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Carcinogenesis Advance Access originally published online on March 2, 2006
Carcinogenesis 2006 27(9):1797-1802; doi:10.1093/carcin/bgl001
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Peroxisome proliferator-activated receptor (PPAR) {gamma} gene polymorphisms and colorectal cancer risk among Chinese in Singapore

Woon-Puay Koh*, Jian-Min Yuan1, David Van Den Berg2, Sue A. Ingles2 and Mimi C. Yu1

Department of Community, Occupational and Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore Singapore
1 The Cancer Center, University of Minnesota MN, USA
2 USC/Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California Los Angeles, CA, USA

*To whom correspondence should be addressed at: Department of Community, Occupational and Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, MD3, 16 Medical Drive, Singapore 117597. Tel: +65 6874 4975; Fax: +65 6779 1489; Email: cofkwp{at}nus.edu.sg


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Peroxisome proliferator-activated receptor (PPAR) {gamma} is a ligand-activated nuclear receptor that plays a key role in adipogenesis and adipocyte gene expression, and has recently been linked with possible antineoplastic effects in colonic carcinogenesis. PPAR{gamma}2 and {gamma}3 are two transcripts arising from the PPAR{gamma} gene through differential promoter usage and alternative splicing. We investigated the associations between PPAR{gamma}2 Pro12Ala and PPAR{gamma}3 C-681G gene polymorphisms and colorectal cancer (CRC) risk in a case–control study nested within the Singapore Chinese Health Study. Genotypes for the PPAR{gamma}2 and PPAR{gamma}3 polymorphisms were determined on 362 incident CRC cases and 1164 cohort controls by direct sequencing and by fluorogenic 5'-nuclease assay. Unconditional logistic regression models were used for statistical analyses. With adjustment for CRC risk factors, subjects with one or two copies of the G allele of the PPAR{gamma}2 Pro12Ala polymorphism showed a statistically significant reduction in risk compared to those with the CC genotype [odds ratio (OR) = 0.53, 95% confidence interval (CI) = 0.30–0.92]. For the PPAR{gamma}3 C-681G polymorphism, subjects with one or two copies of the C allele showed a reduction in risk compared to those with the GG genotype (OR = 0.72, 95% CI = 0.51–1.04). When PPAR{gamma}2 and PPAR{gamma}3 genotypes were considered simultaneously, the number of putative low-risk genotypes was significantly associated with reduced risk of CRC in a gene-dose-dependent manner; the OR (95% CI) was 0.72 (0.49–1.07) among subjects possessing one low-risk genotype (either PPAR{gamma}2 or PPAR{gamma}3), and the comparable figure among subjects possessing both low-risk genotypes was 0.19 (0.07–0.51).

Abbreviations: BMI, body mass index; CRC, colorectal cancer; EM algorithm, expectation–maximization algorithm; LD, linkage disequilibrium; PPAR, peroxisome proliferators-activated receptor


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Colorectal cancer (CRC) has one of the highest incidence rates among cancers in developed countries. The geographical pattern of high rates in the West and lower rates in Asia suggests that in addition to genetic determinants, lifestyle and dietary factors may be important contributors to colonic carcinogenesis (1,2). Among them, obesity, which is more prevalent among Western populations, has been consistently associated with higher risk of CRC among men and women in both case–control and cohort studies (reviewed in ref. 3). Epidemiological data also suggest that both Type 2 diabetes and impaired glucose tolerance are risk factors for colon cancer in Western populations. Together with a growing body of experimental evidence, these epidemiological data suggest that obesity-induced hyperinsulinemia, hyperlipidemia and insulin resistance may play a role in colon carcinogenesis (reviewed in ref. 4).

