Changes in Oral Papilloma Virus Infections Over Six Months in People Living with HIV

Changes in Oral Papilloma Virus Infections Over Six Months in People Living with HIV | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Changes in Oral Papilloma Virus Infections Over Six Months in People Living with HIV Munabi, Ian G., Kamulegeya, Adriane., Kateete, David P., Semitala, Fred., and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6495161/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract There is a paucity of data on changes in oral papilloma virus (PV) infection in people living with HIV (PLHIV) especially in low resource settings. The objective of this study was to determine the changes in oral PV infections in PLHIV from a low resource setting over a six-month follow-up period. This was a cohort study in which data was derived from a sub-sample of a parent study that examined oral human papilloma viruses, microbiota, and cancer in PLWHIV. This as a six-month follow up and a 2 mls saliva sample was collected from 541 participants on both visits. The saliva sample was used for DNA extraction, PV screening and typing using PCR methods. The DNA was subjected to Nanopore PV sequencing and subsequently analyzed using the phyloseq object, followed by a series of comparisons using the Phyloseq and Vegan packages in R to generate the alpha and beta diversity indices of the sequencing data from the sampled participants PV OTUs at the two visits. We found that 60% of participants had no detectable PVs at six-month follow-up, with a significant clearance rate of 84.47%. Oncogenic PVs were less likely to be detected as new infections compared to non-oncogenic PVs (Rate Ratio (RR) 0.42, 95% CI 0.31 to 0.56, P < 0.01). Oncogenic PV types were more likely cleared than non-oncogenic strains (RR 1.16, 95% CI 1.03 to 1.31, P = 0.02), but persistence rates did not significantly differ. This study highlights important trends in the natural course of oral PV infections, demonstrating that while most infections clear over time, there are distinct differences in the behavior of oncogenic versus non-oncogenic strains. These findings have important implications for the understanding of PV epidemiology and may guide future preventive and therapeutic strategies, particularly in the context of Human PV-related cancer prevention. Virology PLHIV PV clearance PV persistence Papilloma viruses' infections Figures Figure 1 Introduction Infections due to Papilloma viruses (PVs) are globally endemic and recognized as a type of sexually transmitted infection by the World Health Organization (WHO) [ 1 – 3 ]. It is estimated that approximately 11.4% of the worldwide population is affected by PVs with the highest prevalence in Sub-Saharan Africa [ 3 , 4 ]. PV infections are typically self-limiting being cleared by the host’s immunity in most healthy individuals[ 5 ], although in some cases the infections may persist [ 6 , 7 ]. In young people, there is an increased risk of infection due to higher sexual activity that may lead to quick re-infection prolonging the exposure to PVs [ 7 ]. This sexual activity may also introduce oncogenic genital PV types into the oral cavity [ 7 ]. HIV infection promotes PV infection through the HIV-tat protein which transactivates the PV long control region, which in turn increases the expression of the E6 and E7 early oncogenes [ 8 – 10 ]. The augmentation effect of HIV-tat extends to the PV E6 and E7 oncoproteins and leads to increased production of L1 which is responsible for increased infectivity of PV [ 11 ]. HIV infection also reduces PV infected cell elimination through the selective destruction of CD4 + lymphocytes and impairing the dendritic cell activation and activity of CD8 + lymphocytes [ 12 , 13 ]. The risks of PV acquisition and related complications do not appear to decline with antiretroviral treatment [ 14 , 15 ]. PV infection remains one of the major factors implicated in the development of squamous cell carcinoma of the cervix, vagina, vulva, penis, larynx, head, and neck [ 16 , 17 ]. A typical infection duration starts with PV accessing the epithelial basement membrane through breaks in the epithelium following micro-trauma, erosion, or inflammation, to which the PV particles attach using the L1 protein and later infect the basal epithelial cells [ 18 , 19 ]. Over the course of time, the PV takes over the cellular process to make several copies of itself that are eventually shed as the infected epithelial cell reaches the epithelial surface [ 19 ]. This cycle is repeated for as long as there are infected basal cells in the epithelium from basal cell division or access points following trauma [ 19 ]. This means that any condition that leads to increased exposure of the basement membrane like periodontitis [ 20 , 21 ], that is commonly seen in patients with HIV [ 22 ], may lead to increased and/or longer duration of PV infection or exposure. Risk factors for oral PV infection include oral sexual contact [ 23 ], age [ 23 ], smoking [ 23 – 25 ], tonsillectomy and years since HIV diagnosis [ 26 ], inflammatory states that include periodontitis [ 20 , 21 ], low CD4 + cell count in people living with HIV (PLHIV) [ 12 , 27 ], and concurrent oral and genital PV infections in women [ 28 ]. PV infections are an important driver of malignancy in people living with HIV [ 29 ]. It is important to note that most PV infections last for a relatively short time ranging from less than 6 months to about two years. In some people the infections last longer and may eventually manifest as cancer. In mixed PV infections, that is, where there is more than one type of PV causing disease, high PV viral loads can be used as biomarkers for HIV disease progression [ 30 ]. Also, PLHIV with lower CD4 + cell counts are more likely to present with mixed PV infections compared to HIV negative individuals [ 31 ]. In HIV negative people, infection with multiple PV types increases the HIV acquisition risk by 20% for each additional PV type detected [ 32 ]. Mixed PV infections, especially those involving the oncogenic PV genotypes, may persist longer than non-mixed PV infections [ 24 , 33 ]. In addition to behavioral factors like having multiple sexual partners and smoking [ 25 ], interactions between viruses during multiple PVs infections, may in part also explain the high prevalence of PV DNA in PLHIV [ 7 , 27 , 34 – 37 ]. There is a paucity of data on the changes in oral PV infections in PLHIV in our low resource setting. In this manuscript we set out to determine the oral PVs changes in PLHIV from a low resource setting over a six-month follow-up period. Methods As has been described elsewhere [38], the participants in this cohort study, were at baseline drawn consecutively from Makerere University Joint AIDS Program clinic (MJAP), situated in Kampala Uganda which serves a total of 18,000 PLHIV drawn from both the urban and peri-urban populations of south-central part of Uganda in East Africa [39]. The data in this report were generated from a sub-sample of the parent case control study that examined oral human PV, microbiota and cancer in PLHIV [40]. In the parent study, participants who were registered patients in the clinic, above the age of 18-years and had provided informed consent, were consecutively recruited over a 6-month period to attain a target sample size of 4,600. The sample size for this cohort sub-study was obtained using the online calculator for Sample size for Survival analysis [41], for the following assumptions: 0.5 as the proportion of participants in both the exposed to the known oncogenic types of PV (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58 and 59 [42, 43]) compared to the other non-oncogenic types of PV; Relative hazard ratio of 0.44 [44], Median survival time with persistence 2.4 [44], censored rate of 0.35 [44], and a maximum of one follow-up visit time unit of six-months; Power 0.95 and significance 0.05. This resulted in an estimated sample size of 492 PLHIV for a total of 77 events (clearance of the previously identified PV infection as evidenced by a negative PV test at next review visit). This was increased by a 10% allowance for loss to follow-up, errors and missing data and rounded up to 542 participants for follow-up. Inclusion criteria : (a) having been seen as part of the baseline study and found being positive for any one of the known PV types, (b) absence of lesions on oral examination at the baseline visit and (c) consent to participate in the follow-up study. Sampling : The participants who qualified for inclusion were selected randomly using computer generated numbers based on MJAP clinic patient identification numbers. Study procedure: Participants who qualified were contacted by phone and requested to return for a repeat assessment 6 months after the initial examination. All participants who agreed to come for the follow-up examination were reconsented on the day of their visit. As was done at the baseline visit, each reconsented participant was asked to provide a sample of saliva for five minutes. After five minutes, participants were asked to top up their samples to 5mls. These saliva samples were immediately placed on ice for transfer to the laboratory within two hours of collection. In the lab, each sample was aliquoted into two 2ml batches that were both centrifuged at 4000 revolutions per minute for four minutes. The supernatant from each