Skip to main content
NCBI home page
Virology Journal logoLink to Virology Journal
. 2015 Jun 11;12:87. doi: 10.1186/s12985-015-0313-5

Associations between hepatitis B virus basal core promoter/pre-core region mutations and the risk of acute-on-chronic liver failure: a meta-analysis

Feishu Hu 1, Sheng Bi 1, Huadong Yan 2, Yu Shi 1, Jifang Sheng 1,✉
PMCID: PMC4485863  PMID: 26063382

Abstract

Background

Several studies have suggested a relationship between hepatitis B virus (HBV) basal core promoter/pre-core mutations and HBV-induced acute-on-chronic liver failure (ACLF). Therefore, we evaluated this potential relationship using a meta-analysis.

Methods

Chinese or English studies from 1966 to January 31, 2014 were included in the analysis. A random or fixed-effects model was used to merge the odds ratios (ORs).

Results

We identified 31 case–control studies containing a total population of 1995 ACLF and 3822 chronic hepatitis B (CHB) patients. Several mutations were significantly correlated with ACLF: T1753V (1.889, 95 % confidence interval (CI) [1.357–2.631]), A1762T (2.696 [2.265–3.207]), G1764A (3.005 [2.077–4.347]), A1762T/G1764A (2.379 [1.519–3.727]), C1766T (1.849 [1.403–2.437]), T1768A (2.440 [1.405–3.494]), A1846T (3.163 [2.157–4.639]), G1896A (2.181 [1.800–2.642]), G1899A (3.569 [2.906–4.385]) and G1896A/A1762T/G1764A (1.575 [1.172–2.116]). Additionally, HBeAg-negative status was also statistically significant for the progression to ACLF (OR = 2.813, 95 % CI = 2.240–3.533, p < 0.001). However, there was no association between ACLF development and HBV genotype.

Conclusions

The HBV basal core promoter/pre-core mutations T1753V, A1762T, G1764A, C1766T, T1768A, A1846T, G1896A and G1899A, and an HBeAg-negative status correlate with an increased risk of HBV-ACLF.

Electronic supplementary material

The online version of this article (doi:10.1186/s12985-015-0313-5) contains supplementary material, which is available to authorized users.

Keywords: Hepatitis B virus, Mutation, Acute-on-chronic liver failure, Hepatitis B e antigen

Background

Acute-on-chronic liver failure (ACLF) occurs when liver function is suddenly compromised as a result of an incident [1]. In 2009, the Asia-Pacific Association for the Study of the Liver (APASL) recommended the following definition for ACLF: acute hepatic damage showing coagulopathy and jaundice, with encephalopathy and/or ascites within 4 weeks, whether or not the patient had been diagnosed with a chronic liver disease [2]. The majority of Chinese ACLF patients showed HBV-induced hepatitis [3, 4]. Although the biological pathways that mediate HBV infection and cause liver failure remain unknown, studies suggest that mutations in the HBV viral genome may play a role in the progression of liver diseases [5–8]. HBV mutations in the basal core promoter (BCP)/pre-core (PC) regions are relatively well understood [9–11]. BCP mutations lead to enhanced HBV replication in vitro, while PC mutations break the immune tolerance of chronic HBV infection by inhibiting hepatitis B e antigen (HBeAg) translation [9–11]. Therefore, it is important to better understand the relationship between HBV mutations and ACLF, which may have clinical utility. Several studies have shown that HBV mutations in the BCP or PC regions are related to the risk of ACLF, although the sample size and the mutational sites tested were limited. Therefore, we performed a meta-analysis to quantitatively evaluate data from several available studies and investigated the relationship between HBV BCP/PC variations and the risk of developing ACLF.

Results

Search results

We identified 2790, 831, 25 and 15 articles from the PubMed, EMbase, Biomed Central and ClinicalTrials databases, respectively. The four primary Chinese databases used were: Chinese Biological Medicine, WANFANG DATA, VIP and China National Knowledge Infrastructure, which yielded 889, 1564, 1011 and 1303 studies, respectively. This approach resulted in 3478 and 2203 studies after removing duplicates from English and Chinese databases, respectively. After title screening (4908 not relevant to HBV mutation or liver failure, 310 associated with human immunodeficiency virus (HIV) or hepatitis C virus), 463 potential articles remained, which were reduced to 61 after reviewing abstracts (338 were not related to mutations, 35 not related to ACLF and 29 related to hepatocellular carcinoma [HCC]). In addition, 30 articles were removed after completing a full text scan (17 lacked control groups, 5 participants were co-infected with other hepatic viruses, 2 were co-infected with HIV and 6 had HCC). We included 31 articles in our meta-analysis (Fig. 1).

Fig. 1.

Fig. 1

Open in a new tab

Flow chart of article selection

Characteristics of trials included in this meta-analysis

The 31 trials were all case–control trials from China. The primary mutation detection method was nested polymerase chain reaction and sequencing. The quality of the studies on the Newcastle-Ottawa Scale (NOS) scale was between 5 and 7 (see Additional file 1: Table S1). There were 5817 HBV patients, 1995 of whom had ACLF. The most common mutations in the BCP/PC regions that were associated with ACLF progression were T1753V, A1762T/G1764A, A1762T, G1764A, C1766T, T1768A, A1846T, G1862T, G1896A, G1899A and G1896A/A1762T/G1764A (Table 1).

Table 1.

