In this review article, we present the major insights from and challenges faced in the acquisition, analysis and modeling of astrocyte calcium activity, aiming at bridging the gap between those fields to crack the complex astrocyte “Calcium Code”. We then propose strategies to reinforce interdisciplinary collaborative projects to unravel astrocyte function in health and disease. Astrocytes, the most abundant non-neuronal cells of the nervous system, are essential to brain function, from synaptogenesis and neurotransmission to higher brain functions such as memory and learning , but its spatial resolution is limited by diffraction (x-y: 0.2–0.3 super-resolution microscopy such as stimulated emission depletion (STED) and stochastic optical reconstruction microscopy (STORM) to study astrocyte morphology at the tripartite synapse level in live tissue  and emphasizes the need to establish collaborations between experimental and computer scientists.Astrocytes display most of their activity in their fine processes. The majority of those signals are spatially restricted, forming so-called microdomains, and display strikingly diverse spatio-temporal properties  as well as the detection, the segmentation and the quantification of the calcium signals in a sequence of microscopy images, which is very challenging due to the complex nature of these signals. First, calcium signals are characterized by various durations (from milliseconds to tens of seconds), frequencies and signal-to-noise ratios. Second, their spatial spreads vary from microdomains to signals that propagate within the astrocyte in regions of various sizes and shapes. Third, they can overlap in space and time , please refer to the dedicated section in the review article from   to train and quantitatively assess the performance of analysis software. This highlights the need for developing models and simulators that are able to mimic real image sequences.The main reason why the quantification of astrocyte calcium signals has been so far restricted to 2D+time images is because of the trade-off between temporal and spatial resolution in microscopy techniques. The access to a refined 3D imaging of the dynamical behavior of calcium signals in astrocytes is quite recent, owing to the emergence of microscopes enabling a high 3D spatio-temporal resolution with low phototoxicity , allowing for better quantification, visualization, and understanding of the system. The famous quotation from George Box, “All models are wrong but some are useful” Box , highlige.g., 1 e.g., 1 millisecond of calcium activity varies not only depending on the modeling technique used, but also on the computational resources available in each laboratory, on the volume and number of reactions modeled as well as the simulation time. To learn more about the different approaches that can be used to model reactions, their insights and limitations, please refer to dedicated reviews  within the cell and explore its impact on astrocyte activity .There is no consensus in key definitions and terminology, which further hinders efficient communication across fields  methods used. This might require the creation of an online platform to store and discuss data on astrocytes.Sharing user-friendly data analysis tools, including providing the code in open-access and the dataset(s) used to facilitate their dissemination to the whole community.Organization of recurrent meetings and events that bring together experts from various fields of expertise.Because of the complexity of astrocyte morphology and signaling, interdisciplinary projects will be essential to not only crack the astrocyte “Calcium Code”, but also to successfully improve our understanding of astrocyte (patho-)physiology and to propose models of astrocyte function.Reinforcing interdisciplinary projects, bringing together experts from different fields, will be crucial to ensure our success in cracking the astrocyte “Calcium Code”. Such collaborative projects are still rare in the field, which might result from the high fragmentation of research projects and fields working on astrocyte physiology, often presenting their work in different, highly specialized conferences and journals. We propose initiatives that will facilitate the emergence of new interdisciplinary projects:


Although other co-viral infections could also be considered influencing factors, cervical human papillomavirus (HPV) infection is the main cause of cervical cancer. Metagenomics have been employed in the NGS era to study the microbial community in each habitat. Thus, in this investigation, virome capture sequencing was used to examine the virome composition in the HPV-infected cervix. Based on the amount of HPV present in each sample, the results revealed that the cervical virome of HPV-infected individuals could be split into two categories: HPV-dominated  and non-HPV-dominated . Cervical samples contained traces of several human viral species, including the molluscum contagiosum virus (MCV), human herpesvirus 4 (HHV4), torque teno virus (TTV), and influenza A virus. When compared to the HD group, the NHD group had a higher abundance of several viruses. Human viral diversity appears to be influenced by HPV dominance. This is the first proof that the diversity of human viruses in the cervix is impacted by HPV abundance. However, more research is required to determine whether human viral variety and the emergence of cancer are related. Persistent infection with HPV, particularly high-risk HPV (hrHPV), is a critical point in the progression of cervical intraepithelial neoplasia (CIN), which leads to the development of cancer . Cervica2O2), and reduce the pH through the production of lactic acid [Besides HPV infection, the main factor of cervical cancer development, other factors also contribute to vaginal health and disease progression. Smoking has been listed as a co-factor of cervical cancer by International Agency for Research on Cancer (IARC) since 2004 ,6. The vtic acid ,10,11,12tic acid ,14,15. Mtic acid . Additiotic acid .polyomaviridae, has been suggested as a contributor towards co-infection with HPV in the initiation and progression of cervical cancer, since BKV was found in 4% of HPV-positive cervical swabs [Papillomaviridae, Anelloviridae, Genomoviridae, and Herpesviridae were found  in the cervix of HIV/HPV co-infected patients in Brazil [The relationship between HPV and other viral infections in the cervix has been observed in many studies. Herpes simplex virus type 2 (HSV-2) seropositive patients had a two- to nine-fold increased risk of cervical squamous cell carcinoma or adenocarcinoma . Approxial swabs . In addial swabs . With thn Brazil . To the Cervical swab samples were collected from patients who visited the Department of Gynecological Outpatient, King Chulalongkorn Memorial Hospital, Bangkok, Thailand from 2019–2020 by gynecologists using colposcopy; the samples were stored at −80 °C. The Cobas 4800 high-risk HPV test  was used to detect the HPV genotyping in all samples. This assay was performed at the Virology Unit, Department of Microbiology, King Chulalongkorn Memorial Hospital, Bangkok. In this study, the archived samples were selected according to inclusion and exclusion criteria. All data were fully anonymized before assessment. This study was approved by the Institutional Review Board (IRB) of the faculty of Medicine, Chulalongkorn University, a WHO-certified ethics committee . The protocol of study was also approved by the Institutional Biosafety Committee (IBC) of the faculty of Medicine, Chulalongkorn University (MDCU-IBC018/2019). The blood-free samples with HPV infection (HPV16 and/or other hrHPVs) and histopathology results diagnosed as CIN1 to CIN3 were selected. The exclusion criteria included: having menstruation on the date of specimen collection, infecting with other active microorganisms , use of antibiotics or vaginal antimicrobials within the last month, and pregnancy. A total of 48 leftover HPV DNA positive specimens were recruited in this study. Due to the very low yield of nucleic acid, only 35 samples were suitable for further experiments. The MEAN ± SEM age of all 35 enrolled patients was 37.971 ± 1.459 years (ranging from 23 to 50 years old). The additional information of each sample, e.g., HPV genotype, cytological and histological characteristics, are shown in The leftover cervical specimens were beaten by Pathogen Lysis Tubes L  at 30 Hz for 5 min using Tissue lyser LT . After that, the COBAS 4800 system  was used for the automatically total nucleic acid extraction. To recover the RNA viruses in samples, cDNA construction and the second strand synthesis step were performed; the cDNA was constructed by Roche Evoscript Universal cDNA Master using random hexamers  by heating at 65 °C for 30 min. After that, the second strand of cDNA was synthesized by using 10 U/µL DNA polymerase I, second Strand buffer (10×NEB Buffer 2), 10 mM dNTP mix, RNaseH, and 0.1 M DTT  by incubating at 16 °C for 2.5 h. The cDNA/second strand was purified by AMPure XP beads and suspended in 33 µL of 10 mM Tris HCl pH 8.0 .In the library preparation step, the guideline from SeqCap EZ Hypercap Workflow Version 2.3 , with slight modification, was used. All reagents, i.e., the KAPA HyperPlus Library Preparation Kit and SeqCap Adaptors Kit A, were purchased from Roche (Switzerland). In brief, the 100 ng of DNA input was enzymatically sheared by incubating at 37 °C for 15 min to obtain an average fragment size of 200 bp and followed by end repair, A-tailing reaction, and adaptor ligation. After that, double-sided size selection using AMPure XP beads and Pre-Capture LM-PCR was performed. The first QC step, including the measurement of yield and fragment size, was performed by using Nano Drop (the yield libraries should be ≥ 1.0 µg) and Fragment Analyzer 3700 (150 to 500 bp with a peak at 320 bp). To capture and enrich the viral sequences, 1 μg of each DNA sample library was hybridized with the SeqCap EZ probe pool (VirCapSeq-VERT Capture Panel); there were approximately 2.1 M probes (variable lengths of 50–105 mers) covering the genomes of 207 viral taxa , in a thBefore sequencing, the yield of libraries was quantitated by the KAPA library quantification kit . The denature and dilute libraries guide for MiSeq System  was used as a guideline for sample preparation. The 4 nM of normalized libraries was adjusted to 18 pM and loaded onto the reagent cartridge for sequencing using a MiSq Reagent Kit v3 . The libraries were sequenced using the Illumina MiSeq platform to generate 2 × 300 bp reads.ftp://ftp.ncbi.nih.gov/refseq/release/viral/ (accessed on 11 July 2020). All scripts for VIP were provided in The raw data in FASTQ files were exported from the Illumina MiSeq. To identify the metadata of viral species, these raw data were analyzed by the Virus Identification Pipeline (VIP) through sense mode, which function on Docker and Ubuntu 20.04 LTS. This pipeline was developed by Li Y. et al. . For theAlpha (Shannon index) and beta diversity, as well as principal coordinate analysis (PCoA) based on Bray-Curtis dissimilarities of the microbial community structure, were calculated by Past 4.03 software; meanwhile, the boxplots, rarefaction curve, bar chart, and pie chart were constructed