Background. The presence or absence of glutathione S-transferase M1 gene (GSTM1) and glutathione S-transferase T1 gene (GSTT1) polymorphisms, and their combined effects have been suggested as a risk factor for colorectal cancer (CRC). However, the results are inconsistent.

Objectives. An updated meta-analysis was performed to solve the controversy.

Methods. Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines were used.

Results. Overall, the GSTM1 null genotype was associated with an increased CRC risk in Caucasians (odds ratio (OR) = 1.14, 95% confidence interval (CI): 1.05–1.23), Asians (OR = 1.19, 95% CI: 1.08–1.32), high-quality studies (OR = 1.12, 95% CI: 1.06–1.18). Moreover, the GSTM1 null genotype was also associated with an increased colon cancer risk (OR = 1.32, 95% CI: 1.16–1.51). The GSTT1 null genotype was also associated with an increased CRC risk in Asians (OR = 1.08, 95% CI: 1.02–1.15) and Caucasians (OR = 1.24, 95% CI: 1.09–1.41). Moreover, The GSTT1 null genotype was associated with an increased rectal cancer risk (OR = 1.13, 95% CI: 1.01–1.27, I2 = 8.3%) in subgroup analysis by tumor location. Last, the GSTM1 null/GSTT1 null genotype was associated with an increased CRC risk in Asians.

Conclusion. This meta-analysis indicates that the GSTM1 and GSTT1 null genotypes are associated with increased CRC risk in Asians and Caucasians, and the GSTM1 null/GSTT1 null genotype was associated with increased CRC risk in Asians.

Colorectal cancer (CRC) is a common form of cancer, with more than 1.5 million new patients diagnosed every year worldwide [1]. It is a complex chronic disease whose development is affected by genetic and environmental factors [2,3]. CRC incidence rates differ between countries indicating that environmental factors may be associated with an increased cancer risk, although. A twin study indicated that the role of genetic factors is around 35% in CRC [4]. A previous genome-wide association study also indicated that single-nucleotide polymorphisms are important risk factors [5].

Glutathione S-transferases (GSTs) are a large family of enzymes that catalyze the conjugation of electrophiles to glutathione and the conversion of toxic compounds to hydrophilic metabolites [6,7]. GSTM1 maps to chromosome 1p13.3 contains 10 exons, while GSTT1 maps to chromosome 22q11.23 and contains six exons. GSTM1 present/null and GSTT1 present/null polymorphisms have been reported in human [8–11]. The null genotypes are the most common polymorphisms in GSTM1 and GSTT1, and have been proven to be associated with the loss of enzyme activity [12,13].

To date, many studies have evaluated the association between GSTM1 present/null and GSTT1 present/null polymorphisms, and their combined effects with CRC risk [14–107,108–114]. Additionally, 13 meta-analyses [115–125,126,127] have been conducted. However, a lot of studies have been published on these associations with CRC risk, therefore, an updated meta-analysis was performed to explore the association between GSTM1 present/null, GSTT1 present/null, and their combined effects on CRC risk in all populations.

Search strategy

Meta-analyses of Observational Studies in Epidemiology (MOOSE) guidelines were used [128]. PubMed, Chinese Biomedical Medical databases (CBM), China National Knowledge Infrastructure (CNKI), and WanFang databases (up to March 15, 2020) were searched to identify eligible studies that analyzed the GSTM1 present/null, GSTT1 present/null, and their combined effects with CRC risk. The following keywords were used: (GSTT1 OR glutathione S-transferase T1 OR GSTM1 OR glutathione S-transferase M1) AND (polymorphism OR variant OR mutation) AND (colorectal OR rectal OR rectum OR colon). The search strategy was designed to be sensitive and broad. We first carefully reviewed the title and abstract of the search results, and then downloaded full articles to identify possible articles. These were evaluated in detail to identify relevant articles. The reference lists of identified articles and reviews was also examined as appropriate. The corresponding author may be contacted by e-mail if only the abstract was available online or the data was incomplete.

Inclusion and exclusion criteria

Inclusion criteria were as follows: (1) articles on the GSTM1 present/null, GSTT1 present/null, and their combined effects with CRC risk; (2) sufficient genotype data to calculate ORs and 95% CIs; and (3) case–control studies. Exclusion criteria were as follows: (1) no raw data; (2) no control; (3) review articles, case reports, editorials, or animal research; (4) duplicate and insufficient data.

Data extraction and quality score assessment

Two investigators independently extracted data using Excel. Any disagreement was solved by iteration, discussion, and consensus. The following data were extracted from eligible studies: (1) first author’s name, (2) publication year, (3) country, (4) source of controls (hospital-based and population-based case–control studies), (5) sample size, (6) genotyping method, and (6) genotype distribution of the GSTM1, GSTT1, and their combined effects in cases and controls. Different ethnicities included “Caucasians”, “Asians”, “Indians”, and “Africans”. If ethnicity was not stated or if the sample size could not be separated, the term “Mixed populations” was used. Two investigators independently assessed the quality of each individual study. The quality assessment criteria (Table 1) were obtained from two previous meta-analyses [129,130]. The highest value is obtained from the quality assessment was nine; studies of quality scoring ≥ 6 were considered as high quality.

Table 1
Scale for quality assessment
CriteriaScore
Representativeness of cases 
Selected from cancer registry or multiple cancer center sites 
Selected from oncology department or cancer institute 
Selected without clearly defined sampling frame or with extensive inclusion/exclusion criteria 
Source of controls 
Population or community based 
Both population-based and hospital-based/healthy volunteers/blood donors 1.5 
Hospital-based controls without colorectal cancer 
Cancer-free controls without total description 0.5 
Not described 
Ascertainment of colorectal cancer 
Histological or pathological confirmation 
Diagnosis of colorectal cancer by patient medical record 
Not described 
Sample size 
>1000 
200–1000 
<200 
Quality control of genotyping methods 
Clearly described a different genotyping assay to confirm the data 
Not described 
CriteriaScore
Representativeness of cases 
Selected from cancer registry or multiple cancer center sites 
Selected from oncology department or cancer institute 
Selected without clearly defined sampling frame or with extensive inclusion/exclusion criteria 
Source of controls 
Population or community based 
Both population-based and hospital-based/healthy volunteers/blood donors 1.5 
Hospital-based controls without colorectal cancer 
Cancer-free controls without total description 0.5 
Not described 
Ascertainment of colorectal cancer 
Histological or pathological confirmation 
Diagnosis of colorectal cancer by patient medical record 
Not described 
Sample size 
>1000 
200–1000 
<200 
Quality control of genotyping methods 
Clearly described a different genotyping assay to confirm the data 
Not described 

Statistical analysis

We used crude odds ratios (ORs) and 95% confidence intervals (CIs) to estimate the association on the above issues. The genetic model of the individual GSTM1 and GSTT1 polymorphisms was null vs. present. Their combined effects used the following five genetic models: − − vs. + +, − − vs. + −, − − vs.− +, − − vs. (+ −) + (− +), and − − vs. (+ −) + (− +) + (+ +). − − referred to the GSTM1 null/GSTT1 null genotype, + − referred to the GSTM1 present/GSTT1 null genotype, − + referred to the GSTM1 null/GSTT1 present genotype, and + + referred to the GSTM1 present/GSTT1 present genotype. Heterogeneity among studies was tested using the I2 value [131]. A fixed-effects model (Mantel–Haenszel method) was used when I2 ≤ 50% [132]; otherwise, a random-effects model (DerSimonian and Laird method) was considered [133] if I2 > 50%. However, these studies cannot be pooled into together when I2 value > 75%. Subgroup analyses were performed by ethnicity, source of controls, tumor location, smoking history, gender, quality score, and tumor site. Then, a sensitivity analysis was carried out to assess the stability, a single study was excluded one at a time. Publication bias was tested by using Begg’s funnel and Egger’s test (significant publication bias was considered if P < 0.05). A nonparametric “trim and fill” method was applied to accredit missing studies if publication bias was detected. Finally, a meta-regression analysis was applied to assess the heterogeneity source. All results were calculated using Stata version 9.0 (Stata Corporation, College Station, TX, U.S.A.).

Study characteristics

A flowchart of study selection is shown in Figure 1. Overall, 472 articles were identified by electronic database searching. Of these, 115 full-text articles were selected after carefully screening titles and abstracts. Fourteen articles were excluded because they were not case-control studies, while the data of fourteen articles [18,25,37,43,61,65,79,84,86,92,94,95,100,110] overlapped with those of another nine articles [26,41,47,48,93,105,107,108,114]. Hence, a total of 87 articles were included in the present meta-analysis.

