Estimating cumulative spatial risk over time with low-rank kriging multiple membership models.

Many health outcomes result from accumulated exposures to one or more environmental factors. Accordingly, spatial risk studies have begun to consider multiple residential locations of participants, acknowledging that participants move and thus are exposed to environmental factors in several places. However, novel methods are needed to estimate cumulative spatial risk for disease while accounting for other risk factors. To this end, we propose a Bayesian model (LRK-MMM) that embeds a multiple membership model (MMM) into a low-rank kriging (LRK) model in order to estimate cumulative spatial risk at the point level while allowing for multiple residential locations per subject. The LRK approach offers a more computationally efficient means to analyze spatial risk in case-control study data at the point level compared with a Bayesian generalized additive model, and as increased precision in spatial risk estimates by analyzing point locations instead of administrative areas. Through a simulation study, we demonstrate the efficacy of the model and its improvement upon an existing multiple membership model that uses area-level spatial random effects to estimate risk. The results show that our proposed method provides greater spatial sensitivity (improvements ranging from 0.12 to 0.54) and power (improvements ranging from 0.02 to 0.94) to detect regions of elevated risk for disease across a range of exposure scenarios. Finally, we apply our model to case-control data from the New England bladder cancer study to estimate cumulative spatial risk while adjusting for many covariates.

Diet quality, common genetic polymorphisms, and bladder cancer risk in a New England population-based study.

PURPOSE: We examined the interaction between common genetic bladder cancer variants, diet quality, and bladder cancer risk in a population-based case-control study conducted in New England. METHODS: At the time of enrollment, 806 bladder cancer cases and 974 controls provided a DNA sample and completed a diet history questionnaire. Diet quality was assessed using the 2010 Alternate Healthy Eating Index (AHEI-2010) score. Single nucleotide polymorphisms (SNPs) reported in genome-wide association studies to be associated with bladder cancer risk were combined into a polygenic risk score and also examined individually for interaction with the AHEI-2010. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression. RESULTS: A 1-standard deviation increase in polygenic risk score was associated with higher bladder cancer risk (OR, 1.34; 95% CI 1.21-1.49). Adherence to the AHEI-2010 was not associated with bladder cancer risk (OR, 0.99; 95% CI 0.98-1.00) and the polygenic risk score did not appear to modify the association between the AHEI-2010 and bladder cancer risk. In single-SNP analyses, rs8102137 (bladder cancer risk allele, C) modified the association between the AHEI-2010 total score and bladder cancer risk, with the strongest evidence for the AHEI-2010 long chain fat guideline (OR for TT, 0.92; 95% CI 0.87-0.98; OR for CT, 1.02; 95% CI 0.96-1.08; OR for CC, 1.03; 95% CI 0.93-1.14; p for interaction, 0.02). CONCLUSIONS: In conclusion, rs8102137 near the cyclin E1 gene ( CCNE1 ) may be involved in gene-diet interactions for bladder cancer risk.

Bladder cancer risk associated with family history of cancer.

Twin studies suggest a familial aggregation of bladder cancer, but elements of this increased familial risk of bladder cancer are not well understood. To characterize familial risk of bladder cancer, we examined the relationship between family history of bladder and other types of cancer among first-degree relatives and risk of bladder cancer in 1193 bladder cancer cases and 1418 controls in a large population-based case-control study. Multivariate logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between family history of bladder cancer (defined as at least one first-degree family member with bladder cancer or a cancer of any other site). We also evaluated cancer aggregation of specific sites in family members. Participants with a first-degree relative with bladder cancer had nearly double the risk of bladder cancer (OR = 1.8, 95% CI 1.2-2.9) as those without a family history of bladder cancer. Risk was increased for having a sibling with bladder cancer (OR = 2.6, 95% CI 1.3-5.3) compared to no siblings with cancer. Bladder cancer risk was elevated when participants reported a first-degree relative with a history of female genital cancer (OR = 1.5, 95% CI 1.1-2.1), melanoma (OR = 1.9, 95% CI 1.02-3.6), and tobacco-associated cancer (OR = 1.3, 95% CI 1.06-1.6). These findings add to evidence of a familial predisposition to bladder cancer. Clarification of the aggregation of bladder cancer in families and with other cancer sites will be of interest as many loci and common polymorphisms related to bladder cancer have yet to be identified in large genomic studies.

