On Mar. 16, 2026, investigators from Mass General Brigham announce they have built metabolic polygenic risk scores (PRS) for predicting obesity and T2D, which outperformed existing disease-prediction models and predicted downstream morbidity and clinical interventions.

Type 2 diabetes (T2D) and obesity are metabolic conditions with many causes, including overlapping and distinct genetic features. A PRS can capture multiple genetic risk factors to provide an estimate for whether a person may develop a complex medical condition and how they might fare long-term.

By integrating genetic findings from several of the world’s largest biobanks, investigators from Mass General Brigham built metabolic PRSs for predicting obesity and T2D, which outperformed existing disease-prediction models and predicted downstream morbidity and clinical interventions. The findings are published in Cell Metabolism

The metabolic PRS designed by the researchers includes one version optimized for obesity and another for T2D. Both scores look beyond widely utilized variables, such as body mass index, and focus on genes associated with 20 different traits related to metabolic function, such as fat distribution and insulin and glucose control. The team used genome-wide association studies (GWAS) performed in some of the largest datasets worldwide, which collectively encompass over 8.5 million participants globally.

The researchers found that the risk scores identified individuals at high risk for clinical outcomes like cardiovascular disease and stroke. Individuals with a high PRS who were initially healthy were about twice as likely to later receive GLP‑1 agonist medications or bariatric surgery compared to those with mid-range PRS scores, during a follow-up period of median 5.5 years.

The use of multi-ancestry GWAS data, with a particular focus on non-European populations, enabled the construction of obesity and T2D risk scores that surpassed prior PRS models in African, East Asian, South Asian, and Middle Eastern individuals.

Going forward, the researchers hope to continue refining understandings of the genetic subtypes of T2D and obesity to improve patient classification and stratification for clinical trials and ultimately foster more tailored interventions.