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Genome-wide association studies have identified 8q24 region variants as risk factors for prostate cancer. In the Agricultural Health Study, a prospective study of licensed pesticide applicators, we observed increased prostate cancer risk with specific pesticide use among those with a family history of prostate cancer. Thus, we evaluated the interaction between pesticide use, 8q24 variants and prostate cancer risk. The authors estimated odds ratios (ORs) and 95% confidence intervals (CIs) for interactions between 211 8q24 variants, 49 pesticides and prostate cancer risk in 776 cases and 1,444 controls. The ORs for a previously identified variant, rs4242382, and prostate cancer increased significantly (p<0.05) with exposure to the organophosphate insecticide, fonofos, after correction for multiple testing, per allele ORnonexposed= 1.17 (95% CI: 0.93, 1.48), per allele ORlow=1.30 (95% CI: 0.75, 2.27), per allele ORhigh=4.46 (95% CI: 2.17, 9.17), p-interaction=0.002, adjusted p-interaction = 0.02. Similar effect modification was observed for three other organophosphate insecticides, coumaphos, terbufos, and phorate and one pyrethroid insecticide, permethrin. Among ever users of fonofos, subjects with 3 or 4 risk alleles at rs7837328 and rs4242382 had approximately 3 times the risk of prostate cancer (OR=3.14 95% CI: 1.41, 7.00) compared with subjects who had zero risk alleles and never used fonofos. We observed a significant interaction between variants on chromosome 8q24, pesticide use, and risk of prostate cancer. Insecticides, particularly organophosphates, were the strongest modifiers of risk, although the biologic mechanism is unclear. This is the first report of effect modification between 8q24 and an environmental exposure on prostate cancer risk.
Until recently, only increasing age, race/ethnicity, and family history have been established as risk factors for prostate cancer. (1) Genome-wide association studies (GWAS) have identified several independent loci on chromosome 8q24 as additional risk factors for prostate cancer. Single nucleotide polymorphisms (SNPs) in four regions of 8q24 (2, 3), including several SNPs in region 2, rs45114 and rs620861 in region 4, rs6983267 in region 3, and rs1447295 and rs4242382 in region 1 were associated with prostate cancer. (3–11) These variants are located in a region with no known protein-coding genes, and thus the mechanism by which they confer greater prostate cancer susceptibility is unclear. Approximately 200 kb from the nearest prostate GWAS locus is the c-myc oncogene (MYC), which has a well established role in carcinogenesis. (12, 13) However, it is still unclear whether 8q24 variants act to influence MYC expression or other yet undetermined biological processes. (14–16) Additional clues to the genetic susceptibility of prostate cancer may be gained from evaluating the interaction of the 8q24 region with environmental exposures and risk for prostate cancer.
The Agricultural Health Study (AHS) is a prospective cohort of licensed private and commercial pesticide applicators in Iowa and North Carolina, with in-depth characterization of lifetime mixing, loading and application of pesticides. We have previously reported that men in this cohort of pesticide applicators have a higher risk of prostate cancer than men in the general population of Iowa and North Carolina (private applicators SIR (standardized incidence ratio) = 1.24, 95% CI (confidence interval): 1.18–1.33 and commercial applicators SIR = 1.37, 95% CI: 0.98–1.86). (17, 18) Previous analyses within the cohort have shown that the use of chlorinated pesticides and the use of the fumigant methyl bromide were associated with increased risk of prostate cancer. (19) Further, among those pesticide applicators with a family history of prostate cancer, we have observed significant (p<0.05) exposure-response associations with four widely-used organophosphate (OP) insecticides (chlorpyrifos, fonofos, phorate, and coumaphos), one pyrethroid insecticide (permethrin), and a thiocarbamate herbicide (butylate). These associations were not observed among those without a family history of disease. (19–23) Thus, these findings suggest that genetic determinants may interact with pesticide exposures experienced by agricultural workers to alter prostate cancer risk.
In this study we evaluated the interaction between pesticide use, genetic variation on chromosome 8q24, and risk of prostate cancer in 2,220 AHS subjects.
