A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer.

BACKGROUND: Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. METHODS: We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. RESULTS: We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E-06 in 1D approach and a Local Moran's Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8-a lncRNA associated with pancreatic carcinogenesis-with a lowest p value = 6.91E-05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1-a major regulator of the ER stress and unfolded protein responses in acinar cells-identified by 3D; all of them with a strong in silico functional support. CONCLUSIONS: This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases.

Understanding racial disparities in renal cell carcinoma incidence: estimates of population attributable risk in two US populations.

PURPOSE: Renal cell carcinoma (RCC) incidence is higher among black than white Americans. The reasons for this disparity remain unclear. METHODS: We calculated race- and sex-specific population attributable risk percentages (PAR%) and their 95% confidence intervals (CI) for hypertension and chronic kidney disease (CKD) among black and white subjects ≥ 50 years of age from the US Kidney Cancer Study (USKC; 965 cases, 953 controls), a case-control study in Chicago and Detroit, and a nested case-control study in the Kaiser Permanente Northern California health care network (KPNC; 2,162 cases, 21,484 controls). We also estimated PAR% for other modifiable RCC risk factors (cigarette smoking, obesity) in USKC. RESULTS: In USKC, the PAR% for hypertension was 50% (95% CI 24-77%) and 44% (95% CI 25-64%) among black women and men, respectively, and 29% (95% CI 13-44%) and 27% (95% CI 14-39%) for white women and men, respectively. In KPNC, the hypertension PAR% was 40% (95% CI 18-62%) and 23% (95% CI 2-44%) among black women and men, and 27% (95% CI 20-35%) and 19% (95% CI 14-24%) among white women and men, respectively. The PAR% for CKD in both studies ranged from 7 to 10% for black women and men but was negligible (<1%) for white subjects. In USKC, the PAR% for current smoking was 20% and 8% among black and white men, respectively, and negligible and 8.6% for black and white women, respectively. The obesity PAR% ranged from 12 to 24% across all race/sex strata. CONCLUSIONS: If the associations found are causal, interventions that prevent hypertension and CKD among black Americans could potentially eliminate the racial disparity in RCC incidence (hypothetical black:white RCC incidence ratio of 0.5).

Use and Reliability of Exposure Assessment Methods in Occupational Case-Control Studies in the General Population: Past, Present, and Future.

Introduction: Retrospective occupational exposure assessment has been challenging in case-control studies in the general population. We aimed to review (i) trends of different assessment methods used in the last 40 years and (ii) evidence of reliability for various assessment methods. Methods: Two separate literature reviews were conducted. We first reviewed all general population cancer case-control studies published from 1975 to 2016 to summarize the exposure assessment approach used. For the second review, we systematically reviewed evidence of reliability for all methods observed in the first review. Results: Among the 299 studies included in the first review, the most frequently used assessment methods were self-report/assessment (n = 143 studies), case-by-case expert assessment (n = 139), and job-exposure matrices (JEMs; n = 82). Usage trends for these methods remained relatively stable throughout the last four decades. Other approaches, such as the application of algorithms linking questionnaire responses to expert-assigned exposure estimates and modelling of exposure with historical measurement data, appeared in 21 studies that were published after 2000. The second review retrieved 34 comparison studies examining methodological reliability. Overall, we observed slightly higher median kappa agreement between exposure estimates from different expert assessors (~0.6) than between expert estimates and exposure estimates from self-reports (~0.5) or JEMs (~0.4). However, reported reliability measures were highly variable for different methods and agents. Limited evidence also indicates newer methods, such as assessment using algorithms and measurement-calibrated quantitative JEMs, may be as reliable as traditional methods. Conclusion: The majority of current research assesses exposures in the population with similar methods as studies did decades ago. Though there is evidence for the development of newer approaches, more concerted effort is needed to better adopt exposure assessment methods with more transparency, reliability, and efficiency.

Inflammatory-Related Genetic Variants in Non-Muscle-Invasive Bladder Cancer Prognosis: A Multimarker Bayesian Assessment.