As a nuclear receptor which plays a pivotal role in regulating adipocyte differentiation, glucose and lipid homeostasis, and intracellular insulin-signaling events, peroxisome proliferators-activated receptor (PPAR) {gamma} has received growing interest for its possible role in CRC. PPAR{gamma} forms functional heterodimers with members of the retinoid X-receptor family of nuclear receptors and activates the transcription of target genes by the release of corepressors and recruitment of coactivators (5). Putative endogenous ligands for PPAR{gamma} include both polyunsaturated fatty acids (PUFAs) and arachidonic acid derivatives (6). Experimental evidence has suggested that activation of PPAR{gamma} in the colon results in growth inhibition and differentiation, and reduces the malignant potential of CRC cells (7). In addition, administration of the PPAR{gamma} ligand troglitazone significantly inhibits chemically induced colitis and formation of aberrant crypt foci in rats (8).

The PPAR{gamma} gene produces four different PPAR{gamma} mRNAs by differential promoter usage and alternative splicing, giving rise to two different protein isoforms. The PPAR{gamma}1, PPAR{gamma}3 and PPAR{gamma}4 transcripts, although possessing different upstream regulatory sequences, give rise to identical proteins encoded by exons 1–6. A functional C-to-G polymorphism in the promoter region for the PPAR{gamma}3 transcript at position –681 from the beginning of exon A2 has been associated with increased body weight and circulating levels of cholesterol (9,10). The PPAR{gamma}2 transcript gives rise to a protein with an additional 28 amino acids encoded by the PPAR{gamma}2-specific exon B (11,12). A polymorphism (proline-to-alanine substitution at codon 12) in exon B has been associated with reduced risk of diabetes mellitus (13–15) and CRC (16). We investigated the associations of these two polymorphisms in the PPAR{gamma}2 coding region and the PPAR{gamma}3 regulatory region with CRC risk in a nested case–control study within the Singapore Chinese Health Study, a prospective investigation of diet and cancer in 63 000 Chinese men and women.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Study population
The study design and subject recruitment of the Singapore Chinese Health Study have been described previously (17). Briefly, 63 257 Chinese women and men aged 45–74 years belonging to the Hokkien or Cantonese dialect group were enrolled in the study between April 1993 and December 1998. At recruitment, a face-to-face interview was conducted in the subject's home by a trained interviewer, using a structured questionnaire, which requested information on demographics, lifetime use of tobacco and alcohol, medical history, family history of cancer and usual diet over the last year (17). The Institutional Review Boards at the University of Southern California and the National University of Singapore had approved this study.

A smoker was defined as a subject who ever smoked at least one cigarette per day for 1 year or longer. Ever smokers were further asked for current smoking status at recruitment, age at which regular smoking was started, the average number of cigarettes smoked per day and the number of years of smoking. An alcohol drinker was defined as a subject who drank any alcoholic beverages on a monthly basis or more often. Each drinker was further asked for the frequency and amount of each of the four types of alcoholic beverages (beer, rice wine, grape wine and hard liquor) consumed. One drink was defined as 375 ml of beer (13.6 g of ethanol), 30 ml of rice wine (10.9 g of ethanol), 118 ml of grape wine (11.7 g of ethanol) and 30 ml of hard liquor (10.9 g of ethanol). Total number of drinks per day was computed based on the amount and type of alcoholic beverages consumed.

Between April 1994 and July 1999, we attempted to collect blood (or buccal cells if subject refused blood donation) and single-void urine specimens from a random 3% sample of study enrollees. Details of the biospecimen collection, processing and storage procedures have been described previously (18). We collected blood/buccal cell samples from 1194 (63% of total eligible) subjects during this period. After we excluded 18 subjects who had a history of CRC at recruitment (n = 5) or developed first CRC (n = 13) by May 31, 2003, the remaining 1176 subjects constituted the referent (i.e. control) group for the present study. Compared with the rest of the cohort members, these subjects had comparable distributions by age, sex, dialect group, level of education, body mass index, alcohol drinking, history of diabetes, or familial history of CRC or any cancer (all P values > 0.10). There was a slightly lower percentage of ever smokers in the control group (27.8%) than that in the rest of the cohort participants (31.6%, P = 0.04).

