Ten Blood Markers Form Personalized Score for Cardiometabolic Risk

Researchers Condense Blood Profiles into a Ten-Marker Score

A research team led by Leiden University Medical Center (LUMC) in the Netherlands and the Max Planck Institute for Biology of Aging in Germany has developed a personalized metabolic indicator based on ten blood markers.

The model evaluates routine chemicals circulating in the blood to assess a patient's trajectory toward healthy aging or functional decline.

Presented at a research meeting organized with the São Paulo Research Foundation (FAPESP), the tool simplifies earlier experimental profiles that required testing more than 200 distinct compounds.

Longitudinal Data from Twelve European Cohorts

The research team developed the initial model using blood samples from 44,000 volunteers tracked across 12 European studies.

During the multi-year follow-up period, 5,500 participants died. Researchers evaluated fat levels, circulating sugars, and markers of inflammation to identify biological signals associated with mortality risk.

Healthy life expectancy after age 65 varies widely across Europe, ranging from roughly four years in Romania to ten years in the Netherlands. The authors noted that lifestyle, socioeconomic factors, and genetics drive these regional differences.

Refining the Calculation for Clinical Practice

The scientists refined the algorithm in collaboration with a researcher from the Albert Einstein Israelite Faculty in São Paulo, Brazil. This update occurred in three distinct stages.

First, investigators calibrated the mathematical model using Dutch population data to generate individualized patient scores. Second, they reduced the panel from hundreds of substances to ten standard markers that clinicians already order in primary care.

Third, the team inverted the numerical scale so that higher values indicate better physiological health. On this updated scale, each one-point increase corresponded to an average delay of 14 years before the diagnosis of a first cardiometabolic condition, including type 2 diabetes, stroke, or myocardial infarction.

Functional Tests and Behavioral Interventions

Scores on the ten-marker panel correlated with physical metrics of biological aging, including handgrip strength, respiratory lung capacity, and cognitive performance. Handgrip measurements served as an objective indicator of skeletal muscle function.

The investigators also tested whether targeted physical and behavioral protocols could alter the score in human volunteers.

Participants completed structured lifestyle modifications and resistance training regimens. The interventions produced measurable improvements primarily in individuals who started with below-average baseline scores.

• Volunteers with low baseline scores experienced reductions in fasting blood insulin.
• Circulating triglyceride levels dropped following the exercise and lifestyle programs.
• Participants in the lower-scoring group demonstrated measurable improvements in body composition.

Current Limitations and Clinical Considerations

The published evidence reflects observational cohorts and targeted intervention trials rather than broad population-level screening programs. While the ten selected markers reflect routine clinical tests, the proprietary calculation itself is not yet an automated standard across commercial diagnostic laboratories.

Additionally, the lifestyle and exercise interventions showed statistically clear improvements only among participants who started below the average score. Individuals with higher baseline health metrics did not experience the same degree of metabolic shift from the tested programs.

Patients interested in tracking circulating lipids, glycemic control, or inflammatory status should review standard laboratory panels directly with a qualified clinician.