The aim of this study was to investigate for the first time the association between body fat and risk of amyotrophic lateral sclerosis (ALS) with an appropriate prospective study design.
The EPIC (European Prospective Investigation into Cancer and Nutrition) study included 518,108 individuals recruited from the general population across 10 Western European countries. At recruitment, information on lifestyle was collected and anthropometric characteristics were measured. Cox hazard models were fitted to investigate the associations between anthropometric measures and ALS mortality.
Two hundred twenty-two ALS deaths (79 men and 143 women) occurred during the follow-up period (mean follow-up = 13 years). There was a statistically significant interaction between categories of body mass index and sex regarding ALS risk (p = 0.009): in men, a significant linear decrease of risk per unit of body mass index was observed (hazard ratio = 0.93, 95% confidence interval 0.86–0.99 per kg/m2); among women, the risk was more than 3-fold increased for underweight compared with normal-weight women. Among women, a significant risk reduction increasing the waist/hip ratio was also evident: women in the top quartile had less than half the risk of ALS compared with those in the bottom quartile (hazard ratio = 0.48, 95% confidence interval 0.25–0.93) with a borderline significant p value for trend across quartiles (p = 0.056).
Increased prediagnostic body fat is associated with a decreased risk of ALS mortality.
Epidemiological studies suggest that trichloroethylene (TCE) exposure may be associated with renal cancer. The biological mechanisms involved are not exactly known although nephrotoxicity is believed to play a role. Studies on TCE nephrotoxicity among humans, however, have been largely inconsistent. We studied kidney toxicity in Chinese factory workers exposed to TCE using novel sensitive nephrotoxicity markers. Eighty healthy workers exposed to TCE and 45 comparable unexposed controls were included in the present analyses. Personal TCE exposure measurements were taken over a 2-week period before urine collection. Ninety-six percent of workers were exposed to TCE below the current US Occupational Safety and Health Administration permissible exposure limit (100 ppm 8h TWA), with a mean (SD) of 22.2 (35.9) ppm. Kidney injury molecule-1 (KIM-1) and Pi-glutathione S transferase (GST) alpha were elevated among the exposed subjects as compared with the unexposed controls with a strong exposure-response association between individual estimates of TCE exposure and KIM-1 (P < 0.0001). This is the first report to use a set of sensitive nephrotoxicity markers to study the possible effects of TCE on the kidneys. The findings suggest that at relatively low occupational exposure levels a toxic effect on the kidneys can be observed. This finding supports the biological plausibility of linking TCE exposure and renal cancer.
Abbreviations:GSTglutathione-S-transferaseKIM-1kidney injury molecule-1NAGN-acetyl-beta-(d)-glucosaminidaseOVMorganic vapour monitoringTCEtrichloroethyleneVEGFvascular endothelial growth factor.
Cancers are heterogeneous and genetically unstable. New methods are needed that provide the sensitivity and specificity to query single cells at the genetic loci that drive cancer progression, thereby enabling researchers to study the progression of individual tumors. Here, we report the development and application of a bead-based hemi-nested microfluidic droplet digital PCR (dPCR) technology to achieve ‘quantitative’ measurement and single-molecule sequencing of somatically acquired carcinogenic translocations at extremely low levels (<10−6) in healthy subjects. We use this technique in our healthy study population to determine the overall concentration of the t(14;18) translocation, which is strongly associated with follicular lymphoma. The nested dPCR approach improves the detection limit to 1 × 10−7 or lower while maintaining the analysis efficiency and specificity. Further, the bead-based dPCR enabled us to isolate and quantify the relative amounts of the various clonal forms of t(14;18) translocation in these subjects, and the single-molecule sensitivity and resolution of dPCR led to the discovery of new clonal forms of t(14;18) that were otherwise masked by the conventional quantitative PCR measurements. In this manner, we created a quantitative map for this carcinogenic mutation in this healthy population and identified the positions on chromosomes 14 and 18 where the vast majority of these t(14;18) events occur.
Bulky DNA adducts are markers of exposure to genotoxic aromatic compounds, which reflect an individual’s ability to metabolically activate carcinogens and to repair DNA damage. Polycyclic aromatic hydrocarbons (PAH) represent a major class of carcinogens that are capable of forming such adducts. Factors that have been reported to be related to DNA adduct levels include smoking, diet, body mass index (BMI), genetic polymorphisms, the season of collection of biologic material, and air pollutants.
We pooled eleven studies (3,600 subjects) in which bulky DNA adducts were measured in human white blood cells with similar 32P-postlabelling techniques and for which a similar set of variables was available, including individual data on age, gender, ethnicity, batch, smoking habits, BMI, season of blood collection and a limited set of gene variants.
