Abstract
Survivin can affect the progression of infection and is considered as a marker of various malignancies. The aim of the study was to investigate the possible association of gene polymorphisms of survivin (-1547A/G, -644C/T, -625 C/G, -241C/T, -31G/C, -141G/C) and chronic hepatitis B infection in Iranian patients. The genotypes of survivin SNPs were investigated by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) method using 100 chronic HBV infected patients (HBV), 40 spontaneously recovered HBV subjects and 100 healthy controls (C). Serum level of survivin was determined using ELISA method. The -1547G, -625C, -241T and -31C alleles were associated with increased susceptibility to chronic hepatitis B infection (P = 0.001, P < 0.001, P = 0.003 and P < 0.001 respectively). Chronic HBV patients with -625CC, -241TT and -31CC genotypes had higher levels of survvin. Survivin -1547A/G, -625 C/G, -241C/T and -31G/C gene polymorphisms may be associated with chronic HBV susceptibility in Iranian HBV patients.
Keywords: Chronic hepatitis B, Polymorphisms, Survivin
Background
Hepatitis B virus (HBV) infection, is one of the most common liver diseases and an important cause of acute or chronic hepatitis with high prevalence especially in Asia and Africa [1]. According to the World Health Organization (WHO), approximately 2 billion people are infected with HBV virus worldwide and bout 360 million of whom are chronic infection. Over one million deaths from this virus are reported annually. At present, HBV is a major health issue in the world because it is the first risk factor for liver cancer-related death, with great geographical variation [1].
So far, little information has been presented about the real mechanism of HBV infection. Therefore, identifying novel biomarkers with high diagnostic value is required. Definitely, some biomarkers that indicate disease activity can be used for detection as well as more specific drug treatments. Several biomarkers such as cytokines chemokines and some special proteins have been identified for HBV [2–6].
Survivin, is an inhibitor protein of apoptosis and a member of the inhibitor of apoptosis family of proteins (IAPs). It is a baculoviral inhibitor of apoptosis repeat-containing 5 or BIRC5, which has been identified to be involved in the regulation of cellular and tissue homeostasis. According to the previous studies, survivin is highly expressed in some chronic diseases such as multiple sclerosis but not in normal human tissues [7]. It means that survivin can affect the progression of disease and is considered as a marker of various malignancies. Survivin can inhibit caspase-3,7 and 9 activity which leads to inactivation of the death receptor and mitochondrial apoptosis pathways [8]. Given that these pathways might control the human immune system, it is presumed that deficiency in survivin level might change the homeostasis of the immune cells and result in inflammation [7].
Studies have shown that survivin has a key role in cell viability and its expression is changed in all parts of the cell, during the outbreaks. Therefore any mutations in this gene or changes in protein structure can alter its function and therefore occurrence and progression of disease are subject to change. Nowadays, there is a number of evidence which represents that host genetic factors such as genetic variations and single nucleotide polymorphisms have a key role in determining the progression of HBV infection [9].
The human BIRC5 gene is located on chromosome 17q25 and consists of: one Baculoviral IAP Repeat (BIR), three Cell-cycle-Dependent Elements (CDE) and one Cell-cycle Homology Region (CHR). These regions contribute in cell-cycle-dependent expression. Mainly, SNPs in the promoter region or other regulatory regions of the gene have a significant impact on the gene expression. Since the SNPs can affect the production or activity of the protein, therefore, various genotypes can also affect HBV risk in each individual. Some polymorphisms have been identified in the promoter region of the survivin gene that might be affected the expression of the protein, such as; -1547A/G (rs3764383), -644C/T (rs8073903), -625 (C/G rs8073069), -241C/T (rs17878467), -31G/C (rs9904341) and -141G/C (rs17882312). In addition, A9194G and T9809C SNPs in exon 4 and 3′-UTR regions might affect gene expression or mRNA stability [10].
Several studies reported that survivin SNPs were associated with various cancers such as HCV related-liver cancer [11]. In the present study, it was hypothesized that genetic variants of survivin play a functional role in chronic HBV infection. Therefore, the objective of our research was to study the association between the six SNPs of BIRC5 gene -1547A/G (rs3764383), -644C/T (rs8073903), -625 C/G (rs8073069), -241C/T (rs17878467), -31G/C (rs9904341), -141G/C (rs17882312 and HBV susceptibility, in a sample of Iranian.
Materials and Methods
Study Population and Samples Collection
This case–control study consisted of 100 chronic HBV infected patients (HBV), 40 subjects with spontaneously recovered from HBV (SR) and 100 healthy controls (C). The study was approved by the Institutional Ethics Committee of the Zahedan University of Medical Sciences (IR.ZAUMS.REC.1394.211, grant number 7868) and carried out in Infectious Diseases and Tropical Medicine Research Center, Zahedan, Iran. Written informed consent was obtained from each participant.
The chronic HBV patients were positive for HBsAg and antibodies against anti-HBc referred to Blood Transfusion Organization clinics in Zahedan, Iran, between July and December 2015. These subjects had impaired liver function test so that their transaminases were more than twofold the normal level for at least 6 months. Serological tests, presence of HBsAg by enzyme-linked immunosorbent assay (ELISA) and HBV-DNA by real-time polymerase chain reaction (RT-PCR) were done according to the manufacturers (Pishtazteb Company, Iran) and clinical findings were compatible with chronic liver disease. Table 1 shows the demographic characteristics of the participants. Patients with HCV, HEV, HAV, HIV, alcohol consumption, drug abuse, liver diseases were excluded. The spontaneously recovered group were negative for HBsAg and anti-HCV and positive for antibodies against anti-HBs and anti-HBc. The control group comprised HBsAg, anti-HBs and anti-HBc negative, healthy volunteers, with negative tests for HBV, HCV and HIV serology and with normal values for alanine transaminase (ALT), without any history of hepatitis B infection. All subjects were in the same geographical area. There was no difference between groups in terms of age, gender and ethnicity.
