Richard K. Kwok

The PhenX Toolkit: Get the Most From Your Measures

The potential for genome-wide association studies to relate phenotypes to specific genetic variation is greatly increased when data can be combined or compared across multiple studies. To facilitate replication and validation across studies, RTI International (Research Triangle Park, North Carolina) and the National Human Genome Research Institute (Bethesda, Maryland) are collaborating on the consensus measures for Phenotypes and eXposures (PhenX) project. The goal of PhenX is to identify 15 high-priority, well-established, and broadly applicable measures for each of 21 research domains. PhenX measures are selected by working groups of domain experts using a consensus process that includes input from the scientific community. The selected measures are then made freely available to the scientific community via the PhenX Toolkit. Thus, the PhenX Toolkit provides the research community with a core set of high-quality, well-established, low-burden measures intended for use in large-scale genomic studies. PhenX measures will have the most impact when included at the experimental design stage. The PhenX Toolkit also includes links to standards and resources in an effort to facilitate data harmonization to legacy data. Broad acceptance and use of PhenX measures will promote cross-study comparisons to increase statistical power for identifying and replicating variants associated with complex diseases and with gene-gene and gene-environment interactions.

Chronic Arsenic Exposure and Cardiac Repolarization Abnormalities with QT Interval Prolongation in a Population-based Study

Background Chronic arsenic exposure is associated with cardiovascular abnormalities. Prolongation of the QT (time between initial deflection of QRS complex to the end of T wave) interval and profound repolarization changes on electrocardiogram (ECG) have been reported in patients with acute promyelocytic leukemia treated with arsenic trioxide. This acquired form of long QT syndrome can result in life-threatening arrhythmias. Objective The objective of this study was to assess the cardiac effects of arsenic by investigating QT interval alterations in a human population chronically exposed to arsenic. Methods Residents in Ba Men, Inner Mongolia, have been chronically exposed to arsenic via consumption of water from artesian wells. A total of 313 Ba Men residents with the mean arsenic exposure of 15 years were divided into three arsenic exposure groups: low (≤ 21 μg/L), medium (100–300 μg/L), and high (430–690 μg/L). ECGs were obtained on all study subjects. The normal range for QTc (corrected QT) interval is 0.33–0.44 sec, and QTc ≥ 0.45 sec was considered to be prolonged. Results The prevalence rates of QT prolongation and water arsenic concentrations showed a dose-dependent relationship (p = 0.001). The prevalence rates of QTc prolongation were 3.9, 11.1, 20.6% for low, medium, and high arsenic exposure, respectively. QTc prolongation was also associated with sex (p < 0.0001) but not age (p = 0.486) or smoking (p = 0.1018). Females were more susceptible to QT prolongation than males. Conclusions We found significant association between chronic arsenic exposure and QT interval prolongation in a human population. QT interval may potentially be useful in the detection of early cardiac arsenic toxicity.

Use of a continuous nephelometer to measure personal exposure to particles during the U.S. Environmental Protection Agency Baltimore and Fresno panel studies

ABSTRACT In population exposure studies, personal exposure to PM is typically measured as a 12- to 24-hr integrated mass concentration. To better understand short-term variation in personal PM exposure, continuous (1-min averaging time) nephelometers were worn by 15 participants as part of two U.S. Environmental Protection Agency (EPA) longitudinal PM exposure studies conducted in Baltimore County, MD, and Fresno, CA. Participants also wore iner-tial impactor samplers (24-hr integrated filter samples) and recorded their daily activities in 15-min intervals. In Baltimore, the nephelometers correlated well (R2 = 0.66) with the PM25 impactors. Time-series plots of personal nephelometer data showed each participants PM exposure to consist of a series of peaks of relatively short duration. Activities corresponding to a significant instrument response included cooking, outdoor activities, transportation, laundry, cleaning, shopping, gardening, moving between microenvironments, and removing/putting on the instrument. On average, 63-66% of the daily PM exposure occurred indoors at home (about 2/3 of which occurred during waking hours), primarily due to the large amount of time spent in that location (an average of 7277%). Although not a reference method for measuring mass concentration, the nephelometer did help identify PM sources and the relative contribution of those sources to an individuals personal exposure.

The use of census data for determining race and education as SES indicators: a validation study.

PURPOSE Little research has examined the validity of using census data to determine an individuals socio-economic status (SES), as measured by race and educational level. This study assessed the accuracy of using aggregate level data from United States Census Block Groups in determining race and education SES indicators in a cohort of women from North Carolina. METHODS The study analyzed patient data from the Carolina Mammography Registry and 1990 United States Census in 21 North Carolina counties. Women (n = 39,546) were geocoded to their census block group and their block group characteristics (surrogate measures) were validated with their self-reported values on race and education. An analysis was performed to explore whether using these surrogate measures would affect measured associations with the self-reported values. RESULTS Whites were accurately identified (84.8%) more consistently than Blacks (14.1%) regardless of their urban/rural status. Women without a high school diploma or equivalent were accurately identified (56.2%) more often than those with higher education levels (45.9%). Analyses using the surrogate measures were significantly different than the true values according to chi-square statistics. CONCLUSIONS Use of census data to derive SES indicators tends to be more accurate for the majority than the minority population. Researchers must be sensitive to the ecologic fallacy when using aggregate level data such as the census to determine individual level characteristics.

