Isabel Garcia-Perez

Metabolome-wide association study identifies multiple biomarkers that discriminate north and south Chinese populations at differing risks of cardiovascular disease: INTERMAP study.

Rates of heart disease and stroke vary markedly between north and south China. A (1)H NMR spectroscopy-based metabolome-wide association approach was used to identify urinary metabolites that discriminate between southern and northern Chinese population samples, to investigate population biomarkers that might relate to the difference in cardiovascular disease risk. NMR spectra were acquired from two 24-h urine specimens per person for 523 northern and 244 southern Chinese participants in the INTERMAP Study of macro/micronutrients and blood pressure. Discriminating metabolites were identified using orthogonal partial least squares discriminant analysis and assessed for statistical significance with conservative family wise error rate < 0.01 to minimize false positive findings. Urinary metabolites significantly (P < 1.2 × 10(-16) to 2.9 × 10(-69)) higher in northern than southern Chinese populations included dimethylglycine, alanine, lactate, branched-chain amino acids (isoleucine, leucine, valine), N-acetyls of glycoprotein fragments (including uromodulin), N-acetyl neuraminic acid, pentanoic/heptanoic acid, and methylguanidine; metabolites significantly (P < 1.1 × 10(-12) to 2 × 10(-127)) higher in the south were gut microbial cometabolites (hippurate, 4-cresyl sulfate, phenylacetylglutamine, 2-hydroxyisobutyrate), succinate, creatine, scyllo-inositol, prolinebetaine, and trans-aconitate. These findings indicate the importance of environmental influences (e.g., diet), endogenous metabolism, and mammalian-gut microbial cometabolism, which may help explain north-south China differences in cardiovascular disease risk.

Urinary metabolic signatures of human adiposity

In a large-scale population-based metabolic phenotyping study, diverse sets of urinary metabolites, including gut microbial co-metabolites, were reproducibly associated with human adiposity. Urinary metabolites and adiposity Elliott et al. examined urinary metabolites over two 24-hour time periods in a large epidemiological study of obese individuals in the United States and UK. The urinary metabolites that were associated with adiposity were related to renal function, gut microbial metabolism, energy metabolism, skeletal muscle metabolism, branched-chain amino acid metabolism, and dietary intake. The urinary excretion patterns were reproducible over time and across the U.S. and UK population cohorts. Together, the metabolites described the metabolic disturbances of adiposity and were visualized in a metabolic reaction network. The network showed unforeseen dependencies and interconnectivities of biochemical pathways that were perturbed in adiposity and pointed to the collective importance of metabolism, diet, environment, and life-style in the ongoing obesity epidemic. Obesity is a major public health problem worldwide. We used 24-hour urinary metabolic profiling by proton (1H) nuclear magnetic resonance (NMR) spectroscopy and ion exchange chromatography to characterize the metabolic signatures of adiposity in the U.S. (n = 1880) and UK (n = 444) cohorts of the INTERMAP (International Study of Macro- and Micronutrients and Blood Pressure) epidemiologic study. Metabolic profiling of urine samples collected over two 24-hour time periods 3 weeks apart showed reproducible patterns of metabolite excretion associated with adiposity. Exploratory analysis of the urinary metabolome using 1H NMR spectroscopy of the U.S. samples identified 29 molecular species, clustered in interconnecting metabolic pathways, that were significantly associated (P = 1.5 × 10−5 to 2.0 × 10−36) with body mass index (BMI); 25 of these species were also found in the UK validation cohort. We found multiple associations between urinary metabolites and BMI including urinary glycoproteins and N-acetyl neuraminate (related to renal function), trimethylamine, dimethylamine, 4-cresyl sulfate, phenylacetylglutamine and 2-hydroxyisobutyrate (gut microbial co-metabolites), succinate and citrate (tricarboxylic acid cycle intermediates), ketoleucine and the ketoleucine/leucine ratio (linked to skeletal muscle mitochondria and branched-chain amino acid metabolism), ethanolamine (skeletal muscle turnover), and 3-methylhistidine (skeletal muscle turnover and meat intake). We mapped the multiple BMI-metabolite relationships as part of an integrated systems network that describes the connectivities between the complex pathway and compartmental signatures of human adiposity.

