(2024) 25:19
Wu et al. BMC Molecular and Cell Biology
https://doi.org/10.1186/s12860-024-00515-7

BMC Molecular andCell Biology

Open Access

RESEARCH

Differential methylation patterns
in paternally imprinted gene promoter regionsin sperm from hepatitis B virus infectedindividuals
Baoyan Wu1,2,3†, Yuying Sheng1,2,3†, Wenwei Yu1,2,3†, Lewen Ruan1,2,3, Hao Geng1,2,3, Chuan Xu1,2,3,
Chao Wang1,2,3, Dongdong Tang1,2,3, Mingrong Lv1,2,3*, Rong Hua2,3* and Kuokuo Li1,2,3*

Abstract
Background Hepatitis B virus (HBV) infection poses a substantial threat to human health, impacting
not only infected individuals but also potentially exerting adverse effects on the health of their offspring. The underlying mechanisms driving this phenomenon remain elusive. This study aims to shed light on this issue by examining
alterations in paternally imprinted genes within sperm.
Methods A cohort of 35 individuals with normal semen analysis, comprising 17 hepatitis B surface antigen (HBsAg)positive and 18 negative individuals, was recruited. Based on the previous research and the Online Mendelian Inheritance in Man database (OMIM, https://​www.​omim.​org/), targeted promoter methylation sequencing was employed
to investigate 28 paternally imprinted genes associated with various diseases.
Results Bioinformatic analyses revealed 42 differentially methylated sites across 29 CpG islands within 19 genes
and four differentially methylated CpG islands within four genes. At the gene level, an increase in methylationof DNMT1 and a decrease in methylation of CUL7, PRKAG2, and TP53 were observed. DNA methylation haplotype
analysis identified 51 differentially methylated haplotypes within 36 CpG islands across 22 genes.
Conclusions This is the first study to explore the effects of HBV infection on sperm DNA methylation and the potential underlying mechanisms of intergenerational influence of paternal HBV infection.
Keywords Hepatitis B virus, Imprinted gene, Paternally, Methylation, Sperm†

Baoyan Wu, Yuying Sheng and Wenwei Yu contributed equally to this workand share first authorship.

*Correspondence:
Mingrong Lv
lmr2010@mail.ustc.edu.cn
Rong Huaahmuhuarong@126.com
Kuokuo Li
likuokuo_bio@163.com
1
Reproductive Medicine Center, Department of Obstetrics
and Gynecology, The First Affiliated Hospital of Anhui Medical University,
No. 218 Jixi Road, Hefei 230022, China

2
NHC Key Laboratory of Study On Abnormal Gametes and Reproductive
Tract (Anhui Medical University), Key Laboratory of Population HealthAcross Life Cycle (Anhui Medical University), Ministry of Educationof the People’s Republic of China, Hefei, Anhui, China
3
Key Laboratory of Population Health Across Life Cycle (Anhui Medical
University), Ministry of Education of the People’s Republic of China, Hefei,
Anhui, China© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as longas you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if
you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article orparts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicatedotherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To
view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Wu et al. BMC Molecular and Cell Biology(2024) 25:19