Table 1.
Demographic data of chronic hepatitis B (HBV) patients, spontaneously recovered (SR) subjects and control group (C)
| Parameters | C, N (%) | SR, N (%) | HBV, N (%) | P |
|---|---|---|---|---|
| Age (years) | 30.44 ± 4.54 | 29.72 ± 5.52 | 29.03 ± 5.71 | 0.125 |
| Sex | ||||
| Male | 51 (51.0) | 25 (62.5) | 57 (57.0) | 0.427 |
| Female | 49 (49.0) | 15 (37.5) | 43 (43.0) | |
| Ethnicities | ||||
| Sistani | 46 (46.0) | 18 (45.0) | 41 (41.0) | 0.292 |
| Baluch | 18 (18.0) | 13 (32.5) | 22 (22.0) | |
| Others | 36 (36.0) | 9 (22.5) | 37 (37.0) |
Three ml of blood was taken in tubes containing EDTA for determining biochemical parameters. The measurement of the serum level of survivin was done using an ELISA kit (EASTBIOPHARM, China), according to the manufacturer’s instructions. Whole-blood samples were tested for DNA extraction. Human DNA was extracted from Buffy coat of 500 μL of whole blood using the salting-out method.
Analysis of the Serum Survivin
Three ml of blood was taken in tubes containing EDTA for determining biochemical parameters. The measurement of the serum level of survivin was done used the sensitive sandwich ELISA technique (EASTBIOPHARM, China), according to the manufacturer’s instruction. In brief flat-bottom polystyrene 96-well microplates were coated overnight at 4 °C with 50 μL per well of carbonate buffer (0.1 mol L−1 Na2CO3, 35 mmol L−1 NaHCO3; pH 9.6) containing 1 mg/L of purified anti-survivin antibodies. All wash steps were carried out three times with PBST, and plates were sealed with plate-sealing film during incubations to minimize evaporation. The wells were blocked with 150 μL per well of PBST-BSA and were incubated for 30 min at room temperature. After washing, 50 μL per well of each sample was added in triplicate. Standards and sample extracts diluted 1:100 in PBST-BSA were incubated for 1 h at 37 °C under gentle shaking on each plate. After washing, bound survivin was detected by adding 50 μL per well of biotinylated anti-survivin antibodies (1.3 mg/L) and incubated for 1 h at 37 °C under gentle shaking. Plates were washed again and were subsequently incubated with 50 μL per well of Streptavidin-HRP conjugated, diluted 1:2000 in PBST-BSA for 1 h at 37 °C. After a final wash, each well was incubated with 50 μL of the substrate solution, a mixture (1:4) of citrate buffer (0.05 mol L−1 citric acid, 0.1 mol L−1 Na2HPO4; pH 5.2), and OPD solution (7 mmol L−1 H2O2, 333 mg/L OPD). Color development was stopped by the addition of 50 μL per well of 2 mol L−1 H2SO4. Absorbance was read at 490 nm in an ELISA plate reader.
Peripheral DNA Isolation
Genomic DNA was extracted from the 500 μL of peripheral blood leukocytes using the salting-out method. In brief, 900 μL of lysis buffer 1 and 50 μL of 1x Triton-X were added to 300 μL of blood in an autoclaved 1.5 ml eppendorf. Incubated at 370 C for 5 min to lyse the RBCs. Cells were centrifuged at 8000 rpm for 3 min and the supernatant was discarded. This step was repeated 2–3 times with decreasing amount of 1x Triton-X till RBC lysis was complete and a white pellet of WBCs was obtained. To the cell pellet, 300 μL of lysis buffer 2 and 40 μL of 10% SDS were added. Mixed thoroughly and incubated at 370 C for 5 min. At the end of incubation, 100 μL of 6 M NaCl was added and vortexed. Cells were centrifuged at 8000 rpm for 5 min. The supernatant was transferred into a new eppendorf tube containing 300 μL of isopropanol. DNA was precipitated by inverting the eppendorf slowly. Further, the eppendorfs were centrifuged at 800 rpm for 10 min to pellet down the DNA. Supernatant was discarded, 70% ethanol was added and mixed slowly to remove any excess salts. Finally the tubes were centrifuged at 8000 rpm for 5 min to pellet down the DNA. Supernatant was discarded and DNA air-dried. After thorough drying, 50 μL of TE buffer was added to dissolve the DNA. These samples were stored at − 80 °C until they were used for the study.
Survivin Genotyping
The -1547A/G (rs3764383), -644C/T (rs8073903), -625 C/G (rs8073069), -241C/T (rs17878467), -141G/C (rs17882312) and -31G/C (rs9904341) SNPs of survivin were identified by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique. The specific primers were designed according to the data achieved from the NCBI data bank (http:www.ncbi.nlm.nih.gov) for identification of SNPs (Table 2). The PCR primers were designed by primer design software primer3 and provided by SinaClon BioScience Company. The restriction enzymes and the fragment length after digestion are shown in Table 2. The restriction enzymes were selected by the WebCutter software (http://rna.lundberg.gu.se/cutter2/). PCR amplification was carried out in a total volume of 20 μL containing 1 μL of each primer, 100 ng of template DNA and 10 μL of 2X Prime Taq Premix (Genet Bio, Korea) and 7 μL ddH2O. The PCR conditions were as follows: initial denaturation at 95 °C for 5 min followed by 35 cycles of denaturation at 95 °C for 30 s, annealing at 60 °C, 61.5 °C, 60.5 °C, 56 °C, 55.5 °C, 53 °C, for -1547A/G, -644C/T, -625 C/G, -241C/T, -141G/C and -31G/C, respectively for 30 s and extension at 72 °C for 30 s, followed by a final extension step at 72 °C for 5 min. Finally, the PCR products digested by the restriction enzymes (Fermentas, Vilnius, Lithuania) and digested products were resolved by electrophoresis in 2–4% agarose gel and stained with ethidium bromide. For doublechecking and to confirm the genotyping quality, 10% of the samples were randomly selected to sequencing, and the results were 100% concordant.
