Clinical indicators and reproductive tract microbiota abnormalities indicate the occurrence of endometriosis

Clinical indicators and reproductive tract microbiota abnormalities indicate the occurrence of endometriosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical indicators and reproductive tract microbiota abnormalities indicate the occurrence of endometriosis Xiaoqing Li, Cong Chen, Yuanyuan Zheng, Wenjing Lin, Hongping Zhang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3806951/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Endometriosis is an inflammation-associated disease, primarily but not always associated with abnormal immune system function and expression of immune factors. The microbiota of the female reproductive tract, including the vagina and cervix, plays a crucial role in health and disease. The immune dysregulation caused by the imbalance of reproductive tract microbiota may contribute to endometriosis. In this study, 35 women was recruited, including 17 women with endometriosis and 18 healthy women, while their general clinical data, cervical secretions and vaginal secretions were collected. High-throughput sequencing technology was performed to analyze the cervical and vaginal microbiota. We found that patients with endometriosis have unique vaginal and cervical microbiota. Romboutsia , Ruminococcus , Phascolarctobacterium , and Olsenella in the reproductive tract had significant positive correlation with the visual analogue scale index for endometriosis, while Mobiluncus displayed a significant negative correlation with the visual analogue scale index, and Lactobacillus showed a significant negative correlation with the thyroid peroxidase antibody index. These clinical and microbiological indicators might be associated with endometriosis, and this study has clinical significance for the detection and prevention of endometriosis. endometriosis vaginal microbiome cervical microbiome clinical indicators Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Endometriosis is a disease characterized by the presence of endometrial or glandular tissue outside the uterine cavity [ 1 ], affecting 5–10% of reproductive-age women worldwide [ 2 ] It is associated with chronic pelvic pain and infertility [ 3 ]. Women with endometriosis lesions have an increased risk of ovarian cancer, breast cancer, melanoma, asthma, rheumatoid arthritis, and cardiovascular diseases [ 4 ], and it significantly impacts women's health. Microorganisms and hosts establish synergistic interactions in almost every ecological niche of the human body, influencing both physiological and pathological processes [ 5 ]. Female reproductive tract microbes, including vaginal and cervical microbes, have been shown to be site-specific and play an important role in maintaining health and homeostasis [ 6 ] Imbalances in reproductive tract bacteria can lead to reproductive tract infections and elevate the risk of various diseases, including endometriosis [ 7 ], recurrent implantation failure [ 8 ] endometritis [ 9 ], and preterm birth [ 10 ]. The microbiota along the female reproductive tract is a continuum, and the microbes in the female upper reproductive tract may have migrated from the lower reproductive tract, but the exact circumstances are not clear [ 6 ]. Endometriosis is a complex disease with multifactorial causes involving genetic and immune pathways, as well as environmental influences such as dietary habits, nutrition, and antibiotic treatments [ 5 ]. However, the pathogenesis of endometriosis has not been consistently explained. Although some studies have suggested that microbes play a small role in endometriosis [ 7 ], a growing number of recent studies have provided strong evidence in support of the important role of microbes, especially those in the reproductive tract, in endometriosis [ 5 , 7 , 11 , 12 ]. Research on vaginal or cervical microbiota could potentially aid in detecting common upper reproductive tract disorders [ 6 ]. Therefore, investigating the reproductive tract microbiota of endometriosis patients is necessary. In this study, we collected vaginal secretions and cervical secretions from both healthy individuals and women with endometriosis to explore the roles of vaginal and cervical microbiota in endometriosis. We also investigated the relationship between clinical indicators and microbiota, laying a foundation for better understanding endometriosis. Results A total of 35 women were recruited in this study, including 17 patients with endometriosis and 18 healthy women, and the cervical tube secretions and vaginal secretions were collected. 16S rRNA gene sequencing was performed in the V3-V4 region of each sample. Finally, 70 samples were sequenced successfully, producing 2,592,100 reads (2×250 bp), with an average of 37,030 reads per sample. Most of the sequence lengths were in the range of 400-430bp. The amount of sequencing data was sufficient, and the number of sequencing sequences could well reflect the microbial diversity of each community. We collected the clinical information of all volunteers, including age, fertility status, body mass index, carbohydrate antigen 125 (CA125), thyroid function, coagulation function, blood routine and leukorrhea routine, and we found that CA125, thyroid peroxidase antibody (TPO-Ab) and visual analogue scale (VAS) in endometriosis were higher than those in healthy women ( P < 0.05, Wilcoxon test), while there was no difference in others. Disorders of vaginal microbiome in women with endometriosis To explore the vaginal microbiota of endometriosis patients, we analyzed the vaginal microbiota of healthy women and women with endometriosis. We found that Chao1 index in women with endometriosis was significantly higher than that in healthy people ( P < 0.05, Wilcoxon test), indicating that the number of vaginal microorganisms in endometriosis was significantly higher than that in healthy people (Fig. 1 A). Principal coordinates analysis based on the Bray‒Curtis distance showed no significant differences between them (Fig. 1 B). It could be seen that Firmicutes dominated in both endometriosis and healthy women at phylum level, while Lactobacillus dominanted at genus level (Fig. 1 C-D). Linear discriminant analysis revealed that Aerococcus , Aerococcaceae, and Megasphaera were dominant in endometriosis (Fig. 1 E-F). We speculated that the role of vaginal microorganisms in endometriosis might be related to these bacteria genera. Disorders of cervical microbiome in women with endometriosis To explore the cervical microbiota of endometriosis patients, we analyzed the cervical microbiota of healthy women and women with endometriosis. We found that Chao1 index ( P < 0.001, Wilcoxon test) and Shannon index ( P < 0.05, Wilcoxon test) were significantly higher in the endometriosis, indicating higher diversity and evenness of cervical secretions in endometriosis compared to healthy individuals (Fig. 2 A). Principal coordinates analysis showed no significant differences between the two groups (Fig. 2 B). Similar to the vaginal microbiota, Firmicutes dominated at phylum level, and Lactobacillus dominanted at genus level (Fig. 2 C-D). Linear discriminant analysis revealed that 17 species of bacteria such as Lactobacillus , Bifidobacterium , and Megasphaera were dominant in healthy individuals, while 108 species of bacteria such as Phascolarctobacterium , Romboutsia , Ruminococcus and Olsenella were dominant in endometriosis, suggesting that the role of cervical microorganisms in endometriosis might be related to these bacteria genera (Fig. 2 E). Specific reproductive tract microbes and clinical indicators were correlated with endometriosis To explore the relationship between reproductive tract microbiota and clinical indicators in endometriosis, spearman correlation analysis was performed on the relative abundances of all vaginal microorganisms (Fig. 3 A-G) and cervical microorganisms (Fig. 4 A-G) at the genus level and the significant different clinical indicators, including VAS, TPO-Ab, CA125 (Table 1 ). We found that 8 vaginal microorganisms, including Romboutsia , Mobiluncus and Ruminococcus , were significantly correlated with VAS, and 5 bacteria, including Ruminococcus , Phascolarctobacterium and Olsenella , were related to CA125. Lactobacillus , DNF00809 , Mycoplasma , and Peptoniphilus were significantly associated with TPO-Ab (Fig. 3 A). Further, we found that 10 cervical microorganisms, including Romboutsia , Mobiluncus and Ruminococcus , were significantly correlated with VAS. 17 bacteria were correlated with CA125, such as Ruminococcus, Phascolarctobacterium and Olsenella , while Lactobacillus and Sneathia were significantly correlated with TPO-Ab (Fig. 4 A). Numerous microbiota showed significant correlations with these indicators. Notably, Romboutsia , Ruminococcus , Phascolarctobacterium , and Olsenella exhibited significant positive