Ronald H. White

Arginase Reciprocally Regulates Nitric Oxide Synthase Activity and Contributes to Endothelial Dysfunction in Aging Blood Vessels

Background—Although abnormal l-arginine NO signaling contributes to endothelial dysfunction in the aging cardiovascular system, the biochemical mechanisms remain controversial. l-arginine, the NO synthase (NOS) precursor, is also a substrate for arginase. We tested the hypotheses that arginase reciprocally regulates NOS by modulating l-arginine bioavailability and that arginase is upregulated in aging vasculature, contributing to depressed endothelial function. Methods and Results—Inhibition of arginase with (S)-(2-boronoethyl)-l-cysteine, HCl (BEC) produced vasodilation in aortic rings from young (Y) adult rats (maximum effect, 46.4±9.4% at 10−5 mol/L, P <0.01). Similar vasorelaxation was elicited with the additional arginase inhibitors N-hydroxy-nor-l-arginine (nor-NOHA) and difluoromethylornithine (DFMO). This effect required intact endothelium and was prevented by 1H-oxadiazole quinoxalin-1-one (P <0.05 and P <0.001, respectively), a soluble guanylyl cyclase inhibitor. DFMO-elicited vasodilation was greater in old (O) compared with Y rat aortic rings (60±6% versus 39±6%, P <0.05). In addition, BEC restored depressed l-arginine (10−4 mol/L)–dependent vasorelaxant responses in O rings to those of Y. Arginase activity and expression were increased in O rings, whereas NOS activity and cyclic GMP levels were decreased. BEC and DFMO suppressed arginase activity and restored NOS activity and cyclic GMP levels in O vessels to those of Y. Conclusions—These findings demonstrate that arginase modulates NOS activity, likely by regulating intracellular l-arginine availability. Arginase upregulation contributes to endothelial dysfunction of aging and may therefore be a therapeutic target.

Socioeconomic and Racial Disparities in Cancer Risk from Air Toxics in Maryland

We linked risk estimates from the U.S. Environmental Protection Agency’s National Air Toxics Assessment (NATA) to racial and socioeconomic characteristics of census tracts in Maryland (2000 Census) to evaluate disparities in estimated cancer risk from exposure to air toxics by emission source category. In Maryland, the average estimated cancer risk across census tracts was highest from on-road sources (50% of total risk from nonbackground sources), followed by nonroad (25%), area (23%), and major sources (< 1%). Census tracts in the highest quartile defined by the fraction of African-American residents were three times more likely to be high risk (> 90th percentile of risk) than those in the lowest quartile (95% confidence interval, 2.0–5.0). Conversely, risk decreased as the proportion of whites increased (p < 0.001). Census tracts in the lowest quartile of socioeconomic position, as measured by various indicators, were 10–100 times more likely to be high risk than those in the highest quartile. We observed substantial risk disparities for on-road, area, and nonroad sources by socioeconomic measure and on-road and area sources by race. There was considerably less evidence of risk disparities from major source emissions. We found a statistically significant interaction between race and income, suggesting a stronger relationship between race and risk at lower incomes. This research demonstrates the utility of NATA for assessing regional environmental justice, identifies an environmental justice concern in Maryland, and suggests that on-road sources may be appropriate targets for policies intended to reduce the disproportionate environmental health burden among economically disadvantaged and minority populations.

State-of-the-Science Workshop Report: Issues and Approaches in Low-Dose― Response Extrapolation for Environmental Health Risk Assessment

Low-dose extrapolation model selection for evaluating the health effects of environmental pollutants is a key component of the risk assessment process. At a workshop held in Baltimore, Maryland, on 23–24 April 2007, sponsored by U.S. Environmental Protection Agency and Johns Hopkins Risk Sciences and Public Policy Institute, a multidisciplinary group of experts reviewed the state of the science regarding low-dose extrapolation modeling and its application in environmental health risk assessments. Participants identified discussion topics based on a literature review, which included examples for which human responses to ambient exposures have been extensively characterized for cancer and/or noncancer outcomes. Topics included the need for formalized approaches and criteria to assess the evidence for mode of action (MOA), the use of human versus animal data, the use of MOA information in biologically based models, and the implications of interindividual variability, background disease processes, and background exposures in threshold versus nonthreshold model choice. Participants recommended approaches that differ from current practice for extrapolating high-dose animal data to low-dose human exposures, including categorical approaches for integrating information on MOA, statistical approaches such as model averaging, and inference-based models that explicitly consider uncertainty and interindividual variability.

