{"paper_id":"f640d8b8-8253-47d8-aa84-f31e63de29f8","body_text":"Endometriosis is a multi-factorial disease defined by the presence of endometrial stroma or glands outside the uterine cavity. Patients with endometriosis, representing approximately 10–15% of reproductive-aged women, commonly experience dysmenorrhea, dyspareunia, and chronic pelvic pain, although there is a wide range in symptom prevalence as well as disease severity ( Dunselman  et al.  2014 ).\nThe most accepted theory on endometriosis pathogenesis is retrograde menstruation, in which reflux of menstrual blood through the fallopian tubes during menstrual cycles associated with an abnormal peritoneal environment permits the implantation and growth of ectopic endometrial tissue ( Burney & Giudice 2019 ).\nThe advent of genomics technologies has greatly facilitated the characterization of the bacterial environment from clinical specimens with granular species-level detail. Previous studies have demonstrated that the microbiome may affect the development and progression of various diseases associated with an abnormal immune/inflammatory response, including inflammatory bowel diseases ( Yang  et al.  2021 ), autoimmune diseases ( Tsai  et al.  2021 ), and cancer ( Lim  et al.  2021 ,  Pothuraju  et al.  2021 ).\nIt is unknown whether an altered microbiome at any anatomical site can cause the development or progression of endometriosis. Similarly, it is not known whether endometriosis can directly induce an altered microbiome. Khan  et al . ( Khan  et al.  2018 ) proposed a ‘bacterial contamination hypothesis’ for endometriosis, whereby bacterial endotoxins activate a peritoneal pro-inflammatory response, increase cell-to-cell adhesion, and facilitate the growth of ectopic endometrial implants.\nEndometriosis most commonly occurs at sites such as the peritoneal cavity that are traditionally assumed to be sterile. However, microbiomal studies have also investigated swabs collected from sites known to have significant bacterial colonization, such as the vagina or rectum ( Chen  et al.  2017 ,  Wang  et al.  2021 ). Previous reviews ( Leonardi  et al.  2020 ,  D’Alterio  et al.  2021 ) have sought to investigate the association between endometriosis and the microbiome from different locations. For this systematic review, we considered microbiome analyses of swabs collected from all potential anatomical sites, regardless of whether the site was locally affected by endometriosis, and also sought to comprehensively collect data on endometriosis stage, menstrual phase, hormonal intake, and endometriosis symptoms.\n\nThe primary objective was to systematically review the association between endometriosis and an altered microbiome across various anatomical sites. Secondary objectives were to evaluate the association between the endometriosis stage or pain symptoms and the microbiome.\n\nBriefly, a literature search was performed on PubMed/Medline, Cochrane, and Embase databases from 1986 to August 2, 2021, using a combination of the following keywords: (microbiome OR microbial OR microbiota) AND (endometriosis OR endometrioma), and only articles published in English were considered. The full search strategy, including a dictionary of synonyms for the above keywords, is described in Supplementary Appendix 1 (see section on  supplementary materials  given at the end of this article).\nAll studies utilizing human subjects that assessed a bacterial microbiome in association with patients with endometriosis were included. Only case–control studies using semi-quantitative methodologies (such as 16s rRNA amplification or shotgun sequencing) capable of quantifying the relative bacterial prevalence between groups were included. Case reports, reviews, conference abstracts, animal studies, and unpublished studies were excluded from this review.\nTwo reviewers (FRO and CHM) independently screened the studies. Conflicts regarding study inclusion were resolved after a discussion between the two reviewers with a third author (MPA) and a senior author (MSA). Reviewers were not blinded to author names, institutional affiliations, or journal identities.\nTwo reviewers (FRO and CHM) independently abstracted data from the selected articles into tables. The following data were extracted for each study: author, year of publication, study design, comparison, sample size, endometriosis type (superficial, ovarian, and deep endometriosis), American Society of Reproductive Medicine (ASRM) stage ( Revised American Society for Reproductive Medicine classification of endometriosis: 1996 1997 ), and results. When data were missing from the manuscript, efforts were made by two of the authors (CHM and FRO) to contact the corresponding authors to obtain complete data.