correlations with the VAS clinical indicator in both vaginal and cervical microbiota (Figs. 3 B-E and 4 B-E). In contrast, Mobiluncus showed a significant negative correlation with the VAS clinical indicator (Figs. 3 F and 4 F). Lactobacillus in two different reproductive tract loci were significantly correlated with TPO-Ab clinical indicators (Figs. 3 G and 4 G), suggesting that these bacteria might be related to the occurrence of endometriosis. Table 1 Baseline characteristics of participants. Variable Endometriosis group (n = 17) Control group (n = 18) P value Age (year) 35 ± 7.04 33.5 ± 5.77 0.716 Body mass index (kg/ m^2) 22.31 ± 3.23 22.31 ± 1.59 0.146 Prothrombin time (s) 12.21 ± 1.16 11.95 ± 0.72 0.716 Activated partial thromboplastin time (s) 31.60 ± 2.96 30.82 ± 3.28 0.334 Thrombin time (s) 6.29 ± 7.13 5.8 ± 6.90 0.488 International normalized ratio 1.06 ± 0.11 1.06 ± 0.11 0.518 Fibrinogen (g/L) 10.39 ± 6.09 10.64 ± 5.81 0.843 D-dimer (mg/L) 2.09 ± 1.27 12.21 ± 1.21 0.355 Fibrin degradation product (mg/L) 1.72 ± 3.55 0.82 ± 0.32 0.986 White blood cell count (10^9/L) 6.27 ± 1.2 6.29 ± 1.76 0.961 Red blood cell count (10^9/L) 4.07 ± 0.35 4.29 ± 0.30 0.788 Hemoglobin (g/L) 114.59 ± 14.21 129 ± 9.44 0.104 Platelet count (10^9/L) 250.29 ± 55.61 230.12 ± 46.34 0.392 Neutrophil-to-lymphocyte ratio 2.4 ± 1.12 2.20 ± 1.09 0.728 Platelet-to-lymphocyte ratio 153.34 ± 46.79 25.87 ± 31.65 0.058 Total triiodothyronine (ng/mL) 1.00 ± 0.17 0.95 ± 0.16 0.338 Total thyroxine (ng/mL) 84.08 ± 15.37 77.83 ± 9.10 0.314 Free triiodothyronine (pmol/L) 4.90 ± 0.79 4.78 ± 0.54 0.518 Free thyroxine (pmol/L) 10.12 ± 2.34 11.07 ± 0.92 0.098 Thyroid-stimulating hormone (mIU/L) 93 ± 2.26 2.23 ± 1.13 0.644 Thyroid peroxidase antibodies (IU/ml) 67.38 ± 143.7 2.28 ± 4.68 0.004 Cancer antigen 125 (U/ml)) 52.35 ± 24.42 16.47 ± 12.97 0.001 Degree of vaginal clearing (number) 0.575 I 1 0 II 14 16 III 2 2 IV 0 0 Number of leukocytes (number) 0.547 0–5/HP 14 15 5–10/HP 0 1 10–30/HP 3 2 <30/HP 0 0 Bacillus vaginalis (number) 0.053 None 9 15 Little 8 3 Medium 0 0 Many 0 0 Positive rate of clue cell (%) 0 0 - Positive rate of fungal (%) 0 0 - Positive rate of trichomonads (%) 0 0 - Positive rate of red blood cells (%) 0 0 - Positive rate of neuraminidase (%) 0 11.11 0.157 Positive rate of hydrogen (%) 0 0 - Positive rate of leukocyte lipase (%) 76.47 50 0.171 Positive rate of β-glucuronic acid (%) 0 0 - Positive rate of acetylglucosaminidase (%) 5.88 5.55 0.967 pH value 4.48 ± 0.17 4.48 ± 0.27 0.93 American society for reproductive medicine stage (%) I or II - 18% - III or IV - 82% - Visual analog scale 5.12 ± 1.86 1.22 ± 1.06 0.002 Discussion In this study, we confirmed that cervical and vaginal microbes were associated with endometriosis. Compared to healthy women, patients with endometriosis had unique vaginal and cervical microbiota. The formation of endometriosis might be related to changes in the reproductive tract microbiota. We also found the correlations between the bacteria of vagina and cervix and clinical indicators, providing a new perspective for exploring endometriosis. Microbial communities differ among different parts of the reproductive tract. The cervix acts as a gateway connecting the vagina and the uterine cavity. Microbial communities in the cervix and endometrium differ from those in the vagina [ 6 ]. In healthy women, the endometrium and vagina are primarily composed of Lactobacillus , Gardnerella , Streptococcus , and Prevotella [ 13 ], with Lactobacillus being dominant. Lactobacillus produces lactic acid, maintaining a low pH in the vagina and inhibiting the growth of pathogenic bacteria. Such an acidic environment also affects cervical mucus function. However, in endometriosis patients, Lactobacillus is reduced in vaginal microbiota, cervical microbial diversity changes, and the differences of the microbial community diversity increase gradually along the reproductive tract [ 14 ]. Chang et al. found that cervical microbiota underwent alterations in endometriosis. In contrast to vaginal microbiota, Lactobacillus and Streptococcus increased, along with Dialister decreased. Furthermore, in patients with more severe clinical symptoms, both the richness and diversity of cervical microbiota were reduced [ 15 ]. Hernandes et al. discovered distinct bacterial composition in deep lesions of endometriosis, Lactobacillus reduced, while Alishewanella , Enterococcus , and Pseudomonas increased [ 13 ]. Our study revealed that the number of vaginal secretions in patients with endometriosis was significantly higher compared to healthy individuals. Additionally, the diversity and evenness of cervical secretions were significantly elevated in endometriosis. These findings indicated a unique microbial composition in individuals with endometriosis, suggesting that changes in reproductive tract microflora were associated with endometriosis. Endometriosis is an inflammatory and estrogen-dependent gynecological disorder characterized by the ectopic growth of endometrial cells outside the uterine cavity, significantly impacting the quality of life of patients [ 5 ]. Typically, the average time from symptom onset to diagnosis of endometriosis is around 8–10 years, and the gold standard for diagnosis is laparoscopy, which is invasive, greatly hinders early diagnosis and treatment of the diseaset [ 5 ]. Multiple factors participating in the chronic inflammatory process of endometriosis had been extensively investigated and linked to its pathogenesis, including hormones, cytokines, chemokines, angiogenic factors, oxidative stress markers, and so on. Nonetheless, no single factor could accurately identify the disease [ 16 ]. Early identification of endometriosis is a difficult clinical problem. Serum CA125, a high-molecular-weight glycoprotein derived from coelomic and mullerian epithelia, including the uterus endometrium, had been reported to be elevated in endometriosis patients and was one of the most commonly described and widely studied biomarkers [ 17 ]. When used as a biomarker, CA-125 showed a sensitivity of 73% and specificity of 98% for diagnosing stage III and IV endometriosis patients when its threshold was 32.4 IU/mL [ 18 ]. The VAS for pain is a diagnostic scoring system to assess the intensity of pain in endometriosis. Studies indicated the VAS scores increased in endometriosis [ 19 ]. TPO-Ab are associated with immune response and thyroid disorders, playing a critical role in cellular metabolism [ 20 ]. Research indicated an elevation of TPO-Ab in endometriosis patients [ 21 ]. These were consistent with our findings that CA-125, TPO-Ab, and VAS were elevated in endometriosis. Furthermore, our research findings revealed that patients with endometriosis had distinctive vaginal and cervical microbiota, and certain specific bacteria were significantly correlated with clinical indicators. For instance, Romboutsia and Ruminococcus were related to VAS, while Ruminococcus , Phascolarctobacterium , and Olsenella were associated with CA125. Lactobacillus was linked to TPO-Ab, these bacteria were also altered in the cervical microbiome of patients with endometriosis (Figs. 2 E), suggesting that these bacteria might be associated with the occurrence of endometriosis. Wei et al. found a correlation between cervical microbiota and the risk of endometriosis [ 14 ] Chang et al. reported that altered cervical microbiota in endometriosis patients was related to CA125 levels, severe pain, and infertility [ 15 ]. Huang et al. discovered distinct microbial communities in endometriosis patients, especially in fecal and peritoneal fluid samples. The abundance of pathogenic organisms increased in peritoneal fluid, while protective microbiota decreased in feces. 