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Nutrigenomics: goals and strategies


Nutrigenomics is the application of high-throughput genomics tools in nutrition research. Applied wisely, it will promote an increased understanding of how nutrition influences metabolic pathways and homeostatic control, how this regulation is disturbed in the early phase of a diet-related disease and to what extent individual sensitizing genotypes contribute to such diseases. Ultimately, nutrigenomics will allow effective dietary-intervention strategies to recover normal homeostasis and to prevent diet-related diseases.

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Figure 1: The 'smart' combination of molecular nutrition and nutrigenomics.


  1. 1

    International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001).

  2. 2

    Waterston, R. H. et al. Initial sequencing and comparative analysis of the mouse genome. Nature 420, 520–562 (2002).

    CAS  Article  Google Scholar 

  3. 3

    Venter, J. C. et al. The sequence of the human genome. Science 291, 1304–1351 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4

    Francis, G. A., Fayard, E., Picard, F. & Auwerx, J. Nuclear receptors and the control of metabolism. Annu. Rev. Physiol. 65, 261–311 (2002).

    PubMed  Google Scholar 

  5. 5

    Willett, W. C. Balancing life-style and genomics research for disease prevention. Science 296, 695–698 (2002).

    CAS  PubMed  Google Scholar 

  6. 6

    Chuaqui, R. F. et al. Post-analysis follow-up and validation of microarray experiments. Nature Genet. 32 (Suppl.), 509–514 (2002).

    CAS  PubMed  Google Scholar 

  7. 7

    Slonim, D. K. From patterns to pathways: gene expression data analysis comes of age. Nature Genet. 32 (Suppl.), 502–508 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8

    Quackenbush, J. Microarray data normalization and transformation Nature Genet. 32 (Suppl.), 496–501 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9

    Churchill, G. A. Fundamentals of experimental design for cDNA microarrays. Nature Genet. 32 (Suppl.), 490–495 (2002).

    CAS  PubMed  Google Scholar 

  10. 10

    Stoeckert, C. J., Causton, H. C. & Ball, C. A. Microarray databases: standards and ontologies. Nature Genet. 32 (Suppl.), 469–473 (2002).

    CAS  PubMed  Google Scholar 

  11. 11

    Roberts, M. A., Mutch, D. M. & German, J. B. Genomics: food and nutrition. Curr. Opin. Biotechnol. 12, 516–522 (2001).

    CAS  PubMed  Google Scholar 

  12. 12

    Peregrin, T. The new frontier of nutrition science: nutrigenomics. J. Am. Diet Assoc. 101, 1306 (2001).

    CAS  PubMed  Google Scholar 

  13. 13

    Elliott, R. & Ong, T. J. Nutritional genomics. BMJ 324, 1438–1442 (2002).

    PubMed  PubMed Central  Google Scholar 

  14. 14

    Daniel, H. Genomics and proteomics: importance for the future of nutrition research. Br. J. Nutr. 87 (Suppl.), 305–311 (2002).

    Google Scholar 

  15. 15

    van Ommen, B. & Stierum, R. Nutrigenomics: exploiting systems biology in the nutrition and health arena. Curr. Opin. Biotechnol. 13, 517–521 (2002).

    CAS  PubMed  Google Scholar 

  16. 16

    Watkins, S. M., Reifsnyder, P. R., Pan, H. J., German, J. B. & Leiter, E. H. Lipid metabolome-wide effects of the PPAR-γ agonist rosiglitazone. J. Lipid Res. 43, 1809–1817 (2002).

    CAS  PubMed  Google Scholar 

  17. 17

    MacBeath, G. Protein microarrays and proteomics. Nature Genet. 32 (Suppl.), 526–532 (2002).

    CAS  PubMed  Google Scholar 

  18. 18

    Evans, W. E. & McLeod, H. L. Pharmacogenomics — drug disposition, drug targets, and side effects. N. Engl. J. Med. 348, 538–549 (2003).

    CAS  PubMed  Google Scholar 

  19. 19

    Evans, W. E. & Johnson, J. A. Pharmacogenomics: the inherited basis for interindividual differences in drug response. Annu. Rev. Genomics Hum. Genet. 2, 9–39 (2001).

    CAS  PubMed  Google Scholar 

  20. 20

    Brouwer, I. A., Zock, P. L., van Amelsvoort, L. G., Katan, M. B. & Schouten, E. G. Association between n-3 fatty acid status in blood and electrocardiographic predictors of arrhythmia risk in healthy volunteers. Am. J. Cardiol. 89, 629–631 (2002).

