Glutathione Transferase P1 Polymorphism Might Be a Risk Determinant in Heart Failure

Potential role of glutathione S‑transferase M1 gene polymorphism in kidney calcium oxalate stone formation

BACKGROUND

The purpose of this study was to look into the effects of glutathione S-transferase M1 (GSTM1) gene polymorphism on the formation of kidney calcium oxalate stones.

METHODS

A total of 159 patients with kidney calcium oxalate stones were included in this study as a case group. One hundred and three healthy individuals were included in the control group. The age, gender, and levels of calcium (Ca), uric acid (UA), creatinine (Cr), and urinary creatinine (Ucr) are tracked. Peripheral blood samples are used to perform a polymerase chain reaction to identify the glutathione S-transferase (GST) gene polymorphism (PCR). A commercial kit was used in this study to measure the levels of malondialdehyde (MDA), nitric oxide (NO), total antioxidant capacity (T-AOC), and 8-hydroxydeoxyguanosine (8-OHdG) in peripheral blood.

RESULTS

There was no difference in age or gender distribution between the case and control groups (P > 0.05). The Cr, Ucr, Ca, UA, 8-OHdG, MDA, NO, and T-AOC in the case group were significantly higher than those in the control group (P < 0.001). The Hardy-Weinberg genetic equilibrium test showed no difference between the case group (P = 0.23) and the control group (P = 0.09). In the case group, the 8-OHdG and NO in GSTM1 null genotype were significantly higher than those in GSTM1 genotype (P < 0.05), but there was no significant difference in MDA and T-AOC (P > 0.05). Multivariate regression analysis showed that the GSTM1 null genotype was positively correlated with 8-OHdG (P < 0.001) and NO (P < 0.001).

CONCLUSIONS

GSTM1 gene polymorphism might be a detecting risk factor for kidney calcium oxalate stone formation.

TRIAL REGISTRATION

ChiCTR2100051300.

The importance of polymorphisms in the genes encoding glutathione S-transferase isoenzymes in development of selected cancers and cardiovascular diseases

Glutathione S-transferases are a family of enzymes, whose main role is to detoxify cells from many exogenous factors, such as xenobiotics or carcinogens. It has also been proven that changes in the genes encoding these enzymes may affect the incidence of selected cancers and cardiovascular diseases. The aim of this study was to review the most important reports related to the role of glutathione S-transferases in the pathophysiology of two of the most common diseases in modern society - cancers and cardiovascular diseases. It was shown that polymorphisms in the genes encoding glutathione S-transferases are associated with the development of these diseases. However, depending on the ethnic group, the researchers obtained divergent results related to this field. In the case of the GSTP1 A/G gene polymorphism was shown an increased incidence of breast cancer in Asian women, while this relationship in European and African women was not found. Similarly. In the case of cardiovascular diseases, the differences in the influence of GSTM1, GSTT1, GSTP1 and GSTA1 polymorphisms on their development or lack of it depending on the continent were shown. These examples show that the development of the above-mentioned diseases is not only influenced by genetic changes, but their pathophysiology is more complex. The mere presence of a specific genotype within a studied polymorphism may not predispose to cancer, but in combination with environmental factors, which often depend on the place of residence, it may elevate the chance of developing the selected disease.

A network medicine approach to study comorbidities in heart failure with preserved ejection fraction

BACKGROUND

Comorbidities are expected to impact the pathophysiology of heart failure (HF) with preserved ejection fraction (HFpEF). However, comorbidity profiles are usually reduced to a few comorbid disorders. Systems medicine approaches can model phenome-wide comorbidity profiles to improve our understanding of HFpEF and infer associated genetic profiles.

METHODS

We retrospectively explored 569 comorbidities in 29,047 HF patients, including 8062 HFpEF and 6585 HF with reduced ejection fraction (HFrEF) patients from a German university hospital. We assessed differences in comorbidity profiles between HF subtypes via multiple correspondence analysis. Then, we used machine learning classifiers to identify distinctive comorbidity profiles of HFpEF and HFrEF patients. Moreover, we built a comorbidity network (HFnet) to identify the main disease clusters that summarized the phenome-wide comorbidity. Lastly, we predicted novel gene candidates for HFpEF by linking the HFnet to a multilayer gene network, integrating multiple databases. To corroborate HFpEF candidate genes, we collected transcriptomic data in a murine HFpEF model. We compared predicted genes with the murine disease signature as well as with the literature.

