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PLoS Med. 2014 Feb 25;11(2):e1001606. doi: 10.1371/journal.pmed.1001606. eCollection 2014 Feb.

Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17,345 persons.

Author information

1
The Estonian Genome Center, University of Tartu, Tartu, Estonia.
2
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland ; Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland ; Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, Finland.
3
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland ; Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, Finland.
4
Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
5
Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, Finland.
6
Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, Finland ; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
7
The Estonian Genome Center, University of Tartu, Tartu, Estonia ; The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America ; Division of Genetics, Children's Hospital, Boston, Massachusetts, United States of America ; Division of Endocrinology, Children's Hospital, Boston, Massachusetts, United States of America ; Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America ; Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America.
8
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland ; The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America ; Wellcome Trust Sanger Institute, Hinxton, United Kingdom.
9
Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland ; Wellcome Trust Sanger Institute, Hinxton, United Kingdom.
10
Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, Finland ; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland ; Computational Medicine, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom.
11
The Estonian Genome Center, University of Tartu, Tartu, Estonia ; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
12
The Estonian Genome Center, University of Tartu, Tartu, Estonia ; Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.

Abstract

BACKGROUND:

Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts.

METHODS AND FINDINGS:

106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18-103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1-standard deviation increment, 95% CI 1.53-1.82, p = 5×10⁻³¹), albumin (HR 0.70, 95% CI 0.65-0.76, p = 2×10⁻¹⁸), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62-0.77, p = 3×10⁻¹²), and citrate (HR 1.33, 95% CI 1.21-1.45, p = 5×10⁻¹⁰). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001).

CONCLUSIONS:

Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention.

PMID:
24586121
PMCID:
PMC3934819
DOI:
10.1371/journal.pmed.1001606
[Indexed for MEDLINE]
Free PMC Article
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