Abstract
Background
Cervical cancer ranks fourth among cancers in women globally, with over 300,000 deaths annually worldwide. Persistent high-risk HPV (HR-HPV) infection is the main cause of cervical cancer. The World Health Organization (WHO) recommends human papillomavirus (HPV) DNA testing for cervical cancer screening. This study analyses the distribution of HPV genotypes and further investigates their association with the severity of cervical lesions, aiming to develop prevention and screening strategies for cervical cancer.
Methods
A retrospective study was conducted on 229,770 females who underwent HPV DNA testing at The First Affiliated Hospital of Chongqing Medical University between January 2015 and December 2023 to assess the epidemiological distribution of HPV genotypes. In addition, HPV genotypes were further analysed in cervical samples from 749 patients in 2023 who were screened for HPV DNA and had available histological diagnoses. HPV genotyping was performed using capillary electrophoresis analysis.
Results
The overall HPV prevalence was 21.41% among 229,770 patients over the past nine years. Among hr-HPV types, the five most common genotypes were HPV52 (4.55%), HPV16 (3.44%), HPV58 (2.94%), HPV56 (1.33%), and HPV39 (1.32%). Single HPV infection (16.89%) was more common than multiple infections. HPV prevalence exhibited a bimodal distribution, peaking in the under-30 and over-60 age groups. Among 749 HPV-positive patients, the cervical cancer group had the highest median age of 55(interquartile range, 48‒65) years. HPV16 showed the highest prevalence across the different degrees of cervical lesions, followed by HPV52 and HPV58. HR-HPV was found in nearly all cervical cancer cases, with a prevalence of 88.43%, 98.55%, and 97.39% in the low-grade squamous intraepithelial lesion, high-grade squamous intraepithelial lesion, and cervical cancer groups, respectively.
Conclusions
The distribution of HPV genotypes varies by year and age group. HPV16, HPV18, HPV52, and HPV58 are the predominant genotypes detected in high-grade cervical lesions and cervical cancer groups. Given the high prevalence in these lesions, vaccines incorporating HPV52 and HPV58 may offer enhanced protection. Based on local epidemiological data, adaptable vaccination programs and effective screening are essential for preventing and reducing the risk of cervical cancer.
Keywords: Human papillomavirus, Genotype, Cervical lesions
Background
According to 2022 global cancer statistics released by the International Agency for Research on Cancer (IARC) in 2024, cervical cancer remains the fourth most frequently diagnosed cancer in women worldwide and continues to be a major cause of cancer-related mortality, particularly in low- and middle-income countries [1, 2]. China bore a substantial portion of global cancer burden, reflecting the urgent need for effective prevention and control measures [3]. Persistent infection with high-risk human papillomavirus (HR-HPV), especially HPV16 and HPV18, constitutes the primary etiological factor in cervical precancerous lesions and cancer [4, 5]. Therefore, preventing human papillomavirus (HPV) infection and implementing regular screening are key to reducing the cervical cancer incidence.
More than 200 HPV genotypes have been identified to date, of which over 40 are known to infect the female genital tract. The majority of mucosal-tropic HPVs belong to the Alphapapillomavirus genus. Based on their carcinogenic potential, these mucosal alpha-papillomaviruses are further classified into high-risk and low-risk (LR-HPV) types. According to the World Health Organization (WHO), approximately 14 HPV genotypes—namely HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68—are designated as high-risk types [6]. In contrast to high-risk HPV types, lr-HPV strains such as HPV6 and HPV11 typically induce genital warts and other benign proliferative lesions. Although more than 90% of HPV infections clear spontaneously within two years, and only some persistent oncogenic HPV infections may progress to malignancies [7]. Thus, cervical cancer is considered a preventable disease through primary and secondary preventive measures [8].
Currently, five HPV prophylactic vaccines have been approved for marketing in mainland China, including both internationally licensed and domestically developed vaccines. These vaccines target HPV16 and HPV18, and some also include additional genotypes, demonstrating high efficacy in clinical trials [9–11]. However, widespread HPV vaccination in China has been limited by factors such as delayed vaccination, financial barriers, and restrictive policies [12].
Alongside vaccination, regular screening plays a crucial role in eliminating cervical cancer. The World Health Organization (WHO) recommends HPV DNA testing as the most sensitive and efficacious method for detecting high-risk infections and associated lesions, with rescreening every five years [13]. Despite this, China only conducts limited screening programs for HPV DNA testing in females. As a result, cervical cancer remains a prevalent malignancy among women in China [11].
Numerous studies have reported variations in HPV genotype distribution across nations and regions [12, 14]. It is of great importance and timeliness to obtain the epidemiological features of HPV infection in a certain population in China. This study aimed to investigate the distribution of HPV types in Chongqing, southwest China, and their association with various cervical lesions, which provides valuable guidelines for developing regional vaccines and cervical cancer prevention programs, ultimately contributing to the reduction of disease burden.
Methods
Subjects
In this study, a retrospective design was employed, covering the period from January 2015 to December 2023 in Chongqing. The study population included 229,770 females who underwent HPV DNA testing at The First Affiliated Hospital of Chongqing Medical University, a national tertiary-grade hospital. Additionally, a smaller subset of 389 patients with low-grade squamous intraepithelial lesions (LSIL), 207 with high-grade squamous intraepithelial lesions (HSIL), and 153 with cervical cancer was analysed based on a single cross-sectional survey conducted in 2023. The exclusion criteria were pregnancy, menstruation, immunodeficiency, and a history of hysterectomy. In the population of 229,770 females (age range 9‒99 years), the participants were classified into the following age groups: ≤ 30, 31‒40, 41‒50, 51‒60 and > 60. Ethics approval was obtained from the Medical Ethics Committee of The First Affiliated Hospital of Chongqing Medical University. All methods were conducted in accordance with relevant guidelines and regulations.
