Abstract
Genetic polymorphisms in cytotoxic T-lymphocyte-associated protein 4 gene (CTLA-4) vary by ethnic background, necessitating population-specific studies. The aim of this study was to assess the association between the CTLA-4 +6230G>A polymorphism, serum CTLA-4 level, and hepatocellular carcinoma (HCC) in Batak patients with chronic hepatitis B, a group with high hepatitis B virus (HBV) endemicity. A case-control study was conducted among cases (Batak patients with chronic hepatitis B and HCC) and controls (chronic hepatitis B without HCC). Genotyping of the CTLA-4 +6230G>A polymorphism was performed using the TaqMan SNP Genotyping Assay. Serum CTLA-4 level was quantified using enzyme-linked immunosorbent assay (ELISA). Patient’s demographic, clinical and laboratory data were recorded and assessed including age, sex, body mass index (BMI), smoking history, cirrhosis status, HBV DNA level, liver function markers (aspartate aminotransferase (AST) and alanine aminotransferase (ALT)), hepatitis B e-antigen (HBeAg) status, smoking history, and alcohol consumption. This study found that G allele was significantly associated with an increased risk of HCC (OR: 2.69; 95%CI: 1.21–6.00; p=0.013). Individuals with GG/AG genotypes had a 2.89-fold higher risk of developing HCC compared to those with the AA genotype (p=0.032). Serum CTLA-4 level was significantly elevated in G allele carriers (GG: 159.9±57.1 pg/mL vs AA: 83.7±44.7 pg/mL; p<0.001). Multivariate analysis identified cirrhosis as the strongest predictor of HCC (OR: 7.60; p<0.001), followed by elevated ALT (OR: 3.42; p=0.018) and high HBV DNA levels (OR: 2.31; p=0.024). In conclusion, the CTLA-4 +6230G>A GG/AG genotype and elevated serum CTLA-4 level were significantly associated with an increased risk of HCC in Batak individuals with chronic HBV infection. Further research is needed to explore additional CTLA-4 polymorphisms and immune regulatory mechanisms in HBV-related HCC to improve risk stratification and therapeutic strategies.
Keywords: Chronic liver disease, hepatocarcinogenesis, genetic polymorphism, CTLA-4 gene, rs3087243
Introduction
Hepatitis B remains a major global health concern. According to a 2019 WHO report, the global chronic infection rate is estimated at 4%, with complications such as liver cirrhosis and hepatocellular carcinoma (HCC) contributing to a 0.3% mortality rate [1]. In 2020, HCC accounted for 900,000 new cases and 830,000 deaths worldwide, with the highest burden observed in East Asia, North Africa, and Southeast Asia. The incidence and mortality of HCC are projected to rise by 55% in 2040 [2]. Currently, HCC ranks among the three leading causes of cancer-related mortality in 46 countries and is among the top five in 90 countries [2]. Indonesia has one of the highest hepatitis B endemicity rate in Southeast Asia with hepatitis B surface antigen (HBsAg) prevalence of 7.1%, corresponding to approximately 18 million cases, with 20–30% of affected individuals at risk of progressing to liver cirrhosis or HCC [3]. HCC is the fourth most common cancer among men in Indonesia, with an incidence of 13.4 per 100,000 population [3]. Chronic hepatitis B remains the primary etiology, responsible for 67% of cases treated at Indonesian national referral hospitals [3]. However, survival outcomes remain poor due to late-stage diagnosis, with a median survival of 138 days and a one-year survival rate of 29.4% [4].
The development of HCC is influenced by viral, biochemical, and host-related factors, with hepatitis B virus (HBV) DNA levels and alanine aminotransferase (ALT) serving as key risk predictors [5,6]. Host factors, including age, sex, obesity, smoking, alcohol consumption, and cirrhosis, contribute to disease progression [7]. In males, androgen-mediated enhancement of viral replication and inflammation increases susceptibility to chronic hepatitis and cirrhosis [8]. Aging further promotes HCC development through the accumulation of oxidative stress over time [9]. Additionally, lifestyle factors such as obesity, alcohol consumption, and smoking exacerbate oxidative stress, further driving hepatocarcinogenesis [10-12].
Genetic factors are increasingly recognized as contributors to HCC risk. Polymorphisms in immune-regulating genes, particularly cytotoxic T-lymphocyte-associated protein 4 gene (CTLA-4), play a crucial role in tumor immunity. CTLA-4, an immune checkpoint molecule, functions as a negative regulator of T-cell activation [13]. Single nucleotide polymorphisms (SNPs) in CTLA-4 can alter its expression and functionality, thereby influencing immune responses [14]. The +6230G>A (rs3087243) polymorphism in the 3′-untranslated region (3′-UTR) modulates mRNA stability and soluble CTLA-4 expression, impacting T-cell activity [15-18]. Furthermore, the +6230A allele has been associated with increased susceptibility to HBV progression and persistence, potentially due to its role in immune regulation [14].
CTLA-4 polymorphisms have been implicated in various immune-related conditions, including autoimmune diseases such as autoimmune hepatitis, type 1 diabetes, and systemic lupus erythematosus, as well as chronic viral infections, including HBV and hepatitis C virus (HCV) [14,19-21]. However, a previous meta-analysis found no statistically significant association between CTLA-4 polymorphisms and HCC risk, suggesting a limited role in hepatocarcinogenesis [22]. Given that CTLA-4 genetic polymorphisms may vary by ethnic background, population-specific studies are warranted to better understand their relevance in different genetic backgrounds. While the +6230G>A variant has been investigated in the context of HBV infection, previous studies have not accounted for ethnic variability, despite known regional differences in genetic associations [14,23]. This highlighted the need for population-specific research to elucidate the role of +6230G>A in disease progression. The aim of this study was to assess the association between the CTLA-4 +6230G>A polymorphism, serum CTLA-4 levels, and HCC occurrence in Batak patients with chronic hepatitis B. As one of the largest ethnic groups in Medan, the Batak population provides a distinct genetic background for investigating HCC susceptibility. The findings from this study may contribute to improved early detection and risk stratification, ultimately enhancing clinical outcomes.
