Journal
AMERICAN JOURNAL OF EPIDEMIOLOGY
Volume 186, Issue 9, Pages 1084-1096Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/aje/kwx016
Keywords
amino acids; biomarkers; drug development; fatty acids; Mendelian randomization; metabolomics; nuclear magnetic resonance; serum
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Funding
- Academy of Finland
- TEKES-the Finnish Funding Agency for Technology and Innovation
- Sigrid Juselius Foundation
- Novo Nordisk Foundation
- Finnish Diabetes Research Foundation
- Paavo Nurmi Foundation
- University of Oulu, Finland
- British Heart Foundation
- Wellcome Trust
- Medical Research Council, UK
- Academy of Finland University of Bristol
- UK Medical Research Council [MC_UU_12013/1, MC_UU_12013/5]
- Medical Research Council [MC_UU_12013/1, MC_UU_12013/5] Funding Source: researchfish
- Novo Nordisk Fonden [NNF15OC0015998] Funding Source: researchfish
- MRC [MC_UU_12013/5, MC_UU_12013/1] Funding Source: UKRI
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Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.
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