Specimen collection
The gynecologist rotated a sampling brush head clockwise five times at the ectocervix to obtain a sufficient amount of exfoliated cervical cells. The cervical brush head was then placed into a sterile sample tube labeled with the patient’s information, sealed, and promptly sent to clinical laboratory for HPV DNA testing.
DNA extraction and HPV genotyping
DNA extraction and HPV genotyping were performed using a domestic commercially available HPV genotyping test kit (Ningbo Health Gene-Tech Co., Ltd). The kit detected 25 genotypes, including 13 hr-HPV genotypes (HPV16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 68) and 12 lr-HPV genotypes (HPV6, 11, 26, 42, 43, 44, 53, 66, 73, 81, 82, and 83). The process consisted of three steps: HPV-DNA extraction, Polymerase Chain Reaction (PCR) amplification and capillary electrophoresis analysis of PCR products. Bioperfectus Diagnostics (Jiangsu Bioperfectus Technologies Co., Ltd) was used for HPV DNA extraction. Tian Long (Suzhou Tianlong Bio-Tech Co., Ltd.) was used for gene amplification. In brief, 9 µL of the extracted DNA was used in an 11 µL PCR master mix reaction solution. The amplification parameters were set as follows: (1) 42 °C for 5 min; (2) 94 °C for 8 min; (3) 35 cycles were performed at 94 °C for 30 s, 60 °C for 30 s, and 70 °C for 1 min. PCR products were analysed by 3500 Dx Genetic Analyzer (Thermo Fisher Scientific) through capillary electrophoresis.
Colposcopy and histology
Patients with hr-HPV positive or abnormal cytological results underwent colposcopy examination, while patients with atypical squamous cells of undetermined significance (ASC-US) who are negative for hr-HPV generally do not require further examination. Direct biopsy was performed for visible or suspicious lesions. A trained pathologist interpreted all specimens in accordance with the 2020 WHO Classification of Female Genital Tumours [15]. Pathological results of this study were characterized as LSIL, HSIL, and cervical cancer (primarily squamous cell carcinoma and adenocarcinoma).
Statistics
Statistical analyses were performed using SPSS 25.0 and GraphPad Prism 10.1.2. The linear-by-linear association and gamma values were used to assess the trend in HPV prevalence over the past nine years. Normality of continuous variables was assessed using the Kolmogorov-Smirnov and Shapiro-Wilk tests. Given non-normal distributions in two of three groups (P < 0.05), all continuous variables are reported as medians with interquartile ranges (IQR) and analysed by Kruskal-Wallis test, followed by Dunn’s post-hoc tests with Bonferroni adjustment (automatically calculated in SPSS). Categorical variables were represented as percentages, with group comparisons made by the Chi-squared test or Fisher’s exact test (if > 20% of cells had expected counts < 5). All analyses were two-sided and P < 0.05 was considered statistically significant.
Results
Overall HPV prevalence and type-specific distribution
The overall HPV prevalence was 21.41% (49,203/229,770); 16.43% (37,757/229,770) of patients were found to have hr-HPV infections, while 7.48% (17,186/229,770) were identified as having low-risk types. The prevalence of single infection, double infection, triple infection, and quadruple or more infections was 16.89%, 3.49%, 0.79%, and 0.24%, respectively. Consequently, single infection was the most common pattern of HPV infection among females. Since HPV73 was not detected in any participants, the analysis focused on the remaining 24 types (Table 1; Figs. 1 and 2B).
Table 1.
Prevalence of HPV infections in Chongqing, China from 2015 to 2023
| HPV genotype | 2015 (n = 24691) | 2016 (n = 27394) | 2017 (n = 25993) | 2018 (n = 27265) | 2019 (n = 30016) | 2020 (n = 27509) | 2021 (n = 31095) | 2022 (n = 21894) | 2023 (n = 13913) | χ² | P | Gamma value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Any HPV | 5369 (21.74%) | 6093 (22.24%) | 5053 (19.44%) | 5676 (20.82%) | 5994 (19.97%) | 5615 (20.41%) | 6414 (20.63%) | 5257 (24.01%) | 3732 (26.82%) | 76.098 | <0.001 | 0.028 |
| HR-HPV | 4103 (16.62%) | 4637 (16.93%) | 3834 (14.75%) | 4332 (15.89%) | 4568 (15.22%) | 4235 (15.39%) | 4929 (15.85%) | 4231 (19.32%) | 2888 (20.76%) | 91.499 | <0.001 | 0.034 |
| HPV16 | 968 (3.92%) | 1151 (4.20%) | 1042 (4.01%) | 979 (3.59%) | 926 (3.09%) | 702 (2.55%) | 845 (2.72%) | 746 (3.41%) | 539 (3.87%) | 82.577 | <0.001 | -0.069 |
| HPV18 | 369 (1.49%) | 287 (1.05%) | 307 (1.18%) | 289 (1.06%) | 318 (1.06%) | 239 (0.87%) | 294 (0.95%) | 229 (1.05%) | 158 (1.14%) | 22.028 | <0.001 | -0.062 |
