Abstract

C677T (Ala>Val, rs1801133 C>T), a non-synonymous variant of methylenetetrahydrofolate reductase (MTHFR) gene, has been found to be associated with an impair enzyme activity of MTHFR. The relationship of MTHFR rs1801133 with hepatocellular carcinoma (HCC) has been extensively investigated. However, the findings were conflicting. Recently, more investigations have been conducted on the relationship of MTHFR rs1801133 with HCC. To obtain a more precise assessment on the effect of this non-synonymous variant to the development of HCC, a pooled-analysis was performed. This meta-analysis consisted of 19 independent case–control studies. By using the odds ratio (OR) combined with 95% confidence interval (CI), the relationship of MTHFR rs1801133 with HCC risk was determined. A total of 19 independent case–control studies were included. Finally, 6,102 HCC cases and 6,526 controls were recruited to examine the relationship of MTHFR rs1801133 with HCC risk. In recessive model (TT vs. CC/CT), the findings reached statistical significance (OR, 0.90; 95%CI, 0.82–0.98; P = 0.016). Subgroup analysis also found an association between MTHFR rs1801133 polymorphism and the decreased risk of HCC in hepatitis/virus related patients (recessive model: OR, 0.85; 95%CI, 0.72–0.99; P = 0.035, and allele model: OR, 0.90; 95%CI, 0.81–0.99; P = 0.028). Subgroup analyses indicated that extreme heterogeneity existed in Asian population, larger sample size investigation, hospital-based study and normal/healthy control subgroups. The shape of Begger’s seemed symmetrical. Egger’s linear regression test also confirmed these evaluations. Sensitivity analyses suggested that our findings were stable. In summary, our results highlight that MTHFR rs1801133 polymorphism decreases HCC susceptibility. The relationship warrants a further assessment.

Introduction

In 2018, global cancer statistics estimated that liver malignancy was the fifth most frequent type of cancer incidence among men and the eleven most frequent type among women, about 596,574 and 244,506 new cases diagnosed worldwide, respectively [1]. However, the fatality was the third most frequent type [1]. The etiology of liver cancer (LC) was not well-established. Hepatocellular carcinoma (HCC) is one of the most important primary LC, which comprised almost 80% of LC cases. Some major susceptibility factors (e.g. aflatoxin-contaminated food, superabundant drinking, tobacco consumption, chronic virus infection, higher body mass index and Type 2 diabetes) [2–6] may contribute to the development of HCC. Additionally, hereditary factor has also been suggested to affect the susceptibility for the occurrence of HCC.

Methylenetetrahydrofolate reductase (MTHFR) locates in 1p36.3, which maps from 11785723 to 11806103 (GRCh38; April, 2018). MTHFR, a key enzyme, plays a vital effect in folate metabolism by the role of catalyzing the 5,10-methylenetetrahydrofolate (5,10-methylene-THF) to 5-methyltetrahydrofolate (5-methylene-THF) irreversibly. In the conversion of homocysteine to methionine, 5-methylene-THF is a primary methyl donor [7]. MTHFR rs1801133 (C677T), a non-synonymous variant (Ala>Val), has been suggested to influence the activity of MTHFR enzyme [8]. The correlation of MTHFR rs1801133 polymorphism with malignancy has been extensively explored. This single-nucleotide polymorphism (SNP) was suggested to be associated with thyroid cancer [9], colorectal cancer [10,11], breast cancer [12], esophagogastric junction adenocarcinoma [13], non-small cell lung cancer [14], acute lymphoblastic leukemia [15,16], gastric cancer [17], renal cell carcinoma [18] and esophageal carcinoma [19], among others.

Recently, many case–control studies have been carried out to determine the relationship of MTHFR rs1801133 polymorphism with the development of HCC [19–29]. However, the observations were controversial. Several meta-analyses also got conflicting results. To shed light on this issue, we conducted an extensive pooled-analysis to determine the role of MTHFR rs1801133 polymorphism on the development of HCC.

Materials and methods

Study searching

Publications were obtained by searching the PubMed and EMBASE databases before October 19, 2019. The following strategy was used: (Methylenetetrahyfrofolate reductase OR MTHFR OR rs1801133) AND (SNP OR polymorphism) AND (cancer OR carcinoma) and (hepatocellular OR liver). The references in reviews and meta-analyses were also retrieved to get data. In this pooled-analysis, there was no language limited.

