Sebastiano Collino

Metabolic Effects of Dark Chocolate Consumption on Energy, Gut Microbiota, and Stress-Related Metabolism in Free-Living Subjects

Dietary preferences influence basal human metabolism and gut microbiome activity that in turn may have long-term health consequences. The present study reports the metabolic responses of free living subjects to a daily consumption of 40 g of dark chocolate for up to 14 days. A clinical trial was performed on a population of 30 human subjects, who were classified in low and high anxiety traits using validated psychological questionnaires. Biological fluids (urine and blood plasma) were collected during 3 test days at the beginning, midtime and at the end of a 2 week study. NMR and MS-based metabonomics were employed to study global changes in metabolism due to the chocolate consumption. Human subjects with higher anxiety trait showed a distinct metabolic profile indicative of a different energy homeostasis (lactate, citrate, succinate, trans-aconitate, urea, proline), hormonal metabolism (adrenaline, DOPA, 3-methoxy-tyrosine) and gut microbial activity (methylamines, p-cresol sulfate, hippurate). Dark chocolate reduced the urinary excretion of the stress hormone cortisol and catecholamines and partially normalized stress-related differences in energy metabolism (glycine, citrate, trans-aconitate, proline, beta-alanine) and gut microbial activities (hippurate and p-cresol sulfate). The study provides strong evidence that a daily consumption of 40 g of dark chocolate during a period of 2 weeks is sufficient to modify the metabolism of free living and healthy human subjects, as per variation of both host and gut microbial metabolism.

Metabolomic Applications to Decipher Gut Microbial Metabolic Influence in Health and Disease

Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial–mammalian cross talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids, and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease etiology, diagnostic stratification, and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR) spectroscopy and mass spectrometry provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation.

Clinical metabolomics paves the way towards future healthcare strategies

Metabolomics is recognized as a powerful top-down system biological approach to understand genetic-environment-health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation.

MARK-AGE biomarkers of ageing

Many candidate biomarkers of human ageing have been proposed in the scientific literature but in all cases their variability in cross-sectional studies is considerable, and therefore no single measurement has proven to serve a useful marker to determine, on its own, biological age. A plausible reason for this is the intrinsic multi-causal and multi-system nature of the ageing process. The recently completed MARK-AGE study was a large-scale integrated project supported by the European Commission. The major aim of this project was to conduct a population study comprising about 3200 subjects in order to identify a set of biomarkers of ageing which, as a combination of parameters with appropriate weighting, would measure biological age better than any marker in isolation.

Multivariate modeling strategy for intercompartmental analysis of tissue and plasma 1H NMR spectrotypes.

Multicompartmental metabolic profiling combined with multivariate data analysis offers a unique opportunity to explore the multidimensional metabolic relationships between various biological matrices. Here, we applied unsupervised chemometric methods for integrating 1H NMR metabolic profiles from mouse plasma, liver, pancreas, adrenal gland and kidney cortex matrices in order to infer intercompartments functional links. Principal Component Analysis (PCA) revealed metabolic differences between matrices but contained limited information on intercompartment metabolic relationships. Multiway PCA enabled the assessment of interindividual metabolic variability across multiple compartments in a single model and, therefore, metabolic correlations between different organs and circulating biofluids. However, this approach does not provide information on the relative contribution of one compartment to another. Integration of metabolic profiles using Multivariate Curve Resolution (MCR) and Parallel Factor Analysis (PARAFAC) methods provided an overview of functional relationships across matrices and enabled the characterization of compartment-specific metabolite signatures, the spectrotypes. In particular, the spectrotypes describe biochemical profiles specific or common to different biological compartments. Consequently, MCR-ALS and PARAFAC appeared to be better adapted for stepwise variable and compartment selection for further correlation analysis. Such a combination of chemometric techniques could provide new research avenues to assess the efficacy of drug or nutritional interventions on targeted organs.

Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links.

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on 1H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10−8) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10−44) and lysine (rs8101881, P = 1.2×10−33), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohns disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.

Metabolomics perspectives in pediatric research

Increasing evidence points toward the critical and long-term involvement of prenatal and early nutrition and lifestyle on later health and disease risk predisposition. Metabolomics is now a well-established top–down systems biology approach that explores the genetic–environment–health paradigm. The generalization of such approaches has opened new research areas to deepen our current understanding of many physiological processes, as well as foods and nutrient functionalities in target populations. It is envisioned that this will provide new avenues toward preventive medicine and prognostic strategies for tailored therapeutic and personalized nutrition management. The development of systems biology approaches and the new generation of biomarker patterns will provide the opportunity to associate complex metabolic regulations with the etiology of multifactorial pediatric diseases. This may subsequently lead to the development of system mechanistic hypotheses that could be targeted with new nutritional personalized concepts. Therefore, this review aims to describe recent applications of metabolomics in preclinical and clinical fields with insights into disease diagnostics/monitoring and improvement of homeostasis metabolic regulation that may be translatable to novel therapeutic and nutrition advances in pediatric research.