Methods
Study design and settings
A case-control study was conducted from in 2024 across six hospitals in Medan, Indonesia: Prof. Dr. Chairuddin P. Lubis Hospital, Mitra Medika Premiere Hospital, Mitra Medika Amplas Hospital, Mitra Medika Bandar Klippa Hospital, Mitra Medika Tanjung Mulia Hospital, and Wulan Windy Hospital. Eligible patients were identified from hepatology outpatient clinics and medical records based on a confirmed diagnosis of chronic hepatitis B. Patients were categorized into case and control groups based on predefined HCC diagnostic criteria. Clinical data, including HCC status, laboratory findings, and patient characteristics, were recorded including age, sex, body mass index (BMI), smoking history, cirrhosis status, HBV DNA levels, liver function markers such as aspartate aminotransferase (AST) and alanine aminotransferase (ALT), hepatitis B e-antigen (HBeAg) status, smoking history, and alcohol consumption. Blood samples were collected for CTLA-4 +6230G>A genotyping and serum CTLA-4 measurement, with laboratory analyses conducted at Research Laboratory of Universitas Sumatera Utara, Medan, Indonesia. Genotyping of the CTLA-4 +6230G>A polymorphism was performed using the TaqMan SNP Genotyping Assay to determine the genotypes (GG, GA, and AA). Serum CTLA-4 levels were quantified via enzyme-linked immunosorbent assay (ELISA) to assess immunoregulatory differences.
Eligibility criteria
Inclusion criteria required patients to be at least 18 years old with a confirmed diagnosis of chronic hepatitis B, with or without HCC. Ethnicity was verified through documented lineage, requiring both paternal and maternal ancestry from the Batak ethnic group, specifically from one of six subgroups: Angkola, Karo, Mandailing, Pakpak-Dairi, Simalungun, or Toba. This verification was further supported by confirmation of the Batak clan name (Marga), a widely recognized marker of Batak descent. Exclusion criteria included recent use of immunomodulatory or immunosuppressive drugs within the past month and coexisting diagnoses of human immunodeficiency virus (HIV) infection, hepatitis C, chronic kidney disease, autoimmune disease, or other malignancies. Pregnant patients were also excluded.
Sample and sampling methods
Sample size calculation was performed using the Cochrane formula, referencing a prior study on CTLA-4 polymorphisms in patients with chronic hepatitis B—indicated that 51% of patients with HCC carried the GG+GA genotype, compared to 17% of those without HCC [24]. To achieve 90% power with a 5% alpha error, a minimum of 39 patients per group was required, yielding a total sample size of at least 78 patients. A consecutive sampling technique was applied, in which all eligible participants who met the inclusion and exclusion criteria were recruited consecutively until the target sample size was obtained. Cases comprised Batak patients with chronic hepatitis B and HCC, while controls were Batak patients with chronic hepatitis B without HCC. Controls were selected from the same population and recruitment period as cases, ensuring comparability while allowing for an unbiased evaluation of the association between the CTLA-4 +6230G>A polymorphism, serum CTLA-4 levels, and HCC.
Diagnosis of chronic hepatitis B and hepatocellular carcinoma
Patients were diagnosed with chronic hepatitis B and HCC based on clinical, serological, and imaging criteria in accordance with the Indonesian Ministry of Health’s Guidelines for Adult Hepatocellular Carcinoma Management (HK.01.07/MENKES/1355/2022) [4] and international standards including the American Association for the Study of Liver Diseases (AASLD) [24] and European Association for the Study of the Liver (EASL) guidelines [25]. Chronic hepatitis B was confirmed by the persistence of HBsAg for ≥6 months. HCC diagnosis was established through triphasic liver computed tomography (CT) scan, characterized by arterial phase hyperenhancement with washout in the venous or delayed phase, supplemented by elevated serum alpha-fetoprotein (AFP) or protein induced by vitamin K absence-II (PIVKA-II) levels.
Demographic, clinical and laboratory assessments
Clinical assessments included structured interviews, physical examinations, and laboratory testing. Paper sheets were used to collect demographic and clinical data, including age, sex, BMI, smoking history, cirrhosis status, HBV DNA levels, liver function markers, specifically AST and ALT, HBeAg status, smoking history, and alcohol consumption. BMI was calculated using measured height and weight, with obesity defined as a BMI >25 kg/m2 according to Asia-Pacific criteria [10]. Alcohol consumption was defined as any history of alcohol intake, with quantification based on daily alcohol consumption (grams) multiplied by the duration of alcohol use (years). Alcohol consumption was categorized as never, light (<24 grams/year), moderate, or heavy (>24 grams/year). Smoking history was assessed using the Brinkman Index, calculated as the number of cigarettes smoked per day multiplied by the duration of smoking (years). Smoking status was classified as light (0–199), moderate (200–599), or heavy (≥600).
Abdominal ultrasonography was performed to evaluate liver cirrhosis status, with cirrhosis defined by the presence of ≥2 major imaging features (irregular liver surface, heterogeneous parenchyma, or reduced liver size) and ≥1 sign of portal hypertension (splenomegaly or ascites). Non-cirrhotic cases had either normal liver architecture or isolated abnormalities without concomitant signs of portal hypertension [9,11].
Liver function markers were evaluated using standard biochemical analyzers. AST, an enzyme predominantly found in the liver, heart, and muscles, was categorized as high (>98 IU/L) or low (<98 IU/L). ALT, a key enzyme for assessing hepatocellular injury, was classified as high (>90 IU/L) or low (<90 IU/L). HBV DNA levels were measured via real-time polymerase chain reaction (RT-PCR) and categorized as high (>6.4 log10 IU/mL) or low (<6.4 log10 IU/mL). HBeAg status, determined using ELISA, was classified as reactive or non-reactive.
Blood sample collection and processing
Venous blood samples (5 mL) were collected into EDTA vacutainer for genetic analysis and serum separation tube for CTLA-4 +6230G>A polymorphism and serum CTLA-4 level measurements. Samples were inverted 10 times for homogenization before centrifugation at 3000 rpm for 15 minutes. Plasma was stored at -70°C for DNA extraction, while serum was stored at -20°C for ELISA analysis. Upon completion of sample collection, specimens were transported on dry ice to the Research Laboratory of Universitas Sumatera Utara, Medan, Indonesia, for further analysis.
Genotyping of CTLA-4 +6230G>A polymorphism
DNA extraction was conducted at the Research Laboratory of Universitas Sumatera Utara, using COBAS DNA Sample Preparation Kit (Roche Applied Science, Penzberg, Germany) following the manufacturer’s protocol. Spectrophotometric quantification was performed using a Nanodrop 2000 at 260/280 nm (Thermo Fisher Scientific, Waltham, MA, USA) to assess DNA concentration and purity before proceeding with genotyping.
