Intro into Nutrigenomics & molecular nutrition research


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

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  • Inflammation has been associated with many disease phenotypes including steatohepatitis or diabetes. This relationship is in particular when inflammation is chronic or non-resolving. There is an interaction between metabolism and inflammation with positive or negative consequences with respect to organ and systemic health.In my talk I will briefly discuss two unpublished studies, one investigating the important interaction of WAT and liver in particular under conditions of diet-induced obesity. Organ-specific macrophages in WAT and liver play an crucial role in progressing organ-specific inflammatory phenotypes. In the second study we found very interesting interaction between dietary fat and macrophages in mesenteric lymph nodes that are exposed postprandially to very high concentrations of chylomicrons. We used a k.o. mouse for ANGPTL4 and could show that chronic consumption of saturated fat can be deadly.
  • A) Bodyweight changes in the 4 subgroups during the 21 week dietary intervention. White squares: LFL, Light grey squares: LFH, dark grey squares: HFL, black squares: HFH. B) Mean daily energy intake. C) Positive correlation between final bodyweight and liver triglyceride concentration (P<0.05). D) Weight of epididymal fat depot. E) Adipose tissue leptin mRNA expression as determined by qPCR. Mean expression in LFL mice was set at 100%. F) Plasma free fatty acid levels. Error bars reflect standard deviation. * = significantly different from HFL mice according to Student’s t-test (P<0.05). Number of mice per group: n=4 (LFL, HFL, HFH), n=6 (LFH).
  • A subpopulation of mice fed HFD develops NASH. Haematoxylin and eosin staining (D) and oil red O staining (E) of representative liver sections of the 4 subgroups
  • (Immuno)histochemical staining confirms enhanced inflammation and early fibrosis in HFH miceImmunohistochemical staining of macrophage activation in representative liver section of HFL and HFH mice using antibody against the specific macrophagemarker Cd68Collagen staining using fast green FCF/sirius red F3B. Staining of stellate cell activation using antibody against GFAP.
  • - Number of genes up- or down-regulated in the various subgroups in comparison to the LFL mice, as determined by Affymetrix GeneChip analysis. Genes with a p-value below 0.05 were considered significantly regulated. - Heat map showing changes in expression of selected genes involved in lipid metabolism, inflammation and fibrosis in liver. Changes in gene expression of selected genes as determined by real-time quantitative PCR. Mean expression in LFL mice was set at 100%. Error bars reflect standard deviation. Bars with different letters are statistically different (P<0.05 according to Student’s t-test). Number of mice per group: n=4 (LFL, HFL, HFH), n=6 (LFH).
  • Haematoxylin and eosin staining of representative adipose tissue sections. Immunohistochemical staining of macrophages using antibody against Cd68. Collagen staining using fast green FCF/sirius red F3B.
  • Adipose tissue mRNA expression of a selected group of genes was determined by quantitative real-time PCR after 21 weeks of dietary intervention. Mean expression in LFL mice was set at 100%. Error bars reflect standard deviation. * = significantly different from HFL mice according to Student’s t-test (P<0.05). Number of mice per group: n=4 (LFL, HFL, HFH), n=6 (LFH).
  • . A) Plasma concentration of haptoglobin, TIMP-1, IL-1β, leptin and insulin were determined by multiplex assay at specific time points during the 21 weeks of dietary intervention after a 6h fast. White squares: LFL, Light grey squares: LFH, dark grey squares: HFL, black squares: HFH. Error bars reflect standard deviation. * = significantly different from HFL mice according to Student’s t-test (P<0.05). Number of mice per group: n=4 (LFL, HFL, HFH), n=6 (LFH).
