Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer

Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer Wei Zhang, YanFei Yin, YiSha Jiang, YangYang Yang, WenTao Wang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3859830/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Apr, 2024 Read the published version in Journal of Translational Medicine → Version 1 posted 4 You are reading this latest preprint version Abstract Background This study aimed to assess the microbial variations and biomarker in the vaginal and oral environment of HPV (human papillomavirus) and cervical cancer (CC) patients and developing novel prediction models. Materials and Methods This study includes 164 samples collected from both the vaginal tract and oral subgingival plaque of 82 women. The participants were divided into four distinct groups based on their vaginal and oral samples including control group (Z/KZ, n = 22), abortion group (AB/KAB, n = 17), HPV-infected group (HP/KHP, n = 21), and cervical cancer group (CC/KCC, n = 22). Microbiota analysis was conducted using full-length 16S rDNA gene sequencing with PacBio platform. Results The vaginal bacterial community in the Z and AB groups exhibited a relatively simple structure predominantly dominated by Lactobacillus. However, CC group shows high diversity and abundances of anaerobic bacteria and alpha diversity. Biomarkers such as Bacteroides, Mycoplasma, Bacillus, Dialister, Porphyromonas , Anaerococcus , and Prevotella were identified as indicator of CC. Correlations were established between elevated blood C-reactive protein (CRP) levels and local/systemic inflammation, pregnancies, childbirths, and abortions, contributing to the unevenness in the vaginal microenvironment. The altered microbial diversity in CC group was confirmed by amino acid metabolism.The oral microbial diversity exhibited inverse pattern to the vaginal microbiome, indicating a unique relationship. The KCC group showed a significantly lower microbial diversity compared to the KZ group, pointing a link between oral health and cancer development. Several microbes including Fusobacterium , Campylobacte , Capnocytophaga , Veillonella , Streptococcus , Lachnoanaerobaculum , Propionibacterium , Prevotella , Lactobacillus , Neisseria were screened as CC biomarkers. Moreover, Periodontal pathogens were associated with blood CRP levels and oral hygiene conditions. Elevated oral microbial amino acid metabolism in CC group was closely linked to the presence of pathogens. positive correlations indicated synergy between vaginal and oral bacteria. Conclusion HPV infection and CC impact both the vaginal and oral microenvironment, affecting systemic metabolism and the synergy between bacteria. This suggests the use oral flora markers as a prospective screening tool for the diagnosis the cervical cancer. vaginal microbiome (VM) Human papillomavirus (HPV) cervical cancer oral microbiome 16S rRNA Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Cervical cancer (CC) ranks as the fourth most frequently diagnosed cancer and the third leading cause of cancers death in the women globally. With more than half million CC cases are annually linked to (human papillomavirus) HPV infection, resulting in 250,000 deaths for per year [ 1 ]. HPV infection is recognized as one of the major causes of CC, as well as other malignancies including anogenital tumors, anal, vulvar, penile, vaginal and oral cancers [ 2 , 3 ]. Recent studies suggest that 90% of oral squamous cell carcinoma are driven by the infection with HPV [ 4 ]. Oral cavity is a natural open system, pool of complex microbiome, comprising over 800 bacterial species inhabiting [ 5 ]. This oral microbiota have been implicated not only in periodontal disease but also in systemic conditions including hematological diseases, lymphatic, lung, pancreatic and breast cancers [ 6 – 10 ]. Changes in oral microbiome composition are now recognized as potential biomarkers for cancers including colorectal cancer (CRC) marked by increased, F. nucleatum abundance [ 11 , 12 ]. Similarly, shifts favoring oral pathogens such as Porphyromonas , Fusobacterium and Prevotella genera have been correlated with CC although mechanisms remain poorly known [ 13 ], these oral pathogens also cause the periodontal disease [ 14 ]. Previous studies have shown that correlation between vaginal bacteria and gingival inflammation [ 15 ], HPV not only invades the basal cells of the vaginal epithelium, but also infects the periodontal tissue and keeps the virus in a latent state [ 16 ]. The oral and vaginal environment may provide similar colonization and growth conditions, resulting a significantly increases the risk of periodontal disease and cancer [ 17 ]. However, there is relatively little literature exists on changes in the oral microbiome when the vaginal microbiota is transformed during the course of HPV infection to CC, suggesting that more research is needed in this area. Population-based CC screening is implemented as a public health priority in China [ 18 ], and the best strategy is Liquid-based cytology test technique (TCT) combined with HPV screening [ 19 , 20 ]. The combined screening technology, although advanced and effective, is costly, suitable for areas with adequate medical and health care. However, there are still many economically less-developed areas (rural areas) in China, it is urgent to find a good quality and cheap method. Changes in oral microbial diversity detectable through low-cost profiling may offer additional value as biomarkers for early screening, diagnosis and monitoring of HPV infection and even CC. This study aims to evaluate the difference and associations between vaginal and oral microorganisms in HPV infection and CC patients. Enhanced understanding of microbial ecology may contribute to the development of accuracy of cervical cancer screening and extend life-saving interventions to vulnerable groups. 2. Materials and methods 2.1 Study design and specimen collection. Ethical approval was obtained from the Ethics Committee of Second Hospital of Lanzhou University (approval no. 2022A-533). All methods were conducted in accordance with the Declaration of Helsinki and relevant guidelines and regulations. Participants were recruited during October 2022 to October 2023 at gynecology outpatient and inpatient departments. Inclusion criteria: 1) age 20-76 years; sexually active; 2) no vaginal irrigation or antibiotic treatment for ≥1 week before the examination and no sexual intercourse within 3 days; 3) regular menstrual cycles; 4) there is no history of cervical surgery and hysterectomy, no diseases seriously affected by other systems; 5) HPV infection positive by diagnostic testing; 6) cervical cancer was confirmed by biopsy tissue histopathological examination; 7) abortion was performed by surgical method and the number of abortions was ≥ 3. Exclusion criteria: 1) menstrual women; 2) vaginal bleeding; 3) patients with intrauterine device; 4) pregnant and lactating women; 5) patients undergoing radiation and chemotherapy; 6) prior medical/ spontaneous abortion. HPV genotype test and TCT were negative in both the control and abortion groups, HPV groups was positive for HPV genotype test and the TCT was normal. All participants completed a clinical questionnaire, oral examination results were recorded, specimen and blood collection was completed. Caries were diagnosed using the International Caries Detection and Assessment System (ICDAS) [21], diagnostic criteria [22] Periodontitis defined as ≥4 teeth with ≥1 site having probing depth ≥4mm, clinical attachment loss ≥1mm and bleeding on probing. Subgingival plaque: subjects cannot eat, drink, smoking or chewing gum, and washed the debris in their mouth with drinking water before 30 minutes. The sterile dental scaler penetrates into the tongue side of the mandibular first molar below the gum to remove dental plaque and prevent blood contamination during the collection process. Vaginal secretion: disposable speculum was inserted, and a sterile swab sample was taken from the posterior vaginal fornix. All specimen stored immediately under −80 °C for DNA extraction. Blood indicators and C-reactive protein (CRP) were analyzed using the automated blood analyzer system (SysmexXN-20; Kobe, Japan). 2.2 The Full-Length 16S Sequencing and data processing Bacterial genomic DNA was extracted from vaginal and subgingival samples using the TGuide S96 Magnetic Universal DNA Kit (Tiangen Biotech (Beijing) Co., Ltd.) according to manufacturer’s instructions. The full-length 16S rRNA gene were amplified with primer pairs 27F: AGRGTTTGATYNTGGCTCAG and 1492R: TASGGHTACCTTGTTASGACTT. Both the forward and reverse 16S primers were tailed with sample-specific PacBio barcode sequences to allow for multiplexed sequencing. After the individual quantification step, amplicons were pooled in equal amounts. SMRTbell libraries were prepared from the amplified DNA by SMRTbell Express Template Prep Kit 2.0 according to the manufacturer’s instructions (Pacific Biosciences). Purified SMRTbell libraries from the pooled and barcoded samples were sequenced on a PacBio Sequel II platform (Beijing Biomarker Technologies Co., Ltd., Beijing, China) using Sequel II binding kit 2.0. The raw subreads correction by Circular Consensus Sequencing (CCS) (SMRT Link, version8.0), then use the Lima software (v1.7.0) and identify different samples of CCS by barcod. Cutadapt software (1.9.1) is used to identify the primer sequences with removal and the length of the filter, and identification and removal of chimeric sequences by UCHIME (version 8.1). A high-quality CCS sequence was obtained. 2.3 Statistical analysis Demographic and oral data, blood indices and were compared between groups using SPSS 27.0 (IBM, Chicago, Illinois, USA). Comparisons between groups were made by ANOVA test, fisher's precision probability test and chi-squared test. The online platform BMKCloud (https://www.biocloud.net) was used to analyze the sequencing data. R (v3.2.0) was used to draw Venn and bubble diagram, correlation analysis. Alpha was performed to identify the complexity of species diversity of each sample utilizing QIIME2 software. Beta diversity among the samples was evaluated by principal coordinate analysis (PCoA) to assess the diversity in samples for species complexity. One-way analysis of variance was used to compare bacterial abundance and diversity. Linear discriminant analysis (LDA) coupled with effect size (LEfSe) was applied to evaluate the differentially abundant taxa. An LDA score of >2 was considered as the cut-of value for biomarker screening, and the differences between groups were assessed by the rank sum test. At the genus level, a threshold p-value of <0.05 and SparCC were used for constructing a correlation plot. Random forest analysis was performed to compare the microbiome characteristics, area under receiver operative characteristic curve (AUC) were assessed to evaluate the performance of the random forest analysis. Statistical comparison of AUCs was performed using pROC package in R. The picrust2 was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) function prediction. 3. Results 3.1 Characteristics of subjects Participants included 82 cases of women, and 164 samples from vagina and gingiva were sequenced. They were divided into four groups: vaginal and oral subgingival plaque control group (Z/KZ, n=22), abortion group (AB/KAB, n=17), HPV group (HP/KHP, n=21) and cervical cancer group (CC/KCC, n=22). Demography, clinical, oral health parameters are shown in Table 1. Table1. Demographic information, blood indices, oral characteristics and different HPV distribution of participants. Normal Abortion HPV Cancer P value (n=22) (n=17) (n=21) (n=22) Age （ year ） 44.68±8.54 43.12±7.67 45.76±11.02 48.05±8.99 0.395 Nation Han nationality 22(100) 17(100) 21(100) 17(77.27) 0.003 other nationalist 0(0) 0(0) 0(0) 5(22.73) Level of education primary school 1(4.55) 6(35.29) 13(61.90) 19(86.36) ＜ 0.001 high school 8(36.36) 6(35.29) 3(14.29) 2(9.09) college degree 13(59.09) 5(29.41) 5(23.81) 1(4.55) Number of pregnancies 0.87±0.94 4.82±1.13 2.48±1.50 3.14±1.61 ＜ 0.01 Number of abortions 0.32±0.48 3.29±0.59 0.62±0.74 0.59±0.85 ＜ 0.01 Number of childbirths 0.55±0.74 1.53±0.94 1.86±1.28 2.55±1.34 ＜ 0.01 Sexual age (year) 21.18±2.70 21.59±3.47 21.81±3.82 20.45±3.10 0.556 BMI (kg/m2) 20.60±1.90 23.61±4.98 22.31±3.03 23.63±3.89 0.02 Smoking 2 （ 9.09 ） 3 （ 17.65 ） 0 （ 0 ） 0 （ 0 ） 0.059 Drinking 4 （ 18.19 ） 6 （ 35.30 ） 3 （ 14.29 ） 4 （ 18.19 ） 0.481 Family history of CC （ % ） 1 （ 4.54 ） 2 （ 11.76 ） 2 （ 9.52 ） 0 （ 0 ） 0.365 CRP(mg/dL) 0.31±0.31 1.89±1.45 2.23±1.79 1.62±1.00 ＜ 0.01 WBC (4.5 to 11.0×10 9 /L) 7.68±3.12 7.75±1.78 6.15±1.88 6.82±2.80 0.635 RBC 4.60±0.36 4.54±0.44 4.46±0.38 4.38±0.57 0.068 HGB 132.41±16.98 135.06±11.14 126.95±15.45 125.55±22.49 0.122 NEUT% 65.42±10.75 64.91±7.76 59.7±7.07 70.20±11.03 0.014 LYM% 27.88±9.69 28.21±7.43 33.02±7.57 23.66±9.83 0.079 MONO% 5.30±1.09 5.63±1.05 5.17±1.29 4.75±1.45 0.461 EOS% 1.06±0.91 0.94±0.63 1.70±2.02 0.93±0.70 0.048 BASO% 0.34±0.30 0.26±0.16 0.41±0.28 0.45±0.33 0.118 PLT 288.09±69.22 266.59±51.26 256.76±71.33 240.55±88.44 0.158 Caries （ % ） 3(13.64) 2(11.76) 1(4.76) 2(9.09) 0.663 Periodontitis （ % ） 3(13.64) 3(17.65) 5(23.81) 8(36.36) 0.34 Frequency of tooth brushing （ % ） ≤1times/day 3(13.64) 8(47.06) 8(38.10) 16(72.73) ＜ 0.001 2times/day 19(86.36) 9(52.94) 13(61.90) 6(27.27) Brushing time （ % ） ≤1 minute 1(4.55) 3(17.65) 12(57.14) 9(40.91) ＜ 0.001 2 minutes 7(31.82) 7(41.18) 6(28.57) 11(50.00) ≥3 minutes 14(63.66) 7(41.18) 3(14.29) 2(9.09) Gingival bleeding （ % ） no 16(72.73) 9(52.94) 7(33.33) 15(68.18) 0.043 yes 6(27.27) 8(47.06) 14(66.67) 7(31.82) Professional dental cleaning （ % ） no 16(72.73) 12(70.59) 18(85.71) 22(100) 0.039 Once a year 5(22.73) 2(11.76) 3(14.29) 0 2-4years/times 0 1(5.89) 0 0 ≥5years/times 1(4.55) 2(11.76) 0 0 Toothache or sensitivity of tooth （ % ） no 20(90.91) 15(88.24) 17(80.95) 17(77.27) 0.768 yes 2(9.09) 2(11.76) 4(19.05) 5(22.73) HPV subtypes 16 – – 13(61.90) 12(54.55) – 18 – – 4(19.05) 6(27.27) 33 – – 1(4.76) 1(4.55) 51 – – 1(4.76) 1(4.55) 52 – – 1(4.76) 0 53 – – 1(4.76) 2(9.09) 58 – – 3(14.29) 5(22.73) BMI:body mass index; CRP: C-reactive protein ; WBC:White Blood Cell Count; RBC:Red Blood Count; HGB:hemoglobin; NEUT%:neutrophilic granulocyte percentage; LYM%:lymphocytes percentage; MONO%:monocytes percentage; EOS%:eosinophils percentage; BASO%:basophil percentage; PLT:Platelets. The P-value is calculated by ANOVA, Fisher exact probability test. There was no significant difference within the three groups regarding age, sexual age, smoking, drinking, and family history of CC for all the p ≥0.05. In the nation, level of education, the number of pregnancies, Number of abortions, Number of childbirths, and BMI was statistically significant and p value range (0.01-0.001). Systemic inflammation marker CRP and eosinophils percentage (EOS%) were higher in patients with HPV+ infection, neutrophilic granulocyte percentage (NEUT%) was higher in patients with CC as compare to their respective control. Dental caries and periodontal disease were not significantly different in groups. However, oral hygiene practices including brushing frequency and duration, gingival bleeding and professional cleaning showed significant differences. HPV genotypes distribution among infected groups revealed predominance of high-risk HPV16, 18 and 58 strains 56%, 23%, 19% respectively. Other high-risk HPV genotyping, including 33, 51, 52, 53, 68, and some patients were infected with multiple genotype HPV, accounting for 23.26% of infections (Table 1). 