Table 2.
PCR-RFLP-based assay of -1547A/G (rs3764383), -644C/T(rs8073903), -625 C/G (rs8073069), -241C/T (rs17878467), -141G/C (rs17882312) and -31G/C (rs9904341) SNPs
| Polymorphism | Primers | Annealing temperature (°C) | Restriction enzyme | Allele phenotype (bp) |
|---|---|---|---|---|
| -1547A/G |
F: GCCCGATGCATTTAAATAAAAGA R: GCAGAGAGTGAATGTTAAAGTTAA |
60 | HincII |
A: 118 G: 96/22 |
| -644C/T |
F: AGGTCGTGCAGTCAACGATGT R: CAGACGGGCATGAAGGACCCATG |
61.5 | StyI |
T: 89 C: 66/23 |
| -625 C/G |
F: TGTTCATTTGTCCTTCATGCGC R: CCAGCCTAGGCAACAAGAGCAA |
60.5 | BstUI |
C: 125 G: 104/21 |
| -241C/T |
F: CTCAGCCTCCCGAGTAGTTG R: TCAAATCTGGCGGTTAATGG |
56 | HaeI |
C: 220/202 T: 422 |
| -141G/C |
F: GATTACAGGCGTGAGCCACT R: TCAAATCTGGCGGTTAATGG |
55.5 | BanI |
G:162/104 C: 266 |
| -31G/C |
F: CGTTCTTTGAAAGCAGTCGAG R: TGTAGAGATGCGGTGGTCCT |
53 | Eco0109I |
C: 326 G: 234/92 |
Statistical Analysis
Statistical analysis was performed by SPSS 20.0. Computing the odds ratio (OR) and 95% confidence intervals (95% CI) from logistic regression analyses were used for assessing the relationship between genotypes and HBV. Categorical data (represented by the mean ± standard deviation) and continuous data (represented by frequency) were analyzed by χ2 test and independent sample t test, respectively. The distributions of genotypes were tested with the Chi square analyses. Chi square analysis was used for contingency table analysis and Fisher’s exact testing proportion independence. Haplotype analysis was performed using SNPSStats software. Data were expressed as mean ± SD. A P-value of < 0.05 indicated the statistical significance.
Results
Demographic Data
Table 1. shows the baseline characteristics of the study participants. One hundred patients with chronic hepatitis B infection, 40 spontaneously recovered subjects and 100 healthy controls were studied. The mean age of HBV, SR and C groups were 29.03 ± 5.710 (age range of 18–43), 29.72 ± 5.517 (age range of 18–42) and 30.44 ± 4.539 (age range of 22–45) respectively. No significant differences were found between the 3 groups regarding age, gender and ethnicities (P > 0.05).
Genotype Analysis
The distributions of alleles from all SNPs were in accordance with Hardy–Weinberg principle (HWE) (P = 0.141 for rs3764383, P = 0.112 for rs8073903, P = 0.160 for rs8073069, P = 0.094 for rs17878467, P = 0.0881 for rs9904341, P = 0.231 for rs9904341, P = 0.212 for rs17882312 P > 0.05). We found significant differences in the prevalence of the -1547A/G, -625 C/G, -241C/T and 31G/C polymorphic variants in HBV patients and healthy subjects (C + SR) (Tables 3, 4). OR for HBV patients with the -1547GG, -625CC, -241TT and -31CC genotypes were 8.298 (95% CI = 2.625–26.230), 9.220 (95% CI = 3.577–23.764), 3.594 (95% CI = 1.642–7.868) and 7.502 (95% CI = 2.906–19.365), respectively. We also observed differences in the distribution of alleles between HBV patients and healthy subjects (C + SR) (Tables 3, 4). OR for the -1547G, -625C, -241T and -31C alleles were 2.110 (95% CI = 1.411–3.153), 2.887 (95% CI = 1.948–4.278), 1.956 (95% CI = 1.346–2.841) and 2.367 (95% CI = 1.610–3.481), respectively. There were not significant associations between the -644C/T and -141G/C genotypes and different groups (P > 0.05).
Table 3.
