New blood analysis predicts risk of death

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.

The current study was cooperation between the University of Oulu, the University of Eastern Finland, the National Institute for Health and Welfare, Institute for Molecular Medicine Finland (FIMM), and Estonian Genome Centre (in the University of Tartu). One of the leaders of this research is Professor Mika Ala-Korpela from the University of Oulu. Dr. Pasi Soininen, the head of the NMR metabolomics laboratory in the University of Eastern Finland, was responsible for the NMR experimentation. The study was published in the prestigious PLoS Medicine publication series on 25 February 2014.

Additional information:

Dr. Mika Ala-Korpela, Professor of Computational Medicine, University of Oulu, Department of Health Sciences, tel. +358 40 1977 657, email: mika.ala-korpela@computationalmedicine.fi

Dr. Pasi Soininen, Head of the Metabolomics Laboratory (technological inquiries), University of Eastern Finland, Department of Pharmacy, tel. +358 40 355 3246, email: pasi.soininen@uef.fi

Home page of the research group: http://www.computationalmedicine.fi/

Scientific publications on this topic:

Latest research paper on this topic:

PLoS Medicine, 11, e1001606, 2014; doi: 10.1371/journal.pmed.1001606
Published 25.2.2014
Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: An observational study of 17,345 persons
K. Fischer, J. Kettunen, P. Würtz, T. Haller, A. S. Havulinna, A. J. Kangas, P. Soininen, T. Esko, M.-L. Tammesoo, R. Mägi, S. Smit, A. Palotie, S. Ripatti, V. Salomaa, M. Ala-Korpela#, M. Perola#, A. Metspalu# (#directors of the research)

Earlier publications related to this topic:

(1) Metabolic signatures of insulin resistance in 7,098 young adults
P. Würtz, V.-P. Mäkinen, P. Soininen, A. J. Kangas, T. Tukiainen, J. Kettunen, M. J. Savolainen, J. S. Viikari, T. Rönnemaa, M. Kähönen, T. Lehtimäki, S. Ripatti, O. T. Raitakari, M.-R. Järvelin, M. Ala-Korpela
Diabetes 61, 1372-1380, 2012

(2) High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis
P. Würtz, J. Raiko, C. G. Magnussen, P. Soininen, A. J. Kangas, T. Tynkkynen, R. Thomson, R. Laatikainen, M. J. Savolainen, J. Laurikka, P. Kuukasjärvi, M. Tarkka, P. J. Karhunen, A. Jula, J. S. Viikari, M. Kähönen, T. Lehtimäki, M. Juonala, M. Ala-Korpela#, O. T. Raitakari# (#directors of the research)
European Heart Journal 33, 2307-2316, 2012

(3) Long-term leisure-time physical activity and serum metabolome
U. M. Kujala, V.-P. Mäkinen, I. Heinonen, P. Soininen, A. J. Kangas, T. H. Leskinen, P. Rahkila, P. Würtz, V. Kovanen, S. Cheng, S. Sipilä, M. Hirvensalo, R. Telama, T. Tammelin, M. J. Savolainen, A. Pouta, P. F. O'Reilly, P. Mäntyselkä, J. Viikari, M. Kähönen, T. Lehtimäki, P. Elliott, M. J. Vanhala, O. T. Raitakari, M.-R. Järvelin, J. Kaprio, H. Kainulainen, M. Ala-Korpela
Circulation 127, 340-348, 2013

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