RESULTS

We found a high degree of variance between the comorbidity profiles of HFpEF and HFrEF, while each was more similar to HFmrEF. The comorbidities present in HFpEF patients were more diverse than those in HFrEF and included neoplastic, osteologic and rheumatoid disorders. Disease communities in the HFnet captured important comorbidity concepts of HF patients which could be assigned to HF subtypes, age groups, and sex. Based on the HFpEF comorbidity profile, we predicted and recovered gene candidates, including genes involved in fibrosis (COL3A1, LOX, SMAD9, PTHL), hypertrophy (GATA5, MYH7), oxidative stress (NOS1, GSST1, XDH), and endoplasmic reticulum stress (ATF6). Finally, predicted genes were significantly overrepresented in the murine transcriptomic disease signature providing additional plausibility for their relevance.

CONCLUSIONS

We applied systems medicine concepts to analyze comorbidity profiles in a HF patient cohort. We were able to identify disease clusters that helped to characterize HF patients. We derived a distinct comorbidity profile for HFpEF, which was leveraged to suggest novel candidate genes via network propagation. The identification of distinctive comorbidity profiles and candidate genes from routine clinical data provides insights that may be leveraged to improve diagnosis and identify treatment targets for HFpEF patients.

Glutathione S-Transferase P1 Genetic Variant's Influence on the HbA1c Level in Type Two Diabetic Patients

GST (glutathione S-transferases) are capable of influencing glucose homeostasis, probably through regulation of the response to oxidant stress. The aim of our study was to investigate the relationship between GSTP1 gene polymorphism and glycated hemoglobin (HbA1c) levels in type two diabetic (T2D) patients. A total of 307 T2D patients were included. Analysis of the GSTP1 gene polymorphism (rs1695) was conducted using the TaqMan qPCR method endpoint genotyping. HbA1c was determined using a COBAS 6000 autoanalyzer. A univariable linear regression and multivariable linear regression model were used to investigate the association between mean HbA1c level and GSTP1 gene polymorphism, age at T2D diagnosis, T2D duration, therapy with insulin, gender, BMI, smoking status. GSTP1 Val/Val genotype, age at T2D diagnosis, T2D duration and therapy with insulin were statistically significant contributors to HbA1c levels (p < 0.05). Multivariable regression analysis revealed that GSTP1 (Val/Val vs. Ile/Ile) was associated with higher HbA1c even after adjustment for variables that showed a statistically significant relationship with HbA1c in univariable analyses (p = 0.024). The results suggest that GSTP polymorphism may be one of the risk factors for higher HbA1c in T2D patients. Our study is limited by the relatively small sample size, cross-sectional design, and lack of inclusion of other oxidative stress-related genetic variants.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis

BACKGROUND

Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF.

METHODS

We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes.

RESULTS

A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B).

CONCLUSIONS

This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

New Biomarkers and Their Potential Role in Heart Failure Treatment Optimisation-An African Perspective

Heart failure is a clinical syndrome resulting from various cardiovascular diseases of different aetiologies and pathophysiology. These varying pathologies involve several complex mechanisms that lead to the activation of the neurohumoral system, inflammation, angiogenesis, apoptosis, fibrosis, and eventually adverse cardiac remodelling associated with a progressive decline in cardiac function. Once a diagnosis is made, the cardiac function has a gradual decline characterised by multiple hospital admissions. It is therefore imperative to identify patients at different stages of the heart failure continuum to better risk stratify and initiate optimal management strategies. Biomarkers may play a role in the diagnosis, prognostication, and monitoring response to treatment. This review discusses the epidemiology of heart failure and biomarkers commonly used in clinical practice such as natriuretic peptides and cardiac troponins. In addition, we provide a brief overview of novel biomarkers and genetic coding and non-coding biomarkers used in the management of patients with heart failure. We also discuss barriers that hinder the clinical application of novel biomarkers. Finally, we appraise the value of polygenic risk scoring, focusing on sub-Saharan Africa.