Genotyping of the CTLA-4 +6230G>A polymorphism was performed using the TaqMan SNP Genotyping Assay (Applied Biosystems, Foster City, CA, USA). The PCR amplification was performed on a C1000 Thermal Cycler CFX96 Real-Time System (Bio-Rad, Hercules, CA, USA). The reaction mixture had a total volume of 25 µL, comprising 2X TaqMan GTXpress Master Mix (Applied Biosystems, Foster City, CA, USA), allele-specific TaqMan probes and primers [26], 50 ng of extracted genomic DNA, and nuclease-free water. The amplification process included an initial step at 95°C for 10 minutes, followed by 40 cycles of denaturation at 92°C for 15 seconds and annealing/extension at 60°C for 1 minute. Allelic discrimination was based on real-time fluorescence data, which was analyzed using StepOnePlus Software (Applied Biosystems, Foster City, CA, USA). The fluorescence signals emitted by the TaqMan probes allowed for differentiation among the GG, GA, and AA genotypes. Each sample underwent genotyping once according to the standardized protocol, without duplicate testing.
Measurement of serum CTLA-4 levels
Serum CTLA-4 levels were quantified using the Quantikine ELISA Human CTLA-4 Immunoassay (R&D Systems, Minneapolis, MN, USA), a sandwich ELISA designed for high specificity and sensitivity. A total of 100 µL of serum samples and standards were tested using antibody-coated 96-well microplates. Absorbance was measured at 450 nm with a reference wavelength of 540 nm using a microplate reader (Multiskan Go, Thermo Fisher Scientific, Waltham, MA, USA). Serum CTLA-4 concentrations were calculated by interpolating absorbance values from a standard curve generated using known concentrations of recombinant CTLA-4. Serum CTLA-4 levels were categorized as low or high based on the median value.
Statistical analysis
The Kolmogorov-Smirnov test was used to assess data normality, while the Hardy-Weinberg equilibrium test evaluated the genotypic distribution of the CTLA-4 +6230G>A polymorphism in the study population. Differences in genotype and allele frequencies between case and control groups were analyzed using the Chi-squared test. Logistic regression was performed to determine the association between the CTLA-4 +6230G>A polymorphism and HCC risk, adjusting for confounding variables such as age, cirrhosis status, HBV DNA level, and liver function markers. Results were presented as odds ratio (OR) and 95% confidence intervals (95%CI). Serum CTLA-4 levels were compared among genotypes using one-way ANOVA with least significant difference (LSD) post hoc analysis, while differences between HCC and non-HCC groups were assessed using independent Student t-tests. Multivariate logistic regression was conducted to evaluate the independent effects of the CTLA-4 +6230G>A polymorphism on HCC risk, incorporating significant covariates. Additionally, a two-way ANOVA was performed to examine interactions between the CTLA-4 +6230G>A polymorphism, serum CTLA-4 levels, and HCC status. Statistical analyses were conducted using SPSS v.26 (IBM, New York, USA), with p<0.05 considered statistically significant.
Results
Patient selections
Patient selection was conducted among individuals aged over 18 years with hepatitis B between 2020 and 2024 (Figure 1). Initially, 660 patients were identified, comprising 102 with HCC and 558 without HCC. Exclusion criteria were applied sequentially, resulting in the removal of patients with incomplete clinical data, leading to the exclusion of 14 patients with HCC and 37 without HCC. Further exclusions were made for patients diagnosed with other malignancies (6 with HCC, 25 without HCC), as well as those with HIV, hepatitis C, or chronic kidney disease (CKD) (3 with HCC, 36 without HCC). Additionally, 29 patients with HCC were excluded due to an inability to be contacted for blood collection for CTLA-4 polymorphism testing or having passed away. Finally, the final study sample consisted of 100 patients, including 50 with HCC and the first 50 patients without HCC whose blood samples were collected consecutively (Figure 1).
Figure 1.
Flowchart of patient selection. CKD: chronic kidney disease; HIV: human immunodeficiency virus; HCC: hepatocellular carcinoma.
Characteristics of patients
The characteristics of patients within case and control groups are presented in Table 1. Among the 100 patients included in the study, 56% were male and 44% were female, with a higher proportion of males in the HCC group (66%) compared to the control group (46%) (Table 1). The mean age of the patients was 55±9.94 years, and a greater proportion of those aged >55 years was observed in the HCC group (62%) compared to controls (40%). Obesity was present in 36% of the total cohort, with a lower prevalence in the HCC group (28%) than in the control group (44%). Liver function markers were elevated in a greater proportion of HCC patients. The median AST level was higher in the HCC group (115 IU/L, range: 42–214) compared to controls (97.5 IU/L, range: 42–527), with elevated AST levels observed in 58% of HCC cases and 50% of controls. Similarly, the median ALT level was higher in HCC patients (113 IU/L, range: 31–230) than in controls (88 IU/L, range: 24–230), with high ALT levels found in 60% of HCC cases compared to 40% of controls. HBV DNA levels were also higher among HCC patients, with a median viral load of 6.60 log10 IU/mL (range: 4.40–8.10) compared to 6.00 log10 IU/mL (range: 1.60–7.90) in controls. High HBV DNA levels (>6.4 log10 IU/mL) were detected in 64% of HCC cases and 42% of controls. HBeAg reactivity was observed in 48% of HCC cases and 36% of controls. Cirrhosis was more prevalent among HCC patients, with 78% having liver cirrhosis compared to 32% in the control group. Serum CTLA-4 levels were also higher in the HCC group, with a median concentration of 105.90 pg/mL (range: 39.60–259.20) compared to 56 pg/mL (range: 36–264) in controls. High serum CTLA-4 levels were found in 62% of HCC cases compared to 40% of controls (Table 1).
Table 1.
