Abstract
To investigate whether selected single nucleotide polymorphisms (SNPs) in miR-146a, miR-196a2, miR-27a, miR-26a-1, miR-124 and miR-149 genes are associated with immune response to hepatitis B vaccine. The genotype and allele frequencies of SNPs were compared between the non-responders (n = 77) and responders (n = 207). The associations of the genotypes with antibody levels were assessed in the responders. Significant associations were observed between SNPs in miR-146a and miR-26a-1 genes and non-response to hepatitis B vaccine (p < 0.05). In addition, SNPs in miR-146a and miR-27a genes were associated with variations in levels of antibodies to hepatitis B antigen. Thus, specific SNPs in microRNAs (miRNAs) genes may affect status of the hepatitis B vaccine induced protective humoral immune response. They also suggest that the three miRNAs play a role in modulating antibody responses to hepatitis B vaccine.
Keywords: polymorphisms, miRNA, hepatitis B vaccine, antibody, immune response
Introduction
Hepatitis B virus (HBV) infection remains a global public health problem. It has been estimated that approximately 57.16% of the Chinese population has serological evidence of past or present infection with HBV, and hepatitis B surface antigen (HBsAg) carriage rate is 9.5%.1 Hepatitis B vaccination is one of the most efficient tools to prevent transmission of the virus. In China, infant immunization against infection has been available since the late 1980s, and the vaccine has been routinely administered since 2002. The antibodies to HBsAg (anti-HBs) titer > 10 IU/ml was considered to be protective.2 Approximately 5–10% of healthy vaccinated individuals fail to produce protective levels of antibodies following standard vaccination protocols. Subsequently, these individuals are still susceptible to HBV infection.3
The precise mechanisms leading to non-responsiveness to hepatitis B vaccine are not yet clearly defined. Genetic background is thought to play a critical role in modulating responsiveness to the vaccine. Among the genes investigated and associated with non-response to hepatitis B vaccine are those encoding human leukocyte antigen (HLA),4,5 Toll-like receptors (TLRs),6 cytokines and cytokine receptors.6,7
microRNAs (miRNAs) are an abundant class of evolutionarily conserved, approximately 22 nt (21–23 nt) nucleotide noncoding RNAs that regulate gene expression post-transcriptionally by affecting the degradation and translation of target mRNAs.8 It has been suggested that miRNAs play an important role in the development and function of adaptive immunity.8,9 MiR-155 knockout mice failed to develop a protective response to bacteria after immunization,10 which suggested that miRNAs may regulate response to vaccination in humans. Single nucleotide polymorphisms (SNPs) or mutations may occur at the level of the miRNA biogenesis pathway genes, pri-miRNA, pre-miRNA or mature miRNA sequences (miRSNPs).11 Such polymorphisms or mutations may alter miRNA expression and/or maturation. Moreover, accumulated evidence suggests a strong association of miRSNPs with disease progression, diagnosis and prognosis12 and drug response.11 To the best of our knowledge, there is no report about the association of this class of SNPs with the response to human vaccine. Therefore, in the present study, we investigated whether six common miRSNPs contributed to variations in hepatitis B vaccine induced immune responses.
Results
SNPs in six miRNAs genes were studied for their influence on the responsiveness to hepatitis B vaccine. The call rates of the 6 SNPs were 100%. All genotype frequencies were in Hardy–Weinberg Equilibrium (HWE) (p > 0.05). Among the six selected miRSNPs, two SNPs (p < 0.05) showed significant association with non-responsiveness to hepatitis B vaccination.
The homozygous CC genotype of SNP rs2910164 in pre-mir-146a gene increased the risk for non-response to hepatitis B vaccine (OR = 1.71; 95% CI = 1.01–2.90; p = 0.045, q = 0.405), as did TT genotype of rs7372209 in pri-miR-26a-1 gene (OR = 2.49; 95% CI = 1.06–5.82; p = 0.031, q = 0.405) (Table 1).
