PDF herunterladen
Aktuelle Ernährungsmedizin 2015; 40(02): 88-92
DOI: 10.1055/s-0034-1387602
Übersicht
© Georg Thieme Verlag KG Stuttgart · New York

Nutrigenomics: Toward a Cross-Disciplinary Understanding of Nutrient-Driven Networks in Health and Disease

What Can we Learn from the Study of Cross-Talk in Complex Protein Kinase and Metabolic Networks?Nutrigenenomik: Interdisziplinäre Forschung zum besseren Verständnis von ernährungsbedingten Einflüssen bei der Entstehung- und Behandlung von KrankheitenWas können wir aus der Analyse der Interaktion von Signaltransduktion und Stoffwechselwegen lernen?
I. Heiland
1   Department of Arctic and Marine Biology, UiT Arctic University of Norway, Naturfagbygget, Tromsø, Norway
,
K. Thedieck
2   Center for Liver, Digestive and Metabolic Diseases, Department of Pediatrics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
3   Department of Neuroscience, School of Medicine and Health Sciences, Carl von Ossietzky University Oldenburg, Oldenburg, Germany
› Institutsangaben
Weitere Informationen

Publikationsverlauf

Publikationsdatum:
28. April 2015 (online)

Auch verfügbar auf
    Lizenzen und Reprints

Zusammenfassung

Die Nutrigenomik untersucht an der Grenze zwischen Life Sciences und Medizin den Einfluss von Nahrungskomponenten auf molekulare Prozesse über alle Skalen hinweg, von der Zelle bis hin zum gesamten Organismus. Eine breite Methodenpalette von Hoch-, Mittel- und Niedrigdurchsatzverfahren sowie bioinformatischen und computergestützten Modellierungsansätzen hat in den letzten Jahren zu neuen Einblicken in die molekularen Antworten auf Nährstoffe und deren Einfluss auf eine Reihe von Krankheitsbildern geführt. Anhand der Beispiele der mammalian target of rapamycin (mTOR)-, aminosäure- und NAD-abhängigen Signalwege diskutieren wir neue Entwicklungen in der Nutrigenomik und ihren möglichen Beitrag zur Entwicklung von zielgerichteteten und individualisierten Ernährungsinterventionen.

Abstract

The emerging discipline of nutrigenomics analyzes the impact of dietary components on health and disease at all scales from cell to organism. Using a wide range of high, medium, and low throughput experimental techniques, bioinformatics and computational modeling, we have in recent years gained some insight into molecular mechanisms underlying nutritional responses and their impact on a wide range of diseases, including neuroinflammatory, neurodegenerative and metabolic diseases, as well as cancer.

Focusing on the examples of mammalian target of rapamycin (mTOR), amino acid, and NAD-dependent signaling in the context of mal- and overnutrition, and caloric restriction, we discuss recent advances in nutrigenomics and their future promises for the development of targeted nutritional interventions.

Keywords

nutrition - (epi-)genome - transcriptome - metabolome - signaling - computational biology

Schlüsselwörter

Ernährung - (Epi-)Genetik - Transkriptom - Metabolom - Signaltransduktion - Bioinformatik und Modellierung
 

