the largest data ever, and it overperforms every single score ever published in multiple ancestries,” Fahed said.
One of the major limitations of earlier genetic risk models has been their heavy reliance on European datasets, reducing accuracy for other groups. The new score was designed with broader representation in mind, with a particular focus on African, East Asian, and South Asian populations, according to MGB.
Why does it matter?
Beyond identifying risk, the calculator also helps forecast real-world outcomes.
Researchers found that individuals with high genetic risk scores — even if initially healthy — were about twice as likely to later require interventions such as GLP-1 medications or bariatric surgery compared to those with mid-range scores, according to the MGB statement.
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That ability to anticipate disease progression is what makes the tool especially promising, Fahed said.
“If you can predict diseases early on, then you can potentially tackle it early,” he added. “You don’t really want to have to deal with obesity after someone had a heart attack. You really want to take people earlier in their life and … not allow them to get to the stage where they have obesity and suffer the consequences.”
Because the score is based on DNA, it can be assessed long before symptoms appear, opening the door to earlier and potentially more effective interventions, Fahed explained. Specifically, the test predicts the “metabolic consequences” of obesity and diabetes, he said, which refers to the conditions that occur from these diseases, such as increased blood pressure and excess body fat.
“That’s really important because what we care about with obesity is really the complications of obesity — not just the body image,” he said.
Fahed said the research is also important for the public to understand how obesity is caused; rather than a product of lifestyle, it’s a condition heavily influenced by genetics.
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Fahed explained how everyone knows someone who can eat unhealthy foods and not experience the repercussions: “That’s because of genetics,” he said.
What’s next?
Looking ahead, Fahed said the next step is implementation.
This step will require building the infrastructure needed to implement genetic risk scoring at scale, Fahed said, including clinical guidelines, lab capacity, and physician training to understand the test results.
“I think there’s a lot of education and standardization that will need to happen in order to start implementing these genetic risk scores at scale,” he added.
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