Flow diagram for identifying and including studies in the current meta-analysis

Figure 1
Flow diagram for identifying and including studies in the current meta-analysis
Figure 1
Flow diagram for identifying and including studies in the current meta-analysis

The main study characteristics are listed in Tables 2 and 3. Eighty-five publications involving eighty-six case–control studies [14–17,19–24,26–36,38–42,44–60,62–64,66–78,80–83,85,87,88,90,91,93,96–99,101,103–107,108,109,111–114] were included on the GSTM1 present/null polymorphism (24,931 cases and 36,537 controls; 44 studies on Caucasians, 31 on Asians, one on Africans, one on Indians, and nine on mixed populations) with CRC risk. Sixty-three articles of sixy-four case–control studies [15–17,19,21–24,26,27,30,31,33,34,36,38–42,45,47,48–52,54–58,62–64,67–70,73,74,76–78,80–82,87–90,93,96–99,102,105,109,111–114] were eligible concerning the GSTT1 present/null polymorphism (19,725 cases and 28,725 controls; 34 studies on Caucasians, 23 on Asians, one on Indians, one on Africans, and five on mixed populations) with CRC risk. Thirty-two publications of thirty-three case–control studies [15,19,22–24,27,31,33,38,39,41,42,45,49,52,55–57,63,67,68,70,76–78,90,96,97,99,105,109,112] were included regarding their combined effects (8270 cases and 14,381 controls; 11 studies on Caucasians, 17 on Asians, one on Indians, one on Africans, and three on mixed populations) with CRC risk. Fifty-five studies had a quality score ≥ 6 and the remaining 31 had a quality score < 6 regarding the GSTM1 present/null polymorphism; 48 high-quality studies were examined and the remaining 16 were low-quality concerning the GSTT1 present/null polymorphism; a total of 25 high-quality and eight low-quality studies were included on their combined effects with CRC risk.

