1. How would nutrition research look like in 10 years, what infrastructures do we need and how do we make these?

2. 1 – The world is my cohort Classical epidemiology will be dead E-health is accessible for research purposes Everybody has open access to all cohort data Virtual cohorts are created by personalized health monitoring and internet communication Food intake quantification is obsolete, and fully replaced by ‘health biomarkers’

3. the “bowtie” principle food / intake absorbed / plasma late effects regulation of homeostasis and efficacy Target organ concentration early effects Individual variation THIS is the point from which nutrient requirements need to be derived Not these …

4. 2 - My health is my concern Personal health monitoring will be daily practice. Access to my health information is normal: my genomic variation is determined and translated in life style advice I have PDA-access to my health status, fed by a series of frequent bioassays in my home setting. My electronic medical record is integrated Food companies have evolved into life style companies, offering diet suggestions based on my lifestyle and monitored health status

5. Routine Analyses on Individual Patients with 10 years Copied from a presentation of Lee Hood Institute for Systems Biology, Seattle

6. Individual Patient High Throughput Assays of the Future Complete individual genome sequences—predictive health history—will be done sequencing families Sequence 1000 transcriptomes simultaneously in one DNA sequencing run from single cancer cells or single cells from biopsies--to stratify disease. 2500 blood organ-specific blood proteins—twice per year (50 proteins from 50 organs)—wellness assessment. Analyze 10,000 B cells and 10,000 T cells for the functional regions of their immune receptors—past and present immune responsiveness—follow vaccinations. Analyze individual stem (iPS) cells from each individual differentiated to relevant tissues to get important phenotypic information—molecular and imaging.

7. 3 - Nutrition research Extensive phenotyping is the keyword Nutritional intervention studies are performed according to accepted standards and protocols This allows seamless merging of study data and integration in WWW information sources. Access to hundreds of ‘gold standard’ intervention studies creates a new virtual cohort and goldmine for ‘in silico nutrition’ research.

8. A major transition! Basic drivers Technology becomes standard and cheap Information becomes accessible Results are shared Participatory research

9. Divergence into 2 types of studies Observational – “worldwide” Interventional – extensive phenotyping

10. So what tools does nutrition research need? 1.Generic information systems 2.Dedicated nutrition research tools 3.A way to share, integrate and evaluate results

11. Generic information systems These are the tools that provide in depth generic biological information Genetics and genetic variation databases Genotype – phenotype translation tools Protein-protein interaction databases Transcriptome databases and bioinformatics Pathway information and tools Etc etc

12. Dedicated nutrition research tools Food composition databases Elaborate information on “nutrient biology” Accepted research methodologies

13. A way to share, integrate and evaluate results My results are mine until I decide to share, and with whom. Once I decide to share, my results connect to all other results because the formats and methods are identical. The advantages of sharing are so obvious that I cannot wait for the moment … We need an IT-infrastructure that facilitates this.

14. Un Oslo TUM Un Florence Un Balearic Illes Un Cork UCD Rowett Un Newcastle Un Reading IFR DiFE Un Krakow Inserm Marseille TNO Un Wageningen Un Maastricht EBI Un Lund Rikilt Rivm Un Ulster Nu GOGO GOGO INRA Clermont ferrant Un Nottingham Un Kiel Un Freiburg Un Kopenhagen Un Kuopio INRAN Tufts Un (Boston) ICLondon Un Varna GSF + 11 groups applying NCC as a nutrigenomics research infrastructure: an introduction

15. The evolution of NuGO Research concepts collaborate Proof of concept, collaboration and technology Externally funded projects using infrastructure and network Technology Implement In network Adapt from mainstream Standardize and test infrastructure technology, informatics and data basis for new nutrition research history

16. –Design and plan –Conduct studies –Share –Disseminate - evaluate –Develop Protocols and Procedures The human study pipeline