Genotyping of prostate cancer cases and controls using buccal cell DNA was performed at NCI’s Core Genotyping Facility, using the Custom InfiniumR BeadChip Assays (iSelect™) from Illumina Inc. as part of an array of 26,512 SNPs. For the 8q24 region encompassing >660 kb including chr8:128,232,156 – 128,816,653, tag SNPs were selected from HapMap CEU using common SNPs (minor allele frequency ≥ 5%) and an r2 threshold > 0.80. Tag SNPs were determined using a modified version of the method described by Carlson et al. (24) as implemented in the GLU software package. (25) The tagged region includes SNPs telomeric to the prostate cancer associated region 2 through the region associated with bladder cancer (26) to ~1kb 5′ of MYC for a total of 211 SNPs. Blinded duplicate samples (2%) were also included and concordance of these samples ranged from 96–100%. The overall genotyping rate was between 97.5% and 100% in the 8q24 region SNPs.
The AHS is a prospective cohort study that includes 57,310 licensed pesticide applicators in Iowa and North Carolina. Applicators were recruited from 1993 through 1997; a detailed description of this cohort has been previously published. (27) During a follow-up telephone interview conducted in 1999–2003, applicators were asked to provide a mouthwash rinse sample for extraction of DNA from buccal cells. Informed consent was obtained and the study protocol was reviewed by all relevant Institutional Review Boards. Approximately 72% of responding applicators returned a sample. Subjects diagnosed with incident prostate cancer between 1993 and 2004 who also provided a buccal cell sample were included in the current nested-case-control study. In addition, applicators with incident prostate cancer that did not return a sample at follow-up and met inclusion criteria for the current study were asked separately to provide a mouthwash rinse sample, with 307/561 (55%) returning a sample. Cancer cases were coded using the International Classification of Diseases for Oncology, 2nd edition, and stage (local, regional, distant, unstaged) and grade (well differentiated, moderately differentiated, poorly differentiated, undifferentiated, missing) were abstracted by the state cancer registries in Iowa and North Carolina. Controls were male applicators who provided buccal cell material, were alive at the time of case diagnosis, and had no previous cancer diagnosis except non-melanoma skin cancer. Eligible controls were frequency matched 2:1 to cases by date of birth (+/− 1 year) and were not lost to follow-up at the time of case diagnosis. All subjects for the nested case-control study are Caucasian. Based on these inclusion criteria, 841 cases (66% of total Caucasian cases as of 2004) and 1,659 controls (total N= 2,500) were identified. Due to genotyping space limitations 164 controls, with the lowest DNA mass, were excluded. Of the remaining samples, 108 were removed due to insufficient or poor DNA quality (N=20; 14 cases, 6 controls) or <90% completion rate (more than 10% of the SNP assays failed for a given sample, N=88; 47 cases, 41 controls).
To explore the underlying genetic structure of the population, we identified 2,563 autosomal SNPs from the genotyping panel with low local background linkage disequilibrium (pair-wise r2 <0.01 measured in the AHS samples for any pairs less than 500 kb apart) using the algorithm described by Yu et al. (28) This set of SNPs was used for population substructure evaluation. Using STRUCTURE (29), we identified three subjects with substantial non-European ancestry (with less than 80% European admixture coefficients). We further identified 5 additional subjects using principal component analysis (PCA) (30) that were outliers in the first 2 axes of variation (i.e., more than 10 standard deviations from the mean on either of top two axes). After removing those subjects, we had a final sample size of 776 cases and 1,444 controls. We conducted another PCA analysis on these 2,220 subjects, and found that case/control status was distributed evenly (the Wilcoxon rank-sum test p-value larger than 0.1) on each of the top five major principal components. Thus, there was no evidence of strong population stratification and we did not adjust for population stratification in our analysis.
