Association of CASP9, CASP10 gene polymorphisms and tea drinking with colorectal cancer risk in the Han Chinese population

Association of CASP9 , CASP10 gene polymorphisms and tea drinking with colorectal cancer risk in the Han Chinese population 1 first-author 1 1 1 1 1 2 2 1 corresp ‡Corresponding Author ‡Corresponding Author †E-mail:ck@zju.edu.cn †E-mail:ck@zju.edu.cn ck@zju.edu.cn Department of Epidemiology and Health Statistics, School of Medicine, Zhejiang University, Hangzhou 310058, China Department of Epidemiology and Health Statistics, School of Medicine, Zhejiang University, Hangzhou 310058, China Institute of Cancer Research and Prevention of Jiashan County, Jiashan 314100, China Institute of Cancer Research and Prevention of Jiashan County, Jiashan 314100, China The initiators caspase-9 ( CASP9 ) and caspase-10 ( CASP10 ) are two key controllers of apoptosis and play important roles in carcinogenesis. This study aims to explore the association between CASPs gene polymorphisms and colorectal cancer (CRC) susceptibility in a population-based study. A two-stage designed population-based case-control study was carried out, including a testing set with 300 cases and 296 controls and a validation set with 206 cases and 845 controls. A total of eight tag selected single nucleotide polymorphisms (SNPs) in CASP9 and CASP10 were chosen based on HapMap and the National Center of Biotechnology Information (NCBI) datasets and genotyped by restriction fragment length polymorphism (RFLP) assay. Multivariate logistic regression models were applied to evaluate the association of SNPs with CRC risk. In the first stage, from eight tag SNPs, three polymorphisms rs4646077 (odds ratio (OR) AA+AG : 0.654, 95% confidence interval (CI): 0.406–1.055; P =0.082), rs4233532 (OR CC : 1.667, 95% CI: 0.967–2.876; OR CT : 1.435, 95% CI: 0.998–2.063; P =0.077), and rs2881930 (OR CC : 0.263, 95% CI: 0.095–0.728, P =0.036) showed possible association with CRC risk. However, none of the three SNPs, rs4646077 (OR AA+AG : 1.233, 95% CI: 0.903–1.683), rs4233532 (OR CC : 0.892, 95% CI: 0.640–1.243; OR CT : 1.134, 95% CI: 0.897–1.433), and rs2881930 (OR CC : 1.096, 95% CI: 0.620–1.938; OR CT : 1.009, 95% CI: 0.801–1.271), remained significant with CRC risk in the validation set, even after stratification for different tumor locations (colon or rectum). In addition, never tea drinking was associated with a significantly increased risk of CRC in testing set together with validation set (OR: 1.755, 95% CI: 1.319–2.334). Our results found that polymorphisms of CASP9 and CASP10 genes may not contribute to CRC risk in Chinese population and thereby the large-scale case-control studies might be in consideration. In addition, tea drinking was a protective factor for CRC. CASP9 CASP10 Colorectal cancer Single nucleotide polymorphisms Susceptibility to cancer Tea drinking Introduction 1 In the past few decades, the incidence of colorectal cancer (CRC) has increased drastically in many Asian countries, especially in China (Sung et al., 2005 2005 ; Yee et al., 2010 2010 ). The Chinese National Office for Cancer Prevention and Control revealed that the large increase in the number of CRC cases (19.1% in men and 17.7% in women) was observed between 2000 and 2005 (Yang et al., 2005 2005 ). Environmental factors are thought to be related with risk of CRC, including lifestyle habits such as smoking, alcohol consumption, and tea consumption (Yang et al., 2007 2007 ; Huxley et al., 2009 2009 ). However, as a chronic complex disease, the genetic makeup of an individual might also contribute to CRC susceptibility (Zhang et al., 2009 2009 ). Apoptosis is the process of programmed cell death (PCD), which mainly acts to develop and maintain tissue homeostasis in multicellular organisms (Grutter, 2000 2000 ; Kumar, 2007 2007 ). Dysregulation of apoptosis has been found to increase the risk of many human disorders, including human malignancies (Hajra and Liu, 2004 2004 ). Caspases (CASPs) are a family of cysteine-dependent aspartate-specific proteases (Nicholson and Thornberry, 1997 1997 ; Budihardjo et al., 1999 1999 ) that play essential roles in apoptosis. The two distinct but converging pathways for CASP activation in human, the extrinsic or receptor-mediated pathway and the intrinsic or mitochondrial pathway, both own an independent group of initiator caspases ( CASP8 and CASP10 for the extrinsic pathway, CASP9 for the intrinsic pathway). The initiator CASPs (Degterev et al., 2003 2003 ; Wang et al., 2005 2005 ) transmit death signals and further activate a cascade of effector CASPs ( CASP3 , CASP6 , and CASP7 ), which result in final cell death by the process of proteolysis. The genetic variants of CASP genes and cancer risk have been studied, covering various CASP genes and multiple cancers; however, the results have been inconsistent (Chen et al., 2008 2008 ; Han et al., 2008 2008 ; Ter-Minassian et al., 2008 2008 ; Lan et al., 2009 2009 ; Srivastava et al., 2010 2010 ). Nevertheless, the association between CASP polymorphisms and CRC risk has been reported in several studies. Liu B. et al. ( 2010 2010 ) observed a marginally significant association of a 6-bp insertion/deletion polymorphism (−652 6N ins/del) of the CASP8 gene and an increased risk of rectum cancer (odds ratio (OR) del/del : 1.92, 95% confidence interval (CI): 0.97–3.79). Sun et al. ( 2007 2007 ) identified the same variant, but with the opposite results of decreasing risk of colorectal cancer (OR del/del : 0.50, 95% CI: 0.31–0.79; OR ins/del : 0.80, 95% CI: 0.65–0.99). Haiman et al. ( 2008 2008 ) and Pittman et al. ( 2008 2008 ) performed case-control studies seeking to replicate Sun’s finding. However, they did not find any statistically significant results. To our knowledge, no study has reported on the association of CASP9 , CASP10 polymorphisms and risk of CRC thus far. Due to complexity of finding low-penetrance risk allele in molecular epidemiological research, expansion of sample size and adjustment of all possible confounding factors are an effective way to promote the efficiency (Ulybina et al., 2009 2009 ). Nevertheless, it is difficult to collect big sample and identify all possible confounding factors. Therefore, alternative strategies and approaches of searching for polymorphic candidate SNPs are needed. In the present study, we have adopted a two-stage molecular epidemiological study, whereby DNA samples were divided into two parts according to the time when they collected. For the preliminary sorting, all the candidate SNPs were genotyped in the testing set, only those demonstrating possible association with CRC risk were further genotyped in the validation set. We hypothesized that CASP9 and CASP10 polymorphisms might affect the susceptibility of CRC. To test our hypothesis, eight tag SNPs in the two mentioned initiator CASP genes were selected and genotyped in a population-based case-control study. Materials and methods 1 Study population 2 Recruitment of this population-based case-control study subjects had been previously reported (Fan et al., 2007 2007 ; Zhang et al., 2009 2009 ). The study protocol was approved by the Institutional Review Board of Medical School of Zhejiang University, China. Briefly, this study included 506 histologically confirmed CRC patients from 2002 to 2008 and 1 141 controls without history of cancer randomly selected from the same population at the same time. In this study, a two-stage approach was utilized to compare single nucleotide polymorphism (SNP) frequencies (Thomas et al., 2004 2004 ; Wang et al., 2006 2006 ). The DNA samples were separated into two parts. Subjects recruited between 2006 and 2008, containing 300 cases and 296 controls, were considered the testing set, while subjects recruited between 2002 and 2005, containing 206 cases as well as 845 controls, were categorized as the validation set. All study subjects were the Han Chinese residents. After receiving written