of these samples was discarded and one of the remaining pellets was immediately placed in Cell lysis solution of the DNA extraction Kit (D4069, Zymoresearch, CA, USA). A second pellet was placed in a cryovial at minus 20 degrees Celsius for later transfer to minus 80 degrees Celsius for long term storage. The remaining 1ml sample was stored immediately at minus 20 degrees Celsius and later transferred to long term storage at minus 80 degrees. The molecular techniques in this manuscript have previously been used by our research group[45]. DNA Extraction, PV screening and typing : DNA extracted from the pellets was done using Quick-DNA Mini prep Plus Kit (D4069, Zymoresearch, CA, USA), with overnight protein kinase digestion, as per the manufacturer’s instructions. The extracted DNA from each sample was quantified using a Nanodrop colorimeter (Thermofisher scientific, MA, USA) following the manufacturer’s instructions. This was followed by subjecting 10-micro-liters of each sample to PV confirmatory screening using the forward FAP 59 and reverse FAP 64 primers [37], that were each respectively designed with an additional forward or reverse nanopore tag. DreamTaq DNA polymerase under the following assay conditions: 5 min at 94 °C, 40 cycles (denaturation 94 °C/30 s, annealing 52 °C/45 s, and extension 72 °C 1 min) followed by a final extension step at 72 °C for 7 min. The 490bp band PV positive PCR products were visualized using 2% agarose gel with ethidium bromide. Samples without any band from the FAP primers were subjected to an additional confirmatory PCR screening for 150bp bands using the double nested PGmy9/11 and Gp+5/+6 primers and protocol [46]. All the HPV positive samples in the study pool were subjected to further PCR based typing using the Sotlar method [47]. Nanopore PV sequencing : Sequencing was carried out on 72/541 samples that had been identified as having remained PV positive at both time points, using the SQK-LSK114 sequencing kit as per manufacturer’s instructions using the protocol for nanopore tagged amplicons [48], with the following modifications. After the above FAP and or GP5+ PCR, the amplicons were cleaned up with Clean NGS beads (Coenecoop 75, 2741 PH Waddinxveen, Netherlands) with the ratio of 1:2 of the amplicons to the beads as per the manufacturer’s instructions. A second bead clean of 1:1 was performed using the supernatant and the beads. The supernatant was removed and the DNA bound to the beads was washed twice with 800µl of freshly prepared 70% ethanol, without disturbing the beads. The beads and DNA were re-suspended in 10 μl of Nuclease free water and incubated at room temperature for 10 min. The sample containing DNA and the beads was pelleted on a magnetic rack and the supernatant containing DNA was collected. The cleaned amplicons were quantified using a Qubit™ 4 Fluorometer (Themo Fisher Scientific, City, Singapore). The purified PCR products were used for Nanopore PCR barcoding using the EXP-PBC096 PCR barcoding expansion pack (Oxford Nanopore Technologies plc, Oxford, UK) under the following conditions 37-degrees Celsius for 20 min and 87-degrees Celsius for 20 min. The barcoded PCR products were purified with Clean Next Generation Sequencing (NGS) beads in a ratio of 1:0.4 for the sample to beads before pooling in equimolar volumes for Ligation using the SQK-LSK114-XL kit (Oxford Nanopore Technologies plc, Oxford, UK) as per the manufacturer’s instructions. The final DNA library was quantified using both Nano drop One (Themo Scientific, USA) and Qubit™ 4 Fluorometer (Themo Fisher Scientific, City, Singapore). The quantified DNA library not exceeding 10-fetomolar based on the Qubit™ 4 Fluorometer (Themo Fisher Scientific, City, Singapore) measurement for each run, was loaded onto the MinION MIN-101B device running a flongle Flow Cell FLO-FLG114 (Oxford Nanopore Technologies plc, Oxford, UK) with the until end-of-life setting. Processing of sequencing data : The data for 72 participants, corresponding to their baseline and follow-up visits, were initially saved as POD5 files during sequencing. Using a python 3.12 jupyter notebook and a series of bash commands, the sequencer-generated POD5 files were converted first to bam files using bash commands for the GPU version of the manufacturer’s demultiplexing software, Dorado version 8.1 running on a Nvidia GPU 3070, AUSUS Tuf Dash F15 i7 64GB ddr5 ram laptop. The highest quality ONT dorado v5 SUP models to ensure that the reads obtained are of the best quality. Sequencing reads with a minimum quality Phred score of 5, were retained in bam files for subsequent analysis. The data in the bam file were converted to the fasta format using SAMtools [49], and later to blast output summary text files of the aligned reads using the whole genome reference sequences for all known PVs from Pave database ( www.pave.niaid.nih.gov (22 December 2024)), for importing into R. At the blast step, only reads longer than 100 bases after trimming the nanopore sequencing adapters, primers and tags, were retained for the blasting against the reference genomes, using the highest settings (-c50 -s) of the blastn based NanoBLASTer [50]. Use of whole genome PV reference data allowed the blast step to capture data both the amplified segments (L1, E6 and E7) and any other regions of the PV virus in the test solutions. Downstream analysis in the R statistical computing environment made use of the data.table (version 1.16.4) related R packages for both the initial data wrangling and later generation of summaries from the data using the identified PV related reads. Analysis of the data: Data analysis: The data were downloaded as excel sheets from redcap and imported into the R version 4.4.2 statistical computing environment running on windows for data wrangling to merge and label all the relevant pieces of data before the production of summaries. Descriptive data summaries were based on counts and frequencies that were followed by a series of multilevel regression analyses using the glmer function of the Lme4 package [51], with a Poisson distribution to compute the rate ratios of the PV infection count outcomes controlling for individual participants. For the sequencing PV data, text or excel file summaries were imported into R and reorganized into a phyloseq object using in-house scripts. Analysis of the sequencing data in the phyloseq object involved recording the total number of segments corresponding to viral genomes or OTUs followed by a series of comparisons using the Phyloseq [33] and Vegan [34] packages in R to generate the alpha and beta diversity indices of the sequencing data from the sampled participants PV OTUs at the two visits. The R code and related datasets used in this sub-analysis have been included as part of the supplementary data supporting this report. Ethical considerations: This study has been approved by Ethics Committee of Makerere University School of Medicine Research and Ethics committee (SOMREC) and the Uganda National Council of Science and technology ((UNCST). The ethics approval numbers are REC REF 2022-451 and HS2541ES respectively. The ethics approval date was November 22, 2022. All procedures followed were in accordance with the ethical standards of the committee responsible for human experimentation (institutional and national) and with the Helsinki Declaration. Informed consent was obtained from all participants, in writing and dated, before enrolment in the study. Results As shown in the participant flow diagram (see Figure 1), a total of 556 participants presented for their agreed upon follow-up appointment. Fifteen of them had missing data and were removed from further analysis, leaving a total of 541 participants. Most participants (75%) were female and 45 years (SD=10) of age. The average follow-up time for all the participants that returned for examination was 5.9 (SD 0.53) months. As summarized in Table 1, most (60%) participants had no detectable infection by the time of the follow-up visit. Also, in Table 1, note the overall reduction in the combinations of PV types detected in participants’ samples for the two visits. Changes in detected PV types at the two participant contact times Considering individual PV infection types, there were 1365 (85%) instances of the previously detected PV type infections that were cleared at the second follow-up contact. There were also 196 (12%) instances of new or incident PV type infections and another 55 (3%) instances of PV type infections that were present at both the baseline and follow-up time points (persistent). Table 2 provides a summary of the changes in PV infections for each of the tested PVs for each of the participants comparing presence at the two time points. Oncogenic PVs were less likely to be detected as new infections compared to non-oncogenic PVs. This was significant (Rate Ratio (RR) 0.42, 95% CI 0.31 to 0.56, P <0.01), and remain unchanged on controlling for gender (Female = RR 1.34, 95% CI 0.86 to 2.07, P= 0.19), unit increase in age (RR = 0.99, 95% CI 0.98 to 1.01, P= 0.41) and each additional month of follow-up (RR 1.16, 95% CI 0.80 to 1.67, P= 0.44). Oncogenic PVs were more likely to be cleared compared to the non-oncogenic PVs. This too was significant (RR 1.16, 95% CI 1.03 to 1.31, P =0.02). This remained unchanged on adjusting for gender (Female = RR 0.96, 95% CI 0.85 to 1.09, P= 0.56), unit increase in age (RR = 1.00, 95% CI 1.00 to 