Debra T Silverman

National Cancer Institute (USA), Maryland, United States

Are you Debra T Silverman?

Claim your profile

Publications (236)1437.02 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Abstract DNA methylation changes contribute to bladder carcinogenesis. Trihalomethanes (THM), a class of disinfection by-products, are associated with increased urothelial bladder cancer (UBC) risk. THM exposure in animal models produces DNA hypomethylation. We evaluated the relationship of LINE-1 5-methylcytosine levels (LINE-1%5mC) as outcome of long-term THM exposure among controls and as an effect modifier in the association between THM exposure and UBC risk. We used a case-control study of UBC conducted in Spain. We obtained personal lifetime residential THM levels and measured LINE-1%5mC by pyrosequencing in granulocyte DNA from blood samples in 548 incident cases and 559 hospital controls. Two LINE-1%5mC clusters (above and below 64%) were identified through unsupervised hierarchical cluster analysis. The association between THM levels and LINE-1%5mC was evaluated with beta regression analyses and logistic regression was used to estimate odds ratios (OR) adjusting for covariables. LINE-1%5mC change between percentiles 75(th) and 25(th) of THM levels was 1.8% (95% confidence interval (CI): 0.1, 3.4%) among controls. THM levels above vs. below the median (26 μg/L) were associated with increased UBC risk, OR = 1.86 (95% CI: 1.25, 2.75), overall and among subjects with low levels of LINE-1%5mC (n = 975), OR = 2.14 (95% CI: 1.39, 3.30), but not associated with UBC risk among subjects' high levels of LINE-1%5mC (n = 162), interaction P = 0.03. Results suggest a positive association between LINE-1%5mC and THM levels among controls, and LINE-1%5mC status may modify the association between UBC risk and THM exposure. Because reverse causation and chance cannot be ruled out, confirmation studies are warranted.
    Epigenetics: official journal of the DNA Methylation Society 12/2014; · 4.58 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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. 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. 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. 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. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.
    Annals of Occupational Hygiene 12/2014; · 2.16 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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. 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. 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. 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. © The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.
    Annals of Occupational Hygiene 11/2014; · 2.16 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: To review the literature on the estimation of the population attributable fraction (PAF) of cancer due to occupational exposures and to describe challenges in the estimation of this metric. To help illustrate the inherent challenges, we also estimate PAFs for selected cancers diagnosed in the United States in 2010 attributable to work as a painter (causally associated with bladder and lung cancer) and shiftwork (possibly associated with breast cancer).Methods We reviewed and summarized previous reports providing quantitative estimates of PAF for total cancer due to occupational exposures. We calculated PAF estimates for painters and shiftwork using methodology from a detailed investigation of the occupational cancer burden in Great Britain, with adaptations made for the U.S. population.ResultsThe estimated occupation-attributable fraction for total cancer generally ranged between 2% and 8% (men, 3-14%; women, 1-2%) based on previous reports. We calculated that employment as a painter accounted for a very small proportion of cancers of the bladder and lung diagnosed in the United States in 2010, with PAFs of 0.5% for each site. In contrast, our calculations suggest that the potential impact of shiftwork on breast cancer (if causal) could be substantial, with a PAF of 5.7%, translating to 11,777 attributable breast cancers.Conclusions Continued efforts to estimate the occupational cancer burden will be important as scientific evidence and economic trends evolve. Such projects should consider the challenges involved in PAF estimation, which we summarize in this report.
    Annals of Epidemiology. 11/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.].
    Journal of Occupational and Environmental Hygiene 11/2014; 11(11):757-70. · 1.28 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: A genome-wide association study (GWAS) of bladder cancer identified a genetic marker rs8102137 within the 19q12 region as a novel susceptibility variant. This marker is located upstream of the CCNE1 gene, which encodes cyclin E, a cell-cycle protein. We performed genetic fine-mapping analysis of the CCNE1 region using data from two bladder cancer GWAS (5,942 cases and 10,857 controls). We found that the original GWAS marker rs8102137 represents a group of 47 linked SNPs (with r(2) ≥ 0.7) associated with increased bladder cancer risk. From this group, we selected a functional promoter variant rs7257330, which showed strong allele-specific binding of nuclear proteins in several cell lines. In both GWASs, rs7257330 was associated only with aggressive bladder cancer, with a combined per-allele OR = 1.18 [95% confidence interval (CI), 