informed consent from each participant, a face-to-face interview was performed by well-trained investigators utilizing a structured questionnaire, consisting of demographic characteristics (age, sex, occupation, education level, etc.), lifestyle habits (smoking, alcohol drinking, tea drinking, etc.), family history of cancer, as well as the reproductive history of the female participants. Lifestyle factors were determined as follows: subjects who had smoked at least once a day for more than one year were considered smokers; those who consumed alcohol or tea once a day for at least three months were defined as alcohol drinkers or tea drinkers, respectively. In addition, a 2-ml venous blood specimen was collected from each participant using a vacuum tube containing ethylene diamine tetraacetic acid (EDTA) and subsequently stored at −60 °C freezer until use. DNA isolation, SNP selection, and genotyping 2 The genomic DNA was isolated from peripheral blood samples using modified salting-out extraction (Nasiri et al., 2005 2005 ), and the concentration as well as purity of DNA was measured by BioPhotometer (Eppendorf, Hamburg, Germany). Selection of tag SNPs in CASP9 and CASP10 was based on the following criteria: at first, based on the National Center of Biotechnology Information (NCBI) SNP database and HapMap the Han Chinese population database, minor allele frequency (MAF) of SNPs more than 5% were picked up. Then, among selected SNPs, Haploview software was used for selecting tag SNP by implementing Paul de Bakker’s Tagger tag SNP selection algorithm. Finally, a total of eight genetic polymorphisms were picked up (Table 1 1 ). The genotypes for CASP9 and CASP10 were detected by restriction fragment length polymorphism (RFLP) assay. The details of this approach has been described earlier (Liu C.Y. et al., 2010 2010 ; Wu et al., 2011 2011 ). Information regarding sequences of the polymerase chain reaction (PCR) primer, restriction enzymes, PCR condition, as well as size of target PCR products is presented in Table 1 1 . Additionally, 10% of the random samples were genotyped repeatedly for quality control and concordance rate was 100%. After enzyme digestion T m : melting temperature Gene/SNP Location SNP Primer Enzyme PCR product * * (bp) T m (°C) CASP9 2  rs4646018 2 Intron 2 A/G L: 5′-TGTCGGGTATTGTTCTATGT-3′ 2 Hae III 2 469 (114+355) 2 56.8 R: 5′-CCCTAATGATGCACCTCTAA-3′ 2  rs4646077 2 Intron 2 A/G L: 5′-TCCTTGCTGTGCTGTTTCAC-3′ 2 Xba I 2 243 (93+150) 2 57.7 R: 5′-ACTGGTCATTGGCATTCTCC-3′ 2  rs4233532 2 Intron 2 C/T L: 5′-TGAGGCACGATTCCTATTCC-3′ 2 Bsh1236 I 2 189 (110+79) 2 58.0 R: 5′-TCTGTCTTTTGCCCCTCTGT-3′ 2  rs4233533 2 Intron 2 C/T L: 5′-CCGGTCCCTCTTTCTCCTAT-3′ 2 Tru1 I 2 211 (139+72) 2 57.1 R: 5′-CTTGGAAGCCCTGCTACTGA-3′ CASP10 2  rs7576306 2 Intron 2 A/G L: 5′-AACCATCTGCCTACCCTCCT-3′ 2 Msp I 2 198 (119+79) 2 56.0 R: 5′-TGAGGGCAAGGACTCTGTCT-3′ 2  rs12613347 2 Intron 2 C/T L: 5′-TAGTTTGACAAGCGCTCCAG-3′ Fok I 2 184 (130+54) 2 58.0 R: 5′-GACCTTTCTCTCGTCCCTCA-3′ 2  rs2881930 2 Intron 2 C/T L: 5′-GCATGATTAAGCAATGTGTGG-3′ Bcl I 2 285 (127+158) 2 55.6 R: 5′-CTCGGCAACATGGTGAGAT-3′ 2  rs3900115 2 Exon cds-synon 2 A/G L: 5′-GGGTCCAAGATGTGGAGAAC-3′ Bts CI 2 218 (82+136) 2 56.0 R: 5′-GTCGCTCCACTTCCTCTTTG-3′ Statistical analysis 2 The distribution of socio-demographic variables between the case and control was analyzed by the Pearson χ 2 test for categorical variables and Student’s t -test for continuous variables. The Hardy-Weinberg equilibrium in control subjects was assessed by a goodness-of-fit χ 2 test with one degree of freedom for all SNPs. The associations of eight tag SNPs with CRC risk were assessed by multivariate unconditional logistic regression models, adjusted by potential confounding covariates, including sex (binary), age (continuous), body mass index (BMI) (binary), smoking (binary), alcohol drinking (binary), tea drinking (binary), and family history of cancer (binary). The ORs and 95% CIs were calculated to assess the