| HPV31 | 85 (0.34%) | 94 (0.34%) | 53 (0.20%) | 58 (0.21%) | 77 (0.26%) | 88 (0.32%) | 118 (0.38%) | 149 (0.68%) | 74 (0.53%) | 44.233 | <0.001 | 0.154 |
| HPV33 | 236 (0.96%) | 257 (0.94%) | 193 (0.74%) | 163 (0.60%) | 171 (0.57%) | 137 (0.50%) | 170 (0.55%) | 196 (0.90%) | 132 (0.95%) | 10.527 | 0.001 | -0.053 |
| HPV35 | 117 (0.47%) | 145 (0.53%) | 100 (0.38%) | 114 (0.42%) | 92 (0.31%) | 96 (0.35%) | 112 (0.36%) | 78 (0.36%) | 59 (0.42%) | 10.164 | 0.001 | -0.069 |
| HPV39 | 285 (1.15%) | 404 (1.47%) | 314 (1.21%) | 332 (1.22%) | 361 (1.20%) | 356 (1.29%) | 361 (1.16%) | 345 (1.58%) | 270 (1.94%) | 16.126 | <0.001 | 0.045 |
| HPV45 | 53 (0.21%) | 68 (0.25%) | 49 (0.19%) | 76 (0.28%) | 62 (0.21%) | 58 (0.21%) | 70 (0.23%) | 66 (0.30%) | 41 (0.29%) | 2.362 | 0.124 | 0.042 |
| HPV51 | 301 (1.22%) | 340 (1.24%) | 267 (1.03%) | 312 (1.14%) | 272 (0.91%) | 280 (1.02%) | 294 (0.95%) | 289 (1.32%) | 164 (1.18%) | 1.355 | 0.244 | -0.016 |
| HPV52 | 1029 (4.17%) | 1108 (4.04%) | 745 (2.87%) | 1067 (3.91%) | 1330 (4.43%) | 1315 (4.78%) | 1562 (5.02%) | 1335 (6.10%) | 959 (6.89%) | 352.665 | <0.001 | 0.121 |
| HPV56 | 398 (1.61%) | 364 (1.33%) | 278 (1.07%) | 335 (1.23%) | 397 (1.32%) | 392 (1.42%) | 393 (1.26%) | 300 (1.37%) | 205 (1.47%) | 0.027 | 0.869 | -0.002 |
| HPV58 | 610 (2.47%) | 801 (2.92%) | 744 (2.86%) | 874 (3.21%) | 825 (2.75%) | 740 (2.69%) | 885 (2.85%) | 758 (3.46%) | 525 (3.77%) | 33.270 | <0.001 | 0.045 |
| HPV59 | 219 (0.89%) | 238 (0.87%) | 219 (0.84%) | 237 (0.87%) | 270 (0.90%) | 307 (1.12%) | 292 (0.94%) | 204 (0.93%) | 138 (0.99%) | 4.892 | 0.027 | 0.031 |
| HPV68 | 104 (0.42%) | 114 (0.42%) | 58 (0.22%) | 138 (0.51%) | 194 (0.65%) | 164 (0.60%) | 207 (0.67%) | 271 (1.24%) | 194 (1.39%) | 257.287 | <0.001 | 0.270 |
| LR-HPV | 1799(7.29%) | 2121(7.74%) | 1707(6.57%) | 2040(7.48%) | 2192(5.69%) | 2052(7.46%) | 2157(6.94%) | 1740(7.95%) | 1378(9.90%) | 33.645 | <0.001 | 0.028 |
| HPV6 | 196 (0.79%) | 220 (0.80%) | 184 (0.71%) | 181 (0.66%) | 176 (0.59%) | 186 (0.68%) | 205 (0.66%) | 158 (0.72%) | 111 (0.80%) | 1.898 | 0.168 | -0.023 |
| HPV11 | 91 (0.37%) | 98 (0.36%) | 83 (0.32%) | 89 (0.33%) | 90 (0.30%) | 50 (0.18%) | 86 (0.28%) | 71 (0.32%) | 41 (0.29%) | 6.684 | 0.010 | -0.064 |
| HPV26 | 6 (0.02%) | 17 (0.06%) | 11 (0.04%) | 14 (0.05%) | 8 (0.03%) | 2 (0.01%) | 5 (0.02%) | 4 (0.02%) | 5 (0.04%) | 6.371 | 0.012 | -0.199 |
| HPV42 | 110 (0.45%) | 113 (0.41%) | 68 (0.26%) | 83 (0.30%) | 74 (0.25%) | 54 (0.20%) | 73 (0.23%) | 68 (0.31%) | 63 (0.45%) | 8.923 | 0.003 | -0.076 |
| HPV43 | 258 (1.04%) | 267 (0.97%) | 223 (0.86%) | 261 (0.96%) | 292 (0.97%) | 252 (0.92%) | 244 (0.78%) | 192 (0.88%) | 157 (1.13%) | 1.517 | 0.218 | -0.019 |
| HPV44 | 165 (0.67%) | 251 (0.92%) | 193 (0.74%) | 248 (0.91%) | 302 (1.01%) | 369 (1.34%) | 327 (1.05%) | 258 (1.18%) | 188 (1.35%) | 74.767 | <0.001 | 0.117 |
| HPV53 | 494 (2.00%) | 552 (2.02%) | 444 (1.71%) | 557 (2.04%) | 662 (2.21%) | 635 (2.31%) | 672 (2.16%) | 535 (2.44%) | 433 (3.11%) | 60.205 | <0.001 | 0.071 |
| HPV66 | 184 (0.75%) | 226 (0.82%) | 191 (0.73%) | 251 (0.92%) | 252 (0.84%) | 181 (0.66%) | 220 (0.71%) | 227 (1.04%) | 146 (1.05%) | 5.364 | 0.021 | 0.033 |
| HPV81 | 343 (1.39%) | 410 (1.50%) | 365 (1.40%) | 453 (1.66%) | 441 (1.47%) | 403 (1.46%) | 386 (1.24%) | 340 (1.55%) | 325 (2.34%) | 10.292 | 0.001 | 0.032 |
| HPV82 | 75 (0.30%) | 120 (0.44%) | 58 (0.22%) | 87 (0.32%) | 87 (0.29%) | 86 (0.31%) | 90 (0.29%) | 47 (0.21%) | 38 (0.27%) | 6.173 | 0.013 | -0.062 |
| HPV83 | 51 (0.21%) | 53 (0.19%) | 50 (0.19%) | 35 (0.13%) | 55 (0.18%) | 51 (0.19%) | 52 (0.17%) | 45 (0.21%) | 33 (0.24%) | 0.091 | 0.763 | 0.009 |
| Single infection | 4288 (17.37%) | 4824 (17.61%) | 4145 (15.95%) | 4458 (16.35%) | 4676 (15.58%) | 4437 (16.13%) | 5199 (16.72%) | 4020 (18.36%) | 2770 (19.91%) | 19.453 | <0.001 | 0.015 |
| Double infection | 846 (3.43%) | 1007 (3.68%) | 702 (2.70%) | 962 (3.53%) | 987 (3.29%) | 904 (3.29%) | 951 (3.06%) | 935 (4.27%) | 725 (5.21%) | 47.175 | <0.001 | 0.048 |
| Triple infection | 191 (0.77%) | 202 (0.74%) | 156 (0.60%) | 188 (0.69%) | 261 (0.87%) | 211 (0.77%) | 204 (0.66%) | 217 (0.99%) | 189 (1.36%) | 28.375 | <0.001 | 0.078 |
| Quadruple or more infection | 44 (0.18%) | 60 (0.22%) | 50 (0.19%) | 68 (0.25%) | 70 (0.23%) | 63 (0.23%) | 60 (0.19%) | 85 (0.39%) | 48 (0.35%) | 15.705 | <0.001 | 0.108 |
HPV, human papillomavirus; HR, high-risk; LR, low-risk
Fig. 1.
