Last data update: May 13, 2024. (Total: 46773 publications since 2009)
Records 1-10 (of 10 Records) |
Query Trace: Portier C[original query] |
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Concordance between sites of tumor development in humans and in experimental animals for 111 agents that are carcinogenic to humans
Krewski D , Rice JM , Bird M , Milton B , Collins B , Lajoie P , Billard M , Grosse Y , Cogliano VJ , Caldwell JC , Rusyn II , Portier CJ , Melnick RL , Baan RA , Little J , Zielinski JM . J Toxicol Environ Health B Crit Rev 2019 22 203-236 Since the inception of the IARC Monographs Programme in the early 1970s, this Programme has developed 119 Monograph Volumes on more than 1000 agents for which there exists some evidence of cancer risk to humans. Of these, 120 agents were found to meet the criteria for classification as carcinogenic to humans (Group 1). Volume 100 of the IARC Monographs, compiled in 2008-2009 and published in 2012, provided a review and update of the 107 Group 1 agents identified as of 2009. These agents were divided into six broad categories: (I) pharmaceuticals; (II) biological agents; (III) arsenic, metals, fibers and dusts; (IV) radiation; (V) personal habits and indoor combustions; and (VI) chemical agents and related occupations. The Group I agents reviewed in Volume 100, as well as five additional Group 1 agents defined in subsequent Volumes of the Monographs, were used to assess the degree of concordance between sites where tumors originate in humans and experimental animals including mice, rats, hamsters, dogs, and non-human primates using an anatomically based tumor nomenclature system, representing 39 tumor sites and 14 organ and tissue systems. This evaluation identified 91 Group 1 agents with sufficient evidence (82 agents) or limited evidence (9 agents) of carcinogenicity in animals. The most common tumors observed in both humans and animals were those of the respiratory system including larynx, lung, and lower respiratory tract. In humans, respiratory system tumors were noted for 31 of the 111 distinct Group 1 carcinogens identified up to and including Volume 109 of the IARC Monographs, comprising predominantly 14 chemical agents and related occupations in category VI; seven arsenic, metals, fibers, and dusts in category III, and five personal habits and indoor combustions in category V. Subsequent to respiratory system tumors, those in lymphoid and hematopoietic tissues (26 agents), the urothelium (18 agents), and the upper aerodigestive tract (16 agents) were most often seen in humans, while tumors in digestive organs (19 agents), skin (18 agents), and connective tissues (17 agents) were frequently seen in animals. Exposures to radiation, particularly X- and gamma-radiation, and tobacco smoke were associated with tumors at multiple sites in humans. Although the IARC Monographs did not emphasize tumor site concordance between animals and humans, substantial concordance was detected for several organ and tissue systems, even under the stringent criteria for sufficient evidence of carcinogenicity used by IARC. Of the 60 agents for which at least one tumor site was identified in both humans and animals, 52 (87%) exhibited tumors in at least one of the same organ and tissue systems in humans and animals. It should be noted that some caution is needed in interpreting concordance at sites where sample size is particularly small. Although perfect (100%) concordance was noted for agents that induce tumors of the mesothelium, only two Group 1 agents that met the criteria for inclusion in the concordance analysis caused tumors at this site. Although the present analysis demonstrates good concordance between animals and humans for many, but not all, tumor sites, limitations of available data may result in underestimation of concordance. |
The Next Generation of Risk Assessment Multiyear Study- Highlights of Findings, Applications to Risk Assessment and Future Directions.
