Determination of contaminants in urine: bisphenols, phthalates, and other chemical substances and their relationship with human health

Sara Catalina Darai Universidad de Valladolid 1 FACULTAD DE CIENCIAS TRABAJO FIN DE MÁSTER Máster en Técnicas Avanzadas en Química. Análisis y Control de Calidad Químicos. Determination of contaminants in urine: bisphenols, phthalates, and other chemical substances and their relationship with human health Sara Catalina-Darai a,b, Daniel Gutiérrez-Martín a,b,c, Rebeca López-Serna a,b a Department of Analytical Chemistry, Faculty of Sciences, University of Valladolid, 47011 Valladolid, Spain b Institute of Sustainable Processes, Dr. Mergelina s/n, Valladolid 47011, Spain c Institute of Environmental Assessment and Water Research (IDAEA), CSIC, Jordi Girona 18, 08034 Barcelona, Spain 2022/2023 Sara Catalina Darai Universidad de Valladolid 2 Contenido ABSTRACT ...................................................................................................................................... 3 1. INTRODUCTION ..................................................................................................................... 4 2. MATERIALS AND METHODS ................................................................................................. 14 2.1. Chemicals and materials.......................................................................................... 14 2.2. Sample collection and preparation ......................................................................... 15 2.3. Instrumental analysis .............................................................................................. 16 2.4. Method quanrification and validation ..................................................................... 16 2.5. Quality assurance and quality control ..................................................................... 18 3. RESULTS AND DISCUSSION .................................................................................................. 19 3.1. Method validation ................................................................................................... 19 3.2. Occurrence of xenobiotics ....................................................................................... 27 4. CONCLUSIONS ..................................................................................................................... 38 5. SUPLEMENTARY INFORMATION .......................................................................................... 39 6. ACKNOWLEDGMENTS ......................................................................................................... 39 7. BIBLIOGRAPHY ..................................................................................................................... 39 Sara Catalina Darai Universidad de Valladolid 3 ABSTRACT The so-called emerging contaminants, which have gained prominence in recent years, are linked to personal care products, pharmaceuticals, and plasticizers, among others. These substances represent potential risks to human health due to their widespread presence in the environment and their ability to enter the human body through various exposure routes. Bisphenols (BPs) and phthalates have received significant attention due to their toxicity and ubiquity in consumer products. Even at low concentrations, they can have adverse effects on health, making essential their comprehensive analysis and regulation. Human biomonitoring studies play a fundamental role in assessing contamination by contaminants of emerging concern (CECs) in populations, particularly through the analysis of urine samples. Urine is preferred for its large sample volume, noninvasiveness, and ease of collection. In this work, we examined the presence and concentration of 36 chemical substances in urine samples from 40 pregnant women from Barcelona, obtained following ethical guidelines and respecting data protection. LC-MS/MS analysis was performed using a UHPLC Sciex Exion system connected to a Sciex 6500+ triple-quadrupole mass spectrometer from Sciex (Washington, DC, USA). The mass spectrometer was equipped with an electrospray ionization (ESI) source and operated in both positive and negative modes within the same run. An exhaustive method validation process was conducted, including extraction recoveries, precision, limits of quantification (LOQs), limits of detection (LODs), and matrix effects, for 3 compounds. Seventysix per cent of the target analytes successfully passed the validation standards demanded. Semi-quantification was used for some compounds due to matrix complexity, setting the minimum amount of these compounds expected to be in the samples. Strategies to mitigate ionization suppression were discussed, highlighting the need for optimization in sample preparation and analytical protocols to ensure result accuracy. This study provides insights into emerging contamination in humans, shedding light on potential health risks associated with these pollutants. Sara Catalina Darai Universidad de Valladolid 4 1. INTRODUCTION Contaminants of emerging concern (CECs) are chemicals that raise concerns within the scientific community due to their toxicity and widespread presence. CECs encompass a diverse range of pollutants, including endocrine disrupting chemicals (EDCs), personal care products (PCPs), pharmaceutically active chemicals (PhACs), or plasticizers, among others. These chemicals can enter the human body through various