Podeu consultar el III Workshop anual INSA-UB complet a: http://hdl.handle.net/2445/118993Sessió 1. Pòster núm. 

Alay, Ania

Andrés Lacueva, Ma. Cristina

Marco Ramell, Anna

Palau Rodríguez, Magalí

Sànchez, Àlex (Sànchez Pla)

Tulipani, Sara

English

Diposit Digital de la Universitat de Barcelona

15  SESSIÓ 1           Pòster 3 Making sense of metabolomic data: comprehensive analysis of altered metabolic pathways in diabetes and obesity Palau-Rodriguez M1,2*, Marco-Ramell A1,2*ǂ, Alay A3, Tulipani S1, Sanchez-Pla A3,4, Andres-Lacueva C1,2ǂ 1Biomarkers & Nutrimetabolomics Laboratory, Nutrition and Food Science Department, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA-UB), Faculty of Pharmacy and Food Sciences, Pharmacy and Food Science Faculty, University of Barcelona, Barcelona/Spain. 2CIBER Fragilidad y Envejecimiento Saludable [CIBERfes], Instituto de Salud Carlos III [ISCIII], Madrid/Spain. 3Genetics, Microbiology and Statistics Department, Biology Faculty, University of Barcelona, Barcelona/Spain. 4Statistics and Bioinformatics Unit Vall d'Hebron Institut de Recerca (VHIR), Barcelona/Spain.  *Equally contributed to this poster and presenting authors. ǂCorresponding authors: anna.marco@ub.edu, candres@ub.edu Background and objectives:  Bioinformatic analysis and visualization techniques for ‘omics’ data are key tools for understanding complex biological systems. They reduce the complexity of data and allow generating hypotheses and searching for disease biomarkers. The aim of this work is to analyse the suitability of bioinformatic tools to interpret metabolomics datasets of a range of diseases including type 1 and 2 diabetes and obesity. Methodology:  We examined several disease datasets from metabolomics studies through different bioinformatic approaches: metabolic pathways, networks and disease-/functional-based analyses. Then we have analysed the accuracy of these tools to identify several traits of the datasets and their suitability to perform enrichment analyses Results and conclusions:  The analysis of metabolic pathways, small-scale systems of biochemical reactions and events of regulation and signalling, proved to be the most appropriate approach to analyse metabolomics datasets. Tools based on KEGG metabolic pathways were the most suitable ones as they allowed us examining metabolic alterations in type 1 and 2 diabetes and obesity and formulating hypotheses about the physiopathology of these diseases. For instance, alterations in the metabolism of amino acids, nitrogen, glutathione, sphingolipids and primary bile acids were revealed in diseased conditions. The study of altered metabolic pathways allowed us interpreting data from metabolomics studies and extracting very valuable information from them that might help identifying disease biomarkers and possible metabolic alterations related to diseases. This information could be translated to the clinical practice to predict metabolic alterations before the onset of diseases. Acknowledgements:  This work was supported by Project PI13/01172 and CIBERfes co-funded by Fondo Europeo de Desarrollo Regional. 2014SGR1566 award from Generalitat de Catalunya's Agency AGAUR. M.P-R acknowlegde the APIF-INSA-UB fellowship (University of Barcelona), A.M-R and S.T. the Juan de la Cierva fellowship (MINECO ), M.U-S the Ramon y Cajal fellowship (MINECO). 

Making sense of metabolomic data: comprehensive analysis of altered metabolic pathways in diabetes and obesity

http://diposit.ub.edu/dspace/bitstream/2445/120301/1/Palau_Rodriguez.pdf

Making sense of metabolomic data: comprehensive analysis of altered metabolic pathways in diabetes and obesity

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