We identified incident CRC cases through the population-based cancer registry in Singapore (19). As of May 31, 2003, CRC occurred among 696 cohort participants. All cases were histologically confirmed except for 15 that were ascertained by clinical evidence (2%) and six by death records (0.8%). We also attempted to collect blood/buccal cell and urine samples from all incident CRC cases. Blood (n = 289) or buccal (n = 85) specimens were available on 374 (53.7%) incident CRC cases. Compared with CRC patients who did not donate a blood or buccal sample, those who donated had a similar mean of age at cancer diagnosis (66.2 versus 67.5 years). Male patients were more likely to donate a biospecimen than female patients (57.1 versus 49.7%). So did the patients with Cantonese dialect compared with those with Hokkien dialect (59.0 versus 49.9%). Patients who did not donate a blood or buccal sample were less educated (53.6% had no formal education) than those who did (46.4%). There was no difference in the percentage of biopecimen availability by level of body mass index, cigarette smoking, alcohol drinking or history of diabetes.

Genotyping methods
DNA was purified from buffy coats of peripheral blood and buccal cell samples using a QIAamp 96 DNA Blood Kit (Qiagen, Valencia, CA). Alleles for the PPAR{gamma}2 Pro12Ala polymorphism (rs1801282) were identified using direct sequencing of the polymorphic region. The region of the gene containing the polymorphism was amplified by polymerase chain reaction (PCR) using primers GC083for (5'-GGAAACTGATGTCTTGACTCATG-3') and GC083rev (5'-GCAGACAGTGTATCAGTGAAGG-3'). PCR reaction mix was prepared using HotStart Taq Polymerase (Qiagen, Valencia, CA) according to manufacturer's instructions using 20 ng of genomic DNA, 2 mM MgCl2 and 300 µM of each primer. PCR amplification was performed in a thermal cycler (MWG Biotech, High Point, NC) using a touchdown protocol with an initial step of 95°C for 15 min finishing with 35 cycles of 95°C per 25 s, 54°C per min and 72°C per min. The PCR reactions are purified using a MAF-NOB PCR purification plate (Millipore, Billerica, MA) to remove dNTPs and primers. A fraction of the samples were analyzed by agarose gel electrophoresis to confirm the success of the PCR reactions and the absence of a product in the negative controls. DNA sequencing was performed using primer GC083S (5'-ACTGATGTCTTGACTCATGGGTG-3') using ~10–20 ng of purified PCR product using fluorescently labeled ddNTPs (ABI Dye Terminator Sequencing Kit, Applied Biosystems) by cycle sequencing for 50 rounds of 95°C per 15 s and 50°C for each 3.5 min. The sequencing reactions were run on an ABI3730xl Capillary DNA Analyzer. The sequence files were run through Phred/Phrap (University of Washington) to align the sequences and mark possible polymorphic positions (20). The sequences were viewed in Consed (University of Washington) and the polymorphic position scored (21).

The PPAR{gamma}3 C-681G polymorphism (rs10865710) was genotyped using the fluorogenic 5'-nuclease assay (TaqMan Assay) (22). The TaqMan assays were performed using a TaqMan PCR Core Reagent kit (Applied Biosystems, Foster City, CA) according to manufacturer's instructions. The oligonucleotide primers for amplification of the PPAR{gamma}3 polymorphic region were GC028for (5'-CCTGATGATAAGGCTTTTGGCATT-3') and GC028rev (5'-TATCTCTTATGAAAGGCTCAAGGATCCT-3'). In addition, the fluorogenic oligonucleotide probes (TaqMan MGB Probes; ABI) used to detect each of the alleles were GC028F (5'-TTTTCCATCAAGACAAAA-3') labeled with 6-FAM to detect the C allele and GC028V (5'- TTTTCCATGAAGACAAAA-3') labeled with VIC to detect the G allele. PCR amplification using ~10 ng of genomic DNA was performed in a thermal cycler (MWG Biotech, High Point, NC) with an initial step of 95°C for 10 min followed by 50 cycles of 95°C for 25 s and 60°C for 1 min. The fluorescence profile of each well was measured in an ABI 7900HT Sequence Detection System and the results analyzed with Sequence Detection Software (Applied Biosystems). Experimental samples were compared with 12 controls to identify the three genotypes at each locus (G/G, G/C, C/C). Samples that were outside the parameters defined by the controls were identified as non-informative and were retested.