    CAS  PubMed  Google Scholar 

  21. 21

    Sacks, F. M. & Katan, M. Randomized clinical trials on the effects of dietary fat and carbohydrate on plasma lipoproteins and cardiovascular disease. Am. J. Med. 113 (Suppl.), S13–S24 (2002).

    Google Scholar 

  22. 22

    Lu, T. T., Repa, J. J. & Mangelsdorf, D. J. Orphan nuclear receptors as eLiXiRs and FiXeRs of sterol metabolism. J. Biol. Chem. 276, 37735–37738 (2001).

    CAS  PubMed  Google Scholar 

  23. 23

    Mangelsdorf, D. J. et al. The nuclear receptor superfamily: the second decade. Cell 83, 835–839 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24

    Chawla, A., Repa, J. J., Evans, R. M. & Mangelsdorf, D. J. Nuclear receptors and lipid physiology: opening the X-files. Science 294, 1866–1870 (2001).

    CAS  Google Scholar 

  25. 25

    Jansen, P. L., Müller, M. & Sturm, E. Genes and cholestasis. Hepatology 34, 1067–1074 (2001).

    CAS  PubMed  Google Scholar 

  26. 26

    Chiang, J. Y. Bile acid regulation of gene expression: roles of nuclear hormone receptors. Endocr. Rev. 23, 443–463 (2002).

    CAS  PubMed  Google Scholar 

  27. 27

    Plass, J. R. et al. Farnesoid X receptor and bile salts are involved in transcriptional regulation of the gene encoding the human bile salt export pump. Hepatology 35, 589–596 (2002).

    CAS  PubMed  Google Scholar 

  28. 28

    Pineda Torra, I. et al. Bile acids induce the expression of the human peroxisome proliferator-activated receptor-α gene via activation of the farnesoid X receptor. Mol. Endocrinol. 17, 259–272 (2003).

    PubMed  Google Scholar 

  29. 29

    Ananthanarayanan, M., Balasubramanian, N., Makishima, M., Mangelsdorf, D. J. & Suchy, F. J. Human bile salt export pump promoter is transactivated by the farnesoid X receptor/bile acid receptor. J. Biol. Chem. 276, 28857–28865 (2001).

    CAS  PubMed  Google Scholar 

  30. 30

    Hwang, S. T., Urizar, N. L., Moore, D. D. & Henning, S. J. Bile acids regulate the ontogenic expression of ileal bile acid binding protein in the rat via the farnesoid X receptor. Gastroenterology 122, 1483–1492 (2002).

    CAS  PubMed  Google Scholar 

  31. 31

    Lu, T. T. et al. Molecular basis for feedback regulation of bile acid synthesis by nuclear receptors. Mol. Cell 6, 507–515 (2000).

    CAS  PubMed  Google Scholar 

  32. 32

    He, K. et al. Fish consumption and risk of stroke in men. JAMA 288, 3130–3136 (2002).

    CAS  PubMed  Google Scholar 

  33. 33

    Albert, C. M. et al. Blood levels of long-chain n-3 fatty acids and the risk of sudden death. N. Engl. J. Med. 346, 1113–1118 (2002).

    CAS  PubMed  Google Scholar 

  34. 34

    Jump, D. B. & Clarke, S. D. Regulation of gene expression by dietary fat. Annu. Rev. Nutr. 19, 63–90 (1999).

    CAS  PubMed  Google Scholar 

  35. 35

    Jump, D. B. Dietary polyunsaturated fatty acids and regulation of gene transcription. Curr. Opin. Lipidol. 13, 155–164 (2002).

    CAS  PubMed  Google Scholar 

  36. 36

    Kersten, S., Desvergne, B. & Wahli, W. Roles of PPARs in health and disease. Nature 405, 421–424 (2000).

    CAS  Google Scholar 

  37. 37

    Barbier, O. et al. Pleiotropic actions of peroxisome proliferator-activated receptors in lipid metabolism and atherosclerosis. Arterioscler. Thromb. Vasc. Biol. 22, 717–726 (2002).

    CAS  PubMed  Google Scholar 

  38. 38

    Walczak, R. & Tontonoz, P. PPARadigms and PPARadoxes: expanding roles for PPAR-γ in the control of lipid metabolism. J. Lipid. Res. 43, 177–186 (2002).

