{"paper_id":"0efa4a85-e976-45b1-9257-849b2bd623c5","body_text":"Vaginal microbiome differences between patients with adenomyosis with different menstrual cycles and healthy controls | 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 Vaginal microbiome differences between patients with adenomyosis with different menstrual cycles and healthy controls Zangyu Pan, Jun Dai, Ming Yuan, Guoyun Wang, Ping Zhang, Qianhui Ren, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3317589/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Jul, 2024 Read the published version in BMC Microbiology → Version 1 posted 4 You are reading this latest preprint version Abstract Background Adenomyosis is a commonly observed benign gynecological disease that affects the quality of life and social psychology of women of childbearing age. However, because of the unknown etiology and incidence of adenomyosis, its pathophysiological mechanism remains unclear; further, because no noninvasive, accurate, and individualized diagnostic methods are available, treatment and efficacy evaluations are limited. Notably, the interaction between the changes in the microecological environment of the female reproductive tract and human immunity, endocrine, and other links leads to the occurrence and development of diseases. In addition, the vaginal microbiome differs in different menstrual cycles; therefore, assessing the differences between the microbiomes of patients with adenomyosis and healthy individuals in different menstrual cycles will improve the understanding of the disease and provide references for the search for noninvasive diagnosis and individualized precision treatment of adenomyosis. This study aimed to explored the data of individuals in different menstrual cycles. Results Differences in the vaginal microbiome between patients with adenomyosis and healthy individuals were observed. At the phylum level, the relative abundance of Firmicutes species in the adenomyosis group was higher when compared with the control group. At the genus level, the relative abundance of Lactobacillus in the adenomyosis and control groups was the highest, which contributed the most to the species difference between the two groups. Alpha-diversity analysis showed significant differences in the adenomyosis and control group during luteal phase (Shannon index p = 0.0087, Simpson index, p = 0.0056). Beta-diversity analysis showed lower microbial richness in the adenomyosis group than that in the control group by weighted unifrac distance ( p = 0.0018). In the same disease group, differences between different menstrual cycles were also observed. Finally, 50 possible biomarkers including were screened and predicted based on the PICRUSt. Conclusions The vaginal microbiome differs between patients with adenomyosis and healthy individuals during difference menstrual periods especially during the luteal phase. These findings facilitate the search for specific biological markers within a limited range and provide a more accurate, objective, and individualized diagnostic and therapeutic evaluation method for patients with adenomyosis than is currently available. Adenomyosis Vaginal microbiome Menstrual cycles Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Background Adenomyosis is a benign uterine myometrial lesion commonly found in women of reproductive age and is characterized by compensatory hypertrophy in the peripheral myometrium, with endometrioid glands and stroma found in the myometrium [ 1 ] . Pathological diagnosis after surgery is the gold standard for clinical diagnosis; however, the exact incidence and pathogenesis of adenomyosis remain unknown [ 2 ] . Studies have shown that a history of uterine surgery is a high risk factor for adenomyosis. For example, the incidence of adenomyosis in patients with the aforementioned surgical history is 1.5 times higher than in patients with a different history [ 3 , 4 ] . In the treatment of adenomyopathy, in addition to surgical treatment, conservative programs are used to regulate endocrine and immune system functions. Diagnostic methods include MRI, transvaginal ultrasonography, and CA125, but no specific, individualized diagnostic method is available. Adenomyosis and other benign gynecological diseases, such as uterine fibroids, endometriosis, and endometrial polyps, have a high comorbidity rate, and attributing specific symptoms to adenomyosis in clinical diagnosis and treatment is difficult. The vagina is an important organ of the female lower genital tract and is an important habitat for microorganisms in the human body. Lactobacillus is the predominant bacterial species and is affected by various exogenous and endogenous factors and the species composition of the vaginal microbiome has a strong dynamic change [ 5 ] . The vaginal microbiome is an important defense mechanism that regulates and maintains reproductive function and relative homeostasis in healthy environments. The stability of the microbiome can prevent the proliferation of symbiotic microorganisms and the colonization of pathogens [ 6 ] . Microorganisms affect the balance of the microenvironment through nutritional competition, intraspecific and interspecific signal transduction, metabolic pathways, and product interactions. The mechanism of microenvironmental imbalance remains unclear; however, this imbalance can disrupt normal homeostasis, resulting in certain pathological signs. The female upper reproductive tract was once considered a sterile environment; however, this theory has been challenged. The presence of microbiota in the endometrial microbiota [ 7 ] was confirmed by the isolation of microbiota from female endometrial aspirated fluid samples. Studies have shown that bacterial DNA can be detected in 95% of post-hysterectomy samples [ 8 ] . Microbial switching occurs in the female reproductive tract, and the flora of the upper and lower reproductive tracts work synergistically to regulate the uterine environment. With increasing age, synchronous changes in the microbiome of the uterus and vagina increasingly converge, showing a mutually parallel relationship. Animal studies have verified the damaging and protective effects of vaginal bacteria on the endometrium using microflora transplantation techniques [ 9 ] . This also indicates that lower reproductive tract bacteria affect or directly interfere with the regulation of some benign and malignant diseases, to some extent, through certain mechanisms. Initial research on vaginal microbes mainly relied on microscopy and microbial culture techniques; however, the vast majority of microorganisms in the physiological or natural environment are difficult to obtain through culture. Using bioinformatics, we used high-throughput sequencing and analysis technology to minimize the dependence on bacterial culture technology used in the literature to enhance the understanding of the structure and function of the microbial community so that the benign and malignant diseases of the female reproductive system and the bacterial community this \"non-visual organ\" the interaction between more clearly. 16S-rRNA is a subunit of ribosomal RNA. With improvements in sequencing technology, 16S-rDNA amplicon sequencing has become an important means to evaluate the colony microenvironment, flora structure, and composition [ 10 – 13 ] . As research progresses, sequencing platforms are updated and iterated. Relying on the upgraded Illumina NovaSeq sequencing platform, we compensated for the inefficiency of single-ended reading and splicing of gene sequences and realized double-ended sequencing; that is, we built small fragment libraries according to the characteristics of the amplified regions. According to our review of the literature, no study has investigated the differences in the vaginal microbiome between patients with different menstrual cycles and healthy individuals. Therefore, based on the analysis of disease and healthy controls, this study further explored the data of sick and healthy individuals in different menstrual cycles. Our results provide a reference for the subsequent screening of characteristic biological markers, disease diagnosis, noninvasive precision treatment, and efficacy prediction based on microbial detection. Materials and methods The case group in this study comprised patients with adenomyosis in the gynecological outpatient department of Affiliated Hospital of Shandong University from November 2021 to October 2022 were selected as the case group. They were evaluated by professional gynecologists, and adenomyosis was confirmed by ultrasound or magnetic resonance imaging (MRI). The control group comprised healthy individuals. The inclusion criteria were as follows: (1) 18–49 years old ; (2) no unhealthy lifestyle; (3) Regular menstrual cycle; (4) non-pregnant, non-puerperal, non-lactation, non-menstrual period; (6) pre-menopause. The exclusion criteria were as follows: (1) no medical history could be provided; (2) cervical intraepithelial lesions, cervical malignancies, vulva lesions and other HPV-related diseases; (3) virus or bacterial infection; (4) history and treatment of endocrine system diseases; (5) autoimmune diseases; (6) acute/chronic inflammation of the urogenital tract; (7) Sexually transmitted diseases and infectious diseases; (8) malignant tumors; (9) History of sexual life, vaginal bleeding, vaginal douching, vaginal medication, sitting bath, pelvic bath, transvaginal examination 48 hours before sampling; (10) History of use of antibiotics, antifungals, and hormonal drugs within 30 days before sampling; (11) Intrauterine device implantation; (12) Recent history of pelvic and abdominal surgery and intrauterine operation. Sample collection The individuals who fulfilled the inclusion criteria had a clinical sample collected on the day of the clinical visit before they received a transvaginal gynecologic examination or gynecologic ultrasound. The posterior vaginal fornix was fully sampled using disposable sterile swabs. During the procedure, contact between the swab head and the speculum, vaginal wall, and other non-sampling sites was avoided. The swab head was cut off with sterile scissors and placed in a sterile centrifuge tube containing Amies culture medium(JINAN BABIO BIOTECHNOLOGY CO,.LTD. ), and stored at -80 ℃ in the laboratory. DNA extraction The genomic DNA of the sample is extracted by CTAB method.Appropriate amount of DNA was collected in a centrifuge tube, the purity and concentration of DNA was detected by agarose gel electrophoresis, and the sample was diluted to 1ng/µL with sterile water. Using the diluted genomic DNA as a template, the V3-V4 region of 16S-rDNA gene was amplified. The primer sequence was as follows: ①F:CCTAYGGGRBGCASCAG; ②R:GGACTACNNGGGTATCTAAT (Phusion® High-Fidelity PCR Master Mix with GC Buffer, New England Biolabs,lnc.). PCR was performed using specific primers with Barcode and high-efficiency high-fidelity enzyme according to the selection of sequencing region to ensure amplification efficiency and accuracy .The amplification was conducted for 30s at 98 ° C to denature the DNA,followed by 25 three-step temperature cycles of 98 ̊C for 10s, 