Ingested Nitrate and Nitrite and Bladder Cancer in Northern New England.

BACKGROUND: N-nitroso compounds are hypothesized human bladder carcinogens. We investigated ingestion of N-nitroso compound precursors nitrate and nitrite from drinking water and diet and bladder cancer in the New England Bladder Cancer Study. METHODS: Using historical nitrate measurements for public water supplies and measured and modeled values for private wells, as well as self-reported water intake, we estimated average nitrate concentrations (mg/L NO3-N) and average daily nitrate intake (mg/d) from 1970 to diagnosis/reference date (987 cases and 1,180 controls). We estimated overall and source-specific dietary nitrate and nitrite intakes using a food frequency questionnaire (1,037 cases and 1,225 controls). We used unconditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI). We evaluated interactions with factors that may affect N-nitroso compound formation (i.e., red meat, vitamin C, smoking), and with water intake. RESULTS: Average drinking water nitrate concentration above the 95th percentile (>2.07 mg/L) compared with the lowest quartile (≤0.21 mg/L) was associated with bladder cancer (OR = 1.5, 95% CI = 0.97, 2.3; P trend = 0.01); the association was similar for average daily drinking water nitrate intake. We observed positive associations for dietary nitrate and nitrite intakes from processed meat (highest versus lowest quintile OR for nitrate = 1.4, 95% CI = 1.0, 2.0; P trend = 0.04; OR for nitrite = 1.5, 95% CI = 1.0, 2.1; P trend = 0.04, respectively), but not other dietary sources. We observed positive interactions between drinking water nitrate and red meat (P-interaction 0.05) and processed red meat (0.07). CONCLUSIONS: Our results suggest the importance of both drinking water and dietary nitrate sources as risk factors for bladder cancer.

Validity of retrospective occupational exposure estimates of lead and manganese in a case-control study.

OBJECTIVES: The validity of surrogate measures of retrospective occupational exposure in population-based epidemiological studies has rarely been evaluated. Using toenail samples as bioindicators of exposure, we assessed whether work tasks and expert assessments of occupational metal exposure obtained from personal interviews were associated with lead and manganese concentrations. METHODS: We selected 609 controls from a case-control study of bladder cancer in New England who had held a job for ≥1 year 8-24 months prior to toenail collection. We evaluated associations between toenail metal concentrations and five tasks extracted from occupational questionnaires (grinding, painting, soldering, welding, working near engines) using linear regression models. For 139 subjects, we also evaluated associations between the toenail concentrations and exposure estimates from three experts. RESULTS: We observed a 1.9-fold increase (95% CI 1.4 to 2.5) in toenail lead concentrations with painting and 1.4-fold increase (95% CI 1.1 to 1.7) in manganese concentrations with working around engines and handling fuel. We observed significant trends with increasing frequency of both activities. For lead, significant trends were observed with the ratings from all three experts. Their average ratings showed the strongest association, with subjects rated as possibly or probably exposed to lead having concentrations that were 2.0 and 2.5 times higher, respectively, than in unexposed subjects (ptrend <0.001). Expert estimates were only weakly associated with manganese toenail concentrations. CONCLUSIONS: Our findings support the ability of experts to identify broad contrasts in previous occupational exposure to lead. The stronger associations with task frequency and expert assessments support using refined exposure characterisation whenever possible.

Potential effect modifiers of the arsenic-bladder cancer risk relationship.

Populations exposed to arsenic in drinking water have an increased bladder cancer risk and evidence suggests that several factors may modify arsenic metabolism, influencing disease risk. We evaluated whether the association between cumulative lifetime arsenic exposure from drinking water and bladder cancer risk was modified by factors that may impact arsenic metabolism in a population-based case-control study of 1,213 cases and 1,418 controls. Unconditional logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for the association between cumulative arsenic intake and bladder cancer stratified by age, sex, smoking status, body mass index (BMI), alcohol consumption and folate intake. P-values for interaction were computed using a likelihood ratio test. We observed no statistically significant multiplicative interactions although some variations in associations were notable across risk factors, particularly for smoking and BMI. Among former smokers and current smokers, those with the highest cumulative arsenic intake had elevated risks of bladder cancer (OR = 1.4, 95% CI: 0.96-2.0 and OR = 1.6, 95% CI: 0.91-3.0, respectively; while the OR among never smokers was 1.1, 95% CI: 0.6-1.9, p-interaction = 0.49). Among those classified as normal or overweight based on usual adult BMI, the highest level of cumulative arsenic intake was associated with elevated risks of bladder cancer (OR = 1.3, 95% CI: 0.89-2.0 and OR = 1.6, 95% CI: 1.1-2.4, respectively), while risk was not elevated among those who were obese (OR = 0.9, 95% CI: 0.4-1.8) (p-interaction = 0.14). Our study provides some limited evidence of modifying roles of age, sex, smoking, BMI, folate and alcohol on arsenic-related bladder cancer risk that requires confirmation in other, larger studies.

