Maternal and child biomonitoring strategies and levels of exposure in western Canada during the past seventeen years: The Alberta Biomonitoring Program: 2005-2021.

The Alberta Biomonitoring Program (ABP) was created in 2005 with the initial goal of establishing baseline levels of exposure to environmental chemicals in specific populations in the province of Alberta, Canada, and was later expanded to include multiple phases. The first two phases focused on evaluating exposure in pregnant women (Phase One, 2005) and children (Phase Two, 2004-2006) by analyzing residual serum specimens. Phase Three (2013-2016) employed active recruitment techniques to evaluate environmental exposures using a revised list of chemicals in paired serum pools from pregnant women and umbilical cord blood. These three phases of the program monitored a total of 226 chemicals in 285 pooled serum samples representing 31,529 individuals. Phase Four (2017-2020) of the ABP has taken a more targeted approach, focusing on the impact of the federal legalization of cannabis on the exposure of pregnant women in Alberta to cannabis, as well as tobacco and alcohol using residual prenatal screening serum specimens. Chemicals monitored in the first three phases include herbicides, neutral pesticides, metals, metalloids, and micronutrients, methylmercury, organochlorine pesticides, organophosphate pesticides, parabens, phthalate metabolites, perfluoroalkyl substances (PFAS), phenols, phytoestrogens, polybrominated compounds, polychlorinated biphenyls (PCBs), dioxins and furans, polycyclic aromatic hydrocarbons (PAHs), and tobacco biomarkers. Phase Four monitored six biomarkers of tobacco, alcohol, and cannabis. All serum samples were pooled. Mean concentrations and 95% confidence intervals (CIs) were calculated for the chemicals detected in ≥25% of the sample pools. cross the first three phases, the data from the ABP has provided baseline exposure levels for the chemicals in pregnant women, children, and newborns across the province. Comparison within and among the phases has highlighted differences in exposure levels with age, geography, seasonality, sample type, and time. The strategies employed throughout the program phases have been demonstrated to provide effective models for population biomonitoring.

Modeling and simulation for toxicity assessment.

The effect of various toxicants on growth/death and morphology of human cells is investigated using the xCELLigence Real-Time Cell Analysis High Troughput in vitro assay. The cell index is measured as a proxy for the number of cells, and for each test substance in each cell line, time-dependent concentration response curves (TCRCs) are generated. In this paper we propose a mathematical model to study the effect of toxicants with various initial concentrations on the cell index. This model is based on the logistic equation and linear kinetics. We consider a three dimensional system of differential equations with variables corresponding to the cell index, the intracellular concentration of toxicant, and the extracellular concentration of toxicant. To efficiently estimate the model's parameters, we design an Expectation Maximization algorithm. The model is validated by showing that it accurately represents the information provided by the TCRCs recorded after the experiments. Using stability analysis and numerical simulations, we determine the lowest concentration of toxin that can kill the cells. This information can be used to better design experimental studies for cytotoxicity profiling assessment.

Comparative cytotoxicity of fourteen trivalent and pentavalent arsenic species determined using real-time cell sensing.

