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Association between an 8q24 locus and the risk of colorectal cancer in Japanese

  • Keitaro Matsuo1, 6Email author,
  • Takeshi Suzuki7,
  • Hidemi Ito1,
  • Satoyo Hosono1,
  • Takakazu Kawase1,
  • Miki Watanabe1,
  • Kohei Shitara3,
  • Koji Komori4,
  • Yukihide Kanemitsu4,
  • Takashi Hirai4,
  • Yasushi Yatabe5,
  • Hideo Tanaka1, 6 and
  • Kazuo Tajima2
BMC Cancer20099:379

https://doi.org/10.1186/1471-2407-9-379

Received: 8 January 2009

Accepted: 26 October 2009

Published: 26 October 2009

Abstract

Background

A genome-wide association study (GWAS), which assessed multiple ethnicities, reported an association between single nucleotide polymorphisms in the 8q24 region and colorectal cancer risk. Although the association with the identified loci was strong, information on its impact in combination with lifestyle factors is limited.

Methods

We conducted a case-control study in 481 patients with colorectal cancer (CRC) and 962 sex-age matched non-cancer controls. Data on lifestyle factors, including diet, were obtained by self-administered questionnaire. Two 8q24 loci, rs6983267 and rs10090154, were assessed by the TaqMan method. Associations were then assessed by multivariate logistic regression models that considered potential confounders.

Results

We found an increased risk of CRC with rs6983267 but not with rs10090154. An allelic OR was 1.22 (1.04-1.44, p for trend = 0.014), which remained significant after adjustment for confounders (OR = 1.25). No statistically significant interaction with potential confounding factors was observed.

Conclusion

The polymorphism rs6983267 showed a significant association with CRC in a Japanese population. Further investigation of the biological mechanism of this association is warranted.

Keywords

8q24 LocusConditional Logistic Regression ModelAichi Cancer Center HospitalJapanese SakeMultivariable Conditional Logistic Regression

Background

Colorectal cancer (CRC) remains major cancer worldwide [1]. Although numerous epidemiological and biological studies have revealed risk/protective factors for CRC, present knowledge is still insufficient to allow the disease to be overcome, and the struggle to elucidate mechanisms is ongoing.

Recently, several a number of genome-wide association studies (GWAS) have revealed an association between variants on chromosome 8q24 and several sites of cancer, including CRC [211]. Each study showed that rs6983267 resides in 128.47-128.54 MB on Chromosome 8, denoted as 'region 3,' [7] and consistently associated with CRC [6, 9, 12]. This association was confirmed in a subsequent large-scale replication study in Caucasians [1318]. Most of these CRC GWASs were conducted in Caucasian populations, however, and the data available for Asian populations is limited especially about possible gene-environment interaction [6, 19].

The aim of the present case-control study was to clarify the impact of rs6983267 on CRC risk in a Japanese population. In addition, we explored the gene-environmental interaction between potential confounders and rs6983267.

Methods

Subjects

Cases were 481 patients who were histologically diagnosed with CRC (245 with colon cancer, 231 with rectum cancer) between January 2001 and November 2005 at Aichi Cancer Center Hospital (ACCH) and who had no prior history of cancer. Controls were first-visit outpatients at ACCH during the same periods who were confirmed to have no cancer or a prior history of neoplasm. Controls were randomly selected and matched for sex and age (± 4 years) with a 1:2 case-control ratio (n = 962). The subjects were selected from the database of the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (HERPACC). The framework of HERPACC has been described elsewhere [20, 21]. Briefly, all outpatients aged 20-79 years were asked at first visit to fill out a questionnaire regarding their lifestyle and provided 7 ml of blood. A trained interviewer checked the completion of each questionnaire. Approximately 95% of eligible subjects completed the questionnaire and 55% provided blood samples. Some 30% of first-visit outpatients were diagnosed at ACCH as having cancer. Under the assumption that the non-cancer population within HERPACC will visit ACCH if they develop cancer in the future, we defined non-cancer first-visit outpatients as those from among whom such cases may arise. Our previous study confirmed that the lifestyle patterns of first-visit outpatients matched the profile of a group randomly selected from the general population of Nagoya City, conferring external validity on the study [22]. Written informed consent was obtained from all subjects and the ethics committee of ACC approved the study.