Table 2
The data between the GSTM1 and GSTT1 polymorphisms and colorectal cancer risk
First author/YearCountryEthnicitySCSample size (case/ control)Genotyping methodsGSTM1 genotype distributionGSTT1 genotype distributionQuality scores
CaseControlCaseControl
PresentNullPresentNullPresentNullPresentNull
Stojkovic [111] 2019 Serbia Caucasian HB 509/399 Multiplex PCR 249 260 204 195 145 364 91 308 
Rodrigues-Fleming [112] 2018 Brazil Mixed HB 232/738 Multiplex PCR and PCR-RFLP 100 132 385 353 192 40 573 165 6.5 
Waś [113] 2018 Poland Caucasian HB 279/233 PCR 151 128 133 100 220 59 189 44 
Klusek [114] 2018 Poland Caucasian HB 197/104 TaqMan 105 92 57 47 166 31 83 21 
Gorukmez [49] 2016 Turkey Caucasian HB 92/116 Multiplex PCR 65 27 67 49 58 34 91 25 
Khabaz [32] 2016 Saudi Arabia Caucasian HB 83/35 PCR 14 69 12 23 NA NA NA NA 
Zeng [99] 2016 China Asian HB 108/215 PCR 38 70 110 105 48 60 117 98 
Djansugurova [34] 2015 Kazakhstan Mixed HB 249/245 Site-specific PCR 124 125 158 87 171 78 164 81 4.5 
Cong [33] 2014 China Asian PB 264/317 Multiplex PCR 122 142 182 135 125 139 190 127 
Procopciuc [85] 2014 Romania Caucasian HB 150/162 PCR-RFLP 60 90 97 65 NA NA NA NA 
Vogtmann [31] 2014 China Asian PB 340/673 Real-time PCR 134 201 259 379 164 173 350 318 
Kassab [76] 2014 Tunisia Caucasian HB 147/128 Multiplex PCR 43 104 41 87 90 57 65 63 
Saeed [14] 2013 Saudi Arabia Caucasian HB 100/79 PCR 98 79 NA NA NA NA 
Chirila [15] 2013 Romania Caucasian HB 19/19 Multiple PCR 14 15 15 16 
Hezova [16] 2012 Czech Caucasian HB 197/218 Duplex PCR 97 100 117 101 157 40 179 39 6.5 
Rudolph [17] 2012 German Caucasian PB 1796/1806 Multiplex PCR 822 932 844 923 1433 313 1459 308 
Huang [96] 2012 China Asian HB 130/100 PCR 71 59 58 42 63 67 52 48 
Darazy [20] 2011 Lebanese Caucasian HB 67/70 PCR 32 25 58 12 NA NA NA NA 3.5 
Wang [23] 2011 India Indian HB 302/291 Multiplex PCR 202 100 215 76 245 57 247 44 
Koh [19] 2011 China Asian PB 480/1167 TaqMan 246 234 641 526 294 186 691 476 
Cleary [21] 2010 Canada Caucasian PB 1174/1293 Multiplex PCR 550 616 608 684 953 213 1,067 223 
Yang [24] 2010 China Asian PB 322/1251 Real-time PCR 133 189 521 730 158 164 639 612 
Nisa [78] 2010 Japan Asian PB 685/778 Multiplex PCR 328 357 356 422 347 338 435 343 
Zhang SS [50] 2010 China Asian PB 197/399 Multiplex PCR 83 114 184 215 150 47 310 89 
Hlavata [22] 2010 Czech Caucasian HB 495/495 PCR-RFLP 228 267 254 241 392 103 395 100 
Csejtei [26] 2009 Hungary Caucasian HB 102/97 PCR 42 60 51 46 68 34 77 20 
Piao [77] 2009 Korea Asian PB 1829/1699 Real-time PCR 825 1,004 776 923 879 950 841 858 
Matakova [27] 2009 Slovak Caucasian PB 183/402 PCR 83 100 202 220 142 41 329 93 
Zupa [28] 2009 Italy Caucasian HB 92/121 PCR 31 61 53 68 NA NA NA NA 
Curtin [29] 2009 U.S.A. Caucasian PB 750/1201 PCR 310 323 465 545 NA NA NA NA 
Epplein [30] 2009 U.S.A. Mixed PB 173/313 TaqMan 82 91 166 147 127 46 201 112 
Lin LM [93] 2008 China Asian HB 120/204 Multiplex PCR 51 69 114 90 56 64 119 85 
Yang ZF [46] 2008 China Asian HB 84/112 PCR 24 60 61 51 NA NA NA NA 
Cotterchio [88] 2008 Canada Caucasian PB 836/1249 Multiplex PCR 395 441 588 661 679 157 1,029 219 
Kury [87] 2008 France Caucasian PB 1023/1121 TaqMan 479 544 553 568 840 183 916 205 
Skjelbred [36] 2007 Norway Caucasian PB 108/299 Multiplex PCR 53 55 148 151 93 15 262 37 
Yoshida [35] 2007 Japan Asian PB 66/121 PCR 30 36 59 62 NA NA NA NA 
Xia [59] 2007 China Asian HB 112/140 PCR 45 67 77 63 NA NA NA NA 
Huang [105] 2007 China Asian HB 57/68 PCR 17 40 33 35 33 24 44 24 
Martínez [38] 2006 Spain Caucasian PB 144/329 Multiplex PCR 55 87 180 149 68 74 253 76 
Probst-Hensch [39] 2006 China Asian PB 300/1169 TaqMan 168 132 643 525 200 100 693 475 
Little [40] 2006 U.K. Caucasian PB 241/383 PCR 110 131 162 221 192 49 318 65 
Fan [41] 2006 China Asian PB 140/343 PCR 58 80 151 188 113 25 270 69 
Huang [42] 2006 U.S.A. Caucasian PB 315/547 Multiplex PCR 135 180 258 289 241 74 385 162 
Huang [42] 2006 U.S.A. African PB 239/327 Multiplex PCR 162 77 245 82 187 56 218 109 
Fu [98] 2006 China Asian PB 315/439 PCR 86 229 117 321 141 174 187 251 
Luo [91] 2006 China Asian HB 56/143 PCR 36 20 95 48 NA NA NA NA 
Rajagopal [89] 2005 U.K. Caucasian HB 361/881 PCR NA NA NA NA 265 96 723 158 
Landi [44] 2005 Spain Caucasian HB 176/162 PCR 77 99 66 96 NA NA NA NA 
Ateş [45] 2005 Turkey Caucasian HB 181/204 Real-Time PCR 83 98 116 88 118 63 151 53 
Yeh [47] 2005 China Asian HB 727/736 Multiplex PCR 325 402 326 410 331 396 376 360 
van der Logt [51] 2004 U.S.A. Caucasian PB 371/415 PCR 186 184 212 203 299 72 346 69 
Kiss [48] 2004 Hungary Caucasian HB 500/500 PCR 209 291 258 242 369 131 392 108 
Chen [109] 2004 China Asian HB 125/339 PCR 56 69 151 188 102 23 270 69 
Smits [53] 2003 Multiple Caucasian PB 724/1743 PCR 381 343 821 922 NA NA NA NA 7.5 
van der Hel [54] 2003 U.S.A. Caucasian PB 212/765 PCR 124 88 396 369 154 58 541 224 
Slattery [107] 2003 U.S.A. Mixed PB 801/1013 PCR 397 404 467 546 NA NA NA NA 
Nascimento [55] 2003 Brazil Mixed HB 102/300 Multiplex PCR 52 50 166 134 85 17 248 52 
Huang [90] 2003 China Asian HB 82/82 Multiplex PCR 36 46 54 28 41 41 42 40 
Yang [101] 2003 China Asian HB 58/65 PCR-RFLP 18 40 36 29 NA NA NA NA 
Zhang [102] 2003 China Asian HB 81/112 Multiplex PCR NA NA NA NA 27 54 54 58 
Zhu [57] 2002 China Asian HB 104/101 Multiplex PCR 56 48 44 57 55 49 40 61 
Ye [58] 2002 U.K. Caucasian HB 41/82 Specific PCR 21 20 49 33 39 73 
Tiemersma [60] 2002 U.S.A. Mixed PB 102/537 PCR 44 58 252 285 NA NA NA NA 
Seow [56] 2002 China Asian PB 213/1194 TaqMan 105 108 653 537 133 80 710 480 
Sachse [81] 2002 U.K. Caucasian PB 490/593 PCR 206 284 291 302 306 184 378 215 
Laso [82] 2002 Spain Caucasian HB 247/296 Multiplex PCR 114 133 138 158 116 131 263 33 
Sgambato [83] 2002 Italy Caucasian HB 44/100 Duplex PCR 12 32 47 53 NA NA NA NA 
Slattery [108] 2002 U.S.A. Mixed PB 1577/1904 PCR 761 816 892 1012 NA NA NA NA 
Butler [62] 2001 Australia Caucasian PB 219/200 PCR 97 106 92 108 123 67 160 40 
Saadat [63] 2001 Iran Caucasian HB 46/131 PCR 21 25 78 53 28 18 90 41 
Loktionov [64] 2001 U.K. Caucasian HB 206/355 PCR 73 133 147 208 166 40 301 54 
Zhang [103] 2001 China Asian HB 52/52 Multiplex PCR 30 22 27 25 NA NA NA NA 
Zhou [97] 2000 China Asian HB 55/62 PCR 21 34 29 33 24 31 31 31 
Gawrońska-Szklarz [66] 1999 Poland Caucasian HB 70/145 PCR 24 46 73 72 NA NA NA NA 
Yoshioka [67] 1999 Japan Asian HB 106/100 PCR 50 56 58 42 55 51 59 41 
Abdel-Rahman [68] 1999 Egypt Caucasian HB 66/55 PCR 26 37 15 30 37 22 30 21 
Zhang [80] 1999 Sweden Caucasian HB 94/109 Multiplex PCR 50 44 54 55 44 50 87 22 
Welfare [69] 1999 U.K. Caucasian PB 196/178 PCR 94 102 88 90 157 39 148 30 
Gao [104] 1998 China Asian HB 19/70 PCR 12 45 25 NA NA NA NA 
Lee [71] 1998 Singapore Asian HB 300/183 NA 172 128 94 89 NA NA NA NA 
Gertig [70] 1998 U.S.A. Mixed PB 212/221 PCR 97 114 104 117 173 36 169 51 
Guo [72] 1996 China Asian HB 19/23 PCR 12 17 NA NA NA NA 
Katoh [73] 1996 Japan Asian HB 103/126 Multiplex PCR 47 56 71 55 53 50 70 56 
Deakin [52] 1996 U.K. Caucasian HB 252/577 PCR 117 135 261 316 189 63 415 94 
Chenevix-Trench [74] 1995 Australia Caucasian HB 132/200 NA 68 64 99 101 79 15 125 23 
Zhong [75] 1993 U.K. Caucasian PB 196/225 PCR 86 110 131 94 NA NA NA NA 
Strange [106] 1991 U.K. Mixed HB 19/502 HSE 14 249 253 NA NA NA NA 
First author/YearCountryEthnicitySCSample size (case/ control)Genotyping methodsGSTM1 genotype distributionGSTT1 genotype distributionQuality scores
CaseControlCaseControl
PresentNullPresentNullPresentNullPresentNull
Stojkovic [111] 2019 Serbia Caucasian HB 509/399 Multiplex PCR 249 260 204 195 145 364 91 308 
Rodrigues-Fleming [112] 2018 Brazil Mixed HB 232/738 Multiplex PCR and PCR-RFLP 100 132 385 353 192 40 573 165 6.5 
Waś [113] 2018 Poland Caucasian HB 279/233 PCR 151 128 133 100 220 59 189 44 
Klusek [114] 2018 Poland Caucasian HB 197/104 TaqMan 105 92 57 47 166 31 83 21 
Gorukmez [49] 2016 Turkey Caucasian HB 92/116 Multiplex PCR 65 27 67 49 58 34 91 25 
Khabaz [32] 2016 Saudi Arabia Caucasian HB 83/35 PCR 14 69 12 23 NA NA NA NA 
Zeng [99] 2016 China Asian HB 108/215 PCR 38 70 110 105 48 60 117 98 
Djansugurova [34] 2015 Kazakhstan Mixed HB 249/245 Site-specific PCR 124 125 158 87 171 78 164 81 4.5 
Cong [33] 2014 China Asian PB 264/317 Multiplex PCR 122 142 182 135 125 139 190 127 
Procopciuc [85] 2014 Romania Caucasian HB 150/162 PCR-RFLP 60 90 97 65 NA NA NA NA 
Vogtmann [31] 2014 China Asian PB 340/673 Real-time PCR 134 201 259 379 164 173 350 318 
Kassab [76] 2014 Tunisia Caucasian HB 147/128 Multiplex PCR 43 104 41 87 90 57 65 63 
Saeed [14] 2013 Saudi Arabia Caucasian HB 100/79 PCR 98 79 NA NA NA NA 
Chirila [15] 2013 Romania Caucasian HB 19/19 Multiple PCR 14 15 15 16 
Hezova [16] 2012 Czech Caucasian HB 197/218 Duplex PCR 97 100 117 101 157 40 179 39 6.5 
Rudolph [17] 2012 German Caucasian PB 1796/1806 Multiplex PCR 822 932 844 923 1433 313 1459 308 
Huang [96] 2012 China Asian HB 130/100 PCR 71 59 58 42 63 67 52 48 
Darazy [20] 2011 Lebanese Caucasian HB 67/70 PCR 32 25 58 12 NA NA NA NA 3.5 
Wang [23] 2011 India Indian HB 302/291 Multiplex PCR 202 100 215 76 245 57 247 44 
Koh [19] 2011 China Asian PB 480/1167 TaqMan 246 234 641 526 294 186 691 476 
Cleary [21] 2010 Canada Caucasian PB 1174/1293 Multiplex PCR 550 616 608 684 953 213 1,067 223 
Yang [24] 2010 China Asian PB 322/1251 Real-time PCR 133 189 521 730 158 164 639 612 
Nisa [78] 2010 Japan Asian PB 685/778 Multiplex PCR 328 357 356 422 347 338 435 343 
Zhang SS [50] 2010 China Asian PB 197/399 Multiplex PCR 83 114 184 215 150 47 310 89 
Hlavata [22] 2010 Czech Caucasian HB 495/495 PCR-RFLP 228 267 254 241 392 103 395 100 
Csejtei [26] 2009 Hungary Caucasian HB 102/97 PCR 42 60 51 46 68 34 77 20 
Piao [77] 2009 Korea Asian PB 1829/1699 Real-time PCR 825 1,004 776 923 879 950 841 858 
Matakova [27] 2009 Slovak Caucasian PB 183/402 PCR 83 100 202 220 142 41 329 93 
Zupa [28] 2009 Italy Caucasian HB 92/121 PCR 31 61 53 68 NA NA NA NA 
Curtin [29] 2009 U.S.A. Caucasian PB 750/1201 PCR 310 323 465 545 NA NA NA NA 
Epplein [30] 2009 U.S.A. Mixed PB 173/313 TaqMan 82 91 166 147 127 46 201 112 
Lin LM [93] 2008 China Asian HB 120/204 Multiplex PCR 51 69 114 90 56 64 119 85 
Yang ZF [46] 2008 China Asian HB 84/112 PCR 24 60 61 51 NA NA NA NA 
Cotterchio [88] 2008 Canada Caucasian PB 836/1249 Multiplex PCR 395 441 588 661 679 157 1,029 219 
Kury [87] 2008 France Caucasian PB 1023/1121 TaqMan 479 544 553 568 840 183 916 205 
Skjelbred [36] 2007 Norway Caucasian PB 108/299 Multiplex PCR 53 55 148 151 93 15 262 37 
Yoshida [35] 2007 Japan Asian PB 66/121 PCR 30 36 59 62 NA NA NA NA 
Xia [59] 2007 China Asian HB 112/140 PCR 45 67 77 63 NA NA NA NA 
Huang [105] 2007 China Asian HB 57/68 PCR 17 40 33 35 33 24 44 24 
Martínez [38] 2006 Spain Caucasian PB 144/329 Multiplex PCR 55 87 180 149 68 74 253 76 
Probst-Hensch [39] 2006 China Asian PB 300/1169 TaqMan 168 132 643 525 200 100 693 475 
Little [40] 2006 U.K. Caucasian PB 241/383 PCR 110 131 162 221 192 49 318 65 
Fan [41] 2006 China Asian PB 140/343 PCR 58 80 151 188 113 25 270 69 
Huang [42] 2006 U.S.A. Caucasian PB 315/547 Multiplex PCR 135 180 258 289 241 74 385 162 
Huang [42] 2006 U.S.A. African PB 239/327 Multiplex PCR 162 77 245 82 187 56 218 109 
Fu [98] 2006 China Asian PB 315/439 PCR 86 229 117 321 141 174 187 251 
Luo [91] 2006 China Asian HB 56/143 PCR 36 20 95 48 NA NA NA NA 
Rajagopal [89] 2005 U.K. Caucasian HB 361/881 PCR NA NA NA NA 265 96 723 158 
Landi [44] 2005 Spain Caucasian HB 176/162 PCR 77 99 66 96 NA NA NA NA 
Ateş [45] 2005 Turkey Caucasian HB 181/204 Real-Time PCR 83 98 116 88 118 63 151 53 
Yeh [47] 2005 China Asian HB 727/736 Multiplex PCR 325 402 326 410 331 396 376 360 
van der Logt [51] 2004 U.S.A. Caucasian PB 371/415 PCR 186 184 212 203 299 72 346 69 
Kiss [48] 2004 Hungary Caucasian HB 500/500 PCR 209 291 258 242 369 131 392 108 
Chen [109] 2004 China Asian HB 125/339 PCR 56 69 151 188 102 23 270 69 
Smits [53] 2003 Multiple Caucasian PB 724/1743 PCR 381 343 821 922 NA NA NA NA 7.5 
van der Hel [54] 2003 U.S.A. Caucasian PB 212/765 PCR 124 88 396 369 154 58 541 224 
Slattery [107] 2003 U.S.A. Mixed PB 801/1013 PCR 397 404 467 546 NA NA NA NA 
Nascimento [55] 2003 Brazil Mixed HB 102/300 Multiplex PCR 52 50 166 134 85 17 248 52 
Huang [90] 2003 China Asian HB 82/82 Multiplex PCR 36 46 54 28 41 41 42 40 
Yang [101] 2003 China Asian HB 58/65 PCR-RFLP 18 40 36 29 NA NA NA NA 
Zhang [102] 2003 China Asian HB 81/112 Multiplex PCR NA NA NA NA 27 54 54 58 
Zhu [57] 2002 China Asian HB 104/101 Multiplex PCR 56 48 44 57 55 49 40 61 
Ye [58] 2002 U.K. Caucasian HB 41/82 Specific PCR 21 20 49 33 39 73 
Tiemersma [60] 2002 U.S.A. Mixed PB 102/537 PCR 44 58 252 285 NA NA NA NA 
Seow [56] 2002 China Asian PB 213/1194 TaqMan 105 108 653 537 133 80 710 480 
Sachse [81] 2002 U.K. Caucasian PB 490/593 PCR 206 284 291 302 306 184 378 215 
Laso [82] 2002 Spain Caucasian HB 247/296 Multiplex PCR 114 133 138 158 116 131 263 33 
Sgambato [83] 2002 Italy Caucasian HB 44/100 Duplex PCR 12 32 47 53 NA NA NA NA 
Slattery [108] 2002 U.S.A. Mixed PB 1577/1904 PCR 761 816 892 1012 NA NA NA NA 
Butler [62] 2001 Australia Caucasian PB 219/200 PCR 97 106 92 108 123 67 160 40 
Saadat [63] 2001 Iran Caucasian HB 46/131 PCR 21 25 78 53 28 18 90 41 
Loktionov [64] 2001 U.K. Caucasian HB 206/355 PCR 73 133 147 208 166 40 301 54 
Zhang [103] 2001 China Asian HB 52/52 Multiplex PCR 30 22 27 25 NA NA NA NA 
Zhou [97] 2000 China Asian HB 55/62 PCR 21 34 29 33 24 31 31 31 
Gawrońska-Szklarz [66] 1999 Poland Caucasian HB 70/145 PCR 24 46 73 72 NA NA NA NA 
Yoshioka [67] 1999 Japan Asian HB 106/100 PCR 50 56 58 42 55 51 59 41 
Abdel-Rahman [68] 1999 Egypt Caucasian HB 66/55 PCR 26 37 15 30 37 22 30 21 
Zhang [80] 1999 Sweden Caucasian HB 94/109 Multiplex PCR 50 44 54 55 44 50 87 22 
Welfare [69] 1999 U.K. Caucasian PB 196/178 PCR 94 102 88 90 157 39 148 30 
Gao [104] 1998 China Asian HB 19/70 PCR 12 45 25 NA NA NA NA 
Lee [71] 1998 Singapore Asian HB 300/183 NA 172 128 94 89 NA NA NA NA 
Gertig [70] 1998 U.S.A. Mixed PB 212/221 PCR 97 114 104 117 173 36 169 51 
Guo [72] 1996 China Asian HB 19/23 PCR 12 17 NA NA NA NA 
Katoh [73] 1996 Japan Asian HB 103/126 Multiplex PCR 47 56 71 55 53 50 70 56 
Deakin [52] 1996 U.K. Caucasian HB 252/577 PCR 117 135 261 316 189 63 415 94 
Chenevix-Trench [74] 1995 Australia Caucasian HB 132/200 NA 68 64 99 101 79 15 125 23 
Zhong [75] 1993 U.K. Caucasian PB 196/225 PCR 86 110 131 94 NA NA NA NA 
Strange [106] 1991 U.K. Mixed HB 19/502 HSE 14 249 253 NA NA NA NA 