1.01, P= 0.65) and each additional month of follow-up (RR 0.99, 95% CI 0.87 to 1.13, P= 0.93). Oncogenic PVs were more likely to be detected as persistent PV infection compared to non-oncogenic PVs. This was not significant (RR 1.02, 95% CI 0.57 to 1.83, P= 0.95). Results of sequencing samples with persistent PVs Sequencing generated 2,791,802 reads of which 405,864 (14.54%) mapped onto one of the known PV genomes. There were only 207,566 of the 405,864 (51.14%) PV reads that had barcodes for linking to the sample data. There were 95,384/207,566 (45.95%) PV reads that could be linked to 72/541 followed-up participants sample identification numbers. A total of 214 PV OTUs or genomes were identified. Table 3, which provides a summary of both the alpha diversity indices, shows there were about the same PV genomes at the first visit (191) compared to the second visit (181). All the other alpha diversity measures were within the same range for the two visits. In the case of similarity indices, the Bray Curtis index was 0.17 while the Jaccard index was 0.45 indicating low similarity of organisms between the first and second visit. There was no association between the distribution of the PVs with regards to the participants first or second visit (F-statistic = 1.40, P = 0.18) age (F-statistic = 0.62, P = 0.65) or gender (F-statistic = 0.82, P = 0.46). Table 4 provides a list of the PVs with the highest number of reads for both the baseline and follow-up visit. Discussion We set out to determine changes in PV related oral infections affecting PLHIV over a six-month follow-up period. Most of the previously PV positive participants had no detectable PVs after the follow-up period. Among those that remained positive there was a general reduction in the number of reads and combinations of PVs found in each participant. The analysis of changes in detected PV types between two contact points for participants reveals key insights into the dynamics of PV infections over time. These results indicate that most PV infections either cleared or did not persist over the follow-up period. This aligns with the natural history of PV infections that PV remains in the epithelial layer of cells until the previously infected basement membrane cells are exhausted, which is further supported by the fact that 85% of previously detected PV types were cleared by the second follow-up visit. This highlights the potential for spontaneous resolution of PV infections, particularly those associated with non-oncogenic strains and is in line with what has been reported in literature with up to 80% clearance within a 6.5-to-18- month period [ 5 ]. We found that the oncogenic PV infections were more likely to be cleared compared to non-oncogenic infections. This finding is consistent with previous research indicating that the immune response to oncogenic PV types, such as Human PV 16 and Human PV 18, may be more pronounced. However, their clearance at 6 months is low compared to the other oncogenic PVs [ 52 ]. In our study we identified more non-oncogenic PVs compared to oncogenic PVs which may explain the high clearance within the six-month follow-up period. This is in line with the findings from Balkans et al [ 52 ]. It is worth noting that some other studies that used modeling did not show any difference in clearance between the different Human PVs based on oncogenicity [ 53 ]. The higher clearance rate of oncogenic PV in our study is not surprising since HIV serostatus has not been reported to affect one’s ability to clear high-risk PVs. However, some studies have reported a negative effect of HIV sero-status on clearance [ 54 ], hence more research needs to be done for a better understanding of HIV infection’s impact on PV persistence [ 55 ]. Interestingly, the likelihood of persistence did not differ significantly between oncogenic and non-oncogenic PV types. From our data we found that only 3.4% of the infections were persistent across the two time-points. Persistence of PV in the oral cavity can have serious consequences, ranging from an increased risk of oral and oropharyngeal cancers to chronic inflammation and the development of other complications such as oral warts and condylomas [ 56 – 58 ]. Preventative measures, including vaccination against high-risk PV strains and early detection of PV-related oral lesions, are essential in minimizing these risks. Additionally, promoting a healthy lifestyle, avoiding smoking, and encouraging regular dental and medical check-ups can help reduce the chances of persistent PV infection in the oral cavity. Thus, finding no difference in the likelihood of persistence suggests that while the immune system may clear oncogenic PV infections more effectively and those infections that persist could have similar characteristics to non-oncogenic strains in terms of persistence. This could indicate that, in some of our participants, there are unique host factors that favor the establishment of persistent PV infections. These factors are separate from the above-mentioned general immune response. This implies that persistence of these PV infections is influenced by factors beyond viral oncogenic potential. Both the viral ability to evade the immune system and the host factors such as age and other behavior (smoking, contraceptive use and number of sexual partners) affect clearance [ 59 ]. From our data, we found that a subset of infections were either incident (12%) across the two time points. The presence of incident PV infections underscores the continued risk of acquiring new infections over time, despite prior exposure. This may be because each PV infection leads to the production of genotype-specific antibodies which may not provide protection against other PVs [ 60 ]. This failure to protect against other PVs has also been reported when it comes to vaccines. Of note is the statistically significant finding that oncogenic PV types were less likely to appear as new infections, a trend that contrasts with non-oncogenic PV types, suggesting that oncogenic PV types may exhibit a lower rate of acquisition compared to non-oncogenic PV types. This could be due to the immune system's more robust response to oncogenic strains or differences in the biology of these viruses that make them less likely to be transmitted or because in this setting they are not as common to acquire as the non-oncogenic types. Overall, the results presented here emphasize the variability in the persistence, acquisition, and clearance of PV infections, with notable differences between oncogenic and non-oncogenic types. These findings are consistent with the broader understanding of PV infection dynamics, wherein high-risk strains, such as Human PV 16 and Human PV 18, are less likely to be cleared and may persist for extended periods, potentially leading to complications like cancer [ 54 , 55 ]. In contrast, low-risk strains typically clear more rapidly, reducing the overall burden of disease. Furthermore, the results suggest that age, gender, and duration of follow-up had limited impact on the detection and clearance of PV infections in this cohort. This indicates that these factors may not be as influential in the short-term dynamics of PV infections, although they could play a role over longer durations or in different populations as reported by other studies [ 54 , 61 ]. The continued monitoring of this cohort and others could provide further insights into the long-term trajectories of PV infections, particularly regarding the persistence of oncogenic strains. Limitations While the study provides valuable insights into the dynamics of PV infection over time, including differences in both the persistence and clearance of oncogenic and non-oncogenic types, it faces several limitations. These include potential biases due to participant selection, possible left censoring since we did not catch participants before the infection started, the short follow-up period, analysis restricted to only the known PV types in the pave database, and the lack of consideration of confounding factors such as sexual behavior, immune status, and vaccination status. Further studies with larger and more diverse populations, longer follow-up durations, and more detailed data on confounding factors are needed to deepen our understanding of PV infection dynamics in this setting. Conclusion This study highlights important trends in the natural course of oral PV infections, demonstrating that while most infections clear over time, there are distinct differences in the behavior of oncogenic versus non-oncogenic strains. Oncogenic PV types are less likely to be newly acquired and more likely to be cleared, but persistence rates do not differ significantly between the two categories. These findings have important implications for the understanding of PV epidemiology and may guide future preventive and therapeutic strategies, particularly in the context of Human PV-related cancer prevention. Declarations All authors have no conflict of interest to declare. Authors contributions FS, WB, IGM and AK conceived the initial research idea. KDP, CJE. DK and PLL were major contributors to the manuscript review. WB, IGM and AK refined the research idea, drafted the initial proposal, and were involved in the whole research process through to the drafting of the manuscript. IGM, DK and KDP were instrumental in data collection and analysing the data. All co-authors reviewed and approved the final manuscript prior to submission. Data availability The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Additional information Acknowledgement: We are grateful for the support from the laboratory team namely: Sylvia Nalwanga and Mark Muwuluzi. We thank the participants and administrators of MJAP for providing a good working environment and donation of samples respectively. We also acknowledge Mr. Mukama Emmanuel and Mr. Tayebwa Mordecai for their support in the implementation of the project as members of the administrative team. Funding: Research reported in this publication was supported by the National Institute of Dental & Craniofacial Research of the National Institutes of Health under Award Number R56DE032217 and by the Fogarty International Centre of the National Institutes of Health, U.S. Department of State’s Office of the U.S. Global AIDS Coordinator and Health Diplomacy (S/GAC), and President’s Emergency Plan for AIDS Relief (PEPFAR) under Award Number 1R25TW011213. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health References Mira A, Simon-Soro A, Curtis MA (2017) Role of microbial communities in the pathogenesis of periodontal diseases and caries. J Clin Periodontol 44(Suppl 18):S23–S38 Eriksson L, Lif Holgerson P, Johansson I (2017) Saliva and tooth biofilm bacterial microbiota in adolescents in a low caries community. 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J Infect Dis 202(3):436–444 Alli BY, Burk RD, Fatahzadeh M, Kazimiroff J, Grossberg RM, Smith RV, Ow TJ, Wiltz M, Polanco J, Rousseau MC et al (2020) HIV Modifies the Effect of Tobacco Smoking on Oral Human Papillomavirus Infection. J Infect Dis 222(4):646–654 Ablanedo-Terrazas Y, Romero-Mora K, Gomez-Palacio M, Alvarado-de la Barrera C, Ruiz-Cruz M, Hernandez-Juan R, Reyes-Teran G (2018) Prevalence and risk factors for oral human papillomavirus infection in Mexican HIV-infected men. Salud Publica Mex 60(6):653–657 Muller K, Kazimiroff J, Fatahzadeh M, Smith RV, Wiltz M, Polanco J, Grossberg RM, Belbin TJ, Strickler HD, Burk RD et al (2015) Oral Human Papillomavirus Infection and Oral Lesions in HIV-Positive and HIV-Negative Dental Patients. J Infect Dis 212(5):760–768 Tahmasebi E, Keshvad A, Alam M, Abbasi K, Rahimi S, Nouri F, Yazdanian M, Tebyaniyan H, Heboyan A, Fernandes GVO (2023) Current Infections of the Orofacial Region: Treatment, Diagnosis, and Epidemiology. Life (Basel) 13(2) Pavone G, Marino A, Fisicaro V, Motta L, Spata A, Martorana F, Spampinato S, Celesia BM, Cacopardo B, Vigneri P et al (2024) Entangled Connections: HIV and HPV Interplay in Cervical Cancer-A Comprehensive Review. Int J Mol Sci 25(19) Zhou Y, Shi X, Liu J, Zhang L (2023) Correlation between human papillomavirus viral load and cervical lesions classification: A review of current research. Front Med (Lausanne) 10:1111269 Camargo M, Del Rio-Ospina L, Soto-De Leon SC, Sanchez R, Pineda-Pena AC, Sussmann O, Patarroyo ME, Patarroyo MA (2018) Association of HIV status with infection by multiple HPV types. Trop Med Int Health 23(11):1259–1268 Liu G, Mugo NR, Brown ER, Mgodi NM, Chirenje ZM, Marrazzo JM, Winer RL, Mansoor L, Palanee-Phillips T, Siva SS et al (2022) Prevalent human papillomavirus infection increases the risk of HIV acquisition in African women: advancing the argument for human papillomavirus immunization. AIDS 36(2):257–265 Louvanto K, Rautava J, Willberg J, Wideman L, Syrjanen K, Grenman S, Syrjanen S (2013) Genotype-specific incidence and clearance of human papillomavirus in oral mucosa of women: a six-year follow-up study. PLoS ONE 8(1):e53413 Visalli G, Di Pietro A, Curro M, Pruiti Ciarello M, D'Andrea F, Nunnari G, Pellicano GF, Facciola A (2021) How Much Does HIV Positivity Affect the Presence of Oral HPV? A Molecular Epidemiology Survey. Int J Environ Res Public Health 18(17) Morhason-Bello IO, Baisley K, Pavon MA, Adewole IF, Bakare R, de Sanjose S, Francis SC, Watson-Jones D (2021) Prevalence and genotype specific concordance of oro-genital and anal human papillomavirus infections among sexually active Nigerian women. Infect Agent Cancer 16(1):59 Vergori A, Garbuglia AR, Piselli P, Del Nonno F, Sias C, Lupi F, Lapa D, Baiocchini A, Cimaglia C, Gentile M et al (2018) Oral human Papillomavirus DNA detection in HIV-positive men: prevalence, predictors, and co-occurrence at anal site. BMC Infect Dis 18(1):25 Sias C, Salichos L, Lapa D, Del Nonno F, Baiocchini A, Capobianchi MR, Garbuglia AR (2019) Alpha, Beta, gamma human PapillomaViruses (HPV) detection with a different sets of primers in oropharyngeal swabs, anal and cervical samples. Virol J 16(1):27 Buwembo W, Kamulegeya A, Kalanzi D, Namuyonga PN, Nakasujja P, Katete DP, Semitala FC, Mwesigwa-Lutalo C, Kalungi S, Cameron JE et al (2024) Periodontal health in a large cohort of Ugandans living with HIV: a cross-sectional study. BMC Oral Health 24(1):1314 Muddu M, Ssinabulya I, Kigozi SP, Ssennyonjo R, Ayebare F, Katwesigye R, Mbuliro M, Kimera I, Longenecker CT, Kamya MR et al (2021) Hypertension care cascade at a large urban HIV clinic in Uganda: a mixed methods study using the Capability, Opportunity, Motivation for Behavior change (COM-B) model. Implement Sci Commun 2(1):121 William B, Adriane K, Dunstan K, Naava NP, Proscovia N, Katete David P, Collins SF, Catherine ML, Samuel K, E CJ (2024) : Periodontal health in a large cohort of Ugandansliving with HIV: A cross-sectional study. Res Sq Kohn MA, Senyak J (2021) Sample size calculators [website]. UCSFCTSI March 26 Chung CH, Bagheri A, D'Souza G (2014) Epidemiology of oral human papillomavirus infection. Oral Oncol 50(5):364–369 Petca A, Borislavschi A, Zvanca ME, Petca RC, Sandru F, Dumitrascu MC (2020) Non-sexual HPV transmission and role of vaccination for a better future (Review). Exp Ther Med 20(6):186 D'Souza G, Clemens G, Strickler HD, Wiley DJ, Troy T, Struijk L, Gillison M, Fakhry C (2020) Long-term Persistence of Oral HPV Over 7 Years of Follow-up. JNCI Cancer Spectr 4(5):pkaa047 Munabi IG, Adrian K, Mark M, Sylvia N, Kateete DP, Semitala FC, Mwaka E, Cameron JE, Buwembo W (2025) Nanopore sequencing of non-oncogenic oral Papillomaviruses from people living with HIV. Res Sq Fuessel Haws AL, He Q, Rady PL, Zhang L, Grady J, Hughes TK, Stisser K, Konig R, Tyring SK (2004) Nested PCR with the PGMY09/11 and GP5(+)/6(+) primer sets improves detection of HPV DNA in cervical samples. J Virol Methods 122(1):87–93 Sotlar K, Diemer D, Dethleffs A, Hack Y, Stubner A, Vollmer N, Menton S, Menton M, Dietz K, Wallwiener D et al (2004) Detection and typing of human papillomavirus by e6 nested multiplex PCR. J Clin Microbiol 42(7):3176–3184 Kiryowa HM, Buwembo W, Munabi IG, Mwaka ES, Rwenyonyi CM, Kaddumukasa M, Kiguli S (2024) A comparison of oral bacteriome isolated from periodontal pockets of participants with or without diabetes mellitus in Uganda: a case control study. BMC Res Notes 17(1):146 Danecek P, Bonfield JK, Liddle J, Marshall J, Ohan V, Pollard MO, Whitwham A, Keane T, McCarthy SA, Davies RM et al (2021) Twelve years of SAMtools and BCFtools. Gigascience 10(2) Amin MR, Skiena S, Schatz MC (2016) NanoBLASTer: Fast alignment and characterization of Oxford Nanopore single molecule sequencing reads. In: IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS): 13–15 Oct. 2016 2016 ; 2016: 1–6 Bates D, Maechler M, Bolker B, Walker S, Christensen RHB, Singmann H, Dai B, Grothendieck G, Green P, Bolker MB (2015) Package ‘lme4’. convergence 12(1):2 Bulkmans NW, Berkhof J, Bulk S, Bleeker MC, van Kemenade FJ, Rozendaal L, Snijders PJ, Meijer CJ, Group PS (2007) High-risk HPV type-specific clearance rates in cervical screening. Br J Cancer 96(9):1419–1424 Johnson HC, Elfstrom KM, Edmunds WJ (2012) Inference of type-specific HPV transmissibility, progression and clearance rates: a mathematical modelling approach. PLoS ONE 7(11):e49614 D'Souza G, Tewari SR, Troy T, Webster-Cyriaque J, Wiley DJ, Lahiri CD, Palella FJ, Gillison ML, Strickler HD, Struijk L et al (2024) Oncogenic Oral Human Papillomavirus Clearance Patterns over 10 Years. Cancer Epidemiol Biomarkers Prev 33(4):516–524 Koshiol JE, Schroeder JC, Jamieson DJ, Marshall SW, Duerr A, Heilig CM, Shah KV, Klein RS, Cu-Uvin S, Schuman P et al (2006) Time to clearance of human papillomavirus infection by type and human immunodeficiency virus serostatus. Int J Cancer 119(7):1623–1629 Betz SJ (2019) HPV-Related Papillary Lesions of the Oral Mucosa: A Review. Head Neck Pathol 13(1):80–90 Syrjanen S (2003) Human papillomavirus infections and oral tumors. Med Microbiol Immunol 192(3):123–128 Reusser NM, Downing C, Guidry J, Tyring SK (2015) HPV Carcinomas in Immunocompromised Patients. J Clin Med 4(2):260–281 Taylor S, Bunge E, Bakker M, Castellsague X (2016) The incidence, clearance and persistence of non-cervical human papillomavirus infections: a systematic review of the literature. BMC Infect Dis 16:293 Bhat P, Mattarollo SR, Gosmann C, Frazer IH, Leggatt GR (2011) Regulation of immune responses to HPV infection and during HPV-directed immunotherapy. Immunol Rev 239(1):85–98 Mane A, Sahasrabuddhe VV, Nirmalkar A, Risbud AR, Sahay S, Bhosale RA, Vermund SH, Mehendale SM (2017) Rates and determinants of incidence and clearance of cervical HPV genotypes among HIV-seropositive women in Pune, India. J Clin Virol 88:26–32 Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations The authors declare no competing interests. Supplementary Files