The occurrence of a large number of diverse arsenic species in the environment and in biological systems makes it important to compare their relative toxicity. The toxicity of arsenic species has been examined in various cell lines using different assays, making comparison difficult. We report real-time cell sensing of two human cell lines to examine the cytotoxicity of fourteen arsenic species: arsenite (AsIII), monomethylarsonous acid (MMAIII) originating from the oxide and iodide forms, dimethylarsinous acid (DMAIII), dimethylarsinic glutathione (DMAGIII), phenylarsine oxide (PAOIII), arsenate (AsV), monomethylarsonic acid (MMAV), dimethylarsinic acid (DMAV), monomethyltrithioarsonate (MMTTAV), dimethylmonothioarsinate (DMMTAV), dimethyldithioarsinate (DMDTAV), 3-nitro-4-hydroxyphenylarsonic acid (Roxarsone, Rox), and 4-aminobenzenearsenic acid (p-arsanilic acid, p-ASA). Cellular responses were measured in real time for 72hr in human lung (A549) and bladder (T24) cells. IC50 values for the arsenicals were determined continuously over the exposure time, giving rise to IC50 histograms and unique cell response profiles. Arsenic accumulation and speciation were analyzed using inductively coupled plasma-mass spectrometry (ICP-MS). On the basis of the 24-hr IC50 values, the relative cytotoxicity of the tested arsenicals was in the following decreasing order: PAOIII≫MMAIII≥DMAIII≥DMAGIII≈DMMTAV≥AsIII≫MMTTAV>AsV>DMDTAV>DMAV>MMAV≥Rox≥p-ASA. Stepwise shapes of cell response profiles for DMAIII, DMAGIII, and DMMTAV coincided with the conversion of these arsenicals to the less toxic pentavalent DMAV. Dynamic monitoring of real-time cellular responses to fourteen arsenicals provided useful information for comparison of their relative cytotoxicity.

Machine learning algorithms for mode-of-action classification in toxicity assessment.

BACKGROUND: Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probing the mode of action (MOA) of the testing substances. RESULTS: In this paper, we present machine learning approaches for MOA assessment. Computational tools based on artificial neural network (ANN) and support vector machine (SVM) are developed to analyze the time-concentration response curves (TCRCs) of human cell lines responding to tested chemicals. The techniques are capable of learning data from given TCRCs with known MOA information and then making MOA classification for the unknown toxicity. A novel data processing step based on wavelet transform is introduced to extract important features from the original TCRC data. From the dose response curves, time interval leading to higher classification success rate can be selected as input to enhance the performance of the machine learning algorithm. This is particularly helpful when handling cases with limited and imbalanced data. The validation of the proposed method is demonstrated by the supervised learning algorithm applied to the exposure data of HepG2 cell line to 63 chemicals with 11 concentrations in each test case. Classification success rate in the range of 85 to 95 % are obtained using SVM for MOA classification with two clusters to cases up to four clusters. CONCLUSIONS: Wavelet transform is capable of capturing important features of TCRCs for MOA classification. The proposed SVM scheme incorporated with wavelet transform has a great potential for large scale MOA classification and high-through output chemical screening.

Real-Time Cell-Electronic Sensing of Coal Fly Ash Particulate Matter for Toxicity-Based Air Quality Monitoring.

The development of a unique bioassay for cytotoxicity analysis of coal fly ash (CFA) particulate matter (PM) and its potential application for air quality monitoring is described. Using human cell lines, A549 and SK-MES-1, as live probes on microelectrode-embedded 96-well sensors, impedance changes over time are measured as cells are treated with varying concentrations (1 µg/mL-20 mg/mL) of CFA samples. A dose-dependent impedance change is determined for each CFA sample, from which an IC50 histogram is obtained. The assay was successfully applied to examine CFA samples collected from three coal-fired power plants (CFPs) in China. The samples were separated into three size fractions: PM2.5 (<2.5 µm), PM10-2.5 (2.5 µm < x < 10 µm), and PM10 (>10 µm). Dynamic cell-response profiles and temporal IC50 histograms of all samples show that CFA cytotoxicity depends on concentration, exposure time (0-60 h), and cell-type (SK-MES-1 > A549). The IC50 values differentiate the cytotoxicity of CFA samples based on size fraction (PM2.5 ≈ PM10-2.5 ≫ PM10) and the sampling location (CFP2 > CFP1 ≈ CFP3). Differential cytotoxicity measurements of particulates in human cell lines using cell-electronic sensing provide a useful tool for toxicity-based air quality monitoring and risk assessment.

Predicting GHS toxicity using RTCA and discrete-time Fourier transform.

