The most common combination of co-infections genotypic distribution and clearance patterns of high-risk human papillomavirus in Southern China: a population-based retrospective study

Abstract

Background

High-risk human papillomavirus (HR-HPV) infection is a well-established cause of cervical cancer. This study aimed to investigate the distribution of HR-HPV genotypes and the infection patterns in the southern Chinese population to provide data to support effective strategies for HPV screening, prevention, and vaccination.

Methods

We conducted a retrospective analysis of HPV genotyping results collected between January 2020 and December 2024. The study examined the distribution of HPV genotypes, the prevalence of single versus multiple infections, and the viral clearance patterns among affected individuals.

Results

A total of 196,103 samples were included in the analysis. The HR-HPV positivity rate was 16.91% and remained consistent over the five years. While a decrease in the positivity rate was observed for HPV-16 and HPV-18, no significant changes were observed for other genotypes. The most commonly detected HR-HPV genotypes were HPV-52, HPV-53, and HPV-58. Among all positive cases, 82.08% were single genotype infections, and 17.92% were multi-genotype infections. The most common co-infection combination was HPV-52 and HPV-53. The median time to viral clearance was 13.45 months. In particular, HPV-16/18 infections cleared more quickly than other genotypes. In contrast, multiple infections took longer to clear and were often resolved by elimination of multiple genotypes.

Conclusions

HR-HPV infections in southern China have unique regional characteristics. These findings contribute to a deeper understanding of HPV epidemiology in the region and may help guide future efforts in HPV vaccination and cervical cancer prevention.

Introduction

Cervical cancer remains one of the most common malignancies in women worldwide. According to the GLOBOCAN 2022 projections, cervical cancer ranked first in both incidence and mortality among cancers of the female reproductive system in 2022 [1, 2]. Persistent human papillomavirus (HPV) infection is the primary cause of cervical cancer [3–5]. HPV genotypes are classified as high-, intermediate-, or low-risk based on their ability to induce precancerous lesions and malignant transformation of cervical tissue [6, 7]. More than ten high-risk HPV (HR-HPV) genotypes are routinely included in molecular screening programs, with HPV-16 and HPV-18 identified as the two most common genotypes associated with cervical cancer [8]. Although considerable progress has been made in understanding HPV prevalence, challenges remain in evaluating the impact of vaccination, understanding the occurrence of multiple infections, and monitoring viral clearance. These aspects continue to pose difficulties for epidemiological research on HPV.

HPV vaccines are now widely used to prevent and control infection [9–11]. Recent implementation of vaccination programs may be changing HPV infection rates [12, 13]. In China, as of October 2024, approximately 40% of eligible women had received the bivalent HPV vaccine free of charge [14–16]. Early vaccination, which aims to interrupt transmission and reduce the risk of infection with high-risk genotypes, may influence the regional patterns of HPV prevalence - particularly in southern China. However, the magnitude and extent of this influence remain to be fully determined.

Most current studies focus on single HPV infections. However, existing evidence suggests that multiple infections occur in 20–40% of HPV-positive individuals. Despite the increasing recognition of multiple genotype infections, their epidemiological characteristics are poorly understood. Multiple infections are more complex in presentation and course than single infections. Unfortunately, epidemiological data on multiple infections remain limited both nationally and globally. Further research is needed to clarify their incidence, distribution, and clearance dynamics.

China contributes to approximately 18.17% of new cervical cancer cases worldwide each year, indicating a significant public health burden. Previous studies have demonstrated that HPV genotype prevalence varies between populations and regions [17, 18]. Nevertheless, more detailed investigations are needed to better understand genotype distribution, particularly in southern China.

In this study, we conducted a large-scale retrospective analysis to investigate the molecular epidemiology of HPV in the southern Chinese population. Our findings reveal distinct patterns of infection in this region. These findings not only contribute to the understanding of HPV transmission and clearance in ongoing vaccination efforts but also provide a valuable reference for future research into multiple infections and genotype-specific outcomes. Data generated from this study can inform more targeted strategies for HPV prevention and cervical cancer control.

