Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses.

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10-32), PRODH with proline (P-value  = 1.11×10-19), SLC16A9 with carnitine level (P-value  = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10-8) and 2p12 locus with valine (P-value  = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.

A metabolomic profile is associated with the risk of incident coronary heart disease.

BACKGROUND: Metabolomics, defined as the comprehensive identification and quantification of low-molecular-weight metabolites to be found in a biological sample, has been put forward as a potential tool for classifying individuals according to their risk of coronary heart disease (CHD). Here, we investigated whether a single-point blood measurement of the metabolome is associated with and predictive for the risk of CHD. METHODS AND RESULTS: We obtained proton nuclear magnetic resonance spectra in 79 cases who developed CHD during follow-up (median 8.1 years) and in 565 randomly selected individuals. In these spectra, 100 signals representing 36 metabolites were identified. Applying least absolute shrinkage and selection operator regression, we defined a weighted metabolite score consisting of 13 proton nuclear magnetic resonance signals that optimally predicted CHD. This metabolite score, including signals representing a lipid fraction, glucose, valine, ornithine, glutamate, creatinine, glycoproteins, citrate, and 1.5-anhydrosorbitol, was associated with the incidence of CHD independent of traditional risk factors (TRFs) (hazard ratio 1.50, 95% CI 1.12-2.01). Predictive performance of this metabolite score on its own was moderate (C-index 0.75, 95% CI 0.70-0.80), but after adding age and sex, the C-index was only modestly lower than that of TRFs (C-index 0.81, 95% CI 0.77-0.85 and C-index 0.82, 95% CI 0.78-0.87, respectively). The metabolite score was also associated with prevalent CHD independent of TRFs (odds ratio 1.59, 95% CI 1.19-2.13). CONCLUSION: A metabolite score derived from a single-point metabolome measurement is associated with CHD, and metabolomics may be a promising tool for refining and improving the prediction of CHD.

Metabolic profiling of accelerated aging ERCC1 d/- mice.

Aging is a fundamental biological process for which the mechanism is still largely unknown due to its complex and multifactorial nature. Animal models allow us to simplify this complexity and to study individual factors separately. As there are many causative links between DNA repair deficiency and aging, we studied the ERCC1(d/-) mouse, which has a modified ERCC1 gene, involved in the Nucleotide Excision Repair, and as a result has a premature aging phenotype. Profiling of these mice on different levels can give an insight into the mechanisms underlying the aging phenotype. In the current study, we have performed metabolic profiling of serum and urine of these mice in comparison to wild type and in relation to aging by (1)H NMR spectroscopy. Analysis of metabolic trajectories of animals from 8 to 20 weeks suggested that wild type and ERCC1(d/-) mutants have similar age-related patterns of changes; however, the difference between genotypes becomes more prominent with age. The main differences between these two genetically diverse groups of mice were found to be associated with altered lipid and energy metabolism, transition to ketosis, and attenuated functions of the liver and kidney.

Metabonomic investigation of human Schistosoma mansoni infection.

Schistosomiasis is a parasitic infection that is endemic in many developing countries in the tropics and subtropics afflicting more than 207 million people primarily in rural areas. After malaria, it is the second most important parasitic infection in terms of socio-economic and public health. Investigation of the host-parasite interaction at the molecular level and identification of biomarkers of infection and infection-related morbidity would be of value for improved strategies for treatment and morbidity control. To this end, we conducted a nuclear magnetic resonance (NMR) based metabonomics study involving a well-characterized cohort of 447 individuals from a rural area in Uganda near Lake Victoria with a high prevalence of Schistosoma mansoni, a species predominantly occurring in Africa including Madagascar and parts of South America. Cohort samples were collected from individuals at five time-points, before and after (one or two times) chemotherapy with praziquantel (PZQ). Using supervised multivariate statistical analysis of the recorded one-dimensional (1D) NMR spectra, we were able to discriminate infected from uninfected individuals in two age groups (children and adults) based on differences in their urinary profiles. The potential molecular markers of S. mansoni infection were found to be primarily linked to changes in gut microflora, energy metabolism and liver function. These findings are in agreement with data from earlier studies on S. mansoni infection in experimental animals and thus provide corroborating evidence for the existence of metabolic response specific for this infection.

Metabolic classification of South American Ilex species by NMR-based metabolomics.

The genus Ilex to which mate (Ilex paraguariensis) belongs, consists of more than 500 species. A wide range of metabolites including saponins and phenylpropanoids has been reported from Ilex species. However, despite the previous works on the Ilex metabolites, the metabolic similarities between species which can be used for chemotaxonomy of the species are not clear yet. In this study, nuclear magnetic resonance (NMR) spectroscopy-based metabolomics was applied to the classification of 11 South American Ilex species, namely, Ilex argentina, Ilex brasiliensis, Ilex brevicuspis, Ilex dumosa var. dumosa, I. dumosa var. guaranina, Ilex integerrima, Ilex microdonta, I. paraguariensis var. paraguariensis, Ilex pseudobuxus, Ilex taubertiana, and Ilex theezans. (1)H NMR combined with principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) showed a clear separation between species and resulted in four groups based on metabolomic similarities. The signal congestion of (1)H NMR spectra was overcome by the implementation of two-dimensional (2D)-J-resolved and heteronuclear single quantum coherence (HSQC). From the results obtained by 1D- and 2D-NMR-based metabolomics it was concluded that species included in group A (I. paraguariensis) were metabolically characterized by a higher amount of xanthines, and phenolics including phenylpropanoids and flavonoids; group B (I. dumosa var. dumosa and I. dumosa var. guaranina) with oleanane type saponins; group C (I. brasiliensis, I. integerrima, I. pseudobuxus and I. theezans) with arbutin and dicaffeoylquinic acids, and group D (I. argentina, I. brevicuspis, I. microdonta and I. taubertiana) with the highest level of ursane-type saponins. Clear metabolomic discrimination of Ilex species and varieties in this study makes the chemotaxonomic classification of Ilex species possible.