\nTo assess the quality of included studies, publicly available study quality assessment tools provided by the National Institutes of Health (NIH) National Heart, Lung and Blood Institute were utilized, with specific forms for case–control and prospective non-randomized studies ( https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools ). Conflicts regarding study quality were resolved with the senior authors (MPA and MSA). Studies that fulfilled 70% or more criteria were classified as good, 30–70% as fair, and less than 30% as poor quality.\nStudies were summarized and described qualitatively. Due to the heterogeneity of included studies, meta-analysis was not performed.\n\nUsing the search strategy described above, the initial search identified 209 studies. After excluding 65 duplicates, 122 of the remaining 144 studies were excluded following title and abstract review. Full-text screening of 23 studies to evaluate for inclusion and exclusion criteria according to the study design, type of publication, methods, and results was performed by two authors (CHM and FOR), yielding 12 articles, all case–control studies ( Khan  et al.  2016 ,  Xu  et al.  2017 ,  Wang  et al.  2018 ,  Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ,  Chao  et al.  2021 ,  Lee  et al.  2021 ,  Svensson  et al.  2021 ), meeting study inclusion criteria for data abstraction and qualitative analysis ( Fig. 1 ). Key design characteristics of included studies are summarized in  Table 1 .\n Figure 1 Flowchart of included studies. \n Table 1 Summary of included studies evaluating the microbiome and endometriosis. Reference Study design n Comparison Age (years) Sample Methods Akiyama  et al.  (2019) Case–control 69 39 endometriosis 33.9 ± 5.7 Cervical Ion Torrent Personal Genome Machine and qPCR 30 controls: laparoscopy for myomas or benign ovarian tumors 32.5 ± 6.0 Ata  et al.  (2019) Case–control 28 14 endometriosis 28.6 ± 4.4 Stool, vaginal and cervical Microbiome Shotgun sequencing 14 controls: asymptomatic reproductive-aged women 27.8 ± 3.5 Chao  et al.  (2021) Case–control 128 37 endo/adeno with CPP (group A) 39.9 ± 6.2 Posterior vaginal fornix  Microbiome Shotgun sequencing 25 controls with CPP (group B) 37.6 ± 5.5 66 controls without CPP (group C) 38.2 ± 7.8 Chen  et al.  (2020) Case–control 68 12 adenomyosis only, 13 endometriosis only, 7 both adenomyosis and endometriosis 36.1 ± 5.6 Cervical canal (67), posterior fornix (65), eutopic endometrium (2)  Microbiome Shotgun sequencing 36 controls: infertility, myomas, ovarian borderline tumor, and teratoma Hernandes  et al.  (2020) Case–control 21 10 endometriosis 18–50 Eutopic endometrium (18), endometriotic lesion (8), vaginal (21)  Microbiome Shotgun sequencing 11 controls: laparoscopy for benign gynecologic diseases or elective tubal ligation Khan  et al.  (2016) Case–control 64 32 endometriosis: with (16) or without (16) GnRHa 21–47 Eutopic endometrium, ovarian endometrioma fluid  Microbiome Shotgun sequencing 32 controls: ovarian cyst or myoma, with (16) or without (16) GnRHa 21–52 Lee  et al.  (2021) Case–control 90 45 endometriosis 36.2 ± 1.3 Peritoneal fluid Microbiome Shotgun sequencing 45 controls: myomas (31) or benign ovarian cyst (14) 39.4 ± 1.1 Perrotta  et al.  (2020) Case–control 59 35 endometriosis 34.9 ± 6.8 Rectal and vaginal Microbiome Shotgun sequencing 24 controls: laparoscopy for benign gynecologic diseases 35.2 ± 6.9 Svensson  et al.  (2021) Case–control 264 66 endometriosis 38.0 ± 7.9 Stool Microbiome Shotgun sequencing 198 matched controls from the general population 37.7 ± 9.0 Wang  et al.  (2018) Case–control 85 55 endometriosis with infertility 37.2 ± 8.2 Peritoneal fluid Microbiome Shotgun sequencing 30 controls with infertility 37.7 ± 7.4 Wei  et al.  (2020) Case–control 50 36 endometriosis 23–44 Lower third of vagina, posterior vaginal fornix and cervical, eutopic endometrium, and peritoneal fluid Ion Torrent Personal Genome Machine 14 controls: laparoscopy for ovarian teratoma (7), serous cystadenoma (4), uterine myomas (3) Xu  et al.  (2017) Case–control 10 5 endometriosis patients with chronic stress 31.8 ± 2.7 Stool Microbiome Shotgun sequencing 5 endometriosis without chronic stress 32 ± 4.1 CPP, chronic pelvic pain; GnRHa, gonadotropin-releasing hormone agonist; LVFX, levofloxacin.\nFlowchart of included studies.\nSummary of included studies evaluating the microbiome and endometriosis.\nCPP, chronic pelvic pain; GnRHa, gonadotropin-releasing hormone agonist; LVFX, levofloxacin.\nThe endometriosis phenotypes of included patients were heterogeneous among studies and included all types of lesions ( Khan  et al.  2016 ,  Xu  et al.  2017 ,  Wang  et al.  2018 ,  Chen  et al.  2020 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ), ASRM stages III–IV disease ( Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Lee  et al.  2021 ), deep endometriosis ( Hernandes  et al.  2020 ), and both ovarian and deep disease ( Svensson  et al.  2021 ).