53 ̊C for 25s, For 10s, 53 ̊C for 25s, and 72 ̊C for 10min.For the final step,the elongation process was performed for 10min at 72 ̊C before obtaining 290bp amplicons.PCR products were detected by electrophoresis using 2% concentration agarose gel,qualified PCR products were purified by magnetic beads;Enzyme quantification;Recovered products (Glue recovery kit provided by qiagen). Library construction and sequencing The library was constructed using TruSeq® DNA PCR-Free Sample Preparation Kit. The constructed library was quantified by Qubit and Q-PCR. After the library was qualified, the computer sequencing was performed using NovaSeq 6000. According to Barcode sequence and PCR amplification primer sequence, each sample data was separated from the disembarkation data. After the amputation of Barcode and primer sequences using FLASH (V1.2.7, http://ccb.jhu.edu/software/FLASH/ ) to splice reads of each sample, the splicing sequence for Raw Tags; Then fastp software is used to strictly filter the obtained Raw Tags to obtain high-quality Clean Tags data. After dealing with the above Tags to get treatment to remove the chimeric sequences, Tags sequence through ( https://github.com/torognes/vsearch/ ) annotation database for matching detection chimeric sequences and species, and eventually chimera is taken out of sequence, get the final Effective Tags. Results The study enrolled 43 patients with adenomyosis and 40 healthy people. There were no significant differences in demographic background between the two groups of participants. (Table 1) Table 1 Demographic data of the subjects Adenomyosis （N=40） Control （N=40） P -value Age,years(mean±SD) 39.81±5.62 38.38±5.51 0.243 BMI,kg/m 2 ,( mean±SD) 23.73±2.81 22.32±3.88 0.060 Gestation 2.19±1.20 1.77±1.07 0.055 Production 1.07±0.67 1.00±0.56 0.687 Menstrual cycle，days 26.88±3.67 27.97±2.15 0.066 Menstrual period，days 5.81±1.33 5.47±1.32 0.153 The vaginal samples were collected from all participants; however, 7 samples in total were excluded from the control group due to poor DNA quality after library quality check. Therefore, 83 samples were used in the subsequent analysis. (Fig 1) Next, the vaginal microbiota was analyzed using 16s rDNA sequencing techniques. The Raw PE data sequenced by Illumina Novaseq were splicing and quality control to obtain Clean Tags, and then chimeric filtering was performed to obtain Effective Tags for subsequent analysis. (S1 Table) Species relative abundances At phylum level, the relative abundance of Firmicutes in adenomyosis group was higher than that in control group (80.70% and 69.72% in adenomyosis and control groups). At the Genus level, the Lactobacillus relative abundance in both adenomyosis group and control group was the highest (72.10% and 66.08%). But the relative abundance of Gardnerella and Atopobium in the adenomyosis group was lower than that in the control group (9.67% and 1.04% in adenomyosis and 14.95% and 4.69% in control groups); At the Species level, the Lactobacillus_iners abundance in the adenomyosis group was higher than that in the control group(43.74% and 32.14%), and showed a diversity of Lactobacillus, including Lactobacillus_delbrueckii and Lactobacillus_jensenii.(Fig 2). Different menstrual cycles The top 35 species with the average abundance of all samples of the same level and different groups are selected for clustering, and the heatmap is drawn by pheatmap package of R software, which is convenient to find the number or content of species in the sample. (Fig 3) Sample complexity analysis In order to study the influence of menstrual cycle on vaginal microecology, we named all the samples in the luteal phase of the adenomyosis group as group C and the follicular phase as group D. All the samples in the luteal phase of the control group were named group E and group F. in the follicular phase. Alpha-diversity analysis showed significant differences in the adenomyosis and control group during luteal phase (Shannon index, p =0.0087; Simpson index, p =0.0056), but we didn’t find the statistically difference in ACE and chao 1 index (Fig 4).It was verified that the amount of sequencing data was progressive and reasonable, and more data would only produce a few new species, thus suggesting a uniform distribution of species. (Fig 5) Comparative analysis of multiple copies The species distributions in the adenomyosis group and the control group were not completely separated, but were similar. (Fig 6) We analyzed the Beta-diversity index by using the t-test and found that the species Beta-diversity index was significantly different between the adenomyosis group and the control group (Fig 7 A, B). However, based on Weighted unifrac analysis, significant differences between the disease group and the control group were only observed throughout the luteal phase( P=0.0146 ) .(Fig 7 C, D) R value was between (-1, 1), and R value was greater than 0, indicating that the difference between groups was greater than the difference within groups, which was significant ( P < 0.05). The reasonableness of the grouping in this study was proved. (Table 2) Table 2 Anosim analysis based on the Bray-Curtis distance. Anosim analysis is a non-parametric test used to test whether the difference between groups is significantly greater than the difference within groups, so as to determine whether the grouping is meaningful. We conducted the significance test of the difference between groups based on the rank of the Bray-Curtis distance value. Group R value P value B-A 0.03067 0.044 At the phylum level, there were no significant species differences between the adenomyosis group and the control group.At the class level the significant differences was in Coriobacteriia and Gammaproteobacteria (P < 0.01). At the class level the significant differences was in Lactobacillales, Coriobacteriales(P < 0.01),and in Pseudomonadales ( p < 0.05). At the class level the significant differences was in Beijerinckiaceae and Listeriaceae ( p < 0.05).At the genus level, that were in Listeria, Ralstonia, Acinetobacter, and Haemophilus ( p < 0.01), and Alloscardovia,Ureaolasma ( p < 0.05).Finally, at the species level ,there was significant difference in Alloscardovia_omnicolens and Lactobacillus_delbrueckii ( p < 0.01).( Fig 8) At the Phylum level, Firmicutes showed the highest species abundance in both the adenomyosis group and the control group, and at the same time, contributed the most to the species difference between the two groups. (Fig 9) Random forest is a classical machine learning model based on classification tree algorithm to screen features (biomarkers) that play an important role in classification or grouping. A default 10-fold cross-validation was performed for each model, and ROC curves were drawn to select potential Biomaker 50 as shown in Fig 10. Discussion This study elucidated the differences in vaginal microbiota characteristics between women with and without adenomyosis with different menstrual cycles. We used the alpha diversity index (e.g., the Shannon index, chao1 index, ACE, and Simpson indices) to analyze the species within the group and calculated the number of microbial species in a single sample and the proportion of each species. The aforementioned analysis indexes of the two groups of samples did not show significant differences, similar to the results of Chen et al. [ 14 ] . The cumulative histogram of the relative abundance of species showed that although the species were similar, abundance significantly differed. At the phylum level, the relative abundance of Firmicutes was higher in the adenomyosis group than in the control group. At the genus level, except for the absolute species dominance of Lactobacillus in both groups, the relative abundance of Gardnerella in the adenomyosis group was significantly lower than that in the control group, which differed from the results of Kunaseth J [ 15 ] . Lactobacillus vegetation in the female reproductive tract is critical for the maintenance of genital health. However, the exact pathogenesis of Gardnerella vaginalis remains unclear [ 16 ] . Lactobacillus and Gardnerella interact in the female reproductive tract; when the amount of Lactobacillus decreases to a certain extent, the growth of Gardnerella can decrease or stop [ 17 ] , and the imbalance of the two bacteria can change the acid-base environment of the vagina and produce mucosal adsorption and biofilm, promoting chronic, persistent infection and inflammation [ 18 , 19 ] . A data analysis using the dominance network analysis framework found that in these \"non-Lactobacillus dominant vaginal flora,” Gardnerella was jointly inhibited by 23 bacteria genera [ 20 ] . Lactobacilli that cooperate with Gardnerella and are inhibited by other species are Lactobacillus-iners [ 21 ] . In this study, we found that the abundance of Lactobacillus inert in the adenomyosis group was significantly higher than that in the control group at the species level, and this significance was verified using the MetaStat method. In conclusion, the variation in Lactobacillus inerta and Gardnerella abundance may be a potential cause of adenomyosis, and maintaining the balance of Lactobacillus normalis and Gardnerella in the body may be a self-mechanism to maintain the stability of vaginal microecology. However, little is known about how the genital microbiota affects host immune function and regulates disease susceptibility. Lactobacillus imbalance and high ecological diversity may be closely related to the concentration of pro-inflammatory cytokines in genital organs [ 22 ] . Patients with adenomyosis show leukocyte infiltration in the endometrial functional layer, and the number of macrophages and natural killer (NK) cells increased [ 23 , 24 ] . Other groups of vaginal bacilli were also detected in this study, second only to Lactobacillus in overall abundance. Transcriptional analysis showed that antigen-presenting cells sense gram-negative bacterial products in situ via Toll-like receptor 4 (TLR-4) signaling, promoting genital organ inflammation by activating the NF-κB signaling pathway and recruiting lymphocytes through chemokine production [ 22 ] . Immune dysregulation is present in the ectopic endometrium of patients with adenomyopathy and manifests as elevated Tim-3/Gal-9 expression and differential RNA methylation [ 25 , 26 ] . Therefore, we speculated that vaginal microecological changes affect the important role of Tim-3/Gal-9 in immunosuppression through some mechanism, causing the persistence of infection, affecting the growth environment of the endometrial tissue, and causing adenomyosis. In addition, the expression of Type I interferon (IFN-I) inducers is increased in the ectopic endometrium in adenomyosis. The increased levels of IFN-Is and expression of interferon-stimulating genes and pro-inflammatory cytokines in tissues may be related to host immunity under the influence of certain microorganisms [ 27 ] . Recent literature has suggested that microbiota-induced interferon activation does not require direct host-bacterial interaction but the remote transport of bacterial DNA into host cells via bacteria-derived membrane vesicles [ 28 ] . In contrast with