by GraphPad Prism 8 software . Mann-Whitney testing (non-parametric Unpaired t test) was used to determine the significant difference of the alpha diversity and relative abundance.n = 21) and CIN2/3 (n = 14). Of those samples, 14 samples had HPV16 infection exclusively, 14 samples had HPV16 infection combined with other hrHPVs, and 7 samples had other hrHPV infection  and non-HPV-dominated (NHD) (n = 16), the average relative abundance of HPVs was 83.73% (ranging from 60% to 98%) (n = 19) . The genome coverage of Alphapapillomavirus ranged from 83.68% to 100% in the HD group, and from 24.27% to 99.75% in the NHD group. Samples in each histological stage of HD and NHD groups were CIN1 47.62% and 52.38%, and CIN2/3 42.86% and 57.14%, respectively. Interestingly, besides humans, viruses from other hosts, e.g., vertebrate viruses, were also found. However, due to the specificity of the viral infection, we only focused on the human-related viruses.The 1.5 M  of viral reads with 43,260 mean of viral reads per sample were subtracted from 8.5 M  high-quality reads by VIP . A totaled (NHD) a. In the to 98%) b. Only 5(n = 19) c; meanwhIn this study, alpha diversity for the observation of human viral diversity within an individual sample was performed by using the Shannon index (estimated evenness and richness). The alpha diversity of viruses in the NHD group was statistically higher than that of the HD group a. The saAs demonstrated in The relative abundance of human viruses between groups was calculated. As predicted, the relative abundance of HPVs and HPV16 in HD group was significantly higher than that of the NHD group. On the other hand, the relative abundances of TTVs, HCoV-229E, and MCV were found to be significantly higher in the NHD group when compared to the HD group , whereasThe most dominant viral species in the HD group was HPV16 (~30% abundance and ~50% proportion), followed by HPV 32 and 53 . The relThe virome in an HPV-infected cervix was investigated. A diverse viral community was discovered . As predDuring viral infections, many cellular mechanisms such as molecular building blocks, e.g., nucleotides and amino acids, a source of chemical energy, and the cellular protein-synthesizing machinery, are hijacked by viruses to support their own replication cycle and express their specific proteins . Once onBesides HPVs, many species of human viruses were shared between HD and NHD groups, e.g., HHV-4, BKV, TTV, and MCV . AlthougPolyomaviridae. Humans are the hosts of this virus [BKV belongs to the family is virus . This viis virus . The coris virus . Anelloviridae is classified as a circular negative ss-DNA virus. Their genome is contained in an icosahedral capsid without an envelope [Alphatorquevirus [The family envelope . This faquevirus . TTV is quevirus . It is mquevirus . Hence, quevirus . To thisquevirus . Some evquevirus . Interesquevirus . NeverthPoxviridae. MCV infection produces benign raised bumps, or lesions, on the upper layers of the skin. The co-infection of MCV and HPV was previously suggested. However, the investigation of this coexistence failed [MCV is an enveloped, linear, ds-DNA genome which is categorized in the family e failed . Hence, In this study, many human respiratory viruses were found in the cervix, such as influenza A virus, HAdV-1, HCoV-229E, and HPIVs. We hypothesized that these viruses were transmitted to the cervix via oral sexual behavior. In addition, it is possible that some viruses might not infect the cells but only the surface or contact of the genetic material residues. Further study is required, since the role of these respiratory viruses in carcinogenesis and their relationships with HPV co-infection is still unknown.The present study is the first study to indicate that the domination of HPVs possesses an important role in human viral diversity. Since HPV infection plays an important role in cancer development, therefore, co-infection with other viruses might act as cofactors in HPV related carcinogenesis. Nevertheless, the route of transmission and the role of pathogenicity of these viruses are still unclear. It would be valuable to conduct follow-up studies to ascertain the involvement of HPV co-infection with various viral species in the development of cervical cancer. An experiment using human organotypic raft culture could be an effective way to demonstrate the role of those viruses in HPV co-infection. The increasing number of clinical specimens should be further investigated to confirm the virome composition. In addition, more thorough investigations with various control groups, such as normal and/or CIN1-3 HPV negative groups, should be planned in future studies to confirm the function of HPVs in the virome composition. As a result, regardless of population, HPV persistence is a dominant factor in cervical cancer progression, though the microbial community may differ in other demographic populations. Therefore, the virome study in other ethnic groups should be further conducted.


Cervarix, the first available HPV vaccine, has been widely administrated to Chinese women, while little was known about its effect on the prevention and control for HPV related diseases in China. The study aims to assess the impact of Cervarix on HPV infection and cervical related diseases in real world.Cervical cancer is one of the most common cancers in women and could be prevented by human papilloma virus (HPV) vaccination. Cervarix vaccination history or without any HPV vaccination history). It is planned to recruit 12,118 eligible women at age of 9 to 45 years from vaccination clinics or hospital outpatient clinics, and then follow up them for three years. The standard questionnaire will be used to collect information such as demographic characteristics, menstruation and obstetrical histories, history of sexual behavior, personal behavior history, history of disease and pathogen infection, medication history, and family history at baseline. After three years, the changes of these behaviors will be investigated again, and other related health status information will be retrieved from the electronic health records during the follow-up period. If available physically and legally, the cervical cancer screening will be performed, including type-specific HPV deoxyribonucleic acid (DNA) polymerase chain reaction (PCR) testing and contingent thinprep cytologic test (TCT) and colposcopy. The free cervical cancer screening will be captured and uploaded timely to the Yinzhou Regional Health Information Platform (YRHIP); therefore, the long-term outcomes of participants will be monitored.This is a prospective, multi-age birth cohort study to investigate the incidence and continuous status of HPV infection, and relevant cervical diseases by exposure status  on April 22, 2022.This study has been retrospectively registered on  Cervical cancer was the fourth most common cancer in women, with approximately 0.60 million cases and over 0.34 million deaths from cervical cancer worldwide in 2020 . China iCervarix (9–45 years old) in 2016, Gardasil 4 (20–45 years old) in 2017, Gardasil 9 (16–26 years old) in 2018 and the domestic bivalent HPV vaccine Cecolin (9–45 years old) in 2019 [Cecolin for now [the Two Cancers  Screening Program in 2009, which provided females aged 35 years and over with cervical cancer and breast cancer screening for free [Expanding the coverage of HPV vaccines is an essential part of the 90–70-90 target proposed by the World Health Organization (WHO) for eliminating cervical cancer . China h in 2019 . These v for now , 14. In for free . ScreeniCervarix, the first available HPV vaccine for Chinese women, have great acceptance in China [Cervarix assesses the impact of HPV vaccination on HPV infection and cervical related diseases in Chinese women. The indicated population of Cervarix are females aged 9–45, thus, the whole indicated population should be included into the real-world study. In addition, the age distribution of HPV-infected population in China is bimodal (< 25 years and 41–45 years) [Several prospective cohort studies assessed the impact of HPV vaccination, such as a Dutch prospective cohort initiated in 2009 , a 10-ye5 years) , therefoYinzhou, in which this study will be conducted, is a district of Ningbo, Zhejiang province, which is one of the most developed provinces of China. The Center for Disease Control and Prevention (CDC) of Yinzhou set up an integrated electronic health information system for local residents in 2005 . By the Cervarix), for HPV infection and related cervical diseases in real world, with the following objectives:Cervarix on HPV 16/18 infection in birth cohortsTo describe the incidence of HPV 16/18 infection by exposure status, and to evaluate the effectiveness of To describe the incidence of cervical lesions or diseases, and other 12 high-risk HPV infection by exposure status in birth cohortsThe study aims to evaluate the impact of the AS04 adjuvanted HPV 16/18 vaccine (Brand name: Cervarix vaccination history or without any HPV vaccination history) in recruited subjects between 9 to 45 years old in Yinzhou District. Participants of this study will be recruited from local vaccination sites and the hospital outpatient clinics, and they will be divided into three age groups  at baseline. Participants who get vaccination of the first or second dose of the AS04 adjuvanted HPV 16/18 vaccine during the recruitment period will be included in the exposed group, and those who are not inoculated with any HPV vaccines before the recruitment will be included in the non-exposed group. All the participants will be visited twice during the study period, one at baseline and the other after a three-year follow-up. A standard questionnaire and cervical cancer screening will be given at each of the two visits to collect information. This whole study process was designed and will be conducted by School of Public Health, Peking University and the CDC of Yinzhou District.Prospective, multi-age birth cohort study to investigate the incidence and its change of HPV infection and relevant cervical disease by exposure status .Between 9 and 45 years old at time of the enrollment.Cervarix (exposed group); or without any HPV vaccination history (non-exposed group).Receiving 1 or 2 doses of Subjects for whom the investigator believes that they or their parent(s)/ Legally Acceptable Representative(s) (LAR(s)) can and will comply with the requirements mentioned in the protocol .Written informed consent will be obtained from the subject. For subjects who are below the legal age of consent, written informed consent must be obtained from the parent(s)/LAR(s) of the subject and informed assent must be obtained from the subject according to EC requirement as well as local law. Subjects must understand the protocol and be voluntarily willing to join this study with written informed consent form.All subjects must satisfy the following criteria at study entry:Pregnancy at the enrollment.Females with historical cervical diseases 1, CIN2, CIN3, and cervical cancer) before the recruitment.After hysterectomy.Females with malignant tumor history or other severe diseases , whose life expectancy is less than 12 months.Females who (1) have historical HPV vaccination, or (2) are in non-exposed groups