    CAS  PubMed  Google Scholar 

  39. 39

    Xu, J. et al. Peroxisome proliferator-activated receptor-α (PPAR-α) influences substrate utilization for hepatic glucose production. J. Biol. Chem. 277, 50237–50244 (2002).

    CAS  PubMed  Google Scholar 

  40. 40

    Kersten, S. et al. Peroxisome proliferator-activated receptor-α mediates the adaptive response to fasting. J. Clin. Invest. 103, 1489–1498 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41

    Jump, D. B., Thelen, A. & Mater, M. Dietary polyunsaturated fatty acids and hepatic gene expression. Lipids 34 (Suppl.), S209–S212 (1999).

    CAS  PubMed  Google Scholar 

  42. 42

    Desvergne, B. & Wahli, W. Peroxisome proliferator-activated receptors: nuclear control of metabolism. Endocr. Rev. 20, 649–688 (1999).

    CAS  PubMed  Google Scholar 

  43. 43

    Hooper, L. V. & Gordon, J. I. Commensal host-bacterial relationships in the gut. Science 292, 1115–1118 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Stappenbeck, T. S., Hooper, L. V., Manchester, J. K., Wong, M. H. & Gordon, J. I. Laser capture microdissection of mouse intestine: characterizing mRNA and protein expression, and profiling intermediary metabolism in specified cell populations. Methods Enzymol. 356, 167–196 (2002).

    CAS  PubMed  Google Scholar 

  45. 45

    Shimomura, I., Shimano, H., Horton, J. D., Goldstein, J. L. & Brown, M. S. Differential expression of exons 1a and 1c in mRNAs for sterol regulatory element binding protein-1 in human and mouse organs and cultured cells. J. Clin. Invest. 99, 838–845 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 46

    Whitney, A. R. et al. Individuality and variation in gene expression patterns in human blood. Proc. Natl Acad. Sci. USA 100, 1896–1901 (2003).

    CAS  PubMed  Google Scholar 

  47. 47

    Staudt, L. M. Gene expression profiling of lymphoid malignancies. Annu. Rev. Med. 53, 303–318 (2002).

    CAS  PubMed  Google Scholar 

  48. 48

    Rosenwald, A. et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma. N. Engl. J. Med. 346, 1937–1947 (2002).

    PubMed  Google Scholar 

  49. 49

    Davis, R. E. & Staudt, L. M. Molecular diagnosis of lymphoid malignancies by gene expression profiling. Curr. Opin. Hematol. 9, 333–338 (2002).

    PubMed  Google Scholar 

  50. 50

    Tang, Y., Lu, A., Aronow, B. J. & Sharp, F. R. Blood genomic responses differ after stroke, seizures, hypoglycemia, and hypoxia: blood genomic fingerprints of disease. Ann. Neurol. 50, 699–707 (2001).

    CAS  PubMed  Google Scholar 

  51. 51

    Boldrick, J. C. et al. Stereotyped and specific gene expression programs in human innate immune responses to bacteria. Proc. Natl Acad. Sci. USA 99, 972–977 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Staudt, L. M. Gene expression physiology and pathophysiology of the immune system. Trends Immunol. 22, 35–40 (2001).

    CAS  PubMed  Google Scholar 

  53. 53

    Shaffer, A. L. et al. Signatures of the immune response. Immunity 15, 375–385 (2001).

    CAS  PubMed  Google Scholar 

  54. 54

    Grody, W. W. Molecular genetic risk screening. Annu. Rev. Med. 54, 473–490 (2003).

    CAS  PubMed  Google Scholar 

  55. 55

    Bailey, L. B. & Gregory, J. F. Polymorphisms of methylenetetrahydrofolate reductase and other enzymes: metabolic significance, risks and impact on folate requirement. J. Nutr. 129, 919–922 (1999).

    CAS  PubMed  Google Scholar 

  56. 56

    Omer, R. E. et al. Peanut butter intake, GSTM1 genotype and hepatocellular carcinoma: a case-control study in Sudan. Cancer Causes Control 12, 23–32 (2001).

    CAS  PubMed  Google Scholar 

  57. 57

    Sachidanandam, R. et al. A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms. Nature 409, 928–933 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58

    Potter, J. D. At the interfaces of epidemiology, genetics and genomics. Nature Rev. Genet. 2, 142–147 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59

    Kong, A. et al. A high-resolution recombination map of the human genome. Nature Genet. 31, 241–247 (2002).