In order to promote the acceptance of cell-based toxicity testings, the accuracy of cytotoxicity test must be determined when compared to in vivo results. Traditional methods of cytotoxicity analysis, such as LC[Formula: see text] (concentration where 50% of the cells are killed) can be problematic since they have been found to vary with time. Technological advances in cytotoxicity testing make it easy to record the dynamic data on changes in cell proliferation, morphology, and damage. To effectively and reasonably analyze the dynamic data, we present a new in vitro toxicity assessed method using the discrete-time Fourier transform (DTFT) which maps the measured cell index from the time domain to the frequency domain. The direct current (DC) component of the DTFT is extracted as a feature which reflects the intensity of cytotoxicity. The smaller the value, the higher the cytotoxicity. Then, a novel toxicity index, as expressed in terms of DC[Formula: see text], is calculated. Results generated with selected test chemicals are compared favorably with data obtained from The Interagency Coordinating Committee on the Validation of Alternative Method (ICCVAM) report concerning the prediction of acute systemic toxicity in rodents. The method can be applied with the standard and high throughput to estimate acute rodent oral toxicity which reduces the number of animals required in subsequent pharmacological/toxicological studies.

High-throughput screening assay for the environmental water samples using cellular response profiles.

Chemical and physical analyses are commonly used as screening methods for the environmental water. However, these methods can only look for the targeted substance but may miss unexpected toxicants. Furthermore, the synergistic effects of mixture cannot be detected. In order to set up the assay criteria for determining various biological activities at a cellular level that could potentially lead to toxicity of environmental water samples, a novel test based on cellular response by using Real-Time Cellular Analyzer (RTCA) is proposed in this study. First, the water sample is diluted to a series of strengths (80%, 60%, 40%, 30%, 20% and 10%) to get the multi-concentration cellular response profile. Then, the area under the cellular response profile (AUCRP) is calculated. Comparing to the normal cell growth of negative control, a new biological activity index named Percentage of Effect (PoE) has been presented which reflects the cumulative inhibitory activity of cell growth over the log-phase. Finally, a synthetical index PoE50 is proposed to evaluate the intensity of biological activities in water samples. The biological experiment demonstrates the effectiveness of the proposed method.

Analysis of inter-/intra-E-plate repeatability in the real-time cell analyzer.

Over the past decade, the real-time cell analyzer (RTCA) has provided a good tool to the cell-based in vitro assay. Unlike the traditional systems that label the target cells with luminescence, fluorescence, or light absorption, RTCA monitors cell properties using noninvasive and label-free impedance measuring. However, realization of the maximum value of RTCA for applications will require assurance of within-experiment repeatability, day-to-day repeatability, and robustness to variations in conditions that might occur from different experiments. In this article, the performance and variability of RTCA is evaluated and a novel repeatability index (RI) is proposed to analyze the intra-/inter-E-plate repeatability of RTCA. The repeatability assay involves six cell lines and two media (water [H2O] and dimethyl sulfoxide [DMSO]). First, six cell lines are exposed to the media individually, and time-dependent cellular response curves characterized as a cell index (CI) are recorded by RTCA. Then, the variations along sampling time and among repeated tests are calculated and RI values are obtained. Finally, a discriminating standard is set up to evaluate the degree of repeatability. As opposed to the standardized methodologies, it is shown that the presented index can give the quantitative evaluation for repeatability of RTCA within E-plate and variation on different days.

Mode of action classification of chemicals using multi-concentration time-dependent cellular response profiles.

In this paper, we present a new statistical pattern recognition method for classifying cytotoxic cellular responses to toxic agents. The advantage of the proposed method is to quickly assess the toxicity level of an unclassified toxic agent on human health by bringing cytotoxic cellular responses with similar patterns (mode of action, MoOA) into the same class. The proposed method is a model-based hierarchical classification approach incorporating principal component analysis (PCA) and functional data analysis (FDA). The cytotoxic cell responses are represented by multi-concentration time-dependent cellular response profiles (TCRPs) which are dynamically recorded by using the xCELLigence real-time cell analysis high-throughput (RTCA HT) system. The classification results obtained using our algorithm show satisfactory discrimination and are validated using biological facts by examining common chemical mechanisms of actions with treatment on human hepatocellular carcinoma cells (HepG2).