Early Metabolic Adaptation in C57BL/6 Mice Resistant to High Fat Diet Induced Weight Gain Involves an Activation of Mitochondrial Oxidative Pathways

We investigated the short-term (7 days) and long-term (60 days) metabolic effect of high fat diet induced obesity (DIO) and weight gain in isogenic C57BL/6 mice and examined the specific metabolic differentiation between mice that were either strong-responders (SR), or non-responders (NR) to weight gain. Mice (n = 80) were fed a standard chow diet for 7 days prior to randomization into a high-fat (HF) (n = 56) or a low-fat (LF) (n = 24) diet group. The (1)H NMR urinary metabolic profiles of LF and HF mice were recorded 7 and 60 days after the diet switch. On the basis of the body weight gain (BWG) distribution of HF group, we identified NR mice (n = 10) and SR mice (n = 14) to DIO. Compared with LF, HF feeding increased urinary excretion of glycine conjugates of β-oxidation intermediate (hexanoylglycine), branched chain amino acid (BCAA) catabolism intermediates (isovalerylglycine, α-keto-β-methylvalerate and α-ketoisovalerate) and end-products of nicotinamide adenine dinucleotide (NAD) metabolism (N1-methyl-2-pyridone-5-carboxamide, N1-methyl-4-pyridone-3-carboxamide) suggesting up-regulation of mitochondrial oxidative pathways. In the HF group, NR mice excreted relatively more hexanoylglycine, isovalerylglycine, and fewer tricarboxylic acid (TCA) cycle intermediate (succinate) in comparison to SR mice. Thus, subtle regulation of ketogenic pathways in DIO may alleviate the saturation of the TCA cycle and mitochondrial oxidative metabolism.

A Whole-Grain–Rich Diet Reduces Urinary Excretion of Markers of Protein Catabolism and Gut Microbiota Metabolism in Healthy Men after One Week

Epidemiological studies consistently find that diets rich in whole-grain (WG) cereals lead to decreased risk of disease compared with refined grain (RG)-based diets. Aside from a greater amount of fiber and micronutrients, possible mechanisms for why WGs may be beneficial for health remain speculative. In an exploratory, randomized, researcher-blinded, crossover trial, we measured metabolic profile differences between healthy participants eating a diet based on WGs compared with a diet based on RGs. Seventeen healthy adult participants (11 female, 6 male) consumed a controlled diet based on either WG-rich or RG-rich foods for 2 wk, followed by the other diet after a 5-wk washout period. Both diets were the same except for the use of WG (150 g/d) or RG foods. The metabolic profiles of plasma, urine, and fecal water were measured using (1)H-nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry (plasma only). After 1 wk of intervention, the WG diet led to decreases in urinary excretion of metabolites related to protein catabolism (urea, methylguanadine), lipid (carnitine and acylcarnitines) and gut microbial (4-hydroxyphenylacetate, trimethylacetate, dimethylacetate) metabolism in men compared with the same time point during the RG intervention. There were no differences between the interventions after 2 wk. Urinary urea, carnitine, and acylcarnitine were lower at wk 1 of the WG intervention relative to the RG intervention in all participants. Fecal water short-chain fatty acids acetate and butyrate were relatively greater after the WG diet compared to the RG diet. Although based on a small population and for a short time period, these observations suggest that a WG diet may affect protein metabolism.

Specific Dietary Preferences Are Linked to Differing Gut Microbial Metabolic Activity in Response to Dark Chocolate Intake

Systems biology approaches are providing novel insights into the role of nutrition for the management of health and disease. In the present study, we investigated if dietary preference for dark chocolate in healthy subjects may lead to different metabolic response to daily chocolate consumption. Using NMR- and MS-based metabolic profiling of blood plasma and urine, we monitored the metabolic response of 10 participants stratified as chocolate desiring and eating regularly dark chocolate (CD) and 10 participants stratified as chocolate indifferent and eating rarely dark chocolate (CI) to a daily consumption of 50 g of dark chocolate as part of a standardized diet over a one week period. We demonstrated that preference for chocolate leads to different metabolic response to chocolate consumption. Daily intake of dark chocolate significantly increased HDL cholesterol by 6% and decreased polyunsaturated acyl ether phospholipids. Dark chocolate intake could also induce an improvement in the metabolism of long chain fatty acid, as noted by a compositional change in plasma fatty acyl carnitines. Moreover, a relationship between regular long-term dietary exposure to a small amount of dark chocolate, gut microbiota, and phenolics was highlighted, providing novel insights into biological processes associated with cocoa bioactives.