A research team has developed an intelligent tool, Obscore, capable of assessing an individual’s risk of developing 18 diseases associated with obesity. This advancement helps prioritize candidates for weight-loss medication therapy.
According to data, over two-thirds of the adult population in the United Kingdom is overweight or obese, which increases the risk of chronic complications. The analysis of data from nearly 200,000 individuals with a body mass index (BMI) of 27 or higher, employing machine learning technologies and the UK Biobank dataset, revealed 20 key indicators. These include age, gender, cholesterol levels, and creatinine levels, enabling the prediction of a 10-year risk for complications like gout and stroke.
Participants were classified into five risk categories based on their likelihood of developing diseases over the next decade, and the tool’s validity was confirmed using independent validation samples. Researchers emphasize that standardized BMI assessment falls short in accurately identifying individuals at high risk, as individuals with identical BMI values can exhibit different profiles of disease susceptibility. Moreover, applying Obscore to data from a randomized tirzepatide trial demonstrated that high-risk individuals achieved outcomes comparable to those of low-risk individuals, highlighting the tool’s potential for precision therapy. Professor Naveed Sattar of the University of Glasgow notes that further refinement and clinical validation are required before broad implementation of this technology in medical practice.