Abbreviations: HB, hospital-based study; HSE, horizontal starch gel electrophoresis; PB, population-based study; SC, source of control.

Table 3
The data between combined effects of GSTM1 and GSTT1 polymorphisms and colorectal cancer risk
First author/YearCountryEthnicitySCSample size+ −− +− −+ ++ − or − ++ +, + −, or − +Quality scores
Case / controlCasesControlsCasesControlsCasesControlsCasesControlsCasesControlsCasesControls
Rodrigues-Fleming [112] 2018 Brazil Mixed HB 232/738 19 82 97 270 14 83 68 303 116 352 184 655 6.5 
Gorukmez [49] 2016 Turkey Caucasian HB 92/116 31 11 24 35 14 34 56 55 46 89 102 
Zeng [99] 2016 China Asian HB 108/215 25 64 35 71 35 34 13 46 60 135 73 181 
Kassab [76] 2014 Tunisia Caucasian HB 147/128 NA NA NA NA 45 26 NA NA NA NA 102 102 
Cong [33] 2014 China Asian PB 264/317 22 54 23 44 119 83 100 136 45 98 145 234 
Vogtmann [31] 2014 China Asian PB 332/633 NA NA NA NA 106 169 67 128 159 336 226 464 
Chirila [15] 2013 Romania Caucasian HB 19/19 NA NA NA NA 15 14 17 16 
Huang [96] 2012 China Asian HB 130/100 NA NA NA NA 15 12 46 42 NA NA 115 88 
Wang [23] 2011 India Indian HB 302/291 42 37 85 69 15 160 178 127 106 287 284 
Koh [19] 2011 China Asian PB 480/1167 NA NA NA NA 163 421 108 263 209 483 317 746 
Yang [24] 2010 China Asian PB 322/1247 NA NA NA NA 96 326 65 234 161 687 226 921 
Nisa [78] 2010 Japan Asian PB 685/778 NA NA NA NA 183 189 NA NA NA NA 502 589 
Hlavata [22] 2010 Czech Caucasian HB 495/495 NA NA NA NA 61 46 186 200 248 249 434 449 
Piao [77] 2009 Korea Asian PB 1829/1699 428 391 477 456 533 467 391 385 905 847 1296 1232 
Matakova [27] 2009 Slovak Caucasian PB 183/422 20 35 83 162 19 58 61 167 103 197 164 364 
Huang [105] 2007 China Asian HB 57/68 13 19 24 19 24 14 20 22 37 36 57 
Martínez [38] 2006 Spain Caucasian PB 142/329 NA NA NA NA 40 24 21 128 81 177 102 305 
Probst-Hensch [39] 2006 China Asian PB 300/1168 NA NA NA NA 45 222 NA NA NA NA 255 946 
Fan [41] 2006 China Asian PB 138/339 33 60 152 20 36 53 118 65 185 118 303 
Huang [42] 2006 U.S.A. Caucasian PB 315/547 36 79 142 206 38 83 99 179 178 285 277 464 
Huang [42] 2006 U.S.A. African PB 239/327 37 82 58 55 19 27 125 163 95 137 220 300 
Ateş [45] 2005 Turkey Caucasian HB 180/204 36 34 71 69 27 19 46 82 107 103 153 185 
Chen [109] 2004 China Asian HB 125/339 32 51 152 18 35 51 119 56 184 107 303 
Nascimento [55] 2003 Brazil Mixed HB 102/300 NA NA NA NA 24 44 138 49 138 93 276 
Huang [90] 2003 China Asian HB 82/82 15 26 20 14 26 14 21 28 35 40 56 68 
Zhu [57] 2002 China Asian HB 104/101 35 37 31 36 28 11 10 17 66 73 76 90 
Seow [56] 2002 China Asian PB 213/1190 NA NA NA NA 39 224 NA NA NA NA 174 966 
Saadat [63] 2001 Iran Caucasian HB 46/131 27 16 39 14 12 51 25 66 37 117 
Zhou [97] 2000 China Asian HB 55/62 14 14 17 16 17 17 15 31 30 38 45 
Yoshioka [67] 1999 Japan Asian HB 106/100 20 22 25 23 31 19 30 36 45 45 75 81 
Abdel-Rahman [68] 1999 Egypt Caucasian HB 56/49 10 18 17 12 17 16 11 28 21 44 32 
Gertig [70] 1998 U.S.A. Mixed PB 208/220 NA NA NA NA 24 23 83 75 101 122 184 197 
Deakin [52] 1996 U.K. Caucasian HB 218/448 38 37 89 207 26 42 65 162 127 244 192 406 
First author/YearCountryEthnicitySCSample size+ −− +− −+ ++ − or − ++ +, + −, or − +Quality scores
Case / controlCasesControlsCasesControlsCasesControlsCasesControlsCasesControlsCasesControls
Rodrigues-Fleming [112] 2018 Brazil Mixed HB 232/738 19 82 97 270 14 83 68 303 116 352 184 655 6.5 
Gorukmez [49] 2016 Turkey Caucasian HB 92/116 31 11 24 35 14 34 56 55 46 89 102 
Zeng [99] 2016 China Asian HB 108/215 25 64 35 71 35 34 13 46 60 135 73 181 
Kassab [76] 2014 Tunisia Caucasian HB 147/128 NA NA NA NA 45 26 NA NA NA NA 102 102 
Cong [33] 2014 China Asian PB 264/317 22 54 23 44 119 83 100 136 45 98 145 234 
Vogtmann [31] 2014 China Asian PB 332/633 NA NA NA NA 106 169 67 128 159 336 226 464 
Chirila [15] 2013 Romania Caucasian HB 19/19 NA NA NA NA 15 14 17 16 
Huang [96] 2012 China Asian HB 130/100 NA NA NA NA 15 12 46 42 NA NA 115 88 
Wang [23] 2011 India Indian HB 302/291 42 37 85 69 15 160 178 127 106 287 284 
Koh [19] 2011 China Asian PB 480/1167 NA NA NA NA 163 421 108 263 209 483 317 746 
Yang [24] 2010 China Asian PB 322/1247 NA NA NA NA 96 326 65 234 161 687 226 921 
Nisa [78] 2010 Japan Asian PB 685/778 NA NA NA NA 183 189 NA NA NA NA 502 589 
Hlavata [22] 2010 Czech Caucasian HB 495/495 NA NA NA NA 61 46 186 200 248 249 434 449 
Piao [77] 2009 Korea Asian PB 1829/1699 428 391 477 456 533 467 391 385 905 847 1296 1232 
Matakova [27] 2009 Slovak Caucasian PB 183/422 20 35 83 162 19 58 61 167 103 197 164 364 
Huang [105] 2007 China Asian HB 57/68 13 19 24 19 24 14 20 22 37 36 57 
Martínez [38] 2006 Spain Caucasian PB 142/329 NA NA NA NA 40 24 21 128 81 177 102 305 
Probst-Hensch [39] 2006 China Asian PB 300/1168 NA NA NA NA 45 222 NA NA NA NA 255 946 
Fan [41] 2006 China Asian PB 138/339 33 60 152 20 36 53 118 65 185 118 303 
Huang [42] 2006 U.S.A. Caucasian PB 315/547 36 79 142 206 38 83 99 179 178 285 277 464 
Huang [42] 2006 U.S.A. African PB 239/327 37 82 58 55 19 27 125 163 95 137 220 300 
Ateş [45] 2005 Turkey Caucasian HB 180/204 36 34 71 69 27 19 46 82 107 103 153 185 
Chen [109] 2004 China Asian HB 125/339 32 51 152 18 35 51 119 56 184 107 303 
Nascimento [55] 2003 Brazil Mixed HB 102/300 NA NA NA NA 24 44 138 49 138 93 276 
Huang [90] 2003 China Asian HB 82/82 15 26 20 14 26 14 21 28 35 40 56 68 
Zhu [57] 2002 China Asian HB 104/101 35 37 31 36 28 11 10 17 66 73 76 90 
Seow [56] 2002 China Asian PB 213/1190 NA NA NA NA 39 224 NA NA NA NA 174 966 
Saadat [63] 2001 Iran Caucasian HB 46/131 27 16 39 14 12 51 25 66 37 117 
Zhou [97] 2000 China Asian HB 55/62 14 14 17 16 17 17 15 31 30 38 45 
Yoshioka [67] 1999 Japan Asian HB 106/100 20 22 25 23 31 19 30 36 45 45 75 81 
Abdel-Rahman [68] 1999 Egypt Caucasian HB 56/49 10 18 17 12 17 16 11 28 21 44 32 
Gertig [70] 1998 U.S.A. Mixed PB 208/220 NA NA NA NA 24 23 83 75 101 122 184 197 
Deakin [52] 1996 U.K. Caucasian HB 218/448 38 37 89 207 26 42 65 162 127 244 192 406 

