Joram M. Posma

Fat, fibre and cancer risk in African Americans and rural Africans

Rates of colon cancer are much higher in African Americans (65:100,000) than in rural South Africans (<5:100,000). The higher rates are associated with higher animal protein and fat and lower fiber consumption, higher colonic secondary bile acids, lower colonic short chain fatty acid quantities and higher mucosal proliferative biomarkers of cancer risk in otherwise healthy middle aged volunteers. Here we investigate further the role of fat and fiber in this association. We performed two-week food exchanges in subjects from the same populations, where African Americans were fed a high-fiber, lowfat African-style diet, and rural Africans a high-fat low-fiber western-style diet under close supervision. In comparison to their usual diets, the food changes resulted in remarkable reciprocal changes in mucosal biomarkers of cancer risk and in aspects of the microbiota and metabolome known to affect cancer risk, best illustrated by increased saccharolytic fermentation and butyrogenesis and suppressed secondary bile acid synthesis in the African Americans.

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.

MetaboNetworks, an interactive Matlab-based toolbox for creating, customizing and exploring sub-networks from KEGG.

Summary: MetaboNetworks is a tool to create custom sub-networks in Matlab using main reaction pairs as defined by the Kyoto Encyclopaedia of Genes and Genomes and can be used to explore transgenomic interactions, for example mammalian and bacterial associations. It calculates the shortest path between a set of metabolites (e.g. biomarkers from a metabonomic study) and plots the connectivity between metabolites as links in a network graph. The resulting graph can be edited and explored interactively. Furthermore, nodes and edges in the graph are linked to the Kyoto Encyclopaedia of Genes and Genomes compound and reaction pair web pages. Availability and implementation: MetaboNetworks is available from http://www.mathworks.com/matlabcentral/fileexchange/42684. Contact: jmp111@ic.ac.uk or j.nicholson@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

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.

Dietary and urinary metabonomic factors possibly accounting for higher blood pressure of black compared with white Americans: Results of international collaborative study on macro-/micronutrients and blood pressure

African-Americans compared to non-Hispanic-White-Americans have higher systolic, diastolic blood pressure and rates of prehypertension/hypertension. Reasons for these adverse findings remain obscure. Analyses here focused on relations of foods/nutrients/urinary metabolites to higher African-American blood pressure for 369 African-Americans compared to 1,190 non-Hispanic-White-Americans ages 40-59 from 8 population samples. Standardized data were from four 24-hour dietary recalls/person, two 24-h urine collections, 8 blood pressure measurements; multiple linear regression quantitating role of foods, nutrients, metabolites in higher African-American blood pressure. Compared to non-Hispanic-White-Americans, African-Americans average systolic/diastolic pressure was higher by 4.7/3.4 mm Hg (men) and 9.0/4.8 mm Hg (women). Control for higher body mass index of African-American women reduced excess African-American systolic/diastolic pressure to 6.8/3.8 mm Hg. African American intake of multiple foods, nutrients related to blood pressure was less favorable - - less vegetables, fruits, grains, vegetable protein, glutamic acid, starch, fiber, minerals, potassium; more processed meats, pork, eggs, sugar-sweetened beverages, cholesterol, higher sodium to potassium ratio. Control for 11 nutrient and 10 non-nutrient correlates reduced higher African-American systolic/diastolic pressure to 2.3/2.3 mm Hg (52% and 33% reduction) (men) and to 5.3/2.8 mm Hg (21% and 27% reduction) (women). Control also for foods/urinary metabolites had little further influence on higher African-American blood pressure. Multiple nutrients with less favorable intakes by African-Americans than non-Hispanic-White-Americans account at least in part for higher African-American blood pressure. Improved dietary patterns can contribute to prevention/control of more adverse African-American blood pressure levels.Black compared with non-Hispanic white Americans have higher systolic and diastolic blood pressure and rates of prehypertension/hypertension. Reasons for these adverse findings remain obscure. Analyses here focused on relations of foods/nutrients/urinary metabolites and higher black blood pressure for 369 black compared with 1190 non-Hispanic white Americans aged 40 to 59 years from 8 population samples. Multiple linear regression, standardized data from four 24-hour dietary recalls per person, two 24-hour urine collections, and 8 blood pressure measurements were used to quantitate the role of foods, nutrients, and metabolites in higher black blood pressure. Compared with non-Hispanic white Americans, blacks’ average systolic/diastolic pressure was higher by 4.7/3.4 mm Hg (men) and 9.0/4.8 mm Hg (women). Control for higher body mass index of black women reduced excess black systolic/diastolic pressure to 6.8/3.8 mm Hg. Lesser intake of vegetables, fruits, grains, vegetable protein, glutamic acid, starch, fiber, minerals, and potassium, and higher intake of processed meats, pork, eggs, and sugar-sweetened beverages, along with higher cholesterol and higher Na/K ratio, related to in higher black blood pressure. Control for 11 nutrient and 10 non-nutrient correlates reduced higher black systolic/diastolic pressure to 2.3/2.3 mm Hg (52% and 33% reduction in men) and to 5.3/2.8 mm Hg (21% and 27% reduction in women). Control for foods/urinary metabolites had little further influence on higher black blood pressure. Less favorable multiple nutrient intake by blacks than non-Hispanic white Americans accounted, at least in part, for higher black blood pressure. Improved dietary patterns can contribute to prevention/control of more adverse black blood pressure levels.

