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

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. METH...

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Detalles Bibliográficos
Autores principales: Fischer, Krista, Kettunen, Johannes, Würtz, Peter, Haller, Toomas, Havulinna, Aki S., Kangas, Antti J., Soininen, Pasi, Esko, Tõnu, Tammesoo, Mari-Liis, Mägi, Reedik, Smit, Steven, Palotie, Aarno, Ripatti, Samuli, Salomaa, Veikko, Ala-Korpela, Mika, Perola, Markus, Metspalu, Andres
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3934819/
https://www.ncbi.nlm.nih.gov/pubmed/24586121
http://dx.doi.org/10.1371/journal.pmed.1001606
Descripción
Sumario: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. Please see later in the article for the Editors' Summary