significance of potential at-risk genotypes. Furthermore, the potential gene-environment interactions were evaluated by stratified analysis. The likelihood ratio test comparing a model with and without the interaction terms was conducted to assess multiplicative interaction (Kleinbaum, 2002 2002 ). P ≤0.1 was determined for statistical significance of the preliminary sorting, and the other statistical significance was assumed at P ≤0.05. Every test was a two-side test. All of the statistical analyses were performed with statistical analysis system (SAS) software Version 9.1.3 (SAS Institute, Cary, NC). Results 1 Characteristics of the study population 2 The distribution of demographics of the cases and controls in the testing set (with 300 cases and 296 controls) and validation set (with 206 cases and 845 controls) are presented in Table 2 2 . Our data showed that the distribution of age, sex, BMI, marital status, education level, family history of cancer, smoking status, alcohol drinking as well as tea drinking in both sets between the cases and controls was similar, with no significant difference. However, in the validation set, the control group owned a higher percentage of farmers (cases vs. controls: 69.90% vs. 78.93%, P =0.006). Data are expressed as mean±standard deviation (SD) for age and number (percentage) for others Data were missed for three cases Data were missed for one case BMI: body mass index 2 Characteristics 3 Years 2006–2008 (testing set) 3 Years 2002–2005 (validation set) Case ( n =300) Control ( n =296) P Case ( n =206) Control ( n =845) P Age (year) 62.11±12.23 61.7158±11.10 0.098 60.51±10.08 60.31±10.88 0.805 Sex  Male 159 (53.00%) 156 (52.70%) 0.942 104 (50.49%) 393 (46.51%) 0.305  Female 141 (47.00%) 140 (47.30%) 102 (49.51%) 452 (53.49%) BMI  <24 239 (76.67%) 219 (73.99%) 0.100 160 (77.67%) 630 (74.56%) 0.354  >24 61 (20.33%) 77 (26.01%) 46 (22.33%) 215 (25.44%) Occupation b b  Farmers 269 (90.57%) 268 (90.54%) 0.989 144 (69.90%) 667 (78.93%) 0.006  Non-farmers 28 (9.43%) 28 (9.46%) 62 (30.10%) 178 (21.07%) Education c c  Illiterate 152 (50.84%) 136 (45.95%) 0.371 99 (48.29%) 449 (53.14%) 0.378  Primary school 107 (35.79%) 110 (37.16%) 64 (31.22%) 261 (30.89%)  Junior school 34 (11.37%) 38 (12.84%) 28 (13.66%) 96 (11.36%)  High school and above 6 (2.01%) 12 (4.05%) 14 (6.83%) 39 (4.61%) Marriage  Unmarried 10 (3.33%) 7 (2.36%) 0.478 22 (10.68%) 80 (9.47%) 0.598  Married 290 (96.67%) 289 (97.64%) 184 (89.32%) 765 (90.53%) Smoking  No 195 (65.00%) 184 (62.16%) 0.472 123 (59.71%) 527 (62.37%) 0.481  Yes 105 (35.00%) 112 (37.84%) 83 (40.29%) 318 (37.63%) Alcohol drinking  No 218 (72.67%) 219 (73.99%) 0.716 146 (70.87%) 601 (71.12%) 0.943  Yes 82 (27.33%) 77 (26.01%) 60 (29.13%) 244 (28.88%) Tea drinking  No 181 (60.33%) 162 (54.73%) 0.166 104 (50.49%) 416 (49.23%) 0.747  Yes 119 (39.67%) 134 (45.27%) 102 (49.51%) 429 (50.77%) Family history of cancer  No 229 (76.33%) 244 (82.43%) 0.066 146 (70.86%) 645 (76.33%) 0.104  Yes 71 (23.67%) 52 (17.57%) 60 (29.13%) 200 (23.67%) Association of lifestyle-related factors with CRC risk 2 When analyzed the adjusted association of lifestyle habits (smoking, alcohol drinking, and tea drinking) with CRC risk, we found that compared with the tea drinking group, the never tea drinking group showed a significantly increased risk of CRC in the testing set (OR: 1.603; 95% CI: 1.026–2.505) and overall subjects (testing set and validation set, OR: 1.755, 95% CI: 1.319–2.334). In validation set, only a marginally significant association was found (OR: 1.295; 95% CI: 0.858–1.955). No significant associations were revealed between smoking or alcohol drinking and CRC risk in any set. Association of CASP gene with CRC risk 2 At the preliminary stage of the study, we used the tagging SNP approach for SNP sorting and selected nine tag SNPs in CASP9 and CASP10 genes for our study. However, we failed in analyzing one polymorphism (rs4661636) in spite of optimization primers and PCR conditions