Materials and methods

Study objectives

This study included women who underwent cervical cancer screening at the Maternal and Child Health Hospital in Longgang District, Shenzhen, between January 2020 and December 2024. As part of a public health initiative, HPV genotyping was provided free of charge to increase screening coverage. Eligible participants were local residents aged 20 to 60 years with a history of sexual activity. Women were excluded if they were pregnant or breastfeeding, had undergone total hysterectomy, had received pelvic radiation, or had a history of cervical precancerous lesions or cervical cancer. The research method of retrospective analysis was adopted to analyze the data included in the study. The study adhered to the principles of the Declaration of Helsinki (2013) and received ethical approval from the Research Ethics Committee of Longgang District Maternity & Child Healthcare Hospital (Ethics ID: LGFYKYXMLL-2025-19). Written informed consent was obtained from all participants.

HPV genotype testing

HPV genotyping was conducted using a reverse dot-blot method. Cervical secretions were collected from non-menstruating participants using a cervical secretion sampler. DNA was extracted using a commercially available nucleic acid kit (Yaneng Bio, China). Polymerase chain reaction (PCR) was performed using an HPV genotyping kit (Yaneng Bio, China), according to the following protocol: 50 °C 15 min., 1 cycle; 95 °C 10 min., 1 cycle; 94 °C 30 s., 42 °C 90 s., 72 °C 30 s., 40 cycles; 72 °C 5 min., 1 cycle. The products were hybridized with specific primers arranged in a spot-like pattern, followed by colorimetric visualization, using a YN-H48 hybridizer (Yaneng Bio, China). The hybridization parameters were as follows: hybridization temperature: 51 °C; hybridization time: 30 min.; B washing time: 10 min.; incubation time: 15 min.; A washing time: 5 min.; C wash time: 2 min.; color development time: 15 min.; wash time: 3 min. Finally, the results were interpreted. The assay identified 17 high-risk HPV genotypes, including HPV-16, 18, 31, 33, 35, 39, 45, 51, 52, 53, 56, 58, 59, 66, 68, 73, and 82.

Genotypes were grouped based on vaccine protection to reflect the impact of regional vaccination coverage. In southern China, the bivalent HPV vaccine targets genotypes 16 and 18, while the quadrivalent vaccine includes genotypes 6, 11, 16, and 18. Therefore, genotypes 16 and 18 have been referred to as the HPV-V2 group. The nine-valent vaccine includes genotypes 6, 11, 16, 18, 31, 33, 45, 52, and 58. Genotypes 31, 33, 45, 52, and 58 were classified as the HPV-V9 group. The remaining high-risk genotypes not covered by vaccines (HPV35, 39, 51, 53, 56, 59, 66, 68, 73, and 82) were grouped as HPV-V0.

Single and multiple infections

Some participants had repeated HPV tests during the study, and all test results were included in the analysis. Annual HR-HPV positivity rates were evaluated for age groups, individual genotypes, and vaccine-defined genotype groups. Participants’ birthplaces were recorded based on their official identification to understand population demographics.

Co-infection was defined as two or more different HR-HPV genotypes in a single individual. The frequency of each combination of co-infections was calculated. New infections with genotypes not previously detected in previously infected individuals were also recorded. To assess the likelihood of co-infection, we assumed that each HPV genotype was acquired independently. The expected probability of co-infection (P) was calculated as P = P1 × P2, where P1 and P2 are the individual prevalence rates of each genotype. The chi-squared test was used to compare the observed and expected frequencies, allowing for the assessment of potential epidemiological associations between genotypes.

HPV clearance

A subset of HPV-positive women who had HPV genotyping performed for three consecutive years was included in the clearance analysis. Clearance was defined as a reduction in the number of HPV genotypes detected in a subsequent test compared with the previous test. Clearance events were categorized as single- or multiple-type clearances. We calculated the median time to clearance and the cumulative clearance rate over a three-year period. Using the log-rank test, the clearance rates were compared between genotypes, age groups, and between single and multiple infections. In addition, the distribution of single versus multiple-type clearance events was assessed to characterize common patterns of viral clearance.

Statistical analysis

All data were processed and visualized using R software version 4.3.0. The Survminer and Survivor packages were used to evaluate HPV clearance rates. The age of participants and other variables were expressed as mean ± standard deviation (SD). The chi-squared test was used to compare positivity rates between groups, with p < 0.05 considered statistically significant.

Results

Participant profile

This study included 196,103 HPV genotyping results from 177,265 women who met the inclusion criteria. The median age of the participants was 38.56 years [IQR: 33.559, 45.600], and 99.95% (196,002/196,103) were aged between 20 and 60 years. To assess any potential age-related confounding, we examined the annual age distribution of participants (Fig. 1A). Although the overall distribution remained consistent over time, statistical differences were observed (p < 0.001), probably due to the large sample size.