Identification and replication of the interplay of four genetic high-risk variants for urinary bladder cancer.

Little is known whether genetic variants identified in genome-wide association studies interact to increase bladder cancer risk. Recently, we identified two- and three-variant combinations associated with a particular increase of bladder cancer risk in a urinary bladder cancer case-control series (Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), 1501 cases, 1565 controls). In an independent case-control series (Nijmegen Bladder Cancer Study, NBCS, 1468 cases, 1720 controls) we confirmed these two- and three-variant combinations. Pooled analysis of the two studies as discovery group (IfADo-NBCS) resulted in sufficient statistical power to test up to four-variant combinations by a logistic regression approach. The New England and Spanish Bladder Cancer Studies (2080 cases and 2167 controls) were used as a replication series. Twelve previously identified risk variants were considered. The strongest four-variant combination was obtained in never smokers. The combination of rs1014971[AA] near apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A) and chromobox homolog 6 (CBX6), solute carrier family 1s4 (urea transporter), member 1 (Kidd blood group) (SLC14A1) exon single nucleotide polymorphism (SNP) rs1058396[AG, GG], UDP glucuronosyltransferase 1 family, polypeptide A complex locus (UGT1A) intron SNP rs11892031[AA] and rs8102137[CC, CT] near cyclin E1 (CCNE1) resulted in an unadjusted odds ratio (OR) of 2.59 (95% CI = 1.93-3.47; P = 1.87 × 10-10), while the individual variant ORs ranged only between 1.11 and 1.30. The combination replicated in the New England and Spanish Bladder Cancer Studies (ORunadjusted = 1.60, 95% CI = 1.10-2.33; P = 0.013). The four-variant combination is relatively frequent, with 25% in never smoking cases and 11% in never smoking controls (total study group: 19% cases, 14% controls). In conclusion, we show that four high-risk variants can statistically interact to confer increased bladder cancer risk particularly in never smokers.

Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies.

BACKGROUND: Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we developed an algorithm called SOCcer (Standardized Occupation Coding for Computer-assisted Epidemiologic Research) to assign SOC-2010 codes based on free-text job description components. METHODS: Job title and task-based classifiers were developed by comparing job descriptions to multiple sources linking job and task descriptions to SOC codes. An industry-based classifier was developed based on the SOC prevalence within an industry. These classifiers were used in a logistic model trained using 14 983 jobs with expert-assigned SOC codes to obtain empirical weights for an algorithm that scored each SOC/job description. We assigned the highest scoring SOC code to each job. SOCcer was validated in 2 occupational data sources by comparing SOC codes obtained from SOCcer to expert assigned SOC codes and lead exposure estimates obtained by linking SOC codes to a job-exposure matrix. RESULTS: For 11 991 case-control study jobs, SOCcer-assigned codes agreed with 44.5% and 76.3% of manually assigned codes at the 6-digit and 2-digit level, respectively. Agreement increased with the score, providing a mechanism to identify assignments needing review. Good agreement was observed between lead estimates based on SOCcer and manual SOC assignments (κ 0.6-0.8). Poorer performance was observed for inspection job descriptions, which included abbreviations and worksite-specific terminology. CONCLUSIONS: Although some manual coding will remain necessary, using SOCcer may improve the efficiency of incorporating occupation into large-scale epidemiological studies.

Combining Decision Rules from Classification Tree Models and Expert Assessment to Estimate Occupational Exposure to Diesel Exhaust for a Case-Control Study.