repeatedly, and the results were barely satisfactory. Subsequently, in the testing set, successful genotyping assays were developed for eight tag SNPs. The associations between the CASP9 and CASP10 gene polymorphisms with CRC risk are summarized in Table 3 3 . All tag SNPs in the control group met to Hardy-Weinberg equilibrium. Of the eight tested SNPs, three of them demonstrated P ≤0.1 and showed a significant or marginally significant association with CRC risk. Based on the results of the preliminary screening, rs4646077 (OR AA+AG : 0.654, 95% CI: 0.406–1.055; P =0.082), rs4233532 (OR CC : 1.667, 95% CI: 0.967–2.876; OR CT : 1.435, 95% CI: 0.998–2.063; P =0.077), and rs2881930 (OR CC : 0.263, 95% CI: 0.095–0.728; P =0.036) were considered to significantly increase risk of CRC and were therefore subjected to the validation set as candidate SNPs for extend analysis. Data are expressed as number (percentage) ORs were adjusted by sex, age, alcohol drinking, tea drinking, smoking, BMI, and family cancer history Genotyping failed in 1 control Genotyping failed in 3 cases and 3 controls Genotyping failed in 4 cases and 1 control Genotyping failed in 3 cases Genotyping failed in 12 cases and 4 controls Genotyping failed in 18 cases and 11 controls Genotyping failed in 2 cases and 2 controls HWE: Hardy-Weinberg equilibrium 2 Genotype 2 n * * 2 Adjusted OR (95% CI) a a 2 HWE P -value 2 P Case ( n =300) 2 Control ( n =296) CASP9  rs4646018 b b   GG 98 (32.67%) 92 (31.19%) 1.00 0.252 0.731   AG 145 (48.33%) 154 (52.20%) 0.881 (0.606–1.281)   AA 57 (19.00%) 49 (16.61%) 1.019 (0.626–1.658)  rs4646077 c c   GG 262 (88.22%) 243 (82.94%) 1.00 0.824 0.082   AA+AG 35 (11.78%) 50 (17.06%) 0.654 (0.406–1.055)  rs4233532 d d   TT 90 (30.20%) 115 (38.98%) 1.00 0.123 0.077   TC 163 (55.37%) 148 (50.17%) 1.435 (0.998–2.063)   CC 43 (14.43%) 32 (10.85%) 1.667 (0.967–2.876)  rs4233533 e e   TT 77 (25.93%) 80 (27.03%) 1.00 0.584 0.888   CT 150 (50.51%) 154 (52.03%) 0.995 (0.671–1.474)   CC 70 (23.57%) 62 (20.95%) 1.100 (0.685–1.766) CASP10  rs7576306 f f   AA 185 (64.24%) 171 (58.56%) 1.00 0.784 0.314   AG 95 (32.99%) 106 (36.30%) 0.879 (0.616–1.253)   GG 8 (2.78%) 15 (5.14%) 0.521 (0.213–1.274)  rs12613347 g g   CC 112 (39.72%) 105 (36.84%) 1.00 0.442 0.613   CT 139 (49.29%) 141 (49.47%) 0.908 (0.633–1.318)   TT 31 (10.99%) 39 (13.68%) 0.762 (0.440–1.318)  rs2881930 h h   TT 186 (62.42%) 174 (59.18%) 1.00 0.550 0.036   CT 107 (35.91%) 102 (34.69%) 1.040 (0.733–1.467)   CC 5 (1.68%) 18 (6.12%) 0.263 (0.095–0.728)  rs3900115   AA 172 (57.33%) 168 (56.76%) 1.00 0.816 0.208   AG 118 (39.33%) 109 (36.82%) 1.103 (0.783–1.554)   GG 10 (3.33%) 19 (6.42%) 0.527 (0.236–1.177) The validation set consisted of 206 cases and 845 controls. We did not consider this validation set alone but jointly analyzed the data from both the two sets as recommended by Skol et al. ( 2006 2006 ), which might increase power to detect genetic associations. However, for all the three SNPs, no significant statistical evidence of association with CRC risk was found, even after subgroup analysis for different tumor locations (Table 4 4 ). Data are expressed as number (percentage) ORs were adjusted for age, sex, alcohol drinking, tea drinking, smoking, BMI, and family cancer history Data were missed for 26 cases and 79 controls due to DNA exhaustion Genotyping failed in 2 cases and 4 controls Genotyping failed in 5 cases and 2 controls 2 Genotype 2 Control ( n =1 141) 3 All the cases ( n =506) 3 Colon cancer ( n =240) 3 Rectal cancer ( n =266) n * * HWE P n * * Adjusted OR (95% CI) a a P n * * Adjusted OR (95% CI) a a P n * * Adjusted OR (95% CI) a a P CASP9  rs4646077 b b 2   GG 925 0.304 407 1.00 0.188 196 1.00 0.487 210 1.00 0.199 (87.10%) (84.79%) (85.59%) (84.06%) 2   AG+AA 137 73 1.233 33 1.158 40 1.291 (12.90%) (15.21%) (0.903–1.683) (14.41%) (0.766–1.751) (15.94%) (0.874–1.907)  rs4233532 c c 2   TT 414 0.755 174 1.00 0.275 83 1.00 0.518 91 1.00 0.463 (36.41%) (34.52%) (34.73%) (34.34%) 