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Metabolic imprinting, programming and epigenetics – a review of present priorities and future opportunities

Published online by Cambridge University Press:  01 July 2010

Bryan Hanley
Affiliation:
William Wrigley Jr Company, Chicago, IL, USA
Jean Dijane
Affiliation:
INRA – Institut National de la Recherche Agronomique, 147 rue de l'Université 75338, Paris Cedex 07, France
Mary Fewtrell
Affiliation:
MRC Childhood Nutrition, Institute of Child Health, 30 Guilford Street, LondonWC1N 1EH, UK
Alain Grynberg
Affiliation:
INRA – Institut National de la Recherche Agronomique, 147 rue de l'Université 75338, Paris Cedex 07, France
Sandra Hummel
Affiliation:
University of Muenchen, Munich, Germany
Claudine Junien
Affiliation:
INSERM, France
Berthold Koletzko
Affiliation:
University of Munich, Munich, Germany
Sarah Lewis
Affiliation:
Bristol University, Wills Memorial Building, Queen's Road, BristolBS8 1RJ, UK
Harald Renz
Affiliation:
University of Marburg, Biegenstrabe 10, 35037Marburg, Germany
Michael Symonds
Affiliation:
Nottingham University, University Park, NottinghamNG7 2RD, UK
Marjan Gros
Affiliation:
FrieslandCampina, Stationsplein 4, PO Box 1551, NL-3818 LE Amersfoort, The Netherlands
Lucien Harthoorn
Affiliation:
Mead Johnson Nutrition, Middenkampweg 2, 6545CJNijmegen, The Netherlands
Katherine Mace
Affiliation:
Nestlé, Lausanne 26, Switzerland
Fiona Samuels*
Affiliation:
ILSI Europe, a.i.s.b.l., Avenue E. Mounier 83, Box 6, B-1200, Brussels, Belgium
Eline M. van Der Beek
Affiliation:
Danone, Wagenin, The Netherlands
*
*Correspondence: ILSI Europe a.i.s.b.l. - Avenue E. Mounier 83, Box 6 - 1200 Brussels - Belgium, fax: +32 2 762 00 44, email: publications@ilsieurope.be
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Abstract

Metabolic programming and metabolic imprinting describe early life events, which impact upon on later physiological outcomes. Despite the increasing numbers of papers and studies, the distinction between metabolic programming and metabolic imprinting remains confusing. The former can be defined as a dynamic process whose effects are dependent upon a critical window(s) while the latter can be more strictly associated with imprinting at the genomic level. The clinical end points associated with these phenomena can sometimes be mechanistically explicable in terms of gene expression mediated by epigenetics. The predictivity of outcomes depends on determining if there is causality or association in the context of both early dietary exposure and future health parameters. The use of biomarkers is a key aspect of determining the predictability of later outcome, and the strengths of particular types of biomarkers need to be determined. It has become clear that several important health endpoints are impacted upon by metabolic programming/imprinting. These include the link between perinatal nutrition, nutritional epigenetics and programming at an early developmental stage and its link to a range of future health risks such as CVD and diabetes. In some cases, the evidence base remains patchy and associative, while in others, a more direct causality between early nutrition and later health is clear. In addition, it is also essential to acknowledge the communication to consumers, industry, health care providers, policy-making bodies as well as to the scientific community. In this way, both programming and, eventually, reprogramming can become effective tools to improve health through dietary intervention at specific developmental points.

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Type
Full Papers
Copyright
Copyright © ILSI Europe
Figure 0

Table 1 Correlations between early exposure and later health outcomes from the Avon longitudinal study of parents and children cohort

Figure 1

Fig. 1 Conceptual figure on the effects of exposure at different developmental ages. , predictive power; , intervention; , long-term effect.

Figure 2

Fig. 2 The shrinking of unmodified endpoints and increase in environmentally modified endpoints over time as external factors impact through a lifetime.

Figure 3

Table 2 Summary of studies into nutritional programming in which outcome measures are potentially confounded by a mismatch between groups in their composition of offspring from singleton and twin pregnancies

Figure 4

Fig. 3 Studies of the hazards ratios for risk of T1D