Statistical analysis
Twelve cases and twelve controls were non-informative in either the PPAR{gamma}2 or PPAR{gamma}3 genotypes. These subjects were excluded from the study. Thus, the present analyses included 362 cases and 1164 controls. The cases patients and control subjects were not genetically related.

The genotypes of control subjects were checked for Hardy–Weinberg equilibrium using the exact test. The differences in genotype distribution between cases and controls by demographic and selected lifestyle characteristics were examined using the {chi}2-test. We examined linkage disequilibrium (LD) between the two gene polymorphisms in control subjects using the Expectation–Maximization (EM) algorithm (23) as implemented in Haploview version 3.2 (24). The measure of the statistical association for LD, R2, a better measure for LD than the commonly used Lewontin's D' in the case of low allele frequency of the gene, was used to assess the correlation of alleles at two sites (25).

We used standard methods for unmatched case–control studies to examine the effects of the PPAR{gamma} gene polymorphisms on CRC risk (26). The strength of a given gene–cancer association was measured by the odds ratios (ORs) and their 95% confidence intervals (CIs) and P-values. Among control subjects, the frequencies of the PPAR{gamma}2 G allele were comparable between Cantonese and Hokkiens (4.0 versus 3.7%, P = 0.53). So were those of the PPAR{gamma}3 G allele (37.8 versus 35.7%, P = 0.45). Therefore, we combined both dialect groups in data analysis. We used a polytomous logistic regression model to estimate ORs of colon and rectal cancers against total control subjects. All ORs were adjusted for age (year) at recruitment, year of recruitment, gender, dialect group (Cantonese, Hokkien), level of education (no formal schooling, primary school, and secondary school or higher), body mass index (BMI) (<20, 20–<24, 24–<28, and 28+ kg/m2), cigarette smoking (non-smokers, light and heavy smokers), alcohol consumption (non-drinkers, <1 and 1+ drink/day), history of diabetes mellitus (yes/no) and familial history of CRC (no/yes). Based on the entire cohort, we classified subjects who started to smoke before 15 years of age and smoked at least 13 cigarettes/day as ‘heavy’ smokers, whereas the remaining smokers as ‘light’ smokers.

Statistical analysis was carried out using the SAS software Version 9.1 (SAS Institute, Cary NC), unless otherwise indicated. All P-values quoted are two-sided. The two-sided P-values < 0.05 were considered statistically significant.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
Of 362 cases, 206 (57%) had cancers of the colon, and the remaining 156 (43%) had either rectal or rectosigmoid cancers. The mean age of cases at the time of diagnosis was 66.1 (SD 7.9) years, with a range of 47–81 years. The median time interval between the baseline interview and cancer diagnosis was 4.7 years (range, 1 month–9.9 years). Table I shows the distributions by selected demographic characteristics and potential risk factors for CRC in the study population. Relative to control subjects, case patients were older at recruitment [mean age at recruitment for cases was 61.0 (SD = 7.6) years and for controls was 56.4 (SD = 8.1) years], had a greater proportion of men, had lower level of education, had higher BMI, were more likely to be cigarette smokers and daily alcohol drinkers, more likely to have a history of diabetes mellitus and more likely to have a first-degree relative with CRC.