    CAS  Google Scholar 

  60. 60

    Boomsma, D., Busjahn, A. & Peltonen, L. Classical twin studies and beyond. Nature Rev. Genet. 3, 872–882 (2002).

    CAS  PubMed  Google Scholar 

  61. 61

    Cascante, M. et al. Metabolic control analysis in drug discovery and disease. Nature Biotechnol. 20, 243–249 (2002).

    CAS  Google Scholar 

  62. 62

    Ideker, T. et al. Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929–934 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63

    Ideker, T., Galitski, T. & Hood, L. A new approach to decoding life: systems biology. Annu. Rev. Genomics Hum. Genet. 2, 343–372 (2001).

    CAS  Google Scholar 

  64. 64

    Jansen, R. C. Studying complex biological systems using multifactorial perturbation. Nature Rev. Genet. 4, 145–151 (2003).

    CAS  PubMed  Google Scholar 

  65. 65

    Kitano, H. Systems biology: a brief overview. Science 295, 1662–1664 (2002).

    CAS  Google Scholar 

  66. 66

    Watkins, S. M. & German, J. B. Toward the implementation of metabolomic assessments of human health and nutrition. Curr. Opin. Biotechnol. 13, 512–516 (2002).

    CAS  PubMed  Google Scholar 

  67. 67

    Ideker, T., Ozier, O., Schwikowski, B. & Siegel, A. F. Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics 18 (Suppl.) 233–240 (2002).

    Google Scholar 

  68. 68

    Bradham, C. A., Plumpe, J., Manns, M. P., Brenner, D. A. & Trautwein, C. Mechanisms of hepatic toxicity. I. TNF-induced liver injury. Am. J. Physiol. 275, 387–392 (1998).

    Google Scholar 

  69. 69

    Streetz, K. L., Wustefeld, T., Klein, C., Manns, M. P. & Trautwein, C. Mediators of inflammation and acute phase response in the liver. Cell. Mol. Biol. 47, 661–673 (2001).

    CAS  PubMed  Google Scholar 

  70. 70

    Diehl, A. M. Cytokine regulation of liver injury and repair. Immunol. Rev. 174, 160–171 (2000).

    CAS  PubMed  Google Scholar 

  71. 71

    Ruminy, P. et al. Gene transcription in hepatocytes during the acute phase of a systemic inflammation: from transcription factors to target genes. Inflamm. Res. 50, 383–390 (2001).

    CAS  PubMed  Google Scholar 

  72. 72

    Pineda Torra, I., Gervois, P. & Staels, B. Peroxisome proliferator-activated receptor-α in metabolic disease, inflammation, atherosclerosis and aging. Curr. Opin. Lipidol. 10, 151–159 (1999).

    CAS  PubMed  Google Scholar 

  73. 73

    Streetz, K. et al. Tumor necrosis factor-α in the pathogenesis of human and murine fulminant hepatic failure. Gastroenterology 119, 446–460 (2000).

    CAS  PubMed  Google Scholar 

  74. 74

    Clark, J. M., Brancati, F. L. & Diehl, A. M. Nonalcoholic fatty liver disease. Gastroenterology 122, 1649–1657 (2002).

    PubMed  Google Scholar 

  75. 75

    Das, U. N. Is metabolic syndrome X an inflammatory condition? Exp. Biol. Med. 227, 989–997 (2002).

    CAS  Google Scholar 

  76. 76

    Evans, J. L., Goldfine, I. D., Maddux, B. A. & Grodsky, G. M. Oxidative stress and stress-activated signaling pathways: a unifying hypothesis of type 2 diabetes. Endocr. Rev. 23, 599–622 (2002).

    CAS  PubMed  Google Scholar 

  77. 77

    Libby, P. Inflammation in atherosclerosis. Nature 420, 868–874 (2002).

    CAS  Google Scholar 

  78. 78

    Tilg, H. & Diehl, A. M. Cytokines in alcoholic and nonalcoholic steatohepatitis. N. Engl. J. Med. 343, 1467–1476 (2000).

    CAS  PubMed  Google Scholar 

  79. 79

    Ren, B., Thelen, A. P., Peters, J. M., Gonzalez, F. J. & Jump, D. B. Polyunsaturated fatty acid suppression of hepatic fatty acid synthase and S14 gene expression does not require peroxisome proliferator-activated receptor-α. J. Biol. Chem. 272, 26827–26832 (1997).

