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. 2016 Sep 27;7(46):75561–75570. doi: 10.18632/oncotarget.12285

SMAD7 polymorphisms and colorectal cancer risk: a meta-analysis of case-control studies

Yongsheng Huang 1, Wenting Wu 2, Meng Nie 1, Chuang Li 1, Lin Wang 1
PMCID: PMC5342761  PMID: 28070019

Abstract

Mothers against decapentaplegic homolog 7 (SMAD7) inhibits the transforming growth factor-β (TGF-β) signaling pathway, which regulates carcinogenesis and cancer progression. A number of studies have reported that SMAD7 polymorphisms (rs4464148, rs4939827, and rs12953717) are associated with colorectal cancer (CRC) risk, but the results from these studies remain conflicting. To determine a more precise estimation of the relationship between SMAD7 and CRC, we undertook a large-scale meta-analysis of 63 studies, which included a total of 187,181 subjects (86,585 cases and 100,596 controls). The results of our meta-analysis revealed that the C allele of rs4464148 [CC vs. TT+TC, odds ratio (OR) =1.23, 95% confidence interval (CI): 1.14–1.33, P < 0.01], the T allele of rs4939827 [TT vs. CC+TC, odds ratio OR=1.15, 95%CI:1.07–1.22, P < 0.01] and the T allele of rs12953717 [TT vs. CC+TC, OR =1.22, 95%CI:1.16–1.29, P < 0.01] were all associated with the increased CRC risk. Subgroup analysis according to ethnicity showed rs4464148 and rs12953717 were associated with the risk of CRC in both Caucasians and Asians, whereas rs4939827 was a risk polymorphism for CRC specifically in Caucasians. In summary, this large-scale meta-analysis indicated that SMAD7 polymorphisms (rs4464148, rs4939827, and rs12953717) correlate with CRC.

Keywords: SMAD7, colorectal cancer, polymorphism, meta-analysis

INTRODUCTION

Cancer is caused by the dysfunction of intricate signaling pathways, leading to abnormal growth, metastasis, and many other events [1]. The transforming growth factor β (TGF-β) signaling pathway is one of major tumor-regulatory pathways, exerting critical tumor-suppressive functions in the early stages of tumorigenesis [2, 3]. When TGF-β signaling is activated, downstream SMAD2 and SMAD3 proteins are phosphorylated, forming a complex with SMAD4 and then translocating to the nucleus to turn on and off the transcription of a wide range of target genes [4, 5]. SMAD7 inhibits TGF-β signaling by preventing the formation of the SMAD2/SMAD4 complex [6]. It also interacts with activated TGF-β type I receptor and blocks the phosphorylation and activation of SMAD2 [6].

SMAD7 has also been reported to affect tumorigenesis via several other mechanisms. First, in FET-1 colon cancer cells, SMAD7 induces the expression of IκB, thereby repressing NF-κB activity [7]. Secondly, SMAD7 up-regulates MYC expression and WNT signaling via interactions with β-catenin in breast cancer [8] and hepatocellular carcinoma [9]. In addition, SMAD7 inhibits ERK1/2, JNK1/2, and p38 MAPKs under some circumstances related with tumorigenesis, such as erythroid differentiation [10] and chondrocyte differentiation [11].

In 2007, Broderick and co-workers [12] conducted a genome-wide association study and identified three polymorphic variants in intron 3 of SMAD7 (rs4464148, rs4939827, and rs12953717). Furthermore, they found these SMAD7 polymorphisms were associated with CRC adenomas and carcinomas [12]. In a number of other studies these SMAD7 polymorphisms have been associated with the risk of developing multiple cancers, including CRC [12–14], renal [15], and liver cancer [16]. However, other case-control studies have reported that these polymorphisms are not associated with cancer risk, in CRC [17–19], breast cancer [20], and lymphocytic leukemia [21]. These inconsistencies may be partially due to the relatively small sample sizes in each of these studies. Therefore, we performed a large-scale meta-analysis of all eligible published studies to derive a more precise quantitative assessment of the association between SMAD7 polymorphisms and CRC risk.