Characteristics of Batak patients with chronic hepatitis included in the study (n=100)
| Variable | Total | Case (n=50) | Control (n=50) |
|---|---|---|---|
| n (%) | n (%) | n (%) | |
| Sex | |||
| Male | 56 (56) | 33 (66) | 23 (46) |
| Female | 44 (44) | 17 (34) | 27 (54) |
| Age (years), mean±SD | 55 ±9.94 | ||
| >55 | 51 (51) | 31 (62) | 20 (40) |
| ≤55 | 49 (49) | 19 (38) | 30 (60) |
| Obesity status | |||
| Yes | 36 (36) | 14 (28) | 22 (44) |
| No | 64 (64) | 36 (72) | 28 (56) |
| Alcohol consumption | |||
| Moderate + heavy | 20 (20) | 13 (26) | 7 (14) |
| Light/none | 80(80) | 37 (74) | 43 (86) |
| Smoking status | |||
| Moderate + heavy | 34 (34) | 16 (32) | 18 (36) |
| Light/none | 66 (66) | 34 (68) | 32 (64) |
| AST levels (IU/L), median (min-max) | 98 (42–527) | 115 (42–214) | 97.50 (42–527) |
| High | 54 (54) | 29 (58) | 25 (50) |
| Normal | 46 (46) | 21 (42) | 25 (50) |
| ALT levels (IU/L), median (min-max) | 90 (24–230) | 113 (31–230) | 88 (24–230) |
| High | 50 (50) | 30 (60) | 20 (40) |
| Normal | 50 (50) | 20 (40) | 30 (60) |
| HBV DNA levels (log10 lU/mL), median (min-max) | 6.40 (1.60–8.10) | 6.60 (4.40–8.10) | 6.00 (1.60–7.90) |
| High | 53 (53) | 32 (64) | 21 (42) |
| Normal | 47 (47) | 18 (36) | 29 (58) |
| HBeAg status | |||
| Reactive | 42 (42) | 24 (48) | 18 (36) |
| Non-reactive | 58 (58) | 26 (52) | 32 (64) |
| Liver cirrhosis status | |||
| Yes | 55 (55) | 39 (78) | 16 (32) |
| No | 45 (45) | 11 (22) | 34 (68) |
| Serum CTLA-4 levels (pg/mL), median (min-max) | 90 (36–264) | 105.90 (39.60–259.20) | 56 (36–264) |
| High | 51 (51) | 31 (62) | 20 (40) |
| Low | 49 (49) | 19 (38) | 30 (60) |
ALT: alanine transaminase; AST: aspartate aminotransferase; CTLA-4: cytotoxic T-lymphocyte-associated protein 4; DNA: deoxyribonucleic acid; HBeAg: hepatitis B e-antigen; HBV: hepatitis B virus; HCC: hepatocellular carcinoma
CTLA-4 +6230G>A genotypic and allelic distribution in Batak patients with chronic hepatitis B
CTLA-4 +6230G>A polymorphism was analyzed in patients with chronic hepatitis B and the genotypic distribution showed AA as the predominant genotype (77%), followed by AG (13%) and GG (10%) (Table 2). Allele frequency analysis indicated that A allele was predominant, accounting for 83.5%, while the G allele was present in 16.5% of the included patients. In the dominant genetic model (GG + AG vs AA), 23% of patients carried at least one G allele (GG or AG), whereas 77% had the AA genotype. In the recessive model (GG vs AG + AA), only 10% of patients had the GG genotype, while 90% carried at least one A allele.
Table 2.
Distribution of CTLA-4 +6230G>A genotypic and allelic distribution in Batak patients with chronic hepatitis B
| Polymorphism CTLA-4 +6230G>A | Frequency (%) |
|---|---|
| Genotype | |
| Genotype GG | 10 (10.0) |
| Genotype AG | 13 (13.0) |
| Genotype AA | 77 (77.0) |
| Allele | |
| Allele G | 33 (16.5) |
| Allele A | 167 (83.5) |
| Dominant model | |
| GG + AG | 23 (23.0) |
| AA | 77 (77.0) |
| Recessive model | |
| GG | 10 (10.0) |
| AG + AA | 90 (90.0) |
CTLA-4: cytotoxic T-lymphocyte-associated protein 4
Hardy-Weinberg equilibrium for the CTLA-4 +6230G>A polymorphism was assessed in both cases and controls. In the case group, the observed genotype frequencies did not deviate from the expected distribution (p=0.987), indicating equilibrium. Similarly, the control group remained in equilibrium (p=0.879) (Table 3). These results confirmed that the genotypic frequencies of CTLA-4 +6230G>A polymorphism in both groups were in Hardy-Weinberg equilibrium (p>0.05).
Table 3.
Hardy-Weinberg equilibrium analysis for CTLA-4 +6230G>A polymorphism in case and control groups
| CTLA-4 +6230G>A polymorphism | Observed (O) | Expected (E) | χ2 | p-valuea |
|---|---|---|---|---|
| Case group (n=50) | ||||
| Genotype GG (n=7) | 19 | 19.38 | 0.0263 | 0.987 |
| Genotype AG (n=9) | 46 | 45.23 | ||
| Genotype AA (n=34) | 26 | 26.38 | ||
| Control group (n=50) | ||||
| Genotype GG (n=3) | 12 | 10.90 | 0.2578 | 0.879 |
| Genotype AG (n=4) | 39 | 41.19 | ||
| Genotype AA (n=43) | 40 | 38.90 |
Analyzed using Chi-squared test
CTLA-4: cytotoxic T-lymphocyte-associated protein 4
Association between demographic and laboratory factors with hepatocellular carcinoma in Batak patients with chronic hepatitis B
The analysis identified significant associations between sex, older age, high ALT levels, high HBV DNA levels, liver cirrhosis, and high CTLA-4 levels with HCC presence (p<0.05) (Table 4). Males had a 2.28-fold increased risk of HCC (p=0.044), while older age was associated with a 2.45-fold higher risk (p=0.028). High ALT levels associated with a 2.25-fold increased risk (p=0.046), whereas high HBV DNA levels were associated with a 2.46-fold greater likelihood of HCC (p=0.028). Liver cirrhosis represented the most significant risk factor, increasing the likelihood of HCC by 7.53 times (p<0.001). Moreover, high serum CTLA-4 levels were associated with a 2.45-fold elevated risk of HCC (p=0.028).
Table 4.