Inclusion criteria

In our meta-analysis, the eligible criteria of the included publications were: (1) designed as a case–control study; (2) focusing on the relationship of the MTHFR rs1801133 polymorphism with HCC risk; (3) genotype data could be extracted and (4) publications were compatible with Hardy–Weinberg equilibrium (HWE) in controls.

Exclusion criteria

The criteria for exclusion were as following: (1) publications incompatible with HWE; (2) overlapping data; (3) not case–control study design and (4) only focusing on the relationship of MTHFR rs1801133 polymorphism with HCC survival.

Data extraction

The authors (S. Zhang and J. Jiang) extracted the following data: the surname of first author, publication year, populations studied, country where the investigation was carried out, ratio of sex, age, drinking, positive (%) of hepatitis B surface antigen (HBsAg), genotyping method, the number of participants and MTHFR rs1801133 genotype. If there was conflicting assessment, another reviewer (W. Tang) was invited. During this process, they made a vote to obtain the final decision.

Statistical methods

In the present study, the odds ratios (ORs) combined with 95% confidence intervals (CIs) were harnessed to compare the difference between HCC group and controls. P value (<0.05) was considered statistically significant. The present meta-analysis determined the correlation in four genetic models [e.g. dominant model (TT/CT vs. CC), homozygote model (TT vs. CC), allele model (T vs. C) and recessive model (TT vs. CC/CT)]. Using I2 metric and Q statistic, the heterogeneity among the eligible case–control studies was evaluated. If P < 0.10 or I2 > 50%, we defined that there was significant heterogeneity. Thus, the random-effect model was used [30,31]. Otherwise, there was no heterogeneity detected. A fixed-effect model was used to combine the data [32]. The Egger test and Begg’s test were used to assess the bias of publication. If P < 0.10, we defined that there was a significant publication bias. By omitting a study one by one and analyzing the remainders, sensitivity analysis was performed to assess the stability of our findings. The distribution of the MTHFR rs1801133 genotype was used to calculate the P value of HWE by using an online software (http://ihg.gsf.de/cgi-bin/hw/hwa1.pl) in controls [33–35]. STATA 12.0 software (Stata Corp., College Station, Texas) was used to conduct the analysis. In this study, P value was two sided.

Quality assessment of meta-analysis

Two authors (S.Z. and J.J.) independently extracted the data and calculated the quality score of the included case–control studies. The detailed scores were determined by a quality assessment criteria, which were presented in previous studies [36,37]. If the scores were more than 6.0, the investigation had an acceptable quality [38].

Results

Eligible studies

A total of 11 publications were eligible (Figure 1). Four articles involved several different subgroups, so we considered them as independent investigations. After a screening, 19 independent case–control studies were included. In addition, five publications were excluded for incompatible with HWE [29,39,40–42]. Finally, 6,102 HCC cases and 6,526 controls were recruited to examine the relationship of MTHFR rs1801133 polymorphism with HCC risk (Table 1). The publication year covered from 2004 to 2019. These investigations were performed in different populations: three were conducted in mixed populations [28,29], four were carried out in Caucasians [26,27], and twelve involved Asians [19–25]. The MTHFR rs1801133 genotypes are summarized in Table 2.