1.09-1.27, P = 4.67 × 10(-5)] versus OR = 1.01 (95% CI, 0.93-1.10, P = 0.79) for nonaggressive disease, with P = 0.0015 for case-only analysis. Cyclin E protein expression analyzed in 265 bladder tumors was increased in aggressive tumors (P = 0.013) and, independently, with each rs7257330-A risk allele (Ptrend = 0.024). Overexpression of recombinant cyclin E in cell lines caused significant acceleration of cell cycle. In conclusion, we defined the 19q12 signal as the first GWAS signal specific for aggressive bladder cancer. Molecular mechanisms of this genetic association may be related to cyclin E overexpression and alteration of cell cycle in carriers of CCNE1 risk variants. In combination with established bladder cancer risk factors and other somatic and germline genetic markers, the CCNE1 variants could be useful for inclusion into bladder cancer risk prediction models. Cancer Res; 74(20); 5808-18. ©2014 AACR.
    Cancer Research 10/2014; 74(20):5808-18. · 9.28 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Through genome wide association analysis and an independent replication study using a total of 1,131 bladder cancer cases and 12,558 non-cancer controls of Japanese populations, we identified a susceptibility locus on chromosome 15q24. SNP rs11543198 was associated with bladder cancer risk with odds ratio (OR) of 1.41 and P value of 4.03 x 10(-9). Subgroup analysis revealed rs11543198 to have a stronger effect in male smokers with OR of 1.66. Imputational analysis in this region suggested CYP1A2, which metabolizes tobacco-derived carcinogen, as a causative candidate gene. We also confirmed the association of previously-reported loci, namely SLC14A1, APOBEC3A, PSCA, and MYC, with bladder cancer. SNP rs8041357, which is in complete linkage disequilibrium (r(2)=1) with rs11543198, was also associated with bladder cancer risk in Europeans (P=0.045 for an additive and P=0.025 for a recessive model), despite much lower MAF in Europeans (3.7%) compared to the Japanese (22.2%). Our finding implies the crucial roles of genetic variations on the chemically-associated development of bladder cancer.
    Human Molecular Genetics 10/2014; · 7.69 Impact Factor
  • Source
    Environmental Health Perspectives 09/2014; 122(9):A230-A231. · 7.26 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We performed a multistage genome-wide association study including 7,683 individuals with pancreatic cancer and 14,397 controls of European descent. Four new loci reached genome-wide significance: rs6971499 at 7q32.3 (LINC-PINT, per-allele odds ratio (OR) = 0.79, 95% confidence interval (CI) 0.74-0.84, P = 3.0 × 10(-12)), rs7190458 at 16q23.1 (BCAR1/CTRB1/CTRB2, OR = 1.46, 95% CI 1.30-1.65, P = 1.1 × 10(-10)), rs9581943 at 13q12.2 (PDX1, OR = 1.15, 95% CI 1.10-1.20, P = 2.4 × 10(-9)) and rs16986825 at 22q12.1 (ZNRF3, OR = 1.18, 95% CI 1.12-1.25, P = 1.2 × 10(-8)). We identified an independent signal in exon 2 of TERT at the established region 5p15.33 (rs2736098, OR = 0.80, 95% CI 0.76-0.85, P = 9.8 × 10(-14)). We also identified a locus at 8q24.21 (rs1561927, P = 1.3 × 10(-7)) that approached genome-wide significance located 455 kb telomeric of PVT1. Our study identified multiple new susceptibility alleles for pancreatic cancer that are worthy of follow-up studies.
    Nature genetics. 08/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: BackgroundA 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.ResultsFor 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. Am. J. Ind. Med. 57:915–927, 2014. © 2014 Wiley Periodicals, Inc.
    American Journal of Industrial Medicine 08/2014; 57(8). · 1.97 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Type 2 diabetes mellitus has been associated with an excess risk of pancreatic cancer, but the magnitude of the risk and the time-risk relationship are unclear, and there is limited information on the role of antidiabetic medications.
    Annals of oncology : official journal of the European Society for Medical Oncology / ESMO. 07/2014;
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Genome-wide association studies (GWAS) have mapped risk alleles for at least ten distinct cancers to a small region of 63,000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (ASSET) across six distinct cancers in 34,248 cases and 45,036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single nucleotide polymorphisms (SNPs): five in the TERT gene (region 1: rs7726159, P=2.10x10-39; region 3: rs2853677, P=3.30x10-36 and PConditional=2.36x10-8; region 4: rs2736098, P=3.87x10-12 and PConditional=5.19x10-6, region 5: rs13172201, P=0.041 and PConditional=2.04x10-6; and region 6: rs10069690, P=7.49x10-15 and PConditional=5.35x10-7) and one in the neighboring CLPTM1L gene (region 2: rs451360; P=1.90x10-18 and PConditional=7.06x10-16). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele specific effects on DNA methylation were seen for a subset of risk loci indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
    Human Molecular Genetics 07/2014; · 7.69 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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.
    Occupational and Environmental Medicine 06/2014; · 3.22 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Clinically evident chronic pancreatitis is a strong risk factor for pancreatic cancer. A small Japanese cohort study previously reported that pre-diagnostic serum transforming growth factor-β1 (TGF-β1) concentration, a potential marker of subclinical pancreatic inflammation, was associated with higher risk of pancreatic cancer. We further explored this association in a larger prospective study.