Prevalence of HPV Genotypes in 229,770 Females from 2015 to 2023 (HR-HPV and LR-HPV). HPV, human papillomavirus; HR, high-risk; LR, low-risk
Fig. 2.
Prevalence of HPV infection from 2015 to 2023. (A) High-risk (HR), low-risk (LR), and any HPV infection. (B) Single, double, triple, and quadruple or more infections
The details of HPV genotypes are summarized in Fig. 1; Table 2. Among the 13 hr-HPV, HPV52 (4.55%), HPV16 (3.44%), HPV58 (2.94%), HPV56 (1.33%), and HPV39 (1.32%) were the five most prevalent in the population, with HPV18 (1.08%) ranking seventh. HPV53 (2.17%) and HPV81 (1.51%) were the most commonly observed genotypes in lr-HPV infections.
Table 2.
Age-Specific distribution of HPV genotypes (N = 229,770)
| HPV genotype | Total | ≤ 30y (n = 36956) | 31-40y (n = 71642) | 41-50y (n = 73846) | 51-60y (n = 35984) | >60y (n = 11342) |
|---|---|---|---|---|---|---|
| Any HPV | 49,203 (21.41%) | 7934 (21.47%) | 13,366 (18.66%) | 15,205 (20.59%) | 9280 (25.79%) | 3418 (30.14%) |
| HR-HPV | 37,757 (16.43%) | 6067 (16.42%) | 10,209 (14.25%) | 11,468 (15.53%) | 7165 (19.91%) | 2848 (25.11%) |
| HPV16 | 7898 (3.44%) | 1207 (3.27%) | 1884 (2.63%) | 2464 (3.34%) | 1511 (4.20%) | 832 (7.34%) |
| HPV18 | 2490 (1.08%) | 452 (1.22%) | 665 (0.93%) | 751 (1.02%) | 443 (1.23%) | 179 (1.58%) |
| HPV31 | 796 (0.35%) | 122 (0.33%) | 220 (0.31%) | 254 (0.34%) | 143 (0.40%) | 57 (0.50%) |
| HPV33 | 1655 (0.72%) | 207 (0.56%) | 396 (0.55%) | 529 (0.72%) | 348 (0.97%) | 175 (1.54%) |
| HPV35 | 913 (0.40%) | 153 (0.41%) | 236 (0.33%) | 263 (0.36%) | 205 (0.57%) | 56 (0.49%) |
| HPV39 | 3028 (1.32%) | 566 (1.53%) | 833 (1.16%) | 876 (1.19%) | 541 (1.50%) | 212 (1.87%) |
| HPV45 | 543 (0.24%) | 85 (0.23%) | 146 (0.20%) | 156 (0.21%) | 109 (0.30%) | 47 (0.41%) |
| HPV51 | 2519 (1.10%) | 558 (1.51%) | 693 (0.97%) | 656 (0.89%) | 414 (1.15%) | 198 (1.75%) |
| HPV52 | 10,450 (4.55%) | 1732 (4.69%) | 2946 (4.11%) | 3080 (4.17%) | 1992 (5.54%) | 700 (6.17%) |
| HPV56 | 3062 (1.33%) | 485 (1.31%) | 758 (1.06%) | 774 (1.05%) | 678 (1.88%) | 367 (3.24%) |
| HPV58 | 6762 (2.94%) | 1057 (2.86%) | 1738 (2.43%) | 2029 (2.75%) | 1373 (3.82%) | 565 (4.98%) |
| HPV59 | 2124 (0.92%) | 471 (1.27%) | 567 (0.79%) | 571 (0.77%) | 370 (1.03%) | 145 (1.28%) |
| HPV68 | 1444 (0.63%) | 230 (0.62%) | 411 (0.57%) | 402 (0.54%) | 279 (0.78%) | 122 (1.08%) |
| LR-HPV | 17,186 (7.48%) | 3005 (8.13%) | 4404 (6.15%) | 5177 (7.01%) | 3405 (9.46%) | 1195 (10.54%) |
| HPV6 | 1617 (0.70%) | 474 (1.28%) | 399 (0.56%) | 375 (0.51%) | 257 (0.71%) | 112 (0.99%) |
| HPV11 | 699 (0.30%) | 220 (0.60%) | 182 (0.25%) | 144 (0.20%) | 107 (0.30%) | 46 (0.41%) |
| HPV26 | 72 (0.03%) | 9 (0.02%) | 12 (0.02%) | 14 (0.02%) | 24 (0.07%) | 13 (0.11%) |
| HPV42 | 706 (0.31%) | 89 (0.24%) | 185 (0.26%) | 212 (0.29%) | 180 (0.50%) | 40 (0.35%) |
| HPV43 | 2146 (0.93%) | 443 (1.20%) | 570 (0.80%) | 605 (0.82%) | 377 (1.05%) | 151 (1.33%) |
| HPV44 | 2301 (1.00%) | 292 (0.79%) | 577 (0.81%) | 797 (1.08%) | 493 (1.37%) | 142 (1.25%) |
| HPV53 | 4984 (2.17%) | 696 (1.88%) | 1237 (1.73%) | 1541 (2.09%) | 1122 (3.12%) | 388 (3.42%) |
| HPV66 | 1878 (0.82%) | 384 (1.04%) | 482 (0.67%) | 488 (0.66%) | 346 (0.96%) | 178 (1.57%) |
| HPV81 | 3466 (1.51%) | 525 (1.42%) | 846 (1.18%) | 1130 (1.53%) | 760 (2.11%) | 205 (1.81%) |
| HPV82 | 688 (0.30%) | 163 (0.44%) | 197 (0.27%) | 173 (0.23%) | 93 (0.26%) | 62 (0.55%) |
| HPV83 | 425 (0.18%) | 46 (0.12%) | 91 (0.13%) | 128 (0.17%) | 125 (0.35%) | 35 (0.31%) |
| Single infection | 38,817 (16.89%) | 5905 (15.98%) | 10,978 (15.32%) | 12,546 (16.99%) | 7068 (19.64%) | 2320 (20.45%) |