our finding that the beta diversity index was significantly higher in the adenomyosis group than in the control group, the increased bacterial diversity in the vagina probably explains the activation of the host’s innate immune response in the ectopic endometrium in adenomyosis [ 15 , 29 ] . The microbiota of the female reproductive system is influenced by changes in age and system physiology, and the menstrual cycle is a major disruptor of the vaginal microbiome. Different microbiota characteristics are observed in women at different physiological stages [ 30 ] . In healthy women of reproductive age, the vaginal microbiome composition changes dramatically before and after menstruation [ 31 ] . Menstrual blood flowing through the vagina leaves sufficient iron for pathogens, and the iron necessary for pathogen metabolism [ 32 ] , which is reduced by the iron-binding affinity of lactoferrin, is replenished. Additionally, studies measuring estradiol levels and vaginal microbiome composition in women who use oral contraceptives to inhibit ovulation have shown that the high diversity observed during menstruation is mainly driven by estradiol withdrawal before menstruation rather than by the dynamic drive of progesterone. Lactobacillus abundance increases during the follicular and luteal phases, gradually normalizing the vaginal microecology [ 31 , 33 ] . Under the influence of this periodicity, combined with our test results, we found different types of dominant bacterial profiles in patients with adenomyosis in both the both luteal and follicular stages, which provided a reference for the detection of biomarkers in patients with specific menstrual cycles or to evaluate their efficacy. In summary, in this study, an increase in microbial richness was associated with adenomyosis, and the microbiome characteristics of patients with and without adenomyosis differed according to the menstrual cycle. This study has three notable limitations: the final sample size was limited because of coronavirus disease 2019 (COVID-19), no large sample of data clinical for verification was available, and the different methods used in each study may have led to different conclusions. In further research, we plan to develop standardized analysis software and large databases to continue our investigation of the mechanisms behind this association. Abbreviations Magnetic resonance imaging (MRI); natural killer (NK) cells; Toll-like receptor 4 (TLR-4); Type I interferon (IFN-I); coronavirus disease 2019 (COVID-19). Declarations The research has been performed in accordance with the Declaration of Helsinki. The patients were informed about the sample collection and had signed informed consent forms. Ethics approval and consent to participate This study was reviewed and approved by the Medical Ethics Committee of the hospital (ethics approval No. : KYLL-20211-092-1). The research has been performed in accordance with the Declaration of Helsinki. The patients were informed about the sample collection and had signed informed consent forms. Consent for publication Not applicable. Availability of data and materials The authors confirm that the data supporting the findings of this study are available within the article or supplementary materials. Competing interests The authors declare no competing interests. Funding This study was supported by the National Key R&D Program of China [2022YFC2704000], the Major Basic Research of Natural Science Foundation of Shandong [ZR2021ZD34], and the National Natural Science Foundation of China [grant numbers 82071621 and 81901458]. Authors' contributions All authors read and approved the final manuscript. Guoyun Wang and Ming Yuan designed the experiments. Zangyu Pan conceived and carried out sample collection, analysis, and interpretation. Jun Dai, Ping Zhang, Qianhui Ren, Xinyu Wang, Hao Sun, Shumin Yan and Xue Jiao carried out sample collection. Zangyu Pan drafted the manuscript and prepared the figures and tables. All authors finalized the final manuscript. Acknowledgements We would like to thank all of the volunteers who participated in this study. We would like to thank Editage (www.editage.cn) for English language editing. We would like to thank Novogene Biotech Co., Ltd for data administration. References Yen CF, Huang SJ, Lee CL, et al. Molecular characteristics of the endometrium in uterine adenomyosis and its biochemical microenvironment[J]. Reprod Sci, 2017, 24(10): 1346-1361. Cunningham RK, Horrow MM, Smith RJ, et al. Adenomyosis: A Sonographic Diagnosis. [J]. Radiographics, 2018, 38(5):1576-1589. Parazzini F, Vercellini P, Panazza S,et al. Risk factors for adenomyosis[J]. Hum Reprod, 1997, 12(6): 1275-1279. Riggs JC, Lim EK, Liang D, et al. Cesarean section as a risk factor for the development of adenomyosis uteri[J]. J Reprod Med, 2014, 59(1-2):20-24. Abou Chacra L, Fenollar F, Diop K. Bacterial Vaginosis: What Do We Currently Know? [J]. Front Cell Infect Microbiol, 2022, 11:672429. Deidda F, Amoruso A, Allesina S, et al. In Vitro Activity of Lactobacillus fermentum LF5 Against Different Candida Species and Gardnerella vaginalis: A New Perspective to Approach Mixed Vaginal Infections? [J]. J Clin Gastroenterol, 2016 Nov/Dec; 50 Suppl 2, Proceedings from the 8th Probiotics, Prebiotics & New Foods for Microbiota and Human Health meeting held in Rome, Italy on September 13-15, 2015: S168-S170. Moreno I, Codoñer FM, Vilella F, et al. Evidence that the endometrial microbiota has an effect on implantation success or failure[J]. Am J Obstet Gynecol, 2016, 215(6): 684-703. Mitchell C.M, Haick A, Nkwopara E, et al. Colonization of the Upper Genital Tract by Vaginal Bacterial Species in Nonpregnant Women[J]. Am. J. Obstet, Gynecol, 2015, 212, 611. e1–611. e9. Wang J, Li Z, Ma X, et al. Translocation of vaginal microbiota is involved in impairment and protection of uterine health[J]. Nat Commun, 2021, 12(1): 4191. Youssef N, Sheik CS, Krumholz LR, et al. Comparison of species richness estimates obtained using nearly complete fragments and simulated pyrosequencing-generated fragments in 16S rRNA gene-based environmental surveys[J]. Appl Environ Microbiol, 2009, 75(16) : 5227- 5236. Hess M, Sczyrba A, Egan R, et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen[J]. Science, 2011, 331(6016) : 463- 467. Lundberg DS, Yourstone S, Mieczkowski P, et al. Practical innovations for high-throughput amplicon sequencing[J]. Nat Methods, 2013, 10(10) : 999- 1002. Hickey RJ, Zhou X, Settles ML, et al. Vaginal microbiota of adolescent girls prior to the onset of menarche resemble those of reproductive-age women[J]. mBio, 2015, 6(2) : e00097- 15. Chen S, Gu Z, Zhang W, et al. Microbiome of the lower genital tract in Chinese women with endometriosis by 16s-rRNA sequencing technique: a pilot study[J]. Ann Transl Med, 2020, 8(21):1440. Kunaseth J, Waiyaput W, Chanchaem P, et al. Vaginal microbiome of women with adenomyosis: A case-control study[J]. PLoS One, 2022, 17(2): e0263283. Djukic M, Schmidt-Samoa C, Lange P, et al. Cerebrospinal fluid findings in adults with acute Lyme neuroborreliosis[J]. J Neurol, 2012, 259(4):630-636. Haedicke J, Iftner T. Human papillomaviruses and cancer[J]. Radiother Oncol, 2013, 108(3):397-402. Machado D, Castro J, Palmeira-de-Oliveira A, et al. Bacterial Vaginosis Biofilms: Challenges to Current Therapies and Emerging Solutions[J]. Front Microbiol, 2016, 6: 1528. Garcia EM, Kraskauskiene V, Koblinski JE,et al. Interaction of Gardnerella vaginalis and Vaginolysin with the Apical versus Basolateral Face of a Three-Dimensional Model of Vaginal Epithelium. Infect Immun. 2019 Mar 25;87(4):e00646-18. Doyle R, Gondwe A, Fan YM,et al. A Lactobacillus-Deficient Vaginal Microbiota Dominates Postpartum Women in Rural Malawi[J]. Appl Environ Microbiol, 2018 , 84(6) : e02150- 17. Li W, Ma ZS. Dominance network analysis of the healthy human vaginal microbiome not dominated by Lactobacillus species[J]. Comput Struct Biotechnol J. 2020, 18: 3447-3456. Anahtar MN, Byrne EH, Doherty KE,et al. Cervicovaginal bacteria are a major modulator of host inflammatory responses in the female genital tract[J]. Immunity, 2015, 42(5) : 965-976. Orazov MR, Radzinsky VE, Nosenko EN, et al. Immune-inflammatory predictors of the pelvic pain syndrome associated with adenomyosis[J]. Gynecol Endocrinol, 2017, 33(sup1) : 44- 46. Tremellen KP, Russell P. The distribution of immune cells and macrophages in the endometrium of women with recurrent reproductive failure. II: adenomyosis and macrophages[J]. J Reprod Immunol, 2012, 93(1) : 58- 63. Huang P, Lv C, Zhang C, et al. Expression and significance of T-cell immunoglobulin mucin molecule 3 and its ligand galectin-9 in patients with adenomyosis[J]. Gynecol Endocrinol, 2020, 36(7) : 605- 610. Zhai J, Li S, Sen S, et al. m6A RNA Methylation Regulators Contribute to Eutopic Endometrium and Myometrium Dysfunction in Adenomyosis[J]. Front Genet, 2020, 11: 716. Qu H, Li L, Wang TL, et al. Epithelial Cells in Endometriosis and Adenomyosis Upregulate STING Expression[J]. Reprod Sci, 2020, 27(6) : 1276- 1284. Erttmann SF, Swacha P, Aung KM, et al. The gut microbiota prime systemic antiviral immunity via the cGAS-STING-IFN-I axis[J]. Immunity, 2022, 55(5) : 847- 861. e10. Abou Chacra L, Fenollar F, Diop K. Bacterial Vaginosis: What Do We Currently Know? [J]. Front Cell Infect Microbiol, 2022, 11:672429. Galkin F, Mamoshina P, Aliper A, et al. Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning[J]. iScience, 2020, 23(6) : 101199. Krog MC, Hugerth LW, Fransson E, et al. The healthy female microbiome across body sites: effect of hormonal contraceptives and the menstrual cycle[J]. Hum Reprod, 2022, 37(7) : 1525- 1543. Roberts SA, Brabin L, Diallo S, et al. Mucosal lactoferrin response to genital tract infections is associated with iron and nutritional biomarkers in young Burkinabé women[J]. Eur J Clin Nutr, 2019, 73(11): 1464-1472. Song SD, Acharya KD, Zhu JE,et al. Daily vaginal microbiota fluctuations associated with natural hormonal cycle, contraceptives, diet, and exercise[J]. MSphere, 2020, 5: 1– 14. 