Cross-model metabolomic signatures of dietary anti-inflammatory (poly) phenols in nutraceutical development: a systematic review.
- 1Department of Biochemistry, Ahmadu Bello University, Zaria, Nigeria.
- 2Department of Pharmacognosy and Herbal Medicine, School of Pharmacy and Pharmaceutical Sciences, University for Development Studies, Tamale, Ghana.
- 3Department of Human Ecology, Food Science & Biotechnology Program, College of Agriculture, Science and Technology, Delaware State University, Dover, DE, United States.
Abstract
Dietary (poly) phenols play a key role in nutraceutical development, due to their diverse positive health benefits such as antioxidant and anti-inflammatory properties. Although these bioactivities have been widely reported, the consistency of metabolomic signatures in experimental systems, ranging from in vitro models to human studies, remains unclear. This systematic review examined metabolomic responses to dietary anti-inflammatory (poly) phenols in vitro, animal, human, and mixed-model studies. Searches were conducted in PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2020 and 2025. Seventy-eight eligible primary studies were included and synthesized narratively due to differences in interventions, models, sample matrices, analytical platforms, and outcomes. The synthesis showed model-dependent recurrence of several metabolomic signatures, with lipids, amino acids, and energy metabolism widely represented in the model groups, including phospholipids, sphingolipids, acylcarnitines, branched-chain and aromatic amino acids, kynurenine metabolites, TCA cycle intermediates, glycolytic metabolites, ketone bodies, and ATP markers. Changes in short-chain fatty acids were most consistent in animal and mixed-model gut studies but limited and matrix-dependent in human studies. Urolithins and ellagic acid-derived metabolites were most prominent in human and mixed-model studies, especially urinary biomarkers and microbiome-dependent metabolites. Overall, dietary anti-inflammatory (poly) phenols were associated with recurring metabolomic changes; however, these patterns were influenced by the model system, sample matrix, analytical platform, and intervention type. Further human studies are required to validate these candidate biomarkers and pathways for nutraceutical application.
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BibTeX
@article{fayomi2026crossmodel,
title = {{Cross-model metabolomic signatures of dietary anti-inflammatory (poly) phenols in nutraceutical development: a systematic review.}},
author = {Adesoji Fayomi and Emmanuel Adom and Alberta N A Aryee},
journal = {Frontiers in molecular biosciences},
year = {2026},
month = oct,
doi = {10.3389/fmolb.2026.1824027},
url = {https://europepmc.org/article/MED/42923736},
note = {CC BY},
}
RIS
TY - JOUR
TI - Cross-model metabolomic signatures of dietary anti-inflammatory (poly) phenols in nutraceutical development: a systematic review.
AU - Adesoji Fayomi
AU - Emmanuel Adom
AU - Alberta N A Aryee
PY - 2026
DA - 2026/10/08
JO - Frontiers in molecular biosciences
DO - 10.3389/fmolb.2026.1824027
UR - https://europepmc.org/article/MED/42923736
AB - Dietary (poly) phenols play a key role in nutraceutical development, due to their diverse positive health benefits such as antioxidant and anti-inflammatory properties. Although these bioactivities have been widely reported, the consistency of metabolomic signatures in experimental systems, ranging from in vitro models to human studies, remains unclear. This systematic review examined metabolomic responses to dietary anti-inflammatory (poly) phenols in vitro, animal, human, and mixed-model studies. Searches were conducted in PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2020 and 2025. Seventy-eight eligible primary studies were included and synthesized narratively due to differences in interventions, models, sample matrices, analytical platforms, and outcomes. The synthesis showed model-dependent recurrence of several metabolomic signatures, with lipids, amino acids, and energy metabolism widely represented in the model groups, including phospholipids, sphingolipids, acylcarnitines, branched-chain and aromatic amino acids, kynurenine metabolites, TCA cycle intermediates, glycolytic metabolites, ketone bodies, and ATP markers. Changes in short-chain fatty acids were most consistent in animal and mixed-model gut studies but limited and matrix-dependent in human studies. Urolithins and ellagic acid-derived metabolites were most prominent in human and mixed-model studies, especially urinary biomarkers and microbiome-dependent metabolites. Overall, dietary anti-inflammatory (poly) phenols were associated with recurring metabolomic changes; however, these patterns were influenced by the model system, sample matrix, analytical platform, and intervention type. Further human studies are required to validate these candidate biomarkers and pathways for nutraceutical application.
SN - 2296-889X
ER -