Table 1. Association between miRSNPs and non-responsiveness to hepatitis B vaccine.
| SNP ID | Non- responder | Responder | p value | OR (95% CI) | q value | miRNAs | |
|---|---|---|---|---|---|---|---|
| n = 77(%) | n = 207(%) | ||||||
| rs11614913 | 0.499 | 0.599 | miR-196a2 | ||||
| CC | 19 (24.68) | 44 (21.26) | 0.538 (CC vs. CT+TT) | 1.21 (0.66,2.25) | 0.745 | ||
| CT | 33 (42.86) | 105 (50.72) | 0.238 (CT vs. CC+TT) | 0.73 (0.43,1.23) | 0.801 | ||
| TT | 25 (32.46) | 58 (28.02) | 0.464 (TT vs. CC+CT) | 1.24 (0.70,2.17) | 0.799 | ||
| C allele | 71 (46.10) | 193 (46.62) | 0.913 | 0.98 (0.68,1.42) | 0.775 | ||
| T allele | 83 (53.90) | 221 (53.38) | 1.02 (0.70,1.48) | ||||
| rs2910164 | 0.123 | 0.369 | miR-146a | ||||
| CC | 43 (55.84) | 88 (42.51) | 0.045 (CC vs. CG+GG) | 1.71 (1.01,2.90) | 0.405 | ||
| CG | 25 (32.47) | 92 (44.44) | 0.068 (CG vs. CC+GG) | 0.60 (0.35,1.04) | 0.408 | ||
| GG | 9 (11.69) | 27 (13.04) | 0.760 (GG vs. CC+CG) | 0.88 (0.40,1.97) | 0.855 | ||
| C allele | 111 (72.08) | 268 (64.73) | 0.099 | 1.41 (0.94,2.11) | 0.417 | ||
| G allele | 43 (27.92) | 146 (35.27) | 0.71 (0.47,1.07) | ||||
| rs895819 | 0.231 | 0.369 | miR-27a | ||||
| CC | 2 (2.60) | 17 (8.21) | 0.092 (CC vs. CT+TT) | 0.30 (0.07,1.32) | 0.408 | ||
| CT | 33 (42.86) | 77 (37.20) | 0.384 (CT vs. CC+TT) | 1.27 (0.70,2.16) | 0.864 | ||
| TT | 42 (54.55) | 113 (54.59) | 0.995 (TT vs. CC+CT) | 1.00 (0.59,1.69) | 0.995 | ||
| C allele | 37 (24.03) | 111 (26.81) | 0.501 | 0.86 (0.56,1.33) | 0.752 | ||
| T allele | 117 (75.97) | 303 (73.19) | 1.16 (0.75,1.78) | ||||
| rs2292832 | 0.494 | 0.462 | miR-149 | ||||
| CC | 11 (14.29) | 20 (9.66) | 0.267 (CC vs. CT+TT) | 1.56 (0.71,3.43) | 0.801 | ||
| CT | 34 (44.16) | 102 (49.28) | 0.443 (CT vs. CC+TT) | 0.81 (0.48,1.38) | 0.835 | ||
| TT | 32 (41.56) | 85 (41.06) | 0.940 (TT vs. CC+CT) | 1.02 (0.60,1.74) | 0.995 | ||
| C allele | 56 (36.36) | 142 (34.30) | 0.646 | 1.10 (0.74,1.61) | 0.775 | ||
| T allele | 98 (63.64) | 272 (65.70) | 0.91 (0.62,1.34) | ||||
| rs531564 | 0.659 | 0.599 | miR-124 | ||||
| CC | 2 (2.60) | 8 (3.86) | 0.606 (CC vs. CG+GG) | 0.66 (0.14,3.20) | 0.727 | ||
| CG | 17 (22.08) | 54 (26.09) | 0.488 (CG vs. CC+GG) | 0.80 (0.43,1.50) | 0.735 | ||
| GG | 58 (75.32) | 145 (70.05) | 0.381 (GG vs. CC+CG) | 1.31 (0.72,2.37) | 0.864 | ||
| C allele | 21 (13.64) | 70 (16.91) | 0.345 | 0.78 (0.46,1.31) | 0.690 | ||
| G allele | 133 (86.36) | 344 (83.09) | 1.29 (0.76,2.18) | ||||
| rs7372209 | 0.098 | 0.369 | miR-26a-1 | ||||
| CC | 37 (48.05) | 109 (52.66) | 0.490 (CC vs. CT+TT) | 0.83 (0.49,1.40) | 0.735 | ||
| CT | 29 (37.66) | 85 (41.06) | 0.603 (CT vs. CC+TT) | 0.87 (0.51,1.49) | 0.727 | ||
| TT | 11 (14.29) | 13 (6.28) | 0.031 (TT vs. CC+CT) | 2.49 (1.06,5.82) | 0.405 | ||
| C allele | 103 (66.88) | 303 (73.19) | 0.139 | 0.74 (0.50,1.10) | 0.417 | ||
| T allele | 51 (33.12) | 111 (26.81) | 1.35 (0.91,2.02) | ||||
All risk factors, including age, gender, BMI and genotype frequencies, were analyzed by multivariable logistic regression analysis, and both SNPs (rs2910164, rs7372209) were still showed significant association with non-responsiveness to hepatitis B vaccination after the analysis (OR = 1.74, 95% CI = 1.01–3.00, p = 0.046, and OR = 2.60, 95% CI = 1.07–6.31, p = 0.035). The present study demonstrated a power to detect an allelic association of 61.2% to 78.6% with an OR of 2.0 at a significance level of 0.05.