BackgroundHepatitis B virus (HBV) infection represents a substantial global health concern, with an estimated 30% of theworld’s population having encountered the virus at somepoint in their lives, notwithstanding the implementationof preventive vaccines over several decades. Recognized
as a significant threat to human health and a prominent
cause of mortality, HBV infection remains a top healthpriority [1, 2].
While the primary mode of HBV transmission is vertical, occurring from mother to neonate. HBV infectionin pregnant females have been clearly related to miscarriage. Infection with HBV has been linked to a higher
risk of miscarriage and preterm birth in natural pregnancies [3–5]. Both horizontal and vertical father-to-childtransmission are also acknowledged as pivotal contributors [6–9]. The potential for sperm-mediated intrauterine HBV infection has stirred considerable controversy.
Some evidence suggests the integration of HBV-DNA
into the chromatin of human sperm, and a small-scale
study employing direct sequencing has indicated paternal
HBV transmission to the fetus via sperm [10–12]. However, a larger body of evidence contradicts this, revealing that a father’s carrier state is unlikely to result in fetal
HBV infection, as evidenced by the absence of HBV DNA
in 164 fetuses from the same study born to HBV-positive
fathers and HBV-negative mothers [13].
Beyond the controversies surrounding vertical transmission, the adverse impact of paternal HBV infection
on sperm quality, chromosomal stability, and pregnancy
outcomes in assisted reproductive technology (ART)
has been extensively documented [10, 14, 15]. Notably,
Lorusso et al. reported significant decreases in sperm
count, motility, viability, and normal morphology in
HBV seropositive patients, while Huang et al. identified
higher chromosomal aberrations in sperm from hepatitis
B patients, suggesting potential adverse effects on chromosomal stability [10, 15]. Furthermore, a meta-analysis
conducted by Xiong et al. revealed reduced clinical pregnancy and live birth rates per cycle in couples undergoing ART where the male partner was exclusively infectedwith HBV [14]. Moreover, the influence of paternallytransmitted HBV infection extends to postnatal health, asevidenced by a cohort study in Taiwan, indicating a significantly increased incidence of hepatoblastoma in children born to fathers with HBV infection [16].
The repercussions on sperm quality and ART pregnancy outcomes attributable to HBV infection may belinked, in part, to sperm chromosomal aberrations andaltered CpG methylation both before and after sperm
maturation and fertilization [10, 14, 17]. Moreover, HBV
infection in pregnant females, can also influence themethylation patterns of the offspring [18]. In a study byPage 2 of 9

Qijun Cheng et al., it was found that prenatal HBV exposure, even in the absence of malformations or prematurity, may alter the epigenomic profile of newborns [19].
Yet, there exists a limited understanding of how paternal
HBV infections lead to adverse fetal health outcomes,
including the rarely attributed occurrence of hepatoblastoma. The present study seeks to elucidate potential
underlying mechanisms through a novel exploration of
the perspective of paternally imprinted genes, shedding
light on how paternal HBV infection may modulate offspring health.

Materials and methods
Participants and study design

A total of 35 subjects from the Reproductive Center of
the First Affiliated Hospital of Anhui Medical University(Hefei, China) were enrolled in this study. All participants
underwent in vitro fertilization due to female causes ofinfertility at this center. Of the 35 patients (Supplementary Dataset 1), 17 were positive for hepatitis B surface
antigen (HBsAg) and constituted the case group, while
the remaining 18 individuals, negative for HBsAg, wererecruited as controls (Fig. 1 illustrates the study workflow) [1].
The inclusion criteria of the study entailed: (I) patient
age between 22–40 years; (II) normal results of routinesemen analysis and sperm morphology according to thesixth edition of the World Health Organization Laboratory Manual for the Examination and Processing of
Human Semen [20]; (III) no history of any mental diseaseor somatic severe disorder; (IV) and no history of smoking, excessive alcohol use, drug consumption, etc.

Semen sample processing
All individuals were required to provide a semen sample
by masturbation that was collected after a previous ejaculation that occurred 3–7 days ago. Subsequently, semen
samples were frozen at -80℃. Semen samples underwent
washing with 10 mL of 1X phosphate-buffered saline, followed by centrifugation and resuspension of the pellet in
10 mL of somatic cell lysis buffer (0.1% SDS, 0.5% Triton
X-100 in DEPC H2O; Sigma-Aldrich). Overnight incubation at 4℃ was followed by multiple centrifugations andresuspension of the pellet in 10 mL phosphate-bufferedsaline.
Selection of genes
According to Tucci’s article, there are more than 200
imprinted genes [21], and in order to further evaluate
the correlation between paternally inherited genes andhuman genetic diseases, we searched for genes among
these 200 genes that may be associated with the occurrence of human genetic diseases. A detailed list of theseWu et al. BMC Molecular and Cell Biology(2024) 25:19

Page 3 of 9

Fig. 1 Workflow of this different methylation study. Hbs Ag: hepatitis B surface antigen; Hbs Ag ( +): hepatitis B surface antigen positive; Hbs Ag (-):
hepatitis B surface antigen negative

genes and their related functional information is provided in Supplementary Dataset 2.