  • Intro into Nutrigenomics & molecular nutrition research

    1. 1. 9th International Master class NutrigenomicsWageningen<br />Defining healthFrom basic science to industrial relevance <br />1<br />1<br />
    2. 2. Nutrigenomics Masterclass2011 How to use Nutrigenomics & molecular nutrition research? From challenges to solutions<br />Michael MüllerNetherlands Nutrigenomics Centre<br />& Nutrition, Metabolism and Genomics GroupDivision of Human Nutrition, Wageningen University<br />
    3. 3. Why we need Nutrigenomics<br />To understand nutrition & metabolic health<br />To comprehensively phenotype<br />To validate FFQs<br />To enable strategies to optimize personal health<br />To provide scientific evidence for health claims of “functional” foods<br />Mechanisms<br />Biomarkers<br />Nutritional Science 2.0<br />Personal Nutrition<br />Health claim support<br />3<br />
    4. 4. Key questions<br />What is your scientific problem? Why do you need nutrigenomics?<br />What are the best suitable genomics tools for your nutrition research and how to apply them?<br />One key question: What is the role of nutrition in the genotype-phenotype relationship?<br />What is healthy and how to measure and quantify the health status?<br />What is the impact of nutrigenomics for nutrition? What are the applications? What is the impact of nutrigenomics for the food (& pharma) industry?<br />
    5. 5. Challenge 1: Successful ageingStay healthy as long as possible<br />100 %<br />Health/ “Quality of life”<br />time<br />
    6. 6. Challenge 2: What's healthy?<br />
    7. 7. Challenge 3: We have a tsunami of health problems<br />
    8. 8. Challenge 4:Our “paleolithic” genes + modern diets<br />Paleolithic era<br />Modern Times<br />1.200.000 Generations between feast en famine<br />2-3 Generations in energy abundance<br />% Energy<br />% Energy<br />100<br />100<br />Grain<br />Milk/-products<br />Isolated Carbohydrates<br />Isolated Fat/OilAlcohol<br />Low-fat meatChicken<br />Eggs<br />Fish<br />50<br />Meat<br />Chicken<br />Fish<br />50<br />Fruit<br />Vegetables (carrots)<br />Nuts<br />Honey<br />Fruit<br />Vegetables<br />Beans<br />0<br />0<br />
    9. 9. We are different<br />
    10. 10. You are what you eat<br />
    11. 11. How many human genes do we have?Not so many but….<br />
    12. 12. Paternal Haplogroup:R1b1b2a1a1 a subgroup of R1b1b2<br />                  <br />Maternal Haplogroup:<br />X2c1 is a subgroup of X<br />.<br />                                                        <br />Where I am coming from?<br />Locations of haplogroup R1b1b2 circa 500 years ago, before the era of intercontinental travel<br />Locations of haplogroupX circa 500 years ago, before the era of intercontinental travel<br />
    13. 13. Genotype<br />A genotype is an individual's collection of genes. The term also can refer to the two alleles inherited for a particular gene. <br />The genotype is expressed when the information encoded in the genes. DNA is used to make protein and RNA molecules. <br />The expression of the genotype contributes to the individual's observable traits, called the phenotype.<br />
    14. 14. Phenotype <br />A phenotype is an individual's observable traits, such as height, eye color, and blood type. <br />The genetic contribution to the phenotype is called the genotype. <br />Some traits are largely determined by the genotype, while other traits are largely determined by environmental factors (including nutrition).<br />
    15. 15. Phenotype plasticity<br /> Phenotypic plasticity is the ability of an organism to change its phenotype in response to changes in the environment (e.g. nutrition).<br />
    16. 16. 1 Genotype => 5 nutritional phenotypes<br />155 kg<br />76 kg<br />
