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PubMed2006

Seasonal variability of oxidative biomarkers, lysosomal parameters, metallothioneins and peroxisomal enzymes in the Mediterranean mussel Mytilus galloprovincialis from Adriatic Sea.

The Mediterranean mussel, Mytilus galloprovincialis, is a classical sentinel organism for monitoring the biological effects of contaminants through the use of molecular and cellular biomarkers. These biological responses can be modulated also by seasonal changes of both environmental and biological factors, potentially influencing responsiveness and sensitivity to pollutants. The aim of this study was to characterize in a reference mussel population from the Adriatic Sea, the natural fluctuations of several oxidative stress biomarkers widely used in ecotoxicological applications. Analyses of individual antioxidant defenses (catalase, glutathione S-transferases, glutathione reductase, glutathione peroxidases, levels of glutathione) were integrated with those of the total oxyradical scavenging capacity (TOSC-assay), which quantify the overall capability of a tissue to neutralize different forms of oxyradicals. Due to the close relationship between antioxidant efficiency and onset of various cellular alteration, the seasonal characterization was carried out also on lysosomal membrane stability, accumulation of malondialdehyde, neutral lipids and lipofuscin, levels of metallothioneins and activity of peroxisomal enzymes (acyl-CoA oxidase and d-aminoacid oxidase). Results indicated a significant seasonality for several biological responses; major variations occurred especially in spring and summer months suggesting the influence of natural factors, such as temperature, reproductive cycle and food availability. The observed seasonal oscillations revealed both similarities and differences with those reported for other Mediterranean mussel populations suggesting that opposite trends can occur when the same environmental prooxidant factors have a different regional influence.

Animals↗

PubMed2006

ELISA microarray technology as a high-throughput system for cancer biomarker validation.

A large gap currently exists between the ability to discover potential biomarkers and the ability to assess the real value of these proteins for cancer screening. One major challenge in biomarker validation is the inherent variability in biomarker levels. This variability stems from the diversity across the human population and the considerable molecular heterogeneity between individual tumors, even those that originate from a single tissue. An additional challenge with cancer screening is that most cancers are rare in the general population, meaning that assay specificity must be very high. Otherwise, the number of false positives will be much greater than the number of true positives. Due to these challenges associated with biomarker validation, it is necessary to analyze thousands of samples in order to obtain a clear idea of the utility of a screening assay. Enzyme-linked immunosorbent assay (ELISA) microarray technology can simultaneously quantify levels of multiple proteins and, thus, has the potential to accelerate validation of protein biomarkers for clinical use. This review will discuss current ELISA microarray technology and potential advances that could help to achieve the reproducibility and throughput that are required to evaluate cancer biomarkers.

Biomarkers, Tumor↗

PubMed2004

Initial analysis of variability among basal hormone biomarkers of ovarian reserve.

The most commonly used biomarker tests of ovarian reserve are basal hormone measurements during the early follicular phase, including mainly FSH but also oestradiol, FSH:LH ratio, and inhibin B. This study was designed to assess prospectively the intra- and inter-cycle variability of serum values of those hormone biomarkers in the early follicular phase of consecutive cycles in a group of women candidates for assisted reproduction. Fifty eumenorrhoeic women underwent blood sampling for hormone measurement on cycle day 3 for three consecutive cycles, and during the first study cycle, daily samples were obtained on cycle days 2, 3, 4 and 5. No significant difference was detected among FSH concentrations and FSH:LH ratios during cycle days 2-5; in contrast, oestradiol and inhibin B were not constant through the early follicular phase. No difference in FSH or inhibin B serum concentrations and FSH:LH ratio on cycle day 3 during three consecutive cycles was noted; however, significant inter-cycle variability for oestradiol serum concentration on cycle day 3 was detected. FSH and inhibin serum concentrations, and FSH:LH ratio varied significantly less than oestradiol on cycle day 3, but inter-cycle variability was similar for the first three hormonal biomarkers of ovarian reserve. There was significantly less intra-cycle variability of FSH serum concentration and FSH:LH ratio than oestradiol and inhibin B serum concentrations. Basal FSH serum concentrations (or FSH:LH ratio) during the early follicular phase showed neither significant inter-cycle nor intra-cycle variability when measured during 3 consecutive months in an assisted reproduction patient population, thus offering greater flexibility of pretreatment sampling.