Fig. 1.

Age distribution and epidemiological characteristics of the population undergoing high-risk HPV screening. (A): Age distribution of individuals undergoing high-risk HPV screening in 2020–2024. This density plot illustrates the age distribution of high-risk HPV screening participants in each respective year. (B): Distribution of high-risk HPV genotypes across months. This stacked area plot illustrates the monthly distribution and relative proportions of high-risk HPV genotypes over the study period. (C): Total frequencies of high-risk HPV genotype groups (HPV-V0, HPV-V2, HPV-V9) from 2020 to 2024. (D): Frequencies of the HPV-V0 genotype group in two age groups from 2020 to 2024. (E): Frequencies of the HPV-V2 genotype group in two age groups from 2020 to 2024.(F): Frequencies of the HPV-V9 genotype group in two age groups from 2020 to 2024. Error bars represent the variability

Within the cohort, 17,884 individuals (10.09%) underwent two or more tests during the study period, with a median interval between tests of 253.16 days [IQR: 100.333, 527.500]. Based on identification records, 81.69% (144,806/177,265) of the participants were confirmed to be from southern China, of whom 53.65% (77,691/144,806) were from Guangdong province and 46.35% (67,115/144,806) from other southern provinces.

HPV genotype distribution

The HR-HPV positivity rate was 16.91% (33,161/196,103), with minimal variation over the five years. We analyzed the annual distribution of individual HR-HPV genotypes (Table 1). The five most prevalent genotypes were HPV-52 (3.97%), HPV-53 (1.87%), HPV-58 (1.76%), HPV-16 (1.60%), and HPV-51 (1.38%). Monthly trends in genotype-specific positivity were stable throughout the study (Fig. 1B).

Table 1.

Prevalence of high-risk HPV genotypes

HPV genotype	2020	2021	2022	2023	2024	Total (2020–2024)	20-40y	40-60y
16	0.0163 (526)	0.0174 (808)	0.016 (766)	0.0157 (684)	0.0132 (344)	0.016 (3128)	0.0162 (1790)	0.0155 (1327)
18	0.0073 (236)	0.0081 (375)	0.0065 (309)	0.0063 (275)	0.0064 (166)	0.0069 (1361)	0.007 (775)	0.0068 (581)
31	0.0035 (113)	0.003 (141)	0.0033 (157)	0.0036 (156)	0.0034 (90)	0.0034 (657)	0.0031 (347)	0.0036 (308)
33	0.0062 (200)	0.0057 (265)	0.0059 (284)	0.0055 (240)	0.0052 (135)	0.0057 (1124)	0.0049 (544)	0.0067 (571)
35	0.0033 (105)	0.0028 (132)	0.003 (143)	0.0024 (106)	0.0033 (86)	0.0029 (572)	0.0023 (256)	0.0037 (316)
39	0.0065 (210)	0.006 (278)	0.0053 (254)	0.0048 (210)	0.006 (156)	0.0057 (1108)	0.0053 (585)	0.0061 (520)
45	0.002 (63)	0.0025 (116)	0.0018 (88)	0.0027 (118)	0.0025 (64)	0.0023 (449)	0.0022 (243)	0.0024 (205)
51	0.0145 (467)	0.0135 (626)	0.0141 (672)	0.0129 (563)	0.0147 (383)	0.0138 (2711)	0.0142 (1574)	0.0133 (1135)
52	0.0419 (1353)	0.0392 (1821)	0.0394 (1883)	0.037 (1610)	0.0427 (1115)	0.0397 (7782)	0.0381 (4215)	0.0416 (3551)
53	0.0205 (660)	0.018 (837)	0.0181 (866)	0.018 (785)	0.02 (523)	0.0187 (3671)	0.0165 (1825)	0.0215 (1839)
56	0.0087 (280)	0.0092 (430)	0.0092 (441)	0.0094 (410)	0.0096 (250)	0.0092 (1811)	0.0083 (915)	0.0104 (890)
58	0.0154 (498)	0.0178 (827)	0.0177 (846)	0.0183 (794)	0.0183 (479)	0.0176 (3444)	0.0169 (1872)	0.0183 (1564)
59	0.0081 (260)	0.007 (325)	0.0081 (385)	0.0083 (359)	0.0076 (199)	0.0078 (1528)	0.008 (890)	0.0075 (636)
66	0.005 (162)	0.005 (231)	0.0051 (242)	0.0055 (238)	0.0054 (142)	0.0052 (1015)	0.0051 (564)	0.0053 (449)
68	0.013 (418)	0.0122 (565)	0.0117 (561)	0.0113 (493)	0.0115 (301)	0.0119 (2338)	0.0117 (1292)	0.0122 (1041)
73	0.0014 (45)	0.0014 (64)	0.001 (50)	0.0014 (59)	0.0013 (34)	0.0013 (252)	0.0012 (138)	0.0013 (114)
82	0.001 (33)	0.0012 (56)	0.0008 (40)	0.0012 (52)	0.0011 (29)	0.0011 (210)	0.001 (110)	0.0012 (100)
Number of case	32,256	46,495	47,749	43,494	26,109	196,103	110,649	85,353
Average age	38.8267(7.905)	40.0098(8.1379)	39.8833(8.0953)	40.2912(8.2621)	40.2288(8.289)	39.8757(8.1525)	33.9127(3.7985)	47.5734(5.3365)