Main characteristics of included trials

Study NCA NCO Mutation site Detection method Matching factors
Age Sex Genotype HBV DNA
Aiming Zhang, 2013 29 52 T1753V, A1762T, G1764A, A1762T/G1764A, A1846T, G1896A, G1899A NP, AS + + + +
Aiming Zhang2, 2013 58 51 T1753V, A1762T, G1764A, A1762T/G1764A, A1846T, G1896A, G1899A NP, AS + + + +
Lei Xiao, 2013 77 136 T1753V, A1762T/G1764A, C1766T, T1768A, A1846T, G1862T, G1896A, G1899A NP, AS + + - -
Xiaodong Li, 2013 146 239 T1753V, A1762T/G1764A, C1766T, T1768A, A1846T, G1896A, G1899A NP, AS + + - -
X Ren, 2010 (40) 75 328 T1753V, A1762T, G1764A, C1766T, T1768A, G1896A, G1899A NP, AS + + + +
Zhihui Xu, 2010 298 495 T1753V, A1762T, G1764A, C1766T, T1768A, G1862T, G1896A, G1899A NP, AS + + + -
Ling Yang, 2010 39 44 A1762T/G1764A, G1862T, G1896A, G1899A SNP, AS - + + -
Zhengang Zhao, 2010 20 19 T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1862T, G1896A, G1899A, A1762T/G1764A/G1896A NP, DS - + + -
Xiaoyan Ma, 2012 44 28 T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1896A, G1899A, A1762T/G1764A/G1896A NP, S - + + -
Zhiwei Li, 2002 13 10 A1846T, G1862T, G1896A RP, SA ND ND ND -
Shoubing Tang, 2005 30 30 A1762T/G1764A, G1896A RP, CS + + ND -
Yintang Jia, 2009 8 78 T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1896A, G1899A NP, DS ND ND ND -
Ling Jiang, 2013 146 239 A1762T/G1764A, G1896A QPMK, DS + + ND -
Wenjun Du, 2005 9 75 A1762T, G1764A, G1896A RP, GC, S ND ND ND -
Xiumei Zhou, 2009 80 80 A1762T/G1764A, G1896A, G1899A RP, GC + + ND -
Mingxian Zhou, 2004 22 56 A1762T, G1896A UK ND ND + -
Xiaoqiang Ren, 2009 348 610 T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, G1862T, G1896A, G1899A, A1762T/G1764A/G1896A NP, AS + + + -
Lei Jiang, 2010 26 78 G1896A NP, RFLP ND ND ND -
Jinqiang Li, 2006 30 20 A1762T/G1764A, G1896A RP, MS + + ND -
Chengyong Liu, 2007 34 186 A1762T/G1764A, G1896A, A1762T/G1764A/G1896A RP, MGS ND ND ND -
Xinyu Liu, 2005 14 75 A1762T, G1764A, A1762T/G1764A, G1896A, A1762T/G1764A/G1896A LAS ND ND ND -
Shuren Liang, 2003 23 68 G1896A RP, OAS ND + ND -
Zhidong Zang, 2007 17 81 A1762T/G1764A RP, LAS ND ND ND -
Tao Yan, 2010 49 45 T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1896A, G1899A, A1762T/G1764A/G1896A NP, AS - + + -
Wei Guo, 2006 38 40 T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, G1862T, G1896A, G1899A, A1762T/G1764A/G1896A RP, CS + + ND -
Yanhong Yu, 2008 25 98 A1762T/G1764A RP, GC ND ND ND -
Guanghui Wu, 2008 30 30 A1762T/G1764A, G1896A RP, RFLP ND + + -
Hangdi Xu, 2013 12 12 A1762T, G1764A, A1846T, G1896A RP, IS + + + +
Fan Li, 2008 (31) 87 196 T1753V, A1762T, G1764A, G1862T, G1896A, G1899A NP, AS ND + ND -
Lu Xu, 2012 64 69 T1753V, A1762T, G1764A, A1762T/G1764A, T1768A, G1862T, G1896A, G1899A, A1762T/G1764A/G1896A RP, AS + - ND -
Hangdi Xu2, 2013 104 254 A1846T, G1896A SNP, AS ND - - -
Open in a new tab

NCA number of ACLF patients, NCO number of CHB patients, S sequencing, Apparatus unknown, NP nested PCR, SNP semi-nested PCR, RP routine PCR, AS ABI3730XL PRISM sequencing, SA Sequence Analysis, CS CEQ2000XL sequencing, DS direct sequencing, QPMK Quickchange point mutation kit, GC gene chip hybrid, UK unknown, RFLP restriction fragment length polymorphism, MS MegaBACE DNA sequencing, MGS Mgeabace-500 sequencing, LAS LicorIR2 Automatic DNA sequencing, OAS OpenGene Automated DNA Sequencing, IS Illumina sequencing, ND not determined, + = matched; - = unmatched; ABI PRISM 3730xl DNA Analyzer

Patient characteristics

The studies that were included in this meta-analysis compared patients with ACLF and patients with CHB of different severities (mild, moderate and severe), or CHB patients without differentiating by severity. There were mostly males in both the ACLF and CHB groups, and the main genotypes were B and C. There were significantly fewer ACLF HBeAg-positive patients than HBeAg-negative patients, while the opposite was seen in the CHB group (Table 2).

Table 2.

