Open Access

Association between alcohol dehydrogenase-2 gene polymorphism and esophageal cancer risk: a meta-analysis

  • Ning Mao1,
  • Siyao Nie2,
  • Bin Hong1,
  • Chao Li1,
  • Xueyuan Shen1 and
  • Tao Xiong1Email author
World Journal of Surgical Oncology201614:191

https://doi.org/10.1186/s12957-016-0937-y

Received: 6 May 2016

Accepted: 8 July 2016

Published: 22 July 2016

Abstract

Background

It has been shown that gene polymorphisms may play an important role in the carcinogenesis of esophageal cancer. This study is to investigate the role of alcohol dehydrogenase 1B (ADH1B) gene Arg47His polymorphism in esophageal cancer susceptibility.

Methods

Case-control studies published between January 2000 and June 2015 were searched to retrieve relevant articles. The pooled odds ratio (OR) and 95 % confidence interval (CI) were employed to calculate the strength of association.

Results

A total of 23 relevant articles were finally selected for the analysis, including 9338 esophageal cancer patients and 14,896 matched controls. Overall, we found that the 47His allele was significant associated with the decreased risk of esophageal cancer when compared with the 47Arg allele in total populations (A vs. G: OR = 0.67, 95 % CI = 0.59–0.76, P < 0.00001). This protective relationship was observed under other genetic models as well (P < 0.00001). Subgroup analysis by ethnicity showed that ADH1B Arg47His variant was associated with the decreased esophageal cancer risk under all the genetic models (P < 0.00001) among Asians, especially in Chinese and Japanese; while in non-Asians, no significant correlation was detected in any genetic models (P > 0.05). Furthermore, Arg/Arg genotype of ADH1B Arg47His variant combined with drinking, smoking and males appeared to show a high risk in patients with esophageal cancer.

Conclusions

Our results suggested that ADH1B gene Arg47His variant was associated with the decreased esophageal cancer risk. Genetic-environmental interaction should be further considered in the future researches.

Keywords

Esophageal cancer Alcohol dehydrogenase 1B Polymorphism Meta-analysis

Background

Esophageal cancer (or oesophageal cancer), a type of cancer arising from the esophagus, is the eighth most common cancer and the sixth leading cause of cancer-related death worldwide [1]. Squamous cell carcinomas (SCC), which is more common in the developing world, and adenocarcinomas (AC), which is more common in the developed world, are two main forms of histologically confirmed esophageal cancer [2, 3]. The clinical symptoms include difficulty in swallowing, enlarged lymph glands around the collarbone, a dry cough, weight loss, and possibly hematemesis [4]. The established risk factors for this disease are environmental factors (alcohol drinking, smoking, infecting bacteria or virus), genetic factors (mutations in enzymes that metabolize alcohol), cultural factors (high-temperature food items such as pork braised in brown sauce and old stocked rice), obesity and gastroesophageal reflux [58]. The incidence of esophageal cancer is threefold higher in men than women [9] and is high in east Asia, southern Africa, and southern Europe while is low in North America and other parts of Europe [10]. The highest reported incidence and mortality rates occur in China, which is almost 20 to 30 times higher than that in the USA [11]. According to cancer statistics, there will be an estimated 16,980 new cases and 15,590 deaths in both sexes in the USA in 2015 [12]. Although many advances in diagnosis and treatment such as endoscopic resection, chemotherapy, and surgery have the potential to substantially reduce mortality and morbidity [13, 14], the prognosis of patients with esophageal cancer remains poor and the 5-year survival rate is still low, ranging from 15 to 25 % [15, 16]. Therefore, identifying new biomarkers for early diagnosis and treatment is vital to decide therapeutic options, improve treatment efficiency, and predict prognosis [17].