By vaccine coverage classification, positivity rates were 2.29% for HPV-V2 (types 16/18), 6.86% for HPV-V9 (types 31/33/45/52/58), and 7.76% for HPV-V0 (all other high-risk types) (Table 2). Annual positivity within these groups remained stable over time (Fig. 1C).

Table 2.

Prevalence of high-risk HPV in the HPV vaccine group

HPV Vaccine Group	2020	2021	2022	2023	2024	Total (2020–2024)	20-40y	40-60y
HPV-V0	0.0818 (2640)	0.0762 (3544)	0.0765 (3654)	0.0753 (3275)	0.0805 (2103)	0.0776 (15216)	0.0736 (8149)	0.0825 (7040) ***
HPV-V2	0.0236 (762)	0.0254 (1183)	0.0225 (1075)	0.022 (959)	0.0195 (510)	0.0229 (4489)	0.0232 (2565)	0.0224 (1908)
HPV-V9	0.069 (2227)	0.0682 (3170)	0.0682 (3258)	0.0671 (2918)	0.0721 (1883)	0.0686 (13456)	0.0653 (7221)	0.0726 (6199) *
Total	0.1744 (5629)	0.1698 (7897)	0.16732 (7987)	0.1644 (7152)	0.1721 (4496)	0.1691 (33161)	0.1621 (17935)	0.1775 (15147) ***

HPV-V0 included HPV 35/39/51/53/56/59/66/68/73/82 genotypes. HPV-V2 included HPV 16 and 18. HPV-V9 included HPV 31/33/45/52/58 genotypes. Compared to left: *: 0.01 ≤ p < 0.05; **: 0.001 ≤ p < 0.01; ***: p < 0.001

To examine age-related trends, participants were divided into two age groups. Table 1 shows significant differences in overall HR-HPV positivity by age (p < 0.0001). Figures 1D–F show that positivity rates in all genotype groups, particularly HPV-V0, and HPV-V9, were significantly higher in women aged 40–60 years compared to those aged 20–40 years (p < 0.0001) (Table 2).

Multiple HPV infections

Among HR-HPV positive individuals, 82.08% (27219/33161) had single-genotype infections, whereas 17.92% (5,942/33161) had multiple-genotype infections (Table 3). The mean age of women with multiple infections (42.85 years) was significantly higher than that of single infections (41.68 years; p = 0.003293).

Table 3.

Relationship between the number of existing high-risk HPV genotypes and the number of additionally infected genotypes

Number of infected genotypes	n	Infection rate	Additional genotypes infection	Additional genotypes infection rate
1	27219	13.880%	855	3.1412%
2	4700	2.397%	818	17.4043%
3	993	0.506%	210	21.1480%
>=4	249	0.127%	56	22.4900%
Total	33161	16.910%	1939	5.8472%

Chi-square test for comparison of multiple group rates, p < 0.0001

Further analysis of cases with multiple infections showed an average of 2.265 genotypes per individual. Those younger than 40 had an average of 2.259 genotypes, compared with 2.274 in women aged 40 years and older - a difference that was not statistically significant (p = 0.3919). Among multiple infections, 79.10% (4,700/5,942) were dual infections, 16.71% (993/5,942) were triple infections, and 4.19% (249/5,942) involved four or more genotypes. Common combinations included HPV-52 with HPV-53 (268 cases), HPV-52 with HPV-58 (218 cases), and HPV-52 with HPV-51 (203 cases) (Fig. 2A and B).