RESULTS

Study selection and characteristics

Figure 1 is a flowchart explaining the study selection process. A total of 62 articles were initially retrieved from PubMed, Web of Science, EBSCO, and Embase electronic databases (last updated in June, 2016). Based on the search criteria, we excluded 33 ineligible records after carefully reviewing the full text and data, leaving 29 articles published between 2007 and 2016 for our quantitative meta-analysis.

Figure 1. Flowchart of the literature selection process.

Figure 1

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The characteristics of SMAD7 polymorphisms (rs4464148, rs4939827, and rs12953717) in selected studies are shown in Table 1. There were 64 eligible studies from 29 articles analyzing the relationship of SMAD7 polymorphisms and CRC risk. Among these studies, one was conducted on rs12953717, with a relatively small sample size (308 subjects) [22], which seems to have affected the results dramatically. Therefore, this study was excluded from analysis. Finally, 63 studies (published from 2007-2016) including 187,181 subjects (86,585 cases and 100,596 controls) were used to estimate the risk of developing CRC with SMAD7 polymorphisms. Each subpopulation in the literature was treated as a separate study in our meta-analysis. Populations were divided into ethnic categories. The Newcastle-Ottawa Scale (NOS) was used for quality assessment [23] and all of the studies achieved moderately high quality scores above 6 (Table 1). Among the included studies, 12 were conducted on rs4464148 (18,303 cases and 16,964 controls), 37 on rs4939827 (48,751 cases and 61,529 controls), and 14 on rs12953717 (19,531 cases and 22,103 controls).

Table 1. Main characteristics of all case-control studies included in the meta-analysis.