but have clear intention for HPV vaccination in next 3 years (confirmed by field investigators before enrollment).31/33/35/39/45/51/52/56/58/59/66/68) positive result at baseline.Any high-risk HPV (hr-HPV) DNA .The following criteria should be checked at the time of study entry. If any apply, the subjects must not be included in the study:Pregnancy within the pre-scheduled visiting phase and not eligible for cervical cancer screening.Subjects in the non-exposure group who received any HPV vaccine during the study period.Death due to causes other than cervical cancer.Lost to follow-up .The following criteria should be checked at or right before the follow-up visit. If any become applicable during the study, the subject will withdraw from the study.Cervarix will be 83%, 66%, and 50% for the cohorts of 9–20, 21–30 and 31–45 years of age respectively [Per the previous research, the effectiveness assumptions for ectively , 24. Thedefined as at least one positive HPV-16 or HPV-18 DNA PCR assay at enrollment (Month 0) or follow-up (Month 36) or any additional screenings during the study period.Cervical infection with HPV-16 and/or HPV-18 (by PCR), defined as at least one positive HPV-16 or HPV-18 DNA PCR assay at the additional visit in 12 months after getting the positive HPV-16 or HPV-18 test result at enrollment (Month 0) or follow-up (Month 36) or any additional screenings during the study period.Cervical infection with HPV-16 and/or HPV-18 over 12 months , defined as at least one positive for HPV 31/33/35/39/45/51/52/56/58/59/66/68 or multiple types DNA PCR assay at enrollment (Month 0) or follow-up (Month 36) or any additional screenings during the study period.Cervical infection with 12 other high-risk HPV besides of type 16/18 (by PCR), defined as atypical squamous cells of undefined significance (ASC-US), atypical glandular cells (AGC), atypical squamous cells, cannot exclude for highly squamous intraepithelial lesions (ASC-H), low-grade squamous intraepithelial lesion (LSIL), high-grade squamous intraepithelial lesion (HSIL), Cervical Intraepithelial Neoplasia (CIN) 1, CIN2, CIN3, squamous cell carcinoma (SCC), adenocarcinoma in situ (AIS) and adenocarcinoma (ADC). Any hr-HPV type infection is defined as at least one positive for HPV 16/18/31/33/35/39/45/51/52/56/58/59/66/68 or multiple types DNA PCR assay in the aforesaid cervical sample.Any cervical lesions or diseases in birth cohorts, Cervarix and its administration service are available and health examination clinics of hospitals where the cervical cancer screening is available. The study subjects will be invited and the ones who have satisfied the inclusion criteria will be enrolled by the field investigators including gynecologists and general practitioners in the aforesaid study sites.Figure Cervarix and the non-exposed group will include subjects who did not receive any doses of HPV vaccine.Subjects will be stratified into three age groups  and divided into exposed and non-exposed groups by vaccination status. The exposed group will include subjects who received 1 or 2 doses of During the study period, two visits will be scheduled for all subjects at Month 0 and Month 36, which means the follow-up period will be 3 years. In the first visit, the questionnaire survey will be administrated for all the subjects to obtain the demographic information, sexual history, menstrual and obstetrical histories, etc. For the ones who are eligible for the cervical cancer screening , the type-specific HPV DNA PCR testing will be given within 2 weeks after the enrollment. After 3-years follow-up, the subjects will be called back for the second visit. A questionnaire which measures any changes of behavior during the follow-up period will be performed. Then the second screening with type-specific HPV DNA PCR testing will be given within 2 weeks after the call-back.At each visit, type-specific HPV DNA PCR testing will be the primary screening approach, and for the ones with unsatisfactory findings  will be referred to the local abnormal cervical cancer screening results management system for further medical activities Fig. Cervarix will be assessed as the exploratory objective.By the end of the follow-up period, the prevalence of the HPV infection, cervical disease  will be described in each birth cohort by their exposure status. If the sample size is sufficient, the effectiveness of For those who were lost, retrieve will be conducted by making phone calls as far as possible. For those who failed to be tracked, the reasons for loss to follow-up will be investigated as far as possible, and the reasons for loss to follow-up will be analyzed. At the same time, the baseline data of lost and non-lost patients, and the ratio of loss to follow-up between exposed and non-exposed groups will be compared to estimate the possible bias.All the data collected from the surveys and cervical cancer screenings will be documented in the YRHIP, .Once the subject is recruited into the study with signed informed consent form, she will be identified in the YRHIP via her resident identification number and marked as the study subject, and new subpage which contains the study data will be created on her personal file in the YRHIP. The data of the paper-based questionnaire survey will be transcribed into corresponding fields and the cervical cancer screening data will be synchronized with existing healthcare activity page on real-time. Besides the survey and screening data, we’ll also obtain the data of general information, enrollment date, scheduled time of second visit, call-back status, HPV vaccination history, self-initiated cervical cancer screening, cervical related treatment or medication from the YRHIP.We will describe the distribution and group differences of the subjects’ general characteristics and the incidence of HPV infection and relevant disease in each age cohort by the exposure status. The categorical data will be described by frequency (proportion) and the Chi-squared test will be performed to show the group difference. The continuous data will be described by mean (standard deviation), and non-normal distribution continuous data will be described by median (quantiles), and then the ANOVA or Wilcoxon rank-sum test will be performed to compare the difference across age groups. Also, the Kaplan–Meier method will be used to draw the survival graph, based on the actual number of cases of each endpoint.The Logistic Regression will be performed to analyze the impact on HPV 16/18 infection, and HPV 31/33/45 infection in each birth cohort 3 years after vaccination, after adjusting the confounders such as the demographic characteristics, history of sexual behavior, personal behavior history, etc. The vaccine impact will be calculated by using (1-Relative Risk) and its 95% CI.Stratification analysis will be conducted by frequency of sexual activity, numbers of sexual partners, extramarital sexual activity, family annual income, education level, and cervical cancer screen history. The interaction term between the above factors and HPV vaccination will be introduced into the Logistic regression model, and the differences between the model with interaction term and the model without interaction term will be compared, so as to evaluate the interaction between different factors and HPV vaccination.clinicaltrials.gov (NCT05341284).The protocol for this study has been approved by the Peking University Institutional Review Board, which have accepted responsibility for supervising all aspects of the study . All subjects and/or their LARs who agree to participate in the study will sign informed consent. Only the researchers associated with the study and the Ethics Committee would have access to the research data. The results of this study will be presented at both national and international conferences and be considered for publication in a peer-reviewed scientific journal. All the results presented in this study will be of group data; therefore, individual participants will not be identifiable. This study has been registered on No subjects or their LARs has been or will be involved in the development of the plan for designing, conducting, reporting or implementing this study.Cervarix’s impact in Chinese females.In order to eliminate cervical cancer during the twenty-first century, WHO recently launched a 90–70-90 target that advocated 90% of girls to be fully vaccinated with HPV vaccines by age 15 years, 70% of women to be screened with a high-performance test, and 90% of women identified with cervical disease received relevant treatment [Cervarix in women of different ages. Previous studies have shown that the age of the HPV vaccination is one of the most important factors affecting its effectiveness [Our study has two main strengths. Firstly, this study will use the multi-age birth cohort design, and adjust the age confounders in multi-factor analysis to evaluate the impact of tiveness . Anothertiveness , 26. A pDespite the above strength, this study will still be facing some limitations and challenges in feasibility. First, the long recruitment period may face more uncertainties, such as the possible shortage of targeting vaccines and public health crisis like COVID-19, etc. If these uncertainties happen, it will eventually extend the whole study period and increase the risk of not completing the study in a timely and high-quality manner. Second, the number of drop-out participants in non-exposed group may lower the statistical power. It is planned that the administration of HPV vaccines in non-exposed group should be excluded during the follow up. Although subjects will be confirmed to be not having the intention to get HPV vaccination in the following 36 months when being recruited into the non-exposed group, there will still be possibility for them to get HPV vaccine. If this unexpected expose happens in large scale because of policy alteration such as the expanded HPV vaccination campaign in local area, this scenario may lead to the insufficient statistical power of final association analyses. However, with the high coverage of HPV vaccines, the alternative study design such as test-negative design may be able to be conducted. Since China is now making great effort to popularize different types of HPV vaccines, it is possible that a nonnegligible number of participants in non-exposure group will get vaccinated by quadrivalent and 9-valent vaccines. Thus, it is valuable to conduct post-hoc analysis by valent in such case. In addition, information on demographic characteristics, menstruation and obstetrical histories, history of sexual behavior, personal behavior history, history of disease and pathogen infection, medication history, and family history are collected using self-administered questionnaires, which will introduce recall bias and reporting bias.This is the first prospective cohort study in China to assess the impact of HPV vaccine on HPV infection and related cervical diseases in females aged 9–45 years, which makes up for the lack of evidence in Chinese females. The results of this study will provide more evidence to understand the impact of bivalent HPV vaccination in Chinese females, and make a contribution to increasing HPV vaccination and cervical cancer screening coverage in China.