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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-3317589\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":230988766,\"identity\":\"30db0dec-ec61-4f52-aa90-d82ee52859a5\",\"order_by\":0,\"name\":\"Zangyu Pan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Zangyu\",\"middleName\":\"\",\"lastName\":\"Pan\",\"suffix\":\"\"},{\"id\":230988767,\"identity\":\"606038e4-2556-4efd-9cf5-0524b3a08cfb\",\"order_by\":1,\"name\":\"Jun Dai\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Qilu hospital of Shandong university\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jun\",\"middleName\":\"\",\"lastName\":\"Dai\",\"suffix\":\"\"},{\"id\":230988770,\"identity\":\"f717999a-06c6-41c2-9645-4c355e9c9227\",\"order_by\":2,\"name\":\"Ming Yuan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ming\",\"middleName\":\"\",\"lastName\":\"Yuan\",\"suffix\":\"\"},{\"id\":230988771,\"identity\":\"545211ee-f4f2-4ebd-8c12-1d283bb041a4\",\"order_by\":3,\"name\":\"Guoyun Wang\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYDADfgYGAyDFTIIWyQaStRgcIFaLwfGzh19+bbNJ3Hz+8DYJhgrrxAb2swfwazmTl2Yt25aWuO1GWpkEw5n0xAaevAS8WswO5JgZS7YdBmrhMZNgBDIaJHgM8Gs5/waiZXP/GaCWf8RouZFj/PAjUMsGhhyglgYitNjfeGPGzHAuzXjGjbRii4Rj6cZtPDn4tUj25xh//FFmI9vff3jjjQ811rL97GfwawECNmkeBgbHBhAzAcQlpB4ImD/+ADqQCIWjYBSMglEwUgEAWcVIm6JfeYYAAAAASUVORK5CYII=\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Guoyun\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":230988773,\"identity\":\"d4f34b04-6c2b-4dd8-9af4-4284cd55f7bc\",\"order_by\":4,\"name\":\"Ping Zhang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ping\",\"middleName\":\"\",\"lastName\":\"Zhang\",\"suffix\":\"\"},{\"id\":230988775,\"identity\":\"c23e5e0e-eea7-49e3-8ecf-c22906b7a714\",\"order_by\":5,\"name\":\"Qianhui Ren\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Qianhui\",\"middleName\":\"\",\"lastName\":\"Ren\",\"suffix\":\"\"},{\"id\":230988776,\"identity\":\"20578cfe-14f6-482f-8177-5acc41c2d670\",\"order_by\":6,\"name\":\"Xinyu Wang\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xinyu\",\"middleName\":\"\",\"lastName\":\"Wang\",\"suffix\":\"\"},{\"id\":230988777,\"identity\":\"990d70c1-e61f-4f49-b7a5-0bd6a2d774c2\",\"order_by\":7,\"name\":\"Shumin Yan\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Shumin\",\"middleName\":\"\",\"lastName\":\"Yan\",\"suffix\":\"\"},{\"id\":230988778,\"identity\":\"8436acab-f8d0-416c-a351-01321fd1286f\",\"order_by\":8,\"name\":\"Sun Hao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sun\",\"middleName\":\"\",\"lastName\":\"Hao\",\"suffix\":\"\"},{\"id\":230988779,\"identity\":\"ae68b6f5-c5c9-4172-87c2-a54c3b70043c\",\"order_by\":9,\"name\":\"Xue Jiao\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Shandong Provincial Hospital\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Xue\",\"middleName\":\"\",\"lastName\":\"Jiao\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2023-09-01 14:59:24\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-3317589/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-3317589/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12866-024-03339-9\",\"type\":\"published\",\"date\":\"2024-07-27T16:16:03+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":42851983,\"identity\":\"2984fd34-d049-4d46-8d07-1aa7a665bcad\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:48:33\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":38344,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eStudy process\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/7296da8e0d0be701d6a436ee.png\"},{\"id\":42851984,\"identity\":\"becdc1a2-81e9-4d81-b6c3-7ff2b3b15de4\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:48:33\",\"extension\":\"jpg\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":200417,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eTaxonomy bar charts of vaginal microbiame at (A) phylum, (B)class, (C)order, (D)family, (D)genus and (E)species level.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/ec92618f78bc7416ab4b759a.jpg\"},{\"id\":42852625,\"identity\":\"d2d85e21-9de9-43ec-a400-74f434ff5d9a\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:56:34\",\"extension\":\"jpg\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":231551,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eHeatmap of species abundance clustering during different menstrual cycles. The top 35 species with the average abundance of all samples of the same level and different groups are selected for clustering at (A) phylum, (B)class, (C)order, (D)family, (D)genus and (E)species level.The heatmap is drawn by pheatmap package of R software, which is convenient to find the number or content of species in the sample.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/d9ca518850eeedfc56671524.jpg\"},{\"id\":42853138,\"identity\":\"e024e8f8-82a1-4791-b7c9-51bbb2774b24\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 19:04:33\",\"extension\":\"jpg\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":141296,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eAlpha-diversity analysis.(A) shannon index, (B)Simpson index , (C) ACE index, (D)chao1 index. Alpha-diversity analysis indices for different samples at 97% consistency thresholds.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/6f5b2584ad38ff52643afe7e.jpg\"},{\"id\":42852621,\"identity\":\"5a09375a-72e2-41db-a446-d0d11955acad\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:56:33\",\"extension\":\"jpg\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":81541,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eRarefaction curve and Rank Abundance curve. In the (A) Rarefaction curve, horizontal coordinate is the number of sequencing strips randomly selected from a sample, and the vertical coordinate is the number of OTUs that can be constructed based on the number of sequencing strips, which is used to reflect the sequencing coverage, and different samples are represented by different colored curves; in the (B) Rank Abundance curve, the horizontal coordinate is the serial number sorted by the abundance of OTUs, and the vertical coordinate is the relative abundance of the corresponding OTUs, and different samples are represented by different colored fold lines.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/802423d75932724e2715779d.jpg\"},{\"id\":42851987,\"identity\":\"c537a7d9-dc4a-43fc-9c8d-8c5a1886e955\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:48:33\",\"extension\":\"jpg\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":174788,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e(A)Weighted Unifrac based distance from PCoA analysis. Horizontal coordinates indicate one principal component, vertical coordinates indicate another principal component, and percentages indicate the contribution of the principal component to the sample variance; each point in the graph indicates a sample, and samples from the same group are indicated using the same color (B) Unweighted Unifrac based distance from PCoA analysis. (C) Euclidean based distances from PCA analysis. The horizontal coordinate indicates the first principal component, and the percentage indicates the contribution value of the first principal component to the sample difference; the vertical coordinate indicates the second principal component, and the percentage indicates the contribution value of the second principal component to the sample difference; each point in the graph indicates a sample, and samples in the same group are indicated using the same color; in PCA graphs with clustering circles, the clustering circle is added with the grouping information (clustering circles need more than 3 samples in the group).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage6.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/9499237f43af34c40d471113.jpg\"},{\"id\":42852624,\"identity\":\"d4e7b520-ed38-494e-b4fb-a50f99b662b9\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:56:34\",\"extension\":\"jpg\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":101678,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e(A)Weighted Unifrac based distance from Beta-diversity analysis. (B) Unweighted Unifrac based distance from Beta-diversity analysis. The box plots of Beta-diversity between-group difference analysis can visualize the median, dispersion, maximum, minimum, and outliers of within-group sample similarity. At the same time, the T-test test was used to analyze whether the Beta diversity differences of species between groups were significant or not. (C) Weighted unifrac ased distance from Beta-diversity analysis during different menstrual cycles. (D) Unweighted unifrac ased distance from Beta-diversity analysis during different menstrual cycles.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage7.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/4f356e6991dc6f210e70e824.jpg\"},{\"id\":42852623,\"identity\":\"dce3e0aa-4628-481e-be2b-9ba8705a8724\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:56:33\",\"extension\":\"jpg\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":196970,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eMetaStat analysis at (A) phylum, (B)class, (C)order, (D)family, (D)genus and (E)species level. For the species with significant differences between study groups, MetaStat method was used to screen the species with significant differences based on the species abundance tables of different levels.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage8.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/f31832743d2fa2302fb67b56.jpg\"},{\"id\":42851994,\"identity\":\"275382a8-413e-4003-aa3b-b882f33b2b16\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:48:34\",\"extension\":\"jpg\",\"order_by\":9,\"title\":\"Figure 9\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":193710,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eSimper analysis. It is a breakdown of the Bray-Curtis difference index that quantifies how much each species contributes to the difference between two groups. The results show the top 10 species with the highest contribution to the difference between the two groups and their abundance.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage9.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/cc43acb0750b2c2e26405c7a.jpg\"},{\"id\":42851993,\"identity\":\"63acdab0-3343-4314-ae4e-e3c236139609\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:48:34\",\"extension\":\"jpg\",\"order_by\":10,\"title\":\"Figure 10\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":370619,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e(A) MeanDecreaseAccuracy based analysis and MeanDecreaseGin based analysis.(B) proportion of false positive (Specificity), ordinate: proportion of true Sensitivity; (C) ROC curve of the test pair, abscess: proportion of false positive (Specificity), ordinate: proportion of true Sensitivity (specificity). MeanDecreaseAccuracy measures the extent to which the prediction accuracy of random forest is reduced when the value of a variable is changed to a random number. The greater the value, the greater the importance of the variable. MeanDecreaseGini compared the importance of the variables by calculating the effect of each variable on the heterogeneity of the observed values at each node of the classification tree using the Gini index.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage10.jpg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/231724aa7b9048c6b24ac4a1.jpg\"},{\"id\":61596166,\"identity\":\"6fd96c65-959a-4d32-b1b3-5698f1958498\",\"added_by\":\"auto\",\"created_at\":\"2024-08-01 17:25:17\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2191964,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/d1b2972a-1b03-4c19-bb71-bdfba9d45a4b.pdf\"},{\"id\":42851991,\"identity\":\"b9ec1528-3f18-455a-9d7b-630d3b0ba8ea\",\"added_by\":\"auto\",\"created_at\":\"2023-09-08 18:48:34\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":33319,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Supplementarymaterial.