In vitro cytotoxicity assessment based on KC(50) with real-time cell analyzer (RTCA) assay.

Technological advances in cytotoxicity analysis have now made it possible to obtain real time data on changes in cell growth, morphology and cell death. This type of testing has a great potential for reducing and refining traditional in vivo toxicology tests. By monitoring the dynamic response profile of living cells via the xCELLigence real-time cell analyzer for high-throughput (RTCA HT) system, cellular changes including cell number (cell index, CI) are recorded and analyzed. A special scaled index defined as normalized cell index (NCI) is used in the analysis which reduces the influence of inter-experimental variations. To assess the extent of exposure of the tested chemicals, a two-exponent model is presented to describe rate of cell growth and death. This model is embodied in the time and concentration-dependent cellular response curves, and the parameters k1 and k2 in this model are used to describe the rate of cell growth and death. Based on calculated k2 values and the corresponding concentrations, a concentration-response curve is fitted. As a result, a cytotoxicity assessment named KC50 is calculated. The validation of the proposed method is demonstrated by exposing six cell lines to 14 chemical compounds. Our findings suggest that the proposed KC50-based toxicity assay can be an alternative to the traditional single time-point assay such as LC50 (the concentration at which 50% of the cells are killed). The proposed index has a potential for routine evaluation of cytotoxicities. Another advantage of the proposed index is that it extracts cytotoxicity information when CI fails to detect the low toxicity.

Real-time cell-microelectronic sensing of nanoparticle-induced cytotoxic effects.

We report a real-time cell analysis (RTCA) sensing method of 96 electronic microwells for profiling the cytotoxicity of nanoparticles on different cell lines. The method consists of 96 microwells embedded with microelectrodes (96x E-plate) to measure impedance changes of adherent cell lines. When the testing cells change in population, adhesion, and/or morphology, the impedance at the cell-electrode interface changes to provide real-time monitoring of overall cell status. To demonstrate this technique, we used three cell lines as sensing probes: two human lung carcinoma cell lines, A549 and SK-MES-1, and a normal mammalian cell line, CHO-K1. We tested two well-characterized nanoparticles: nano-titanium dioxide (nTiO2) and nano-silver (nAg). The three cell lines were separately seeded into 96x E-plates and treated with varying concentrations of nanoparticles (0.078-160 µg mL(-1)). This method provides dynamic cell response profiles and temporal IC50 histograms, showing concentration-, time-, particle-, and cell-dependent cytotoxicity. The 24 h and 48 h IC50 values of nAg obtained using both the RTCA and the neutral red uptake (NRU) assays were in good agreement, validating the RTCA technique. The RTCA assay does not suffer interference from nTiO2, whereas the NRU assay cannot be used due to severe interference from nTiO2. A cytostatic response was observed in CHO-K1 cells after 24 h exposure to 40 µg mL(-1) nTiO2, which was correlated with S-phase cell cycle arrest based on cell cycle analysis using flow cytometry. This suggests that the shapes of the response curves provide indicative information, directing further studies into the mode of action of the toxicant. Advantages of the RTCA technique over traditional colorimetric assays for screening the cytotoxicity of nanoparticles include minimizing interference, qualitative and quantitative cytotoxicity data, and the capability of real-time and high-throughput measurements.

Cytotoxicity assessment based on the AUC50 using multi-concentration time-dependent cellular response curves.

