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Single Blood Test Predicts Risk of Death in 5 to 10 Years

Posted on 11 October 2019

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New study identifies a set of 14 biomarkers in blood that are independently associated with mortality in people of all ages.

“It is really surprising that if you measure blood samples only once in the lifetime of older persons, that the blood molecules reflect vulnerability in such a way that you can indicate 5- and 10-year mortality risk so well,” says Joris Deelen, an author of this study.

A meta-analysis was performed in 44,168 individuals from 12 cohorts to narrow down the metabolic biomarkers associated with all-cause mortality, from an initial 226 in the primary survival analysis to a final 14 biomarkers listed below:

Biomarker Hazard Ratio Association with Mortality
Total lipids in chylomicrons and extremely large VLDL 0.80 Decreased Mortality
Total lipids in small HDL 0.87 Decreased Mortality
Mean diameter for VLDL particles 0.85 Decreased Mortality
Ratio of polyunsaturated fatty acids to total fatty acids 0.78 Decreased Mortality
Histidine 0.93 Decreased Mortality
Leucine 0.82 Decreased Mortality
Valine 0.87 Decreased Mortality
Albumin 0.89 Decreased Mortality
Glucose 1.16 Increased Mortality
Lactate 1.06 Increased Mortality
Isoleucine 1.23 Increased Mortality
Phenylalanine 1.13 Increased Mortality
Acetoacetate 1.08 Increased Mortality
Glycoprotein acetyls (GlycA) 1.32 Increased Mortality

“The 14 identified biomarkers are involved in various processes, such as lipoprotein and fatty acid metabolism, glycolysis, fluid balance, and inflammation. Although the majority of these biomarkers have been associated with mortality before, this is the first study that shows their independent effect when combined into one model,” the researchers wrote.

Based on the 14 identified biomarkers, a model was used to generate a metabolic biomarker score, which typically ranged between -2 and 3 in most cohorts of this study, and was shown to improve accuracy of risk prediction as compared to a score based on conventional risk factors (such as systolic blood pressure and total cholesterol).

The findings of this study suggests that metabolic biomarker profiling has potential to be adopted in a clinical setting for targeted prevention of mortality and to guide treatment strategies e.g. when deciding whether an elderly person is too fragile for an invasive operation.

However, all individuals included in the study were of European descent, so further research is necessary to determine whether the predictive ability still stands when applied to cohorts with different genetic ancestry. Future efforts should also focus on constructing a standardised metabolic biomarker score that is suitable for classification of patients, and more fully realises the potential of metabolic biomarker profiling in patient care and for clinical research.

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