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3317589/v1/52da86120c63025d369d6189.docx\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Vaginal microbiome differences between patients with adenomyosis with different menstrual cycles and healthy controls\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eAdenomyosis is a benign uterine myometrial lesion commonly found in women of reproductive age and is characterized by compensatory hypertrophy in the peripheral myometrium, with endometrioid glands and stroma found in the myometrium\\u003csup\\u003e[\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]\\u003c/sup\\u003e. Pathological diagnosis after surgery is the gold standard for clinical diagnosis; however, the exact incidence and pathogenesis of adenomyosis remain unknown\\u003csup\\u003e[\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e]\\u003c/sup\\u003e. Studies have shown that a history of uterine surgery is a high risk factor for adenomyosis. For example, the incidence of adenomyosis in patients with the aforementioned surgical history is 1.5 times higher than in patients with a different history\\u003csup\\u003e[\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e]\\u003c/sup\\u003e. In the treatment of adenomyopathy, in addition to surgical treatment, conservative programs are used to regulate endocrine and immune system functions. Diagnostic methods include MRI, transvaginal ultrasonography, and CA125, but no specific, individualized diagnostic method is available. Adenomyosis and other benign gynecological diseases, such as uterine fibroids, endometriosis, and endometrial polyps, have a high comorbidity rate, and attributing specific symptoms to adenomyosis in clinical diagnosis and treatment is difficult.\\u003c/p\\u003e \\u003cp\\u003eThe vagina is an important organ of the female lower genital tract and is an important habitat for microorganisms in the human body. Lactobacillus is the predominant bacterial species and is affected by various exogenous and endogenous factors and the species composition of the vaginal microbiome has a strong dynamic change\\u003csup\\u003e[\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e]\\u003c/sup\\u003e. The vaginal microbiome is an important defense mechanism that regulates and maintains reproductive function and relative homeostasis in healthy environments. The stability of the microbiome can prevent the proliferation of symbiotic microorganisms and the colonization of pathogens\\u003csup\\u003e[\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e]\\u003c/sup\\u003e. Microorganisms affect the balance of the microenvironment through nutritional competition, intraspecific and interspecific signal transduction, metabolic pathways, and product interactions. The mechanism of microenvironmental imbalance remains unclear; however, this imbalance can disrupt normal homeostasis, resulting in certain pathological signs. The female upper reproductive tract was once considered a sterile environment; however, this theory has been challenged. The presence of microbiota in the endometrial microbiota\\u003csup\\u003e[\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e]\\u003c/sup\\u003e was confirmed by the isolation of microbiota from female endometrial aspirated fluid samples. Studies have shown that bacterial DNA can be detected in 95% of post-hysterectomy samples\\u003csup\\u003e[\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]\\u003c/sup\\u003e. Microbial switching occurs in the female reproductive tract, and the flora of the upper and lower reproductive tracts work synergistically to regulate the uterine environment. With increasing age, synchronous changes in the microbiome of the uterus and vagina increasingly converge, showing a mutually parallel relationship. Animal studies have verified the damaging and protective effects of vaginal bacteria on the endometrium using microflora transplantation techniques\\u003csup\\u003e[\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e]\\u003c/sup\\u003e. This also indicates that lower reproductive tract bacteria affect or directly interfere with the regulation of some benign and malignant diseases, to some extent, through certain mechanisms.\\u003c/p\\u003e \\u003cp\\u003eInitial research on vaginal microbes mainly relied on microscopy and microbial culture techniques; however, the vast majority of microorganisms in the physiological or natural environment are difficult to obtain through culture. Using bioinformatics, we used high-throughput sequencing and analysis technology to minimize the dependence on bacterial culture technology used in the literature to enhance the understanding of the structure and function of the microbial community so that the benign and malignant diseases of the female reproductive system and the bacterial community this \\\"non-visual organ\\\" the interaction between more clearly.\\u003c/p\\u003e \\u003cp\\u003e16S-rRNA is a subunit of ribosomal RNA. With improvements in sequencing technology, 16S-rDNA amplicon sequencing has become an important means to evaluate the colony microenvironment, flora structure, and composition\\u003csup\\u003e[\\u003cspan additionalcitationids=\\\"CR11 CR12\\\" citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e10\\u003c/span\\u003e\\u0026ndash;\\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e13\\u003c/span\\u003e]\\u003c/sup\\u003e. As research progresses, sequencing platforms are updated and iterated. Relying on the upgraded Illumina NovaSeq sequencing platform, we compensated for the inefficiency of single-ended reading and splicing of gene sequences and realized double-ended sequencing; that is, we built small fragment libraries according to the characteristics of the amplified regions.\\u003c/p\\u003e \\u003cp\\u003eAccording to our review of the literature, no study has investigated the differences in the vaginal microbiome between patients with different menstrual cycles and healthy individuals. Therefore, based on the analysis of disease and healthy controls, this study further explored the data of sick and healthy individuals in different menstrual cycles. Our results provide a reference for the subsequent screening of characteristic biological markers, disease diagnosis, noninvasive precision treatment, and efficacy prediction based on microbial detection.\\u003c/p\\u003e\"},{\"header\":\"Materials and methods\",\"content\":\"\\u003cp\\u003eThe case group in this study comprised patients with adenomyosis in the gynecological outpatient department of Affiliated Hospital of Shandong University from November 2021 to October 2022 were selected as the case group. They were evaluated by professional gynecologists, and adenomyosis was confirmed by ultrasound or magnetic resonance imaging (MRI). The control group comprised healthy individuals. The inclusion criteria were as follows: (1) 18\\u0026ndash;49 years old ; (2) no unhealthy lifestyle; (3) Regular menstrual cycle; (4) non-pregnant, non-puerperal, non-lactation, non-menstrual period; (6) pre-menopause. The exclusion criteria were as follows: (1) no medical history could be provided; (2) cervical intraepithelial lesions, cervical malignancies, vulva lesions and other HPV-related diseases; (3) virus or bacterial infection; (4) history and treatment of endocrine system diseases; (5) autoimmune diseases; (6) acute/chronic inflammation of the urogenital tract; (7) Sexually transmitted diseases and infectious diseases; (8) malignant tumors; (9) History of sexual life, vaginal bleeding, vaginal douching, vaginal medication, sitting bath, pelvic bath, transvaginal examination 48 hours before sampling; (10) History of use of antibiotics, antifungals, and hormonal drugs within 30 days before sampling; (11) Intrauterine device implantation; (12) Recent history of pelvic and abdominal surgery and intrauterine operation.\\u003c/p\\u003e \\u003cdiv id=\\\"Sec3\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSample collection\\u003c/h2\\u003e \\u003cp\\u003eThe individuals who fulfilled the inclusion criteria had a clinical sample collected on the day of the clinical visit before they received a transvaginal gynecologic examination or gynecologic ultrasound. The posterior vaginal fornix was fully sampled using disposable sterile swabs. During the procedure, contact between the swab head and the speculum, vaginal wall, and other non-sampling sites was avoided. The swab head was cut off with sterile scissors and placed in a sterile centrifuge tube containing Amies culture medium(JINAN BABIO BIOTECHNOLOGY CO,.LTD. ), and stored at -80 ℃ in the laboratory.\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDNA extraction\\u003c/h2\\u003e \\u003cp\\u003eThe genomic DNA of the sample is extracted by CTAB method.Appropriate amount of DNA was collected in a centrifuge tube, the purity and concentration of DNA was detected by agarose gel electrophoresis, and the sample was diluted to 1ng/\\u0026micro;L with sterile water. Using the diluted genomic DNA as a template, the V3-V4 region of 16S-rDNA gene was amplified. The primer sequence was as follows: ①F:CCTAYGGGRBGCASCAG; ②R:GGACTACNNGGGTATCTAAT (Phusion\\u0026reg; High-Fidelity PCR Master Mix with GC Buffer, New England Biolabs,lnc.). PCR was performed using specific primers with Barcode and high-efficiency high-fidelity enzyme according to the selection of sequencing region to ensure amplification efficiency and accuracy .The amplification was conducted for 30s at 98 \\u0026deg; C to denature the DNA,followed by 25 three-step temperature cycles of 98 ̊C for 10s, 53 ̊C for 25s, For 10s, 53 ̊C for 25s, and 72 ̊C for 10min.For the final step,the elongation process was performed for 10min at 72 ̊C before obtaining 290bp amplicons.PCR products were detected by electrophoresis using 2% concentration agarose gel,qualified PCR products were purified by magnetic beads;Enzyme quantification;Recovered products (Glue recovery kit provided by qiagen).\\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eLibrary construction and sequencing\\u003c/h2\\u003e \\u003cp\\u003eThe library was constructed using TruSeq\\u0026reg; DNA PCR-Free Sample Preparation Kit. The constructed library was quantified by Qubit and Q-PCR. After the library was qualified, the computer sequencing was performed using NovaSeq 6000. According to Barcode sequence and PCR amplification primer sequence, each sample data was separated from the disembarkation data. After the amputation of Barcode and primer sequences using FLASH (V1.2.7, \\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttp://ccb.jhu.edu/software/FLASH/\\u003c/span\\u003e\\u003cspan address=\\\"http://ccb.jhu.edu/software/FLASH/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) to splice reads of each sample, the splicing sequence for Raw Tags; Then fastp software is used to strictly filter the obtained Raw Tags to obtain high-quality Clean Tags data. After dealing with the above Tags to get treatment to remove the chimeric sequences, Tags sequence through (\\u003cspan class=\\\"ExternalRef\\\"\\u003e\\u003cspan class=\\\"RefSource\\\"\\u003ehttps://github.com/torognes/vsearch/\\u003c/span\\u003e\\u003cspan address=\\\"https://github.com/torognes/vsearch/\\\" targettype=\\\"URL\\\" class=\\\"RefTarget\\\"\\u003e\\u003c/span\\u003e\\u003c/span\\u003e) annotation database for matching detection chimeric sequences and species, and eventually chimera is taken out of sequence, get the final Effective Tags.