An updated analysis on the association of GSTM1 polymorphism and smoking exposure with the increased risk of coronary heart disease

Objective

To undertake a meta-analysis to investigate if there is an association between the glutathione S-transferase mu 1 (GSTM1) gene polymorphism, coronary artery disease (CAD) susceptibility and smoking.

Methods

Electronic databases, including PubMed®, Web of Science and Embase®, were searched for relevant case–control studies. Data were extracted and the odds ratio (OR) was calculated and appropriate statistical methods were used for the meta-analysis.

Results

The analysis included eight studies with a total of 1880 cases with CAD and 1758 control subjects. The results of this meta-analysis demonstrated that there is no association between the GSTM1 null and CAD (OR 1.24, 95% confidence interval [CI] 1.00, 1.55). An increased risk of CAD was observed in the smoking population with the GSTM1 null genotype (OR 1.48, 95% CI 1.02, 2.15). Subgroup analyses of geographical region, genotyping method and publication language category demonstrated potential relationships among gene polymorphism, smoking and CAD.

Conclusions

Based on the current literature, the GSTM1 null genotype was associated to CAD in the smoking population. The interaction between smoking and GSTM1 polymorphism may contribute to the susceptibility of CAD.

Expression Signatures of Long Noncoding RNAs in Left Ventricular Noncompaction

Long noncoding RNAs have gained widespread attention in recent years for their crucial role in biological regulation. They have been implicated in a range of developmental processes and diseases including cancer, cardiovascular, and neuronal diseases. However, the role of long noncoding RNAs (lncRNAs) in left ventricular noncompaction (LVNC) has not been explored. In this study, we investigated the expression levels of lncRNAs in the blood of LVNC patients and healthy subjects to identify differentially expressed lncRNA that develop LVNC specific biomarkers and targets for developing therapies using biological pathways. We used Agilent Human lncRNA array that contains both updated lncRNAs and mRNAs probes. We identified 1,568 upregulated and 1,141 downregulated (log fold-change > 2.0) lncRNAs that are differentially expressed between LVNC and the control group. Among them, RP11-1100L3.7 and XLOC_002730 are the most upregulated and downregulated lncRNAs. Using quantitative real-time reverse transcription polymerase chain reaction (RT-QPCR), we confirmed the differential expression of three top upregulated and downregulated lncRNAs along with two other randomly picked lncRNAs. Gene Ontology (GO) and KEGG pathways analysis with these differentially expressed lncRNAs provide insight into the cellular pathway leading to LVNC pathogenesis. We also identified 1,066 upregulated and 1,017 downregulated mRNAs. Gene set enrichment analysis (GSEA) showed that G2M, Estrogen, and inflammatory pathways are enriched in differentially expressed genes (DEG). We also identified miRNA targets for these differentially expressed genes. In this study, we first report the use of LncRNA microarray to understand the pathogenesis of LVNC and to identify several lncRNA and genes and their targets as potential biomarkers.

Association of GSTP1 Ile105Val polymorphism with the risk of coronary heart disease: An updated meta-analysis

Background

Numerous case-control studies have investigated the association between GSTP1 Ile105Val polymorphism and CHD risk, but the results from published studies were inconclusive. The present meta-analysis was performed to derive a more precise estimation.

Methods

PubMed, EMBASE, and Web of Science database searches were conducted to retrieve relevant articles.

Results

Ultimately, 5,451 CHD cases and 5,561 controls from 15 studies were included. Pooled analysis did not yield any statistically significant association between GSTP1 Ile105Val polymorphism and CHD risk for the overall population (Val vs. Ile: OR, 1.05; 95% CI, 0.93 to 1.18; Val/Val vs. Ile/Ile: OR, 1.09; 95% CI, 0.83 to 1.42; Val/Ile vs. Ile/Ile: OR, 1.09; 95% CI, 0.93 to 1.28; Val/Val vs. Val/Ile+Ile/Ile: OR, 1.04; 95% CI, 0.83 to 1.30; Val/Val+Val/Ile vs. Ile/Ile: OR, 1.14; 95% CI, 0.97 to 1.33). Subgroup analyses and sensitivity analyses indicated that GSTP1 Ile105Val polymorphism was still not associated with an increased risk of CHD. After excluding studies detected by Galbraith plots as major sources of heterogeneity, these relationships were still not significant.

