A Hybrid Approach for Mining Metabolomic Data

International audienceIn this paper, we introduce a hybrid approach for analyzing metabolomic data about the so-called diabetes of type 2. The identi-cation of biomarkers which are witness of the disease is very important and can be guided by data mining methods. The data to be analyzed are massive and complex and are organized around a small set of individuals and a large set of variables (attributes). In this study, we based our experiments on a combination of ecient numerical supervised methods , namely Support Vector Machines (SVM), Random Forests (RF), and ANOVA, and a symbolic non supervised method, namely Formal Concept Analysis (FCA). The data mining strategy is based on ten spe-cic classication processes which are organized around three main operations , ltering, feature selection, and post-processing. The numerical methods are mainly used in ltering and feature selection while FCA is mainly used for visualization and interpretation purposes. The rst results are encouraging and show that the present strategy is well-adapted to the mining of such complex biological data and the identication of potential predictive biomarkers

Identification of Pre-frailty Sub-Phenotypes in Elderly Using Metabolomics

Aging is a dynamic process depending on intrinsic and extrinsic factors and its evolution is a continuum of transitions, involving multifaceted processes at multiple levels. It is recognized that frailty and sarcopenia are shared by the major age-related diseases thus contributing to elderly morbidity and mortality. Pre-frailty is still not well understood but it has been associated with global imbalance in several physiological systems, including inflammation, and in nutrition. Due to the complex phenotypes and underlying pathophysiology, the need for robust and multidimensional biomarkers is essential to move toward more personalized care. The objective of the present study was to better characterize the complexity of pre-frailty phenotype using untargeted metabolomics, in order to identify specific biomarkers, and study their stability over time. The approach was based on the NU-AGE project (clinicaltrials.gov, NCT01754012) that regrouped 1,250 free-living elderly people (65–79 y.o., men and women), free of major diseases, recruited within five European centers. Half of the volunteers were randomly assigned to an intervention group (1-year Mediterranean type diet). Presence of frailty was assessed by the criteria proposed by Fried et al. (2001). In this study, a sub-cohort consisting in 212 subjects (pre-frail and non-frail) from the Italian and Polish centers were selected for untargeted serum metabolomics at T0 (baseline) and T1 (follow-up). Univariate statistical analyses were performed to identify discriminant metabolites regarding pre-frailty status. Predictive models were then built using linear logistic regression and ROC curve analyses were used to evaluate multivariate models. Metabolomics enabled to discriminate sub-phenotypes of pre-frailty both at the gender level and depending on the pre-frailty progression and reversibility. The best resulting models included four different metabolites for each gender. They showed very good prediction capacity with AUCs of 0.93 (95% CI = 0.87–1) and 0.94 (95% CI = 0.87–1) for men and women, respectively. Additionally, early and/or predictive markers of pre-frailty were identified for both genders and the gender specific models showed also good performance (three metabolites; AUC = 0.82; 95% CI = 0.72–0.93) for men and very good for women (three metabolites; AUC = 0.92; 95% CI = 0.86–0.99). These results open the door, through multivariate strategies, to a possibility of monitoring the disease progression over time at a very early stage

Therapeutic paracetamol treatment in older persons induces dietary and metabolic modifications related to sulfur amino acids

Sulfur amino acids are determinant for the detoxification of paracetamol (N-acetyl-p-aminophenol) through sulfate and glutathione conjugations. Long-term paracetamol treatment is common in the elderly, despite a potential cysteine/glutathione deficiency. Detoxification could occur at the expense of anti-oxidative defenses and whole body protein stores in elderly. We tested how older persons satisfy the extra demand in sulfur amino acids induced by long-term paracetamol treatment, focusing on metabolic and nutritional aspects. Effects of 3 g/day paracetamol for 14 days on fasting blood glutathione, plasma amino acids and sulfate, urinary paracetamol metabolites, and urinary metabolomic were studied in independently living older persons (five women, five men, mean (+/- SEM) age 74 +/- 1 years). Dietary intakes were recorded before and at the end of the treatment and ingested sulfur amino acids were evaluated. Fasting blood glutathione, plasma amino acids, and sulfate were unchanged. Urinary nitrogen excretion supported a preservation of whole body proteins, but large-scale urinary metabolomic analysis revealed an oxidation of some sulfur-containing compounds. Dietary protein intake was 13% higher at the end than before paracetamol treatment. Final sulfur amino acid intake reached 37 mg/kg/day. The increase in sulfur amino acid intake corresponded to half of the sulfur excreted in urinary paracetamol conjugates. In conclusion, older persons accommodated to long-term paracetamol treatment by increasing dietary protein intake without any mobilization of body proteins, but with decreased anti-oxidative defenses. The extra demand in sulfur amino acids led to a consumption far above the corresponding population-safe recommendation

