Un Oslo

1. Un Oslo Rowett Un. Ulster Un Newcastle Un Lund Trinity DiFE IFR Un Cork EBI Rivm Rikilt TNO Un Reading Un Wageningen Un Maastricht Un Krakow Nu GO Un Munich Nutrigenomics: a new way of nutritional sciences. Un Florence Inserm Marseille The EU Network of Excellence establishing the European NutriGenomics Organisation Un Balearic Illes the European Nutrigenomics Organisation

2. Mission Statement NuGO will form a world-leading virtual centre of excellence: the European Nutrigenomics Organisation • to develop and integrate genomic technologies for the benefit of European nutritional science, • to facilitate the application of these technologies, • and to train a new generation of European scientists to use them. the European Nutrigenomics Organisation

3. 1.The nutrition and health relationship the European Nutrigenomics Organisation

4. What are the specific nutrition needs in earlier life stages to prevent chronic disease? Prevention (food) Nutrigenomics: prevention instead of therapy! well-being Therapy (drugs) age Adapted from Verrips et al, Cur.op.biotech. 12 (2001) 483-487 the European Nutrigenomics Organisation

5. Eye –Retinopathy Kidney –Nephropathy Nerves –Neuropathy Heart disease Systemic disease Loss of Homeostasis Treatment of early Type 2 Diabetes will have an enormous impact on Health Care : For real prevention, we need to act here, where multiple minor changes can only be captured throuhg “omics” approaches At the time of diagnosis Patients have lost 50% of their β-cell function β-cell Function in % 100 75 50 25 0 IGT Type 2 Diabetes Phase I Postprandial Hyperglycemia Type 2 Diabetes Phase II Type 2 Diabetes Phase III -8 -2 0 2 8 14 Years from diagnosis Lebovitz, Diabetes Rev., 1999

6. “old age disorders” and nutrition • Obesity & related disorders • Diabetes • Cardiovascular Diseases • Osteoporosis • Many forms of cancer (e.g. 60% of colon cancers) • Inflammatory disorders (e.g. arthritis) • Liver disorders • Various bowel disorders • Etc. the European Nutrigenomics Organisation

7. New approaches needed … • To get nutrition research to merge physiology and biomedical research • To work on disease prevention instead of therapy (which doesn`t work for nutrition) • To tackle the complex genetic differences involved in the nutrition and health relationship the European Nutrigenomics Organisation

8. 2.From nutrition to nutritional systems biology the European Nutrigenomics Organisation

9. Hexokinase ATP ADP glucose Glucose-6-phosphate It’s revolution in biological sciences. And it should also be so in Nutrition … Gene enzyme Metabolism the European Nutrigenomics Organisation

10. hexokinase ATP ADP Glucose Glucose-6-phosphate What about the effect of a big apple pie with lots of doublewhipped cream, espresso & sugar? What about the difference between you and me? the European Nutrigenomics Organisation

11. proteomics DNA array (transcriptomics) pI 4 5 6 7 Mr 97 23; GRP-78 31; HSP70 76; CH60_HUMAN 99; Probable disulfide isomerase 66 154; ATP-synthetase b-subunit 30 g-actin 272; GR78 HUMAN 45 341 376; ENOA_HUMAN 368; ENOA_HUMAN b-actin 13 537 592; KCRB_HUMAN 407; ENOA_HUMAN 447; CH60 HUMAN 30 20 730; ER60_HUMAN 705; Rho GDP 807 8 800; TPIS_HUMAN 902; TCTP_HUMAN 824 798 765 10 AOP-1 914; Natural killer cell enhancing factor 20.1 958; GTA1_HUMAN 7 10 1035 6 14.4 1088; NDKA_HUMAN 1 4 2 1277; COF1_HUMAN 5 1294; FABL_HUMAN 3 1297; thioredoxin 9 12 11 0 metabolomics 10 15 20 25 30 35 40 45 50 55 the technologies ... the European Nutrigenomics Organisation

12. How to approach these issue? The example of cholesterol homeostasis the European Nutrigenomics Organisation

13. Statin Specifically interfere in the HC-driven development of the disease 2) AT2 R antagonist Fibrate All used drugs have anti-atherosclerotic activity but act via different mechanisms. LXR Example of systems biology approach Induce disease with cholesterol in ApoE3L 1) High Chol diet Low Chol diet Control diet the European Nutrigenomics Organisation

14. Mode of action of drugs used LXR-activators (T0901317) Statins (Rosuvastatin) AT2R-antagonist (Irsebertan) Fibrates (Fenofibrate) blocks angiotensin II receptor inhibits HMG-Co reductase Activates PPARa Activates LXRa/b • Increases HDL-Chol • Stimulates FA uptake and metabolism; • stimulates reversecholesterol pathway • Anti-inflammatory:in liver and aortaNFkB; AP-1; Stat3 • stimulates reversecholesterol pathway • and bile acid synthesisanti-inflammatoryin aorta: • (MMPs, COX-2, IL-6) • Lowers LDL-Chol; • anti-inflammatoryin liver and aorta:NFkB, AP-1; • (VCAM,TNFa, MCP-1) • Lowers blood • pressure;anti-inflammatoy • NFkB • (NADP(H) oxidase) the European Nutrigenomics Organisation