    Cancer causes & control : CCC. 06/2014;
  • [Show abstract] [Hide abstract]
    ABSTRACT: To assess the association between occupational exposure to carbon nanotubes (CNTs) and early immunological and cardiovascular health effects.
    Occupational and environmental medicine. 06/2014; 71 Suppl 1:A35.
  • [Show abstract] [Hide abstract]
    ABSTRACT: We examined the association between lifetime occupational diesel engine exhaust (DEE) exposure and risk of bladder cancer in 1171 cases and 1418 controls in a population-based case-control study.
    Occupational and environmental medicine. 06/2014; 71 Suppl 1:A75.
  • [Show abstract] [Hide abstract]
    ABSTRACT: To build a predictive model for urothelial carcinoma of the bladder (UCB) risk combining both genomic and nongenomic data, 1,127 cases and 1,090 controls from the Spanish Bladder Cancer/EPICURO study were genotyped using the HumanHap 1M SNP array. After quality control filters, genotypes from 475,290 variants were available. Nongenomic information comprised age, gender, region, and smoking status. Three Bayesian threshold models were implemented including: (1) only genomic information, (2) only nongenomic data, and (3) both sources of information. The three models were applied to the whole population, to only nonsmokers, to male smokers, and to extreme phenotypes to potentiate the UCB genetic component. The area under the ROC curve allowed evaluating the predictive ability of each model in a 10-fold cross-validation scenario. Smoking status showed the highest predictive ability of UCB risk (AUCtest = 0.62). On the other hand, the AUC of all genetic variants was poorer (0.53). When the extreme phenotype approach was applied, the predictive ability of the genomic model improved 15%. This study represents a first attempt to build a predictive model for UCB risk combining both genomic and nongenomic data and applying state-of-the-art statistical approaches. However, the lack of genetic relatedness among individuals, the complexity of UCB etiology, as well as a relatively small statistical power, may explain the low predictive ability for UCB risk. The study confirms the difficulty of predicting complex diseases using genetic data, and suggests the limited translational potential of findings from this type of data into public health interventions.
    Genetic Epidemiology 05/2014; · 4.02 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Background:Epidemiologic studies have consistently found that self-reported allergies are associated with reduced risk of pancreatic cancer. Our aim was to prospectively assess the relationship between serum IgE, a marker of allergy, and risk. Methods: This nested case-control study within the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) included subjects enrolled in 1994-2001 and followed through 2010. There were 283 cases of pancreatic cancer and 544 controls matched on age, gender, race, and calendar date of blood draw. Using the ImmunoCAP system, we measured total IgE (normal, borderline, elevated), IgE to respiratory allergens, and IgE to food allergens (negative or positive) in serum collected at baseline. Odds ratios (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression. We assessed interactions with age, gender, smoking, body mass index, and time between randomization and case diagnosis. Results:Overall, there was no association between the IgE measures and risk. We found a statistically significant interaction by baseline age: in those aged >65, elevated risks were observed for borderline total IgE (OR=1.43; 95% CI, 0.88-2.32) and elevated total IgE (OR=1.98; 95% CI, 1.16-3.37) and positive IgE to food allergens (OR=2.83; 95% CI, 1.29-6.20); among participants <65, ORs were <1. Other interactions were not statistically significant. Conclusions:The reduced risk of pancreatic cancer associated with self-reported allergies is not reflected in serum IgE. Among older participants, higher total IgE and IgE to food allergens significantly increased risk. Impact:The association of pancreatic cancer risk with allergies is not reflected in serum IgE.
    Cancer Epidemiology Biomarkers &amp Prevention 04/2014; · 4.56 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 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. 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. 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. 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.
    Occupational and environmental medicine 03/2014; · 3.64 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study of smoking and bladder cancer risk based on primary scan data from 3,002 cases and 4,411 controls from the NCI Bladder Cancer Genome- Wide Association Study (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 <5x10(-5) were evaluated further in an independent dataset of 2,422 bladder cancer cases and 5,751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial data set and in the combined data set, 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 OR=1.34, 95% CI=1.20-1.50, P-value=5.18x10(-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=6.35x10(-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, while 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.
    Carcinogenesis 03/2014; · 5.64 Impact Factor

