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Diisocyanates are a group of chemicals widely used in different industrial applications. The critical health effects related to diisocyanate exposure are isocyanate sensitisation, occupational asthma and bronchial hyperresponsiveness (BHR). Industrial air measurements and human biomonitoring (HBM) samples were gathered in specific occupational sectors to examine MDI, TDI, HDI and IPDI and the respective metabolites from Finnish screening studies. HBM data can give a more accurate picture of diisocyanate exposure, especially if workers have been exposed dermally or used respiratory protection. The HBM data were used for conducting a health impact assessment (HIA) in specific Finnish occupational sectors. For this purpose, exposure reconstruction was performed on the basis of HBM measurements of TDI and MDI exposures using a PBPK model, and a correlation equation was made for HDI exposure. Subsequently, the exposure estimates were compared to a previously published dose-response curve for excess BHR risk. The results showed that the mean and median diisocyanate exposure levels and HBM concentrations were low for all diisocyanates. In HIA, the excess risk of BHR from MDI exposure over a working life period was highest in the construction and motor and vehicle industries and repair sectors, resulting in estimated excess risks of BHR of 2.0% and 2.6%, and 113 and 244 extra BHR cases in Finland, respectively. Occupational exposure to diisocyanates must be monitored because a clear threshold for DI sensitisation cannot be established.

There is limited evidence regarding the exposure-effect relationship between lung-cancer risk and hexavalent chromium (Cr(VI)) or nickel. We estimated lung-cancer risks in relation to quantitative indices of occupational exposure to Cr(VI) and nickel and their interaction with smoking habits. We pooled 14 case-control studies from Europe and Canada, including 16 901 lung-cancer cases and 20 965 control subjects. A measurement-based job-exposure-matrix estimated job-year-region specific exposure levels to Cr(VI) and nickel, which were linked to the subjects' occupational histories. Odds ratios (OR) and associated 95% confidence intervals (CI) were calculated by unconditional logistic regression, adjusting for study, age group, smoking habits and exposure to other occupational lung carcinogens. Due to their high correlation, we refrained from mutually adjusting for Cr(VI) and nickel independently. In men, ORs for the highest quartile of cumulative exposure to CR(VI) were 1.32 (95% CI 1.19-1.47) and 1.29 (95% CI 1.15-1.45) in relation to nickel. Analogous results among women were: 1.04 (95% CI 0.48-2.24) and 1.29 (95% CI 0.60-2.86), respectively. In men, excess lung-cancer risks due to occupational Cr(VI) and nickel exposure were also observed in each stratum of never, former and current smokers. Joint effects of Cr(VI) and nickel with smoking were in general greater than additive, but not different from multiplicative. In summary, relatively low cumulative levels of occupational exposure to Cr(VI) and nickel were associated with increased ORs for lung cancer, particularly in men. However, we cannot rule out a combined classical measurement and Berkson-type of error structure, which may cause differential bias of risk estimates., (© 2022 The Authors. International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Background: Children are born with a burden of persistent organic pollutants (POPs) which may have endocrine disrupting properties and have been postulated to contribute to the rise in childhood obesity. The current evidence is equivocal, which may partly because many studies investigate the effects at one time point during childhood. We assessed associations between prenatal exposure to POPs and growth during infancy and childhood., Methods: We used data from two Belgian cohorts with cord blood measurements of five organochlorines [(dichlorodiphenyldichloroethylene (p,p'-DDE), hexachlorobenzene (HCB), polychlorinated biphenyls (PCB-138, -150, -180)] (N = 1418) and two perfluoroalkyl substances [perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS)] (N = 346). We assessed infant growth, defined as body mass index (BMI) z-score change between birth and 2 years, and childhood growth, characterized as BMI trajectory from birth to 8 years. To evaluate associations between POP exposures and infant growth, we applied a multi-pollutant approach, using penalized elastic net regression with stability selection, controlling for covariates. To evaluate associations with childhood growth, we used single-pollutant linear mixed models with random effects for child individual, parametrized using a natural cubic spline formulation., Results: PCB-153 was associated with increased and p,p'-DDE with decreased infant growth, although these results were imprecise. No clear association between any of the exposures and longer-term childhood growth trajectories was observed. We did not find evidence of effect modification by child sex., Conclusion: Our results suggest that prenatal exposure to PCB-153 and p,p'-DDE may affect infant growth in the first two years, with no evidence of more persistent effects., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objective: Women of reproductive age are exposed to ubiquitous chemicals such as phthalates, parabens, and per- and polyfluoroalkyl substances (PFAS), which have potential endocrine disrupting properties and might affect fertility. Our objective was to investigate associations between potential endocrine-disrupting chemicals (EDCs) and female fertility in two cohorts of women attending fertility clinics., Methods: In a total population of 333 women in Sweden and Estonia, we studied the associations between chemicals and female fertility, evaluating ovarian sensitivity index (OSI) as an indicator of ovarian response, as well as clinical pregnancy and live birth from fresh and frozen embryo transfers. We measured 59 chemicals in follicular fluid samples and detected 3 phthalate metabolites, di-2-ethylhexyl phthalate (DEHP) metabolites, 1 paraben, and 6 PFAS in >90% of the women. Associations were evaluated using multivariable-adjusted linear or logistic regression, categorizing EDCs into quartiles of their distributions, as well as with Bayesian Kernel Machine Regression., Results: We observed statistically significant lower OSI at higher concentrations of the sum of DEHP metabolites in the Swedish cohort (Q4 vs Q1, β = -0.21, 95% CI: -0.38, -0.05) and methylparaben in the Estonian cohort (Q3 vs Q1, β = -0.22, 95% CI: -0.44, -0.01). Signals of potential associations were also observed at higher concentrations of PFUnDA in both the combined population (Q2 vs. Q1, β = -0.16, 95% CI -0.31, -0.02) and the Estonian population (Q2 vs. Q1, β = -0.27, 95% CI -0.45, -0.08), and for PFOA in the Estonian population (Q4 vs. Q1, β = -0.31, 95% CI -0.61, -0.01). Associations of chemicals with clinical pregnancy and live birth presented wide confidence intervals., Conclusions: Within a large chemical mixture, we observed significant inverse associations levels of DEHP metabolites and methylparaben, and possibly PFUnDA and PFOA, with OSI, suggesting that these chemicals may contribute to altered ovarian function and infertility in women., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Type 2 diabetes (T2D) is thought to be influenced by environmental stressors such as air pollution and noise. Although environmental factors are interrelated, studies considering the exposome are lacking. We simultaneously assessed a variety of exposures in their association with prevalent T2D by applying penalised regression Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), and Artificial Neural Networks (ANN) approaches. We contrasted the findings with single-exposure models including consistently associated risk factors reported by previous studies., Methods: Baseline data (n = 14,829) of the Occupational and Environmental Health Cohort study (AMIGO) were enriched with 85 exposome factors (air pollution, noise, built environment, neighbourhood socio-economic factors etc.) using the home addresses of participants. Questionnaires were used to identify participants with T2D (n = 676(4.6 %)). Models in all applied statistical approaches were adjusted for individual-level socio-demographic variables., Results: Lower average home values, higher share of non-Western immigrants and higher surface temperatures were related to higher risk of T2D in the multivariable models (LASSO, RF). Selected variables differed between the two multi-variable approaches, especially for weaker predictors. Some established risk factors (air pollutants) appeared in univariate analysis but were not among the most important factors in multivariable analysis. Other established factors (green space) did not appear in univariate, but appeared in multivariable analysis (RF). Average estimates of the prediction error (logLoss) from nested cross-validation showed that the LASSO outperformed both RF and ANN approaches., Conclusions: Neighbourhood socio-economic and socio-demographic characteristics and surface temperature were consistently associated with the risk of T2D. For other physical-chemical factors associations differed per analytical approach., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Objectives: Never-smoking women in Xuanwei (XW), China, have some of the highest lung cancer rates in the country. This has been attributed to the combustion of smoky coal used for indoor cooking and heating. The aim of this study was to evaluate the spectrum of cause-specific mortality in this unique population, including among those who use smokeless coal, considered 'cleaner' coal in XW, as this has not been well-characterised., Design: Cohort study., Setting: XW, a rural region of China where residents routinely burn coal for indoor cooking and heating., Participants: Age-adjusted, cause-specific mortality rates between 1976 and 2011 were calculated and compared among lifetime smoky and smokeless coal users in a cohort of 42 420 men and women from XW. Mortality rates for XW women were compared with those for a cohort of predominately never-smoking women in Shanghai., Results: Mortality in smoky coal users was driven by cancer (41%), with lung cancer accounting for 88% of cancer deaths. In contrast, cardiovascular disease (CVD) accounted for 32% of deaths among smokeless coal users, with 7% of deaths from cancer. Total cancer mortality was four times higher among smoky coal users relative to smokeless coal users, particularly for lung cancer (standardised rate ratio (SRR)=17.6). Smokeless coal users had higher mortality rates of CVD (SRR=2.9) and pneumonia (SRR=2.5) compared with smoky coal users. These patterns were similar in men and women, even though XW women rarely smoked cigarettes. Women in XW, regardless of coal type used, had over a threefold higher rate of overall mortality, and most cause-specific outcomes were elevated compared with women in Shanghai., Conclusions: Cause-specific mortality burden differs in XW based on the lifetime use of different coal types. These observations provide evidence that eliminating all coal use for indoor cooking and heating is an important next step in improving public health particularly in developing countries., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Competing Interests: The authors report no conflicts of interest.

