Metabolite Profiling and Cardiovascular Event Risk. Issue 9 (3rd March 2015)

• Record Type: Journal Article
• Authors: Würtz, Peter; Havulinna, Aki S.; Soininen, Pasi; Tynkkynen, Tuulia; Prieto-Merino, David; Tillin, Therese; Ghorbani, Anahita; Artati, Anna; Wang, Qin; Tiainen, Mika; Kangas, Antti J.; Kettunen, Johannes; Kaikkonen, Jari; Mikkilä, Vera; Jula, Antti; Kähönen, Mika; Lehtimäki, Terho; Lawlor, Debbie A.; Gaunt, Tom R.; Hughes, Alun D.; Sattar, Naveed; Illig, Thomas; Adamski, Jerzy; Wang, Thomas J.; Perola, Markus; Ripatti, Samuli; Vasan, Ramachandran S.; Raitakari, Olli T.; Gerszten, Robert E.; Casas, Juan-Pablo; Chaturvedi, Nish; Ala-Korpela, Mika; Salomaa, Veikko;
• Is Part Of: Circulation. Volume 131:Issue 9(2015)
• Publication Date: 2015-03-03
• Subjects: Blood -- Circulation -- Periodicals; Cardiovascular system -- Periodicals; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; Blood Circulation; Cardiovascular System; Vascular Diseases; 616.1
• DOI: 10.1161/CIRCULATIONAHA.114.013116
• Languages: English
• ISSNs: 0009-7322

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <sec> <title>Background—</title> <p>High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.</p> </sec> <sec> <title>Methods and Results—</title> <p>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 <italic>P</italic><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; <italic>P</italic>=4×10<sup>–10</sup>) and monounsaturated fatty acid levels (1.17; 1.11–1.24; <italic>P</italic>=1×10<sup>–8</sup>) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84–0.94; <italic>P</italic>=6×10<sup>–5</sup>) and docosahexaenoic acid levels (0.90; 0.86–0.95; <italic>P</italic>=5×10<sup>–5</sup>) 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).</p> </sec> <sec> <title>Conclusions—</title> <p>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.</p> </sec> </abstract>