DNA methylation sequencing and bioinformatics
analyses
Given the crucial role of CpG island methylation in influencing gene expression and functionality, we analyzed
methylation differences at different levels from CpG sites,
CpG island regions and individual genes. Therefore ourinvestigation focused on CpG islands within potential
promoter regions spanning + 2000 bp to -1000 bp of thetranscriptional start site. Putative CpG islands were predicted using EMBOSS Explore, with regions having anobserved/expected ratio exceeding 0.6, a length surpassing 200 bp, and a GC content exceeding 50% defined as
CpG islands. These islands underwent targeted methylation sequencing.
Sperm DNA underwent treatment using the sodium
bisulfite-based EZ DNA Methylation-Gold™ Kit, effecting the conversion of unmethylated cytosine (C) to uridine (U) while preserving the methylated cytosine state.
Specific primers targeting CpG island sequences weregenerated using Primer3. High-throughput sequencing
was performed on an Illumina Hiseq with a 2 × 150 bp
paired-end configuration.
To ensure sequencing quality, FastQC was employed,
facilitating the exclusion of low-quality reads. FLASH
executed joint paired-end sequencing, establishing aminimum acceptable length of 15 bp and an error rate
below 10%. BLAST + facilitated mapping to the humanreference genome, defining a helpful sequence with ajoint coverage fraction exceeding 90%. Principal component analysis (PCA) using the R prompt function enabled
sample clustering based on sperm methylation patterns.

Real‑time quantitative PCR (RT‑qPCR)
We meticulously selected five sets of semen samples forthe analysis of four genes, and used TRIzol reagent (Invitrogen, Carlsbad, CA92008 USA) to extract total RNA
from semen samples of control and experimental groups.
Subsequently, cDNA synthesis was performed using
the PrimeScript RT reagent Kit (Takara, Shiga, Japan),followed by amplification with gene-specific primers
and RT-qPCR analysis using the LightCycler 480 SYBRGreen I Master (Roche). Primer details can be found in
the Table S1. β-actin served as the internal reference fornormalization. Data analysis was conducted using the
2 − ΔΔCt method in GraphPad Prism to determine themRNA expression levels of the four genes.
Statistical analyses
Continuous variables were expressed as means ± standard deviations, counting data were expressed as frequencies (percentages) and analyzed using the chi-square test.
Continuous data with a normal distribution were analyzed using t-test assessments to ascertain differences inmethylation at specific sites, regions, genes, and methylation haplotypes between cases and unaffected controls.
Significance in DNA methylation differences was determined at a p-value < 0.05 (two-tailed).

Wu et al. BMC Molecular and Cell Biology(2024) 25:19

Results
Clinical features

A comprehensive overview of demographic characteristics is provided in Table 1. The absence of significant
differences observed in critical variables such as age,
BMI, educational status, and residence between the twogroups is noteworthy. Furthermore, an in-depth analysis of semen parameters, encompassing semen volume,
sperm counts, progressive sperm malformation rate,
DNA fragmentation index, and abstinence time, revealed
no significant disparities between the studied cohorts.