| Double infection | 8019 (3.49%) | 1500 (4.06%) | 1956 (2.73%) | 2191 (2.97%) | 1636 (4.55%) | 736 (6.49%) |
| Triple infection | 1819 (0.79%) | 398 (1.08%) | 357 (0.50%) | 395 (0.53%) | 418 (1.16%) | 251 (2.21%) |
| Quadruple or more infection | 548 (0.24%) | 131 (0.35%) | 75 (0.10%) | 73 (0.10%) | 158 (0.44%) | 111 (0.98%) |
HPV, human papillomavirus; HR, high-risk; LR, low-risk
Year-specific prevalence of HPV genotypes
A significant upward trend in overall HPV prevalence from 2015 to 2023 was identified, as detailed in Table 1; Fig. 2A (P < 0.001). Similar trends were observed for HPV31, HPV39, HPV44, HPV52, HPV53, HPV58, HPV59, HPV66, HPV68, and HPV81, as shown exclusively in Table 1. With the increase in the aforementioned ten types, HPV16 and HPV18 significantly decreased over the calendar years (P < 0.001). Among all participants, hr-HPV, lr-HPV infection, as well as single and multiple infections, demonstrated significant differences and an increasing trend during the same period (P < 0.001; Table 1; Fig. 2).
Age-specific distribution of HPV infection
Among the 229,770 participants, the median age was 41 (IQR, 33‒49) years (D = 0.054, P < 0.001), and there were differences in the age distribution of HPV infection. The age groups ≤ 30, 31–40, 41–50, 51‒60 and > 60 accounted for 16.08%, 31.18%, 32.14%, 15.66%, 4.94%, respectively (Table 2). Therefore, the 41‒50 years group represented the largest proportion in this study. The age groups 31‒40 also exhibited similar infection rates. As shown in Fig. 3A, the overall HPV infection displayed a bimodal distribution with age. The prevalence peaked first in women ≤ 30 years (21.47%), then declined moderately, and rose again in the 51‒60 age group (25.79%). The second peak, observed in the > 60 years age group (30.14%), was higher than the first peak. hr-HPV and lr-HPV infection curves showed a very similar U-shaped distribution across age groups, as did the overall infection (Table 2; Fig. 3A). In the younger group (≤ 30 years), HPV52 (4.69%), HPV16 (3.27%), HPV58 (2.86%), HPV39 (1.53%), and HPV51 (1.51%) were the most prevalent hr-HPV genotypes. In the older group (> 60 years), the most prevalent hr-HPV were HPV16, HPV52, HPV58, HPV56, and HPV39, with the infection rates of 7.34%, 6.17%, 4.98%, 3.24%, and 1.87%, respectively. The prevalence of single infection across the age groups gradually increased. In the groups of ≤ 30 years and > 60 years, the single infection rates were 15.98% and 20.45%, respectively. (Table 2; Fig. 3B).
Fig. 3.
Age distribution of HPV genotypes. (A) High-risk (HR), low-risk (LR), and any HPV infection. (B) Single, double, triple, and quadruple or more infections
Distribution of single and multiple HPV infections
There existed some differences in the prevalence rates across hr-HPV genotypes and between different patterns of infection. Among all high-risk genotypes, the single infection pattern demonstrated the highest prevalence, followed by a consistent decline in frequency from double to multiple infection patterns. The top five genotypes of single infection were HPV52 (3.18%), HPV16 (2.46%), HPV58 (1.92%), HPV39 (0.79%), and HPV56 (0.75%), with HPV18 ranking sixth. In the double infection group, the most common genotypes were HPV52 (0.99%), HPV58 (0.72%), HPV16 (0.68%), HPV56 (0.37%), and HPV39 (0.36%) (Table 3). Both single and double infection patterns shared the same top five HPV genotypes, albeit in a slightly different order (Table 3; Fig. 4).
Table 3.
