Blood Bacterial 16S rRNA Gene Alterations in Women With Polycystic Ovary Syndrome - Wang, Qing; Wang, Qi; Zhao, Lanbo; Bin, Yadi; Wang, Li; Wang, Lei; Zhang, Kailu; Li, Qiling (Frontiers in Endocrinology, 2022)
Background: Evidence proved the association between gut microbiome dysbiosis and polycystic ovary syndrome (PCOS) in metabolic disorder, decreased fertility and hyperandrogenism. However, alterations in blood microbiome of PCOS remained unknown. Objective: We aimed to measure the blood microbiome profile of PCOS patients compared with healthy controls by 16S rRNA sequencing to investigate its association with PCOS. Methods: In this case-control study, bacterial DNA in blood of 24 PCOS patients and 24 healthy controls was investigated by 16S rRNA Gene Sequencing using the MiSeq technology. Alpha and beta diversity were used to analyze within-sample biodiversity and similarity of one group to another, respectively. Linear discriminant analysis effect size (LEfSe) was calculated to determine biomarkers between groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional prediction was performed at genera level. Result: Alpha diversity of blood microbiome decreased significantly in women with PCOS, and beta diversity analysis demonstrated a major separation between two groups. In PCOS group, the relative abundance of Proteobacteria, Firmicutes and Bacteroidetes decreased significantly, while Actinobacteria increased significantly. Cladogram demonstrated the microbiome differences between two groups at various phylogenic levels. Meanwhile, LDA presented a significant decrease in Burkholderiaceae, Lachnospiraceae, Bacteroidaceae, Ruminococcaceae and S24-7, and a significant increase in Nocardioidaceae and Oxalobacteraceae of the PCOS group. KEGG pathway analysis at genera level suggested that there were 14 pathways had significant differences between two groups. Conclusion: Our findings demonstrated that blood microbiome had a significant lower alpha diversity, different beta diversity and significant taxonomic variations in PCOS patients compared with healthy controls.