Objective assessment of dietary patterns by use of metabolic phenotyping: a randomised, controlled, crossover trial

Summary Background Accurate monitoring of changes in dietary patterns in response to food policy implementation is challenging. Metabolic profiling allows simultaneous measurement of hundreds of metabolites in urine, the concentrations of which can be affected by food intake. We hypothesised that metabolic profiles of urine samples developed under controlled feeding conditions reflect dietary intake and can be used to model and classify dietary patterns of free-living populations. Methods In this randomised, controlled, crossover trial, we recruited healthy volunteers (aged 21–65 years, BMI 20–35 kg/m2) from a database of a clinical research unit in the UK. We developed four dietary interventions with a stepwise variance in concordance with the WHO healthy eating guidelines that aim to prevent non-communicable diseases (increase fruits, vegetables, whole grains, and dietary fibre; decrease fats, sugars, and salt). Participants attended four inpatient stays (72 h each, separated by at least 5 days), during which they were given one dietary intervention. The order of diets was randomly assigned across study visits. Randomisation was done by an independent investigator, with the use of opaque, sealed, sequentially numbered envelopes that each contained one of the four dietary interventions in a random order. Participants and investigators were not masked from the dietary intervention, but investigators analysing the data were masked from the randomisation order. During each inpatient period, urine was collected daily over three timed periods: morning (0900–1300 h), afternoon (1300–1800 h), and evening and overnight (1800–0900 h); 24 h urine samples were obtained by pooling these samples. Urine samples were assessed by proton nuclear magnetic resonance (1H-NMR) spectroscopy, and diet-discriminatory metabolites were identified. We developed urinary metabolite models for each diet and identified the associated metabolic profiles, and then validated the models using data and samples from the INTERMAP UK cohort (n=225) and a healthy-eating Danish cohort (n=66). This study is registered with ISRCTN, number ISRCTN43087333. Findings Between Aug 13, 2013, and May 18, 2014, we contacted 300 people with a letter of invitation. 78 responded, of whom 26 were eligible and invited to attend a health screening. Of 20 eligible participants who were randomised, 19 completed all four 72 h study stays between Oct 2, 2013, and July 29, 2014, and consumed all the food provided. Analysis of 1H-NMR spectroscopy data indicated that urinary metabolic profiles of the four diets were distinct. Significant stepwise differences in metabolite concentrations were seen between diets with the lowest and highest metabolic risks. Application of the derived metabolite models to the validation datasets confirmed the association between urinary metabolic and dietary profiles in the INTERMAP UK cohort (p<0·0001) and the Danish cohort (p<0·0001). Interpretation Urinary metabolite models developed in a highly controlled environment can classify groups of free-living people into consumers of diets associated with lower or higher non-communicable disease risk on the basis of multivariate metabolite patterns. This approach enables objective monitoring of dietary patterns in population settings and enhances the validity of dietary reporting. Funding UK National Institute for Health Research and UK Medical Research Council.

Metabolic fingerprinting of Schistosoma mansoni infection in mice urine with capillary electrophoresis.

Schistosoma mansoni infection in mice has been fingerprinted using CE to study the capabilities of this technique as a diagnostic tool for this parasitic disease. Two modes of separation were used in generating the electrophoretic data, with each untreated urine sample the following methods were applied: (i) a fused‐silica capillary, operating with an applied potential of 18 kV, in micellar EKC (MEKC) and (ii) a polyacrylamide‐coated capillary, operating with an applied potential of −20 kV under zonal CZE conditions. By combining normal and reverse polarities in the data treatment we have extracted more information from the samples, which is a better approach for CE metabolomics. The traditional problems associated with variability in electrophoretic peak migration times for analytes were countered by using a dynamic programming algorithm for the electropherograms alignment. Principal component analyses of these aligned electropherograms and partial least square discriminant analysis (PLS‐DA) data are shown to provide a valuable means of rapid and sample classification. This approach may become an important tool for the identification of biomarkers, diagnosis and disease surveillance.