OBJECTIVES: To efficiently and reproducibly assess occupational diesel exhaust exposure in a Spanish case-control study, we examined the utility of applying decision rules that had been extracted from expert estimates and questionnaire response patterns using classification tree (CT) models from a similar US study. METHODS: First, previously extracted CT decision rules were used to obtain initial ordinal (0-3) estimates of the probability, intensity, and frequency of occupational exposure to diesel exhaust for the 10 182 jobs reported in a Spanish case-control study of bladder cancer. Second, two experts reviewed the CT estimates for 350 jobs randomly selected from strata based on each CT rule's agreement with the expert ratings in the original study [agreement rate, from 0 (no agreement) to 1 (perfect agreement)]. Their agreement with each other and with the CT estimates was calculated using weighted kappa (κ w) and guided our choice of jobs for subsequent expert review. Third, an expert review comprised all jobs with lower confidence (low-to-moderate agreement rates or discordant assignments, n = 931) and a subset of jobs with a moderate to high CT probability rating and with moderately high agreement rates (n = 511). Logistic regression was used to examine the likelihood that an expert provided a different estimate than the CT estimate based on the CT rule agreement rates, the CT ordinal rating, and the availability of a module with diesel-related questions. RESULTS: Agreement between estimates made by two experts and between estimates made by each of the experts and the CT estimates was very high for jobs with estimates that were determined by rules with high CT agreement rates (κ w: 0.81-0.90). For jobs with estimates based on rules with lower agreement rates, moderate agreement was observed between the two experts (κ w: 0.42-0.67) and poor-to-moderate agreement was observed between the experts and the CT estimates (κ w: 0.09-0.57). In total, the expert review of 1442 jobs changed 156 probability estimates, 128 intensity estimates, and 614 frequency estimates. The expert was more likely to provide a different estimate when the CT rule agreement rate was <0.8, when the CT ordinal ratings were low to moderate, or when a module with diesel questions was available. CONCLUSIONS: Our reliability assessment provided important insight into where to prioritize additional expert review; as a result, only 14% of the jobs underwent expert review, substantially reducing the exposure assessment burden. Overall, we found that we could efficiently, reproducibly, and reliably apply CT decision rules from one study to assess exposure in another study.

Is the inverse association between selenium and bladder cancer due to confounding by smoking?

Selenium has been linked to a reduced risk of bladder cancer in some studies. Smoking, a well-established risk factor for bladder cancer, has been associated with lower selenium levels in the body. We investigated the selenium-bladder cancer association in subjects from Maine, New Hampshire, and Vermont in the New England Bladder Cancer Case-Control Study. At interview (2001-2005), participants provided information on a variety of factors, including a comprehensive smoking history, and submitted toenail samples, from which we measured selenium levels. We estimated odds ratios and 95% confidence intervals among 1,058 cases and 1,271 controls using logistic regression. After controlling for smoking, we saw no evidence of an association between selenium levels and bladder cancer (for fourth quartile vs. first quartile, odds ratio (OR) = 0.98, 95% confidence interval (CI): 0.77, 1.25). When results were restricted to regular smokers, there appeared to be an inverse association (OR = 0.76, 95% CI: 0.58, 0.99); however, when pack-years of smoking were considered, this association was attenuated (OR = 0.91, 95% CI: 0.68, 1.20), indicating potential confounding by smoking. Despite some reports of an inverse association between selenium and bladder cancer overall, our results, combined with an in-depth evaluation of other studies, suggested that confounding from smoking intensity or duration could explain this association. Our study highlights the need to carefully evaluate the confounding association of smoking in the selenium-bladder cancer association.

Comparison of ordinal and nominal classification trees to predict ordinal expert-based occupational exposure estimates in a case-control study.