Patient characteristics of included trials

Trials Group N Age, y Gender (m/f) Genotype (B/O) HBeAg (P/N) TB (μmol/L) HBV DNA (log10IU/ml)
Aiming Zhang A 29 43.4 27/2 7/22 11/18 330.2 3.86
C 52 42.3 42/10 16/36 32/20 NG 4.63
Aiming Zhang2 A 58 47.4 48/10 12/46 26/32 338.4 4.02
C 51 46.2 39/12 8/43 19/32 NG 4.69
Lei Xiao A 77 38.2 70/7 71/6 22/55 427.5 NG
C 136 36.9 113/23 82/54 79/57 37.62 NG
Xiaodong Li A 146 47.4 119/27 30/116 45/101 313.4 5
C 239 46.2 207/32 52/187 140/99 74.4 5.8
X Ren A 75 39 67/8 23/52 29/46 451 5.3
C 328 38 281/47 54/274 194/134 12.8 5.2
Zhihui Xu A 298 45.9 255/43 63/235 99/199 418.5 5.48
C-M/S 495 38.3/39.1 427/68 82/413 261/234 16.4/164.2 5.26/5.99
Ling Yang A 39 36 36/3 24/10 11/28 353 5.75
C 44 26 36/8 22/22 36/8 NG 9.16
Zhengang Zhao A 20 49.7 14/6 0/16 8/12 287.37 5.82
C 19 40.37 14/5 2/15 14/5 19.75 7.67
Xiaoyan Ma A 44 51.6 31/13 0/44 NG NG NG
C 28 38.7 20/8 2/26 NG NG NG
Zhiwei Li A 13 21 to 58 17/6 NG NG NG NG
C 10 NG NG NG NG
Shoubing Tang A 30 21 25/5 NG 13/17 NG 1.47
C 30 20 24/6 NG 16/14 NG 3.29
Yintang Jia A 8 NG NG NG NG NG NG
C 78 NG NG NG NG NG NG
Ling Jiang A 146 46 119/27 NG 49/97 313.4 5
C-M/S 239 41/38 206/33 NG 146/93 42.38/106.54 6.27/5.39
Wenjun Du A 9 NG NG NG NG NG NG
C 75 NG NG NG NG NG NG
Xiumei Zhou A 80 48.6 108/72 NG NG NG NG
C 80 NG NG NG NG
Mingxian Zhou A 22 NG NG 3/19 NG NG 4.31
C 56 NG NG 9/47 NG NG 4.72
Xiaoqiang Ren A 348 46 292/56 53/200 132/216 255.9 4.55
C-M/S 610 38/35 518/92 95/476 386/224 12.4/55.4 4.43/5.21
Lei Jiang A 26 NG NG NG NG NG NG
C 78 NG NG NG NG NG NG
Jinqiang Li A 30 48.1 24/6 NG NG NG NG
C 20 43.9 15/5 NG NG NG NG
Chengyong Liu A 34 NG NG NG NG NG NG
C 186 NG NG NG NG NG NG
Xinyu Liu A 14 NG NG NG NG NG NG
C 75 NG NG NG NG NG NG
Shuren Liang A 23 39.71 18/5 NG NG NG NG
C-M0/M1/S 68 35/36.1/35.5 55/13 NG NG NG NG
Zhidong Zang A 17 NG 10/7 NG NG 342.3 2.25
C 81 NG 64/17 NG NG 51.9 1.83
Tao Yan A 49 45.8 42/7 9/40 23/26 312.2 4.88
C 45 33.9 36/9 12/33 36/9 16.5 6.91
Wei Guo A 38 32.6 34/4 NG 21/17 NG 5.09
C 40 30.2 33/7 NG 26/14 NG 5.48
Yanhong Yu A 25 NG NG NG NG NG NG
C 98 NG NG NG NG NG NG
Guanghui Wu A 30 40 25/5 6/24 NG NG NG
C 30 29 20/10 4/26 NG NG NG
Hangdi Xu A 12 35 11/1 10/2 4/8 324.9 6.71
C 12 35.7 10/2 8/4 10/2 15.6 6.74
Fan Li A 87 45.4 69/18 NG 27/60 331 4.42
C 196 38.8 170/26 NG 130/66 23.8 5.42
Lu Xu A 64 35.1 57/7 NG 31/33 372.2 3.89
C 69 29.5 48/21 NG 53/16 46.5 5.49
Hangdi Xu2 A 104 40.9 91/13 68/36 51/53 317.5 6.09
C-M/S 254 37.6/40.7 186/68 51/203 185/69 14.9/98.3 6.14/5.77
Open in a new tab

A ACLF patient group, C CHB patient group, N number of subjects, M0 mild, M1 moderate, S severe, NG not given, m/f male/female, B/O genotype B/other genotypes, TB Total bilirubin, HBeAg hepatitis B e antigen, P HBeAg positive, N HBeAg negative, PTA Prothrombin activity, ALT alanine aminotransferase, AST Aspertate Aminotransferase

Data synthesis

Overall risk estimates

The risk assessment for ACLF patients with the mutations of interest in the individual trials is summarized in Additional file 2: Table S2 and Fig. 2. Overall, the following mutations were found to be meaningfully related to ACLF risk (shown as summary OR and 95 % [CI]): T1753V (1.919 [1.414–2.606]), A1762T (2.685 [2.264–3.185]), G1764A (2.901 [2.041–4.122]), A1762T/G1764A double mutation (2.376 [1.548–3.648]), C1766T (1.849 [1.403–2.437]), T1768A (2.199 [1.563–3.094]), A1846T (3.163 [2.157–4.639]), G1896A (2.181 [1.800–2.642]), G1899A (3.525 [2.882–4.312]) and G1896A/A1762T/G1764A triple mutation (1.575 [1.172–2.116]). G1862T was not significantly associated with ACLF risk, but when we removed the study conducted by Xiaoqiang Ren, statistical significance was achieved (summary OR = 2.579 [1.510–4.405], p = 0.001).

Fig. 2.

Fig. 2

Open in a new tab

Summary odds ratio (OR) of acute-on-chronic liver failure for A1762T, G1764A, A1762T/G1764A and G1896A mutations. Squares represent study-specific estimates (size of the square reflects the study-specific statistical weight); horizontal lines represent 95 % confidence intervals (CIs); diamonds represent summary estimates with corresponding 95 % CIs. Test for heterogeneity: (G1896A) p = 0.002, I2 = 48.1 %; (A1762T/G1764A) p < 0.001, I2 = 80.7 %; (A1762T) p = 0.164, I2 = 25.7 %; (G1764A) p = 0.004, I2 = 56.4 %. A random-effects model was used for G1896A, A1762T/G1764A and G1764A, and a fixed-effects model was used for A1762T. All statistical tests were two-sided

Subgroup analysis

We evaluated two subgroups, one matched by only patient age and sex, and the other matched by HBV genotype and DNA load, age and sex. The summary OR of ACLF risk for several variations was lower in matched subgroups than that in unmatched subgroups, such as T1753V, A1762T, G1764A, C1766T, G1896A, G1899A and A1846T, while an opposite result was observed for A1762T/G1764A and T1768A (Table 3).

Table 3.

