Abstract:

Objective To investigate the microbiome composition of deep invasive endometriosis lesions， offering novel insights into its pathogenesis， diagnosis， and treatment strategies. Methods From May 2021 to May 2022， we collected samples of normal endometrium （normal group， n = 10）， endometrium from patients with deep infiltrating endometriosis （DIE endometrium group， n = 14）， and lesions from these patients （DIE lesion group， n = 10） for 16s rRNA sequencing analysis. We employed the bacterial community diversity algorithm （alpha diversity and beta diversity）， principal coordinate analysis （PCoA） distance matrix algorithms （Bray?Curtis and Unifrac matrices）， as well as the biological identification algorithm （LeFSe） to investigate microbiome differences between groups and identify differentially abundant bacteria and enriched KEGG functions. Results The diversity of the three groups did not show any significant difference， while the β diversity exhibited a statistically significant distinction （P = 0.005 5）. The focus group had a relatively low abundance of Firmicutes at the phylum level and a relatively increased abundance of Fusobacteria. At the genus level， there was an increased relative abundance of Enterococcus and Prevotella. LEFse analysis suggested that Proteobacteria and Gammaproteobacteria were the main dominant in the lesion group. Notably， Gamma proteobacteria emerged as a key differential species among the three groups' microbial flora with statistical significance （P = 0.021 2）. Conclusion Compared to the normal group and DIE group， there was a significant increase in the abundance of Fusobacteria， Proteobacteria， Gammaproteobacteria， Enterococcus， and Prevotella. These findings offer novel therapeutic targets for the prevention and intervention of deep infiltrating endometriosis.

Key words: deep invasive endometriosis, microbiome, gut microbiome