Lowest DNA adduct levels were observed in the spring (median 0.50 adducts per 108 nucleotides), followed by summer (0.64), autumn (0.70) and winter (0.85) (p=0.006). The same pattern emerged in multivariate analysis, but only among never smokers (p=0.02). Adduct levels were significantly lower (p=0.001) in Northern Europe (the Netherlands, Denmark) (mean 0.60, median 0.40) than in Southern Europe (Italy, Spain, France, Greece) (mean 0.79, median 0.60).
In this large pooled analysis, we have found only weak associations between bulky DNA adducts and exposure variables. Seasonality (with higher adducts levels in winter) and air pollution may partly explain some of the inter-area differences (North vs South Europe), but most inter-area and inter-individual variation in adduct levels still remain unexplained.
Our study describes the largest pooled analysis of bulky DNA adducts so far, showing that inter-individual variation is still largely unexplained, though seasonality appears to play a role.
DNA adducts; air pollution; seasonality
Background Exposure to occupational carcinogens is an important preventable cause of lung cancer. Most of the previous studies were in highly exposed industrial cohorts. Our aim was to quantify lung cancer burden attributable to occupational carcinogens in a general population.
Methods We applied a new job–exposure matrix (JEM) to translate lifetime work histories, collected by personal interview and coded into standard job titles, into never, low and high exposure levels for six known/suspected occupational lung carcinogens in the Environment and Genetics in Lung cancer Etiology (EAGLE) population-based case–control study, conducted in Lombardy region, Italy, in 2002–05. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated in men (1537 cases and 1617 controls), by logistic regression adjusted for potential confounders, including smoking and co-exposure to JEM carcinogens. The population attributable fraction (PAF) was estimated as impact measure.
Results Men showed an increased lung cancer risk even at low exposure to asbestos (OR: 1.76; 95% CI: 1.42–2.18), crystalline silica (OR: 1.31; 95% CI: 1.00–1.71) and nickel–chromium (OR: 1.18; 95% CI: 0.90–1.53); risk increased with exposure level. For polycyclic aromatic hydrocarbons, an increased risk (OR: 1.64; 95% CI: 0.99–2.70) was found only for high exposures. The PAFs for any exposure to asbestos, silica and nickel–chromium were 18.1, 5.7 and 7.0%, respectively, equivalent to an overall PAF of 22.5% (95% CI: 14.1–30.0). This corresponds to about 1016 (95% CI: 637–1355) male lung cancer cases/year in Lombardy.
Conclusions These findings support the substantial role of selected occupational carcinogens on lung cancer burden, even at low exposures, in a general population.
lung neoplasms; case–control study; carcinogens; occupational health
Benzene exposure causes acute myeloid leukemia, and hematotoxicity, shown as suppression of mature blood and myeloid progenitor cell numbers. As the leukemia-related aneuploidies monosomy 7 and trisomy 8 previously had been detected in the mature peripheral blood cells of exposed workers, we hypothesized that benzene could cause leukemia through the induction of these aneuploidies in hematopoietic stem and progenitor cells. We measured loss and gain of chromosomes 7 and 8 by fluorescence in situ hybridization in interphase colony-forming unit-granulocyte-macrophage (CFU-GM) cells cultured from otherwise healthy benzene-exposed (n=28) and unexposed (n=14) workers. CFU-GM monosomy 7 and 8 levels (but not trisomy) were significantly increased in subjects exposed to benzene overall, compared to levels in the control subjects (p=0.0055 and p=0.0034, respectively). Levels of monosomy 7 and 8 were significantly increased in subjects exposed to <10 ppm (20%, p=0.0419 and 28%, p=0.0056, respectively) and ≥10 ppm (48%, p=0.0045 and 32%, p=0.0354) benzene, compared with controls, and significant exposure-response trends were detected (ptrend=0.0033 and 0.0057). These data show that monosomies 7 and 8 are produced in a dose-dependent fashion in the blood progenitor cells of workers exposed to benzene and may be mechanistically relevant biomarkers of early effect for benzene and other leukemogens.
Benzene; leukemia; monosomy; hematopoietic progenitor
Background: The suitability for omic analysis of biosamples collected in previous decades and currently stored in biobanks is unknown.
Objectives: We evaluated the influence of handling and storage conditions of blood-derived biosamples on transcriptomic, epigenomic (CpG methylation), plasma metabolomic [UPLC-ToFMS (ultra performance liquid chromatography–time-of-flight mass spectrometry)], and wide-target proteomic profiles.
Methods: We collected fresh blood samples without RNA preservative in heparin, EDTA, or citrate and held them at room temperature for ≤ 24 hr before fractionating them into buffy coat, erythrocytes, and plasma and freezing the fractions at –80oC or in liquid nitrogen. We developed methodology for isolating RNA from the buffy coats and conducted omic analyses. Finally, we analyzed analogous samples from the EPIC-Italy and Northern Sweden Health and Disease Study biobanks.