Evidences have shown that gene polymorphisms may play an important role in the carcinogenesis of esophageal cancer [18]. Alcohol dehydrogenase gene (ADH), at chromosome 4, is a key cytosolic enzyme for ethanol [19]. It encodes at least seven ADH isoforms (ADH1–ADH7), each with slightly different properties [20], and may be involved in the metabolic pathways of several neurotransmitters [21]. The ADH1B (also known as ADH2) gene is located on human chromosome 4q21-q23. It is the locus responsible for most of the ADH activity on ethanol in the liver [22]. Single nucleotide polymorphisms (SNPs) occurring in this gene may be capable of altering ethanol metabolism, and individuals expressing the ADH1B variants would have different alcohol elimination rates [23]. One of the most studied SNP was Arg47His (rs1229984), a G to A base transition in exon 3 leading to the substitution of arginine (ADH1B*1) to histidine (ADH1B*2) at codon 47th position. ADH1B*2 is common in more than 90 % of Asians and reduced their risk for alcoholism but fewer than 20 % of Caucasians or Africans [24]. This variant was shown to be strongly associated with alcohol dependence, abuse, consumption, and alcohol-induced liver diseases [25, 26].

Several studies have identified the relationship between ADH1B polymorphism and esophageal cancer susceptibility, but the consistent results were not obtained. For example, Ito et al. demonstrated that ADH1B Arg47His variant was associated with esophageal cancer in Japanese and might be used in personalized prevention programs [27], while Ma et al. did not show significant associations between variations in the ADH1B gene and esophageal squamous cell carcinoma (ESCC) risk in Chinese [28]. Although previous meta-analyses were performed to evaluate this association [2931], limited articles were selected, only Asian population was used for analysis, and some repeated participants were included. Furthermore, Asians and Caucasians may have different incidence, distribution, and susceptibilities to esophageal cancer due to different heritage backgrounds [32]. All these factors may influence the reliable of the results. Therefore, we conducted the present meta-analysis to review all the published articles among any ethnicities to obtain a relative reliable result.

Methods

Identification of relevant studies

Electronic databases of PubMed, Web of Science, Medline, Embase, CNKI (China National Knowledge Internet), and Wanfang were comprehensively searched to retrieve relevant articles published between January 2000 and June 2015. The MeSH terms were as follows: “esophageal cancer or oesophageal cancer or esophageal squamous cell carcinomas or esophageal adenocarcinomas,” “alcohol dehydrogenase or ADH1B or ADH2,” and “polymorphism or variant or mutation” as well as their combinations. The equivalent Chinese characters were used in Chinese database. We also manually searched the references of included studies in order to obtain more related articles. Our analysis only considered studies that were written in English and Chinese.

Inclusion and exclusion criteria

The eligible articles must meet the following criteria. The inclusion criteria were as follows: (1) case-control studies evaluating the correlation of ADH1B Arg47His polymorphism in esophageal cancer occurrence; (2) patents with esophageal cancer should be diagnosed clinically and confirmed histologically, the controls should be age-, ethnicity-matched participants without malignancy and digestive and chronic diseases; (3) the genotype information were available to extract; and (4) the genotypes of controls were consistent with Hardy-Weinberg equilibrium (HWE). The exclusion criteria were as follows: (1) duplicate articles from the same authors or laboratories or conducted among the same populations; (2) conference reports or reviews; (3) without control group; and (4) data could not be extracted.

Data extraction

Two of our authors independently assessed the quality of selected studies. Each item of a single study should be achieved a final consensus. The extracted information was as follow: the name of first author, published year, country, ethnicity, mean age, sample size, genotype method, alleles and genotypes distribution, source of cases and controls, and HWE of genotypes in controls.

Statistical analysis

The pooled odds ratio (OR) with its 95 % confidence interval (CI) were employed to estimate the association between ADH1B Arg47His variant and esophageal carcinoma susceptibility. The Z test was used to determine the significance of ORs, and P value was less than 0.05 considered as statistically significance. The allelic model (His vs. Arg), the homologous model (His/His vs. Arg/Arg), the heterogeneous model (Arg/His vs. Arg/Arg), the dominant model (His/His+Arg/His vs. Arg/Arg) and the recessive model (His/His vs. Arg/His+Arg/Arg) were examined. The Q test and the I 2 test were used to assess the degree and proportion of between-study heterogeneity, respectively. The fixed-effect model was used when the P value of the Q test was more than 0.10 and the I 2 of the I 2 test was less than 50 %; otherwise, the random-effect model was used. All statistical analyses were conducted in Review Manager 5.2 (the Cochrane Collaboration, Oxford, England). All the tests were two-sided.