Determination of the 8q24 loci genotype

DNA of each subject was extracted from the buffy coat fraction with a Blood Mini Kit (Qiagen K.K., Tokyo, Japan) and assessed using the polymerase chain reaction (PCR) TaqMan method [23] with the 7500 Fast Real-time PCR system (Applied Biosystems, Foster City, CA, USA). The probes used were specifically designed for rs6983267 and rs10090154 in 8q24. rs10090154 in the 8q24 'region 1' [7] was chosen because it showed a significant association for a Japanese population in Hawaii [6]. The quality of genotyping was assessed by duplicate analysis of 5% of random samples, with an agreement rate of 100%.

Exposure data

Cumulative smoking dose was evaluated as pack-years, the product of the number of packs consumed per day and years of smoking. Smoking habit was classified into the three categories of never, pack-years < 20 (low-moderate) and ≥ 20 pack years (heavy). Consumption of types of alcoholic beverages (Japanese sake, beer, shochu, whiskey and wine) per occasion was determined with reference to the average number of drinks per day, which was then converted into a Japanese sake (rice wine) equivalent (one unit sake = 23 g ethanol) [24]. Daily ethanol consumption was estimated as the product of the frequency of alcohol beverage and average ethanol consumption occasion, and drinking habit was classified into the four categories of non-drinker, low (< 5 g/day), moderate (< 23 g/day) and heavy (≥ 23 g/day). Consumption of folate was determined using a semi-quantitative food frequency questionnaire (SQFFQ) as described in detail elsewhere [25]. Briefly, the SQFFQ consisted of 47 single food items with frequencies in the eight categories of never or seldom, 1-3 times/month, 1-2 times/week, 3-4 times/week, 5-6 times/week, once/day, twice/day, and 3+ times/day. Average daily intake of nutrients was estimated by multiplying the food intake (in grams) or serving size by the nutrient content per 100 grams of food as listed in the Standard Tables of Food Composition in Japan, 5th edition. Consumption of supplemental folate was not considered in total consumption because the questionnaire for multi-vitamins was not quantitative. Energy-adjusted intake of nutrients was calculated by the residual method [26]. The SQFFQ was validated by reference to a 3-day weighted dietary record as a standard, which showed the reproducibility and validity to be acceptable [27, 28]. The de-attenuated correlation coefficients for energy-adjusted intakes of folate were 0.36 in men and 0.38 in women. Body mass index (BMI) was calculated as the self-reported weight (kilograms) divided by the square of self-reported height (meters). A family history of CRC in first-degree relatives was based on self-reporting, as described elsewhere [29]. The questionnaire also covered the regularity of physical exercise: subjects were asked to report the frequency and intensity of recreational exercise, with average daily exercise hours in any intensity calculated and categorized into the three levels of none, and < 0.5 and ≥ 0.5 hours/day.

Statistical analysis

Odds ratios (ORs) and 95% confidence intervals (CIs) for assessment of the impact of each 8q24 locus, included in the model as an ordinal score (1 to 3), were calculated using multivariable conditional logistic regression models. We explored two models: model 1 was a crude model; model 2 included age and sex plus potential confounders as indicator variables. Confounders considered in model 2 were smoking status (never, former, current moderate, and heavy), drinking habit (non, low, moderate, and heavy), folate consumption by tertile (T1-3), BMI (< 22.5, 22.5 - 24.9, 25.0-27.4 and ≥ 27.5 kg/m2), family history of colorectal cancer (yes or no), and regular exercise (none, < 0.5 hour/day, and ≥ 0.5 hour/day). Interactions between rs6983267 assuming linear effect of allele and potential confounders similarly assuming linear effect were assessed in multivariable unconditional logistic regression models to avoid the dropping of subjects in conditional logistic regression models. To assess possible discrepancies between expected and observed haplotypes, accordance with the Hardy-Weinberg equilibrium (HWE) was checked for controls with the χ2 test. Statistical analyses were performed using STATA version 10 (Stata, College Station, TX), with P-values < 0.05 considered statistically significant.