DNA methylation profiles of paternally imprinted
genes in sperm of HBsAg‑positive and controls
The curated set of 28 paternally imprinted genes under
scrutiny encompassed 84 CpG islands and 1501 CpG
sequences, as detailed in Supplementary Dataset 3. Notably, GNAS featured the highest count of CpG islands[15], while CACNA1A, CUL7, DNMT1, and MOCS1
each bore a single CpG island. All identified CpG islands
harbored more than 10 CpG sequences, with the CACNA1C_5 island exhibiting the highest count at 36.
Evaluation of sulfite conversion efficiency indicatedcomparable outcomes between the experimental andcontrol groups, suggesting the absence of systemic errors(Figure S1). Furthermore, the quality of DNA methylation was deemed satisfactory based on quality value andcoverage, as outlined in Supplementary Dataset 4. Comprehensive methylation values for CpG sites targeted
CpG island regions and individual genes are documented
in Supplementary Dataset 5.

Page 4 of 9

Principal component analysis (PCA) grounded in DNA
methylation values of the CpG sites did not reveal significant distinctions between the two groups (Figure S2).
This suggests a degree of homogeneity in DNA methylation patterns across the majority of promoter regions
associated with the paternally imprinted genes.

Bioinformatic analyses of differential sperm DNA
methylation between HBsAg positive and controls
A meticulous evaluation of methylation values at specific sites targeted CpG island regions and genes wereconducted to delineate differential DNA methylation
patterns.
In each site’s initial DNA methylation analysis, 42 significantly different methylation sites were identified
across 29 CpG islands within 19 genes (Supplementary
Dataset 6). Notably, eight genes displayed only one significantly different CpG site, while three genes harbored
two such sites. Furthermore, four genes contained threesignificantly different CpG sites, and four more exhibited four significantly different CpG sites. The analysis
of DNA methylation at each CpG island revealed significant differences in four islands, including CUL7_10,
PRKAG2_56, DNMT1_11, and TP53_83 (Fig. 2, Supplementary Dataset 7). Among these, CUL7_10,
PRKAG2_56, and TP53_83 exhibited significantly lower
DNA methylation, while DNMT1_11 demonstrated significantly higher DNA methylation in HBsAg-positive
patients compared to controls. These differences translated into substantial variations within the CpG methylation islands, indicating region-specific methylation
alterations (Fig. 2).

Table 1 Comparison of demographic characteristics between HBsAg positive and negative subjects
Controls(N = 18)

Cases(N = 17)

t/χ2

P

Age

31.72 ± 4.24

33.65 ± 2.91

1.556

0.129

BMI

25.20 ± 2.36

24.46 ± 2.90

0.829

0.413

0.238

0.625

Middle School

8

7

University

9

11
0..02

0.877

8

8

Educational Status

Residence
Rural
Urban

9

10

Semen volume(ml)3.16 ± 0.79

2.92 ± 0.86

0.854

0.399

Sperm concentration(× 10^6/ml)

77.63 ± 33.20

78.70 ± 57.88

0.068

0.946

Progressive rate(PR%)

49.58 ± 12.80

44.10 ± 11.28

1.341

0.189

Sperm malformation rate(%)

94.72 ± 1.02

95.92 ± 0.85

1.799

0.081

DFI(%)

13.10 ± 5.85

16.87 ± 9.07

1.467

0.152

Abstinence time(days)

2.50 ± 0.51

2.41 ± 0.62

0.460

0.649

Chi-squared, or t -tests was used as appropriate. DFI DNA fragmentation index

Wu et al. BMC Molecular and Cell Biology(2024) 25:19

Page 5 of 9

Fig. 2 Different methylation of targeted regions. Panels A, C, E, and G illustrated significant methylation in four targeted regions (CUL7_10,
PRKAG2_56, DNMT1_11, TP53_83). Panels B, D, F, and H provided detailed methylation information for CpG sites in these regions

Wu et al. BMC Molecular and Cell Biology(2024) 25:19

At the gene level, significant differences were observedin CUL7, PRKAG2, DNMT1, and TP53, corroborating
findings from the targeted CpG island regions (Fig. 3,
Supplementary Dataset 8). In order to explore the impact
of methylation on the genes, we further conducted Realtime quantitative PCR (RT-qPCR) and found that the
methylation can regulate the expression of gene. DNMT1case group exhibited significantly decreased expression (increased methylation), and PRKAG2 and TP53

