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 journalArticlepeer-review

479 Scopus citations


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 (US)
Pages (from-to)774-785
Number of pages12
Issue number9
StatePublished - 2015
Externally publishedYes


  • Amino acids
  • Biological markers
  • Fatty acids
  • Metabolomics
  • Risk factors

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Physiology (medical)


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