Univariate analysis showing the associations between demographic and clinical characteristics with hepatocellular carcinoma in Batak patients with chronic hepatitis B
| Variables | HCC, n (%) | OR (95%CI) | p-valuea | |
|---|---|---|---|---|
| Case (n=50) | Control (n=50) | |||
| Sex | ||||
| Male | 33 (66) | 23 (46) | 2.28 (1.02–5.11) | 0.044* |
| Female | 17 (34) | 27 (54) | ||
| Age (years) | ||||
| >55 | 31(62) | 20 (40) | 2.45 (1.10–5.47) | 0.028* |
| ≤55 | 19 (38) | 30 (60) | ||
| Obesity status | ||||
| Yes | 14 (28) | 22 (44) | 0.50 (0.22–1.14) | 0.096 |
| No | 36 (72) | 28 (56) | ||
| Alcohol consumption | ||||
| Moderate + heavy | 13 (26) | 7 (14) | 2.16 (0.78–5.98) | 0.134 |
| Light/none | 37 (74) | 43 (86) | ||
| Smoking status | ||||
| Moderate + heavy | 16 (32) | 18 (36) | 0.84 (0.37–1.92) | 0.673 |
| Light/none | 34 (68) | 32 (64) | ||
| AST levels (IU/L) | ||||
| High | 29 (58) | 25 (50) | 1.38 (0.63–3.04) | 0.422 |
| Low | 21 (42) | 25 (50) | ||
| ALT levels (IU/L) | ||||
| High | 30 (60) | 20 (40) | 2.25 (1.01–5.00) | 0.046* |
| Low | 20 (40) | 30 (60) | ||
| HBV DNA levels | ||||
| High | 32 (64) | 21 (42) | 2.46 (1.10–5.49) | 0.028* |
| Low | 18 (36) | 29 (58) | ||
| HBeAg status | ||||
| Reactive | 24 (48) | 18 (36) | 1.64 (0.74–3.66) | 0.224 |
| Non-reactive | 26 (52) | 32 (64) | ||
| Liver cirrhosis | ||||
| Yes | 39 (78) | 16 (32) | 7.53 (3.08–18.44) | <0.001** |
| No | 11 (22) | 34 (68) | ||
| Serum CTLA-4 levels | ||||
| High | 31 (62) | 20 (40) | 2.45 (1.10–5.47) | 0.028* |
| Low | 19 (38) | 30 (60) |
ALT: alanine transaminase; AST: aspartate aminotransferase; CI: confidence interval; CTLA-4: cytotoxic T-lymphocyte-associated protein 4; DNA: deoxyribonucleic acid; HBeAg: hepatitis B e-antigen; HBV: hepatitis B virus; HCC: hepatocellular carcinoma; OR: odds ratio
Analyzed using logistic regression
Statistically significant at p<0.05
Statistically significant at p<0.01
Association between CTLA-4 +6230G>A polymorphism and hepatocellular carcinoma in Batak patients with chronic hepatitis B
The association between the CTLA-4 +6230G>A polymorphism and HCC was evaluated. A significant association was identified between the combined GG+AG genotypes and HCC, with these genotypes conferring a 2.89-fold increased risk compared to the AA genotype (p=0.032) (Table 5). Furthermore, the presence of the G allele was associated with a 2.69-fold higher risk of HCC compared to the A allele (p=0.013).
Table 5.
Association between CTLA-4 +6230G>A polymorphism and hepatocellular carcinoma in Batak patients with chronic hepatitis B
| CTLA-4 +6230G>A polymorphism | Case, n (%) | Control, n (%) | OR (95%CI) | p-value |
|---|---|---|---|---|
| Genotype | ||||
| GG | 7 (14) | 3 (6) | 2.55 (0.59–10.86) | 0.102a |
| AG | 9 (18) | 4 (8) | 2.52 (0.81–10.04) | 0.094a |
| AA (Reference group) | 34 (68) | 43 (86) | ||
| GG + AG | 16 (32) | 7 (14) | 2.89 (1.07–7.82) | 0.032a* |
| Allele | ||||
| G | 23 (23) | 10 (10) | 2.69 (1.21–6.00) | 0.013b* |
| A (Reference group) | 77 (77) | 90 (90) |
CI: confidence interval; CTLA-4: cytotoxic T-lymphocyte-associated protein 4; OR: odds ratio
Analyzed using logistic regression
Analyzed using Chi-squared test
Statistically significant at p<0.05
Multivariate logistic regression analysis of hepatocellular carcinoma risk factors in Batak patients with chronic hepatitis B
Seven variables identified in the univariate analysis—sex, age, ALT level, HBV DNA level, liver cirrhosis, serum CTLA-4 level, and CTLA-4 +6230G>A polymorphism—were included in a multivariate logistic regression model with HCC as the dependent variable. Liver cirrhosis emerged as the strongest predictor of HCC, increasing the risk by 7.6 times (p<0.001) (Table 6). High ALT level was associated with a 3.42-fold increased risk (p=0.018), while high HBV DNA level associated with a 2.31-fold higher likelihood of HCC (p=0.024). High CTLA-4 level and older age also demonstrated significant associations, with ORs of 2.16 (p=0.040) and 1.65 (p=0.043), respectively. The presence of the G allele in the CTLA-4 +6230G>A polymorphism was associated with a 1.45-fold increased risk of HCC (p=0.046). Sex did not have a significant association with HCC in the multivariate analysis (p>0.05). The Nagelkerke R-squared value was 0.627, indicating that the model explained 62.7% of the variability in HCC risk, with the remaining 37.3% attributable to other factors not included in the model.
Table 6.
Multivariate logistic regression analysis of factors associated with hepatocellular carcinoma in Batak patients with chronic hepatitis B
| Variables | β | OR (95%CI) | p-valuea |
|---|---|---|---|
| Liver cirrhosis | 6.687 | 7.597 (1.53–8.66) | <0.001** |
| High ALT levels | 3.310 | 3.420 (1.08–4.38) | 0.018* |
| High HBV DNA levels | 2.140 | 2.310 (1.05–3.62) | 0.024* |
| High CTLA-4 levels | 1.962 | 2.162 (1.04–3.56) | 0.040* |
| Age >55 years | 1.511 | 1.65 (1.04–3.20) | 0.043* |
| Allele G CTLA-4 +6230G>A polymorphism | 1.206 | 1.45 (1.02–3.08) | 0.046* |
| Male | 1.180 | 1.24 (0.87–2.44) | 0.108 |
ALT: alanine transaminase; CI: confidence interval; CTLA-4: cytotoxic T-lymphocyte-associated protein 4;
DNA: deoxyribonucleic acid; HBV: hepatitis B virus; OR: odds ratio
Analyzed using multivariate logistic regression
Statistically significant at p<0.05
Statistically significant at p<0.01
Association between CTLA-4 +6230G>A polymorphism and serum CTLA-4 levels in Batak patients with chronic hepatitis B
The association between the CTLA-4 +6230G>A polymorphism and serum CTLA-4 levels was also analyzed. Significant differences in serum CTLA-4 level was observed among genotypes (p<0.001), with the GG and AG genotypes showing higher levels compared to the AA genotype (Table 7). Additionally, the presence of the G allele was associated with significantly high CTLA-4 level compared to the A allele (p<0.001).
Table 7.
Association between serum CTLA-4 levels and CTLA-4 +6230G>A genotypes and alleles in Batak patients with chronic hepatitis B
| CTLA-4 +6230G>A polymorphism | Serum CTLA-4 levels (pg/mL), mean±SD | p-value |
|---|---|---|
| Genotype | ||
| Genotype GG | 159.86±57.10# | <0.001*a |
| Genotype AG | 147.24±70.99# | |
| Genotype AA | 83.66±44.72 | |
| Allele | ||
| Allele G | 154.89±61.34 | <0.001*b |
| Allele A | 88.61±49.88 |
CTLA-4: cytotoxic T-lymphocyte-associated protein 4; SD: standard deviation.