Page 6 of 9

exhibited significantly increased expression relative tothe control group (decreased methylation) (Fig. 3). These
results suggest a potential modulation of paternal gene
expression in offspring born to HBsAg-positive patients.
Conducting a DNA methylation haplotype analysis
on the 28 imprinted genes (Supplementary Dataset 9)
unveiled 51 significantly different DNA methylation haplotypes within 36 CpG islands across 22 genes (Fig. 4).
Notably, PRKAG2 and GNAS harbored six and fourFig. 3 Differential methylation and gene expression in genes. The results revealed statistically significant differences in methylation (P < 0.05) in fourgenes

Fig. 4 Differential methylation haplotypes. The line in the figure indicated P = 0.05, and the dots above denoted significant methylation haplotypes
with P < 0.05

Wu et al. BMC Molecular and Cell Biology(2024) 25:19

significantly different DNA methylation haplotypes,
respectively, while CACNA1C, CACNA1E, and IRF7 contained four such haplotypes.
These findings illuminate the complex landscape ofdifferential DNA methylation within imprinted genes
associated with HBsAg-positive individuals, suggesting
potential implications for offspring health.

Discussion
This is the first study to explore the uncharted territoryof understanding how Hepatitis B Virus (HBV) infection
influences DNA methylation in sperm. The comprehensive analysis unveiled 42 differentially methylated sites
spread across 29 CpG islands within 19 genes. At thegene level, distinct patterns emerged, revealing an augmentation in methylation of DNMT1 and a concomitant
reduction in CUL7, PRKAG2, and TP53 methylation.
The exploration also extended to a DNA methylation
haplotype analysis, uncovering 51 differentially methylated haplotypes within 36 CpG islands across 22 genes.
These intricate findings offer a glimpse into the potential
mechanisms underpinning the intergenerational impactof paternal HBV infection. Identifying specific methylation alterations within essential genes adds a layer ofunderstanding to the complex interplay between HBV
infection and epigenetic modifications, shedding light on
the intricate processes influencing paternal transmission
effects across generations.
Epigenetics, the heritable regulation of gene expression through non-DNA encoded mechanisms, is a pivotal
factor influencing cellular behavior [22, 23]. While previous studies have unequivocally demonstrated the correlation between Hepatitis B Virus (HBV) infection andadverse effects on sperm, including decreased motility
and heightened rates of apoptosis and necrosis leading
to diminished fertility [24, 25], the influence of HBV on
sperm epigenetic information has remained unexploreduntil now. Our focus on DNA methylation, a fundamental mechanism of epigenetic inheritance, unravels
intriguing insights into the potential impact of HBV on
the epigenetic landscape of paternally imprinted genes insperm.
DNA methylation of cytosine residues has been suggested to mediate parental effects in mammals [26].
Genomic imprinting, wherein gene expression depends
on parental inheritance, is linked to differences in DNA
methylation states that can be transmitted across generations in mammals [27]. Despite parental HBV infection being identified as a risk factor for hepatoblastoma
in children [16], the underlying mechanisms haveremained elusive. Our study suggests that HBV infection induces alterations in DNA methylation patterns,
specifically within disease-causing paternally imprinted

