Advertisement

Der Diabetologe

, Volume 13, Issue 4, pp 260–267 | Cite as

Die Bedeutung des Mikrobioms für die Adipositas

Machen Darmbakterien dick?
  • F. Bertram
  • D. Menge
  • V. Andresen
Übersichten

Zusammenfassung

Das Darmmikrobiom des Menschen ist dank des rapiden Fortschritts der Genanalytik und Bioinformatik in den letzten Jahren für unterschiedlichste forschende Fachdisziplinen weiter zugänglich geworden. In großen Metaanalysen von Stuhlproben und Anamnesen und über Tierexperimente mit keimfreien Mäusen werden Zusammenhänge zwischen unterschiedlichen Pathologien und der Darmbesiedlung hergestellt. Neben immunologischen und neuropsychologischen Erkrankungen stehen metabolische Erkrankungen im Vordergrund, wie Insulinresistenz und Adipositas. Dabei scheint Übergewicht mit Verschiebungen des Mikrobioms assoziiert, die Charakterisierung eines „übergewichtigen Mikrobioms“ ist bisher noch nicht gelungen. Neben der Ernährung wird auch der Einfluss von Geburtsmodus, frühkindlicher Ernährung und Antibiotikatherapien neu diskutiert. Tierexperimente zeigen, dass steril aufwachsende Mäuse trotz hochkalorischer Ernährung kein Gewicht zunehmen, jedoch nach einer Stuhltransplantation Übergewicht entwickeln. Die Inzidenz von Insulinresistenz in dieser Gruppe ist dabei von der Fütterung der Spendermäuse abhängig. In ersten klinischen Studien gelang es zum Teil, diese Ergebnisse auf den Menschen zu übertragen. Wegen der geringen Gesamtzahl von Studien und dem noch immer sehr begrenzten Wissen über konkrete Eigenschaften und Zusammensetzung der Mikrobiota ist jedoch vorerst nicht mit klinischer Anwendung von Mikrobiomtherapien zu rechnen.

Schlüsselwörter

Insulinresistenz  Metabolisches Syndrom Immunsystem Sectio caesarea Antibiotika 

The importance of the microbiome in obesity

Do intestinal bacteria make people fat?

Abstract

Due to the rapid progress of genetic and bioinformatic analysis techniques, the human gut microbiome has increasingly become the subject of research for a growing variety of medical fields. Large meta-analyses of stool samples in various diseases as well as germ-free animal models are used to assess possible associations between the gut microbiome and various pathogenic findings. In addition to associations with immunologic and neuropsychological disorders, one of the main areas of research has been metabolic diseases such as insulin resistance and obesity. In this context, it has been shown that obesity may be associated with a shift in the gut microbiome. However, a distinct characterization of an “obese microbiome” has not yet been established. In addition to nutrition and the mode of birth, early childhood nutrition and antibiotic therapies are suggested to play an influential role on the gut microbiome. Animal models have been used to demonstrate that germ-free mice, which do not gain extra weight despite a high calorie intake, develop obesity after a fecal transfer. In these mice, the incidence of insulin resistance depends on the nutrition of the fecal donor mice. Preliminary data in humans seem to confirm these findings. However, due to the still only limited data and knowledge on the specific alterations and pathogenic role of the human microbiome composition in relation to various diseases, a general clinical use of a specific microbiome therapy is currently not established.

Keywords

Insulin resistance Metabolic syndrome Immune system Cesarean section Antibiotics 

Notes

Einhaltung ethischer Richtlinien

Interessenkonflikt

F. Bertram und D. Menge geben an, dass kein Interessenkonflikt besteht. V. Andresen weist auf folgende Beziehungen hin: Vorträge und/oder Beratungstätigkeiten für folgende Firmen: Allergan, Almirall, AstraZeneca, Boehringer Ingelheim, Falk, KyowaKirin, Nordmark, Schwabe, Shire, Yakult.

Dieser Beitrag beinhaltet keine von den Autoren durchgeführten Studien an Menschen oder Tieren.