Results

Characteristics of included studies

We firstly identified 105 articles. After the inclusion and exclusion criteria filtering, a total of 23 relevant articles were finally screened out, including 9338 esophageal cancer patients and 14,896 matched controls. Figure 1 presented the selection process. Of the 23 articles, two were written in Chinese [33, 34] and 21 were in English [3555]. The participants of Hashibe et al.’s study were from five countries (Romania, Poland, Russia, Slovakia, and Czech Republic) [38], while other studies were from seven countries (Japan, Thailand, Iran, Kashmir, Sudan, Dutch and China), respectively. There were two sources of controls: population-based controls and hospital-based controls. The ADH1B Arg47His variant was measured in eight methods. Table 1 listed the main characteristics of included studies. Table 2 displayed the alleles and genotypes information of ADH1B Arg47His variant in each included studies.
Fig. 1

Flow diagram of the selection process

Table 1

Main characteristics of included studies in this meta-analysis

First author

Year

Country

Ethnicity

Mean age

Sample size

Source of

Genotyping methods

    

Cases

Controls

Cases

Controls

Cases

Controls

Yokoyama A

2001

Japan

Asian

56 ± 7

53 ± 8

112

526

ESCC

HB

PCR-RFLP

Boonyaphiphat P

2002

Thailand

Asian

64.0 ± 9.7

64.5 ± 12.3

202

261

ESCC

HB

APLP

Chao YC

2003

China (Taiwan)

Asian

64.6 ± 12.3

53.0 ± 18.8

88

105

EC

HB

PCR-RFLP

Yokoyama T

2003

Japan

Asian

61.7 ± 7.9

58.9 ± 7.1

233

610

ESCC

PB

PCR-RFLP

Chen HG

2005

China

Asian

58.06 (35–80)

58.53 (35–82)

137

137

EC

PB

PCR

Yang CX

2005

Japan

Asian

61.4 ± 0.6

61.4 ± 0.4

165

495

ESCC/EAC

HB

PCR-CTPP

Hashibe M

2006

Mixed

Caucasian

56.7 ± 2.1

58.9 ± 3.4

167

887

ESCC

PB

TaqMan

Yang SJ

2007

China

Asian

58.3 ± 8.3

52.8 ± 13.2

191

198

EC

PB

PCR-CTPP

Guo YM

2008

China

Asian

60.2 ± 8.9

59.7 ± 9.7

80

480

ESCC

PB

PCR-RFLP

Lee CH

2008

China (Taiwan)

Asian

60.2 ± 3.8

61.3 ± 3.9

406

656

ESCC

HB

PCR-RFLP

Akbai

2009

Iran

Asian

63.6 (25–89)

55.2 (24–90)

746

1373

ESCC

PB

Sequenom

Cui R

2009

Japan

Asian

64.2 ± 8.7

59.7 ± 16.2

1070

2836

ESCC

PB

BeadChip

Ding JH

2010

China

Asian

68.2 ± 5.6

69.8 ± 7.3

221

191

EC

PB

PCR-DHPLC

Tanaka F

2010

Japan

Asian

67.2 ± 7.3

66.5 ± 7.2

742

820

OSCC

PB

BRLMM

Iqbal B

2011

Kashmir

Asian

NA

NA

50

50

EC

PB

Sequencing

Wang YL

2011

China

Asian

57.2 ± 9.4

56.1 ± 7.3

81

162

EC

PB

PCR-CTPP

Gu HY

2012

China

Asian

62.5 ± 6.2

63.8 ± 7.1

380

380

ESCC

HB

MALDI-ToF-MS

Dura P

2013

Dutch

Caucasian

65.0 ± 10.9

64.9 ± 11.1

351

430

ESCC/EAC

PB

TaqMan

Gao Y

2013

China

Asian

NA

NA

2139

2273

ESCC

PB

TaqMan

Wu M

2013

China

Asian

63.7 ± 9.4

63.7 ± 10.3

846

1079

EC

PB

Sequencing

Hou AM

2014

China

Asian

56.5 ± 5.5

58.7 ± 6.3

110

110

ESCC/EAC

PB

PCR-RFLP

Ye B

2014

China

Asian

58.7 ± 6.4

59.9 ± 7.2

1001

1391

ESCC

HB

PCR-RFLP

Babiker H

2015

Sudan

Africa

56.41

47.87

134

233

ESCC/EAC

PB

PCR-RFLP

NA not available, ESCC esophageal squamous cell carcinoma, EAC esophageal adenocarcinoma, OSCC oesophageal squamous cell carcinoma, HB hospital-based, PB population-based, NP normal healthy population, APLP amplified product length polymorphism method, PCR-CTPP polymerase chain reaction with the confronting two-pair primer, PCR-DHPLC polymerase chain reaction and denaturing high-performance liquid chromatography, BRLMM Bayesian robust linear model with Mahalanobis algorithm, MALDI-ToF-MS matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry

Table 2

Distribution of alleles and genotypes in each included studies

First author

Cases

Controls

 

Arg/Arg

Arg/His

His/His

Arg

His

Arg/Arg

Arg/His

His/His

Arg

His

HWE

 

(*1/*1)

(*1/*2),

(*2/*2)

(*1)

(*2)

(*1/*1)

(*1/*),

(*2/*2)

(*1)

(*2)

 

Yokoyama A

56

56*

 

145

381*

  

Boonyaphiphat P

101

86

15

288

116

94

139

28

327

195

0.08

Chao YC

19

41

28

79

97

7

43

55

57

153

0.94

Yokoyama T

51

73

109

175

291

31

212

367

274

946

0.99

Chen HG

26

54

57

106

168

14

49

74

77

197

0.40

Yang CX

6

85

74

97

233

22

168

304

212

776

0.98

Hashibe M

163

4*

 

792

95*

 

Yang SJ

33

80

78

146

236

22

76

100

120

276

0.44

Guo YM

17

25

38

59

101

24

168

288

216

744

0.99

Lee CH

117

149

140

383

429

46

275

335

367

945

0.59

Akbai

21

232

490

274

1212

73

471

827

617

2125

0.86

Cui R

194

363

510

751

1383

151

986

1626

1288

4238

0.99

Ding JH

19

96

106

134

308

8

75

108

91

291

0.53

Tanaka F

149

237

356

535

949

49

287

484

385

1255

0.76

Iqbal B

12

36

2

60

40

12

37

1

61

39

0.30

Wang YL

15

34

33

64

100

17

67

78

101

223

0.90

Gu HY

53

168

158

274

484

26

170

182

222

534

0.26

Dura P

326

20

0

672

20

406

23

0

835

23

0.85

Gao Y

252

907

939

1411

2785

199

909

1155

1307

3219

0.57

Wu M

138

309

355

585

1019

101

410

510

612

1430

0.38

Hou AM

59*

 

51

48*

 

62

Ye B

224

400

377

848

1154

150

578

663

878

1904

0.36

Babiker H

115

8

2

238

12

188

18

4

394

26

0.06

HWE Hardy-Weinberg Equilibrium;–, not applicable; *for Yokoyama A and Hashibe M means His/His+Arg/His; *for Hou AM means Arg/His+Arg/Arg

Overall association between ADH1B Arg47His polymorphism and esophageal cancer risk

A significant heterogeneity among all the included studies was observed (P < 0.01 and I 2 > 50 %), and the random-effect model was used. Table 3 listed the results of the association between the ADH1B Arg47His polymorphism and esophageal cancer susceptibility. Overall, we found that the frequency of 47His allele was higher than the 47Arg allele in both cases and controls, and the statistical analysis demonstrated that the 47His allele was significant associated with the decreased risk of esophageal cancer in total populations (His vs. Arg: OR = 0.67, 95 % CI = 0.59–0.76, P < 0.00001) as shown in Fig. 2. This significant protective relationship was also identified under other genetic models (P < 0.00001). Subgroup analysis by ethnicity showed that this polymorphism revealed an ethnic difference and geographic variance. In Asians, ADH1B 47His variant was shown to be associated with the decreased esophageal cancer risk under all the genetic models (P < 0.00001); while in non-Asians, no significant correlation was detected in any genetic models (P > 0.05). Figure 3 showed the result of the His carriers of the His/His and Arg/His genotypes compared with the Arg/Arg genotype in both groups. Furthermore, we also considered the role of this genetic variant in esophageal cancer among different countries. There were 12 articles in China (5485 patients and 6982 controls), five in Japan (2319 patients and 5213 controls), and six in other countries. Our result demonstrated that ADH1B Arg47His variant was a protective factor for cancer risk in Chinese and Japanese populations as shown in Fig. 4.
Table 3