Effets comparatifs des acides gras omega-3 (ALA, EPA, DHA) sur la sensibilité à l’insuline des cellules musculaires C2C12 dans un contexte lipotoxique

Objectifs :Etudier le rôle des ω3 sur la lipotoxicité induite par l’acide gras saturé palmitate (PAL, C16:0) dans un modèle de cellule musculaire C2C12.Identifier les effets propres de chaque w3 (ALA, EPA et DHA) à dose équivalente sur la fluidité des membranes et la réponse à l’insuline.Suivre le devenir intracellulaire du [1-14C]-palmitate en présence d’un w3 et définir les classes de lipides altérées.Rechercher les voies de signalisation impliquées dans la modulation de la réponse à l’insuline

Network and systems medicine: Position paper of the European Collaboration on Science and Technology action on Open Multiscale Systems Medicine

Introduction: Network and systems medicine has rapidly evolved over the past decade, thanks to computational and integrative tools, which stem in part from systems biology. However, major challenges and hurdles are still present regarding validation and translation into clinical application and decision making for precision medicine. Methods: In this context, the Collaboration on Science and Technology Action on Open Multiscale Systems Medicine (OpenMultiMed) reviewed the available advanced technologies for multidimensional data generation and integration in an open-science approach as well as key clinical applications of network and systems medicine and the main issues and opportunities for the future. Results: The development of multi-omic approaches as well as new digital tools provides a unique opportunity to explore complex biological systems and networks at different scales. Moreover, the application of findable, applicable, interoperable, and reusable principles and the adoption of standards increases data availability and sharing for multiscale integration and interpretation. These innovations have led to the first clinical applications of network and systems medicine, particularly in the field of personalized therapy and drug dosing. Enlarging network and systems medicine application would now imply to increase patient engagement and health care providers as well as to educate the novel generations of medical doctors and biomedical researchers to shift the current organ- and symptom-based medical concepts toward network- and systems-based ones for more precise diagnoses, interventions, and ideally prevention. Conclusion: In this dynamic setting, the health care system will also have to evolve, if not revolutionize, in terms of organization and management

Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort

Scope: Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome. Methods and results: A case-control study nested in the prospective Three-City study includes participants aged &65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gen- der, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium-chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE-ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross-validated Area Under the Receiver Operating Curve = 75% [95% CI 70-80%] compared to 62% [95% CI 56-67%]. Conclusions: The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging

Food metabolomics applied in cohorts to accelerate the discovery of nutritional biomarkers

communication orale : Claudine ManachThe Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomics.The purpose of dietary assessment is to estimate usual and recent intake of foods, nutrients, bioactive compounds and food contaminants for exploration of associations with health outcomes and monitoring of population nutritional status. These data are still extremely difficult to obtain. Methods currently used are based on dietary questionnaires which have inherent limitations linked to self-reporting. A complementary approach to questionnaires is the use of biomarkers. However, only a few biomarkers have been properly validated, which do not cover the wide range offoods consumed. Metabolomics has emerged as a promising approach to discover nutritional biomarkers. Typically, plasma or urine samples collected before and after acute intake of a specific food are profiled using NMR or high resolution Mass Spectrometry (MS) and compared usingmultivariate statistics to pinpoint the signals reflecting the consumption of the target food. In a proof-of-concept study on citrus, we showed that urine profiling of cohort subjects stratified by consumption could be a more effective strategy for discovery of sensitive biomarkers of intake

Use of high resolution mass spectrometry for identification of specific biomarkers of coffee consumption

Présentation poster : Y. FillâtreThe Second International Congress of Translational Research in Human Nutrition is organised by the Research Centre in Human Nutrition (CRNH) of Auvergne, of which INRA is a member, in collaboration with NuGO, European Association of universities and research institutes in the field of nutrigenomicsANR Phenomenep ALIA-2010-007 Conseil Regional Auvergne-FEDER post-doc grantAs part of the ANR PhenoMeNEp project, non-targeted profiling is used to identify potential biomarkers of plant food consumption. Using 24 hour dietary recall and food frequency questionnaire data, 144 high (median 974 grams/day) and 66 low (median 305 grams/day) consumers of fruit and vegetables were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subjec