Flow diagram of this meta-analysis

Figure 1
Flow diagram of this meta-analysis
Figure 1
Flow diagram of this meta-analysis
Table 1
Characteristics of the studies in meta-analysis
StudyYearSample sizeCountryEthnicitySex, male (%); Case/ControlAge (years); Case/ControlDrinkinge (%); Case/ControlHBsAg, positive (%); Case/ControlGenotype methodSource of controlType of control
Cui 2012 356/641 China Asian 83.1/43.5 56.6/58.7 44.1/30.3 77.5/8.6 Real-time PCR PB Normal or healthy control 
Fabris 2009 65/147 Italy Caucasian NA/NA NA/NA NA 26.2/10.9 PCR-RFLP HB Hepatitis or virus related control 
Fabris 2009 65/236 Italy Caucasian NA/69.5 NA/48 NA NA/NA PCR-RFLP HB NA 
Jiao 2017 726/549 China Asian 72.7/54.6 56.5/41.5 24.5/NA 89.1/0.0 TaqMan HB Normal or healthy control 
Jiao 2017 726/558 China Asian 72.7/53.6 56.5/33.7 24.5/NA 89.1/0.0 TaqMan HB Normal or healthy control 
Jiao 2017 726/81 China Asian 72.7/61.7 56.5/34.4 24.5/NA 89.1/100 TaqMan HB Hepatitis or virus related control 
Jiao 2017 726/442 China Asian 72.7/66.5 56.5/39.6 24.5/13.6 89.1/100 TaqMan HB Hepatitis or virus related control 
Jiao 2017 726/704 China Asian 72.7/64.9 56.5/53.7 24.5/23.6 89.1/88.7 TaqMan HB Hepatitis or virus related control 
Kwak 2008 96/201 Korea Asian NA 57.6/53.6 NA NA PCR-RFLP HB Normal or healthy control 
Peres 2016 71/356 Brazil Mixed 73.2/73.3 NA 62.0/46.0 NA PCR-RFLP HB Normal or healthy control 
Peres 2016 71/116 Brazil Mixed 73.2/74.1 NA 62.0/53.4 NA PCR-RFLP HB Hepatitis or virus related control 
Saffroy 2004 72/122 France Caucasian 84.7/85.2 55/50 NA NA PCR-RFLP HB Hepatitis or virus related control 
Saffroy 2004 27/80 France Caucasian 74.1/86.3 54/54 NA NA PCR-RFLP HB Normal or healthy control 
Saffroy 2004 49/30 France Caucasian 85.7/66.7 56/52 NA NA PCR-RFLP HB Hepatitis or virus related control 
Xu 2014 205/200 China Asian NA 52.0/61.0 NA NA PCR NA NA 
Yuan 2007 118/209 USA Mixed 68.6/61.2 NA 71.2/68.4 28.0/11.5 TaqMan PB Normal or healthy control 
Zhu 2006 508/543 China Asian 85.8/48.8 50/45 39.8/17.9 72.8/17.9 PCR-RFLP HB Normal or healthy control 
Chang 2014 204/415 China Asian 77.9/69.2 53.9/57.7 41.7/35.7 64.7/24.6 PCR-RFLP PB Normal or healthy control 
Zhang 2019 584/923 China Asian 89.9/90.5 53.2/53.7 29.1/16.0 70.6/9.2 SNPscan HB Normal or healthy control 
StudyYearSample sizeCountryEthnicitySex, male (%); Case/ControlAge (years); Case/ControlDrinkinge (%); Case/ControlHBsAg, positive (%); Case/ControlGenotype methodSource of controlType of control
Cui 2012 356/641 China Asian 83.1/43.5 56.6/58.7 44.1/30.3 77.5/8.6 Real-time PCR PB Normal or healthy control 
Fabris 2009 65/147 Italy Caucasian NA/NA NA/NA NA 26.2/10.9 PCR-RFLP HB Hepatitis or virus related control 
Fabris 2009 65/236 Italy Caucasian NA/69.5 NA/48 NA NA/NA PCR-RFLP HB NA 
Jiao 2017 726/549 China Asian 72.7/54.6 56.5/41.5 24.5/NA 89.1/0.0 TaqMan HB Normal or healthy control 
Jiao 2017 726/558 China Asian 72.7/53.6 56.5/33.7 24.5/NA 89.1/0.0 TaqMan HB Normal or healthy control 
Jiao 2017 726/81 China Asian 72.7/61.7 56.5/34.4 24.5/NA 89.1/100 TaqMan HB Hepatitis or virus related control 
Jiao 2017 726/442 China Asian 72.7/66.5 56.5/39.6 24.5/13.6 89.1/100 TaqMan HB Hepatitis or virus related control 
Jiao 2017 726/704 China Asian 72.7/64.9 56.5/53.7 24.5/23.6 89.1/88.7 TaqMan HB Hepatitis or virus related control 
Kwak 2008 96/201 Korea Asian NA 57.6/53.6 NA NA PCR-RFLP HB Normal or healthy control 
Peres 2016 71/356 Brazil Mixed 73.2/73.3 NA 62.0/46.0 NA PCR-RFLP HB Normal or healthy control 
Peres 2016 71/116 Brazil Mixed 73.2/74.1 NA 62.0/53.4 NA PCR-RFLP HB Hepatitis or virus related control 
Saffroy 2004 72/122 France Caucasian 84.7/85.2 55/50 NA NA PCR-RFLP HB Hepatitis or virus related control 
Saffroy 2004 27/80 France Caucasian 74.1/86.3 54/54 NA NA PCR-RFLP HB Normal or healthy control 
Saffroy 2004 49/30 France Caucasian 85.7/66.7 56/52 NA NA PCR-RFLP HB Hepatitis or virus related control 
Xu 2014 205/200 China Asian NA 52.0/61.0 NA NA PCR NA NA 
Yuan 2007 118/209 USA Mixed 68.6/61.2 NA 71.2/68.4 28.0/11.5 TaqMan PB Normal or healthy control 
Zhu 2006 508/543 China Asian 85.8/48.8 50/45 39.8/17.9 72.8/17.9 PCR-RFLP HB Normal or healthy control 
Chang 2014 204/415 China Asian 77.9/69.2 53.9/57.7 41.7/35.7 64.7/24.6 PCR-RFLP PB Normal or healthy control 
Zhang 2019 584/923 China Asian 89.9/90.5 53.2/53.7 29.1/16.0 70.6/9.2 SNPscan HB Normal or healthy control 