The frequency of genotypes and alleles of the -1547A/G (rs3764383), -644C/T (rs8073903), -625 C/G (rs8073069), -241C/T (rs17878467), -141G/C (rs17882312) and -31G/C (rs9904341) polymorphisms between chronic hepatitis B (HBV) patients, spontaneously recovered (SR) subjects and control group (C)
| BIRC5 polymorphisms | C vs SR | SR vs HBV | |||||
|---|---|---|---|---|---|---|---|
| C (%) | SR (%) | P value | Odds ratio | HBV (%) | P value | Odds ratio | |
| -1547A/G | |||||||
| AA | 58 (58.0) | 24 (60.0) | Ref = 1 | – | 42 (42.0) | Ref = 1 | – |
| AG | 40 (40.0) | 14 (35.0) | 0.671 | 0.846 (0.391–1.831) | 41 (41.0) | 0.248 | 1.415 (0.785–2.552) |
| GG | 2 (2.0) | 2 (5.0) | 0.391 | 2.417 (0.322–18.161) | 17 (17.0) | 0.001 | 11.738 (2.572–53.563) |
| GG + AG | 42 (42.0) | 16 (40.0) | 0.828 | 0.921 (0.436–1.943 | 58 (58.0) | 0.024 | 1.907 (1.088–3.344) |
| A | 156 (78.0) | 62 (77.5) | Ref = 1 | – | 125 (62.5) | Ref = 1 | – |
| G | 44 (22.0) | 18 (22.5) | 0.927 | 1.029 (0.552–1.918) | 75 (37.5) | 0.001 | 2.127 (1.370–3.304) |
| -644C/T | |||||||
| CC | 6 (6.0) | 2 (5.0) | 0.885 | 0.884 (0.166–4.699) | 8 (8.0) | 0.772 | 1.179 (0.387–3.588) |
| CT | 33 (33.0) | 15 (37.5) | 0.637 | 1.206 (0.555–2.620) | 23 (23.0) | 0.134 | 0.616 (0.327–1.162) |
| TT | 61 (61.0) | 23 (57.5) | Ref = 1 | – | 69 (69.0) | Ref = 1 | – |
| CC + CT | 39 (39.0) | 17 (42.5) | 0.786 | 1.109 (0.527–2.332) | 31 (31.0) | 0.236 | 0.703 (0.392–1.260) |
| C | 45 (22.5) | 19 (23.8) | 0.822 | 1.073 (0.581–1.980) | 39 (19.5) | 0.462 | 0.834 (0.515–1.351) |
| T | 155 (77.5) | 61 (76.2) | Ref = 1 | – | 161 (80.5) | Ref = 1 | – |
| -625C/G | |||||||
| CC | 29 (29.0) | 12 (30.0) | 0.754 | 1.166 (0.446–3.052) | 54 (54.0) | 0.000 | 9.621 (3.597–25.730) |
| CG | 40 (40.0) | 17 (42.5) | 0.692 | 1.198 (0.491–2.922) | 40 (40.0) | 0.001 | 5.167 (1.943–13.737) |
| GG | 31 (31.0) | 11 (27.5) | Ref = 1 | – | 6 (6.0) | Ref = 1 | – |
| CC + CG | 69 (69.0) | 29 (72.5) | 0.683 | 1.184 (0.525–2.671) | 94 (94.0) | 0.000 | 7.039 (2.783–17.799) |
| C | 98 (49.0) | 41 (51.2) | 0.734 | 1.094 (0.651–1.838) | 148 (74.0) | 0.000 | 2.962 (1.946–4.510) |
| G | 102 (51.0) | 39 (48.8) | Ref = 1 | – | 52 (26.0) | Ref = 1 | – |
| -241C/T | |||||||
| CC | 46 (46.0) | 19 (47.5) | Ref = 1 | – | 26 (26.0) | Ref = 1 | – |
| CT | 43 (43.0) | 16 (40.0) | 0.794 | 0.901 (0.411–1.974) | 51 (51.0) | 0.021 | 2.098 (1.118–3.937) |
| TT | 11 (11.0) | 5 (12.5) | 0.874 | 1.100 (0.337–3.598) | 23 (23.0) | 0.003 | 3.699 (1.558–8.782) |
| TT + TC | 54 (54.0) | 21 (52.5) | 0.872 | 0.942 (0.452–1.963) | 74 (74.0) | 0.004 | 2.425 (1.337–4.397) |
| C | 135 (67.5) | 54 (67.5) | Ref = 1 | – | 103 (51.1) | Ref = 1 | – |
| T | 65 (32.5) | 26 (32.5) | 1.000 | 1.000 (0.575–1.739) | 97 (48.5) | 0.001 | 1.956 (1.304–2.934) |
| -141G/C | |||||||
| CC | 73 (73.0) | 28 (70.0) | Ref = 1 | – | 72 (72.0) | Ref = 1 | – |
| CG | 25 (25.0) | 10 (25.0) | 0.391 | 0.400 (0.049–3.243) | 25 (25.0) | 0.671 | 0.667 (0.102–4.339) |
| GG | 2 (2.0) | 2 (5.0) | 0.350 | 0.384 (0.052–2.856) | 3 (3.0) | 0.651 | 0.658 (0.107–4.052) |
| CC + CG | 98 (98.0) | 38 (95.0) | 0.352 | 0.338 (0.053–2.852) | 97 (97.0) | 0.653 | 0.660 (0.108–4.036) |
| C | 171 (85.5) | 66 (82.5) | Ref = 1 | – | 169 (84.5) | Ref = 1 | – |
| G | 29 (14.5) | 14 (17.5) | 0.530 | 1.251 (0.622–2.514) | 31 (15.5) | 0.779 | 1.082 (0.625–1.873) |
| -31G/C | |||||||
| CC | 5 (5.0) | 2 (5.0) | 0.991 | 1.010 (0.182–5.615) | 22 (22.0) | 0.000 | 7.523 (2.587–21.874) |
| CG | 42 (42.0) | 17 (42.5) | 0.956 | 1.022 (0.479–2.177) | 47 (47.0) | 0.036 | 1.913 (1.042–3.514) |
| GG | 53 (53.0) | 21 (52.5) | Ref = 1 | – | 31 (31.0) | Ref = 1 | – |
| CC + CG | 47 (47.0) | 19 (47.5) | 0.957 | 1.020 (0.490–2.126) | 69 (69.0) | 0.002 | 2.510 (1.408–4.473) |
| C | 52 (26.0) | 21 (26.2) | 0.966 | 1.013 (0.562–1.827) | 91 (45.5) | 0.000 | 2.376 (1.560–3.620) |
| G | 148 (74.0) | 59 (73.8) | Ref = 1 | – | 109 (54.5) | Ref = 1 | – |
Table 4.