\\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003eThe study enrolled 43 patients with adenomyosis and 40 healthy people. There were no significant differences in demographic background between the two groups of participants. (Table 1)\\u003c/p\\u003e\\n\\u003cp\\u003eTable 1 Demographic data of the subjects\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"553\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAdenomyosis \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; （N=40）\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;Control\\u003c/p\\u003e\\n \\u003cp\\u003e（N=40）\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u003c/em\\u003e-value\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eAge,years(mean\\u0026plusmn;SD)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e39.81\\u0026plusmn;5.62\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e38.38\\u0026plusmn;5.51\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.243\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eBMI,kg/m\\u003csup\\u003e2\\u003c/sup\\u003e,( mean\\u0026plusmn;SD)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e23.73\\u0026plusmn;2.81\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e22.32\\u0026plusmn;3.88\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.060\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGestation\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e2.19\\u0026plusmn;1.20\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1.77\\u0026plusmn;1.07\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.055\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eProduction\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1.07\\u0026plusmn;0.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e1.00\\u0026plusmn;0.56\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.687\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eMenstrual cycle，days\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e26.88\\u0026plusmn;3.67\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e27.97\\u0026plusmn;2.15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.066\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"34.23913043478261%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eMenstrual period，days\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"22.10144927536232%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5.81\\u0026plusmn;1.33\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"27.717391304347824%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e5.47\\u0026plusmn;1.32\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"15.942028985507246%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.153\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eThe vaginal samples were collected from all participants; however, 7 samples in total were excluded from the control group due to poor DNA quality after library quality check. Therefore, 83 samples were used in the subsequent analysis. (Fig 1)\\u003c/p\\u003e\\n\\u003cp\\u003eNext, the vaginal microbiota was analyzed using 16s rDNA sequencing techniques. The Raw PE data sequenced by Illumina Novaseq were splicing and quality control to obtain Clean Tags, and then chimeric filtering was performed to obtain Effective Tags for subsequent analysis. (S1 Table)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eSpecies relative abundances\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAt phylum level, the relative abundance of\\u0026nbsp;Firmicutes\\u0026nbsp;in adenomyosis group was higher than that in control group (80.70% and 69.72% in adenomyosis and control groups). At the Genus level, the\\u0026nbsp;Lactobacillus\\u0026nbsp;relative abundance in both adenomyosis group and control group was the highest (72.10% and 66.08%). But the relative abundance of Gardnerella and Atopobium in the adenomyosis group was lower than that in the control group (9.67% and 1.04% in adenomyosis and 14.95% and 4.69% in control groups); At the Species level, the Lactobacillus_iners abundance in the adenomyosis group was higher than that in the control group(43.74% and 32.14%), and showed a diversity of Lactobacillus, including Lactobacillus_delbrueckii and Lactobacillus_jensenii.(Fig 2).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eDifferent menstrual cycles\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe top 35 species with the average abundance of all samples of the same level and different groups are selected for clustering, and the heatmap is drawn by pheatmap package of R software, which is convenient to find the number or content of species in the sample. (Fig 3)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eSample complexity analysis\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eIn order to study the influence of menstrual cycle on vaginal microecology, we named all the samples in the luteal phase of the adenomyosis group as group C and the follicular phase as group D. All the samples in the luteal phase of the control group were named group E and group F. in the follicular phase.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eAlpha-diversity analysis showed significant differences in the adenomyosis and control group during luteal phase (Shannon index, \\u003cem\\u003ep\\u003c/em\\u003e=0.0087; Simpson index, \\u003cem\\u003ep\\u003c/em\\u003e=0.0056), but we didn\\u0026rsquo;t find the statistically difference in ACE and chao 1 index (Fig 4).It was verified that the amount of sequencing data was progressive and reasonable, and more data would only produce a few new species, thus suggesting a uniform distribution of species. (Fig 5)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003e\\u003cem\\u003eComparative analysis of multiple copies\\u003c/em\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe species distributions in the adenomyosis group and the control group were not completely separated, but were similar. (Fig 6)\\u003c/p\\u003e\\n\\u003cp\\u003eWe analyzed the Beta-diversity index by using the t-test and found that the species Beta-diversity index was significantly different between the adenomyosis group and the control group (Fig 7 A, B). However, based on Weighted unifrac analysis, significant differences between the disease group and the control group were only observed throughout the luteal phase(\\u003cem\\u003eP=0.0146\\u003c/em\\u003e) .(Fig 7 C, D)\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eR value was between (-1, 1), and R value was greater than 0, indicating that the difference between groups was greater than the difference within groups, which was significant (\\u003cem\\u003eP\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05). The reasonableness of the grouping in this study was proved. (Table 2)\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 \\u0026nbsp;Anosim analysis based on the Bray-Curtis distance. Anosim analysis is a non-parametric test used to test whether the difference between groups is significantly greater than the difference within groups, so as to determine whether the grouping is meaningful. We conducted the significance test of the difference between groups based on the rank of the Bray-Curtis distance value.\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" align=\\\"\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"33.333333333333336%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eGroup\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.333333333333336%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eR\\u003c/em\\u003e value\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.333333333333336%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e\\u003cem\\u003eP\\u0026nbsp;\\u003c/em\\u003evalue\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd width=\\\"33.333333333333336%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003eB-A\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.333333333333336%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.03067\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd width=\\\"33.333333333333336%\\\" valign=\\\"top\\\"\\u003e\\n \\u003cp\\u003e0.044\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAt the phylum level, there were no significant species differences between the adenomyosis group and the control group.At the class level the significant differences was in Coriobacteriia and Gammaproteobacteria (P \\u0026lt; 0.01). At the class level the significant differences was in Lactobacillales, Coriobacteriales(P \\u0026lt; 0.01),and in Pseudomonadales \\u0026nbsp;(\\u003cem\\u003ep\\u003c/em\\u003e\\u0026lt; 0.05). At the class level the significant differences was in Beijerinckiaceae and Listeriaceae \\u0026nbsp;(\\u003cem\\u003ep\\u003c/em\\u003e\\u0026lt; 0.05).At the genus level, that were in Listeria, Ralstonia, Acinetobacter, and Haemophilus (\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01), and Alloscardovia,Ureaolasma (\\u003cem\\u003ep\\u0026nbsp;\\u003c/em\\u003e\\u0026lt; 0.05).Finally, at the species level ,there was significant difference in Alloscardovia_omnicolens and Lactobacillus_delbrueckii (\\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.01).( Fig 8)\\u003c/p\\u003e\\n\\u003cp\\u003eAt the Phylum level, Firmicutes showed the highest species abundance in both the adenomyosis group and the control group, and at the same time, contributed the most to the species difference between the two groups. (Fig 9)\\u003c/p\\u003e\\n\\u003cp\\u003eRandom forest is a classical machine learning model based on classification tree algorithm to screen features (biomarkers) that play an important role in classification or grouping. A default 10-fold cross-validation was performed for each model, and ROC curves were drawn to select potential Biomaker 50 as shown in Fig 10.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study elucidated the differences in vaginal microbiota characteristics between women with and without adenomyosis with different menstrual cycles.\\u003c/p\\u003e \\u003cp\\u003eWe used the alpha diversity index (e.g., the Shannon index, chao1 index, ACE, and Simpson indices) to analyze the species within the group and calculated the number of microbial species in a single sample and the proportion of each species. The aforementioned analysis indexes of the two groups of samples did not show significant differences, similar to the results of Chen et al.