E6/E7 genes. We further demonstrate that multiple clonal integration events are involved in the use of shared breakpoints, the induction of inter-chromosomal translocations and the formation of extrachromosomal circular virus-human hybrid structures. Combined with the corresponding RNA-seq data, we highlight LINC00290, LINC02500 and LENG9 as potential driver genes in cervical cancer. Finally, we reveal the spatial relationship of HPV integration and its various structural variations as well as their functional consequences in cervical cancer. These findings provide insight into HPV integration and its oncogenic progression in cervical cancer.Integration of human papillomavirus (HPV) DNA into the human genome is considered as a key event in cervical carcinogenesis. Here, we perform comprehensive characterization of large-range virus-human integration events in 16 HPV16-positive cervical tumors using the Nanopore long-read sequencing technology. Four distinct integration types characterized by the integrated HPV DNA segments are identified with Type B being particularly notable as lacking  The molecular mechanisms underlying cervical carcinogenesis following integration of HPV DNA into the human genome remain elusive. Here, the authors perform long-read sequencing in 16 HPV16-positive cervical tumors and identify distinct integration types, structural variations and potential driver genes. Persistent infection with high-risk human papillomavirus (HPV) is the main cause of cervical cancer3. HPV incorporates a group of small (~7.9 kb in size) circular double-stranded DNA viruses that commonly infect humans, often showing considerable tropism on cutaneous and mucosal epithelia. It consists mainly of three functional parts: an early region that encodes for proteins of E1, E2, E4–E7 genes required for viral replication; a late region that encodes for proteins of L1 and L2 genes necessary for viral assembly; and an upstream regulatory region (URR) between E6 and L1, important for viral gene transcription and DNA replication. To date, more than 200 types of HPV have been identified5, of which 15 are assigned as high-risk types because of their association with carcinogenicity7. HPV16 is the most predominant high-risk type detected in cervical diseases, followed by HPV18, which together contribute to over 70% of cervical cancers worldwide9.Cervical cancer has the second-highest incidence rate and mortality rate of all gynecological malignancies worldwide, accounting for ~604,000 new cases and 342,000 deaths in 202011. Contrary to the episomal state during the normal infectious cycle, high-risk HPV DNA is often integrated into the host genome during persistent infections. This is considered an important molecular event in cervical carcinogenesis14. Upon integration, deregulated expression of viral oncogenes E6 and E7 is frequently observed, which may result from the disruption of their negative regulators E1 and/or E215, and the increased stability of E6 and E7 mRNAs expressed from the viral-host fusion transcripts17. Of note, a study also showed that there was no significant association between the expression levels of viral oncogenes and the physical state of the viral genome based on cervical biopsy materials, implying that the constitutive expression rather than the expression level of viral oncogenes seems to play a decisive role in the transformation and the maintenance of malignant phenotype18. Oncoproteins E6 and E7 are thought to be major contributors to cervical malignant transformation by interfering with a variety of key cellular molecules, including the inactivation of the cellular tumor suppressors p53 and pRb, respectively21. Concomitants to this process are accumulated genetic alterations  in the host genome, which is another frequently observed event associated with HPV integration and represents important co-factors in tumorigenesis24. Notably, it has been argued that enhanced expression of viral oncogenes per se is sufficient for cellular immortalization but not for malignant transformation and that secondary genetic events centered on the host genome are also necessary for malignant progression of HPV-related cancers23.Most HPV infections are transient and can be cleared spontaneously by the immune system within 1–2 years. However, a few persist for many years or even decades, and eventually lead to cancer31. Although the integration sites were dispersed across the human genome, several recurrent genomic hotspots that are potentially involved in important cancer-related pathways were also identified28. Likewise, viral breakpoints also occurred throughout the viral genome, although these were more likely to occur in E1 or E227. The coexistence of scattered breakpoints and recurrent hotspots could be the combined result of genomic accessibility 33 and selective advantage27. HPV integration can trigger rearrangements and amplification of the host genome, especially changing (most likely increasing) the expression of host genes around integration sites28. Several integration mechanisms have been proposed, two of which are widely accepted. In the first, a microhomology-mediated DNA repair model is suggested based on the frequent observation of microhomologous sequence between the host and viral genomes near the integration site27. In the second, the “looping” model mediated by DNA replication and recombination is proposed to explain the HPV-host integrant concatemers at integration sites though it is not experimentally verified25.Next-generation sequencing (NGS) technologies can process millions to billions of short reads (~150–300 bp) in parallel over short time periods. This has revolutionized genomic and biomedical research. Using NGS technologies, several studies have been carried out to characterize genome-wide alterations in both viral and host genomes upon HPV integration in cervical cancer35. In other studies, two or more close breakpoints (about hundreds of kb apart) were inferred as an integration event27. Due to the heterogeneity of tumor cells, these integration breakpoints were not necessarily from the same clone. Therefore, the integration events defined by these discrete breakpoints may not represent a single clonal integration event in tumors. In addition, it is difficult to identify long or complex structural variations in the host genome upon HPV integration using the current short-read NGS technologies.One drawback of the short-read length (~150–300 bp) of the current NGS technologies is that this limits further characterization of HPV integration on the genome. It only allows detection of integration sites  between virus and human genomes, rather than complete clonal integration events that incorporate the collection of chimeric reads (>5 kb) containing at least one fragment of HPV DNA surrounded by the human genome on both sides. In some short-read NGS studies, integration site and integration event were used interchangeably to express the same molecular event, that is, the integration site was taken for granted as an integration eventLINC00290, LINC02500, and LENG9 as potential driver genes for cervical cancer. Finally, we reveal the spatial relationship of HPV integration and its various structural variations (SVs) as well as the functional consequences of these SVs in cervical cancer. These findings provide insight into the HPV integration and its oncogenic progression in cervical cancer.To address the above challenges, in this study, we perform a comprehensive characterization of large-range virus-human integration events in 16 HPV16-positive primary cervical tumors using the Nanopore long-read sequencing technology. We identify a total of 63 HPV integration breakpoints in 15 cervical tumors, of which 12 are identified with at least one clonal integration event. Four distinct integration types that are frequently present in the identified clonal integration events are characterized. We reveal that multiple clonal integration events are involved in the use of shared breakpoints. Moreover, we demonstrate the induction of HPV-mediated translocations between chromosomes and the formation of extrachromosomal circular (ECC) human-virus hybrid DNA structures in these clonal integration events. Combined with the corresponding RNA-seq data, we highlight 36, the cleaned long reads were aligned to a custom in-house reference genome comprised of the human genome and multiple HPV genomes. Sniffles, an SV caller for long-read sequences36, was then employed to detect virus-human integration breakpoints with at least three supporting chimeric reads. As a result, a total of 63 integration breakpoints were identified in 15 out of 16 cervical tumors  and E2 gene (P = 0.009)  is preferred, which may lead to the dysregulation of oncoproteins E6 and E7, thereby promoting cervical carcinogenesis. In the host genome, integration breakpoints occurred more frequently in intragenic regions  than intergenic regions  (P = 1.0e-4)  Fig. . These fe P = 0.05 and E2 By taking advantage of long-read sequencing, we detected clonal integration events which were defined as a collection of chimeric reads (> 5 kb) containing at least one fragment of HPV DNA wrapped on both sides by the human genome Table . NanoporE6/E7 genes . While we did not find evident associations between other integration features (such as integration types) and clinical consequences.Based on the integration features identified above, we explored their association with clinical consequences Table . To dateNext, we analyzed the relationship between integration breakpoints and clonal integration events Fig. . As descBased on the shared breakpoints discovered above, we further analyzed their possible intrinsic links to intratumor heterogeneity in cervical cancer. Figure P = 0.009).In addition to ZLR-12, two other patients (ZLR-08 and ZLR-11) carrying shared breakpoints were also inferred to bear some intratumor heterogeneity. Patient ZLR-8 completely lost contact with us and her status was