26 intestinal microbes were selected to effectively distinguish endometriosis and the area under the curve was 0.840. Among them, Ruminococcus and Pseudomonas were identified as potential biomarkers in intestinal and peritoneal fluid, respectively [ 12 ]. These results suggested that studying reproductive tract microbiota could potentially facilitate non-invasive diagnosis of endometriosis. Currently, numerous studies have found that the modulation of the microbiota played a significant role in restoring uterine function through antibiotics, probiotics, prebiotics, or diet [ 22 , 23 ]. The use of antibiotics in treating chronic endometritis was shown to effectively improve the fertility rates of reproductive-age women [ 24 ]. Women suffering from endometriosis could alleviate pain by orally consuming Lactobacilli [ 25 ], and Lactobacilli could have beneficial effects on interleukin-12 levels and natural killer cell activity, which were relevant to endometriosis [ 26 ]. Diet-induced microbiota reshaping was considered another potential therapeutic strategy for treating endometriosis, with studies indicating that women who consumed high levels of omega-3 polyunsaturated fatty acids had a lower risk of developing endometriosis [ 27 ]. Cervical microbiota was shown to be associated with abnormal apoptosis of endometrial epithelial cells, new blood vessel formation, and host metabolism [ 28 ]. These findings suggest that monitoring changes in the reproductive tract microbiota may potentially play a role in the prevention, diagnosis, and treatment of endometriosis. Previous studies have primarily focused on the correlation between changes in endometrial microbiota and endometriosis, often requiring specimens obtained through surgery or invasive methods. The cervix and vagina, as integral anatomical and histological components of the female reproductive tract, offer clinical advantages in terms of convenient and non-invasive sample collection. Our research findings contributed to the potential of non-invasive diagnosis of endometriosis by investigating the microbiota. Furthermore, although we described the relationships between microbial communities, clinical indicators, and endometriosis, these results are still required larger multicenter cohort studies to further validate. Methods Participant Recruitment This study recruited volunteers who underwent endometriosis surgery and physical examination in Wenzhou People's Hospital from February 2021 to February 2022. All volunteers were Han Chinese and permanent residents of Wenzhou. The study was approved by the ethics committee of Wenzhou People's Hospital (ethics number:2021 − 295) and all patients provided informed consent. Study Groups In this study, 17 women from Wenzhou People's Hospital who underwent laparoscopic ovarian endometriosis surgery and were pathologically diagnosed with endometriosis and 18 healthy women were recruited. Clinical data, including demographic characteristics, medical and reproductive histories, clinical symptom manifestations, laboratory test results (including fertility status, body mass index, carbohydrate antigen 125, thyroid function, coagulation function, blood routine, leukorrhea routine and visual analog scale) and medication usage were collected. All patients were excluded if they had used antibiotics or probiotics within the past 30 days, engaged in sexual activity within the past 2 days, received vaginal treatment or irrigation, had bacterial vaginosis, cervicitis, pelvic inflammatory diseases, acute systemic inflammation, were pregnant, had malignant tumors, or autoimmune diseases. Endometriosis diagnosis followed pathological criteria and was confirmed by two professional physicians [ 29 ]. Sample Collection Vaginal and cervical secretions were collected during the follicular phase of the menstrual cycle. Sterile speculum was used for vaginal and cervical collection, two cotton swabs were rotated gently in the vaginal fornix for 15 seconds to collect the vaginal secretions. For cervical samples, iodine was used to disinfect the cervix and vagina, and a sterile cotton swab was inserted into the cervix and rotated 3–5 times. All samples were stored at -80°C within 4 hours for subsequent testing. DNA Extraction and High-Throughput Sequencing DNA extraction was performed using the QIAamp PowerFecal DNA Kit (QIAGEN, Germany) from vaginal and cervical secretion samples (0.5g). The V3 and V4 regions of bacterial 16S rDNA genes were amplified using primers. The PCR reaction mixture consisted of 5 µL 5× GC buffer, 0.5 µL KAPA dNTP Mix, 0.5 µL KAPA HiFi HotStart DNA polymerase, 0.5 µL primers (10 pM), and 50 ~ 100 ng template DNA, with a final volume of 25 µL. The PCR reaction conditions were as follows: 95°C for 3 min; 95°C for 30 s, 55°C for 30 s, 72°C for 30 s, for 25 cycles; 72°C for 5 min. The PCR products were purified using AMPure XP magnetic beads to remove excess primers and primer dimers.For the secondary amplification, a unique eight-base barcode sequence was added to each sample using indexed primers. The 25 µL PCR reaction mixture for the secondary amplification contained 5 µL 5× GC buffer, 0.75 µL KAPA dNTP Mix, 0.5 µL KAPA HiFi HotStart DNA polymerase, 1.5 µL primers (10 pM), and 5 µL purified products. The PCR conditions for the secondary amplification were: 95°C for 3 min; 95°C for 30 s, 55°C for 30 s, 72°C for 30 s, for 8 cycles; 72°C for 5 min. Subsequently, the amplified products were purified using AMPure XP magnetic beads to generate libraries.Finally, sequencing of the 16S rDNA V3-V4 regions was performed on the MiSeq PE250 sequencing platform. Bioinformatics and Multivariate Statistical Analysis The Fast Length Adjustment of SHort reads (FLASH) was employed to merge paired-end sequencing reads into a single target region sequence. Quality control filtering of the target sequences was performed using the "fastq_quality_filter" function with parameters (-p 90 -q 25 -Q33) from FASTX Toolkit 0.0.14. After filtering, the resulting sequences were aligned to the reference database USEARCH 64 bit v8.0.1517. Chimeric sequences were removed to obtain the final optimized sequences. Random subtraction was used to normalize the read counts for each sample based on the minimum value. At a 97% sequence similarity level, OTU clustering analysis was conducted using the Uclust algorithm from the QIIME software package. Subsequently, taxonomic annotation of OTUs for each sample was performed based on the Silva reference database (Release 128: https://www.arb-silva.de/documentation/release-128/ ). Alpha and beta diversity of samples were computed using the Quantitative Insights to Microbial Ecology (QIIME) software, based on weighted and unweighted Unifrac distance matrices. Additionally, the Linear Discriminant Analysis (LDA) Effect Size (LEfSe) method was utilized to identify statistically significant differences in species abundance between groups, LDA score > 2.0. Statistical comparisons of quantitative clinical data between two groups were conducted using the Wilcoxon rank-sum test, while count data were analyzed using the chi-square test. Correlation analyses were performed using Spearman correlation analysis, and results with a P -value < 0.05 were considered statistically significant. Declarations Acknowledgements This study was supported by the Medical Health Science and Technology Project of Zhejiang Provincial (2023RC272 and 2022KY1207), the Zhejiang Provincial Natural Science Foundation of China (LBY23H200008), and the Science and Technology Planning Project of Wenzhou (Y2023088, Y20210325 and ZY2021025). We thank all participants and their families. Competing interests statement The authors declare no competing interests. Ethics approval The study was approved by the ethics committee of Wenzhou People's Hospital (ethics number:2021-295). Consent to participate All subjects provided informed written consent. Consent for publication All authors agreed with the final version of the manuscript and the order of authors. Data Availability The dataset used and analyzed during the current study is available from the corresponding author on reasonable request. Author contributions Xiaoqing Li: Data interpretation, Writing - original draft, Data analysis, Data visualization. Cong Chen: Project administration. Yuanyuan Zheng: Sample collection, Investigation. WenJing Lin: Data Curation. Hongping Zhang: Sample collection, Supervision. QiongHui Pan: Conceptualization, Supervision, Methodology, Review &editing. References Burney RO, Giudice LC. Pathogenesis and pathophysiology of endometriosis. Fertil Steril. 2012 Sep;98(3):511-9. doi: 10.1016/j.fertnstert.2012.06.029. Taylor HS, Kotlyar AM, Flores VA. 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Lactobacillus gasseri OLL2809 is effective especially on the menstrual pain and dysmenorrhea in endometriosis patients: randomized, double-blind, placebo-controlled study. Cytotechnology. 2011 Mar;63(2):153-61. doi: 10.1007/s10616-010-9326-5. Itoh H, Sashihara T, Hosono A, Kaminogawa S, Uchida M. Lactobacillus gasseri OLL2809 inhibits development of ectopic endometrial cell in peritoneal cavity via activation of NK cells in a murine endometriosis model. Cytotechnology. 2011 Mar;63(2):205-10. doi: 10.1007/s10616-011-9343-z. Hopeman MM, Riley JK, Frolova AI, Jiang H, Jungheim ES. Serum Polyunsaturated Fatty Acids and Endometriosis. Reprod Sci. 2015 Sep;22(9):1083-7. doi: 10.1177/1933719114565030. Yang X, Pan X, Li M, Zeng Z, Guo Y, Chen P, et al. Interaction between Cervical Microbiota and Host Gene Regulation in Caesarean Section Scar Diverticulum. Microbiol Spectr. 2022 Aug 31;10(4):e0167622. doi: 10.1128/spectrum.01676-22. Horne AW, Missmer SA. Pathophysiology, diagnosis, and management of endometriosis. BMJ. 2022 Nov 14;379:e070750. doi: 10.1136/bmj-2022-070750. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3806951","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264542440,"identity":"e6b2b1c1-6359-4ea1-bd35-dc204dea0fa6","order_by":0,"name":"Xiaoqing Li","email":"","orcid":"","institution":"The Third Affiliated Hospital of Shanghai University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqing","middleName":"","lastName":"Li","suffix":""},{"id":264542441,"identity":"67fcd3ac-18f7-4205-b175-e99f60570ba9","order_by":1,"name":"Cong Chen","email":"","orcid":"","institution":"The Third Clinical Institute Affiliated to Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"","lastName":"Chen","suffix":""},{"id":264542442,"identity":"335c0409-75a7-4f82-8331-32c47a7046b7","order_by":2,"name":"Yuanyuan Zheng","email":"","orcid":"","institution":"The Third Clinical Institute Affiliated to Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuanyuan","middleName":"","lastName":"Zheng","suffix":""},{"id":264542443,"identity":"eb17ebb0-4191-460e-93c5-8d007c27c126","order_by":3,"name":"Wenjing Lin","email":"","orcid":"","institution":"The Third Clinical Institute Affiliated to Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenjing","middleName":"","lastName":"Lin","suffix":""},{"id":264542444,"identity":"05c4cd03-c3e1-4598-a632-81ae1c8a6529","order_by":4,"name":"Hongping Zhang","email":"","orcid":"","institution":"The Third Clinical Institute Affiliated to Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hongping","middleName":"","lastName":"Zhang","suffix":""},{"id":264542445,"identity":"9079e404-a5af-47fe-9e25-f69c13fdce83","order_by":5,"name":"Qionghui Pan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0ElEQVRIiWNgGAWjYLCCBCA2YGBsfJBQUUOalmaDB2eOkWCTAQMDm+TDFmbCKs3Zzx688aDijt12ieS2isQGNgb+9u4EvFose/KSLRLOPEveOSOx7UbiDhkGiTNnN+B3z4EcM4nEtsPJBjdAWs6wMRhI5BLQcv4NQktBYhszEVpuQGyxA2lhIEqL5Yw3xkC/HE4wOPOwWSLhzDEegn4x588xvPmj4rC9wfH0hx9/VNTI8bf3EnAYEEsAcWIDVIAHr3JkLfYEVY6CUTAKRsHIBQDpQk+CtQF+dgAAAABJRU5ErkJggg==","orcid":"","institution":"The Third Clinical Institute Affiliated to Wenzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Qionghui","middleName":"","lastName":"Pan","suffix":""}],"badges":[],"createdAt":"2023-12-26 07:59:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3806951/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3806951/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49126480,"identity":"15d5b2cc-388b-4b60-8b1d-9bb1267242c7","added_by":"auto","created_at":"2024-01-03 14:56:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":195811,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVaginal microbiota in healthy women and patients with endometriosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Chao1 index and Shannon index of vaginal microbiota in healthy women and patients with endometriosis; B. Principal coordinates analysis of vaginal microbiota in healthy women and patients with endometriosis; C-D. Relative abundance of vaginal microbiota at phylum level (C) and genus level (D) in healthy women and patients with endometriosis; E-F. Different bacteria of vaginal microbiota in healthy women and patients with endometriosis.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3806951/v1/8db12b8acabe6ce667dae03b.png"},{"id":49126481,"identity":"3ca984c1-b8bc-4381-8419-68f8b2e8d7ee","added_by":"auto","created_at":"2024-01-03 14:56:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":554309,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCervical microbiota in healthy women and patients with endometriosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Chao1 index and Shannon index of cervical microbiota in healthy women and patients with endometriosis; B. Principal coordinates analysis of cervical microbiota in healthy women and patients with endometriosis; C-D. Relative abundance of cervical microbiota at phylum level (C) and genus level (D) in healthy women and patients with endometriosis; E-F. Different bacteria of cervical microbiota in healthy women and patients with endometriosis.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3806951/v1/294ad48aa353a51be3a72bf4.png"},{"id":49126483,"identity":"80d0e033-b627-4783-962c-46f110b2ab19","added_by":"auto","created_at":"2024-01-03 14:56:58","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":421743,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVaginal microbiota associated with clinical indicators in healthy women and patients with endometriosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Vaginal microbiota associated with clinical indicators, green represents that the bacteria is also associated with this clinical marker in the cervix; B. Correlation between VAS and \u003cem\u003eRuminococcus\u003c/em\u003e; C. Correlation between VAS and \u003cem\u003eOlsenella\u003c/em\u003e; D. Correlation between VAS and \u003cem\u003ePhascolarctobacterium\u003c/em\u003e; E. Correlation between VAS and \u003cem\u003eRomboutsia\u003c/em\u003e; F. Correlation between VAS and \u003cem\u003eMobiluncus\u003c/em\u003e; G. Correlation between TPO-Ab and \u003cem\u003eLactobacillus\u003c/em\u003e; H. Correlation between CA125 and \u003cem\u003eRuminococcus\u003c/em\u003e; I. Correlation between CA125 and\u003cem\u003e Olsenella\u003c/em\u003e; J. Correlation between CA125 and \u003cem\u003ePhascolarctobacterium\u003c/em\u003e. VAS represents visual analogue scale, TPO-Ab represents thyroid peroxidase antibody, CA125 represents carbohydrate antigen 125.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3806951/v1/99b0dad7876e98160fd75387.png"},{"id":49126482,"identity":"f8e4978f-8cbd-410c-a23d-aca8b8c5132f","added_by":"auto","created_at":"2024-01-03 14:56:58","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":556706,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCervical microbiota associated with clinical indicators in healthy women and patients with endometriosis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. Cervical microbiota associated with clinical indicators, green represents that the bacteria is also associated with this clinical marker in the vaginal; B. Correlation between VAS and \u003cem\u003eRuminococcus\u003c/em\u003e; C. Correlation between VAS and \u003cem\u003eOlsenella\u003c/em\u003e; D. Correlation between VAS and \u003cem\u003ePhascolarctobacterium\u003c/em\u003e; E. Correlation between VAS and \u003cem\u003eRomboutsia\u003c/em\u003e; F. Correlation between VAS and \u003cem\u003eMobiluncus\u003c/em\u003e; G. Correlation between TPO-Ab and \u003cem\u003eLactobacillus\u003c/em\u003e; H. Correlation between CA125 and \u003cem\u003eRuminococcus\u003c/em\u003e; I. Correlation between CA125 and \u003cem\u003eOlsenella\u003c/em\u003e; J. Correlation between CA125 and \u003cem\u003ePhascolarctobacterium\u003c/em\u003e; K. Correlation between CA125 and \u003cem\u003eRomboutsia\u003c/em\u003e. VAS represents visual analogue scale, TPO-Ab represents thyroid peroxidase antibody, CA125 represents carbohydrate antigen 125.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3806951/v1/d37506c6008a76e082462235.png"},{"id":60572552,"identity":"70f00014-c2a5-45e4-a4b6-dce2394491ab","added_by":"auto","created_at":"2024-07-18 09:52:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2112287,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3806951/v1/e786afe7-2876-4dba-bbd2-4bc6057cc43e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Clinical indicators and reproductive tract microbiota abnormalities indicate the occurrence of endometriosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEndometriosis is a disease characterized by the presence of endometrial or glandular tissue outside the uterine cavity [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], affecting 5\u0026ndash;10% of reproductive-age women worldwide [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] It is associated with chronic pelvic pain and infertility [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Women with endometriosis lesions have an increased risk of ovarian cancer, breast cancer, melanoma, asthma, rheumatoid arthritis, and cardiovascular diseases [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and it significantly impacts women's health.