Cote I , Andersen ME , Ankley GT , Barone S , Birnbaum LS , Boekelheide K , Bois FY , Burgoon LD , Chiu WA , Crawford-Brown D , Crofton KM , DeVito M , Devlin RB , Edwards SW , Guyton KZ , Hattis D , Judson RS , Knight D , Krewski D , Lambert J , Maull EA , Mendrick D , Paoli GM , Patel CJ , Perkins EJ , Poje G , Portier CJ , Rusyn I , Schulte PA , Simeonov A , Smith MT , Thayer KA , Thomas RS , Thomas R , Tice RR , Vandenberg JJ , Villeneuve DL , Wesselkamper S , Whelan M , Whittaker C , White R , Xia M , Yauk C , Zeise L , Zhao J , DeWoskin RS . Environ Health Perspect 2016 124 (11) 1671-1682 BACKGROUND: The Next Generation (NexGen) of Risk Assessment effort is a multiyear collaboration among several organizations evaluating new, potentially more efficient molecular, computational and systems biology approaches to risk assessment. This paper summarizes our findings, suggests applications to risk assessment, and identifies strategic research directions. OBJECTIVE: Our specific objectives were to test whether advanced biological data and methods could better inform our understanding of public health risks posed by environmental exposures. METHODS: New data and methods were applied and evaluated for use in hazard identification and dose-response assessment. Biomarkers of exposure and effect, and risk characterization were also examined. Consideration was given to various decision contexts with increasing regulatory and public health impacts. Data types included transcriptomics, genomics, and proteomics; methods included molecular epidemiology and clinical studies, bioinformatic knowledge mining, pathway and network analyses, short-duration in vivo and in vitro bioassays, and quantitative structure activity relationship modeling. DISCUSSION: NexGen has advanced our ability to apply new science by more rapidly identifying chemicals and exposures of potential concern, helping characterize mechanisms of action that influence conclusions about causality, exposure-response relationships, susceptibility and cumulative risk, and by elucidating new biomarkers of exposure and effects. Additionally, NexGen has fostered extensive discussion among risk scientists and managers and improved confidence in interpreting and applying new data streams. CONCLUSIONS: While considerable uncertainties remain, thoughtful application of new knowledge to risk assessment appears reasonable for augmenting major scope assessments, forming the basis for or augmenting limited scope assessments, and for prioritization and screening of very data limited chemicals. |
Environmental predictors of US county mortality patterns on a national basis
Chan MP , Weinhold RS , Thomas R , Gohlke JM , Portier CJ . PLoS One 2015 10 (12) e0137832 A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level. |
A simple procedure for estimating pseudo risk ratios from exposure to non-carcinogenic chemical mixtures
Scinicariello F , Portier C . Arch Toxicol 2015 90 (3) 513-23 Non-cancer risk assessment traditionally assumes a threshold of effect, below which there is a negligible risk of an adverse effect. The Agency for Toxic Substances and Disease Registry derives health-based guidance values known as Minimal Risk Levels (MRLs) as estimates of the toxicity threshold for non-carcinogens. Although the definition of an MRL, as well as EPA reference dose values (RfD and RfC), is a level that corresponds to "negligible risk," they represent daily exposure doses or concentrations, not risks. We present a new approach to calculate the risk at exposure to specific doses for chemical mixtures, the assumption in this approach is to assign de minimis risk at the MRL. The assigned risk enables the estimation of parameters in an exponential model, providing a complete dose-response curve for each compound from the chosen point of departure to zero. We estimated parameters for 27 chemicals. The value of k, which determines the shape of the dose-response curve, was moderately insensitive to the choice of the risk at the MRL. The approach presented here allows for the calculation of a risk from a single substance or the combined risk from multiple chemical exposures in a community. The methodology is applicable from point of departure data derived from quantal data, such as data from benchmark dose analyses or from data that can be transformed into probabilities, such as lowest-observed-adverse-effect level. The individual risks are used to calculate risk ratios that can facilitate comparison and cost-benefit analyses of environmental contamination control strategies. |
Blood lead level association with lower body weight in NHANES 1999-2006
Scinicariello F , Buser MC , Mevissen M , Portier CJ . Toxicol Appl Pharmacol 2013 273 (3) 516-23 BACKGROUND: Lead exposure is associated with low birth-weight. The objective of this study is to determine whether lead exposure is associated with lower body weight in children, adolescents and adults. METHODS: We analyzed data from NHANES 1999-2006 for participants aged ≥3 using multiple logistic and multivariate linear regression. Using age- and sex-standardized BMI Z-scores, overweight and obese children (ages 3-19) were classified by BMI ≥85th and ≥95th percentiles, respectively. The adult population (age ≥20) was classified as overweight and obese with BMI measures of 25-29.9 and ≥30, respectively. Blood lead level (BLL) was categorized by weighted quartiles. RESULTS: Multivariate linear regressions revealed a lower BMI Z-score in children and adolescents when the highest lead quartile was compared to the lowest lead quartile (beta (SE)=-0.33 (0.07), p<0.001), and a decreased BMI in adults (beta (SE)=-2.58 (0.25), p<0.001). Multiple logistic analyses in children and adolescents found a negative association between BLL and the percentage of obese and overweight with BLL in the highest quartile compared to the lowest quartile (OR=0.42, 95% CI: 0.30-0.59; and OR=0.67, 95% CI: 0.52-0.88, respectively). Adults in the highest lead quartile were less likely to be obese (OR=0.42, 95% CI: 0.35-0.50) compared to those in the lowest lead quartile. Further analyses with blood lead as restricted cubic splines, confirmed the dose-relationship between blood lead and body weight outcomes. CONCLUSIONS: BLLs are associated with lower body mass index and obesity in children, adolescents and adults. |
Biological networks for predicting chemical hepatocarcinogenicity using gene expression data from treated mice and relevance across human and rat species.