Pooled unadjusted risk estimates of ACLF after stratification or matching

Mutation site Matching factor OR _LCI _UCI P
T1753V unmatched 1.919 1.414 2.606 0.000
age and sex matched 1.481 0.982 2.234 0.061
age, sex, genotype and HBV DNA matched ND ND ND ND
A1762T unmatched 2.685 2.264 3.185 0.000
age and sex matched 2.307 1.555 3.422 0.000
age, sex, genotype and HBV DNA matched 1.326 0.585 3.007 0.499
G1764A unmatched 2.901 2.041 4.122 0.000
age and sex matched 2.023 1.013 4.041 0.046
age, sex, genotype and HBV DNA matched 1.310 0.555 3.094 0.538
A1762T/G1764A unmatched 2.376 1.548 3.648 0.000
age and sex matched 2.602 1.270 5.333 0.009
age, sex, genotype and HBV DNA matched ND ND ND ND
G1896A unmatched 2.181 1.800 2.642 0.000
age and sex matched 2.014 1.505 2.695 0.000
age, sex, genotype and HBV DNA matched 1.479 1.017 2.152 0.041
G1899A unmatched 3.525 2.882 4.312 0.000
age and sex matched 3.171 2.464 4.081 0.000
age, sex, genotype and HBV DNA matched ND ND ND ND
C1766T unmatched 1.849 1.403 2.437 0.000
age and sex matched 1.719 1.226 2.411 0.002
age, sex, genotype and HBV DNA matched ND ND ND ND
T1768A unmatched 2.199 1.563 3.094 0.000
age and sex matched 2.203 1.425 3.405 0.000
age, sex, genotype and HBV DNA matched ND ND ND ND
A1846T unmatched 3.163 2.157 4.639 0.000
age and sex matched 2.854 2.127 3.831 0.000
age, sex, genotype and HBV DNA matched ND ND ND ND
Open in a new tab

ND not determined, OR odds ratio, _LCI low limit of 95 % confidence interval, _UCI upper limit of 95 % confidence interval

Prediction of ACLF by HBV mutation

We evaluated mutation frequency as a possible biomarker to predict ACLF. Most of the mutation sites showed low sensitivity and relatively high specificity, except A1762T, which had a sensitivity of 74.5 % (95 % CI = 71.9–76.9 %) and specificity of 45.8 % (95 % CI = 43.7–47.9 %). G1764A showed a high positive prediction value (PPV; 80.1 %, 95 % CI, 77.7–82.4; Table 4).

Table 4.

Sensitivity and specificity of single and combined mutations for prediction of ACLF

Mutation site Mutation status No. of ACLF patients No. of patients without ACLF Sensitivity % (95 % CI) Specificity, % (95 % CI) PPV NPV
T1753V pos 392 397 29.3 (26.9 to 31.9) 83.3 (81.8 to 84.8) 49.7 (46.1 to 53.2) 67.8 (66.0 to 69.5)
neg 945 1986
A1762T pos 872 1207 74.5 (71.9 to 76.9) 45.8 (43.7 to 47.9) 41.9 (39.8 to 44.1) 77.3 (75.0 to 80.0)
neg 299 1019
G1764A pos 921 228 43.0 (40.9 to 45.1) 80.6 (78.3 to 82.9) 80.1 (77.7 to 82.4) 43.7 (41.6 to 45.9)
neg 1221 949
A1762T/G1764A pos 678 825 51.6 (48.9 to 54.4) 63.1 (61.1 to 65.1) 45.1 (42.6 to 47.7) 69.0 (66.9 to 71.0)
neg 635 1412
C1766T pos 113 118 10.3 (8.6 to 12.2) 94.1 (93.0 to 95.1) 48.9 (42.3 to 55.6) 65.8 (64.0 to 67.5)
neg 986 1897
T1768A pos 80 64 6.9 (5.5 to 8.5) 96.9 (96.1 to 97.6) 55.6 (47.1 to 63.8) 65.1 (63.4 to 66.8)
neg 1083 2020
A1846T pos 304 251 54.7 (50.4 to 58.9) 72.8 (69.8 to 75.6) 54.8 (50.5 to 59.0) 72.7 (69.7 to 75.5)
neg 252 670
G1896A pos 1025 1254 52.6 (50.4 to 54.8) 65.6 (64.0 to 67.1) 45.0 (42.9 to 47.0) 72.1 (70.5 to 73.6)
neg 924 2386
G1899A pos 323 182 22.2 (20.1 to 24.4) 92.7 (91.7 to 93.7) 64.0 (59.6 to 68.2) 67.2 (65.6 to 68.8)
neg 1133 2325
G1896A/A1762T/G1764A pos 107 135 17.6 (14.7 to 20.9) 87.4 (85.2 to 89.3) 44.2 (37.9 to 50.7) 65.1 (62.6 to 67.6)
neg 500 934
Open in a new tab

Pos mutation positive, neg mutation negative, PPV positive predictive value, NPV negative predictive value

HBV genotype and HBeAg status

The summary OR of HBeAg-negative was 2.813 (95 % CI [2.240–3.533], p < 0.001). However, there was no evidence indicating that the HBV genotype B was significantly related to ACLF (Fig. 3), although we found that this result was unstable using a sensitivity analysis of the following studies: Aiming Zhang, Xiaodong Li, Zhengang Zhao, Xiaoyan Ma, Mingxian Zhou and Tao Yan. When these studies were removed, the summary OR p value was less than 0.05, indicating that more studies were needed to determine the relationship between HBV genotypes and ACLF development.

Fig. 3.

Fig. 3

Open in a new tab

Summary OR of acute-on-chronic liver failure for genotypes and HBeAg status. Summary OR for genotypes B and C and for HBeAg-negative to HBeAg-positive status. Squares represent study-specific estimates (the size of the square reflects the study-specific statistical weight); horizontal lines represent 95 % CIs; diamonds represent summary estimates with corresponding 95 % CIs. Test for heterogeneity: p < 0.001, I2 = 79.0 %. A random-effects model was used. All statistical tests were two-sided

Assessment of within-group heterogeneity, publication bias and sensitivity analysis

There was a large amount of heterogeneity between different trials for T1753V, G1764A, A1846T, G1862T, G1896A and A1762T/G1764A. We therefore conducted a sensitivity analysis using a “leave one out” approach and Egger’s testing, and found that these mutations were not influential, except for G1862T. Except for those with G1764A and G1896A/A1762T/G1764A, we did not observe any publication bias with T1753V, A1762T, A1762T/G1764A, C1766T, T1768A, A1846T, G1862T, G1896A or G1899A, (Table 5 and Fig. 4).

Table 5.