  • References

  • 1 van Abeelen AF, Elias SG, Bossuyt PM et al. Famine exposure in the young and the risk of type 2 diabetes in adulthood. Diabetes 2012; 61: 2255-2260
    CrossrefPubMedGoogle Scholar
  • 2 Veenendaal MV, Painter RC, de Rooij SR et al. Transgenerational effects of prenatal exposure to the 1944-45 Dutch famine. BJOG 2013; 120: 548-553
    CrossrefPubMedGoogle Scholar
  • 3 Elias SG, Peeters PH, Grobbee DE et al. Transient caloric restriction and cancer risk (The Netherlands). Cancer Causes Control 2007; 18: 1-5
    CrossrefPubMedGoogle Scholar
  • 4 Nelissen EC, Van Montfoort AP, Smits LJ et al. IVF culture medium affects human intrauterine growth as early as the second trimester of pregnancy. Hum Reprod 2013; 28: 2067-2074
    CrossrefPubMedGoogle Scholar
  • 5 Dumoulin JC, Land JA, Van Montfoort AP et al. Effect of in vitro culture of human embryos on birthweight of newborns. Hum Reprod 2010; 25: 605-612
    CrossrefPubMedGoogle Scholar
  • 6 Kleijkers SH, van Montfoort AP, Smits LJ et al. IVF culture medium affects post-natal weight in humans during the first 2 years of life. Hum Reprod 2014; 29: 661-669
    CrossrefPubMedGoogle Scholar
  • 7 Martorell R, Stein AD, Schroeder DG. Early nutrition and later adiposity. J Nutr 2001; 131: 874S-880S
    CrossrefPubMedGoogle Scholar
  • 8 Quilter CR, Cooper WN, Cliffe KM et al. Impact on offspring methylation patterns of maternal gestational diabetes mellitus and intrauterine growth restraint suggest common genes and pathways linked to subsequent type 2 diabetes risk. FASEB J 2014; 28: 4868-4879
    CrossrefPubMedGoogle Scholar
  • 9 Radford EJ, Ito M, Shi H et al. In utero effects. In utero undernourishment perturbs the adult sperm methylome and intergenerational metabolism. Science 2014; 345: 1255903
    CrossrefPubMedGoogle Scholar
  • 10 Sachlova M, Majek O, Tucek S. Prognostic Value of Scores Based on Malnutrition or Systemic Inflammatory Response in Patients With Metastatic or Recurrent Gastric Cancer. Nutr Cancer 2014; 1-9
    PubMedGoogle Scholar
  • 11 Loeffen EA, Brinksma A, Miedema KG et al. Clinical implications of malnutrition in childhood cancer patients-infections and mortality. Support Care Cancer 2015; 23: 143-150
    CrossrefPubMedGoogle Scholar
  • 12 Fijlstra M, Tissing WJ, Stellaard F et al. Reduced absorption of long-chain fatty acids during methotrexate-induced gastrointestinal mucositis in the rat. Clin Nutr 2013; 32: 452-459
    CrossrefPubMedGoogle Scholar
  • 13 El-Serag HB, Rudolph KL. Hepatocellular carcinoma: epidemiology and molecular carcinogenesis. Gastroenterology 2007; 132: 2557-2576
    CrossrefPubMedGoogle Scholar
  • 14 Kohsaka A, Laposky AD, Ramsey KM et al. High-fat diet disrupts behavioral and molecular circadian rhythms in mice. Cell Metab 2007; 6: 414-421
    CrossrefPubMedGoogle Scholar
  • 15 Colman RJ, Beasley TM, Kemnitz JW et al. Caloric restriction reduces age-related and all-cause mortality in rhesus monkeys. Nat Commun 2014; 5: 3557
    CrossrefPubMedGoogle Scholar
  • 16 Mattison JA, Roth GS, Beasley TM et al. Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study. Nature 2012; 489: 318-321
    CrossrefPubMedGoogle Scholar
  • 17 McCay CM, Crowell MF, Maynard LA. The Effect of Retarded Growth Upon the Length of Life Span and Upon the Ultimate Body Size: One Figure. The Journal of Nutrition 1935; 10: 63-79
    PubMedGoogle Scholar
  • 18 Matsuoka Y, Matsumae H, Katoh M et al. A comprehensive map of the influenza A virus replication cycle. BMC Syst Biol 2013; 7: 97
    CrossrefPubMedGoogle Scholar
  • 19 Hase T, Ghosh S, Yamanaka R et al. Harnessing diversity towards the reconstructing of large scale gene regulatory networks. PLoS Comput Biol 2013; 9: e1003361
    CrossrefPubMedGoogle Scholar
  • 20 D’Alessandro LA, Meyer R, Klingmuller U. Hepatocellular carcinoma: a systems biology perspective. Front Physiol 2013; 4: 28
    PubMedGoogle Scholar
  • 21 Boehm ME, Adlung L, Schilling M et al. Identification of Isoform-Specific Dynamics in Phosphorylation-Dependent STAT5 Dimerization by Quantitative Mass Spectrometry and Mathematical Modeling. J Proteome Res 2014; 13: 5685-5694
    CrossrefPubMedGoogle Scholar
  • 22 Stavrum AK, Heiland I, Schuster S et al. Model of tryptophan metabolism, readily scalable using tissue-specific gene expression data. J Biol Chem 2013; 288: 34555-34566
    CrossrefPubMedGoogle Scholar
  • 23 Dalle Pezze P, Sonntag AG, Thien A et al. A dynamic network model of mTOR signaling reveals TSC-independent mTORC2 regulation. Sci Signal 2012; 5: ra25
