The signature of HBV-related liver disease in peripheral blood mononuclear cell DNA methylation

Analysis of differentially methylated sites and regions associated with intrauterine transmission of hepatitis B virus in infants

BACKGROUND

The goal is to identify methylation sites linked to transmission and their impact on host gene expression and HBV spread, aiming to uncover new molecular targets for preventing and treating intrauterine HBV infection.

METHODS

This study recruited 1205 infants born to HBsAg-positive mothers in Liuzhou City, China, between July 2023 and January 2024. Infants were followed up at 7-12 months of age and classified as HBsAg-positive (case, n = 5) or HBsAg-negative (control, n = 14) based on serological testing. Peripheral blood samples were collected for DNA extraction. DNA methylation profiling was performed using the Illumina Infinium MethylationEPIC BeadChip (850 K). Data were processed using the ChAMP package in R, including quality control, normalization, and identification of Differentially Methylated Positions (DMPs) and differentially methylated regions (DMRs). DMPs and DMRs were annotated using ANNOVAR 2018Apr16, and GO enrichment analysis was conducted using DAVID. The study was approved by the Guangxi University of Chinese Medicine Ethics Committee, and informed consent was obtained.

RESULTS

We identified 734,978 DMPs and 660 DMRs, with 1813 DMPs and 221 DMRs showing significant differences between groups. HBV-infected infants exhibited lower overall genomic methylation levels, with significant concentrations in gene body regions and CpG islands. GO enrichment analysis indicated that differentially methylated genes were enriched in processes related to cell adhesion and calcium ion binding.

CONCLUSIONS

Prenatal HBV exposure was associated with significant infant hypomethylation, particularly in regulatory regions like TSS1500, TSS200, and CpG islands, potentially impacting gene expression. Enrichment of immune-related pathways among differentially methylated genes suggests that HBV may alter infant immune development through epigenetic modifications.

Autophagy-related gene model as a novel risk factor for schizophrenia

Autophagy, a cellular process where cells degrade and recycle their own components, has garnered attention for its potential role in psychiatric disorders, including schizophrenia (SCZ). This study aimed to construct and validate a new autophagy-related gene (ARG) risk model for SCZ. First, we analyzed differential expressions in the GSE38484 training set, identifying 4,754 differentially expressed genes (DEGs) between SCZ and control groups. Using the Human Autophagy Database (HADb) database, we cataloged 232 ARGs and pinpointed 80 autophagy-related DEGs (AR-DEGs) after intersecting them with DEGs. Subsequent analyses, including metascape gene annotation, pathway and process enrichment, and protein-protein interaction enrichment, were performed on the 80 AR-DEGs to delve deeper into their biological roles and associated molecular pathways. From this, we identified 34 candidate risk AR-DEGs (RAR-DEGs) and honed this list to final RAR-DEGs via a constructed and optimized logistic regression model. These genes include VAMP7, PTEN, WIPI2, PARP1, DNAJB9, SH3GLB1, ATF4, EIF4G1, EGFR, CDKN1A, CFLAR, FAS, BCL2L1 and BNIP3. Using these findings, we crafted a nomogram to predict SCZ risk for individual samples. In summary, our study offers deeper insights into SCZ's molecular pathogenesis and paves the way for innovative approaches in risk prediction, gene-targeted diagnosis, and community-based SCZ treatments.

Association of psychological distress and DNA methylation: A 5-year longitudinal population-based twin study

AIM

To identify the psychological distress (PD)-associated 5'-cytosine-phosphate-guanine-3' sites (CpGs), and investigate the temporal relationship between dynamic changes in DNA methylation (DNAm) and PD.

METHODS

This study included 1084 twins from the Chinese National Twin Register (CNTR). The CNTR conducted epidemiological investigations and blood withdrawal twice in 2013 and 2018. These included twins were used to perform epigenome-wide association studies (EWASs) and to validate the previously reported PD-associated CpGs selected from previous EWASs in PubMed, Embase, and the EWAS catalog. Next, a cross-lagged study was performed to examine the temporality between changes in DNAm and PD in 308 twins who completed both 2013 and 2018 surveys.

RESULTS

The EWAS analysis of our study identified 25 CpGs. In the validation analysis, 741 CpGs from 29 previous EWASs on PD were selected for validation, and 101 CpGs were validated to be significant at a false discovery rate <0.05. The cross-lagged analysis found a unidirectional path from PD to DNAm at 14 CpGs, while no sites showed significance from DNAm to PD.