Analyzed using two-way ANOVA
Analyzed using independent Student t-test
Statistically significant at p<0.001
Significant compared to AA genotype
Discussion
Chronic hepatitis B posed a significant global health burden, particularly in Indonesia, due to its association with severe complications such as HCC. This study, which focused on the Batak ethnic group, investigated the association between the CTLA-4 +6230G>A polymorphism and its impact on serum CTLA-4 levels. The findings demonstrated that individuals carrying the G allele (GG and AG genotypes) had significantly higher serum CTLA-4 levels compared to those with the AA genotype. These results suggested that the G allele may have contributed to enhanced CTLA-4 expression, potentially influencing immune regulation in patients with chronic hepatitis B.
The CTLA-4 +6230G>A polymorphism, located in the 3′-UTR of the CTLA-4 gene, has been implicated in the regulation of mRNA stability and splicing efficiency [26,27]. Functional studies have demonstrated that variations in the 3′-UTR can influence the balance between membrane-bound and soluble forms of CTLA-4, thereby modulating its inhibitory effects on T-cell activation [27-29]. Specifically, the G allele has been associated with increased production of soluble CTLA-4, which enhances immune suppression by competitively binding to B7 ligands on antigen-presenting cells, thereby blocking the co-stimulatory signals required for full T-cell activation [28]. This competitive inhibition compromises T-cell activation, leading to immune exhaustion, impaired clearance of HBV-infected hepatocytes, and sustained viral replication [28,30,31]. Consequently, persistent HBV infection, coupled with chronic immune dysfunction, contributes to progressive hepatic injury, fibrosis, and hepatocarcinogenesis [32,33].
In the Batak population, high CTLA-4 expression level associated with the G allele was associated with an increased risk of HCC. This association highlights the pivotal role of CTLA-4 in regulating immune responses against HBV. Increased serum CTLA-4 levels have been shown to impair T-cell function, reduce cytokine production, and diminish cytotoxic activity— mechanisms essential for effective viral clearance and hepatocyte protection [30,31]. As a result, increased CTLA-4 expression may contribute to accelerated disease progression and an increased risk of HCC development in individuals with chronic hepatitis B.
A study conducted in Han Chinese individuals identified an association between the CTLA-4 +6230G/A polymorphism and HBV persistence as well as HCC susceptibility, indicating that individuals carrying the A allele had a higher susceptibility to HBV-related liver cirrhosis and HCC, whereas the G allele was associated with HBV clearance [14]. These results contrasted with the present study, in which the G allele was associated with high serum CTLA-4 levels and an increased risk of HCC. This discrepancy may be attributed to genetic differences between the Han Chinese and Batak populations. The Batak ethnic group possesses a distinct ancestry and immune response profile, which may influence the functional impact of CTLA-4 polymorphisms. Genetic studies have demonstrated that allele frequencies of immune-regulatory genes vary across ethnic groups, potentially contributing to differences in disease susceptibility and progression [34,35]. The mechanistic differences between these findings and those from the Chinese cohort may be explained by population-specific variations in linkage disequilibrium patterns and haplotype structures of the CTLA-4 gene [36]. CTLA-4 polymorphisms formed haplotypes that influenced immune responses, with the C-A-A and T-A-G haplotypes conferring an increased risk for HBV progression and persistence [14]. Although the present study did not conduct haplotype analysis, it remains possible that distinct CTLA-4 haplotypes exist in the Batak population, resulting in different associations with chronic hepatitis B and HCC risk.
The Batak population may possess distinct genetic characteristics that contribute to the observed findings. Previous studies have indicated that Indonesian populations had a higher frequency of pro-inflammatory alleles in immune-related genes, including those involved in human leukocyte antigen (HLA) and cytokine signaling [37,38]. This predisposition to increased immune activation may lead to a more pronounced inflammatory response to HBV infection, promoting hepatic fibrosis and accelerating progression to HCC [6,8,31]. Such a mechanism may partially explain why individuals of Batak ethnicity with the GG genotype in CTLA-4-1661G>A demonstrated a stronger association with HCC risk compared to other populations. Additionally, the predominant HBV genotypes in Indonesia are B and C, with genotype B being the most prevalent [39,40]. Notably, HBV genotype C has been independently associated with an increased risk of HCC compared to genotype B [39]. The distribution of viral genotypes suggests that Batak individuals may experience a more aggressive course of chronic HBV infection, potentially amplifying the oncogenic impact of CTLA-4 polymorphisms.
Cirrhosis emerged as the strongest independent predictor of HCC, increasing risk more than sevenfold, likely due to its pro-inflammatory and fibrotic microenvironment, which promotes oxidative stress, genomic instability, and aberrant cellular signaling [6,12,41]. High HBV DNA levels further exacerbated this risk by enhancing viral replication, facilitating immune evasion, and integrating viral DNA into the host genome—key processes in HBV-induced hepatocarcinogenesis [6,41]. Age also demonstrated a significant association, with individuals over 55 years exhibiting a higher risk, potentially due to cumulative inflammation, immune senescence, and prolonged HBV exposure [42]. Although male sex was associated with HCC in univariate analysis, it lost significance in multivariate analysis, possibly reflecting an indirect effect mediated through higher cirrhosis rates and other risk factors. The protective role of estrogen in modulating inflammation and enhancing viral clearance in women may further explain this difference [7]. Additionally, high ALT levels were identified as a significant predictor, reinforcing their specificity for liver injury and chronic inflammation, both of which are critical precursors to fibrosis and malignant transformation [43].
Established risk factors for liver disease, including obesity and alcohol consumption, did not show a significant association with HCC in Batak population, likely due to cultural and religious influences on dietary and lifestyle habits. Alcohol consumption remains relatively low in Indonesia, reducing its impact on liver disease at the population level [44]. Additionally, interview-based assessments may have been affected by social desirability bias, as discussing or admitting to alcohol consumption is often considered a social taboo, potentially leading to underreporting and obscuring any true associations [45].
Identifying individuals with high-risk CTLA-4 genotypes could enable early intervention strategies, such as more frequent monitoring for liver fibrosis and HCC development. Additionally, therapies targeting CTLA-4 pathways, such as immune checkpoint inhibitors, may have potential applications in chronic hepatitis B patients with high CTLA-4 expression. However, caution is needed, as excessive immune activation could lead to liver inflammation and autoimmunity. Further studies are needed to explore the therapeutic modulation of CTLA-4 in chronic hepatitis B and its potential role in antiviral and anti-cancer strategies.
