Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Randomized Controlled Trial
. 2025 Mar 4;64(3):106.
doi: 10.1007/s00394-025-03627-8.

Multi-study feasibility analysis on a composite biomarker of inflammatory resilience to quantify the effects of energy restriction on low-grade inflammation in overweight and obese individuals

Mark C Dessing  1 , Tim J van den Broek  2 , Femke P M Hoevenaars  2 , Willem J van den Brink  2 , Milena Rundle  3 , Gary Frost  3 , Lydia Afman  4 , Suzan Wopereis  2
Affiliations
Randomized Controlled Trial

Multi-study feasibility analysis on a composite biomarker of inflammatory resilience to quantify the effects of energy restriction on low-grade inflammation in overweight and obese individuals

Mark C Dessing et al. Eur J Nutr. .

Abstract

Purpose: Assessing the health impacts of nutritional interventions in metabolically compromised but otherwise healthy individuals is challenging, necessitating sensitive tools. Phenotypic flexibility offers an innovative way to measure homeostatic capacity during challenge tests. A composite biomarker of inflammatory resilience has proven useful in evaluating the health benefits of whole-grain wheat interventions in overweight and obese individuals. Expanding this method to other dietary interventions to combat low-grade inflammation is essential.

Methods: This study investigated the feasibility of a composite biomarker of inflammatory resilience through secondary analysis of samples from two independent energy restriction (ER) trials, Bellyfat (NCT02194504) and Nutritech (NCT01684917). In these trials, fasting and postprandial inflammation was analysed using a variety of markers. Four composite biomarker models were developed on the basis of postprandial inflammatory marker responses via the 'health space' model method. These models were statistically evaluated for their sensitivity in detecting the effects of 12 weeks of ER.

Results: The minimal composite biomarkers, consisting of IL-6, IL-8, IL-10, and TNF-α, lacked the ability to detect postprandial intervention effects in both ER trials. However, in the Nutritech study, the extended, endothelial, and optimized composite biomarkers of inflammatory resilience displayed significant responses to the ER (all P < 0.005). In the latter 3 models, a reduction in the inflammatory score was correlated with a reduction in BMI and body fat percentage.

Conclusion: This study underscores the feasibility of employing a composite biomarker of inflammatory resilience to evaluate ER interventions. Further validation in additional nutritional intervention studies is necessary. Once validated, this composite biomarker could offer a novel approach for assessing low-grade inflammation and phenotypic flexibility.

Keywords: Biomarker; Inflammation; Low-grade inflammation; Obesity; Resilience.

PubMed Disclaimer

Conflict of interest statement

Declarations. Conflict of interest: Gary Frost has received research funding from Nestle, Quorn and Sosei Heptares but not in relation to this work; he is also a director of the metabolomic profiling company Melico Sciences. Lydia Afman, Milena Rundle: no disclosures. TNO auteurs: This research was funded by a public‒private partnership entitled “PhenFlex-based resilience as a measure for health effects of diet” financed by Topsector Agri & Food (TKI-AF-16035) and cofunded by the PPP allowance made available by Health ~ Holland, Top Sector Life Sciences & Health, to stimulate public–private partnerships. This project was sponsored by TNO roadmap Biomedical Health and cofunded by Pfizer, Inc., BASF SE, By-Health, Roquette, Biofortis Merieux NutriSciences and CIRO. Neither the sponsors nor the co-funders had a role in the analysis, interpretation of the data or writing of the publication. Ethical approval: All the participants provided informed consent prior to their inclusion in the Bellyfat and Nutritech studies [13, 14]. Studies were approved by the appropriate ethics committee and were performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments.

Figures

Fig. 1
Fig. 1
Minimal composite biomarkers of inflammatory resilience (TNF-α, IL-6, IL-8, and IL-10). Baseline (week 0 in red) and follow-up (week 12 in blue) data of each intervention group in the Bellyfat and Nutritech studies. The groups were compared to the metabolically healthy (aged 20–29 years, lean (L) to normal (N) body fat composition) and the metabolically compromised (aged 60–70 years, normal (N) to high (H) body fat composition) reference groups. LQ-ER low-quality energy-restricted diet; HQ-ER high-quality energy-restricted diet
Fig. 2
Fig. 2
Extended composite biomarkers of inflammatory resilience (adiponectin, leptin, CRP, SAA, E-selectin, P-selectin, IFN-γ, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, MPO, PAI-1, sVCAM-1 and sICAM-1). Baseline (week 0 in red) and follow-up (week 12 in blue) data of each intervention group in the Nutritech study, both for the total population and for metabotype A and metabotype B. Compared with metabotype B, metabotype A (less compromised) is characterized by faster glucose clearance, lower intra-abdominal fat, and lower liver lipid levels (compromised) [15]. The groups are compared to the metabolically healthy (aged 20–29 years, lean (L) to normal (N) body fat composition) and the metabolically compromised (aged 60–70 years, normal (N) to high (H) body fat composition) reference groups. *p < 0.0005 between occasions
Fig. 3
Fig. 3
Endothelial activation composite biomarkers of inflammatory resilience (E-selectin, P-selectin, sICAM-1, sVCAM-1 and PAI-1). Baseline (week 0 in red) and follow-up (week 12 in blue) data of each intervention group in the Nutritech study, both for the total population and for metabotype A and metabotype B. Compared with metabotype B, metabotype A (less compromised) is characterized by faster glucose clearance, lower intra-abdominal fat, and lower liver lipid levels (compromised) [15]. The groups are compared to the metabolically healthy (aged 20–29 years, lean (L) to normal (N) body fat composition) and the metabolically compromised (aged 60–70 years, normal (N) to high (H) body fat composition) reference groups. *p < 0.05 between interventions. **p < 0.0010 between occasions
Fig. 4
Fig. 4
Specific Nutritech composite biomarkers of inflammatory resilience (E-selectin, sICAM-1, PAI-1, CRP and SAA). Baseline (week 0 in red) and follow-up (week 12 in blue) data of each intervention group in the Nutritech study, both for the total population and for metabotype A and metabotype B. Compared with metabotype B, metabotype A (less compromised) is characterized by faster glucose clearance, lower intra-abdominal fat, and lower liver lipid levels (compromised) (15). The groups are compared to the metabolically healthy (aged 20–29 years, lean (L) to normal (N) body fat composition) and the metabolically compromised (aged 60–70 years, normal (N) to high (H) body fat composition) reference groups. *p < 0.05 between or within groups. **p < 0.0005 between occasions
See this image and copyright information in PMC

References

    1. van den Broek TJ, Bakker GCM, Rubingh CM, Bijlsma S, Stroeve JHM, van Ommen B et al (2017) Ranges of phenotypic flexibility in healthy subjects. Genes Nutr 12:32 - PMC - PubMed
    1. van Ommen B, van der Greef J, Ordovas JM, Daniel H (2014) Phenotypic flexibility as key factor in the human nutrition and health relationship. Genes Nutr 9(5):423 - PMC - PubMed
    1. Huber M, Knottnerus JA, Green L, van der Horst H, Jadad AR, Kromhout D et al (2011) How should we define health? BMJ 343:d4163 - PubMed
    1. Wopereis S (2023) Phenotypic flexibility in nutrition research to quantify human variability: building the bridge to personalised nutrition. Proc Nutr Soc 82(3):346–358 - PubMed
    1. Stroeve JHM, van Wietmarschen H, Kremer BHA, van Ommen B, Wopereis S (2015) Phenotypic flexibility as a measure of health: the optimal nutritional stress response test. Genes Nutr 10(3):13 - PMC - PubMed

Publication types

LinkOut - more resources