Objectives: Regulators frequently deviate from health-based recommendations when setting occupational exposure limits, but the impact on workers' health is rarely made explicit. We present a quantitative evaluation of the expected impact of recently proposed regulatory limits for occupational diesel engine exhaust (DEE) exposure on the excess burden of lung cancer (LC) in Europe., Methods: We used a lifetable approach, basing our analyses on the DEE exposure distribution in a large general population study, as well as the 5% prevalence used in earlier DEE burden calculations. We evaluated the effects of intervention on DEE exposures according to a health based limit (1 ug/m 3 of elemental carbon (EC)) and both Dutch (10 ug/m 3 ) and European (50 ug/m 3 ) proposed regulatory limit values. Results were expressed as individual excess lifetime risks (ELR), total excess number of cases and population attributable fraction of LC., Results: The ELR for the EU working population was estimated to be 341/10 000 workers based on our empirical exposure distribution and 46/10 000 workers based on the 5% prevalence. Implementing the proposed health based DEE limit would reduce the ELR by approximately 93%, while the proposed regulatory limits of 10 and 50 ug/m 3 EC would reduce the ELR by 51% and 21%, respectively., Discussion: Although the proposed regulatory limits are expected to reduce the number of DEE related LC deaths, the residual ELRs are still significantly higher than the targets used for deriving health-based risk limits. The number of additional cases of LC in Europe due to DEE exposure, therefore, remains significant., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

COVID-19 is characterised by a dysregulated immune response, that involves signalling lipids acting as mediators of the inflammatory process along the innate and adaptive phases. To promote understanding of the disease biochemistry and provide targets for intervention, we applied a range of LC-MS platforms to analyse over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). The second publication in a series reports the results of quantitative LC-MS/MS profiling of 63 small lipids including oxylipins, free fatty acids, and endocannabinoids. Compared to samples taken from ward patients, intensive care unit (ICU) patients had 2−4-fold lower levels of arachidonic acid (AA) and its cyclooxygenase-derived prostanoids, as well as lipoxygenase derivatives, exhibiting negative correlations with inflammation markers. The same derivatives showed 2−5-fold increases in recovering ward patients, in paired comparison to early hospitalisation. In contrast, ICU patients showed elevated levels of oxylipins derived from poly-unsaturated fatty acids (PUFA) by non-enzymatic peroxidation or activity of soluble epoxide hydrolase (sEH), and these oxylipins positively correlated with markers of macrophage activation. The deficiency in AA enzymatic products and the lack of elevated intermediates of pro-resolving mediating lipids may result from the preference of alternative metabolic conversions rather than diminished stores of PUFA precursors. Supporting this, ICU patients showed 2-to-11-fold higher levels of linoleic acid (LA) and the corresponding fatty acyl glycerols of AA and LA, all strongly correlated with multiple markers of excessive immune response. Our results suggest that the altered oxylipin metabolism disrupts the expected shift from innate immune response to resolution of inflammation.

The COVID-19 pandemic raised a need to characterise the biochemical response to SARS-CoV-2 infection and find biological markers to identify therapeutic targets. In support of these aims, we applied a range of LC-MS platforms to analyse over 100 plasma samples from patients with varying COVID-19 severity and with detailed clinical information on inflammatory responses (>30 immune markers). The first publication in a series reports the results of quantitative LC-MS/MS profiling of 56 amino acids and derivatives. A comparison between samples taken from ICU and ward patients revealed a notable increase in ten post-translationally modified amino acids that correlated with markers indicative of an excessive immune response: TNF-alpha, neutrophils, markers for macrophage, and leukocyte activation. Severe patients also had increased kynurenine, positively correlated with CRP and cytokines that induce its production. ICU and ward patients with high IL-6 showed decreased levels of 22 immune-supporting and anti-oxidative amino acids and derivatives (e.g., glutathione, GABA). These negatively correlated with CRP and IL-6 and positively correlated with markers indicative of adaptive immune activation. Including corresponding alterations in convalescing ward patients, the overall metabolic picture of severe COVID-19 reflected enhanced metabolic demands to maintain cell proliferation and redox balance, alongside increased inflammation and oxidative stress.

Background: Several studies have confirmed associations between air pollution and overall mortality, but it is unclear to what extent these associations reflect causal relationships. Moreover, few studies to our knowledge have accounted for complex mixtures of air pollution. In this study, we evaluate the causal effects of a mixture of air pollutants on overall mortality in a large, prospective cohort of Dutch individuals., Methods: We evaluated 86,882 individuals from the LIFEWORK study, assessing overall mortality between 2013 and 2017 through national registry linkage. We predicted outdoor concentration of five air pollutants (PM2.5, PM10, NO2, PM2.5 absorbance, and oxidative potential) with land-use regression. We used logistic regression and mixture modeling (weighted quantile sum and boosted regression tree models) to identify potential confounders, assess pollutants' relevance in the mixture-outcome association, and investigate interactions and nonlinearities. Based on these results, we built a multivariate generalized propensity score model to estimate the causal effects of pollutant mixtures., Results: Regression model results were influenced by multicollinearity. Weighted quantile sum and boosted regression tree models indicated that all components contributed to a positive linear association with the outcome, with PM2.5 being the most relevant contributor. In the multivariate propensity score model, PM2.5 (OR=1.18, 95% CI: 1.08-1.29) and PM10 (OR=1.02, 95% CI: 0.91-1.14) were associated with increased odds of mortality per interquartile range increase., Conclusion: Using novel methods for causal inference and mixture modeling in a large prospective cohort, this study strengthened the causal interpretation of air pollution effects on overall mortality, emphasizing the primary role of PM2.5 within the pollutant mixture., Competing Interests: The authors report no conflicts of interest., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Real-time quantitative PCR (qPCR) is an affordable method to quantify antimicrobial resistance gene (ARG) targets, allowing comparisons of ARG abundance along animal production chains., Objectives: We present a comparison of ARG abundance across various animal species, production environments and humans in Europe. AMR variation sources were quantified. The correlation of ARG abundance between qPCR data and previously published metagenomic data was assessed., Methods: A cross-sectional study was conducted in nine European countries, comprising 9572 samples. qPCR was used to quantify abundance of ARGs [aph(3')-III, erm(B), sul2, tet(W)] and 16S rRNA. Variance component analysis was conducted to explore AMR variation sources. Spearman's rank correlation of ARG abundance values was evaluated between pooled qPCR data and earlier published pooled metagenomic data., Results: ARG abundance varied strongly among animal species, environments and humans. This variation was dominated by between-farm variation (pigs) or within-farm variation (broilers, veal calves and turkeys). A decrease in ARG abundance along pig and broiler production chains ('farm to fork') was observed. ARG abundance was higher in farmers than in slaughterhouse workers, and lowest in control subjects. ARG abundance showed a high correlation (Spearman's ρ > 0.7) between qPCR data and metagenomic data of pooled samples., Conclusions: qPCR analysis is a valuable tool to assess ARG abundance in a large collection of livestock-associated samples. The between-country and between-farm variation of ARG abundance could partially be explained by antimicrobial use and farm biosecurity levels. ARG abundance in human faeces was related to livestock antimicrobial resistance exposure., (© The Author(s) 2022. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy.)

Background: Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure-response curve (ERC) modeling when data across the exposure range are sparse., Methods: We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies., Results: A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [<40 parts per million (ppm)-years] from this model were comparable, but more precise when the ERC was derived using all available data than when using AML data only. Allowing for between-study heterogeneity, RRs and 95% prediction intervals (95% PI) at 5 ppm-years were 1.58 (95% PI, 1.01-3.22) and 1.44 (95% PI, 0.85-3.42), respectively., Conclusions: Integrating the available epidemiologic, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation., Impact: By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.See related commentary by Keil, p. 695., (©2021 American Association for Cancer Research.)

