Search

Awareness of the adverse effects of exposure to pollutant mixtures, possibly much more severe than individual chemicals, has drawn attention towards the necessity of using multi-residue methods to obtain the most possible comprehensive information on exposome. Among the different biological matrices used for exposure assessment, hair enables to detect the largest number of chemicals, including many classes such as persistent pollutants, hydrophilic metabolites and metals. Most biomonitoring studies are however focused on a limited number of pollutants and only give a partial information on exposure. Combining several multi-residue methods, the present study aimed at assessing the exposure of a population to an extensive variety of chemicals by hair analysis. One hair sample was collected from each participant (55 children and 134 adults). Samples were analysed with three different multi-residue methods, targeting, respectively, 152 organic pollutants (pesticides, PCBs, bisphenols, PBDEs), 62 polycyclic aromatic hydrocarbons (PAHs) and metabolites, nicotine and cotinine and 36 metals. From 33 to 70 organic chemicals were detected in each child’s hair sample, and from 34 up to 74 in adults. From 7 to 26 PAH were detected per child, and 7 to 21 in adults. Twenty-three to 27 metals were detected per child and 21 to 28 per adult. The highest median concentration were observed for zinc (143 μg /mg in children; 164 μg /mg in adults), bisphenol A (95.9 pg/mg in children; 64.7 pg/mg in adults) and nicotine (66.4 pg/mg in children; 51.9 pg/mg in adults). The present study provides the most comprehensive exposure assessment ever and highlights the simultaneous exposure to multiple classes of pollutants in the general population. The results support the use of multi-residue methods for future studies on exposure-associated effects, to document exposome and better consider the effect of chemical mixtures.

Pesticide exposure has been associated with hormonal disruption in both animals and humans. However, there is limited knowledge of the combined effects of complex mixtures of pesticides on endogenous hormone levels. Here, we used hair analysis to assess the impact of a pesticide mixture comprising 19 components from multiple chemical classes at eight doses of 0-400 μg/kg body weight (bw) three times per week per component on concentrations of 36 steroid and thyroid hormones in female rats over a 90-day exposure period. We detected 13 hormones in rat hair, namely estradiol (E2), androstenedione (AD), testosterone (T), dehydroepiandrosterone (DHEA), dehydroepiandrosterone sulfate (DHEAS), pregnenolone (P5), progesterone (P4), 11-deoxycorticosterone (11-DOC), corticosterone (CORT), 3,3'-l-diiodothyronine (T2), 3,5,3'-l-triiodothyronine (T3), 3,3',5'-l-triiodothyronine (rT3), and 3,5,3',5'-l-tetraiodothyronine (T4). In comparison to the control group, hair E2 concentration was significantly lower in the two highest (200 and 400 μg/kg bw) exposure groups, whereas hair DHEAS and CORT concentrations were significantly higher in the 40 μg/kg bw and the highest exposure groups, respectively. Results from generalized additive models suggest that pesticide exposure resulted in monotonic dose responses in hair E2 concentration, CORT concentration and DHEA/CORT molar ratio but nonmonotonic dose responses in hair T concentration, DHEAS concentration, P4/P5 and DHEA/DHEAS molar ratios. The associations of E2, CORT and DHEA/CORT ratio with exposure intensity were confirmed by their significant linear relationships with hair concentrations of at least 23 of the 25 exposure biomarkers analyzed. Our results demonstrate that exposure to low levels of the pesticide mixture evaluated here can alter hair reproductive and adrenal hormones levels.

Polycyclic aromatic hydrocarbons (PAHs) have been shown to influence endogenous hormones levels in animal models, but little is known about the effects of their mixtures. For hormone measurements, hair analysis is a promising approach to provide information on long-term status of hormones. Herein we used hair analysis to assess the combined effects of 13 PAHs on steroid and thyroid hormones levels in a rat model. The PAH mixture was administered orally three times per week to female rats at doses of 0, 10, 20, 40, 80, 200, 400 and 800 μg/kg of body weight for each compound over a 90-day exposure period. Fourteen out of 36 analyzed hormones were detected in rat hair, including pregnenolone (P5), 17α-hydroxyprogesterone (17-OHP4), corticosterone (CORT), dehydroepiandrosterone (DHEA), androstenedione (AD), 3,3'-diiodo-L-thyronine (T2), 3,3',5-triiodo-L-thyronine (T3), and 3,5,3',5'-triiodo-L-thyronine (T4). The PAH mixture significantly elevated P5 and DHEA levels at the doses of 200 and 400 μg/kg but reduced T2 and T3 levels at the highest dose as compared to the control. While P5, DHEA, 17-OHP4 and AD concentrations exhibited inverted U-shaped dose responses, T2, T3 and T4 concentrations exhibited inverse linear dose responses, which are further confirmed by their relationships with hair hydroxylated PAHs (OH-PAHs) concentrations. Likewise, there were significant nonmonotonic relationships of hormone molar ratios (e.g., AD/17-OHP4 and DHEA/CORT ratios) with exposure intensity and OH-PAHs. Overall, our results demonstrate the capability of PAH mixtures to interfere with steroid and thyroid hormones in female rats.