Conclusions

The overall results did not reveal a major role of the GSTP1 Ile105Val polymorphism in modulating CHD risk. Well-designed studies with large sample sizes are needed to validate our findings and explore the possible gene-gene or gene-environment interactions.

A novel gene associated with small bowel bleeding in patients taking low-dose aspirin

OBJECTIVE

We have previously revealed the clinical factors and genetic polymorphisms associated with gastrointestinal mucosal injury and bleeding, induced by low-dose aspirin (LDA). After performing genome-wide analysis of single nucleotide polymorphisms (SNPs) using the Drug Metabolizing Enzymes and Transporters (DMET) system among drug metabolism and transporter genes, certain SNPs were found to increase the risk for LDA-induced small bowel bleeding. The aim of this study was to identify the SNPs involved in LDA-induced small bowel bleeding.

SUBJECTS AND METHODS

Subjects were patients taking LDA, with small bowel bleeding diagnosed using capsule endoscopy. We investigated the clinical characteristics and the previously identified SNPs, that were examined by the DNA direct sequence method.

RESULTS

56 patients with bleeding and 410 controls taking LDA were enrolled. The risk factors associated with small bowel bleeding included smoking, cerebrovascular diseases, chronic renal failure, non-steroidal anti-inflammatory drug (NSAID) or anticoagulants combination, and two SNPs (CYP4F11 20043G>A (D446N) rs1060463, GSTP1 313A>G rs1695). After propensity score matching, GSTP1 rs1695 was significantly associated with small bowel bleeding.

CONCLUSION

The GSTP1 SNP may be a predictive marker for small bowel bleeding among patients taking LDA.

Activity of glutathione S-transferase and its π isoenzyme in the context of single nucleotide polymorphism in the GSTP1 gene (rs1695) and tobacco smoke exposure in the patients with acute pancreatitis and healthy subjects

Oxidative stress associated with the course of acute pancreatitis (AP) can cause changes in the involvement of antioxidants, which can result in the increased production of free radicals with pro-inflammatory potential. Through its noncatalytic activity, the glutathione S-transferase and its π isoenzyme (GST-π), apart from cellular xenobiotics detoxification, are involved in the regulation of cellular signalling, metabolism and apoptosis. This study aimed to evaluate the impact of SNP rs1695 in the GSTP1 gene on GST and GST-π activity in healthy subjects and patients with acute pancreatitis (AP). The concentration of glutathione (GSH) as an important component of the antioxidant system, necessary for environmental xenobiotics detoxification by GST, and malonyldialdehyde (MDA) as a marker of oxidative stress induced by inflammation were also assessed. SNP was examined in 39 AP patients and 51 healthy subjects using PCR-RFLP methods. GST activity (in plasma and erythrocyte lysate) and GST-π activity (in erythrocyte lysate) were measured using the spectrophotometric method with 1-chloro-2,4-dinitrobenzene and ethacrynic acid as substrate, respectively. Blood GSH concentration was measured using the Patterson method. Concentrations of high-sensitive C-reactive protein (hs-CRP) and MDA were measured using commercial tests. In the blood of non-smoking AP patients with GG genotypes for SNP rs1695 in the GSTP1 gene, the lowest GST-π activity was shown. It was accompanied by the lowest hsCRP concentration in this group. In the blood of smoking healthy subjects with AG genotype, a decrease in GST-π activity was noted compared to non-smokers from this group. However, in the blood of smokers with AP, a gradually decreasing GST-π activity was noted in individuals with AA genotype, which was associated with the increasing MDA concentration. It confirms the role of GST-π in the neutralization of oxidative stress induced by the exposure to smoke xenobiotics.

