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Endometriosis affects approximately 6 to 10% of reproductive-age women globally. Despite much effort invested, the pathogenesis that promotes the development, as well as the progression of this chronic inflammatory disease, is poorly understood. The imbalance in the microbiome or dysbiosis has been implicated in a variety of human diseases, especially the gut microbiome. In the case of endometriosis, emerging evidence suggests that there may be urogenital-gastrointestinal crosstalk that leads to the development of endometriosis. Along with these findings, several studies have reported the potential of probiotics in managing endometriosis, however subsequent investigations on microbial dynamics post administration of probiotics as well as route of administration and formulation of probiotics would be needed to strengthen the rationale of using such microbiome-based intervention in the management of endometriosis.
Given the challenges in obtaining cervical specimens without cervicovaginal contamination and the nature of biomass in the upper FRT, several teams have attempted to study the differences in the microbiome of the lower FRT. For instance, three studies in Brazil and China studied the vaginal swab or fluid obtained from patients and observed a lower abundance of Lactobacillus in the endometriosis group as compared to the control [24][28][29]. Besides that, the study by Ata et al. discussed the differences in vaginal samples obtained from Stage III or IV endometriosis patients as compared to healthy women [18]. At the genus level, Gemella and Atopobium spp. was absent in the vaginal samples obtained from the endometriosis group. A similar approach was taken by Perrotta et al., but the team took a broader approach to look at the vaginal CST rather than looking at just a specific group of microbes [30]. These data then allowed the team to build a random forest-based classification model with machine-learning methods on microbiota composition to predict r-ASRM stages of endometriosis. Analyzing the changes during follicular and menstrual phases yielded highly predictive taxa which can be used to predict either stage I-II or stage III-IV endometriosis—the genus Anaerococcus (phylum Firmicutes).