SNP Author Year Ethnicity Cancer type Case Control HWE (Control P value) Study design Genotyping method Quality assessment
rs4464148 TT TC CC TT TC CC
Broderick et al. [12]
-A group		 2007 Caucasian Colon 389 425 116 486 394 80 0.991 GWAS Illumina 8
-B group 2007 Caucasian Colon 2017 1952 472 1886 1617 346 0.982 Replication Allele-PCR 8
-C group 2007 Caucasian Colon 922 845 193 827 696 146 0.980 Replication Allele-PCR 8
-D group 2007 Caucasian Colon 422 408 99 171 137 27 0.952 Replication Allele-PCR 8
Thompson et al. [28] 2009 Caucasian Colon 269 231 61 342 324 53 0.045 Replication TaqMan 8
Curtin et al. [43] 2009 Caucasian Colon 503 472 95 535 423 89 0.678 Replication SNPlex 8
Pittman et al. [44] 2009 Caucasian Colon 1161 1107 264 1095 1277 235 0.996 Replication Allele-PCR 8
Ho et al. [35] 2011 Asian Colon 739 146 7 770 116 4 0.869 Replication Sequenom 7
Zhang et al. [38] 2014 Asian Colon 1 52 675 14 305 2957 0.999 Replication TaqMan 8
Kurlapska et al. [17] 2014 Caucasian Colon 1214 1228 400 84 96 33 0.523 Replication Sequenom 7
Damavand et al. [29] 2015 Caucasian Colon 138 78 37 113 101 20 0.700 Replication Taqman 7
Serrano-Fernandez et al. [45] 2015 Caucasian Colon 507 517 141 561 490 114 0.643 Replication Taqman 8
rs4939827 CC TC TT CC TC TT
Broderick et al. [12]
-A group		 2007 Caucasian Colon 153 449 328 229 480 251 0.987 GWAS Illumina 8
-B group 2007 Caucasian Colon 852 2178 1392 845 1915 1084 0.989 Replication Allele-PCR 8
-C group 2007 Caucasian Colon 387 982 623 410 840 430 0.995 Replication Allele-PCR 8
-D group 2007 Caucasian Colon 194 477 292 76 171 96 0.923 Replication Allele-PCR 8
Tenesa et al. [14]
-Scotland(GWAS)		 2008 Caucasian Colon 538 1521 926 706 1508 845 0.506 GWAS Illumina 8
-Japan 2008 Asian Colon 233 1582 2576 131 1028 2019 0.992 Replication TaqMan 8
-Canada 2008 Caucasian Colon 225 593 355 284 576 322 0.402 Replication TaqMan 8
-England 2008 Caucasian Colon 418 1120 694 546 1126 578 0.959 Replication TaqMan 8
-Spain 2008 Caucasian Colon 62 156 131 57 143 95 0,808 Replication TaqMan 8
-Germany 2008 Caucasian Colon 420 1071 659 541 1057 530 0.765 Replication TaqMan- 8
-Germany 2008 Caucasian Colon 289 617 412 378 704 358 0.403 Replication TaqMan 8
-Scotland 2008 Caucasian Colon 156 420 254 189 446 288 0.497 Replication TaqMan 8
-Israel 2008 Caucasian Colon 267 638 447 312 627 397 0.035 Replication TaqMan 8
Curtin et al. [43] 2009 Caucasian Colon 221 520 324 229 538 274 0.251 Replication SNPlex 8
Thompson et al. [28] 2009 Caucasian Colon 125 275 154 146 378 185 0.064 Replication TaqMan 8
Pittman et al. [44] 2009 Caucasian Colon 785 1250 497 725 1300 582 0.987 Replication Allele-PCR 8
Slattery et al. [46] 2010 Caucasian Colon 360 773 457 492 992 503 0.947 Replication TaqMan 8
Xiong et al. [33] 2010 Asian Colon 1370 677 77 1442 570 74 0.061 Replication T-ARMS-PCR 8
von Hoslt et al. [47] 2010 Caucasian Colon 395 886 501 387 884 408 0.930 Replication deCode test 8