The association of glutathione S-transferase T1 and M1 deletions with myocardial infarction

Glutathione S-transferases (GSTs) are the family of enzymes involved in the second line of defense against oxidative stress (OS). The lack of GSTT1/GSTM1 enzyme quantity or activity, due to the presence of homozygous deletion compromises antioxidative defense resulting in OS. OS is the critical mechanism in the pathophysiology of atherosclerosis, coronary artery disease, and myocardial infarction (MI). The increase in reactive oxygen species together with the process of apoptosis plays a role in left ventricular remodeling (LVR) after MI. The associations of GSTT1 and GSTM1 gene polymorphisms with the risk of MI are inconsistent. The aim was to analyze the association of GSTT1/GSTM1 null genotypes with first MI and LVR 8 months after the MI. The study involved 330 controls and 438 consecutive patients with symptoms and signs of first MI. The subgroup of 150 MI patients was prospectively followed up for 6 months. Evidence of maladaptive LVR was obtained by 2D Doppler echocardiography 3-5 days and 6 months after the MI. A multiplex polymerase chain reaction was used to detect the deletion in GSTT1 and GSTM1 genes. GSTM1 null genotype was significantly and independently associated with first MI (adjusted OR = 1.45 95% CI 1.03-2.03, p = 0.03). Association of double null genotypes with maladaptive LVR in patients 6 months after the first MI was no longer significant after adjustment for factors that differed significantly between patients with and without maladaptive LVR. This study demonstrated the association of GSTM1 null genotypes with the risk of MI in the Serbian population.

Genetic Variability of Antioxidative Mechanisms and Cardiotoxicity after Adjuvant Radiotherapy in HER2-Positive Breast Cancer Patients

Background

Breast cancer treatment is associated with the occurrence of various cardiac adverse events. One of the mechanisms associated with cardiotoxicity is oxidative stress, against which cells are protected by antioxidative enzymes. Genetic variability of antioxidative enzymes can affect enzyme activity or expression, which modifies the ability of cells to defend themselves against oxidative stress and could consequently contribute to the occurrence of treatment-related cardiotoxicity. Our aim was to evaluate the association of common polymorphisms in antioxidative genes with cardiotoxicity after adjuvant radiotherapy (RT) in HER2-positive breast cancer patients.

Methods

Our retrospective study included 101 HER2-positive early breast cancer patients who received trastuzumab and adjuvant RT. We isolated DNA from buccal swabs and used competitive allele-specific PCR for genotyping of PON1 rs854560 and rs662, GSTP1 rs1138272 and rs1695, SOD2 rs4880, CAT rs1001179, and HIF1 rs1154965 polymorphisms. N-terminal pro B-type natriuretic peptide (NT-proBNP), left ventricular ejection fraction, and NYHA class were used as markers of cardiotoxicity. We used logistic regression to evaluate the association of genetic factors with markers of cardiotoxicity.

Results

Carriers of at least one polymorphic PON1 rs854560 allele were less likely to have increased NT-proBNP (OR = 0.34; 95% CI = 0.15-0.79; P = 0.012), even after adjustment for age (OR = 0.35; 95% CI = 0.15-0.83; P = 0.017). Carriers of at least one polymorphic PON1 rs662 allele were more likely to have increased NT-proBNP (OR = 4.44; 95% CI = 1.85-10.66; P = 0.001), even after adjustment for age (OR = 5.41; 95% CI = 2.12-13.78; P < 0.001). GSTP1 rs1695 was also associated with decreased NT-proBNP in the multivariable analysis (P = 0.026), while CAT rs1001179 was associated with NYHA class in the univariable (P = 0.012) and multivariable analysis (P = 0.023).

Conclusion

In our study, polymorphisms PON1 rs662 and rs854560, CAT rs1001179, and GSTP1 rs1695 were significantly associated with the occurrence of cardiac adverse events after adjuvant RT and could serve as biomarkers contributing to treatment personalization.