Meta-analysis of the overall association between ADH1B Arg47His polymorphism and esophageal cancer risk

Classification

Comparisons

Number of included studies

Test of association

Test of heterogeneity

   

OR (95 % CI)

P

Ph

I2

Model

Total

His vs. Arg

20

0.67 (0.59, 0.76)

<0.00001

<0.00001

87 %

R

 

His/His vs. Arg/Arg

20

0.40 (0.30, 0.54)

<0.00001

<0.00001

86 %

R

 

Arg/His vs. Arg/Arg

20

0.52 (0.40, 0.68)

<0.00001

<0.00001

85 %

R

 

His/His+Arg/His vs. Arg/Arg

22

0.46 (0.36, 0.59)

<0.00001

<0.00001

86 %

R

 

His/His vs. Arg/His+Arg/Arg

21

0.69 (0.61, 0.77)

<0.00001

<0.00001

69 %

R

Asian

His vs. Arg

18

0.66 (0.57, 0.75)

<0.00001

<0.00001

88 %

R

 

His/His vs. Arg/Arg

18

0.40 (0.30, 0.54)

<0.00001

<0.00001

87 %

R

 

Arg/His vs. Arg/Arg

18

0.49 (0.38, 0.65)

<0.00001

<0.00001

86 %

R

 

His/His+Arg/His vs. Arg/Arg

19

0.44 (0.34, 0.58)

<0.00001

<0.00001

87 %

R

 

His/His vs. Arg/His+Arg/Arg

19

0.68 (0.61, 0.77)

<0.00001

<0.00001

71 %

R

Non-Asian

His vs. Arg

2

0.93 (0.59, 1.47)

0.75

0.46

0 %

F

 

His/His vs. Arg/Arg

1

0.82 (0.15, 4.53)

0.82

NA

NA

 
 

Arg/His vs. Arg/Arg

2

0.95 (0.57, 1.56)

0.83

0.46

0 %

F

 

His/His+Arg/His vs. Arg/Arg

3

0.59 (0.23, 1.48)

0.26

0.02

75 %

R

 

His/His vs. Arg/His+Arg/Arg

1

0.84 (0.15, 4.64)

0.84

NA

NA

 

China

His vs. Arg

11

0.64 (0.56, 0.73)

<0.00001

<0.00001

78 %

R

 

His/His vs. Arg/Arg

11

0.37 (0.29, 0.50)

<0.00001

<0.00001

79 %

R

 

Arg/His vs. Arg/Arg

11

0.47 (0.35, 0.63)

<0.00001

<0.00001

77 %

R

 

His/His+Arg/His vs. Arg/Arg

11

0.41 (0.31, 0.55)

<0.00001

<0.00001

80 %

R

 

His/His vs. Arg/His+Arg/Arg

12

0.71 (0.66, 0.76)

<0.00001

0.16

29 %

F

Japan

His vs. Arg

4

0.55 (0.51, 0.60)

<0.00001

0.41

0 %

F

 

His/His vs. Arg/Arg

4

0.26 (0.18, 0.38)

<0.00001

0.03

66 %

R

 

Arg/His vs. Arg/Arg

4

0.35 (0.21, 0.59)

<0.00001

0.0008

82 %

R

 

His/His+Arg/His vs. Arg/Arg

5

0.31 (0.22, 0.44)

<0.00001

0.004

74 %

R

 

His/His vs. Arg/His+Arg/Arg

4

0.62 (0.56, 0.69)

<0.00001

0.65

0 %

F

NA not applicable, OR odds ratio, 95 % CI 95 % confidence interval, Ph and I 2 test of heterogeneity, F fixed-effect model, R random-effect model

Fig. 2

Meta-analysis of ADH1B Arg47His polymorphism and esophageal cancer risk in a random-effect model under the allelic models (His vs. Arg)

Fig. 3

Subgroup analysis by ethnicity of ADH1B Arg47His polymorphism and esophageal cancer susceptibility under the dominant model (His/His+Arg/His vs. Arg/Arg)

Fig. 4

Association between ADH1B Arg47His polymorphism and esophageal cancer under the dominant model based on countries

Combined effect of ADH1B Arg47His variant and alcohol drinking, tobacco smoking, and gender difference on esophageal cancer risk