Little is known about personal and time-integrated exposure to past and current used pesticides in agricultural areas and within-family exposure similarities. We aimed to assess exposure to pesticides using silicone wristbands in child/guardian pairs living on farms and in villages within two agricultural areas in South Africa. Using silicone wristbands, we quantified 21 pesticides in child/guardian pairs in 38 households over six days in 2018. Levels (in ng/g wristband) of pesticides and their transformation products (12 current-use pesticides and nine organochlorine pesticides) were measured using GC-MS/MS. We assessed the correlation between pesticide levels and between household members using Spearman correlation coefficients (r s ). Multivariable generalized least squares (GLS) models, using household id as intercept, were used to determine level of agreement between household members, exposure differences between children and guardians and exposure predictors (study area, household location [farm vs. village] and household pesticide use). We detected 16 pesticides with highest detection frequencies for deltamethrin (89%), chlorpyrifos (78%), boscalid (56%), cypermethrin (55%), and p,p'-DDT (48%). Most wristbands (92%) contained two or more pesticides (median seven (range one to 12)). Children had higher concentrations than guardians for four pesticides. Correlation between the pesticide levels were in most cases moderate (rs 0.30-0.68) and stronger in children than in guardians. Five pesticides showed moderate to strong correlation between household members, with the strongest correlation for boscalid (r s 0.84). Exposure differences between the two agricultural areas were observed for chlorpyrifos, diazinon, prothiofos, cypermethrin, boscalid, p,p'-DDT and p,p'-DDE and within areas for cypermethrin. We showed that for several pesticides children had higher exposure levels than guardians. The positive correlations observed for child/guardian pairs living in the same household suggest non-occupational shared exposure pathways in these communities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Objectives: Benzene is a known haematoxin and leukemogen that can cause benzene poisoning (BP), that is, a persistent reduction in white cell counts that is strongly associated with increased risk of lymphohaematopoietic malignancies. Data are needed on the exposure-response, particularly at low doses and susceptible populations for clinical and regulatory purposes., Methods: In a case-cohort study among 110 631 Chinese workers first employed 1949-1987 and followed up during 1972-1999, we evaluated BP risk according to benzene exposure level and investigated risk modification by subject (sex, attained age) and exposure-related factors (latency, exposure windows, age at first benzene exposure, coexposure to toluene) using excess relative risk and excess absolute risk models., Results: There were 538 BP cases and 909 benzene-exposed referents. The exposure metric with best model fit was cumulative benzene exposure during a 5-year risk window, followed by a 9-month lag period before BP diagnosis. Estimated excess absolute risk of BP at age 60 increased from 0.5% for subjects in the lowest benzene exposure category (>0 to 10 ppm-years) to 5.0% for those in the highest category (>100 ppm-years) compared with unexposed subjects. Increased risks were apparent at low cumulative exposure levels and for workers who were first exposed at <30 years of age., Conclusions: Our data show a clear association between benzene exposure and BP, beginning at low cumulative benzene exposure levels with no threshold, and with higher risks for workers exposed at younger ages. These findings are important because BP has been linked to a strongly increased development of lymphohaematopoietic malignancies., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Characteristics of the urban environment may contain upstream drivers of obesity. However, research is lacking that considers the combination of environmental factors simultaneously., Objectives: We aimed to explore what environmental factors of the urban exposome are related to body mass index (BMI), and evaluated the consistency of findings across multiple statistical approaches., Methods: A cross-sectional analysis was conducted using baseline data from 14,829 participants of the Occupational and Environmental Health Cohort study. BMI was obtained from self-reported height and weight. Geocoded exposures linked to individual home addresses (using 6-digit postcode) of 86 environmental factors were estimated, including air pollution, traffic noise, green-space, built environmental and neighborhood socio-demographic characteristics. Exposure-obesity associations were identified using the following approaches: sparse group Partial Least Squares, Bayesian Model Averaging, penalized regression using the Minimax Concave Penalty, Generalized Additive Model-based boosting Random Forest, Extreme Gradient Boosting, and Multiple Linear Regression, as the most conventional approach. The models were adjusted for individual socio-demographic variables. Environmental factors were ranked according to variable importance scores attributed by each approach and median ranks were calculated across these scores to identify the most consistent associations., Results: The most consistent environmental factors associated with BMI were the average neighborhood value of the homes, oxidative potential of particulate matter air pollution (OP), healthy food outlets in the neighborhood (5 km buffer), low-income neighborhoods, and one-person households in the neighborhood. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households and smaller amount of healthy food retailers. Higher BMI levels were observed in low-income neighborhoods, with lower average house values, lower share of one-person households, smaller amounts of healthy food retailers and higher OP levels. Across the approaches, we observed consistent patterns of results based on model's capacity to incorporate linear or nonlinear associations., Discussion: The pluralistic analysis on environmental obesogens strengthens the existing evidence on the role of neighborhood socioeconomic position, urbanicity and air pollution., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objectives: Psychosocial factors have been hypothesized to increase the risk of cancer. This study aims (1) to test whether psychosocial factors (depression, anxiety, recent loss events, subjective social support, relationship status, general distress, and neuroticism) are associated with the incidence of any cancer (any, breast, lung, prostate, colorectal, smoking-related, and alcohol-related); (2) to test the interaction between psychosocial factors and factors related to cancer risk (smoking, alcohol use, weight, physical activity, sedentary behavior, sleep, age, sex, education, hormone replacement therapy, and menopausal status) with regard to the incidence of cancer; and (3) to test the mediating role of health behaviors (smoking, alcohol use, weight, physical activity, sedentary behavior, and sleep) in the relationship between psychosocial factors and the incidence of cancer., Methods: The psychosocial factors and cancer incidence (PSY-CA) consortium was established involving experts in the field of (psycho-)oncology, methodology, and epidemiology. Using data collected in 18 cohorts (N = 617,355), a preplanned two-stage individual participant data (IPD) meta-analysis is proposed. Standardized analyses will be conducted on harmonized datasets for each cohort (stage 1), and meta-analyses will be performed on the risk estimates (stage 2)., Conclusion: PSY-CA aims to elucidate the relationship between psychosocial factors and cancer risk by addressing several shortcomings of prior meta-analyses., (© 2021 The Authors. Brain and Behavior published by Wiley Periodicals LLC.)

Background: Multiple epidemiological studies have shown that exposure to single pesticide active ingredients or chemical groups is associated with adverse neurobehavioral outcomes in farmers. In agriculture, exposure to multiple pesticide active ingredients is the rule, rather than exception. Therefore, occupational studies on neurobehavioral effects of pesticides should account for potential co-exposure confounding., Methods: We conducted a cross-sectional study of 288 Ugandan smallholder farmers between September and December 2017. We collected data on self-reported use of pesticide products during the 12 months prior to survey and estimated yearly exposure-intensity scores for 14 pesticide active ingredients using a semi-quantitative exposure algorithm. We administered 11 neurobehavioral tests to assess five neurobehavioral domains. We implemented a Bayesian Model-Averaging (BMA) approach to examine the association between exposure to multiple pesticides and neurobehavioral outcomes, while accounting for multiple testing. We applied two levels of inference to determine (1) which neurobehavioral outcomes were associated with overall pesticide exposure (marginal inclusion probability (MIP) for covariate-only models <0.5) and (2) which specific pesticide active ingredients were associated with these outcomes (MIP for models where active ingredient was included >0.5)., Results: Seventy-two percent of farmers reported use of pesticide products that contained at least one of 14 active ingredients, while the applicators used in median three different active ingredients (interquartile range (IQR) 4) in the 12 months prior to the study. The most widely used active ingredients were glyphosate (79%), cypermethrin (60%), and mancozeb (55%). We found that overall pesticide exposure was associated with impaired visual memory (Benton Visual Retention Test (BVRT)), language (semantic verbal fluency test), perceptual-motor function (Finger tapping test), and complex attention problems (Trail making A test and digit symbol test). However, when we looked at the associations for individual active ingredients, we only observed a positive association between glyphosate exposure and impaired visual memory (-0.103 [95% Bayesian Credible Interval (BCI)] [-0.24, 0] units in BVRT scores per interquartile range (IQR) increase in annual exposure to glyphosate, relative to a median [IQR] of 6 [3] units in BVRT across the entire study population)., Conclusions: We found that overall pesticide exposure was associated with several neurobehavioral outcome variables. However, when we examined individual pesticide active ingredients, we observed predominantly null associations, except for a positive association between glyphosate exposure and impaired visual memory. Additional epidemiologic studies are needed to evaluate glyphosate's neurotoxicity, while accounting for co-pollutant confounding., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background and Aims: Prenatal chemical exposure has frequently been associated with reduced fetal growth although results have been inconsistent. Most studies associate single pollutant exposure to this health outcome, even though this does not reflect real life situations as humans are exposed to many pollutants during their life time. The objective of this study is to investigate the association between prenatal exposure to a mixture of persistent environmental chemicals and birth weight using multipollutant models., Methods: We combined exposure biomarker data measured in cord blood samples of 1579 women from four Flemish birth cohorts collected over a 10 years' time period. The common set of available and detectable exposure measures in these cohorts are three polychlorinated biphenyls (PCB) congeners (138, 153 and 180), hexachlorobenzene (HCB), dichlorodiphenyldichloroethylene (p,p'-DDE) and the metals cadmium and lead. Multiple linear regression (MLR), Bayesian Information Criterion (BIC), penalized regression using minimax concave penalty (MCP) and Bayesian Adaptive Sampling (BAS) were applied to assess the influence of multiple pollutants in a single analysis on birth weight, adjusted for a priori selected covariates., Results: In the pooled dataset, a median (P25-P75) birth weight and gestational age of 3420 (3140-3700) grams and 39 (39-40) weeks was observed respectively. The median contaminant levels in cord blood were: 15.8, 26.5, 18.0, 16.9 and 91.5 ng/g lipid for PCB 138, PCB 153, PCB 180, HCB and p,p'-DDE, respectively, 0.075 µg/L for cadmium and 9.7 µg/L for lead. According to the applied statistical methods for multipollutant assessment, p,p'-DDE and PCB 180 were most consistently associated with birth weight. In addition, PCB 153 was selected when applying MCP and BAS. An inverse association with birth weight was found for the PCB congeners, while an increased birth weight was observed for elevated levels of p,p'-DDE., Conclusions: Assessing the health risk of combinations of exposure biomarkers reflects better real-world situations and thereby allows more effective risk assessment. Our results add to the existing evidence based on detrimental effects of PCBs on birth weight and indicate a possible increase in birth weight due to p,p'-DDE (while correcting for PCBs)., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

COVID-19 differs substantially between individuals, ranging from mild to severe or even fatal. Heterogeneity in the immune response against SARS-COV-2 likely contributes to this. Therefore, we explored the temporal dynamics of key cellular and soluble mediators of innate and adaptive immune activation in relation to COVID-19 severity and progression. Forty-four patients with a PCR-proven diagnosis of COVID-19 were included. Extensive cellular (leukocytes and T-lymphocyte subsets) and serological immune profiling (cytokines, soluble cell surface molecules, and SARS-CoV-2 antibodies) was performed at hospital admission and every 3-4 days during hospitalization. Measurements and disease outcome were compared between patients with an unfavorable (IC admission and/or death) and favorable (all others) outcome. Patients with an unfavorable outcome had higher leukocyte numbers at baseline, mostly due to increased neutrophils, whereas lymphocyte and monocyte numbers were reduced. CRP, IL-6, CCL2, CXCL10, and GM-CSF levels were higher at baseline in the unfavorable group, whereas IL-7 levels were lower. SARS-CoV-2 antibodies were more frequently absent in the unfavorable group. Longitudinal analysis revealed delayed kinetics of activated CD4 and CD8 T-lymphocyte subsets in the unfavorable group. Furthermore, whereas CRP, IL-6, CXCL10, and GM-CSF declined in the favorable group, these cytokines declined with delayed kinetics, remained increased, or even increased further in the unfavorable group. Our data indicate a state of increased innate immune activation in COVID19-patients with an unfavorable outcome at hospital admission, which remained over time, as compared with patients with a favorable outcome.