Although many indices have been developed to quantify chemical toxicity, substantial shortcoming is inherent in most of them, such as observation time dependence, insufficient robustness, and no comparison with the negative control. To assess the extent of exposure of the tested substance, a cytotoxicity assay named AUC(50) was developed to describe the time and concentration-dependent cellular responses. By monitoring the dynamic cytotoxicity response profile of living cells via the xCELLigence real-time cell analysis high-throughput (RTCA HT) system, changes in cell number (named cell index, CI) were recorded and analyzed subsequently. A normalized cell index (NCI) is introduced to reduce the influence of inter-experimental variations. The log-phase of cellular growth is considered, which alleviates the cell's spontaneous effect. The area between the control line and the assessed time-dependent cellular response curve (TCRC) of the tested substance was calculated, and the corresponding exponential kill model (concentration-response curve) was developed along with exploiting the concept of AUC(50). The validation of the proposed method is demonstrated by exposing HepG2 cell line to seven chemical compounds. Our findings suggested that the proposed AUC-based toxicity assay could be an alternative to the traditional single time-point assay, and it has potential to become routine settings for evaluating the cell-based in vitro assay. Furthermore, the AUC(50) combined with RTCA HT assay can be used to achieve a high-throughput screening that conventional cellular assay cannot achieve.

High-throughput quantitative analysis with cell growth kinetic curves for low copy number mutant cells.

The mutation rate in cells induced by environmental genotoxic hazards is very low and difficult to detect using traditional cell counting assays. The established genetic toxicity tests currently recognized by regulatory authorities, such as conventional Ames and hypoxanthine guanine phosphoribosyl-transferase (HPRT) assays, are not well suited for higher-throughput screening as they require large amounts of test compounds and are very time consuming. In this study, we developed a novel cell-based assay for quantitative analysis of low numbers of cell copies with HPRT mutation induced by an environmental mutagen. The HPRT gene mutant cells induced by the mutagen were selected by 6-thioguanine (6-TG) and the cell's kinetic growth curve monitored by a real-time cell electronic sensor (RT-CES) system. When a threshold is set at a certain cell index (CI) level, samples with different initial mutant cell copies take different amounts of time in order for their growth (or CI accumulation) to cross this threshold. The more cells that are initially seeded in the test well, the faster the cell accumulation and therefore the shorter the time required to cross this threshold. Therefore, the culture time period required to cross the threshold of each sample corresponds to the original number of cells in the sample. A mutant cell growth time threshold (MT) value of each sample can be calculated to predict the number of original mutant cells. For mutagenesis determination, the RT-CES assay displayed an equal sensitivity (p > 0.05) and coefficients of variation values with good correlation to conventional HPRT mutagenic assays. Most importantly, the RT-CES mutation assay has a higher throughput than conventional cellular assays.

Pre-analytical and analytical procedures for the detection of enteric viruses and enterovirus in water samples.

Practical pre-analytical and analytical procedures were developed and validated for detection of enteric viruses in three water matrices. Both RNA viruses (norovirus, coxsackievirus, echovirus, and rotavirus) and DNA virus (adenovirus 41) were included in the study. The NanoCeram 90mm laminated disc with electropositive filter and procedures of filtration, elution and flocculation were utilized to concentrate known amount of viruses in different water matrices. Real time quantitative PCR was used to evaluate the recovery of virus and cell culture to assess viral infectivity. There was no PCR inhibition using various concentrations and pH of beef extract eluting buffer. A good recovery of the viruses spiked in 10L of deionized water was achieved for serial dilutions of coxsackievirus (41-67%), echovirus (22-90%), norovirus (23-44%) and rotavirus (24-46%). Relatively lower recovery was observed for adenovirus 41 (24-35%). There was no significant difference in viral recovery from deionized, tap and river water samples. The infectivity of recovered adenovirus, coxsackievirus and echovirus was demonstrated using in vitro cell culture. The pre-analytical and analytic procedures attained consistent recovery of RNA and DNA viruses both as infectious viral particles and viral genome, provided effective removal of inhibitory substances, achieved reliable reproducibility, and were relatively inexpensive for monitoring viruses in water.

Real-time cell-impedance sensing assay as an alternative to clonogenic assay in evaluating cancer radiotherapy.