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  		Table I Distributions by selected demographic characteristics and potential risk factors for CRC in the study population at baseline, the Singapore Chinese Health Study

 
Among the control subjects, the frequencies of the C and G alleles of the PPAR{gamma}2 polymorphism were 0.961 and 0.039, respectively, whereas the frequencies of the C and G alleles of the PPAR{gamma}3 polymorphism were 0.634 and 0.366, respectively. All genotypic distributions were in Hardy–Weinberg equilibrium (P-values > 0.7). The R2 for the correlation of alleles at two sites (i.e., for LD) was 0.07 between the PPAR{gamma}2 Pro12Ala and PPAR{gamma}3 C-681G polymorphisms, indicating a lack of LD. Table II shows PPAR{gamma}2 and PPAR{gamma}3 genotypes in relation to CRC risk. For the PPAR{gamma}2 polymorphism, the CG and GG genotypes were grouped owing to the low frequency of the GG genotype. Subjects possessing at least one copy of the G allele had an ~50% reduction in risk of CRC (OR = 0.53, 95% CI = 0.30–0.92). For the PPAR{gamma}3 polymorphism, subjects with at least one copy of the C allele showed a >25% reduction in CRC risk compared with those homozygous for the G allele. Having two copies of the C allele was not associated with any additional reduction in risk. Hence the PPAR{gamma}2 CG/GG genotypes and the PPAR{gamma}3 GC/CC genotypes were considered as putative low-risk genotypes for CRC. When both PPAR{gamma}2 and PPAR{gamma}3 gene polymorphisms were examined simultaneously, the ORs (95% CIs) for CRC were 0.72 (0.49–1.07) for subjects possessing only one low-risk genotype and 0.19 (0.07–0.51) for those possessing two low-risk genotypes when compared to subjects without any low-risk genotype (P for trend = 0.002). There is no material difference in any of the gene–risk associations across subsites (i.e. colon versus rectal cancer).


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  		Table II PPAR{gamma}2 and PPAR{gamma}3 genotype in relation to risk of CRC, the Singapore Chinese Health Study

 
We also examined the association between the PPAR{gamma}2 and PPAR{gamma}3 genotypes and risk of CRC among non-diabetic subjects. After exclusion of subjects who reported a history of physician-diagnosed diabetes at recruitment, ORs (95% CIs) of CRC for subjects possessing only one and both low-risk genotypes were 0.66 (0.43–1.01) and 0.16 (0.05–0.41), respectively, compared with those without any low-risk genotype of the two PPAR{gamma} polymorphisms studied (P for trend = 0.0001). We also performed subgroup analyses stratified by age (<60 and 60+ years), gender, dialect group (Cantonese, Hokkien), body mass index (<24 and 24+ kg/m2), cigarette smoking (no/yes), alcohol drinking (no/yes) and familial history of CRC (no/yes). The inverse associations between the combined genotypes of PPAR{gamma}2 and PPAR{gamma}3 and risk of CRC risk were comparable between subgroups of any stratifying variable (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
In this cohort of Singapore Chinese, we reported a significant effect of the PPAR{gamma}2 Pro12Ala and PPAR{gamma}3 C-681G gene polymorphisms on CRC risk. Although the risk reduction associated with the PPAR{gamma}2 variant is similar to that reported for CRC in a Spanish population (16) and colorectal adenoma in a US population (27), this is the first study relating a PPAR{gamma}3 gene polymorphism with CRC risk.