Tables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6495161","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":445712533,"identity":"1a30c9bc-892f-4e32-9340-8b929c24f19b","order_by":0,"name":"Munabi, Ian G.","email":"","orcid":"","institution":"Department of Dentistry, School of Dentistry, Makerere University College of Health Sciences, Kampala, Uganda","correspondingAuthor":false,"prefix":"","firstName":"Ian","middleName":"G.","lastName":"Munabi","suffix":""},{"id":445712534,"identity":"b4dcc7d9-17d8-40a1-a417-ba8d81adfecf","order_by":1,"name":"Kamulegeya, 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L.","email":"","orcid":"","institution":"Department of Craniofacial and Surgical Care, Adams School of Dentistry, University of North Carolina Chapel Hill, North Carolina, USA. f Pediatric Dentistry and Dental Public Health, Adams School of Dentistry, University of North Carolina Chapel Hill, North Carolina, USA.","correspondingAuthor":false,"prefix":"","firstName":"Lauren","middleName":"L.","lastName":"Patton","suffix":""},{"id":445712540,"identity":"25631b8e-cdd1-43fa-975f-f3265f131a7d","order_by":7,"name":"Divaris, Kimon.","email":"","orcid":"","institution":"Department of Pediatric Dentistry and Dental Public Health, Adams School of Dentistry, University of North Carolina Chapel Hill, North Carolina, USA., Department of Pediatric Dentistry and Dental Public Health, Adams School of Dentistry, University of North Carolina Chapel Hill, North Carolina, USA.Gillings School of Global Public Health, University of North Carolina Chapel Hill, North Carolina, USA,","correspondingAuthor":false,"prefix":"","firstName":"Kimon.","middleName":"","lastName":"Divaris","suffix":""},{"id":445712541,"identity":"011b82da-c0e8-4339-a61b-ba35d2ea97fc","order_by":8,"name":"Buwembo, William.","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYDACZubGAwlA2gDEYWxgkGNgYCOkhbEBRYsxYS1AZQcYkLQkNhDSYnAcqOVBzTYGc4kcw0c3d9ikr20/lsDwo4Yhcb4DDi2HQQ47dpvBckaOsXHumbTcbWfSDjD2HGNI3HgAuxYzsBa22wwGN3K3See2Hc7ddiC9gYEX6MKNDfi0/ANr2f4bqCXd7PzzBsa/hLQktkFsYQZqSTC7kXaAGWTLfBzetwdr6bvNY9nz/rM00C+G2248Szgsc0zCeAMOLZL9hw8+/PHttpw5e1ri59wdNvJm59MMH76psZGdj8NhMMCDwjvAwCDBYHAAvxYsQJ6ALaNgFIyCUTBiAABV12nhEigKiQAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Anatomy, School of Biomedical Sciences, Makerere University College of Health Sciences, Kampala, 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diagram\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6495161/v1/400526bd5751257938af4788.jpg"},{"id":81199225,"identity":"a4b1d1de-ce9f-4220-85fd-f7c973f43b17","added_by":"auto","created_at":"2025-04-23 10:54:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":451026,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6495161/v1/6cc9dc0a-1f84-46a8-ab2b-5ba20000f0ac.pdf"},{"id":81199223,"identity":"d21d100a-76f1-409d-8856-7d4dce4f34b2","added_by":"auto","created_at":"2025-04-23 10:54:26","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":25757,"visible":true,"origin":"","legend":"","description":"","filename":"Tables.docx","url":"https://assets-eu.researchsquare.com/files/rs-6495161/v1/32f373e37e03c7bfa0a925fc.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eChanges in Oral Papilloma Virus Infections Over Six Months in People Living with HIV\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInfections due to Papilloma viruses (PVs) are globally endemic and recognized as a type of sexually transmitted infection by the World Health Organization (WHO) [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is estimated that approximately 11.4% of the worldwide population is affected by PVs with the highest prevalence in Sub-Saharan Africa [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. PV infections are typically self-limiting being cleared by the host\u0026rsquo;s immunity in most healthy individuals[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], although in some cases the infections may persist [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In young people, there is an increased risk of infection due to higher sexual activity that may lead to quick re-infection prolonging the exposure to PVs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This sexual activity may also introduce oncogenic genital PV types into the oral cavity [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. HIV infection promotes PV infection through the HIV-tat protein which transactivates the PV long control region, which in turn increases the expression of the E6 and E7 early oncogenes [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The augmentation effect of HIV-tat extends to the PV E6 and E7 oncoproteins and leads to increased production of L1 which is responsible for increased infectivity of PV [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. HIV infection also reduces PV infected cell elimination through the selective destruction of CD4\u0026thinsp;+\u0026thinsp;lymphocytes and impairing the dendritic cell activation and activity of CD8\u0026thinsp;+\u0026thinsp;lymphocytes [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The risks of PV acquisition and related complications do not appear to decline with antiretroviral treatment [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePV infection remains one of the major factors implicated in the development of squamous cell carcinoma of the cervix, vagina, vulva, penis, larynx, head, and neck [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A typical infection duration starts with PV accessing the epithelial basement membrane through breaks in the epithelium following micro-trauma, erosion, or inflammation, to which the PV particles attach using the L1 protein and later infect the basal epithelial cells [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Over the course of time, the PV takes over the cellular process to make several copies of itself that are eventually shed as the infected epithelial cell reaches the epithelial surface [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This cycle is repeated for as long as there are infected basal cells in the epithelium from basal cell division or access points following trauma [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This means that any condition that leads to increased exposure of the basement membrane like periodontitis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], that is commonly seen in patients with HIV [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], may lead to increased and/or longer duration of PV infection or exposure. Risk factors for oral PV infection include oral sexual contact [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], age [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], smoking [\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], tonsillectomy and years since HIV diagnosis [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], inflammatory states that include periodontitis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], low CD4\u0026thinsp;+\u0026thinsp;cell count in people living with HIV (PLHIV) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and concurrent oral and genital PV infections in women [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. PV infections are an important driver of malignancy in people living with HIV [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is important to note that most PV infections last for a relatively short time ranging from less than 6 months to about two years. In some people the infections last longer and may eventually manifest as cancer. In mixed PV infections, that is, where there is more than one type of PV causing disease, high PV viral loads can be used as biomarkers for HIV disease progression [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Also, PLHIV with lower CD4\u0026thinsp;+\u0026thinsp;cell counts are more likely to present with mixed PV infections compared to HIV negative individuals [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In HIV negative people, infection with multiple PV types increases the HIV acquisition risk by 20% for each additional PV type detected [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Mixed PV infections, especially those involving the oncogenic PV genotypes, may persist longer than non-mixed PV infections [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In addition to behavioral factors like having multiple sexual partners and smoking [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], interactions between viruses during multiple PVs infections, may in part also explain the high prevalence of PV DNA in PLHIV [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan additionalcitationids=\"CR35 CR36\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. There is a paucity of data on the changes in oral PV infections in PLHIV in our low resource setting. In this manuscript we set out to determine the oral PVs changes in PLHIV from a low resource setting over a six-month follow-up period.