Results

Table 1 shows baseline characteristics of the 481 CRC cases, with an average age of 60 years, and the 962 controls matched for sex and age. Males accounted for 62.4% of subjects. Apart from a family history of CRC in a first-degree relative, potential confounders showed no clear difference between cases and controls. A family history of CRC was significantly more frequent among CRC cases.
Table 1

Characteristics of cases and controls

Variables

Cases

Controls

p-values

Total

481

962

 

Sex

    

1.00

Male

300

62.4%

600

62.4%

 

Female

181

37.6%

362

37.6%

 

Age (years)

    

0.803

< 40

20

4.2%

39

4.1%

 

40-49

50

10.4%

105

10.9%

 

50-59

169

35.1%

328

34.1%

 

60-69

164

34.1%

353

36.7%

 

70-

78

16.2%

137

14.2%

 

Mean age (SD)

60 (10.2)

60 (9.86)

 

Site of Cancer

     

Colon

245

50.9%

   

Rectum

236

49.1%

   

Smoking

    

0.102

None

215

44.7%

493

51.3%

 

Low-moderate (< 20 pack-years)

59

12.3%

116

12.1%

 

Heavy (≥ 20 pack-years)

203

42.2%

345

35.9%

 

Unknown

4

0.8%

8

0.8%

 

Drinking

    

0.695

None

190

39.5%

383

39.8%

 

Low (< 5 g ethanl/day)

64

13.3%

125

13.0%

 

Moderate (5≤ and < 23 g ethanol/day)

85

17.7%

196

20.4%

 

High (≥ 23 g ethanol/day)

135

28.1%

243

25.3%

 

Unknown

7

1.5%

15

1.6%

 

Daily folate consumption

    

0.857

T1 (≤ 262.0 μg/day)

153

31.8%

286

29.7%

 

T2 (≤ 346.6 μg/day)

158

32.9%

318

33.1%

 

T3 (> 346.6 μg/day)

162

33.7%

341

35.5%

 

Unknown

8

1.7%

17

1.8%

 

Body-Mass Index (BMI) kg/m2

    

0.923

< 22.5

206

42.8%

397

41.3%

 

22.5 ≤ and < 25

157

32.6%

314

32.6%

 

25 ≤ and < 27.5

73

15.2%

162

16.8%

 

≥ 27.5

41

8.5%

79

8.2%

 

Unknown

4

0.8%

10

1.0%

 

Family history of colorectal cancer in the first degree relatives

    

0.014

No

453

94.2%

932

96.9%

 

Yes

28

5.8%

30

3.1%

 

Average recreational exercise

    

0.329

None

192

39.9%

349

36.3%

 

< 0.5 hour/day

194

40.3%

398

41.4%

 

0.5 ≤ hour/day

95

19.8%

215

22.4%

 
Genotype distributions for 8q24 rs6983267 and rs10090154 are shown in Table 2. Among controls, both genotypes were accordant with the HWE. The minor allele frequency for rs6983267 was 0.338 (G-allele). The age- and sex-adjusted in the allelic model showed an OR of 1.22 (1.04-1.44, p = 0.0144) and the confounder-adjusted model an OR of 1.25 (1.06-1.48, p = 0.0071). Genotypic model showed a significant association only with rs6983267 GG genotype (OR = 1.64, 1.15-2.35, p = 0.0063). In contrast, rs10090154 showed no association with CRC risk. Table 3 shows stratified analyses conducted to explore possible interactions between potential confounders although point estimates for ORs were not static; no significant interactions were seen between the factors examined and rs6983267. The lack of association in those with a positive family history was of interest vis a vis the significant association in those without it, albeit that the number of subjects with a family history was limited.
Table 2

Genotypes distribution of 8q24 polymorphisms and odds ratios for the minor alleles and genotypes.

     

Allelic model

Genotype model

     

Model 1 *1

  

Model 2 *2

  

Heterozygote

  

Minor homozygote

  

8q24 locus

 

Genotype

  

OR

95% CI

p-value

ORa

95% CI

p-value

ORa

95% CI

p-value

ORa

95% CI

p-value

rs6983267 (Minor allele: G, MAF*1 in controls = 0.338)

 

TT

TG

GG

UK*4

            

case/control

181/418

222/436

73/107

3/1

1.22

1.04-1.44

0.0144

1.25

1.06-1.48

0.0071

1.19

0.93-1.52

0.1665

1.64

1.15-2.35

0.0063

rs10090154 (Minor allele: T, MAF in controls = 0.153)

 

CC

CT

TT

UK

            

case/control

355/689

112/247

11/23

3/3

0.90

0.72-1.12

0.3443

0.87

0.69-1.09

0.2140

0.83

0.63-1.08

0.1690

0.90

0.43-1.89

0.7854

*1 Crude conditional logistic regression model.

*2 Adjusted for age as continuous variable, drinking (non, low, moderate, heavy, and unknown), smoking (non, moderate, heavy, unknwon), BMI (< 22.5, < 25, < 27.5, 27.5-, unknown), folate in tertile (T1, T2, T3, and unknown), total energy intake, family history of colorectal cancer, average recreational exercise (none, < 0.5 hour/day, 0.5-hour/day) in conditional logisitic regression.