Kupfer et al. [48] 2010 African Colon 379 340 76 455 429 101 0.994 Replication Sequenom 7
Caucasian Colon 88 199 112 85 183 99 0.981 Replication Sequenom 7
Mates et al. [49] 2010 Caucasian Colon 28 37 27 15 57 23 0.061 Replication Centaurus 6
Mates et al. [50] 2011 Caucasian Colon 42 69 42 32 106 43 0.225 Replication Centaurus 7
Cui et al. [34] 2011 Asian Colon 1628 1007 155 2247 1190 147 0.501 Replication Illumina 8
Li et al. [22] 2011 Asian Colon 73 53 12 81 73 14 0.665 Replication Sequenom 7
Ho et al. [35] 2011 Asian Colon 343 420 129 376 405 109 0.997 Replication Sequenom 7
Song et al. [36] 2012 Asian Colon 399 232 10 732 272 33 0.214 Replication TaqMan 6
Lubbe et al. [51] 2012 Caucasian Colon 444 969 624 1394 3021 1636 0.993 Replication Allele-PCR 7
Garcia-Albeniz et al. [52] 2012 Caucasian Colon 90 233 118 538 1120 600 0.731 Replication TaqMan 8
Phipps et al. [53] 2012 Caucasian Colon 657 1526 884 574 1597 1112 0.988 Replication TaqMan 7
Kirac et al. [54] 2013 Caucasian Colon 63 143 96 172 291 131 0.705 Replication Illumina 8
Yang et al. [37] 2014 Asian Colon 342 298 65 891 752 159 0.985 Replication Allele-PCR 7
Kurlapska et al. [17] 2014 Caucasian Colon 54 93 65 716 1394 730 0.330 Replication Sequenom 7
Zhang et al. [38] 2014 Asian Colon 400 277 51 1894 1170 212 0.858 Replication TaqMan 7
Hong et al. [19] 2015 Asian Colon 126 63 9 182 127 19 0.608 Replication Illumina 7
Baert-Desurmont et al. [55] 2016 Caucasian Colon 89 157 104 191 493 343 0.555 Replication SNaPshot 8
Abd EI-Fattah et al. [18] 2016 Caucasian Colon 20 35 22 11 15 10 0.319 Replication TaqMan 7
rs12953717 CC TC TT CC TC TT
Broderick et al.-A group [12] 2007 Caucasian Colon 159 309 151 326 467 167 0.991 GWAS Illumina 8
-B group 2007 Caucasian Colon 1247 2204 973 1248 1898 722 0.994 Replication Allele-PCR 8
-C group 2007 Caucasian Colon 582 991 422 558 834 312 0.990 Replication Allele-PCR 8
-D group 2007 Caucasian Colon 277 468 198 106 168 67 0.976 Replication Allele-PCR 8
Middeldorp et al. [13] 2009 Caucasian Colon 301 493 201 482 643 215 0.982 Replication TaqMan 7
Curtin et al. [43] 2009 Caucasian Colon 314 530 226 332 521 188 0.509 Replication SNPlex 8
Thompson et al. [28] 2009 Mixed Colon 196 248 116 220 370 129 0.218 Replication TaqMan 8
Pittman et al. [56] 2009 Caucasian Colon 716 1261 555 859 1275 473 0.998 Replication Allele-PCR 8
Kupfer et al. [48] 2010 African Colon 401 327 67 525 388 72 0.979 Replication Sequenom 7
2010 Caucasian Colon 197 121 81 119 180 68 0.996 Replication Sequenom 7
Slattery et al. [46] 2010 Caucasian Colon 503 754 332 676 928 327 0.779 Replication Illumina 8
Ho et al. [35] 2011 Asian Colon 276 343 97 304 345 65 0.557 Replication Sequenom 7
Scollen et al. [56] 2011 Mixed Colon 710 1031 425 730 1083 437 0.326 Replication TaqMan 8
Zhang et al. [38] 2014 Asian Colon 418 263 47 1947 1135 194 0.096 Replication TaqMan 8
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SNP: single nucleotide polymorphisms: HWE: Hardy-Weinberg equilibrium.