3.2 Composition and diversity of vaginal and oral microbiota Venn diagrams showed the highest unique OTU count in the CC vaginal microbiota, while control (Z) and abortion history groups harbored substantial overlap (Figure S1A). A total of 736 OTUs were shared among groups. Figure S1C shows the composition of bacteria greater than 0.1% at the genus level in vaginal specimen, the top ten bacteria species ranked by the relative abundance are shown on the bubble plot (Fig. 1A). Lactobacillus dominance was found among AB group (88.45%), controls (74.75%) and declined drastically in cancer samples (16.24%). Alpha diversity metrics including Shannon, Simpson and Chao1 indices significantly differed by vaginal microbiome richness and evenness (all p < 0.05) (Fig. 1B-D). We confirmed that the composition of vaginal microbiota gradually changed from control to HPV infection, and then to the occurrence of CC having highest alpha diversity ( p <0.05). The PCoA based on the weighted and unweighted unifrac analysis were conducted. According to the weighted unifrac, the first and second primary components accounted for 35.06% and 14.16%, while in the case of unweighted unifrac analysis, the first and second primary components were 14.49% and 5.85% (Fig. 1E-F). The community population distributions of four groups were found to be overlapped; however, the weighted and unweighted unifrac PERMANOVA suggested that the microbiota distribution varied significantly among the groups ( p =0.001, p =0.017). In the oral microbiota, there was no significant difference in the number of OTUs among the four groups (Fig. S1B), and a total of 1411 OTUs were overlapping. The number and species of oral microorganisms were significantly more than those of vaginal microorganisms (Fig. S1D). The top ten species accounting for oral microorganisms were Leptotrichia , Capnpcytophaga , Prevotella , Fusobacterium , Aggregatibacter , Selenomonas , Veillonella , Streptococcus , Treponema , Campylobacter (Fig. 2A). The KZZ and KCC groups showed the most significant differences at alpha diversity (for shannon index, simpson index, chao1 index, the values of p < 0.05 were noted) (Fig. 2B-D). The oral microbiome diversity was highest in the control group and lowest in the cancer group, in contrast to changes in the vaginal microbiome. Weighted and unweighted unifrac PERMANOVA also showed that the oral microbiota distribution varied significantly among the groups at beta diversity ( p =0.022, p =0.002) (Fig. 2E-F). 3.3 Identification of Z and CC patients based on cervical microbiota and oral microbiota Linear discriminant analysis (LDA) effect size (LEfSe) model was used to show biomarker in all groups such as Z, AB, HP and CC ( p 2) (Fig. S2A). With an LDA score >4, the most distinct vaginal biomarkers emerged (Fig. 3A, B). The CC group were enriched for genera including Mycoplasma , Bacillus , Bacteroides , Dialister , Peptoniphilus , Porphyromonas , Anaerococcus , Prevotella , Sneathia . Bifidobacteriales is biomarkers in HP group, while Lactobacillus predominated in AB group. Random forest classification and rank sum testing verified discriminatory species (top 30 and 20 bacterial species) (Fig. 3C-D). Lactobacillus was found to be the most important species to distinguish the four groups, along with some other genera, similar to the LEfSe results. After performing 10-fold cross-validation on random forest analysis between every two groups found that several important species, including Bacteroides , Hungatella , Lactobacillus , Ruminococcus , Moryella etc., is to distinguish between CC and control. The receiver operating characteristic (ROC) curve could effectively distinguish the CC group from the Z group (AUC=93.75%) (Fig. S2D). Pseudomonas levels differentiated between HPV+ and CC group with an area under the ROC curve of 87.5% (Fig. S2C, E). However, it was difficult to classify HPV-infected patients and control (AUC=64.29%) (Fig. S2F). Subgingival microbiome LDA and LEfSe markers varied inversely to the vaginal niche, with control (KZZ group) plaques harboring the most distinct taxa including Prevotella , Selenomonas , Saccharibacteria , Campylobacter , Amnipila , Centipeda ( p 2; Fig. S3A,B). The markers of the AB group were Pelospora and Filifactor , HPV infection group were Haemophilus , Gemmatimonadaceae . Monoglobus was the effective marker of subgingival plaque of cervical cancer patients, but the relative abundance was low in plaque microbiome. Combined with the previous diversity analysis, only two groups of KCC and KZ were compared (Fig. 4A, B), we screened bacteria with more than 10% composition and found that Capnocytophaga , Lautropia , Streptococcus , Lachnoanaerobaculum , Propionibacterium , F0332 , Prevotella , Lactobacillus , Neisseria , Parabacteroides , and Roseburi could become oral markers for cervical cancer patients. Combining random forest model analysis with 10-fold cross-validation to draw the ROC curve, and the AUC reached 89.06% (Fig. 4 C, D). The following bacteria, including Fusobacterium ， Campylobacter , Oribacterium , Selenomonas , Haemophilus , unclassified _ SR1_bacterium_human_oral_taxon_HOT_345 , Leptotrichia , Parvimonas , Phocaeicola , Capnocytophaga , Lautropia , Streptococcus , Lachnoanaerobaculum , Propionibacterium , F0332 , Prevotella , Lactobacillus , Neisseria , Parabacteroides , Roseburi , Fretibacterium , Peptostreptococcus , All o prevotella , Pseudopropionibacterium , and Saccharibacteria were further screened as marker biomarkers, and although the AUC decreased to 80.95%, it had a certain accuracy. 3.4 Association between microorganisms and environmental factors Co-occurrence networks displayed complexes of synergistically promoted microbes across vaginal and oral environment. The network shows the correlations between bacterial species common to both vaginal and oral microbiotas. The nodes represent bacterial species, and the edges (the lines connecting the nodes) illustrate the strength and type of correlation between these species. The node size likely corresponds to the abundance of the species, and the edge thickness might indicate the strength of the correlation (Fig. 5). The results showed that the presence of one species promote the growth of another, indicating a synergistic promotion effect. For example, Treponema and Selenomonas , Lautropia and Capnocytophaga , Lachnoanaerobaculum and Leptotrichia , Lautropia and Neisseria , Saccharibacteria and F0058 , Tannerella and Fusobacterium have co-occurrence network (Fig. 5A). The correlation between vaginal microbiota was also positive, such as Peptoniphilus and Dialister , Porphyromonas and Peptoniphilus , Porphyromonas and Dialister (Fig. 5B). However, it was negatively correlated between Fretibacterium and Capnocytophaga in oral microenviroment, and other bacteria relationship was positively correlated. In addition, Peptostreptococcus and Roseburia had cross nodes with multiple bacteria (Fig. 5C). We performed a Spearman analysis of these four groups to explore the correlation between the vaginal microbiome and demography, blood indices, oral diseases and oral hygiene practices. Vaginal Lactobacillus abundance negatively correlated with childbirths ( p =0.010) but positively associated with prevotella ( p =0.035) among the top ten species in vaginal abundance. BMI was positively correlated with Bacillus ( p =0.046), In vaginal microbiota, Lactobacillus show positive correlation to frequency of tooth brushing (FB) ( p =0.024) and inversely corelated to carries ( p =0.011). Similarly, Gardnerella showed positive relation to CRP ( p =0.040) and were negatively correlated to platelets (PLT) ( p =0.026), Brushing time (BT) ( p =0.005), and monocytes percentage (MONO) ( p =0.007). Sneathia was positive corelated to carries ( p =0.012) while negatively related to BT ( p =0.035), number of abortions (NB) ( p =0.048), periodontal ( p =0.039) disease were negatively related. The levels of lymphocytes percentage (LYM) have negative correlation with the presence of Mycoplasma ( p =0.031) (Fig. 6A). For oral microorganisms, CRP was positively associated with Capnocytophaga ( p =0.042) and negatively association with Selenomonas ( p= 0.003), prevotella ( p= 0.007), and Treponema ( p= 0.020). Childbirths positively correlated with Capnocytophaga ( p =0.027) , however negatively related Selenomonas ( p= 0.001), Fusobacterium ( p= 0.009), Treponema ( p= 0.025). Toothache or sensitivity of tooth (TOS) exhibited negative relation to Treponema ( p =0.035). The genera Camplylobacter ( p =0.015), Selenomonas ( p <0.001), also shown negative correlations to the number of pregnancies (NP). In addition, we observed a negative association of the caries with the genus Aggregatibacter ( p =0.010) and periodontitis has a positive association with the genus Campylobacter ( p =0.022). FB and BT showed significantly positive correlations with Selenomonas ( p =0.008), and Treponema respectively ( p =0.027) and professional dental cleaning (OP) with Fusobacterium ( p =0.045) (Fig. 6B). 3.5 Predictive Function Analysis Metagenomic functional potential based on 16S profiles revealed altered vaginal microbiome pathway activities differentiating CC from controls Z (Fig. 7). The level 2 KEGG pathway indicated that the microbial gene functions, namely global and overview maps, amino acid metabolism, metabolism of cofactors and vitamins, were higher in the CC group than Z group. Carbohydrate and nucleotide metabolism, translation, membrane transport, replication and repair were more prominent in Z group ( p <0.05) (Fig. 7A). In addition, microbial gene functions of KZ group had lower level in metabolism of other amino acids, aging, excretory system, infectious diseases when compared with the KCC group. In terms of cell motility, cell growth and death, endocrine and metabolic diseases, and immune system, the KZ group was higher than the KCC group ( p < 0.05) (Fig. 7B). In addition, the CC group showed over expression amino acid metabolism compared to the HP group and the AB group. The functional genes in metabolic pathways of cancer patients are still higher in global and overview maps, amino acid metabolism, metabolism of cofactors and vitamins, and the HP group is higher in global and overview maps, amino acid metabolism than the AB group (Fig. S4). This suggests that the presence of certain bacteria may play a role in the metabolic processes of cancer patients. There was a significant difference in oral microbial flora structure between the KCC group and the KZ group, while in comparison other groups found similar. However, due to the small sample size, these findings should be interpreted with caution. Discussions This study evaluated that vaginal and oral microbiota composition and changes in women with abortion, HPV infection to cervical cancer. In addition to the different vaginal microecological environments of the four groups, we determined that there are significant differences in the composition, abundance, diversity, marker genera, and functional pathways of oral microorganisms between cervical cancer patients and healthy people, which further proves that the vaginal and oral microbes are not independent entities, and there is flora transfer between different parts of the body, which may be associated with systemic metabolic [ 23 ]. To our knowledge, this is the first study to explore the oral microbiome’s role in patients with CC, improving the accuracy of CC screening process and broaden the scope of universal screening through insights gained from changes of oral microbiome. Our team previously reported meta-analysis and systematic review, found that sampled specimens studied for cervical cancer included cervix, vagina, rectum, feces, urine samples, without oral subgingival plaque (unpublished). In exploring vaginal microecological shifts, there is no significant difference in the microbial composition between the AB group and the control group, which is dominated by Lactobacillus [ 24 ]. The effect of recurrent abortion on vaginal flora is transient, regardless of cervical lesions[ 25 ]. As long as the surgery does not cause substantial damage to vaginal tissues, the equilibrium betweencommensal bacteria and opportunistic pathogens remains same. With the occurrence of HPV infection and cervical cancer, the species diversity increased, the proportion of lactobacillus gradually decreased, and the internal structure of the microbiome became more complex, similar to the previous studies findings [ 26 , 27 ]. Z group, AB group and HP group had a large overlap, which was significantly different from CC group at beta diversity. It was further confirmed that the depletion of Lactobacillus and the increase of specific anaerobes (such as Megasphaera , Prevotell and Gardnerella vaginalis ) were related to cervical lesions [ 25 ]. LEfSe analysis identified cancer-specific vaginal biomarkers including Mycoplasma , Bacillus , Bacteroides , Dialister , Peptoniphilus , Porphyromonas , Anaerococcus , Prevotella , Sneathia , and for HPV + biomarker is bifidobacterium distinct them from control, the reliability of experimental findings are confirmed by other studies [ 13 , 28 – 30 ]. Bifidobacterium is a beneficial microorganism of intestinal flora, which has many functions such as resisting harmful bacteria, providing nutrition, anti-tumor, anti-aging, enhancing immunity and improving gastrointestinal function, it also exists in the oral cavity and vagina [ 31 ]. This research found that Bifidobacterium species to distinguish whether cervical lesions, which is of great significance for the diagnosis of women's health. Bifidobacterium abundanc decreased, which is associated with high grade squamous intraepithelial lision (HSIL) [ 32 , 33 ]. Wang et al. found that the increased abundance of bifidobacterium in the vaginal microbiome may be related to the clearance of HR-HPV infection, focused ultrasound treatment (FU) may help to increase the abundance of Bifidobacterium [ 34 ], the possible reason is that Bifidobacterium can survive in acidic environment and produce lactic acid and hydrogen peroxide, has a protective effect on the vaginal environment [ 35 ]. Additionally, identified the shared periodontal pathogens Porphyromonas and Prevotella as cervical cancer biomarkers which may be the dynamic colonization of opportunistic bacterial pathogens on squamous epithelial cells in the oral or vaginal cavities and communication with the external environment. Oral pathogens can be transmitted from the gastrointestinal tract or through blood transmission to the vaginal cavity, it can also be transmitted through person-to-person oral-genital contact [ 36 ]. This suggests that oral and vagina share a common microbial community and there is also a reciprocal exchange of related microbial communities. The salivary microbiota of participants with bacterial vaginosis (BV) was more diverse than BV negative participants[ 37 ], Prevotella intermedia and Porphyromonas endodontalis were enriched in the subgingival gingival microbiota of BV women compared to women without BV, it indicates the presence of a vagino-oral axis [ 38 ]. At the same time, Porphyromonas and Prevotella has been proved to be carcinogenic potential of several different mechanisms. For example, Porphyromonas can maintain chronic periodontal infection, leading to increased expression of proinflammatory molecules such as IL-6, IL-8, IL-1β, and TNF-α and activation of Toll-like receptors (TLRs) and antiapoptotic pathways (JAK/STAT and MAPK pathways), decreased expression of proapoptotic proteins, increased cancer cell migration and invasion [ 39 ]. Gingipain proteases of Porphyromonas gingivalis activate NF-κB and MMP-9 in oral squamous cells, which are important for cancer cell invasion and metastasis [ 40 ]. Similarly, Prevotella produces virulence factors, fimbriae adhesins, lipopolysaccharides (LPS), peptidoglycan and lipoteichoic acid, which induce the release of pro-inflammatory cytokines [ 41 ], it also has the ability to stimulate tyrosine kinase receptors, degrade immunoglobulin and has toxic effects on fibroblasts, and coordinates with other pathogens to promote the migration and invasion of cancer cell [ 42 , 43 ]. Therefore, the pathogenic mechanisms of these periodontal pathogens are summarized as follows: they can stimulate chronic inflammation, inhibit cell apoptosis, activate cell proliferation and promote cell invasion resulting cancer [ 44 ]. Vaginal microbiome transformations along the cervical carcinogenesis route have been characterized, associated impacts on the