Genotype-Specific distribution of single, double, and multiple HPV infections (N = 229,770)
| HPV genotype | Total | Single infection | Double infection | Multiple infection |
|---|---|---|---|---|
| HPV16 | 7898 (3.44%) | 5650 (2.46%) | 1572 (0.68%) | 676 (0.29%) |
| HPV18 | 2490 (1.08%) | 1514 (0.66%) | 669 (0.29%) | 307 (0.13%) |
| HPV31 | 796 (0.35%) | 485 (0.21%) | 205 (0.09%) | 106 (0.05%) |
| HPV33 | 1655 (0.72%) | 1030 (0.45%) | 398 (0.17%) | 227 (0.10%) |
| HPV35 | 913 (0.40%) | 500 (0.22%) | 238 (0.10%) | 175 (0.08%) |
| HPV39 | 3028 (1.32%) | 1826 (0.79%) | 828 (0.36%) | 374 (0.16%) |
| HPV45 | 543 (0.24%) | 246 (0.11%) | 189 (0.08%) | 108 (0.05%) |
| HPV51 | 2519 (1.10%) | 1426 (0.62%) | 679 (0.30%) | 414 (0.18%) |
| HPV52 | 10450 (4.55%) | 7318 (3.18%) | 2285 (0.99%) | 847 (0.37%) |
| HPV56 | 3062 (1.33%) | 1725 (0.75%) | 849 (0.37%) | 488 (0.21%) |
| HPV58 | 6762 (2.94%) | 4419 (1.92%) | 1660 (0.72%) | 683 (0.30%) |
| HPV59 | 2124 (0.92%) | 1208 (0.53%) | 597 (0.26%) | 319 (0.14%) |
| HPV68 | 1444 (0.63%) | 885 (0.39%) | 388 (0.17%) | 171 (0.07%) |
| HPV6 | 1617 (0.70%) | 882 (0.38%) | 479 (0.21%) | 256 (0.11%) |
| HPV11 | 699 (0.30%) | 402 (0.17%) | 180 (0.08%) | 117 (0.05%) |
| HPV26 | 72 (0.03%) | 30 (0.01%) | 24 (0.01%) | 18 (0.01%) |
| HPV42 | 706 (0.31%) | 401 (0.17%) | 206 (0.09%) | 99 (0.04%) |
| HPV43 | 2146 (0.93%) | 1130 (0.49%) | 631 (0.27%) | 385 (0.17%) |
| HPV44 | 2301 (1.00%) | 1274 (0.55%) | 693 (0.30%) | 334 (0.15%) |
| HPV53 | 4984 (2.17%) | 3008 (1.31%) | 1332 (0.58%) | 644 (0.28%) |
| HPV66 | 1878 (0.82%) | 1057 (0.46%) | 537 (0.23%) | 284 (0.12%) |
| HPV81 | 3466 (1.51%) | 1829 (0.80%) | 1068 (0.46%) | 569 (0.25%) |
| HPV82 | 688 (0.30%) | 394 (0.17%) | 187 (0.08%) | 107 (0.05%) |
| HPV83 | 425 (0.18%) | 178 (0.08%) | 144 (0.06%) | 103 (0.04%) |
HPV, human papillomavirus
Fig. 4.
Prevalence of single, double, and multiple HPV infections over the past 9 years
Single and multiple HPV infection patterns in cervical lesions
Of the 749 patients with cervical lesions in 2023, all tested positive for HPV, with a median age of 45 (IQR, 35‒55) years (W = 0.978, P < 0.001). As shown in Table 4, the Kruskal-Wallis test revealed a statistically significant difference in age distribution among the LSIL, HSIL, and cervical cancer groups (H = 118.248, P < 0.001). Dunn’s post-hoc analysis revealed significant age differences: the cervical cancer group was significantly older than both HSIL (Padj < 0.001) and LSIL (Padj < 0.001), while the HSIL group had higher median age than LSIL (Padj = 0.002). Additionally, other categorical variables were compared across the three groups using chi-square or Fisher’s exact test, without any pairwise comparisons being performed.
Table 4.
Age distribution and HPV infection characteristics according to histological diagnosis among 749 females
| Variables | Total | LSIL | HSIL | Cervical cancer | χ² | P |
|---|---|---|---|---|---|---|
| Number | 749 | 389 | 207 | 153 | - | - |
| Age* | 45(35–55) | 39(31.5–50)a | 43(35–55)b | 55(48–65)c | - | - |
| HR-HPV | 697(93.06%) | 344(88.43%) | 204(98.55%) | 149(97.39%) | 26.988 | <0.001 |
| single high-risk | 575(76.77%) | 279(71.72%) | 169(81.64%) | 127(83.01%) | 11.650 | 0.003 |
| multiple high-risk | 122(16.29%) | 65(16.71%) | 35(16.91%) | 22(14.38%) | 0.518 | 0.772 |
| LR-HPV | 167(22.56%) | 120(30.85%) | 29(14.01%) | 18(11.76%) | 34.421 | <0.001 |
| Single infection | 540(72.10%) | 260(66.84%) | 157(75.85%) | 123(80.39%) | 12.027 | 0.002 |
| Double infection | 147(19.63%) | 93(23.91%) | 35(16.91%) | 19(12.42%) | 10.529 | 0.005 |
| Triple infection | 44(5.87%) | 30(7.71%) | 9(4.35%) | 5(3.27%) | 5.128 | 0.077 |
| Quadruple or more infection | 18(2.40%) | 6(1.54%) | 6(2.90%) | 6(3.92%) | 3.170 | 0.194 |
HPV, human papillomavirus; HR, high-risk; LR, low-risk; LSIL, low-grade squamous lesion; HSIL, high-grade squamous lesion
*Age: Kruskal-Wallis/Dunn’s test; Other variables: χ² or Fisher’s exact test
Significant comparisons (adjusted P < 0.05):
a) LSIL vs. HSIL (Padj = 0.002);
b) HSIL vs. Cervical cancer (Padj < 0.001);
c) LSIL vs. Cervical cancer (Padj < 0.001)
Infection with any high-risk genotype was the most common HPV infection, where the minimum proportion was 88.43% (344/389) in LSIL group. The prevalence of hr-HPV infection was 98.55% (204/207), and 97.39% (149/153) in HSIL, and cervical cancer groups, respectively. Among the overall high-risk infections (93.06%), single high-risk type accounted for a substantial portion, representing 76.77% of the total population. Single infection constituted the predominant pattern, accounting for 72.10% (540/749) of the cases. There were significant differences between single infection and double infection across the pathological groups (P < 0.05). Single infection predominated in the LSIL, HSIL, and cervical cancer groups, with ratios of 66.84% (260/389), 75.85% (157/207), and 80.39% (123/153). With the progression of cervical lesions, a decreasing trend in multiple infections was observed, with the exception of quadruple or more infections (Table 4). Significant differences were identified across the pathological groups in various HPV infection patterns, including overall hr-HPV, single hr-HPV, lr-HPV, single infection, and double infection. However, no significant differences were found in the multiple high-risk, triple, and higher infection groups (Table 4).