Background: While international agreement supports a causal relationship of benzene exposure with acute myeloid leukemia, there is debate about benzene and lymphoid neoplasm risks., Methods: In a case-cohort study with follow-up of 110 631 Chinese workers during 1972-1999, we evaluated benzene exposure-response for non-Hodgkin lymphoma (NHL), lymphoid leukemias (LL), acute lymphocytic leukemia (ALL), and total lymphoid neoplasms (LN). We estimated benzene exposures using state-of-the-art hierarchical modeling of occupational factors calibrated with historical routine measurements and evaluated cumulative exposure-response using Cox regression., Results: NHL and other specified LN were increased in exposed vs unexposed workers. However, there was no evidence of exposure-response for NHL or other specified LN. Based on a linear exposure-response, relative risks at 100 parts per million-years (RR at 100 ppm-years) for cumulative benzene exposure using a 2-year lag (exposure at least 2 years before the time at risk) were 1.05 for NHL (95 percent confidence interval (CI) = 0.97, 1.27; 32 cases), 1.11 for LL (95% CI < 0, 1.66; 12 cases), 1.21 for ALL (95% CI < 0, 3.53; 10 cases), and 1.02 for total LN (95% CI < 0, 1.16; 49 cases). No statistically significant exposure-response trends were apparent for these LN for 2 to <10-year or ≥10-year lags. NHL risks were not significantly modified by sex, age, or year at first exposure, attained age, or time since exposure., Conclusion: Given the study strengths and limitations, we found little evidence of exposure-response for benzene and NHL, LL, ALL, or total LN, although NHL and other specified LN were increased in exposed vs unexposed individuals., (© 2020 Wiley Periodicals LLC.)

Background: Beneficial effects of pulmonary rehabilitation at high-altitude (HAPR) in patients with severe refractory asthma have been reported earlier, but evidence for the effectiveness is limited., Aim: To investigate the effectiveness of high-altitude pulmonary rehabilitation to comparable treatment at sea-level (LAPR) on patient outcome parameters., Methods: Adults with severe refractory asthma living in The Netherlands were included. Treatment consisted of a 12-week personalized multidisciplinary rehabilitation program either at high-altitude (Davos Switzerland) (n = 93) or in a tertiary lung center at sea-level in The Netherlands (n = 45). At baseline, after treatment, and during 12 months follow-up asthma related quality of life (AQLQ), asthma control (ACQ), pulmonary function and OCS-dose were assessed. Patients could not be randomized resulting in different asthma populations. Groups were compared using linear regression analysis (ANCOVA) adjusted for baseline values, in addition to age, atopy, smoking history, BMI and gender., Results: After treatment, and at 12 months follow-up, improved AQLQ(0.92,p < 0.001 and 0.82,p = 0.001, respectively), ACQ(-0.87,p < 0.001 and -0.69,p = 0.008, respectively) and lower maintenance OCS dose (Unadjusted linear regression analysis-5.29 mg, p = 0.003 and Crude Odds Ratio-1.67, p = 0.003, respectively) were observed in the HAPR-group compared to the LAPR group. Patients receiving HAPR also had less asthma exacerbations (≥1 exacerbation: 20% vs 60%,p < 0.001) and showed improvement in lung function (%predFEV 1 3.4%,p = 0.014) compared to the LAPR group, but at 12 months no differences between groups were observed., Conclusion: HAPR resulted in a larger improvement in patient outcome parameters compared to LAPR, on the long run the improvement in patient reported symptoms and lower maintenance OCS-dose persists. Underlying factors that explain this observed effect need to be investigated., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Background: The genotoxicity of benzene has been investigated in dozens of biomonitoring studies, mainly by studying (classical) chromosomal aberrations (CAs) or micronuclei (MN) as markers of DNA damage. Both have been shown to be predictive of future cancer risk in cohort studies and could, therefore, potentially be used for risk assessment of genotoxicity-mediated cancers., Objectives: We sought to estimate an exposure-response curve (ERC) and quantify between-study heterogeneity using all available quantitative evidence on the cytogenetic effects of benzene exposure on CAs and MN respectively., Methods: We carried out a systematic literature review and summarized all available data of sufficient quality using meta-analyses. We assessed the heterogeneity in slope estimates between studies and conducted additional sensitivity analyses to assess how various study characteristics impacted the estimated ERC., Results: Sixteen CA (1,356 individuals) and 13  MN studies (2,097 individuals) were found to be eligible for inclusion in a meta-analysis. Studies where benzene was the primary genotoxic exposure and that had adequate assessment of both exposure and outcomes were used for the primary analysis. Estimated slope estimates were an increase of 0.27% CA [(95% CI: 0.08%, 0.47%); based on the results from 4 studies] and 0.27% MN [(95% CI: - 0.23 % , 0.76%); based on the results from 7 studies] per parts-per-million benzene exposure. We observed considerable between-study heterogeneity for both end points ( I 2 > 90 % )., Discussion: Our study provides a systematic, transparent, and quantitative summary of the literature describing the strong association between benzene exposure and accepted markers of genotoxicity in humans. The derived consensus slope can be used as a best estimate of the quantitative relationship between real-life benzene exposure and genetic damage in future risk assessment. We also quantitate the large between-study heterogeneity that exists in this literature, a factor which is crucial for the interpretation of single-study or consensus slopes. https://doi.org/10.1289/EHP6404.

Rationale: Although the carcinogenicity of diesel engine exhaust has been demonstrated in multiple studies, little is known regarding exposure-response relationships associated with different exposure subgroups and different lung cancer subtypes. Objectives: We expanded on a previous pooled case-control analysis on diesel engine exhaust and lung cancer by including three additional studies and quantitative exposure assessment to evaluate lung cancer and subtype risks associated with occupational exposure to diesel exhaust characterized by elemental carbon (EC) concentrations. Methods: We used a quantitative EC job-exposure matrix for exposure assessment. Unconditional logistic regression models were used to calculate lung cancer odds ratios and 95% confidence intervals (CIs) associated with various metrics of EC exposure. Lung cancer excess lifetime risks (ELR) were calculated using life tables accounting for all-cause mortality. Additional stratified analyses by smoking history and lung cancer subtypes were performed in men. Measurements and Main Results: Our study included 16,901 lung cancer cases and 20,965 control subjects. In men, exposure response between EC and lung cancer was observed: odds ratios ranged from 1.09 (95% CI, 1.00-1.18) to 1.41 (95% CI, 1.30-1.52) for the lowest and highest cumulative exposure groups, respectively. EC-exposed men had elevated risks in all lung cancer subtypes investigated; associations were strongest for squamous and small cell carcinomas and weaker for adenocarcinoma. EC lung cancer exposure response was observed in men regardless of smoking history, including in never-smokers. ELR associated with 45 years of EC exposure at 50, 20, and 1 μg/m 3 were 3.0%, 0.99%, and 0.04%, respectively, for both sexes combined. Conclusions: We observed a consistent exposure-response relationship between EC exposure and lung cancer in men. Reduction of workplace EC levels to background environmental levels will further reduce lung cancer ELR in exposed workers.

Rationale: Millions of workers around the world are exposed to respirable crystalline silica. Although silica is a confirmed human lung carcinogen, little is known regarding the cancer risks associated with low levels of exposure and risks by cancer subtype. However, little is known regarding the disease risks associated with low levels of exposure and risks by cancer subtype. Objectives: We aimed to address current knowledge gaps in lung cancer risks associated with low levels of occupational silica exposure and the joint effects of smoking and silica exposure on lung cancer risks. Methods: Subjects from 14 case-control studies from Europe and Canada with detailed smoking and occupational histories were pooled. A quantitative job-exposure matrix was used to estimate silica exposure by occupation, time period, and geographical region. Logistic regression models were used to estimate exposure-disease associations and the joint effects of silica exposure and smoking on risk of lung cancer. Stratified analyses by smoking history and cancer subtypes were also performed. Measurements and Main Results: Our study included 16,901 cases and 20,965 control subjects. Lung cancer odds ratios ranged from 1.15 (95% confidence interval, 1.04-1.27) to 1.45 (95% confidence interval, 1.31-1.60) for groups with the lowest and highest cumulative exposure, respectively. Increasing cumulative silica exposure was associated ( P trend < 0.01) with increasing lung cancer risks in nonsilicotics and in current, former, and never-smokers. Increasing exposure was also associated ( P trend ≤ 0.01) with increasing risks of lung adenocarcinoma, squamous cell carcinoma, and small cell carcinoma. Supermultiplicative interaction of silica exposure and smoking was observed on overall lung cancer risks; superadditive effects were observed in risks of lung cancer and all three included subtypes. Conclusions: Silica exposure is associated with lung cancer at low exposure levels. An exposure-response relationship was robust and present regardless of smoking, silicosis status, and cancer subtype.