Health benefits from large-scale ozone reduction in the United States

Background: Exposure to ozone has been associated with adverse health effects, including premature mortality and cardiopulmonary and respiratory morbidity. In 2008, the U.S. Environmental Protection Agency (EPA) lowered the primary (health-based) National Ambient Air Quality Standard (NAAQS) for ozone to 75 ppb, expressed as the fourth-highest daily maximum 8-hr average over a 24-hr period. Based on recent monitoring data, U.S. ozone levels still exceed this standard in numerous locations, resulting in avoidable adverse health consequences. Objectives: We sought to quantify the potential human health benefits from achieving the current primary NAAQS standard of 75 ppb and two alternative standard levels, 70 and 60 ppb, which represent the range recommended by the U.S. EPA Clean Air Scientific Advisory Committee (CASAC). Methods: We applied health impact assessment methodology to estimate numbers of deaths and other adverse health outcomes that would have been avoided during 2005, 2006, and 2007 if the current (or lower) NAAQS ozone standards had been met. Estimated reductions in ozone concentrations were interpolated according to geographic area and year, and concentration–response functions were obtained or derived from the epidemiological literature. Results: We estimated that annual numbers of avoided ozone-related premature deaths would have ranged from 1,410 to 2,480 at 75 ppb to 2,450 to 4,130 at 70 ppb, and 5,210 to 7,990 at 60 ppb. Acute respiratory symptoms would have been reduced by 3 million cases and school-loss days by 1 million cases annually if the current 75-ppb standard had been attained. Substantially greater health benefits would have resulted if the CASAC-recommended range of standards (70–60 ppb) had been met. Conclusions: Attaining a more stringent primary ozone standard would significantly reduce ozone-related premature mortality and morbidity.

Predictive models for nanotoxicology: Current challenges and future opportunities

Characterizing the risks posed by nanomaterials is extraordinarily complex because these materials can have a wide range of sizes, shapes, chemical compositions and surface modifications, all of which may affect toxicity. There is an urgent need for a testing strategy that can rapidly and efficiently provide a screening approach for evaluating the potential hazard of nanomaterials and inform the prioritization of additional toxicological testing where necessary. Predictive toxicity models could form an integral component of such an approach by predicting which nanomaterials, as a result of their physico-chemical characteristics, have potentially hazardous properties. Strategies for directing research towards predictive models and the ancillary benefits of such research are presented here.

The Next Generation of Risk Assessment Multi-Year Study—Highlights of Findings, Applications to Risk Assessment, and Future Directions

Background: The Next Generation (NexGen) of Risk Assessment effort is a multi-year collaboration among several organizations evaluating new, potentially more efficient molecular, computational, and systems biology approaches to risk assessment. This article 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. Citation: 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. 2016. The Next Generation of Risk Assessment multiyear study—highlights of findings, applications to risk assessment, and future directions. Environ Health Perspect 124:1671–1682; http://dx.doi.org/10.1289/EHP233

Report of Workshop on Traffic, Health, and Infrastructure Planning

Recent air pollutant measurement data document unique aspects of the air pollution mixture near roadways, and an expanding body of epidemiological data suggests increased risks for exacerbation of asthma and other respiratory diseases, premature mortality, and certain cancers and birth outcomes from air pollution exposures in populations residing in relatively close proximity to roadways. The Workshop on Traffic, Health, and Infrastructure Planning, held in February 2004, was convened to provide a forum for interdisciplinary discussion of motor vehicle emissions, exposures and potential health effects related to proximity to motor vehicle traffic. This report summarizes the workshop discussions and findings regarding the current science on this issue, identifies planning and policy issues related to localized motor vehicle emissions and health concerns, and provides recommendations for future research and policy directions.

Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead

Susceptibility to chemical toxins has not been adequately addressed in risk assessment methodologies. As a result, environmental policies may fail to meet their fundamental goal of protecting the public from harm. This study examines how characterization of risk may change when susceptibility is explicitly considered in policy development; in particular we examine the process used by the U.S. Environmental Protection Agency (EPA) to set a National Ambient Air Quality Standard (NAAQS) for lead. To determine a NAAQS, EPA estimated air lead-related decreases in child neurocognitive function through a combination of multiple data elements including concentration-response (CR) functions. In this article, we present alternative scenarios for determining a lead NAAQS using CR functions developed in populations more susceptible to lead toxicity due to socioeconomic disadvantage. The use of CR functions developed in susceptible groups resulted in cognitive decrements greater than original EPA estimates. EPA’s analysis suggested that a standard level of 0.15 µg/m3 would fulfill decision criteria, but by incorporating susceptibility we found that options for the standard could reasonably be extended to lower levels. The use of data developed in susceptible populations would result in the selection of a more protective NAAQS under the same decision framework applied by EPA. Results are used to frame discussion regarding why cumulative risk assessment methodologies are needed to help inform policy development.

Linear Low-Dose Extrapolation for Non-Cancer Responses: Burke et al. Respond.