Unconditional logistic regression was used to estimate odds ratios (ORs) and 95% CIs for the association between 8q24 SNPs and prostate cancer and the interaction between SNPs in 8q24, pesticide use and prostate cancer risk. Genotypes were coded as counts of the risk allele assuming a log-additive model. Exposure to pesticides was classified from responses to two self-administered questionnaires that were administered at enrollment. These questionnaires collected comprehensive data on lifetime use of 49 pesticides (18 herbicides, 21 insecticides, 4 fumigants, and 6 fungicides). Participants were asked how many years they applied each chemical (1 year or less, 2–5, 6–10, 11–20, 21–30, or more than 30 years) and how many days it was personally used in an average year (less than 5, 5–9, 10–19, 20–39, 40–59, 60–150, or more than 150 days). Pesticides were categorized as either ever/never use and by lifetime exposure days [years of use × days per year] in this analysis from AHS data release version P1REL0712.04. Lifetime exposure days were categorized as nonexposed, low, and high exposed to a given chemical using the median cut-point based on distribution of lifetime days among cases and controls together for each chemical. Previously reported GWAS SNPs and those with a main effect of p<0.01 were evaluated for interaction. SNP-pesticide interactions were examined using a multiplicative model. The p-value for each SNP-pesticide interaction was computed by comparing nested models with and without the cross-product terms using a likelihood ratio test. SNP-pesticide (ever/never) interactions with p-interaction<0.20 were carried further for exploration with expanded pesticide categories (nonexposed, low, high). All models were adjusted for age (10 yr-intervals) and state of residence (Iowa or North Carolina). Because GWAS have identified variants in regions 3 and 1 to have independent effects on prostate cancer, we also decided to explore whether a combination of risk alleles in these two independent regions further increased risk of prostate cancer in the presence of exposure. Additional factors that were examined but ultimately not considered in the modeling because they did not change point estimates by more than 10% were family history of prostate cancer in first degree relative (no, yes, missing), type of applicator (private or commercial), and other pesticide adjustment based on the correlations between selected pesticides. We were not able to explore aggressive prostate cancer (distant and poorly differentiated) alone due to small numbers.
In order to take into account the large number of tests performed, the number of effective tests, Meff, was calculated for the 15 8q24 SNPs carried forward for interaction analyses by use of the SNP Spectral Decomposition approach (31) and p-values adjusted for multiple testing were calculated using the region Meff value of 11. This correction is similar to a Bonferroni correction (assumes independence) but takes into account the correlation between SNPs, which are not all independent. We considered each chemical as independent. All statistical tests were two-sided and interactions were considered to be significant if the adjusted p-interaction values were less than p<0.05 (after correction for multiple tests). All p-value presented represent uncorrected p-values unless otherwise stated.
Similar to the characteristics of the whole cohort, applicators in this nested case-control study tended to be private applicators and were predominantly from Iowa (Table 1). Cases selected for the nested case-control study were similar to all prostate cancer cases from the cohort in age, state of residence, applicator type, presence of familial prostate cancer, and in prostate cancer disease characteristics. Cases tended to have a higher proportion of first degree relatives with a family history of prostate cancer compared with controls (16.7% vs. 10.0%) and 57.8% of prostate cancers were diagnosed while the cancer is still confined to the primary site (local). A list of all 49 pesticides, their prevalence, and the median level of lifetime days of exposure to each chemical is presented in Supplemental Table 1.
Of the 211 SNPs evaluated, 12 were associated with prostate cancer at the p<0.01 level, and three SNPs previously reported by GWAS of prostate cancer were associated with prostate cancer at the p<0.05 level (Table 2). GWAS SNPs in region 3 (rs6983267) and region 1 (rs4242382) were associated with prostate cancer, OR=1.23 (95% CI: 1.09, 1.40), p-trend=1.02 × 10−3 and OR=1.35 (95% CI: 1.11, 1.64), p-trend=2.28 × 10−3 respectively. Several other SNPs in region 1 showed similar associations and were highly correlated (r2=0.74–0.99) with rs4242382. Five additional SNPs in region 3 were associated with risk; however, not all were strongly correlated with the GWAS SNP rs6983267 (r2=0.06–0.94). SNPs rs445114 and rs620861 in region 4 and rs1447295 in region 1, were significant only at the p<0.05 level. One additional SNP, telomeric to region 1 and about 30 kb upstream of MYC, rs12547643, was also associated with prostate cancer. Main effect p-values for all 211 SNPs in 8q24 are shown in Supplemental Table 2.
All 15 8q24 SNPs associated with risk in Table 2 were examined for potential effect modification by pesticide use. Those interactions with a p for interaction <0.20 (based on pesticide defined as ever/never) and which showed an increasing trend in risk across strata are presented in Tables 3; 7 SNPs from Table 2 showed interactive effects. All other interactions p<0.20 are presented in Supplemental Table 3.