Adult↗

PubMed1996

Air toxics regulatory issues facing urban settings.

Biomarker research does not exist in isolation. Its usefulness can only be realized when it is translated into prevention strategies to protect public health. In the context of air toxics, these prevention strategies begin with the development of regulatory standards derived from risk assessment schemes. The Clean Air Act Amendments of 1990 list 189 air toxics, including many volatile organics, metals, and pesticides. The National Institute of Environmental Health Sciences (NIEHS), through its affiliation with the National Toxicology Program, has generated toxicity and carcinogenicity data on more than 100 of these air toxics. The NIEHS extramural and intramural research portfolios support a variety of projects that develop and validate biomarkers for use in environmental health science and risk assessment. Biomarkers have a tremendous potential in the areas of regulating air toxics and protecting public health. Risk assessors need data provided by biomarkers of exposure, biomarkers of dose/pharmacokinetics, biomarkers of susceptibility or individual variability, and biomarkers of effects. The greatest benefit would be realized if biomarkers could be employed in four areas of primary and secondary prevention. The first is the use of biomarkers to enhance extrapolation of animal data to human exposure situations in establishing risk standards. The second is the use of biomarkers that assess noncancer, as well as cancer, end points. Important health end points include pulmonary dysfunction, immunotoxicity, and neurotoxicity. Third, biomarkers that serve as early waming signs to detect intermediate effects would enhance our ability to design timely and cost-effective intervention strategies. Finally, biomarkers used to evaluate the effectiveness of intervention strategies, both in clinical and regulatory settings, would enable us to ensure that programs designed to protect public health do, in fact, achieve the desired outcome.

Air Pollutants↗

PubMed1999

Physiologically based toxicokinetic modeling of inhaled ethyl tertiary-butyl ether in humans.

A physiologically based toxicokinetic (PBTK) model was developed for evaluation of inhalation exposure in humans to the gasoline additive, ethyl tertiary-butyl ether (ETBE). PBTK models are useful tools to relate external exposure to internal doses and biological markers of exposure in humans. To describe the kinetics of ETBE, the following compartments were used: lungs (including arterial blood), liver, fat, rapidly perfused tissues, resting muscles, and working muscles. The same set of compartments and, in addition, a urinary excretion compartment were used for the metabolite tertiary-butyl alcohol (TBA). First order metabolism was assumed in the model, since linear kinetics has been shown experimentally in humans after inhalation exposure up to 50 ppm ETBE. Organ volumes and blood flows were calculated from individual body composition based on published equations, and tissue/blood partition coefficients were calculated from liquid/air partition coefficients and tissue composition. Estimates of individual metabolite parameters of 8 subjects were obtained by fitting the PBTK model to experimental data from humans (5, 25, 50 ppm ETBE, 2-h exposure; Nihlén et al., Toxicol. Sci., 1998; 46, 1-10). The PBTK model was then used to predict levels of the biomarkers ETBE and TBA in blood, urine, and exhaled air after various scenarios, such as prolonged exposure, fluctuating exposure, and exposure during physical activity. In addition, the interindividual variability in biomarker levels was predicted, in the eight experimentally exposed subjects after a working week. According to the model, raising the work load from rest to heavy exercise increases all biomarker levels by approximately 2-fold at the end of the work shift, and by 3-fold the next morning. A small accumulation of all biomarkers was seen during one week of simulated exposure. Further predictions suggested that the interindividual variability in biomarker levels would be higher the next morning than at the end of the work shift, and higher for TBA than for ETBE. Monte Carlo simulations were used to describe fluctuating exposure scenarios. These simulations suggest that ETBE levels in blood and exhaled air at the end of the working day are highly sensitive to exposure fluctuations, whereas ETBE levels the next morning and TBA in urine and blood are less sensitive. Considering these simulations, data from the previous toxicokinetic study and practical issues, we suggest that TBA in urine is a suitable biomarker for exposure to ETBE and gasoline vapor.