Maternal drinking water arsenic exposure and perinatal outcomes in Inner Mongolia, China

Background Bayingnormen is a region located in western Inner Mongolia China, with a population that is exposed to a wide range of drinking water arsenic concentrations. The relationship between maternal drinking water arsenic exposure and perinatal endpoints (term birth weight, preterm birth, stillbirth and neonatal death) in this region was evaluated in this study. Methods An analysis was conducted of all singleton deliveries in a defined geographical area of Inner Mongolia from December 1996 to December 1999 (n=9890). Outcome and covariate data were abstracted from prenatal care records. Exposure was based on well-water measures for the maternal subvillage. Mean birth weight at term was compared across four arsenic categories using analysis of covariance. ORs for stillbirth, preterm birth and neonatal death were estimated by logistic regression with arsenic exposure dichotomised at 50 μg/l. Results Term birth weight was 0.05 kg higher (95% CI 0.02 to 0.08) in the highest exposure category (>100 μg/l) compared to the reference (below limit of detection to 20 μg/l). Arsenic >50 μg/l was associated with an increased risk of neonatal death (OR 2.01, 95% CI 1.12 to 3.59). No relationship was found between maternal arsenic exposure and preterm or stillbirth delivery. Conclusions At the levels observed in our study, arsenic does not appear to contribute to adverse birth outcomes. Exposure may play a role in neonatal death; however, the neonatal death rate in this population was low and this potential association merits further research.

Comparison of PM2.5 and PM10 monitors.

An extensive PM monitoring study was conducted during the 1998 Baltimore PM Epidemiology-Exposure Study of the Elderly. One goal was to investigate the mass concentration comparability between various monitoring instrumentation located across residential indoor, residential outdoor, and ambient sites. Filter-based (24-h integrated) samplers included Federal Reference Method Monitors (PM2.5-FRMs), Personal Environmental Monitors (PEMs), Versatile Air Pollution Samplers (VAPS), and cyclone-based instruments. Tapered element oscillating microbalances (TEOMs) collected real-time data. Measurements were collected on a near-daily basis over a 28-day period during July–August, 1998. The selected monitors had individual sampling completeness percentages ranging from 64% to 100%. Quantitation limits varied from 0.2 to 5.0 µg/m3. Results from matched days indicated that mean individual PM10 and PM2.5 mass concentrations differed by less than 3 µg/m3 across the instrumentation and within each respective size fraction. PM10 and PM2.5 mass concentration regression coefficients of determination between the monitors often exceeded 0.90 with coarse (PM10–2.5) comparisons revealing coefficients typically well below 0.40. Only one of the outdoor collocated PM2.5 monitors (PEM) provided mass concentration data that were statistically different from that produced by a protoype PM2.5 FRM sampler. The PEM had a positive mass concentration bias ranging up to 18% relative to the FRM prototype.

Agreement between diary records of time spent outdoors and personal ultraviolet radiation dose measurements.

Little is known about the validity of self‐recorded sun exposure and time spent outdoors for epidemiological research. The aims of the current study were to assess how well participants’ self‐recorded time outdoors compared to objective measurements of personal UVR doses. We enrolled 124 volunteers aged 40 and above who were identified from targeted subgroups of US radiologic technologists. Each volunteer was instructed to wear a polysulfone (PS) dosimeter to measure UVR on their left shoulder and to complete a daily activity diary, listing all activities undertaken in each 30 min interval between 9:00 A.M. and 5:00 P.M. during a 7 day period. In a linear regression model, self‐recorded daily time spent outdoors was associated with an increase of 8.2% (95% CI: 7.3–9.2%) in the personal UVR exposure with every hour spent outdoors. The amount of self‐recorded total daily time spent outdoors was better correlated with the personal daily UVR dose for activities conducted near noon time compared to activities conducted in the morning or late afternoon, and for activities often performed in the sun (e.g. gardening or recreation activities) compared to other outdoor activities (e.g. driving) in which the participant is usually shaded from the sun. Our results demonstrated a significant correlation between diary records of time spent outdoors with objective personal UVR dose measurements.