In region 1, the association between rs4242382 and prostate cancer was statistically significantly increased across strata of fonofos exposure, ORnonexposed= 1.17 (95% CI: 0.93, 1.48), ORlow=1.30 (95% CI: 0.75, 2.27), ORhigh=4.46 (95% CI: 2.17, 9.17), p-interaction=0.002, adjusted p-interaction=0.02 (Table 3). A similar exposure-response association was observed for terbufos, ORnonexposed= 1.13 (95% CI: 0.87, 1.47), ORlow=1.71 (95% CI: 1.07, 2.74), ORhigh=2.15 (95% CI: 1.32, 3.52), p-interaction=0.02 and to a lesser degree for phorate (p-interaction=0.26). A similar pattern was observed for the association between rs4242382 and prostate cancer across strata of permethrin exposure, ORnonexposed= 1.18 (95% CI: 0.94, 1.47), ORlow=1.66 (95% CI: 0.87, 3.18), ORhigh=2.73 (95% CI: 1.31, 5.69), p-interaction=0.03. Comparable associations were observed for other SNPs in region 1, which were highly correlated with rs4242382. After correction for multiple tests only those interactions with fonofos and region 1 variants remained statistically significant.
Several insecticides also modified the association between region 3 SNPs and prostate cancer risk. The association between rs7837328 and prostate cancer increased across strata of coumaphos exposure, ORnonexposed= 1.16 (95% CI: 1.01, 1.33), ORlow=1.26 (95% CI: 0.66, 2.42), ORhigh=3.02 (95% CI: 1.48, 6.16), p-interaction=0.02. Fonofos and terbufos exposure also appeared to modify the association between rs7837328 and prostate cancer although these interactions were not statistically significant, p-interaction=0.30 and 0.16, respectively. The association between several region 3 SNPs and prostate cancer increased across strata of methyl bromide and heptachlor exposure although these interactions were also not statistically significant, smallest p-interaction=0.27 and 0.24, respectively (Table 3). The interaction between toxaphene and rs10505476 was not significant, p-interaction= 0.07, although an interesting trend across strata was evident.
Six chemicals (diazinon, parathion, captan, chlordane, dieldrin, and metolachlor) appeared to modify the associations between rs12547643, which is telomeric to regions 3 and 1, and prostate cancer risk, although even those for captan and diazinon were not statistically significant after correction for multiple testing, p-interaction=0.01, p-interaction=0.007 respectively (Table 3). Additional adjustment for family history did not alter the risk estimates across strata for any chemical-SNP combination, and analyses among subjects with no family history of prostate cancer yielded similar results (data not shown). The correlations between the pesticides presented in Table 1 were modest (Pearson r2 range 0.01–0.42); adjustment for other pesticides in interaction models did not alter the risk estimates across strata for any chemical-SNP combination (data not shown).
Because rs7837328 and rs4242382 show the most consistent trends across exposure strata, the associations between joint categories of fonofos or terbufos exposure and the combination of rs7837328 and rs4242382 genotypes and prostate cancer risk were assessed and presented in Table 4. Among ever users of fonofos, subjects with 3 or 4 risk alleles had 3.14 times the risk of prostate cancer (95% CI: 1.41, 7.00) compared with subjects who had zero risk alleles and had never used fonofos. Among ever users of terbufos, subjects with 3 or 4 risk alleles had 3.15 times the risk of prostate cancer (95% CI: 1.65, 6.02), compared with subjects who had zero risk alleles and had never used terbufos.
In this nested case-control study the association between 8q24 SNPs and prostate cancer is modified by pesticide use. In particular, the association between rs4242382 and prostate cancer is increased across strata of fonofos, terbufos, and permethrin exposure. Furthermore, the joint effect of fonofos exposure and carriage of three or four risk alleles in rs7837328 and rs4242382 resulted in a 3-fold increased risk of prostate cancer risk compared to subjects who had zero risk alleles and had never used fonofos. The association between several region 3 SNPs and prostate cancer also appeared to be modified by several pesticides including coumaphos and permethrin, and increased risks associated with rs12547643 (telomeric to regions 3 and 1) across strata of other chemicals are also evident.
