Incorporation of Fast-Elimination Chemicals in Hair Is Governed by Pharmacokinetics-Implications for Exposure Assessment.

Mechanisms governing chemicals' incorporation in hair are incompletely understood, and gaps remain to link the concentration of chemicals in hair to level of exposure and internal dose present in the body. This study assesses the relevance of hair analysis for the biomonitoring of exposure to fast-elimination compounds and investigates the role of pharmacokinetics (PK) in their incorporation in hair. Rats were administered with pesticides, bisphenols, phthalates, and DINCH over 2 months. Hairs were analyzed for 28 chemicals/metabolites to investigate correlations between their concentration in hair and the dose administered to the animals. Urine collected over 24 h after gavage was used to determine chemicals' PK and to investigate their influence on incorporation into hair by means of linear mixed models (LMMs). Eighteen chemicals presented a significant correlation between concentration in hair and level of exposure. In models combining all chemicals, agreement between concentration in hair predicted by LMM and experimental values was moderate (R2 = 0.19) but significantly increased when PK were included in the models (R2 = 0.37), and even more when chemical families were considered separately (e.g., R2 = 0.98 for pesticides). This study shows that pharmacokinetics mediate incorporation of chemicals in hair and suggests the relevance of hair for assessing exposure to fast-elimination chemicals.

Environmental tobacco smoke at home and in public places prior to smoking ban enforcement: Assessment by hair analysis in a population of young adult students.

Despite inititatives to reduce tobacco consumption, smoking remains a primary cause of death for both smokers and nonsmokers exposed to environmental tobacco smoke (ETS). The characteristics of some specific groups can make them more exposed to ETS or limit the benefit of prevention measures. This study investigated determinants of ETS in a population of young adult students, considered at higher risk of exposure due to their specific lifestyle. This cross-sectional study involved 90 students aged 20 ± 1.7 years, from the University of Luxembourg, prior to the smoking ban enforcement in public places in the country. Participants reported their tobacco consumption and exposure to ETS at home and/or in public places, and provided a hair sample analyzed for nicotine and cotinine. Nicotine and cotinine were significantly higher in smokers than in nonsmokers' hair in general (median: 2.6 vs. 0.9 ng/mg and 87.1 vs. 22.5 pg/mg respectively). However, nonsmokers exposed to ETS at home and in public places had comparable concentrations to smokers (nic = 2.2 ng/mg; cot = 56.2 pg/mg), whereas unexposed nonsmokers presented significantly lower values (nic = 0.4 ng/mg, cot = 8.5 pg/mg). Nonsmokers exposed to ETS only at home presented higher values than nonsmokers only exposed in public places (nic: 1.3 vs. 0.8 ng/mg, cot: 70.4 vs. 15.0 pg/mg). The study shows the widespread exposure to ETS in this population, the importance of exposure assessment, and the relevance of hair analysis for this purpose. Results suggest that ETS can lead to equivalent exposure to active smoking and that exposure at home can highly contribute to ETS, which is not solved by smoking ban in public places.

Biomonitoring of fast-elimination endocrine disruptors - Results from a 6-month follow up on human volunteers with repeated urine and hair collection.