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eAs has been described elsewhere [38], the participants in this cohort study, were at baseline drawn consecutively from Makerere University Joint AIDS Program clinic (MJAP), situated in Kampala Uganda which serves a total of 18,000 PLHIV drawn from both the urban and peri-urban populations of south-central part of Uganda in East Africa [39]. The data in this report were generated from a sub-sample of the parent case control study that examined oral human PV, microbiota and cancer in PLHIV [40]. In the parent study, participants who were registered patients in the clinic, above the age of 18-years and had provided informed consent, were consecutively recruited over a 6-month period to attain a target sample size of 4,600. The sample size for this cohort sub-study was obtained using the online calculator for Sample size for Survival analysis [41], for the following assumptions: 0.5 as the proportion of participants in both the exposed to the known oncogenic types of PV (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58 and 59 \u0026nbsp;[42, 43]) compared to the other non-oncogenic types of PV; Relative hazard ratio of 0.44 [44], Median survival time with persistence 2.4 [44], censored rate of 0.35 [44], and a maximum of one follow-up visit time unit of six-months; Power 0.95 and significance 0.05. This resulted in an estimated sample size of 492 PLHIV for a total of 77 events (clearance of the previously identified PV infection as evidenced by a negative PV test at next review visit). This was increased by a 10% allowance for loss to follow-up, errors and missing data and rounded up to 542 participants for follow-up. \u003cu\u003eInclusion criteria\u003c/u\u003e: (a) having been seen as part of the baseline study and found being positive for any one of the known PV types, (b) absence of lesions on oral examination at the baseline visit and (c) consent to participate in the follow-up study. \u003cu\u003eSampling\u003c/u\u003e: The participants who qualified for inclusion were selected randomly using computer generated numbers based on MJAP clinic patient identification numbers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy procedure:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eParticipants who qualified were contacted by phone and requested to return for a repeat assessment 6 months after the initial examination. All participants who agreed to come for the follow-up examination were reconsented on the day of their visit. As was done at the baseline visit, each reconsented participant was asked to provide a sample of saliva for five minutes. After five minutes, participants were asked to top up their samples to 5mls. These saliva samples were immediately placed on ice for transfer to the laboratory within two hours of collection. In the lab, each sample was aliquoted into two 2ml batches that were both centrifuged at 4000 revolutions per minute for four minutes. The supernatant from each of these samples was discarded and one of the remaining pellets was immediately placed in Cell lysis solution of the DNA extraction Kit (D4069, Zymoresearch, CA, USA). A second pellet was placed in a cryovial at minus 20 degrees Celsius for later transfer to minus 80 degrees Celsius for long term storage. The remaining 1ml sample was stored immediately at minus 20 degrees Celsius and later transferred to long term storage at minus 80 degrees. The molecular techniques in this manuscript have previously been used by our research group[45].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDNA Extraction, PV screening and typing\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eDNA extracted from the pellets was done using Quick-DNA Mini prep Plus Kit (D4069, Zymoresearch, CA, USA), with overnight protein kinase digestion, as per the manufacturer’s instructions. The extracted DNA from each sample was quantified using a Nanodrop colorimeter (Thermofisher scientific, MA, USA) following the manufacturer’s instructions. This was followed by subjecting 10-micro-liters of each sample to PV confirmatory screening using the forward FAP 59 and reverse FAP 64 primers [37], that were each respectively designed with an additional forward or reverse nanopore tag. DreamTaq DNA polymerase under the following assay conditions: 5 min at 94 °C, 40 cycles (denaturation 94 °C/30 s, annealing 52 °C/45 s, and extension 72 °C 1 min) followed by a final extension step at 72 °C for 7 min. The 490bp band PV positive PCR products were visualized using 2% agarose gel with ethidium bromide. Samples without any band from the FAP primers were subjected to an additional confirmatory PCR screening for 150bp bands using the double nested PGmy9/11 and Gp+5/+6 primers and protocol [46]. All the HPV positive samples in the study pool were subjected to further PCR based typing using the Sotlar method [47].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNanopore PV sequencing\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eSequencing was carried out on 72/541 samples that had been identified as having remained PV positive at both time points, using the SQK-LSK114 sequencing kit as per manufacturer’s instructions using the protocol for nanopore tagged amplicons [48], with\u0026nbsp;the following modifications. After the above FAP and or GP5+ PCR, the amplicons were cleaned up with Clean NGS beads (Coenecoop 75, 2741 PH Waddinxveen, Netherlands) with the ratio of 1:2 of the amplicons to the beads as per the manufacturer’s instructions. A second bead clean of 1:1 was performed using the supernatant and the beads. The supernatant was removed and the DNA bound to the beads was washed twice with 800µl of freshly prepared 70% ethanol, without disturbing the beads. The beads and DNA were re-suspended in 10 μl of Nuclease free water and incubated at room temperature for 10 min. The sample containing DNA and the beads was pelleted on a magnetic rack and the supernatant containing DNA was collected. The cleaned amplicons were quantified using a Qubit™ 4 Fluorometer (Themo Fisher Scientific, City, Singapore). The purified PCR products were used for Nanopore PCR barcoding using the EXP-PBC096 PCR barcoding expansion pack (Oxford Nanopore Technologies plc, Oxford, UK) under the following conditions 37-degrees Celsius for 20 min and 87-degrees Celsius for 20 min. The barcoded PCR products were purified with Clean Next Generation Sequencing (NGS) beads in a ratio of 1:0.4 for the sample to beads before pooling in equimolar volumes for Ligation using the SQK-LSK114-XL kit (Oxford Nanopore Technologies plc, Oxford, UK) as per the manufacturer’s instructions. The final DNA library was quantified using both Nano drop One (Themo Scientific, USA) and Qubit™ 4 Fluorometer (Themo Fisher Scientific, City, Singapore). The quantified DNA library not exceeding 10-fetomolar based on the Qubit™ 4 Fluorometer (Themo Fisher Scientific, City, Singapore) measurement for each run, was loaded onto the MinION MIN-101B device running a flongle Flow Cell FLO-FLG114 (Oxford Nanopore Technologies plc, Oxford, UK) with the until end-of-life setting.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProcessing of sequencing data\u003c/em\u003e:\u003c/p\u003e\n\u003cp\u003eThe data for 72 participants, corresponding to their baseline and follow-up visits, were initially saved as POD5 files during sequencing. Using a python 3.12 jupyter notebook and a series of bash commands, the sequencer-generated POD5 files were converted first to bam files using bash commands for the GPU version of the manufacturer’s demultiplexing software, Dorado version 8.1 running on a Nvidia GPU 3070, AUSUS Tuf Dash F15 i7 64GB ddr5 ram laptop. The highest quality ONT dorado v5 SUP models to ensure that the reads obtained are of the best quality. Sequencing reads with a minimum quality Phred score of 5, were retained in bam files for subsequent analysis. The data in the bam file were converted to the fasta format using SAMtools [49], and later to blast output summary text files of the aligned reads using the whole genome reference sequences for all known PVs from Pave database (\u003ca href=\"http://www.pave.niaid.nih.gov\"\u003ewww.pave.niaid.nih.gov\u003c/a\u003e (22 December 2024)), for importing into R. \u0026nbsp;At the blast step, only reads longer than 100 bases after trimming the nanopore sequencing adapters, primers and tags, were retained for the blasting against the reference genomes, using the highest settings (-c50 -s) of the blastn based NanoBLASTer\u0026nbsp;[50]. Use of whole genome PV reference data allowed the blast step to capture data both the amplified segments (L1, E6 and E7) and any other regions of the PV virus in the test solutions. Downstream analysis in the R statistical computing environment made use of the data.table (version 1.16.4) related R packages for both the initial data wrangling and later generation of summaries from the data using the identified PV related reads.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAnalysis of the data:\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eData analysis: The data were downloaded as excel sheets from redcap and imported into the R version 4.4.2 statistical computing environment running on windows for data wrangling to merge and label all the relevant pieces of data before the production of summaries. Descriptive data summaries were based on counts and frequencies that were followed by a series of multilevel regression analyses using the glmer function of the Lme4 package\u0026nbsp;[51], with a Poisson distribution to compute the rate ratios of the PV infection count outcomes controlling for individual participants. For the sequencing PV data, text or excel file summaries were imported into R and reorganized into a phyloseq object using in-house scripts. Analysis of the sequencing data in the phyloseq object involved recording the total number of segments corresponding to viral genomes or OTUs followed by a series of comparisons using the Phyloseq [33] and Vegan [34] packages in R to generate the alpha and beta diversity indices of the sequencing data from the sampled participants PV OTUs at the two visits. The R code and related datasets used in this sub-analysis have been included as part of the supplementary data supporting this report.