\\u003csup\\u003e[\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e]\\u003c/sup\\u003e. The cumulative histogram of the relative abundance of species showed that although the species were similar, abundance significantly differed. At the phylum level, the relative abundance of Firmicutes was higher in the adenomyosis group than in the control group. At the genus level, except for the absolute species dominance of Lactobacillus in both groups, the relative abundance of Gardnerella in the adenomyosis group was significantly lower than that in the control group, which differed from the results of Kunaseth J\\u003csup\\u003e[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e]\\u003c/sup\\u003e. Lactobacillus vegetation in the female reproductive tract is critical for the maintenance of genital health. However, the exact pathogenesis of Gardnerella vaginalis remains unclear\\u003csup\\u003e[\\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e16\\u003c/span\\u003e]\\u003c/sup\\u003e. Lactobacillus and Gardnerella interact in the female reproductive tract; when the amount of Lactobacillus decreases to a certain extent, the growth of Gardnerella can decrease or stop\\u003csup\\u003e[\\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e17\\u003c/span\\u003e]\\u003c/sup\\u003e, and the imbalance of the two bacteria can change the acid-base environment of the vagina and produce mucosal adsorption and biofilm, promoting chronic, persistent infection and inflammation\\u003csup\\u003e[\\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e18\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e19\\u003c/span\\u003e]\\u003c/sup\\u003e. A data analysis using the dominance network analysis framework found that in these \\\"non-Lactobacillus dominant vaginal flora,\\u0026rdquo; Gardnerella was jointly inhibited by 23 bacteria genera\\u003csup\\u003e[\\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e20\\u003c/span\\u003e]\\u003c/sup\\u003e. Lactobacilli that cooperate with Gardnerella and are inhibited by other species are \\u003cem\\u003eLactobacillus-iners\\u003c/em\\u003e\\u003csup\\u003e[\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e21\\u003c/span\\u003e]\\u003c/sup\\u003e. In this study, we found that the abundance of Lactobacillus inert in the adenomyosis group was significantly higher than that in the control group at the species level, and this significance was verified using the MetaStat method. In conclusion, the variation in Lactobacillus inerta and Gardnerella abundance may be a potential cause of adenomyosis, and maintaining the balance of Lactobacillus normalis and Gardnerella in the body may be a self-mechanism to maintain the stability of vaginal microecology.\\u003c/p\\u003e \\u003cp\\u003eHowever, little is known about how the genital microbiota affects host immune function and regulates disease susceptibility. Lactobacillus imbalance and high ecological diversity may be closely related to the concentration of pro-inflammatory cytokines in genital organs\\u003csup\\u003e[\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]\\u003c/sup\\u003e. Patients with adenomyosis show leukocyte infiltration in the endometrial functional layer, and the number of macrophages and natural killer (NK) cells increased\\u003csup\\u003e[\\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e23\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e24\\u003c/span\\u003e]\\u003c/sup\\u003e. Other groups of vaginal bacilli were also detected in this study, second only to Lactobacillus in overall abundance. Transcriptional analysis showed that antigen-presenting cells sense gram-negative bacterial products in situ via Toll-like receptor 4 (TLR-4) signaling, promoting genital organ inflammation by activating the NF-κB signaling pathway and recruiting lymphocytes through chemokine production\\u003csup\\u003e[\\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e22\\u003c/span\\u003e]\\u003c/sup\\u003e. Immune dysregulation is present in the ectopic endometrium of patients with adenomyopathy and manifests as elevated Tim-3/Gal-9 expression and differential RNA methylation\\u003csup\\u003e[\\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e25\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e26\\u003c/span\\u003e]\\u003c/sup\\u003e. Therefore, we speculated that vaginal microecological changes affect the important role of Tim-3/Gal-9 in immunosuppression through some mechanism, causing the persistence of infection, affecting the growth environment of the endometrial tissue, and causing adenomyosis. In addition, the expression of Type I interferon (IFN-I) inducers is increased in the ectopic endometrium in adenomyosis. The increased levels of IFN-Is and expression of interferon-stimulating genes and pro-inflammatory cytokines in tissues may be related to host immunity under the influence of certain microorganisms\\u003csup\\u003e[\\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e27\\u003c/span\\u003e]\\u003c/sup\\u003e. Recent literature has suggested that microbiota-induced interferon activation does not require direct host-bacterial interaction but the remote transport of bacterial DNA into host cells via bacteria-derived membrane vesicles\\u003csup\\u003e[\\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e28\\u003c/span\\u003e]\\u003c/sup\\u003e. In contrast with our finding that the beta diversity index was significantly higher in the adenomyosis group than in the control group, the increased bacterial diversity in the vagina probably explains the activation of the host\\u0026rsquo;s innate immune response in the ectopic endometrium in adenomyosis\\u003csup\\u003e[\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e29\\u003c/span\\u003e]\\u003c/sup\\u003e.\\u003c/p\\u003e \\u003cp\\u003eThe microbiota of the female reproductive system is influenced by changes in age and system physiology, and the menstrual cycle is a major disruptor of the vaginal microbiome. Different microbiota characteristics are observed in women at different physiological stages\\u003csup\\u003e[\\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e30\\u003c/span\\u003e]\\u003c/sup\\u003e. In healthy women of reproductive age, the vaginal microbiome composition changes dramatically before and after menstruation\\u003csup\\u003e[\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e]\\u003c/sup\\u003e. Menstrual blood flowing through the vagina leaves sufficient iron for pathogens, and the iron necessary for pathogen metabolism\\u003csup\\u003e[\\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e32\\u003c/span\\u003e]\\u003c/sup\\u003e, which is reduced by the iron-binding affinity of lactoferrin, is replenished. Additionally, studies measuring estradiol levels and vaginal microbiome composition in women who use oral contraceptives to inhibit ovulation have shown that the high diversity observed during menstruation is mainly driven by estradiol withdrawal before menstruation rather than by the dynamic drive of progesterone. Lactobacillus abundance increases during the follicular and luteal phases, gradually normalizing the vaginal microecology \\u003csup\\u003e[\\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e31\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e33\\u003c/span\\u003e]\\u003c/sup\\u003e. Under the influence of this periodicity, combined with our test results, we found different types of dominant bacterial profiles in patients with adenomyosis in both the both luteal and follicular stages, which provided a reference for the detection of biomarkers in patients with specific menstrual cycles or to evaluate their efficacy.\\u003c/p\\u003e \\u003cp\\u003eIn summary, in this study, an increase in microbial richness was associated with adenomyosis, and the microbiome characteristics of patients with and without adenomyosis differed according to the menstrual cycle. This study has three notable limitations: the final sample size was limited because of coronavirus disease 2019 (COVID-19), no large sample of data clinical for verification was available, and the different methods used in each study may have led to different conclusions. In further research, we plan to develop standardized analysis software and large databases to continue our investigation of the mechanisms behind this association.\\u003c/p\\u003e\"},{\"header\":\"Abbreviations\",\"content\":\"\\u003cp\\u003eMagnetic resonance imaging (MRI); natural killer (NK) cells; Toll-like receptor 4 (TLR-4); Type I interferon (IFN-I); coronavirus disease 2019 (COVID-19).\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003eThe research has been performed in accordance with the Declaration of Helsinki. The patients were informed about the sample collection and had signed informed consent forms.\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eThis study was reviewed and approved by the Medical Ethics Committee of the hospital (ethics approval No. : KYLL-20211-092-1). The research has been performed in accordance with the Declaration of Helsinki. The patients were informed about the sample collection and had signed informed consent forms.\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eThe authors confirm that the data supporting the findings of this study are available within the article or supplementary materials.\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests.\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eThis study was supported by the National Key R\\u0026amp;D Program of China [2022YFC2704000], the Major Basic Research of Natural Science Foundation of Shandong [ZR2021ZD34], and the National Natural Science Foundation of China [grant numbers 82071621 and 81901458].\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eAuthors\\u0026apos; contributions\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eAll authors read and approved the final manuscript. Guoyun Wang and Ming Yuan designed the experiments. Zangyu Pan conceived and carried out sample collection, analysis, and interpretation. Jun Dai, Ping Zhang, Qianhui Ren, Xinyu Wang, Hao Sun, Shumin Yan and Xue Jiao carried out sample collection. Zangyu Pan drafted the manuscript and prepared the figures and tables. All authors finalized the final manuscript.\\u003c/p\\u003e\\n\\u003cul type=\\\"disc\\\"\\u003e\\n \\u003cli\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/li\\u003e\\n\\u003c/ul\\u003e\\n\\u003cp\\u003eWe would like to thank all of the volunteers who participated in this study. We would like to thank Editage (www.editage.cn) for English language editing. We would like to thank Novogene Biotech Co., Ltd for data administration.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eYen CF, Huang SJ, Lee CL, et al. Molecular characteristics of the endometrium in uterine adenomyosis and its biochemical microenvironment[J]. Reprod Sci, 2017, 24(10): 1346-1361.\\u003c/li\\u003e\\n\\u003cli\\u003eCunningham RK, Horrow MM, Smith RJ, et al. Adenomyosis: A Sonographic Diagnosis. [J]. Radiographics, 2018, 38(5):1576-1589.\\u003c/li\\u003e\\n\\u003cli\\u003eParazzini F, Vercellini P, Panazza S,et al. Risk factors for adenomyosis[J]. Hum Reprod, 1997, 12(6): 1275-1279.\\u003c/li\\u003e\\n\\u003cli\\u003eRiggs JC, Lim EK, Liang D, et al. Cesarean section as a risk factor for the development of adenomyosis uteri[J]. J Reprod Med, 2014, 59(1-2):20-24.\\u003c/li\\u003e\\n\\u003cli\\u003eAbou Chacra L, Fenollar F, Diop K. Bacterial Vaginosis: What Do We Currently Know? [J]. Front Cell Infect Microbiol, 2022, 11:672429.