Outdoor air pollution is a growing public health concern, particularly in urban settings. However, there are limited epidemiological data on outdoor air pollution in rural areas with substantial levels of air pollution attributed to solid fuel burning for household cooking and heating. Xuanwei and Fuyuan are rural counties in China where the domestic combustion of locally sourced bituminous ("smoky") coal has been associated with the highest lung cancer rates in China. We previously assessed indoor and personal air pollution exposures in this area; however, the influence of indoor coal combustion and household ventilation on outdoor air pollution has not been assessed. Therefore, we measured outdoor fine particulate matter (PM 2.5 ), species of polycyclic aromatic hydrocarbons (PAHs) including naphthalene (NAP) and the known carcinogen benzo(a)pyrene (BaP), sulfur dioxide (SO 2 ), and nitrogen dioxide (NO 2 ) over two consecutive 24-h sampling periods in 29 villages. Just over half of the villages were revisited two to nine months after the initial sampling period to repeat all measurements. The overall geometric mean (GM) of outdoor PM 2.5 , BaP, NAP, and NO 2 were 45.3 µg/m 3 , 9.7 ng/m 3 , 707.7 ng/m 3 , and 91.5 µg/m 3 , respectively. Using linear mixed effects models, we found that burning smoky coal was associated with higher outdoor BaP concentrations [GM ratio (GMR) = 2.79] and lower outdoor SO 2 detection rates (GMR = 0.43), compared to areas burning smokeless coal. Areas with predominantly ventilated stoves (> 50% of stoves) had higher outdoor BaP (GMR = 1.49) compared to areas with fewer ventilated stoves. These results show that outdoor air pollution in a rural region of China was associated with the type of coal used for cooking and heating indoors and the presence of stove ventilation. Our findings suggest that efforts of household stove improvement to reduce indoor air pollution have resulted in higher outdoor air pollution levels. Further reducing adverse health effects in rural villages from household coal combustion will require the use of cleaner fuel types.

Background: Previous results from the Diesel Exhaust in Miners Study (DEMS) demonstrated a positive exposure-response relation between lung cancer and respirable elemental carbon (REC), a key surrogate for diesel exhaust exposure. Two issues have been raised regarding DEMS: (i) the use of historical carbon monoxide (CO) measurements to calibrate models used for estimating historical exposures to REC in the DEMS exposure assessment; and (ii) potential confounding by radon., Methods: We developed alternative REC estimates using models that did not rely on CO for calibration, but instead relied on estimated use of diesel equipment, mine ventilation rates and changes in diesel engine emission rates over time. These new REC estimates were used to quantify cumulative REC exposure for each subject in the nested case-control study. We conducted conditional logistic regression to estimate odds ratios (ORs) and 95% confidence intervals for lung cancer. To evaluate the impact of including radon as a potential confounder, we estimated ORs for average REC intensity adjusted for cumulative radon exposure in underground miners., Results: Validation of the new REC exposure estimates indicated that they overestimated historical REC by 200-400%, compared with only 10% for the original estimates. Effect estimates for lung cancer using these alternative REC exposures or adjusting for radon typically changed by <10% when compared with the original estimates., Conclusions: These results emphasize the robustness of the DEMS findings, support the use of CO for model calibration and confirm that radon did not confound the DEMS estimates of the effect of diesel exposure on lung cancer mortality., (© The Author(s) 2019. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Background: Lifetime use of bituminous ('smoky') coal is associated with nearly a 100-fold higher risk of lung cancer mortality compared with anthracite ('smokeless') coal use in rural Xuanwei, China, among women. Risk of mortality from ischaemic heart disease (IHD) and stroke for these coal types has not been evaluated., Methods: A cohort of 16 323 non-smoking women in Xuanwei, who were lifetime users of either smoky or smokeless coal, were followed up from 1976 to 2011. We estimated hazard ratios (HRs) and 95% confidence intervals (CI) to evaluate lifetime use of coal types and stoves in the home in relation to risk of IHD and stroke mortality., Results: Among lifetime users of smokeless coal, higher average exposure intensity (≥4 tons/year vs <2.5 tons/year, HR = 7.9, 95% CI = 3.5-17.8; Ptrend =<0.0001) and cumulative exposure (>64 ton-years vs ≤28 ton-years, HR = 6.5, 95% CI = 1.5-28.3; Ptrend =0.003) during follow-up and over their lifetime was associated with increased IHD mortality, and ventilated stove use dramatically reduced this risk (HR = 0.2, 95% CI 0.1-0.5). Higher cumulative exposure to smoky coal during follow-up showed positive associations with IHD mortality, but the evidence for other metrics was less consistent compared with associations with smokeless coal use., Conclusions: Higher use of smokeless coal, which is burned throughout China and is generally regarded to be a cleaner fuel type, is associated with IHD mortality. Use of cleaner fuels or stove interventions may be effective in reducing the increasing burden of IHD in developing regions that currently rely on smokeless coal for cooking and heating., (Published by Oxford University Press on behalf of the International Epidemiological Association 2019. This work is written by US Government employees and is in the public domain in the US.)

Background: We investigated the association between cigarette smoking and risk of amyotrophic lateral sclerosis (ALS) in a pooled analysis of population-based case-control studies and explored the independent effects of intensity, duration and time-since-quitting., Methods: ALS cases and controls, matched by age, sex and region, were recruited in the Netherlands, Italy and Ireland (*Euro-MOTOR project). Demographics and detailed lifetime smoking histories were collected through questionnaires. Effects of smoking status, intensity (cigarettes/day), duration (years), pack-years and time-since-quitting (years) on ALS risk were estimated using logistic regression models, adjusting for age, sex, alcohol, education and centre. We further investigated effect modification of the linear effects of pack-years by intensity, duration and time-since-quitting using excess OR (eOR) models., Results: Analyses were performed on 1410 cases and 2616 controls. Pack-years were positively associated with ALS risk; OR=1.26 (95% CI: 1.03 to 1.54) for the highest quartile compared with never smokers. This association appeared to be predominantly driven by smoking duration (p trend =0.001) rather than intensity (p trend =0.86), although the trend for duration disappeared after adjustment for time-since-quitting. Time-since-quitting was inversely related to ALS (p trend <0.0001). The eOR decreased with time-since-quitting smoking, until about 10 years prior to disease onset. High intensity smoking with shorter duration appeared more deleterious than lower intensity for a longer duration., Conclusions: Our findings provide further support for the association between smoking and ALS. Pack-years alone may be insufficient to capture effects of different smoking patterns. Time-since-quitting appeared to be an important factor, suggesting that smoking may be an early disease trigger., Competing Interests: Competing interests: EB reports grants from UCB-PHARMA, personal fees from MA-Provider, grants from American ALS Association, grants from EISAI, grants from Shire. AC reports personal fees from Biogen, grants from Italfarmaco, personal fees from Roche, personal fees from Cytokinetics, personal fees from Mitsubishi Tanabe. OH has received speaking honoraria from Novartis, Biogen Idec, Sanofi Aventis and Merck-Serono; and has been a member of advisory panels for Biogen Idec, Allergen, Ono Pharmaceuticals, Novartis, Cytokinetics and Sanofi Aventis. LvdB serves on scientific advisory boards for the Prinses Beatrix Spierfonds, Thierry Latran Foundation, Biogen, Cytokinetics, Orion and Sarepta. SP, AEV, FD, JV, LP, GL, EP, JHV and RV report no potential conflicts of interest., (© Author(s) (or their employer(s)) 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Various established occupational lung carcinogens are also suspected risk factors for laryngeal cancer. However, individual studies are often inadequate in size to investigate this relatively rare outcome. Other limitations include imprecise exposure assessment and inadequate adjustment for confounders., Methods: This study applied a quantitative job exposure matrix (SYN-JEM) for four established occupational lung carcinogens to five case-control studies within the International Head and Neck Cancer Epidemiology Consortium. We used occupational histories for 2256 laryngeal cancer cases and 7857 controls recruited from 1989 to 2007. We assigned quantitative exposure levels for asbestos, respirable crystalline silica, chromium-VI, and chromium-VI and nickel combined (to address highly correlated exposures) via SYN-JEM. We assessed effects of occupational exposure on cancer risk for males (asbestos, respirable crystalline silica, chromium-VI, and chromium-VI and nickel combined) and females (asbestos and respirable crystalline silica), adjusting for age, study, tobacco smoking, alcohol consumption, and asbestos exposure where relevant., Results: Among females, odds ratios (ORs) were increased for ever versus never exposed. Among males, P values for linear trend were <0.05 for estimated cumulative exposure (all agents) and <0.05 for exposure duration (respirable crystalline silica, chromium-VI, and chromium-VI and nickel combined); strongest associations were for asbestos at >90th percentile cumulative exposure (OR = 1.3, 95% confidence interval [CI] = 1.0, 1.6), respirable crystalline silica at 30+ years duration (OR = 1.4, 95% CI = 1.2, 1.7) and 75th-90th percentile cumulative exposure (OR = 1.4, 95% CI = 1.1, 1.8), chromium-VI at >75th percentile cumulative exposure (OR = 1.9, 95% CI = 1.2, 3.0), and chromium-VI and nickel combined at 20-29 years duration (OR = 1.5, 95% CI = 1.1, 2.2)., Conclusions: These findings support hypotheses of causal links between four lung carcinogens (asbestos, respirable crystalline silica, chromium-VI, and nickel) and laryngeal cancer.