OBJECTIVES: To evaluate occupational exposures in case-control studies, exposure assessors typically review each job individually to assign exposure estimates. This process lacks transparency and does not provide a mechanism for recreating the decision rules in other studies. In our previous work, nominal (unordered categorical) classification trees (CTs) generally successfully predicted expert-assessed ordinal exposure estimates (i.e. none, low, medium, high) derived from occupational questionnaire responses, but room for improvement remained. Our objective was to determine if using recently developed ordinal CTs would improve the performance of nominal trees in predicting ordinal occupational diesel exhaust exposure estimates in a case-control study. METHODS: We used one nominal and four ordinal CT methods to predict expert-assessed probability, intensity, and frequency estimates of occupational diesel exhaust exposure (each categorized as none, low, medium, or high) derived from questionnaire responses for the 14983 jobs in the New England Bladder Cancer Study. To replicate the common use of a single tree, we applied each method to a single sample of 70% of the jobs, using 15% to test and 15% to validate each method. To characterize variability in performance, we conducted a resampling analysis that repeated the sample draws 100 times. We evaluated agreement between the tree predictions and expert estimates using Somers' d, which measures differences in terms of ordinal association between predicted and observed scores and can be interpreted similarly to a correlation coefficient. RESULTS: From the resampling analysis, compared with the nominal tree, an ordinal CT method that used a quadratic misclassification function and controlled tree size based on total misclassification cost had a slightly better predictive performance that was statistically significant for the frequency metric (Somers' d: nominal tree = 0.61; ordinal tree = 0.63) and similar performance for the probability (nominal = 0.65; ordinal = 0.66) and intensity (nominal = 0.65; ordinal = 0.65) metrics. The best ordinal CT predicted fewer cases of large disagreement with the expert assessments (i.e. no exposure predicted for a job with high exposure and vice versa) compared with the nominal tree across all of the exposure metrics. For example, the percent of jobs with expert-assigned high intensity of exposure that the model predicted as no exposure was 29% for the nominal tree and 22% for the best ordinal tree. CONCLUSIONS: The overall agreements were similar across CT models; however, the use of ordinal models reduced the magnitude of the discrepancy when disagreements occurred. As the best performing model can vary by situation, researchers should consider evaluating multiple CT methods to maximize the predictive performance within their data.

Using hierarchical cluster models to systematically identify groups of jobs with similar occupational questionnaire response patterns to assist rule-based expert exposure assessment in population-based studies.

OBJECTIVES: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure. METHODS: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster. RESULTS: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs. CONCLUSIONS: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process.

Common genetic variants in the PSCA gene influence gene expression and bladder cancer risk.

Genome-wide association studies have identified a SNP, rs2294008, on 8q24.3 within the prostate stem cell antigen (PSCA) gene, as a risk factor for bladder cancer. To fine-map this region, we imputed 642 SNPs within 100 Kb of rs2294008 in addition to 33 markers genotyped in one of the reported genome-wide association study in 8,652 subjects. A multivariable logistic regression model adjusted for rs2294008 revealed a unique signal, rs2978974 (r(2) = 0.02, D' = 0.19 with rs2294008). In the combined analysis of 5,393 cases and 7,324 controls, we detected a per-allele odds ratio (OR) = 1.11 [95% confidence interval (CI) = 1.06-1.17, P = 5.8 × 10(-5)] for rs2294008 and OR = 1.07 (95% CI = 1.02-1.13, P = 9.7 × 10(-3)) for rs2978974. The effect was stronger in carriers of both risk variants (OR = 1.24, 95% CI = 1.08-1.41, P = 1.8 × 10(-3)) and there was a significant multiplicative interaction (P = 0.035) between these two SNPs, which requires replication in future studies. The T risk allele of rs2294008 was associated with increased PSCA mRNA expression in two sets of bladder tumor samples (n = 36, P = 0.0007 and n = 34, P = 0.0054) and in normal bladder samples (n = 35, P = 0.0155), but rs2978974 was not associated with PSCA expression. SNP rs2978974 is located 10 Kb upstream of rs2294008, within an alternative untranslated first exon of PSCA. The non-risk allele G of rs2978974 showed strong interaction with nuclear proteins from five cell lines tested, implying a regulatory function. In conclusion, a joint effect of two PSCA SNPs, rs2294008 and rs2978974, suggests that both variants may be important for bladder cancer susceptibility, possibly through different mechanisms that influence the control of mRNA expression and interaction with regulatory factors.

Genome-wide interaction study of smoking and bladder cancer risk.

Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 × 10(-) (5) were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20-1.50, P value = 5.18 × 10(-) (7)]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67-0.84, P value = 6.35 × 10(-) (7)). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers-including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene-environment interactions for tobacco and bladder cancer.

Mapping of the UGT1A locus identifies an uncommon coding variant that affects mRNA expression and protects from bladder cancer.