2   CC 183 70 0.892 33 0.899 37 0.905 (16.09%) (13.89%) (0.640–1.243) (13.81%) (0.578–1.399) (13.96%) (0.589–1.390) 2   CT 540 260 1.134 123 1.127 137 1.141 (47.49%) (51.59%) (0.897–1.433) (51.46%) (0.828–1.535) (51.70%) (0.845–1.541) CASP10  rs2881930 d d 2   TT 737 0.484 323 1.00 0.951 159 1.00 0.811 164 1.00 0.589 (64.71%) (64.47%) (67.09%) (62.12%) 2   CC 39 19 1.096 7 0.825 12 1.377 (3.42%) (3.79%) (0.620–1.938) (2.95%) (0.361–1.889) (4.55%) (0.699–2.712) 2   CT 363 159 1.009 71 0.923 88 1.092 (31.87%) (31.74%) (0.801–1.271) (29.96%) (0.678–1.256) (33.33%) (0.814–1.465) Furthermore, the wild-type G allele of rs4646077, the variant C allele of rs4233532, and the wild-type T allele of rs2881930 were considered as risk alleles. Both cases and controls were classified based on the individual number of risk alleles, and divided into three groups (number of risk alleles ≤1, =2, and ≥3). No significant results were observed even after a stratified analysis for tumor location (Table 5 5 ). Data are expressed as number (percentage) Variant A allele of rs4646077, the variant C allele of rs4233532, and the variant C allele of rs2881930 were categorized as risk allele ORs were adjusted for age, sex, alcohol drinking, tea drinking, smoking, BMI, and family cancer history Number of risk alleles a a Controls ( n =1 141) 3 All the cases ( n =506) 3 Colon cancer ( n =240) 3 Rectal cancer ( n =266) n * * n * * Adjusted OR (95% CI) b b P n * * Adjusted OR (95% CI) b b P n * * Adjusted OR(95% CI) b b P 2 <1 610 267 1.00 142 1.00 125 1.00 (57.65%) (56.45%) (63.11%) (50.40%) 2 2 311 143 1.088 0.507 53 0.760 0.121 90 1.479 0.139 (29.40%) (30.23%) (0.848–1.396) (23.56%) (0.537–1.075) (36.29%) (0.983–2.019) 2 >3 137 63 1.045 0.799 30 0.965 0.874 33 1.175 0.497 (12.95%) (13.32%) (0.747–1.462) (13.33%) (0.623–1.496) (13.31%) (0.764–1.806) Gene-environment interaction 2 Conducting likelihood ratio test was used to explore the multiplicative interaction between CASP9 and CASP10 polymorphisms and tea drinking (Table 6 6 ). For rs4646077, the significantly increased risk associated with GG or AA+AG genotype was apparent in the group of never tea drinking, with ORs of 1.832 (95% CI: 1.347–2.492) and 1.862 (95% CI: 1.168–2.969), respectively, compared with tea drinkers with the GG genotype. For rs4233532, never tea drinkers having CC+CT genotype significantly increased CRC risk, with an OR of 1.788 (95% CI: 1.245–2.568) compared with tea drinkers carrying the TT genotype. Additionally, for rs2881930, in the never tea drinking group, individuals carrying TT or CC+CT genotype were found to show an increased risk, the adjusted odds ratio being 1.695 (95% CI: 1.217–2.361) and 1.784 (95% CI: 1.246–2.555), respectively. Nevertheless, no significant multiplicative interaction was observed ( P for interaction is 0.1559, 0.1255, and 0.7129, for rs4646077, rs4233532, and rs2881930, respectively). The interactions between CASP genotype and smoking or alcohol drinking on CRC risk were not statistically significant. Data are expressed as number (percentage) ORs were adjusted for age, sex, alcohol drinking, smoking, BMI, and family cancer history Data were missed for 26 cases and 79 controls due to DNA exhaustion Genotyping failed in 2 cases and 4 controls Genotyping failed in 5 cases and 2 controls 2 Tea drinking 2 Genotype Control ( n =1 141) 3 All cases ( n =506) 3 Colon cancer ( n =240) 3 Rectal cancer ( n =266) n * * n * * Adjusted OR (95% CI) a a P n * * Adjusted OR (95% CI) a a P n * * Adjusted OR (95% CI) a a P rs4646077 b b 4 Yes 2 GG 467 181 1.00 93 1.00 88 1.00 (43.90%) (37.71%) (40.61%) (35.06%) 2 AA+AG 56 33 1.599 0.048 15 1.360 0.328 18 1.853 0.039 (5.27%) (6.88%) (1.002–2.553) (6.55%) (0.735–2.515) (7.17%) (1.032–3.328) 4 No 2 GG 458 226 1.832 <0.001 103 1.408 0.100 123 2.302 <0.0001 (43.10%) (47.08%) (1.347–2.492) (44.98%) (0.937–2.115) (49.00%) (1.559–3.400) 2 AA+AG 81 40 1.862 0.009 18 1.439 0.250 22 2.319 0.005 (7.63%) (8.33%) (1.168–2.969) (7.86%) (0.774–2.676) (8.77%) (1.297–4.146) rs4233532 c c 4 Yes 2 TT 207 87 1.00 45 1.00 42 1.00 (18.21%) (17.26%) (18.82%) (15.85%) 2 CC+CT 355 132 0.892 0.489 64 0.846 0.435 68 0.940 0.778 (31.22%) (26.19%) (0.645–1.233) (26.78%) (0.556–1.288) (25.66%) (0.612–1.443) 4 No 2 TT 207 87 1.414 0.092 38 1.803 0.772 49 1.784 0.027 (18.21%) (17.26%) (0.945–2.116) (15.90%) (0.633–1.852) (18.49%) (1.069–2.978) 2 CC+CT 368 198 1.788 0.002 92 1.447 0.125 106 2.161 0.001 (32.36%) (39.29%) (1.245–2.568) (38.50%) (0.903–2.319) (40.00%) (1.357–3.441) rs2881930 d d 4 Yes 2 TT 368 147 1.00 78 1.00 69 1.00 (32.31%) (29.34%) (32.91%) (26.14%) 2 CC+CT 194 73 0.968 0.847 31 0.770 0.257 42 1.194 0.417 (17.03%) (14.58%) (0.693–1.350) (13.08%) (0.489–1.210) (15.90%) (0.779–1.830) 4 No 2 TT 369 176 1.695 0.002 81 1.295 0.244 95 2.164 0.000 (32.40%) (35.13%) (1.217–2.361) (34.18%) (0.838–2.003) (35.99%) (1.416–3.307) 2 CC+CT 208 105 1.784 0.002 47 1.354 0.213 58 2.284 0.000 (18.26%) (20.96%) (1.246–2.555) (19.83%) (0.841–2.182) (21.97%) (1.450–3.600) Discussion 1 In the present study, we investigated the association of CASP9 and CASP10 polymorphisms with CRC susceptibility in a two stage designed population-based case-control study in the Han Chinese population. However, no significant effects of eight tag SNPs involved in apoptosis genes on CRC predisposition were detected in our study. However, we found that tea drinking might be involved in reducing CRC risk. Many studies (Kuzuhara et al., 2007 2007 ; Hakim et al., 2008 2008 ; Kawai et al., 2008 2008 ) have demonstrated that tea drinking was a protective factor for CRC risk, consistent with our results. Our data suggested that no statistical significance for interaction between CASP9 , CASP10 and tea drinking was detected, which was also consistent with previous studies. Zhang et al. ( 2005 2005 ) found that never tea consumption increased risk of the non-cardiac gastric cancer with thymidylate synthase 3′-untranslated region (TS3′-UTR) 6-bp/6-bp genotype (OR: 3.19, 95% CI: 1.54–6.60). Wu et al. ( 2011 2011 ) reported that never tea drinkers carrying xeroderma pigmentosum complementation group C (XPC) polymorphisms had a higher risk of CRC than tea drinkers. No significant interaction of TS3′-UTR or XPC polymorphism with tea drinking was found. Consequently, it was the positive effect of tea drinking itself mainly contributing to the association between CASP9 , CASP10 genotypes and CRC risk among never tea drinkers compared with tea drinkers. Many epidemiological studies have focused on the association between CASP polymorphisms and risk of varied cancers, yet with inconsistent results. To our knowledge, only five articles related to CASP polymorphisms and CRC risk have been reported, with all the attention focused on CASP8 . Sun et al. ( 2007 2007 ) identified that a 6-bp deletion (−652 6N del) variant in the CASP8 gene was associated with a decreased risk of multiple cancers, including CRC in a Chinese population. Haiman et al. ( 2008 2008 ) and Pittman et al. ( 2008 2008 ) conducted case-control studies in a Caucasian population with a relatively large sample size; however, no statistical significant results were observed in CRC (OR del/del : 1.08, 95% CI: 0.90–1.30; OR ins/del : 0.99, 95% CI: 0.86–1.14; and OR del/del : 0.99, 95% CI: 0.87–1.12; OR ins/del : 0.91, 95% CI: 0.81–1.01). In addition, our research group tested the same polymorphism in CASP8 , and also did not find any significant association in a Chinese population (Liu C.Y. et al., 2010 2010 ). It is plausible that CASP9 and CASP10 , as the initiator CASPs , might confer cancer susceptibility based on the results of previous studies. Lan et al. ( 2006 2006 ; 2009 2009 ) and Hosgood et al. ( 2008 2008 ; 2009 2009 ) carried out a series of case-control studies looking at the association between CASP polymorphisms and the risk of blood system neoplasms, and reported that rs1052576 of CASP9 significantly decreased risk in both multiple