The SNPs in pre-mir-146a (rs2910164) was associated with variations in anti-HBs antibody levels (p = 0.035). And the GG genotype was associated with higher serum antibody levels (p = 0.011). The TT genotype of SNP (rs895819) in pre-miR-27a was associated with lower serum antibody levels than the other two genotypes (p = 0.046) (Table 2).
Table 2. Association between miRSNPs and antibody responses to hepatitis B vaccine.
| miRNAs | SNP ID | Responder n = 207(%) | Mean antibody level (mIU/ml) | p value |
|---|---|---|---|---|
| MiR-196a2 | rs11614913 | 0.344 | ||
| CC | 44 (21.26) | 572.31± 313.99 | ||
| CT | 105 (50.72) | 543.06 ± 274.37 | ||
| TT | 58 (28.02) | 490.55 ± 305.24 | ||
| CT+TT | 163 (78.74) | 524.38 ± 285.91 | 0.335 (CC vs. CT+TT) | |
| CT+CC | 102 (49.28) | 525.82 ± 310.18 | 0.672 (TT vs. CT+CC) | |
| CC+TT | 149 (71.98) | 551.70 ± 285.87 | 0.177 (CT vs. CC+TT) | |
| miR-146a | rs2910164 | 0.035 | ||
| CC | 88 (42.51) | 523.84 ± 305.29 | 0.024 (CC vs. GG) | |
| CG | 92 (44.44) | 505.71 ± 285.37 | 0.011 (CG vs. GG) | |
| GG | 27 (13.04) | 667.87 ± 238.22 | ||
| CG+GG | 119 (57.49) | 542.50 ± 282.77 | 0.651 (CC vs. CG+GG) | |
| CC+GG | 115 (55.56) | 557.67 ± 296.36 | 0.204 (CG vs. CC+GG) | |
| CC+CG | 180 (86.96) | 514.57 ± 294.59 | 0.011 (GG vs. CC+CG) | |
| miR-27a | rs895819 | 0.130 | ||
| CC | 17 (8.21) | 598.83 ± 280.36 | ||
| CT | 77 (37.20) | 574.64 ± 288.77 | ||
| TT | 113 (54.59) | 497.60 ± 293.05 | ||
| CT+TT | 190 (91.79) | 528.82 ± 293.02 | 0.345 (CC vs. CT+TT) | |
| CC+TT | 130 (62.80) | 510.83 ± 292.37 | 0.129(CT vs. CC+TT) | |
| CC+CT | 94 (45.41) | 579.01 ± 285.93 | 0.046(TT vs. CC+CT) | |
| miR-149 | rs2292832 | 0.798 | ||
| CC | 20 (9.66) | 495.38 ± 286.27 | ||
| CT | 102 (49.28) | 543.37 ± 296.67 | ||
| TT | 85 (41.06) | 533.23 ± 290.24 | ||
| CT+TT | 187 (90.34) | 538.76 ± 293.02 | 0.529 (CC vs. CT+TT) | |
| CC+TT | 105 (50.72) | 526.02 ± 288.51 | 0.670(CT vs. CC+TT) | |
| CC+TT | 122 (58.94) | 535.50 ± 294.37 | 0.956 (TT vs. CC+CT) | |
| miR-124 | rs531564 | 0.709 | ||
| CC | 8 (3.86) | 549.10 ± 373.60 | ||
| CG | 54 (26.09) | 561.83 ± 333.60 | ||
| GG | 145 (70.05) | 523.61 ± 271.66 | ||
| CG+GG | 199 (96.14) | 533.98 ± 289.40 | 0.886 (CC vs. CG+GG) | |
| CC+GG | 153 (73.91) | 524.95 ± 276.36 | 0.426 (CG vs. CC+GG) | |
| CC+CG | 62 (29.95) | 560.19 ± 335.74 | 0.410 (GG vs. CG+CC) | |
| miR-26a-1 | rs7372209 | 0.303 | ||
| CC | 109 (52.66) | 562.30 ± 304.75 | ||
| CT | 85 (41.06) | 510.26 ± 270.43 | ||
| TT | 13 (6.28) | 461.01 ± 314.08 | ||
| CT+TT | 98 (47.34) | 503.73 ± 275.35 | 0.150 (CC vs. CT+TT) | |
| CC+TT | 122 (58.94) | 551.50 ± 306.04 | 0.319 (CT vs. CC+TT) | |
| CC+CT | 194 (93.72) | 539.50 ± 290.64 | 0.349 (TT vs. CC+CT) |
Discussion
Vaccination is first selection to avoid the transmission of HBV. However, among people who receive hepatitis B vaccination according to the standard protocol, 5–10% are non-responders,3 and they remain susceptible to hepatitis B infection.
