Ten-marker blood score aims to flag cardiometabolic risk and track healthy ageing

A European team has refined a blood-based metabolic score into a ten-marker tool that estimates a person's risk of cardiometabolic disease and functional decline in middle age. Joris Deelen of Leiden University Medical Center (LUMC) presented the work at FAPESP Week Netherlands. According to his account, the score also appears to track the benefits of exercise and lifestyle change in people who start out less healthy.

Building the score

Biological ageing cannot be measured directly, so the researchers looked for indirect signals in blood. They drew on about 44,000 volunteers followed over several years in 12 European studies, with more than 200 substances measured, among them fats, sugars and markers of inflammation. During follow-up, 5,500 deaths were recorded. Comparing blood profiles with those outcomes allowed the team to identify which metabolic features were linked to higher mortality risk. Colleagues from the Max Planck Institute for Biology of Aging in Cologne also took part.

Three changes to make it usable

An exchange student from São Paulo, Gabriela Natalle Lopes of the Albert Einstein Israelite Faculty, worked with the Leiden group to update the score in three steps:

• The calculation was adjusted using Dutch population data, so that each patient receives an individual result.
• The test was cut from hundreds of items to ten blood markers that clinicians already routinely assess.
• The scale was reversed so that a higher score means better health, whereas a high number previously signalled poorer health.

The updated version predicted cardiometabolic disease, including diabetes, heart attack and stroke, more effectively than the original. Deelen reported that each one-point rise corresponds, on average, to a 14-year delay in the first such diagnosis. The score also correlates with cognitive function, lung capacity and handgrip strength.

Responding to lifestyle change

To test whether the score can be shifted, volunteers took part in lifestyle and strength-training programmes. Across whole groups, the score did not change significantly. When participants were split by starting value, however, those with a score below zero benefited. In this group, fasting insulin and triglycerides fell significantly and body composition improved. Deelen interpreted this as evidence that the score can help identify who most needs intervention and monitor gains from exercise.

The analyses suggest the score is roughly 40% heritable, with the remaining 60% shaped by lifestyle and environment. Smoking had the largest negative effect among the behaviours examined, while more regular physical activity improved the score. Childhood malnutrition was also linked to a lower score in adulthood.

Context and limits

The source is a conference-based report, and it gives no detail on the statistical performance of the score, the design of the intervention trials or their sample sizes. The 14-year figure is an average association, not a guarantee for an individual. Independent validation in other populations would be needed before routine clinical use. Deelen also noted that healthy life expectancy after 65 differs widely across Europe, from about four years in Romania to ten in the Netherlands, attributing this mainly to socioeconomic, educational, lifestyle and genetic factors.

A related Brazilian line of work

The report also covers research at the Federal University of São Carlos led by Tiago da Silva Alexandre, which examines links between musculoskeletal ageing and dementia. His group describes molecular exchange among muscle, bone, fat and brain, including myokines released by working muscle. Fat infiltration of muscle with age may disrupt lipid and carbohydrate metabolism and has been associated with metabolic syndrome, loss of mobility and dementia. Visceral fat may also reduce circulating vitamin D, which is relevant to both muscle strength and brain protection.

A new centre at the university, CCD-MIDEM, will use artificial intelligence and biomarkers drawn from health records and imaging to estimate dementia probability early in Brazil's public health system. Together, the two projects point towards routine biomarker-based tools for stratifying older adults and targeting interventions.

Source: Personalized score uses ten blood markers to flag disease risk and assess healthy aging (Medical Xpress, 31 October 2026).

Image: AI-generated illustration.