The observed associations for prostate cancer among 8q24 variants in our study are consistent with GWAS reports. Similar to several reports, we observed a stronger association for rs4242382 compared to rs1447295 in region 1 and risk of prostate cancer. (5, 6, 10) The independent risk marker rs6983267 in region 3 (9, 11) was also associated with prostate cancer, although other correlated variants in regions 3 showed stronger signals in our study. Additionally, the reported prostate cancer susceptibility loci rs445114 and rs620861 were also associated with prostate cancer risk, however, these were not among the strongest signals. Another locus, rs12547643, telomeric to regions 3 and 1, was found to be associated with prostate cancer in our study. This marker lies in a separate block of linkage disequilibrium from the other regions and is close to a marker, rs9642880, which has been associated with susceptibility to bladder cancer. (26) Although the association between rs9642880 and prostate cancer was not significant in our study (p-trend=0.153), the pairwise correlation between rs9642880 and rs12547643 is not negligible (r2=0.20). This variant however, has not been shown to be associated with prostate cancer in GWAS (p=0.77) (11), thus the observed association in our study may be due to chance. GWAS SNPs from region 2 were not genotyped in this study.
In the AHS we have observed the association between prostate cancer and pesticides to be modified by family history of prostate cancer (19), which could be a marker of genetic susceptibility. Some of the chemicals that are shown here to modify the association between 8q24 variants and prostate cancer have also been associated with prostate cancer among those with a family history in pesticide-specific analyses within the AHS (19–22), and include fonofos, phorate, coumaphos, and permethrin. Thus, we also explored whether family history of prostate cancer was related to 8q24 variants. Two studies have reported a potential association between region 1 SNPs, rs4242382 and rs1447295, and family history of prostate cancer, though both studies are noted to be underpowered due to the limited number of cases and controls with a family history of prostate cancer. (32, 33) Larger GWAS reports have reported no significant interaction between rs1447295 or rs6983267 and family history prostate cancer (9, 34) although not all GWAS loci have been evaluated. We did not observe an association between region 1 variants and family history of cancer. We did observe a greater proportion of subjects with risk alleles in region 3 variants among those with a family history (data not shown), however, the proportions among cases and controls were similar and adjustment for family history in all interaction models did not change the risk estimates. When we restricted analyses to those with no family history of prostate cancer all results persisted. Thus, the previously observed effect modification of family history on the association between pesticides and prostate cancer does not appear to be explained by variants on chromosome 8q24. It is possible that other genes, multiple genes, or non-genetic factors that track in families might account for this previously observed association.
Several pesticides of similar chemical structure were observed to modify the association between 8q24 SNPs and prostate cancer. The organophosphate insecticides, coumaphos, fonofos, phorate, and terbufos consistently modified the association between regions 3 and 1 SNPs and prostate cancer. The strongest association is for fonofos where the risk of prostate cancer was over three times as likely per rs4242382 risk allele among high users. Among ever users of fonofos, subjects with 3 or 4 risk alleles in rs7837328 and rs4242382 had 3.14 times the risk of prostate cancer compared with subjects who had zero risk alleles and had never used fonofos. Previous analyses revealed the strongest effect modification for any particular pesticide and family history was for fonofos. (21) Thus, the risk of prostate cancer among fonofos users may be especially important among genetically susceptible subgroups. Ten OP chemicals were examined and results for coumaphos, phorate, and terbufos were similar to those observed for fonofos although not statistically significant. Fonofos, coumaphos, phorate, and terbufos are all classified by the U.S. Environmental Protection Agency as Group E for carcinogenicity (evidence of non-carcinogenicity for humans) based on the absence of mutagenic, genotoxic, and carcinogenic observations in limited experimental and animal tests. (35) In 1998, the registrant of fonofos voluntarily cancelled its registration (36) while the other OPs are still in widespread agricultural use.
Although interactions were not statistically significant after correction for multiple testing, several other pesticides appeared to modify the association between 8q24 SNPs and prostate cancer. The increasing pattern of risk across permethrin exposure strata is similar to that observed for the four OPs, possibly due to the fact that it is also an insecticide, although not all insecticides examined modified risk. Several other compounds with chlorine substituents including captan, chlordane, dieldrin, and metolachlor appeared to modify risk with rs12547643 (telomeric to regions 3 and 1). We have previously reported that AHS applicators over the age of 50 who used chlorinated pesticides had an increased risk of prostate cancer. (19) It is unclear whether the chlorinated components of these chemicals are relevant to risk or whether this SNP is truly associated with prostate cancer. Thus, it is possible that these trends across strata may be due to chance.