BACKGROUND: The assessment of human exposure to fast-elimination endocrine disruptors (ED) such as phthalates, bisphenols or pesticides is usually based on urinary biomarkers. The variability of biomarkers concentration, due to rapid elimination from the body combined with frequent exposure is however pointed out as a major limitation to exposure assessment. Other matrices such as hair, less sensitive to short-term variations in the exposure, have been proposed as possible alternatives. Nevertheless, no study compared the information obtained from hair and urine respectively in a follow-up allowing to assess biomarkers variability over time in these two matrices, and to compare the correlation between them. METHODS: In the present study, hair and urine samples were collected from 16 volunteers over a 6 months follow-up. All in all, 92 hair samples and 805 urines samples were collected and analyzed for the presence of 16 phthalate metabolites, 4 bisphenols and 8 pesticides/metabolites. RESULTS: All the biomarkers analyzed were detected in at least one of the two matrices. 21 biomarkers were more frequently detected in hair, 6 in urine, and 1 was equivalent. Biomarkers intraclass correlation coefficients (ICC) ranged from 0.1 to 0.8 (ten above 0.4) in hair, and from 0.09 to 0.51 in urine (two above 0.4). The concentrations of biomarkers in hair and urine were significantly correlated for only one compound. CONCLUSION: This study highlights the complexity of assessing exposure to fast-elimination ED and suggests considering with caution the specificity of the matrix in data interpretation. The results document the respective advantages and limitations of urine and hair, and provide new insight in the understanding of the information provided by these biological matrices and their relevance for the assessment of human exposure to fast elimination contaminants. CAPSULE: 92 hair and 805 urine samples collected from 16 volunteers over 6 months, tested for phthalate metabolites, bisphenols and pesticides. 19 biomarkers (in hair) and 24 (in urine) were detected in >50% of the samples.

Hair analysis for the biomonitoring of polycyclic aromatic hydrocarbon exposure: comparison with urinary metabolites and DNA adducts in a rat model.

Alongside the analysis of urinary metabolites which are traditional biomarkers of polycyclic aromatic hydrocarbons (PAH) exposure, the possibility of detecting PAH as well as their metabolites in hair has also recently been demonstrated. As the concentration of pollutants detected in hair is not impacted by short-term variations in exposure as can be observed with urine, it accurately represents an individual's average level of exposure, which is the most relevant information when investigating possible linkages with biological effects. In the current study, based on a rat model exposed to a mixture of PAHs for a 90-day period, the linkage between the PAH exposure level and the resulting concentration of their metabolites in hair was then investigated. The linkage between exposure levels and the concentrations of OH-PAH in hair collected at the end of the experiment were compared to those obtained using urinary concentration of OH-PAH collected from the same animals. Linear relationship between levels of exposure and the concentration of OH-PAH in the rats' hair (R2 0.722-0.965, p < 0.001) was observed for 28 OH-PAH out of the 54 investigated. The difference in PAH concentration between the different groups of exposure and the possibility to back determine the animals' level of exposure on the basis of PAH-metabolite concentrations in both hair and urine was also demonstrated. In addition to the strong linear relation observed between the doses of exposure and the levels of concentration of hydroxylated metabolites in hair (p < 0.001), the analysis of a subset of animals demonstrated a linkage between 3-OH-benzo[a]pyrene concentration levels in hair and the levels of B[a]P-DNA adduct formed (p < 0.05), thereby suggesting the potential of their analysis to predict genetic alteration.

Identification of beta-arrestin-1 as a diagnostic biomarker in lung cancer.

BACKGROUND: Distinguishing lung adenocarcinoma (ADC) from squamous cell carcinoma (SCC) has a tremendous therapeutic implication. Sometimes, the commonly used immunohistochemistry (IHC) markers fail to discriminate between them, urging for the identification of new diagnostic biomarkers. METHODS: We performed IHC on tissue microarrays from two cohorts of lung cancer patients to analyse the expression of beta-arrestin-1, beta-arrestin-2 and clinically used diagnostic markers in ADC and SCC samples. Logistic regression models were applied for tumour subtype prediction. Parallel reaction monitoring (PRM)-based mass spectrometry was used to quantify beta-arrestin-1 in plasma from cancer patients and healthy donors. RESULTS: Beta-arrestin-1 expression was significantly higher in ADC versus SCC samples. Beta-arrestin-1 displayed high sensitivity, specificity and negative predictive value. Its usefulness in an IHC panel was also shown. Plasma beta-arrestin-1 levels were considerably higher in lung cancer patients than in healthy donors and were higher in patients who later experienced a progressive disease than in patients showing complete/partial response following EGFR inhibitor therapy. CONCLUSIONS: Our data identify beta-arrestin-1 as a diagnostic marker to differentiate ADC from SCC and indicate its potential as a plasma biomarker for non-invasive diagnosis of lung cancer. Its utility to predict response to EGFR inhibitors is yet to be confirmed.

