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Cited by 150Nutrition and Health StudiesNutritional Studies and DietExercise and Physiological Responses

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Monitoring immune modulation by nutrition in the general population: identifying and substantiating effects on human health

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Albers, Ruud, Bourdet-Sicard, Raphaëlle, Braun, Deborah, Calder, Philip C., Herz, Udo, Lambert, Claude, Lenoir-Wijnkoop, Irene, Méheust, Agnès, Ouwehand, Arthur, Phothirath, Phoukham, Sako, Tomoyuki, Salminen, Seppo, Siemensma, André, van Loveren, Henk, Sack, Ulrich·2013·British Journal of Nutrition
DOI 10.1017/s0007114513001505PMC PMC3734536
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Abstract

Optimal functioning of the immune system is crucial to human health, and nutrition is one of the major exogenous factors modulating different aspects of immune function. Currently, no single marker is available to predict the effect of a dietary intervention on different aspects of immune function. To provide further guidance on the assessment and interpretation of the modulation of immune functions due to nutrition in the general population, International Life Sciences Institute Europe commissioned a group of experts from academia, government and the food industry to prepare a guidance document. A draft of this paper was refined at a workshop involving additional experts. First, the expert group defined criteria to evaluate the usefulness of immune function markers. Over seventy-five markers were scored within the context of three distinct immune system functions: defence against pathogens; avoidance or mitigation of allergy; control of low-grade (metabolic) inflammation. The most useful markers were subsequently classified depending on whether they by themselves signify clinical relevance and/or involvement of immune function. Next, five theoretical scenarios were drafted describing potential changes in the values of markers compared with a relevant reference range. Finally, all elements were combined, providing a framework to aid the design and interpretation of studies assessing the effects of nutrition on immune function. This stepwise approach offers a clear rationale for selecting markers for future trials and provides a framework for the interpretation of outcomes. A similar stepwise approach may also be useful to rationalise the selection and interpretation of markers for other physiological processes critical to the maintenance of health and well-being.

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Fig. 1 Illustration of the general paradigm postulating that fluctuations within the boundaries of a normal range support the maintenance of optimal health. Regardless of the marker or assay used, immune functions vary between subjects and they fluctuate within subjects over time (), although apparently within some normal limits (green zone) that may be individually defined. Certain (combinations of) factors can drive immune function(s) to a state of hypo- or hyperactivity (). The objective of a (nutritional) intervention is to restore functions to the normal range () and/or to strengthen the resilience of these function(s), reducing the amplitude of fluctuations and thus reinforcing the homeodynamic regulation within the normal range. Adapted from Hamer et al. ( 30 ).
Fig. 1 Illustration of the general paradigm postulating that fluctuations within the boundaries of a normal range support the maintenance of optimal health. Regardless of the marker or assay used, immune functions vary between subjects and they fluctuate within subjects over time (), although apparently within some normal limits (green zone) that may be individually defined. Certain (combinations of) factors can drive immune function(s) to a state of hypo- or hyperactivity (). The objective of a (nutritional) intervention is to restore functions to the normal range () and/or to strengthen the resilience of these function(s), reducing the amplitude of fluctuations and thus reinforcing the homeodynamic regulation within the normal range. Adapted from Hamer et al. ( 30 ).CC BY-NC-SA · PubMed Central
Fig. 2 Graphical representation indicating the classification of immune function markers from the most integrated/physiologically relevant to the most isolated/mechanistically insightful, with the basal markers being positioned on the side as they do not indicate a function by themselves, but aid in the interpretation of the functional markers.
Fig. 2 Graphical representation indicating the classification of immune function markers from the most integrated/physiologically relevant to the most isolated/mechanistically insightful, with the basal markers being positioned on the side as they do not indicate a function by themselves, but aid in the interpretation of the functional markers.CC BY-NC-SA · PubMed Central
Fig. 3 Graphical representation of the five different scenarios for the modulation of immune function markers relative to the reference range. Scenario 1: statistically significant modulation within the reference range or within the range of a relevant control population, a very common scenario for modulation due to nutrition. Scenario 2: statistically significant modulation from outside the reference or control range of a relevant control population back into the range. Cases are different before intervention and become similar after intervention. Scenario 3: statistically significant modulation from within the reference or control range of a relevant control population out of the range. Cases are similar before intervention and become different after intervention. Scenario 4: nutritional prevention of statistically significant modulation induced by other endogenous or exogenous factors. Markers move out of the reference range of a relevant control population in the reference group, but this is prevented by nutrition in the intervention group (e.g. prevention of negative effects on the immune function of ageing or UV-B exposure or prevention of allergic sensitisation). Scenario 5: statistically significant modulation from a less favourable reference range to the reference range of a comparator group with a more desired immune function (e.g. from bottle-fed infants to breast-fed infants, elderly individuals to healthy adults, strenuous exercise to healthy controls, sleep deprivation to sleep sufficiency, etc.).
Fig. 3 Graphical representation of the five different scenarios for the modulation of immune function markers relative to the reference range. Scenario 1: statistically significant modulation within the reference range or within the range of a relevant control population, a very common scenario for modulation due to nutrition. Scenario 2: statistically significant modulation from outside the reference or control range of a relevant control population back into the range. Cases are different before intervention and become similar after intervention. Scenario 3: statistically significant modulation from within the reference or control range of a relevant control population out of the range. Cases are similar before intervention and become different after intervention. Scenario 4: nutritional prevention of statistically significant modulation induced by other endogenous or exogenous factors. Markers move out of the reference range of a relevant control population in the reference group, but this is prevented by nutrition in the intervention group (e.g. prevention of negative effects on the immune function of ageing or UV-B exposure or prevention of allergic sensitisation). Scenario 5: statistically significant modulation from a less favourable reference range to the reference range of a comparator group with a more desired immune function (e.g. from bottle-fed infants to breast-fed infants, elderly individuals to healthy adults, strenuous exercise to healthy controls, sleep deprivation to sleep sufficiency, etc.).CC BY-NC-SA · PubMed Central
Fig. 4 Flow chart to aid the interpretation of changes in immune function markers in nutrition studies based on information on the type of markers in which significant changes are observed (groups A–D) and the relative change compared with the reference range (scenarios 1–5). Blue indicates a health effect but not necessarily due to immune modulation, green indicates beneficial modulation of immune function, orange indicates potentially undesired modulation of immune function and red indicates no effect or interpretation not possible. Group A, relevance AND the involvement of immune functions (e.g. response to vaccination). Group B, relevance BUT NOT necessarily the involvement of immune functions (e.g. diarrhoea). Group C, involvement of immune function(s) AND associated with clinical relevance in specific (sub)populations (e.g. NK-cell activity in athletes and elderly). Group D, mechanistic insights BUT NOT directly associated with clinical relevance (e.g. cytokines).
Fig. 4 Flow chart to aid the interpretation of changes in immune function markers in nutrition studies based on information on the type of markers in which significant changes are observed (groups A–D) and the relative change compared with the reference range (scenarios 1–5). Blue indicates a health effect but not necessarily due to immune modulation, green indicates beneficial modulation of immune function, orange indicates potentially undesired modulation of immune function and red indicates no effect or interpretation not possible. Group A, relevance AND the involvement of immune functions (e.g. response to vaccination). Group B, relevance BUT NOT necessarily the involvement of immune functions (e.g. diarrhoea). Group C, involvement of immune function(s) AND associated with clinical relevance in specific (sub)populations (e.g. NK-cell activity in athletes and elderly). Group D, mechanistic insights BUT NOT directly associated with clinical relevance (e.g. cytokines).CC BY-NC-SA · PubMed Central