Quantitative data synthesis

SMAD7 rs4464148 polymorphism

For each study, we investigated the association between the SMAD7 rs4464148 polymorphism and CRC risk, assuming different inheritance models. When all eligible studies were pooled into the meta-analysis, significant associations were found for the recessive genetic model (Table 2): CC vs. TC+TT (OR = 1.23; 95% CI: 1.14–1.33; PZ < 0.01; PH = 0.43], while only a slight association was found for the dominant genetic model: CC +TC vs. TT (OR = 1.10; 95% CI: 0.99–1.22; PZ = 0.51; PH = 0.00). Subgroup analysis according to ethnicity showed that rs4464148 was significantly associated with CRC risk in both Caucasian and Asian populations (Table 2).

Table 2. Meta-analysis of the association between SMAD7 polymorphisms and colorectal cancer risk.
SNP Comparison Subgroup Heterogeneity test Model PZ PE OR (95% CI)
I2 (%) PH
rs4464148 CC vs. TT+TC Overall 1.3 0.43 F <0.01 0.13 1.23(1.14–1.33)
Caucasian 12.3 0.33 F <0.01 1.22(1.13–1.32)
Asian 0 0.71 F 0.03 1.39(1.04–1.87)
CC+TC vs. TT Overall 73.8 0.00 R 0.07 0.51 1.10(0.99–1.22)
Caucasian 76.8 0.00 R 0.16 1.08(0.97–1.21)
Asian 0 0.41 F 0.02 1.36(1.05–1.75)
C vs. T Overall 66.2 0.00 R <0.01 0.36 1.12(1.04–1.19)
Caucasian 67.7 0.00 R 0.01 1.10(1.02–1.18)
Asian 66 0.09 F <0.01 1.35(1.12–1.63)
rs4939827 TT vs. CC+TC Overall 73.3 0.00 R <0.01 0.89 1.15(1.07–1.22)
Caucasian 61.2 0.00 R <0.01 1.19(1.12–1.26)
Asian 75.8 0.00 R 0.73 1.04(0.84–1.28)
TT+TC vs. CC Overall 71.8 0.00 R <0.01 0.14 1.13(1.07–1.20)
Caucasian 71.6 0.00 R <0.01 1.16(1.08–1.24)
Asian 74.0 0.00 R 0.31 1.07(0.94–1.23)
T vs. C Overall 79.6 0.00 R <0.01 0.45 1.11(1.06–1.16)
Caucasian 74.7 0.00 R <0.01 1.13(1.08–1.18)
Asian 56.9 0.00 R 0.33 1.07(0.94–1.21)
rs12952717 TT vs. CC+TC Overall 13.2 0.31 F <0.01 0.54 1.22(1.16–1.29)
Caucasian 0 0.87 F <0.01 1.25(1.18–1.32)
Asian 54.9 0.14 F 0.02 1.31(1.04–1.65)
TT+TC vs. CC Overall 51.3 0.02 R <0.01 0.66 1.15(1.08–1.23)
Caucasian 45.3 0.06 F <0.01 1.19(1.13–1.25)
Asian 0.0 0.54 F 0.082 1.12(0.99–1.28)
T vs. C Overall 51.5 0.02 R <0.01 0.85 1.13(1.09–1.19)
Caucasian 29.8 0.17 F <0.01 1.16(1.12–1.20)
Asian 19.6 0.27 F 0.02 1.13(1.02–1.25)
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PH : P value of heterogeneity test; PZ : P value of Z test; PE : P value of Egger's test. R: random-effects model. F: fixed-effects model

SMAD7 rs4939827 polymorphism

Similarly, we investigated the association between the SMAD7 rs4939827 polymorphism and CRC risk. Significant associations were found for both the recessive (Figure 2): TT vs. TC+CC (OR = 1.15; 95% CI: 1.07–1.22; PZ < 0.01; PH = 0.00) and the dominant genetic models: TT+ TC vs. CC (OR = 1.13; 95% CI: 1.07–1.20; PZ < 0.01; PH = 0.00; Table 2). Subgroup analysis according to ethnicity showed that rs4939837 was significantly associated with CRC risk in the Caucasian population (27 studies: 36,062 cases and 43,518 controls): TT vs. TC+CC (OR = 1.19; 95% CI: 1.12–1.26; PZ < 0.01; PH = 0.00 for heterogeneity), whereas it had no association with CRC risk among Asians (9 studies: 12,607 cases and 16,349 controls): TT vs. TC+CC (OR = 1.04; 95% CI: 0.84–1.28; PZ = 0.73; PH = 0.00; Table 2).

Figure 2. Forest plot of cancer risk associated with the SMAD7 polymorphisms in colorectal cancer studies with recessive genetic models.

Figure 2

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The squares and horizontal lines correspond to the study-specific odds ratio (OR) and 95% confidence interval (95% CI). The area of the squares reflects the weight (inverse of the variance). A. SMAD7 rs4464148; B. SMAD7 rs4939827; C. SMAD7 rs12953717.

SMAD7 rs12953717 polymorphism

In this meta-analysis, a strong association between the rs12953717 polymorphism and CRC risk was found for both the recessive: TT vs. CC+TC (OR = 1.22; 95% CI: 1.16–1.29; PZ < 0.01; PH = 0.31) and the dominant genetic models: TT+TC vs. CC (OR = 1.15; 95% CI: 1.08–1.23; PZ < 0.01; PH = 0.02; Table 2). Further subgroup analysis based on ethnicity showed that rs12953717 was significantly associated with the risk of CRC in both Caucasians and Asians (Table 2).