Genetic predisposition to the development of congenital heart diseases: Role of xenobiotic biotransformation genes

Congenital heart diseases are one of the most common multi-factorial fetal abnormalities caused by a complex of endo- and exogenous factors. It is known that mutations in xenobiotic biotransformation genes can be associated with the pathogenesis of congenital heart diseases. In the presented research, 131 children with congenital heart diseases and 101 women having children with this pathology were included in the study group. In control group, 103 healthy children and their mothers were included. Single-nucleotide polymorphisms in the xenobiotic biotransformation genes CYP1A1 (rs1048943), CYP1A2 (rs762551), GSTP1 (rs6591256, rs1871042 and rs17593068) were detected by the real-time polymerase chain reaction. Gene-gene interactions were determined using the Multifactor Dimensionality Reduction method. We obtained no difference in the frequency of CYP1A1, CYP1A2 and GSTP1 between the study and control groups. At the same time, the genetic combinations GSTP1 (rs6591256)-GSTP1 (rs1871042) and GSTP1 (rs6591256)-GSTP1 (rs1871042)-CYP1A1 (rs1048943) in women; and GSTP1 (rs1793068)-GSTP1 (rs6591256)-GSTP1 (rs1871042)-CYP1A1 (rs1048943)-CYP1A2 (rs762551) in children contribute to the pathogenesis of congenital heart diseases.

Genetic Polymorphism of GSTP-1 Affects Cyclophosphamide Treatment of Autoimmune Diseases

Cyclophosphamide is one of the most potent and reliable anti-cancer and immunosuppressive drugs. In our study, 33 individuals with different autoimmune diseases were treated with cyclophosphamide according to standard protocols. The responses to the treatments were determined by measuring the alteration of several typical parameters characterizing the given autoimmune diseases over time. We concluded that about 45% of the patients responded to the treatment. Patients were genotyped for polymorphisms of the CYP3A4, CYP2B6, GSTM1, GSTT1, and GSTP1 genes and disease remission cases were compared to the individual polymorphic genotypes. It was found that the GSTP1 I105V allelic variation significantly associated with the cyclophosphamide treatment-dependent disease-remissions. At the same time the GSH content of the erythrocytes in the patients with I105V allelic variation did not change. It appears that the individuals carrying the Ile105Val SNP in at least one copy had a significantly higher response rate to the treatment. Since this variant of GSTP1 can be characterized by lower conjugation capacity that results in an elongated and higher therapeutic dose of cyclophosphamide, our data suggest that the decreased activity of this variant of GSTP1 can be in the background of the more effective disease treatment.

Gene-environment interactions between GSTs polymorphisms and targeted epigenetic alterations in hepatocellular carcinoma following organochlorine pesticides (OCPs) exposure

Exposure to environmental pollutant organochlorine pesticides (OCPs) and the role of tumour suppressor GSTs gene polymorphisms as well as epigenetic alterations have all been well reported in hepatocarcinogenesis. However, the interplay between environmental risk factors and polymorphic tumour suppressor genes or epigenetic factors in hepatocellular carcinoma (HCC) development remains ambiguous. Herein, we investigated the relationship of three GSTs polymorphisms (GSTT1 deletion, GSTM1 deletion, GSTP1 rs1695) as well as GSTP1 promoter region DNA methylation and HCC risk with a particular focus on the interaction with OCPs exposure among 90 HCC cases and 99 controls in a Chinese population. Serum samples were analysed for OCPs exposure employing gas chromatography coupled with mass selective detector (GC-MS). GSTs polymorphisms and epigenetic alterations were determined using high-resolution melting PCR (HRM PCR) and DNA sequencing. After adjusting for confounders (HBV infection, smoking, alcohol consumption, BMI, age, gender), OCPs exposure and GSTP1 methylation is significantly associated with elevated risk of HCC, while no significance is observed for GSTs polymorphisms. Moreover, the effects of OCPs exposure on HCC risk are more pronounced amongst GSTP1 (Ile/Val + Val/Val) and GSTP1 promoter methylation subjects than those who were GSTP1 (Ile/Ile) and unmethylated subjects. The interactions between OCPs exposure and GSTP1 genotype as well as GSTP1 epigenetic status are statistically significant. The current study demonstrates the importance of gene-environment interactions in the multifactorial development of HCC.