\nEight studies were rated as fair ( Khan  et al.  2016 ,  Xu  et al.  2017 ,  Wang  et al.  2018 ,  Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Wei  et al.  2020 ,  Lee  et al.  2021 ), three as good ( Hernandes  et al.  2020 ,  Perrotta  et al.  2020 ,  Svensson  et al.  2021 ), and one as poor quality ( Chao  et al.  2021 ). Only one study ( Perrotta  et al.  2020 ) included a sample size justification and only one ( Svensson  et al.  2021 ) included concurrent controls. Researchers were not blinded in any of included studies ( Tables 2  and  3 ). Owing to their case–control designs, no studies provided more than limited evidence (level 3b according to Oxford Center for Evidence-Based Medicine) for their findings.\n Table 2 Quality assessment of case–control studies. Question Akiyama  et al.  (2019) Ata  et al.  (2019) Chao  et al.  (2021) Chen  et al.  (2020) Hernandes  et al.  (2020) Khan  et al.  (2016) Lee  et al.  (2021) Perrotta  et al.  (2020) Svensson  et al.  (2021) Wang  et al.  (2018) Wei  et al.  (2020) Xu  et al.  (2017) 1. Was the research question or objective in this paper clearly stated and appropriate? Y Y Y Y Y Y Y Y Y Y Y Y 2. Was the study population clearly specified and defined? Y Y Y Y Y Y Y Y Y Y Y Y 3. Did the authors include a sample size justification? N N N N N N N Y N N N N 4. Were controls selected or recruited from the same or similar population that gave rise to the cases (including the same timeframe)? Y Y N Y Y Y Y Y Y Y Y Y 5. Were the definitions, inclusion and exclusion criteria, and algorithms or processes used to identify or select cases and controls valid, reliable, and implemented consistently across all study participants? Y Y Y Y Y Y Y Y Y Y Y Y 6. Were the cases clearly defined and differentiated from controls? Y Y N Y Y Y Y Y Y Y Y Y 7. If less than 100% of eligible cases and/or controls were selected for the study, were the cases and/or controls randomly selected from those eligible? Y Y N Y Y N/A N/A Y N N/A Y N/A 8. Was there use of concurrent controls? N N N Y Y Y Y Y Y Y Y N/A 9. Were the investigators able to confirm that the exposure/risk occurred prior to the development of the condition or event that defined a participant as a case? N N N Y Y Y Y Y N/A Y Y N/A 10. Were the measures of exposure/risk clearly defined, valid, reliable, and implemented consistently (including the same time period) across all study participants? Y Y Y Y Y Y Y Y Y Y Y Y 11. Were the assessors of exposure/risk blinded to the case or control status of participants? N N N N N N N N N N N N 12. Were key potential confounding variables measured and adjusted statistically in the analyses? If matching was used, did the investigators account for matching during study analysis? N N N N N/A N N Y Y Y N N Quality Fair Fair Poor Fair Good Fair Fair Good Good Fair Fair Fair Case–control studies were assessed using NIH study quality assessment tools. The replies represents if the study fulfilled each criteria (Y, yes; N, no: N/A, not applicable, not reported, or cannot determine). Overall study quality is summarized in the final row. \n Table 3 Relative expression of bacterial loads in patients with endometriosis compared to patients without endometriosis. Summary of studies that evaluated the microbiome at different sites in patients with and without endometriosis. All studies compared relative frequencies of all bacteria reads performed by 16S RNA next generation sequencing. Site Decreased Increased Bacterial sp. Reference Bacterial sp. Reference Vagina Atopobium Ata  et al.  (2019) Aerococcus Wei  et al.  (2020) Gardenerella Hernandes  et al.  (2020) Alloscardovia Chao  et al.  (2021) Gemella Ata  et al.  (2019) Atopobium * Chen  et al.  (2020) Lactobacillus Chao  et al.  (2021) Campylobacter * Chen  et al.  (2020) Megasphaera Chao  et al.  (2021) Clostridium Chao  et al.  (2021) Prevotella Hernandes  et al.  (2020) Escherichia /  Shigella Ata  et al.  (2019), Chen  et al.  (2020) Shuttleworthia Chao  et al.  (2021) Ezakiella * Chen  et al.  (2020) Faecalibaterium * Chen  et al.  (2020) Gardnerella Ata  et al.  (2019) Lactobacillus Chen  et al.  (2020) Prevotella Wei  et al.  (2020) Stenotrophomonas Chao  et al.  (2021) Veillonella Chao  et al.  (2021) Cervix Atopobium Ata  et al.  (2019) Comamonadaceae Wei  et al.  (2020) Dialister Ata  et al.  (2019) Delftia Wei  et al.  (2020) Megasphaera Ata  et al.  (2019) Enterobacteriaceae Akiyama  et al.  (2019) Prevotella Ata  et al.  (2019) Escherichia /  Shigella Ata  et al.  (2019), Chen  et al.  (2020) Snethia Ata  et al.  (2019) Pseudomonas Wei  et al.  (2020) Snethia Ata  et al.  (2019) Sphingobium  spp Wei  et al.  (2020) Streptococcus Ata  et al.  (2019), Akiyama  et al.  (2019) Ureaplasma Ata  et al.  (2019) Vagococcus Wei  et al.  (2020) Fecal Barnesella Ata  et al.  (2019) Lachnospira Svensson  et al.  (2021) Gardnerella Ata  et al.  (2019) Oscillospira Svensson  et al.  (2021) Snethia Ata  et al.  (2019) Endometrium Gardnerella Hernandes  et al.  (2020) Acinetobacter Wei  et al.  (2020) Prevotella Hernandes  et al.  (2020) Delftia Wei  et al.  (2020) Moraxellaceae Khan  et al.  (2016) Pseudomonas Wei  et al.  (2020) Sphingobium Wei  et al.  (2020) Streptococcaceae Khan  et al.  (2016) Lesion Alishewanella Hernandes  et al.  (2020) Enterococcus Hernandes  et al.  (2020) Pseudomonas Hernandes  et al.  (2020) Peritoneal Fluid Actinomyces Lee  et al.  (2021) Acinetobacter guillouiae Wei  et al.  (2020), Lee  et al.  (2021) Propionibacterium Lee  et al.  (2021) Clostridiales Wei  et al.  (2020) Rothia Lee  et al.  (2021) Enhydrobacter Lee  et al.  (2021) Erysipelothrix  sp. Wei  et al.  (2020) Pseudomonas viridiflava Wei  et al.  (2020), Lee  et al.  (2021) Shewanella  sp. Wei  et al.  (2020) Sphingobium Wei  et al.  (2020) Sphingomonas  sp. Wei  et al.  (2020) Streptococcus Lee  et al.  (2021) Tissierellaceae Wei  et al.  (2020) *Only on both endometriosis and adenomyosis group.\nQuality assessment of case–control studies.\nCase–control studies were assessed using NIH study quality assessment tools. The replies represents if the study fulfilled each criteria (Y, yes; N, no: N/A, not applicable, not reported, or cannot determine). Overall study quality is summarized in the final row.\nRelative expression of bacterial loads in patients with endometriosis compared to patients without endometriosis. Summary of studies that evaluated the microbiome at different sites in patients with and without endometriosis. All studies compared relative frequencies of all bacteria reads performed by 16S RNA next generation sequencing.\n*Only on both endometriosis and adenomyosis group.\nTwo next-generation sequencing (NGS) techniques were used to evaluate microbiomes: microbiome shotgun sequencing ( Khan  et al.  2016 ,  Xu  et al.  2017 ,  Wang  et al.  2018 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Perrotta  et al.  2020 ,  Chao  et al.  2021 ,  Lee  et al.  2021 ,  Svensson  et al.  2021 ) and Ion Torrent Personal Genome Machine ( Akiyama  et al.  2019 ,  Wei  et al.  2020 ).  Akiyama  et al.  (2019) , real‐time PCR was also used for quantification of  Enterobacteriaceae ,  Streptococcus ,  Pseudomonas , and  Corynebacterium  genus.\nStudies using NGS techniques analyzed different amplified regions of 16s-rRNA, including V1–V3 ( Svensson  et al.  2021 ), V3–V4 ( Xu  et al.  2017 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Lee  et al.  2021 ), V4 ( Perrotta  et al.  2020 ,  Chao  et al.  2021 ), V4–V5 ( Wang  et al.  2018 ,  Wei  et al.  2020 ), or V5–V6 ( Khan  et al.  2016 ,  2021 ,  Xu  et al.  2017 ,  Wang  et al.  2018 ,  Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ,  Chao  et al.  2021 ,  Lee  et al.  2021 ,  Svensson  et al.  2021 ). One study ( Khan  et al.  2016 ) did not specify the rRNA amplification region.\nEleven studies ( Khan  et al.  2016 ,  Wang  et al.  2018 ,  Ata  et al.  2019 ,  Akiyama  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ,  Chao  et al.  2021 ,  Lee  et al.  2021 ,  Svensson  et al.  2021 ) compared the microbiome between patients with and without endometriosis and one ( Xu  et al.  2017 ) compared endometriotic patients with and without chronic stress. In these studies, the control groups comprised patients who underwent surgery for other benign gynecological conditions ( Khan  et al.  2016 ,  Akiyama  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Lee  et al.  2021 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ), infertility ( Wang  et al.  2018 ), or chronic pelvic pain (CPP) ( Chao  et al.  2021 ) or asymptomatic patients who presented for routine gynecologic ( Ata  et al.  2019 ,  Chao  et al.  2021 ) or general visits ( Svensson  et al.  2021 ). The relative expression of bacteria across anatomical sites in patients with endometriosis compared to those without endometriosis is summarized in  Table 3 .\nSeven studies evaluated the microbiome in vaginal and cervical samples ( Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Hernandes  et al.  2020 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ,  Chao  et al.  2021 ) and three ( Khan  et al.  2016 ,  Hernandes  et al.  2020 ,  Wei  et al.  2020 ) in endometrial samples.  Akiyama  et al.  (2019)  performed a case–control study comparing 39 moderate-to-severe endometriosis patients against 30 patients with benign gynecological conditions undergoing surgery and found that the cervical microbiota was similar between the two groups.  Lactobacilli  species were predominant in both groups whereas  Enterobacteriaceae  and  Streptococcus  were more prevalent in women with endometriosis ( P  < 0.05).\nChen  et al.  (2020)  compared the cervical and vaginal microbiome in 68 Chinese women stratified by the presence of endometriosis and adenomyosis and defined 4 groups: no endometriosis or adenomyosis, endometriosis only, adenomyosis only, and both adenomyosis and endometriosis ( n   = 36, 13, 12 and 7, respectively).  Lactobacillus  was the most prevalent genus in the vagina in all groups, but the genus  Atopobium  was more commonly identified in women with both endometriosis and adenomyosis.  Campylobacter ,  Ezakiella , and  Faecalibaterium  were also more abundant among patients with both endometriosis and adenomyosis.