Cited by 344Metabolomics and Mass Spectrometry StudiesLipoproteins and Cardiovascular HealthHealth, Environment, Cognitive Aging

Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons

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Fischer, Krista, Kettunen, Johannes, Würtz, Peter, Haller, Toomas, Havulinna, Aki S., Kangas, Antti J., Soininen, Pasi, Esko, Tõnu +9 more·2014·PLoS Medicine

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.

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Crossref · 10.1371/journal.pmed.1001606

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  • The authors identified well-studied metabolites, such as albumin, very low-density lipoprotein particles and amino acids, that were associated with mortality due to multiple causes.

    “The authors identified well-studied metabolites, such as albumin, very low-density lipoprotein particles and amino acids, that were associated with mortality due to multiple causes.”

    From Measuring biological age using omics data (2022) · cites this paper as [117]

  • A large-scale biobank study used 1H-NMR of blood plasma to identify metabolites predictive of mortality risk in an Estonian and Finnish cohort.

    “A large-scale biobank study used 1H-NMR of blood plasma to identify metabolites predictive of mortality risk in an Estonian and Finnish cohort117,118.”

    From Measuring biological age using omics data (2022) · cites this paper as [117]

  • Metabolomic clocks have demonstrated lower age prediction accuracy than other omics data types despite training on extremely large sample sizes, and effect sizes for ageing traits have been modest.

    “Furthermore, metabolomic clocks have demonstrated lower age prediction accuracy than other omics data types despite training on extremely large sample sizes, and effect sizes for ageing traits have been modest113,116–121.”

    From Measuring biological age using omics data (2022) · cites this paper as [117]

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References 35 · Cited by 344

Authors
Fischer, K., Kettunen, J., Würtz, P., Haller, T., Havulinna, A. S., Kangas, A. J., Soininen, P., Esko, T., Tammesoo, M.-L., Mägi, R., Smit, S., Palotie, A., Ripatti, S., Salomaa, V., Ala-Korpela, M., Perola, M., & Metspalu, A.
Affiliations
  • University of Tartu (EE)
  • University of Helsinki (FI)
  • Finnish Institute for Health and Welfare (FI)
  • Oulu University Hospital (FI)
  • University of Eastern Finland (FI)
  • Broad Institute (US)
Corresponding author
  • Fischer, Krista
  • Würtz, Peter
Venue
PLoS Medicine
Published
2014-02-25
Volume
11
Issue
2
Pages
e1001606
ISSN
  • 1549-1277 (ISSN-L)
  • 1549-1676
OpenAlex
W2147063947
Cited by
344
References
35
Citations by year
2026: 7 · 2025: 35 · 2024: 29 · 2023: 22 · 2022: 22 · 2021: 33 · 2020: 34 · 2019: 34 · 2018: 29 · 2017: 28 · 2016: 38 · 2015: 21 · 2014: 10 · 2013: 1 · 2012: 1
FWCI
13.27
Type
journal article
Language
en
Open access
Locations
  • PLoS Medicine (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Työväentutkimus Vuosikirja (submittedVersion)
  • Explore Bristol Research (submittedVersion)
  • STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
Funders
  • Foundation for Cardiovascular Research
  • Wellcome Trust (139635, 261433, 213506, 201413, 129680, HEALTH-F4-2007-201413)
  • European Commission (306031, 213506, 313010, 278913, 261433, 201413)
  • University of Bristol
  • European Foundation for the Study of Diabetes
  • Eesti Teadusfondi (SP1GVARENG, ETF9353)
  • Eesti Teadusagentuur (IUT20-60, SP1GVARENG)
  • Academy of Finland (129680, 137870, 129429, 250422, #213506, 139635, 251217)
  • Novo Nordisk
  • Sydäntutkimussäätiö
  • Oulun Yliopisto (137870, 129429)
  • Tartu Ülikool (SP1GVARENG)
  • Novo Nordisk Fonden
  • Medical Research Council
  • Jenny ja Antti Wihurin Rahasto
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
  • Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
Keywords
all-cause mortality, circulating biomarkers, mortality prediction, alpha-1-acid glycoprotein, albumin, citrate, frailty, cardiovascular mortality, cancer mortality, risk scoring, Estonian Biobank, biomarker profiling
MeSH terms
Serum Albumin, Human, Adolescent, Adult, Aged, Aged, 80 and over, Cause of Death, Estonia, Female, Finland, Humans, Lipoproteins, LDL, Male, Middle Aged, Magnetic Resonance Spectroscopy, Orosomucoid, Particle Size, Predictive Value of Tests, Prognosis, Risk Factors, Serum Albumin, Time Factors, Reproducibility of Results, Biomarkers, Proportional Hazards Models, Biological Specimen Banks, Risk Assessment, Citric Acid, Kaplan-Meier Estimate, Young Adult, High-Throughput Screening Assays

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