Literatur

  1. 1.
    Putignani L, Del Chierico F, Petrucca A et al (2014) The human gut microbiota: a dynamic interplay with the host from birth to senescence settled during childhood. Pediatr Res 76:2–10CrossRefPubMedGoogle Scholar
  2. 2.
    Fu BC, Randolph TW, Lim U et al (2016) Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience. Ann Epidemiol 26:373–379CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Jandhyala SM, Talukdar R, Subramanyam C et al (2015) Role of the normal gut microbiota. World J Gastroenterol 21:8787–8803CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Arumugam M, Raes J, Pelletier E et al (2011) Enterotypes of the human gut microbiome. Nature 473:174–180CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Stallmach A, Vehreschild MJGT (Hrsg) (2016) Mikrobiom – Wissensstand und Perspektiven. De Gruyter, BerlinGoogle Scholar
  6. 6.
    Claesson MJ, Jeffery IB, Conde S et al (2012) Gut microbiota composition correlates with diet and health in the elderly. Nature 488:178–184PubMedGoogle Scholar
  7. 7.
    Rodriguez JM, Murphy K, Stanton C et al (2015) The composition of the gut microbiota throughout life, with an emphasis on early life. Microb Ecol Health Dis 26:26050PubMedGoogle Scholar
  8. 8.
    Madan JC, Farzan SF, Hibberd PL et al (2012) Normal neonatal microbiome variation in relation to environmental factors, infection and allergy. Curr Opin Pediatr 24:753–759CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Clemente JC, Dominguez-Bello MG (2016) Safety of vaginal microbial transfer in infants delivered by caesarean, and expected health outcomes. BMJ 352:i1707CrossRefPubMedGoogle Scholar
  10. 10.
    Dominguez-Bello MG, De Jesus-Laboy KM, Shen N et al (2016) Partial restoration of the microbiota of cesarean-born infants via vaginal microbial transfer. Nat Med 22:250–253CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Stokholm J, Thorsen J, Chawes BL et al (2016) Cesarean section changes neonatal gut colonization. J Allergy Clin Immunol 138:881–889.e2CrossRefPubMedGoogle Scholar
  12. 12.
    Bokulich NA, Chung J, Battaglia T et al (2016) Antibiotics, birth mode, and diet shape microbiome maturation during early life. Sci Transl Med 8:343ra82CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Flint HJ, Bayer EA, Rincon MT et al (2008) Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis. Nat Rev Microbiol 6:121–131CrossRefPubMedGoogle Scholar
  14. 14.
    Lemas DJ, Yee S, Cacho N et al (2016) Exploring the contribution of maternal antibiotics and breastfeeding to development of the infant microbiome and pediatric obesity. Semin Fetal Neonatal Med. doi: 10.1016/j.siny.2016.04.013 PubMedGoogle Scholar
  15. 15.
    Membrez M, Blancher F, Jaquet M et al (2008) Gut microbiota modulation with norfloxacin and ampicillin enhances glucose tolerance in mice. FASEB J 22:2416–2426CrossRefPubMedGoogle Scholar
  16. 16.
    John GK, Mullin GE (2016) The gut microbiome and obesity. Curr Oncol Rep 18:45CrossRefPubMedGoogle Scholar
  17. 17.
    Alhagamhmad MH, Day AS, Lemberg DA et al (2016) An overview of the bacterial contribution to Crohn disease pathogenesis. J Med Microbiol. doi: 10.1099/jmm.0.000331 PubMedGoogle Scholar
  18. 18.
    Pirbaglou M, Katz J, de Souza RJ et al (2016) Probiotic supplementation can positively affect anxiety and depressive symptoms: a systematic review of randomized controlled trials. Nutr Res 36:889–898CrossRefPubMedGoogle Scholar
  19. 19.
    Hu X, Wang T, Jin F (2016) Alzheimer’s disease and gut microbiota. Sci China Life Sci 59:1006–1023CrossRefPubMedGoogle Scholar
  20. 20.
    Kelly TN, Bazzano LA, Ajami NJ et al (2016) Gut microbiome associates with lifetime cardiovascular disease risk profile among Bogalusa Heart Study Participants. Circ Res 119:956–964CrossRefPubMedGoogle Scholar
  21. 21.
    Gerard P (2016) Gut microbiota and obesity. Cell Mol Life Sci 73:147–162CrossRefPubMedGoogle Scholar
  22. 22.
    Wostmann BS, Larkin C, Moriarty A et al (1983) Dietary intake, energy metabolism, and excretory losses of adult male germfree Wistar rats. Lab Anim Sci 33:46–50PubMedGoogle Scholar
  23. 23.
    Backhed F, Ding H, Wang T et al (2004) The gut microbiota as an environmental factor that regulates fat storage. Proc Natl Acad Sci U S A 101:15718–15723CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Backhed F, Manchester JK, Semenkovich CF et al (2007) Mechanisms underlying the resistance to diet-induced obesity in germ-free mice. Proc Natl Acad Sci U S A 104:979–984CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Brown AJ, Goldsworthy SM, Barnes AA et al (2003) The Orphan G protein-coupled receptors GPR41 and GPR43 are activated by propionate and other short chain carboxylic acids. J Biol Chem 278:11312–11319CrossRefPubMedGoogle Scholar
  26. 26.
    Tarini J, Wolever TM (2010) The fermentable fibre inulin increases postprandial serum short-chain fatty acids and reduces free-fatty acids and ghrelin in healthy subjects. Appl Physiol Nutr Metab 35:9–16CrossRefPubMedGoogle Scholar
  27. 27.
    Rabot S, Membrez M, Blancher F et al (2016) High fat diet drives obesity regardless the composition of gut microbiota in mice. Sci Rep 6:32484CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Alang N, Kelly CR (2015) Weight gain after fecal microbiota transplantation. Open Forum Infect Dis 2:ofv004CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Tanca A, Palomba A, Fraumene C et al (2016) The impact of sequence database choice on metaproteomic results in gut microbiota studies. Microbiome 4:51CrossRefPubMedPubMedCentralGoogle Scholar
  30. 30.
    Vrieze A, Van Nood E, Holleman F et al (2012) Transfer of intestinal microbiota from lean donors increases insulin sensitivity in individuals with metabolic syndrome. Gastroenterology 143:913–916.e7CrossRefPubMedGoogle Scholar
  31. 31.
    Ejtahed HS, Soroush AR, Angoorani P et al (2016) Gut microbiota as a target in the pathogenesis of metabolic disorders: a new approach to novel therapeutic agents. Horm Metab Res 48:349–358CrossRefPubMedGoogle Scholar

Copyright information

© Springer Medizin Verlag GmbH 2017

Authors and Affiliations

  1. 1.Israelitisches KrankenhausHamburgDeutschland

Personalised recommendations