unavailable, while patients ZLR-11 and ZLR-12 died of tumor recurrence, suggesting that intratumor heterogeneity may contribute to their poor prognosis 40.We then identified genes potentially disrupted by HPV integration, including those directly disrupted by HPV integration or those closest to HPV integration sites. As a result, a total of 34 genes (including 27 protein-coding genes and 7 non-coding RNAs) were annotated near integration breakpoints  terms and KEGG pathways showed that these genes potentially disrupted by HPV integration were involved in Rho protein signal transduction and in the regulation of cytokine production  = 1.21e-58). A total of 12 breakpoints were detected in ZLR-08, of which 6 were involved in 5 detected integration events, with 1 breakpoint being commonly used in all 5 integration events . For the overexpression assay, a full-length human LENG9 sequence was obtained by PCR and subcloned into the PLVX-puro vector by Lipofectamine 3000 to establish cells that stably overexpressed LENG9. Consistently, upregulation of LENG9 in CaSki and SiHa cells significantly increased proliferation, migration, and invasion of cervical cancer cells  with relatively low expression of Finally, we evaluated the potential biological relevance of somatic SVs detected by long-read sequencing to HPV integration. We first checked the overall somatic SV landscape in cervical cancer with HPV integration. The median number of purified somatic SVs per genome was 5324. However, an extremely high SV burden was found in ZLR-08 tumor. INVDUP and DEL were the main SV types, accounting for 78.0% of the total SVs  regions46, implying a potential preference for HPV integration-related SVs arising from DSBs. Disruption of TAD boundaries by structural variants has also been reported to cause developmental disorders47. In our data, the relative proximity of SVs and TAD also reveals the potential consequence of SVs occurring near HPV integration sites  boundaries Fig. . The strtes Fig. .Z score was used to estimate the expression change in samples with SVs, as compared to other samples. In this, 33.3% of genes had aberrantly high expressions in DUPs  detected three or more clonal integration events. These distinct integration events in the same sample tended to be clustered together and partially overlapped with different breakpoints. The Nanopore long-read sequencing technology used in this study is amplification-free and allowed direct, long-read sequencing of native DNA, thereby eliminating any potential PCR bias. Each chimeric read likely represents a single cell within the sequenced bulk cells. It is less likely that these integration events simultaneously occurred in a diploid cell since there are generally only two copies of a specific chromosomal site for viral integration. Second, some of these events shared the use of the same integration breakpoints within the same tumor. It is also less likely that these distinct integration events occurred in different cells independently yet produced the same breakpoint. A reasonable inference is that these integration events are evolutionarily related, and some integration events may derive from a primary integration event in a subset of its clonal cells. Understanding clonal evolution related to HPV integration is of great significance in revealing the mechanism of cervical tumor progression and metastasis which could then lead to the development of new cancer therapeutic strategies.Our study reveals that these integration events may contribute to another layer of intratumor heterogeneity in cervical cancer in addition to somatic mutations and copy-number alterations. Of note, a recent study identified one of eight tumors displaying intratumor heterogeneity with respect to junction distribution through microdissection of tumor tissues52. However, current knowledge of viral integration in cervical tumors was mostly based on Southern blot and short-read sequencing analyses. These analyses yielded limited characterization of the complete virus-human integration events in cervical cancer. Using long-read sequencing technologies, we accurately characterized four distinct types of integrated HPV DNA segments that are frequently present in clonal integration events: Type A, a truncated HPV genome containing E6/E7; Type B, a truncated HPV genome lacking E6/E7; Type C, an overflowing continuous segment containing the intact HPV genome; and Type D, a combination of Type A, Type B or Type C. Of note, Type B, which lacks E6/E7 genes previously considered to be the main causes for cervical cancer, has been not reported in the literature to our knowledge. Despite this, Type B was not very rare in our dataset where 5 out of 22 detected integration events contained the integration Type B. On the other hand, based on our dataset , thereby likely promoting cervical carcinogenesis independently of E6/E7 oncogenesis. These remain to be further studied. In addition, our long-read sequencing analysis provides a high-resolution structure of these complex HPV integrations. This is best exemplified by the sample ZLR-02 where two different disrupted HPV16 genomes are interspersed with 5-bp cellular sequences and integrated at a single locus. Such an occurrence could not have been detected by previous methods such as Southern blot and short-read sequencing analyses.Characterization of integrated HPV DNA segments in the host genome will enable a better understanding of the pathogenic mechanism and the role of HPV in cervical cancer. Several forms of viral DNA integrated into the host genome have been previously proposed, including a single viral genome, multiple head-to-tail tandemly repeated viral genomes, and tandem copies of the HPV genome interspersed with host DNAset Fig. , the TypE6/E7 genes upon HPV integration is frequently observed in HPV-associated cancers. It is this that has been thought to be a primary trigger of the oncogenic progression by disturbing the cell cycle and inducing genomic instability in cervical cancer14. Secondary genetic events in the host genome, resulting from HPV integration, are also essential for the development and progression of cervical cancer. Combined with the corresponding RNA-seq data, we found 9 genes with significantly altered expressions near integration breakpoints. We further highlighted LINC00290, LINC02500, and LENG9 as potential driver genes in cervical cancer. Especially in the case of LENG9, we revealed the virus-human hybrid ECC structure, which can replicate autonomously and lead to subsequent amplification, possibly as a potential mechanism for the upregulation of target genes. We also performed functional analysis of LEGN9 using gain- and loss-of-function assays and validated its oncogenic role in cervical cancer. LENG9 is rarely reported in the literature. GO function analysis revealed that the molecular function of LENG9 is metal ion binding (GO:0046872), and the BioGRID database53 showed that LENG9 has 6 interactors, including C9ORF41, B4GALT2, CDC5L, D2HGDH, FOXS1 and OGT (https://thebiogrid.org/125106). In particular, B4GALT2 is also annotated to GO term of metal ion binding and its expression is dramatically reduced in tumor ZLR-08 compared to adjacent normal tissue. It has been reported that depletion of B4GALT2 inhibits p53-mediated cell apoptosis in Hela cells54. Furthermore, CDC5L  has been reported as a positive regulator of cell cycle G2/M progression55. Their interactions with LENG9 may be a potential mechanism underlying the promotion of cell proliferation and migration when LENG9 is upregulated in cervical cancer cells while these warrant further functional investigation in the future.Dysregulated expression of LENG9, two other genes, LENG8 and CDC42EP5, were also affected by HPV-related aberrant genomic events in ZLR-08 . The study was conducted in accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects. All subjects provided informed consent to participate in the study. All tumor tissues were obtained at the time of diagnosis before any treatment was administered. Fresh tissues were collected, snap-frozen in liquid nitrogen, and stored at −80 °C. Clinical information  was extracted from pathology reports. A review of hematoxylin and eosin (H&E) slides was performed by a gynecologic pathologist to confirm the diagnosis. Tumor cell content of sections from frozen cervical tissue samples embedded in optimal cutting temperature medium was confirmed to be > 70% by H&E staining.TM PCR thermal cycler. The 16 HPV16 E6 positive samples were then prepared for Nanopore sequencing.Genomic DNA was extracted from 25 mg of the tissue using PureLink® Genomic DNA Kit . The DNA concentration of each sample was measured using Nanodrop 2000  and DNA integrity was assessed using agarose gel electrophoresis. DNA samples were subjected to PCR using specific primers of HPV16 E6. PCR was performed using a ProFlexSequencing libraries were constructed following the instructions from Oxford Nanopore Technologies (ONT) for 1D ligation sequencing on PromethION. Firstly, the quality of input genomic DNA was checked and 2 μg high molecular weight genomic DNA was sheared into long fragments with an average size of 8 kb using g-TUBE (Covaris). These DNA fragments were then repaired, end-repaired, A-tailed, and adapter-ligated. DNA repair was conducted using NEBNext FFPE DNA Repair Mix . DNA end repair and dA-tailing were performed using NEBNext Ultra II End Repair/dA-Tailing Module . Adapter ligation was performed using the NEBNext Blunt/TA Ligase Master Mix (M0367L NEB) and a Ligation Sequencing Kit 1D (SQK-LSK109). DNA was purified between each step using Agencourt AMPure XP beads  and was quantified via a Qubit Fluorometer 2.0 . The prepared libraries were sequenced using a PromethION sequencer and 1D flow cell with protein pore R9.4.1 1D chemistry following the manufacturer’s guidelines. The Nanopore sequencing results were basecalled using the ONT’s basecaller Guppy (v4.0.11), converting the current intensity