BACKGROUND: Increasing evidence points to the role of tumor immunologic environment on urothelial bladder cancer prognosis. This effect might be partly dependent on the host genetic context. We evaluated the association of SNPs in inflammation-related genes with non-muscle-invasive bladder cancer (NMIBC) risk-of-recurrence and risk-of-progression. METHODS: We considered 822 NMIBC included in the SBC/EPICURO Study followed-up >10 years. We selected 1,679 SNPs belonging to 251 inflammatory genes. The association of SNPs with risk-of-recurrence and risk-of-progression was assessed using Cox regression single-marker (SMM) and multimarker methods (MMM) Bayes A and Bayesian LASSO. Discriminative abilities of the models were calculated using the c index and validated with bootstrap cross-validation procedures. RESULTS: While no SNP was found to be associated with risk-of-recurrence using SMM, three SNPs in TNIP1, CD5, and JAK3 showed very strong association with posterior probabilities >90% using MMM. Regarding risk-of-progression, one SNP in CD3G was significantly associated using SMM (HR, 2.69; P = 1.55 × 10(-5)) and two SNPs in MASP1 and AIRE, showed a posterior probability ≥80% with MMM. Validated discriminative abilities of the models without and with the SNPs were 58.4% versus 60.5% and 72.1% versus 72.8% for risk-of-recurrence and risk-of-progression, respectively. CONCLUSIONS: Using innovative analytic approaches, we demonstrated that SNPs in inflammatory-related genes were associated with NMIBC prognosis and that they improve the discriminative ability of prognostic clinical models for NMIBC. IMPACT: This study provides proof of concept for the joint effect of genetic variants in improving the discriminative ability of clinical prognostic models. The approach may be extended to other diseases. Cancer Epidemiol Biomarkers Prev; 25(7); 1144-50. ©2016 AACR.

Retrospective benzene exposure assessment for a multi-center case-cohort study of benzene-exposed workers in China.

Quality of exposure assessment has been shown to be related to the ability to detect risk of lymphohematopoietic disorders in epidemiological investigations of benzene, especially at low levels of exposure. We set out to build a statistical model for reconstructing exposure levels for 2898 subjects from 501 factories that were part of a nested case-cohort study within the NCI-CAPM cohort of more than 110,000 workers. We used a hierarchical model to allow for clustering of measurements by factory, workshop, job, and date. To calibrate the model we used historical routine monitoring data. Measurements below the limit of detection were accommodated by constructing a censored data likelihood. Potential non-linear and industry-specific time-trends and predictor effects were incorporated using regression splines and random effects. A partial validation of predicted exposures in 2004/2005 was performed through comparison with full-shift measurements from an exposure survey in facilities that were still open. Median cumulative exposure to benzene at age 50 for subjects that ever held an exposed job (n=1175) was 509 mg/m(3) years. Direct comparison of model estimates with measured full-shift personal exposure in the 2004/2005 survey showed moderate correlation and a potential downward bias at low (<1 mg/m(3)) exposure estimates. The modeling framework enabled us to deal with the data complexities generally found in studies using historical exposure data in a comprehensive way and we therefore expect to be able to investigate effects at relatively low exposure levels.

Predictors and long-term reproducibility of urinary phthalate metabolites in middle-aged men and women living in urban Shanghai.

Phthalate esters are man-made chemicals commonly used as plasticizers and solvents, and humans may be exposed through ingestion, inhalation, and dermal absorption. Little is known about predictors of phthalate exposure, particularly in Asian countries. Because phthalates are rapidly metabolized and excreted from the body following exposure, it is important to evaluate whether phthalate metabolites measured at a single point in time can reliably rank exposures to phthalates over a period of time. We examined the concentrations and predictors of phthalate metabolite concentrations among 50 middle-aged women and 50 men from two Shanghai cohorts, enrolled in 1997-2000 and 2002-2006, respectively. We assessed the reproducibility of urinary concentrations of phthalate metabolites in three spot samples per participant taken several years apart (mean interval between first and third sample was 7.5 years [women] or 2.9 years [men]), using Spearman's rank correlation coefficients and intra-class correlation coefficients. We detected ten phthalate metabolites in at least 50% of individuals for two or more samples. Participant sex, age, menopausal status, education, income, body mass index, consumption of bottled water, recent intake of medication, and time of day of collection of the urine sample were associated with concentrations of certain phthalate metabolites. The reproducibility of an individual's urinary concentration of phthalate metabolites across several years was low, with all intra-class correlation coefficients and most Spearman rank correlation coefficients ≤0.3. Only mono(2-ethylhexyl) phthalate, a metabolite of di(2-ethylhexyl) phthalate, had a Spearman rank correlation coefficient ≥0.4 among men, suggesting moderate reproducibility. These findings suggest that a single spot urine sample is not sufficient to rank exposures to phthalates over several years in an adult urban Chinese population.

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.

Hypertension and risk of renal cell carcinoma among white and black Americans.