\u003c/p\u003e\n\u003cp\u003eEthical considerations:\u003c/p\u003e\n\u003cp\u003eThis study has been approved by Ethics Committee of Makerere University School of Medicine Research and Ethics committee (SOMREC) and the Uganda National Council of Science and technology ((UNCST). The ethics approval numbers are REC REF 2022-451 and HS2541ES respectively. The ethics approval date was November 22, 2022. All procedures followed were in accordance with the ethical standards of the committee responsible for human experimentation (institutional and national) and with the Helsinki Declaration. Informed consent was obtained from all participants, in writing and dated, before enrolment in the study.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAs shown in the participant flow diagram (see Figure 1), a total of 556 participants presented for their agreed upon follow-up appointment. Fifteen of them had missing data and were removed from further analysis, leaving a total of 541 participants. Most participants (75%) were female and 45 years (SD=10) of age. The average follow-up time for all the participants that returned for examination was 5.9 (SD 0.53) months. As summarized in Table 1, most (60%) participants had no detectable infection by the time of the follow-up visit. Also, in Table 1, note the overall reduction in the combinations of PV types detected in participants’ samples for the two visits. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eChanges in detected PV types at the two participant contact times\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConsidering individual PV infection types, there were 1365 (85%) instances of the previously detected PV type infections that were cleared at the second follow-up contact. There were also 196 (12%) instances of new or incident PV type infections and another 55 (3%) instances of PV type infections that were present at both the baseline and follow-up time points (persistent). Table 2 provides a summary of the changes in PV infections for each of the tested PVs for each of the participants comparing presence at the two time points. Oncogenic PVs were less likely to be detected as new infections compared to non-oncogenic PVs. This was significant (Rate Ratio (RR) 0.42, 95% CI 0.31 to 0.56, P \u0026lt;0.01), and remain unchanged on controlling for gender (Female = RR 1.34, 95% CI 0.86 to 2.07, P= 0.19), unit increase in age (RR = 0.99, 95% CI 0.98 to 1.01, P= 0.41) and each additional month of follow-up (RR 1.16, 95% CI 0.80 to 1.67, P= 0.44). Oncogenic PVs were more likely to be cleared compared to the non-oncogenic PVs. This too was significant (RR 1.16, 95% CI 1.03 to 1.31, P =0.02). This remained unchanged on adjusting for gender (Female = RR 0.96, 95% CI 0.85 to 1.09, P= 0.56), unit increase in age (RR = 1.00, 95% CI 1.00 to 1.01, P= 0.65) and each additional month of follow-up (RR 0.99, 95% CI 0.87 to 1.13, P= 0.93). Oncogenic PVs were more likely to be detected as persistent PV infection compared to non-oncogenic PVs. This was not significant (RR 1.02, 95% CI 0.57 to 1.83, P= 0.95).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResults of sequencing samples with persistent PVs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSequencing generated 2,791,802 reads of which 405,864 (14.54%) mapped onto one of the known PV genomes. There were only 207,566 of the 405,864 (51.14%) PV reads that had barcodes for linking to the sample data. There were 95,384/207,566 (45.95%) PV reads that could be linked to 72/541 followed-up participants sample identification numbers. A total of 214 PV OTUs or genomes were identified. Table 3, which provides a summary of both the alpha diversity indices, shows there were about the same PV genomes at the first visit (191) compared to the second visit (181). All the other alpha diversity measures were within the same range for the two visits. In the case of similarity indices, the Bray Curtis index was 0.17 while the Jaccard index was 0.45 indicating low similarity of organisms between the first and second visit. There was no association between the distribution of the PVs with regards to the participants first or second visit (F-statistic = 1.40, P = 0.18) age (F-statistic = 0.62, P = 0.65) or gender (F-statistic = 0.82, P = 0.46). Table 4 provides a list of the PVs with the highest number of reads for both the baseline and follow-up visit.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe set out to determine changes in PV related oral infections affecting PLHIV over a six-month follow-up period. Most of the previously PV positive participants had no detectable PVs after the follow-up period. Among those that remained positive there was a general reduction in the number of reads and combinations of PVs found in each participant. The analysis of changes in detected PV types between two contact points for participants reveals key insights into the dynamics of PV infections over time. These results indicate that most PV infections either cleared or did not persist over the follow-up period. This aligns with the natural history of PV infections that PV remains in the epithelial layer of cells until the previously infected basement membrane cells are exhausted, which is further supported by the fact that 85% of previously detected PV types were cleared by the second follow-up visit. This highlights the potential for spontaneous resolution of PV infections, particularly those associated with non-oncogenic strains and is in line with what has been reported in literature with up to 80% clearance within a 6.5-to-18- month period [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe found that the oncogenic PV infections were more likely to be cleared compared to non-oncogenic infections. This finding is consistent with previous research indicating that the immune response to oncogenic PV types, such as Human PV 16 and Human PV 18, may be more pronounced. However, their clearance at 6 months is low compared to the other oncogenic PVs [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. In our study we identified more non-oncogenic PVs compared to oncogenic PVs which may explain the high clearance within the six-month follow-up period. This is in line with the findings from Balkans et al [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. It is worth noting that some other studies that used modeling did not show any difference in clearance between the different Human PVs based on oncogenicity [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. The higher clearance rate of oncogenic PV in our study is not surprising since HIV serostatus has not been reported to affect one\u0026rsquo;s ability to clear high-risk PVs. However, some studies have reported a negative effect of HIV sero-status on clearance [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], hence more research needs to be done for a better understanding of HIV infection\u0026rsquo;s impact on PV persistence [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, the likelihood of persistence did not differ significantly between oncogenic and non-oncogenic PV types. From our data we found that only 3.4% of the infections were persistent across the two time-points. Persistence of PV in the oral cavity can have serious consequences, ranging from an increased risk of oral and oropharyngeal cancers to chronic inflammation and the development of other complications such as oral warts and condylomas [\u003cspan additionalcitationids=\"CR57\" citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Preventative measures, including vaccination against high-risk PV strains and early detection of PV-related oral lesions, are essential in minimizing these risks. Additionally, promoting a healthy lifestyle, avoiding smoking, and encouraging regular dental and medical check-ups can help reduce the chances of persistent PV infection in the oral cavity. Thus, finding no difference in the likelihood of persistence suggests that while the immune system may clear oncogenic PV infections more effectively and those infections that persist could have similar characteristics to non-oncogenic strains in terms of persistence. This could indicate that, in some of our participants, there are unique host factors that favor the establishment of persistent PV infections. These factors are separate from the above-mentioned general immune response. This implies that persistence of these PV infections is influenced by factors beyond viral oncogenic potential. Both the viral ability to evade the immune system and the host factors such as age and other behavior (smoking, contraceptive use and number of sexual partners) affect clearance [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom our data, we found that a subset of infections were either incident (12%) across the two time points. The presence of incident PV infections underscores the continued risk of acquiring new infections over time, despite prior exposure. This may be because each PV infection leads to the production of genotype-specific antibodies which may not provide protection against other PVs [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. This failure to protect against other PVs has also been reported when it comes to vaccines. Of note is the statistically significant finding that oncogenic PV types were less likely to appear as new infections, a trend that contrasts with non-oncogenic PV types, suggesting that oncogenic PV types may exhibit a lower rate of acquisition compared to non-oncogenic PV types. This could be due to the immune system's more robust response to oncogenic strains or differences in the biology of these viruses that make them less likely to be transmitted or because in this setting they are not as common to acquire as the non-oncogenic types.