values (in fast5 format) to nucleic acid sequences (in fastq format). The original fastq data were further filtered to remove adapters, short reads (length < 500 bp), and low-quality reads , and then the total cleaned sequence data was obtained (Supplementary Table https://hgdownload.soe.ucsc.edu/goldenPath/hg19/chromosomes/) and multiple HPV genomes using the long-read mapper NGMLR 36. The output sequence alignment results in SAM format were further transformed to BAM format and sorted by genomic coordinates using samtools 56 for subsequent SV identification and breakpoints detection.The clean long reads were aligned to a custom in-house reference genome that comprises the human genome 36 was employed to detect all types of SVs  with three minimum supporting reads. The SV type breakends (BND) involving HPV were extracted and the junction position of human and HPV sequence was reported as the breakpoint for HPV integration. The breakpoint positions on the human genome were then extracted and annotated using ANNOVAR57; while corresponding positions on the HPV16 genome were annotated using an in-house program based on the latest HPV16 reference sequence with gene annotation (7906 bp) from the Papilloma Virus Episteme (PaVE) (https://pave.niaid.nih.gov).The long-read SV caller Sniffles . First, chimeric reads were extracted from the NGMLR alignment results using samtools56. These read sequences were then realigned to the custom in-house reference genome as described above, using megablast of local BLAST+ . Finally, using in-house Perl scripts, these chimeric reads containing at least one intact integration event  were further analyzed on a case-by-case basis. Some representative clonal integration events were visualized using the R statistical package .Although the alignment results from NGMLR already contained partial integration event information, these were not sufficient to identify HPV clonal integration events. Therefore, we re-analyzed chimeric reads that span both human and virus genomes using BLAST+ 36. Prior to SV annotation and analysis, we filtered SVs using the following criteria: (1) removal of variants covered by less than three reads to reduce the false negative, (2) removal of SVs whose length < 50 bp, (3) removal of non-canonical SV types including DEL/INV, DUP/INS and INV/INVDUP. AnnotSV 59 was then used to annotate filtered SV and provide gene-level information.SV types including BND, deletion (DEL), duplication (DUP), insertion (INS), inversion (INV), and inverted duplication (INVDUP) were detected using Sniffleshttps://github.com/arq5x/bedtools2)60. The replication time metric was calculated as averaged Wavelet-smoothed signal value per window by Repli-Seq data in HeLa-S3 cell line from ENCODE61. A TAD boundary was obtained from the study of Dixon et al.62, where the distance to nearest boundary was normalized as log2(kb of distance + 1). A recombination value was obtained from the HapMap Project63, with the value at the nearest point taken for annotation. The core 15 chromatin states were then downloaded from the Roadmap Epigenomics Project64.We divided the reference genome into non-overlapping windows of 1 kb, summarized each genomic feature per window, and then mapped the summarized metrics to each variant using bedtools 66.RNA-seq libraries were prepared for the same set of cervical tumor tissues using the NEBNext Ultra RNA Directional Library Prep Kit according to the manufacturer’s instructions. Libraries were multiplexed and sequenced on a HiSeq X10 sequencer with 150 bp paired-end reads . Briefly, adapters and low-quality  sequences were trimmed from the output reads  at 37°C in a heating block and the digestion was carried out continuously for 5 days, adding additional ATP and DNase every 24 h according to the manufacturer’s protocol. Then, the exonuclease was heat-inactivated at 70°C for 30 min. The complete removal of linear DNA was confirmed by qPCR of the COX5B gene.PCR oligos were designed using Primer3web (version 4.0) to yield products across junctions of ECC DNA evaluated in the study  were purchased from the American Type Culture Collection (ATCC) . CaSki cells were cultured in RPMI-1640 medium . SiHa cells were cultured in MEM medium (Gibco). All medium was supplemented with 10% fetal bovine serum  and 1% penicillin/streptomycin solution (Gibco). The two cell lines were maintained in a humidified atmosphere with 5% COLENG9, whereas the mock vector without LENG9 sequence was used as a control. For knockdown assays, three short interfering RNAs (siRNAs) targeting LENG9  at a final concentration of 10 μM following the manufacturer’s instructions. The transfection efficiency of LENG9 in cells was determined by western blot with antibody LENG9 . GAPDH antibody was used as a loading control antibody .For overexpression assay, the full-length human LENG9 sequence  was obtained by PCR and subcloned into the PLVX-puro vector by Lipofectamine 3000  to establish cells stably overexpressing RNA was isolated from cells using Trizol reagent  following the manufacturer’s instructions. Reverse transcription was performed using HiScript® II Q RT SuperMix . Quantitative real-time (RT) PCR was performed on the cDNA using the ChamQ Universal SYBR qPCR Master Mix (Vazyme). GAPDH was used as an endogenous control for normalizing the expression of tested genes.Cell proliferation assays were performed using the Cell Counting Kit 8 . First, cells were seeded at a density of 1000 cells/well in 96-well plates containing 100 µL of the medium. Then, OD450 was measured 2 h after adding 10 µL of CCK8 solution. Cell migration and invasion assays were performed using Transwell chambers  following the manufacturer’s instructions. Cells were transfected and cultured with a serum-free medium for 24 h. Next, these cells were detached and resuspended in a serum-free medium. Then, these suspended cells were added to the upper transwell chambers for migration and invasion assays. At the same time, RPMI-1640 medium (for CaSki) or MEM medium (for SiHa) supplemented with 10% FBS was added to the bottom chamber. After an appropriate time to migrate or invade, the cells that migrated into the bottom chamber were fixed with 100% methanol and stained with 0.1% crystal violet staining solution. Images were captured from each membrane and the number of migratory cells was counted under a microscope .t test was used to analyze the differences between groups. KEGG pathways and GO terms that were enriched for genes potentially disrupted by HPV integration were detected using Metascape (https://metascape.org/gp/index.html/main/step1). Fisher’s exact test was used for assessing the association of integration features with clinical consequences. All statistical analyses were implemented in the statistical package R .Data are presented as mean ± standard deviation of three or more independent experiments. A two-sided Student’s Further information on research design is available in the Supplementary InformationPeer review fileReporting Summary


Metabolic disturbances and immune alterations caused by diabetes are not just bystanders of HPV infection, but the conclusion that diabetes increases the risk of HPV infection requires more clinical epidemiological evidence to confirm. Our aim was to evaluate the association of diabetes with HPV infection risk in female patients aged over 50 years in the cervical clinic.We conducted a cross-sectional study of 6402 women aged over 50 years in the cervical clinic between May 2019 and March 2022 from China’s largest academic woman’s hospital. The quantitative-effect relationship between diabetes and HPV infection was observed by dose-response graph. Segmented multivariate logistic regression analysis was conducted to estimate the relative risk of HPV infection in diabetes patients. Multivariable predicted marginal proportions from logistic regression models were used to compute adjusted risk ratios.There is a nonlinear relationship between HbA1c and the risk of HPV infection. When the HbA1c exceeds 5.7%, there is a saturation effect. After adjustment for confounders, the risk ratio for HPV infection in women with prediabetes was 1.09 (95% CI: 1.00-1.18) compared with women with HbA1c <5.7%, and the risk ratio for HPV infection in women with diabetes was 1.18 (95%). CI: 1.04-1.33). Sensitivity analysis showed that the risk ratio for HPV infection was 1.47 (95% CL: 1.07-1.91) when diabetes was associated with vaginitis. E-value analysis suggested robustness to unmeasured confounding.Diabetes and prediabetes are at increased risk of coinfection with HPV in female patients aged over 50 years in the cervical clinic. The prevalence of diabetes has increased dramatically globally, affecting more than 8% of the world’s adults , and in Diabetes can lead to metabolic disorders and immune alterations that may be potential triggers for persistent HPV infection, diabetes rather than it being just a “bystander” of the infection of HPV . HoweverTo elucidate the risk of persistent HPV infection in women with diabetes or prediabetes, our cross-sectional study, using HbA1c as a diagnostic criterion for diabetes, explored the association between diabetes and HPV in female cervical outpatients over 50 years of age, and risk ratios adjusted for confounders were calculated by multivariate predictive marginal proportions from a logistic regression model.Our study was a cross-sectional study with a total of 6402 women aged over 50 years between May 2019 and March 2022 at the Obstetrics & Gynecology Hospital of Fudan University , which was China’s largest academic woman’s hospital. Inclusion criteria: HPV-DNA examination and HbA1c determination were performed at our cervical clinic, aged over 50 years. Study exclusion criteria were as follows: HPV and HbA1c related records were not performed. Clinical data and results were obtained from Hospital Information System (HIS) and Laboratory Information Management System (LIS). All patients in this study were anonymous, in