Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts

Peter Würtz, Aki S Havulinna, Pasi Soininen, Tuulia Tynkkynen, David Prieto-Merino, Therese Tillin, Anahita Ghorbani, Anna Artati, Qin Wang, Mika Tiainen, Antti J Kangas, Johannes Kettunen, Jari Kaikkonen, Vera Mikkilä, Antti Jula, Mika Kähönen, Terho Lehtimäki, Debbie A Lawlor, Tom R Gaunt, Alun D HughesNaveed Sattar, Thomas Illig, Jerzy Adamski, Thomas J Wang, Markus Perola, Samuli Ripatti, Ramachandran S Vasan, Olli T Raitakari, Robert E Gerszten, Juan-Pablo Casas, Nish Chaturvedi, Mika Ala-Korpela, Veikko Salomaa

Research output: Contribution to journalArticle (Academic Journal)peer-review

283 Citations (Scopus)


BACKGROUND: High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.

METHODS AND RESULTS: We applied quantitative nuclear magnetic resonance metabolomics to identify the biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the National Finnish FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the Southall and Brent Revisited (SABRE) study (n=2622; 573 events) and British Women's Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes mellitus, and medication. When further adjusting for routine lipids, 4 metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation, 1.18; 95% confidence interval, 1.12-1.24; P=4×10(-10)) and monounsaturated fatty acid levels (1.17; 1.11-1.24; P=1×10(-8)) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84-0.94; P=6×10(-5)) and docosahexaenoic acid levels (0.90; 0.86-0.95; P=5×10(-5)) were associated with lower risk. A risk score incorporating these 4 biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the 2 validation cohorts (relative integrated discrimination improvement, 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5% to 10% risk range (net reclassification, 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289).

CONCLUSIONS: Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated fatty acids, and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment.

Original languageEnglish
Pages (from-to)774-85
Number of pages12
Issue number9
Early online date8 Jan 2015
Publication statusPublished - 3 Mar 2015


  • Adolescent
  • Adult
  • Age Distribution
  • Aged
  • Biomarkers
  • Blood Pressure
  • Cardiovascular Agents
  • Cardiovascular Diseases
  • Child
  • Comorbidity
  • Diabetes Mellitus
  • Docosahexaenoic Acids
  • Endophenotypes
  • Fatty Acids, Monounsaturated
  • Fatty Acids, Omega-6
  • Female
  • Finland
  • Great Britain
  • Health Surveys
  • High-Throughput Screening Assays
  • Humans
  • Male
  • Mass Spectrometry
  • Metabolomics
  • Middle Aged
  • Nuclear Magnetic Resonance, Biomolecular
  • Phenylalanine
  • Prospective Studies
  • Risk Assessment
  • Risk Factors
  • Sex Distribution
  • Smoking
  • United States
  • Young Adult

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