The frequency of genotypes and alleles of the -1547A/G (rs3764383), -644C/T (rs8073903), -625 C/G (rs8073069), -241C/T (rs17878467), -141G/C (rs17882312) and -31G/C (rs9904341) polymorphisms between control group (C)/spontaneously recovered (SR) subjects (C + SR) and chronic hepatitis B (HBV) groups
| BIRC5 polymorphisms | HBV (%) | Healthy (C + SR) (%) | P value | Odds ratio |
|---|---|---|---|---|
| -1547A/G | ||||
| AA | 42 (42.0) | 82 (58.6) | Ref = 1 | – |
| AG | 41 (41.0) | 54 (38.6) | 0.161 | 1.482 (0.855–2.571) |
| GG | 17 (17.0) | 4 (2.9) | 0.000 | 8.298 (2.625–26.230) |
| GG + AG | 58 (58.0) | 58 (41.1) | 0.012 | 1.952 (1.160–3.285) |
| A | 125 (62.5) | 218 (77.9) | Ref = 1 | – |
| G | 75 (37.5) | 62 (22.1) | 0.000 | 2.110 (1.411–3.153) |
| -644C/T | ||||
| CC | 8 (8.0) | 8 (5.7) | 0.708 | 1.217 (0.434–3.411) |
| CT | 23 (23.0) | 48 (34.3) | 0.074 | 0.583 (0.323–1.053) |
| TT | 69 (69.0) | 84 (60.0) | Ref = 1 | – |
| CC + CT | 31 (31.0) | 56 (40.0) | 0.154 | 0.674 (0.392–1.159) |
| C | 39 (19.5) | 64 (22.9) | 0.378 | 0.818 (0.523–1.276) |
| T | 161 (80.5) | 216 (77.1) | Ref = 1 | – |
| -625CG | ||||
| CC | 54 (54.0) | 41 (29.3) | 0.000 | 9.220 (3.577–23.764) |
| CG | 40 (40.0) | 57 (40.7) | 0.001 | 4.912 (1.907–12.653) |
| GG | 6 (6.0) | 42 (30.0) | Ref = 1 | – |
| CC + CG | 94 (94.0) | 98 (70.0) | 0.000 | 6.714 (2.727–16.531) |
| C | 148 (74.0) | 139 (49.6) | 0.000 | 2.887 (1.948–4.278) |
| G | 52 (26.0) | 141 (50.4) | Ref = 1 | – |
| -241C/T | ||||
| CC | 26 (26.0) | 65 (46.4) | Ref = 1 | – |
| CT | 51 (51.0) | 59 (42.1) | 0.010 | 2.161 (1.199–3.896) |
| TT | 23 (23.0) | 16 (11.4) | 0.001 | 3.594 (1.642–7.868) |
| TT + TC | 74 (74.0) | 75 (53.6) | 0.001 | 2.467 (1.414–4.304) |
| C | 103 (51.1) | 189 (67.5) | Ref = 1 | – |
| T | 97 (48.5) | 91 (32.5) | 0.000 | 1.956 (1.346–2.841) |
| -141G/C | ||||
| CC | 72 (72.0) | 101 (72.1) | Ref = 1 | – |
| CG | 25 (25.0) | 35 (25.0) | 0.952 | 0.952 (0.196–4.635) |
| GG | 3 (3.0) | 4 (2.9) | 0.948 | 0.950 (0.206–4.377) |
| CC + CG | 97 (97.0) | 136 (97.1) | 0.948 | 0.951 (0.208–4.346) |
| C | 169 (84.5) | 237 (84.6) | Ref = 1 | – |
| G | 31 (15.5) | 43 (15.4) | 0.966 | 1.011 (0.612–1.671) |
| -31G/C | ||||
| CC | 22 (22.0) | 7 (5.0) | 0.000 | 7.502 (2.906–19.365) |
| CG | 47 (47.0) | 59 (42.1) | 0.027 | 1.902 (1.078–3.356) |
| GG | 31 (31.0) | 74 (52.9) | Ref = 1 | – |
| CC + CG | 69 (69.0) | 66 (47.1) | 0.001 | 2.496 (1.457–4.275) |
| C | 91 (45.5) | 73 (26.1) | 0.000 | 2.367 (1.610–3.481) |
| G | 109 (54.5) | 207 (73.9) | Ref = 1 | – |
In addition, the -1547GG, -625CC, -241TT and -31CC genotypes and -1547G, -625C, -241T and -31C alleles were more frequent in HBV patient than in subjects who spontaneously recovered from infection (Table 3). It means that -1547A/G, -625 C/G, -241C/T and 31G/C increased the risk of developing a persistent hepatitis B infection.
Haplotype Analysis
The haplotype distribution results between C, SR and HBV groups are shown in Tables 5, 6. In this study, 5 haplotypes were derived. The haplotype association analysis showed significant differences between groups (P = 0.015). The frequency of the GCCTGC genotype (resulting from the combination of the -1547A/G, -644C/T, -625C/G, -241C/T, -141G/C, -31G/C SNPs) were 15.0%, 10.0 and 36.0% in the C, SR and HBV groups, respectively. It revealed that individuals with -1547G, -644C, -625C, -241T, -141G and -31C alleles has an increased risk of chronic HBV infection.
Table 5.
