Abstract

To date, many genome-wide association studies (GWAS) have examined genetic variation in >100 individual blood metabolites or smaller panels of metabolites known to be related to cardiovascular diseases, such as lipids and glucose homeostasis markers. Emerging high-throughput technologies to determine components of the serum metabolome in combination with an unbiased GWAS approach may be capable of identifying genetic variation and unravel novel disease pathways beyond traditionally known blood metabolites in unselected population-based samples. Although less sensitive than mass spectrometry, nuclear magnetic resonance (NMR) spectroscopy is one of the methods that has emerged to examine serum metabolites, with little blood sample preparation required. NMR can be applied at a larger scale for targeted analyte measurement. In 5 cohorts of >8000 unrelated individuals from the Finnish population and 561 twins, 117 fasting serum metabolites were measured and 99 additional variables derived.1 Metabolites chosen covered mostly lipoproteins and lipids but also small molecules such as pyruvic and amino acids. Derived variables, predominantly ratios of metabolites, were selected to represent enzymatic reactions of lipolysis, proteolysis, ketogenesis, glycolysis, and their substrates. Three molecular windows for metabolite quantification were applied on the metabolomics platform (ie, separate windows for lipoproteins, lipids, and low-molecular-weight metabolites). Genetic variation of the phenotypes was determined through GWAS applying a comprehensive imputation panel of 7.7 million single …

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