HR-HPV distribution in patients with cervical lesions
Among 749 patients with cervical abnormalities, the distribution of hr-HPV genotypes varied, with these high-risk infections predominantly leading to disease development. In patients with cervical lesions, the most frequently detected hr-HPV types were HPV16 (32.58%), HPV52 (25.63%), HPV58 (16.82%), HPV18 (6.41%), and HPV33 (5.87%). In the LSIL group, HPV52 (34.70%) was the most common genotype, as shown in Fig. 5, followed by HPV16 (17.48%), HPV58 (15.94%), HPV18 (6.68%), and HPV56 (6.68%). Among the HSIL group, the leading hr-HPV genotypes identified were HPV16 (36.71%), HPV58 (23.67%), HPV52 (22.22%), HPV33 (9.66%), and HPV18 (3.86%). The most common types identified in cervical cancer groups were HPV16 (65.36%), HPV58 (9.80%), HPV18 (9.15%), HPV52 (7.19%), HPV39 (5.23%), and HPV68 (5.23%). Regarding the types, the prevalence of HPV16 increased with the severity of cervical lesions (P < 0.001). In contrast, the prevalence of HPV52 dropped drastically, from 34.70% in patients with LSIL to 7.19% in patients with cervical cancer (P < 0.001). Compared with HPV16 and HPV52, only HPV33 and HPV58 showed significant differences in prevalence from LSIL to cervical cancer (P < 0.05), while the other high-risk genotypes did not (all P > 0.05; Table 5).
Fig. 5.
The infection rate of high-risk human papillomaviruses (HR-HPV) across different groups of cervical lesions. HSIL, high-grade squamous intraepithelial lesion; LSIL, low-grade squamous intraepithelial lesion
Table 5.
Genotype-specific HR-HPVs in cervical pathology
| HR HPV | Total | LSIL | HSIL | Cervical cancer | χ² | P * |
|---|---|---|---|---|---|---|
| Number | 749 | 389 | 207 | 153 | - | - |
| HPV16 | 244(32.58%) | 68(17.48%) | 76(36.71%) | 100(65.36%) | 116.837 | <0.001 |
| HPV18 | 48(6.41%) | 26(6.68%) | 8(3.86%) | 14(9.15%) | 4.200 | 0.122 |
| HPV31 | 13(1.74%) | 6(1.54%) | 5(2.42%) | 2(1.31%) | 0.828 | 0.751 |
| HPV33 | 44(5.87%) | 17(4.37%) | 20(9.66%) | 7(4.58%) | 7.429 | 0.024 |
| HPV35 | 16(2.14%) | 7(1.80%) | 6(2.90%) | 3(1.96%) | 0.906 | 0.629 |
| HPV39 | 39(5.21%) | 23(5.91%) | 8(3.86%) | 8(5.23%) | 1.148 | 0.563 |
| HPV45 | 7(0.93%) | 2(0.51%) | 4(1.93%) | 1(0.65%) | 2.765 | 0.237 |
| HPV51 | 24(3.20%) | 12(3.08%) | 8(3.86%) | 4(2.61%) | 0.481 | 0.786 |
| HPV52 | 192(25.63%) | 135(34.70%) | 46(22.22%) | 11(7.19%) | 45.357 | <0.001 |
| HPV56 | 37(4.94%) | 26(6.68%) | 8(3.86%) | 3(1.96%) | 5.921 | 0.052 |
| HPV58 | 126(16.82%) | 62(15.94%) | 49(23.67%) | 15(9.80%) | 12.543 | 0.002 |
| HPV59 | 23(3.07%) | 16(4.11%) | 4(1.93%) | 3(1.96%) | 2.955 | 0.228 |
| HPV68 | 31(4.14%) | 19(4.88%) | 4(1.93%) | 8(5.23%) | 3.543 | 0.170 |
HPV, human papillomavirus; HR, high-risk; LSIL, low-grade squamous lesion; HSIL, high-grade squamous lesion
* represents comparisons among the three groups (LSIL, HSIL, and Cervical cancer), analysed using the chi-square test or Fisher’s exact test
Discussion
In the current study, our analysis showed that the overall prevalence of HPV infection was 21.41%, consistent with the 21.66% reported in Southern Guangzhou [13] and slightly lower than the 23.28% observed in neighboring Chengdu [16]. Previous studies have, however, demonstrated considerable disparities in HPV infection rates across 37 cities in China, with prevalence ranging from 18.42 to 31.94% [17]. For example, rates were reported as 18.71% in Hunan [18], 18.81% in Shanghai [19], 26.92% in Jiangsu [20] and as high as 34.40% in Jilin [21]. Various factors, including economic conditions, vaccination efforts, and cervical screening strategies, significantly influenced these disparities. As a result, HPV prevalence varies across regions in China. Thus, more refined strategies to enhance the coverage of HPV vaccine and screening programs, reducing cervical cancer risk, are needed.
The most common genotypes in our study were HPV52, HPV16, HPV58, HPV53, and HPV81, which were consistent with the results from Chengdu and Chenzhou [16, 18]. In contrast, our data differed from other regions in China, including Jingzhou (HPV52, 58, 16, 68 and 51) [22], Shandong(HPV16, 52, 58, 51 and 56) [23], and Xinjiang(HPV16, 51, 52, 56 and 39) [24]. A decrease in HPV11, HPV16, HPV18, and HPV33 was observed, alongside an increase in HPV31, HPV52, and HPV58. Considering these trends, the nonavalent HPV vaccine (Gardasil®9, targeting HPV6, 11, 16, 18, 31, 33, 45, 52, and 58) appears to be a more appropriate option.