17. –Design and plan –Bio-ethics –Human studies –Conduct studies –Standard Operating Procedures –Human studies pipeline –Omics technology pipelines –Share –Metabolomics portal –NuGOwiki –e-learning module –Disseminate and evaluate –Workshops –Publications –Develop –Assessment of dietary intake –Micronutrient exemplar Protocols and Procedures The human study pipeline (detail)

19. Integrate the human study pipeline with all technologies – current state

20. proteomics transcriptomics metabolomics genetics biomarkers Food intake study Study design evaluation sampling & storage measurements data preprocessing bioinformatics sharing Integrate the human study pipeline with all technologies – next design phase

21. Transcriptomics pipeline –Study –Array admin –Sample prep –Hybridize –Pre-process –Store and share –Disseminate and evaluate  So far, 4000 NuGO Affymetrix arrays have entered in this pipeline  This year, 130 young NuGO scientist will have had an intense training in bioinformatics  Both in house and centralized services  Tailor made routines developed  LIMS adapted to nutrition studies Same pipeline for nutritional metabolomics Based on two NuGO symposia and collaboration with Metabolomics Society

22. Results of the first nutritional metabolomics workshop We are now organizing the third – which is STUPID! Technology should be developed by the technology community These efforts are now alligned with the Metabolomics Society

23. For each of the technologies in the nutritional phenotype, NuGO develops a pipeline of tools analytical technology procedures standards database share analyse preprocess

24. transcriptomics procedures standards database analyse preprocess metabolomics biomarkers Food intake genetics Study design Evaluation - single technology - single study - multiple studies The nutritional phenotype database

25. the “bowtie” principle food / intake absorbed / plasma late effects regulation of homeostasis and efficacy Target organ concentration early effects Individual variation THIS Is the area targeted by extensive phenotyping

26. dbNP – general scheme

27. Fundamentals of dbNP Environment for extensive phenotyping in nutrition studies Study driven instead of technology driven All part stick to basic rules (a.o. ISA-tab) Nobody owns - everybody contributes (open source community project) You have your own local installation – free to adapt All parts are modular – take out one, insert yours –example: Arraytrack, Base, Madmax: input is the same: RNA-sample Output is the same: annotated relative gene expressions Made for nutrition research, applications are much broader Nutrigenomics Organisation is ‘governing body’

28. The birth process of an infrastructure discovery isolated pioneers broadening acceptance commercial push minimal data standards technology harmonisation standardized technology standard operating procedures community overhaul data federation virtual institute (society) fully accepted data standard federated or real institute

29. The information providers – Elixir model in Europe (virtual) nutrition research infrastructure

30. Or, from a dbNP perspective: metabolite info genome info Biological information Bioinformatics Toolbox Food composition Food metabolome Intake Nutition information Genepattern R proteome db metabolite db Generic Data storage GEO Array Express Pathvisio Cytoscape Specific db`s SelenoDB HuGE- net Polyphenol db proteome info

31. Now that we know this, we can act accordingly … A small problem: everybody needs it, nobody wants to do it. –(“Saturday morning projects”)

32. Datasharing IT network within NuGO: distributed information system Control & IP remain with partner Data and results are standardized Software is centrally updated  “ ready to share”

33. The NuGO Black Box (NBX) distributed network

34. Partner 2: Transcriptome analysis Statistics Partner 3 Intervention study Clinical chemistry Metabolome analysis Partner 4 Intervention study Biomarker analysis Partner 5: Intervention study Partner 1: Intervention study NBX

35. Study A NBX Open access server

36. From NuGO to NuGO Infrastructure needs a global dimension, so we transform the European Nutrigenomics Organisation (NuGO) to the Nutrigenomics Organisation (NuGO)

37. So The research infrastructure side of NuGO develops into a bridge between generic infrastructure (NCBI, EBI) and the nutrition research community NuGO moves from European to Global NuGO moves from a funded organisation to a community effort

38. Conditions for the optimal roadmap Between Wild West and Kremlin? Between Chaos and Despautism? Create a “servant leadership model”? –nobody owns –everybody is recognized –all contribute –complete data ownership –agreed standards –agreed agenda Forget about ego`s –only ONE global roadmap