Abbreviations: HB hospital-based studies; NA not available; PB population-based studies; SC, source of controls.

Meta-analysis results

GSTM1 present/null polymorphisms

Table 4 lists the summary ORs and 95% CIs on the GSTM1 null genotype with CRC risk. The GSTM1 null genotype was associated with an increased CRC risk (OR = 1.17, 95% CI: 1.10–1.23, I2 = 55.8%) in the overall population. In subgroup analyses by ethnicity, source of controls, and quality score, a significantly increased CRC risk was observed in Caucasians (OR = 1.14, 95% CI: 1.05–1.23, I2 = 56.7%, Figure 2) and Asians (OR = 1.19, 95% CI: 1.08–1.32, I2 = 52.7%, Figure 3), hospital-based studies (OR = 1.32, 95% CI: 1.20–1.46, I2 = 51.4%), high-quality studies (OR = 1.12, 95% CI: 1.06–1.18, I2 = 50.7%) and low quality studies (OR = 1.38, 95% CI: 1.17–1.62, I2 = 58.9%). Moreover, the GSTM1 null genotype was also associated with an increased colon cancer risk (OR = 1.32, 95% CI: 1.16–1.51, I2 = 57.7%).

Forest plot of the association between GSTM1 present/null polymorphism and CRC risk in Caucasians
Figure 2
Forest plot of the association between GSTM1 present/null polymorphism and CRC risk in Caucasians
Figure 2
Forest plot of the association between GSTM1 present/null polymorphism and CRC risk in Caucasians
Forest plot of the association between GSTM1 present/null polymorphism and CRC risk in Asians
Figure 3
Forest plot of the association between GSTM1 present/null polymorphism and CRC risk in Asians
Figure 3
Forest plot of the association between GSTM1 present/null polymorphism and CRC risk in Asians
Table 4
Odds ratios and 95% confidence intervals for the association between GSTM1 present/null polymorphism and colorectal cancer
VariableNo. of studiesNo. of cases/controlsNo. of GSTM1 null cases/controlsTest of associationTest of heterogeneity
OR95% CIZPChi-squareI2 (%)
Overall 86 24,931/36,537 13,180/18,518 1.17 1.10–1.23* 5.24 <0.001 192.37 55.8 
Ethnicity 
Caucasian 44 13,363/17,720 7073/9042 1.14 1.05–1.23* 3.22 0.001 99.37 56.7 
Asian 31 7561/12,426 4126/6384 1.19 1.08–1.32* 3.39 0.001 63.44 52.7 
Source of controls 
HB 51 7892/10,179 4168/4867 1.32 1.20–1.46* 5.59 <0.001 102.97 51.4 
PB 35 17,039/26,358 9012/13,651 1.03 0.99–1.07 1.30 0.195 59.04 42.4 
Quality score 
≥6 55 21,644/32,009 11,484/16,403 1.11 1.05–1.18* 3.84 <0.001 109.44 50.7 
<6 31 3287/4528 1696/2115 1.38 1.17–1.62 3.78 <0.001 73.05 58.9 
Location 
Colon cancer 23 5020/9672 2674/4728 1.32 1.16–1.51* 4.13 <0.001 51.95 57.7 
Rectal cancer 15 3696/9355 1787/4544 0.99 0.91–1.07 0.27 0.79 21.72 35.5 
Smoking 
Smokers 16 3444/4007 1778/2027 1.03 0.94–1.13 0.56 0.572 20.26 26.0 
Non-smokers 15 2722/4177 1344/2083 1.05 0.87–1.25* 0.56 0.578 37.26 62.4 
Gender 
Males 3410/4132 1832/2226 1.02 0.93–1.11 0.32 0.748 12.07 33.7 
Females 2607/3905 1424/2198 0.99 0.85–1.17 0.08 0.932 15.14 47.2 
Site 
Distal 10 1631/4017 880/2075 1.26 0.98–1.63* 1.81 0.071 30.55 70.5 
Proximal 10 1246/4017 631/2075 1.03 0.78–1.36* 0.21 0.832 24.41 63.1 
VariableNo. of studiesNo. of cases/controlsNo. of GSTM1 null cases/controlsTest of associationTest of heterogeneity
OR95% CIZPChi-squareI2 (%)
Overall 86 24,931/36,537 13,180/18,518 1.17 1.10–1.23* 5.24 <0.001 192.37 55.8 
Ethnicity 
Caucasian 44 13,363/17,720 7073/9042 1.14 1.05–1.23* 3.22 0.001 99.37 56.7 
Asian 31 7561/12,426 4126/6384 1.19 1.08–1.32* 3.39 0.001 63.44 52.7 
Source of controls 
HB 51 7892/10,179 4168/4867 1.32 1.20–1.46* 5.59 <0.001 102.97 51.4 
PB 35 17,039/26,358 9012/13,651 1.03 0.99–1.07 1.30 0.195 59.04 42.4 
Quality score 
≥6 55 21,644/32,009 11,484/16,403 1.11 1.05–1.18* 3.84 <0.001 109.44 50.7 
<6 31 3287/4528 1696/2115 1.38 1.17–1.62 3.78 <0.001 73.05 58.9 
Location 
Colon cancer 23 5020/9672 2674/4728 1.32 1.16–1.51* 4.13 <0.001 51.95 57.7 
Rectal cancer 15 3696/9355 1787/4544 0.99 0.91–1.07 0.27 0.79 21.72 35.5 
Smoking 
Smokers 16 3444/4007 1778/2027 1.03 0.94–1.13 0.56 0.572 20.26 26.0 
Non-smokers 15 2722/4177 1344/2083 1.05 0.87–1.25* 0.56 0.578 37.26 62.4 
Gender 
Males 3410/4132 1832/2226 1.02 0.93–1.11 0.32 0.748 12.07 33.7 
Females 2607/3905 1424/2198 0.99 0.85–1.17 0.08 0.932 15.14 47.2 
Site 
Distal 10 1631/4017 880/2075 1.26 0.98–1.63* 1.81 0.071 30.55 70.5 
Proximal 10 1246/4017 631/2075 1.03 0.78–1.36* 0.21 0.832 24.41 63.1 

GSTT1 present/null polymorphisms–

Table 5 lists the summary ORs and 95% CIs on the GSTT1 null genotype with CRC risk. The included studies could not be merged together because I2 > 75% was found between the GSTT1 present/null polymorphism and CRC risk in the overall analysis and Caucasians. In subgroup analysis by ethnicity and quality score, a significantly increased CRC risk was observed in Asians (OR = 1.08, 95% CI: 1.02–1.15, I2 = 43.6%, Figure 4) and low-quality studies (OR = 1.33, 95% CI: 1.16–1.53, I2 = 17.3%). The GSTT1 null genotype was also associated with an increased rectal cancer risk (OR = 1.13, 95% CI: 1.01–1.27, I2 = 8.3%) in subgroup analysis by tumor location.