    CAS  PubMed  Google Scholar 

  80. 80

    Dallongeville, J. et al. Peroxisome proliferator-activated receptor-α is not rate-limiting for the lipoprotein-lowering action of fish oil. J. Biol. Chem. 276, 4634–4639 (2001).

    CAS  PubMed  Google Scholar 

  81. 81

    Clagett-Dame, M. & DeLuca, H. F. The role of vitamin A in mammalian reproduction and embryonic development. Annu. Rev. Nutr. 22, 347–381 (2002).

    CAS  PubMed  Google Scholar 

  82. 82

    Stanford, W. L., Cohn, J. B. & Cordes, S. P. Gene-trap mutagenesis: past, present and beyond. Nature Rev. Genet. 2, 756–768 (2001).

    CAS  PubMed  Google Scholar 

  83. 83

    Copeland, N. G., Jenkins, N. A. & Court, D. L. Recombineering: a powerful new tool for mouse functional genomics. Nature Rev. Genet. 2, 769–779 (2001).

    CAS  Google Scholar 

  84. 84

    Lewandoski, M. Conditional control of gene expression in the mouse. Nature Rev. Genet. 2, 743–755 (2001).

    CAS  Google Scholar 

  85. 85

    Weindruch, R., Kayo, T., Lee, C. K. & Prolla, T. A. Gene expression profiling of aging using DNA microarrays. Mech. Ageing Dev. 123, 177–193 (2002).

    CAS  PubMed  Google Scholar 

  86. 86

    Cao, S. X., Dhahbi, J. M., Mote, P. L. & Spindler, S. R. Genomic profiling of short- and long-term caloric restriction effects in the liver of aging mice. Proc. Natl Acad. Sci. USA 98, 10630–10635 (2001).

    CAS  PubMed  Google Scholar 

  87. 87

    Lee, C. K., Allison, D. B., Brand, J., Weindruch, R. & Prolla, T. A. Transcriptional profiles associated with aging and middle age-onset caloric restriction in mouse hearts. Proc. Natl Acad. Sci. USA 99, 14988–14993 (2002).

    CAS  PubMed  Google Scholar 

  88. 88

    Prolla, T. A. DNA microarray analysis of the aging brain. Chem. Senses 27, 299–306 (2002).

    CAS  PubMed  Google Scholar 

  89. 89

    Sreekumar, R., Halvatsiotis, P., Schimke, J. C. & Nair, K. S. Gene expression profile in skeletal muscle of type 2 diabetes and the effect of insulin treatment. Diabetes 51, 1913–1920 (2002).

    CAS  PubMed  Google Scholar 

  90. 90

    Maier, S. & Olek, A. Diabetes: a candidate disease for efficient DNA methylation profiling. J. Nutr. 132, 2440–2443 (2002).

    Google Scholar 

  91. 91

    Shalev, A. et al. Oligonucleotide microarray analysis of intact human pancreatic islets: identification of glucose-responsive genes and a highly regulated TGFβ signaling pathway. Endocrinology 143, 3695–3698 (2002).

    CAS  PubMed  Google Scholar 

  92. 92

    Shih, D. Q. et al. Hepatocyte nuclear factor-1α is an essential regulator of bile acid and plasma cholesterol metabolism. Nature Genet. 27, 375–382 (2001).

    CAS  PubMed  Google Scholar 

  93. 93

    Naiki, T. et al. Analysis of gene expression profile induced by hepatocyte nuclear factor 4α in hepatoma cells using an oligonucleotide microarray. J. Biol. Chem. 277, 14011–14019 (2002).

    CAS  PubMed  Google Scholar 

  94. 94

    Ross, S. E. et al. Microarray analyses during adipogenesis: understanding the effects of Wnt signaling on adipogenesis and the roles of liver X receptor-α in adipocyte metabolism. Mol. Cell. Biol. 22, 5989–5999 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95

    Kersten, S. et al. The peroxisome proliferator-activated receptor-α regulates amino acid metabolism. FASEB J. 15, 1971–1978 (2001).

    CAS  PubMed  Google Scholar 

  96. 96

    Lichtlen, P. et al. Target gene search for the metal-responsive transcription factor MTF-1. Nucleic Acids Res. 29, 1514–1523 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. 97

    Blanchard, R. K., Moore, J. B., Green, C. L. & Cousins, R. J. Modulation of intestinal gene expression by dietary zinc status: effectiveness of cDNA arrays for expression profiling of a single nutrient deficiency. Proc. Natl Acad. Sci. USA 98, 13507–13513 (2001).