\u003c/p\u003e \u003cp\u003eMicroorganisms and hosts establish synergistic interactions in almost every ecological niche of the human body, influencing both physiological and pathological processes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Female reproductive tract microbes, including vaginal and cervical microbes, have been shown to be site-specific and play an important role in maintaining health and homeostasis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] Imbalances in reproductive tract bacteria can lead to reproductive tract infections and elevate the risk of various diseases, including endometriosis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], recurrent implantation failure [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] endometritis [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and preterm birth [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The microbiota along the female reproductive tract is a continuum, and the microbes in the female upper reproductive tract may have migrated from the lower reproductive tract, but the exact circumstances are not clear [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEndometriosis is a complex disease with multifactorial causes involving genetic and immune pathways, as well as environmental influences such as dietary habits, nutrition, and antibiotic treatments [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the pathogenesis of endometriosis has not been consistently explained. Although some studies have suggested that microbes play a small role in endometriosis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], a growing number of recent studies have provided strong evidence in support of the important role of microbes, especially those in the reproductive tract, in endometriosis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Research on vaginal or cervical microbiota could potentially aid in detecting common upper reproductive tract disorders [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Therefore, investigating the reproductive tract microbiota of endometriosis patients is necessary.\u003c/p\u003e \u003cp\u003eIn this study, we collected vaginal secretions and cervical secretions from both healthy individuals and women with endometriosis to explore the roles of vaginal and cervical microbiota in endometriosis. We also investigated the relationship between clinical indicators and microbiota, laying a foundation for better understanding endometriosis.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 35 women were recruited in this study, including 17 patients with endometriosis and 18 healthy women, and the cervical tube secretions and vaginal secretions were collected. 16S rRNA gene sequencing was performed in the V3-V4 region of each sample. Finally, 70 samples were sequenced successfully, producing 2,592,100 reads (2\u0026times;250 bp), with an average of 37,030 reads per sample. Most of the sequence lengths were in the range of 400-430bp. The amount of sequencing data was sufficient, and the number of sequencing sequences could well reflect the microbial diversity of each community. We collected the clinical information of all volunteers, including age, fertility status, body mass index, carbohydrate antigen 125 (CA125), thyroid function, coagulation function, blood routine and leukorrhea routine, and we found that CA125, thyroid peroxidase antibody (TPO-Ab) and visual analogue scale (VAS) in endometriosis were higher than those in healthy women (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Wilcoxon test), while there was no difference in others.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDisorders of vaginal microbiome in women with endometriosis\u003c/h2\u003e \u003cp\u003eTo explore the vaginal microbiota of endometriosis patients, we analyzed the vaginal microbiota of healthy women and women with endometriosis. We found that Chao1 index in women with endometriosis was significantly higher than that in healthy people (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Wilcoxon test), indicating that the number of vaginal microorganisms in endometriosis was significantly higher than that in healthy people (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Principal coordinates analysis based on the Bray‒Curtis distance showed no significant differences between them (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). It could be seen that Firmicutes dominated in both endometriosis and healthy women at phylum level, while \u003cem\u003eLactobacillus\u003c/em\u003e dominanted at genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC-D). Linear discriminant analysis revealed that \u003cem\u003eAerococcus\u003c/em\u003e, Aerococcaceae, and \u003cem\u003eMegasphaera\u003c/em\u003e were dominant in endometriosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE-F). We speculated that the role of vaginal microorganisms in endometriosis might be related to these bacteria genera.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDisorders of cervical microbiome in women with endometriosis\u003c/h2\u003e \u003cp\u003eTo explore the cervical microbiota of endometriosis patients, we analyzed the cervical microbiota of healthy women and women with endometriosis. We found that Chao1 index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Wilcoxon test) and Shannon index (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Wilcoxon test) were significantly higher in the endometriosis, indicating higher diversity and evenness of cervical secretions in endometriosis compared to healthy individuals (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Principal coordinates analysis showed no significant differences between the two groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Similar to the vaginal microbiota, Firmicutes dominated at phylum level, and \u003cem\u003eLactobacillus\u003c/em\u003e dominanted at genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC-D). Linear discriminant analysis revealed that 17 species of bacteria such as \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, and \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eMegasphaera\u003c/span\u003e were dominant in healthy individuals, while 108 species of bacteria such as \u003cem\u003ePhascolarctobacterium\u003c/em\u003e, \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e and \u003cem\u003eOlsenella\u003c/em\u003e were dominant in endometriosis, suggesting that the role of cervical microorganisms in endometriosis might be related to these bacteria genera (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSpecific reproductive tract microbes and clinical indicators were correlated with endometriosis\u003c/h2\u003e \u003cp\u003eTo explore the relationship between reproductive tract microbiota and clinical indicators in endometriosis, spearman correlation analysis was performed on the relative abundances of all vaginal microorganisms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-G) and cervical microorganisms (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA-G) at the genus level and the significant different clinical indicators, including VAS, TPO-Ab, CA125 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We found that 8 vaginal microorganisms, including \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eMobiluncus\u003c/em\u003e and \u003cem\u003eRuminococcus\u003c/em\u003e, were significantly correlated with VAS, and 5 bacteria, including \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e and \u003cem\u003eOlsenella\u003c/em\u003e, were related to CA125. \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eDNF00809\u003c/em\u003e, \u003cem\u003eMycoplasma\u003c/em\u003e, and \u003cem\u003ePeptoniphilus\u003c/em\u003e were significantly associated with TPO-Ab (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Further, we found that 10 cervical microorganisms, including \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eMobiluncus\u003c/em\u003e and \u003cem\u003eRuminococcus\u003c/em\u003e, were significantly correlated with VAS. 17 bacteria were correlated with CA125, such as \u003cem\u003eRuminococcus, Phascolarctobacterium\u003c/em\u003e and \u003cem\u003eOlsenella\u003c/em\u003e, while \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003eSneathia\u003c/em\u003e were significantly correlated with TPO-Ab (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Numerous microbiota showed significant correlations with these indicators. Notably, \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e, and \u003cem\u003eOlsenella\u003c/em\u003e exhibited significant positive correlations with the VAS clinical indicator in both vaginal and cervical microbiota (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB-E and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB-E). In contrast, \u003cem\u003eMobiluncus\u003c/em\u003e showed a significant negative correlation with the VAS clinical indicator (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eF and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). \u003cem\u003eLactobacillus\u003c/em\u003e in two different reproductive tract loci were significantly correlated with TPO-Ab clinical indicators (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eG), suggesting that these bacteria might be related to the occurrence of endometriosis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEndometriosis group (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eControl group (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e35\u0026thinsp;\u0026plusmn;\u0026thinsp;7.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/ m^2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e22.31\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.31\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProthrombin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e12.