Our study showed a ‘two-peak’ pattern in the age-specific distribution of overall HPV infection rates. The first peak was observed in the younger age group (≤ 30 years), while the second peak appeared in the age group (> 60 years). Before reaching the second peak, a rapidly increasing minor peak was observed in the age group (51‒60 years), similar to previous studies [17, 25, 26]. In this study, the prevalence of hr-HPV infection, both single and multiple infections, exhibited a comparable trend. HR-HPV infections were prevalent across different age groups, with single infections being the dominant pattern. In the younger group, the higher rate may be attributed to sexual behavior and immature immunity. Similarly, in women over 50, the rise in HPV prevalence may be explained by postmenopausal hormonal changes that weaken local immune defenses and the reactivation of latent HPV infections [27]. Based on age-specific incidence peaks, early vaccination for adolescents (13‒15years) [28], vaccination of females before sexual activity, and continued screening for older adults (over 50 years) are recommended, which underscores the importance of maintaining vigilance in this population.
Age is an important factor in the progression of cervical lesions. As the severity of the lesions increases, the median age also rises, with the median age in the cervical cancer group being significantly higher than that in the HSIL and LSIL groups. This suggests that increasing age may elevate the risk of progression from low-grade lesions to cervical cancer. Therefore, age should be carefully considered when developing screening and prevention strategies, and appropriate stratification should be implemented. After analyzing age, the focus shifted to the distribution of hr-HPV, which was detected in nearly all cervical neoplasia [29]. In this study, the hr-HPV infection rate approached 100% during the progression of cervical lesions, further supporting the strong link between HPV infection, particularly high-risk HPV, and cervical cancer development. Based on these findings, prioritizing hr-HPV genotyping for vaccination and screening in regions with limited resources is recommended. By focusing on hr-HPV infections, early prevention of cervical cancer can be enhanced, leading to a reduction in its incidence and mortality.
In this study, HPV16 exhibited the highest prevalence among different groups of cervical pathological lesions, particularly in the cervical cancer group. This finding was consistent with previous studies [30, 31], indicating that HPV16 remains a major factor in the progression of cervical lesions. The study also observed that other high-risk HPV types, such as HPV52 and HPV58, are frequently found in different pathological groups. Compared with the overall prevalence of specific HPV types, HPV52 and HPV58 exhibit high prevalence both in the general population and in cervical lesions. Our results, consistent with those reported in Zhejiang [31], indicated that vaccines targeting HPV16, HPV18, HPV52, and HPV58 would be effective in preventing cervical cancer. Currently, four vaccines, including HPV52 and HPV58, are under development and undergoing clinical trials in China [32].
Our study investigated the characteristics of HPV infection and its association with different degrees of cervical lesions in females from Chongqing. However, there are several limitations in our study. We used a retrospective observational method based on a single-center study, which may have introduced selection bias due to sampling methods, information bias, and loss to follow-up. The limited sample size may not fully represent the population in Chongqing. The lack of cytological data from HPV-positive cases precludes comparisons with cervical pathology, limiting comprehensive diagnostic insights. Furthermore, untracked vaccination status in a subset of the general population renders vaccine effectiveness uncertain. Additionally, as the study focused solely on histologically confirmed HPV-positive cervical lesions, we could not analyze non-HPV-related lesions or their trends. Finally, longitudinal HPV data were unavailable, preventing assessment of cervical lesion progression in persistent infections. Future studies should adopt multi-center designs, cytology-histology integration, broader population coverage, and longitudinal follow-up.
Conclusions
Our study revealed an overall HPV prevalence of 21.41% over the past nine years, with a notable decline in vaccine-targeted HPV16 and HPV18 but a concerning rise in HPV52 and HPV58. Given the significant association of HPV52 and HPV58 with HSIL and cervical cancer, these genotypes should be prioritized in vaccination programs, especially in resource-limited settings. Additionally, HPV prevalence exhibited a bimodal age distribution, peaking in both younger and older populations. Significantly, the median age of cervical cancer patients (55 years) was higher than in other groups, underscoring the importance of age-specific strategies in screening and clinical management. Moving forward, integrating age-specific considerations into prevention and treatment protocols will be critical for reducing HPV-related disease burden.
Acknowledgements
The authors express their appreciation to the hospital pathologists and coordinators for their involvement in the clinical work.
Abbreviations
- HPV
Human papillomavirus
- HR
High-risk
- HSIL
High-grade squamous intraepithelial lesion
- IARC
International Agency for Research on Cancer
- IQR
Interquartile ranges
- LR
Low-risk
- LSIL
Low-grade squamous intraepithelial lesion
- PCR
Polymerase Chain Reaction
- WHO
World Health Organization
Author contributions
Y.S.T. (Yishu Tang) designed the study and coordinated its execution. H.L.D. (Hongli Ding) participated in data collection, statistical analysis, and interpretation of results, and drafted the manuscript. H.J. (Hao Jin) was involved in data analysis and the preparation of tables and figures. All authors contributed to manuscript revisions and approved the final version for publication. H.L.D. and H.J. contributed equally to this work and should be considered co-first authors.
Funding
This study was supported by the National Natural Science Foundation of Chongqing, China (No. cstc2019jcyj-msxm0314 of Yishu Tang) and the Natural Science Foundation of China (No. 81501818 of Yishu Tang).
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
As this study was a retrospective study and the identities of patients were intentionally anonymized, no individual informed consent was required, so this study was approved by the Ethics Committee of The First Affiliated Hospital of Chongqing Medical University (approval number K2024-124-01) and subject informed consent was exempted.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Hongli Ding and Hao Jin contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.