My recent introduction talk for the Nutrigenomics Masterclass 2011in Wageningen (The Netherlands): How to use Nutrigenomics & molecular nutrition?  From challenges to solutions

1. 9th International Master class NutrigenomicsWageningen Defining healthFrom basic science to industrial relevance 1 1

2. Nutrigenomics Masterclass2011 How to use Nutrigenomics & molecular nutrition research? From challenges to solutions Michael MüllerNetherlands Nutrigenomics Centre & Nutrition, Metabolism and Genomics GroupDivision of Human Nutrition, Wageningen University

3. Why we need Nutrigenomics To understand nutrition & metabolic health To comprehensively phenotype To validate FFQs To enable strategies to optimize personal health To provide scientific evidence for health claims of “functional” foods Mechanisms Biomarkers Nutritional Science 2.0 Personal Nutrition Health claim support 3

4. Key questions What is your scientific problem? Why do you need nutrigenomics? What are the best suitable genomics tools for your nutrition research and how to apply them? One key question: What is the role of nutrition in the genotype-phenotype relationship? What is healthy and how to measure and quantify the health status? What is the impact of nutrigenomics for nutrition? What are the applications? What is the impact of nutrigenomics for the food (& pharma) industry?

5. Challenge 1: Successful ageingStay healthy as long as possible 100 % Health/ “Quality of life” time

6. Challenge 2: What's healthy?

7. Challenge 3: We have a tsunami of health problems

8. Challenge 4:Our “paleolithic” genes + modern diets Paleolithic era Modern Times 1.200.000 Generations between feast en famine 2-3 Generations in energy abundance % Energy % Energy 100 100 Grain Milk/-products Isolated Carbohydrates Isolated Fat/OilAlcohol Low-fat meatChicken Eggs Fish 50 Meat Chicken Fish 50 Fruit Vegetables (carrots) Nuts Honey Fruit Vegetables Beans 0 0

9. We are different

10. You are what you eat

11. How many human genes do we have?Not so many but….

12. Paternal Haplogroup:R1b1b2a1a1 a subgroup of R1b1b2 Maternal Haplogroup: X2c1 is a subgroup of X . Where I am coming from? Locations of haplogroup R1b1b2 circa 500 years ago, before the era of intercontinental travel Locations of haplogroupX circa 500 years ago, before the era of intercontinental travel

13. Genotype A genotype is an individual's collection of genes. The term also can refer to the two alleles inherited for a particular gene. The genotype is expressed when the information encoded in the genes. DNA is used to make protein and RNA molecules. The expression of the genotype contributes to the individual's observable traits, called the phenotype.

14. Phenotype A phenotype is an individual's observable traits, such as height, eye color, and blood type. The genetic contribution to the phenotype is called the genotype. Some traits are largely determined by the genotype, while other traits are largely determined by environmental factors (including nutrition).

15. Phenotype plasticity Phenotypic plasticity is the ability of an organism to change its phenotype in response to changes in the environment (e.g. nutrition).

16. 1 Genotype => 5 nutritional phenotypes 155 kg 76 kg

17. Duality of biological information:Epigenetic & Genetic

18. Nutrigenomics Quantification of the nutritional genotype-phenotype Lifestyle Nutrition Environment

19. Nutrigenomics will provide solutions ….but only if ask the right questions Complex Nutrition + Complex Genotypes + Complex Lifestyles + Complex Omics Technologies Simple solutions?

20. From mouse to men: From big to small signals Small Human muscle High Fat Diet decreases mRNA for genes involved in OXPHOS in healthy young men and mice Big Mouse muscle Diabetes 54:1926-1933, 2005

21. Challenges in nutrigenomics research: Small signals 24 H fasting 20 W high-fat 6 H WY KO mice vs C.

23. Identification of dietary sensors

24. Identification of target genes

25. Reconstruction of signaling pathways

26. Measurement of stress signatures

27. Identification of early biomarkers

28. Nutritional plasma proteome and metabolome + ++++ Complexity L. Afman & M. Müller J Am Diet Assoc. 2006;106:569-576.

29. Nutrigenomics – molecular nutrition and genomics 5 -10000 (?)metabolites 90000 (?)proteins 100000 (?) transcripts 20000 genes Müller & Kersten NRG 2003