exposure pathways such as inhalation, ingestion, or dermal contact according to the Environmental Protection Agency (EPA). Among these pollutants, bisphenols (BPs) and phthalates have attracted significant attention due to their widespread use in the production of various consumer products, such as plastics, food packaging, and personal care products [1]. Even at low concentrations, they can have adverse effects with longterm exposure, potentially leading to severe health issues. Hence, it is crucial to comprehensively understand their presence and levels to identify which chemicals may pose threats to human health and establish regulatory measures for their control. Human biomonitoring (HBM) studies focus on this and include the development and application of analytical methods to accurately determine the presence of these contaminants and their concentration. Among the various biofluids, the application of these analytical methodologies to human urine is justified by the access to high sample volume, ease of collection, and non-invasive nature, in comparison to other biofluids. In this context, intense sampling campaigns are allowed to assess the contamination in large populations. Bisphenols (BPs) are one of the most common phenols in the environment, characterized by the presence of two phenols connected by an alkyl group. Sara Catalina Darai Universidad de Valladolid 5 Figure 1. Chemical structures of bisphenol analogues [2]. BPs are essential components of polycarbonate plastics, widely used in consumer goods and packaging that store food and beverages. They are also employed in the production of epoxy resin coatings in metal-based cans for food and beverages, as well as in other consumer products such as thermal paper, medical equipment, toys, electronics, and water pipes [3]. Bisphenol A is commonly measured in urine to monitor human exposure to this compound. Recent studies have started to evaluate urinary concentrations of other bisphenol analogues, but available data is still limited (see Table 1). Sara Catalina Darai Universidad de Valladolid 6 Table 1. Concentrations of bisphenols in urine across different regions and years. Region Year n Units BPA BPAF BPAP BPB BPE BPF BPP BPS BPZ Reference China 2013 94 ng/mL 0.886 0.018 - - - 0.228 - 0.029 - [4] Saudi Arabia 2014 130 ng/mL 4.92 0.05 0.3 0.05 - 0.19 0.093 13.3 0.06 [5] India 20122013 76 ng/mL 5.08 - - - - - - 0.04 - [6] USA 2016 380 ng/mL 1.32 - - - - - - - - [7] USA 2000 79 ng/mL 1340 - - - - 340 - - - [8] USA 2001 67 ng/mL 1290 - - - - 300 - - - [8] USA 2007 27 ng/mL 740 - - - - 160 - - - [8] USA 2009 122 ng/mL 1340 - - - - 540 - - - [8] USA 2010 43 ng/mL 2070 - - - - 170 - - - [8] USA 2011 95 ng/mL 960 - - - - 150 - - - [8] USA 2013 141 ng/mL 670 - - - - 180 - - - [8] USA 2014 42 ng/mL 360 - - - - 410 - - - [8] Sara Catalina Darai Universidad de Valladolid 7 Exposure to BPs can occur through the ingestion of food and liquids that have encountered containers or coatings which contain these compounds. Additionally, humans can be exposed through inhalation of contaminated dust particles and direct dermal contact with products containing bisphenols. This exposure derived in the presence of BPs in human serum, urine, placental tissue, umbilical cord blood, and breast milk, revealing global distribution [1], [9], [10]. Thus, a growing concern exists regarding the potential negative impact of bisphenols on human health and the environment. Bisphenol A (BPA), a widely produced chemical, and other bisphenols have been found to disrupt the endocrine system, affecting human development and function [1]. Research indicated adverse effects of BPA on reproduction, development, neural networks, cardiovascular health, metabolism, and the immune system. The risk of over widespread human exposure and associated adverse effects has led to regulations on BPA production and use in North America and the European Union [11]. Additionally, analogues such as BPF, BPS, BPAF, BPB, and BPC demonstrated similar or greater toxicity estrogenic and antiandrogenic potency compared to BPA, thus requiring its assessment as well [12][13]. Phthalates, derived from phthalic acid, have different chemical structures: some are di-phthalates, replacing two hydrogen atoms, while others are monophthalates, replacing one hydrogen atom. They have low water solubility, long-lasting properties, and various toxicity levels depending on their side chains. Common phthalates include DMP (dimethyl phthalate), mono-2-ethylhexyl phthalate (MEHP), DEP (diethyl phthalate), BBzP (butyl benzyl phthalate), DnBP (dibutyl phthalate), and DiBP (diisobutyl phthalate), used in solvents, lubricants, textiles, personal care products, paints, and adhesives [14]. Phthalates have been found in human urine samples, indicating widespread exposure (see Table 2). Sara Catalina Darai Universidad de Valladolid 8 MEHP MEHHP MEOHP MCMHP MECPP MEP Figure 2. Chemical structures of phthalates. Sara Catalina Darai Universidad de Valladolid 9 Region Year n Units MEHP MEHHP MEOHP MECPP MCMHP MEP MnBP MiBP MBzP Citation Germany - 19 ng/mL 9.8 47.5 39.7 85.5 36.6 - - - - [15] USA - 129 ng/mL 3.3 15.1 7.8 16.2 5.2 - - - - [16] USA 19992000 328 ng/mL 4.9 - - - - 50 40 - 29 [16] USA 20012002 393 ng/mL 4.4 33 23 - - 48 32 4.4 27 [16] USA 2003.2 342 ng/mL 2.7 37 26 52 - 54 37 7 25 [16] USA 20052006 356 ng/mL 3 36 25 54 - 48 32 9 24 [16] USA 20072008 389 ng/mL 2.2 27 17 44 - 45 29 11 18 [16] Germany 2007 111 ng/mL 4.7 17 15 28 - - 37 43 7.2 [17] South Korea 2008 621 ng/mL 25 - 2 - - - 51 - - [18] Spain 20052006 30 ng/mL 6.2 57 45 115 - 755 30 42 33 [19] Denmark 2007 129 ng/mL - - 137 - - 46 188 32 [15] Egypt (urban) 2009 28 ng/mL ng/mL 4.7 29 19 2 - 99 54 25 2.2 [20] Sara Catalina Darai Universidad de Valladolid 16 µL of the filtered solution was mixed with 1 mL of buffer preparation, and deconjugation was performed at 48°C for 3 hours. Then, 950 µL of the liquid was transferred to a chromatographic vial and stored at -80°C. Prior to instrumental analysis, 50 µL of the IS mix at 1 ppm were added to every sample. 