The PPAR{gamma}2 gene polymorphism in this study is a C-to-G missense mutation, which results in a proline (Pro) to alanine (Ala) substitution at codon 12 in the PPAR{gamma}2-specific exon B. This substitution is within a domain of the protein that enhances ligand-independent activation (28,29). The reported allele frequency of this variant varies in different populations, from 0.12 among Caucasian Americans, 0.10 among Mexican Americans and 0.03 among African Americans to 0.01 among Chinese from mainland China (29). Our Ala allelic frequency of 0.039 among the controls in our Chinese population is consistent with the frequency reported previously for Singapore Chinese (30). Our finding of a lack of strong LD between the two polymorphic sites is consistent with the HapMap data (31), which show an R2 value of 0.08 for Han Chinese and 0.31 for Caucasians. In contrast to R2, Lewontin's D' values were high in our dataset (1.0, 95% CI = 0.92–1.0), and in the HapMap dataset (1.0, 95% CI = 0.11–0.99 for Han Chinese; 1.0, 95% CI = 0.69–1.0 for European whites), indicating high LD. However, in the case of low allele frequency, such as the case of PPAR{gamma}2 (0.039 in our study population; 0.075 in HapMap whites), D' may not be valid since it can be greatly inflated (25). Therefore, in our study, we think it is more appropriate to use R2 instead of D', and the low value of R2 in our study indicated a lack of LD.

A case–control study among Spanish participants found that subjects with the G allele had an ~45% reduction in CRC risk (16), which is similar to the magnitude of risk reduction noted in our study. These empirical data suggest that the putative low-risk G allele may be associated with biologically higher PPAR{gamma}2 activity. On the other hand, Jiang et al. (32) examined the PPAR{gamma}2 Pro12Ala polymorphism among CRC cases and controls in an Indian population in Chennai, India, which had a higher G allelic frequency of 0.11 compared with our study population, and observed no significant association between this gene polymorphism and CRC risk (OR = 1.06; 95% CI = 0.70–1.61). Since putative ligands for PPAR{gamma} include both dietary polyunsaturated fatty acids (PUFAs) and arachidonic acid derivatives (6), it is plausible that dietary factors can exert an influence on the effect of PPAR{gamma} on colorectal carcinogenesis. In support of this hypothesis, Jiang et al. (32) did find a reduced risk of CRC associated with the G allele among subjects with higher fish intake (OR = 0.51), although this did not reach statistical significance. Thus, differences in the prevalence of dietary cofactors may explain, at least in part, the disparate findings among different populations.

The PPAR{gamma}3 gene polymorphism examined in this study is a C-to-G substitution –681 bp upstream from the PPAR{gamma}3 transcription start site and is located in a putative DNA-binding site for transcription factors of the signal transducer and activator of transcription (STAT) family (9). The G allele frequency has been described as 0.25 in the French population, which is lower than that found among our Chinese population. The G variant completely abolishes the binding of STAT5B to the cognate promoter element and decreases the transactivation of PPAR{gamma}3 promoter by the growth hormone/STAT5B pathway and has been associated with increased plasma apolipoprotein B and LDL-cholesterol levels (10). Alternatively, the C allele is associated with higher PPAR{gamma}3 receptor activity in vitro (9).

Adipose PPAR{gamma} has been identified as an important mediator for the maintenance of insulin sensitivity in the body. Recent experimental data have suggested that ligand-activation of PPAR{gamma} in adipose tissues improves obesity-associated insulin resistance by regulating expression of adipocyte-secreted hormones that regulate glucose homeostasis (reviewed in ref. 33). Obesity-induced insulin resistance results in hyperinsulinemia that can in turn lead to a decrease in synthesis of insulin-like growth factor binding protein and an increase in levels of bioavailable insulin-like growth factor-1 (IGF-1). Both insulin and IGF-1 can signal through their receptors to promote cellular proliferation and angiogenesis, or inhibit apoptosis in CRC cells (34–36). Such experimental evidence is consistent with epidemiological data associating clinical conditions of high levels of insulin and IGF-1 with increased risk of colon cancer (reviewed in ref. 37). Hence better insulin sensitivity and lower insulin levels mediated by adipose PPAR{gamma} can potentially reduce CRC risk. Consistent with this hypothesis, the Pro12Ala polymorphism of the PPAR{gamma}2 gene that is associated with lower CRC risk in our study has indeed been associated with lower fasting insulin concentrations, improved insulin sensitivity and reduced risk of Type II diabetes mellitus (13–15).

