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Background  We aimed to identify novel metabolite and lipid signatures connected with the metabolic syndrome in a Dutch middle-aged population.    Methods  115 individuals with a metabolic syndrome score ranging from 0 to 5 [50 cases of the metabolic syndrome (score ≥ 3) and 65 controls] were enrolled from the Leiden Longevity Study, and LC/GC–MS metabolomics and lipidomics profiling were performed on fasting plasma samples. Data were analysed with principal component analysis and orthogonal projections to latent structures (OPLS) to study metabolite/lipid signatures associated with the metabolic syndrome. In addition, univariate analyses were done with linear regression, adjusted for age and sex, for the study of individual metabolites/lipids in relation to the metabolic syndrome.    Results  Data was available on 103 metabolites and 223 lipids. In the OPLS model with metabolic syndrome score (Y-variable), 9 metabolites were negatively correlated and 26 metabolites (mostly acylcarnitines, amino acids and keto acids) were positively correlated with the metabolic syndrome score. In addition, a total of 100 lipids (mainly triacylglycerides) were positively correlated and 10 lipids from different lipid classes were negatively correlated with the metabolic syndrome score. In the univariate analyses, the metabolic syndrome (score) was associated with multiple individual metabolites (e.g., valeryl carnitine, pyruvic acid, lactic acid, alanine) and lipids [e.g., diglyceride(34:1), diglyceride(36:2)].    Conclusion  In this first study on metabolomics/lipidomics of the metabolic syndrome, we identified multiple novel metabolite and lipid signatures, from different chemical classes, that were connected to the metabolic syndrome and are of interest to cardiometabolic disease biology.    Electronic supplementary material  The online version of this article (10.1007/s11306-019-1484-7) contains supplementary material, which is available to authorized users.

metabolomics

Metabolomic and lipidomic assessment of the metabolic syndrome in Dutch middle-aged individuals reveals novel biological signatures separating health and disease