MicroRNA 150-5p Improves Risk Classification for Mortality within 90 Days after Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Micro ribonucleic acid-150-5p (miR-150-5p) regulates proinflammatory cytokines as well as vessel integrity. We evaluated the incremental prognostic value of logarithm (log) of miR-150-5p plasma levels after ischemic stroke. METHODS: In a prospective cohort study, levels of miR-150-5p were measured within 72 hours of symptom onset in 329 ischemic stroke patients. The outcome measures were unfavorable functional outcome (assessed by the modified Rankin Scale score >2) and mortality within 90 days. Logistic regression and Cox proportional hazards models were fitted to estimate odds ratio (OR), respectively hazard ratio (HR) and 95% confidence interval (CI) for the association between log-miR-150-5p and the outcome measures. The discriminatory accuracy was assessed with the area under the receiver-operating-characteristic curve (AUC) and the incremental prognostic value was estimated with the net reclassification index. RESULTS: After adjusting for demographic and vascular risk factors, lower log-miR-150-5p levels were independently associated with mortality (HR 0.21 [95% CI, 0.08-0.51], P=0.001) but not functional outcome (OR 1.10 [95% CI, 0.54-2.25], P=0.79). Adding log-miR-150-5p improved the discriminatory accuracy of the best multivariate model to predict mortality from an AUC of 0.91 (95% CI, 0.88-0.95) to 0.92 (95% CI, 0.88-0.96 Likelihood-ratio test-P<0.001), and resulted in a net reclassification index of 37.3% (95% CI, 0.28-0.52). CONCLUSIONS: In patients with ischemic stroke, log-miR-150-5p is a novel prognostic biomarker, highly associated with mortality within 90 days, improving risk classification beyond traditional risk factors.

Protein S100 as outcome predictor after out-of-hospital cardiac arrest and targeted temperature management at 33 °C and 36 °C.

BACKGROUND: We aimed to investigate the diagnostic performance of S100 as an outcome predictor after out-of-hospital cardiac arrest (OHCA) and the potential influence of two target temperatures (33 °C and 36 °C) on serum levels of S100. METHODS: This is a substudy of the Target Temperature Management after Out-of-Hospital Cardiac Arrest (TTM) trial. Serum levels of S100 were measured a posteriori in a core laboratory in samples collected at 24, 48, and 72 h after OHCA. Outcome at 6 months was assessed using the Cerebral Performance Categories Scale (CPC 1-2 = good outcome, CPC 3-5 = poor outcome). RESULTS: We included 687 patients from 29 sites in Europe. Median S100 values were higher in patients with a poor outcome at 24, 48, and 72 h: 0.19 (IQR 0.10-0.49) versus 0.08 (IQR 0.06-0.11) µg/ml, 0.16 (IQR 0.10-0.44) versus 0.07 (IQR 0.06-0.11) µg/L, and 0.13 (IQR 0.08-0.26) versus 0.06 (IQR 0.05-0.09) µg/L (p < 0.001), respectively. The ability to predict outcome was best at 24 h with an AUC of 0.80 (95% CI 0.77-0.83). S100 values were higher at 24 and 72 h in the 33 °C group than in the 36 °C group (0.12 [0.07-0.22] versus 0.10 [0.07-0.21] µg/L and 0.09 [0.06-0.17] versus 0.08 [0.05-0.10], respectively) (p < 0.02). In multivariable analyses including baseline variables and the allocated target temperature, the addition of S100 improved the AUC from 0.80 to 0.84 (95% CI 0.81-0.87) (p < 0.001), but S100 was not an independent outcome predictor. Adding S100 to the same model including neuron-specific enolase (NSE) did not further improve the AUC. CONCLUSIONS: The allocated target temperature did not affect S100 to a clinically relevant degree. High S100 values are predictive of poor outcome but do not add value to present prognostication models with or without NSE. S100 measured at 24 h and afterward is of limited value in clinical outcome prediction after OHCA. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01020916 . Registered on 25 November 2009.