Fifteen studies estimated the combined effect of ADH1B Arg47His polymorphism and alcohol drinking on esophageal cancer risk. However, the relevant data could be extracted only from 12 studies, including 3545 patients and 6909 controls. Based on these data, we could only assess the combined effect on esophageal cancer susceptibility under the Arg/Arg versus His/His+Arg/His model. We divided the subjects into two groups: non-drinking group (1134 cases and 3526 controls) and drinking group (2411 cases and 3383 controls). Our results found that Arg/Arg genotype compared with the His carrier of His/His and Arg/His genotypes was significantly associated with the increased higher risk of esophageal cancer in the drinking group (OR = 3.15, 95 % CI = 2.66–3.74, P < 0.00001) and lower in the non-drinking group (OR = 1.71, 95 % CI = 1.23–2.38, P = 0.001) as shown in Fig. 5.
Fig. 5

Forest plot of the combined effect of ADH1B Arg47His polymorphism and alcohol drinking condition and esophageal cancer risk under the Arg/Arg versus Arg/His+His/His model (a non-drinkers; b drinkers)

Four articles considered the combined effect of ADH1B Arg47His polymorphism and tobacco smoking on esophageal cancer susceptibility, containing 2382 patients and 4792 controls. Our result demonstrated that the Arg/Arg genotype was associated with esophageal cancer occurrence in both non-smokers (OR = 2.40, 95 % CI = 1.44–3.98, P = 0.0007) and smokers (OR = 3.35, 95 % CI = 2.22–5.05, P < 0.00001) in the random-effect model as shown in Fig. 6, and this relationship was a bit stronger in smokers than that in non-smokers.
Fig. 6

Meta-analysis of the combined effect of ADH1B Arg47His polymorphism and smoking status and esophageal cancer risk under the Arg/Arg versus Arg/His+His/His model

Six articles were selected for gender variance (five for males and two for females). Our result showed that the Arg/Arg genotype of ADH1B Arg47His variant increased the esophageal cancer risk in male patients (OR = 3.44, 95 % CI = 2.42–4.89, P < 0.0001), while not in female patients (OR = 1.62, 95 % CI = 0.90–2.91, P = 0.11) as shown in Fig. 7.
Fig. 7

Forest plot of the combined effect of ADH1B Arg47His polymorphism and gender variance and esophageal cancer risk under the Arg/Arg versus Arg/His+His/His model (a males; b females)

Sensitivity analysis and publication bias

We deleted a single included study at a time to verify whether our results were influenced by each study. The result showed that even though the between-study heterogeneity was reduced, the pooled ORs were not significantly changed, indicating that there was no publication bias in the present meta-analysis. The funnel plot among the total population under the dominant model further reveal no publication bias as shown in Fig. 8.
Fig. 8

Funnel plot of the publication bias in this meta-analysis under the dominant model in total population (His/His+Arg/His vs. Arg/Arg)

Discussion

In this meta-analysis, we totally screened out 23 relevant articles. Our results showed that the ADH1B Arg47His variant was correlated with the decreased occurrence of esophageal cancer under all the genetic models among total population. Subgroup analysis by ethnicity demonstrated that this variant was associated with the decreased cancer risk in Asian populations as well, especially in Chinese and Japanese. However, in non-Asian population, no significant relationship was observed. Furthermore, we found that the combined effect of Arg/Arg genotype in ADH1B Arg47His variant and alcohol drinking, tobacco smoking, and male patients revealed a higher risk on esophageal cancer risk when compared with the His carrier of His/His and Arg/His genotypes, respectively. Our results were consistent with previous meta-analyses which showed that ADH1B*47Arg could significantly increase the risk of ESCC in Asians, especially when coupled with alcohol drinking [2931].