Fig. 2.

(A): Chord diagram of high-risk HPV genotype correlations in women with multiple infections in southern China. (B): The relationship between the number of high-risk HPV combinations and the theoretical observation of HPV combinations. (C): Horizontal axis: Multiple infections with different high-risk HPV genotypes. Histogram above: Frequency of infection for each high-risk HPV genotype. Scatter plot: Association of HPV genotypes with multiple infections. Right grey bar: Frequency of infection values for different combinations

To explore potential epidemiological relationships between co-infecting genotypes, we compared observed versus theoretical co-infection frequencies based on individual genotype prevalence. The combinations of HPV-52 with HPV-53 (P = 4.21 × 10⁻²⁴), HPV-52 with HPV-51 (P = 4.66 × 10⁻¹⁶), and HPV52 with HPV68 (P = 2.19 × 10⁻¹⁹) were significantly more frequent than expected (Fig. 2C). These frequent co-infections may reflect a pattern of regional co-transmission. In contrast, some genotype combinations were less common than predicted, suggesting selective absence.

We also assessed reinfection with new genotypes among individuals previously infected with at least one HPV type. The overall rate of reinfection with a new genotype was 5.85%. Importantly, the likelihood of new infection increased with the number of pre-existing infections (p < 0.0001), suggesting a dose-response relationship between pre-existing infection burden and susceptibility to additional types (Table 3).

HPV clearance

Given the known association between the duration of infection and cervical cancer risk, we investigated patterns of HPV clearance. Of the 17,884 individuals who had repeat testing, 9,591 were followed for at least three years after an initial positive result, with testing intervals of two years or less. The median time to clearance was 13.45 months, and the three-year clearance rate was 88.43% (8481/9,591) (Fig. 3A).

Fig. 3.

Time to clearance of high-risk HPV infection in HPV-positive women during long-term follow-up. Shaded areas represent 95% CIs. (A): Comparison between the 16/18 genotype group and other genotype groups; (B): Comparison between the 20–40 age group and the 40–60 age group; (C): Comparison between the single infection group and the multiple infection group. (D): Proportion relationship between the number of high-risk HPV types infected and the number of high-risk HPV types deleted

Clearance was significantly faster for HPV-16/18 genotypes targeted by the bivalent vaccine than other genotypes (p < 0.0001). Specifically, the median clearance time was 11.90 months for HPV-16/18 and 13.93 months for other types. The corresponding three-year clearance rates were 91.00% for HPV-16/18 and 88.00% for other genotypes.

When stratified by age, the median clearance times were similar between age groups: 13.55 months in women aged 20–40 and 13.36 months in those aged 40–60 (Fig. 3B). Three-year clearance rates were 88.00% and 89.00%, respectively, with no significant difference between groups (p = 0.093).

Clearance dynamics differed between single and multiple infections. The median clearance time for single infections was 12.83 months, compared to 15.36 months for multiple infections. Corresponding three-year clearance rates were 90.00% for single infections and 85.00% for multiple infections (p < 0.0001) (Fig. 3C).

For individuals with two, three, or four concurrent genotypes, each clearance event eliminated an average of 1.575 ± 0.495, 2.069 ± 0.824, and 3.114 ± 0.895 types, respectively. This indicates that multiple infections were generally cleared by simultaneous resolution of multiple genotypes (Fig. 3D).

Discussion

This study examined the epidemiological characteristics of HPV genotypes in a southern Chinese population based on genotyping data from 177,265 individuals. It investigated the impact of vaccination on HPV prevalence, identified common infection patterns with multiple genotypes, and analyzed clearance trends. The findings make a significant contribution to HPV epidemiological research in southern China and may inform future public health policy development.

The high-risk HPV (HR-HPV) positivity rate of 16.92% observed in this study remained stable over the five years and was generally consistent with previous studies. The age distribution of the study population remained relatively consistent across years, supporting the reliability of the data and reducing the likelihood of confounding. Although this pattern differs from some global and regional reports - such as those from other parts of south China reported by Yan-Qin Yu [19] - our results are consistent with findings from nearby Guangzhou [20]. The most common genotypes identified were HPV-52, HPV-53, and HPV-58, mirroring patterns found in other studies from Asia [21] and different regions of China [22]. HPV-52 had the highest infection rate, reinforcing its role as the dominant genotype in the region.