CONCLUSIONS

This study identified and validated PD-related CpGs in a Chinese twin population, and suggested that PD may be the cause of changes in DNAm over time. The findings provide new insights into the molecular mechanisms underlying PD pathophysiology.

Identification and verification of characteristic differentially expressed ferroptosis-related genes in osteosarcoma using bioinformatics analysis

BACKGROUND

This study identified and verified the characteristic differentially expressed ferroptosis-related genes (CDEFRGs) in osteosarcoma (OS).

METHODS

We extracted ferroptosis-related genes (FRGs), identified differentially expressed FRGs (DEFRGs) in OS, and conducted correlation analysis between DEFRGs. Next, we conducted GO and KEGG analyses to explore the biological functions and pathways of DEFRGs. Furthermore, we used LASSO and SVM-RFE algorithms to screen CDEFRGs, and evaluated its accuracy in diagnosing OS through ROC curves. Then, we demonstrated the molecular function and pathway enrichment of CDEFRGs through GSEA analysis. In addition, we evaluated the differences in immune cell infiltration between OS and NC groups, as well as the correlation between CDEFRGs expressions and immune cell infiltrations. Finally, the expression of CDEFRGs was verified through qRT-PCR, western blotting, and immunohistochemistry experiments.

RESULTS

We identified 51 DEFRGs and the expression relationship between them. GO and KEGG analysis revealed their key functions and important pathways. Based on four CDEFRGs (PEX3, CPEB1, NOX1, and ALOX5), we built the OS diagnostic model, and verified its accuracy. GSEA analysis further revealed the important functions and pathways of CDEFRGs. In addition, there were differences in immune cell infiltration between OS group and NC group, and CDEFRGs showed significant correlation with certain infiltrating immune cells. Finally, we validated the differential expression levels of four CDEFRGs through external experiments.

CONCLUSIONS

This study has shed light on the molecular pathological mechanism of OS and has offered novel perspectives for the early diagnosis and immune-targeted therapy of OS patients.

Unlocking the secrets: the power of methylation-based cfDNA detection of tissue damage in organ systems

BACKGROUND

Detecting organ and tissue damage is essential for early diagnosis, treatment decisions, and monitoring disease progression. Methylation-based assays offer a promising approach, as DNA methylation patterns can change in response to tissue damage. These assays have potential applications in early detection, monitoring disease progression, evaluating treatment efficacy, and assessing organ viability for transplantation. cfDNA released into the bloodstream upon tissue or organ injury can serve as a biomarker for damage. The epigenetic state of cfDNA, including DNA methylation patterns, can provide insights into the extent of tissue and organ damage.

CONTENT

Firstly, this review highlights DNA methylation as an extensively studied epigenetic modification that plays a pivotal role in processes such as cell growth, differentiation, and disease development. It then presents a variety of highly precise 5-mC methylation detection techniques that serve as powerful tools for gaining profound insights into epigenetic alterations linked with tissue damage. Subsequently, the review delves into the mechanisms underlying DNA methylation changes in organ and tissue damage, encompassing inflammation, oxidative stress, and DNA damage repair mechanisms. Next, it addresses the current research status of cfDNA methylation in the detection of specific organ tissues and organ damage. Finally, it provides an overview of the multiple steps involved in identifying specific methylation markers associated with tissue and organ damage for clinical trials. This review will explore the mechanisms and current state of research on cfDNA methylation-based assay detecting organ and tissue damage, the underlying mechanisms, and potential applications in clinical practice.

Reprogramming of lipid metabolism in hepatocellular carcinoma resulting in downregulation of phosphatidylcholines used as potential markers for diagnosis and prediction

BACKGROUND

Aberrant methylation and metabolic perturbations may deepen our understanding of hepatocarcinogenesis and help identify novel biomarkers for diagnosing hepatocellular carcinoma (HCC). We aimed to develop an HCC model based on a multi-omics.

RESEARCH DESIGN AND METHODS

Four hundred patient samples (200 with HCC and 200 with hepatitis B virus-related liver disease (HBVLD)) were subjected to liquid chromatography-mass spectrometry and multiplex bisulfite sequencing. Integrative analysis of clinical data, CpG data, and metabolome for the 20 complete imputation datasets within a for-loopwas used to identify biomarker.