BACKGROUND: Renal cell carcinoma and hypertension (a well-established renal cancer risk factor) are both more frequent among blacks than whites in the United States. The association between hypertension and renal cell carcinoma has not been examined in black Americans. We investigated the hypertension-renal cancer association by race, and we assessed the role of hypertension in the racial disparity of renal cancer incidence. METHODS: Participants were enrolled in a population-based case-control study in Detroit and Chicago during 2002-2007 (number of cases: 843 whites, 358 blacks; number of controls: 707 whites, 519 blacks). Participants reported their history of hypertension and antihypertensive drug use. We used unconditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs), adjusted for demographic characteristics, smoking, body mass index, and family history of cancer. RESULTS: Hypertension doubled renal cancer risk (OR = 2.0 [CI = 1.7-2.5]) overall. For whites, the OR was 1.9 (CI = 1.5-2.4), whereas for blacks it was 2.8 (2.1-3.8) (P for interaction = 0.11). ORs increased with time after hypertension diagnosis (P for trend <0.001), reaching 4.1 (CI = 2.3-7.4) for blacks and 2.6 (CI = 1.7-4.1) for whites after 25 years. ORs for poorly controlled hypertension were 4.5 (CI = 2.3-8.8) for blacks and 2.1 (CI = 1.2-3.8) for whites. If these estimates correctly represent causal effects and if, hypothetically, hypertension could be prevented entirely among persons aged 50-79 years, the black/white disparity in renal cancer could be reversed among women and reduced by two-thirds among men. CONCLUSIONS: Hypertension is a risk factor for renal cancer among both blacks and whites, and might explain a substantial portion of the racial disparity in renal cancer incidence. Preventing and controlling hypertension might reduce renal cancer incidence, adding to the known benefits of blood pressure control for heart disease and stroke reduction, particularly among blacks.

Power of data mining methods to detect genetic associations and interactions.

BACKGROUND: Genetic association studies, thus far, have focused on the analysis of individual main effects of SNP markers. Nonetheless, there is a clear need for modeling epistasis or gene-gene interactions to better understand the biologic basis of existing associations. Tree-based methods have been widely studied as tools for building prediction models based on complex variable interactions. An understanding of the power of such methods for the discovery of genetic associations in the presence of complex interactions is of great importance. Here, we systematically evaluate the power of three leading algorithms: random forests (RF), Monte Carlo logic regression (MCLR), and multifactor dimensionality reduction (MDR). METHODS: We use the algorithm-specific variable importance measures (VIMs) as statistics and employ permutation-based resampling to generate the null distribution and associated p values. The power of the three is assessed via simulation studies. Additionally, in a data analysis, we evaluate the associations between individual SNPs in pro-inflammatory and immunoregulatory genes and the risk of non-Hodgkin lymphoma. RESULTS: The power of RF is highest in all simulation models, that of MCLR is similar to RF in half, and that of MDR is consistently the lowest. CONCLUSIONS: Our study indicates that the power of RF VIMs is most reliable. However, in addition to tuning parameters, the power of RF is notably influenced by the type of variable (continuous vs. categorical) and the chosen VIM.

Socioeconomic status and exposure to disinfection by-products in drinking water in Spain.

BACKGROUND: Disinfection by-products in drinking water are chemical contaminants that have been associated with cancer and other adverse effects. Exposure occurs from consumption of tap water, inhalation and dermal absorption. METHODS: We determined the relationship between socioeconomic status and exposure to disinfection by-products in 1271 controls from a multicentric bladder cancer case-control study in Spain. Information on lifetime drinking water sources, swimming pool attendance, showering-bathing practices, and socioeconomic status (education, income) was collected through personal interviews. RESULTS: The most highly educated subjects consumed less tap water (57%) and more bottled water (33%) than illiterate subjects (69% and 17% respectively, p-value = 0.003). These differences became wider in recent time periods. The time spent bathing or showering was positively correlated with attained educational level (p < 0.001). Swimming pool attendance was more frequent among highly educated subjects compared to the illiterate (odds ratio = 3.4; 95% confidence interval 1.6-7.3). CONCLUSIONS: The most highly educated subjects were less exposed to chlorination by-products through ingestion but more exposed through dermal contact and inhalation in pools and showers/baths. Health risk perceptions and economic capacity may affect patterns of water consumption that can result in differences in exposure to water contaminants.

Assessment of copy number variation using the Illumina Infinium 1M SNP-array: a comparison of methodological approaches in the Spanish Bladder Cancer/EPICURO study.