Results: Microarray-quality RNA could be isolated from buffy coats (including most biobank samples) that had been frozen within 8 hr of blood collection by thawing the samples in RNA preservative. Different anticoagulants influenced the metabolomic, proteomic, and to a lesser extent transcriptomic profiles. Transcriptomic profiles were most affected by the delay (as little as 2 hr) before blood fractionation, whereas storage temperature had minimal impact. Effects on metabolomic and proteomic profiles were noted in samples processed ≥ 8 hr after collection, but no effects were due to storage temperature. None of the variables examined significantly influenced the epigenomic profiles. No systematic influence of time-in-storage was observed in samples stored over a period of 13–17 years.
Conclusions: Most samples currently stored in biobanks are amenable to meaningful omics analysis, provided that they satisfy collection and storage criteria defined in this study.
biomarkers; epigenomics; metabolomics; metabonomics; molecular epidemiology; proteomics; transcriptomics
Generic job-exposure matrices (JEMs) are often used in population-based epidemiologic studies to assess occupational risk factors when only the job and industry information of each subject is available. JEM ratings are often based on professional judgment, are usually ordinal or semi-quantitative, and often do not account for changes in exposure over time. We present an empirical Bayesian framework that combines ordinal subjective JEM ratings with benzene measurements. Our aim was to better discriminate between job, industry, and time differences in exposure levels compared to using a JEM alone.
We combined 63 221 short-term area air measurements of benzene exposure (1954–2000) collected during routine health and safety inspections in Shanghai, China, with independently developed JEM intensity ratings for each job and industry using a mixed-effects model. The fixed-effects terms included the JEM intensity ratings for job and industry (both ordinal, 0–3) and a time trend that we incorporated as a b-spline. The random-effects terms included job (n = 33) and industry nested within job (n = 399). We predicted the benzene concentration in two ways: (i) a calibrated JEM estimate was calculated using the fixed-effects model parameters for calendar year and JEM intensity ratings; (ii) a job-/industry-specific estimate was calculated using the fixed-effects model parameters and the best linear unbiased predictors from the random effects for job and industry using an empirical Bayes estimation procedure. Finally, we applied the predicted benzene exposures to a prospective population-based cohort of women in Shanghai, China (n = 74 942).
Exposure levels were 13 times higher in 1965 than in 2000 and declined at a rate that varied from 4 to 15% per year from 1965 to 1985, followed by a small peak in the mid-1990s. The job-/industry-specific estimates had greater differences between exposure levels than the calibrated JEM estimates (97.5th percentile/2.5th percentile exposure level, BGR95B: 20.4 versus 3.0, respectively). The calibrated JEM and job-/industry-specific estimates were moderately correlated in any given year (Pearson correlation, rp = 0.58). We classified only those jobs and industries with a job or industry JEM exposure probability rating of 3 (>50% of workers exposed) as exposed. As a result, 14.8% of the subjects and 8.7% of the employed person-years in the study population were classified as benzene exposed. The cumulative exposure metrics based on the calibrated JEM and job-/industry-specific estimates were highly correlated (rp = 0.88).
We provide a useful framework for combining quantitative exposure data with expert-based exposure ratings in population-based studies that maximized the information from both sources. Our framework calibrated the ratings to a concentration scale between ratings and across time and provided a mechanism to estimate exposure when a job/industry group reported by a subject was not represented in the exposure database. It also allowed the job/industry groups’ exposure levels to deviate from the pooled average for their respective JEM intensity ratings.
benzene; job-exposure matrix; mixed-effects models; retrospective exposure assessment
Occupational studies often involve multiple comparisons and therefore suffer from false positive findings. Semi-Bayes adjustment methods have sometimes been used to address this issue. Hierarchical regression is a more general approach, including Semi-Bayes adjustment as a special case, that aims at improving the validity of standard maximum-likelihood estimates in the presence of multiple comparisons by incorporating similarities between the exposures of interest in a second-stage model.
We re-analysed data from an occupational case-control study of lung cancer, applying hierarchical regression. In the second-stage model, we included the exposure to three known lung carcinogens (asbestos, chromium and silica) for each occupation, under the assumption that occupations entailing similar carcinogenic exposures are associated with similar risks of lung cancer. Hierarchical regression estimates had smaller confidence intervals than maximum-likelihood estimates. The shrinkage toward the null was stronger for extreme, less stable estimates (e.g., “specialised farmers”: maximum-likelihood OR: 3.44, 95%CI 0.90–13.17; hierarchical regression OR: 1.53, 95%CI 0.63–3.68). Unlike Semi-Bayes adjustment toward the global mean, hierarchical regression did not shrink all the ORs towards the null (e.g., “Metal smelting, converting and refining furnacemen”: maximum-likelihood OR: 1.07, Semi-Bayes OR: 1.06, hierarchical regression OR: 1.26).
Hierarchical regression could be a valuable tool in occupational studies in which disease risk is estimated for a large amount of occupations when we have information available on the key carcinogenic exposures involved in each occupation. With the constant progress in exposure assessment methods in occupational settings and the availability of Job Exposure Matrices, it should become easier to apply this approach.