Background: To curb increasing resistance rates, responsible antimicrobial use (AMU) is needed, both in human and veterinary medicine. In human healthcare, antimicrobial stewardship programmes (ASPs) have been implemented worldwide to improve appropriate AMU. No ASPs have been developed for and implemented in companion animal clinics yet., Objectives: The objective of the present study was to implement and evaluate the effectiveness of an ASP in 44 Dutch companion animal clinics. The objectives of the ASP were to increase awareness on AMU, to decrease total AMU whenever possible and to shift AMU towards 1st choice antimicrobials, according to Dutch guidelines on veterinary AMU., Methods: The study was designed as a prospective, stepped-wedge, intervention study, which was performed from March 2016 until March 2018. The multifaceted intervention was developed using previous qualitative and quantitative research on current prescribing behaviour in Dutch companion animal clinics. The number of Defined Daily Doses for Animal (DDDAs) per clinic (total, 1st, 2nd and 3rd choice AMU) was used to quantify systemic AMU. Monthly AMU data were described using a mixed effect time series model with auto-regression. The effect of the ASP was modelled using a step function and a change in the (linear) time trend., Results: A statistically significant decrease of 15% (7%-22%) in total AMU, 15% (5%-24%) in 1st choice AMU and 26% (17%-34%) in 2nd choice AMU was attributed to participation in the ASP, on top of the already ongoing time trends. Use of 3rd choice AMs did not significantly decrease by participation in the ASP. The change in total AMU became more prominent over time, with a 16% (4%-26%) decrease in (linear) time trend per year., Conclusions: This study shows that, although AMU in Dutch companion animal clinics was already decreasing and changing, AMU could be further optimised by participation in an antimicrobial stewardship programme., Competing Interests: The authors have declared that no competing interests exist.

Background: Lung cancer rates among never-smoking women in Xuanwei and Fuyuan in China are among the highest in the world and have been attributed to the domestic use of smoky (bituminous) coal for heating and cooking. However, the key components of coal that drive lung cancer risk have not been identified., Objectives: We aimed to investigate the relationship between lifelong exposure to the constituents of smoky coal (and other fuel types) and lung cancer., Methods: Using a population-based case-control study of lung cancer among 1,015 never-smoking female cases and 485 controls, we examined the association between exposure to 43 household air pollutants and lung cancer. Pollutant predictions were derived from a comprehensive exposure assessment study, which included methylated polycyclic aromatic hydrocarbons (PAHs), which have never been directly evaluated in an epidemiological study of any cancer. Hierarchical clustering and penalized regression were applied in order to address high colinearity in exposure variables., Results: The strongest association with lung cancer was for a cluster of 25 PAHs [odds ratio (OR): 2.21; 95% confidence interval (CI): 1.67, 2.87 per 1 standard deviation (SD) change], within which 5-methylchrysene (5-MC), a mutagenic and carcinogenic PAH, had the highest individual observed OR (5.42; 95% CI: 0.94, 27.5). A positive association with nitrogen dioxide ([Formula: see text]) was also observed (OR: 2.06; 95% CI: 1.19, 3.49). By contrast, neither benzo(a)pyrene (BaP) nor fine particulate matter with aerodynamic diameter [Formula: see text] ([Formula: see text]) were associated with lung cancer in the multipollutant models., Conclusions: To our knowledge, this is the first study to comprehensively evaluate the association between lung cancer and household air pollution (HAP) constituents estimated over the entire life course. Given the global ubiquity of coal use domestically for indoor cooking and heating and commercially for electric power generation, our study suggests that more extensive monitoring of coal combustion products, including methylated PAHs, may be warranted to more accurately assess health risks and develop prevention strategies from this exposure. https://doi.org/10.1289/EHP4913.

Any antimicrobial use (AMU) in humans and animals selects for antimicrobial resistance (AMR) and responsible AMU should therefore be promoted both in human and veterinary medicine. Insight into current AMU in companion animal clinics is necessary to be able to optimise antimicrobial (AM) prescribing behaviour. The objective of this study was to describe systemic AMU in 44 Dutch companion animal clinics over a 3-year time period (2012-2015), using retrospectively collected data. The number of Defined Daily Doses for Animals (DDDAs) per month and per clinic were calculated from prescription data for total, 1st, 2nd and 3rd choice AMU (classification according to Dutch policy on veterinary AMU). Time trends, seasonality and the influence of potential determinants (e.g., the number of dogs, cats and rabbits per clinic and other clinic characteristics) were explored using statistical modelling. Overall, the findings show that total AMU decreased over time and a shift in used classes of antimicrobials towards more 1st choice AMs was visible. Mean total AMU decreased from 1.82 DDDA/year in 2012-2013 to 1.56 DDDA/year in 2014-2015. Aminopenicillins, with and without clavulanic acid, accounted for the largest group of antimicrobials used; 38.7% (2012-2013), 40.2% (2013-2014) and 39.3% (2014-2015) of total AMU, respectively. Strong seasonal differences in AMU were found, with highest AMU in July-August and lowest in February-March. The distribution of different animal species per clinic appeared to affect AMU as well. In clinics with a larger proportion of dogs, 2nd choice AMU was significantly higher, whereas in clinics with a larger proportion of rabbits, 2nd choice AMU was significantly lower. Despite the decrease of AMU during the study period, there is still room for improvement left, especially with regard to the antimicrobial classes prescribed. According to Dutch classification of veterinary AMU, 1st choice AMs should be used as empirical therapy. A decrease in 2nd (might select for ESBL-producing bacteria) and 3rd choice AMU (i.e. fluoroquinolones and 3rd generation cephalosporins) should be aimed for., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Coal types vary around the world because of geochemical differences in their source deposits; however, the influence of coal emissions from different deposits on human health remains unexplored. To address this issue, we conducted the first study of the relationship between coal use from various deposits and lung cancer risk in Xuanwei and Fuyuan, counties in China where lung cancer rates are among the highest in the world among female never-smokers due to use of bituminous ("smoky") coal for heating and cooking. We conducted a population-based case-control study of 1031 lung cancer cases and 493 controls among never-smoking women in Xuanwei and Fuyuan. Logistic regression models were used to estimate associations between coal use from various deposits across the lifecourse and lung cancer risk. There was substantial heterogeneity in risks by coal deposit (p = 7.8E-05). Compared to non-smoky coal users, risks by smoky coal deposit ranged from OR = 7.49 (95% CI: 3.43-16.38) to OR = 33.40 (95% CI: 13.07-85.34). Further, women born into homes that used smoky coal and subsequently changed to non-smoky coal had a higher risk (OR = 10.83 (95% CI: 4.61-25.46)) than women born into homes that used non-smoky coal and changed to smoky coal (OR = 4.74 (95% CI: 2.03-11.04, p difference = 0.04)). Our study demonstrates that various sources of coal have considerably different impact on lung cancer in this population and suggests that early-life exposure to carcinogenic emissions may exert substantial influence on health risks later in life. These factors should be considered when evaluating the health risks posed by exposure to coal combustion emissions., (© 2018 UICC.)

Background: There is international consensus that benzene exposure is causally related to acute myeloid leukemia (AML), and more recent evidence of association with myelodysplastic syndromes (MDS). However, there are uncertainties about the exposure response, particularly risks by time since exposure and age at exposure., Methods: In a case-cohort study in 110 631 Chinese workers followed up during 1972-1999 we evaluated combined MDS/AML (n = 44) and chronic myeloid leukemia (n = 18). We estimated benzene exposures using hierarchical modeling of occupational factors calibrated with historical routine measurements, and evaluated exposure response for cumulative exposure and average intensity using Cox regression; P values were two-sided., Results: Increased MDS/AML risk with increasing cumulative exposure in our a priori defined time window (2 to <10 years) before the time at risk was suggested (Ptrend = 08). For first exposure (within the 2 to <10-year window) before age 30 years, the exposure response was stronger (P = .004) with rate ratios of 1.12 (95% confidence interval [CI] = 0.27 to 4.29), 5.58 (95% CI = 1.65 to 19.68), and 4.50 (95% CI = 1.22 to 16.68) for cumulative exposures of more than 0 to less than 40, 40 to less than 100, and at least 100 ppm-years, respectively, compared with no exposure. There was little evidence of exposure response after at least 10 years (Ptrend = .94), regardless of age at first exposure. Average intensity results were generally similar. The risk for chronic myeloid leukemia was increased in exposed vs unexposed workers, but appeared to increase and then decrease with increasing exposure., Conclusion: For myeloid neoplasms, the strongest effects were apparent for MDS/AML arising within 10 years of benzene exposure and for first exposure in the 2 to less than 10-year window before age 30 years., (Published by Oxford University Press 2018.)