Poor immune response to hepatitis B vaccine is influenced by several factors such as increasing age, male sex, smoking and immunological tolerance.13-15 In addition, genetic associations with non-responsiveness have been identified. Here, we report the discovery of a potential new class of SNPs associated with non-responsiveness to hepatitis B vaccine: miRSNPs. Six common miRSNPs were selected, and an association analysis was performed to investigate the impact on immune response to hepatitis B vaccine.
We identified genetic variations in miRNA genes that were significantly associated with variations in antibody responses to hepatitis B vaccination. The frequency of two miRSNPs, rs2910164 in pre-miR-146a and rs7372209 in pri-miR-26a-1 gene, were differed significantly between non-responders and responders. The CC genotype of rs2910164 and TT genotype of rs7372209 resulted in a 1.74- and 2.60-fold increased risk of non-responsiveness compared with other genotypes, respectively. After correction for multiple testing by FDR analysis, both the two SNPs remained significant at the q value < 0.50, hence we expect at least 50% of these associations to be true positives. As this is the first study on the association of SNPs in miRNAs genes with response to hepatitis B vaccine. We tend to accept that the association is statistically significant, which may offer directions for further studies.
The GG genotype of SNP rs2910164 showed an association with higher anti-HBs titer. The TT genotype of SNP rs895819 was significantly associated with lower anti-HBs titer.
There are some speculative explanations for the association that we found. MiR-146a plays a critical role in regulation of innate and adaptive immune responses. MiR-146a is among the most highly expressed miRNAs in murine regulatory T cells and is induced upon activation of effector T cells.16 In an expression-profiling study in mice, Monticelli et al. demonstrated that miR-146a expression was higher in murine T helper (Th) type 1 cells but lower in Th2 and naïve T cells.17 All of these suggest an important role for miR-146a in regulation of T-cell-mediated response. HBsAg, the main component of hepatitis B vaccine, is a T-cell-dependent antigen. For it to activate immune response, Th cells must be involved. The SNP (rs2910164) in pre-miR-146a would affect mature miR-146a expression. Shen et al. reported that variant C allele miR-146a may result in high levels of mature miR-146.18 MiR146 has been proposed to target the 3′ UTRs of the TRAF6 and IRAK-1 genes, and regulated Toll-like receptor and cytokine signaling through a negative feedback loop.19 Curtale et al. reported that miR-146a is a modulator of IL-2 expression and activation-induced cell death in T lymphocytes.20 In our data, the frequency of the C allele of rs2910164 was higher in non-responders than it in the responders. However, further studies are needed to determine whether the SNP cause miR-146a overexpression in non-responsiveness group, and in consequently impair activation of T cells and Th immune response through deregulate Toll-like receptor signaling and/or reduce interleukin-2 expression.
Both miR-26 and miR-27a are among the 20 miRNAs that most frequently target immune genes.21 And miR-26 may contribute significantly to the regulation of innate immune responses.22 Similar to miR-146a, the potential mechanism of the effect of rs7372209 and rs895819 on the response to hepatitis B vaccine may be due to impairment of immunoregulation. Another possible reason is that the associations may be due to these polymorphisms being in linkage disequilibrium with other polymorphisms elsewhere in or located near the study genes that are related to non-responsiveness to hepatitis B vaccine. Therefore, further studies should focus on the precise mechanism of these miRNAs in response to hepatitis B vaccine.
This is the first evidence about an association between SNPs in miRNAs genes with immune response to hepatitis B vaccine. Although it was clear that miRNAs are class crucial regulators in required immunization, however, there was no published study about the role of miRNAs in human vaccine immune response. In addition, our study provides additional insights into the mechanism studies of the non-response to human vaccine. Furthermore, both qualitative analysis and quantitative analysis were used in our study to demonstrate the association, and the SNP (rs2910164) in pre-miR-146a showed significantly in both analyses, suggesting that it was statistically significant associations than expected by chance alone.