RESULTS

Totally, 1,140 metabolites were annotated, of which 125 were differentially expressed. Lipid metabolism reprogramming in HCC, resulting in phosphatidylcholines (PC) significantly downregulated, partly due to the altered mitochondrial beta-oxidation of fatty acids with diverse chain lengths. Age, sex, serum-fetoprotein levels, cg05166871,cg14171514, cg18772205, PC (O-16:0/20:3(8Z, 11Z, 14Z)), and PC (16:1(9Z)/P-18:0) were used to develop the HCC model. The model presented a good diagnostic and an acceptable predictive performance. The cumulative incidence of HCC in low- and high-risk groups of HBVLD patients were 1.19% and 21.40%, respectively (p = 0.0039).

CONCLUSIONS

PCs serve as potential plasma biomarkers and help identify patients with HBVLD at risk of HCC who should be screened for early diagnosis and intervention.

Virus-induced breath biomarkers: A new perspective to study the metabolic responses of COVID-19 vaccinees

Coronavirus disease 2019 (COVID-19) vaccines can protect people from the infection; however, the action mechanism of vaccine-mediated metabolism remains unclear. Herein, we performed breath tests in COVID-19 vaccinees that revealed metabolic reprogramming induced by protective immune responses. In total, 204 breath samples were obtained from COVID-19 vaccinees and non-vaccinated controls, wherein numerous volatile organic compounds (VOCs) were detected by comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry system. Subsequently, 12 VOCs were selected as biomarkers to construct a signature panel using alveolar gradients and machine learning-based procedure. The signature panel could distinguish vaccinees from control group with a high prediction performance (AUC, 0.9953; accuracy, 94.42%). The metabolic pathways of these biomarkers indicated that the host-pathogen interactions enhanced enzymatic activity and microbial metabolism in the liver, lung, and gut, potentially constituting the dominant action mechanism of vaccine-driven metabolic regulation. Thus, our findings of this study highlight the potential of measuring exhaled VOCs as rapid, non-invasive biomarkers of viral infections. Furthermore, breathomics appears as an alternative for safety evaluation of biological agents and disease diagnosis.

Blood cell DNA methylation biomarkers in preclinical malignant pleural mesothelioma: The EPIC prospective cohort

Malignant pleural mesothelioma (MPM) is a rare and aggressive cancer mainly caused by asbestos exposure. Specific and sensitive noninvasive biomarkers may facilitate and enhance screening programs for the early detection of cancer. We investigated DNA methylation (DNAm) profiles in MPM prediagnostic blood samples in a case-control study nested in the European Prospective Investigation into Cancer and nutrition (EPIC) cohort, aiming to characterise DNAm biomarkers associated with MPM. From the EPIC cohort, we included samples from 135 participants who developed MPM during 20 years of follow-up and from 135 matched, cancer-free, controls. For the discovery phase we selected EPIC participants who developed MPM within 5 years from enrolment (n = 36) with matched controls. We identified nine differentially methylated CpGs, selected by 10-fold cross-validation and correlation analyses: cg25755428 (MRI1), cg20389709 (KLF11), cg23870316, cg13862711 (LHX6), cg06417478 (HOOK2), cg00667948, cg01879420 (AMD1), cg25317025 (RPL17) and cg06205333 (RAP1A). Receiver operating characteristic (ROC) analysis showed that the model including baseline characteristics (age, sex and PC1wbc) along with the nine MPM-related CpGs has a better predictive value for MPM occurrence than the baseline model alone, maintaining some performance also at more than 5 years before diagnosis (area under the curve [AUC] < 5 years = 0.89; AUC 5-10 years = 0.80; AUC >10 years = 0.75; baseline AUC range = 0.63-0.67). DNAm changes as noninvasive biomarkers in prediagnostic blood samples of MPM cases were investigated for the first time. Their application can improve the identification of asbestos-exposed individuals at higher MPM risk to possibly adopt more intensive monitoring for early disease identification.

Association Between DNA Methylation and Blood Pressure: A 5-Year Longitudinal Twin Study

BACKGROUND

Previous EWASs (Epigenome-Wide Association Studies) have reported hundreds of blood pressure (BP) associated 5'-cytosine-phosphate-guanine-3' (CpG) sites. However, their results were inconsistent. Longitudinal observations on the temporal relationship between DNA methylation and BP are lacking.

