Harmonising and Unifying Blood Metabolomic Analysis Networks (HUMAN)

Metabolomics provides a real-time view of the metabolic state of the examined samples. The past decade the field showed strong growth, however limitations intrinsic to the field hinder further application in epidemiology level. Key obstacles include: variety of analyte molecular structures, slow marker identification, large differences in concentrations, poor validation, incomplete combination of data from different analyses and fragmentation of research. The consortium brings together scientists from different complementary disciplines and sectors to collaborate and set a research training network, combining infrastructure experience, knowledge and skills. The research scope is to identify the source of problems that hinder development, and recommend measures to overcome these. Training through research will promote a new generation of omics researchers. Networking, joining forces via secondments will enhance research
productivity transfer of knowledge. The project will train 10 ESRs in work-packages aiming toward improvement of design of experiment, harmonization of analytical methods, improved Data Mining and biochemical pathway analysis and translational research. Application will be in the study of blood metabolome of exhaustive physical exercise.
We aim to study sample stability & preparation (including blood and alternative forms such as dried blood spots), biomarker identification, exploitation of multiple datasets, promote standard procedures, develop robust pipelines, develop and implement machine searchable notations of metadata, central database for data storage, compare datasets, automate cross-laboratory data combination, develop novel algorithms for multidimensional data mining and reconstruct biochemical pathways. The overall goal is to train the ESRs in cutting edge metabolomics research and at the same time provide proof of concept of democratizing metabolomics by the use of patient centric sampling.