Haplotype frequencies in chronic hepatitis B (HBV) patients, spontaneously recovered (SR) subjects and control group (C)
| Haplotypes | C vs SR | SR vs HBV | |||||
|---|---|---|---|---|---|---|---|
| C group n (%) | SR group n (%) | P value | Odds ratio | HBV group n (%) | P value | Odds ratio | |
| ATCCCG | 21 (21.0) | 10 (25.0) | 0.881 | 1.082 (0.385–3.045) | 14 (14.0) | 0.931 | 1.042 (0.414–2.620) |
| ATGTCC | 25 (25.0) | 11 (27.5) | Ref = 1 | – | 16 (16.0) | Ref = 1 | – |
| GCCTGC | 15 (15.0) | 4 (10.0) | 0.454 | 0.606 (0.163–2.249) | 36 (36.0) | 0.003 | 3.750 (1.571–8.949) |
| GTCTCC | 19 (19.0) | 7 (17.5) | 0.756 | 0.837 (0.273–2.566) | 19 (19.0) | 0.328 | 1.562 (0.639–3.818) |
| GTGCCG | 20 (20.0) | 8 (20.0) | 0.863 | 0.909 (0.307–2.688) | 15 (15.0) | 0.735 | 1.172 (0.468–2.933) |
Table 6.
Haplotype frequencies in control group (C)/spontaneously recovered (SR) subjects (C + SR) and chronic hepatitis B (HBV) groups
| Haplotypes | Healthy (C + SR) n (%) | HBV group n (%) | P value | Odds ratio |
|---|---|---|---|---|
| ATCCCG | 31 (22.1) | 14 (14.0) | 0.971 | 1.016 (0.429–2.409) |
| ATGTCC | 36 (25.7) | 16 (16.0) | Ref = 1 | – |
| GCCTGC | 19 (13.6) | 36 (36.0) | 0.000 | 4.263 (1.897–9.581) |
| GTCTCC | 26 (18.6) | 19 (19.0) | 0.243 | 1.644 (0.714–3.789) |
| GTGCCG | 28 (20.0) | 15 (15.0) | 0.670 | 1.205 (0.510–2.849) |
Analysis of the Serum Survivin
Serum levels of the survivin were significantly increased in the chronic HBV patients comparison to the healthy groups (C + SR) (P < 0.05) (Fig. 1). Statistical analysis indicated positive correlations between survivin genotypes and serum levels of the survivin in HBV patients (Table 7). Chronic HBV patients with -625CC, -241TT and -31CC genotypes had higher levels of survvin compared to -625CG (P = 0.014), -241CC (P = 0.029)/-241CT (P = 0.004), -31GG (P = 0.011) genotypes, respectively. The results showed that the risk of HBV infection was significantly increased in subjects with GCCTGC genotype that had higher levels of survivin, comparison to the other genotype (P = 0.029) (Table 8).
Fig. 1.
Comparison of survivin levels between chronic hepatitis B (HBV) patients, spontaneously recovered (SR) subjects and control group (C). *P < 0.001, Compared to the C and SR groups
Table 7.
Association of genotypes of BIRC5 polymorphisms with serum survivin levels between control group (C)/spontaneously recovered (SR) subjects (C + SR) and chronic hepatitis B (HBV) groups
| BIRC5 genotyp | HBV N |
HBV Survivin (pg/ml) |
Healthy (C + SR) N |
Healthy (C + SR) Survivin (pg/ml) |
|---|---|---|---|---|
| -1547A/G | ||||
| AA | 42 (42.0) | 48.90 ± 14.40 | 82 (58.6) | 11.39 ± 1.77 |
| AG | 41 (41.0) | 47.47 ± 14.79 | 54 (38.6) | 11.73 ± 1.73 |
| GG | 17 (17.0) | 47.982 ± 12.86 | 4 (2.9) | 12.87 ± 1.31 |
| P | 0.901 | 0.172 | ||
| F | 0.105 | 1.786 | ||
| -644C/T | 8 (8.0) | 8 (5.7) | ||
| CC | 23 (23.0) | 53.68 ± 13.35 | 48 (34.3) | 10.73 ± 1.51 |
| CT | 69 (69.0) | 46.82 ± 14.58 | 84 (60.0) | 11.62 ± 1.78 |
| TT | 47.96 ± 14.21 | 11.60 ± 1.76 | ||
| P | 0.494 | 0.393 | ||
| F | 0.711 | 0.941 | ||
| -625C/G | 54 (54.0) | 41 (29.3) | ||
| CC | 40 (40.0) | 51.34 ± 13.51* | 57 (40.7) | 11.94 ± 1.74 |
| CG | 6 (6.0) | 43.62 ± 12.11 | 42 (30.0) | 11.35 ± 1.79 |
| GG | 50.08 ± 11.71 | 11.47 ± 1.70 | ||
| P | 0.018 | 0.254 | ||
| F | 4.198 | 1.385 | ||
| -241C/T | ||||
| CC | 26 (26.0) | 46.48 ± 12.90 | 65 (46.4) | 11.43 ± 1.81 |
| CT | 51 (51.0) | 45.40 ± 13.65 | 59 (42.1) | 11.58 ± 1.74 |
| TT | 23 (23.0) | 46.16 ± 11.59** | 16 (11.4) | 12.01 ± 1.61 |
| P | 0.005 | 0.491 | ||
| F | 5.710 | 0.715 | ||
| -141G/C | ||||
| CC | 72 (72.0) | 53.83 ± 4.45 | 101 (72.1) | 10.70 ± 2.19 |
| CG | 25 (25.0) | 49.24 ± 14.03 | 35 (25.0) | 11.58 ± 1.67 |
| GG | 3 (3.0) | 47.54 ± 14.26 | 4 (2.9) | 11.56 ± 1.75 |
| P | 0.680 | 0.616 | ||
| F | 0.387 | 0.486 | ||
| -31G/C | ||||
| CC | 22 (22.0) | 53.83 ± 4.45*** | 7 (5.0) | 11.75 ± 2.10 |
| CG | 47 (47.0) | 49.24 ± 14.03 | 59 (42.1) | 11.68 ± 1.71 |
| GG | 31 (31.0) | 47.54 ± 14.26 | 74 (52.9) | 11.45 ± 1.76 |
| P | 0.014 | 0.722 | ||
| F | 4.434 | 0.326 |
*P = 0.014, Compared with genotype CG
**P = 0.029, Compared with genotype CC; P = 0.004, Compared with genotype CT
***P = 0.011, Compared with genotype GG
Table 8.