Thomas R , Thomas RS , Auerbach SS , Portier CJ . PLoS One 2013 8 (5) e63308 BACKGROUND: Several groups have employed genomic data from subchronic chemical toxicity studies in rodents (90 days) to derive gene-centric predictors of chronic toxicity and carcinogenicity. Genes are annotated to belong to biological processes or molecular pathways that are mechanistically well understood and are described in public databases. OBJECTIVES: To develop a molecular pathway-based prediction model of long term hepatocarcinogenicity using 90-day gene expression data and to evaluate the performance of this model with respect to both intra-species, dose-dependent and cross-species predictions. METHODS: Genome-wide hepatic mRNA expression was retrospectively measured in B6C3F1 mice following subchronic exposure to twenty-six (26) chemicals (10 were positive, 2 equivocal and 14 negative for liver tumors) previously studied by the US National Toxicology Program. Using these data, a pathway-based predictor model for long-term liver cancer risk was derived using random forests. The prediction model was independently validated on test sets associated with liver cancer risk obtained from mice, rats and humans. RESULTS: Using 5-fold cross validation, the developed prediction model had reasonable predictive performance with the area under receiver-operator curve (AUC) equal to 0.66. The developed prediction model was then used to extrapolate the results to data associated with rat and human liver cancer. The extrapolated model worked well for both extrapolated species (AUC value of 0.74 for rats and 0.91 for humans). The prediction models implied a balanced interplay between all pathway responses leading to carcinogenicity predictions. CONCLUSIONS: Pathway-based prediction models estimated from sub-chronic data hold promise for predicting long-term carcinogenicity and also for its ability to extrapolate results across multiple species. |
Adverse effects in risk assessment: modeling polychlorinated biphenyls and thyroid hormone disruption outcomes in animals and humans
Parham F , Wise A , Axelrad DA , Guyton KZ , Portier C , Zeise L , Zoeller RT , Woodruff TJ . Environ Res 2012 116 74-84 There is a growing need for quantitative approaches to extrapolate relationships between chemical exposures and early biological perturbations from animals to humans given increasing use of biological assays to evaluate toxicity pathways. We have developed such an approach using polychlorinated biphenyls (PCBs) and thyroid hormone (TH) disruption as a case study. We reviewed and identified experimental animal literature from which we developed a low-dose, linear model of PCB body burdens and decrements in free thyroxine (FT(4)) and total thyroxine (TT(4)), accounting for 33 PCB congeners; extrapolated the dose-response from animals to humans; and compared the animal dose-response to the dose-response of PCB body burdens and TH changes from eleven human epidemiological studies. We estimated a range of potencies for PCB congeners (over 4 orders of magnitude), with the strongest for PCB 126. Our approach to developing toxic equivalency models produced relative potencies similar to the toxicity equivalency factors (TEFs) from the World Health Organization (WHO). We generally found that the dose-response extrapolated from the animal studies tends to under-predict the dose-response estimated from human epidemiological studies. A quantitative approach to evaluating the relationship between chemical exposures and TH perturbations, based on animal data can be used to assess human health consequences of thyroid toxicity and inform decision-making. |
Predicting US- and state-level cancer counts for the current calendar year: Part II: evaluation of spatiotemporal projection methods for incidence
Zhu L , Pickle LW , Ghosh K , Naishadham D , Portier K , Chen HS , Kim HJ , Zou Z , Cucinelli J , Kohler B , Edwards BK , King J , Feuer EJ , Jemal A . Cancer 2012 118 (4) 1100-9 BACKGROUND: The current study was undertaken to evaluate the spatiotemporal projection models applied by the American Cancer Society to predict the number of new cancer cases. METHODS: Adaptations of a model that has been used since 2007 were evaluated. Modeling is conducted in 3 steps. In step I, ecologic predictors of spatiotemporal variation are used to estimate age-specific incidence counts for every county in the country, providing an estimate even in those areas that are missing data for specific years. Step II adjusts the step I estimates for reporting delays. In step III, the delay-adjusted predictions are projected 4 years ahead to the current calendar year. Adaptations of the original model include updating covariates and evaluating alternative projection methods. Residual analysis and evaluation of 5 temporal projection methods were conducted. RESULTS: The differences between the spatiotemporal model-estimated case counts and the observed case counts for 2007 were < 1%. After delays in reporting of cases were considered, the difference was 2.5% for women and 3.3% for men. Residual analysis indicated no significant pattern that suggested the need for additional covariates. The vector autoregressive model was identified as the best temporal projection method. CONCLUSIONS: The current spatiotemporal prediction model is adequate to provide reasonable estimates of case counts. To project the estimated case counts ahead 4 years, the vector autoregressive model is recommended to be the best temporal projection method for producing estimates closest to the observed case counts. (Cancer 2012;. (c) 2012 American Cancer Society.) |