    17. 17. Duality of biological information:Epigenetic & Genetic<br />
    18. 18. Nutrigenomics Quantification of the nutritional genotype-phenotype <br />Lifestyle<br />Nutrition<br />Environment<br />
    19. 19. Nutrigenomics will provide solutions ….but only if ask the right questions<br />Complex Nutrition<br />+<br />Complex Genotypes<br />+<br />Complex Lifestyles<br />+<br />Complex Omics Technologies<br />Simple solutions? <br />
    20. 20. From mouse to men: From big to small signals<br />Small<br />Human muscle<br />High Fat Diet decreases mRNA for genes involved in OXPHOS in healthy young men and mice<br />Big<br />Mouse muscle<br />Diabetes 54:1926-1933, 2005 <br />
    21. 21. Challenges in nutrigenomics research: Small signals<br />24 H fasting<br />20 W high-fat<br />6 H WY<br />KO mice vs C.<br />
    22. 22. Nutrigenomics: The two strategies<br />SignaturesProfilesBiomarkers<br />Target GenesMechanismsPathways<br />Molecular Nutrition& Genomics<br />NutritionalSystems Biology<br /><ul><li>Identification of dietary signals
    23. 23. Identification of dietary sensors
    24. 24. Identification of target genes
    25. 25. Reconstruction of signaling pathways
    26. 26. Measurement of stress signatures
    27. 27. Identification of early biomarkers
    28. 28. Nutritional plasma proteome </li></ul> and metabolome<br />+<br />++++<br />Complexity<br />L. Afman & M. Müller J Am Diet Assoc. 2006;106:569-576.<br />
    29. 29. Nutrigenomics – molecular nutrition and genomics<br />5 -10000 (?)metabolites<br />90000 (?)proteins<br />100000 (?) transcripts<br />20000 genes<br />Müller & Kersten<br />NRG 2003<br />
    30. 30. 24<br />A scientific question: What is the role of “free fatty acids”?<br />During fasting<br />During long endurance activity<br />In obese people <br />“Hunger” signal or<br />“Need for glucose” signal ?<br />time (hours)<br />
    31. 31. Fats<br />FFA<br />Remnant<br />LPL<br />VLDL<br />Chylomicrons<br />We are what we eat<br />
    32. 32. Transcription-factor pathways mediating nutrient-gene interactions<br />Müller & Kersten<br />NRG 2003<br />
    33. 33. Orphans?<br />Endocrine receptorsSteroid hormonesHigh affinity<br />Endocrine receptorsLipidsLow affinity<br />Chawla, Science 2001 <br />Nuclear hormone receptors<br />
    34. 34. Intestine<br />LXR Decreased cholesterol absorption<br />FXR<br /> Increased bile salt recirculation<br />PPARα<br /> Improved lipid handling<br />Regulation of Cholesterol and Lipid Handling in Metabolic Organ Systems by Nuclear Receptors<br />
    35. 35. Nuclear receptors – how does it work?<br />
    36. 36. Understanding NutritionHow nutrients regulate our genes: via sensing molecular switches<br />Improved organcapacity by PUFAs<br />Am J ClinNutr. 2009; 90:415-24Am J ClinNutr. 2009;90:1656-64Mol CellBiology2009;29:6257-67<br />Am J ClinNutr. 2010;91:208-17BMC Genomics2009<br />Physiol. Genomics2009Circulation 2010Diabetes 2010<br />Cell Metabolism 2010<br />Am J Clin Nutr. 2007;86(5):1515-23<br />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.<br />Plos One 2009;4(8):e6796HEPATOLOGY 2010;51:511-522<br />J Clin Invest. 2004;114:94-103<br />J Biol Chem. 2006;28:934-44 <br />Endocrinology. 2006;147:1508-16<br />Physiol Genomics. 2007;30:192-204Endocrinology. 2007;148:2753-63 <br />BMC Genomics 2007; 8:267 Arterioscler Thromb Vasc Biol. 2007;27:2420-7 <br />
    37. 37. Is PPARa the hepatic fatty acid sensor? <br />YES!<br />
    38. 38. Disturbance of hepatic lipid handling leads to steatosis<br />Mitochondrial fatty acid oxidation/<br />Fatty acid binding/activation<br />ketone body synthesis<br />Lipid transport<br />Lipogenesis<br />Peroxisomal/microsomal<br />fatty acid oxidation<br />Steatosis<br />Lipases<br />