Esophageal cancer is considered as a serious malignancy worldwide for its extremely aggressive nature and poor survival rate [56]. It is a multistep, multifactorial disease, and the incidence is varied due to the geographical diversities; thus, the therapeutic management might be different as well. Genetic variations might be involved in esophageal cancer development and predict the prognosis [57]. Studies have shown that ADH gene might play a role in carcinogenesis. ADH constitutes a large family of enzymes and is a metabolic barrier against self-administer ethanol [58]. ADH isoenzyme is responsible for the reversible oxidation of alcohols to acetaldehyde, which is in turn oxidized to aldehyde by aldehyde dehydrogenases (ALD) [59]. ADH1B and ALDH2 are the major enzymes involved in the alcohol-metabolizing pathways in humans. ADH1B is one member of ADH family and is expressed in the liver and presented in gastrointestinal tract. This gene is mainly contributed for ethanol to carcinogenic metabolite conversion during the elimination phage [60]. In addition, ADH1B expression could result in high blood acetaldehyde levels, which can easily give rise to DNA damage, and finally cause the cancer occurrence [61]. Genetic polymorphisms of ADH1B could modulate exposure levels to ethanol. ADH1B can include three alleles (ADH2*1, ADH2*2, and ADH2*3). Among which, the Arg47His variant (ADH2*2) was the most studied. The activity of ADH1B was increased by 40-fold in ADH1B His/His individuals [62], resulting in the fast accumulation of acetaldehyde.

SNPs of ADH1B gene (the major alcohol-metabolizing enzyme gene) may modify the effects of alcohol on metabolic and clinical phenotypes [63]. Blood ethanol concentrations of ADH1B*2/*2 group were shown higher than those of ADH1B*1/*2 group [64]. ADH1B allele was associated with a reduction in alcohol consumption [65] and might be an important protective factor for alcoholic liver cirrhosis, especially for Asians [66]. ADH2*2 predicted less drinking and was a protective effect against heavy drinking in Jewish samples [67]. Heavy alcohol consumption and heavy smoking were shown to be associated with the increased risk of esophageal cancer particularly in individuals with the flushing response [68].

Previous studies have found that ADH1B Arg47His polymorphism was associated with the pathogenesis of cancers such as colorectal cancer [69] and head and neck cancer [70], while no positive correlation was found in hepatocellular carcinoma [71] and gastric cancer [72]. Several studies have identified the association between ADH1B polymorphism and esophagus cancer susceptibility. Chen et al. have observed that individuals with ADH1BArg/Arg genotype had a 3.99-fold risk of developing esophageal cancer compared with those with ADH1B His/His genotype [73]. Li et al. have demonstrated that ADH2*1 was associated with the increased risk of oesophageal cancer, possibly due to the tolerance of the carriers of these alleles to alcohol consumption compared to those with high-activity alleles ADH2*2 which are associated with higher production of the unpleasant acetaldehyde intermediate [74]. Oze et al. found that the magnitude of effect of ADH1B polymorphisms was greater in subjects who were heavy drinkers, heavy smokers, and had esophageal cancer [75]. Consumption of tobacco and alcohol, coupled with ADH1B genotypes, determines a substantial magnitude of tumorigenetic effect on earlier age ESCC diagnosis [76].

Several limitations were presented in this meta-analysis. Firstly, most of the included studies were conducted in the Asian population, while other ethnicities should be considered in the future. Secondly, the stages of patients with esophageal cancer could not be extracted from the included studies, which might limit the application of our results. Thirdly, the combined effect of ADH1B Arg47His variant and age group also should be focused on. Lastly, other polymorphisms in ADH1B gene or other ADH genes which might alter the metabolism of alcohol should be included.

Conclusions

In conclusion, our results suggested that ADH1B Arg47His polymorphism might be a protective factor on esophageal cancer susceptibility in Asians. The Arg/Arg genotypes combined with alcohol drinking, tobacco smoking, and males might be strongly increased the risk of esophageal cancer. However, further studies with more ethnicities should be taken into account in future researches.

Abbreviations

AC, adenocarcinomas; ADH, alcohol dehydrogenase gene; ADH1B, alcohol dehydrogenase 1B; ALD, aldehyde dehydrogenases; CI, confidence interval; OR, odds ratio; SCC, squamous cell carcinomas; SNPs, single nucleotide polymorphisms

Declarations

Acknowledgements

None.

Funding

No funding supported this study.

Availability of data and materials

The data will not be shared because not all authors agreed with this.

Authors’ contributions

NM, SYN, and TX designed and conducted the experiments. BH and CL surveyed the literature and developed the text of the manuscript. XYS helped in the statistical analysis. NM, BH, and TX refined the write-up. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Cardiothoracic Surgery, Yongchuan Hospital of Chongqing Medical University
(2)
Department of Infectious Disease, Yongchuan Hospital of Chongqing Medical University

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