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivated partial thromboplastin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e31.60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.82\u0026thinsp;\u0026plusmn;\u0026thinsp;3.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.334\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrombin time (s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6.29\u0026thinsp;\u0026plusmn;\u0026thinsp;7.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInternational normalized ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrinogen (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e10.39\u0026thinsp;\u0026plusmn;\u0026thinsp;6.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.64\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2.09\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.21\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrin degradation product (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.72\u0026thinsp;\u0026plusmn;\u0026thinsp;3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell count (10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e6.27\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.29\u0026thinsp;\u0026plusmn;\u0026thinsp;1.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRed blood cell count (10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e114.59\u0026thinsp;\u0026plusmn;\u0026thinsp;14.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129\u0026thinsp;\u0026plusmn;\u0026thinsp;9.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count (10^9/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e250.29\u0026thinsp;\u0026plusmn;\u0026thinsp;55.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e230.12\u0026thinsp;\u0026plusmn;\u0026thinsp;46.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.392\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil-to-lymphocyte ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.20\u0026thinsp;\u0026plusmn;\u0026thinsp;1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet-to-lymphocyte ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e153.34\u0026thinsp;\u0026plusmn;\u0026thinsp;46.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.87\u0026thinsp;\u0026plusmn;\u0026thinsp;31.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal triiodothyronine (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal thyroxine (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e84.08\u0026thinsp;\u0026plusmn;\u0026thinsp;15.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77.83\u0026thinsp;\u0026plusmn;\u0026thinsp;9.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.314\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree triiodothyronine (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4.90\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFree thyroxine (pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e10.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid-stimulating hormone (mIU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e93\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.23\u0026thinsp;\u0026plusmn;\u0026thinsp;1.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid peroxidase antibodies (IU/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e67.38\u0026thinsp;\u0026plusmn;\u0026thinsp;143.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.28\u0026thinsp;\u0026plusmn;\u0026thinsp;4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCancer antigen 125 (U/ml))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e52.35\u0026thinsp;\u0026plusmn;\u0026thinsp;24.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.47\u0026thinsp;\u0026plusmn;\u0026thinsp;12.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDegree of vaginal clearing (number)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of leukocytes (number)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.547\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;5/HP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u0026ndash;10/HP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u0026ndash;30/HP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;30/HP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacillus vaginalis (number)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLittle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMany\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of clue cell (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of fungal (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of trichomonads (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of red blood cells (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of neuraminidase (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of hydrogen (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of leukocyte lipase (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e76.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.171\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of β-glucuronic acid (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive rate of acetylglucosaminidase (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.967\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epH value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmerican society for reproductive medicine stage (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI or II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII or IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVisual analog scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e5.12\u0026thinsp;\u0026plusmn;\u0026thinsp;1.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we confirmed that cervical and vaginal microbes were associated with endometriosis. Compared to healthy women, patients with endometriosis had unique vaginal and cervical microbiota. The formation of endometriosis might be related to changes in the reproductive tract microbiota. We also found the correlations between the bacteria of vagina and cervix and clinical indicators, providing a new perspective for exploring endometriosis.\u003c/p\u003e \u003cp\u003eMicrobial communities differ among different parts of the reproductive tract. The cervix acts as a gateway connecting the vagina and the uterine cavity. Microbial communities in the cervix and endometrium differ from those in the vagina [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In healthy women, the endometrium and vagina are primarily composed of \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eGardnerella\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, and \u003cem\u003ePrevotella\u003c/em\u003e [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], with \u003cem\u003eLactobacillus\u003c/em\u003e being dominant. \u003cem\u003eLactobacillus\u003c/em\u003e produces lactic acid, maintaining a low pH in the vagina and inhibiting the growth of pathogenic bacteria. Such an acidic environment also affects cervical mucus function. However, in endometriosis patients, \u003cem\u003eLactobacillus\u003c/em\u003e is reduced in vaginal microbiota, cervical microbial diversity changes, and the differences of the microbial community diversity increase gradually along the reproductive tract [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Chang et al. found that cervical microbiota underwent alterations in endometriosis. In contrast to vaginal microbiota, \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003eStreptococcus\u003c/em\u003e increased, along with \u003cem\u003eDialister\u003c/em\u003e decreased. Furthermore, in patients with more severe clinical symptoms, both the richness and diversity of cervical microbiota were reduced [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Hernandes et al. discovered distinct bacterial composition in deep lesions of endometriosis, \u003cem\u003eLactobacillus\u003c/em\u003e reduced, while \u003cem\u003eAlishewanella\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003ePseudomonas\u003c/em\u003e increased [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Our study revealed that the number of vaginal secretions in patients with endometriosis was significantly higher compared to healthy individuals. Additionally, the diversity and evenness of cervical secretions were significantly elevated in endometriosis. These findings indicated a unique microbial composition in individuals with endometriosis, suggesting that changes in reproductive tract microflora were associated with endometriosis.