*3 MAF indicates minor allele frequency.

*4 UK indicates the subjects whose genotyping was unsuccessful.

Table 3

Stratified analysis according to potential confounding factors for 8q24 rs6983267 genotype

   

rs6983267 allelic model

 
   

Model 1*1

  

Model*2

   

Exposure

Number of controls with each genotype (TT/TG/GG)

Number of cases with each genotype (TT/TG/GG)

OR*1

95% CI

p-value

OR

95% CI

p-value

Interaction P

Sex

        

0.181

Male

122/133/43

259/270/70

1.11

0.91-1.37

0.295

1.14

0.93-1.41

0.212

 

Female

61/89/30

159/166/37

1.44

1.10-1.88

0.007

1.34

1.01-1.78

0.040

 

Smoking

        

0.401

None

73/106/35

206/232/55

1.34

1.05-1.70

0.018

1.29

1.01-1.65

0.042

 

Low-moderate (< 20 pack-years)

19/31/9

52/52/12

1.51

0.93-2.43

0.094

1.49

0.89-2.49

0.130

 

Heavy (≥ 20 pack-years)

88/84/29

158/147/39

1.11

0.86-1.43

0.423

1.12

0.86-1.44

0.407

 

Drinking

        

0.437

None

69/92/30

166/179/38

1.36

1.04-1.76

0.023

1.35

1.03-1.77

0.028

 

Low (< 5 g ethanl/day)

23/29/12

51/58/16

1.25

0.81-1.93

0.308

1.44

0.91-2.28

0.124

 

Moderate (5≤ and < 23 g ethanol/day)

34/41/9

85/83/27

0.98

0.67-1.43

0.918

0.99

0.67-1.46

0.941

 

High (≥ 23 g ethanol/day)

55/59/19

112/108/23

1.22

0.89-1.67

0.217

1.22

0.88-1.69

0.231

 

Daily folate consumption

        

0.694

T1 (≤ 262.0 μg/day)

54/73/25

112/137/37

1.14

0.85-1.53

0.375

1.22

0.90-1.66

0.197

 

T2 (≤ 346.6 μg/day)

59/75/22

104/141/36

1.21

0.91-1.61

0.191

1.25

0.93-1.67

0.141

 

T3 (> 346.6 μg/day)

66/72/24

157/152/32

1.24

0.94-1.64

0.135

1.30

0.97-1.73

0.080

 

Body-Mass Index (BMI) kg/m 2

        

0.678

< 22.5

73/100/32

177/176/44

1.34

1.05-1.72

0.020

1.43

1.10-1.85

0.007

 

22.5 ≤ and < 25

69/69/19

128/148/37

0.93

0.70-1.25

0.663

0.93

0.69-1.25

0.637

 

25 ≤ and < 27.5

23/34/16

74/69/19

1.58

1.06-2.36

0.024

1.67

1.09-2.55

0.018

 

≥ 27.5

18/17/5

31/41/7

0.98

0.54-1.79

0.944

1.06

0.54-2.10

0.863

 

Family history of colorectal cancer in the first degree relatives

        

0.765

No

169/212/69

404/422/105

1.24

1.05-1.46

0.011

1.26

1.06-1.48

0.008

 

Yes

14/10/4

14/14/2

1.09

0.50-2.38

0.833

0.84

0.29-2.43

0.741

 

Average recreational exercise

        

0.109

None

77/90/24

161/140/48

1.10

0.85-1.42

0.462

1.13

0.87-1.47

0.356

 

< 0.5 hour/day

73/89/31

158/199/40

1.20

0.93-1.56

0.163

1.20

0.92-1.57

0.174

 

0.5 ≤ hour/day

33/43/18

99/97/19

1.59

1.11-2.28

0.012

1.70

1.15-2.50

0.008

 

*1 Odds ratios were adjusted for age and sex in unconditional logistic regression models. Conditional logistic models were not applied because keeping matching in stratficiation gave unstabel estimation.

*2 Odds ratio adjusted for age, sex and all variables in this examination except variable used for stratification.

*3 Interaction term between rs6983267 genotype in score and stratifiying factor in socre was added in model 2.