Sensitivity analyses and publication bias

Our results suggested that the influence of individual data sets to the pooled ORs were not significant. Sensitivity analysis showed that no single study qualitatively altered the pooled ORs, providing evidence of the stability of the meta-analysis (Supplementary Figure S1). Funnel plots and Egger's test were performed to assess publication bias. The results suggested that there was no publication bias for the comparison of rs4464148 allele C vs. allele T (t =0.96, PE = 0.36), rs4939827 allele T vs. allele C (t =−0.76, PE = 0.45), or rs12953717 allele T vs. allele C (t =−0.19, PE = 0.85). The shape of Begg's funnel plot did not reveal any obvious asymmetry (Supplementary Figure S2).

DISCUSSION

TGF-β signaling is essential for maintaining homeostasis, cell differentiation, and tumor suppression [3, 24, 25]. Increased production of TGF-β occurs in various tumor types, such as CRC [26]. As one of the key effectors of TGF-β signaling, perturbation of SMAD7 expression has been documented to influence CRC progression [7][27]. Though the functional role of the SMAD7 polymorphisms (rs4464148, rs4939827, and rs12953717) has not yet been interpreted, a number of published epidemiological studies have reported that these polymorphisms are correlated with the risk of developing multiple cancers [12, 28, 29]. However, other studies have reported that these polymorphisms are not associated with cancer development [17–20].

These conflicting studies based their conclusions on small numbers of samples and different detection methods. Therefore ameta-analysis from large-scale samples of all available studies is required to have a more accurate assessment as to whether the SMAD7 polymorphisms are related to risk of developing CRC. Our group has already used meta-analysis to systematically investigate the association between cancer risk and several SNPs involved in TGF-β signaling [30–32]. In this meta-analysis, we found SMAD7 polymorphisms (rs4464148, rs4939827, and rs12953717) in the combined population were all significantly associated with CRC risk. Subgroup analysis according to ethnicity showed that rs4464148 and rs12953717 were significantly associated with the risk of CRC among both Caucasian and Asian population, whereas rs4939827 seems to be a risk polymorphism for CRC only within a Caucasian population. There could be several possibilities to explain such a differential association. First, the difference in association may result from differences in socioeconomic environment, regional dietary habits, and race. Second, the number of rs4939827 in Asian studies is still not as large as desired. In addition, the results from nine studies incorporated in this meta-analysis conflict with each other [14, 19, 22, 33–38]. Therefore, more Asian studies are still needed to clearly evaluate the interactions of SMAD7 rs4939827 and CRC in this ethnic group.

One recent study [39] also assessed the associations between these three SNPs and CRC risk by meta-analysis; however, there were significant limitations. First, the number of studies included in their analysis was smaller than ours. Only 4 publications for rs4464148, which also lack relevant studies for Asian population, and 13 publications for rs4939827 were included in their meta-analysis, while 9 publications for rs4464148 and 25 publications for rs4939827 were included in our work. Second, they only analyzed the relationship between SMAD7 polymorphisms and CRC risk under an allelic model, while we also analyzed under dominant and recessive models. Therefore, our updated meta-analysis at a much larger scale clearly provides a more credible and reliable assessment for the association between SMAD7 polymorphisms and the risk to develop CRC.

Nonetheless, we also wish to acknowledge the limitations in our study. First, we stratified the studies by ethnic subtypes as Caucasian and Asian. However, we could not assess the association in the African population due to the insufficient number of African studies. Second, further subtle adjusted analysis could be carried out if more detailed individual information was available. Third, we only assessed the association of SMAD7 polymorphisms with CRC risk, because there were not sufficient studies conducted on other cancers.

