Akl Fahed, MD, MPH, Interventional Cardiologist at Massachusetts General Hospital and Instructor in Medicine at Harvard Medical School.

Akl Fahed, MD, MPH

When DNA Meets BMI: A New Way to Predict Metabolic Disease Earlier, With Akl Fahed, MD, MPH

A biologically enriched metabolic polygenic risk score built from 20 traits and > 8.5 million individuals outperformed existing disease-prediction models and predicted downstream morbidity and clinical interventions for obesity and type 2 diabetes (T2D).

According to study investigators, the score effectively identifies individuals at high risk for metabolic multimorbidity, including predicting GLP-1 receptor agonist initiation, and should be used alongside body mass index (BMI) rather than as a replacement.

"This new score is not looking to replace body mass index at all…" Akl Fahed, MD, MPH, Interventional Cardiologist at Massachusetts General Hospital and Instructor in Medicine at Harvard Medical School, said in an interview. "The power of a DNA-based assessment such as this one is being able to detect risk of disease way earlier than the body mass index, and also to complement it."

Study investigators developed the metabolic PRS with one version optimized for obesity (O-MetPRS) and another for T2D (D-MetPRS), incorporating genes associated with 20 different traits related to metabolic function, including fat distribution measures such as visceral and subcutaneous adipose tissue, as well as insulin and glucose control. Using genome-wide association studies from worldwide datasets, with a particular focus on non-European populations, investigators reported obesity and T2D risk scores outperforming prior PRS models across six ancestries, including African, East Asian, and South Asian individuals.

"One of the limitations in the field of genomics, really for the past 10 years, has been what we call a Eurocentric bias, which means most of the genetic data in the world has come from individuals of European ancestry," Fahed explained. "That field is really shifting pretty quickly now, through 2 ways: accumulating a lot of genomic data on individuals of non-European ancestry, but also improvement in our methods."

The model was trained and tested in the UK Biobank before being externally validated in 3 multi-ethnic cohorts comprising up to 300,000 participants. According to investigators, the risk scores identified individuals at high risk for clinical outcomes such as cardiovascular disease and stroke. In a median 5.5 years follow-up, even individuals with a high PRS who were healthy at baseline were approximately 2 times as likely, specifically, those in the top decile compared to the middle quintile, to eventually receive GLP-1 agonist medications or bariatric surgery.

Investigators say the PRS represents a potential shift in how metabolic disease risk is assessed, offering clinicians an earlier, more biologically comprehensive view of a patient's trajectory before traditional markers like BMI signal concern.

Editor’s Note: Fahed reports relevant disclosures with Goodpath, MyOme, HeartFlow, and Foresite Labs.

Kim MS, Chen Q, Sui Y, et al. Metabolic polygenic risk scores for prediction of obesity, type 2 diabetes, and related morbidities. 

https://doi.org/10.1016/j.cmet.2026.02.009

New genetic risk score better predicts diabetes, obesity and downstream complications. EurekAlert! Published March 16, 2026. Accessed March 24, 2026. 

https://www.eurekalert.org/news-releases/1119751

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A metabolic polygenic risk score built from 20 traits and more than 8.5 million individuals outperformed existing disease-prediction models.

Akl Fahed, MD, MPH

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