High-throughput single nucleotide polymorphism (SNP)-array technologies allow to investigate copy number variants (CNVs) in genome-wide scans and specific calling algorithms have been developed to determine CNV location and copy number. We report the results of a reliability analysis comparing data from 96 pairs of samples processed with CNVpartition, PennCNV, and QuantiSNP for Infinium Illumina Human 1Million probe chip data. We also performed a validity assessment with multiplex ligation-dependent probe amplification (MLPA) as a reference standard. The number of CNVs per individual varied according to the calling algorithm. Higher numbers of CNVs were detected in saliva than in blood DNA samples regardless of the algorithm used. All algorithms presented low agreement with mean Kappa Index (KI) <66. PennCNV was the most reliable algorithm (KI(w=) 98.96) when assessing the number of copies. The agreement observed in detecting CNV was higher in blood than in saliva samples. When comparing to MLPA, all algorithms identified poorly known copy aberrations (sensitivity = 0.19-0.28). In contrast, specificity was very high (0.97-0.99). Once a CNV was detected, the number of copies was truly assessed (sensitivity >0.62). Our results indicate that the current calling algorithms should be improved for high performance CNV analysis in genome-wide scans. Further refinement is required to assess CNVs as risk factors in complex diseases.

Micronuclei assessment in the urothelial cells of women using hair dyes and its modulation by genetic polymorphisms.

Increases in the frequency of micronuclei (MN) in exposed cells can be used as a measure of genotoxicity. Hair dyes contain chemicals that are eliminated by urine and could be genotoxic to urothelial cells. To address this question, we evaluated whether hair dye use is associated with an increase in the frequency of MN in urothelial cells, and whether this association is modified by NAT1 (N-acetyltransferase 1), NAT2 (N-acetyltransferase 2) and GSTM1 (glutathione-S-transferase M1) genotypes. We included 92 women participating as controls in a bladder cancer case-control study in Spain. Of those, 72 had adequate number of cells to be included in the MN analysis. There were no significant differences in the mean MN frequency in women using hair dyes in the last month (9.88 MN/1000 cells), in comparison with the MN in unexposed women (9.50 MN/1000 cells). No statistically significant differences in MN frequency were observed by type of hair dye or color of the hair dye. Comparison of subjects in the highest quartile of MN frequency (> or = 12 MN/1000 cells) and those in the lowest quartile (< or = 4 MN/1000 cells) suggested an association between hair dye use and elevated MN frequency (OR 14.2 (95% CI 0.81-247.8; P=0.069)). None of the polymorphisms examined significantly modified association between hair dye use and frequency of MN. Findings of an increased frequency of MN in urothelial cells of hair dye users suggest a possible genotoxic effect of hair dye compounds and need confirmation in larger studies.

Assessment of dermal exposure to benzene and toluene in shoe manufacturing by activated carbon cloth patches.

OBJECTIVES: The aim of this investigation was to use activated carbon cloth (ACC) patches to study the probability and extent of dermal exposure to benzene and toluene in a shoe factory. METHODS: Inhalation and dermal exposure loading were measured simultaneously in 70 subjects on multiple days resulting in 113 observations. Dermal exposure loading was assessed by ACC patches attached to likely exposed skin areas (e.g. the palm of the hand and abdomen). A control patch at the chest and an organic vapor monitor (OVM) were used to adjust the hand and abdomen patches for the contribution from the air through passive absorption of benzene and toluene on the ACC patches. Systemic exposure was assessed by quantification of unmetabolized benzene (UBz) and toluene (UTol) in urine. RESULTS: Mean air concentrations for the study population were 1.5 and 7.5 ppm for benzene and toluene, respectively. Iterative regression analyses between the control patch, OVM and the dermal patches showed that only a small proportion of the ACC patches at the hand had likely benzene (n = 4; mean 133 microg cm(-2) h(-1)) or toluene (n = 5; mean 256 microg cm(-2) h(-1)) contamination. Positive patches were exclusively observed among subjects performing the task of gluing. Significant dermal exposure loading to the abdomen was detected only for toluene (n = 2; mean 235 microg cm(-2) h(-1)). No relation was found between having a positive hand or abdomen ACC patch and UBz or UTol levels. In contrast a strong association was found between air levels of benzene (p = 0.0016) and toluene (p < 0.0001) and their respective urinary levels. CONCLUSIONS: ACC patches are shown to be a useful technique for quantifying the probability of dermal exposure to organic solvents and to provide estimates of the potential contribution of the dermal pathway to systemic exposure. Using ACC patches we show that dermal exposure to benzene and toluene in a shoe manufacturing factory is probably rare, and when it occurred exposures were relatively low and did not significantly contribute to systemic exposure.