However, several limitations should be noted in our study. The study was performed only in Chinese Han population, further replication studies in other populations are thus needed to test this results. Additionally, there was limited powered to detect genes with small effects in our study. Hence the associations identified in the current study still need further validation in a larger cohort.
In conclusion, our study suggests the possible influence of SNPs in miRNAs genes in modulating the immune response to human vaccine. It also suggests that miRNAs play a role in the regulation of antibody responses to hepatitis B vaccine. Due to miRNA plasticity and its central role in transcriptional and post-transcriptional regulation, any such association could suggest a target for developing new hepatitis B vaccines for low responders.
Materials and Methods
Study subjects
The present study was conducted in a Chinese Han population. A total of 1481 study subjects were voluntarily recruited from the freshers at Guangdong Medical College in 2010 and 2011. All of them received written information about the study and gave their informed consent, and the study was approved by The Research Ethics Committee of Guangdong Medical College. None of the subjects included had any history of infection with HBV, hepatitis C virus or human immunodeficiency virus, and none were immunodeficient. None were vaccinated with hepatitis B vaccine, hepatitis A and B combined vaccine or anti-hepatitis B immunoglobulin. There were no smokers among the study subjects.
Hepatitis B vaccine (20 μg) was administered by deltoid intramuscular injection according to a 0-, 1- and 6-mo standard schedule (recombinant hepatitis B vaccine, Engerix-B, GlaxoSmithKline). Four to six weeks after the third dose, 5 ml peripheral venous blood was collected. The serum was separated for immediate testing of the anti-HBs level by commercial ELISA kits (Da An Gene Co. Ltd). Non-responders were defined as subjects with anti-HBs levels below 10 mUI/ml.
There were 77 participants with anti-HBs levels below 10 mIU/ml (5.20%), and they were included in the non-responder group. In addition, 207 controls were randomly selected from the responders (anti-HBs antibody > 10 mIU/ml). There were no significant differences in age, sex, and body mass index (BMI) between the two groups (Table 3). The allelic and genotypic frequencies were compared between the two groups. The association of the genotype with anti-HBs level was assessed in the control group.
Table 3. Demographic characteristic of the non-responders and responders.
| Non- responders (n = 77) | Responders (n = 207) | |
|---|---|---|
| Age (y) | 19.32 ± 0.81 | 19.00 ± 1.02* |
| Male sex | 45 | 97# |
| BMI | 19.30 ± 1.79 | 19.74 ± 1.92* |
*t-test, p > 0.05; #Pearson χ2 test, p > 0.05.
SNP selection and genotyping
SNP rs2910164 in pre-miR-146a,23,24 rs11614913 in pre-miR-196a225 and rs7372209 in pri-miR-26a-123 were considered as candidates for these miRNAs involvement in antigen recognition or immune response activation. rs895819 in pre-miR-27a and rs531564 in pri-miR-124 were also included. By using computational analyses to identify miRNAs binding sites, it has been found that miR-27 is one of preferentially target immune genes and miR-124 is one of most frequently target immune genes.21 Another common SNP, rs2292832 in pre-miR-149, was also included.
Genomic DNA was extracted from frozen clotted blood using RelaxGene Blood DNA System (Tiangen Biotech) according to the manufacturer’s instructions.
Genotyping of these SNPs was performed by multiplex SNaPshot technology as previously described,26,27 using an ABI fluorescence-based assay discrimination method (Applied Biosystems). The multiplex SNaPshot detection of single-base extended probe primers was based on fluorescence and extended length detected by capillary electrophoresis on an ABI3130XL Sequencer (Applied Biosystems).
The primers for polymerase chain reaction (PCR) amplification and SNaPshot extension reactions were both designed by Primer3 online software (frodo.wi.mit.edu/primer3/) according to the reference sequences from dbSNP (www.ncbi.nlm.nih.gov/SNP). The primers used in this study are listed in Table 4.