Despite these insights, certain limitations should be acknowledged. The focus on a single polymorphism does not fully capture the genetic complexity of immune regulation in chronic hepatitis B. The exclusion of other genetic markers, such as HBsAg quantification and covalently closed circular DNA (cccDNA) levels, may have restricted the ability to comprehensively assess HCC risk factors. Additionally, the absence of sequencing for other CTLA-4 polymorphic sites limits the genetic scope of the study. Future research should incorporate haplotype analysis to elucidate how different CTLA-4 variants interact to influence disease progression. Studies with larger sample sizes and multi-ethnic comparisons are warranted to validate these findings and assess their generalizability beyond the Batak population. Furthermore, functional studies investigating the impact of +6230G>A on CTLA-4 mRNA stability and expression across different immune cell subsets would provide mechanistic insights into its role in HBV persistence and HCC development. A broader evaluation incorporating additional immune-related genetic markers and functional assays could enhance the understanding of the molecular mechanisms underlying HBV-induced hepatocarcinogenesis.
Conclusion
Batak patients with chronic hepatitis B carrying the CTLA-4 +6230G>A GG+AG genotype had a significantly higher risk of HCC. Elevated CTLA-4 level was also associated with an increased risk of HCC, with significantly higher levels observed in patients with the GG and AG genotypes compared to those with the AA genotype. Liver cirrhosis, elevated ALT levels, high HBV DNA levels, and older age showed significant associated with HCC. Further investigations should examine additional CTLA-4 polymorphisms, haplotype variations, HBsAg levels, and cccDNA to enhance understanding of immune regulation in HBV-induced HCC and its broader clinical implications.
Ethics approval
The study received ethical approval from the Health Research Ethics Committee of all relevant institutions in Indonesia prior to the commencement of any research activities (Approval number: 791/KEPK/USU/2024). Patients meeting the inclusion criteria provided informed consent for inclusion in the study.
Acknowledgments
None to declare.
Competing interests
All the authors declare that there are no conflicts of interest.
Funding
This study received no external funding.
Underlying data
Derived data supporting the findings of this study are available from the corresponding author on request.
Declaration of artificial intelligence use
We hereby confirm that no artificial intelligence (AI) tools or methodologies were utilized at any stage of this study, including during data collection, analysis, visualization, or manuscript preparation. All work presented in this study was conducted manually by the authors without the assistance of AI-based tools or systems.
How to cite
Darmadi D, Rey I, Lubis M, et al. CTLA-4 +6230G>A polymorphism and its impact on CTLA-4 level and risk of hepatocellular carcinoma: A case-control study in Batak patients with chronic hepatitis B. Narra J 2025; 5 (2): e1959 - http://doi.org/10.52225/narra.v5i2.1959.
References
- 1.GBD 2019 Hepatitis B Collaborators. Global, regional, and national burden of hepatitis B, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019. Lancet Gastroenterol Hepatol 2022;7(9):796–829. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Rumgay H, Arnold M, Ferlay J, et al. Global burden of primary liver cancer in 2020 and predictions to 2040. J Hepatol 2022;77:1598–606. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Kementerian Kesehatan Republik Indonesia. Riset kesehatan dasar (Riskesdas) 2013. Jakarta: Kementerian Kesehatan Republik Indonesia; 2013. [Google Scholar]
- 4.Kementerian Kesehatan Republik Indonesia. Keputusan Menteri Kesehatan Republik Indonesia nomor HK.01.07/MENKES/1355/2022 tentang pedoman nasional pelayanan kedokteran tata laksana karsinoma sel hati pada dewasa. Jakarta: Kementerian Kesehatan Republik Indonesia; 2022. [Google Scholar]
- 5.Du Y, Du B, Fang X, et al. ALT flare predicts hepatocellular carcinoma among antiviral treated patients with chronic hepatitis B: A cross-country cohort study. Front Oncol 2020;10:615203. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Tarocchi M, Polvani S, Marroncini G, Galli A. Molecular mechanism of hepatitis B virus-induced hepatocarcinogenesis. World J Gastroenterol 2014;20:11630–11640. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Klein SL. Sex influences immune responses to viruses, and efficacy of prophylaxis and treatments for viral diseases. BioEssays News Rev Mol Cell Dev Biol 2012;34:1050–1059. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Liu WC, Liu QY. Molecular mechanisms of gender disparity in hepatitis B virus-associated hepatocellular carcinoma. World J Gastroenterol 2014;20:6252–6261. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tandya R, Rakhman MF, Mustika S. Profile of chronic hepatitis B in liver and non liver malignancies at Dr. Saiful Anwar Malang General Hospital. J Ners 2023;7:467–472. [Google Scholar]
- 10.Ali Kamkar MM, Ahmad R, Alsmadi O, Behbehani K. Insight into the impact of diabetes mellitus on the increased risk of hepatocellular carcinoma: Mini-review. J Diabetes Metab Disord 2014;13:57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Petrick JL, Campbell PT, Koshiol J, et al. Tobacco, alcohol use and risk of hepatocellular carcinoma and intrahepatic cholangiocarcinoma: The Liver Cancer Pooling Project. Br J Cancer 2018;118:1005–1012. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Yu JH, Cho SG, Jin YJ, Lee JW. The best predictive model for hepatocellular carcinoma in patients with chronic hepatitis B infection. Clin Mol Hepatol 2022;28:351–361. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Hung AL, Garzon-Muvdi T, Lim M. Biomarkers and Immunotherapeutic targets in glioblastoma. World Neurosurg 2017;102:494–506. [DOI] [PubMed] [Google Scholar]
- 14.Chen M, Chang Y, Tang F, et al. Influence of cytotoxic T lymphocyte-associated antigen 4 polymorphisms on the outcomes of hepatitis B virus infection. Mol Med Rep 2014;9:645–652. [DOI] [PubMed] [Google Scholar]
- 15.Corvalan AH, Carrasco G, Saavedr K. The genetic and epigenetic bases of gastritis. In: Mozsik G, editor. Current Topics in Gastritis - 2012. London: InTech; 2013. [Google Scholar]