*4 Subjects were exlucded from analysis because of lack of information, smoking (4 cases and 8 controls), drinking (7 cases and 15 controls), folate (8 cases and 17 controls), and BMI (3 cases and 10 controls)

Discussion

In this study, we found that the G allele in rs6983267 was associated with a significantly increased risk of CRC in a Japanese population. This finding is consistent with those from previous GWASs [6, 9, 11] and a pooled analysis [12], as reviewed in Table 4, which reported the consistency of this association with CRC and colorectal adenoma in populations with European ancestry. The only previous study of rs6983267 in a population with Asian ethnicity (Japanese-American) was that by Haiman et al [6], and to our knowledge the present study is the first indication in Japanese living in Japan. Tenesa et al. reported significant association with rs7014346 in 8q24, which is in high linkage disequilibrium with rs6983267, in Japanese population [19], supporting significant association between the rs6983267 in CRC in Japanese. Recent advances in genetic analysis have enabled a comprehensive approach to identifying disease susceptibility loci. The consistency of findings in this and the previous studies warrants the usefulness of the GWAS approach across ethnicities. We also evaluated potential interactions between common background factors and rs6983267, but found no significant interaction between them. Berndt et al. also reported a lack of interaction between rs6983267 and age, sex, smoking, family history of CRC and cancer site [12]. The consistency of this finding indicates that rs6983267 is associated with CRC risk independently of common risk factors.
Table 4

Review of results of 8q24 rs6983267 for colorectal cancer in allelic model.

Author

Year

Case/Control

Country

Study subjects

Per allele OR (95%CI)

Adjustment

Haiman et al.

2007

1,807/5,511

USA

Pooled

1.25 (1.12-1.38)

Sex

  

217/1,049

 

African American

1.37 (0.98-1.91)

Sex

  

381/1,197

 

Japanese American

1.13 (0.96-1.34)

Sex

  

61/347

 

Native Hawaiian

1.59 (1.02-2.47)

Sex

  

251/1,007

 

Latinos

1.26 (1.02-1.55)

Sex

  

214/973

 

European Americans

1.28 (1.03-1.58)

Sex

Tomlinson et al.

2007

7,954/6,206

UK

CRC pooled

1.21 (1.15-1.27)

Crude

  

620/960

 

Panel A CRC White UK residents

1.38 (1.19-1.59)

Crude

  

4,361/3,752

 

Panel B White UK residents

1.19 (1.12-1.26)

Crude

  

1,901/1,079

 

Panel C

1.21 (1.09-1.35)

Crude

  

1,072/415

 

Panel D European Ancestry

1.13 (0.96-1.33)

Crude

  

1,425/2,255

 

Adenoma pooled

1.22 (1.10-1.34)

Crude

  

407/1,027

 

Panel A Adenoma White UK residents

1.53 (1.29-1.81)

Crude

  

607/765

 

Panel E

1.05 (0.90-1.23)

Crude

  

411/463

 

Panel F

1.13 (0.93-1.37)

Crude

Poynter et al.

2007

1,339/2,191

USA

Population -- based

1.11 (0.96-1.29)

Age and sex

Tuupanen et al.

2008

996/1,012

Finland

Population-based

1.22 (1.08-1.38)

Crude

Berndt et al.

2008

3,134/4,454

USA

Colorectal neoplasms pooled

1.16 (1.07-1.25)

Age, sex, and study

  

547/1,656

 

PLCO

1.17 (1.01-1.35)

Age and sex

  

1,174/1,293

 

PLCO adenoma

1.24 (1.11-1.39)

Age and sex

  

364/363

 

PLCO II

0.93 (0.75-1.16)

Age and sex

  

544/542

 

NHS

1.10 (0.93-1.30)

Age and sex

  

505/600

 

Minnesota

1.21 (1.01-1.44)

Age and sex

Ghousaini et al.

2008

2,299/2,284

UK

Cases from prospective study at East Anglia

1.27 (1.16-1.37)

Crude

Lie et al.

2008

561/721

USA

Colon cancer cases from SEER Kentucky

1.69 (1.19-2.40)

Age, sex, BMI, and NSAID use.

    

Cuacasian

1.61 (1.36-2.30)

Age, sex, BMI, and NSAID use.

Schafmayer

2009

2,713/2,718

Germany

Colorectal cancer cases with German ancestry

1.22 (1.13-1.31)

Crude

Curtin et al.