In his letter, Rhomberg raises several issues concerning recommendations in our report of the workshop “Issues and Approaches to Low Dose–Response Extrapolation for Environmental Health Risk Assessment” (White et al. 2009). One recommendation of the workshop was to set aside the generally held presumption that dose–response functions should follow a threshold model when extrapolating from higher dose studies of non-carcinogenic responses to lower dose levels typical for environmental exposures to chemicals. Workshop participants generally concluded that the selection of population-level low-dose extrapolation models should be informed by population factors such as inter individual variability in susceptibility and coexposures, as well as by categorization of mechanisms of toxicity. As indicated in the meeting report (White et al. 2009), most workshop participants preferred a linear, no-threshold approach to low-dose extrapolation modeling, combined with modeled estimates of the low range of observed data, for noncancer, as well as cancer, outcomes in the absence of convincing evidence to indicate that an alternative model is more appropriate. We recognize that this recommendation represents a departure from current generally accepted practice. On a nonsubstantive point, Rhomberg’s comment that we did not include additional information regarding “fuller discussions” at the workshop on this and other issues reflects the constraints imposed by EHP’s article length limits and changes made to accommodate reviewer comments encouraging emphasis on workshop findings and recommendations rather than on workshop discussions. We disagree with Rhomberg’s assertion that the finding of a linear, no-threshold exposure–response relationship in many epidemiologic studies of the effect of environmental pollutants, such as particulate matter and ozone air pollution, can be attributed entirely to a small range of exposures and measurement error. Although these factors need to be considered in evaluating epidemiologic study results, modeling techniques such as non parametric smoothing methods have demonstrated the capacity to identify potential threshold relationships even in the context of relatively extreme measurement error (Cakmak et al. 1999; Schwartz and Zanobetti 2000). As we noted in our meeting report (White et al. 2009), for the limited number of chemicals and agents for which robust low-dose response data exists (e.g., epidemiologic studies of large populations with exposures to particulate matter and ozone air pollution extending from relatively high to low ambient levels), thresholds have not been observed for non cancer or cancer outcomes [U.S. Environmental Protection Agency (EPA) 2006a, 2006b]. Additionally, for some of the exposures considered, the mechanisms of action thought to underlie the observed effects have been characterized by some as threshold mechanisms (e.g., the disruption of the homeostatic conditions for reactive oxygen species). In such cases, interindividual variability, background disease processes, and coexposures may explain the observed linearity. Although we acknowledge that there are differences in the intrinsic biological processes involved in generating cancer and non cancer outcomes, we disagree with Rhomberg’s assertion that heterogeneity in intrinsic population susceptibility and additivity to background disease processes result in simply “broadening” the dose–response relationship (which we presume means making the dose–response curve shallower). The underlying concept that additivity to background disease processes and variability in population susceptibility results in a linearization of the dose–response function for populations exposed to environmentally relevant levels was originally discussed in the context of cancer outcomes [Crump et al. 1976; Lutz 1990; National Research Council (NRC) 2005], and the suggestion that this same concept applies to noncancer outcomes is not novel (Clewell and Crump 2005; Crawford and Wilson 1996). Similarly, the importance of considering interindividual variability in assessing uncertainty associated with chemical risk assessments of noncancer effects has been recognized (Hattis and Silver 1994). The significance of these factors in the selection of dose–response models for use in environmental health risk assessment was also highlighted in a recent NRC report (NRC 2008). Regarding the assumption of additivity to background disease on low-dose extrapolation, in our meeting report (White et al. 2009) we noted the importance of assessing, to the extent possible, whether the mode or mechanism of action of the key events involved are consistent. However, current knowledge of these detailed biologic processes is still quite limited for most chemicals and pollutants, and as noted by Hoel (1997) [L]ow-dose linearity is speculative and it is a reasonable assumption for public health purposes in those instances where there is no scientific evidence to the contrary. We recognize that uncertainty increases as the dose–response extrapolation extends farther below observed data. The findings regarding exposure–response relationships from large-scale epidemiologic studies of environmental pollutants suggest that when considering population-level dose–response factors, interindividual variability, additivity to background disease processes, coexposures, and mechanisms of action, warrant careful consideration. As a consequence, we continue to recommend that the approach proposed in our meeting report (White et al. 2009) is appropriate and necessary.

Premature Mortality in the Kingdom of Saudi Arabia Associated with Particulate Matter Air Pollution from the 1991 Gulf War

ABSTRACT The State of Kuwait oil fires and military operations associated with the 1991 Gulf War resulted in substantially increased levels of airborne particulate matter (PM) in the Kingdom of Saudi Arabia (KSA) during 1991 and 1992. Using quantitative risk assessment methodology, this article estimates the increase in premature deaths in citizens of the KSA associated with the Gulf War–related increase in PM air pollution levels. Meta-analysis of daily time-series studies of non-accidental mortality associated with increased PM10 levels using two alternative methodologies yielded exposure-response relative risk functions of 2.7% and 3.5% per 50 μ g/m3 increase in PM10 concentration. Combining these exposure-response functions with estimates of the magnitude and duration of the increased PM10 exposure, the size of the exposed population and baseline mortality rates provided an estimate of approximately 1,080 to 1,370 excess non-accidental deaths of Saudi citizens during 1991–1992 associated with the Gulf War–related increase in PM levels.