Assessment of within-group heterogeneity, publication bias and sensitivity analysis

Mutation site P value for heterogeneity P value for Egger’s test Sensitivity analysis
T1753V 0.006 0.923 -
A1762T 0.164 0.181 -
G1764A 0.004 0.100 -
A1762T/G1764A 0.000 0.455 -
C1766T 0.852 0.300 -
T1768A 0.681 0.291 -
A1846T 0.037 0.856 -
G1862T 0.001 0.125 +
G1896A 0.002 0.520 -
G1899A 0.307 0.591 -
G1896A/A1762T/G1764A 0.073 0.045 -
Open in a new tab

The summary OR did not change statistical significance when running sensitivity analysis. ‘+’ = the P value for summary OR reached statistical significance of 0.001 when the trial conducted by Xiaoqiang Ren was removed

Fig. 4.

Fig. 4

Open in a new tab

Funnel plot for A1762T, G1764A, A1762T/G1764A and G1896A. The dashed line represents 95 % CIs. Circles represent individual studies

Discussion

Our meta-analysis showed that T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1896A, G1899A and G1896A/A1762T/G1764A were all related to increasing the risk of HBV-ACLF by a factor of 1.919, 2.685, 2.901, 2.376, 1.849, 2.199, 3.163, 2.181, 3.525 and 1.575, respectively.

To further confirm these results, several significant confounders were matched. Age and sex have been shown to influence progression of high-level hepatic diseases in CHB patients [12]. A high HBV DNA copy number may independently accelerate progression of hepatocirrhosis and HCC [13, 14]. Additionally, compared with genotype B, genotype C was related to more aggressive hepatic necroinflammation, a more rapid rate of progression to cirrhosis and HCC development [15–17], although an association between HBV genotypes B and C and ACLF was not suggested in our study. Most mutations remained significantly associated with ACLF development in age and sex-matched groups and the association with G1896A was still significant after matching age, sex, HBV genotype and HBV DNA load. However, the summary ORs were higher in the confounder-unmatched and age- or sex-only-matched studies than in the age, sex, genotype and DNA load-matched studies. Thus, our results suggest a significant association between HBV variations in BCP/PC regions and the risks of developing ACLF.

The causal relationship between HBV BCP/PC mutations and ACLF development remains unknown. ACLF development was promoted by both acute factors (precipitating events) and chronic factors (underlying chronic liver diseases) [18]. Previous studies indicated that the role of HBV BCP/PC mutations that promote ACLF were more likely to influence the severity of chronic factors, because the mutations were detected both in CHB and HBV-ACLF patients. It was also reported that HBV BCP/PC variations appeared less frequently in CHB patients than in cirrhotic patients [19, 20], suggesting a process where mutations accumulate during CHB infection and are associated with late-stage viral infection. Thus, these results suggested that patients with BCP/PC mutations had more advanced HBV-related chronic liver diseases, and thus were more susceptible to hepatic insult and more likely to develop ACLF. Accumulating evidence suggests that mutations in the BCP/PC region might exacerbate liver injury by affecting HBeAg expression and/or viral replication, which may in turn affect the immune response to HBV [21]. For example, Yang et al. suggested that HBeAg expression in the perinatal infection period caused immune tolerance [22]. Another characteristic of HBeAg that might accelerate chronic infection is that it may imitate the core protein to weaken the immune response caused by antibodies in infected hepatocytes [10]. When the occurrence of HBV mutants in different phenotypes disturbs the balance, the altered virus–cell relationship might activate adverse immune responses in some patients, causing massive hepatocyte necrosis.

When exploring the potential value of HBV variation in predicting HBV-ACLF, we found that T1753V, G1764A, C1766T, T1768A, G1899A and G1896A/A1762T/G1764A triple mutations were useful in predicting ACLF. A combination of A1762T/G1764A and G1896A showed a higher specificity than A1762T/G1764A double mutations (Table 4), suggesting that mutations that accumulate at different sites have synergistic effects in promoting the risk of HBV-ACLF. The results indicated that the above HBV mutations may be used as biomarkers for supporting the development of HBV-associated ACLF.

Our study also showed the relationship between HBeAg-negative status and the risk of ACLF using a pooled OR = 2.813, p < 0.001. However this relationship was probably not independent. In G1896A patients, the concentration of serum toll-like receptor 2 (TLR2) reached a significantly higher level than in HBV-infected patients lacking G1896A [23]. In the absence of HBeAg, HBV up-regulated TLR2 expression on CD14+ cells [24]. TLR2 is a potential connection between G1896A and HBeAg-negative status.

This study had several limitations. First, all trials were observational so that unidentified confounders could not be eliminated. Second, because we searched only Chinese and English articles, selection bias based on language could not be avoided. Third, the data was insufficient to allow analysis of mutations such as G1896A/G1899A, G1896A/G1899A/A1762T/G1764A and C1913V that were implicated in ACLF development in some studies [25–31]. Additionally, HBV mutations in other regions were not analyzed in the study. For example, pre-S/S region mutations were observed at an advanced stage of chronic HBV infection [32, 33]. The pre-S deletion mutation has been reported to increase with liver disease progression [34]. In addition, pre-S/S region mutations could alter the immune response against HBV by affecting neutralization antibody epitopes [35] or cytotoxic T lymphocyte epitope binding affinity [36]. Thus, ongoing studies are needed to evaluate the clinical relevance of rare mutations in the BCP region and mutations in other regions. Fourth, the conclusions in this article might not be universally applicable, because all the selected trials were conducted in China. Although no study has reported a direct relationship between the risk of ACLF and country or race, the distribution of HBV genotypes or quasispecies differs among countries and races. For example, the most prevalent HBV genotypes in China are B and C, whereas genotypes A and D are the most prevalent in Europe [37]. Although our analysis did not show a different association between genotype B or C and ACLF risk, it is unknown whether there was a different connection between other HBV genotypes and ACLF. Thus, this conclusion needs to be validated for countries or races where other HBV genotypes are the most prevalent. Fifth, summary ORs were not conducted in most manuscripts included in this meta-analysis and there were no adjusted ORs. Sixth, if the sample size were sufficiently large, grouping the HBV patients based on grades, such as HBV carriers, CHB and hepatocirrhosis, would show whether the mutations accumulated during CHB progressed to advanced liver diseases, including ACLF.