PCR-RFLP: polymerase chain reaction-restriction fragment length polymorphism

PCR: polymerase chain reaction

SNP: single-nucleotide polymorphism

HP: hospital-based

PB: population-based

NA: not available

Table 2
Distribution of MTHFR rs1801133 C>T polymorphism genotype and allele
StudyYearCase TTCase CTCasde CCControl TTControl TCControl CCCase TCase CControl TControl CHWEQuality assessment
Cui 2012 125 179 52 195 325 121 429 283 715 567 Yes 7.0 
Fabris 2009 13 – CC/CT = 52 23 – CC/CT = 124 – – – – Yes 6.5 
Fabris 2009 13 – CC/CT = 52 54 113 69 – – – – Yes 6.5 
Jiao 2017 188 370 168 176 263 110 746 706 615 483 Yes 7.5 
Jiao 2017 188 370 168 169 268 121 746 706 606 510 Yes 7.5 
Jiao 2017 188 370 168 29 35 17 746 706 93 69 Yes 6.5 
Jiao 2017 188 370 168 120 222 100 746 706 462 422 Yes 7.5 
Jiao 2017 188 370 168 215 338 151 746 706 768 640 Yes 7.5 
Kwak 2008 18 46 32 31 106 64 82 110 168 234 Yes 6.5 
Peres 2016 36 28 33 174 149 50 92 240 472 Yes 7.0 
Peres 2016 36 28 13 55 48 50 92 81 151 Yes 6.0 
Saffroy 2004 24 43 10 60 52 34 110 80 164 Yes 6.5 
Saffroy 2004 16 13 37 30 20 34 63 97 Yes 6.5 
Saffroy 2004 29 15 17 10 39 59 23 37 Yes 6.5 
Xu 2014 50 112 43 50 111 39 212 198 211 189 Yes 6.5 
Yuan 2007 14 51 53 30 99 80 79 157 159 259 Yes 7.0 
Zhu 2006 110 226 172 102 268 173 446 570 472 614 Yes 8.0 
Chang 2014 30 114 50 57 199 135 174 214 313 469 Yes 7.5 
Zhang 2019 49 227 299 103 446 372 325 825 652 1190 Yes 8.0 
StudyYearCase TTCase CTCasde CCControl TTControl TCControl CCCase TCase CControl TControl CHWEQuality assessment
Cui 2012 125 179 52 195 325 121 429 283 715 567 Yes 7.0 
Fabris 2009 13 – CC/CT = 52 23 – CC/CT = 124 – – – – Yes 6.5 
Fabris 2009 13 – CC/CT = 52 54 113 69 – – – – Yes 6.5 
Jiao 2017 188 370 168 176 263 110 746 706 615 483 Yes 7.5 
Jiao 2017 188 370 168 169 268 121 746 706 606 510 Yes 7.5 
Jiao 2017 188 370 168 29 35 17 746 706 93 69 Yes 6.5 
Jiao 2017 188 370 168 120 222 100 746 706 462 422 Yes 7.5 
Jiao 2017 188 370 168 215 338 151 746 706 768 640 Yes 7.5 
Kwak 2008 18 46 32 31 106 64 82 110 168 234 Yes 6.5 
Peres 2016 36 28 33 174 149 50 92 240 472 Yes 7.0 
Peres 2016 36 28 13 55 48 50 92 81 151 Yes 6.0 
Saffroy 2004 24 43 10 60 52 34 110 80 164 Yes 6.5 
Saffroy 2004 16 13 37 30 20 34 63 97 Yes 6.5 
Saffroy 2004 29 15 17 10 39 59 23 37 Yes 6.5 
Xu 2014 50 112 43 50 111 39 212 198 211 189 Yes 6.5 
Yuan 2007 14 51 53 30 99 80 79 157 159 259 Yes 7.0 
Zhu 2006 110 226 172 102 268 173 446 570 472 614 Yes 8.0 
Chang 2014 30 114 50 57 199 135 174 214 313 469 Yes 7.5 
Zhang 2019 49 227 299 103 446 372 325 825 652 1190 Yes 8.0 