Biomarkers↗

PubMed1999

Biomarkers of dose and susceptibility in cyclists exposed to monoaromatic hydrocarbons.

A quasi-experimental field study was carried out in 24 volunteers with the aim of: (i) assessing personal exposure to aromatic hydrocarbons polluting urban areas; and (ii) exploring the role of polymorphic enzymes relevant to the biotransformation of benzene in the inter-individual variability of biomarkers. Each subject covered by bicycle: (i) inner city routes with often jammed traffic; and (ii) open rural routes. Time-weighted average airborne concentrations of benzene, toluene, ethylbenzene and xylenes (BTEX) were determined during 2-h runs. BTEX were determined by solid-phase micro-extraction (SPME) followed by gas chromatography coupled with mass spectrometry (GC-MS) in blood and spot urine samples collected just before and immediately after the runs. Urinary t,t-muconic acid was measured by high performance liquid chromatography (HPLC)-UV. Genotypes of epoxide hydrolase (EH) and glutathione-S-transferase class mu-1 (GSTM1) were also characterised. As compared to pre-run values, benzene and toluene in blood, and toluene and xylenes in urine significantly increased after urban runs. Urinary t,t-muconic acid was significantly higher in post-run samples after both urban (P < 0.001) and rural runs (P < 0.05). Despite a narrow range of exposure levels, a significant relationship was observed between airborne benzene and post-run t,t-muconic acid (r2 = 0.349, P < 0.00). When subgroups were distinguished according to EH and GSTM, subjects bearing both the EH wild type and GSTM 'null' genotype showed significant exposure-related changes in t,t-muconic acid excretion. Even at very low exposure levels, a 2-h bike run in a polluted urban environment may give rise to measurable changes in biomarkers of internal dose of selected aromatic hydrocarbons. Genetically-based metabolic differences may account for part of the inter-individual variability of biomarkers of exposure.

Adult↗

PubMed2006

Intraindividual variability of plasma antioxidants, markers of oxidative stress, C-reactive protein, cotinine, and other biomarkers.

BACKGROUND: Within-person variability in biomarkers results in random error that can attenuate estimates of association. Little information on such variability is available for a number of nutrition-related biomarkers. METHODS: Blood samples obtained 2 to 4 weeks apart were analyzed for tocopherols, carotenoids, ascorbate, lipids, cotinine, C-reactive protein, and oxidative stress. Subjects (n = 206 men and women, mean age 45.4 years) were either smokers or passively exposed to smoke. We calculated intraindividual and interindividual variability and the number of measurements required to reduce attenuation. RESULTS: For most biomarkers, 2 measurements would be required to limit the attenuation of correlation coefficients to no lower than 90% of the true correlation. If only one measurement were obtained, observed correlations would be approximately 80-88% of true correlations. For regression coefficients, 3 or 4 measures would be required. Exceptions were ascorbic acid and malondialdehyde, for which a single measure resulted in little attenuation. CONCLUSIONS: For most serum markers, collection of 2 or more measurements per person is desirable to increase the ability to detect associations between biomarkers and health-related variables. If only one measure is possible, sample sizes should be planned to permit detection of associations that are likely to be observed, not the theoretical true associations. The results of this study, in which measurements were obtained 2 to 4 weeks apart, are relevant for epidemiologic research in which the exposure of interest is the subject's baseline or current status. It is likely that within-person variability would be greater over a period of months or years.

Adolescent↗

PubMedDate not supplied

Intra- and inter-individual variability in measurements of biomarkers for oxidative damage in vivo: Nutrition and Breast Health Study.