While some similar chemicals were observed to interact with the 8q24 region suggesting a common biological mechanism of action, the precise mechanism is unclear. Little is known overall about whether or how pesticides may be associated with cancer; however, substantial literature documents the principal involvement of phase I and phase II enzymes in the metabolism of specific xenobiotic substrates, including pesticides. (37, 38) Most organophosphate insecticides (including coumaphos, terbufos, fonofos, and phorate) must be activated to their oxon (potent cholinesterase inhibitors) to be excreted. The oxon form of these compounds has been associated with a number of biological endpoints including neurotoxicity, the generation of reactive oxygen species, and DNA damage. (39) Currently however, there is no evidence to suggest that variation in the 8q24 region impacts xenobiotic metabolism. Other evidence indicates that at least one of the 8q24 variants resides in an androgen receptor transcriptional enhancer site, suggesting a potential hormone-related mechanism. (40)
Recent studies have explored whether 8q24 variants might be related to the nearest coding region, the MYC gene and its expression. Two studies show that rs6983267 is located in a transcriptional enhancer and affects a binding site for TCF4, a transcription factor which interacts with β-catenin to activate transcription of Wnt target genes. (15, 16) It was also demonstrated that a DNA restriction fragment containing rs6983267 physically interacts with the MYC promoter in colorectal cancer cell lines. (16) Imbalances in Wnt-mediated regulation of MYC are associated with altered cellular adhesion, proliferation, and differentiation. (12, 13, 41) In addition, experimental animal studies have also shown that Wnt signaling can be altered upon exposure to OPs (42) and chlorinated pesticides (43, 44) and that pesticides can influence MYC expression as well. (45–47) Thus, this may be a potential mechanism by which genetic variation in 8q24 modifies the risk associated with pesticide use and suggests a role for enhanced alterations in important global cancer signaling pathways.
Several strengths and limitations of our study should be recognized. High quality genotype and pesticide information is available in the AHS. For many gene-exposure studies, the key limitation is the quality of the exposure information. The information on pesticide use among AHS participants is superior to any other epidemiologic studies of cancer. This is because farmers are aware of the type and duration of pesticides they use as these are often restricted use chemicals for which a license is required; self-reported pesticide use information has been found to be reliable in this cohort. (48, 49) Furthermore, the ability of the AHS to look at individual pesticides rather than groups (herbicides or insecticides or chemical classes) is critical because observed cancer risks appear to be chemical-specific. Under this premise, we chose to treat each pesticide as independent in the multiple comparison correction which results in a less conservative correction. Thus, the highlighted results for fonofos interactions, like all the interactions presented in this study, would need to be confirmed to see if they are truly important for prostate cancer. In addition, the numbers within some pesticide use strata were small, however, to our knowledge there are no other studies with more power to examine this interaction. Also, we were not able to examine disease aggressiveness due to small numbers. Finally, subjects in this study were all Caucasian, which limits the generalizability of the results to other racial/ethnic groups.
In conclusion, we observed an interaction between variants on chromosome 8q24, pesticide use, and risk of prostate cancer. Insecticides, particularly several organophosphates, appear to be the strongest modifiers of risk. This is the first report of effect modification between an 8q24 region variant and environmental exposure on prostate cancer risk. These results need to be subjected to replication due to the high probability of false positive results from the multiple tests of interaction. Opportunities for replication, however, are currently limited because of the lack of comparable agricultural populations with sufficient sample size, detailed information on pesticide use, as well as DNA for genetic analyses. We continue, however, to look for possible studies in which to replicate these findings. Further research should continue to explore the possible mechanism or mechanisms for pesticide induced prostate carcinogenesis because if the current interactions are indeed true, this could provide critical new information about a previously unsuspected biological pathway through which prostate carcinogenesis occurs. Similarly, mechanistic studies that help identify the role of the 8q24 region on prostate cancer risk may also offer critical new clues to help explain prostate carcinogenesis.
This research was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119) and National Institute of Environmental Health Sciences (Z01ES049030). We thank the participants in the Agricultural Health Study for their contributions in support of this research.