Estimating the global public health implications of electricity and coal consumption
Gohlke JM , Thomas R , Woodward A , Campbell-Lendrum D , Pruss-Ustun A , Hales S , Portier CJ . Environ Health Perspect 2011 119 (6) 821-6 BACKGROUND: The growing health risks associated with greenhouse gas emissions highlight the need for new energy policies that emphasize efficiency and low-carbon energy intensity. OBJECTIVES: We assessed the relationships among electricity use, coal consumption, and health outcomes.Methods: Using time-series data sets from 41 countries with varying development trajectories between 1965 and 2005, we developed an autoregressive model of life expectancy (LE) and infant mortality (IM) based on electricity consumption, coal consumption, and previous year's LE or IM. Prediction of health impacts from the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) integrated air pollution emissions health impact model for coal-fired power plants was compared with the time-series model results. RESULTS: The time-series model predicted that increased electricity consumption was associated with reduced IM for countries that started with relatively high IM (> 100/1,000 live births) and low LE (< 57 years) in 1965, whereas LE was not significantly associated with electricity consumption regardless of IM and LE in 1965. Increasing coal consumption was associated with increased IM and reduced LE after accounting for electricity consumption. These results are consistent with results based on the GAINS model and previously published estimates of disease burdens attributable to energy-related environmental factors, including indoor and outdoor air pollution and water and sanitation. CONCLUSIONS: Increased electricity consumption in countries with IM < 100/1,000 live births does not lead to greater health benefits, whereas coal consumption has significant detrimental health impacts. |
Comprehensive environmental public health
Portier CJ . Public Health Rep 2011 126 Suppl 1 3-6 Typically, people thinking about environmental health focus on how the environment can affect the four key physiological factors: air, water, food, and shelter. However, the environment can have a much broader impact on human health through changes to security, and personal and endogenous factors, such as genes, age, and past medical history. Every change in an external environmental factor can affect a broad array of diseases and alter morbidity and mortality in a population, sometimes in unpredictable ways. Our nation's disease burden is due to numerous causes, and we must address the complexity of the environment in which we live in a comprehensive way if we are to make significant strides in reducing morbidity and mortality. Addressing single issues undoubtedly will help to reduce health risks, but not nearly as well as addressing a much broader range of exposures that can harm an individual. | The human body consists of a series of interconnected systems. At the highest level is the entire human, where our major concerns are overall morbidity and mortality and general health. As defined by the World Health Organization, health is not merely the absence of disease or infirmity; rather, a healthy human being is one in a state of complete physical, mental, and social well-being.1 To achieve this state, our organ systems must function properly, doing their jobs to provide oxygen and nutrients to the body and to mount a comprehensive defense against environmental agents and pathogens that would otherwise overwhelm us. Paracrine, autocrine, and other signaling processes must function according to plan. Each cell contributes to this interplay, and for each cell to function properly, the intricate intercellular biochemistry that drives that function must be maintained and balanced. This happens through a complex array of organelles and intracellular components that form their own system, with each cell type in each different organ of the body maintaining its own special biochemistry. This cellular machinery comes about as a function of genetic and epigenetic controls during development and then functions throughout the life of that cell. Molecular control mechanisms under genetic control are subject to changes in nutrition and other environmental factors. Hence, from the molecular level to the functioning of the whole, humans are very complex biochemical reactors that have to be maintained throughout a lifetime. |
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