Multi-omics analyses reveal the specific changes in gut metagenome and serum metabolome of patients with polycystic ovary syndrome
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI Uniform resource identifier for web resources.
Authors
Yang Z, Fu H, Su H, Cai X, Wang Y, Hong Y, Hu J, Xie Z, Wang X
Journal
Frontiers in microbiology
Year
2022
Keywords:
fecal microbiota transplantation, gut microbiota, polycystic ovary syndrome, serum metabolome, shotgun metagenomics, untargeted metabolomics
OBJECTIVE: The purpose of this study was to investigate the specific alterations in gut microbiome and serum metabolome and their interactions in patients with polycystic ovary syndrome (PCOS). METHODS: The stool samples from 32 PCOS patients and 18 healthy controls underwent the intestinal microbiome analysis using shotgun metagenomics sequencing approach. Serum metabolome was analyzed by ultrahigh performance liquid chromatography quadrupole time-of-flight mass spectrometry. An integrative network by combining metagenomics and metabolomics datasets was constructed to explore the possible interactions between gut microbiota and circulating metabolites in PCOS, which was further assessed by fecal microbiota transplantation (FMT) in a rat trial. RESULTS: Fecal metagenomics identified 64 microbial strains significantly differing between PCOS and healthy subjects, half of which were enriched in patients. These changed species showed an ability to perturb host metabolic homeostasis (including insulin resistance and fatty acid metabolism) and inflammatory levels (such as PI3K/Akt/mTOR signaling pathways) by expressing sterol regulatory element-binding transcription factor-1, serine/threonine-protein kinase mTOR, and 3-oxoacyl-[acyl-cattier-protein] synthase III, possibly suggesting the potential mechanisms of gut microbiota underlying PCOS. By integrating multi-omics datasets, the panel comprising seven strains (Achromobacter xylosoxidans, Pseudomonas sp. M1, Aquitalea pelogenes, Porphyrobacter sp. HL-46, Vibrio fortis, Leisingera sp. ANG-Vp, and Sinorhizobium meliloti) and three metabolites [ganglioside GM3 (d18:0/16:0), ceramide (d16:2/22:0), and 3Z,6Z,9Z-pentacosatriene] showed the highest predictivity of PCOS (AUC: 1.0) with sensitivity of 0.97 and specificity of 1.0. Moreover, the intestinal microbiome modifications by FMT were demonstrated to regulate PCOS phenotypes including metabolic variables and reproductive hormones. CONCLUSION: Our findings revealed key microbial and metabolite features and their interactions underlying PCOS by integrating multi-omics approaches, which may provide novel insights into discovering clinical diagnostic biomarkers and developing efficient therapeutic strategies for PCOS.
Experiment 1
Reviewed Marked as Reviewed by KateRasheed on 2025-7-3
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Polycystic ovary syndrome Cystic disease of ovaries,hyperandrogenemia,Multicystic ovaries,multicystic ovaries,Ovarian Degeneration, Sclerocystic,Ovarian Syndrome, Polycystic,Ovarian Syndromes, Polycystic,Ovaries, Sclerocystic,Ovary Syndrome, Polycystic,Ovary, Sclerocystic,PCO - Polycystic ovaries,Pco1,PCOD - Polycystic ovarian disease,PCOS,Pcos,PCOS - Polycystic ovarian syndrome,PCOS1,Polycystic ovarian disease,polycystic ovarian disease,Polycystic ovarian syndrome,Polycystic ovaries,polycystic ovaries,Polycystic ovaries (disorder),polycystic ovary,polycystic ovary syndrome,polycystic ovary syndrome 1,Sclerocystic Ovarian Degeneration,Sclerocystic Ovaries,Sclerocystic Ovary,Sclerocystic Ovary Syndrome,Stein Leventhal Syndrome,Stein-Leventhal synd.,Stein-Leventhal Syndrome,Stein-Leventhal syndrome,Syndrome, Polycystic Ovary,Syndrome, Stein-Leventhal,Polycystic ovary syndrome
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy individuals (Control)
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Polycystic ovary syndrome (PCOS)
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients diagnosed with polycystic ovary syndrome (PCOS) according to the Rotterdam criteria, which include at least two of the following: oligo- or anovulation, clinical/biochemical signs of hyperandrogenism, and polycystic ovaries detected by ultrasound.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 18
- Group 1 sample size Number of subjects in the case (exposed) group
- 32
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- 1 Month
Lab analysis
- Sequencing type
- WMS
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Illumina
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- Mann-Whitney (Wilcoxon)
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- Yes
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- decreased
Signature 1
Reviewed Marked as Reviewed by KateRasheed on 2025-7-3
Source: Figure S2B and S3B
Description: Different microbial genera with abundance of over 0.05% between PCOS and healthy controls. The comparison between two groups is performed by the two-tailed Mann-Whitney U-test, and P value is adjusted by Benjamini-Hochberg method.
Abundance in Group 1: increased abundance in Polycystic ovary syndrome (PCOS)
| NCBI | Quality Control | Links |
|---|---|---|
| Blautia | ||
| Actinomycetota | ||
| Actinomyces | ||
| Enterococcus | ||
| Coprobacillus | ||
| Pseudomonas | ||
| Thomasclavelia | ||
| Gordonibacter |
Revision editor(s): Shulamite
Signature 2
Reviewed Marked as Reviewed by KateRasheed on 2025-7-3
Source: Figure S2B and S3B
Description: Different microbial genera with abundance of over 0.05% between PCOS and healthy controls. The comparison between two groups is performed by the two-tailed Mann-Whitney U-test, and P value is adjusted by Benjamini-Hochberg method.
Abundance in Group 1: decreased abundance in Polycystic ovary syndrome (PCOS)
| NCBI | Quality Control | Links |
|---|---|---|
| Faecalibacterium | ||
| Odoribacter | ||
| Parabacteroides | ||
| Paraprevotella | ||
| Phascolarctobacterium | ||
| Roseburia |
Revision editor(s): Shulamite
Experiment 2
Reviewed Marked as Reviewed by KateRasheed on 2025-7-3
Differences from previous experiment shown
Subjects
Lab analysis
Statistical Analysis
- Statistical test
- LEfSe
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- decreased
Signature 1
Reviewed Marked as Reviewed by KateRasheed on 2025-7-3
Source: Figure 1A
Description: Linear discrimination analysis (LDA) effect size (LEfSe) approach was used to identify the discriminatory microbial species with the LDA score (log10) ≥ 2.0 and the adjusted p < 0.05.
Abundance in Group 1: increased abundance in Polycystic ovary syndrome (PCOS)
Signature 2
Reviewed Marked as Reviewed by KateRasheed on 2025-7-3
Source: Figure 1A
Description: Linear discrimination analysis (LDA) effect size (LEfSe) approach was used to identify the discriminatory microbial species with the LDA score (log10) ≥ 2.0 and the adjusted p < 0.05.
Abundance in Group 1: decreased abundance in Polycystic ovary syndrome (PCOS)
Revision editor(s): Shulamite
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