Genetic variation and willingness to participate in epidemiologic research: data from three studies.

The differences in common genetic polymorphism frequencies by willingness to participate in epidemiologic studies are unexplored, but the same threats to internal validity operate as for studies with nongenetic information. We analyzed single nucleotide polymorphism genotypes, haplotypes, and short tandem repeats among control groups from three studies with different recruitment designs that included early, late, and never questionnaire responders, one or more participation incentives, and blood or buccal DNA collection. Among 2,955 individuals, we compared 108 genotypes, 8 haplotypes, and 9 to 15 short tandem repeats by respondent type. Among our main comparisons, single nucleotide polymorphism genotype frequencies differed significantly (P < 0.05) between respondent groups in six instances, with 13 expected by chance alone. When comparing the odds of carrying a variant among the various response groups, 19 odds ratios were /=1.40, levels that might be notably different. Among the various respondent group comparisons, haplotype and short tandem repeat frequencies were not significantly different by willingness to participate. We observed little evidence to suggest that genotype differences underlie response characteristics in molecular epidemiologic studies, but a greater variety of genes should be examined, including those related to behavioral traits potentially associated with willingness to participate. To the extent possible, investigators should evaluate their own genetic data for bias in response categories.

Detailed exposure assessment for a molecular epidemiology study of benzene in two shoe factories in China.

OBJECTIVES: We carried out a detailed exposure assessment of benzene and toluene in two shoe factories in Tianjin, China. Our goal was to identify workers with a broad range of benzene exposures, for an epidemiologic study relating exposure to early biologic effects. METHODS: A comprehensive exposure survey program was initiated. Over a period of 16 months, 2783 personal solvent exposure samples were collected in two workplaces from 250 workers. Mixed-effects models were used to identify factors affecting exposure. Principal component analyses (PCA) and subsequent regression analyses on the scores of the identified principal components were used to relate potential co-exposures to various exposure sources present in the workplace. RESULTS: The mean benzene exposure level was 21.86 p.p.m. (10th-90th percentiles 5.23-50.63 p.p.m.) in the smaller shoe factory (factory A) and 3.46 p.p.m. (10th-90th percentiles 0.20-7.00 p.p.m.) in the larger shoe factory (factory B). Within-factory exposure levels differed among job titles and were higher for subjects directly involved in handling glues. In contrast, mean toluene levels were relatively similar in the two factories (factory A, 9.52 p.p.m.; factory B, 15.88 p.p.m.). A seasonal trend was identified for both benzene and toluene in factory B. This could be explained in part by changes in air movement and ventilation patterns occurring during the year. A seasonal trend was not present in the smaller shoe factory, where general ventilation was absent. Supplemental analysis showed that exposure levels to other hydrocarbons were low (< or =5 p.p.m.), less than 5% of their respective ACGIH threshold limit values, and generally comparable in the two factories. PCA showed that co-exposures in factory B could largely be explained by glue sources that were used in distinct areas in the workplace. CONCLUSIONS: We demonstrated the occurrence of a broad range of benzene exposure levels in two shoe manufacturing factories in Tianjin, China. Benzene and toluene exposures were determined in part by the degree of contact with glues, the benzene and toluene content of each glue, air movement and ventilation patterns. The availability of long-term monthly personal monitoring data provides an excellent opportunity to estimate individual exposures at different times during the 1 yr period of observation.

Assessing the probability that a positive report is false: an approach for molecular epidemiology studies.

Too many reports of associations between genetic variants and common cancer sites and other complex diseases are false positives. A major reason for this unfortunate situation is the strategy of declaring statistical significance based on a P value alone, particularly, any P value below.05. The false positive report probability (FPRP), the probability of no true association between a genetic variant and disease given a statistically significant finding, depends not only on the observed P value but also on both the prior probability that the association between the genetic variant and the disease is real and the statistical power of the test. In this commentary, we show how to assess the FPRP and how to use it to decide whether a finding is deserving of attention or "noteworthy." We show how this approach can lead to improvements in the design, analysis, and interpretation of molecular epidemiology studies. Our proposal can help investigators, editors, and readers of research articles to protect themselves from overinterpreting statistically significant findings that are not likely to signify a true association. An FPRP-based criterion for deciding whether to call a finding noteworthy formalizes the process already used informally by investigators--that is, tempering enthusiasm for remarkable study findings with considerations of plausibility.