To date, a large number of studies have focused on the relationship between SMAD7 polymorphisms and cancer. However, controversies remain as whether those polymorphisms indeed associate with increased cancer risks. Our large-scale meta-analysis demonstrated that the C allele of rs4464148, the T allele of rs4939827, and the T allele of rs12953717 were all significantly associated with the increased CRC risk, which may provide a basis for genetic testing in the development of CRC. Consistent with our findings, Noci et al. [40] recently showed that SMAD7 rs4939827 is also associated with cancer survival rate after therapy. Therefore, the identification of SMAD7 polymorphisms may also benefit developing targeted and personalized therapy against CRC. However, more comparative studies are needed to evaluate interactions of SMAD7 polymorphisms and cancer risk in other specific cancer subtypes and ethnic subtypes

MATERIALS AND METHODS

Literature Search strategy

We searched for relevant case-control studies using the following words and terms: “SMAD7”, “Mothers against decapentaplegic homolog 7”, “rs4464148”, “rs4939827”, “rs12953717”, “polymorphism” or “variation”, “susceptibility”, and “tumor” or “cancer” or “carcinoma” or “neoplasia” or “colorectal caner” or “CRC” in PubMed, the Web of Science, EBSCO, and Embase databases. There were no limitations on the language and year for the literature search. The last search was updated on June 30, 2016. References of the retrieved publications were also screened.

Inclusion criteria

Two authors independently screened titles and abstracts to identify relevant studies. Full-text articles of these studies were then carefully read to select eligible studies. Studies had to meet the following inclusion criteria: (a) were a case-control study, nested case-control or a cohort study; (b) evaluated the association between SMAD7 polymorphisms (“rs4464148”, “rs4939827”, and “rs12953717”) and CRC risk; (c) had available genotype frequencies both in cases and controls; (d) the genotype distribution in control groups was in Hardy-Weinberg equilibrium (HWE). (e) In cases of multiple studies with overlapping, redundant data published, only the most recent or complete study was included.

Qualitative assessment

Two authors independently conducted the quality assessment. The Newcastle–Ottawa Scale (NOS) was used to evaluate the study quality, which scored studies by the selection of the groups, the comparability of cases and controls, and the ascertainment of the exposure. We considered a study awarded 0-3, 4-6, or 7-9 as a low-, moderate-, or high-quality study, respectively [23].

Data extraction

Two authors independently selected the relevant articles and extracted the following data: first author's name, publication date, ethnicity, cancer type, genotyping methods, number of cases and controls, and number of genotypes in case-control groups. In addition, P values according to the HWE in controls were extracted from the included studies.

Statistical analysis

Our meta-analysis was performed using Stata software (version 12.0; StataCorp LP, College Station, TX, USA). We first calculated the strength of the association between SMAD7 polymorphisms and CRC by odds ratio (OR) corresponding to 95% confidence interval (CI) for different genetic models. Then we stratified the studies by ethnic subtypes and examined the association between SMAD7 polymorphisms and the CRC risk (Table 2). A chi-square-based Q-statistic test [41] was performed to evaluate the between-study heterogeneity of the studies. PH < 0.05 was considered significant for heterogeneity. We also calculated the quantity I2 that represents the percentage of total variation across studies. As a guide, values of I2 less than 25% were considered “low”, values about 50% were considered “moderate”, and values greater than 75% were considered “high”[42]. The fixed effects model was used when there was no heterogeneity of the results of studies; otherwise, the random-effects model was chosen. A pooled OR obtained by meta-analysis was used to give a more reasonable evaluation of the association. The significance of the pooled OR was determined by Z test (PZ ≤0.05 suggests a significant OR). Funnel plots were used to access publication bias by the method of Begg's test and Egger's test. A T test was performed to determine the significance of the asymmetry. An asymmetric plot suggested possible publication bias (PE ≥ 0.05 suggests no bias).

SUPPLEMENTARY FIGURES

Acknowledgments

This study was supported by grants from the National Natural Science Foundation of China (Grant No. 31201050 and 81372201).

Footnotes

CONFLICTS OF INTEREST

The authors declare no competing financial interests.

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