Association of haplotypes of BIRC5 polymorphisms with serum survivin levels between control group (C)/spontaneously recovered (SR) subjects (C + SR) and chronic hepatitis B (HBV) groups
| Haplotypes | HBV N |
HBV Survivin (pg/ml) |
Healthy (C + SR) N |
Healthy (C + SR) Survivin (pg/ml) |
|---|---|---|---|---|
| ATCCCG | 14 (14.0) | 41.97 ± 11.87 | 31 (22.1) | 11.47 ± 1.99 |
| ATGTCC | 16 (16.0) | 41.08 ± 6.43 | 36 (25.7) | 10.76 ± 1.97 |
| GCCTGC | 36 (36.0) | 52.53 ± 13.43* | 19 (13.6) | 12.30 ± 1.85 |
| GTCTCC | 19 (19.0) | 50.74 ± 15.37 | 26 (18.6) | 11.88 ± 1.68 |
| GTGCCG | 15 (15.0) | 47.70 ± 13.28 | 28 (20.0) | 11.89 ± 1.65 |
| TOTAL | 100 (100.0) |
P = 0.014 F = 3.306 |
140 (100.0) |
P = 0.026 F = 2.862 |
*P = 0.029, Compared with genotype ATGTCC
Discussion
In the present study, we found that the polymorphisms in the promoter region of survivin were associated with the susceptibility to chronic hepatitis B infection in an Iranian population. This study evaluated the role of the -1547A/G, -644C/T, -625 C/G, -241C/T, -31G/C, -141G/C SNPs of the BIRC5 gene in the susceptibility to chronic HBV infection. In this study, the prevalence of high survivin level in HBV infected patients was significantly greater than the healthy controls (SR and C). In addition, the frequency of high survivin level was significantly greater in HBV infected patients carrying the homozygote of -625C/G, -241C/T and -31G/C SNPs than other polymorphisms. More importantly, high survivin levels were significantly associated with HBV. These findings suggested that a high survivin level with existence of -625CC, -241TT and -31CC genotypes were potential risk factors for HBV infection. Also, our results showed that -644C/T and -141G/C polymorphisms did not associate with the risk of HBV. It means that these polymorphisms may not have an effect on the survivin level.
More evidences revealed that the genomic variations probably change the susceptibility to infectious diseases [12, 13]. Many SNPs were identified as having an association with the risk of HBV infection [4, 13–19]. Therefore, the host genetic factors are pivotal elements to affect the occurrence of HBV. Hence, the comparison of SNPs between HBV infected patients and healthy subjects might be a useful strategy to introduce a biomarker for predicting risk of HBV.
Survivin contributes in cell proliferation and increases malignancy development via the reduced apoptosis in damaged cells. Therefore the cells which have wrong biological function, continue to the cell cycle without correction of cell defects. Under these circumstances, the expression level of survivin increases specially in liver related inflammations compare to other organs [14]. Considering the role of survivin in chronic disease, this study hypothesized that promoter SNPs in BIRC5 gene might associate with the HBV susceptibility and disease progression.
Guo et al. [15] and Jang et al. [16] identified the various distribution of sirvivin SNPs (-644T > C, -625G > C, -31C > G, -9194A > G, -9386T > C, -9809T > C, -9974C > T and -10347G > A) between lung cancer patients and healthy controls in different populations. They concluded that, only the -31C > G genotype distribution was significantly different between the cases and controls. Similarly, Boidot et al. [17] studied 7 SNPs (-267G > A, -241C > T, -235G > A, -198, -191, -141 and -31C > G) for breast cancer in a French population and reported that -31C > G has a role in cancer development. In both studies -31C > G affected the expression level of mRNA. In accordance with our results, there are more evidences indicating the correlation between -31C > G and chronic inflammatory diseases in Asian and European populations [18–21]. In contrast, some studies did not report an association between polymorphisms in the promoter region and survivin function in inflammations [13, 22, 23]. Li et al. [23], in a case–control study which was conducted in Chinese han population which most of them were HbsAg + , did not find any association between -31C > G and -625G > C in BIRC5 gene and the risk of HCC, but they reported that -625G/-31C/-3′UTRT is perhaps a protective haplotype for HCC. In another study, Bayram et al. [24] by genotyping the frequency of -31C > G polymorphism in subjects with HCC and cancer-free control subjects, did not find statistically significant differences in the genotype distributions of the polymorphism and reported that -31C > G polymorphism have not been any major role in genetic susceptibilty to hepatocellular carcinogenesis.
Current study identified the -1547A/G, -644C/T, -625 C/G, -241C/T, -31G/C, -141G/C SNPs and results showed association between -1547A/G, -625C/G, -241C/T, and -31G/C SNPs and risk of HBV infection. Our findings are in agreement with some previous studies [11, 25] but the real mechanism is not known. It is reported that survivin -31G/C polymorphism has important role in inflammation, especially in the Asian population [26]. Our findings demonstrated that the serum levels of survivin in HBV infected patients with the -1547GG, -625CC, -241TT and -31CC genotypes was significantly increased compare to the -1547AA, -625GG, -241CC and -31GG genotypes. In vitro studies indicated that the -31GG genotype could increase the mRNA and protein levels of survivin in different cancer cell lines [27]. The inconsistent results may be due to different mechanisms of inflammations.
