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. 2024 May 17;24(1):169.
doi: 10.1186/s12866-024-03329-x.

Characterization of the gut microbiota in polycystic ovary syndrome with dyslipidemia

Tianjin Yang #  1 , Guanjian Li #  1   2   3   4   5 , Yuping Xu #  1   2   3   4   5 , Xiaojin He  6   7 , Bing Song  8   9   10   11   12 , Yunxia Cao  13   14   15   16   17
Affiliations

Characterization of the gut microbiota in polycystic ovary syndrome with dyslipidemia

Tianjin Yang et al. BMC Microbiol. .

Abstract

Background: Polycystic ovary syndrome (PCOS) is an endocrinopathy in childbearing-age females which can cause many complications, such as diabetes, obesity, and dyslipidemia. The metabolic disorders in patients with PCOS were linked to gut microbial dysbiosis. However, the correlation between the gut microbial community and dyslipidemia in PCOS remains unillustrated. Our study elucidated the different gut microbiota in patients with PCOS and dyslipidemia (PCOS.D) compared to those with only PCOS and healthy women.

Results: In total, 18 patients with PCOS, 16 healthy females, and 18 patients with PCOS.D were enrolled. The 16 S rRNA sequencing in V3-V4 region was utilized for identifying the gut microbiota, which analyzes species annotation, community diversity, and community functions. Our results showed that the β diversity of gut microbiota did not differ significantly among the three groups. Regarding gut microbiota dysbiosis, patients with PCOS showed a decreased abundance of Proteobacteria, and patients with PCOS.D showed an increased abundance of Bacteroidota compared to other groups. With respect to the gut microbial imbalance at genus level, the PCOS.D group showed a higher abundance of Clostridium_sensu_stricto_1 compared to other two groups. Furthermore, the abundances of Faecalibacterium and Holdemanella were lower in the PCOS.D than those in the PCOS group. Several genera, including Faecalibacterium and Holdemanella, were negatively correlated with the lipid profiles. Pseudomonas was negatively correlated with luteinizing hormone levels. Using PICRUSt analysis, the gut microbiota community functions suggested that certain metabolic pathways (e.g., amino acids, glycolysis, and lipid) were altered in PCOS.D patients as compared to those in PCOS patients.

Conclusions: The gut microbiota characterizations in patients with PCOS.D differ from those in patients with PCOS and controls, and those might also be related to clinical parameters. This may have the potential to become an alternative therapy to regulate the clinical lipid levels of patients with PCOS in the future.

Keywords: Dyslipidemia; Gut microbiota; Polycystic ovary syndrome.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Gut microbial diversity in all participants. (A) The rarefaction curve based on the number of observed OTUs in the three groups. The boxplots of α diversity among the three groups in Chao1 (B), Simpson (C), and Shannon indices (D). (E) Venn diagram displaying the common and distinct OTUs among the three groups. (F) PCoA analysis through weighted UniFrac metric on gut microbial communities among the three groups
Fig. 2
Fig. 2
The results of gut microbiota in participants. (A) A phylum-level heatmap of the gut microbiota. (B) Gut microbiota of three groups at phylum level. (C) Abundance comparison of three groups at family level. (D) Gut microbiota of three groups at genus level
Fig. 3
Fig. 3
The comparison of gut bacteria at genus level among the groups. LEfSe and Cladogram analyses of significantly different classification units between Control and PCOS (A), Control and PCOS.D (B), PCOS and PCOS.D (C)
Fig. 4
Fig. 4
Pathway features related to gut microbial communities based on PICRUSt analysis. (A) The heatmap of functions in gut microbiota among the three groups. PICRUSt analysis between Control and PCOS (B), Control and PCOS.D (C), and PCOS and PCOS.D (D). The data was statistically significant (P < 0.05)
Fig. 5
Fig. 5
Correlation between clinical parameters in patients with PCOS and gut microbial communities. (A) Correlations of gut microbial genera and clinical parameters. Spot colors indicate the R value of Spearman correlation between clinical parameters and gut microbial compositions. *P < 0.05 and **P < 0.01. (B) The correlation between the abundance of Pseudomonas and the serum level of LH. (C) The correlation between the abundance of Pseudomonas and the serum level of LDL-C. (D) The correlation between the abundance of Faecalibacterium and the level of TC. (E) The correlation between the abundance of Faecalibacterium and the level of TG. (F) The correlation between the abundance of Faecalibacterium and the serum level of SHBG. (G) The correlation between the abundance of Clostridium_sensu_strictio_1 and the serum level of FSH
Fig. 6
Fig. 6
The flowchart of study participants
See this image and copyright information in PMC

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