accordance with the principles of the Declaration of Helsinki and approved by Ethics Committee of the Obstetrics & Gynecology Hospital of Fudan University.HbA1c results were used as exposure factors in this study. HbA1c was analyzed using the Hemoglobin Testing System . Confounding factors included age, BMI, history of adverse pregnancy, vaginitis, and syphilis. According to the American Diabetes Association, an HbA1c level of 6.5% or higher defines diabetes. An HbA1c level of 5.7%-6.4% was defined as prediabetes.HPV testing was performed in the pathology department with 1 of 2 HR-HPV testing methods during the study period: the Cobas 4800 system (Roche Diagnostics), or BioPerfect (Bioperfectus Technology). Any type of HPV positive is considered a positive event.Data are presented as means (SD) for continuous variables and percentages (%) for dichotomous variables. A smooth curve fit plot of HbA1c was created to examine the shape of the relationship between HbA1c and HPV. We applied a two-segment linear regression model to test the saturation effect of HbA1c on HPV based on smoothing plots. A segmented regression model was then used to compare the differences between models I and II by performing log-likelihood ratio tests for the single-linear linear regression model and the two-segment linear model. P-value<0.05 means Model II is significantly different from Model I, which indicates a non-linear relationship. We used multivariable predicted marginal proportions from logistic regression models to compute adjusted risk ratios for the association between HbA1c and HPV. The models were adjusted for age, obesity, abnormal pregnancy history, vaginitis, history of syphilis. The robustness of these findings was assessed in multiple sensitivity analyses. First, Subgroup analyses were performed according to BMI and vaginitis as stratification factors, and interaction tests assessed whether the relationship between diabetes and HPV was consistent across subgroups. Second, we explored the potential for unmeasured confounding between diabetes and HPV by calculating E-values . The E-vOur study included 6402 cervical outpatients over the age of 50, with a mean age of 58.01 ± 6.51 and an HPV-positive rate of 34.16% (2187 cases). Mean glycated hemoglobin was 5.79 ± 0.75%. A piecewise regression model between HbA1c and HPV found a saturation effect when HbA1c was 5.7%. When HbA1c<5.7%, for every 1% increase in HbA1c, the risk of HPV positivity increased by 44% . When HbA1c≥5.7%, for every 1% increase in HbA1c, the risk of HPV positivity increased, the risk was increased by 7% . Log-likelihood ratio test: P<0.001, there is a non-linear relationship between HbA1c and HPV risk Table 2.After adjustment for confounders, the risk ratio for HPV infection in women with prediabetes was 1.09 (95% CI: 1.00-1.18) compared with women with HbA1c <5.7%, and the risk ratio for HPV infection in women with diabetes was 1.18 (95%CI: 1.04-1.33) Table 3.Sensitivity analyses by BMI and vaginitis found that the effect of HbA1c on HPV was consistent between subgroups Table 4.Our large cross-sectional study analyzed the association between diabetes and prediabetes and HPV positivity, adjusting for confounders including age, BMI, history of adverse pregnancy, vaginitis, and history of syphilis. We found that both diabetic and prediabetes patients had different degrees of increased HPV positivity. Subgroup analyses showed a consistent association between diabetes and HPV infection in women with different characteristics, with a significant 47% higher risk of persistent HPV infection when diabetes was associated with vaginitis. At the same time, we found for the first time that there is a saturation effect on the effect of different blood glucose control levels on HPV persistent infection. Elevated HbA1c increases the risk of HPV persistent infection, but when HbA1c exceeds 5.7%, the effect is weakened. Our study suggests that high blood sugar levels may be one of the triggers of HPV persistent infection, and provides clinical epidemiological evidence for a deeper understanding of the mechanism of HPV persistent infection.The results of existing studies are inconsistent, and there is no consensus on the relationship between diabetes and HPV infection. A study in Turkey found that diabetic patients (30-65 years old) had higher HPV 16 positivity than non-diabetic patients . A DanisOur research is based on a cross-sectional study of cervical outpatient clinics in China’s largest academic woman’s hospital. Since we did not find an association between glycated hemoglobin and HPV infection in women aged 20-50, we only found an association between 20-50-year-old women. The association was found in women with cervical clinic visits. Among these patients over 50 years old, there were 3135 (48.97%) non-diabetic patients, 2651 (41.41%) prediabetes patients, and 616 (9.62%) diabetic patients. The HPV positive rate of diabetic patients was as high as 36.69%, and the HPV positive rate of non-diabetic patients was 33.14%.Since the median age of onset of diabetes in China is 51.3 years , infectiA picture emerges in which diabetes is not only a metabolic disease, but one with profound and sustained effects on immune cell function . DiabetiA normal immune system clears most HPV infections quickly. However, hyperglycemia may contribute to virus-host interactions as well as changes in the immune system in diabetic patients, possibly increasing the risk of reactivation of latent HPV infections and/or reducing the ability to clear newly acquired HPV infections , 21–23.Given the increased risk of various infections in people with diabetes, poor glycemic control appears to exacerbate this risk. Studies evaluating the effect of glycemic control (HbA1c) on HPV infection are therefore warranted, as good glycemic control has previously been shown to reduce the risk of other infections , 25. ComOur study was a large cross-sectional study using relatively recent data (2019–2022) reflecting current disease patterns and trends; adjusted for age, BMI, adverse maternal history, vaginitis, syphilis History-inclusive risk factors reduce selection bias. Our data provide clinicians with additional evidence that women over 50 years of age with diabetes are at higher risk for persistent HPV infection. Using single and stable glycated hemoglobin to assess glycemic status is more clinically attractive.Our study also has some limitations. First, the cross-sectional data cannot be used to determine causal relationships. Second, retrospective studies are imperfect and lack information on lifestyle-related factors such as sexual behavior and smoking. But we included a history of syphilis to make up for the lack of an adverse sexual life history, and the smoking rate of Chinese women is about 2.1%, which is at a very low level . These uThe findings of this study have important clinical and public health implications. Our study found a higher risk of persistent HPV infection among women with diabetes over the age of 50. There are differences in the HPV positive rate among people with different blood sugar levels. This difference suggests that clinicians need to pay attention to the blood sugar control of HPV positive patients. For women over 50 years old with hyperglycemia, cervical cancer screening strategies need to be re-established.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Ethics Committee of the Obstetrics & Gynecology Hospital of Fudan University (2022-78). The data are anonymous, and the requirement for informed consent was therefore waived.CYY analyzed the data, drafted the manuscript and contributed to study design. CYZ contributed to data collation. CMY and HJ revised the article. All authors contributed to the article and approved the submitted version.This work was supported by the program for National Natural Science Foundation of China (No. 81902131) and Shanghai “Rising Stars of Medical Talents” Youth Development Program (SHWRS (2020)_087).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


HPV52, 16, 58, CP8304, 51, 53, 39, and 68 were the most prevalent HPV types. The relative HPV-positive rate correlated positively with the progression of cervical intraepithelial neoplasia (p < 0.001); HPV16 was the predominant carcinogenic type, followed by HPV52 and HPV18. HPV infections were significantly age-specific, and 26.51%  of cases were caused by multiple HPV types. In addition, HPV infections typically cleared over a median time of 16 (interquartile range 9–31) months, and the clearance of HPV16 was significantly faster than that of other types (p < 0.001). These findings may serve as a guide for local governments to evaluate HPV vaccination and cervical cancer prevention strategies in south China.Persistent high-risk human papillomavirus (HPV) infection is the pivotal cause of cervical carcinogenesis. HPV types distribution varies greatly by region, and its long-term changes of prevalence remain to be fully characterized in China. Here, the largest population of 198,111 consecutive women who underwent routine cervical screening were investigated from 2015 to 2021 in Guangzhou, south China. The results showed that the overall HPV prevalence was 21.66% , and the annual prevalence increased significantly from 2015 to 2021 ( Cervical cancer (CC) is the fourth most common malignancy in women. Approximately 604,000 CC cases and 342,000 deaths, equivalent to 7.7% of all cancer deaths, were reported worldwide in 2020 by the International Agency for Research on Cancer (IARC) . In fortHPV is typically divided into “low-risk” and “high-risk” types , and 12 Vaccination against HPV16 and 18, and some other high-risk types has the potential to prevent HPV-related infection by up to 90% . MoreoveAs the main contributor to the global cancer burden, China accounted for 18.7% of the overall morbidity and 15.3% of the mortality associated with CC . A detaiThe study population constituted women who underwent routine cervical exams at Guangdong