    CAS  PubMed  Google Scholar 

  98. 98

    Xiao, J. et al. The effect of chronic exposure to fatty acids on gene expression in clonal insulin-producing cells: studies using high density oligonucleotide microarray. Endocrinology 142, 4777–4784 (2001).

    CAS  PubMed  Google Scholar 

  99. 99

    Endo, Y., Fu, Z., Abe, K., Arai, S. & Kato, H. Dietary protein quantity and quality affect rat hepatic gene expression. J. Nutr. 132, 3632–3637 (2002).

    CAS  PubMed  Google Scholar 

  100. 100

    Mariadason, J. M., Corner, G. A. & Augenlicht, L. H. Genetic reprogramming in pathways of colonic cell maturation induced by short chain fatty acids: comparison with trichostatin A, sulindac, and curcumin and implications for chemoprevention of colon cancer. Cancer Res. 60, 4561–4572 (2000).

    CAS  Google Scholar 

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The authors thank their colleagues from the Division of Human Nutrition, the Centre of Human Nutrigenomics and the Innovative Cluster Nutrigenomics group for critical discussions. The work of the authors is supported by the Dutch Scientific Organization (NOW), the Dutch Diabetes Foundation, the Wageningen Centre of Food Sciences, the Dutch Dairy Foundation for Nutrition and Health, the Innovative Research Programme (IOP) Genomics and the Food Technology, Agrobiotechnology, Nutrition and Health Sciences (VLAG) research school.

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Correspondence to Michael Müller.

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Centre for Human Nutrigenomics

Michael Müller's laboratory

NCMHD Center of Excellence for Nutritional Genomics



The early and immediate set of homeostatic control reactions that are induced during inflammation.


A half tubule that is formed by the apical membranes of two hepatocytes, and is limited laterally by their smooth surfaces.


The apical membrane of liver epithelial cells (hepatocytes) that lines the bile canaliculus. Members of the ABC-transporter superfamily that are localized in this membrane are responsible for bile secretion.


Epithelial cells that are the main functional units of the liver, and comprise 80% of the organ's cytoplasmic mass.


Expression systems that regulate mammalian gene expression with, for example, tetracycline or its derivatives (Tet-On/Tet-Off gene expression systems).


The complex series of reactions that occur in the host as a response to injury, trauma or infection of a tissue, which prevent ongoing tissue damage, isolate and destroy the infective organism and activate the repair processes that are necessary to return the organism to normal function.


The production of ketone bodies — such as acetoacetate and β-hydroxybutyrate — which are the intermediate products of fatty-acid catabolism and can be used to provide energy.


A method in which cells are cut out from a tissue sample using a laser beam, allowing single cell expression analysis.


A type of white blood cell that is responsible for the adaptive immune response; for example, B lymphocytes and T lymphocytes.


Organic compounds, including proteins, amino acids, carbohydrates and lipids, that are required in large amounts in the diet.


The study of the metabolome, which is the entire metabolic content of a cell or organism, at a given time.


Dietary compounds, including vitamins and minerals that are required in small amounts in the diet.


The relationship between genotype and the risk of developing diet-related diseases, such as cancer, diabetes type II and cardio-vascular diseases.


The study of the genome-wide influences of nutrition or dietary components on the transcriptome, proteome and metabolome, of cells, tissues or organisms, at a given time.


A term often used to mean the influence of DNA-sequence variation — in drug targets, Phase I or Phase II drug-metabolizing enzymes, and transporters — on the effect of a drug, which ultimately allows physicians to design individualized therapy.


The study of proteomes (the complete collection of proteins in a cell or tissue at a given time), which attempts to determine their role inside cells and the molecules with which they interact.


(RNAi). The process by which double-stranded RNA silences homologous genes.


The binding state of a C–C bond in a fatty acid molecule.


The study of whole biological systems (cells, tissues and organisms) using holistic methods.


The complete collection of gene transcripts in a cell or a tissue at a given time.


A recombinant adenovirus that infects cells, resulting in the high-level expression of a mutant protein that, for example, specifically blocks a given signalling pathway (superrepressor) by competing with the endogenous protein.

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Müller, M., Kersten, S. Nutrigenomics: goals and strategies. Nat Rev Genet 4, 315–322 (2003).

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