Publication Stats

7k Citations
1,437.02 Total Impact Points


  • 1987–2014
    • National Cancer Institute (USA)
      • • Division of Cancer Epidemiology and Genetics
      • • Occupational and Environmental Epidemiology
      • • Nutritional Epidemiology
      • • Epidemiology and Biostatistics
      • • Cancer Etiology Branch (CEB)
      Maryland, United States
  • 1986–2014
    • National Institutes of Health
      • • Division of Cancer Epidemiology and Genetics
      • • Branch of Occupational and Environmental Epidemiology
      • • Branch of Nutritional Epidemiology
      • • Branch of Hormonal and Reproductive Epidemiology
      • • Branch of Cancer Etiology
      Maryland, United States
  • 2012–2013
    • Catalan Institute of Oncology
      • • Infections and Cancer Unit
      • • Cancer Epidemiology Research Programme (PREC)
      Badalona, Catalonia, Spain
  • 2009–2012
    • Centro Nacional de Investigaciones Oncológicas
      • Molecular Pathology Programme
      Madrid, Madrid, Spain
  • 2011
    • University of Texas MD Anderson Cancer Center
      Houston, Texas, United States
    • Mario Negri Institute for Pharmacological Research
      • Department of Epidemiology
      Milano, Lombardy, Italy
  • 2006–2011
    • CREAL Center for Research in Environmental Epidemiology
      Barcino, Catalonia, Spain
    • Autonomous University of Barcelona
      Cerdanyola del Vallès, Catalonia, Spain
  • 2007
    • University Pompeu Fabra
      • Department of Experimental and Health Sciences
      Barcino, Catalonia, Spain
    • Harvard University
      • Department of Epidemiology
      Boston, MA, United States
  • 1990
    • Walter Reed Army Institute of Research
      Silver Spring, Maryland, United States