Background: Land use regression (LUR) models are commonly used in environmental epidemiology to assign spatially resolved estimates of air pollution to study participants. In this setting, estimated LUR model parameters are assumed to be transportable to a main study (the ''transportability assumption''). We provide an empirical illustration of how violation of this assumption can affect exposure predictions and bias health-effect estimates., Methods: We based our simulation on two existing LUR models, one for nitrogen dioxide, the other for particulate matter with aerodynamic diameter <2.5 μm. We assessed the impact of error in exposure determinants used in the LUR models on resultant air pollution predictions and on bias in an exposure-health-effect estimate assessed in a hypothetical cohort. We assigned error to predictors at monitoring sites (sites used to develop the LUR model) and at prediction sites (sites for which exposure predictions were needed), allowing for different error levels between site types., Results: Realistic error in the exposure determinants of the selected LUR models did not induce large additional error in exposure predictions and resulted in only minor (<1%) bias in health-effect estimates. Bias in the health-effect estimates strongly increased (up to 13.6%) when exposure determinant errors were different for monitoring sites than for prediction sites., Conclusions: These results suggest that only modest reductions in bias in estimated exposure health-effects are to be expected from reducing error in exposure determinants. It is important to avoid heterogeneous errors in exposure determinants between monitoring sites and prediction sites to satisfy the transportability assumption and avoid bias in estimated exposure health-effects.

Land use regression (LUR) models for air pollutants are often developed using multiple linear regression techniques. However, in the past decade linear (stepwise) regression methods have been criticized for their lack of flexibility, their ignorance of potential interaction between predictors, and their limited ability to incorporate highly correlated predictors. We used two training sets of ultrafine particles (UFP) data (mobile measurements (8200 segments, 25 s monitoring per segment), and short-term stationary measurements (368 sites, 3 × 30 min per site)) to evaluate different modeling approaches to estimate long-term UFP concentrations by estimating precision and bias based on an independent external data set (42 sites, average of three 24-h measurements). Higher training data R 2 did not equate to higher test R 2 for the external long-term average exposure estimates, making the argument that external validation data are critical to compare model performance. Machine learning algorithms trained on mobile measurements explained only 38-47% of external UFP concentrations, whereas multivariable methods like stepwise regression and elastic net explained 56-62%. Some machine learning algorithms (bagging, random forest) trained on short-term measurements explained modestly more variability of external UFP concentrations compared to multiple linear regression and regularized regression techniques. In conclusion, differences in predictive ability of algorithms depend on the type of training data and are generally modest.

Exposure to traffic-related air pollution (TRAP) has been associated with adverse health outcomes but underlying biological mechanisms remain poorly understood. Two randomized crossover trials were used here, the Oxford Street II (London) and the TAPAS II (Barcelona) studies, where volunteers were allocated to high or low air pollution exposures. The two locations represent different exposure scenarios, with Oxford Street characterized by diesel vehicles and Barcelona by normal mixed urban traffic. Levels of five and four pollutants were measured, respectively, using personal exposure monitoring devices. Serum samples were used for metabolomic profiling. The association between TRAP and levels of each metabolic feature was assessed. All pollutant levels were significantly higher at the high pollution sites. 29 and 77 metabolic features were associated with at least one pollutant in the Oxford Street II and TAPAS II studies, respectively, which related to 17 and 30 metabolic compounds. Little overlap was observed across pollutants for metabolic features, suggesting that different pollutants may affect levels of different metabolic features. After observing the annotated compounds, the main pathway suggested in Oxford Street II in association with NO 2 was the acyl-carnitine pathway, previously found to be associated with cardio-respiratory disease. No overlap was found between the metabolic features identified in the two studies., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Recent prospective studies have shown that dysregulation of the immune system may precede the development of B-cell lymphomas (BCL) in immunocompetent individuals. However, to date, the studies were restricted to a few immune markers, which were considered separately. Using a nested case-control study within two European prospective cohorts, we measured plasma levels of 28 immune markers in samples collected a median of 6 years before diagnosis (range 2.01-15.97) in 268 incident cases of BCL (including multiple myeloma [MM]) and matched controls. Linear mixed models and partial least square analyses were used to analyze the association between levels of immune marker and the incidence of BCL and its main histological subtypes and to investigate potential biomarkers predictive of the time to diagnosis. Linear mixed model analyses identified associations linking lower levels of fibroblast growth factor-2 (FGF-2 p = 7.2 × 10 -4 ) and transforming growth factor alpha (TGF-α, p = 6.5 × 10 -5 ) and BCL incidence. Analyses stratified by histological subtypes identified inverse associations for MM subtype including FGF-2 (p = 7.8 × 10 -7 ), TGF-α (p = 4.08 × 10 -5 ), fractalkine (p = 1.12 × 10 -3 ), monocyte chemotactic protein-3 (p = 1.36 × 10 -4 ), macrophage inflammatory protein 1-alpha (p = 4.6 × 10 -4 ) and vascular endothelial growth factor (p = 4.23 × 10 -5 ). Our results also provided marginal support for already reported associations between chemokines and diffuse large BCL (DLBCL) and cytokines and chronic lymphocytic leukemia (CLL). Case-only analyses showed that Granulocyte-macrophage colony stimulating factor levels were consistently higher closer to diagnosis, which provides further evidence of its role in tumor progression. In conclusion, our study suggests a role of growth-factors in the incidence of MM and of chemokine and cytokine regulation in DLBCL and CLL., (© 2018 The Authors International Journal of Cancer published by John Wiley & Sons Ltd on behalf of UICC.)

Objective: In epidemiological and clinical studies, whole blood assay (WBA) has been used as a measure to characterize inter-individual differences in the cytokine response of individuals exposed to inflammatory agents, such as endotoxins. Several short-time repeatability studies have shown stable cytokine levels in individuals over periods of days, weeks or months, but little is known about the long-term stability of cytokine reactivity., Methods: We studied cytokine response levels in LPS-stimulated whole blood in a cohort of 193 farmers and agricultural industry workers at two time points with a five-year interval., Results: IL-10 and IL-1β responses measured with a five-year time interval showed a weak positive correlation (r = 0.22 and 0.27, respectively), whereas no correlation was observed for TNFα (r = 0.06). Cytokine reactivity measured repeatedly at the same time point showed high correlations (IL-10 r = 0.80, IL-1β r = 0.53 and TNFα r = 0.74), suggesting that the observed weak correlations over time are reflective of actual variations in cytokine reactivity over time., Conclusions: Repeatability of ex vivo cytokine reactivity showed to be differential for the measured cytokines, being more stable for IL-10 and IL-1β than for TNFα. However, in general, repeatability of ex vivo cytokine reactivity was weak, reflecting that cytokine reactivity can mostly be explained by (short term) intra-individual (immunological) or time varying environmental factors and less by genetic or other time-invariant factors. Therefore, WBA should be regarded as a viable tool to study relationships with current health status and exposure, and only partially as a predictor for a future response., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Chronic inflammation may be involved in cancer development and progression. Using 28 inflammatory-related proteins collected from prospective blood samples from two case-control studies nested in the Italian component of the European Prospective Investigation into Cancer and nutrition (n = 261) and in the Northern Sweden Health and Disease Study (n = 402), we tested the hypothesis that an inflammatory score is associated with breast cancer (BC) and Β-cell Non-Hodgkin Lymphoma (B-cell NHL, including 68 multiple myeloma cases) onset. We modelled the relationship between this inflammatory score and the two cancers studied: (BC and B-cell NHL) using generalised linear models, and assessed, through adjustments the role of behaviours and lifestyle factors. Analyses were performed by cancer types pooling both populations, and stratified by cohorts, and time to diagnosis. Our results suggested a lower inflammatory score in B-cell NHL cases (β = -1.28, p = 0.012), and, to lesser, extent with BC (β = -0.96, p = 0.33) compared to controls, mainly driven by cancer cases diagnosed less than 6 years after enrolment. These associations were not affected by subsequent adjustments for potential intermediate confounders, notably behaviours. Sensitivity analyses indicated that our findings were not affected by the way the inflammatory score was calculated. These observations call for further studies involving larger populations, larger variety of cancer types and repeated measures of larger panel of inflammatory markers.