\nAta  et al.  (2019)  studied the cervical and vaginal microbiome of 28 Caucasian women (14 with endometriosis ASRM stages III–IV and 14 asymptomatic patients without endometriosis who presented for a routine gynecological visit). They found that women with endometriosis were more likely to harbor  Alloprevotella  in the cervix, while  Atopobium  and  Sneathia  were only identified in the controls.  Gemella  and  Atopobium  were not detected in the vaginal microbiomes of endometriosis patients. When excluding  Lactobacillus  from the analysis, the relative abundance of  Gardnerella ,  Streptococcus ,  Escherichia / Shigella , and  Ureaplasma  was found to be increased in endometriosis patients.\nHernandes  et al.  (2020)  compared vaginal fluid and endometrial samples between 10 women with deep endometriosis and 11 without endometriosis undergoing benign gynecological surgery. While  Lactobacillus  predominated in the vaginal fluid of both endometriosis and control patients,  Gardnerella  and  Prevotella  were in lower relative abundance in samples of vaginal fluid and endometrium from endometriosis patients.\nPerrotta  et al.  (2020)  conducted an observational study comparing 35 Brazilian women with endometriosis stages I–IV against 24 without endometriosis undergoing surgery for benign gynecological diseases. The authors found no significant differences in the vaginal and rectal microbiome between endometriosis and control patients.\nWei  et al.  (2020)  compared vaginal and cervical swabs from 16 Chinese women with stage I–II and 20 III–IV endometriosis against 14 women undergoing surgery for benign gynecological diseases. While the lower reproductive tract of both groups was dominated by  Lactobacillus, Aerococcus,  and  Prevotella  were enriched in endometriosis patients. Cervical swabs demonstrated enrichment of  Vagococcus ,  Arthrobacter ,  Pseudomonas ,  Sphingobium ,  Comamonadaceae,  and  Delftia  in women with endometriosis. Endometrial samples showed enrichment of  Sphingobium ,  Pseudomonas ,  Delftia , and  Acinetobacter .\nChao  et al.  (2021)  compared 128 samples from the posterior vaginal fornix of Chinese women and divided them into 3 groups: 37 women with CPP plus endometriosis or adenomyosis, 25 women with CPP without endometriosis/adenomyosis, and 66 without CPP with endometriosis/adenomyosis who presented for a routine gynecologic visit. The group with endometriosis/adenomyosis and associated CPP was associated with a greater relative abundance of bacteria of the genera  Clostridium, Alloscardovia, \n Veillonella,  and  Stenotrophomonas  and a lower abundance of  Megasphaera ,  Lactobacillus,  and  Shuttleworthia  compared to those without endometriosis.\nKhan  et al.  (2016)  identified 32 women with endometriosis stages I–IV and 32 without endometriosis who underwent benign gynecological surgery and compared the presence of 5 bacterial families in endometrial samples:  Lactobacillacae ,  Streptococcaceae ,  Staphylococaceae ,  Enterobacteriaceae , and  Moraxellaceae . In women with endometriosis, there was an increase in  Streptococcaceae  and  Moraxellaceae .\nThree studies ( Wang  et al.  2018 ,  Wei  et al.  2020 ,  Lee  et al.  2021 ) analyzed the relationship between endometriosis and the microbiome within the peritoneal fluid, one of which ( Wei  et al.  2020 ) also collected samples from other sites.\nLee  et al.  (2021) , compared 45 women with stages III and IV endometriosis (mean age: 36.2 ± 1.3 years old) against 45 controls who underwent laparoscopy, 31 for myomas and 14 for benign ovarian cysts (mean age: 39.4 ± 1.1 years old). At a genus level, there was a significant increase in  Acinetobacter ,  Pseudomonas ,  Streptococcus , and  Enhydrobacter  in the endometriosis group compared to the control group ( P   < 0.05), as well as a significant reduction in the genera  Propionibacterium ,  Actinomyces , and  Rothia  ( P  <  0.05).\nWang  et al.  (2018)  compared 55 individuals with endometriosis and infertility (mean age: 37.2 ± 8.2 years old) against 30 controls with infertility without endometriosis (mean age: 37.7 ± 7.4 years old). The main bacteria detected in the peritoneal fluid were  Proteobacteria  and  Firmicutes , followed by  Actinobacteria ,  Bacteroides ,  Fusobacterium , and  Tenericutes . There was no statistically significant difference between endometriosis and control groups ( P   > 0.05).\nWei  et al.  (2020)  compared peritoneal fluid samples of 50 Chinese women, 36 with pelvic endometriosis and 14 who underwent laparoscopy for ovarian teratoma, serous cystadenoma, or uterine fibroids. They found a significant increase in  Pseudomonas  and  Sphingobium  in the peritoneal fluid of women with endometriosis.\nTwo case–control studies compared the fecal microbiome of women with and without endometriosis ( Ata  et al.  2019 ,  Svensson  et al.  2021 ).  Svensson  et al.  (2021)  included 264 patients, comparing 66 women with endometriosis and with 198 matched controls from a cohort of descendants participating in the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). The analysis showed only three bacteria with a significant difference with higher abundance between endometriosis and control groups:  Lachnospira ,  Oscillospira , and a genus in the order  Bacterioidales  ( P  <  0.05).\nAta  et al.  (2019)  compared 14 women with endometriosis against 14 asymptomatic reproductive-aged women who presented for a routine well-woman visit or preconception counseling. They found that the relative abundance of bacteria in the genera  Sneathia ,  Barnesella , and  Gardnerella  from stool samples of the endometriosis group was significantly decreased ( P  <  0.001).\nThree studies ( Khan  et al.  2016 ,  Perrotta  et al.  2020 ,  Svensson  et al.  2021 ) compared the microbiome between patients across different endometriosis types or stages ( Table 4 ).  Perrotta  et al.  (2020)  showed that the vaginal microbiome during the menstrual phase was significantly different between patients with ASRM stages III–IV compared to stages I–II ( P   = 0.019), which was not significantly different from the vaginal microbiome of control patients. Patients with ASRM stage III–IV endometriosis had vaginal microbiomes enriched for  Anaerococcus  compared with lower-stage patients.\n Table 4 Microbiomal studies comparing menstrual cycle phase, hormonal intake, or endometriosis type. Reference n \n Hormonal treatment ( n ) Menstrual phase ( n , proliferative/secretory) Endometriosis type ( n ) Comparison of symptoms Akiyama  et al.  (2019) 69 No Control (17/22) Endometriosis (16/14) No difference between menstrual phase ASRM stages III–IV Not reported Ata  et al.  (2019) 28 No Control (7/7) Endometriosis (7/7) ASRM stages III–IV Not reported Chao  et al.  (2021) 128 Combined oral contraceptives (75) and IUD (11). No comparison between groups Endometriosis/adenomyosis with CPP (12/15) Controls with CPP (5/16) Controls without CPP (22/35) Not reported ↓Lactobacillus jensenii, ↓ Shuttleworthia, ↑ Clostridium butyricum, ↑ Alloscardovia in endometriosis patients with chronic pelvic pain Chen  et al.  (2020) * 68 No Not reported Ovarian endometriosis, deep, and peritoneal Not reported Hernandes  et al.  (2020) 21 Yes ** Not reported Deep endometriosis Not reported Khan  et al.  (2016) 64 GnRHa (16) ↓ Lactobacillacae, ↑ Streptococcaceae , ↑ Staphylococaceae , ↑ Enterobacteriaceae  in GnRHa-treated women with endometriosis vs untreated women.  ↑ Staphylococaceae  in GnRH-treated compared with untreated control women Control (4/10) Endometriosis (2/9) ASRM stage I (11), II (2), III (7), and IV (12) Not reported Lee  et al.  (2021) 90 No Not reported ASRM stages III (34) and IV (11) Not reported Perrotta  et al.  (2020) 59 No Menstrual and proliferative ↑  Lactobacillus  in proliferative phase compared to secretory and menstrual Bowel (13), retrocervical (14), bladder (4), ovarian (2), superficial (1), and abdominal wall (1). ASRM stages I (9), II (12), III (4), and IV (10). Not reported Svensson  et al.  (2021) 264 Yes (41) ↑  Blautia,  ↑  Ruminococcus,  ↑ Butyricimonas  among those taking hormones Not reported Ovarian (27), Gastrointestinal (18) No significant association with the intensity of pain symptoms or digestive complaints Wang  et al.  (2018) 85 No Not reported ASRM stages I–II (28) and stages III–IV (27) Not reported Wei  et al.  (2020) 50 No Proliferative (50) ASRM stage I–II (16) and stages III–IV (20) Not reported Xu  et al.  (2017) 10 Not reported Not reported ASRM stages I–II (2) and stages III–IV (8) ↓ Paraprevotella, ↓Odoribacter, ↓Veillonella ↓Ruminococcus, and ↑  Prevotella  in chronically stressed endometriosis patients * This study included four groups: no endometriosis or adenomyosis ( n  = 36), endometriosis only ( n  = 13), adenomyosis only ( n  = 12), and both adenomyosis and endometriosis ( n   = 7).  ** Number of patients taking hormones not reported. ASRM, American Association for Reproductive Medicine Classification; CPP, chronic pelvic pain.\nMicrobiomal studies comparing menstrual cycle phase, hormonal intake, or endometriosis type.\n* This study included four groups: no endometriosis or adenomyosis ( n  = 36), endometriosis only ( n  = 13), adenomyosis only ( n  = 12), and both adenomyosis and endometriosis ( n   = 7).  ** Number of patients taking hormones not reported.\nASRM, American Association for Reproductive Medicine Classification; CPP, chronic pelvic pain.\nTwo studies ( Khan  et al.  2016 ,  Svensson  et al.  2021 ) compared the fecal or ovarian cyst microbiome among different types of endometriosis without using the ASRM staging system.  Svensson  et al.  (2021)  found no significant difference in the stool microbiome between ovarian and deep endometriosis.  Khan  et al.  (2016)  found a significantly higher percentage of  Streptococcaceae  and  Staphylococaceae  and a significant reduction in  Lactobacillacae  in the ovarian endometrioma cystic fluid in comparison with non-endometriotic cysts.