\\u003c/li\\u003e\\n\\u003cli\\u003eDeidda F, Amoruso A, Allesina S, et al. In Vitro Activity of Lactobacillus fermentum LF5 Against Different Candida Species and Gardnerella vaginalis: A New Perspective to Approach Mixed Vaginal Infections? [J]. J Clin Gastroenterol, 2016 Nov/Dec; 50 Suppl 2, Proceedings from the 8th Probiotics, Prebiotics \\u0026amp; New Foods for Microbiota and Human Health meeting held in Rome, Italy on September 13-15, 2015: S168-S170.\\u003c/li\\u003e\\n\\u003cli\\u003eMoreno I, Codo\\u0026ntilde;er FM, Vilella F, et al. Evidence that the endometrial microbiota has an effect on implantation success or failure[J]. Am J Obstet Gynecol, 2016, 215(6): 684-703.\\u003c/li\\u003e\\n\\u003cli\\u003eMitchell C.M, Haick A, Nkwopara E, et al. Colonization of the Upper Genital Tract by Vaginal Bacterial Species in Nonpregnant Women[J]. Am. J. Obstet, Gynecol, 2015, 212, 611. e1\\u0026ndash;611. e9.\\u003c/li\\u003e\\n\\u003cli\\u003eWang J, Li Z, Ma X, et al. Translocation of vaginal microbiota is involved in impairment and protection of uterine health[J]. Nat Commun, 2021, 12(1): 4191.\\u003c/li\\u003e\\n\\u003cli\\u003eYoussef N, Sheik CS, Krumholz LR, et al. Comparison of species richness estimates obtained using nearly complete fragments and simulated pyrosequencing-generated fragments in 16S rRNA gene-based environmental surveys[J]. Appl Environ Microbiol, 2009, 75(16) : 5227- 5236.\\u003c/li\\u003e\\n\\u003cli\\u003eHess M, Sczyrba A, Egan R, et al. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen[J]. Science, 2011, 331(6016) : 463- 467.\\u003c/li\\u003e\\n\\u003cli\\u003eLundberg DS, Yourstone S, Mieczkowski P, et al. Practical innovations for high-throughput amplicon sequencing[J]. Nat Methods, 2013, 10(10) : 999- 1002.\\u003c/li\\u003e\\n\\u003cli\\u003eHickey RJ, Zhou X, Settles ML, et al. Vaginal microbiota of adolescent girls prior to the onset of menarche resemble those of reproductive-age women[J]. mBio, 2015, 6(2) : e00097- 15. \\u003c/li\\u003e\\n\\u003cli\\u003eChen S, Gu Z, Zhang W, et al. Microbiome of the lower genital tract in Chinese women with endometriosis by 16s-rRNA sequencing technique: a pilot study[J]. Ann Transl Med, 2020, 8(21):1440. \\u003c/li\\u003e\\n\\u003cli\\u003eKunaseth J, Waiyaput W, Chanchaem P, et al. Vaginal microbiome of women with adenomyosis: A case-control study[J]. PLoS One, 2022, 17(2): e0263283. \\u003c/li\\u003e\\n\\u003cli\\u003eDjukic M, Schmidt-Samoa C, Lange P, et al. Cerebrospinal fluid findings in adults with acute Lyme neuroborreliosis[J]. J Neurol, 2012, 259(4):630-636.\\u003c/li\\u003e\\n\\u003cli\\u003eHaedicke J, Iftner T. Human papillomaviruses and cancer[J]. Radiother Oncol, 2013, 108(3):397-402.\\u003c/li\\u003e\\n\\u003cli\\u003eMachado D, Castro J, Palmeira-de-Oliveira A, et al. Bacterial Vaginosis Biofilms: Challenges to Current Therapies and Emerging Solutions[J]. Front Microbiol, 2016, 6: 1528.\\u003c/li\\u003e\\n\\u003cli\\u003eGarcia EM, Kraskauskiene V, Koblinski JE,et al. Interaction of Gardnerella vaginalis and Vaginolysin with the Apical versus Basolateral Face of a Three-Dimensional Model of Vaginal Epithelium. Infect Immun. 2019 Mar 25;87(4):e00646-18.\\u003c/li\\u003e\\n\\u003cli\\u003eDoyle R, Gondwe A, Fan YM,et al. A Lactobacillus-Deficient Vaginal Microbiota Dominates Postpartum Women in Rural Malawi[J]. Appl Environ Microbiol, 2018 , 84(6) : e02150- 17.\\u003c/li\\u003e\\n\\u003cli\\u003eLi W, Ma ZS. Dominance network analysis of the healthy human vaginal microbiome not dominated by Lactobacillus species[J]. Comput Struct Biotechnol J. 2020, 18: 3447-3456. \\u003c/li\\u003e\\n\\u003cli\\u003eAnahtar MN, Byrne EH, Doherty KE,et al. Cervicovaginal bacteria are a major modulator of host inflammatory responses in the female genital tract[J]. Immunity, 2015, 42(5) : 965-976. \\u003c/li\\u003e\\n\\u003cli\\u003eOrazov MR, Radzinsky VE, Nosenko EN, et al. Immune-inflammatory predictors of the pelvic pain syndrome associated with adenomyosis[J]. Gynecol Endocrinol, 2017, 33(sup1) : 44- 46.\\u003c/li\\u003e\\n\\u003cli\\u003eTremellen KP, Russell P. The distribution of immune cells and macrophages in the endometrium of women with recurrent reproductive failure. II: adenomyosis and macrophages[J]. J Reprod Immunol, 2012, 93(1) : 58- 63.\\u003c/li\\u003e\\n\\u003cli\\u003eHuang P, Lv C, Zhang C, et al. Expression and significance of T-cell immunoglobulin mucin molecule 3 and its ligand galectin-9 in patients with adenomyosis[J]. Gynecol Endocrinol, 2020, 36(7) : 605- 610.\\u003c/li\\u003e\\n\\u003cli\\u003eZhai J, Li S, Sen S, et al. m6A RNA Methylation Regulators Contribute to Eutopic Endometrium and Myometrium Dysfunction in Adenomyosis[J]. Front Genet, 2020, 11: 716.\\u003c/li\\u003e\\n\\u003cli\\u003eQu H, Li L, Wang TL, et al. Epithelial Cells in Endometriosis and Adenomyosis Upregulate STING Expression[J]. Reprod Sci, 2020, 27(6) : 1276- 1284.\\u003c/li\\u003e\\n\\u003cli\\u003eErttmann SF, Swacha P, Aung KM, et al. The gut microbiota prime systemic antiviral immunity via the cGAS-STING-IFN-I axis[J]. Immunity, 2022, 55(5) : 847- 861. e10.\\u003c/li\\u003e\\n\\u003cli\\u003eAbou Chacra L, Fenollar F, Diop K. Bacterial Vaginosis: What Do We Currently Know? [J]. Front Cell Infect Microbiol, 2022, 11:672429.\\u003c/li\\u003e\\n\\u003cli\\u003eGalkin F, Mamoshina P, Aliper A, et al. Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning[J]. iScience, 2020, 23(6) : 101199.\\u003c/li\\u003e\\n\\u003cli\\u003eKrog MC, Hugerth LW, Fransson E, et al. The healthy female microbiome across body sites: effect of hormonal contraceptives and the menstrual cycle[J]. Hum Reprod, 2022, 37(7) : 1525- 1543. \\u003c/li\\u003e\\n\\u003cli\\u003eRoberts SA, Brabin L, Diallo S, et al. Mucosal lactoferrin response to genital tract infections is associated with iron and nutritional biomarkers in young Burkinab\\u0026eacute; women[J]. Eur J Clin Nutr, 2019, 73(11): 1464-1472.\\u003c/li\\u003e\\n\\u003cli\\u003eSong SD, Acharya KD, Zhu JE,et al. Daily vaginal microbiota fluctuations associated with natural hormonal cycle, contraceptives, diet, and exercise[J]. MSphere, 2020, 5: 1\\u0026ndash; 14.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-microbiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"mcro\",\"sideBox\":\"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/mcro\",\"title\":\"BMC Microbiology\",\"twitterHandle\":\"#bmcmicrobiology\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"Adenomyosis, Vaginal microbiome, Menstrual cycles\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-3317589/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-3317589/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003ch2\\u003eBackground\\u003c/h2\\u003e \\u003cp\\u003eAdenomyosis is a commonly observed benign gynecological disease that affects the quality of life and social psychology of women of childbearing age. However, because of the unknown etiology and incidence of adenomyosis, its pathophysiological mechanism remains unclear; further, because no noninvasive, accurate, and individualized diagnostic methods are available, treatment and efficacy evaluations are limited. Notably, the interaction between the changes in the microecological environment of the female reproductive tract and human immunity, endocrine, and other links leads to the occurrence and development of diseases. In addition, the vaginal microbiome differs in different menstrual cycles; therefore, assessing the differences between the microbiomes of patients with adenomyosis and healthy individuals in different menstrual cycles will improve the understanding of the disease and provide references for the search for noninvasive diagnosis and individualized precision treatment of adenomyosis. This study aimed to explored the data of individuals in different menstrual cycles.\\u003c/p\\u003e\\u003ch2\\u003eResults\\u003c/h2\\u003e \\u003cp\\u003eDifferences in the vaginal microbiome between patients with adenomyosis and healthy individuals were observed. At the phylum level, the relative abundance of Firmicutes species in the adenomyosis group was higher when compared with the control group. At the genus level, the relative abundance of Lactobacillus in the adenomyosis and control groups was the highest, which contributed the most to the species difference between the two groups. Alpha-diversity analysis showed significant differences in the adenomyosis and control group during luteal phase (Shannon index \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.0087, Simpson index, \\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.0056). Beta-diversity analysis showed lower microbial richness in the adenomyosis group than that in the control group by weighted unifrac distance (\\u003cem\\u003ep\\u003c/em\\u003e\\u0026thinsp;=\\u0026thinsp;0.0018). In the same disease group, differences between different menstrual cycles were also observed. Finally, 50 possible biomarkers including were screened and predicted based on the PICRUSt.\\u003c/p\\u003e\\u003ch2\\u003eConclusions\\u003c/h2\\u003e \\u003cp\\u003eThe vaginal microbiome differs between patients with adenomyosis and healthy individuals during difference menstrual periods especially during the luteal phase. These findings facilitate the search for specific biological markers within a limited range and provide a more accurate, objective, and individualized diagnostic and therapeutic evaluation method for patients with adenomyosis than is currently available.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Vaginal microbiome differences between patients with adenomyosis with different menstrual cycles and healthy controls\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2023-09-08 18:48:28\",\"doi\":\"10.21203/rs.3.rs-3317589/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Major revision\",\"date\":\"2023-09-07T12:26:11+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2023-09-05T10:52:09+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2023-09-05T07:28:01+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Microbiology\",\"date\":\"2023-09-01T14:52:16+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-microbiology\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"mcro\",\"sideBox\":\"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/mcro\",\"title\":\"BMC Microbiology\",\"twitterHandle\":\"#bmcmicrobiology\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"601d8f87-7d23-425e-ba73-a10aa61fb4b6\",\"owner\":[],\"postedDate\":\"September 8th, 2023\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-08-01T17:09:03+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-3317589\",\"link\":\"https://doi.org/10.1186/s12866-024-03339-9\",\"journal\":{\"identity\":\"bmc-microbiology\",\"isVorOnly\":false,\"title\":\"BMC Microbiology\"},\"publishedOn\":\"2024-07-27 16:16:03\",\"publishedOnDateReadable\":\"July 27th, 2024\"},\"versionCreatedAt\":\"2023-09-08 18:48:28\",\"video\":\"\",\"vorDoi\":\"10.1186/s12866-024-03339-9\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12866-024-03339-9\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-3317589\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-3317589\",\"identity\":\"rs-3317589\",\"version\":[\"v1\"]},\"buildId\":\"k6vKHA0u1VdKjwwnw531e\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC0","license_restricted":false}