\u003c/p\u003e \u003cp\u003eOverall, the results presented here emphasize the variability in the persistence, acquisition, and clearance of PV infections, with notable differences between oncogenic and non-oncogenic types. These findings are consistent with the broader understanding of PV infection dynamics, wherein high-risk strains, such as Human PV 16 and Human PV 18, are less likely to be cleared and may persist for extended periods, potentially leading to complications like cancer [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. In contrast, low-risk strains typically clear more rapidly, reducing the overall burden of disease. Furthermore, the results suggest that age, gender, and duration of follow-up had limited impact on the detection and clearance of PV infections in this cohort. This indicates that these factors may not be as influential in the short-term dynamics of PV infections, although they could play a role over longer durations or in different populations as reported by other studies [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The continued monitoring of this cohort and others could provide further insights into the long-term trajectories of PV infections, particularly regarding the persistence of oncogenic strains.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eWhile the study provides valuable insights into the dynamics of PV infection over time, including differences in both the persistence and clearance of oncogenic and non-oncogenic types, it faces several limitations. These include potential biases due to participant selection, possible left censoring since we did not catch participants before the infection started, the short follow-up period, analysis restricted to only the known PV types in the pave database, and the lack of consideration of confounding factors such as sexual behavior, immune status, and vaccination status. Further studies with larger and more diverse populations, longer follow-up durations, and more detailed data on confounding factors are needed to deepen our understanding of PV infection dynamics in this setting.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights important trends in the natural course of oral PV infections, demonstrating that while most infections clear over time, there are distinct differences in the behavior of oncogenic versus non-oncogenic strains. Oncogenic PV types are less likely to be newly acquired and more likely to be cleared, but persistence rates do not differ significantly between the two categories. These findings have important implications for the understanding of PV epidemiology and may guide future preventive and therapeutic strategies, particularly in the context of Human PV-related cancer prevention.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAll authors have no conflict of interest to declare.\u003c/p\u003e\n\u003cp\u003eAuthors contributions\u003c/p\u003e\n\u003cp\u003eFS, WB, IGM and AK conceived the initial research idea. KDP, CJE. DK and PLL were major contributors to the manuscript review. WB, IGM and AK refined the research idea, drafted the initial proposal, and were involved in the whole research process through to the drafting of the manuscript. IGM,\u0026nbsp;DK and KDP\u0026nbsp;were instrumental in data collection and analysing the data. All co-authors reviewed and approved the final manuscript prior to submission.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003eAdditional information\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgement:\u003c/p\u003e\n\u003cp\u003eWe are grateful for the support from the laboratory team namely: Sylvia Nalwanga and Mark Muwuluzi. We thank the participants and administrators of MJAP for providing a good working environment and donation of samples respectively. We also acknowledge Mr. Mukama Emmanuel and Mr. Tayebwa Mordecai for their support in the implementation of the project as members of the administrative team.\u003c/p\u003e\n\u003cp\u003eFunding:\u0026nbsp;Research reported in this publication was supported by the National Institute of Dental \u0026amp; Craniofacial Research of the National Institutes of Health under Award Number R56DE032217\u0026nbsp;\u0026nbsp;and by the Fogarty International Centre of the National Institutes of Health, U.S. Department of State’s Office of the U.S. Global AIDS Coordinator and Health Diplomacy (S/GAC), and President’s Emergency Plan for AIDS Relief (PEPFAR) under Award Number 1R25TW011213.\u0026nbsp;\u0026nbsp;The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMira A, Simon-Soro A, Curtis MA (2017) Role of microbial communities in the pathogenesis of periodontal diseases and caries. 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Cancer Biol Ther 5(6):684\u0026ndash;690\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarillari G, Palladino C, Bacigalupo I, Leone P, Falchi M, Ensoli B (2016) Entrance of the Tat protein of HIV-1 into human uterine cervical carcinoma cells causes upregulation of HPV-E6 expression and a decrease in p53 protein levels. Oncol Lett 12(4):2389\u0026ndash;2394\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMakgoo L, Mosebi S, Mbita Z (2022) Long noncoding RNAs (lncRNAs) in HIV-mediated carcinogenesis: Role in cell homeostasis, cell survival processes and drug resistance. Noncoding RNA Res 7(3):184\u0026ndash;196\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eProulx J, Ghaly M, Park IW, Borgmann K (2022) HIV-1-Mediated Acceleration of Oncovirus-Related Non-AIDS-Defining Cancers. 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J Clin Virol 88:26\u0026ndash;32\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PLHIV, PV clearance, PV persistence, Papilloma viruses' infections","lastPublishedDoi":"10.21203/rs.3.rs-6495161/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6495161/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere is a paucity of data on changes in oral papilloma virus (PV) infection in people living with HIV (PLHIV) especially in low resource settings. The objective of this study was to determine the changes in oral PV infections in PLHIV from a low resource setting over a six-month follow-up period. This was a cohort study in which data was derived from a sub-sample of a parent study that examined oral human papilloma viruses, microbiota, and cancer in PLWHIV. This as a six-month follow up and a 2 mls saliva sample was collected from 541 participants on both visits. The saliva sample was used for DNA extraction, PV screening and typing using PCR methods. The DNA was subjected to Nanopore PV sequencing and subsequently analyzed using the phyloseq object, followed by a series of comparisons using the Phyloseq and Vegan packages in R to generate the alpha and beta diversity indices of the sequencing data from the sampled participants PV OTUs at the two visits. We found that 60% of participants had no detectable PVs at six-month follow-up, with a significant clearance rate of 84.47%. Oncogenic PVs were less likely to be detected as new infections compared to non-oncogenic PVs (Rate Ratio (RR) 0.42, 95% CI 0.31 to 0.56, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Oncogenic PV types were more likely cleared than non-oncogenic strains (RR 1.16, 95% CI 1.03 to 1.31, P\u0026thinsp;=\u0026thinsp;0.02), but persistence rates did not significantly differ. This study highlights important trends in the natural course of oral PV infections, demonstrating that while most infections clear over time, there are distinct differences in the behavior of oncogenic versus non-oncogenic strains. These findings have important implications for the understanding of PV epidemiology and may guide future preventive and therapeutic strategies, particularly in the context of Human PV-related cancer prevention.\u003c/p\u003e","manuscriptTitle":"Changes in Oral Papilloma Virus Infections Over Six Months in People Living with HIV","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-23 10:46:20","doi":"10.21203/rs.3.rs-6495161/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f49d6428-fb43-48ce-8c7a-1263b6d46c16","owner":[],"postedDate":"April 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":47496880,"name":"Virology"}],"tags":[],"updatedAt":"2025-04-23T10:46:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-23 10:46:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6495161","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6495161","identity":"rs-6495161","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}