HWE: Hardy–Weinberg equilibrium.

Meta-analysis results

In the eligible investigations, the MAF of MTHFR rs1801133 C/T polymorphism was 0.475 in HCC patients (5,670/11,944) and was 0.466 in controls (5,721/12,288). In different race, the MAF of controls was not similar in controls. The MAFs were 0.352 (480/1,362) in mixed populations, 0.328 (214/652) in Caucasians, and that was 0.485 (5,075/10,462) in Asians.

The pooled-analysis findings were reported in four genetic models including 19 independent case–control studies. In recessive model (TT vs. CC/CT), the findings reached statistical significance (OR, 0.90; 95%CI, 0.82–0.98; P = 0.016, Table 3 and Figure 2). In other genetic models, we failed to obtain the significance (dominant model: OR, 0.92; 95%CI, 0.81–1.05; P = 0.209, homozygote model: OR, 0.88; 95%CI, 0.77–1.01; P = 0.078, and allele model: OR, 0.93; 95%CI, 0.85–1.01; P = 0.077, Table 3).

Meta-analysis of the association between MTHFR rs1801133 polymorphism and HCC risk (recessive model, fixed-effects model)

Figure 2
Meta-analysis of the association between MTHFR rs1801133 polymorphism and HCC risk (recessive model, fixed-effects model)
Figure 2
Meta-analysis of the association between MTHFR rs1801133 polymorphism and HCC risk (recessive model, fixed-effects model)
Table 3
Results of the meta-analysis from different comparative genetic models
No. of studiesT vs. CTT vs. CCTT/CT vs. CCTT vs. CT/CC
OR (95% CI)PI2P(Q-test)OR(95% CI)PI2P(Q-test)OR(95% CI)PI2P(Q-test)OR(95% CI)PI2P(Q-test)
Total 19 0.93(0.85–1.01) 0.077 48.7% 0.013 0.88(0.77–1.01) 0.078 25.8% 0.158 0.92(0.81–1.05) 0.209 47.3% 0.016 0.90(0.82–0.98) 0.016 11.9% 0.309 
Ethnicity 
Asians 11 0.94(0.85–1.03) 0.182 63.4% 0.002 0.90(0.75–1.06) 0.210 50.1% 0.029 0.94(0.80–1.09) 0.380 59.3% 0.006 0.90(0.79–1.03) 0.133 44.4% 0.055 
Caucasians 0.79(0.57–1.09) 0.153 0.0% 0.405 0.67(0.30–1.50) 0.331 0.0% 0.781 0.73(0.47–1.13) 0.155 42.2% 0.177 0.92(0.61–1.40) 0.693 0.0% 0.712 
Mixed 0.94(0.76–1.17) 0.592 0.0% 0.549 0.86(0.52–1.41) 0.550 0.0% 0.721 0.94(0.70–1.27) 0.679 0.0% 0.494 0.89(0.56–1.42) 0.619 0.0% 0.874 
Sample sizes 
<1000 13 1.02(0.93–1.13) 0.631 25.8% 0.198 1.06(0.86–1.31) 0.559 0.0% 0.488 1.05(0.90–1.22) 0.537 31.3% 0.149 1.02(0.87–1.19) 0.857 0.0% 0.686 
≥1000 0.88(0.80–0.96) 0.006 52.6% 0.061 0.80(0.70–0.92) 0.001 29.1% 0.217 0.84(0.73–0.97) 0.020 48.8% 0.082 0.85(0.76–0.94) 0.002 35.3% 0.172 
Source of control 
P-B 1.10(0.89–1.36) 0.374 53.7% 0.116 1.30(0.97–1.73) 0.080 39.9% 0.190 1.19(0.81–1.75) 0.385 65.0% 0.057 1.14(0.91–1.43) 0.248 0.0% 0.490 
