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Comparing apples to apples: Evaluating foodomics in precision nutrition research featuring the influence of polyphenols on the gut microbiome.

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Titel: Comparing apples to apples: Evaluating foodomics in precision nutrition research featuring the influence of polyphenols on the gut microbiome.
Autoren: Keohane, Eva1 (AUTHOR), Prenni, Jessica1 (AUTHOR), Johnson, Sarah A.2 (AUTHOR), Van Buiten, Charlene1,3 (AUTHOR) charlene.vanbuiten@colostate.edu
Quelle: Nutrition Research. Oct2025, Vol. 142, p76-90. 15p.
Schlagwörter: *PHENOL analysis, *DIETARY patterns, *GUT microbiota, *FOOD chemistry, *NUTRITIONAL requirements, *MEDICAL research, *PHENOLS, *MASS spectrometry, *METABOLOMICS, *NUTRITION, *DIET, *DIETARY supplements, *BIOMARKERS, *ANALYTICAL chemistry
Abstract: • Polyphenol composition of dietary interventions may influence the gut microbiome. • Strategies to characterize polyphenols in food vary widely across clinical trials. • Food chemical composition can be characterized using untargeted mass spectrometry. • Untargeted analyses are applied to clinical samples, but not food interventions. • Comprehensive profiling of polyphenols may allow comparison between clinical trials. • Untargeted analysis of food composition can advance precision nutrition research. This review aimed to evaluate the use of advanced omics methodologies in dietary intervention clinical trials investigating the influence of polyphenols on the gut microbiome. All published clinical studies in the Cochrane Library database from 2014 to 2024 containing the keywords "polyphenols" and "gut microbiome" were compiled and categorized based on experimental design, analytical methodologies, and findings. We found that despite known variability in food composition across agricultural and processing parameters, omics analysis of the food used in clinical nutrition interventions has not been widely embraced. None of the studies evaluated employed untargeted omics approaches for food composition analysis, while 5 of the 38 studies used untargeted omics for clinical samples analysis. Targeted analytical methods focused on known compounds or proxies were more commonly used for food composition analysis (18 of 38 studies) and clinical samples (24 of 38 studies), though analysis of clinical samples focused on a greater number of target compounds. Data from these studies support relationships between the gut microbiome, clinical outcomes, and specific metabolites. However, several studies highlight inconsistencies between their findings and previous literature, which may be attributed to unrealized differences in polyphenol composition. We propose that inclusion of comprehensive omics-based food composition analyses in dietary intervention clinical trials may increase study value by accounting for variability in food composition and enabling novel discovery. Such data would support the emerging fields of personalized and precision nutrition, aimed at understanding the influence of individual human characteristics on physiological responses to foods, nutrients, phytochemicals, and dietary patterns. Untargeted analysis of metabolites is widely used in clinical studies to analyze biological samples, but compositional analysis of intervention foods is limited and relies on nonspecific methods or targeted approaches with limited scope. The application of robust compositional analysis of food interventions to clinical trials may enhance precision nutrition research by allowing clinical findings to be linked to the food metabolome. Image created with BioRender (https://BioRender.com). [Display omitted] [ABSTRACT FROM AUTHOR]
Datenbank: Academic Search Index
Beschreibung
Abstract:• Polyphenol composition of dietary interventions may influence the gut microbiome. • Strategies to characterize polyphenols in food vary widely across clinical trials. • Food chemical composition can be characterized using untargeted mass spectrometry. • Untargeted analyses are applied to clinical samples, but not food interventions. • Comprehensive profiling of polyphenols may allow comparison between clinical trials. • Untargeted analysis of food composition can advance precision nutrition research. This review aimed to evaluate the use of advanced omics methodologies in dietary intervention clinical trials investigating the influence of polyphenols on the gut microbiome. All published clinical studies in the Cochrane Library database from 2014 to 2024 containing the keywords "polyphenols" and "gut microbiome" were compiled and categorized based on experimental design, analytical methodologies, and findings. We found that despite known variability in food composition across agricultural and processing parameters, omics analysis of the food used in clinical nutrition interventions has not been widely embraced. None of the studies evaluated employed untargeted omics approaches for food composition analysis, while 5 of the 38 studies used untargeted omics for clinical samples analysis. Targeted analytical methods focused on known compounds or proxies were more commonly used for food composition analysis (18 of 38 studies) and clinical samples (24 of 38 studies), though analysis of clinical samples focused on a greater number of target compounds. Data from these studies support relationships between the gut microbiome, clinical outcomes, and specific metabolites. However, several studies highlight inconsistencies between their findings and previous literature, which may be attributed to unrealized differences in polyphenol composition. We propose that inclusion of comprehensive omics-based food composition analyses in dietary intervention clinical trials may increase study value by accounting for variability in food composition and enabling novel discovery. Such data would support the emerging fields of personalized and precision nutrition, aimed at understanding the influence of individual human characteristics on physiological responses to foods, nutrients, phytochemicals, and dietary patterns. Untargeted analysis of metabolites is widely used in clinical studies to analyze biological samples, but compositional analysis of intervention foods is limited and relies on nonspecific methods or targeted approaches with limited scope. The application of robust compositional analysis of food interventions to clinical trials may enhance precision nutrition research by allowing clinical findings to be linked to the food metabolome. Image created with BioRender (https://BioRender.com). [Display omitted] [ABSTRACT FROM AUTHOR]
ISSN:02715317
DOI:10.1016/j.nutres.2025.09.003