Most studies of the association between diesel exhaust exposure and lung cancer suggest
a modest, but consistent, increased risk. However, to our knowledge, no study to date
has had quantitative data on historical diesel exposure coupled with adequate sample
size to evaluate the exposure–response relationship between diesel exhaust and
lung cancer. Our purpose was to evaluate the relationship between quantitative estimates
of exposure to diesel exhaust and lung cancer mortality after adjustment for smoking and
other potential confounders.
We conducted a nested case–control study in a cohort of 12 315 workers in
eight non-metal mining facilities, which included 198 lung cancer deaths and 562
incidence density–sampled control subjects. For each case subject, we selected up
to four control subjects, individually matched on mining facility, sex, race/ethnicity,
and birth year (within 5 years), from all workers who were alive before the day the case
subject died. We estimated diesel exhaust exposure, represented by respirable elemental
carbon (REC), by job and year, for each subject, based on an extensive retrospective
exposure assessment at each mining facility. We conducted both categorical and
continuous regression analyses adjusted for cigarette smoking and other potential
confounding variables (eg, history of employment in high-risk occupations for lung
cancer and a history of respiratory disease) to estimate odds ratios (ORs) and 95%
confidence intervals (CIs). Analyses were both unlagged and lagged to exclude recent
exposure such as that occurring in the 15 years directly before the date of death (case
subjects)/reference date (control subjects). All statistical tests were two-sided.
We observed statistically significant increasing trends in lung cancer risk with
increasing cumulative REC and average REC intensity. Cumulative REC, lagged 15 years,
yielded a statistically significant positive gradient in lung cancer risk overall
trend = .001); among heavily exposed workers (ie, above the median of
the top quartile [REC ≥ 1005 μg/m3-y]), risk was approximately three
times greater (OR = 3.20, 95% CI = 1.33 to 7.69) than that among workers
in the lowest quartile of exposure. Among never smokers, odd ratios were 1.0, 1.47 (95%
CI = 0.29 to 7.50), and 7.30 (95% CI = 1.46 to 36.57) for workers with
15-year lagged cumulative REC tertiles of less than 8, 8 to less than 304, and 304
μg/m3-y or more, respectively. We also observed an interaction between
smoking and 15-year lagged cumulative REC (P
interaction = .086) such that the effect of each of these exposures
was attenuated in the presence of high levels of the other.
Our findings provide further evidence that diesel exhaust exposure may cause lung
cancer in humans and may represent a potential public health burden.
Current information points to an association between diesel exhaust exposure and lung
cancer and other mortality outcomes, but uncertainties remain.
We undertook a cohort mortality study of 12 315 workers exposed to diesel
exhaust at eight US non-metal mining facilities. Historical measurements and surrogate
exposure data, along with study industrial hygiene measurements, were used to derive
retrospective quantitative estimates of respirable elemental carbon (REC) exposure for
each worker. Standardized mortality ratios and internally adjusted Cox proportional
hazard models were used to evaluate REC exposure–associated risk. Analyses were
both unlagged and lagged to exclude recent exposure such as that occurring in the 15
years directly before the date of death.
Standardized mortality ratios for lung cancer (1.26, 95% confidence interval [CI]
= 1.09 to 1.44), esophageal cancer (1.83, 95% CI = 1.16 to 2.75), and
pneumoconiosis (12.20, 95% CI = 6.82 to 20.12) were elevated in the complete
cohort compared with state-based mortality rates, but all-cause, bladder cancer, heart
disease, and chronic obstructive pulmonary disease mortality were not. Differences in
risk by worker location (ever-underground vs surface only) initially obscured a positive
diesel exhaust exposure–response relationship with lung cancer in the complete
cohort, although it became apparent after adjustment for worker location. The hazard
ratios (HRs) for lung cancer mortality increased with increasing 15-year lagged
cumulative REC exposure for ever-underground workers with 5 or more years of tenure to a
maximum in the 640 to less than 1280 μg/m3-y category compared with the
reference category (0 to <20 μg/m3-y; 30 deaths compared with eight
deaths of the total of 93; HR = 5.01, 95% CI = 1.97 to 12.76) but declined
at higher exposures. Average REC intensity hazard ratios rose to a plateau around 32
μg/m3. Elevated hazard ratios and evidence of exposure–response
were also seen for surface workers. The association between diesel exhaust exposure and
lung cancer risk remained after inclusion of other work-related potentially confounding
exposures in the models and were robust to alternative approaches to exposure
The study findings provide further evidence that exposure to diesel exhaust increases
risk of mortality from lung cancer and have important public health implications.