Increased colonic propionate reduces anticipatory reward responses in the human striatum to high-energy foods

Background: Short-chain fatty acids (SCFAs), metabolites produced through the microbial fermentation of nondigestible dietary components, have key roles in energy homeostasis. Animal research suggests that colon-derived SCFAs modulate feeding behavior via central mechanisms. In humans, increased colonic production of the SCFA propionate acutely reduces energy intake. However, evidence of an effect of colonic propionate on the human brain or reward-based eating behavior is currently unavailable. Objectives: We investigated the effect of increased colonic propionate production on brain anticipatory reward responses during food picture evaluation. We hypothesized that elevated colonic propionate would reduce both reward responses and ad libitum energy intake via stimulation of anorexigenic gut hormone secretion. Design: In a randomized crossover design, 20 healthy nonobese men completed a functional magnetic resonance imaging (fMRI) food picture evaluation task after consumption of control inulin or inulin-propionate ester, a unique dietary compound that selectively augments colonic propionate production. The blood oxygen level–dependent (BOLD) signal was measured in a priori brain regions involved in reward processing, including the caudate, nucleus accumbens, amygdala, anterior insula, and orbitofrontal cortex (n = 18 had analyzable fMRI data). Results: Increasing colonic propionate production reduced BOLD signal during food picture evaluation in the caudate and nucleus accumbens. In the caudate, the reduction in BOLD signal was driven specifically by a lowering of the response to high-energy food. These central effects were partnered with a decrease in subjective appeal of high-energy food pictures and reduced energy intake during an ad libitum meal. These observations were not related to changes in blood peptide YY (PYY), glucagon-like peptide 1 (GLP-1), glucose, or insulin concentrations. Conclusion: Our results suggest that colonic propionate production may play an important role in attenuating reward-based eating behavior via striatal pathways, independent of changes in plasma PYY and GLP-1. This trial was registered at clinicaltrials.gov as NCT00750438.

The microbiome of professional athletes differs from that of more sedentary subjects in composition and particularly at the functional metabolic level

Objective It is evident that the gut microbiota and factors that influence its composition and activity effect human metabolic, immunological and developmental processes. We previously reported that extreme physical activity with associated dietary adaptations, such as that pursued by professional athletes, is associated with changes in faecal microbial diversity and composition relative to that of individuals with a more sedentary lifestyle. Here we address the impact of these factors on the functionality/metabolic activity of the microbiota which reveals even greater separation between exercise and a more sedentary state. Design Metabolic phenotyping and functional metagenomic analysis of the gut microbiome of professional international rugby union players (n=40) and controls (n=46) was carried out and results were correlated with lifestyle parameters and clinical measurements (eg, dietary habit and serum creatine kinase, respectively). Results Athletes had relative increases in pathways (eg, amino acid and antibiotic biosynthesis and carbohydrate metabolism) and faecal metabolites (eg, microbial produced short-chain fatty acids (SCFAs) acetate, propionate and butyrate) associated with enhanced muscle turnover (fitness) and overall health when compared with control groups. Conclusions Differences in faecal microbiota between athletes and sedentary controls show even greater separation at the metagenomic and metabolomic than at compositional levels and provide added insight into the diet–exercise–gut microbiota paradigm.

Multiplatform characterization of dynamic changes in breast milk during lactation

The multicomponent analysis of human breast milk (BM) by metabolic profiling is a new area of study applied to determining milk composition, and is capable of associating BM composition with maternal characteristics, and subsequent infant health outcomes. A multiplatform approach combining HPLC‐MS and ultra‐performance LC‐MS, GC‐MS, CE‐MS, and 1H NMR spectroscopy was used to comprehensively characterize metabolic profiles from seventy BM samples. A total of 710 metabolites spanning multiple molecular classes were defined. The utility of the individual and combined analytical platforms was explored in relation to numbers of metabolites identified, as well as the reproducibility of the methods. The greatest number of metabolites was identified by the single phase HPLC‐MS method, while CE‐MS uniquely profiled amino acids in detail and NMR was the most reproducible, whereas GC‐MS targeted volatile compounds and short chain fatty acids. Dynamic changes in BM composition were characterized over the first 3 months of lactation. Metabolites identified as altering in abundance over lactation included fucose, di‐ and triacylglycerols, and short chain fatty acids, known to be important for infant immunological, neurological, and gastrointestinal development, as well as being an important source of energy. This extensive metabolic coverage of the dynamic BM metabolome provides a baseline for investigating the impact of maternal characteristics, as well as establishing the impact of environmental and dietary factors on the composition of BM, with a focus on the downstream health consequences this may have for infants.