Hair analysis for the biomonitoring of pesticide exposure: comparison with blood and urine in a rat model.

Urine and plasma have been used to date for the biomonitoring of exposure to pollutants and are still the preferred fluids for this purpose; however, these fluids mainly provide information on the short term and may present a high level of variability regarding pesticide concentrations, especially for nonpersistent compounds. Hair analysis may provide information about chronic exposure that is averaged over several months; therefore, this method has been proposed as an alternative to solely relying on these fluids. Although the possibility of detecting pesticides in hair has been demonstrated over the past few years, the unknown linkage between exposure and pesticides concentration in hair has limited the recognition of this matrix as a relevant tool for assessing human exposure. Based on a rat model in which there was controlled exposure to a mixture of pesticides composed of lindane, ß-hexachlorocyclohexane, ß-endosulfan, p,p'-DDT, p,p'-DDE, dieldrin, pentachlorophenol, diazinon, chlorpyrifos, cyhalothrin, permethrin, cypermethrin, propiconazole, fipronil, oxadiazon, diflufenican, trifluralin, carbofuran, and propoxur, the current work demonstrates the association between exposure intensity and resulting pesticide concentration in hair. We also compared the results obtained from a hair analysis to urine and plasma collected from the same rats. Hair, blood, and urine were collected from rats submitted to 90-day exposure by gavage to the aforementioned mixture of common pesticides at different levels. We observed a linear relationship between exposure intensity and the concentration of pesticides in the rats' hair (R Pearson 0.453-0.978, p < 0.01). A comparison with results from urine and plasma samples demonstrated the relevance of hair analysis and, for many chemicals, its superiority over using fluids for differentiating animals from different groups and for re-attributing animals to their correct groups of exposure based on pesticide concentrations in the matrix. Therefore, this study strongly supports hair analysis as a reliable tool to be used during epidemiological studies to investigate exposure-associated adverse health effects.

Reduced Rapid Eye Movement Density in Parkinson Disease: A Polysomnography-Based Case-Control Study.

STUDY OBJECTIVES: To explore rapid eye movement density (RD) in patients with idiopathic Parkinson disease (IPD) and to investigate its usefulness as surrogate marker of excessive daytime sleepiness, a frequent complaint in IPD patients. METHODS: Retrospective polysomnography study on 81 subjects without dementia: 29 patients with early stage IPD (disease duration ≤ 3 y), 21 patients with middle- stage IPD (disease duration > 3 and < 8 y) and 31 healthy controls (HC). Rapid eye movement (REM) sleep was defined as any REM episode with > 3 min of continuous REM sleep. RD was defined as number of ocular movements per minute of REM sleep. Patients with early stage IPD and HC fulfilled the PD-specific sleepiness questionnaires Parkinson's Disease Sleep Scale (PDSS) and the Nonmotor Symptoms Questionnaire for Parkinson's disease (NMSQuest). RESULTS: RD was lower in patients with IPD than in HC. The difference was most significant between patients with middle stage IPD and HC (P = 0.001), and most prominent for the third REM episode, again when comparing patients with middle stage IPD and HC (P = 0.03). RD was independent from sex, age, and other sleep parameters. In early stage IPD, RD correlated with the PDSS score (r = -0.63, P = 0.001) and the sleep-related questions of the NMSQuest score (r = 0.48, P = 0.017). CONCLUSIONS: REM density is reduced in patients with IPD and correlates with subjective scores on sleep impairment. As an indicator of persistent high sleep pressure, reduced RD in IPD is eligible as a biomarker of excessive daytime sleepiness in IPD. It possibly reflects direct involvement of the brainstem REM generation sites by the disease process. RD is a promising new tool for sleep research in IPD.