Faecal microbiota and serum metabolome association with equine metabolic syndrome in connemara ponies

Background: Faecal microbiome and serum metabolome have been studied in human medicine to provide a better understanding of metabolic derangements including diabetes; however, equivalent studies in equine medicine are limited. This was a case–control study conducted to identify differences in faecal microbiota composition and concurrent serum metabolite patterns between metabolically normal Connemara ponies and those with Equine Metabolic Syndrome (EMS). Thirty privately owned Connemara ponies (15 EMS and 15 controls) were included in the study. EMS was diagnosed by oral sugar test (OST). Blood samples were collected before and after an oral sugar challenge. One concurrent faecal sample was collected from each pony. Sequencing of the V3-V4 region of 16S rRNA gene was used to identify the microbial communities in faecal samples and assess the differences in microbial profiles between groups. Serum metabolites were analyzed using liquid chromatography–high-resolution mass spectrometry (LC–MS). Finally, multi-omics analysis was conducted by integration of microbiota-metabolome datasets to determine potential associations between metabolites and microbiota in EMS. Results: The faecal microbiota community composition was significantly different between EMS and control groups (p = 0.04 and r² = 4.3%). EMS ponies showed reduced species richness and evenness compared to normal ponies, however it did not reach significant difference. The EMS ponies showed an enrichment of serum metabolites belonging to triglycerides (TGs), along with a reduction of other metabolite classes. Integrative multi-omics analysis revealed two modules in the metabolome and microbiota datasets that were significantly different between the EMS and control groups (p < 0.05). Conclusions: This study suggests that concurrent faecal microbiota and serum metabolome features significantly differ between Connemara ponies with and without EMS. These results provide insights that may assist in the search for diagnostic markers associated with microbiota changes and novel preventative management methods to manipulate microbiota in horses with EMS.