oral niche remain underexplored. This study shows that the oral cavity contains a significantly greater number of bacterial species compared to the vagina, and also uncover extensive bidirectional sharing of microbial communities between vaginal and oral cavities through an emerging vagino-oral axis [ 38 ]. This provides insight into the shared one microbial community between the oral and vagina parts of the human body, as well as the exchange of related microbial communities. This study have shown that only patients with vaginal HPV infection and multiple abortion exhibit no obvious impact on their oral flora. However, the presence of cervical cancer can cause significant changes in the composition and abundance of oral microorganisms, leading to a lower diversity of oral microbiome compared to the normal population, which is contrary to the changes in vaginal microbiota. The periodontal pathogens in patients with cervical cancer was significantly increased, combined with ELfse and random forest analysis, Fusobacterium , Campylobacte , Capnocytophaga , Veillonella , Streptococcus , Lachnoanaerobaculum , Propionibacterium , Prevotella , Lactobacillus and Neisser were identified as oral bacterial markers for cervical cancer. The changes in these bacterial proportion can cause oral microflora dysbiosis and are also associated with all systemic diseases, including cancer [ 5 , 39 , 41 , 45 – 48 ]. It has been pointed out that different bacteria such as Fusobacterium nucleatum , periodonticum , Streptococcus salivarius , Porphyromonas , and different Lactobacillus subspecies are associated with the diagnosis of this kind of cancer. The periodontal pathogens Fusobacterium nucleatum , Campylobacter , Pseudomonas aeruginosa and Porphyromonas are considered "mobile microbiota" because they originate in the oral cavity but are also associated with extra-oral infections and inflammation [ 46 ]. Tumorigenesis mechanism associated with oral microbiome is various, mainly in: increase cell factors and inflammatory factors, lead to chronic inflammation and cell proliferation of metabolic pathways changes, pathogenic bacteria metabolites, suppress the immune response, induced tumor genetic damage, alter epithelial barrier and so on [ 48 – 50 ]. Most of the current research focuses on how the dysfunction of oral microorganisms affects the major organs and systems of the whole body. However, there is a bidirectional relationship between oral and general health, and how systemic diseases adversely affect oral microorganisms need more explored. In this study, a positive correlation was observed between vaginal and oral microorganisms, where certain bacteria exhibited connections with many others. Many studies have already found the synergistic effect of pathogenic microorganisms. Lo CH et al. found that Prevotella intermedia is enriched in CRC and enhances the migration and invasion of cancer cells, moreover, Prevotella intermedia and Fusobacterium nucleatum collectively contribute on the malignant transformation of colorectal adenoma into carcinoma [ 42 ]. Streptococcus gordonii , Fusobacterium nucleatum and Porphyromonas gingivalis synergistically promote the formation and proliferation of plaque biofilms, inhibit the growth of dendritic cells [ 51 ], and cause peripheral blood infection that is based on bacterial tyrosine (BY) kinase, (Ptk1), is an important part of the signaling pathway that controls the synergistic interaction between Porphyromonas gingivalis , and Streptococcus gordonii [ 52 ]. Colonization of vaginal epithelial Atopobium enhances virulence of Gardnerella , and biofilms formed by Gardnerella also dominate the other bacteria to colonize [ 53 ]. The interaction of a variety of microbial synergy mechanism is very complex, These mechanisms encompass not only metabolite cross-feeding, but also a large number of microbiota quorum-sensing signal result in enhancing resistance against the immune system, antibiotics, or direct contact between microorganisms to promote synergy [ 54 ]. Thus, the comprehensive impact of two or more microorganisms on disease is more severe impact than single, and the complex interaction network may enhance the pathogenicity of multi-microbial infections, ultimately affecting disease initiation and progression. It should be noted that these studies are based on different bacteria in the same site, while the composition of the vaginal microbiome is different from the oral microbiome, and more studies are needed to clarify the mechanisms of action of the microbiome at different sites. Systemic inflammation (such as cervical lesions and HPV infection) caused significant variation in CRP concentration across all the groups. The increase in the number of pregnancies, childbirth and abortions can easily have disturbed the vaginal microenvironment, the Lactobacillus abundance decreases, while the proportion of anaerobic bacteria Prevotella and Gardnerella increases. Severe systemic and local inflammations are closely related to the imbalance of vaginal microbiome [ 55 ]. Similarly, when oral hygiene was good and brushing frequency was high, the pathogenic microorganisms associated with periodontal disease, such as Selenomonas , prevotella , Treponema , and Aggregatibacter , were reduced. The reason is that oral microorganisms or their metabolites directly migrate through the blood or indirectly affect the inflammatory mediators produced in the oral [ 56 ]. Cervical cancer of microbial diversity changes consistent with the amino acid metabolism. It is well known that cancer cells grow rapidly, the metabolites are overexpressed and glycogen consumption to produce large amounts of energy and intermediate [ 57 ]. It has been verified by metabolomics and transcriptomics that the occurrence of cervical cancer is significantly related to metabolism, proteolysis or proteoglycan process pathway [ 58 ]. The higher the degree of cervical lesions, the consumption of lactic acid also gradually peaks, the metabolic characteristics turn to the increased consumption of glutamine after the development of CC, and these metabolite changes are negatively correlated with the abundance of Lactobacillus [ 59 ]. Studies in humans have shown that CC has distinct metabolic fingerprint in blood, tumor tissue, faeces, and urine [ 60 ]. However lacking metabolic maps in the oral cavity, and the PICRUST predictive analysis of this study adds some data. Cervical lesions also affect the oral microbial metabolites, the amino acid metabolism of oral bacterium in patients with CC is higher than control relating to the corresponding pathogenic microorganisms. Capnocytophaga grows in places with high glycogen consumption[ 61 ], Porphyromonas , Prevotella and Fusobacterium are closely related to the differences in metabolites. The pyrimidine metabolism is significantly increased in the patients with CC, which is positively correlated with the enrichment of periodontal disease[ 62 ]. The glutamate, histidine, and tyrosine metabolisms are also involved in the development of periodontitis. Cervical lesions lead to changes in the oral microenvironment, which may enhance the pathogenic effect of periodontal bacterium, induce the selective growth and reproduction of oral pathogens, produce more pathogenic microbiome, and even produce the "Warburg effect". Limitation As a case-control study, and we cannot conclude whether oral microbiome changes affect the vaginal microbiome, or whether changes in the vaginal microbiome affect the oral microenvironment after the onset of cervical lesions. Second, Cervical cancer patients were not tested for the presence of HPV virus in the oral cavity. It is generally believed that oral sex may be the link to transmission from vaginal to oral site [ 63 ], which causes viral infection of the oral mucosa and causes a dysbiosis. However, the overall risk of oral HPV infection in published studies was low, HPV transmission to the oropharynx by autoinoculation or oral-genital contact constitute a rare and unlikely event [ 64 ]. Therefore, it is more likely to believe that cervical lesions affect the oral microenvironment through retrograde flow. Third, considering the use of oral PICRUSt to predict microbiome function has some limitations, including the accuracy of functional prediction differences, should be hold cautious attitude to result. Fourth, the sample size of this study is small, the results of this study still need to be improved by expanding the sample quantity and cohort study in the future. Conclusions This study revealed that vaginal and oral microbiota composition and changes in women with abortion, HPV infection to cervical cancer. Decline lactobacillus dominancy and increasing microbiota diversity (such as Megasphaera , Prevotell and Gardnerella vaginalis ) were associated with progression from control through precancer to malignancy within the vaginal niche. HPV infection and CC not only have a certain impact on the vaginal microenvironment, but also effect the oral microenvironment through the synergistic mechanism on microbiome and systemic metabolism. The global and overview maps, as well as in amino acid metabolism, metabolism of cofactors and vitamins are highly expressed in CC exhibiting the fluctuation in the niche. This can lead to a decrease in oral microbial diversity and an increase in the composition of pathogenic microorganisms, increasing the risk of infections and cancer. In the future, it is expected to screen cervical cancer through oral flora markers. Declarations Author Contributions Z.W.: conceptualization, methodology, writing-original draft, and project administration. Y.Y.F.: methodology, software, investigation, writing. J.Y.S.: investigation, writing, analysis, visualization. Y.Y.Y.: software, investigation, writing. W.W.T.: analysis, visualization. W.X.Y.: analysis, visualization. L.B.: Writing-review & editing, Resources. Y.L.H.: conceptualization, Writing-review & editing, Resources. All authors have read and agreed to the published version of the manuscript. Funding This study was financially supported by the Health Industry Scientific Research Rrogram of Gansu Province, China (GSWSKY2021-026), Natural Science Foundation of Gansu Province, China (22JR5RA941 and 22JR5RA998), Project of the First Hospital of Lanzhou University (ldyyyn2022-49 and ZX-62000002-2021-225). Data Availability Statement The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi. nlm.nih.gov/sra/PRJNA1055682. Acknowledgments We acknowledge sequencing platform provided by Biomark Biotechnology Co., Ltd, the data were analyzed using the BMK Cloud Platform. Conflicts of Interest The authors declare no conflflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. References Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394424. https://doi.org/10.3322/caac.21492 . 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Venn diagrams illustrating the number of bacterial differentially expressed OTUs from four groups, (A) vagina specimen; (B) subgingival plaque specimen. (C) Relative abundance of the cervical microbiota at the genus level; (D) Relative abundance of the oral microbiota at the genus level. FigureS2.jpg Fig. S2. Taxonomic differences at vaginal microbiome. (A) Linear discriminative analysis (LDA) effect size (LEfSe) analysis among four groups. (B) 10-fold cross-validation on random forest analysis to distinguish between cervical cancer and normal groups of bacteria. (C) A random forest model to distinguish bacterial genera in patients with HPV infection and cervical cancer. Mean test prediction accuracy measured by the area under the ROC curve (AUC), (D) There was a high accuracy of distinguishment CC group (AUC=93.75%) from Z group, (E) it distinguished patients with HPV infection from cervical cancer with an area under the ROC curve of 87.5%, (F) and it was difficult to classify HPV-infected patients and healthy people (AUC=64.29%). FigureS3.jpg Fig. S3. Identification biomarker in oral microbiome. (A) LEfSe identifies bacterial clades that are differentially abundant within four groups. The threshold for the logarithmic LDA score was 2.0. (B) The signifcance taxa were tested by LEfSe analysis and showed using histogram. FigureS4.jpg Fig. S4. PICRUSt infers the cellular functions of bacterial communities in different groups. (A) AB group and CC group; (B) CC group and HP group; (C) AB group and HP group. Cite Share Download PDF Status: Published Journal Publication published 29 Apr, 2024 Read the published version in Journal of Translational Medicine → Version 1 posted Reviewers agreed at journal 22 Jan, 2024 Reviewers invited by journal 22 Jan, 2024 Editor assigned by journal 13 Jan, 2024 First submitted to journal 11 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About In Review Editorial Policies 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-3859830","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":268645499,"identity":"6172e1d2-d84e-43a5-a138-e3fedcb5b723","order_by":0,"name":"Wei Zhang","email":"","orcid":"","institution":"Lanzhou University Second Clinical Medical School: Lanzhou University Second Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Zhang","suffix":""},{"id":268645500,"identity":"fb216e9a-57b2-42a8-b950-742be51c2d4d","order_by":1,"name":"YanFei Yin","email":"","orcid":"","institution":"Lanzhou University Second Clinical Medical School: Lanzhou University Second Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"YanFei","middleName":"","lastName":"Yin","suffix":""},{"id":268645501,"identity":"97d681b5-32bf-46b7-9053-2577fc8e12ba","order_by":2,"name":"YiSha Jiang","email":"","orcid":"","institution":"Lanzhou University First Clinical Medical College: Lanzhou University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"YiSha","middleName":"","lastName":"Jiang","suffix":""},{"id":268645502,"identity":"51ee1d63-eef5-41f5-b9b0-4e9f852b1ba6","order_by":3,"name":"YangYang Yang","email":"","orcid":"","institution":"Lanzhou University First Clinical Medical College: Lanzhou University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"YangYang","middleName":"","lastName":"Yang","suffix":""},{"id":268645503,"identity":"9d684039-d704-47ba-8acd-5ee0eb562d4f","order_by":4,"name":"WenTao Wang","email":"","orcid":"","institution":"Lanzhou University First Clinical Medical College: Lanzhou University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"WenTao","middleName":"","lastName":"Wang","suffix":""},{"id":268645504,"identity":"5d52fba4-f392-4c9d-ba3e-ba4d7ede112e","order_by":5,"name":"XiaoYa Wang","email":"","orcid":"","institution":"Lanzhou University Stomatology Hospital: Lanzhou University School of Stomatology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"XiaoYa","middleName":"","lastName":"Wang","suffix":""},{"id":268645505,"identity":"08116346-458a-44e4-9b0e-29b54cd71d98","order_by":6,"name":"Yan Ge","email":"","orcid":"","institution":"Lanzhou University First Clinical Medical College: Lanzhou University First Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Ge","suffix":""},{"id":268645506,"identity":"814311c8-aa07-455a-8ef3-ae03b78e0de2","order_by":7,"name":"Bin Liu","email":"","orcid":"","institution":"Lanzhou University Stomatology Hospital: Lanzhou University School of Stomatology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Liu","suffix":""},{"id":268645507,"identity":"c05f3ab0-696a-4323-8be4-927e123b49f7","order_by":8,"name":"Lihe Yao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIie3RvQrCMBDA8SuBm4JdTxTrI0QE8XFShE4VHDuICkod/FoVxGdwdFSETtHZseLqoJujVUfF1M0hv/n+XD4ADOMPod3dxpcbtUPntIll0NQnGYq80mxYtcbg1USsIn1SAL+Y4xhYC/Ar2WOPpTgYKChzTgxhXQncDoLdH8jvCRutj/MqIVod7+Cu8kBqt9Rs2Utx5sSRQXRwFYKgui7xRTJPjzVhww1ZuiSbJAJ5cp10yeuRSSIhI6kirr2LM3l+ZUs6U/t6vQXNgt0ffU/e8N/GDcMwjI/uZ11EKC2luq8AAAAASUVORK5CYII=","orcid":"https://orcid.org/0009-0004-0256-0316","institution":"Lanzhou University First Affiliated Hospital: Lanzhou University First Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Lihe","middleName":"","lastName":"Yao","suffix":""}],"badges":[],"createdAt":"2024-01-13 10:38:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3859830/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3859830/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12967-024-05124-8","type":"published","date":"2024-04-29T23:32:40+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":50122344,"identity":"1b496307-72b8-49c9-8c31-51a6c6e8654f","added_by":"auto","created_at":"2024-01-24 19:57:54","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":796313,"visible":true,"origin":"","legend":"\u003cp\u003eCommunity compositions and diversity at the genus level of vaginal microbes. (\u003cstrong\u003eA\u003c/strong\u003e) Bubble diagram of relative abundance of top ten genus of each group, the size of the dots represents the species proportion. Microbiota Alpha diversity; (\u003cstrong\u003eB\u003c/strong\u003e) Shannon index; (\u003cstrong\u003eC\u003c/strong\u003e) Simpson index; (D) Chao 1 index. Principal coordinate analysis (PCoA) derived from weighted (\u003cstrong\u003eE\u003c/strong\u003e) and unweighted (\u003cstrong\u003eF\u003c/strong\u003e) UniFrac distances among the samples of the four groups. Every group is represented by diferent colors.