- 16.Barrett LW, Fletcher S, Wilton SD. Regulation of eukaryotic gene expression by the untranslated gene regions and other non-coding elements. Cell Mol Life Sci 2012;69:3613–3634. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Goldberg-Cohen I, Furneauxb H, Levy AP. A 40-bp RNA element that mediates stabilization of vascular endothelial growth factor mRNA by HuR. J Biol Chem 2002;277:13635–13640. [DOI] [PubMed] [Google Scholar]
- 18.Duan S, Zhang G, Han Q, et al. CTLA-4 exon 1 +49 polymorphism alone and in a haplotype with −318 promoter polymorphism may confer susceptibility to chronic HBV infection in Chinese Han patients. Mol Biol Rep 2011;38:5125–5132. [DOI] [PubMed] [Google Scholar]
- 19.Danilovic DLS, Mendes-Correa MC, Lima EU, et al. Correlations of CTLA-4 gene polymorphisms and hepatitis C chronic infection. Liver Int Off J Int Assoc Study Liver 2012;32:803–808. [DOI] [PubMed] [Google Scholar]
- 20.Kristiansen OP, Larsen ZM, Pociot F. CTLA-4 in autoimmune diseases--A general susceptibility gene to autoimmunity?. Genes Immun 2000;1:170–184. [DOI] [PubMed] [Google Scholar]
- 21.Lee YH, Harley JB, Nath SK. CTLA-4 polymorphisms and systemic lupus erythematosus (SLE): A meta-analysis. Hum Genet 2005;116:361–367. [DOI] [PubMed] [Google Scholar]
- 22.Tan X, Liu C, Sun L. Association between CTLA4 + 49A/G polymorphism and risk of hepatocellular carcinoma: A systematic review and meta-analysis. Nucleosides Nucleotides Nucleic Acids 2024;43(4):302–315. [DOI] [PubMed] [Google Scholar]
- 23.Thio CL, Mosbruger TL, Kaslow RA, et al. Cytotoxic T-lymphocyte antigen 4 gene and recovery from hepatitis B virus infection. J Virol 2004;78:11258–11262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Singal AG, Llovet JM, Yarchoan M, et al. AASLD Practice Guidance on prevention, diagnosis, and treatment of hepatocellular carcinoma. Hepatology 2023;78:1922–1965. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Galle PR, Forner A, Llovet JM, et al. EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. J Hepatol 2018;69:182–236. [DOI] [PubMed] [Google Scholar]
- 26.Wang L, Li D, Fu Z, et al. Association of CTLA-4 gene polymorphisms with sporadic breast cancer in Chinese Han population. BMC Cancer 2007;7:173. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Anjos SM, Polychronakos C. Functional evaluation of the autoimmunity-associated CTLA4 gene: The effect of the (AT) repeat in the 3’untranslated region (UTR). J Autoimmun 2006;27:105–109. [DOI] [PubMed] [Google Scholar]
- 28.Parry CM. The treatment of multidrug-resistant and nalidixic acid-resistant typhoid fever in Viet Nam. Trans R Soc Trop Med Hyg 2004;98:413–422. [DOI] [PubMed] [Google Scholar]
- 29.Wongjitrat C, Sukwit S, Chuenchitra T, et al. CTLA-4 and its ligands on the surface of T- and B-lymphocyte subsets in chronic hepatitis B virus infection. J Med Assoc Thail Chotmaihet Thangphaet 2013;96 Suppl 1:S54–S59. [PubMed] [Google Scholar]
- 30.Apol ÁD, Winckelmann AA, Duus RB, et al. The role of CTLA-4 in T cell exhaustion in chronic hepatitis B virus infection. Viruses 2023;15:1141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Cao H, Zhang R, Zhang W. CTLA-4 interferes with the HBV-specific T cell immune response (Review). Int J Mol Med 2018;42:703–712. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Tapirdamaz Ö, Pravica V, Metselaar HJ, et al. Polymorphisms in the T cell regulatory gene cytotoxic T lymphocyte antigen 4 influence the rate of acute rejection after liver transplantation. Gut 2006;55:863–868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Waldman AD, Fritz JM, Lenardo MJ. A guide to cancer immunotherapy: From T cell basic science to clinical practice. Nat Rev Immunol 2020;20:651–668. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Hudson LL, Silver RM, Pandey JP. Ethnic differences in cytotoxic T lymphocyte associated antigen 4 genotype associations with systemic sclerosis. J Rheumatol 2004;31:85–87. [PubMed] [Google Scholar]
- 35.Van Dyke AL, Cote ML, Wenzlaff AS, et al. Cytokine SNPs: Comparison of allele frequencies by race & implications for future studies. Cytokine 2009;46:236–244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Isitmangil G, Gurleyik G, Aker FV, et al. Association of CTLA4 and CD28 gene variants and circulating levels of their proteins in patients with breast cancer. Vivo Athens Greece 2016;30:485–493. [PubMed] [Google Scholar]
- 37.Pradana KA, Widjaya MA, Wahjudi M. Indonesians human leukocyte antigen (HLA) distributions and correlations with global diseases. Immunol Invest 2020;49:333–363. [DOI] [PubMed] [Google Scholar]
- 38.Yuliwulandari R, Prayuni K, Viyati K, et al. Frequencies of HLA-B alleles in Indonesian Malay Ethnic. Heliyon 2024;10:e26713. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Lusida MI, Nugrahaputra VE, Soetjipto, et al. Novel subgenotypes of hepatitis B virus genotypes C and D in Papua, Indonesia. J Clin Microbiol 2008;46:2160–2166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Siburian MD, Utama A, Dhenni R, et al. High prevalence of hepatitis B virus genotype C/C1 in the Minangkabau ethnic group in Indonesia. Virol J 2013;10:27. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Chun HS, Papatheodoridis GV, Lee M, et al. PAGE-B incorporating moderate HBV DNA levels predicts risk of HCC among patients entering into HBeAg-positive chronic hepatitis B. J Hepatol 2024;80:20–30. [DOI] [PubMed] [Google Scholar]
- 42.Lee E, Xuan Mai TT, Chang Y, Ki M. Trends of liver cancer and its major risk factors in Korea. Epidemiol Health 2015;37:e2015016. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Ishiguro S, Inoue M, Tanaka Y, et al. Serum aminotransferase level and the risk of hepatocellular carcinoma: A population-based cohort study in Japan. Eur J Cancer Prev 2009;18(1):26–32. [DOI] [PubMed] [Google Scholar]
- 44.Respatiadi H, Tandra S. Fighting unrecorded alcohol : A policy priority for Bandung, West Java. Jakarta: Center for Indonesian Policy Studies; 2018. [Google Scholar]
- 45.Anyanwu OA, Naumova EN, Chomitz VR, et al. The socio-ecological context of the nutrition transition in Indonesia: A qualitative investigation of perspectives from multi-disciplinary stakeholders. Nutrients 2023;15:25. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Derived data supporting the findings of this study are available from the corresponding author on request.