\u003c/p\u003e \u003cp\u003eEndometriosis is an inflammatory and estrogen-dependent gynecological disorder characterized by the ectopic growth of endometrial cells outside the uterine cavity, significantly impacting the quality of life of patients [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Typically, the average time from symptom onset to diagnosis of endometriosis is around 8\u0026ndash;10 years, and the gold standard for diagnosis is laparoscopy, which is invasive, greatly hinders early diagnosis and treatment of the diseaset [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Multiple factors participating in the chronic inflammatory process of endometriosis had been extensively investigated and linked to its pathogenesis, including hormones, cytokines, chemokines, angiogenic factors, oxidative stress markers, and so on. Nonetheless, no single factor could accurately identify the disease [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Early identification of endometriosis is a difficult clinical problem. Serum CA125, a high-molecular-weight glycoprotein derived from coelomic and mullerian epithelia, including the uterus endometrium, had been reported to be elevated in endometriosis patients and was one of the most commonly described and widely studied biomarkers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. When used as a biomarker, CA-125 showed a sensitivity of 73% and specificity of 98% for diagnosing stage III and IV endometriosis patients when its threshold was 32.4 IU/mL [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The VAS for pain is a diagnostic scoring system to assess the intensity of pain in endometriosis. Studies indicated the VAS scores increased in endometriosis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. TPO-Ab are associated with immune response and thyroid disorders, playing a critical role in cellular metabolism [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Research indicated an elevation of TPO-Ab in endometriosis patients [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These were consistent with our findings that CA-125, TPO-Ab, and VAS were elevated in endometriosis.\u003c/p\u003e \u003cp\u003eFurthermore, our research findings revealed that patients with endometriosis had distinctive vaginal and cervical microbiota, and certain specific bacteria were significantly correlated with clinical indicators. For instance, \u003cem\u003eRomboutsia\u003c/em\u003e and \u003cem\u003eRuminococcus\u003c/em\u003e were related to VAS, while \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e, and \u003cem\u003eOlsenella\u003c/em\u003e were associated with CA125. \u003cem\u003eLactobacillus\u003c/em\u003e was linked to TPO-Ab, these bacteria were also altered in the cervical microbiome of patients with endometriosis (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE), suggesting that these bacteria might be associated with the occurrence of endometriosis. Wei et al. found a correlation between cervical microbiota and the risk of endometriosis [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] Chang et al. reported that altered cervical microbiota in endometriosis patients was related to CA125 levels, severe pain, and infertility [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Huang et al. discovered distinct microbial communities in endometriosis patients, especially in fecal and peritoneal fluid samples. The abundance of pathogenic organisms increased in peritoneal fluid, while protective microbiota decreased in feces. 26 intestinal microbes were selected to effectively distinguish endometriosis and the area under the curve was 0.840. Among them, \u003cem\u003eRuminococcus\u003c/em\u003e and \u003cem\u003ePseudomonas\u003c/em\u003e were identified as potential biomarkers in intestinal and peritoneal fluid, respectively [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. These results suggested that studying reproductive tract microbiota could potentially facilitate non-invasive diagnosis of endometriosis.\u003c/p\u003e \u003cp\u003eCurrently, numerous studies have found that the modulation of the microbiota played a significant role in restoring uterine function through antibiotics, probiotics, prebiotics, or diet [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The use of antibiotics in treating chronic endometritis was shown to effectively improve the fertility rates of reproductive-age women [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Women suffering from endometriosis could alleviate pain by orally consuming Lactobacilli [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and Lactobacilli could have beneficial effects on interleukin-12 levels and natural killer cell activity, which were relevant to endometriosis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Diet-induced microbiota reshaping was considered another potential therapeutic strategy for treating endometriosis, with studies indicating that women who consumed high levels of omega-3 polyunsaturated fatty acids had a lower risk of developing endometriosis [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Cervical microbiota was shown to be associated with abnormal apoptosis of endometrial epithelial cells, new blood vessel formation, and host metabolism [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. These findings suggest that monitoring changes in the reproductive tract microbiota may potentially play a role in the prevention, diagnosis, and treatment of endometriosis.\u003c/p\u003e \u003cp\u003ePrevious studies have primarily focused on the correlation between changes in endometrial microbiota and endometriosis, often requiring specimens obtained through surgery or invasive methods. The cervix and vagina, as integral anatomical and histological components of the female reproductive tract, offer clinical advantages in terms of convenient and non-invasive sample collection. Our research findings contributed to the potential of non-invasive diagnosis of endometriosis by investigating the microbiota. Furthermore, although we described the relationships between microbial communities, clinical indicators, and endometriosis, these results are still required larger multicenter cohort studies to further validate.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eParticipant Recruitment\u003c/h2\u003e \u003cp\u003eThis study recruited volunteers who underwent endometriosis surgery and physical examination in Wenzhou People's Hospital from February 2021 to February 2022. All volunteers were Han Chinese and permanent residents of Wenzhou. The study was approved by the ethics committee of Wenzhou People's Hospital (ethics number:2021\u0026thinsp;\u0026minus;\u0026thinsp;295) and all patients provided informed consent.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStudy Groups\u003c/h2\u003e \u003cp\u003eIn this study, 17 women from Wenzhou People's Hospital who underwent laparoscopic ovarian endometriosis surgery and were pathologically diagnosed with endometriosis and 18 healthy women were recruited. Clinical data, including demographic characteristics, medical and reproductive histories, clinical symptom manifestations, laboratory test results (including fertility status, body mass index, carbohydrate antigen 125, thyroid function, coagulation function, blood routine, leukorrhea routine and visual analog scale) and medication usage were collected.\u003c/p\u003e \u003cp\u003eAll patients were excluded if they had used antibiotics or probiotics within the past 30 days, engaged in sexual activity within the past 2 days, received vaginal treatment or irrigation, had bacterial vaginosis, cervicitis, pelvic inflammatory diseases, acute systemic inflammation, were pregnant, had malignant tumors, or autoimmune diseases. Endometriosis diagnosis followed pathological criteria and was confirmed by two professional physicians [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSample Collection\u003c/h2\u003e \u003cp\u003eVaginal and cervical secretions were collected during the follicular phase of the menstrual cycle. Sterile speculum was used for vaginal and cervical collection, two cotton swabs were rotated gently in the vaginal fornix for 15 seconds to collect the vaginal secretions. For cervical samples, iodine was used to disinfect the cervix and vagina, and a sterile cotton swab was inserted into the cervix and rotated 3\u0026ndash;5 times. All samples were stored at -80\u0026deg;C within 4 hours for subsequent testing.