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/b15045801bbd76c317ed2967.jpg"},{"id":50123156,"identity":"0e6d6900-f92f-417e-a4d9-01f1eb0adda0","added_by":"auto","created_at":"2024-01-24 20:21:54","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":803471,"visible":true,"origin":"","legend":"\u003cp\u003eCommunity compositions and diversity at the genus level of oral microbes. (\u003cstrong\u003eA\u003c/strong\u003e) Bubble diagram of relative abundance of top ten genus of each group, the size of the dots represents the species proportion. Microbiota Alpha diversity; (\u003cstrong\u003eB\u003c/strong\u003e) Shannon index; (\u003cstrong\u003eC\u003c/strong\u003e) Simpson index; (\u003cstrong\u003eD\u003c/strong\u003e) Chao 1 index. Principal coordinate analysis (PCoA) derived from weighted (\u003cstrong\u003eE\u003c/strong\u003e) and unweighted (\u003cstrong\u003eF\u003c/strong\u003e) UniFrac distances among the samples of the four groups. Every group is represented by diferent colors.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/42e8b64dc8ef0ccada9a086b.jpg"},{"id":50122349,"identity":"a3a52de3-9543-4793-96c5-086ce36ee36e","added_by":"auto","created_at":"2024-01-24 19:57:54","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2130773,"visible":true,"origin":"","legend":"\u003cp\u003eIdentification biomarker in vaginal microbiome. Linear discriminant analysis (LDA) effect size (LEfSe) analysis among four groups. Clades in this graph were both statistically significant (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) and had an LDA score＞4, considered a significant effect size. (\u003cstrong\u003eA\u003c/strong\u003e) Shows the representative genera; (\u003cstrong\u003eB\u003c/strong\u003e) Cladogram of tax associated with four groups. (\u003cstrong\u003eC\u003c/strong\u003e) Random forest analysiswas used to screen the top 30 significant bacterial to distinguish CC, HP, AB groups and Z group; (\u003cstrong\u003eD\u003c/strong\u003e) Rank sum test screened the top 20 differential bacteria among four groups.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/7cfcf881c295170dfeaa5726.jpg"},{"id":50122350,"identity":"5b5150e4-bf5c-43be-9825-a3ad136eaf57","added_by":"auto","created_at":"2024-01-24 19:57:54","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2105970,"visible":true,"origin":"","legend":"\u003cp\u003eOral biomarkers in patients with cervical cancer. (\u003cstrong\u003eA\u003c/strong\u003e) Shows the representative genera for KCC and KZ; (\u003cstrong\u003eB\u003c/strong\u003e) The signifcance taxa were tested by LEfSe analysis and showed using histogram. The threshold for the logarithmic LDA score was 2.0. (\u003cstrong\u003eC\u003c/strong\u003e) Random forest analysis with 10-fold cross-validation was used to screen the different bacterial genera in the oral cavity of patients with cervical cancer. (\u003cstrong\u003eD\u003c/strong\u003e) Mean test prediction accuracy measured by the area under the ROC curve (AUC); (\u003cstrong\u003eE\u003c/strong\u003e) the receiver operating characteristic curves were calculated by combining LEfSe analysis and random forest analyses using the 25 genus-level signficant bacterium segregate cancer patients from controls.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/a483c11b51c4972c5186d966.jpg"},{"id":50122937,"identity":"f5889fcf-738d-471f-a5a3-51efda8706cf","added_by":"auto","created_at":"2024-01-24 20:13:54","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":305483,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between bacteria. (\u003cstrong\u003eA\u003c/strong\u003e) Correlation network between different species in the vagina and oral. (\u003cstrong\u003eB\u003c/strong\u003e) The correlation at vaginal microbiota; (\u003cstrong\u003eC\u003c/strong\u003e) The correlation at oral microbiota.\u003c/p\u003e","description":"","filename":"Figure5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/e4e36a4812396af779a8bca2.jpg"},{"id":50122784,"identity":"ea1f23b6-8a00-4711-90b0-eb525c16f828","added_by":"auto","created_at":"2024-01-24 20:05:54","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1260438,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between microbiota species, demographic information, blood indices, oral disease and oral hygiene habits. (\u003cstrong\u003eA\u003c/strong\u003e) vaginal microbial community. (\u003cstrong\u003eB\u003c/strong\u003e) oral microbial community. Spearman rank correlation coefficient is indicated using a color gradient, as follows: red indicates a positive correlation and blue indicates a negative correlation. *, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05; **, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; and ***, \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001. SA, Sexual age; BMI, body mass index; NC, Number of childbirths; NP, Number of pregnancies; BASO, basophil percentage; NEUT, neutrophilic granulocyte percentage; EOS, eosinophils percentage; MONO, monocytes percentage; CRP, C-reactive protein; LYM, lymphocytes percentage; PLT, Platelets; WBC, White Blood Cell Count; RBC, Red Blood Count; NB, Number of abortions; HGB, hemoglobin; GB, Gingival bleeding; FB, Frequency of tooth brushing; Period, Periodontitis; Caries, Caries; OP, Professional dental cleaning; BT, Brushing time; TOS, Toothache or sensitivity of tooth.\u003c/p\u003e","description":"","filename":"Figure6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/85aec43c7baab65a41099919.jpg"},{"id":50122346,"identity":"7b5af879-09df-42e6-85b0-cff01100e847","added_by":"auto","created_at":"2024-01-24 19:57:54","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":713044,"visible":true,"origin":"","legend":"\u003cp\u003ePredicted functions of the bacterial communities at the second level in different group. The middle shows the difference ratio of the function abundance within the 95% confidence interval, and the rightmost value is the p value. (\u003cstrong\u003eA\u003c/strong\u003e) KEGG pathway difference between CC group and Z group; (\u003cstrong\u003eB\u003c/strong\u003e) KEGG pathway difference between KCC group and Z group.\u003c/p\u003e","description":"","filename":"Figure7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/f4efc4a1ac61f40056ba3a0e.jpg"},{"id":55696509,"identity":"c8d72644-be48-4e7d-872f-a93db77c41c2","added_by":"auto","created_at":"2024-05-02 01:43:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1655821,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/a7c042d5-4bc3-4ae1-bf7d-cebcb5c724f7.pdf"},{"id":50122781,"identity":"28da29e8-9ffe-47b6-8c17-0e39f5d0480a","added_by":"auto","created_at":"2024-01-24 20:05:54","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1273989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S1\u003c/strong\u003e. Microbial composition. Venn diagrams illustrating the number of bacterial differentially expressed OTUs from four groups, (\u003cstrong\u003eA\u003c/strong\u003e) vagina specimen; (\u003cstrong\u003eB\u003c/strong\u003e) subgingival plaque specimen. (\u003cstrong\u003eC\u003c/strong\u003e) Relative abundance of the cervical microbiota at the genus level; (\u003cstrong\u003eD\u003c/strong\u003e) Relative abundance of the oral microbiota at the genus level.\u003c/p\u003e","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/b04c7a64846f185dd01f5a22.jpg"},{"id":50122935,"identity":"12fb04b4-34b7-4fbc-918c-beaf8cada214","added_by":"auto","created_at":"2024-01-24 20:13:54","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1919264,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S2.\u003c/strong\u003e Taxonomic differences at vaginal microbiome. (\u003cstrong\u003eA\u003c/strong\u003e) Linear discriminative analysis (LDA) effect size (LEfSe) analysis among four groups. (\u003cstrong\u003eB\u003c/strong\u003e) 10-fold cross-validation on random forest analysis to distinguish between cervical cancer and normal groups of bacteria. (\u003cstrong\u003eC\u003c/strong\u003e) A random forest model to distinguish bacterial genera in patients with HPV infection and cervical cancer. Mean test prediction accuracy measured by the area under the ROC curve (AUC), (\u003cstrong\u003eD\u003c/strong\u003e) There was a high accuracy of distinguishment CC group (AUC=93.75%) from Z group, (\u003cstrong\u003eE\u003c/strong\u003e) it distinguished patients with HPV infection from cervical cancer with an area under the ROC curve of 87.5%, (\u003cstrong\u003eF\u003c/strong\u003e) and it was difficult to classify HPV-infected patients and healthy people (AUC=64.29%).\u003c/p\u003e","description":"","filename":"FigureS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/7c30c18aec345bff2f11b158.jpg"},{"id":50122352,"identity":"61125505-c8a9-4f23-a0d8-02a720b46a42","added_by":"auto","created_at":"2024-01-24 19:57:54","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1157588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S3. \u003c/strong\u003eIdentification biomarker in oral microbiome. (\u003cstrong\u003eA\u003c/strong\u003e) LEfSe identifies bacterial clades that are differentially abundant within four groups. The threshold for the logarithmic LDA score was 2.0. (\u003cstrong\u003eB\u003c/strong\u003e) The signifcance taxa were tested by LEfSe analysis and showed using histogram.\u003c/p\u003e","description":"","filename":"FigureS3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/cb6c35493f2d1daef8495af1.jpg"},{"id":50122785,"identity":"c31be036-f9a0-4532-84dd-8be3aba11429","added_by":"auto","created_at":"2024-01-24 20:05:54","extension":"jpg","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":427257,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFig. S4. \u003c/strong\u003ePICRUSt infers the cellular functions of bacterial communities in different groups. (\u003cstrong\u003eA\u003c/strong\u003e) AB group and CC group; (\u003cstrong\u003eB\u003c/strong\u003e) CC group and HP group; (\u003cstrong\u003eC\u003c/strong\u003e) AB group and HP group.\u003c/p\u003e","description":"","filename":"FigureS4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3859830/v1/5aeef6c5bdefb3530a512936.jpg"}],"financialInterests":"","formattedTitle":"Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCervical cancer (CC) ranks as the fourth most frequently diagnosed cancer and the third leading cause of cancers death in the women globally. With more than half million CC cases are annually linked to (human papillomavirus) HPV infection, resulting in 250,000 deaths for per year [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. HPV infection is recognized as one of the major causes of CC, as well as other malignancies including anogenital tumors, anal, vulvar, penile, vaginal and oral cancers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Recent studies suggest that 90% of oral squamous cell carcinoma are driven by the infection with HPV [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOral cavity is a natural open system, pool of complex microbiome, comprising over 800 bacterial species inhabiting [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This oral microbiota have been implicated not only in periodontal disease but also in systemic conditions including hematological diseases, lymphatic, lung, pancreatic and breast cancers [\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eChanges in oral microbiome composition are now recognized as potential biomarkers for cancers including colorectal cancer (CRC) marked by increased, \u003cem\u003eF. nucleatum\u003c/em\u003e abundance [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Similarly, shifts favoring oral pathogens such as \u003cem\u003ePorphyromonas\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e genera have been correlated with CC although mechanisms remain poorly known [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], these oral pathogens also cause the periodontal disease [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Previous studies have shown that correlation between vaginal bacteria and gingival inflammation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], HPV not only invades the basal cells of the vaginal epithelium, but also infects the periodontal tissue and keeps the virus in a latent state [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The oral and vaginal environment may provide similar colonization and growth conditions, resulting a significantly increases the risk of periodontal disease and cancer [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, there is relatively little literature exists on changes in the oral microbiome when the vaginal microbiota is transformed during the course of HPV infection to CC, suggesting that more research is needed in this area.\u003c/p\u003e \u003cp\u003ePopulation-based CC screening is implemented as a public health priority in China [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and the best strategy is Liquid-based cytology test technique (TCT) combined with HPV screening [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The combined screening technology, although advanced and effective, is costly, suitable for areas with adequate medical and health care. However, there are still many economically less-developed areas (rural areas) in China, it is urgent to find a good quality and cheap method. Changes in oral microbial diversity detectable through low-cost profiling may offer additional value as biomarkers for early screening, diagnosis and monitoring of HPV infection and even CC. This study aims to evaluate the difference and associations between vaginal and oral microorganisms in HPV infection and CC patients. Enhanced understanding of microbial ecology may contribute to the development of accuracy of cervical cancer screening and extend life-saving interventions to vulnerable groups.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study design and specimen collection.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Ethics Committee of Second Hospital of Lanzhou University (approval no. 2022A-533). All methods were conducted in accordance with the Declaration of Helsinki and relevant guidelines and regulations. Participants were recruited during October 2022 to October 2023 at gynecology outpatient and inpatient departments.\u003c/p\u003e\n\u003cp\u003eInclusion criteria: 1) \u0026nbsp;age 20-76 years; sexually active; 2) no vaginal irrigation or antibiotic treatment for \u0026ge;1 week before the examination and no sexual intercourse within 3 days; 3) regular menstrual cycles; 4) there is no history of cervical surgery and hysterectomy, no diseases seriously affected by other systems; 5) HPV infection positive by \u0026nbsp;diagnostic testing; 6) cervical cancer was confirmed by biopsy tissue histopathological examination; 7) abortion was performed by surgical method and the number of abortions was \u0026ge; 3. Exclusion criteria: 1) menstrual women; 2) vaginal bleeding; 3) patients with intrauterine device; 4) pregnant and lactating women; 5) patients undergoing radiation and chemotherapy; 6) prior medical/ spontaneous abortion. HPV genotype test and TCT were negative in both the control and abortion groups, HPV groups was positive for HPV genotype test and the TCT was normal.