We discovered that HBV BCP/PC variations such as T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1896A, G1899A and G1896A/A1762T/G1764A, and HBeAg-negative status correlated with an increased risk of HBV-ACLF. Detecting these variations in CHB patients may help to identify those who are at a high risk of developing ACLF. However, further prospective studies are needed to confirm our findings and whether HBV BCP/PC mutations contribute directly to the development of ACLF. The effect of HBV BCP/PC mutations on host viral-specific immunity also needs to be clarified.

Conclusions

The HBV BCP/PC mutations T1753V, A1762T, G1764A, C1766T, T1768A, A1846T, G1896A and G1899A, and an HBeAg-negative status correlate with an increased risk of HBV-ACLF.

Methods

Search strategy and inclusion/exclusion criteria

We searched PubMed using the following strategy: (“Hepatitis B virus” [Mesh]) AND “mutation” [Mesh] from January 1, 1950 to January 31, 2014. The search strategy for EMbase was “pub-date > 1994 and TITLE-ABSTR-KEY (hepatitis B virus), and TITLE-ABSTR-KEY (mutation)”. Biomed Central was searched using “hepatitis B virus (All words) in Title + Abstract + Text, and mutation (All words) in Title + Abstract + Text from 1997 to 2014”. ClinicalTrials was searched with “hepatitis B virus” AND “mutation” without limitation. The main Chinese databases were searched using: Chinese Biological Medicine (1978 to January 31, 2014), WANFANG DATA (1997 to January 31, 2014), VIP (1989 to January 31, 2014), China National Knowledge Infrastructure (1994 to January 31, 2014); the search strategy was “hepatitis B” [Abstract] AND “mutation” [Abstract]. The inclusion criteria were: 1) studies contained control groups; 2) ACLF diagnosis was based on the APASL criteria, as follows: serum bilirubin ≥5 mg/dl and coagulopathy (INR ≥ 1.5 or PTA < 40 %) are mandatory. Ascites and/or encephalopathy were determined by physical examination within 4 weeks [38], or the ACLF diagnosis was based on the criteria recommended by the Chinese Society of Infectious Disease and the Chinese Society of Hepatology: HBV infection history; total serum bilirubin >10 mg/dl, PTA < 40 % and recent complications that also meet APASL criteria; 3) BCP or PC mutations were detected; 4) the outcome was ACLF; and 5) ORs and 95 % CIs were shown or could be calculated from original data. Studies without control groups or studies in which patients were co-infected with another hepatitis virus or HIV, with the presence of other underlying chronic liver diseases (such as Wilson disease and autoimmune hepatitis) or liver cancer were excluded. For studies that contained over-lapping populations, the study containing the larger number of participants or the most recent study was included.

Data extraction

Feishu Hu and Sheng Bi extracted information independently as follows: publication year, location, study design, number and subject characteristics, HBV mutations, genotypes, HBeAg status, variation testing approach and probable confounding factors. All authors discussed results and reached an agreement if there were discrepancies. BCP/PC region mutation sites were included. Patients co-infected with wild-type viruses and BCP/PC mutated viruses were excluded. Subjects with a single mutation were excluded when assessing A1762T/G1764A double mutations and A1762T/G1764A/G1896A triple mutations.

Study quality assessment

Feishu Hu and Sheng Bi independently evaluated the quality of trials using the NOS, which was developed for case–control studies. Each study that was included was judged on three broad perspectives: selection of study groups, comparability of groups and ascertainment of exposure for case–control studies. Disagreements were resolved by discussion between all authors.

Statistical analysis

The effect measures were ORs and the corresponding 95 % CIs. Within-study heterogeneity was assessed using Cochrane’s Q-test and the I2 test [39]. Summary ORs were pooled by a random or fixed-effect model based on the results of a heterogeneity test. To detect the stability with primary analysis, we conducted a sensitivity analysis using a “leave one out analysis”. Publication bias was detected using funnel plots and the Egger test [40]. Significant publication bias was believed to be present if a p value was less than 0.1. We also conducted subgroup analysis by stratifying the study participants according to probable confounders such as sex, age, HBV DNA and HBV genotype and we calculated the respective summary risk estimates. We used Stata software (version 12.0; Stata Corp, College Station, TX) to conduct the analysis and to calculate the ACLF summary estimates for the HBV genotype, HBeAg status and T1753V, A1762T, G1764A, A1762T/G1764A, C1766T, T1768A, A1846T, G1862T, G1896A, G1899A and A1762T/G1764A/G1896A mutations for ACLF patients. The following mutation sites were also detected in the included studies: G1613A, C1653T, 1752G, T1754V, T1753V/A1762T/G1764A, T1758C, G1764A/C1766T/T1768A, T1770A, 1773 T, G1775A, C1799V, T1800C, T1803C, G1809T, A1814C, A1837G, A1846G, T1853C, T1858C, G1896A/G1899A, G1896A/G1899A/A1762T/G1764A, C1913V, 1915A/C, T1938C, A1979G, T1961V and T1753V/A1762T/G1764A/G1896A/G1899A, but they were not included in this meta-analysis because the data was insufficient. Variation frequency between CHB patients and HBV-ACLF patients was compared using the Chi-squared test. Sensitivity and specificity of HBV mutations for ACLF was evaluated to indicate the possibility of using certain mutations to predict the development of HBV-ACLF.

Acknowledgements

We wish to thank our colleagues Zhongkang Ji for critically revising the manuscript; Chenjing Zhang and Jingxin Shao who helped with data acquisition and Wei Chen, Jiajie Zhang, Xiaowei Xue and Zhibo Zhou who were involved in drafting the manuscript.

Additional files

Additional file 1: Table S1. (68KB, doc)

The Newcastle-Ottawa Scale (NOS) for assessing the quality of the included studies.

Additional file 2: Table S2. (39.5KB, doc)

Pooled unadjusted risk estimates of ACLF of specific mutation sites.

Footnotes

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

FH participated in the design of the study, performed the literature search, study quality assessment, data extraction, statistical analysis and drafted the manuscript. SB carried out the study design and participated in the literature search, study quality assessment, data extraction, statistical analysis and revised the manuscript. HY participated in the literature search, study quality assessment and data extraction. YS participated in the literature search and data extraction. JS helped design the study and write the manuscript. All authors have read and approved the final manuscript.