Forest plot of the association between GSTT1 present/null polymorphism and CRC risk in Asians
Figure 4
Forest plot of the association between GSTT1 present/null polymorphism and CRC risk in Asians
Figure 4
Forest plot of the association between GSTT1 present/null polymorphism and CRC risk in Asians
Table 5
Odds ratios and 95% confidence intervals for the association between GSTT1 present/null polymorphism and colorectal cancer risk
VariableNo. of studiesNo. of cases/controlsNo. of GSTT1 null cases/controlsTest of associationTest of heterogeneity
OR95% CIZPChi-squareI2 (%)
Overall 64 19,725/28,725 6512/8888 – – – – 260.28 75.8 
Ethnicity 
Caucasian 34 11,337/14,632 2896/3205 – – – – 188.52 82.5 
Asian 23 6878/11,659 3286/5069 1.08 1.02–1.15 2.49 0.013 39.03 43.6 
Source of controls 
HB 36 6801/8894 2459/2552 – – – – 154.05 77.3 
PB 28 12,924/19,831 4053/6336 1.05 0.95–1.16* 0.96 0.337 90.02 70.0 
Quality score 
≥6 48 17,832/26,262 5903/8253 – – – – 234.52 80.0 
<6 16 1893/2463 609/635 1.33 1.16-1.53 4.09 <0.001 18.14 17.3 
Location 
Colon cancer 11 2324/6062 679/1889 1.11 0.94-1.32 1.22 0.224 16.48 39.3 
Rectal cancer 10 2079/6661 695/2143 1.13 1.01-1.27 2.09 0.036 9.81 8.3 
Smoking 
Smokers 12 2037/2405 537/641 1.04 0.83–1.30 0.36 0.721 21.46 48.7 
Non-smokers 11 1730/2605 386/641 0.96 0.74–1.25 0.28 0.777 23.33 57.1 
Gender 
Males 1930/2401 615/752 1.13 0.98–1.30 1.71 0.087 3.12 0.0 
Females 1467/2436 493/930 1.10 0.95–1.28 1.24 0.217 3.51 0.0 
Site 
Distal 723/1677 194/368 1.24 0.91–1.69 1.34 0.179 10.99 45.4 
Proximal 340/1677 83/368 1.04 0.78–1.39 0.27 0.786 3.51 0.0 
VariableNo. of studiesNo. of cases/controlsNo. of GSTT1 null cases/controlsTest of associationTest of heterogeneity
OR95% CIZPChi-squareI2 (%)
Overall 64 19,725/28,725 6512/8888 – – – – 260.28 75.8 
Ethnicity 
Caucasian 34 11,337/14,632 2896/3205 – – – – 188.52 82.5 
Asian 23 6878/11,659 3286/5069 1.08 1.02–1.15 2.49 0.013 39.03 43.6 
Source of controls 
HB 36 6801/8894 2459/2552 – – – – 154.05 77.3 
PB 28 12,924/19,831 4053/6336 1.05 0.95–1.16* 0.96 0.337 90.02 70.0 
Quality score 
≥6 48 17,832/26,262 5903/8253 – – – – 234.52 80.0 
<6 16 1893/2463 609/635 1.33 1.16-1.53 4.09 <0.001 18.14 17.3 
Location 
Colon cancer 11 2324/6062 679/1889 1.11 0.94-1.32 1.22 0.224 16.48 39.3 
Rectal cancer 10 2079/6661 695/2143 1.13 1.01-1.27 2.09 0.036 9.81 8.3 
Smoking 
Smokers 12 2037/2405 537/641 1.04 0.83–1.30 0.36 0.721 21.46 48.7 
Non-smokers 11 1730/2605 386/641 0.96 0.74–1.25 0.28 0.777 23.33 57.1 
Gender 
Males 1930/2401 615/752 1.13 0.98–1.30 1.71 0.087 3.12 0.0 
Females 1467/2436 493/930 1.10 0.95–1.28 1.24 0.217 3.51 0.0 
Site 
Distal 723/1677 194/368 1.24 0.91–1.69 1.34 0.179 10.99 45.4 
Proximal 340/1677 83/368 1.04 0.78–1.39 0.27 0.786 3.51 0.0 

Combined effects of GSTM1 and GSTT1 present/null polymorphisms

Table 6 lists the summary ORs and 95% CIs on their combined effects with CRC risk. The GSTM1 null/GSTT1 null genotype was associated with an increased CRC risk in the overall analysis (− − vs. + +: OR = 1.42, 95% CI: 1.17–1.73, I2 = 68.6%; − − vs. + −: OR = 1.37, 95% CI: 1.00–1.88, I2 = 73.0%; − − vs. (+ −) + (− +): OR = 1.26, 95% CI: 1.05–1.51, I2 = 70.4%; − − vs. (+ −) + (− +) + (+ +): OR = 1.26, 95% CI: 1.09–1.46, I2 = 69.0%).