Women and Children Hospital between 2015 and 2021 in Guangzhou, China. All females underwent genotype testing of HPV and cervical cytological evaluations combined with colposcopy. The exclusion criteria were pregnancy, a total hysterectomy, systemic infection or autoimmune diseases, surgery for uterine diseases within 3 days, or other cancers. Ethics approval was obtained from the Ethics Committee of the Guangdong Women and Children Hospital .Patients with cervical abnormalities, based on cytological screening cytological screening  and colposcopy, underwent histopathological examination for a final diagnosis as per the criteria of Bethesda 2014 . PatholoHPV deoxyribonucleic acid (DNA) typing was performed using an HPV genotyping kit , which was based on DNA amplification with HPV L1 consensus polymerase chain reaction primers and the flow-through hybridization technique. It can recognize 21 common types (15 high-risk and six low-risk). All protocols were performed according to supplier's manual, as described previously ,20.HPV clearance was defined as one getting at least two consecutive HPV-negative results after being tested positive. The HPV-positive women who received HPV DNA testing at least once a year within the subsequent 5 years after the initial visit were enrolled in the cohort of HPV clearance, excluding HPV infections confirmed before the initial visit and those who had one or more HPV types and obtained a new and different HPV type later. The estimated time to HPV clearance in HPV-positive women was depicted as a Kaplan–Meier plot, and the hazard ratios (HRs) and 95% confidence intervals (CIs) for the time to HPV clearance were calculated using a Cox proportional-hazards model.2 test was used to evaluate the significant differences. The linear regression models with gamma value were used to assess the changes of prevalence in different diagnosis groups and over the calendar year. Chord diagrams were constructed using HPV type co-infection data. Moreover, to quantify the age patterns of different diagnoses, we also created a heatmap of the proportions of age groups identified in each group. p < 0.05 was considered statistically significant.SPSS 25.0  was used for statistical analysis. The quantitative data are presented as the median and interquartile range (IQR), and Kruskal–Wallis/Dunn’s test were used for comparisons between groups. The categorical variables are described as percentages, and the χp < 0.001). The median age was 50 (43–56) years in the ICC group, which was significantly higher than that in the other groups ; in contrast, the median age was 32 (28–39) years in the inflammation group , which was lower than that in the other groups. However, no significant difference was observed between the LSIL and normal cervix groups (p > 0.05).In total, 198,111 females were enrolled, with a median age of 33 (IQR 28–40) years. Among them, 53,439 (26.97%) had a normal cervix, 112,999 (57.04%) were diagnosed with inflammation, 12,251 (6.18%) were diagnosed with ASC-US/-H, 8108 (4.09%) were diagnosed with an LSIL, 3243 (1.64%) were diagnosed with an HSIL, 799 (0.40%) were diagnosed with ICC, 1257 (0.63%) were diagnosed with CA, and the remaining 6015 (3.04%) cases showed other clinical features. As shown in As shown in p < 0.001), except for HPV66 in ICC (p > 0.05). Specifically, the most prevalent types were HPV52 (13.90%), HPV16 (6.73%), and HPV58 (6.30%) in ASC-US/-H patients; HPV52 (22.02%), HPV58 (12.79%), and HPV16 (12.60%) in LSIL patients; HPV16 (28.31%), HPV52 (20.63%), and HPV58 (17.73%) in HSIL patients; and HPV16 (37.17%), HPV52 (13.77%), and HPV18 (8.39%) in ICC patients (p < 0.001). In detail, the prevalence of high-risk HPV, specifically HPV35, 45, 52, 56, 59, and 68, was significantly increased from 2015 to 2021 ; however, substantial decreasing trends were found for HPV33 and HPV66 , HPV58 (1.70%), and HPV16 (1.54%) were the most observed types in normal cervixes, similar to the prevalence of HPV52 (3.83%), HPV58 (1.44%), and HPV16 (1.46%) in the inflammation group. In the abnormal cervix groups , the positivity rates for all high-risk types were significantly higher than those in the normal cervix group . Regarding the types, HPV16 showed a significant increase with the progressive cancer, from 12.60% in patients with LSIL to 37.17% in those with ICC (p < 0.001), as did HPV31, HPV33, and HPV58. In contrast, the prevalence of HPV 52 decreased from 22.02% in patients with LSILs to 13.77% in patients with ICC (p < 0.001), which is in line with the trends observed for other HPV, including HPV35, 39, 51, 53, 59, 66, and 68 (p < 0.01) and HSIL , but no significant difference was found between LSIL and HSIL (p > 0.05).With the development of cervical carcinogenesis, the HPV prevalence significantly increased, from 78.91% in LSIL to 84.48% in ICC  were caused by a single HPV type, especially one high-risk type . Regarding the 26.51% (11375/42911) of multiple infections, 18.83% comprised double infections, 5.24% were triple infections, 1.67% comprised quadruple infections, and 0.77% were quintuple infections or more. With the development of cervical lesions, a decreasing trend in the prevalence of multiple infections was found from LSIL (38.72%) to HSIL (33.49%) to ICC (22.52%)  months, and the viral clearance rate within 5 years was 89.94% (2996/3331). The median times to HPV clearance of high-risk and low-risk were 16 (9–31) and 18 (10–31) months, and the viral clearance rates within 5 years were 89.82% (2699/3005) and 88.73% (551/621), respectively. No significant difference was found between women infected with high-risk and low-risk HPV . The median times to viral clearance in females aged < 21, 21-25, 26-30, 31-35, 36-40, 41-45, 46-50, 51-55, 56-60, and > 60 years old were 24 (11.5–36), 22 (11–40), 18 (10–36), 21 (10–38), 18 (9–38), 21 (10–39), 17 (9–36), 20 (12–41), 24 (8–51), and 30 (14–60) months, respectively, and the viral clearance rates within 5 years were 92.73% (51/55), 89.43% (364/407), 91.95% (742/807), 89.52% (675/754), 89.54% (471/526), 91.38% (350/383), 90.78% (187/206), 84.40% (92/109), 77.78% (42/54), and 73.33% (22/30), respectively (p > 0.05).The median times to viral clearance in patients infected with HPV16, 51, 52, 53, 58, and other high-risk types were 14 (7–36), 24 (11–40), 22 (11–42), 27 (14–47), 25 (11–52), and 20 (10–39) months, respectively, and the viral clearance rates within 5 years were 90.86% (547/602), 90.06% (290/322), 88.79% (705/794), 85.98% (227/264), 81.84% (338/413), and 89.60% (1103/1231), respectively  months, and the viral clearance rate within 5 years was 89.94%.HPV prevalence varies greatly in different regions of the world. In this study, the HPV prevalence over the past 7 years was 21.66%, which was consistent with the 21.07% (ranging from 18.42% to 31.94%) previously reported in 37 cities in China . HoweverAs the main cause of cervical malignancy, HPV can be found in almost all CCs tested under ideal conditions . This anp < 0.001; Supplementary Table S1). The higher positivity rate in ICC compared with the rate of 4.02% reported in individuals with a normal cervix also seems to confirm that HPV52 is the most carcinogenic type only after HPV16. When excluding co-infection with HPV16 or HPV18, HPV52-associated ICC was significantly less common than lesions associated with HPV16  and HPV18  . These observations reveal that compared with HPV16 and HPV18, the advantage of HPV52 in terms of persistence and progression to CC needs further investigation.Similar to that in other regions in China such as Beijing (5.64%) , SichuanMost notably, the prevalence of HPV52 increased by year, ranging from 5.04% in 2016–6.40% in 2020, whereas no change in prevalence was found for both HPV16 and 58. However, previous studies have shown that HPV52 was the second-most frequent type after HPV16 in this region before 2014 . This reConsistent with the results of previous studies ,16,21, oUsually, most HPV is rapidly eliminated by immunological intervention after viral infection , and onlOur results revealed that the clearance of HPV16 occurs faster than that of other types. This phenomenon is compatible with the potentially increased awareness of HPV16-associated cancer in females and the fact that these infections are more likely to receive timely and standardized treatment than other types. However, another study showed that the clearance time of some other types can be prolonged . As oldeFinally, CA refers to benign hypertrophic lesions in anal/genital area, attributed mostly to low-risk HPV types, which are frequently present as co-infections with high-risk HPV. In our analysis, most CA patients were infected by low-risk HPV6 and HPV11, and 7.52% were infected by a single strain or co-infected with HPV52. This observation is concordant with those in other prospective studies ,44.Our work has produced some convincing results, but there are still several limitations. First, this study is a single-center, hospital-based, and retrospective study. Second, we were unable to reliably track whether those females received additional therapies or medication treatment in other hospital after the initial visit. The HPV clearance was evaluated in females with and without treatment or surgery. Third, as some behaviors  may be associated with infection of HPV ,46. FurtIn summary, this study showed an overall HPV prevalence of 21.66% (42911/198111), with the annual rate significantly increasing from 2015 to 2021 in Guangzhou, China. HPV52, 16, 58, CP8304, 51, 53, 39, and 68 were the most prevalent HPV types. HPV16 was the predominant carcinogenic type, followed by HPV52 and HPV18. HPV infections were significantly age-specific, and 26.51%  of cases were caused by multiple HPV types. HPV infections were typically cleared with a median time of 16 months. These findings provide a valuable guide for local governments to evaluate cervical screening and vaccination programs in south China.Click here for additional data file.