Evidence suggests that de novo, therapy-related and benzene-induced acute myeloid leukemias (AML) occur via similar cytogenetic and genetic pathways, several of which involve aneuploidy, the loss or gain of chromosomes. Aneuploidy of specific chromosomes has been detected in benzene-related leukemia patients as well as in healthy benzene-exposed workers, suggesting that aneuploidy precedes and may be a potential mechanism underlying benzene-induced leukemia. Here, we analyzed the peripheral blood lymphocytes of 47 exposed workers and 27 unexposed controls using a novel OctoChrome fluorescence in situ hybridization (FISH) technique that simultaneously detects aneuploidy in all 24 chromosomes. Through this chromosome-wide aneuploidy study (CWAS) approach, we found heterogeneity in the monosomy and trisomy rates of the 22 autosomes when plotted against continuous benzene exposure. In addition, statistically significant, chromosome-specific increases in the rates of monosomy [5, 6, 7, 10, 16 and 19] and trisomy [5, 6, 7, 8, 10, 14, 16, 21 and 22] were found to be dose dependently associated with benzene exposure. Furthermore, significantly higher rates of monosomy and trisomy were observed in a priori defined ‘susceptible’ chromosome sets compared with all other chromosomes. Together, these findings confirm that benzene exposure is associated with specific chromosomal aneuploidies in hematopoietic cells, which suggests that such aneuploidies may play roles in benzene-induced leukemogenesis.
Transient receptor potential (TRP) vanilloid and ankyrin cation channels are activated by various noxious chemicals and may play an important role in the pathogenesis of cough. The aim was to study the influence of single nucleotide polymorphisms (SNPs) in TRP genes and irritant exposures on cough.
Nocturnal, usual, and chronic cough, smoking, and job history were obtained by questionnaire in 844 asthmatic and 2046 non-asthmatic adults from the Epidemiological study on the Genetics and Environment of Asthma (EGEA) and the European Community Respiratory Health Survey (ECRHS). Occupational exposures to vapors, gases, dusts, and/or fumes were assessed by a job-exposure matrix. Fifty-eight tagging SNPs in TRPV1, TRPV4, and TRPA1 were tested under an additive model.
Statistically significant associations of 6 TRPV1 SNPs with cough symptoms were found in non-asthmatics after correction for multiple comparisons. Results were consistent across the eight countries examined. Haplotype-based association analysis confirmed the single SNP analyses for nocturnal cough (7-SNP haplotype: p-global = 4.8 × 10-6) and usual cough (9-SNP haplotype: p-global = 4.5 × 10-6). Cough symptoms were associated with exposure to irritants such as cigarette smoke and occupational exposures (p < 0.05). Four polymorphisms in TRPV1 further increased the risk of cough symptoms from irritant exposures in asthmatics and non-asthmatics (interaction p < 0.05).
TRPV1 SNPs were associated with cough among subjects without asthma from two independent studies in eight European countries. TRPV1 SNPs may enhance susceptibility to cough in current smokers and in subjects with a history of workplace exposures.
Asthma; Gene-environment interaction; Irritant exposure; Smoking; TRP channel
Exposure to respirable elemental carbon (REC), a component of diesel exhaust (DE), was assessed for an epidemiologic study investigating the association between DE and mortality, particularly from lung cancer, among miners at eight mining facilities from the date of dieselization (1947–1967) through 1997. To provide insight into the quality of the estimates for use in the epidemiologic analyses, several approaches were taken to evaluate the exposure assessment process and the quality of the estimates. An analysis of variance was conducted to evaluate the variability of 1998–2001 REC measurements within and between exposure groups of underground jobs. Estimates for the surface exposure groups were evaluated to determine if the arithmetic means (AMs) of the REC measurements increased with increased proximity to, or use of, diesel-powered equipment, which was the basis on which the surface groups were formed. Estimates of carbon monoxide (CO) (another component of DE) air concentrations in 1976–1977, derived from models developed to predict estimated historical exposures, were compared to 1976–1977 CO measurement data that had not been used in the model development. Alternative sets of estimates were developed to investigate the robustness of various model assumptions. These estimates were based on prediction models using: (i) REC medians rather AMs, (ii) a different CO:REC proportionality than a 1:1 relation, and (iii) 5-year averages of historical CO measurements rather than modeled historical CO measurements and DE-related determinants. The analysis of variance found that in three of the facilities, most of the between-group variability in the underground measurements was explained by the use of job titles. There was relatively little between-group variability in the other facilities. The estimated REC AMs for the surface exposure groups rose overall from 1 to 5 μg m−3 as proximity to, and use of, diesel equipment increased. The alternative estimates overall were highly correlated (∼0.9) with the primary set of estimates. The median of the relative differences between the 1976–1977 CO measurement means and the 1976–1977 estimates for six facilities was 29%. Comparison of estimated CO air concentrations from the facility-specific prediction models with historical CO measurement data found an overall agreement similar to that observed in other epidemiologic studies. Other evaluations of components of the exposure assessment process found moderate to excellent agreement. Thus, the overall evidence suggests that the estimates were likely accurate representations of historical personal exposure levels to DE and are useful for epidemiologic analyses.
diesel exhaust; elemental carbon; exposure assessment; mining
Background: Previous systematic reviews have indicated that pesticide exposure is possibly associated with Parkinson disease (PD). However, considerable heterogeneity has been observed in study results.
