Microbial-Derived Polyphenol Metabolites and the Gut Microbiota: A Scoping Review of Clinical Studies

Dietary (poly)phenols are widely recognized for their health-promoting properties, yet their bioactivity is largely contingent upon gut microbial metabolism. Individual differences in microbiome composition lead to variable production of microbial-derived (poly)phenol metabolites (MPMs) and thus contribute to divergent health outcomes.

This scoping review aimed to systematically map the scope of clinical evidence reporting relationships between MPMs and gut microbiota composition and function, highlighting research gaps to guide future investigations.

Using predefined search criteria, 2 reviewers identified human clinical studies reporting relationships between metabolite concentrations and microbiome outcomes.

Fifty-six studies were included. Evidence was frequently focused on phenolic acids (n = 20), phytoestrogens (n = 18), and urolithins (n = 17), with relationships between microbiota and other MPMs being reported in only 1 to 2 studies. The majority of studies across MPM categories used 16S rRNA gene sequencing for the identification of gut microbiota (n = 42), among other methods, with only 6 studies using metagenomic shotgun sequencing, thus limiting taxonomic resolution and functional inference. Findings revealed recurrent associations between specific microbes and MPMs. Although some reflected known producer taxa (e.g., Gordonibacter and urolithins), others may represent broader community-level interactions (e.g., Alistipes and equol). However, these results varied across (poly)phenol class, intervention type, and host-specific context.

This scoping review identified recurrent microbiota-MPM associations alongside major evidence gaps, including limited functional microbiome characterization and sparse investigation of several MPM classes/subclasses (e.g., resveratrol-, flavanone-, and flavan-3-ol-related MPMs). Future research using standardized, high-resolution multi-omics approaches is needed to improve the identification of reproducible microbial signatures and mechanisms underlying (poly)phenol metabolism and to link these features with functional health outcomes.