    39. 39. PPARa controls lipid metabolism<br />Mitochondrial fatty acid oxidation/<br />Fatty acid binding/activation<br />ketone body synthesis<br />Acsl1<br />Acsl3<br />Acsl4<br />Lipid transport<br />Acsl5<br />Acsm3<br />Hahd2<br />Acaa2<br />Acss2<br />Hadha<br />Adad8<br />Fabp1<br />Acot2<br />Hadhb<br />Acad9<br />Fabp2<br />Acot9<br />Hadhsc<br />Acad10<br />Cpt1a<br />Fabp3<br />Abca1<br />Hibch<br />Acads<br />Slc27a1<br />Cpt1b<br />Fabp4<br />Abcb4<br />Npc1<br />Hmgcl<br />Acadm<br />Slc27a2<br />Fabp5<br />Cpt2<br />Vldlr<br />Abcb11<br />Hmgcs2<br />Acadl<br />Crat<br />Slc27a4<br />Abcg5<br />Lrp4<br />Slc25a20<br />Cd36<br />Acadvl<br />Dci<br />Abcg8<br />Slc22a5<br />Acat1<br />Decr1<br />Lipogenesis<br />Miscellaneous<br />Acaca<br />Elovl5<br />Acacb<br />Peroxisomal/microsomal<br />Elovl6<br />Agpat2<br />Elovl7<br />Acot1<br />fatty acid oxidation<br />Agpat3<br />Acot7<br />Gpam<br />Agpat5<br />Hsd17b12<br />Acot10<br />Agpat6<br />Mod1<br />Acot12<br />Fads1<br />Adfp<br />Mogat1<br />Scd2<br />Fads2<br />Mttp<br />Adipor2<br />Slc25a10<br />Acaa1a<br />Fasn<br />Bdh<br />Acox1<br />Scd1<br />Srebf1<br />Cyp4a10<br />Acaa1b<br />Dgat1<br />Crot1<br />G0s2<br />Cyp4a12<br />Acot3<br />Ech1<br />Lepr<br />Cyp4a14<br />Acot4<br />Ehhadh<br />Lpin2<br />Aldh3a<br />2<br />Acot5<br />Lrp4<br />Decr2<br />Acot8<br />Hsd17b4<br />Mlycd<br />Abcd2<br />Peci<br />Scrab2<br />Glycerol metabolism<br />Abcd3<br />Pctp<br />Ppar<br />a<br />Pdk4<br />Gpd1<br />Pltp<br />Pnlpa2<br />Gpd2<br />Ppargc1a<br />Mgll<br />Gyk<br />Ucp2<br />Lipe<br />Aqp3<br />Ucp3<br />Aqp7<br />Lipases<br />Lipl<br />Lipg<br />Angptl4<br />
    40. 40. DIETome database forevidence-basednutrition<br />Evidence-basedNutrition<br />Genes regulated by fatty acidsGenes regulated by high fat<br />Genes also regulated by inflammation<br />Query<br />DIET<br />GenomeEpigenomeTranscriptomeProteomeMetabolome<br />“DIETome”database<br />Query<br />Nutrigenomics<br />Potential BiomarkersOrgan-specific secreted proteins<br />
    41. 41. Adipocytes at the crossroads of energy homeostasis<br />
    42. 42. Nutrition<br />Pharma<br /> Insulin ± oral agents<br />Oral combination<br />Oral monotherapy<br />Diet & exercise<br />Nutritional prevention of complex diseases needs new biomarkers<br />Complex Disease<br />100<br />Different & similar targets<br />80<br />60<br />DISEASE STATE (%) <br />40<br />20<br />0<br />TIME (months/years)<br />HomeostasisHealth<br />L. Afman & M. Müller J Am Diet Assoc. 2006;106:569-576.<br />
    43. 43. Metabolic defects leading to the development of hepatic steatosis<br />
    44. 44. Metabolism & Inflammation<br />
    45. 45. Liver, FAT & NASH/NAFLD<br /><ul><li>Nonalcoholic Fatty Liver Diseases (NAFLD):Liver component of Metabolic Syndrome
    46. 46. Different stages in NAFLD progression:
    47. 47. Molecular events involved in NASH pathogenesis:
    48. 48. Role of PPARa (Endocrinology 2008 & Hepatology 2010)
    49. 49. Role Kupffer cells (Hepatology 2010)
    50. 50. Role of macrophages in lipid metabolism (JBC 2008; Cell Metabolism 2010)</li></ul>hepatic steatosis steatohepatitis (NASH) & fibrosis cirrhosis<br />
    51. 51. Interaction between WAT and liver tissue essential for NASH/NAFLD in C57Bl/6 mice<br />Objective: <br />Nonalcoholic fatty liver disease (NAFLD) is strongly linked to obesity and diabetes, suggesting an important role of adipose tissue in the pathogenesis of NAFLD. <br />Here we aimed to investigate the interaction between adipose tissue and liver in NAFLD, and identify potential early plasma markers that predict NASH. <br />
    52. 52. Experimental Design<br />tissue collection<br />run-in diet<br />20 weeks diet intervention<br /><ul><li>plasma collection</li></ul>multiple proteinassays<br /><ul><li>liver