Objective: We aimed at providing an update of the literature published on PD and exposure to pesticides by performing a systematic review and meta-analysis. In addition, we investigated whether methodological differences between studies could explain the heterogeneity in study results.
Methods: We identified studies through a systematic literature search. We calculated summary risk ratios (sRRs) for pesticide exposure and subcategories using random effects meta-analyses and investigated sources of heterogeneity by meta-regression and stratified analyses.
Results: Thirty-nine case–control studies, four cohort studies, and three cross-sectional studies were identified. An sRR of 1.62 [95% confidence interval (CI): 1.40, 1.88] for pesticide exposure (ever vs. never) was found. Summary estimates for subclasses of pesticides indicated a positive association with herbicides and insecticides, but not with fungicides. Heterogeneity in individual study results was not related to study design, source of control population, adjustment of results for potential confounders, or geographical area. However, results were suggestive for heterogeneity related to differences in the exposure assessment. Job title–based exposure assignment resulted in a higher sRR (2.5; 95% CI: 1.5, 4.1) than did assignment based on self-reported exposure (e.g., for self-reported ever/never exposure, sRR = 1.5; 95% CI: 1.3, 1.8).
Conclusions: This review affirms the evidence that exposure to herbicides and insecticides increase the risk of PD. Future studies should focus on more objective and improved methods of pesticide exposure assessment.
exposure assessment; fungicides; herbicides; insecticides; meta-analysis; Parkinson disease; pesticides; systematic review
Objectives: Few epidemiological studies have studied the effect of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on blood cytokine levels. In this study we investigated changes in plasma levels of a large panel of cytokines, chemokines, and growth factors among workers from a Dutch historical cohort occupationally exposed to chlorophenoxy herbicides and contaminants including TCDD. Methods: Eighty-five workers who had been exposed to either high (n = 47) or low (n = 38) TCDD levels more than 30 years before serum collection were included in the current investigation. Plasma level of 16 cytokines, 10 chemokines, and 6 growth factors were measured. Current plasma levels of TCDD (TCDDcurrent) were determined by high-resolution gas chromatography/isotope-dilution high-resolution mass spectrometry. TCDD blood levels at the time of last exposure (TCDDmax) were estimated using a one-compartment first order kinetic model. Results: Blood levels of most analytes had a negative association with current and estimated past maximum TCDD levels. These decreases reached formal statistical significance for fractalkine, transforming growth factor alpha (TGF-α), and fibroblast growth factor 2 (FGF2) with increasing TCDD levels. Conclusion: Our study showed a general reduction in most analyte levels with the strongest effects for fractalkine, FGF2, and TGF-α. These findings suggest that TCDD exposure could suppress the immune system and that chemokine and growth factor-dependent cellular pathway changes by TCDD may play role in TCDD toxicity and associated health effects.
dioxin; cytokine; chemokine; growth factor; NHL
Background: Asbestos is a well-recognized cause of lung cancer, but there is considerable between-study heterogeneity in the slope of the exposure–response relationship.
Objective: We considered the role of quality of the exposure assessment to potentially explain heterogeneity in exposure–response slope estimates.
Data sources: We searched PubMed MEDLINE (1950–2009) for studies with quantitative estimates of cumulative asbestos exposure and lung cancer mortality and identified 19 original epidemiological studies. One was a population-based case–control study, and the others were industry-based cohort studies.
Data extraction: Cumulative exposure categories and corresponding risks were abstracted. Exposure–response slopes [KL (lung cancer potency factor of asbestos)] were calculated using linear relative risk regression models.
Data synthesis: We assessed the quality of five exposure assessment aspects of each study and conducted random effects univariate and multivariate meta-regressions. Heterogeneity in exposure–response relationships was greater than expected by chance (I2 = 64%). Stratification by exposure assessment characteristics revealed that studies with well-documented exposure assessment, larger contrast in exposure, greater coverage of the exposure history by exposure measurement data, and more complete job histories had higher meta-KL values than did studies without these characteristics. The latter two covariates were most strongly associated with the KL value. Meta-KL values increased when we incrementally restricted analyses to higher-quality studies.
Conclusions: This meta-analysis indicates that studies with higher-quality asbestos exposure assessment yield higher meta-estimates of the lung cancer risk per unit of exposure. Potency differences for predominantly chrysotile versus amphibole asbestos-exposed cohorts become difficult to ascertain when meta-analyses are restricted to studies with fewer exposure assessment limitations.
amphiboles; asbestos; chrysotile; lung cancer; meta-analysis
Valentina Gallo and colleagues provide detailed guidance to authors to help more accurately report the findings of epidemiological studies involving biomarkers. Their guidance covers issues regarding collection, handling and storage of biological samples; laboratory methods, validity and reliability of biomarkers; specificities of study design; and ethical considerations.