A recent genome-wide association study of bladder cancer identified the UGT1A gene cluster on chromosome 2q37.1 as a novel susceptibility locus. The UGT1A cluster encodes a family of UDP-glucuronosyltransferases (UGTs), which facilitate cellular detoxification and removal of aromatic amines. Bioactivated forms of aromatic amines found in tobacco smoke and industrial chemicals are the main risk factors for bladder cancer. The association within the UGT1A locus was detected by a single nucleotide polymorphism (SNP) rs11892031. Now, we performed detailed resequencing, imputation and genotyping in this region. We clarified the original genetic association detected by rs11892031 and identified an uncommon SNP rs17863783 that explained and strengthened the association in this region (allele frequency 0.014 in 4035 cases and 0.025 in 5284 controls, OR = 0.55, 95%CI = 0.44-0.69, P = 3.3 × 10(-7)). Rs17863783 is a synonymous coding variant Val209Val within the functional UGT1A6.1 splicing form, strongly expressed in the liver, kidney and bladder. We found the protective T allele of rs17863783 to be associated with increased mRNA expression of UGT1A6.1 in in-vitro exontrap assays and in human liver tissue samples. We suggest that rs17863783 may protect from bladder cancer by increasing the removal of carcinogens from bladder epithelium by the UGT1A6.1 protein. Our study shows an example of genetic and functional role of an uncommon protective genetic variant in a complex human disease, such as bladder cancer.

0084†A Case-Control Study of Occupational Exposure to Metalworking Fluids and Bladder Cancer Risk among Men.

OBJECTIVES: Metalworking has been associated with bladder cancer risk in many studies. Metalworking fluids (MWFs) are suspected as the putative exposure, but epidemiologic data are limited. Based on state-of-the-art, quantitative exposure assessment, we examined MWF exposure and bladder cancer risk in the New England Bladder Cancer Study. METHOD: Male cases (n = 895) and population controls (n = 1031) provided occupational histories and information on use of each of three MWF types: (1) straight (mineral oil, additives), (2) soluble (mineral oil, water, additives), and (3) synthetic (water, organics, additives) or semi-synthetic (soluble/synthetic hybrid), in response to exposure-oriented modules administered during personal interviews. We estimated the probability, frequency, and intensity of exposure to each MWF type and, if probability exceeded 50%, cumulative exposure. Logistic regression was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusting for smoking and other risk factors. RESULTS: Risk was increased for men reporting use of straight MWFs (OR=1.7, 95% CI=1.1-2.8), with a significant trend with increasing cumulative exposure (p = 0.024). Use of soluble MWFs conferred a 50% elevated risk (95% CI=0.96-2.5). ORs were nonsignificantly elevated for synthetic MWFs, based on small numbers. Men who were never metalworkers, but held jobs with possible exposure to mineral oil, had a 40% increased risk (95% CI=1.1-1.8). CONCLUSIONS: In the most comprehensive assessment of MWF exposure in a bladder cancer case-control study, exposure to straight MWFs significantly increased bladder cancer risk, as did employment in non-metalworking jobs with possible mineral oil exposure. Our results strengthen prior evidence for mineral oil as a bladder carcinogen.

A case-control study of occupational exposure to metalworking fluids and bladder cancer risk among men.

OBJECTIVES: Metalworking has been associated with an excess risk of bladder cancer in over 20 studies. Metalworking fluids (MWFs) are suspected as the responsible exposure, but epidemiological data are limited. We investigated this association among men in the New England Bladder Cancer Study using state-of-the-art, quantitative exposure assessment methods. METHODS: Cases (n=895) and population controls (n=1031) provided occupational histories during personal interviews. For selected jobs, exposure-oriented modules were administered to collect information on use of three MWF types: (1) straight (mineral oil, additives), (2) soluble (mineral oil, water, additives) and (3) synthetic (water, organics, additives) or semisynthetic (hybrid of soluble and synthetic). We computed ORs and 95% CIs relating bladder cancer risk to a variety of exposure metrics, adjusting for smoking and other factors. Non-metalworkers who had held jobs with possible exposure to mineral oil were analysed separately. RESULTS: Bladder cancer risk was elevated among men who reported using straight MWFs (OR=1.7, 95% CI 1.1 to 2.8); risk increased monotonically with increasing cumulative exposure (p=0.041). Use of soluble MWFs was associated with a 50% increased risk (95% CI 0.96 to 2.5). ORs were non-significantly elevated for synthetic/semisynthetic MWFs based on a small number of exposed men. Non-metalworkers holding jobs with possible exposure to mineral oil had a 40% increased risk (95% CI 1.1 to 1.8). CONCLUSIONS: Exposure to straight MWFs was associated with a significantly increased bladder cancer risk, as was employment in non-metalworking jobs with possible exposure to mineral oil. These findings strengthen prior evidence for mineral oil as a bladder carcinogen.