myeloma (OR AG : 0.8, 95% CI: 0.5–1.3; OR AA : 0.5, 95% CI: 0.3–0.9) (Hosgood et al., 2008 2008 ) and non-Hodgkin lymphoma (OR AG+AA : 0.6, 95% CI: 0.4–1.0) (Lan et al., 2006 2006 ), while CASP10 rs11674246 showed a marginally protective effect in chronic lymphocytic leukemia (OR TT : 0.74, 95% CI: 0.54–1.00) (Enjuanes et al., 2008 2008 ). Liu C.Y. et al. ( 2010 2010 ) suggested that the genotype rs4661636 in CASP9 increased risk of esophageal adenocarcinoma (OR TT+CT : 3.52, 95% CI: 2.12–5.87). Li et al. ( 2008 2008 ) and Frank et al. ( 2006 2006 ) evaluated CASP10 rs13006529 polymorphism on the risk of cutaneous melanoma and familial breast cancer, with neither of the results reaching statistical significance. In the breast cancer, rs13010627 of CASP10 was found to be associated with a decreased risk (OR AA+AG : 0.62, 95% CI: 0.43–0.88) (Frank et al., 2006 2006 ); however, this conclusion failed to remain significant in a subsequent large-scale pooled analysis (OR AA : 0.94, 95% CI: 0.72–1.22; OR AG : 1.03, 95% CI: 0.98–1.09) (Gaudet et al., 2009 2009 ). Oh et al. ( 2010 2010 ) showed that CASP10 polymorphism increased the risk of CRC. Two CASP10 mutations were observed in 43 colon cancers (2/43, 4.3%) harboring additional CASP3 , CASP7 , and CASP8 mutations. In spite of low incidence, the data indicated that a CASP10 mutation might arouse the pathological changes of some colon carcinomas with other CASP gene mutations. Moreover, rs1052576, rs11674246, and rs13006529 detected above were in linkage disequilibrium with rs4646018 ( r 2 =0.857 for rs1052576) and rs7576306 ( r 2 =1.0 for rs11674246, r 2 =0.932 for rs13006529), which were genotyped in our study; however, we failed to find an association between any polymorphisms of the two SNPs in CASP9 and CASP10 with CRC risk. There were some limitations in our population-based case-control study. First, this study had insufficient power to detect very weak associations of CASP polymorphisms on CRC risk. Assuming the risk allele frequency ranged from 0.2 to 0.4, the power to detect an OR of 1.2 at a two-sided α =0.05 was less than 40% (from 28.8% to 39.2%). Second, because of the exhaustion of DNA samples, 26 cases (5.1%) and 79 (6.9%) controls were missed for rs4646077 in the joint analyses of both the testing set and validation set. However, these missing data displayed balanced distribution of demographic factors except tea drinking (tea drinkers 26.92% in cases vs. 50.63% in controls, P =0.03) (Table 7 7 ), thus the negative influence on our result due to missing data may be reduced. Moreover, our research was not able to cover all the tag SNPs of CASP9 and CASP10 because one polymorphism (rs4661636) failed to be genotyped using current experimental technologies. Data are expressed as mean±standard deviation (SD) for age, and number (percentage) for others 2 Characteristics 3 Missing data of rs4646077 Case ( n =26) Control ( n =79) P Age (year) 56.69±10.48 58.61±10.37 0.421 4 Sex  Male 7 (26.92%) 34 (43.04%) 0.144  Female 19 (73.08%) 45 (56.96%) 4 BMI  <24 21 (80.77%) 63 (79.75%) 0.910  >24 5 (19.23%) 16 (20.25%) 4 Occupation  Farmers 7 (26.92%) 66 (83.54%) 0.238  Non-farmers 19 (73.08%) 19 (73.08%) 4 Education  Illiterate 14 (53.85%) 38 (48.10%) 0.955  Primary school 8 (30.77%) 29 (36.71%)  Junior school 3 (11.54%) 9 (11.39%)  High school and above 1 (3.85%) 3 (3.80%) 4 Marriage  Unmarried 1 (3.85%) 6 (7.59%) 0.678  Married 25 (96.15%) 73 (92.41%) 4 Smoking  No 21 (80.77%) 49 (62.03%) 0.100  Yes 5 (19.23%) 30 (37.97%) 4 Alcohol drinking  No 23 (88.46%) 56 (70.89%) 0.070  Yes 3 (11.54%) 23 (29.11%) 4 Tea drinking  No 19 (73.08%) 39 (49.37%) 0.030  Yes 7 (26.92%) 40 (50.63%) 4 Family history of cancer  No 18 (69.23%) 6 (87.34%) 0.068  Yes 8 (30.77%) 10 (12.66%) Conclusions 1 In conclusion, this study utilized a two-stage design for systematic analysis of association of tag SNPs in apoptotic genes CASP9 and CASP10 with CRC risk. 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