This report provides an overview of the exposure assessment process for an epidemiologic study that investigated mortality, with a special focus on lung cancer, associated with diesel exhaust (DE) exposure among miners. Details of several components are provided in four other reports. A major challenge for this study was the development of quantitative estimates of historical exposures to DE. There is no single standard method for assessing the totality of DE, so respirable elemental carbon (REC), a component of DE, was selected as the primary surrogate in this study. Air monitoring surveys at seven of the eight study mining facilities were conducted between 1998 and 2001 and provided reference personal REC exposure levels and measurements for other agents and DE components in the mining environment. (The eighth facility had closed permanently prior to the surveys.) Exposure estimates were developed for mining facility/department/job/year combinations. A hierarchical grouping strategy was developed for assigning exposure levels to underground jobs [based on job titles, on the amount of time spent in various areas of the underground mine, and on similar carbon monoxide (CO, another DE component) concentrations] and to surface jobs (based on the use of, or proximity to, diesel-powered equipment). Time trends in air concentrations for underground jobs were estimated from mining facility-specific prediction models using diesel equipment horsepower, total air flow rates exhausted from the underground mines, and, because there were no historical REC measurements, historical measurements of CO. Exposures to potentially confounding agents, i.e. respirable dust, silica, radon, asbestos, and non-diesel sources of polycyclic aromatic hydrocarbons, also were assessed. Accuracy and reliability of the estimated REC exposures levels were evaluated by comparison with several smaller datasets and by development of alternative time trend models. During 1998–2001, the average measured REC exposure level by facility ranged from 40 to 384 μg m−3 for the underground workers and from 2 to 6 μg m−3 for the surface workers. For one prevalent underground job, ‘miner operator’, the maximum annual REC exposure estimate by facility ranged up to 685% greater than the corresponding 1998–2001 value. A comparison of the historical CO estimates from the time trend models with 1976–1977 CO measurements not used in the modeling found an overall median relative difference of 29%. Other comparisons showed similar levels of agreement. The assessment process indicated large differences in REC exposure levels over time and across the underground operations. Method evaluations indicated that the final estimates were consistent with those from alternative time trend models and demonstrated moderate to high agreement with external data.
diesel exhaust; elemental carbon; exposure assessment; miners
Diesel exhaust (DE) has been implicated as a potential lung carcinogen. However, the exact components of DE that might be involved have not been clearly identified. In the past, nitrogen oxides (NOx) and carbon oxides (COx) were measured most frequently to estimate DE, but since the 1990s, the most commonly accepted surrogate for DE has been elemental carbon (EC). We developed quantitative estimates of historical exposure levels of respirable elemental carbon (REC) for an epidemiologic study of mortality, particularly lung cancer, among diesel-exposed miners by back-extrapolating 1998–2001 REC exposure levels using historical measurements of carbon monoxide (CO). The choice of CO was based on the availability of historical measurement data. Here, we evaluated the relationship of REC with CO and other current and historical components of DE from side-by-side area measurements taken in underground operations of seven non-metal mining facilities. The Pearson correlation coefficient of the natural log-transformed (Ln)REC measurements with the Ln(CO) measurements was 0.4. The correlation of REC with the other gaseous, organic carbon (OC), and particulate measurements ranged from 0.3 to 0.8. Factor analyses indicated that the gaseous components, including CO, together with REC, loaded most strongly on a presumed ‘Diesel exhaust’ factor, while the OC and particulate agents loaded predominantly on other factors. In addition, the relationship between Ln(REC) and Ln(CO) was approximately linear over a wide range of REC concentrations. The fact that CO correlated with REC, loaded on the same factor, and increased linearly in log–log space supported the use of CO in estimating historical exposure levels to DE.
carbon dioxide; carbon monoxide; diesel exhaust; elemental carbon; miners; nitric oxide; nitrogen dioxide; particulates
Occupational cohort and case–control studies suggest that trichloroethylene (TCE) exposure may be associated with non-Hodgkin lymphoma (NHL) but findings are not consistent. There is a need for mechanistic studies to evaluate the biologic plausibility of this association. We carried out a cross-sectional molecular epidemiology study of 80 healthy workers that used TCE and 96 comparable unexposed controls in Guangdong, China. Personal exposure measurements were taken over a three-week period before blood collection. Ninety-six percent of workers were exposed to TCE below the current US Occupational Safety and Health Administration Permissible Exposure Limit (100 p.p.m. 8 h time-weighted average), with a mean (SD) of 22.2 (36.0) p.p.m. The total lymphocyte count and each of the major lymphocyte subsets including CD4+ T cells, CD8+ T cells, natural killer (NK) cells and B cells were significantly decreased among the TCE-exposed workers compared with controls (P < 0.05), with evidence of a dose-dependent decline. Further, there was a striking 61% decline in sCD27 plasma level and a 34% decline in sCD30 plasma level among TCE-exposed workers compared with controls. This is the first report that TCE exposure under the current Occupational Safety and Health Administration workplace standard is associated with a decline in all major lymphocyte subsets and sCD27 and sCD30, which play an important role in regulating cellular activity in subsets of T, B and NK cells and are associated with lymphocyte activation. Given that altered immunity is an established risk factor for NHL, these results add to the biologic plausibility that TCE is a possible lymphomagen.