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDNA Extraction and High-Throughput Sequencing\u003c/h2\u003e \u003cp\u003eDNA extraction was performed using the QIAamp PowerFecal DNA Kit (QIAGEN, Germany) from vaginal and cervical secretion samples (0.5g). The V3 and V4 regions of bacterial 16S rDNA genes were amplified using primers. The PCR reaction mixture consisted of 5 \u0026micro;L 5\u0026times; GC buffer, 0.5 \u0026micro;L KAPA dNTP Mix, 0.5 \u0026micro;L KAPA HiFi HotStart DNA polymerase, 0.5 \u0026micro;L primers (10 pM), and 50\u0026thinsp;~\u0026thinsp;100 ng template DNA, with a final volume of 25 \u0026micro;L. The PCR reaction conditions were as follows: 95\u0026deg;C for 3 min; 95\u0026deg;C for 30 s, 55\u0026deg;C for 30 s, 72\u0026deg;C for 30 s, for 25 cycles; 72\u0026deg;C for 5 min. The PCR products were purified using AMPure XP magnetic beads to remove excess primers and primer dimers.For the secondary amplification, a unique eight-base barcode sequence was added to each sample using indexed primers. The 25 \u0026micro;L PCR reaction mixture for the secondary amplification contained 5 \u0026micro;L 5\u0026times; GC buffer, 0.75 \u0026micro;L KAPA dNTP Mix, 0.5 \u0026micro;L KAPA HiFi HotStart DNA polymerase, 1.5 \u0026micro;L primers (10 pM), and 5 \u0026micro;L purified products. The PCR conditions for the secondary amplification were: 95\u0026deg;C for 3 min; 95\u0026deg;C for 30 s, 55\u0026deg;C for 30 s, 72\u0026deg;C for 30 s, for 8 cycles; 72\u0026deg;C for 5 min. Subsequently, the amplified products were purified using AMPure XP magnetic beads to generate libraries.Finally, sequencing of the 16S rDNA V3-V4 regions was performed on the MiSeq PE250 sequencing platform.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatics and Multivariate Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe Fast Length Adjustment of SHort reads (FLASH) was employed to merge paired-end sequencing reads into a single target region sequence. Quality control filtering of the target sequences was performed using the \"fastq_quality_filter\" function with parameters (-p 90 -q 25 -Q33) from FASTX Toolkit 0.0.14. After filtering, the resulting sequences were aligned to the reference database USEARCH 64 bit v8.0.1517. Chimeric sequences were removed to obtain the final optimized sequences. Random subtraction was used to normalize the read counts for each sample based on the minimum value. At a 97% sequence similarity level, OTU clustering analysis was conducted using the Uclust algorithm from the QIIME software package. Subsequently, taxonomic annotation of OTUs for each sample was performed based on the Silva reference database (Release 128: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arb-silva.de/documentation/release-128/\u003c/span\u003e\u003cspan address=\"https://www.arb-silva.de/documentation/release-128/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlpha and beta diversity of samples were computed using the Quantitative Insights to Microbial Ecology (QIIME) software, based on weighted and unweighted Unifrac distance matrices. Additionally, the Linear Discriminant Analysis (LDA) Effect Size (LEfSe) method was utilized to identify statistically significant differences in species abundance between groups, LDA score\u0026thinsp;\u0026gt;\u0026thinsp;2.0. Statistical comparisons of quantitative clinical data between two groups were conducted using the Wilcoxon rank-sum test, while count data were analyzed using the chi-square test. Correlation analyses were performed using Spearman correlation analysis, and results with a \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Medical Health Science and Technology Project of Zhejiang Provincial (2023RC272 and 2022KY1207), the Zhejiang Provincial Natural Science Foundation of China (LBY23H200008), and the Science and Technology Planning Project of Wenzhou (Y2023088, Y20210325 and ZY2021025). We thank all participants and their families.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the ethics committee of Wenzhou People\u0026apos;s Hospital (ethics number:2021-295).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll subjects provided informed written consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors agreed with the final version of the manuscript and the order of authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used and analyzed during the current study is available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXiaoqing Li: Data interpretation, Writing - original draft, Data analysis, Data visualization. Cong Chen: Project administration. Yuanyuan Zheng: Sample collection, Investigation. WenJing Lin: Data Curation. Hongping Zhang: Sample collection, Supervision. QiongHui Pan: Conceptualization, Supervision, Methodology, Review \u0026amp;editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBurney RO, Giudice LC. Pathogenesis and pathophysiology of endometriosis. Fertil Steril. 2012 Sep;98(3):511-9. doi: 10.1016/j.fertnstert.2012.06.029.\u003c/li\u003e\n\u003cli\u003eTaylor HS, Kotlyar AM, Flores VA. Endometriosis is a chronic systemic disease: clinical challenges and novel innovations. Lancet. 2021 Feb 27;397(10276):839-852. doi: 10.1016/S0140-6736(21)00389-5.\u003c/li\u003e\n\u003cli\u003eSaunders PTK, Horne AW. Endometriosis: Etiology, pathobiology, and therapeutic prospects. Cell. 2021 May 27;184(11):2807-2824. doi: 10.1016/j.cell.2021.04.041.\u003c/li\u003e\n\u003cli\u003eKvaskoff M, Mu F, Terry KL, Harris HR, Poole EM, Farland L, Missmer SA. 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Chronic endometritis due to common bacteria is prevalent in women with recurrent miscarriage as confirmed by improved pregnancy outcome after antibiotic treatment. Reprod Sci. 2014 May;21(5):640-7. doi: 10.1177/1933719113508817.\u003c/li\u003e\n\u003cli\u003eItoh H, Uchida M, Sashihara T, Ji ZS, Li J, Tang Q, et al. Lactobacillus gasseri OLL2809 is effective especially on the menstrual pain and dysmenorrhea in endometriosis patients: randomized, double-blind, placebo-controlled study. Cytotechnology. 2011 Mar;63(2):153-61. doi: 10.1007/s10616-010-9326-5.\u003c/li\u003e\n\u003cli\u003eItoh H, Sashihara T, Hosono A, Kaminogawa S, Uchida M. Lactobacillus gasseri OLL2809 inhibits development of ectopic endometrial cell in peritoneal cavity via activation of NK cells in a murine endometriosis model. Cytotechnology. 2011 Mar;63(2):205-10. doi: 10.1007/s10616-011-9343-z.\u003c/li\u003e\n\u003cli\u003eHopeman MM, Riley JK, Frolova AI, Jiang H, Jungheim ES. Serum Polyunsaturated Fatty Acids and Endometriosis. Reprod Sci. 2015 Sep;22(9):1083-7. doi: 10.1177/1933719114565030.\u003c/li\u003e\n\u003cli\u003eYang X, Pan X, Li M, Zeng Z, Guo Y, Chen P, et al. Interaction between Cervical Microbiota and Host Gene Regulation in Caesarean Section Scar Diverticulum. Microbiol Spectr. 2022 Aug 31;10(4):e0167622. doi: 10.1128/spectrum.01676-22.\u003c/li\u003e\n\u003cli\u003eHorne AW, Missmer SA. Pathophysiology, diagnosis, and management of endometriosis. BMJ. 2022 Nov 14;379:e070750. doi: 10.1136/bmj-2022-070750.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"endometriosis, vaginal microbiome, cervical microbiome, clinical indicators","lastPublishedDoi":"10.21203/rs.3.rs-3806951/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3806951/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEndometriosis is an inflammation-associated disease, primarily but not always associated with abnormal immune system function and expression of immune factors. The microbiota of the female reproductive tract, including the vagina and cervix, plays a crucial role in health and disease. The immune dysregulation caused by the imbalance of reproductive tract microbiota may contribute to endometriosis. In this study, 35 women was recruited, including 17 women with endometriosis and 18 healthy women, while their general clinical data, cervical secretions and vaginal secretions were collected. High-throughput sequencing technology was performed to analyze the cervical and vaginal microbiota. We found that patients with endometriosis have unique vaginal and cervical microbiota. \u003cem\u003eRomboutsia\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003ePhascolarctobacterium\u003c/em\u003e, and \u003cem\u003eOlsenella\u003c/em\u003e in the reproductive tract had significant positive correlation with the visual analogue scale index for endometriosis, while \u003cem\u003eMobiluncus\u003c/em\u003e displayed a significant negative correlation with the visual analogue scale index, and \u003cem\u003eLactobacillus\u003c/em\u003e showed a significant negative correlation with the thyroid peroxidase antibody index. These clinical and microbiological indicators might be associated with endometriosis, and this study has clinical significance for the detection and prevention of endometriosis.\u003c/p\u003e","manuscriptTitle":"Clinical indicators and reproductive tract microbiota abnormalities indicate the occurrence of endometriosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 14:56:54","doi":"10.21203/rs.3.rs-3806951/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"edc4cb2b-f298-4db5-868f-019decdcb2da","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-07-18T09:44:27+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-03 14:56:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3806951","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3806951","identity":"rs-3806951","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}