30. 24 A scientific question: What is the role of “free fatty acids”? During fasting During long endurance activity In obese people “Hunger” signal or “Need for glucose” signal ? time (hours)

31. Fats FFA Remnant LPL VLDL Chylomicrons We are what we eat

32. Transcription-factor pathways mediating nutrient-gene interactions Müller & Kersten NRG 2003

33. Orphans? Endocrine receptorsSteroid hormonesHigh affinity Endocrine receptorsLipidsLow affinity Chawla, Science 2001 Nuclear hormone receptors

34. Intestine LXR Decreased cholesterol absorption FXR Increased bile salt recirculation PPARα Improved lipid handling Regulation of Cholesterol and Lipid Handling in Metabolic Organ Systems by Nuclear Receptors

35. Nuclear receptors – how does it work?

36. Understanding NutritionHow nutrients regulate our genes: via sensing molecular switches Improved organcapacity by PUFAs Am J ClinNutr. 2009; 90:415-24Am J ClinNutr. 2009;90:1656-64Mol CellBiology2009;29:6257-67 Am J ClinNutr. 2010;91:208-17BMC Genomics2009 Physiol. Genomics2009Circulation 2010Diabetes 2010 Cell Metabolism 2010 Am J Clin Nutr. 2007;86(5):1515-23 PLOS ONE 2008;3(2):e1681 BMC Genomics 2008; 9:231BMC Genomics 2008; 9:262J Biol Chem. 2008;283:22620-7Arterioscler Thromb Vasc Biol. 2009;29:969-74. Plos One 2009;4(8):e6796HEPATOLOGY 2010;51:511-522 J Clin Invest. 2004;114:94-103 J Biol Chem. 2006;28:934-44 Endocrinology. 2006;147:1508-16 Physiol Genomics. 2007;30:192-204Endocrinology. 2007;148:2753-63 BMC Genomics 2007; 8:267 Arterioscler Thromb Vasc Biol. 2007;27:2420-7

37. Is PPARa the hepatic fatty acid sensor? YES!

38. Disturbance of hepatic lipid handling leads to steatosis Mitochondrial fatty acid oxidation/ Fatty acid binding/activation ketone body synthesis Lipid transport Lipogenesis Peroxisomal/microsomal fatty acid oxidation Steatosis Lipases

39. PPARa controls lipid metabolism Mitochondrial fatty acid oxidation/ Fatty acid binding/activation ketone body synthesis Acsl1 Acsl3 Acsl4 Lipid transport Acsl5 Acsm3 Hahd2 Acaa2 Acss2 Hadha Adad8 Fabp1 Acot2 Hadhb Acad9 Fabp2 Acot9 Hadhsc Acad10 Cpt1a Fabp3 Abca1 Hibch Acads Slc27a1 Cpt1b Fabp4 Abcb4 Npc1 Hmgcl Acadm Slc27a2 Fabp5 Cpt2 Vldlr Abcb11 Hmgcs2 Acadl Crat Slc27a4 Abcg5 Lrp4 Slc25a20 Cd36 Acadvl Dci Abcg8 Slc22a5 Acat1 Decr1 Lipogenesis Miscellaneous Acaca Elovl5 Acacb Peroxisomal/microsomal Elovl6 Agpat2 Elovl7 Acot1 fatty acid oxidation Agpat3 Acot7 Gpam Agpat5 Hsd17b12 Acot10 Agpat6 Mod1 Acot12 Fads1 Adfp Mogat1 Scd2 Fads2 Mttp Adipor2 Slc25a10 Acaa1a Fasn Bdh Acox1 Scd1 Srebf1 Cyp4a10 Acaa1b Dgat1 Crot1 G0s2 Cyp4a12 Acot3 Ech1 Lepr Cyp4a14 Acot4 Ehhadh Lpin2 Aldh3a 2 Acot5 Lrp4 Decr2 Acot8 Hsd17b4 Mlycd Abcd2 Peci Scrab2 Glycerol metabolism Abcd3 Pctp Ppar a Pdk4 Gpd1 Pltp Pnlpa2 Gpd2 Ppargc1a Mgll Gyk Ucp2 Lipe Aqp3 Ucp3 Aqp7 Lipases Lipl Lipg Angptl4