\u003c/p\u003e\n\u003cp\u003eAll participants completed a clinical questionnaire, oral examination results were recorded, specimen and blood collection was completed. Caries were diagnosed using the International Caries Detection and Assessment System (ICDAS)\u0026nbsp;[21], diagnostic criteria\u0026nbsp;[22]\u0026nbsp;Periodontitis defined as \u0026ge;4 teeth with \u0026ge;1 site having probing depth \u0026ge;4mm, clinical attachment loss \u0026ge;1mm and bleeding on probing. Subgingival plaque: subjects cannot eat, drink, smoking or chewing gum, and washed the debris in their mouth with drinking water before 30 minutes. The sterile dental scaler penetrates into the tongue side of the mandibular first molar below the gum to remove dental plaque and prevent blood contamination during the collection process. Vaginal secretion: disposable speculum was inserted, and a sterile swab sample was taken from the posterior vaginal fornix. All specimen stored immediately under \u0026minus;80 \u0026deg;C for DNA extraction. Blood indicators and C-reactive protein (CRP) were analyzed using the automated blood analyzer system (SysmexXN-20; Kobe, Japan).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eThe Full-Length 16S Sequencing and data processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBacterial genomic DNA was extracted from vaginal and subgingival samples using the TGuide S96 Magnetic Universal DNA Kit (Tiangen Biotech (Beijing) Co., Ltd.) according to manufacturer\u0026rsquo;s instructions. The full-length 16S rRNA gene were amplified with primer pairs 27F: AGRGTTTGATYNTGGCTCAG and 1492R: TASGGHTACCTTGTTASGACTT. Both the forward and reverse 16S primers were tailed with sample-specific PacBio barcode sequences to allow for multiplexed sequencing. After the individual quantification step, amplicons were pooled in equal amounts. SMRTbell libraries were prepared from the amplified DNA by SMRTbell Express Template Prep Kit 2.0 according to the manufacturer\u0026rsquo;s instructions (Pacific Biosciences). Purified SMRTbell libraries from the pooled and barcoded samples were sequenced on a PacBio Sequel II platform (Beijing Biomarker Technologies Co., Ltd., Beijing, China) using Sequel II binding kit 2.0. The raw subreads correction by Circular Consensus Sequencing (CCS) (SMRT Link, version8.0), then use the Lima software (v1.7.0) and identify different samples of CCS by barcod. Cutadapt software (1.9.1) is used to identify the primer sequences with removal and the length of the filter, and identification and removal of chimeric sequences by UCHIME (version 8.1). A high-quality CCS sequence was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic and oral data, blood indices and were compared between groups using SPSS 27.0 (IBM, Chicago, Illinois, USA). Comparisons between groups were made by ANOVA test, fisher\u0026apos;s precision probability test and chi-squared test. The online platform BMKCloud (https://www.biocloud.net) was used to analyze the sequencing data. R (v3.2.0) was used to draw Venn and bubble diagram, correlation analysis. Alpha was performed to identify the complexity of species diversity of each sample utilizing QIIME2 software. Beta diversity among the samples was evaluated by principal coordinate analysis (PCoA) to assess the diversity in samples for species complexity. One-way analysis of variance was used to compare bacterial abundance and diversity. Linear discriminant analysis (LDA) coupled with effect size (LEfSe) was applied to evaluate the differentially abundant taxa. An LDA score of \u0026gt;2 was considered as the cut-of value for biomarker screening, and the differences between groups were assessed by the rank sum test. At the genus level, a threshold p-value of \u0026lt;0.05 and SparCC were used for constructing a correlation plot. Random forest analysis was performed to compare the microbiome characteristics, area under receiver operative characteristic curve (AUC) were assessed to evaluate the performance of the random forest analysis. Statistical comparison of AUCs was performed using pROC package in R. The picrust2 was used for Kyoto Encyclopedia of Genes and Genomes (KEGG) function prediction.\u0026nbsp;\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Characteristics of subjects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants included 82 cases of women, and 164 samples from vagina and gingiva were sequenced. They were divided into four groups: vaginal and oral subgingival plaque control group (Z/KZ, n=22), abortion group (AB/KAB, n=17), HPV group (HP/KHP, n=21) and cervical cancer group (CC/KCC, n=22). Demography, clinical, oral health parameters are shown in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eTable1. Demographic information, blood indices, oral characteristics and different HPV distribution of participants.\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable style=\"border: none;width:702.6pt;border-collapse:collapse;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width:2.3in;border-top:solid black 1.0pt;border-left:none;border-bottom:solid black 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:17.1pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:81.3pt;border:none;border-top:solid black 1.0pt;padding:0in 5.4pt 0in 5.4pt;height:17.1pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:91.9pt;border:none;border-top:solid black 1.0pt;padding:0in 5.4pt 0in 5.4pt;height:17.1pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eNormal\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:78.6pt;border:none;border-top:solid black 1.0pt;padding:0in 5.4pt 0in 5.4pt;height:17.1pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eAbortion\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:101.25pt;border:none;border-top:solid black 1.0pt;padding:0in 5.4pt 0in 5.4pt;height:17.1pt;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eHPV\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;border-right: none;border-bottom: none;border-left: none;border-image: initial;border-top: 1pt solid black;padding: 0in 5.4pt;height: 17.1pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eCancer\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width:93.45pt;border-top:solid black 1.0pt;border-left:none;border-bottom:solid black 1.0pt;border-right:none;padding:0in 5.4pt 0in 5.4pt;height:17.1pt;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eP value\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"border:none;border-bottom:solid black 1.0pt;padding:0in 5.4pt 0in 5.4pt;height:16.35pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:91.9pt;border:none;border-bottom:solid black 1.0pt;padding:0in 5.4pt 0in 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style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e(n=21)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid black;padding: 0in 5.4pt;height: 16.35pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e(n=22)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eAge\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eyear\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e44.68\u0026plusmn;8.54\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e43.12\u0026plusmn;7.67\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e45.76\u0026plusmn;11.02\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e48.05\u0026plusmn;8.99\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.395\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eNation\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003eHan nationality\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e22(100)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e17(100)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e21(100)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n 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style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003eother nationalist\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0(0)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0(0)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0(0)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e5(22.73)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eLevel of education\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003eprimary school\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1(4.55)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e6(35.29)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e13(61.90)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e19(86.36)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:15px;font-family: SimSun;color:red;\"\u003e＜\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.001\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003ehigh school\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e8(36.36)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e6(35.29)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(14.29)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2(9.09)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003ecollege degree\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e13(59.09)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e5(29.41)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e5(23.81)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1(4.55)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eNumber of pregnancies\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.87\u0026plusmn;0.94\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e4.82\u0026plusmn;1.13\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2.48\u0026plusmn;1.50\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3.14\u0026plusmn;1.61\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 16pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:15px;font-family: SimSun;color:red;\"\u003e＜\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.01\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eNumber of abortions\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.32\u0026plusmn;0.48\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3.29\u0026plusmn;0.59\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.62\u0026plusmn;0.74\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.59\u0026plusmn;0.85\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:15px;font-family: SimSun;color:red;\"\u003e＜\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.01\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eNumber of childbirths\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.55\u0026plusmn;0.74\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1.53\u0026plusmn;0.94\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1.86\u0026plusmn;1.28\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2.55\u0026plusmn;1.34\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:15px;font-family: SimSun;color:red;\"\u003e＜\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.01\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eSexual age (year)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e21.18\u0026plusmn;2.70\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e21.59\u0026plusmn;3.47\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e21.81\u0026plusmn;3.82\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e20.45\u0026plusmn;3.10\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.556\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eBMI (kg/m2)\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e20.60\u0026plusmn;1.90\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e23.61\u0026plusmn;4.98\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e22.31\u0026plusmn;3.03\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e23.63\u0026plusmn;3.89\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.02\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eSmoking\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e9.09\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e17.65\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.059\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eDrinking\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e4\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e18.19\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e6\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e35.30\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 101.25pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e14.29\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90.5pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e4\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e18.19\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.481\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 2.3in;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eFamily history of CC\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e%\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 91.9pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e4.54\u003c/span\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 78.6pt;padding: 0in 5.4pt;height: 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Roman\",serif;color:black;'\u003ePeriodontitis\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e%\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(13.64)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(17.65)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e5(23.81)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e8(36.36)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93.45pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0.34\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:31.2pt;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eFrequency of tooth brushing\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family: SimSun;color:black;\"\u003e（\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e%\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 31.2pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026le;1times/day\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 31.2pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(13.64)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 31.2pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e8(47.06)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 31.2pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e8(38.10)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 31.2pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e16(72.73)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 31.2pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:red;\"\u003e＜\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.001\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:15.6pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2times/day\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e19(86.36)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e9(52.94)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e13(61.90)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e6(27.27)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:15.6pt;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eBrushing time\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e%\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026le;1 minute\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1(4.55)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(17.65)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e12(57.14)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e9(40.91)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:15px;font-family:SimSun;color:red;\"\u003e＜\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.001\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:15.6pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2 