H-B 15 0.88(0.83–0.93) <0.001 22.9% 0.212 0.81(0.71–0.92) 0.001 0.0% 0.642 0.84(0.77–0.93) <0.001 23.2% 0.209 0.85(0.77–0.94) 0.002 0.0% 0.498 
NA 0.96(0.73–1.26) 0.766 – – 0.91(0.51–1.63) 0.743 – – 0.91(0.56–1.48) 0.712 – – 0.97(0.62–1.52) 0.887 – – 
Control type 
Normal or healthy 10 0.95(0.84–1.08) 0.428 66.3% 0.002 0.92(0.74–1.16) 0.487 53.9% 0.021 0.95(0.79–1.15) 0.590 65.0% 0.002 0.94(0.79–1.11) 0.439 42.3% 0.076 
Hepatitis or virus related 0.90(0.81–0.99) 0.028 0.0% 0.533 0.82(0.67–1.00) 0.054 0.0% 0.905 0.90(0.56–1.06) 0.208 0.0% 0.463 0.85(0.72–0.99) 0.035 0.0% 0.695 
NA 0.96(0.73–01.26) 0.766 – – 0.91(0.51–1.63) 0.743 – – 0.91(0.56–1.48) 0.712 – – 0.93(0.64–1.35) 0.684 0.0% 0.729 
No. of studiesT vs. CTT vs. CCTT/CT vs. CCTT vs. CT/CC
OR (95% CI)PI2P(Q-test)OR(95% CI)PI2P(Q-test)OR(95% CI)PI2P(Q-test)OR(95% CI)PI2P(Q-test)
Total 19 0.93(0.85–1.01) 0.077 48.7% 0.013 0.88(0.77–1.01) 0.078 25.8% 0.158 0.92(0.81–1.05) 0.209 47.3% 0.016 0.90(0.82–0.98) 0.016 11.9% 0.309 
Ethnicity 
Asians 11 0.94(0.85–1.03) 0.182 63.4% 0.002 0.90(0.75–1.06) 0.210 50.1% 0.029 0.94(0.80–1.09) 0.380 59.3% 0.006 0.90(0.79–1.03) 0.133 44.4% 0.055 
Caucasians 0.79(0.57–1.09) 0.153 0.0% 0.405 0.67(0.30–1.50) 0.331 0.0% 0.781 0.73(0.47–1.13) 0.155 42.2% 0.177 0.92(0.61–1.40) 0.693 0.0% 0.712 
Mixed 0.94(0.76–1.17) 0.592 0.0% 0.549 0.86(0.52–1.41) 0.550 0.0% 0.721 0.94(0.70–1.27) 0.679 0.0% 0.494 0.89(0.56–1.42) 0.619 0.0% 0.874 
Sample sizes 
<1000 13 1.02(0.93–1.13) 0.631 25.8% 0.198 1.06(0.86–1.31) 0.559 0.0% 0.488 1.05(0.90–1.22) 0.537 31.3% 0.149 1.02(0.87–1.19) 0.857 0.0% 0.686 
≥1000 0.88(0.80–0.96) 0.006 52.6% 0.061 0.80(0.70–0.92) 0.001 29.1% 0.217 0.84(0.73–0.97) 0.020 48.8% 0.082 0.85(0.76–0.94) 0.002 35.3% 0.172 
Source of control 
P-B 1.10(0.89–1.36) 0.374 53.7% 0.116 1.30(0.97–1.73) 0.080 39.9% 0.190 1.19(0.81–1.75) 0.385 65.0% 0.057 1.14(0.91–1.43) 0.248 0.0% 0.490 
H-B 15 0.88(0.83–0.93) <0.001 22.9% 0.212 0.81(0.71–0.92) 0.001 0.0% 0.642 0.84(0.77–0.93) <0.001 23.2% 0.209 0.85(0.77–0.94) 0.002 0.0% 0.498 
NA 0.96(0.73–1.26) 0.766 – – 0.91(0.51–1.63) 0.743 – – 0.91(0.56–1.48) 0.712 – – 0.97(0.62–1.52) 0.887 – – 
Control type 
Normal or healthy 10 0.95(0.84–1.08) 0.428 66.3% 0.002 0.92(0.74–1.16) 0.487 53.9% 0.021 0.95(0.79–1.15) 0.590 65.0% 0.002 0.94(0.79–1.11) 0.439 42.3% 0.076 
Hepatitis or virus related 0.90(0.81–0.99) 0.028 0.0% 0.533 0.82(0.67–1.00) 0.054 0.0% 0.905 0.90(0.56–1.06) 0.208 0.0% 0.463 0.85(0.72–0.99) 0.035 0.0% 0.695 
NA 0.96(0.73–01.26) 0.766 – – 0.91(0.51–1.63) 0.743 – – 0.91(0.56–1.48) 0.712 – – 0.93(0.64–1.35) 0.684 0.0% 0.729 