Page 7 of 9

genes in sperm [28]. This intriguing discovery implies
that such changes may be transmitted to offspring,potentially influencing their health and development.
Notably, among the differentially methylated genes,
TP53, encoding a well-known tumor suppressor,
emerges as a candidate influencing cancer incidence
in the offspring [29], paving the way for further investigations into tumorigenesis in children born to HBVinfected male patients.
While methylation is predominantly erased upon
fertilization in mammals [30], the impact of alterations in this process on gene expression in progeny
remains unclear. Evidence supporting the possibility of imprinted genes escaping erasure processes andpassing on their DNA methylation status to progeny
is known [31]. Our study systematically screened forpaternally imprinted genes represented in diseasecausing genes listed in the OMIM database, targeting
their promoter regions for DNA methylation detection. Accurate quantification of methylation levels intarget genes, such as CUL7, PRKAG2, DNMT1, andTP53, offers insight into potential cascading effects
stemming from alterations in the expression patternsof these proteins. This has significant implications forthe health of future generations. Notably, CUL7, recognized as a modifier in ubiquitination processes [32],and PRKAG2, involved in phosphorylation modifications, may additionally govern the function of multiple
proteins during post-translational modifications [33].
Furthermore, DNMT1, a DNA methyltransferase, has
the capacity to regulate DNA methylation in embryos
and offspring [34].
Acknowledging the limitations of a small sample sizethat may have influenced result accuracy due to random
factors, our study focuses solely on promoter DNA methylation without analyzing other epigenetic alterations
associated with HBV infection. Future endeavors within
our group aim to address these limitations by investigating larger sample groups to gain a more comprehensive
understanding of the additional effects exerted by HBV
infection in sperm.

Conclusion
In conclusion, our study identifies significant differences in promoter DNA methylation levels within several paternally imprinted genes between HBV-positive
patients and control individuals. As the first to shed lighton the effects of HBV infection on sperm DNA methylation, our findings provide valuable clues to the transmission mechanisms responsible for the intergenerational
effects of HBV, opening avenues for further research into
potential health-related consequences in offspring.

Wu et al. BMC Molecular and Cell Biology(2024) 25:19

Competing of interests
The authors declare that they have no competinginterests.
Abbreviations
HBV	Hepatitis B virusART​	Assisted reproductive technology
HBsAg	Hepatitis B surface antigen
PCA	Principal component analysis

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12860-​024-​00515-7.
Supplementary Material 1.
Supplementary Material 2.
Supplementary Material 3.
Supplementary Material 4.
Supplementary Material 5.
Supplementary Material 6.
Supplementary Material 7.
Supplementary Material 8.
Supplementary Material 9.
Supplementary Material 10.
Supplementary Material 11: Figure S1. Assessment of sulfite conversion
efficiency. The result indicated comparable outcomes between the experimental and control groups, suggesting the absence of systemic errors.
Supplementary Material 12: Figure S2. Principal component analysis. PCA
based on DNA methylation values of CpG sites did not reveal significant
distinctions between the experimental and control groups.
Acknowledgements
We want to thank all the individuals who participated in and supported thisresearch.
Authors’ contributions
KL, RH, ML and DT designed the study. BW, YS, ML, LR, HG, WY, CW and CX
collected the samples and data. KL and DT performed the data analysis. KL,
ML and WY wrote the paper. All authors have read and approved the final
manuscript.
Funding
This study was supported by the National Natural Science Foundation ofChina (No. 82101681 and 82101944), Research Fund of Anhui Institute oftranslational medicine (2023zhyx-C26 and 2023zhyx-C58).
Availability of data and materials
The datasets used and analyzed during the current study are available fromthe corresponding author on reasonable request, without undue reservation.
The datasets generated and/or analysed during the current study are available
in the NCBI’s Gene Expression Omnibus and are accessible through GEO Series
accession number GSE270937 (https://​www.​ncbi.​nlm.​nih.​gov/​geo/​query/​acc.​
cgi?​acc = GSE270937).

Declarations
Ethics approval and consent to participate
The local research ethics committee of the First Affiliated Hospital of Anhui
Medical University approved this study. Informed consent was obtained
from all subjects. All methods were carried out in accordance with relevant
guidelines and regulations.

Page 8 of 9Consent for publication
Not applicable.
Competing of interests
The authors declare that they have no competing interests.
Received: 19 December 2023 Accepted: 24 July 2024

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