Intrinsic radiosensitivity of normal and tumour tissues has been shown to be an independent prognostic factor for patients' response to radiotherapy. This study compares the real-time cell-impedance sensing (RT-CES) assay with the conventional clonogenic assay in terms of in-vitro radiosensitivity. One objective in this study was to predict in-vivo response to gold nanoparticle (GNP) treatment on the basis of in-vitro RT-CES testing results. Four adenocarcinoma cancer cell lines were tested using both the RT-CES and the clonogenic assays. Cell-survival curves were plotted, and the mean SF2 values obtained by these two different assay methods were compared using ANOVA. Radiation sensitivities obtained in-vitro were then compared with the in-vivo results. On the basis of the measurement of cell colonies, the RT-CES assay has similar radiosensitivity to the clonogenic assay, but significantly shortens the testing time from 14-21 days to only 72 h. Intrinsic GNP enhanced radiation sensitivity using tumour volume (mm(3)) in vivo is comparable with that using RT-CES cell survival assay in vitro. Furthermore, the RT-CES system provides real-time information regarding the state of cell radiosensitivity that may give useful information towards personalizing radiotherapy. The RT-CES assay enables more reliable and time-efficient results in the evaluation of radiosensitivity.

Biomonitoring of arsenic in urine and saliva of children playing on playgrounds constructed from chromated copper arsenate-treated wood.

Children may be exposed to arsenic during contact with structures treated with chromated copper arsenate (CCA). A high frequency of hand-to-mouth activity may increase their risk of ingesting arsenic. Previous work showed that arsenic concentrations in the hand-wash samples of children playing on CCA playgrounds were four times higher than those playing on non-CCA playgrounds. It is not clear whether playing on CCA playgrounds results in elevated overall exposure to arsenic. The objective of this study was to perform arsenic biomonitoring in children to determine whether playing on CCA-treated playgrounds substantially contributes to their overall exposure to arsenic. One hundred and twenty five saliva samples from 61 children and 101 urine samples from 45 children were collected after children played on 8 CCA and 8 non-CCA playgrounds. Arsenic speciation analysis was conducted using high performance liquid chromatography combined with inductively coupled plasma mass spectrometry. The arsenic species detected in the urine and saliva samples from children playing on CCA and non-CCA playgrounds were similar. Dimethylarsinic acid and arsenobetaine were the main arsenic species found in urine samples. The sum of inorganic trivalent and pentavalent arsenic, monomethylarsonic acid, and dimethylarsinic acid in urine was 15 +/- 28 microg/L in the CCA group and 12 +/- 23 microg/L in the non-CCA group (p = 0.60). The sum of these species in saliva was 1.1 +/- 2.1 microg/L in the CCA group and 1.4 +/- 1.1 microg/L in the non-CCA group (p = 0.32). These results show that there is no significant difference in the concentration or speciation of arsenic between the samples from children playing on CCA and non-CCA playgrounds. Contact with CCA playgrounds is not likely to significantly contribute to the overall arsenic exposure in children; other sources such as dietary arsenic may be a main contributor to their overall exposure.

A multi-function public health surveillance system and the lessons learned in its development: the Alberta Real Time Syndromic Surveillance Net.

OBJECTIVE: We describe a centralized automated multi-function detection and reporting system for public health surveillance--the Alberta Real Time Syndromic Surveillance Net (ARTSSN). This improves upon traditional paper-based systems which are often fragmented, limited by incomplete data collection and inadequate analytical capacity, and incapable of providing timely information for public health action. METHODS: ARTSSN concurrently analyzes multiple electronic data sources in real time to describe results in tables, charts and maps. Detected anomalies are immediately disseminated via alerts to decision-makers for action. RESULTS: ARTSSN provides richly integrated information on a variety of health conditions for early detection of and prompt action on abnormal events such as clusters, outbreaks and trends. Examples of such health conditions include chronic and communicable disease, injury and environment-mediated adverse incidents. DISCUSSION: Key advantages of ARTSSN over traditional paper-based methods are its timeliness, comprehensiveness and automation. Public health surveillance of communicable disease, injury, environmental hazard exposure and chronic disease now occurs in a single system in real time year round. Examples are given to demonstrate the public health value of this system, particularly during Pandemic (H1N1) 2009.

Dynamic cytotoxic response to microcystins using microelectronic sensor arrays.