15. Atherosclerosis model: APOE*3-Leiden Endpoint: organs Disease Development Systems Biology: a dynamic approach Groups: 1: Control diet 2: High cholesterol (HC) 3: HC + PPARa-activator (FF) 4: HC + Statin 5: HC + LXR-agonist 6: HC + AT2R-antagonist 7: Low cholesterol Over time: plasma samples • CLASSICAL ‘Non-OMICS’: • Score atherosclerosis • Follow plasma markers (TG, Chol, SAA, …) the European Nutrigenomics Organisation

16. Systems Biology: a dynamic approach Atherosclerosis model: APOE*3-Leiden Endpoint: organs Disease Development Groups: 1: Control diet 2: High cholesterol (HC) 3: HC + PPARa-activator (FF) 4: HC + Statin 5: HC + LXR-agonist 6: HC + AT2R-antagonist 7: Low cholesterol Over time: plasma samples • CLASSICAL ‘Non-OMICS’: • Score atherosclerosis • Follow plasma markers (TG, Chol, SAA, …) METABOLOMICS: LC-MS the European Nutrigenomics Organisation

17. LOW CHOL Statin AT2 R antagonist Fibrate Control LXR Systems Biology: a dynamic approach GENOMICS:Affymetrix 430 2.0 total genome array Atherosclerosis model: APOE*3-Leiden High CHOL Endpoint: organs Disease Development Overlap: crucial pathways contributing to disease development Groups: 1: Control diet 2: High cholesterol (HC) 3: HC + PPARa-activator (FF) 4: HC + Statin 5: HC + LXR-agonist 6: HC + AT2R-antagonist 7: Low cholesterol Over time: plasma samples • CLASSICAL ‘No-OMICS’: • Score atherosclerosis • Follow plasma markers (TG, Chol, SAA, …) METABOLOMICS: LC-MS the European Nutrigenomics Organisation

18. Metabolomics:Example of a base peak chromatogram obtained by analysis of plasma by the LC-MS lipid platform

19. Example of selected ion chromatograms of several triglycerides

20. NL: 14.64 100 4.28E6 Heparine-plasma + IS 14.60 Base Peak 80 MS 15.13 9.81 ee346176 7.53 15.35 11.70 9.84 60 19.40 9.45 19.53 40 14.19 18.98 7.26 7.19 20.01 15.62 7.65 16.31 20 10.19 16.84 9.23 7.04 8.38 18.81 20.18 13.40 11.26 8.67 6.77 18.57 20.67 12.99 17.21 21.30 5.30 22.76 23.69 24.40 6.43 0 14.67 Treatment-specific changes (MVA) of plasma lipids FF HC Statin control LC AT2R LXR the European Nutrigenomics Organisation

21. Genes of high interest in the processes involved – Now in their biochemical perspective

22. Role of ZNF202 in atherosclerosis: driver of pre-inflammatory processes

23. SCAP Cholesterol Sterols insulin INSIG2 ER srebf2 SREBP HMG CoA reductase Ubiquitinat. Proteas.degradation Golgi acetyl CoA carboxylase Genes for synthesis of cholesterol, fatty acids, triglycerides, phospholipids Fatty acid synthase LDL receptor SREBP: Key factor in regulation of cholesterol synthesis (the Goldstein & Brown scheme) WH, 17 february, 2005

24. Node indicates closely regulated part A correlation network, based on statistically selected variables (RNA, protein, metabolite) Box indicates type, up/down Line indicates relation the European Nutrigenomics Organisation

25. Cellular regulatory influence diagrams. Each gene group is represented by its number, along with those ontology labels that are overrepresented in that gene group. The mean level of gene group output influences across all 12 target groups is plotted versus the time step.

26. Cartographic representation of the metabolic network of E. coli. Each circle represents a module and is coloured according to the KEGG pathway classification of the metabolites it contains. Interactions between modules and nodes are depicted using lines, with thickness proportional to the number of actual links. Inset: metabolic network of E. coli, which contains 473 metabolites and 574 links. the European Nutrigenomics Organisation

27. Lessons: • Merge of physiology and biomedical research • Big machinery needed • Bioinformatics essential • Complexity of nutrition needs systems biology • Early effects need careful description • Multidisciplinary approach – datawarehousing? the European Nutrigenomics Organisation

28. The future of Nutrigenomics? brainwash Nutrigenomics Nutrition 2004 2005 2006 200X 20XX the European Nutrigenomics Organisation

