Multi-omics analyses reveal the specific changes in gut metagenome and serum metabolome of patients with polycystic ovary syndrome Original paper

What was studied?

This original research article investigated how polycystic ovary syndrome (PCOS) alters the gut microbiome and serum metabolome, aiming to identify a multi-omics microbiome signature that characterizes the disorder. By integrating shotgun metagenomics with untargeted serum metabolomics, the authors examined how gut microbial shifts correlate with key metabolic and hormonal disturbances in PCOS. The goal was to construct mechanistic links between microbial taxa, functional gene pathways, and circulating metabolites—including ganglioside GM3 (d18:0/16:0), ceramide (d16:2/22:0), and 3Z,6Z,9Z-pentacosatriene—that could serve as reliable microbial biomarkers. Findings revealed reductions in microbial diversity, expansion of inflammatory Proteobacteria, loss of short-chain-fatty-acid–producing taxa, and concurrent disruptions in lipid, steroid, and porphyrin metabolism, forming a distinctive gut-metabolite axis in PCOS.

Who was studied?

The study examined 32 women with PCOS and 18 healthy controls, classified using Rotterdam diagnostic criteria. Participants were screened to exclude confounding factors such as recent antibiotics, probiotics, endocrine-active medications, or comorbid gastrointestinal, hepatic, cardiac, or renal disorders. All participants provided stool and serum samples during days 3–5 of the menstrual cycle, ensuring hormonal comparability. Clinical profiling showed typical PCOS phenotypes: elevated testosterone, DHEAS, LH/FSH, AMH, fasting insulin, HOMA-IR, and CRP, along with reduced SHBG. These clinical patterns were directly correlated with microbial and metabolite shifts highlighted through multi-omics integration.

Most important findings

PCOS demonstrated decreased gut microbial α-diversity and a distinct β-diversity profile. Significant species-level alterations involved 64 discriminatory strains: enrichment of pro-inflammatory Proteobacteria (e.g., Pseudomonas sp. M1, Aquitalea pelogenes, Vibrio fortis, Achromobacter xylosoxidans, Sinorhizobium meliloti, Leisingera spp.), and depletion of beneficial SCFA-producers, including Faecalibacterium prausnitzii, Roseburia hominis, Parabacteroides merdae, Odoribacter splanchnicus, and multiple Bacteroides species. Functional metagenomic analysis showed upregulation of mTOR, PI3K/Akt, JAK–STAT, and insulin-signaling pathways, suggesting microbial contributions to insulin resistance and systemic inflammation. Serum metabolomics identified 35 differential metabolites, predominantly lipids and steroid-related molecules. Notably, ganglioside GM3, ceramide (d16:2/22:0), and 3Z,6Z,9Z-pentacosatriene were strongly associated with both microbial shifts and clinical severity. Multi-omics modeling achieved perfect PCOS discrimination (AUC = 1.0) when integrating seven key microbial species with three discriminatory metabolites.

Key implications

The study reveals a mechanistic gut–metabolite–hormone axis in PCOS marked by inflammatory microbial enrichment, loss of SCFA-producing symbionts, and disruptions in lipid and steroid metabolic pathways. These findings underscore the gut microbiome’s potential causal contribution to hyperandrogenism, insulin resistance, and chronic inflammation. The integrative signature identified—particularly the Proteobacteria cluster and its associated ganglioside and ceramide metabolites—offers a promising foundation for diagnostic biomarkers and microbiome-targeted interventions. Fecal microbiota transplantation experiments further support causality, demonstrating that PCOS-derived microbiota can induce metabolic and reproductive abnormalities in rats, while healthy-donor microbiota partially reverse them.

Citation

Yang Z, Fu H, Su H, Cai X, Wang Y, Hong Y, Hu J, Xie Z, Wang X. Multi-omics analyses reveal the specific changes in gut metagenome and serum metabolome of patients with polycystic ovary syndrome.Frontiers in Microbiology. 2022;13:1017147. doi:10.3389/fmicb.2022.1017147