Oxidative stress has been implicated in the pathogenesis of various chronic diseases, such as cancer, cardiovascular disease and inflammatory conditions, as well as in ageing. Although a number of markers are now available, little is known about the reliability of single measurements of such markers in healthy individuals. The study examined the distribution of variance for three oxidative stress markers, 8-oxo-2'-deoxyguanosine (8-oxodG), 5-hydroxymethyl-2'-deoxyuridine (5-OHmdU) and total 8-isoprostane-F2alpha, which were measured every 3-6 months over 1 year in blood and breast nipple aspirate fluid (NAF) for 103 premenopausal women. For both plasma and NAF, the between-subject variances of 8-isoprostane-F2alpha were consistently greater than the within-subject variances. Consequently, their reliability coefficients were close to the level of those for cholesterol. On the other hand, the within-subject variances were much greater than the between-subjects variances for blood 5-OHmdU, resulting in low reliability coefficients, i.e. <0.3. Overall, the reliability coefficients for blood 8-oxodG were between those of 8-isoprostane-F2alpha and 5-OHmdU, but closer to those of 8-isoprostane-F2alpha. The results suggest that the reliability of oxidative stress markers may vary considerably depending on the type of marker. Caution should be exercised in selecting markers as well as in determining the number of study subjects or the number of samples per subject in a study. There also may be ample room to optimize laboratory techniques to quantify markers of oxidative DNA damage.

8-Hydroxy-2'-Deoxyguanosine↗

PubMed2005

Biomarkers, health, lifestyle, and demographic variables as correlates of reaction time performance in early, middle, and late adulthood.

We aimed to identify demographic, health, and biomarker correlates of reaction time performance and to determine whether biomarkers explained age differences in reaction time performance. TIhe sample comprised three representative cohorts aged 20-24, 40-44, and 60-64 years, including a total of 7,485 participants. Reaction time measures of intraindividual variability and latency were used. The measure of intraindividual variability used was independent of mean reaction time. Older adults were more variable than younger adults in choice reaction time performance but not simple reaction time performance. The most important correlates of reaction time performance after gender and education were biological markers such as forced expiratory volume at one second, grip strength, and vision. Few measures of physical or mental health or lifestyle were associated with poorer performance on reaction time measures. Biomarkers explained the majority of age-related variance in simple reaction time and a large proportion of variance in choice reaction time. We conclude that for the ages studied, biomarkers are more important than health factors for explaining age differences in reaction time performance.

Adult↗

PubMedDate not supplied

A proposal for the use of biomarkers for the assessment of chronic pollution and in regulatory toxicology.

Despite a wealth of information on biomarkers, they are not routinely used for regulatory purposes, even though the potential benefits of biomarkers to rationalise complex exposure-response relationships are clear. Biomarkers can be inappropriately applied or misinterpreted, because the fundamental assumptions in exposure-response relations have not been considered. Factors causing temporal and spatial variability in biomarker responses are reviewed. These include numerous geochemical and biotic variables. The variation can be minimised by appropriate study site selection, experimental replication, multivariate epidemiological approaches, normalised controls, and temporal calibration of responses; so that the regulatory use of biomarkers for biomonitoring and tracking pollution events, including chronic or multiple exposures to complex mixtures is possible. We propose and define the characteristics of biomarkers of chronic exposure or effect, which must measure changes in pollution/effect against long-term changes in other general stresses (disease, nutrition, environmental quality), relate to cumulative injury, and remain responsive over months or years. Neuroendocrine, immunological, and histological biomarkers are suggested for chronic pollution. We propose a regulatory framework for biomarkers based on a weight of evidence approach that can integrate biomarkers in risk assessment and long-term monitoring programmes.

Animals↗

PubMed1996

Identification of needs in biomarker research.