\nWhile six microbiomal studies among endometriosis patients ( Khan  et al.  2016 ,  Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Wei  et al.  2020 ,  Perrotta  et al.  2020 ,  Chao  et al.  2021 ) reported on the menstrual cycle phase, only two compared the microbiome during different menstrual phases ( Table 4 ).  Akiyama  et al.  (2019)  found no significant differences in the cervical microbiome across different menstrual phases of either endometriosis or control patients.  Perrotta  et al.  (2020)  observed an increase in vaginal  Lactobacillus  species in the proliferative phase compared to the secretory and menstrual phases. The authors ( Perrotta  et al.  2020 ) also observed an increase in anaerobic bacteria in the endometrium or peritoneal fluid during the proliferative and secretory phases compared to the menstrual phase.\nFour studies ( Khan  et al.  2016 ,  Hernandes  et al.  2020 ,  Chao  et al.  2021 ,  Svensson  et al.  2021 ) included women possibly taking hormonal agents, while seven ( Wang  et al.  2018 ,  Akiyama  et al.  2019 ,  Ata  et al.  2019 ,  Chen  et al.  2020 ,  Perrotta  et al.  2020 ,  Wei  et al.  2020 ,  Lee  et al.  2021 ) were restricted to patients without current hormonal intake ( Table 4 ).  Khan  et al.  2016  evaluated the effect of the use of a gonadotropin-releasing hormone agonist (GnRHa) on women with endometriosis and showed that  Lactobacillacae  was significantly decreased ( P   < 0.01), while  Streptococcaceae ,  Staphylococaceae,  and  Enterobacteriaceae  were significantly increased ( P   < 0.05 for each) in vaginal swabs from GnRHa-treated women with endometriosis compared with GnRHa-untreated women. In contrast, vaginal samples from GnRHa-treated control women showed significantly higher colonization with  Staphylococaceae  ( P   < 0.05) and insignificant colonization with  Enterobacteriaceae  ( P   = 0.071) compared with samples from GnRHa-untreated control women.  Svensson  et al.  (2021)  examined the fecal microbiome among women with endometriosis and identified a higher abundance of  Blautia ,  Ruminococcus , and  Butyricimonas  among those taking hormonal medications, including estrogen, combined oral contraceptives, progestin, or gonadotropin-releasing hormone analogs. The remaining studies did not report on changes in the microbiome in association with hormonal intake.\nThree studies ( Xu  et al.  2017 ,  Chao  et al.  2021 ,  Svensson  et al.  2021 ) compared the association between endometriosis symptoms and the microbiome.  Svensson  et al.  (2021)  compared 66 patients with endometriosis and 198 asymptomatic women without endometriosis from the MDC-CC cohort described above. In a subanalysis of the 66 endometriosis patients, they reported no significant association of their stool microbiome with the intensity of pain symptoms or digestive complaints, including abdominal pain, constipation, diarrhea, bloating, and vomiting.\nXu  et al.  (2017)  studied the fecal microbiome of ten subjects with endometriosis, five reporting chronic stress and five not reporting chronic stress. They found significantly decreased levels of  Paraprevotella ,  Odoribacter ,  Veillonella  and  Ruminococcus  in chronically stressed endometriosis patients, while  Prevotella  was significantly increased among the chronically stressed endometriosis patients.\nChao  et al.  (2021)  compared the fecal microbiome of 37 patients with endometriosis or adenomyosis plus (CPP, 25 patients without endometriosis but reporting CPP, and 66 without endometriosis or CPP. Patients with endometriosis and CPP were found to have the lowest relative abundance of  Lactobacillus jensenii  and the highest abundance of  Clostridium butyricum  compared to the other two groups. Endometriosis patients with CPP also had significantly lower  Lactobacillus  and  Shuttleworthia  and significantly higher  Clostridiales  and  Alloscardovia  abundance compared with no endometriosis patients without CPP, but no difference compared to patients with CPP and without endometriosis.\n\nThis review identified multiple microbiome studies on patients with endometriosis. This systematic review highlighted many of the limitations of such studies, including heterogeneous methods for identifying and typing bacteria, various anatomical sources for microbiomal sample collection (fecal, vaginal, cervical, peritoneal, endometrial, and intra-lesional), significant heterogeneity among patients both with endometriosis and the so-called controls (including heterogeneity in menstrual cycle timing, use of hormonal medications, symptomatology, disease severity, and the presence of comorbid conditions such as adenomyosis), and inherent publication bias. Such limitations collectively have precluded completing a meta-analysis of the underlying studies.