Objectives: There is growing recognition that simultaneously assessing multiple exposures may reduce false positive discoveries and improve epidemiological effect estimates. We evaluated the performance of statistical methods for identifying exposure-outcome associations across various data structures typical of environmental and occupational epidemiology analyses., Methods: We simulated a case-control study, generating 100 data sets for each of 270 different simulation scenarios; varying the number of exposure variables, the correlation between exposures, sample size, the number of effective exposures and the magnitude of effect estimates. We compared conventional analytical approaches, that is, univariable (with and without multiplicity adjustment), multivariable and stepwise logistic regression, with variable selection methods: sparse partial least squares discriminant analysis, boosting, and frequentist and Bayesian penalised regression approaches., Results: The variable selection methods consistently yielded more precise effect estimates and generally improved selection accuracy compared with conventional logistic regression methods, especially for scenarios with higher correlation levels. Penalised lasso and elastic net regression both seemed to perform particularly well, specifically when statistical inference based on a balanced weighting of high sensitivity and a low proportion of false discoveries is sought., Conclusions: In this extensive simulation study with multicollinear data, we found that most variable selection methods consistently outperformed conventional approaches, and demonstrated how performance is influenced by the structure of the data and underlying model., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Background: Exposure to disinfection by-products (DBPs) in drinking water and chlorinated swimming pools are associated with adverse health outcomes, but biological mechanisms remain poorly understood., Objectives: Evaluate short-term changes in metabolic profiles in response to DBP exposure while swimming in a chlorinated pool., Materials and Methods: The PISCINA-II study (EXPOsOMICS project) includes 60 volunteers swimming 40min in an indoor pool. Levels of most common DBPs were measured in water and in exhaled breath before and after swimming. Blood samples, collected before and 2h after swimming, were used for metabolic profiling by liquid-chromatography coupled to high-resolution mass-spectrometry. Metabolome-wide association between DBP exposures and each metabolic feature was evaluated using multivariate normal (MVN) models. Sensitivity analyses and compound annotation were conducted., Results: Exposure levels of all DBPs in exhaled breath were higher after the experiment. A total of 6,471 metabolic features were detected and 293 features were associated with at least one DBP in exhaled breath following Bonferroni correction. A total of 333 metabolic features were associated to at least one DBP measured in water or urine. Uptake of DBPs and physical activity were strongly correlated and mutual adjustment reduced the number of statistically significant associations. From the 293 features, 20 could be identified corresponding to 13 metabolites including compounds in the tryptophan metabolism pathway., Conclusion: Our study identified numerous molecular changes following a swim in a chlorinated pool. While we could not explicitly evaluate which experiment-related factors induced these associations, molecular characterization highlighted metabolic features associated with exposure changes during swimming., (Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Swimming in a chlorinated pool results in high exposure levels to disinfection by-products (DBPs), which have been associated with an increased risk of bladder cancer., Objectives: By studying molecular responses at the blood transcriptome level we examined the biological processes associated with exposure to these compounds., Methods: Whole-genome gene expression and microRNA analysis was performed on blood samples collected from 43 volunteers before and 2h after 40min swimming in an indoor chlorinated pool (PISCINAII study). Exposure to THMs was measured in exhaled breath. Heart rate and kcal expenditure were measured as proxies for physical activity. Associations between exposure levels and gene expression were assessed using multivariate normal models (MVN), correcting for age, body mass index and sex. A Bonferroni threshold at 5% was applied., Results: MVN-models for the individual exposures identified 1778 genes and 23 microRNAs that were significantly associated with exposure to at least one DBP. Due to co-linearity it was not possible to statistically disentangle responses to DBP exposure from those related to physical activity. However, after eliminating previously reported transcripts associated with physical activity a large number of hits remained associated with DBP exposure. Among those, 9 were linked with bladder and 31 with colon cancer. Concordant microRNA/mRNA expressions were identified in association with DBP exposure for hsa-mir-22-3p and hsa-miR-146a-5p and their targets RCOR1 and TLR4, both related to colon cancer in association with DBP exposure., Conclusions: Short-term exposure to low levels of DBPs shows genomics responses that may be indicative of increased cancer risk., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Exposure to disinfectants and disinfection byproducts (DBPs) due to swimming in chlorinated water has been associated with allergic and respiratory health effects, including asthma., Objectives: Biological mechanisms contributing to these associations are largely unknown. We hypothesized a potential pathway involving modulation of the immune system., Methods: We assessed levels of immune markers (CCL11, CCL22, CXCL10, CRP, EGF, GCSF, IL-8, IL-17, IL-1RA, MPO, VEGF, Periostin) in serum collected from 30 women and 29 men before and after 40min of swimming in a chlorinated pool. Exposure to DBPs was assessed by measuring bromodichloromethane, bromoform, chloroform, and dibromochloromethane in exhaled breath before and after swimming. Covariate data including information on physical activity was available through questionnaires and measurements. We assessed the association between indicators of swimming in a chlorinated pool and changes in serum immune marker concentrations using linear regression with bivariate normal distributions and adjusted for multiple comparisons by applying the Benjamini-Hochberg procedure., Results: We observed a significant decrease in serum concentrations of IL-8 (-12.53%; q=2.00e-03), CCL22 (-7.28%; q=4.00e-04), CCL11 (-7.15%; q=9.48e-02), CRP (-7.06%; q=4.68e-05), and CXCL10 (-13.03%; q=6.34e-14) and a significant increase in IL-1RA (20.16%; q=4.18e-06) from before to after swimming. Associations with quantitative measurements of DBPs or physical activity were similar in direction and strength. Most of the observed associations became non-significant when we adjusted the effects of exposure to DBPs for physical activity or vice-versa., Conclusions: Our study indicates that swimming in a chlorinated pool induces perturbations of the immune response through acute alterations of patterns of cytokine and chemokine secretion. The observed effects could not be uniquely attributed to either exposure to DBPs or physical activity. Evidence in the literature suggests that observed decreases in immune markers are possibly due to an immunosuppressive effect of DBPs, while the increase in IL-1RA might be due to physical activity., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Background: Occupational allergic diseases are a major problem in some workplaces like in the baking industry. Diagnostic rules have been used in surveillance but not yet in the occupational respiratory clinic., Objective: To develop diagnostic models predicting baker's asthma and rhinitis among bakery workers at high risk of sensitisation to bakery allergens referred to a specialised clinic., Methods: As part of a medical surveillance programme, clinical evaluation was performed on 436 referred Dutch bakery workers at high risk for sensitisation to bakery allergens. Multivariable logistic regression analyses were developed to identify the predictors of onset of baker's asthma and rhinitis using a self-administered questionnaire and compared using a structured medical history. Performance of models was assessed by discrimination (area under the receiver operating characteristics curve) and calibration (Hosmer-Lemeshow test). Internal validity of the models was assessed by a bootstrapping procedure., Results: The prediction models included the predictors of work-related upper and lower respiratory symptoms, the presence of allergy and allergic symptoms, use of medication (last year), type of job, type of shift and working years with symptoms (≥10 years). The developed models derived from both self-administered questionnaire and the medical history showed a relatively good discrimination and calibration. The internal validity showed that the models developed had satisfactory discrimination. To improve calibrations of models, shrinkage factors were applied to model coefficients., Conclusion: The probability of allergic asthma and rhinitis in referred bakers could be estimated by diagnostic models based on both a self-administered questionnaire and by taking a structured medical history., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Background: There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the totality of human environmental exposures from conception onwards). Uncovering such combined effects is challenging owing to the large number of exposures, several of them being highly correlated. We performed a simulation study in an exposome context to compare the performance of several statistical methods that have been proposed to detect statistical interactions., Methods: Simulations were based on an exposome including 237 exposures with a realistic correlation structure. We considered several statistical regression-based methods, including two-step Environment-Wide Association Study (EWAS 2 ), the Deletion/Substitution/Addition (DSA) algorithm, the Least Absolute Shrinkage and Selection Operator (LASSO), Group-Lasso INTERaction-NET (GLINTERNET), a three-step method based on regression trees and finally Boosted Regression Trees (BRT). We assessed the performance of each method in terms of model size, predictive ability, sensitivity and false discovery rate., Results: GLINTERNET and DSA had better overall performance than the other methods, with GLINTERNET having better properties in terms of selecting the true predictors (sensitivity) and of predictive ability, while DSA had a lower number of false positives. In terms of ability to capture interaction terms, GLINTERNET and DSA had again the best performances, with the same trade-off between sensitivity and false discovery proportion. When GLINTERNET and DSA failed to select an exposure truly associated with the outcome, they tended to select a highly correlated one. When interactions were not present in the data, using variable selection methods that allowed for interactions had only slight costs in performance compared to methods that only searched for main effects., Conclusions: GLINTERNET and DSA provided better performance in detecting two-way interactions, compared to other existing methods.

Background: We hypothesize that biological perturbations due to exposure to ambient air pollution are reflected in gene expression levels in peripheral blood mononuclear cells., Methods: We assessed the association between exposure to ambient air pollution and genome-wide gene expression levels in peripheral blood mononuclear cells collected from 550 healthy subjects participating in cohorts from Italy and Sweden. Annual air pollution estimates of nitrogen oxides (NOx) at time of blood collection (1990-2006) were available from the ESCAPE study. In addition to univariate analysis and two variable selection methods to investigate the association between expression and exposure to NOx, we applied gene set enrichment analysis to assess overlap between our most perturbed genes and gene sets hypothesized to be related to air pollution and cigarette smoking. Finally, we assessed associations between NOx and CpG island methylation at the identified genes., Results: Annual average NOx exposure in the Italian and Swedish cohorts was 94.2 and 6.7 µg/m, respectively. Long-term exposure to NOx was associated with seven probes in the Italian cohort and one probe in the Swedish (and combined) cohorts. For genes AHCYL2 and MTMR2, changes were also seen in the methylome. Genes hypothesized to be downregulated due to cigarette smoking were enriched among the most strongly downregulated genes from our study., Conclusion: This study provides evidence of subtle changes in gene expression related to exposure to long-term NOx. On a global level, the observed changes in the transcriptome may indicate similarities between air pollution and tobacco induced changes in the transcriptome.

Background: We recently identified 700 genes whose expression levels were predictive of chronic lymphocytic leukemia (CLL) in a genome-wide gene expression analysis of prediagnostic blood from future cases and matched controls. We hypothesized that a large fraction of these markers were likely related to early disease manifestations. Here we aim to gain a better understanding of the natural history of the identified markers by comparing results from our prediagnostic analysis, the only prediagnostic analysis to date, to results obtained from a meta-analysis of a series of publically available transcriptomics profiles obtained in incident CLL cases and controls., Results: We observed considerable overlap between the results from our prediagnostic study and the clinical CLL signals (p-value for overlap Bonferroni significant markers 0.01; p-value for overlap nominal significant markers < 2.20e-16). We observed similar patterns with time to diagnosis and similar functional annotations for the markers that were identified in both settings compared to the markers that were only identified in the prediagnostic study. These results suggest that both gene sets operate in similar pathways., Conclusion: An overlap exists between expression levels of genes predictive of CLL identified in prediagnostic blood and expression levels of genes associated to CLL at the clinical stage. Our analysis provides insight in a set of genes for which expression levels can be used to follow the time-course of the disease; providing an opportunity to study CLL progression in more detail in future studies.