Interest in the use of biological markers to evaluate future disease risk has increased greatly in recent years. Biomarkers are observable end points in a continuum of events leading from exposure to toxic agents to diseases that ultimately result from exposure. Because many significant diseases develop over long periods of time, methods for detecting early events that can predict risk are important for disease prevention. Biomarkers are generally categorized as detecting exposure, effects of exposure, or individual susceptibility to exposure. Although there has been significant progress in the technical development of biomarkers, implementation of their use in human populations has progressed much more slowly. We discuss four major needs in the development of biomarkers. First, new biomarkers need to be developed to fill gaps in our ability to observe steps in the continuum from exposure to disease. Second, the relationships between biomarker responses and disease pathology needs to be better understood. Third, the sensitivity, specificity, and variability of biomarkers need to be better characterized and they must be better validated as predictors of disease risk. Fourth, there are several societal impediments to the practical implementation of biomarker studies as public health tools. A common agreement among employers, employees, regulators, and the legal community must be established regarding appropriate and ethical uses and interpretation of biomarker data.

Biomarkers↗

PubMed1993

Evaluation of stable isotope-labeled probes in the study of solvent pharmacokinetics in human subjects.

The relationship between biomarkers of exposure (such as concentrations of toxicants in blood or breath, or metabolites in urine) and toxicant dose for individuals is influenced by many person- and episode-specific factors which contribute to overall variability in biomarker level for a given dose. This variability results in imprecise biological marker-based estimates of dose for individuals. We hypothesize that pharmacokinetic data from stable-isotope (deuterated) analogs can be used with a pharmacokinetic model to account for individual-related sources of variation, leading to more precise methods of dose estimation for individuals. To establish the degree of similarity in the pharmacokinetics of unlabeled (d0-) and fully deuterated (D8-) toluene, 21 men (ages 20-45) inhaled an equal molar mixture for 2h. Washout kinetics for both compounds were followed for 4 d in alveolar air and blood. Both compounds exhibited three-phase elimination kinetics in both fluids. The third phase was not always definable for d0-toluene because of concurrent uncontrolled environmental exposures. Considering data from only the first two phases, concentrations of d0- and d8-toluene in alveolar air and blood were well correlated for all subjects, even though pharmacokinetic parameters varied among individuals by 5-9 folds. Further experiments are needed to discern whether correlations between d0- and d8-toluene for the third phase are influenced by an isotope effect; present data support use of d8-toluene as a suitable probe for d0-kinetics.

Adult↗

PubMed2002

Delivery of high-quality biomarker assays.

Biomarker measurements now support key decisions throughout the drug development process, from lead optimization to regulatory approvals. They are essential for documenting exposure-response relationships, specificity and potency toward the molecular target, untoward effects, and therapeutic applications. In a broader sense, biomarkers constitute the basis of clinical pathology and laboratory medicine. The utility of biomarkers is limited by their specificity and sensitivity toward the drug or disease process and by their overall variability. Understanding and controlling sources of variability is not only imperative for delivering high-quality assay results, but ultimately for controlling the size and expense of research studies. Variability in biomarker measurements is affected by: biological and environmental factors (e.g., gender, age, posture, diet and biorhythms), sample collection factors (e.g., preservatives, transport and storage conditions, and collection technique), and analytical factors (e.g., purity of reference material, pipetting precision, and antibody specificity). The quality standards for biomarker assays used in support of nonclinical safety studies fall under GLP (FDA) regulations, whereas, those assays used to support human diagnostics and healthcare are established by CLIA (CMS) regulations and accrediting organizations such as the College of American Pathologists. While most research applications of biomarkers are not regulated, biomarker laboratories in all settings are adopting similar laboratory practices in order to deliver high-quality data. Because of the escalation in demand for biomarker measurements, the highly-parallel (multi-plexed) assay platforms that have fueled the rise of genomics will likely evolve into the analytical engines that drive the biomarker laboratories of tomorrow.

Biomarkers↗

PubMedDate not supplied

Exploratory data analysis of the Mediterranean component of the BEEP programme.

