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Nutrigenomics of FAT

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Recent lecture (june 2011) …

Recent lecture (june 2011)
Nutrigenomics of FAT: What is “good” or “bad” for human health?

Less healthy: Dietary fats rich in long chain saturated fatty acids that can be pro-inflammatory if chronically “overconsumed”
More favorable: Unsaturated fatty acids (in particular PUFAs from fish oil) have anti-inflammatory properties
A healthy adipose tissue is essential to efficiently store fat and prevent ectopic fat deposition
Healthy : Subcutanous fat > visceral fat > ectopic fat : Unhealthy

Future challenge: To prevent the unhealthy effects of a surplus of added sugars (sucrose, fructose) & high GI carbs
Will be converted into saturated fat
Linked to ectopic fat deposition e.g. NASH
Linked to obesity, diabetes, CVD….
Childhood obesity

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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with positive or negative consequences with respect to organ and systemic health.In my talk I will briefly discuss two unpublished studies, one investigating the important interaction of WAT and liver in particular under conditions of diet-induced obesity.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).
  • Transcript

    • 1. Nutrigenomics of FAT: What is “good” or “bad” for human health?
      Michael MüllerNetherlands Nutrigenomics Centre
      & Nutrition, Metabolism and Genomics GroupDivision of Human Nutrition, Wageningen University
    • 2. 2 Meals a day, work as long as possible & embrace challenge
      Walter Breuning (1896 - 2011)
    • 3. We have a tsunami of health problems
    • 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
    • 5. Nutrigenomics Quantification of the nutritional genotype-phenotype
      Lifestyle
      Nutrition
      Environment
    • 6. 1 Genotype => 5 nutritional phenotypes
      155 kg
      76 kg
    • 7. Lipids
      FFA
      Remnant
      LPL
      VLDL
      Chylomicrons
      Organ and systemic responses to dietary lipids
    • 8. 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 2010Nature 2011
      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
    • 9. Chylomicron
      CE/TG
      Angptl4
      LPL
      CE/TG
      FFA
      Chylomicron remnant
    • 10. Kersten, S. et al. ArteriosclerThrombVascBiol 2009;29:969-974
      Expression profile of ANGPTL4 mRNA in human tissues
    • 11. Angptl4-- mice on HFD become very ill
      Lichtenstein et al. Cell Metabolism 2010
    • 12. Inflammatory response independent of microbiota
      Lichtenstein et al. Cell Metabolism 2010
    • 13. Massive enlargement of mesenteric lymph nodes in Angptl4-/- mice fed HFD
      Lichtenstein et al. Cell Metabolism 2010
    • 14. No effect of medium chain or PUFA TGs
      Lichtenstein et al. Cell Metabolism 2010
    • 15. Angptl4 protects against lipolysis and subsequent foam cell formation
    • 16. Angptl4 protects against lipolysis and subsequent foam cell formation
    • 17. Adipocytes at the crossroads of energy homeostasis
    • 18. Normal
      Type 2 Diabetes
      Visceral Fat Distribution:Normal vs Type 2 Diabetes
    • 19.
    • 20. Metabolic defects leading to the development of hepatic steatosis
    • 21. Metabolism & Inflammation
    • 22. Liver, FAT & NASH/NAFLD
      • Nonalcoholic Fatty Liver Diseases (NAFLD):Liver component of Metabolic Syndrome
      • 23. Different stages in NAFLD progression:
      • 24. Molecular events involved in NASH pathogenesis:
      • 25. Role of PPARa (Endocrinology 2008 & Hepatology 2010)
      • 26. Role Kupffer cells (Hepatology 2010)
      • 27. Role of macrophages in lipid metabolism (JBC 2008; Cell Metabolism 2010)
      hepatic steatosis steatohepatitis (NASH) & fibrosis cirrhosis
    • 28. 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.
    • 29. Experimental Design
      tissue collection
      run-in diet
      20 weeks diet intervention
      • plasma collection
      multiple proteinassays
      • liver
      • 30. stratification on body weight
      frozen sections: histological feat.
      lipid content
      RNA extraction:Affx microarrays
      10 LFD
      0
      2
      4
      8
      12
      16
      20 weeks
      20 LFD
      -3
      quality control & data analysis pipeline
      10 HFD
      Mouse genome
      430 2.0
      10% low
      fat diet
      (palm oil)
      45% high fat diet (palm oil)
      • ep. white adipose tissue
      paraffin sections: histological feat.
      RNA extraction: real-time PCR
    • 31. 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
    • 32. Adipose dysfunction in HFH mice
      Leptin
    • 33. A subpopulation of mice fed HFD develops NASH
    • 34. Immunohistochemicalstaining confirms enhanced inflammation and early fibrosis in HFH mice
      Macrophage CD68
      Collagen
      Stellate cell GFAP
    • 35. 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.
    • 36. Upregulation of inflammatory and fibrotic gene expression in HFH responder mice
    • 37. Adipose dysfunction in HFH mice
    • 38. Change in adipose gene expression indicate adipose tissue dysfunction
    • 39. Plasma proteins as early predictive biomarker for NASH in C57Bl/6 mice
    • 40. 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.
    • 41. Human applications?Individual protein profiles
      Population I (MARIS, n=56)
      Van Dijk et al. Plos One 2010
    • 42. Design of the SFA vs MUFA-rich intervention study
      T=10 wks
      T=0 wks
      T=2 wks
      Run-in
      SFA-rich diet
      (n=20)
      SFA-rich diet (n=10)
      MUFA-rich diet (n=10)
      After intervention
      • Clamp
      • 43. Adipose tissue biopsy
      • 44. Blood sampling
      Baseline
      • Clamp
      • 45. Adipose tissue biopsy
      • 46. Blood sampling
      Van Dijk et al. AJCN 2009
    • 47. ‘Obese-linked’ pro-inflammatory gene expression profile by SFAs
      MUFA diet
      SFA diet
      The SFA-rich diet:
      Induces a pro-inflammatory obese-linked gene expression profile
      Decreases expression and plasma level of the anti-inflammatory cytokine adiponectin
      “Personal Transcriptomes”
      Van Dijk et al. AJCN 2009
    • 48. Fish-oil supplementation induces anti-inflammatory gene expression profiles in human blood mononuclear cells
      Less inflammation & decreased pro-arteriosclerosis markers= Anti-immuno-senescence
      Bouwens et al. Am J ClinNutr. 2009
    • 49. Summary
      Less healthy: Dietary fats rich in long chain saturated fatty acids that can be pro-inflammatory if chronically “overconsumed”
      More favourable: Unsaturated fatty acids (in particular PUFAs from fish oil) have anti-inflammatory properties
      A healthy adipose tissue is essential to efficiently store fat and prevent ectopic fat deposition
      Healthy : Subcutanous fat > visceral fat > ectopic fat : Unhealthy
      Future challenge: To prevent the unhealthy effects of a surplus of added sugars (sucrose, fructose) & high GI carbs
      Will be converted into saturated fat
      Linked to ectopic fat deposition e.g. NASH
      Linked to obesity, diabetes, CVD….
      Childhood obesity
    • 50. 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

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