New scientific blood analysis predicts short-term mortality in humans

University of Eastern FinlandFeb 26 2014

The general state of a person's metabolism can be diversely illustrated with a new scientific blood analysis. With the aid of the analysis biomarkers predicting short-term mortality have now been discovered.

If a person belongs to a risk group based on these biomarker concentrations, he/she has a multifold risk of dying in the next five years compared to the general population. The study is based on blood samples of over 17,000 Finnish and Estonian people.

Mortality was related to four biomarkers in the blood: levels of two proteins (albumin and alpha-1 acidic glycoprotein), lipid metabolism variables (size of large lipoprotein particles responsible for lipid metabolism in the body) and citric acid concentration. These biomarkers relate to normal metabolism and are present in the blood of all people, but according to the study, their relative amounts are crucial.

The biomarkers were independent of known mortality risk factors such as age, smoking, alcohol use, cholesterol, obesity, and blood pressure. The biomarkers associated with mortality also in healthy subjects with no diagnosed diabetes, cancer or vascular diseases.

The new method gives hope that in the future it would be possible to identify increased risk of death at an early stage, so that people could be directed to appropriate follow-up examinations and treatment.

This study is the first of its kind in the world. More research is needed for possible clinical applications in health care.

The new blood analysis utilised in the research was developed by the Computational Medicine Research Group in cooperation between the University of Oulu and the University of Eastern Finland over nearly ten years. The method is based on Nuclear Magnetic Resonance (NMR) spectroscopy and it enables determination of over 200 biomarkers for body metabolism in one blood sample.

The new blood analysis method has been applied in recent years extensively for the research of metabolic diseases such as type 2 diabetes and cardiovascular diseases. Application of this methodology has also provided new information on the health effects of long-term exercise. Around 50 scientific articles have been published on the applications of this method during the last three years.