title: Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17,345 persons.
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.
  
  
  RESULTS
  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.
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia.
authors.forename: Krista
authors.initials: K
authors.lastname: Fischer
authors.affiliation: 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.
authors.forename: Johannes
authors.initials: J
authors.lastname: Kettunen
authors.affiliation: 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.
authors.forename: Peter
authors.initials: P
authors.lastname: Würtz
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia.
authors.forename: Toomas
authors.initials: T
authors.lastname: Haller
authors.affiliation: Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
authors.forename: Aki S
authors.initials: AS
authors.lastname: Havulinna
authors.affiliation: Computational Medicine, Institute of Health Sciences, University of Oulu and Oulu University Hospital, Oulu, Finland.
authors.forename: Antti J
authors.initials: AJ
authors.lastname: Kangas
authors.affiliation: 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.
authors.forename: Pasi
authors.initials: P
authors.lastname: Soininen
authors.affiliation: 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.
authors.forename: Tõnu
authors.initials: T
authors.lastname: Esko
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia.
authors.forename: Mari-Liis
authors.initials: ML
authors.lastname: Tammesoo
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia.
authors.forename: Reedik
authors.initials: R
authors.lastname: Mägi
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia.
authors.forename: Steven
authors.initials: S
authors.lastname: Smit
authors.affiliation: 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.
authors.forename: Aarno
authors.initials: A
authors.lastname: Palotie
authors.affiliation: Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland ; Wellcome Trust Sanger Institute, Hinxton, United Kingdom.
authors.forename: Samuli
authors.initials: S
authors.lastname: Ripatti
authors.affiliation: Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
authors.forename: Veikko
authors.initials: V
authors.lastname: Salomaa
authors.affiliation: 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.
authors.forename: Mika
authors.initials: M
authors.lastname: Ala-Korpela
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia ; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.
authors.forename: Markus
authors.initials: M
authors.lastname: Perola
authors.affiliation: The Estonian Genome Center, University of Tartu, Tartu, Estonia ; Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
authors.forename: Andres
authors.initials: A
authors.lastname: Metspalu
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D018070:Biological Specimen Banks; D015415:Biomarkers / Q000097:blood*; D002423:Cause of Death; D019343:Citric Acid / Q000097:blood; D004957:Estonia / Q000453:epidemiology; D005260:Female; D005387:Finland / Q000453:epidemiology; D057166:High-Throughput Screening Assays / Q000379:methods*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008077:Lipoproteins, LDL / Q000097:blood; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D008875:Middle Aged; D009961:Orosomucoid / Q000032:analysis; D010316:Particle Size; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D012709:Serum Albumin / Q000032:analysis; D000075462:Serum Albumin, Human; D013997:Time Factors; D055815:Young Adult
chemical_list: C422455:ALB protein, human; D015415:Biomarkers; D008077:Lipoproteins, LDL; D009961:Orosomucoid; D012709:Serum Albumin; D019343:Citric Acid; D000075462:Serum Albumin, Human