Gut Microbiome

Analysis of gut microbiota characteristics in osteoarthritis patients.

TL;DR

OA patients exhibit both elevated serum inflammatory factors and gut microbial dysbiosis, and a combination of five microbial taxa (Eubacterium coprostanoligenes group, Subdoligranulum, Ruminococcus gauvreauii group, Malassezia, and Aspergillus) showed strong diagnostic potential for OA.

Key Findings

Serum levels of inflammatory biomarkers LPS, IL-1β, IL-6, and IL-10 were significantly elevated in OA patients compared to healthy controls.

  • Fecal samples from 32 OA patients and 26 healthy controls were analyzed.
  • ELISA was used to measure serum levels of LPS, IL-1β, IL-6, and IL-10.
  • All four inflammatory markers were significantly elevated in OA patients.
  • Significant associations were found between specific microbiota and these inflammatory markers using Spearman's rank correlation coefficient.

Both alpha diversity and overall composition of gut bacterial and fungal microbiota were altered in OA patients.

  • 16S rRNA sequencing was used to characterize bacterial microbiota and ITS high-throughput sequencing was used for fungal microbiota.
  • Alpha diversity was reduced in OA patients for both bacterial and fungal communities.
  • Overall microbial community composition differed significantly between OA patients and healthy controls.
  • These changes were observed across both bacterial and fungal kingdoms.

At the bacterial phylum level, Proteobacteria increased significantly while Firmicutes and Bacteroidota decreased markedly in OA patients.

  • Proteobacteria abundance was significantly higher in OA patients compared to healthy controls.
  • Firmicutes abundance was markedly decreased in OA patients.
  • Bacteroidota abundance was markedly decreased in OA patients.
  • These phylum-level changes reflect broad shifts in bacterial community structure in OA.

At the bacterial genus level, Escherichia-Shigella and the Ruminococcus gnavus group were significantly increased, while Bacteroides, the Eubacterium halli group, Subdoligranulum, and Faecalibacterium were significantly decreased in OA patients.

  • Escherichia-Shigella, a genus associated with pathogenic bacteria and inflammation, was significantly enriched in OA patients.
  • The Ruminococcus gnavus group was also significantly increased in OA patients.
  • Bacteroides, the Eubacterium halli group, Subdoligranulum, and Faecalibacterium — genera generally associated with gut health — were all significantly reduced.
  • These genus-level differences were identified through 16S rRNA high-throughput sequencing.

At the fungal phylum level, Ascomycota and Basidiomycota were significantly enriched in OA patients, while at the genus level, Saccharomyces and Aureobasidium were more abundant and Aspergillus, Exophiala, and Kurtzmaniella were reduced.

  • ITS high-throughput sequencing was used to characterize the gut mycobiome.
  • Ascomycota and Basidiomycota were the two fungal phyla significantly enriched in OA patients.
  • Saccharomyces and Aureobasidium were significantly more abundant at the genus level in OA patients.
  • Aspergillus, Exophiala, and Kurtzmaniella were significantly reduced in OA patients compared to healthy controls.

Cross-kingdom network analysis revealed weakened interactions between gut bacteria and fungi in OA patients, disrupting the overall ecological balance of the gut microbiome.

  • Cross-kingdom network analysis was applied to assess inter-kingdom microbial interactions.
  • Interactions between bacterial and fungal taxa were weakened in OA patients relative to healthy controls.
  • This weakening of interactions was interpreted as disruption of the overall gut microbiome ecological balance.
  • The finding highlights that OA-associated dysbiosis extends beyond individual kingdoms to affect inter-kingdom dynamics.

A combination of five microbial taxa — the Eubacterium coprostanoligenes group, Subdoligranulum, the Ruminococcus gauvreauii group, Malassezia, and Aspergillus — exhibited strong diagnostic potential for OA based on random forest and ROC analyses.

  • Random forest analysis was used to identify characteristic microbial taxa associated with OA.
  • ROC (receiver operating characteristic) analysis was applied to evaluate diagnostic performance of identified taxa.
  • The five-taxon combination included both bacterial genera (Eubacterium coprostanoligenes group, Subdoligranulum, Ruminococcus gauvreauii group) and fungal genera (Malassezia, Aspergillus).
  • The authors noted that further validation is necessary to confirm clinical applicability of these potential biomarkers.

Specific gut microbiota changes in OA patients were closely correlated with serum inflammatory markers.

  • Spearman's rank correlation coefficient was used to assess relationships between gut microbiota and inflammatory markers.
  • Correlations were identified between specific bacterial and fungal taxa and levels of LPS, IL-1β, IL-6, and IL-10.
  • These correlations suggest a link between gut microbial dysbiosis and systemic inflammation in OA, consistent with the 'gut-bone axis' theory.
  • The study framed these associations as identifying 'potential biological targets for clinical diagnosis and treatment.'

What This Means

This research suggests that people with osteoarthritis (OA) — a common and painful joint disease — have distinct differences in the communities of bacteria and fungi living in their guts compared to healthy individuals. The study analyzed stool samples from 32 OA patients and 26 healthy people and found that OA patients had higher blood levels of inflammatory proteins (LPS, IL-1β, IL-6, and IL-10), reduced diversity in their gut microbes, and specific shifts in the types of bacteria and fungi present. For example, bacteria linked to inflammation (such as Escherichia-Shigella) were more common in OA patients, while bacteria associated with gut health (such as Faecalibacterium and Bacteroides) were reduced. Similar patterns were seen in gut fungi. The study also found that in OA patients, the interactions between gut bacteria and gut fungi were weaker than in healthy people, suggesting that the overall gut ecosystem is disrupted in OA. Using machine learning (random forest analysis) and diagnostic testing methods (ROC analysis), the researchers identified a combination of five microbial groups — three bacterial and two fungal — that together showed promise as potential diagnostic markers to distinguish OA patients from healthy individuals. This research suggests that the gut microbiome may play a role in the development or progression of OA through its influence on inflammation, supporting the concept of a 'gut-bone axis.' The identified microbial signatures could potentially serve as future diagnostic tools or treatment targets, though the authors emphasize that further research and validation in larger populations are needed before any clinical applications could be considered.

Have a question about this study?

Citation

Zou P, Liu X, Wang Y, Xue Z, Yang J, Meng F, et al.. (2026). Analysis of gut microbiota characteristics in osteoarthritis patients.. Frontiers in cellular and infection microbiology. https://doi.org/10.3389/fcimb.2026.1915556