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Peter Würtz¹, Aki S Havulinna¹, Pasi Soininen¹

¹From Computational Medicine, Institute of Health Sciences, University of Oulu, Finland (P.W., P.S., T. Tynkkynen, Q.W., M.T., A.J.K., J. Kettunen, M.A.-K.); Department of Chronic Disease Prevention, National Institute for Health and Welfare, Finland (P.W., A.S.H., J. Kettunen, A.J., M.P., V.S.); Institute for Molecular Medicine Finland, University of Helsinki (P.W., A.S.H., M.P., S.P.); NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio (P.S., T. Tynkkynen, Q.W., M.T., M.A.-K.); Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, United Kingdom (D.P.-M., J.-P.C.); Institute of Cardiovascular Science, University College London, United Kingdom (T. Tillin, A.D.H., J.-P.C., N.C.); Framingham Heart Study of the National Heart, Lung, and Blood Institute and Boston University School of Medicine, Framingham, MA (A.G., R.S.V.); Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany (A.A., J.A.); Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Finland (J. Kaikkonen, V.M., O.T.R.); Department of Food and Environmental Sciences, University of Helsinki, Finland (V.M.,); Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Finland (M.K.); Department of Clinical Chemistry, Fimlab Laboratories, and School of Medicine, University of Tampere, Finland (T.L.); Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom (D.A.L., T.R.G., M.A.-K.); School of Social and Community Medicine, University of Bristol, United Kingdom (D.A.L., T.R.G., M.A.-K.); Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (N.S.); Hannover Medical School, Hannover Unified Biobank, Germany (T.I.); Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany

|January 10, 2015

Resumen

Los metabolomicos de alto rendimiento identificaron cuatro biomarcadores clave para la predicción del riesgo de enfermedad cardiovascular. Estos incluyen fenilalanina y ácidos grasos monoinsaturados (riesgo aumentado), y ácidos grasos omega-6 y docosahexaenoico (riesgo reducido).

Área de la Ciencia:

Investigación de Enfermedades Cardiovasculares Investigación de Enfermedades Cardiovasculares
La Metabolomía es una parte de la Metabolomía.
El descubrimiento de biomarcadores.

Sus antecedentes:

Los factores de riesgo cardiovascular establecidos tienen limitaciones en la predicción de enfermedades.
El perfil de alto rendimiento de los metabolitos circulantes ofrece potencial para mejorar la predicción del riesgo cardiovascular.

Objetivo del estudio:

Identificar nuevos biomarcadores para enfermedades cardiovasculares incidentes utilizando metabolomía cuantitativa de resonancia magnética nuclear.
Para evaluar el valor de predicción de riesgo incremental de los metabolitos identificados en grandes cohortes prospectivas.

Principales métodos:

Metabolomía de resonancia magnética nuclear cuantitativa aplicada a las cohortes FINRISK, SABRE y al Estudio de Salud y Corazón de la Mujer Británica.
Análisis dirigido de 68 lípidos y metabolitos, seguido de metanálisis ajustando los factores clínicos y los lípidos de rutina.
Desarrollo de una puntuación de riesgo utilizando cuatro biomarcadores validados y evaluación de su rendimiento predictivo.

Principales resultados:

Cuatro metabolitos asociados con eventos cardiovasculares después del ajuste: fenilalanina y ácidos grasos monoinsaturados (riesgo aumentado), ácidos grasos omega-6 y ácido docosahexaenoico (riesgo reducido).
Una puntuación de riesgo que incorpora estos biomarcadores mejora la precisión de la predicción de riesgos y la clasificación en cohortes de validación.
Las asociaciones de biomarcadores se corroboraron utilizando espectrometría de masas en cohortes independientes.

Conclusiones:

El perfil de metabolitos en grandes cohortes prospectivas identificó la fenilalanina, los ácidos grasos monoinsaturados y los ácidos grasos poliinsaturados como biomarcadores valiosos para el riesgo cardiovascular.
La metabolomía de alto rendimiento proporciona una plataforma robusta para el descubrimiento de biomarcadores y mejora las capacidades de evaluación del riesgo cardiovascular.

Palabras clave:

aminoácidos y aminoácidos.marcadores biológicos marcadores biológicos ácidos grasos y ácidos grasos.Los metabolomicos son aquellos que se encuentran en factores de riesgo de los factores de riesgo.

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