Microcystins are bioactive metabolites produced by cyanobacteria in water. These cyclic heptapeptides have caused public health concern worldwide. By interfering with cellular phosphorylation and signaling, microcystins can cause acute and chronic liver diseases. Therefore, the World Health Organization (WHO) has set the provisional drinking water guideline value at 1.0 microg/L for microcystin-LR (free plus cell-bound). Microcystins do not readily cross cell membranes in in vitro cell-based assays, except for those using freshly isolated hepatocytes. However, the sensitivity of in vitro cell-based assays is not adequate for testing samples at low environmental concentrations. Hence, there is a need to develop a sensitive and stable cytotoxicity assay for use in environmental studies. On the basis of the observation that microcystin-LR can be transported by the liver-specific members of the organic anion transporting polypeptides (OATPs), we investigated the potential of using an OATP1B3-expressing cell line in a cytotoxicity assay for microcystins. Using a novel cell electronic sensing system (RT-CES), we were able to monitor the real-time, dynamic cytotoxic response to microcystins at microgram per liter concentrations. We demonstrated that the cytotoxicity of the most common microcystins, -LR, -YR, -RR, -LF, and -LW, was mediated by OATP1B3 transporters. Microcystin-LF is the most potent toxin among the five congeners. In conclusion, we have established a highly automated, real-time, sensitive, and stable assay for measuring microcystin cytoxicity.

Reliability of using urinary and blood trichloroacetic acid as a biomarker of exposure to chlorinated drinking water disinfection byproducts.

This study was designed to analyse the reliability of using urinary and blood trichloroacetic acid (TCAA) as a biomarker of exposure. A total of 46 healthy women consumed supplied TCAA-containing tap water for 15 days and provided urine and blood samples for TCAA measurements. The findings revealed that the reliability of measurements was excellent by using measures of TCAA ingestion, blood concentration and urinary excretion (intraclass correlation coefficients (ICC) > 0.75, p < 0.001). Volume of tap water consumption (ICC = 0.69) and creatinine-adjusted urinary concentration (ICC = 0.72) were less reliable. This indicated that the intraindividual variability was small and the interindividual reliability was high by using these measures in this cohort study. Laboratory variability did not significantly contribute to total variance (ICC > 0.95, p < 0.001). Other possible sources of variation such as bathing, showering, dishwashing and physical activities were unlikely to contribute significantly to total variance. For sampling strategies, 1-day blood sampling and 2-day urine sampling are sufficient to achieve reliability for an epidemiological study if a quasi-steady-state TCAA level in the body is reached. The results suggest that TCAA ingestion, TCAA loading in blood and urinary TCAA excretion are reliable measures for use as biomarkers in epidemiological studies.

Validation of urinary trichloroacetic acid as a biomarker of exposure to drinking water disinfection by-products.

Disinfection by-products (DBPs) in drinking water represent a public health issue and a challenge for epidemiology to provide evidence towards the causation of various hypothesized health effects. Validation of a biomarker of exposure to DBPs is a strategy to achieve progress which has been advocated. The objective of this study was to validate urinary trichloroacetic acid (TCAA) excretion as a biomarker of exposure to DBPs in an experimental exposure cohort. A total of 52 healthy women participated in the study. Participants consumed supplied tap water for 15 d and provided urine and blood samples for TCAA measurements. The findings revealed that (1) background levels of TCAA in urine and blood were readily detectable, (2) TCAA levels in blood and urine increased with increased amounts of TCAA ingested, (3) the correlations between measurements of TCAA ingestion and urinary excretion were modest (r=0.66, p<0.001) based on one days' sampling and high (r=0.77-0.83, p<0.001) based on two to four days' sampling, (4) the correlations between measurements of TCAA ingestion and blood TCAA concentration were high (r=0.80, p<0.001) and (5) multiple days' urinary TCAA measures improved the prediction of TCAA ingestion through urinary TCAA excretion. TCAA can be a valid biomarker of exposure for DBPs in drinking water.