Table 6
Combined genotype analysis of the GSTM1 and GSTT1 polymorphisms on risk of colorectal cancer
VariablesNo. of studiesNo. of cases/controlsTest of associationTest of heterogeneity
OR95% CIZPChi-squaredI2 (%)
− − vs. + +         
Overall 29 3543/5647 1.42 1.17–1.73* 3.50 <0.001 89.24 68.6 
Ethnicity         
Caucasian 10 780/1371 – – – – 52.35 82.8 
Asian 14 2202/3255 1.41 1.15–1.73* 3.29 0.001 28.51 54.4 
Source of controls         
HB 18 1193/1954 1.53 1.28–1.83 4.66 <0.001 31.24 45.6 
PB 11 2350/3337 – – – – 51.81 80.7 
Quality score         
≥ 6 21 3257/5144 1.43 1.15–1.77 3.19 0.001 75.95 73.7 
< 6 286/503 1.38 0.852.24* 1.32 0.187 12.76 45.1 
− − vs. − +         
Overall 20 2469/3221 1.15 0.92–1.44* 1.21 0.226 46.25 58.9 
Ethnicity         
Caucasian 577/982 0.89 0.61–1.28* 0.64 0.522 11.35 47.1 
Asian 10 1604/1728 1.28 1.11–1.48 3.42 0.001 17.16 47.6 
Source of controls         
HB 14 878/1392 1.21 0.99–1.48 1.89 0.059 24.25 46.4 
PB 1591/1829 – – – – 20.28 75.3 
Quality score         
≥ 6 13 2154/2727 1.20 0.91–1.60* 1.28 0.199 40.26 70.2 
< 6 315/494 1.07 0.77–1.47 0.39 0.693 5.99 0.0 
− − vs. + −         
Overall 20 1878/2218 1.37 1.00–1.88* 1.98 0.048 70.50 73.0 
Ethnicity         
Caucasian 314/474 0.66 0.37–1.17* 1.42 0.154 18.89 68.2 
Asian 10 1418/1426 – – – – 36.61 75.4 
Source of controls         
HB 14 582/790 1.32 0.83–2.09* 1.18 0.239 44.80 71.0 
PB 1296/1428 – – – – 24.47 79.6 
Quality score         
≥ 6 13 1646/1944 1.60 1.15–2.22* 2.82 0.005 39.67 69.7 
< 6 232/274 – – – – 28.60 79.0 
− − vs.(− +) + (+ −)         
Overall 28 4842/7564 1.26 1.05–1.51* 2.45 0.014 91.18 70.4 
Ethnicity         
Caucasian 10 1203/1709 – – – – 41.23 78.2 
Asian 13 3070/4836 1.50 1.20–1.86* 3.60 <0.001 40.06 70.0 
Source of controls         
HB 17 1563/2293 1.23 0.92–1.63* 1.40 0.162 39.44 59.4 
PB 11 3279/5271 – – – – 50.60 80.2 
Quality score         
≥ 6 20 4391/6934 1.33 1.09–1.62* 2.85 0.004 71.8 73.6 
< 6 451/630 0.91 0.531.54 0.36 0.715 18.80 62.8 
− − vs.(− +) + (+ −) + (+ +)         
Overall 33 8270/14,381 1.26 1.09–1.46* 3.08 0.002 103.11 69.0 
Ethnicity         
Caucasian 1893/2888 – – – – 47.52 79.0 
Asian 17 5328/9617 1.30 1.10–1.53* 3.14 0.002 47.75 66.5 
Source of controls         
HB 19 2620/3998 1.38 1.19-1.60 4.17 <0.001 35.47 49.3 
PB 14 5650/10,383 – – – – 61.31 78.8 
Quality score         
≥ 6 25 7647/13,393 1.29 1.10–1.51* 3.08 0.002 88.88 73.0 
< 6 623/988 1.10 0.72–1.70* 0.45 0.656 14.27 0.047 
VariablesNo. of studiesNo. of cases/controlsTest of associationTest of heterogeneity
OR95% CIZPChi-squaredI2 (%)
− − vs. + +         
Overall 29 3543/5647 1.42 1.17–1.73* 3.50 <0.001 89.24 68.6 
Ethnicity         
Caucasian 10 780/1371 – – – – 52.35 82.8 
Asian 14 2202/3255 1.41 1.15–1.73* 3.29 0.001 28.51 54.4 
Source of controls         
HB 18 1193/1954 1.53 1.28–1.83 4.66 <0.001 31.24 45.6 
PB 11 2350/3337 – – – – 51.81 80.7 
Quality score         
≥ 6 21 3257/5144 1.43 1.15–1.77 3.19 0.001 75.95 73.7 
< 6 286/503 1.38 0.852.24* 1.32 0.187 12.76 45.1 
− − vs. − +         
Overall 20 2469/3221 1.15 0.92–1.44* 1.21 0.226 46.25 58.9 
Ethnicity         
Caucasian 577/982 0.89 0.61–1.28* 0.64 0.522 11.35 47.1 
Asian 10 1604/1728 1.28 1.11–1.48 3.42 0.001 17.16 47.6 
Source of controls         
HB 14 878/1392 1.21 0.99–1.48 1.89 0.059 24.25 46.4 
PB 1591/1829 – – – – 20.28 75.3 
Quality score         
≥ 6 13 2154/2727 1.20 0.91–1.60* 1.28 0.199 40.26 70.2 
< 6 315/494 1.07 0.77–1.47 0.39 0.693 5.99 0.0 
− − vs. + −         
Overall 20 1878/2218 1.37 1.00–1.88* 1.98 0.048 70.50 73.0 
Ethnicity         
Caucasian 314/474 0.66 0.37–1.17* 1.42 0.154 18.89 68.2 
Asian 10 1418/1426 – – – – 36.61 75.4 
Source of controls         
HB 14 582/790 1.32 0.83–2.09* 1.18 0.239 44.80 71.0 
PB 1296/1428 – – – – 24.47 79.6 
Quality score         
≥ 6 13 1646/1944 1.60 1.15–2.22* 2.82 0.005 39.67 69.7 
< 6 232/274 – – – – 28.60 79.0 
− − vs.(− +) + (+ −)         
Overall 28 4842/7564 1.26 1.05–1.51* 2.45 0.014 91.18 70.4 
Ethnicity         
Caucasian 10 1203/1709 – – – – 41.23 78.2 
Asian 13 3070/4836 1.50 1.20–1.86* 3.60 <0.001 40.06 70.0 
Source of controls         
HB 17 1563/2293 1.23 0.92–1.63* 1.40 0.162 39.44 59.4 
PB 11 3279/5271 – – – – 50.60 80.2 
Quality score         
≥ 6 20 4391/6934 1.33 1.09–1.62* 2.85 0.004 71.8 73.6 
< 6 451/630 0.91 0.531.54 0.36 0.715 18.80 62.8 
− − vs.(− +) + (+ −) + (+ +)         
Overall 33 8270/14,381 1.26 1.09–1.46* 3.08 0.002 103.11 69.0 
Ethnicity         
Caucasian 1893/2888 – – – – 47.52 79.0 
Asian 17 5328/9617 1.30 1.10–1.53* 3.14 0.002 47.75 66.5 
Source of controls         
HB 19 2620/3998 1.38 1.19-1.60 4.17 <0.001 35.47 49.3 
PB 14 5650/10,383 – – – – 61.31 78.8 
Quality score         
≥ 6 25 7647/13,393 1.29 1.10–1.51* 3.08 0.002 88.88 73.0 
< 6 623/988 1.10 0.72–1.70* 0.45 0.656 14.27 0.047 

+ −: GSTM1 present/GSTT1 null; − +: GSTM1 null/GSTT1 present; − −: GSTM1 null/GSTT1 null; + +: GSTM1 present/GSTT1 present; HB Hospital-based studies; PB Population-based studies

In subgroup analyses by ethnicity, source of controls, and quality score, the GSTM1 null/GSTT1 null genotype was associated with an increased CRC risk in Asians (− − vs. + +: OR = 1.41, 95% CI: 1.15–1.73, I2 = 54.4%, Figure 5; − − vs. − +: OR = 1.28, 95% CI: 1.11–1.48, I2 = 47.6%; − − vs. (+ −) + (− +): OR = 1.50, 95% CI: 1.20–1.86, I2 = 70.0%; − − vs. (+ −) + (− +) + (+ +): OR = 1.38, 95% CI: 1.19–1.60, I2 = 49.3%), hospital-based studies (− − vs. + +: OR = 1.53, 95% CI: 1.28–1.83, I2 = 45.6%; − − vs. (+ −) + (− +) + (+ +): OR = 1.38, 95% CI: 1.19–1.60, I2 = 49.3%) and high-quality studies (− − vs. − +: OR = 1.43, 95% CI: 1.15–1.77, I2 = 73.7%; − − vs. + −: OR = 1.60, 95% CI: 1.16–2.22, I2 = 69.7%; − − vs. (+ −) + (− +): OR = 1.33, 95% CI: 1.09–1.62, I2 = 73.6%; − − vs. (+ −) + (− +) + (+ +): OR = 1.29, 95% CI: 1.10–1.51, I2 = 73.0%).

Forest plot of the association between the combined of GTSM1 present/null and GSTT1 present/null polymorphisms and CRC risk in Asians
Figure 5
Forest plot of the association between the combined of GTSM1 present/null and GSTT1 present/null polymorphisms and CRC risk in Asians
Figure 5
Forest plot of the association between the combined of GTSM1 present/null and GSTT1 present/null polymorphisms and CRC risk in Asians

Heterogeneity and sensitivity analyses

Significant heterogeneity was detected in the meta-analysis, as shown in Tables 46. A meta-regression analysis revealed that sample size (P=0.002) was the source of heterogeneity for the GSTM1 present/null polymorphism. Concerning the GSTT1 present/null polymorphism and the combined effects of GSTM1 and GSTT1, meta-regression analysis did not reveal a source of heterogeneity under any genetic model. Additionally, I2 > 75% as shown in Tables 46.

When the study of Laso et al. [82] was excluded, the values of heterogeneity dropped and the GSTT1 null genotype was associated with an increased CRC risk in the following subgroups: Caucasians (OR = 1.24, 95% CI: 1.09–1.41, I2 = 70.8%) and hospital-based studies (OR = 1.19, 95% CI: 1.06–1.35, I2 = 54.5%). When the study of Martínez et al. [38] was excluded, the I2 value dropped and no significant association was found between the combined effects of GSTM1 and GSTT1 polymorphisms and CRC risk in Caucasians (− − vs. + +: OR = 1.22, 95% CI: 0.83–1.78, I2 = 55.6%; − − vs. (+ −) + (− +): OR = 0.81, 95% CI: 0.53–1.26, I2 = 68.1%; − − vs. (+ −) + (− +) + (+ +): OR = 0.99, 95% CI: 0.69–1.41, I2 = 57.0%) and population-based studies (− − vs. + +: OR = 1.11, 95% CI: 0.99–1.24, I2 = 28.9%; − − vs. (+ −) + (− +): OR = 1.16, 95% CI: 0.93–1.45, I2 = 73.9%; − − vs. (+ −) + (− +) + (+ +): OR = 1.08, 95% CI: 0.93–1.26, I2 = 63.5%). When the study of Gorukmez [49] was deleted, the I2 value dropped and no significant association was observed between the combined effects of GSTM1 and GSTT1 polymorphisms and CRC risk in low-quality studies (− − vs. + −: OR = 1.23, 95% CI: 0.58–2.59, I2 = 68.3%). When the study of Cong et al. [33] was excluded, the I2 value dropped and no significant association was observed between the combined effects of GSTM1 present/null and GSTT1 present/null polymorphisms and CRC risk in population-based studies (− − vs. + −: OR = 1.13, 95% CI: 0.78–1.65, I2 = 54.4%; − − vs. − +: OR = 0.88, 95% CI: 0.65–1.19, I2 = 55.3%). A single study was excluded each time to assess the stability of the results. Figures 612 suggest that the results are stable in the present meta-analysis.

Sensitive analysis of the null genotype of GSTM1 on CRC risk in overall population
Figure 6
Sensitive analysis of the null genotype of GSTM1 on CRC risk in overall population
Figure 6
Sensitive analysis of the null genotype of GSTM1 on CRC risk in overall population
Sensitive analysis of the null genotype of GSTT1 on CRC risk in overall population
Figure 7
Sensitive analysis of the null genotype of GSTT1 on CRC risk in overall population
Figure 7
Sensitive analysis of the null genotype of GSTT1 on CRC risk in overall population
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. + +)
Figure 8
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. + +)
Figure 8
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. + +)
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. + −)
Figure 9
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. + −)
Figure 9
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. + −)
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. − +)
Figure 10
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. − +)
Figure 10
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. − +)
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. (+ −) + (− +))
Figure 11
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. (+ −) + (− +))
Figure 11
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population (− − vs. (+ −) + (− +))
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population ((+ −) + (− +) + (+ +))
Figure 12
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population ((+ −) + (− +) + (+ +))
Figure 12
Sensitive analysis of the combined effects of GSTM1 and GSTT1 on CRC risk in overall population ((+ −) + (− +) + (+ +))

Publication bias

Begg's funnel plot and Egger's test were used to assess publication bias in the meta-analysis. The Begg's funnel plot shape and Egger’s test (P<0.001) revealed obvious publication bias between the GSTM1 present/null polymorphism and CRC risk in the overall analysis. Figure 13 shows the Begg’s funnel plots by the trim and fill method; 24 missing studies should be added to this. Notably, log OR and 95% CI did not alter significantly when the trim and fill method was used. No significant publication bias was observed for the GSTT1 present/null polymorphism (P=0.195). Concerning their combined effects, no publication bias was detected under any genetic model (P=0.093 for − − vs. + +; P=0.398 for − − vs. + −; P=0.764 for − − vs. − +; P=0.643 for − − vs. (+ −) + (− +); P=0.280 for − − vs. (+ −) + (− +) + (+ +)).