minutes\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e7(31.82)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e7(41.18)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e6(28.57)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e11(50.00)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:15.6pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026ge;3 minutes\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e14(63.66)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e7(41.18)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(14.29)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e2(9.09)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New 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15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003eno\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e16(72.73)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e9(52.94)\u003c/span\u003e\u003c/p\u003e\n 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style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.043\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:15.6pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003eyes\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: 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style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003eProfessional dental cleaning\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:middle;'\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e（\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e%\u003c/span\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cspan style=\"font-size:16px;font-family:SimSun;color:black;\"\u003e）\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;padding: 0in 5.4pt;height: 15.6pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New 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style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e18(85.71)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e22(100)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:left;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cstrong\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:red;'\u003e0.039\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n 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style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 13.8pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width:2.3in;padding:0in 5.4pt 0in 5.4pt;height:15.6pt;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size:16px;font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/strong\u003e\u003c/p\u003e\n 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style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e1(5.89)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e0\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"padding: 0in 5.4pt;height: 15.6pt;vertical-align: bottom;\"\u003e\n \u003cp 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bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81.3pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 13.8pt;vertical-align: top;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:top;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e58\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 13.8pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"font-size:13px;font-family:SimSun;color:black;\"\u003e\u0026ndash;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 13.8pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"font-size:13px;font-family:SimSun;color:black;\"\u003e\u0026ndash;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 13.8pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e3(14.29)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 13.8pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:center;font-size:14px;font-family:\"Calibri\",sans-serif;vertical-align:bottom;'\u003e\u003cspan style='font-size:15px;font-family:\"Times New Roman\",serif;color:black;'\u003e5(22.73)\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;padding: 0in 5.4pt;height: 13.8pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Arial\",sans-serif;color:black;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-size:13px;font-family:\"Cambria\",serif;color:#333333;background:#FFFCF0;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eBMI:body mass index; CRP:\u003c/span\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eC-reactive protein\u003c/span\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003e;\u003c/span\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003e\u0026nbsp;WBC:White Blood Cell Count; RBC:Red Blood Count; HGB:hemoglobin; NEUT%:neutrophilic granulocyte percentage; LYM%:lymphocytes percentage; MONO%:monocytes percentage; EOS%:eosinophils percentage; BASO%:basophil percentage; PLT:Platelets.\u003c/span\u003e\u003c/p\u003e\n\u003cp style='margin:0in;text-align:justify;font-size:14px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style='font-family:\"Times New Roman\",serif;color:black;'\u003eThe P-value is calculated by ANOVA, Fisher exact probability test.\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThere was no significant difference within the three groups regarding age, sexual age, smoking, drinking, and family history of CC for all the \u003cem\u003ep\u003c/em\u003e\u0026ge;0.05. In the nation, level of education, the number of pregnancies, Number of abortions, Number of childbirths, and BMI was statistically significant and \u003cem\u003ep\u003c/em\u003e value range (0.01-0.001). Systemic inflammation marker CRP and eosinophils percentage (EOS%) were higher in patients with HPV+ infection, neutrophilic granulocyte percentage (NEUT%) was higher in patients with CC as compare to their respective control. Dental caries and periodontal disease were not significantly different in groups. However, oral hygiene practices including brushing frequency and duration, gingival bleeding and professional cleaning showed significant differences. HPV genotypes distribution among infected groups revealed predominance of high-risk HPV16, 18 and 58 strains 56%, 23%, 19% respectively. Other high-risk HPV genotyping, including 33, 51, 52, 53, 68, and some patients were infected with multiple genotype HPV, accounting for 23.26% of infections (Table 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eComposition and diversity of vaginal and oral microbiota\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVenn diagrams showed the highest unique OTU count in the CC vaginal microbiota, while control (Z) and abortion history groups harbored substantial overlap (Figure S1A). A total of 736 OTUs were shared among groups. Figure S1C shows the composition of bacteria greater than 0.1% at the genus level in vaginal specimen, the top ten bacteria species ranked\u0026nbsp;by\u0026nbsp;the relative\u0026nbsp;abundance\u0026nbsp;are shown on the bubble plot (Fig. 1A).\u0026nbsp;\u003cem\u003eLactobacillus\u003c/em\u003e dominance was found among AB group (88.45%), controls (74.75%) and declined drastically in cancer samples (16.24%). Alpha diversity metrics including Shannon, Simpson and Chao1 indices significantly differed by vaginal microbiome richness and evenness (all \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05) (Fig. 1B-D). We confirmed that the composition of vaginal microbiota gradually changed from control to HPV infection, and then to the occurrence of CC having highest alpha diversity (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05). The PCoA based on the weighted and unweighted unifrac analysis were conducted. According to the weighted unifrac, the first and second primary components accounted for 35.06% and 14.16%, while in the case of unweighted unifrac analysis, the first and second primary components were 14.49% and 5.85% (Fig. 1E-F). The community population distributions of four groups were found to be overlapped; however, the weighted and unweighted unifrac PERMANOVA suggested that the microbiota distribution varied significantly among the groups (\u003cem\u003ep\u003c/em\u003e=0.001, \u003cem\u003ep\u003c/em\u003e=0.017).\u003c/p\u003e\n\u003cp\u003eIn the oral microbiota, there was no significant difference in the number of OTUs among the four groups (Fig. S1B), and a total of 1411 OTUs were overlapping. The number and species of oral microorganisms were significantly more than those of vaginal microorganisms (Fig. S1D).\u0026nbsp;The top\u0026nbsp;ten\u0026nbsp;species\u0026nbsp;accounting for oral microorganisms were \u003cem\u003eLeptotrichia\u003c/em\u003e, \u003cem\u003eCapnpcytophaga\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eFusobacterium\u003c/em\u003e, \u003cem\u003eAggregatibacter\u003c/em\u003e, \u003cem\u003eSelenomonas\u003c/em\u003e, \u003cem\u003eVeillonella\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eTreponema\u003c/em\u003e, \u003cem\u003eCampylobacter\u0026nbsp;\u003c/em\u003e(Fig. 2A). The KZZ and KCC groups showed the most significant differences at alpha diversity (for shannon index, simpson index, chao1 index, the values of \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; 0.05 were noted) (Fig. 2B-D). The oral microbiome diversity was highest in the control group and lowest in the cancer group, in contrast to changes in the vaginal microbiome. Weighted and unweighted unifrac PERMANOVA also showed that the oral microbiota distribution varied significantly among the groups at beta diversity (\u003cem\u003ep\u003c/em\u003e=0.022, \u003cem\u003ep\u003c/em\u003e=0.002) (Fig. 2E-F).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Identification of Z and CC patients based on cervical microbiota and oral microbiota\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLinear discriminant analysis (LDA) effect size (LEfSe) model was used to show biomarker in all groups such as Z, AB, HP and CC (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, LDA \u0026gt; 2) (Fig. S2A). With an LDA score \u0026gt;4, the most distinct vaginal biomarkers emerged (Fig. 3A, B). The CC group were enriched for genera including \u003cem\u003eMycoplasma\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eDialister\u003c/em\u003e, \u003cem\u003ePeptoniphilus\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e, \u003cem\u003eAnaerococcus\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eSneathia\u003c/em\u003e. \u003cem\u003eBifidobacteriales\u003c/em\u003e is biomarkers in HP group, while \u003cem\u003eLactobacillus\u003c/em\u003e predominated in AB group. Random forest classification and rank sum testing verified discriminatory species (top 30 and 20 bacterial species) (Fig. 3C-D). \u003cem\u003eLactobacillus\u003c/em\u003e was found to be the most important species to distinguish the four groups, along with some other genera, similar to the LEfSe results. After performing 10-fold cross-validation on random forest analysis between every two groups found that several important species, including \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eHungatella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eRuminococcus\u003c/em\u003e, \u003cem\u003eMoryella\u003c/em\u003e etc., is to distinguish between CC and control. The receiver operating characteristic (ROC) curve could effectively distinguish the CC group from the Z group (AUC=93.75%) (Fig. S2D). \u003cem\u003ePseudomonas\u003c/em\u003e levels differentiated between HPV+ and CC group with an area under the ROC curve of 87.5% (Fig. S2C, E). However, it was difficult to classify HPV-infected patients and control (AUC=64.29%) (Fig. S2F).\u003c/p\u003e\n\u003cp\u003eSubgingival microbiome LDA and LEfSe markers varied inversely to the vaginal niche, with control (KZZ group) plaques harboring the most distinct taxa including\u0026nbsp;\u003cem\u003ePrevotella\u003c/em\u003e,\u0026nbsp;\u003cem\u003eSelenomonas\u003c/em\u003e,\u0026nbsp;\u003cem\u003eSaccharibacteria\u003c/em\u003e,\u0026nbsp;\u003cem\u003eCampylobacter\u003c/em\u003e,\u0026nbsp;\u003cem\u003eAmnipila\u003c/em\u003e,\u0026nbsp;\u003cem\u003eCentipeda\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, LDA \u0026gt; 2; Fig. S3A,B). The markers of the AB group were \u003cem\u003ePelospora\u003c/em\u003e and \u003cem\u003eFilifactor\u003c/em\u003e, HPV infection group were \u003cem\u003eHaemophilus\u003c/em\u003e, \u003cem\u003eGemmatimonadaceae\u003c/em\u003e. \u003cem\u003eMonoglobus\u003c/em\u003e was the effective marker of subgingival plaque of cervical cancer patients, but the relative abundance was low in plaque microbiome. Combined with the previous diversity analysis, only two groups of KCC and KZ were compared (Fig. 4A, B), we screened bacteria with more than 10% composition and found that \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eLautropia\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eLachnoanaerobaculum\u003c/em\u003e, \u003cem\u003ePropionibacterium\u003c/em\u003e, \u003cem\u003eF0332\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eNeisseria\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, and \u003cem\u003eRoseburi\u003c/em\u003e could become oral markers for cervical cancer patients. Combining random forest model analysis with 10-fold cross-validation to draw the ROC curve, and the AUC reached 89.06% (Fig. 4 C, D). The following bacteria, including \u003cem\u003eFusobacterium\u003c/em\u003e，\u003cem\u003eCampylobacter\u003c/em\u003e, \u003cem\u003eOribacterium\u003c/em\u003e, \u003cem\u003eSelenomonas\u003c/em\u003e, \u003cem\u003eHaemophilus\u003c/em\u003e, \u003cem\u003eunclassified\u003c/em\u003e_\u003cem\u003eSR1_bacterium_human_oral_taxon_HOT_345\u003c/em\u003e, \u003cem\u003eLeptotrichia\u003c/em\u003e, \u003cem\u003eParvimonas\u003c/em\u003e, \u003cem\u003ePhocaeicola\u003c/em\u003e, \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eLautropia\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eLachnoanaerobaculum\u003c/em\u003e, \u003cem\u003ePropionibacterium\u003c/em\u003e, \u003cem\u003eF0332\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eNeisseria\u003c/em\u003e, \u003cem\u003eParabacteroides\u003c/em\u003e, \u003cem\u003eRoseburi\u003c/em\u003e, \u003cem\u003eFretibacterium\u003c/em\u003e, \u003cem\u003ePeptostreptococcus\u003c/em\u003e, \u003cem\u003eAll\u003c/em\u003eo\u003cem\u003eprevotella\u003c/em\u003e, \u003cem\u003ePseudopropionibacterium\u003c/em\u003e, and \u003cem\u003eSaccharibacteria\u003c/em\u003e were further screened as marker biomarkers, and although the AUC decreased to 80.95%, it had a certain accuracy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Association between microorganisms and environmental factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCo-occurrence networks displayed complexes of synergistically promoted microbes across vaginal and oral environment. The network shows the correlations between bacterial species common to both vaginal and oral microbiotas. The nodes represent bacterial species, and the edges (the lines connecting the nodes) illustrate the strength and type of correlation between these species. The node size likely corresponds to the abundance of the species, and the edge thickness might indicate the strength of the correlation (Fig. 5). The results showed that the presence of one species promote the growth of another, indicating a synergistic promotion effect. For example, \u003cem\u003eTreponema\u003c/em\u003e and \u003cem\u003eSelenomonas\u003c/em\u003e, \u003cem\u003eLautropia\u003c/em\u003e and \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eLachnoanaerobaculum\u003c/em\u003e and \u003cem\u003eLeptotrichia\u003c/em\u003e, \u003cem\u003eLautropia\u003c/em\u003e and \u003cem\u003eNeisseria\u003c/em\u003e, \u003cem\u003eSaccharibacteria\u003c/em\u003e and \u003cem\u003eF0058\u003c/em\u003e, \u003cem\u003eTannerella\u003c/em\u003e and \u003cem\u003eFusobacterium\u003c/em\u003e have co-occurrence network\u0026nbsp;(Fig. 5A). The correlation between vaginal microbiota was also positive, such as \u003cem\u003ePeptoniphilus\u003c/em\u003e and \u003cem\u003eDialister\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e and \u003cem\u003ePeptoniphilus\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e and \u003cem\u003eDialister\u003c/em\u003e (Fig. 5B). However, it was negatively correlated between \u003cem\u003eFretibacterium\u003c/em\u003e and \u003cem\u003eCapnocytophaga\u003c/em\u003e in oral microenviroment, and other bacteria relationship was positively correlated. In addition, \u003cem\u003ePeptostreptococcus\u003c/em\u003e and \u003cem\u003eRoseburia\u003c/em\u003e had cross nodes with multiple bacteria (Fig. 5C).