Putative biomarkers of environmental enteric disease fail to correlate in a cross-sectional study in two study sites in Sub-Saharan Africa

Environmental enteric dysfunction (EED) is an elusive, inflammatory syndrome of the small intestine thought to be associated with enterocyte loss and gut leakiness and lead to stunted child growth. To date, the gold standard for diagnosis is small intestine biopsy followed by histology. Several putative biomarkers for EED have been proposed and are widely used in the field. Here, we assessed in a cross-sectional study of children aged 2-5 years for a large set of biomarkers including markers of protein exudation (duodenal and fecal alpha-1-antitrypsin (AAT)), inflammation (duodenal and fecal calprotectin, duodenal, fecal and blood immunoglobulins, blood cytokines, C-reactive protein (CRP)), gut permeability (endocab, lactulose-mannitol ratio), enterocyte mass (citrulline) and general nutritional status (branched-chain amino acids (BCAA), insulin-like growth factor) in a group of 804 children in two Sub-Saharan countries. We correlated these markers with each other and with anemia in stunted and non-stunted children. AAT and calprotectin, CRP and citrulline and citrulline and BCAA correlated with each other. Furthermore, BCAA, citrulline, ferritin, fecal calprotectin and CRP levels were correlated with hemoglobin levels. Our results show that while several of the biomarkers are associated with anemia, there is little correlation between the different biomarkers. Better biomarkers and a better definition of EED are thus urgently needed

MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures

<p>Abstract</p> <p>Background</p> <p>One-dimensional ¹H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.</p> <p>Results</p> <p>We introduce a web server application, called MetaboHunter, which can be used for automatic assignment of ¹H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunter's metabolite identification methods.</p> <p>Conclusions</p> <p>MetaboHunter is a freely accessible, easy to use and user friendly ¹H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.</p> <p>Availability</p> <p><url>http://www.nrcbioinformatics.ca/metabohunter/</url></p

Metabolomic profiles of hepatocellular carcinoma in a European prospective cohort

Background: Hepatocellular carcinoma (HCC), the most prevalent form of liver cancer, is difficult to diagnose and has limited treatment options with a low survival rate. Aside from a few key risk factors, such as hepatitis, high alcohol consumption, smoking, obesity, and diabetes, there is incomplete etiologic understanding of the disease and little progress in identification of early risk biomarkers. Methods: To address these aspects, an untargeted nuclear magnetic resonance metabolomic approach was applied to pre-diagnostic serum samples obtained from first incident, primary HCC cases (n = 114) and matched controls (n = 222) identified from amongst the participants of a large European prospective cohort. Results: A metabolic pattern associated with HCC risk comprised of perturbations in fatty acid oxidation and amino acid, lipid, and carbohydrate metabolism was observed. Sixteen metabolites of either endogenous or exogenous origin were found to be significantly associated with HCC risk. The influence of hepatitis infection and potential liver damage was assessed, and further analyses were made to distinguish patterns of early or later diagnosis. Conclusion: Our results show clear metabolic alterations from early stages of HCC development with application for better etiologic understanding, prevention, and early detection of this increasingly common cancer.This work was supported by the French National Cancer Institute (L’Institut National du Cancer; INCA; grant number 2009-139; PI: M. Jenab). AF received financial support (BDI fellowship) from the Centre National de la Recherche Scientifique (CNRS) and Bruker Biospin. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, and Institut National de la Santé et de la Recherche Médicale (INSERM) (France); Deutsche Krebshilfe, Deutsches Krebsforschungszentrum (DKFZ), and Federal Ministry of Education and Research (Germany); Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC), National Research Council, Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy, and AIRE-ONLUS Ragusa, AVIS Ragusa, Sicilian Government (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), and Statistics Netherlands (the Netherlands); European Research Council (ERC; grant number ERC-2009-AdG 232997) and Nordforsk, and Nordic Center of Excellence Programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia (No. 6236) and Navarra, and ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Scientific Council, and Regional Government of Skåne and Västerbotten (Sweden); Cancer Research UK, Medical Research Council, Stroke Association, British Heart Foundation, Department of Health, Food Standards Agency, and Wellcome Trust (UK)

SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets

International audienc

Impact of trial registration on reporting of negative results in the literature

International audienc

Broad-ranging natural metabotype variation drives physiological plasticity in healthy control inbred rat strains.

Maintaining homeostasis in higher organisms involves a complex interplay of multiple ubiquitous and organ-specific molecular mechanisms that can be characterized using functional genomics technologies such as transcriptomics, proteomics, and metabonomics and dissected out through genetic investigations in healthy and diseased individuals. We characterized the genomic, metabolic, and physiological divergence of several inbred rat strains--Brown Norway, Lewis, Wistar Kyoto, Fisher (F344)--frequently used as healthy controls in genetic studies of the cardiometabolic syndrome. Hierarchical clustering of (1)H NMR-based metabolic profiles (n = 20 for urine, n = 16 for plasma) identified metabolic phenotype (metabotype) divergence patterns similar to the phylogenetic variability based on single nucleotide polymorphisms. However, the observed urinary metabotype variation exceeded that explainable by genetic polymorphisms. To understand further this natural variation, we used an integrative, knowledge-based network biology metabolic pathway analysis approach, coined Metabolite-Set Enrichment Analysis (MSEA). MSEA reveals that homeostasis and physiological plasticity can be achieved despite widespread divergences in glucose, lipid, amino acid, and energy metabolism in the host, together with different gut microbiota contributions suggestive of strain-specific transgenomic interactions. This work illustrates the concept of natural metabolomic variation, leading to physiologically stable albeit diverse strategies within the range of normality, all of which are highly relevant to animal model physiology, genetical genomics, and patient stratification in personalized healthcare