Molecular validation of the acute phencyclidine rat model for schizophrenia: identification of translational changes in energy metabolism and neurotransmission

Administration of the noncompetitive N-methyl-D-aspartate (NMDA) receptor antagonist phencyclidine (PCP) to rodents is widely used as preclinical model for schizophrenia. Most studies on this model employ methods investigating behavior and brain abnormalities. However, little is known about the corresponding peripheral effects. In this study, we analyzed changes in brain and serum molecular profiles, together with alterations in behavior after acute PCP treatment of rats. Furthermore, abnormalities in peripheral protein expression of first and recent onset antipsychotic free schizophrenia patients were assessed for comparison with the preclinical model. PCP treatment induced hyperlocomotion and stereotypic behavior, which have been related to positive symptoms of schizophrenia. Multiplex immunoassay profiling of serum revealed molecular abnormalities similar to those seen in first and recent onset, antipsychotic free schizophrenia patients. Also, increased insulin levels were detected after administration of a glucose tolerance test (GTT), consistent with previous studies showing changes in insulin signaling in patients with schizophrenia. Finally, schizophrenia-relevant alterations in brain molecules were found in the hippocampus and to a lesser extent in the frontal cortex using liquid-chromatography mass spectrometry and (1)H nuclear magnetic resonance spectroscopy. In conclusion, this study identified behavioral and molecular alterations in the acute PCP rat model, which are also observed in human schizophrenia. We propose that the corresponding changes in serum in both animals and patients may have utility as surrogate markers in this model to facilitate discovery and development of novel drugs for treatment of certain pathological features of schizophrenia.

Breast milk metabolome characterization in a single-phase extraction, multiplatform analytical approach.

Breast milk (BM) is a biofluid that has a fundamental role in early life nutrition and has direct impact on growth, neurodevelopment, and health. Global metabolic profiling is increasingly being utilized to characterize complex metabolic changes in biological samples. However, in order to achieve broad metabolite coverage, it is necessary to employ more than one analytical platform, typically requiring multiple sample preparation protocols. In an effort to improve analytical efficiency and retain comprehensive coverage of the metabolome, a new extraction methodology was developed that successfully retains metabolites from BM in a single-phase using an optimized methyl-tert-butyl ether solvent system. We conducted this single-phase extraction procedure on a representative pool of BM, and characterized the metabolic composition using LC-QTOF-MS and GC-Q-MS for polar and lipidic metabolites. To ensure that the extraction method was reproducible and fit-for-purpose, the analytical procedure was evaluated on both platforms using 18 metabolites selected to cover a range of chromatographic retention times and biochemical classes. Having validated the method, the metabolic signature of BM composition was mapped as a metabolic reaction network highlighting interconnected biological pathways and showing that the LC-MS and GC-MS platforms targeted largely different domains of the network. Subsequently, the same protocol was applied to ascertain compositional differences between BM at week 1 (n = 10) and 4 weeks (n = 9) post-partum. This single-phase approach is more efficient in terms of time, simplicity, cost, and sample volume than the existing two-phase methods and will be suited to high-throughput metabolic profiling studies of BM.

Bidirectional Correlation of NMR and Capillary Electrophoresis Fingerprints: A New Approach to Investigating Schistosoma mansoni Infection in a Mouse Model

We demonstrate the statistical integration of nuclear magnetic resonance (NMR) spectroscopy and capillary electrophoresis (CE) data in order to describe a pathological state caused by Schistosoma mansoni infection in a mouse model based on urinary metabolite profiles. Urine samples from mice 53 days post infection with S. mansoni and matched controls were analyzed via NMR spectroscopy and CE. The two sets of metabolic profiles were first processed and analyzed independently and were subsequently integrated using statistical correlation methods in order to facilitate cross assignment of metabolites. Using this approach, metabolites such as 3-ureidopropionate, p-cresol glucuronide, phenylacetylglycine, indoxyl sulfate, isocitrate, and trimethylamine were identified as differentiating between infected and control animals. These correlation analyses facilitated structural elucidation using the identification power of one technique to enhance and validate the other, but also highlighted the enhanced ability to detect functional correlations between metabolites, thereby providing potential for achieving deeper mechanistic insight into the biological process.