Environmental pollution is composed of several factors, namely particulate matter (PM2.5, PM10), ozone and Ultra Violet (UV) rays among others and first and the most exposed tissue to these substances is the skin epidermis. It has been established that several skin disorders such as eczema, acne, lentigines and wrinkles are aggravated by exposure to atmospheric pollution. While pollutants can interact with skin surface, contamination of deep skin by ultrafine particles or Polycyclic aromatic hydrocarbons (PAH) might be explained by their presence in blood and hair cortex. Molecular mechanisms leading to skin dysfunction due to pollution exposure have been poorly explored in humans. In addition to various host skin components, cutaneous microbiome is another target of these environment aggressors and can actively contribute to visible clinical manifestation such as wrinkles and aging. The present study aimed to investigate the association between pollution exposure, skin microbiota, metabolites and skin clinical signs in women from two cities with different pollution levels. Untargeted metabolomics and targeted proteins were analyzed from D-Squame samples from healthy women (n = 67 per city), aged 25–45 years and living for at least 15 years in the Chinese cities of Baoding (used as a model of polluted area) and Dalian (control area with lower level of pollution). Additional samples by swabs were collected from the cheeks from the same population and microbiome was analysed using bacterial 16S rRNA as well as fungal ITS1 amplicon sequencing and metagenomics analysis. The level of exposure to pollution was assessed individually by the analysis of polycyclic aromatic hydrocarbons (PAH) and their metabolites in hair samples collected from each participant. All the participants of the study were assessed for the skin clinical parameters (acne, wrinkles, pigmented spots etc.). Women from the two cities (polluted and less polluted) showed distinct metabolic profiles and alterations in skin microbiome. Profiling data from 350 identified metabolites, 143 microbes and 39 PAH served to characterize biochemical events that correlate with pollution exposure. Finally, using multiblock data analysis methods, we obtained a potential molecular map consisting of multi-omics signatures that correlated with the presence of skin pigmentation dysfunction in individuals living in a polluted environment. Overall, these signatures point towards macromolecular alterations by pollution that could manifest as clinical sign of early skin pigmentation and/or other imperfections.

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.

International audience; Humans are exposed to various anthropogenic chemicals in daily life, including endocrine-disrupting chemicals (EDCs). However, there are limited data on chronic, low-level exposure to such contaminants among the general population. Here hair analysis was used to investigate the occurrence of four polychlorinated biphenyls (PCBs), seven polybrominated diphenyl ethers (PBDEs) and two bisphenols (BPs) in 204 Chinese women living in the urban areas of Baoding and Dalian and 311 pregnant French women. All the PCBs and PBDEs tested here were more frequently detected in the hair samples of the French women than in those of the Chinese women. In both cohorts, PCB 180 and BDE 47 were the dominant PCB and PBDE congener, respectively. PCB 180 was found in 82% of the French women and 44% of the Chinese women, while the corresponding values of BDE 47 were 54% and 11%, respectively. A discriminant analysis further demonstrated the difference in PCBs and PBDEs exposure profile between the two cohorts. These results demonstrate that hair analysis is sufficiently sensitive to detect exposure to these pollutants and highlight differences in exposure between populations even at environmental levels. Although BPA and BPS were found in 100% of the hair samples in both cohorts, the French women had significantly higher levels of BPA and BPS than the Chinese women. The median concentrations of BPA were one order of magnitude higher than BPS in both the Chinese (34.9 versus 2.84 pg/mg) and the French women (118 versus 8.01 pg/mg) respectively. Our results suggest that both French and Chinese populations were extensively exposed to BPA and BPS.

In studies investigating the effects of endocrine disruptors (ED) such as phthalates, bisphenols and some pesticides on human health, exposure is usually characterized with urinary metabolites. 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. This study was conducted to assess variability of urinary metabolites of ED, and to investigate how sampling time and number of samples analyzed impacts exposure assessment. Urine samples were collected over 6 months from 16 volunteers according to a random sampling design, and analyzed for 16 phthalate metabolites, 9 pesticide metabolites and 4 bisphenols. The amount of biomarkers excreted in urine at different times of the day were compared. In parallel, 2 algorithms were developed to investigate the effect of the number of urine samples analyzed per subject on exposure assessment reliability. In the 805 urine samples collected from the participants, all the biomarkers tested were detected, and 18 were present in >90% of the samples. Biomarkers variability was highlighted by the low intraclass correlation coefficients (ICC) ranging from 0.09 to 0.51. Comparing the amount of biomarkers excreted in urine at different time did not allow to identify a preferred moment for urine collection between first day urine, morning, afternoon and evening. Algorithms demonstrated that between 10 (for monobenzyl (MBzP) phthalate) and 31 (for bisphenol S) samples were necessary to correctly classify 87.5% of the subjects into quartiles according to their level of exposure. The results illustrate the high variability of urinary biomarkers of ED over time and the impossibility to reliably classify subjects based on a single urine sample (or a limited number). Results showed that classifying individuals based on urinary biomarkers requires several samples per subject, and this number is highly different for different biomarkers.

The impact of pollution on children's health has been increasingly pointed out in numerous studies which emphasized their increased vulnerability compared to adults. This pilot study investigated the relevance of hair analysis for the assessment of children exposure to pollution and to environmental tobacco smoke (ETS). The methodology based on GC–MS/MS and LC-MS/MS, is the first one to investigate simultaneously parent PAH (n = 15), PAH metabolites (n = 56), nicotine and cotinine in a biological matrix. The method was applied to hair samples collected from 25 children, aged from 2 to 11 years, living in Paris, France, selected as densely populated area with urban pollution including vehicle exhausts, and Yeu Island, a French island in the Atlantic ocean, selected as control area with low population density and no fuel powered vehicles. Nicotine and cotinine were detected in all the samples at concentrations up to 2275 pg/mg and 110 pg/mg respectively, suggesting exposure to ETS in the two areas. 10 parent PAH and 10 metabolites were detected in 100% and in >90% of the samples respectively. Eight of these biomarkers presented a significantly higher concentration in children from Paris than from Yeu Island. The results suggest association between PAH exposure and estimated time of exposure to vehicle exhaust as well as higher exposure to both PAH and ETS in the youngest children. Although these findings need to be confirmed on wider populations, the results obtained in this pilot study strongly support the relevance of hair analysis for the biomonitoring of children exposure to urban pollution and ETS.