METHODS

A candidate CpG site association study for BP was conducted on 1072 twins in the Chinese National Twin Registry. PubMed and EMBASE were searched for candidate CpG sites. Cross-lagged models were used to assess the temporal relationship between BP and DNA methylation in 308 twins who completed 2 surveys in 2013 and 2018. Then, the significant cross-lagged associations were validated by adopting the Inference About Causation From Examination of Familial Confounding approach. Finally, to evaluate the cumulative effects of DNA methylation on the progression of hypertension, we established methylation risk scores based on BP-associated CpG sites and performed Markov multistate models.

RESULTS

16 and 20 CpG sites were validated to be associated with systolic BP and diastolic BP, respectively. In the cross-lagged analysis, we detected that methylation of 2 CpG sites could predict subsequent systolic BP, and systolic BP predicted methylation at another 3 CpG sites. For diastolic BP, methylation at 3 CpG sites had significant cross-lagged effects for predicting diastolic BP levels, while the prediction from the opposite direction was observed at one site. Among these, 3 associations were validated in the Inference About Causation From Examination of Familial Confounding analysis. Using the Markov multistate model, we observed that methylation risk scores were associated with the development of hypertension.

CONCLUSIONS

Our findings suggest the significance of DNA methylation in the development of hypertension.

Exploration of the Effect on Genome-Wide DNA Methylation by miR-143 Knock-Out in Mice Liver

MiR-143 play an important role in hepatocellular carcinoma and liver fibrosis via inhibiting hepatoma cell proliferation. DNA methyltransferase 3 alpha (DNMT3a), as a target of miR-143, regulates the development of primary organic solid tumors through DNA methylation mechanisms. However, the effect of miR-143 on DNA methylation profiles in liver is unclear. In this study, we used Whole-Genome Bisulfite Sequencing (WGBS) to detect the differentially methylated regions (DMRs), and investigated DMR-related genes and their enriched pathways by miR-143. We found that methylated cytosines increased 0.19% in the miR-143 knock-out (KO) liver fed with high-fat diet (HFD), compared with the wild type (WT). Furthermore, compared with the WT group, the CG methylation patterns of the KO group showed lower CG methylation levels in CG islands (CGIs), promoters and hypermethylation in CGI shores, 5'UTRs, exons, introns, 3'UTRs, and repeat regions. A total of 984 DMRs were identified between the WT and KO groups consisting of 559 hypermethylation and 425 hypomethylation DMRs. Furthermore, DMR-related genes were enriched in metabolism pathways such as carbon metabolism (serine hydroxymethyltransferase 2 (Shmt2), acyl-Coenzyme A dehydrogenase medium chain (Acadm)), arginine and proline metabolism (spermine synthase (Sms), proline dehydrogenase (Prodh2)) and purine metabolism (phosphoribosyl pyrophosphate synthetase 2 (Prps2)). In summary, we are the first to report the change in whole-genome methylation levels by miR-143-null through WGBS in mice liver, and provide an experimental basis for clinical diagnosis and treatment in liver diseases, indicating that miR-143 may be a potential therapeutic target and biomarker for liver damage-associated diseases and hepatocellular carcinoma.

A CpG Methylation Signature as a Potential Marker for Early Diagnosis of Hepatocellular Carcinoma From HBV-Related Liver Disease Using Multiplex Bisulfite Sequencing

Background

Aberrant methylation of CpG sites served as an epigenetic marker for building diagnostic, prognostic, and recurrence models for hepatocellular carcinoma (HCC).

Methods

Using Illumina 450K and EPIC Beadchip, we identified 34 CpG sites in peripheral blood mononuclear cell (PBMC) DNA that were differentially methylated in early HCC versus HBV-related liver diseases (HBVLD). We employed multiplex bisulfite sequencing (MBS) based on next-generation sequencing (NGS) to measure methylation of 34 CpG sites in PBMC DNA from 654 patients that were divided into a training set (n = 442) and a test set (n = 212). Using the training set, we selected and built a six-CpG-scorer (namely, cg14171514, cg07721852, cg05166871, cg18087306, cg05213896, and cg18772205), applying least absolute shrinkage and selection operator (LASSO) regression. We performed multivariable analyses of four candidate risk predictors (namely, six-CpG-scorer, age, sex, and AFP level), using 20 times imputation of missing data, non-linearly transformed, and backwards feature selection with logistic regression. The final model’s regression coefficients were calculated according to “Rubin’s Rules”. The diagnostic accuracy of the model was internally validated with a 10,000 bootstrap validation dataset and then applied to the test set for validation.