P-B: population-based;

H-B: hospital-based

NA: not available

Subgroup analyses were carried out according to the following terms: ethnicity (Caucasians or Asians or mixed), sample sizes (<1000 or ≥1000 subjects), control type [normal/healthy subjects or hepatitis/virus related patients or not available (NA)] and source of control [hospital-based (HB) or population-based (PB) or NA]. We pooled seven case–control studies (including 2,435 HCC cases and 1,642 hepatitis/virus related patients) and found an association between MTHFR rs1801133 polymorphism and decreased risk of HCC in hepatitis/virus related patients (recessive model: OR, 0.85; 95%CI, 0.72–0.99; P = 0.035, and allele model: OR, 0.90; 95%CI, 0.81–0.99; P = 0.028, Table 3). When we conducted a subgroup analysis by ethnicity, null association between MTHFR rs1801133 C>T polymorphism and the risk of HCC was found.

Heterogeneity assessment

In some genetic models, heterogeneity was significant (Table 3). Subgroup analyses indicated that extreme heterogeneity existed in Asian populations, larger sample size investigation, HB study and normal/healthy control subgroups. If we excluded these subgroups in our meta-analysis, the heterogeneity significantly decreased.

Bias evaluation

We used Begger’s and Egger’s tests to identify the bias of publication among the included investigations. The shape of Begger’s test seemed symmetrical (Figure 3). Egger’s linear regression test also confirmed these evaluations.

Begg’s funnel plot of meta–analysis of the association between MTHFR rs1801133 polymorphism and HCC risk (recessive model, fixed-effects model)

Figure 3
Begg’s funnel plot of meta–analysis of the association between MTHFR rs1801133 polymorphism and HCC risk (recessive model, fixed-effects model)
Figure 3
Begg’s funnel plot of meta–analysis of the association between MTHFR rs1801133 polymorphism and HCC risk (recessive model, fixed-effects model)

Sensitivity analyses

By sequentially omitting an individual investigation, sensitivity analysis was carried out. This method is considered as a criterion for meta-analysis. The results indicated that the significance of the present study could not be altered by removing any case–control study (Figure 4), suggesting that our findings were stable.

Sensitivity analysis of the influence of MTHFR rs1801133 polymorphism to HCC risk (recessive model, fixed-effects model)

Figure 4
Sensitivity analysis of the influence of MTHFR rs1801133 polymorphism to HCC risk (recessive model, fixed-effects model)
Figure 4
Sensitivity analysis of the influence of MTHFR rs1801133 polymorphism to HCC risk (recessive model, fixed-effects model)

Quality assessment

Table 2 presents the results of the quality evaluation. Each eligible study had an acceptable quality (scores ≥ 6).

Discussion

Accumulating investigations highlight that MTHFR rs1801133 polymorphism may be associated with the development of HCC. However, the findings of the previous case–control studies were conflicting, with several investigations suggesting a potential relationship, whereas others did not support the correlation. In this investigation, to explore whether the MTHFR rs1801133 polymorphism was implicated in the etiology of HCC, we carried out a pooled-analysis of 19 eligible studies, which recruited 6,102 HCC cases and 6,526 controls. This meta-analysis indicated that the MTHFR rs1801133 polymorphism was a protective factor for the development of HCC in the overall comparison. Compared with the previous study, this pooled-analysis first confirmed the association of MTHFR rs1801133 polymorphism with a decreased risk of HCC.