Contributor Information

Feishu Hu, Email: 06yxsyhfs@163.com.

Sheng Bi, Email: 372640052@qq.com.

Huadong Yan, Email: jifangsheng9200@163.com.

Yu Shi, Email: zjushiyu@zju.edu.cn.

Jifang Sheng, Email: shengji.fang@163.com.

References

  • 1.Olson JC, Kamath PS. Acute-on-chronic liver failure: concept, natural history, and prognosis. Curr Opin Crit Care. 2011;17(2):165–9. doi: 10.1097/MCC.0b013e328344b42d. [DOI] [PubMed] [Google Scholar]
  • 2.Sarin SK, Kumar A, Almeida JA, Chawla YK, Fan ST, Garg H, et al. Acute-on-chronic liver failure: consensus recommendations of the Asian Pacific Association for the study of the liver (APASL) Hepatol Int. 2009;3(1):269–82. doi: 10.1007/s12072-008-9106-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Liver Failure and Artificial Liver Group. Chinese Society of Infectious Diseases. Chinese Medical Association Severe Liver Diseases and Artificial Liver Group. Chinese Society of Hepatology. Chinese Medical Association Diagnostic and treatment guidelines for liver failure. Zhonghua Gan Zang Bing Za Zhi. 2006;14(9):643–6. [PubMed] [Google Scholar]
  • 4.You SL, Rong YH, Zhu B, Zhang AM, Zang H, Liu HL, et al. Changing etiology of liver failure in 3,916 patients from northern China: a 10-year survey. Hepatol Int. 2013;7(2):714–20. doi: 10.1007/s12072-013-9424-5. [DOI] [PubMed] [Google Scholar]
  • 5.Kao JH, Chen PJ, Lai MY, Chen DS. Hepatitis B genotypes correlate with clinical outcomes in patients with chronic hepatitis B. Gastroenterology. 2000;118(3):554–9. doi: 10.1016/S0016-5085(00)70261-7. [DOI] [PubMed] [Google Scholar]
  • 6.Malik A, Singhal DK, Albanyan A, Husain SA, Kar P. Hepatitis B virus gene mutations in liver diseases: a report from New Delhi. PLoS One. 2012;7(6):e39028. doi: 10.1371/journal.pone.0039028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Omata M, Ehata T, Yokosuka O, Hosoda K, Ohto M. Mutations in the precore region of hepatitis B virus DNA in patients with fulminant and severe hepatitis. N Engl J Med. 1991;324(24):1699–704. doi: 10.1056/NEJM199106133242404. [DOI] [PubMed] [Google Scholar]
  • 8.Ozasa A, Tanaka Y, Orito E, Sugiyama M, Kang JH, Hige S, et al. Influence of genotypes and precore mutations on fulminant or chronic outcome of acute hepatitis B virus infection. Hepatology. 2006;44(2):326–34. doi: 10.1002/hep.21249. [DOI] [PubMed] [Google Scholar]
  • 9.Baumert TF, Rogers SA, Hasegawa K, Liang TJ. Two core promoter mutation identified in a hepatitis B virus strain associated with fulminant hepatitis result in enhanced viral replication. J Clin Invest. 1996;98:2268–76. doi: 10.1172/JCI119037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Tong S, Kim KH, Chante C, Wands J, Li J. Hepatitis B virus e antigen variants. Int J Med Sci. 2005;2(1):2–7. doi: 10.7150/ijms.2.2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Kay A, Zoulim F. Hepatitis B virus genetic variability and evolution. Virus Res. 2007;127(2):164–7. doi: 10.1016/j.virusres.2007.02.021. [DOI] [PubMed] [Google Scholar]
  • 12.Fattovich G. Natural history and prognosis of hepatitis B. Semin Liver Dis. 2003;23(1):47–58. doi: 10.1055/s-2003-37590. [DOI] [PubMed] [Google Scholar]
  • 13.Chen CJ, Yang HI, Su J, Jen CL, You SL, Lu SN, et al. Risk of hepatocellular carcinoma across a biological gradient of serum hepatitis B virus DNA level. JAMA. 2006;295(1):65–73. doi: 10.1001/jama.295.1.65. [DOI] [PubMed] [Google Scholar]
  • 14.Iloeje UH, Yang HI, Su J, Jen CL, You SL, Chen CJ. Predicting cirrhosis risk based on the level of circulating hepatitis B viral load. Gastroenterology. 2006;130(3):678–86. doi: 10.1053/j.gastro.2005.11.016. [DOI] [PubMed] [Google Scholar]
  • 15.Chu CJ, Hussain M, Lok AS. Hepatitis B virus genotype B is associated with earlier HBeAg seroconversion compared with hepatitis B virus genotype C. Gastroenterology. 2002;122(7):1756–62. doi: 10.1053/gast.2002.33588. [DOI] [PubMed] [Google Scholar]
  • 16.Sumi H, Yokosuka O, Seki N, Arai M, Imazeki F, Kurihara T, et al. Influence of hepatitis B virus genotypes on the progression of chronic type B liver disease. Hepatology. 2003;37(1):19–26. doi: 10.1053/jhep.2003.50036. [DOI] [PubMed] [Google Scholar]
  • 17.Yu MW, Yeh SH, Chen PJ, Liaw YF, Lin CL, Liu CJ, et al. Hepatitis B virus genotype and DNA level and hepatocellular carcinoma: a prospective study in men. J Natl Cancer Inst. 2005;97(4):265–72. doi: 10.1093/jnci/dji043. [DOI] [PubMed] [Google Scholar]
  • 18.Seto WK, Lai CL, Yuen MF. Acute-on-chronic liver failure in chronic hepatitis B. J Gastroenterol Hepatol. 2012;27(4):662–9. doi: 10.1111/j.1440-1746.2011.06971.x. [DOI] [PubMed] [Google Scholar]
  • 19.Du H, Li T, Zhang HY, He ZP, Dong QM, Duan XZ, et al. Correlation of hepatitis B virus (HBV) genotypes and mutations in basal core promoter/precore with clinical features of chronic HBV infection. Liver Int. 2007;27(2):240–6. doi: 10.1111/j.1478-3231.2006.01400.x. [DOI] [PubMed] [Google Scholar]