The role of metabonomics as a tool for augmenting nutritional information in epidemiological studies

Most chronic diseases have been demonstrated to have a link to nutrition. Within food and nutritional research there is a major driver to understand the relationship between diet and disease in order to improve health of individuals. However, the lack of accurate dietary intake assessment in free‐living populations, makes accurate estimation of how diet is associated with disease risk difficulty. Thus, there is a pressing need to find solutions to the inaccuracy of dietary reporting. Metabolic profiling of urine or plasma can provide an unbiased approach to characterizing dietary intake and various high‐throughput analytical platforms have been used in order to implement targeted and nontargeted assays in nutritional clinical trials and nutritional epidemiology studies. This review describes first the challenges presented in interpreting the relationship between diet and health within individual and epidemiological frameworks. Second, we aim to explore how metabonomics can benefit different types of nutritional studies and discuss the critical importance of selecting appropriate analytical techniques in these studies. Third, we propose a strategy capable of providing accurate assessment of food intake within an epidemiological framework in order establish accurate associations between diet and health.

An analytical pipeline for quantitative characterization of dietary intake: application to assess grape intake.

Lack of accurate dietary assessment in free-living populations requires discovery of new biomarkers reflecting food intake qualitatively and quantitatively to objectively evaluate effects of diet on health. We provide a proof-of-principle for an analytical pipeline to identify quantitative dietary biomarkers. Tartaric acid was identified by nuclear magnetic resonance spectroscopy as a dose-responsive urinary biomarker of grape intake and subsequently quantified in volunteers following a series of 4-day dietary interventions incorporating 0 g/day, 50 g/day, 100 g/day, and 150 g/day of grapes in standardized diets from a randomized controlled clinical trial. Most accurate quantitative predictions of grape intake were obtained in 24 h urine samples which have the strongest linear relationship between grape intake and tartaric acid excretion (r(2) = 0.90). This new methodological pipeline for estimating nutritional intake based on coupling dietary intake information and quantified nutritional biomarkers was developed and validated in a controlled dietary intervention study, showing that this approach can improve the accuracy of estimating nutritional intakes.

Metabolic, immune, and gut microbial signals mount a systems response to Leishmania major infection

Parasitic infections such as leishmaniasis induce a cascade of host physiological responses, including metabolic and immunological changes. Infection with Leishmania major parasites causes cutaneous leishmaniasis in humans, a neglected tropical disease that is difficult to manage. To understand the determinants of pathology, we studied L. major infection in two mouse models: the self-healing C57BL/6 strain and the nonhealing BALB/c strain. Metabolic profiling of urine, plasma, and feces via proton NMR spectroscopy was performed to discover parasite-specific imprints on global host metabolism. Plasma cytokine status and fecal microbiome were also characterized as additional metrics of the host response to infection. Results demonstrated differences in glucose and lipid metabolism, distinctive immunological phenotypes, and shifts in microbial composition between the two models. We present a novel approach to integrate such metrics using correlation network analyses, whereby self-healing mice demonstrated an orchestrated interaction between the biological measures shortly after infection. In contrast, the response observed in nonhealing mice was delayed and fragmented. Our study suggests that trans-system communication across host metabolism, the innate immune system, and gut microbiome is key for a successful host response to L. major and provides a new concept, potentially translatable to other diseases.

MetaboSignal, a network-based approach for topological analysis of metabotype regulation via metabolic and signaling pathways

Abstract Summary MetaboSignal is an R package that allows merging metabolic and signaling pathways reported in the Kyoto Encyclopaedia of Genes and Genomes (KEGG). It is a network-based approach designed to navigate through topological relationships between genes (signaling- or metabolic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape of metabolic phenotypes. Availability and Implementation MetaboSignal is available from Bioconductor: https://bioconductor.org/packages/MetaboSignal/ Supplementary information Supplementary data are available at Bioinformatics online.