Debra T Silverman

National Cancer Institute (USA), 베서스다, Maryland, United States

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Publications (252)1552.37 Total impact

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    ABSTRACT: 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. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
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    ABSTRACT: Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.
    The American Journal of Human Genetics 03/2015; 96(3):487-97. DOI:10.1016/j.ajhg.2015.01.011 · 10.99 Impact Factor
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    ABSTRACT: The International Agency for Research on Cancer recently classified diesel engine exhaust (DEE) as a Group I carcinogen based largely on its association with lung cancer. However, the exposure-response relationship is still a subject of debate and the underlying mechanism by which DEE causes lung cancer in humans is not well understood. We conducted a cross-sectional molecular epidemiology study in a diesel engine truck testing facility of 54 workers exposed to a wide range of DEE (ie, elemental carbon air levels, median range: 49.7, 6.1-107.7 µg/m(3)) and 55 unexposed comparable controls. The total lymphocyte count (p=0.00044) and three of the four major lymphocyte subsets (ie, CD4+ T cells (p=0.00019), CD8+ T cells (p=0.0058) and B cells (p=0.017)) were higher in exposed versus control workers and findings were highly consistent when stratified by smoking status. In addition, there was evidence of an exposure-response relationship between elemental carbon and these end points (ptrends<0.05), and CD4+ T cell levels were significantly higher in the lowest tertile of DEE exposed workers compared to controls (p=0.012). Our results suggest that DEE exposure is associated with higher levels of cells that play a key role in the inflammatory process, which is increasingly being recognised as contributing to the aetiology of lung cancer. This study provides new insights into the underlying mechanism of DEE carcinogenicity. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
    Occupational and Environmental Medicine 02/2015; 72(5). DOI:10.1136/oemed-2014-102556 · 3.23 Impact Factor
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    ABSTRACT: Prospective cohorts have played a major role in understanding the contribution of diet, physical activity, medical conditions, and genes to the development of many diseases, but have not been widely used for occupational exposures. Studies in agriculture are an exception. We draw upon our experience using this design to study agricultural workers to identify conditions that might foster use of prospective cohorts to study other occupational settings. Prospective cohort studies are perceived by many as the strongest epidemiologic design. It allows updating of information on exposure and other factors, collection of biologic samples before disease diagnosis for biomarker studies, assessment of effect modification by genes, lifestyle, and other occupational exposures, and evaluation of a wide range of health outcomes. Increased use of prospective cohorts would be beneficial in identifying hazardous exposures in the workplace. Occupational epidemiologists should seek opportunities to initiate prospective cohorts to investigate high priority, occupational exposures. Am. J. Ind. Med. 58:113–122, 2015.
    American Journal of Industrial Medicine 02/2015; 58(2):113-122. DOI:10.1002/ajim.22403 · 1.59 Impact Factor
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    ABSTRACT: Nitrate is a widespread contaminant in drinking water and ingested nitrate under conditions resulting in endogenous nitrosation is suspected to be carcinogenic. However, the suggested association between nitrate in drinking water and bladder cancer remains inconsistent. We evaluated the long-term exposure to drinking water nitrate as a risk factor for bladder cancer, considering endogenous nitrosation modifiers and other covariables. We conducted a hospital-based case-control study of bladder cancer in Spain (1998-2001). Residential histories and water consumption information were ascertained through personal interviews. Historical nitrate levels (1940-2000) were estimated in study municipalities based on monitoring records and water source. Residential histories of study subjects were linked with nitrate estimates by year and municipality to calculate individual exposure from age 18 to recruitment. We calculated odds ratios (OR) and 95% confidence intervals (CI) for bladder cancer among 531 cases and 556 controls with reliable interviews and nitrate exposure information covering at least 70% of years from age 18 to interview. Average residential levels ranged from 2.1mg/L to 12.0mg/L among regions. Adjusted OR (95%CI) for average residential levels relative to ≤5mg/L were 1.2 (0.7-2.0) for >5-10mg/L and 1.1 (0.6-1.9) for >10mg/L. The OR for subjects with longest exposure duration (>20 years) to highest levels (>9.5mg/L) was 1.4 (0.9-2.3). Stratification by intake of vitamin C, vitamin E, meat, and gastric ulcer diagnosis did not modify these results. A non-significant negative association was found with waterborne ingested nitrate with an OR of 0.7 (0.4-1.0) for >8 vs. ≤4mg/day. Adjustment for several covariables showed similar results to crude analyses. Bladder cancer risk was inconsistently associated with chronic exposure to drinking water nitrate at levels below the current regulatory limit. Elevated risk is suggested only among subjects with longest exposure duration to the highest levels. No evidence of interaction with endogenous nitrosation modifiers was observed. Copyright © 2014 Elsevier Inc. All rights reserved.
    Environmental Research 01/2015; 137C:299-307. DOI:10.1016/j.envres.2014.10.034 · 3.95 Impact Factor
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    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; 9(11):1532--1539. DOI:10.4161/15592294.2014.983377 · 5.11 Impact Factor
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    ABSTRACT: 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.
    Annals of Occupational Hygiene 12/2014; 59(4). DOI:10.1093/annhyg/meu101 · 2.07 Impact Factor
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    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; DOI:10.1093/annhyg/meu098 · 2.07 Impact Factor
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    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; 25(3). DOI:10.1016/j.annepidem.2014.11.009 · 2.15 Impact Factor
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    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. DOI:10.1080/15459624.2014.918984 · 1.21 Impact Factor
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    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. DOI:10.1158/0008-5472.CAN-14-1531. · 9.28 Impact Factor
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    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; 24(4). DOI:10.1093/hmg/ddu512 · 6.68 Impact Factor
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    Environmental Health Perspectives 09/2014; 122(9):A230-A231. DOI:10.1289/ehp.1408428R · 7.03 Impact Factor
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    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; 46(9). DOI:10.1038/ng.3052 · 29.65 Impact Factor
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    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). DOI:10.1002/ajim.22328 · 1.59 Impact Factor
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    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.
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    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; DOI:10.1093/hmg/ddu363 · 6.68 Impact Factor
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    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 07/2014; 38(5). DOI:10.1002/gepi.21809 · 2.95 Impact Factor

Publication Stats

9k Citations
1,552.37 Total Impact Points

Institutions

  • 1987–2015
    • National Cancer Institute (USA)
      • • Division of Cancer Epidemiology and Genetics
      • • Occupational and Environmental Epidemiology
      • • Epidemiology and Biostatistics
      • • Cancer Etiology Branch (CEB)
      베서스다, Maryland, United States
  • 1986–2015
    • National Institutes of Health
      • • Division of Cancer Epidemiology and Genetics
      • • Branch of Occupational and Environmental Epidemiology
      베서스다, Maryland, United States
  • 2004–2014
    • Northern Inyo Hospital
      BIH, California, United States
  • 2001–2014
    • NCI-Frederick
      Фредерик, Maryland, United States
  • 2006–2012
    • University Pompeu Fabra
      • Department of Experimental and Health Sciences
      Barcino, Catalonia, Spain
    • Autonomous University of Barcelona
      Cerdanyola del Vallès, Catalonia, Spain
    • IMIM Hospital del Mar Medical Research Institute
      Barcino, Catalonia, Spain
    • Hospital General Universitario de Elche
      Elche, Valencia, Spain
  • 2006–2009
    • CREAL Center for Research in Environmental Epidemiology
      Barcino, Catalonia, Spain
  • 2004–2006
    • University of Oviedo
      Oviedo, Asturias, Spain
  • 1990
    • Walter Reed Army Institute of Research
      Silver Spring, Maryland, United States