  • 20.Chu CM, Lin CC, Chen YC, Jeng WJ, Lin SM, Liaw YF. Basal core promoter mutation is associated with progression to cirrhosis rather than hepatocellular carcinoma in chronic hepatitis B virus infection. Br J Cancer. 2012;107(12):2010–5. doi: 10.1038/bjc.2012.474. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Ranjit C, Syed NK, Jayshree B, Puja S, Shiv KS. Basal core promoter, precore region mutations of HBV and their association with e antigen, genotype, and severity of liver disease in patients with chronic hepatitis B in India. J Med Virol. 2006;78(8):1047–54. doi: 10.1002/jmv.20661. [DOI] [PubMed] [Google Scholar]
  • 22.Trehanpati N, Hissar S, Shrivastav S, Sarin SK. Immunological mechanisms of hepatitis B virus persistence in newborns. Indian J Med Res. 2013;138(5):700–10. [PMC free article] [PubMed] [Google Scholar]
  • 23.Moradzadeh M, Tayebi S, Poustchi H, Sayehmiri K, Shahnazari P, Naderi E, et al. The possible role of TLR2 in chronic hepatitis B patients with precore mutation. Adv Virology. 2013;2013:780319. doi: 10.1155/2013/780319. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Han YP, Li J, Wan YF, Kong LH, Cai J, Dong L, et al. The influence of hepatitis B e antigen on the expression of toll-like receptor 2 on peripheral monocytes. Zhonghua Gan Zang Bing Za Zhi. 2008;16(10):739–42. [PubMed] [Google Scholar]
  • 25.Zhang AM, Wan ZH, You SL, Liu HL, Zhu B, Chen J, et al. Association of hepatitis B virus mutations of A1846T and C1913A/G with acute-on-chronic liver failure development from different underlying chronic liver diseases. Hepat Mon. 2013;13(9) doi: 10.5812/hepatmon.12445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Li XD, Liu Y, Xu ZH, Wan ZH, Bai SY, Mao PY, et al. A complete genomic analysis of hepatitis B virus isolated from 516 Chinese patients with different clinical manifestations. J Med Virol. 2013;85:1698–704. doi: 10.1002/jmv.23640. [DOI] [PubMed] [Google Scholar]
  • 27.Zhao ZG. Study on the relationship between hepatitis B virus mutations and HBV related acute-on-chronic liver failure, Master Thesis. Tianjin China: Tianjin Medical School; 2010. [Google Scholar]
  • 28.Ma XY, Han T, Pei YZ, Zhao ZG, Gao YT, Li Y, et al. The relationship between hepatitis B virus PC/BCP region mutations and acute-on-chronic liver failure. Chin J Hepatol. 2012;20(9):644–8. doi: 10.3760/cma.j.issn.1007-3418.2012.09.002. [DOI] [PubMed] [Google Scholar]
  • 29.Jia YT, Huang T, Liu BF, Song HB, Wu JX. Sequence of basic core promoter and pre-C gene of hepatitis B virus in 130 cases. J Shanxi Med Univ. 2009;40(4):302–7. [Google Scholar]
  • 30.Jiang L, Xu ZH, Liu Y, Li XD, Xin SJ, Xu DP. Incidences of hepatitis B virus genome C1913A/G mutation in different disease progressions and the effect on viral replication. Chin J Clinicians (Electronic Edition) 2013;7(8):3357–61. [Google Scholar]
  • 31.Yuan T-T, Faruqi A, Shih JWK, Shih C. The mechanism of natural occurrence of two closely-linked HBV precore predominant mutations. Virology. 1995;211:144–56. doi: 10.1006/viro.1995.1387. [DOI] [PubMed] [Google Scholar]
  • 32.Peijun Y. Clinical study on the relevance between HBV PreS mutations and advanced liver disease, Master Thesis. Kunming China: Kunming Medical University; 2014. [Google Scholar]
  • 33.Qu LS, Liu JX, Liu TT, Shen XZ, Chen TY, Ni ZP, et al. Association of hepatitis B virus pre-S deletions with the development of hepatocellular carcinoma in Qidong, China. PLoS One. 2014;9(5):e98257. doi: 10.1371/journal.pone.0098257. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Miao FZ, Xu ZH, Liu Y, Li Q, Li XD, Yao WM, et al. Down-regulation effect of HBV genome pre-S deletion mutation on viral replication capacity and the transcriptional activity of the overlapping surface antigen promoter II. Infect Dis Info. 2013;26(6):334–8. [Google Scholar]
  • 35.Tai P-C, Suk FM, Gerlich W, Neurath R, et al. Hypermodification of an internally deleted middle envelope (M) protein of frequent and predominant hepatitis B virus variants. Virology. 2002;292:44–58. doi: 10.1006/viro.2001.1239. [DOI] [PubMed] [Google Scholar]
  • 36.Sun ZQ, Xu ZH, Ren XQ, Liu Y, Wang Y, Li XD, et al. Affinity analysis of variant forms of HBV preS/S antigen-specific CTL epitopes in patients with hepatitis B infection. Med J Chin PLA. 2010;35(12):1459–61. [Google Scholar]
  • 37.Sunbul M. Hepatitis B, virus genotypes: global distribution and clinical importance. World J Gastroenterol. 2014;20(18):5427–34. doi: 10.3748/wjg.v20.i18.5427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Xu L, Chen EQ, Lei J, Liu L, Zhou TY, Gao Z, et al. Pre-core/basal-core promoter and reverse transcriptase mutations in chronic HBV infected-patients. Hepatogastroenterology. 2012;59(113):212–5. doi: 10.5754/hge10122. [DOI] [PubMed] [Google Scholar]
  • 39.Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med. 2002;21(11):1539–58. doi: 10.1002/sim.1186. [DOI] [PubMed] [Google Scholar]
  • 40.Sterne JA, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001;54(10):1046–55. doi: 10.1016/S0895-4356(01)00377-8. [DOI] [PubMed] [Google Scholar]

Articles from Virology Journal are provided here courtesy of BMC

RESOURCES