2009

1,069/1,040

USA/UK

Colorectal cancer cases from USA/UK

1.17 (1.03-1.32)

Crude

Our study

 

481/962

Japan

HERPACC II participatns (Japanese)

1.22 (1.04-1.44)

Age and sex

     

1.26 (1.06-1.48)

Age, sex, drinking, smoking, BMI, folate consumption, energy, physical exercise, and family history of CRC

Rs6983267 was originally identified using a non-hypothesis-based approach, and evidence has suggested a possible biological mechanism behind this observed association. The rs6983267 polymorphism resides 15 kb upstream of a processed pseudogene (POU5F1P1) of the POU-domain factor gene, POU5F1, which encodes transcription factor OCT4, with 97.5% shared identity [30]. OCT4, a transcript of POU5F1, plays a role in maintaining stem cell pluripotency, self-renewal and chromatin structure in stem cells [31], and promotes tumor growth in a dose-dependent manner [32]. A conserved POU5F1-binding site I at the 5' promoter region of the WNT-signaling gene, FZD5, has been reported [33]. Tomlinson et al. reported the expression of either POU5F1 or POU5F1P1 in cell lines and primary CRCs [9], while Suo et al. similarly reported the expression of these genes in cancer cell lines and cancer tissues [30]. Given that OCT4 pseudogenes in mice are reported to mediate stem cell regulatory function [34], it is possible to hypothesize that OCT4 pseudogenes, including POU5F1P1, might play a role in stem cell proliferation. However, no difference in expression according to rs6983267 status was observed [9]. Berndt discussed the potential contribution of MYC, which is located > 300 KB distant to rs6983267[12]. Recently, Pomerantz et al. reported rs6983267 displays a difference in binding of transcription factor 7-like 2 (TCF7L2) leading to a different physical interaction with MYC [35]; however, Tuupanen et al. failed to find clear association between rs6983267 genotype and MYC expression. There still remains controversy between MYC and rs6983267 requiring further studies. Moreover, Tuupanen et al. reported rs6983267 affects a binding site for the Wnt-regulated transcription factor (TCF4), with the risk allele G showing stronger binding in vivo and in vitro. Overall, these findings indicate that the possible biological mechanism behind the effect of rs6983267 polymorphism on CRC carcinogenesis requires further study.

We did not observe any association with rs10090154 (OR = 0.90) on the contrary to the results from Multi-ethnic cohort study [6]. The point estimate for minor allele in the previous study was 1.41 (95%CI: 1.14-1.75). Following case-control study for Japanese American in Hawaii showed lack of association (OR = 1.07, 95%CI: 0.78-1.48)[6]. Inconsistency across studies might come from the finding in the original GWAS was by chance although threshold in statistical significance was high enough. Or, statistical power in following studies including ours was not good enough. By all means, more evidence is needed to clarify significance of the locus.

Several potential limitations of the present study require consideration. First, use of hospital-based control in this study for potential cause of selection bias. We used non-cancer patients at our hospital as controls, given the likelihood that our cases arose within this population base. Moreover, we previously showed that individuals selected randomly from our control population were similar to the general population in terms of baseline characteristics [22]. Given the similarity in minor allele frequency between our controls and that in the HapMap database for Japanese, it is reasonable to assume the external validity of our study results to the general population. Second, as with other case-control studies, this study may have suffered from information bias: although the questionnaires were completed before the diagnosis in our hospital, some patients referred from other institutions might have known their diagnosis. Lack of interaction needs careful interpretation because confounders assessed in this study showed no association with CRC risk by themselves.

Conclusion

Our present investigation showed that rs6983267 in 8q24 is an independent risk factor of CRC in a Japanese population. Further studies to clarify the biological mechanisms of this association are warranted.

Declarations

Acknowledgements

The authors are grateful to the many doctors, nurses, and technical and administration staff of Aichi Cancer Center Hospital for the daily administration of the HERPACC study.

This study was supported by a Grants-in-Aid for Scientific Research from the Ministry of Education, Science, Sports, Culture and Technology of Japan, for Cancer Research from the Ministry of Health, Labour and Welfare of Japan, and for the Third Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan.

Financial disclosure: The authors declare that they have nothing to disclose regarding financial issues.

Authors’ Affiliations

(1)
Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
(2)
Director, Aichi Cancer Center Research Institute, Nagoya, Japan
(3)
Department of Medical Oncology, Aichi Cancer Center Hospital, Nagoya, Japan
(4)
Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, Nagoya, Japan
(5)
Department of Pathology and Molecular Diagnosis, Aichi Cancer Center Hospital, Nagoya, Japan
(6)
Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
(7)
Department of Medical Oncology and Immunology, Nagoya City University Graduate School of Medical Science, Nagoya, Japan

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  36. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/9/379/prepub

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