Identifying gender differences in reported occupational information from three US population-based case-control studies.

OBJECTIVES: Growing evidence suggests that gender-blind assessment of exposure may introduce exposure misclassification, but few studies have characterised gender differences across occupations and industries. We pooled control responses to job-specific, industry-specific and exposure-specific questionnaires (modules) that asked detailed questions about work activities from three US population-based case-control studies to examine gender differences in work tasks and their frequencies. METHODS: We calculated the ratio of female-to-male controls that completed each module. For four job modules (assembly worker, machinist, health professional, janitor/cleaner) and for subgroups of jobs that completed those modules, we evaluated gender differences in task prevalence and frequency using χ(2) and Mann-Whitney U tests, respectively. RESULTS: The 1360 female and 2245 male controls reported 6033 and 12 083 jobs, respectively. Gender differences in female:male module completion ratios were observed for 39 of 45 modules completed by ≥20 controls. Gender differences in task prevalence varied in direction and magnitude. For example, female janitors were significantly more likely to polish furniture (79% vs 44%), while male janitors were more likely to strip floors (73% vs 50%). Women usually reported more time spent on tasks than men. For example, the median hours per week spent degreasing for production workers in product manufacturing industries was 6.3 for women and 3.0 for men. CONCLUSIONS: Observed gender differences may reflect actual differences in tasks performed or differences in recall, reporting or perception, all of which contribute to exposure misclassification and impact relative risk estimates. Our findings reinforce the need to capture subject-specific information on work tasks.

Developing estimates of frequency and intensity of exposure to three types of metalworking fluids in a population-based case-control study of bladder cancer.

BACKGROUND: A systematic, transparent, and data-driven approach was developed to estimate frequency and intensity of exposure to straight, soluble, and synthetic/semi-synthetic metalworking fluids (MWFs) within a case-control study of bladder cancer in New England. METHODS: We assessed frequency using individual-level information from job-specific questionnaires wherever possible, then derived and applied job group-level patterns to likely exposed jobs with less information. Intensity estimates were calculated using a statistical model developed from measurements and determinants extracted from the published literature. RESULTS: For jobs with probabilities of exposure≥0.5, median frequencies were 8-10 hr/week, depending on MWF type. Median intensities for these jobs were 2.5, 2.1, and 1.0 mg/m3 for soluble, straight, and synthetic/semi-synthetic MWFs, respectively. CONCLUSIONS: Compared to case-by-case assessment, these data-driven decision rules are transparent and reproducible and may result in less biased estimates. These rules can also aid future exposure assessments of MWFs in population-based studies.

Estimation of the probability of exposure to machining fluids in a population-based case-control study.

We describe an approach for estimating the probability that study subjects were exposed to metalworking fluids (MWFs) in a population-based case-control study of bladder cancer. Study subject reports on the frequency of machining and use of specific MWFs (straight, soluble, and synthetic/semi-synthetic) were used to estimate exposure probability when available. Those reports also were used to develop estimates for job groups, which were then applied to jobs without MWF reports. Estimates using both cases and controls and controls only were developed. The prevalence of machining varied substantially across job groups (0.1->0.9%), with the greatest percentage of jobs that machined being reported by machinists and tool and die workers. Reports of straight and soluble MWF use were fairly consistent across job groups (generally 50-70%). Synthetic MWF use was lower (13-45%). There was little difference in reports by cases and controls vs. controls only. Approximately, 1% of the entire study population was assessed as definitely exposed to straight or soluble fluids in contrast to 0.2% definitely exposed to synthetic/semi-synthetics. A comparison between the reported use of the MWFs and U.S. production levels found high correlations (r generally >0.7). Overall, the method described here is likely to have provided a systematic and reliable ranking that better reflects the variability of exposure to three types of MWFs than approaches applied in the past. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resources: a list of keywords in the occupational histories that were used to link study subjects to the metalworking fluids (MWFs) modules; recommendations from the literature on selection of MWFs based on type of machining operation, the metal being machined and decade; popular additives to MWFs; the number and proportion of controls who reported various MWF responses by job group; the number and proportion of controls assigned to the MWF types by job group and exposure category; and the distribution of cases and controls assigned various levels of probability by MWF type.].