The GuLF STUDY: A Prospective Study of Persons Involved in the Deepwater Horizon Oil Spill Response and Clean-Up

Background: The 2010 Deepwater Horizon disaster led to the largest ever marine oil spill. Individuals who worked on the spill were exposed to toxicants and stressors that could lead to adverse effects. Objectives: The GuLF STUDY was designed to investigate relationships between oil spill exposures and multiple potential physical and mental health effects. Methods: Participants were recruited by telephone from lists of individuals who worked on the oil spill response and clean-up or received safety training. Enrollment interviews between 2011 and 2013 collected information about spill-related activities, demographics, lifestyle, and health. Exposure measurements taken during the oil spill were used with questionnaire responses to characterize oil exposures of participants. Participants from Gulf states completed a home visit in which biological and environmental samples, anthropometric and clinical measurements, and additional health and lifestyle information were collected. Participants are being followed for changes in health status. Results: Thirty-two thousand six hundred eight individuals enrolled in the cohort, and 11,193 completed a home visit. Most were young (56.2% ≤ 45 years of age), male (80.8%), lived in a Gulf state (82.3%), and worked at least 1 day on the oil spill (76.5%). Workers were involved in response (18.0%), support operations (17.5%), clean-up on water (17.4%) or land (14.6%), decontamination (14.3%), and administrative support (18.3%). Using an ordinal job exposure matrix, 45% had maximum daily total hydrocarbon exposure levels ≥ 1.0 ppm. Conclusions: The GuLF STUDY provides a unique opportunity to study potential adverse health effects from the Deepwater Horizon oil spill. Citation: Kwok RK, Engel LS, Miller AK, Blair A, Curry MD, Jackson WB II, Stewart PA, Stenzel MR, Birnbaum LS, Sandler DP for the GuLF STUDY Research Team. 2017. The GuLF STUDY: a prospective study of persons involved in the Deepwater Horizon oil spill response and clean-up. Environ Health Perspect 125:570–578; http://dx.doi.org/10.1289/EHP715

Comparison of Methods for Analyzing Left-Censored Occupational Exposure Data

The National Institute for Environmental Health Sciences (NIEHS) is conducting an epidemiologic study (GuLF STUDY) to investigate the health of the workers and volunteers who participated from April to December of 2010 in the response and cleanup of the oil release after the Deepwater Horizon explosion in the Gulf of Mexico. The exposure assessment component of the study involves analyzing thousands of personal monitoring measurements that were collected during this effort. A substantial portion of these data has values reported by the analytic laboratories to be below the limits of detection (LOD). A simulation study was conducted to evaluate three established methods for analyzing data with censored observations to estimate the arithmetic mean (AM), geometric mean (GM), geometric standard deviation (GSD), and the 95th percentile (X0.95) of the exposure distribution: the maximum likelihood (ML) estimation, the β-substitution, and the Kaplan-Meier (K-M) methods. Each method was challenged with computer-generated exposure datasets drawn from lognormal and mixed lognormal distributions with sample sizes (N) varying from 5 to 100, GSDs ranging from 2 to 5, and censoring levels ranging from 10 to 90%, with single and multiple LODs. Using relative bias and relative root mean squared error (rMSE) as the evaluation metrics, the β-substitution method generally performed as well or better than the ML and K-M methods in most simulated lognormal and mixed lognormal distribution conditions. The ML method was suitable for large sample sizes (N ≥ 30) up to 80% censoring for lognormal distributions with small variability (GSD = 2-3). The K-M method generally provided accurate estimates of the AM when the censoring was <50% for lognormal and mixed distributions. The accuracy and precision of all methods decreased under high variability (GSD = 4 and 5) and small to moderate sample sizes (N < 20) but the β-substitution was still the best of the three methods. When using the ML method, practitioners are cautioned to be aware of different ways of estimating the AM as they could lead to biased interpretation. A limitation of the β-substitution method is the absence of a confidence interval for the estimate. More research is needed to develop methods that could improve the estimation accuracy for small sample sizes and high percent censored data and also provide uncertainty intervals.

The Exposome: Embracing the Complexity for Discovery in Environmental Health

Summary: Environmental exposures are ubiquitous and play a fundamental role in the development of complex human diseases. The exposome, which is defined as the totality of environmental exposures over the life course, allows for systematic evaluation of the relationship between exposures and associated biological consequences, and represents a powerful approach for discovery in environmental health research. However, implementing the exposome concept is challenged by the ability to accurately assess multiple exposures and the ability to integrate information across the exposure–disease continuum. On 14–15 January 2015, the National Institute of Environmental Health Sciences (NIEHS) held the Exposome Workshop where a group of international and U.S. scientists from different disciplines gathered to review the state of the science in research areas related to the exposome and to provide recommendations for incorporating the exposome concept into each research area. To move the field forward, the NIEHS is establishing a Children’s Health Exposure Analysis Resource (CHEAR) to provide infrastructure support for access to laboratory and statistical analyses to children’s health studies. It is recognized that incorporating the exposome concept into exposure and environmental health research will be a long journey and will require significant collaborative efforts from different scientific disciplines, nations, and stakeholders.