Journal
CIRCULATION
Volume 131, Issue 9, Pages 774-U52Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIRCULATIONAHA.114.013116
Keywords
amino acids; biological markers; fatty acids; metabolomics; risk factors
Funding
- Academy of Finland [139635, 137870, 250422, 251217, 266199]
- European Commission Seventh Framework Programme [BioSHaRE 261433]
- Sigrid Juselius Foundation
- Yrjo Jahnsson Foundation
- Emil Aaltonen Foundation
- Paavo Nurmi Foundation
- Finnish Foundation for Cardiovascular Research
- Medical Research Fund of Tampere
- UK Medical Research Council via the University of Bristol Integrative Epidemiology Unit (IEU) [MC_UU_12013/5]
- University of Oulu, Finland
- Wellcome Trust [WT082464AIA]
- British Heart Foundation [SP/07/001/23603]
- Diabetes UK [13/0004774]
- UK Department of Health Policy Research Programme - UK Medical Research Council [G1000427]
- US National Institutes of Health [R01 DK 081572, R01 HL98280]
- NHLBI [N01-HC-25195]
- MRC [G1000427, MC_UU_12013/5, MC_UU_12013/8] Funding Source: UKRI
- British Heart Foundation [PG/08/103/26133, CS/13/1/30327, PG/12/29/29497, PG/13/66/30442] Funding Source: researchfish
- Medical Research Council [G1000427, MC_UU_12013/8, MC_UU_12013/5] Funding Source: researchfish
- Academy of Finland (AKA) [250422, 266199, 266199, 250422] Funding Source: Academy of Finland (AKA)
Ask authors/readers for more resources
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 = 4x10(-10)) and monounsaturated fatty acid levels (1.17; 1.11-1.24; P = 1x10(-8)) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84-0.94; P = 6x10(-5)) and docosahexaenoic acid levels (0.90; 0.86-0.95; P = 5x10(-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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available