Serum protein profiles have been investigated frequently to discover early biomarkers for breast cancer. So far, these studies used biological samples collected at or after diagnosis. This may limit these studies' value in the search for cancer biomarkers because of the often advanced tumor stage, and consequently risk of reverse causality. We present for the first time pre-diagnostic serum protein profiles in relation to breast cancer, using the Prospect-EPIC (European Prospective Investigation into Cancer and nutrition) cohort.
In a nested case-control design we compared 68 women diagnosed with breast cancer within three years after enrollment, with 68 matched controls for differences in serum protein profiles. All samples were analyzed with SELDI-TOF MS (surface enhanced laser desorption/ionization time-of-flight mass spectrometry). In a subset of 20 case-control pairs, the serum proteome was identified and relatively quantified using isobaric Tags for Relative and Absolute Quantification (iTRAQ) and online two-dimensional nano-liquid chromatography coupled with tandem MS (2D-nanoLC-MS/MS).
Two SELDI-TOF MS peaks with m/z 3323 and 8939, which probably represent doubly charged apolipoprotein C-I and C3a des-arginine anaphylatoxin (C3adesArg), were higher in pre-diagnostic breast cancer serum (p = 0.02 and p = 0.06, respectively). With 2D-nanoLC-MS/MS, afamin, apolipoprotein E and isoform 1 of inter-alpha trypsin inhibitor heavy chain H4 (ITIH4) were found to be higher in pre-diagnostic breast cancer (p < 0.05), while alpha-2-macroglobulin and ceruloplasmin were lower (p < 0.05). C3adesArg and ITIH4 have previously been related to the presence of symptomatic and/or mammographically detectable breast cancer.
We show that serum protein profiles are already altered up to three years before breast cancer detection.
Biomarkers; Breast cancer; Early diagnosis; 2D-nanoLC-MS/MS; Prospective; Proteomics; SELDI-TOF MS
Benzene, a recognized hematotoxicant and carcinogen, can damage the human immune system. We studied the association between single nucleotide polymorphisms (SNPs) in genes involved in innate immunity and benzene hematotoxicity in a cross-sectional study of workers exposed to benzene (250 workers and 140 controls). A total of 1,236 tag SNPs in 149 gene regions of six pathways were included in the analysis. Six gene regions were significant for their association with white blood cell (WBC) counts (MBP, VCAM1, ALOX5, MPO, RAC2, and CRP) based on gene-region (P < 0.05) and SNP analyses (FDR < 0.05). VCAM1 rs3176867, ALOX5 rs7099684, and MPO rs2071409 were the three most significant SNPs. They showed similar effects on WBC subtypes, especially granulocytes, lymphocytes, and monocytes. A 3-SNP block in ALOXE3 (rs7215658, rs9892383, and rs3027208) showed a global association (omnibus P = 0.0008) with WBCs even though the three SNPs were not significant individually. Our study suggests that polymorphisms in innate immunity genes may play a role in benzene-induced hematotoxicity; however, independent replication is necessary.
benzene; hematology; immunity, innate; polymorphism, single nucleotide; toxicity
Benzene, an established cause of acute myeloid leukemia (AML), may also cause one or more lymphoid malignancies in humans. Previously, we identified genes and pathways associated with exposure to high (> 10 ppm) levels of benzene through transcriptomic analyses of blood cells from a small number of occupationally exposed workers.
The goals of this study were to identify potential biomarkers of benzene exposure and/or early effects and to elucidate mechanisms relevant to risk of hematotoxicity, leukemia, and lymphoid malignancy in occupationally exposed individuals, many of whom were exposed to benzene levels < 1 ppm, the current U.S. occupational standard.
We analyzed global gene expression in the peripheral blood mononuclear cells of 125 workers exposed to benzene levels ranging from < 1 ppm to > 10 ppm. Study design and analysis with a mixed-effects model minimized potential confounding and experimental variability.
We observed highly significant widespread perturbation of gene expression at all exposure levels. The AML pathway was among the pathways most significantly associated with benzene exposure. Immune response pathways were associated with most exposure levels, potentially providing biological plausibility for an association between lymphoma and benzene exposure. We identified a 16-gene expression signature associated with all levels of benzene exposure.
Our findings suggest that chronic benzene exposure, even at levels below the current U.S. occupational standard, perturbs many genes, biological processes, and pathways. These findings expand our understanding of the mechanisms by which benzene may induce hematotoxicity, leukemia, and lymphoma and reveal relevant potential biomarkers associated with a range of exposures.
benzene; biomarker; human; microarray; transcriptomics