    53. 53. stratification on body weight</li></ul>frozen sections: histological feat.<br />lipid content<br />RNA extraction:Affx microarrays<br />10 LFD<br />0<br />2<br />4<br />8<br />12<br />16<br />20 weeks<br />20 LFD<br />-3<br />quality control & data analysis pipeline<br />10 HFD<br />Mouse genome <br />430 2.0<br />10% low <br />fat diet <br />(palm oil)<br />45% high fat diet (palm oil)<br /><ul><li>ep. white adipose tissue</li></ul>paraffin sections: histological feat.<br />RNA extraction: real-time PCR<br />
    54. 54. High fat diet-induced obesity<br />0<br />2<br />4<br />8<br />12<br />16<br />20<br />HFL<br />LFL<br />HFH<br />LFH<br />25<br />20<br />*<br />*<br />15<br />**<br />BW gain (g)<br />*<br />10<br />*<br />*<br />*<br />*<br />5<br />0<br />weeks under diet intervention<br />Liver TG content<br />Hepatomegaly<br />ALT plasma activity<br />200<br />10<br />100<br />***<br />***<br />**<br />160<br />8<br />80<br />**<br />120<br />6<br />60<br />*<br />Ratio LW/BW (%)<br />mg TG/g liver<br />ALT activity (UI)<br />80<br />4<br />40<br />*<br />*<br />40<br />2<br />20<br />0<br />0<br />0<br />LFL<br />LFH<br />HFL<br />HFH<br />
    55. 55. Adipose dysfunction in HFH mice<br />Leptin<br />
    56. 56. A subpopulation of mice fed HFD develops NASH<br />
    57. 57. Immunohistochemicalstaining confirms enhanced inflammation and early fibrosis in HFH mice<br />Macrophage CD68<br />Collagen<br />Stellate cell GFAP<br />
    58. 58. Results I<br />Mice exhibited pronounced heterogeneity in liver histological scoring, leading to classification into 4 subgroups: <br />LF-low (LFL) responders displaying normal liver morphology, <br />LF-high (LFH) responders showing benign hepatic steatosis, <br />HF-low (HFL) responders displaying pre-NASH with macrovesicular lipid droplets, <br />HF-high (HFH) responders exhibiting overt NASH characterized by ballooning of hepatocytes, presence of Mallory bodies, and activated inflammatory cells. <br />
    59. 59. Upregulation of inflammatory and fibrotic gene expression in HFH responder mice<br />
    60. 60. Adipose dysfunction in HFH mice<br />
    61. 61. Change in adipose gene expression indicate adipose tissue dysfunction<br />
    62. 62. Plasma proteins as early predictive biomarker for NASH in C57Bl/6 mice<br />
    63. 63. Conclusions<br />Our data support the existence of a tight relationship between adipose tissue dysfunction and NASH pathogenesis.<br />It points to several novel potential predictive biomarkers for NASH.<br />Diabetes. 2010;59:3181-91.<br />
    64. 64. Nutrigenomics enables us<br /><ul><li>To understand how nutrition precisely works (evidence-based nutrition);
    65. 65. To quantify the nutritional needs for optimized fitness at different life stages (“personalized” nutrition);
    66. 66. To improve early diagnostics of nutrition related disorders (“challenge tests”);
    67. 67. To support the development of “smart healthy food patterns” for modern mankind (healthy and tasty, sustainable, affordable)
    68. 68. To enable the transition of nutritional science to nutritional science 2.0.</li></li></ul><li>How to stay healthy and keep our organs fit and vital?<br />By “challenging” our organs with a diverse and healthy food pattern to improve their capability, capacity, and performance.<br />
    69. 69. 2 Meals a day, work as long as possible & embrace challenge<br />Walter Breuning (1896 - 2011)<br />
    70. 70. Thanks<br />Lydia Afman<br />Mark Bouwens<br />Susan van Dijk<br />DiederikEsser<br />Sergio Lopez<br />Lisette de Groot<br />Marianne Geleijnse<br />Ondine van de Rest<br />MariekeBos<br />Edith Feskens<br />RikHeijligenberg<br />Dianne Hoelen<br />Jeanne de Vries<br />Geert Heidema<br />
    71. 71. Visit the Kröller-Müller Museum!<br />56<br />