Work Package 3 (WP3) uses the data generated by ecotoxicologists from 11 laboratories who sample twice per year at four sites (France, Italy, Spain and Greece) to conduct the Mediterranean portion of the BEEP programme (Biological Effects of Environmental Pollution in marine coastal ecosystems). The WP3 data have been compiled into files using a data base structure (one record=one measurement) that eases statistical analysis and importation of new data. Here we present our first attempt of exploratory analysis based on a subset of data from the campaigns in May and September of 2001 and 2002. For most biomarkers, data plot revealed a strong station*campaign interaction, confirmed by two-way ANOVAs. This could be "true" variability with biomarkers responding to contaminant inputs that have changed among the four sampling times. Alternatively it could betray analytical problems and inadequate sampling designs or a lack of stability in the biomarkers themselves whereby they change in random ways unrelated to environmental factors.

Acetylcholinesterase↗

PubMed2006

Evaluation of the global protein synthesis in Mytilus galloprovincialis in marine pollution monitoring: seasonal variability and correlations with other biomarkers.

Protein synthesis down-regulation is a life-saving mechanism for many organisms exposed to xenobiotics that threaten normal life. The present study was designed to assess the spatial and seasonal variability of global protein synthesis, determined in the microsomal fraction of digestive glands from caged Mytilus galloprovincialis mussels exposed for 30 days in a relatively clean region and two unevenly polluted areas (Stations 1 and 2) along the Gulf of Patras (Greece). The in vivo activity of translating ribosomes was evaluated by analyzing the translating ribosomes, polysome content, which may serve as an indicator of the efficiency of the protein-synthesizing machinery. To correlate with classical biomonitoring strategies, various biomarkers were measured in digestive glands, including metallothionein content, heavy-metal content, and lysosomal membrane stability. In parallel, gill cells were examined for micronucleus frequency. Metal ion concentrations were also estimated in the surrounding waters as a measure of metal exposure. Substantially lower polysome content was recorded in caged mussels collected from Station 1, in particular during the winter and spring sampling. As verified by chemical analysis of the seawater and measurement of other biomarkers, Station 1 was more contaminated than Station 2. Polysome content was found negatively correlated with metallothionein levels, micronucleus frequency and cytosolic Cu and Hg in all seasons. In addition, negative correlations were obtained between polysome content and lysosomal membrane stability in winter and spring. A progressive increase in polysomes was observed from winter to autumn, in particular in samples from Station 1. A non-uniform trend was detected in 80S ribosomal monosomes, whereas the seasonal changes in ribosomal subunits were opposite to those found in polysome content. Comparisons between seasonal and local site-specific influences on polysome content provides evidence that winter and spring are the most appropriate sampling seasons for application of translation activity as a possible biomarker in biomonitoring studies.

Animals↗

PubMed2002

Relationship between baseline white blood cell count and degree of coronary artery disease and mortality in patients with acute coronary syndromes: a TACTICS-TIMI 18 (Treat Angina with Aggrastat and determine Cost of Therapy with an Invasive or Conservative Strategy- Thrombolysis in Myocardial Infarction 18 trial)substudy.

OBJECTIVES: This study was designed to determine the relationship between baseline white blood cell (WBC) count and angiographic and clinical outcomes in patients with unstable angina (UA)/non-ST-segment elevation myocardial infarction (NSTEMI) and to see if WBC count was a significant predictor of outcomes independent of other biomarkers. BACKGROUND: Inflammation has been shown to play a role in atherosclerosis and acute coronary syndromes. METHODS: We evaluated the relationship between baseline WBC count, other baseline variables and biomarkers, angiographic findings, and clinical outcomes in 2,208 patients in the Treat angina with Aggrastat and determine Cost of Therapy with an Invasive or Conservative Strategy-Thrombolysis In Myocardial Infarction 18 (TACTICS-TIMI 18) trial. RESULTS: Higher baseline WBC counts were associated with lower Thrombolysis In Myocardial Infarction (TIMI) flow grades (p = 0.0045) and TIMI myocardial perfusion grades (p = 0.03) as well as a greater extent of coronary artery disease (CAD) (p < 0.0001). A higher baseline WBC count was predictive of higher six-month mortality, ranging from 1.5% to 3.6% to 5.1% for patients with low, intermediate, and high WBC counts, respectively (p = 0.0017). In a multivariable proportional hazards model, patients with a low C-reactive protein (CRP) but an elevated WBC remained at significantly higher risk of death at six months (hazard ratio [HR] 4.3, p = 0.049), and patients with a high CRP were at even higher risk (HR 8.6, p = 0.004). conclusions: In patients with UA/NSTEMI, elevations in a simple, widely available blood test, the WBC count, were associated with impaired epicardial and myocardial perfusion, more extensive CAD, and higher six-month mortality. After adjustment for traditional risk factors and other biomarkers, assessment of two inflammatory markers, WBC count and CRP, can be used to stratify patients across an eightfold gradation of six-month mortality risk.