The Duval and Tweedie nonparametric “trim and fill” method’s funnel plot of the GSTM1 present/null polymorphism
Figure 13
The Duval and Tweedie nonparametric “trim and fill” method’s funnel plot of the GSTM1 present/null polymorphism
Figure 13
The Duval and Tweedie nonparametric “trim and fill” method’s funnel plot of the GSTM1 present/null polymorphism

Strange et al. [106] in 1991 first reported an association between the GSTM1 null genotype and colon adenocarcinoma risk. Chenevix-Trench et al. [21] first analyzed the association between the GSTT1 null genotype and CRC risk in 1996. Deakin et al. [52] first examined their combined effects with CRC risk in 1996. Since then, many case-control studies have investigated the associations but the results are still inconsistent. Hence, an updated meta-analysis was performed to explore the GSTM1 null genotype, GSTT1 null genotype, and their combined effects with CRC risk.

Overall, this meta-analysis indicates that the GSTM1 and GSTT1 null genotypes are associated with increased CRC risk in Asians and Caucasians, and the GSTM1 null/GSTT1 null genotype was associated with increased CRC risk in Asians, but not in Africans and Indians. In addition, the GSTM1 null genotype was associated with colon cancer risk but not rectal cancer, while conversely that the GSTT1 null genotype was associated with rectal caner but not colon cancer.

Actually, it may not be uncommon that the same polymorphism played different roles in cancer risk among different ethnic population, because cancer is a complicated multi-genetic disease, and different genetic backgrounds may contribute to the discrepancy [134]. In addition, the differences might arise by chance because studies in Indians and Africans with small sample size may have insufficient statistical power to generate an authoritative risk estimate [135]. Therefore, a large population-based case-control study is required to confirm the GSTM1, GSTT1 and their combined effects with CRC risk in Indians and Africans. Nine [32,33,46,59,90,93,99,101,105] and seven [38,45,48,75,81,83,85] studies indicated that the GSTM1 null genotype was associated with an increased CRC risk in Asians and Caucasians, respectively. Five [33,47,78,93,102] and eight [26,38,49,52,62,80,82,89] studies indicated that the GSTT1 null genotype had a significantly increased CRC risk in Asians and Caucasians, respectively. Moreover, five studies [33,41,57,90,99] reported a significant association between their combined effects and CRC risk in Asians. The results of present study strongly supported these findings.

Subgroup analysis by source of control found a significant association in hospital-based studies, but not in population-based studies in the present meta-analysis. However, hospital-based controls are not likely to replace the general population because they may have more bias than population-based studies [136]. Therefore, the results of hospital-based controls should be carefully explained. Heterogeneity is a common problem in meta-analyses. The present study observed several high levels of heterogeneity (I2 > 75%), and the results of meta-regression analysis indicated that sample size was the source of heterogeneity between the GSTM1 null genotype and CRC risk. Small sample size studies may be important confounding bias in molecular epidemiological studies, because random error and bias were common in the studies with small sample sizes, and the results were unreliable [137]. Furthermore, small sample studies were easier to accept if there was a positive report as they tend to yield false-positive results because they may be not rigorous and are often of low-quality. In addition, several value of I2 > 75% dropped when a single study was excluded, the results indicate that source of heterogeneity also may be from one or multiple small sample or low quality studies. Figure 13 indicates that the asymmetry of the funnel plot was caused by studies with low-quality small samples.

A total of 13 meta-analyses [115–125,126,127] were conducted between 2010 and 2019 reported on the associations between the GSTM1 present/null and/or GSTT1 present/null polymorphisms with CRC risk. Cai et al. [115] examined 17 studies that included 5907 CRC cases and 9726 controls to explore the association between the GSTM1 null genotype and CRC risk in Asians, reporting that the GSTM1 null genotype was associated with an increased CRC risk. Liao et al. [116] examined 23 studies including 5058 cases and 5999 controls to show that the GSTT1 null genotype was associated with an increased CRC risk in Caucasians and Asians. Wan et al. [117] identified 30 studies of 7635 cases and 12,911 controls in all races, and demonstrated that the GSTT1 null genotype was associated with an increased CRC risk in Caucasians. Teng et al. [118] examined 13 studies (including 2225 cases and 3990 controls) to assess the GSTM1 null genotype with CRC risk and they found that the GSTM1 null genotype was associated with an increased CRC risk in Chinese. Gao et al. [119] assessed the association of the GSTM1 null genotype with CRC risk in all races (including 10,009 cases and 15,070 controls from 36 studies) and indicated that the GSTM1 null genotype was associated with an increased risk of CRC, especially in Caucasians. Qin et al. [120] selected 46 studies including 15,373 cases and 21,238 controls to show that the GSTT1 null genotype may contribute to an increased CRC risk in Asians and Caucasians. Wang et al. [121] (19 studies including 3130 cases and 6423 controls) found that the null genotypes of GSTM1 and GSTT1 and the dual null genotype of GSTM1/GSTT1 were not associated with CRC risk in Chinese population. The examination of 44 studies of GSTM1 (11,998 CRC cases and 17,552 controls) and 34 studies of GSTT1 (8596 CRC cases and 13,589 controls) by Economopoulos and Sergentanis [122] indicated that the GSTM1 and GSTT1 null genotypes were associated with an increased CRC risk in Caucasians. Li et al. [123] analyzed 33 studies (including 8502 CRC Asian cases and 13,699 controls) and indicated that the GSTM1 null genotype conferred susceptibility to CRC, especially in Chinese population. Xu et al. [124] examined 13 publications of 4832 cases and 7045 controls, demonstrating that the GSTT1 null genotype was associated with an increased CRC risk in Asians. Zhong et al. [125] conducted an association of 12 studies involving 4517 cases and 6607 controls, and suggested that the GSTT1 null genotype contributed to an increased CRC risk in Asians. Du et al. [126] examined 12 studies of GSTM1 and 8 studies of GSTT1, and found no association on the GSTM1 or GSTT1 null genotype with CRC risk. Huang et al. [127] selected 55 studies including 17,498 cases and 26,441 controls to show that the GSTM1 null genotype was a risk factor for CRC.

The current meta-analysis has several advantages over previous meta-analyses [115–125,126,127]. First, the sample size was much larger, with 86 case–control studies including 24,931 CRC cases and 36,537 controls evaluated for the GSTM1 present/null polymorphism, 64 case–control studies including 19,725 CRC cases and 28,725 controls for the GSTT1 present/null polymorphism, and 33 case-control studies including 8306 CRC cases and 14,369 controls for their combined effects in all races. Second, this is the first meta-analysis to explore their combined effects in overall population. Third, we used a meta-regression analysis method to explore the source of heterogeneity. Finally, the current meta-analysis included the most recent relevant publications to produce more accurate results.

Similar to previous meta-analyses, our study also has several limitations. First, only published articles were selected. Hence, publication bias may be found as shown in Figure 13. Moreover, positive results are known to be published more readily than negative ones. If negative results were included, an underestimation of the effect may be observed. Second, some case–control studies were based on hospital-based controls. These controls with non-cancerous disease may influence the pooled results in this study. Therefore, the use of population-based control studies may be more appropriate than hospital-based control studies. Third, only one study on Africans and Indians were included in the present study. Further new original studies were need on these issues in Africans and Indians.

In summary, the present study indicates that the GSTM1 null genotype is associated with increased CRC risk in Asians and Caucasians, the GSTT1 null genotype is associated with increased CRC risk in Asians, and the GSTM1 null/GSTT1 null genotype was associated with increased CRC risk in Asians. Further investigations involving large population-based studies should be conducted to explore the associations on the GSTM1 null genotype, GSTT1 null genotype and their combined effects with CRC risk.

All relevant data are within the paper.

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

The authors declare that there are no sources of funding to be acknowledged.

Liang Song: Performed research, collected data, check data, and wrote manuscript. Chen Yang: Performed research, collected data, check data, and revised manuscript. Xiao-Feng He: designed research, analyzed data, and revised manuscript.

     
  • CBM

    Chinese Biomedical Medical

  •  
  • CI

    confidence interval

  •  
  • CNKI

    China National Knowledge Infrastructure

  •  
  • CRC

    colorectal cancer

  •  
  • GSTM1

    glutathione S-transferase M1

  •  
  • GSTT1

    glutathione S-transferase T1

  •  
  • MOOSE

    Meta-analyses of Observational Studies in Epidemiology

  •  
  • OR

    odds ratio

1.
Brenner
H.
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Author notes

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These authors contributed equally to this work and should be considered as co-first authors.

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