Results

The area under the receiver operating characteristic curve (AUROC) of the model was 0.81 (95% CI, 0.77–0.85) and it showed good calibration and decision curve analysis. Using enhanced bootstrap validation, adjusted C-statistics and adjusted Brier score were 0.809 and 0.199, respectively. The model also showed an AUROC value of 0.84 (95% CI 0.79–0.88) of diagnosis for early HCC in the test set.

Conclusions

Our model based on the six-CpG-scorer was a reliable diagnosis tool for early HCC from HBVLD. The usage of the MBS method can realize large-scale detection of CpG sites in clinical diagnosis of early HCC and benefit the majority of patients.

Are Humanized Mouse Models Useful for Basic Research of Hepatocarcinogenesis through Chronic Hepatitis B Virus Infection?

Chronic hepatitis B virus (HBV) infection is a global health problem that can lead to liver dysfunction, including liver cirrhosis and hepatocellular carcinoma (HCC). Current antiviral therapies can control viral replication in patients with chronic HBV infection; however, there is a risk of HCC development. HBV-related proteins may be produced in hepatocytes regardless of antiviral therapies and influence intracellular metabolism and signaling pathways, resulting in liver carcinogenesis. To understand the mechanisms of liver carcinogenesis, the effect of HBV infection in human hepatocytes should be analyzed. HBV infects human hepatocytes through transfer to the sodium taurocholate co-transporting polypeptide (NTCP). Although the NTCP is expressed on the hepatocyte surface in several animals, including mice, HBV infection is limited to human primates. Due to this species-specific liver tropism, suitable animal models for analyzing HBV replication and developing antivirals have been lacking since the discovery of the virus. Recently, a humanized mouse model carrying human hepatocytes in the liver was developed based on several immunodeficient mice; this is useful for analyzing the HBV life cycle, antiviral effects of existing/novel antivirals, and intracellular signaling pathways under HBV infection. Herein, the usefulness of human hepatocyte chimeric mouse models in the analysis of HBV-associated hepatocarcinogenesis is discussed.

Mechanisms of DNA Methylation in Virus-Host Interaction in Hepatitis B Infection: Pathogenesis and Oncogenetic Properties

Hepatitis B virus (HBV), the well-studied oncovirus that contributes to the majority of hepatocellular carcinomas (HCC) worldwide, can cause a severe inflammatory microenvironment leading to genetic and epigenetic changes in hepatocyte clones. HBV replication contributes to the regulation of DNA methyltransferase gene expression, particularly by X protein (HBx), and subsequent methylation changes may lead to abnormal transcription activation of adjacent genes and genomic instability. Undoubtedly, the altered expression of these genes has been known to cause diverse aspects of infected hepatocytes, including apoptosis, proliferation, reactive oxygen species (ROS) accumulation, and immune responses. Additionally, pollutant-induced DNA methylation changes and aberrant methylation of imprinted genes in hepatocytes also complicate the process of tumorigenesis. Meanwhile, hepatocytes also contribute to epigenetic modification of the viral genome to affect HBV replication or viral protein production. Meanwhile, methylation levels of HBV integrants and surrounding host regions also play crucial roles in their ability to produce viral proteins in affected hepatocytes. Both host and viral changes can provide novel insights into tumorigenesis, individualized responses to therapeutic intervention, disease progress, and early diagnosis. As such, DNA methylation-mediated epigenetic silencing of cancer-related genes and viral replication is a compelling therapeutic goal to reduce morbidity and mortality from liver cancer caused by chronic HBV infection. In this review, we summarize the most recent research on aberrant DNA methylation associated with HBV infection, which is involved in HCC development, and provide an outlook on the future direction of the research.

Interaction analysis of gene variants related to one-carbon metabolism with chronic hepatitis B infection in Chinese patients

BACKGROUND

The risk of chronic hepatitis B (CHB) infection is influenced by aberrant DNA methylation and altered nucleotide synthesis and repair, possibly caused by polymorphic variants in one-carbon metabolism genes. In the present study, we investigated the relationship between polymorphisms belonging to the one-carbon metabolic pathway and CHB infection.

METHODS

A case-control study using 230 CHB patients and 234 unrelated healthy controls was carried out to assess the genetic association of 24 single nucleotide polymorphisins (SNPs) determined by mass spectrometry.