\u003c/p\u003e\n\u003cp\u003eWe performed a Spearman analysis of these four groups to explore the correlation between the vaginal microbiome and demography, blood indices, oral diseases and oral hygiene practices. Vaginal \u003cem\u003eLactobacillus\u003c/em\u003e abundance negatively correlated with childbirths (\u003cem\u003ep\u003c/em\u003e=0.010) but positively associated with\u0026nbsp;\u003cem\u003eprevotella\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e=0.035) among the top ten species in vaginal abundance. BMI was positively correlated with\u0026nbsp;\u003cem\u003eBacillus\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e=0.046), In vaginal microbiota,\u0026nbsp;\u003cem\u003eLactobacillus\u003c/em\u003e show positive correlation to frequency of tooth brushing (FB) (\u003cem\u003ep\u003c/em\u003e=0.024) and inversely corelated to carries (\u003cem\u003ep\u003c/em\u003e=0.011). Similarly, \u003cem\u003eGardnerella\u003c/em\u003e showed positive relation to CRP (\u003cem\u003ep\u003c/em\u003e=0.040)\u003cem\u003e\u0026nbsp;\u003c/em\u003eand were negatively correlated to platelets (PLT) (\u003cem\u003ep\u003c/em\u003e=0.026), Brushing time (BT) (\u003cem\u003ep\u003c/em\u003e=0.005), and monocytes percentage (MONO) (\u003cem\u003ep\u003c/em\u003e=0.007).\u0026nbsp;\u003cem\u003eSneathia\u003c/em\u003e was positive corelated to carries (\u003cem\u003ep\u003c/em\u003e=0.012) while negatively related to BT (\u003cem\u003ep\u003c/em\u003e=0.035), number of abortions (NB) (\u003cem\u003ep\u003c/em\u003e=0.048), periodontal (\u003cem\u003ep\u003c/em\u003e=0.039) disease were negatively related. The levels of lymphocytes percentage (LYM) have negative correlation with the presence of\u0026nbsp;\u003cem\u003eMycoplasma\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e=0.031) (Fig. 6A).\u003c/p\u003e\n\u003cp\u003eFor oral microorganisms, CRP was positively associated with\u0026nbsp;\u003cem\u003eCapnocytophaga\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.042) and\u0026nbsp;\u003cem\u003enegatively\u003c/em\u003e association with\u0026nbsp;\u003cem\u003eSelenomonas\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep=\u003c/em\u003e0.003),\u0026nbsp;\u003cem\u003eprevotella\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep=\u003c/em\u003e0.007), and\u0026nbsp;\u003cem\u003eTreponema\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep=\u003c/em\u003e0.020). Childbirths positively correlated with\u0026nbsp;\u003cem\u003eCapnocytophaga\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.027)\u003cem\u003e,\u003c/em\u003e however negatively related\u0026nbsp;\u003cem\u003eSelenomonas\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep=\u003c/em\u003e0.001),\u0026nbsp;\u003cem\u003eFusobacterium\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep=\u003c/em\u003e0.009),\u0026nbsp;\u003cem\u003eTreponema\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep=\u003c/em\u003e0.025). Toothache or sensitivity of tooth (TOS) exhibited negative relation to\u0026nbsp;\u003cem\u003eTreponema\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.035). The genera\u0026nbsp;\u003cem\u003eCamplylobacter\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.015),\u0026nbsp;\u003cem\u003eSelenomonas\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), also shown negative correlations to the number of pregnancies (NP). In addition, we observed a negative association of the caries with the genus\u0026nbsp;\u003cem\u003eAggregatibacter\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e=0.010) and periodontitis has a positive association with the genus\u0026nbsp;\u003cem\u003eCampylobacter\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.022). FB and BT showed significantly positive correlations with\u0026nbsp;\u003cem\u003eSelenomonas\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.008), and\u0026nbsp;\u003cem\u003eTreponema\u003c/em\u003e respectively (\u003cem\u003ep\u003c/em\u003e=0.027) and\u0026nbsp;professional\u0026nbsp;dental cleaning (OP) with\u0026nbsp;\u003cem\u003eFusobacterium\u0026nbsp;\u003c/em\u003e(\u003cem\u003ep\u003c/em\u003e=0.045) (Fig. 6B).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Predictive Function Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMetagenomic functional potential based on 16S profiles revealed altered vaginal microbiome pathway activities differentiating CC from controls Z (Fig. 7). The level 2 KEGG pathway indicated that the microbial gene functions, namely global and overview maps, amino acid metabolism, metabolism of cofactors and vitamins, were higher in the CC group than Z group. Carbohydrate and nucleotide metabolism, translation, membrane transport, replication and repair were more prominent in Z group (\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05) (Fig. 7A). In addition, microbial gene functions of KZ group had lower level in metabolism of other amino acids, aging, excretory system, infectious diseases when compared with the KCC group. In terms of cell motility, cell growth and death, endocrine and metabolic diseases, and immune system, the KZ group was higher than the KCC group (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05) (Fig. 7B).\u003c/p\u003e\n\u003cp\u003eIn addition, the CC group showed over expression amino acid metabolism compared to the HP group and the AB group. The functional genes in metabolic pathways of cancer patients are still higher in global and overview maps, amino acid metabolism, metabolism of cofactors and vitamins, and the HP group is higher in global and overview maps, amino acid metabolism than the AB group (Fig. S4). This suggests that the presence of certain bacteria may play a role in the metabolic processes of cancer patients. There was a significant difference in oral microbial flora structure between the KCC group and the KZ group, while in comparison other groups found similar. However, due to the small sample size, these findings should be interpreted with caution.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eThis study evaluated that vaginal and oral microbiota composition and changes in women with abortion, HPV infection to cervical cancer. In addition to the different vaginal microecological environments of the four groups, we determined that there are significant differences in the composition, abundance, diversity, marker genera, and functional pathways of oral microorganisms between cervical cancer patients and healthy people, which further proves that the vaginal and oral microbes are not independent entities, and there is flora transfer between different parts of the body, which may be associated with systemic metabolic [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. To our knowledge, this is the first study to explore the oral microbiome\u0026rsquo;s role in patients with CC, improving the accuracy of CC screening process and broaden the scope of universal screening through insights gained from changes of oral microbiome. Our team previously reported meta-analysis and systematic review, found that sampled specimens studied for cervical cancer included cervix, vagina, rectum, feces, urine samples, without oral subgingival plaque (unpublished).\u003c/p\u003e \u003cp\u003eIn exploring vaginal microecological shifts, there is no significant difference in the microbial composition between the AB group and the control group, which is dominated by \u003cem\u003eLactobacillus\u003c/em\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The effect of recurrent abortion on vaginal flora is transient, regardless of cervical lesions[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. As long as the surgery does not cause substantial damage to vaginal tissues, the equilibrium betweencommensal bacteria and opportunistic pathogens remains same. With the occurrence of HPV infection and cervical cancer, the species diversity increased, the proportion of lactobacillus gradually decreased, and the internal structure of the microbiome became more complex, similar to the previous studies findings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Z group, AB group and HP group had a large overlap, which was significantly different from CC group at beta diversity. It was further confirmed that the depletion of \u003cem\u003eLactobacillus\u003c/em\u003e and the increase of specific anaerobes (such as \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003ePrevotell\u003c/em\u003e and \u003cem\u003eGardnerella vaginalis\u003c/em\u003e) were related to cervical lesions [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. LEfSe analysis identified cancer-specific vaginal biomarkers including \u003cem\u003eMycoplasma\u003c/em\u003e, \u003cem\u003eBacillus\u003c/em\u003e, \u003cem\u003eBacteroides\u003c/em\u003e, \u003cem\u003eDialister\u003c/em\u003e, \u003cem\u003ePeptoniphilus\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e, \u003cem\u003eAnaerococcus\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eSneathia\u003c/em\u003e, and for HPV\u0026thinsp;+\u0026thinsp;biomarker is \u003cem\u003ebifidobacterium\u003c/em\u003e distinct them from control, the reliability of experimental findings are confirmed by other studies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. \u003cem\u003eBifidobacterium\u003c/em\u003e is a beneficial microorganism of intestinal flora, which has many functions such as resisting harmful bacteria, providing nutrition, anti-tumor, anti-aging, enhancing immunity and improving gastrointestinal function, it also exists in the oral cavity and vagina [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. This research found that \u003cem\u003eBifidobacterium\u003c/em\u003e species to distinguish whether cervical lesions, which is of great significance for the diagnosis of women's health. \u003cem\u003eBifidobacterium\u003c/em\u003e abundanc decreased, which is associated with high grade squamous intraepithelial lision (HSIL) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Wang et al. found that the increased abundance of \u003cem\u003ebifidobacterium\u003c/em\u003e in the vaginal microbiome may be related to the clearance of HR-HPV infection, focused ultrasound treatment (FU) may help to increase the abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], the possible reason is that \u003cem\u003eBifidobacterium\u003c/em\u003e can survive in acidic environment and produce lactic acid and hydrogen peroxide, has a protective effect on the vaginal environment [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAdditionally, identified the shared periodontal pathogens \u003cem\u003ePorphyromonas\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e as cervical cancer biomarkers which may be the dynamic colonization of opportunistic bacterial pathogens on squamous epithelial cells in the oral or vaginal cavities and communication with the external environment. Oral pathogens can be transmitted from the gastrointestinal tract or through blood transmission to the vaginal cavity, it can also be transmitted through person-to-person oral-genital contact [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This suggests that oral and vagina share a common microbial community and there is also a reciprocal exchange of related microbial communities. The salivary microbiota of participants with bacterial vaginosis (BV) was more diverse than BV negative participants[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], \u003cem\u003ePrevotella intermedia\u003c/em\u003e and \u003cem\u003ePorphyromonas endodontalis\u003c/em\u003e were enriched in the subgingival gingival microbiota of BV women compared to women without BV, it indicates the presence of a vagino-oral axis [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. At the same time, \u003cem\u003ePorphyromonas\u003c/em\u003e and \u003cem\u003ePrevotella\u003c/em\u003e has been proved to be carcinogenic potential of several different mechanisms. For example, \u003cem\u003ePorphyromonas\u003c/em\u003e can maintain chronic periodontal infection, leading to increased expression of proinflammatory molecules such as IL-6, IL-8, IL-1β, and TNF-α and activation of Toll-like receptors (TLRs) and antiapoptotic pathways (JAK/STAT and MAPK pathways), decreased expression of proapoptotic proteins, increased cancer cell migration and invasion [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Gingipain proteases of \u003cem\u003ePorphyromonas gingivalis\u003c/em\u003e activate NF-κB and MMP-9 in oral squamous cells, which are important for cancer cell invasion and metastasis [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Similarly, \u003cem\u003ePrevotella\u003c/em\u003e produces virulence factors, fimbriae adhesins, lipopolysaccharides (LPS), peptidoglycan and lipoteichoic acid, which induce the release of pro-inflammatory cytokines [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], it also has the ability to stimulate tyrosine kinase receptors, degrade immunoglobulin and has toxic effects on fibroblasts, and coordinates with other pathogens to promote the migration and invasion of cancer cell [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Therefore, the pathogenic mechanisms of these periodontal pathogens are summarized as follows: they can stimulate chronic inflammation, inhibit cell apoptosis, activate cell proliferation and promote cell invasion resulting cancer [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eVaginal microbiome transformations along the cervical carcinogenesis route have been characterized, associated impacts on the oral niche remain underexplored. This study shows that the oral cavity contains a significantly greater number of bacterial species compared to the vagina, and also uncover extensive bidirectional sharing of microbial communities between vaginal and oral cavities through an emerging vagino-oral axis [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This provides insight into the shared one microbial community between the oral and vagina parts of the human body, as well as the exchange of related microbial communities. This study have shown that only patients with vaginal HPV infection and multiple abortion exhibit no obvious impact on their oral flora. However, the presence of cervical cancer can cause significant changes in the composition and abundance of oral microorganisms, leading to a lower diversity of oral microbiome compared to the normal population, which is contrary to the changes in vaginal microbiota. The periodontal pathogens in patients with cervical cancer was significantly increased, combined with ELfse and random forest analysis, \u003cem\u003eFusobacterium\u003c/em\u003e, \u003cem\u003eCampylobacte\u003c/em\u003e, \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eVeillonella\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eLachnoanaerobaculum\u003c/em\u003e, \u003cem\u003ePropionibacterium\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e and \u003cem\u003eNeisser\u003c/em\u003e were identified as oral bacterial markers for cervical cancer. The changes in these bacterial proportion can cause oral microflora dysbiosis and are also associated with all systemic diseases, including cancer [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan additionalcitationids=\"CR46 CR47\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. It has been pointed out that different bacteria such as \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e, \u003cem\u003eperiodonticum\u003c/em\u003e, \u003cem\u003eStreptococcus salivarius\u003c/em\u003e, \u003cem\u003ePorphyromonas\u003c/em\u003e, and different \u003cem\u003eLactobacillus\u003c/em\u003e subspecies are associated with the diagnosis of this kind of cancer. The periodontal pathogens \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e, \u003cem\u003eCampylobacter\u003c/em\u003e, \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e and \u003cem\u003ePorphyromonas\u003c/em\u003e are considered \"mobile microbiota\" because they originate in the oral cavity but are also associated with extra-oral infections and inflammation [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Tumorigenesis mechanism associated with oral microbiome is various, mainly in: increase cell factors and inflammatory factors, lead to chronic inflammation and cell proliferation of metabolic pathways changes, pathogenic bacteria metabolites, suppress the immune response, induced tumor genetic damage, alter epithelial barrier and so on [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Most of the current research focuses on how the dysfunction of oral microorganisms affects the major organs and systems of the whole body. However, there is a bidirectional relationship between oral and general health, and how systemic diseases adversely affect oral microorganisms need more explored.