29. “pure science” commerce communication ethics (science) science science science science The future of Nutrigenomics? Nutritional systems biology Nutrigenomics Personalised nutrition 2004 2005 2006 200X 20XX the European Nutrigenomics Organisation

30. 3. From nutrition to personalised nutrition the European Nutrigenomics Organisation

31. How to approach these issue? The example of cholesterol homeostasis the European Nutrigenomics Organisation

32. Effects of genetic differences on the processes invovled in cholesterol homeostasis Genetic polymorphism affecting cholesterol homeostasis Processes involved in cholesterol homeostasis the European Nutrigenomics Organisation

33. SNPs present in the LEPTIN gene Leptin is a protein that tells my brain that I have enough calories Identical mice, except for one gene… Many differences in the gene exist between humans the European Nutrigenomics Organisation

34. the European Nutrigenomics Organisation

35. the European Nutrigenomics Organisation

36. whole-genome patterns of common human DNA variation by genotyping 1,586,383 SNPs the European Nutrigenomics Organisation

37. How to study this genetic component of the nutrition and health relationship? • Pathological: medical genetics • Minor impact genes: genetic epidemiology (cohorts) • More minor impact genes: cohort merging • Multiple minor impact genes (real life): new approach needed (modelling?) the European Nutrigenomics Organisation

38. Nutrigenomics on the shelves? the European Nutrigenomics Organisation

39. The nutrigenomics data challenge Enormous amounts of data and results are and will become available [Genetic epidemiology, cohort studies, SNP databases, intervention studies, omics data, etc.] So, we should set up a system to better exploit this:one day, all study data should be available for all nutrition scientists, allowing them (us) to perform “in silico nutritional systems biology” Advanced information technology: the Nutrigenomics Information Portal the European Nutrigenomics Organisation

40. Un Oslo Rowett Un. Ulster Un Newcastle Un Lund Trinity DiFE IFR Un Cork EBI Rivm Rikilt TNO Un Reading Un Wageningen Un Maastricht Un Krakow Nu GO Un Munich Un Florence Inserm Marseille Un Balearic Illes the European Nutrigenomics Organisation

41. Nu GO Un Oslo Rowett Un. Ulster Un Newcastle Un Lund Trinity DiFE IFR Un Cork EBI Rivm Rikilt TNO Un Reading Un Wageningen Un Maastricht Un Krakow Un Munich Un Florence Inserm Marseille central datawarehouse Un Balearic Illes the European Nutrigenomics Organisation

42. Federated Database the European Nutrigenomics Organisation

43. The key issues: • Enormous amounts or data and results • Standardisation of data formats • Federation of databases • Merging of available studies • Perform new studies (partly) based on existing data. the European Nutrigenomics Organisation

44. 4.Let`s collaborate and shape this area together. The big lesson the European Nutrigenomics Organisation

45. The biomed to nutrition brainwash • Multiple targets, usually with low affinity – systems biology needed • Prevention, not therapy – new biomarkers needed • No disease genes but many minor SNPs – new approach, large numbers • No tradition – brainwash needed • No big money – collaboration needed • Tox based safety assessment – systems biology needed the European Nutrigenomics Organisation

46. Un Oslo Rowett Un. Ulster Un Newcastle Un Lund Trinity DiFE IFR Un Cork EBI Rivm Rikilt TNO Un Reading Un Wageningen Un Maastricht Un Krakow Nu GO Un Munich Nutrigenomics: a new way of nutritional sciences. Un Florence Inserm Marseille The EU Network of Excellence establishing the European NutriGenomics Organisation Un Balearic Illes the European Nutrigenomics Organisation

47. How? • Grant for integration – 17.23 ME • No IP barriers – contract signed by all partners, thus all activities and knowledge of all partners can be shared. • Standardization of methods, facilities (e.g. joint Affymetrix platform). • Joint Research Activities: Staff exchange, shift in research topics, etc • Joint information systems • Joint data storage (European Bioinformatics Institute). the European Nutrigenomics Organisation

48. How (2)? • Joint bioinformatics • Joint training • Merging 6 obesity & metabolic health cohorts • Linking to funding opportunities • Leading global efforts on nutrigenomics (e.g. metabolomics database) • Etc, etc. the European Nutrigenomics Organisation

49. - Gut Health - Metabolic health - Early life nutrition - Risk Benefit analysis • - Standardisation • Innovation • Human studies • Animal models • Bioinformatics • Information systems • & databases • - Training • Communication • Society • Commercialisation The current NuGO structure Three main areas: • Joint research • Integration • Spreading excellence the European Nutrigenomics Organisation

50. Year 1 Setting the stage Year 2 Implement Year 3 Integrate Year 4 onwards Reshape Research: - who does what? - what can we do together? - what are facility and technology needs Integration - what do we have? - what do we need? - what do others need? Research: - form small functional teams - develop key emerging areas - drive technology developments Integration - standardise / share technology - new bioinformatics - data / protocol standards The integration process the European Nutrigenomics Organisation