40. DIETome database forevidence-basednutrition Evidence-basedNutrition Genes regulated by fatty acidsGenes regulated by high fat Genes also regulated by inflammation Query DIET GenomeEpigenomeTranscriptomeProteomeMetabolome “DIETome”database Query Nutrigenomics Potential BiomarkersOrgan-specific secreted proteins

41. Adipocytes at the crossroads of energy homeostasis

42. Nutrition Pharma Insulin ± oral agents Oral combination Oral monotherapy Diet & exercise Nutritional prevention of complex diseases needs new biomarkers Complex Disease 100 Different & similar targets 80 60 DISEASE STATE (%) 40 20 0 TIME (months/years) HomeostasisHealth L. Afman & M. Müller J Am Diet Assoc. 2006;106:569-576.

43. Metabolic defects leading to the development of hepatic steatosis

44. Metabolism & Inflammation

46. Different stages in NAFLD progression:

47. Molecular events involved in NASH pathogenesis:

48. Role of PPARa (Endocrinology 2008 & Hepatology 2010)

49. Role Kupffer cells (Hepatology 2010)

50. Role of macrophages in lipid metabolism (JBC 2008; Cell Metabolism 2010)hepatic steatosis steatohepatitis (NASH) & fibrosis cirrhosis

51. Interaction between WAT and liver tissue essential for NASH/NAFLD in C57Bl/6 mice Objective: Nonalcoholic fatty liver disease (NAFLD) is strongly linked to obesity and diabetes, suggesting an important role of adipose tissue in the pathogenesis of NAFLD. Here we aimed to investigate the interaction between adipose tissue and liver in NAFLD, and identify potential early plasma markers that predict NASH.

54. High fat diet-induced obesity 0 2 4 8 12 16 20 HFL LFL HFH LFH 25 20 * * 15 ** BW gain (g) * 10 * * * * 5 0 weeks under diet intervention Liver TG content Hepatomegaly ALT plasma activity 200 10 100 *** *** ** 160 8 80 ** 120 6 60 * Ratio LW/BW (%) mg TG/g liver ALT activity (UI) 80 4 40 * * 40 2 20 0 0 0 LFL LFH HFL HFH

55. Adipose dysfunction in HFH mice Leptin

56. A subpopulation of mice fed HFD develops NASH

57. Immunohistochemicalstaining confirms enhanced inflammation and early fibrosis in HFH mice Macrophage CD68 Collagen Stellate cell GFAP

58. Results I Mice exhibited pronounced heterogeneity in liver histological scoring, leading to classification into 4 subgroups: LF-low (LFL) responders displaying normal liver morphology, LF-high (LFH) responders showing benign hepatic steatosis, HF-low (HFL) responders displaying pre-NASH with macrovesicular lipid droplets, HF-high (HFH) responders exhibiting overt NASH characterized by ballooning of hepatocytes, presence of Mallory bodies, and activated inflammatory cells.

59. Upregulation of inflammatory and fibrotic gene expression in HFH responder mice

60. Adipose dysfunction in HFH mice

61. Change in adipose gene expression indicate adipose tissue dysfunction

62. Plasma proteins as early predictive biomarker for NASH in C57Bl/6 mice

63. Conclusions Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis. It points to several novel potential predictive biomarkers for NASH. Diabetes. 2010;59:3181-91.

65. To quantify the nutritional needs for optimized fitness at different life stages (“personalized” nutrition);

66. To improve early diagnostics of nutrition related disorders (“challenge tests”);

67. To support the development of “smart healthy food patterns” for modern mankind (healthy and tasty, sustainable, affordable)

69. 2 Meals a day, work as long as possible & embrace challenge Walter Breuning (1896 - 2011)

70. Thanks Lydia Afman Mark Bouwens Susan van Dijk DiederikEsser Sergio Lopez Lisette de Groot Marianne Geleijnse Ondine van de Rest MariekeBos Edith Feskens RikHeijligenberg Dianne Hoelen Jeanne de Vries Geert Heidema

71. Visit the Kröller-Müller Museum! 56