MTHFR rs1801133 polymorphism locates on 11796321 (NCBI Build 38) of Chromosome 1. Zhu and her/his colleagues first reported that MTHFR rs1801133 polymorphism might confer a risk to HCC [24]. In addition, Cui et al. also suggested that this polymorphism could increase the risk of HCC [20]. However, some case–control studies indicated that the rs1801133 polymorphism in MTHFR gene might decrease the susceptibility of HCC [21,25]. And most studies reported that this SNP in MTHFR gene could not alter the risk of HCC. Thus, the association of MTHFR rs1801133 polymorphism with the susceptibility of HCC was more conflicting. Here, we performed a pooled-analysis of nineteen eligible studies involving 6,102 HCC cases and 6,526 controls to explore the correlation of rs1801133 with the etiology of HCC. The results indicated that this SNP in MTHFR gene could be a protective factor for the occurrence of HCC. Two meta-analyses suggested that rs1801133 was not associated with HCC development [43,44]. Others pooled-analyses reported that MTHFR rs1801133 polymorphism was associated with an increased risk of HCC [45–48]. Compared with these early meta-analyses, our analysis included more large sample size studies [21,25]. It is worth mentioning that these more recent case–control studies have recruited more participants and reported that rs1801133 polymorphism was a protective factor for the development of HCC. Compared with the most recent meta-analysis [23], the merit of our study was the larger sample size and the detailed subgroup analysis. Combined the eligible studies, we observed that rs1801133 decreased the susceptibility of HCC in the overall comparison. The quality score was evaluated in our study. Each eligible study had an acceptable quality (scores ≥6). This indicated that our findings were reliable. We also found an association between MTHFR rs1801133 polymorphism and decreased risk of HCC in hepatitis/virus related patients. Of late, in Asian population, some meta-analyses identified that MTHFR rs1801133 polymorphism decreased the risk of colorectal cancer [49,50]. Some publications [51,52] suggested that MTHFR rs1801133 C>T polymorphism (Ala→Val) could promote the level of 5,10-methylene-THF for DNA synthesis, which might be protective to carcinogenesis. In the future, a functional study should be carried out to address how this Ala→Val substitution could decrease the risk of HCC.

Heterogeneity was identified in the overall comparison. In the present study, we conducted subgroup analyses to explore the major source among the eligible studies. Subgroup analysis suggested that major heterogeneity might be due to different populations, sample size, and characteristics of controls.

Some potential limitations should be addressed in this pooled-analysis. First, only published investigations were eligible in our study. Thus, the number of included case–control studies might be inadequate. Second, for lacking of sufficient data, only crude ORs and CIs were calculated. Third, the controls in some of the case–control studies were hepatitis or virus related patients. Fourth, a recent investigation contained some subgroups, we treated them as independent case–control studies. However, in this literature, the same HCC group was used in different stratified analysis. Finally, our study did not focus on the gene–gene and gene–environment interactions.

In summary, the present pooled-analysis highlights that MTHFR rs1801133 polymorphism is a protective factor for the occurrence of HCC, especially in hepatitis/virus related patients. The relationship of MTHFR rs1801133 polymorphism with HCC risk warrants a further determination.

Competing Interests

The authors declare that there are no competing interests associated with the manuscript.

Funding

The project was supported by the Application and Basic Research Project of Changzhou City [grant number CJ20180068].

Author Contribution

Conceived and designed the experiments: S.Z. and L.L. Performed the experiments: S.Z. and J.J. Analyzed the data: W.T. and S.Z. Contributed reagents/materials/analysis tools: L.L. Wrote the manuscript: S.Z. and J.J.

Acknowledgements

We wish to thank Dr Yan Liu (Genesky Biotechnologies Inc., Shanghai, China) for technical support.

Abbreviations

     
  • CI

    confidence interval

  •  
  • HCC

    hepatocellular carcinoma

  •  
  • MTHFR

    methylenetetrahydrofolate reductase

  •  
  • OR

    odds ratio

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Author notes

*

These authors have contributed equally to this work.

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