Although both the PPAR{gamma}2 and PPAR{gamma}3 isoforms are expressed in adipose tissues, the PPAR{gamma} protein expressed in normal and neoplastic colonic epithelial cells is predominantly, if not solely, the {gamma}3 isoform. The distribution of PPAR{gamma}3 mRNA in human colon cancer cell lines is 100-fold more abundant than the {gamma}2 isoform under basal condition and increased by >600-fold over {gamma}2 with induced differentiation (38). Exposure of cultured human CRC cell lines to PPAR{gamma} agonists induces growth inhibition that is associated with a G1 cell cycle arrest (7), an increase in several markers of differentiation (39) and in apoptosis (40). In addition, PPAR{gamma} ligands have been shown to dramatically attenuate cytokine gene expression in colon cancer cell lines by inhibiting the activation of nuclear factor-kappa B, suggesting that PPAR{gamma}3 may also be important in modulating the intestinal inflammatory response (41). Examination of human CRC cells has revealed loss-of-function mutations in the PPAR{gamma} gene in 7% of tumors from 55 unrelated individuals (42). Collectively, these experimental studies have provided evidence for a putative role of PPAR{gamma}3 as a tumor suppressor in CRC. The association of the putative high-activity C allele with a lower risk of CRC in our study supports the hypothesis that a higher PPAR{gamma}3 activity in the colon also leads to enhanced antineoplastic and prodifferentiation effects in colonic epithelial cells.

A chief limitation of our study is a lack of information on the use of PPAR{gamma} agonists such as thiazolidinediones, a class of recently available drugs for the treatment of diabetes mellitus. These drugs may potentially intensify the effects of PPAR{gamma}. We have shown that our results on PPAR{gamma}2 and risk were independent of the subjects' self-reported history of diabetes mellitus, and remained unchanged after exclusion of subjects with a history of diabetes, thus suggesting that the use of these drugs was not a significant confounder. Another limitation of the present study was lower statistical power due to small sample size, especially when we examined the genotype–CRC risk association in stratified analyses. The present study had a 73% statistical power to detect a 50% risk reduction in CRC among subjects with the PPAR{gamma}2 CG and GG genotypes, and a 59% statistical power to detect a 30% risk reduction associated with the PPAR{gamma}3 GC or CC genotypes. When PPAR{gamma}2 and PPAR{gamma}3 genotypes were combined, the present study had sufficient power (>80%) to detect a statistically significant trend in the risk of developing colon (minimal detectable OR = 0.36) or rectal cancer (minimal detectable OR = 0.32) alone or CRC combined (minimal detectable OR = 0.43).

The current study has several strengths. Singapore is a small city-state where there is good access to specialized medical care. The nationwide cancer registry has been in place since 1968 and has been shown to be comprehensive in its recording of cancer cases (43). Thus, CRC case ascertainment can be assumed to be complete. Our study subjects originated from two contiguous regions in South China, leading to a high degree of genetic homogeneity. All dietary factors, measurement of BMI and history of diabetes mellitus were assessed prior to cancer diagnosis and, thus, can be presumed to be free of recall bias (17).

In summary, the present study implicates a role for PPAR{gamma} in CRC. These findings may have clinical implications. One may target the PPAR{gamma} activation pathway in drug development efforts as part of prevention and treatment strategies for CRC.


   Acknowledgments
 
We thank Ms Siew-Hong Low of the National University of Singapore for supervising the field work of the Singapore Chinese Health Study and Ms Kazuko Arakawa of the University of Southern California for the development and management of the cohort study database. We also thank the Singapore Cancer Registry for assistance with the identification of cancer outcomes. This work was supported by grants R01 CA55069, R35 CA53890, R01 CA80205 and R01 CA98497 from the United States National Cancer Institute, Bethesda, MD.

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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Received November 23, 2005; revised January 31, 2006; accepted February 21, 2006.


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