New Blood Test Scores Metabolic Health to Predict Aging and Disease Risk
European researchers have developed a personalized health indicator using ten blood markers to assess metabolic function and predict the likelihood of chronic diseases and functional decline in middle age. The tool, derived from data on 44,000 European volunteers, identifies early biological warning signs linked to higher mortality risk. It aims to support early interventions for healthier aging across diverse populations.
European researchers led by Joris Deelen of Leiden University Medical Center (LUMC) developed a personalized metabolic health score using ten blood markers to predict chronic disease risk and functional decline in middle age. The tool was derived from data on 44,000 European volunteers across 12 longitudinal studies, with 5,500 recorded deaths over time. By analyzing over 200 substances—including glucose, lipids, and inflammation markers—the team identified biological warning signs linked to higher mortality. The score was refined through collaboration with Brazil’s Albert Einstein Israelite Faculty, where student Gabriela Natalle Lopes contributed to personalizing the model. The final version simplified testing to just ten commonly measured blood components and restructured the scoring so that higher values indicate better health. A one-point increase correlates with a 14-year delay in onset of cardiometabolic disease. The research revealed that 60% of people over 65 in Europe live with two or more chronic conditions, highlighting the urgency of early intervention. The score is influenced 40% by genetics and 60% by lifestyle—smoking being the most detrimental behavior, while physical activity improves it. Early-life malnutrition was also found to have lasting negative effects on metabolic health. In clinical trials, lifestyle interventions significantly improved markers like insulin and triglycerides in individuals with low initial scores, demonstrating the tool’s utility fo
This blood test could transform preventive healthcare by enabling early identification of metabolic vulnerability before disease onset, particularly benefiting populations with wide disparities in healthy aging—such as Romania versus the Netherlands. By focusing on modifiable factors like smoking and physical activity, it may empower clinicians to tailor interventions more effectively, potentially reducing long-term healthcare costs. The tool’s simplicity—using only ten standard blood markers—makes it feasible for integration into routine check-ups across diverse medical systems. Comparable in impact to the development of the Framingham Risk Score for heart disease, this score could become a foundational metric in primary care. However, its effectiveness across non-European populations remains unverified, and long-term outcomes of interventions guided by the score are still unknown. The next critical step will be validating the tool in broader, more diverse cohorts—especially in low- a