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Research works printed but not linked: 7

  1. Clifton, 2003, How effective are meal replacements for treating obesity?, Asia Pac J Clin Nutr, 12, S51
  2. Rechkemmer, 2002, Use of fecal water as a biomarker in dietary intervention studies, J Nutr, 132, 3537S
  3. 2005, The Treatment of Diarrhoea: A Manual for Physicians and Other Senior Health Workers
  4. 2006, Guideline on Clinical Evaluation of New Vaccines
  5. Mackinnon, 1999, Advances in Exercise and Immunology
  6. Barriga-Ibars, 2005, [Interrelations between sleep and the immune status], Rev Neurol, 40, 548
  7. 1997, Note for Guidance on Harmonisation of Requirements for Influenza Vaccines

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Metadata

Authors
Albers, R., Bourdet-Sicard, R., Braun, D., Calder, P. C., Herz, U., Lambert, C., Lenoir-Wijnkoop, I., Méheust, A., Ouwehand, A., Phothirath, P., Sako, T., Salminen, S., Siemensma, A., van Loveren, H., & Sack, U.
Affiliations
  • Unilever Research and Development Vlaardingen (NL)
  • University of Southampton (GB)
  • Centre Hospitalier Universitaire de Saint-Étienne (FR)
  • International Life Sciences Institute Europe (BE)
  • DuPont (Finland) (FI)
  • Nestlé (Switzerland) (CH)
  • Yakult (Netherlands) (NL)
  • University of Turku (FI)
  • FrieslandCampina (Netherlands) (NL)
  • Leipzig University (DE)
ORCID
Venue
British Journal of Nutrition
Publisher
Cambridge University Press (CUP)
Published
2013-08-01
Volume
110
Issue
S2
Pages
S1-S30
ISSN
  • 0007-1145 (ISSN-L)
  • 1475-2662
DOI
10.1017/s0007114513001505
PMC
PMC3734536
OpenAlex
W2169076799
Cited by
150
References
305
Citations by year
2026: 5 · 2025: 4 · 2024: 12 · 2023: 8 · 2022: 14 · 2021: 13 · 2020: 12 · 2019: 10 · 2018: 12 · 2017: 15 · 2016: 13 · 2015: 15 · 2014: 14 · 2013: 2
FWCI
14.96
Type
journal article
Language
en
Open access
Licence
Locations
  • British Journal Of Nutrition (publishedVersion, cc-by-nc-sa)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by-nc-sa)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion)
  • reroDoc Digital Library (submittedVersion)
  • Research Publications (Maastricht University) (submittedVersion, cc-by-nc-sa)
  • ePrints Soton (University of Southampton) (submittedVersion)
  • Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
  • Research Publications (Maastricht University) (submittedVersion, other-oa)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders
  • Mead Johnson Nutrition
  • Danone
  • Loughborough University
  • Universiteit Utrecht
  • Consiglio Nazionale delle Ricerche
  • Università di Bologna
  • Université de Lausanne
  • FrieslandCampina
  • Wageningen University and Research
  • DSM Nutritional Products
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutrition and Health Studies
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Nutritional Studies and Diet
  • Health Sciences › Medicine › Physiology (medical) › Exercise and Physiological Responses
Keywords
immune function, nutrition, dietary intervention, pathogen defense, allergy, metabolic inflammation, marker selection, research design, outcome interpretation, general population
MeSH terms
Health Status, Humans, Hypersensitivity, Immune System, Infections, Inflammation, Nutritional Physiological Phenomena, Research Design, Biomarkers, Outcome Assessment, Health Care, Guidelines as Topic

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