    PubMedGoogle Scholar
  • 24 Harrison DE, Strong R, Sharp ZD et al. Rapamycin fed late in life extends lifespan in genetically heterogeneous mice. Nature 2009; 460: 392-395
    PubMedGoogle Scholar
  • 25 Hansen M, Chandra A, Mitic LL et al. A role for autophagy in the extension of lifespan by dietary restriction in C. elegans. PLoS Genet 2008; 4: e24
    CrossrefPubMedGoogle Scholar
  • 26 Inoki K, Kim J, Guan KL. AMPK and mTOR in cellular energy homeostasis and drug targets. Annu Rev Pharmacol Toxicol 2012; 52: 381-400
    CrossrefPubMedGoogle Scholar
  • 27 Benjamin D, Colombi M, Moroni C et al. Rapamycin passes the torch: a new generation of mTOR inhibitors. Nat Rev Drug Discov 2011; 10: 868-880
    CrossrefPubMedGoogle Scholar
  • 28 Nyman E, Rohini Rajan M, Fagerholm S et al. A Single Mechanism can Explain Network-Wide Insulin Resistance in Adipocytes from Obese Patients with Type 2 Diabetes. J Biol Chem 2014; 289: 33215-33230
    CrossrefPubMedGoogle Scholar
  • 29 Thedieck K, Sonntag A, Shanley D et al. Method for modelling, optimizing, parameterizing, testing and/or validating a dynamic network or network perturbations. Patent publication number WO2012163440 A8
    PubMedGoogle Scholar
  • 30 Kim SG, Buel GR, Blenis J. Nutrient regulation of the mTOR complex 1 signaling pathway. Mol Cells 2013; 35: 463-473
    CrossrefPubMedGoogle Scholar
  • 31 Ban H, Shigemitsu K, Yamatsuji T et al. Arginine and Leucine regulate p70 S6 kinase and 4E-BP1 in intestinal epithelial cells. Int J Mol Med 2004; 13: 537-543
    PubMedGoogle Scholar
  • 32 Metz R, Rust S, Duhadaway JB et al. IDO inhibits a tryptophan sufficiency signal that stimulates mTOR: A novel IDO effector pathway targeted by D-1-methyl-tryptophan. Oncoimmunology 2012; 1: 1460-1468
    CrossrefPubMedGoogle Scholar
  • 33 Schwarcz R, Bruno JP, Muchowski PJ et al. Kynurenines in the mammalian brain: when physiology meets pathology. Nat Rev Neurosci 2012; 13: 465-477
    CrossrefPubMedGoogle Scholar
  • 34 Opitz CA, Litzenburger UM, Sahm F et al. An endogenous tumour-promoting ligand of the human aryl hydrocarbon receptor. Nature 2011; 478: 197-203
    CrossrefPubMedGoogle Scholar
  • 35 Campbell BM, Charych E, Lee AW et al. Kynurenines in CNS disease: regulation by inflammatory cytokines. Front Neurosci 2014; 8: 12
    CrossrefPubMedGoogle Scholar
  • 36 Rios-Avila L, Nijhout HF, Reed MC et al. A mathematical model of tryptophan metabolism via the kynurenine pathway provides insights into the effects of vitamin B-6 deficiency, tryptophan loading, and induction of tryptophan 2,3-dioxygenase on tryptophan metabolites. J Nutr 2013; 143: 1509-1519
    CrossrefPubMedGoogle Scholar
  • 37 Choi S, DiSilvio B, Fernstrom MH et al. The chronic ingestion of diets containing different proteins produces marked variations in brain tryptophan levels and serotonin synthesis in the rat. Neurochem Res 2011; 36: 559-565
    CrossrefPubMedGoogle Scholar
  • 38 Wan P, Moat S, Anstey A. Pellagra: a review with emphasis on photosensitivity. Br J Dermatol 2011; 164: 1188-1200
    CrossrefPubMedGoogle Scholar
  • 39 Ulanovskaya OA, Zuhl AM, Cravatt BF. NNMT promotes epigenetic remodeling in cancer by creating a metabolic methylation sink. Nat Chem Biol 2013; 9: 300-306
    CrossrefPubMedGoogle Scholar
  • 40 Chiarugi A, Dolle C, Felici R et al. The NAD metabolome – a key determinant of cancer cell biology. Nat Rev Cancer 2012; 12: 741-752
    CrossrefPubMedGoogle Scholar
  • 41 Belenky P, Bogan KL, Brenner C. NAD+ metabolism in health and disease. Trends Biochem Sci 2007; 32: 12-19
    CrossrefPubMedGoogle Scholar
  • 42 Houtkooper RH, Canto C, Wanders RJ et al. The secret life of NAD+: an old metabolite controlling new metabolic signaling pathways. Endocr Rev 2010; 31: 194-223
    CrossrefPubMedGoogle Scholar
  • 43 Berger F, Ramirez-Hernandez MH, Ziegler M. The new life of a centenarian: signalling functions of NAD(P). Trends Biochem Sci 2004; 29: 111-118
    CrossrefPubMedGoogle Scholar
  • 44 DiPalma JR, Thayer WS. Use of niacin as a drug. Annu Rev Nutr 1991; 11: 169-187
    CrossrefPubMedGoogle Scholar
  • 45 Feige JN, Lagouge M, Canto C et al. Specific SIRT1 activation mimics low energy levels and protects against diet-induced metabolic disorders by enhancing fat oxidation. Cell Metab 2008; 8: 347-358
    CrossrefPubMedGoogle Scholar
  • 46 Brandauer J, Vienberg SG, Andersen MA et al. AMP-activated protein kinase regulates nicotinamide phosphoribosyl transferase expression in skeletal muscle. J Physiol 2013; 591: 5207-5220
    CrossrefPubMedGoogle Scholar