\nNonetheless, several trends appear to stand out from these imperfect, heterogeneous studies. Several studies suggest that peritoneal fluid appears to contain a different distribution of bacteria among women with endometriosis, though only  Pseudomonas  ( Wei  et al.  2020 ,  Lee  et al.  2021 ) was found to be overrepresented among patients with endometriosis in multiple studies. Fecal microbiome studies ( Xu  et al.  2017 ,  Ata  et al.  2019 ,  Svensson  et al.  2021 ) appear to be conflicting in the reported prevalence of various bacteria. The one study that reported an association between chronic stress in endometriosis and an altered fecal microbiome ( Xu  et al.  2017 ) is yet to be validated.\nWhile the association between the fecal microbiome and endometriosis remains inconclusive, the topic remains biologically plausible. The gut microbiome interacts with immune and metabolic systems and is associated with various disease states, including inflammatory bowel syndrome, arthritis, psoriasis, and cancer ( Smet  et al.  2021 ,  Wertman  et al.  2021 ). The dysbiosis of the gastrointestinal tract can lead to higher gut permeability, a higher concentration of macrophages in peritoneal fluid, secretion of interleukin IL-1 and IL-10, and modulation of local immune response to the clearance of menstrual debris and thus potentiate endometriosis development ( D’Alterio  et al.  2021 ). Also, it has been suggested that dysbiosis of the gut microbiome may alter the so-called estrobolome and lead to enhanced estrogen deconjugation and increased free circulating levels, potentially contributing to endometriosis progression ( García-Peñarrubia  et al.  2020 ).\nThe inferior female reproductive tract is a major source of human microbiota, urogenital microbiota being responsible for 9% of all bacterial species in the human body ( Cani 2018 ). Cervicovaginal lactobacilli deficiency is correlated with higher genital pro-inflammatory cytokines and activation of antigen-presenting cells through lipopolysaccharide (LPS) pathways ( Cani 2018 ). Also, studies have shown that the fecal and vaginal microbiota are correlated and that the use of probiotics can impact both the fecal and vaginal environments, suppressing pro-inflammatory cytokine production ( Melis  et al.  2018 ).\nWhile the diversity of the vaginal and fecal microbiome is well-recognized, the presence of meaningful bacterial colonization at other sites such as the endometrium or within endometriosis biopsies remains controversial. Identification of bacteria at supposedly sterile sites may suggest contamination or another infectious process rather than evidence of endometriosis ( Chen  et al.  2017 ). The upper genital tract may become colonized via the bloodstream, mesenteric lymph nodes, or through the retrograde progression of cervical and vaginal bacteria, though its role in modulating uterine health in unclear ( Baker  et al.  2018 ,  Wang  et al.  2021 ).\nPrevious studies suggested that the microbiome in the vaginal tract may be influenced by hormonal treatments and the menstrual cycle phase. Despite this, only two studies ( Akiyama  et al.  2019 ,  Perrotta  et al.  2020 ) attempted to address confounding from the menstrual phase. The lack of such standardization and correction for clear confounding variables is a significant limitation that should be addressed in future studies. Similarly, most studies did not attempt to control for the endometriosis stage, thus limiting the generalizability of observed results. For example, patients with endometriosis infiltrating the bowel have a much more plausible and direct connection to developing an altered fecal microbiome than patients with endometriosis without bowel involvement. Future prospective studies with larger samples and stricter methodology combined with patient standardization are needed to clarify the role of the microbiome in endometriosis pathogenesis and clinical features and allow for a precise measurement of the effect of any interventions.\n\nClear differences have been reported from studies of the fecal, vaginal, cervical, endometrial, and peritoneal microbiomes of women with and without endometriosis. An association of the microbiome with the hormonal intake, menstrual cycle phase, and pain symptoms in patients with endometriosis was reported by a few studies. However, studies are limited due to a lack of standardization and small samples, and the cause–effect relationship between the microbiome and endometriosis is yet to be established.\n\nThe authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.\n\nThis work did not receive any specific grant from any funding agency in the public, commercial, or not-for-profit sector.\n\nCarlos H Miyashira: study design, data collection, data analysis and interpretation, manuscript preparation. Fernanda Reali Oliveira: study design, data collection, data analysis and interpretation, manuscript preparation. Marina Paula Andres: study design, data analysis and interpretation, manuscript preparation. Julian A Gingold: manuscript preparation. Mauricio Simões Abrão: study design, manuscript preparation.","source_license":"CC-BY-4.0","license_restricted":false}