\u003c/p\u003e \u003cp\u003eIn this study, a positive correlation was observed between vaginal and oral microorganisms, where certain bacteria exhibited connections with many others. Many studies have already found the synergistic effect of pathogenic microorganisms. Lo CH et al. found that \u003cem\u003ePrevotella intermedia\u003c/em\u003e is enriched in CRC and enhances the migration and invasion of cancer cells, moreover, \u003cem\u003ePrevotella intermedia\u003c/em\u003e and \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e collectively contribute on the malignant transformation of colorectal adenoma into carcinoma [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. \u003cem\u003eStreptococcus gordonii\u003c/em\u003e, \u003cem\u003eFusobacterium nucleatum\u003c/em\u003e and \u003cem\u003ePorphyromonas gingivalis synergistically\u003c/em\u003e promote the formation and proliferation of plaque biofilms, inhibit the growth of dendritic cells [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], and cause peripheral blood infection that is based on bacterial tyrosine (BY) kinase, (Ptk1), is an important part of the signaling pathway that controls the synergistic interaction between \u003cem\u003ePorphyromonas gingivalis\u003c/em\u003e, and \u003cem\u003eStreptococcus gordonii\u003c/em\u003e [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Colonization of vaginal epithelial \u003cem\u003eAtopobium\u003c/em\u003e enhances virulence of \u003cem\u003eGardnerella\u003c/em\u003e, and biofilms formed by \u003cem\u003eGardnerella\u003c/em\u003e also dominate the other bacteria to colonize [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The interaction of a variety of microbial synergy mechanism is very complex, These mechanisms encompass not only metabolite cross-feeding, but also a large number of microbiota quorum-sensing signal result in enhancing resistance against the immune system, antibiotics, or direct contact between microorganisms to promote synergy [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Thus, the comprehensive impact of two or more microorganisms on disease is more severe impact than single, and the complex interaction network may enhance the pathogenicity of multi-microbial infections, ultimately affecting disease initiation and progression. It should be noted that these studies are based on different bacteria in the same site, while the composition of the vaginal microbiome is different from the oral microbiome, and more studies are needed to clarify the mechanisms of action of the microbiome at different sites.\u003c/p\u003e \u003cp\u003eSystemic inflammation (such as cervical lesions and HPV infection) caused significant variation in CRP concentration across all the groups. The increase in the number of pregnancies, childbirth and abortions can easily have disturbed the vaginal microenvironment, the \u003cem\u003eLactobacillus\u003c/em\u003e abundance decreases, while the proportion of anaerobic bacteria \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eGardnerella\u003c/em\u003e increases. Severe systemic and local inflammations are closely related to the imbalance of vaginal microbiome [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Similarly, when oral hygiene was good and brushing frequency was high, the pathogenic microorganisms associated with periodontal disease, such as \u003cem\u003eSelenomonas\u003c/em\u003e, \u003cem\u003eprevotella\u003c/em\u003e, \u003cem\u003eTreponema\u003c/em\u003e, and \u003cem\u003eAggregatibacter\u003c/em\u003e, were reduced. The reason is that oral microorganisms or their metabolites directly migrate through the blood or indirectly affect the inflammatory mediators produced in the oral [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCervical cancer of microbial diversity changes consistent with the amino acid metabolism. It is well known that cancer cells grow rapidly, the metabolites are overexpressed and glycogen consumption to produce large amounts of energy and intermediate [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. It has been verified by metabolomics and transcriptomics that the occurrence of cervical cancer is significantly related to metabolism, proteolysis or proteoglycan process pathway [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. The higher the degree of cervical lesions, the consumption of lactic acid also gradually peaks, the metabolic characteristics turn to the increased consumption of glutamine after the development of CC, and these metabolite changes are negatively correlated with the abundance of \u003cem\u003eLactobacillus\u003c/em\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Studies in humans have shown that CC has distinct metabolic fingerprint in blood, tumor tissue, faeces, and urine [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. However lacking metabolic maps in the oral cavity, and the PICRUST predictive analysis of this study adds some data. Cervical lesions also affect the oral microbial metabolites, the amino acid metabolism of oral bacterium in patients with CC is higher than control relating to the corresponding pathogenic microorganisms. \u003cem\u003eCapnocytophaga\u003c/em\u003e grows in places with high glycogen consumption[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], \u003cem\u003ePorphyromonas\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e and \u003cem\u003eFusobacterium\u003c/em\u003e are closely related to the differences in metabolites. The pyrimidine metabolism is significantly increased in the patients with CC, which is positively correlated with the enrichment of periodontal disease[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. The glutamate, histidine, and tyrosine metabolisms are also involved in the development of periodontitis. Cervical lesions lead to changes in the oral microenvironment, which may enhance the pathogenic effect of periodontal bacterium, induce the selective growth and reproduction of oral pathogens, produce more pathogenic microbiome, and even produce the \"Warburg effect\".\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitation\u003c/h2\u003e \u003cp\u003eAs a case-control study, and we cannot conclude whether oral microbiome changes affect the vaginal microbiome, or whether changes in the vaginal microbiome affect the oral microenvironment after the onset of cervical lesions. Second, Cervical cancer patients were not tested for the presence of HPV virus in the oral cavity. It is generally believed that oral sex may be the link to transmission from vaginal to oral site [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], which causes viral infection of the oral mucosa and causes a dysbiosis. However, the overall risk of oral HPV infection in published studies was low, HPV transmission to the oropharynx by autoinoculation or oral-genital contact constitute a rare and unlikely event [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Therefore, it is more likely to believe that cervical lesions affect the oral microenvironment through retrograde flow. Third, considering the use of oral PICRUSt to predict microbiome function has some limitations, including the accuracy of functional prediction differences, should be hold cautious attitude to result. Fourth, the sample size of this study is small, the results of this study still need to be improved by expanding the sample quantity and cohort study in the future.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study revealed that vaginal and oral microbiota composition and changes in women with abortion, HPV infection to cervical cancer. Decline \u003cem\u003elactobacillus\u003c/em\u003e dominancy and increasing microbiota diversity (such as \u003cem\u003eMegasphaera\u003c/em\u003e, \u003cem\u003ePrevotell\u003c/em\u003e and \u003cem\u003eGardnerella vaginalis\u003c/em\u003e) were associated with progression from control through precancer to malignancy within the vaginal niche. HPV infection and CC not only have a certain impact on the vaginal microenvironment, but also effect the oral microenvironment through the synergistic mechanism on microbiome and systemic metabolism. The global and overview maps, as well as in amino acid metabolism, metabolism of cofactors and vitamins are highly expressed in CC exhibiting the fluctuation in the niche. This can lead to a decrease in oral microbial diversity and an increase in the composition of pathogenic microorganisms, increasing the risk of infections and cancer. In the future, it is expected to screen cervical cancer through oral flora markers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ.W.: conceptualization, methodology, writing-original draft, and project administration. Y.Y.F.: methodology, software, investigation, writing. J.Y.S.: investigation, writing, analysis, visualization. Y.Y.Y.: software, investigation, writing. W.W.T.: analysis, visualization. W.X.Y.: analysis, visualization. L.B.: Writing-review \u0026amp; editing, Resources. Y.L.H.: conceptualization, Writing-review \u0026amp; editing, Resources. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was financially supported by the Health Industry Scientific Research Rrogram of Gansu Province, China (GSWSKY2021-026), Natural Science Foundation of Gansu\u0026nbsp;Province, China (22JR5RA941 and 22JR5RA998), Project of the First Hospital of Lanzhou University (ldyyyn2022-49 and ZX-62000002-2021-225).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi. nlm.nih.gov/sra/PRJNA1055682.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge sequencing platform provided by Biomark Biotechnology Co., Ltd, the data were analyzed using the BMK Cloud Platform.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. 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Arch Gynecol Obstet. 2019;299(6):1659\u0026ndash;65. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00404-019-05135-7\u003c/span\u003e\u003cspan address=\"10.1007/s00404-019-05135-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"vaginal microbiome (VM), Human papillomavirus (HPV), cervical cancer, oral microbiome, 16S rRNA","lastPublishedDoi":"10.21203/rs.3.rs-3859830/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3859830/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThis study aimed to assess the microbial variations and biomarker in the vaginal and oral environment of HPV (human papillomavirus) and cervical cancer (CC) patients and developing novel prediction models.\u003c/p\u003e\u003ch2\u003eMaterials and Methods\u003c/h2\u003e \u003cp\u003eThis study includes 164 samples collected from both the vaginal tract and oral subgingival plaque of 82 women. The participants were divided into four distinct groups based on their vaginal and oral samples including control group (Z/KZ, n\u0026thinsp;=\u0026thinsp;22), abortion group (AB/KAB, n\u0026thinsp;=\u0026thinsp;17), HPV-infected group (HP/KHP, n\u0026thinsp;=\u0026thinsp;21), and cervical cancer group (CC/KCC, n\u0026thinsp;=\u0026thinsp;22). Microbiota analysis was conducted using full-length 16S rDNA gene sequencing with PacBio platform.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe vaginal bacterial community in the Z and AB groups exhibited a relatively simple structure predominantly dominated by \u003cem\u003eLactobacillus.\u003c/em\u003e However, CC group shows high diversity and abundances of anaerobic bacteria and alpha diversity. Biomarkers such as Bacteroides, Mycoplasma, Bacillus, \u003cem\u003eDialister, Porphyromonas\u003c/em\u003e, \u003cem\u003eAnaerococcus\u003c/em\u003e, and \u003cem\u003ePrevotella\u003c/em\u003e were identified as indicator of CC. Correlations were established between elevated blood C-reactive protein (CRP) levels and local/systemic inflammation, pregnancies, childbirths, and abortions, contributing to the unevenness in the vaginal microenvironment. The altered microbial diversity in CC group was confirmed by amino acid metabolism.The oral microbial diversity exhibited inverse pattern to the vaginal microbiome, indicating a unique relationship. The KCC group showed a significantly lower microbial diversity compared to the KZ group, pointing a link between oral health and cancer development. Several microbes including \u003cem\u003eFusobacterium\u003c/em\u003e, \u003cem\u003eCampylobacte\u003c/em\u003e, \u003cem\u003eCapnocytophaga\u003c/em\u003e, \u003cem\u003eVeillonella\u003c/em\u003e, \u003cem\u003eStreptococcus\u003c/em\u003e, \u003cem\u003eLachnoanaerobaculum\u003c/em\u003e, \u003cem\u003ePropionibacterium\u003c/em\u003e, \u003cem\u003ePrevotella\u003c/em\u003e, \u003cem\u003eLactobacillus\u003c/em\u003e, \u003cem\u003eNeisseria\u003c/em\u003e were screened as CC biomarkers. Moreover, Periodontal pathogens were associated with blood CRP levels and oral hygiene conditions. Elevated oral microbial amino acid metabolism in CC group was closely linked to the presence of pathogens. positive correlations indicated synergy between vaginal and oral bacteria.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eHPV infection and CC impact both the vaginal and oral microenvironment, affecting systemic metabolism and the synergy between bacteria. This suggests the use oral flora markers as a prospective screening tool for the diagnosis the cervical cancer.\u003c/p\u003e","manuscriptTitle":"Relationship between vaginal and oral microbiome in patients of human papillomavirus (HPV) infection and cervical cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-24 19:57:49","doi":"10.21203/rs.3.rs-3859830/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-01-22T15:02:09+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-22T11:02:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-13T09:08:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2024-01-12T03:50:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"18a4af50-27e6-4109-a3f2-b3f953fd0f88","owner":[],"postedDate":"January 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-01T23:32:40+00:00","versionOfRecord":{"articleIdentity":"rs-3859830","link":"https://doi.org/10.1186/s12967-024-05124-8","journal":{"identity":"journal-of-translational-medicine","isVorOnly":false,"title":"Journal of Translational Medicine"},"publishedOn":"2024-04-29 23:32:40","publishedOnDateReadable":"April 29th, 2024"},"versionCreatedAt":"2024-01-24 19:57:49","video":"","vorDoi":"10.1186/s12967-024-05124-8","vorDoiUrl":"https://doi.org/10.1186/s12967-024-05124-8","workflowStages":[]},"version":"v1","identity":"rs-3859830","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3859830","identity":"rs-3859830","version":["v1"]},"buildId":"re_ckhLnmML6MCF96OHNJ","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}