RESULTS

Three SNPs, comprising rs10717122 and rs2229717 in serine hydroxymethyltransferase1/2 (SHMT2) and rs585800 in betaine-homocysteine S-methyltransferase (BHMT), were associated with the risk of CHB. Patients with DEL allele, DEL.DEL and DEL.T genotypes of rs10717122 had a 1.40-, 2.00- and 1.83-fold increased risk for CHB, respectively. Cases inheriting TA genotype of rs585800 had a 2.19-fold risk for CHB infection. The T allele of rs2229717 was less represented in the CHB cases (odds ratio = 0.66, 95% confidence interval = 0.48-0.92). The T allele of rs2229717 was less in patients with a low hepatitis B virus-DNA level compared to the control group (odds ratio = 0.49, 95% confidence interval = 0.25-0.97) and TT genotype of rs2229717 had a significant correlation with hepatitis B surface antigen level (p = 0.0195). Further gene-gene interaction analysis showed that subjects carrying the rs10717122 DEL.DEL/DEL.T and rs585800 TT/TA genotypes had a 2.74-fold increased risk of CHB.

CONCLUSIONS

The results of the present study suggest that rs10717122, rs585800 and rs2229717 and gene-gene interactions of rs10717122 and rs585800 affect the outcome of CHB infection, at the same time as indicating their usefulness as a predictive and diagnostic biomarker of CHB infection.

Effect of DNA methylation on gene transcription is associated with the distribution of methylation sites across the genome in osteoarthritis

Genetics and epigenetics are important subjects in the field of osteoarthritis (OA) research. DNA methylation may affect gene transcription, but the specific mechanisms have remained to be fully elucidated. In the present study, the ChAMP methylation analysis package was used to identify differentially methylated genes (DMGs) from the dataset GSE63695 from the Gene Expression Omnibus (GEO) database. The distribution of differentially methylated sites (DMS) and the total array sites across the genome were analyzed by enrichment analysis. Subsequently, two mRNA expression profiling datasets, GSE114007 and GSE113825, were obtained from the GEO database and common differentially expressed genes (DEGs) were identified using the Limma package. Key genes were screened by analyzing the distribution of DMS across the genome consisting of DEGs and DMGs. A total of 1,662 and 1,986 DEGs were identified between OA and normal human cartilage from the GSE113825 and GSE114007 dataset, respectively. A further screening revealed 292 genes with common differences between the two datasets. A total of 574 DMS containing 394 DMGs were observed between OA and normal cartilage. Integrative analysis revealed a corresponding subset of 15 genes. Of these, 6 genes were verified by reverse transcription-quantitative PCR, confirming that the mRNA expression of 5 genes (MAP1B, FNDC1, ANLN, SCNN1A and STC2) in OA cartilage was consistent with the mRNA expression from the analysis of the datasets. Upon treatment with the DNA methylation inhibitor 5-aza-2'-deoxycytidine, the mRNA levels of FNDC1 and SCNN1A were decreased, and no significant alteration in the mRNA levels of MAP1B, ANLN, KCNN4 and STC2 was observed. The incidence of differential methylation varied in subregions of the genome and the effects on transcription were associated with the distribution of DEGs across the genome. The regulation of this appears more complex than initially postulated. Combining the data on epigenetic differences of OA with the genome or transcriptome data for analysis may improve the understanding of the pathophysiological processes of OA. FNDC1 and SCNN1A may potentially be valuable biomarkers for OA.

Profibrotic Signaling and HCC Risk during Chronic Viral Hepatitis: Biomarker Development

Despite breakthroughs in antiviral therapies, chronic viral hepatitis B and C are still the major causes of liver fibrosis and hepatocellular carcinoma (HCC). Importantly, even in patients with controlled infection or viral cure, the cancer risk cannot be fully eliminated, highlighting a persisting oncogenic pressure imposed by epigenetic imprinting and advanced liver disease. Reliable and minimally invasive biomarkers for early fibrosis and for residual HCC risk in HCV-cured patients are urgently needed. Chronic infection with HBV and/or HCV dysregulates oncogenic and profibrogenic signaling within the host, also displayed in the secretion of soluble factors to the blood. The study of virus-dysregulated signaling pathways may, therefore, contribute to the identification of reliable minimally invasive biomarkers for the detection of patients at early-stage liver disease potentially complementing existing noninvasive methods in clinics. With a focus on virus-induced signaling events, this review provides an overview of candidate blood biomarkers for liver disease and HCC risk associated with chronic viral hepatitis and epigenetic viral footprints.