Acute Disease↗

PubMed1996

Biomarker studies in northern Bohemia.

Studies were conducted in northern Bohemia to simultaneously evaluate personal exposures to air pollution in the form of respirable particles containing polycyclic aromatic hydrocarbons (PAHs) and biomarkers of exposure, biological effective dose, genetic effects, and metabolic susceptibility. The series of biomarkers included PAH metabolites in urine, urine mutagenicity, PAH-DNA adducts in white blood cells determined by 32P-postlabeling, PAH-albumin adducts determined by enzyme-linked immunosorbent assay (ELISA), DNA damage in lymphocytes detected by comet assay, chromosomal aberrations, sister chromatid exchanges, and glutathione S-transferase M1 (GSTM1) genotypes. For these studies, a group of women who work outdoors about 30% of their daily time was selected. In a pilot study, a group of women from a polluted area of the Teplice district (northern Bohemia) was compared with a group of women from a control district of southern Bohemia (Prachatice). In a follow-up repeated-measures study, a group of nonsmoking women from Teplice was sampled repeatedly during the winter season of 1993 to 1994. Personal exposure monitoring for respirable particles (< 2.5 microns) was conducted for the 24-hr period before collection of blood and urine. Particle extracts were analyzed for carcinogenic PAHs. In the pilot study and in the follow-up study, a highly significant correlation between individual personal exposures to PAHs and DNA adducts was found (r = 0.54, p = 0.016; r = 0.710, p < 0.001, respectively). The comet parameter (percentage DNA in tail; %T) correlated with exposures to respirable particles (r = 0.304, p = 0.015). The GSTM1 genotype had a significant effect on urinary PAH metabolites, urine mutagenicity, and comet parameters (% T and tail moment) when the GSTM1 genotype was considered as a single factor affecting these biomarkers. Multifactor analysis o variance considering exposure and adjusting the data for GSTM1, age, and diet showed that the effect of personal exposures to PAHs on the variability of biomarkers (DNA adducts, comet parameters, urine mutagenicity) might be higher than the effect of the GSTM1 genotype. These results show the importance of considering all potential factors that may affect the biomarkers being analyzed.

Adolescent↗

PubMed2005

Evaluation of the orthogonal projection on latent structure model limitations caused by chemical shift variability and improved visualization of biomarker changes in 1H NMR spectroscopic metabonomic studies.

In general, applications of metabonomics using biofluid NMR spectroscopic analysis for probing abnormal biochemical profiles in disease or due to toxicity have all relied on the use of chemometric techniques for sample classification. However, the well-known variability of some chemical shifts in 1H NMR spectra of biofluids due to environmental differences such as pH variation, when coupled with the large number of variables in such spectra, has led to the situation where it is necessary to reduce the size of the spectra or to attempt to align the shifting peaks, to get more robust and interpretable chemometric models. Here, a new approach that avoids this problem is demonstrated and shows that, moreover, inclusion of variable peak position data can be beneficial and can lead to useful biochemical information. The interpretation of chemometric models using combined back-scaled loading plots and variable weights demonstrates that this peak position variation can be handled successfully and also often provides additional information on the physicochemical variations in metabonomic data sets.

3-Hydroxybutyric Acid↗