The -241C/T polymorphism is a genetic candidate for the regulation of survivin level [27]. According to the Hsieh et al. [10] study, the -241C/T polymorphism of survivin was undetectable in the Taiwanese population and also has normal genotype distribution between patients with ovarian cancer. Also, Lamp et al. [28]. found that -241C/T genotype distributions were similar in endometriosis patients and controls. Current study showed an important association between -241TT genotype and risk of HBV infection in Iranian population. In other words, T allele was correlated to the higher amount of survivin in patients. This is a critical finding and need further studies to investigate the real effect of this SNP on HBV infection in different populations.
The -625 C/G polymorphis; in the promoter region of BIRC5 gene has been reported to be a risk factor for esophageal squamous cell carcinoma in a way that -625CC genotype associated with higher level of protein and increased susceptibility to cancer [29]. However, in Asian populations, this SNP was not related to the lung cancer [16] and HCC [11]. Our study are in line with the Yang et al. [29] and show that -625 C/G polymorphism correlates with the esophageal squamous cell carcinoma as a chronic disease. But Lee et al. did not find any relationship between -625 C/G polymorphism and clearance of HBV infection and HCC occurrence in a Korean population [13]. The best answer to explain the conflicting results is that host genetic background may be different in various inflammations. Also, some other mechanisms may be involved in survivin production.
In regard to the -1547A/G polymorphism, we found that -1547GG genotype was associated with the risk of HBV infection but not the survivin level. In one study, Han et al. [18] monitored the -1547A/G polymorphism in clinical outcomes of patients with ovarian cancer. They found that -1547A/G was significantly associated with age of disease onset and the -1547AA genotype showed a significantly younger age of disease onset. However, this variant is located in the regulatory region of the gene, but, it is difficult to consider it as a risk factor for HBV, because the data about the impact of the -1547A/G on hepatic diseases and other inflammatory diseases is scarce. Validation studies with larger sample sizes and other hepatic inflammation in various populations in this field are warranted.
In connection with this study, Lee et al. [13] identified eight sequence variants of BIRC5 through direct DNA sequencing. Among the eight SNPs (-1547T/C, -644C/T, -625C/G, -241C/T, +9194A/G, +9386T/C, +9625G/A, +9809T/C) six common variants with frequencies higher than 0.05 were selected for larger-scale genotyping (n = 1066). They did not show any association between the promoter region polymorphisms and the clearance of HBV infection and hepatocellular carcinoma (HCC) occurrence. This is not in line with our study in which polymorphisms in the promoter region influences the function of BIRC5.
In the present study, we observed that the individual carrying GCCTGC haplotype (-1547A/G, -644C/T, -625C/G, -241C/T, -141G/C, -31G/C) had a higher risk of HBV than those carrying other genotypes. The existence of this genotype caused higher expression of survivin in HBV infected patients.
Marusawa et al. has revealed that survivin forms complexes with hepatitis B X-interacting protein (HBXIP). This complex reduces the mediator proteins in apoptosis [30]. In addition, SNP studies reported that variations in gene promoter might be related with hepatic inflammation. In other words, alteration in sequences of regulatory regions can affect protein expression, so, it can change the combination of HBXIP and survivin. In the current study, -1547A/G, -625C/G, -241C/T and -31G/C SNPs revealed associations with the risk of HBV infection. The results of this study might be useful for future investigations which should include additional studies on the function of the survivin. To our knowledge, this is the first study showing that -1547A/G, -625C/G, -241C/T and -31G/C polymorphisms of the BIRC5 gene increase the risk of HBV infection.
At this stage, it is difficult to derive a conclusion because previous studies have worked on other cases. However, different malignancy, inadequate study design (limited sample size), other genetic variants in the BIRC5 gene and habitual characteristics (smoking) could affect the results. Our findings need to be interpreted with caution and also must further examine other polymorphisms in regulatory genes and the association between them in patients with HBV infection.
Conclusions
In conclusion, we found that the BIRC5 gene promoter polymorphisms are associated with an increased risk of HBV. The polymorphisms in the promoter region of survivin were associated with the susceptibility to chronic hepatitis B infection in an Iranian population. Our findings suggested that a high survivin level with existence of -625CC, -241TT and -31CC genotypes were potential risk factors for HBV infection. Current study revealed that the genomic variations probably change the susceptibility to HBV infection. Because of the limitations of our study, further large sample studies, including different ethnicities are needed.
Acknowledgements
The authors would like to thank all participants who willingly participated in this study. We appreciate all who helped us in this work, especially in the Blood Transfusion Research Center of Zahedan, Iran. This study was approved by the Institutional Ethics Committee of the Zahedan University of Medical Sciences (IR.ZAUMS.REC.1395.159, Grant Number 7868).
Abbreviations
- SNP
Single nucleotide polymorphisms
- HBV
Hepatitis B virus
- SR
Spontaneously recovered
- PCR-RFLP
Polymerase chain reaction restriction fragment length polymorphism
- ELISA
Enzyme-linked immunosorbent assay
- IAPs
Inhibitor of apoptosis family of proteins
- BIRC5
Baculoviral inhibitor of apoptosis repeat containing 5
- RT-PCR
Reverse transcription polymerase chain reaction
Author’s Contribution
BM, ZH, HM-S conceived and co-designed the study, supervised all the experimental design, analyzed the results, and drafted the manuscript. All authors read, modified and approved the final version of the manuscript. These authors equally contributed to this work.
Funding
This project was supported by the vice chancellor of Research and Technology of Zahedan University of Medical Sciences (ZUMS) and Infectious Diseases and Tropical Medicine Research Center, Zahedan University of Medical Sciences.
Compliance with Ethical Standards
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical Approval
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed Consent
Informed consent was written and signed by all individual participants included in the study.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Bita Moudi, Email: bita.moudi@yahoo.com.
Zahra Heidari, Email: histology_iri@yahoo.com.
Hamidreza Mahmoudzadeh-Sagheb, Email: histology@ymail.com.
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