Table 4. Primers Sequences of six SNPs.
| SNP ID | PCR primer sequence | Extension primer sequence |
|---|---|---|
| rs11614913 | F:CCCCTTCCCTTCTCCTCCAGAT R:CCTCGACGAAAACCGACTGATG |
SR:TTTTTTTTTTTTTTTTTTTTTCGACGAAAACCGACTGATGTAACTCAG |
| rs2910164 | F:CTGGACTGCAAGGAGGGGTCTT R:GTCCTCAAGCCCACGATGACAG |
SR:TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTATATCCCAGCTGAAGAACTGAATTTCA |
| rs895819 | F:ACCCCTGTTCCTGCTGAACTGA R:GCAGGGCTTAGCTGCTTGTGAG |
SR:TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTGCTGCTTGTGAGCAGGGTYCAC |
| rs2292832 | F:GTCTTCACTCCCGTGCTTGTCC R:GGCCCGAAACACCCGTAAGATA |
SR:TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTCGGCGACCTGCGTTGTTCC |
| rs531564 | F:GTCACGGAGGAAGGTGTTGACC R:GCCTGTGACAGACAGGGGCTTA |
SR:TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTACAGACAGGGGCTTAGAGATGCAAA |
| rs7372209 | F:TGCCCAATGGCATAGCAAGAAT R:CTCTTGGCTCCTGTGGCTTCAT |
SR:TTTTTTTTTTTTTCCAGTCATGCTTACAGTCACGTGGTAC |
The PCR reactions for rs11614913, rs7372209 and rs2910164 was performed in a total volume of 20 μL containing 1 μL of DNA, 1 μL multiple PCR primers (the concentration was 1 μM), 10 × HotStarTaq buffer, 3.0 mM Mg2+, 0.3 mM dNTP and 1 unit of HotStarTaq polymerase (Qiagen Inc.). The PCR reactions for rs531564, rs2292832 and rs895819 were performed with 1 μL of DNA, 1 μL multiple PCR primers (the concentration was 1 μM except the primer for rs895819 was 2 μM) in a total volume of 20 μL containing 1 × GC buffer I, 3.0 mM Mg2+, 0.3 mM dNTP and 1 unit of HotStarTaq polymerase (Qiagen Inc.). The cycling conditions were 95 °C for 2 min, 11 cycles × (94 °C 20s, 65 °C–0.5 °C/cycle 40 sec, 72 °C 1 min 30 sec), 24 cycles × (94 °C 20 sec, 59 °C 30 sec, 72 °C 1 min 30 sec) and then 72 °C for 2 min.
The extension reaction to identify single nucleotide polymorphisms in the PCR products was performed in a total volume of 10 μL containing 5 μL SNaPshot Multiplex Kit (Applied Biosystems), 2 μL purified PCR product, 1 μL primer (the concentration was 0.8 μM except the primer for rs895819 was 1.6 μM) and 2 mL ultrapure water. The cycling conditions for extension were 96 °C for 1 min, 28 cycles of 96 °C for 10 sec, 52 °C for 5 sec, and 60 °C for 30 sec, and kept at 4 °C. Then each extended product (10 μL) was added to 1 unit shrimp alkaline phosphatase, incubated at 37 °C for 1 h, and the enzyme inactivated at 75 °C for 15 min. Then, 0.5 μL was added to 0.5 μL Liz120 SIZE STANDARD (Applied Biosystems), 9μL Hi-Di (Applied Biosystems), and sequenced by ABI3130XL Sequencer. Finally, genotypes were determined automatically using Genemapper4.0 software (Applied Biosystems).
Statistical analysis
Allele and genotype frequencies were calculated by direct counting. SNP-specific deviations from the HWE were tested using χ2 goodness-of-fit tests. Anti-HBs antibody level was expressed as mean and standard deviation. The genotype frequencies were compared between two groups by Pearson χ2 test. The strength of association was also assessed by calculating the odds ratio (OR) and 95% confidence interval (CI). Multivariable logistic regression analysis was used to adjust for confounders such as ages, genders and BMI. Univariate associations between genotypes and antibody levels were assessed by analysis of variance. All statistical tests were two-sided and p values < 0.05 were considered statistical significance. To correct for multiple hypothesis testing, the q value derived from the false discovery rate (FDR) was applied. A q value threshold of 0.50 was used to define significance.28 The statistical analyses were performed with SPSS (version 15.0).
Acknowledgments
This work was partly supported by grants from the Natural Science Foundation of Guangdong Province (s2011040002978), Guangdong Medical Research Foundation (A2012422) and Science Foundation of Dongguan (201010815214). We would like to thank Shanghai Genesky Bio-Tech Genetic Core Lab for their assistance in genotyping techniques.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Footnotes
These authors contributed equally to this work.
Previously published online: www.landesbioscience.com/journals/vaccines/article/24938
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