Following the World Health Organization’s Global Strategy to Accelerate the Elimination of Cervical Cancer by 2020 [23], vaccination has become a key tool in HPV control efforts [24, 25]. Numerous studies have confirmed the efficacy of HPV vaccines, especially in individuals vaccinated before the onset of sexual activity [26–29]. Our study categorized genotypes according to their inclusion in current vaccines. We observed a notable decrease in the infection rates of HPV-16 and HPV-18 types covered by the bivalent vaccine, suggesting an early vaccine effect [30–32]. However, the genotypes covered by the nine-valent vaccine did not show a similar decline, possibly due to higher vaccine costs, limited availability, and lower uptake. As the nine-valent vaccine is recommended for individuals aged 16–26, we analyzed age-specific trends and found significantly lower infection rates among women aged 20–40 compared to those aged 40–60. These findings highlight current gaps in vaccine coverage and the need to expand access to more comprehensive protection. However, ongoing surveillance is essential given the time required for population-wide effects to materialize.

Multiple HPV infections remain common and contribute to a more complex epidemiological landscape. In our study, multiple infections were more common in older individuals, possibly associated with age-related changes in the cervicovaginal epithelium and cumulative immune decline over time [33]. By comparing theoretical and observed co-infection rates, we found that certain genotype pairings -particularly those involving HPV-52 - occurred more frequently than expected. This suggests a possible synergistic effect or shared routes of transmission within the community. Pre-existing infection significantly increased the risk of acquiring additional genotypes, and the likelihood of new infection increased with the number of pre-existing types. HPV-52 was consistently involved in the most common co-infections, supporting the idea that multiple infections tend to cluster rather than occur independently. This may be due to impaired local immune responses or disruption of the epithelial barrier caused by previous infections [34–36].

The clearance of HPV plays a critical role in understanding infection dynamics and cancer risk. Compared with similar studies in nearby regions such as Guangzhou [20], our results showed a faster overall clearance rate. This may reflect improved public health initiatives in our study setting, including increased funding for cervical cancer screening and heightened awareness of HPV. The clearance of HPV-16/18 was significantly faster than that of other genotypes, probably due to vaccine-induced immune priming. Although positivity rates differed between age groups, no significant differences in clearance rates were observed between women aged 20–40 and those aged 40–60. Interestingly, while multiple infections took longer to clear than single infections, the predominant clearance pattern involved the simultaneous clearance of multiple genotypes. This may reflect the effect of broad-spectrum antiviral interventions, such as interferon therapy, which enhances immune cell function and promotes viral clearance [37]. Clinical procedures such as laser therapy, cryotherapy, or surgical excision can also reduce viral load across multiple genotypes [37, 38].

This study has several limitations. First, it was a single-center, retrospective analysis based on genotypic testing only. It did not include pathological or cytological evaluations of cervical lesions. Second, not all HPV-positive individuals were followed longitudinally for the entire study period, limiting the completeness of the clearance data. Third, we lacked individualized vaccination histories and behavioral or clinical variables that may influence HPV acquisition and persistence. These factors warrant further investigation in future multicenter prospective studies.

Conclusion

This study provides a comprehensive overview of HPV genotype distribution, multiple infection patterns, and viral clearance in southern China. While there are early signs of vaccine efficacy, particularly for HPV-16/18, longer-term monitoring is needed to evaluate the full impact. Our findings highlight a “linkage” phenomenon, whereby multiple infections often co-occur and increase susceptibility to additional genotypes. Clearance of multiple infections was slower than for single infections, but typically occurred through simultaneous resolution of multiple types. These findings provide valuable guidance for cervical cancer screening strategies and HPV vaccination policies in southern China.

Author contributions

S.Z., W.L., and F.W. made the design of the work; H.L. and W.D. analyzed the data; X.C. and Z.L. interpreted of data; W.L. and F.W. contributed to funding acquisition; S.Z.、H.L. and L.W. drafted the work; Y.P. and Y.Y. substantively revised it; F.W. have approved the submitted version; W.L. and F.W. agreed both to be personally accountable for the author’s contributions. All authors read and approved the final manuscript.

Funding

This work was supported by the Medical and Health Technology Research Project, Special Funds for Science and Technology, from Innovation Longgang District of Shenzhen City (LGWJ2024-51).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki (2013) and approved by the Research Ethics Committee of Longgang District Maternity & Child Healthcare Hospital of Shenzhen City (Ethics ID: LGFYKYXMLL-2025-19). Written informed consent was obtained from all participants.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.