2.3. Instrumental analysis LC-MS/MS was carried out using a UHPLC Sciex Exion system connected to a Sciex 6500+ triple-quadrupole mass spectrometer from Sciex (Washington, DC, USA). The mass spectrometer was equipped with an electrospray ionization (ESI) source and operated in both positive and negative mode within the same run. Chromatographic separation was accomplished using a Phenomenex (Washington, DC, USA) reversed-phase column Kinetex EVO C18 (2.1 mm × 50 mm, particle size 1.7 μm), which was temperature-controlled at 40 °C throughout the entire chromatogram. The gradient method employed water (mobile phase A) and MeOH (mobile phase B) as described in Table S2. A 10 µL injection volume was utilized. For mass spectrometry acquisition, the selected-reaction monitoring (SRM) mode was employed. This mode recorded the transitions between the precursor ion and the two most abundant product ions for each target analyte, resulting in four identification points per compound (2002/657/EC) [29]. The specific UHPLCMS/MS conditions can be found in the Supplementary data (Table S3). Additionally, the ESI operational settings were as follows: capillary voltage, 4500 V; capillary temperature, 400 °C; gas 1 and 2 pressure, 45 psi. SciexOS software was employed for data acquisition and evaluation. 2.4. Method quanrification and validation The methodology employed in this study builds upon the previous validated methodology by Gutiérrez-Martín et al. [28], which focused on CECs, specifically pharmaceuticals, plastic additives, food related chemicals, personal care products, insect repellents and UV-filters. The focus of the current investigation was to test the methodology on a more comprehensive list of analytes including Sara Catalina Darai Universidad de Valladolid 17 36 CECs, in particular, plastic additives (BPs and phthalates) and PhACs (antibiotics, analgesic and anti-inflammatory drugs) and biocides (see Table S.1.). The validation process relied on several parameters: extraction recoveries, precision, limits of quantification (LOQs), limits of detection (LODs), and the matrix effect. In this context, a urine pool (n=5) was made. To establish a calibration curve, the urine pool underwent the same pretreatment as the samples and was spiked with the target analytes right before executing UHPLC-MS/MS analysis. To adjust for chemicals already present in the urine, peak areas identified in a non-spiked urine pool sample were deducted from the calibration curve's peak areas. A parallel calibration curve in a solvent composed of 95% water and 5% MeOH was established following the same protocol. The concentration levels built in both calibration curves were 0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10, 52, 100 ng/mL. LOQs were estimated as the minimum concentration at which a peak was noticeable on the matrix-matched calibration curve. LODs were derived by taking three-tenths of the LOQ values. A linear range was established between the LOQ and the uppermost concentration on the calibration curve, ensuring linearity. To account for potential losses during the sample treatment, extraction recoveries (R%) were computed. Fourteen pooled samples underwent processing. Six of these samples were pre-spiked with target analytes at an in-vial concentration of 10 ng/mL (n=3) and 50 ng/mL (n=3), respectively, prior to the sample treatment. An additional six-sample batch were spiked with target analytes at an in-vial concentration of 10 ng/mL (n=3) and 50 ng/mL (n=3), respectively, right before the instrumental analysis (post-spikes). Two samples remained non-spiked to track for chemicals already existing in the urine pool. Subsequently, R% was calculated as outlined in Equation 1, for both concentration levels. Eq. 1: R% =Area for each analyte in pre-spiked sample Area for each analyte in post-spiked sample × 100 Sara Catalina Darai Universidad de Valladolid 18 The matrix effect (ME) was assessed by comparing the average peak area for the post-spiked sample (n=3, 10 ng/mL concentration level) with the peak area obtained from spikes in the solvent for each analyte at the same concentration level, as shown in Equation 2. Eq.2: ME% = Area for each analyte in post-spiked sample Area for each analyte in solvent × 100 Precision was calculated by computing the coefficient of variation (CV%) of the peak area from a quality control sample (10 ng/mL), injected nine times within a single day. To account for potential contamination during sample treatment or instrumental analysis, eight procedural blanks were performed (2 blanks per 10 samples), following the same treatment procedure using Milli-Q water instead of urine. Quantification was executed for chemicals that satisfactorily passed the validation process. It was achieved by interpolating the peak area obtained for the chemicals in each sample, corrected by the peak area for the procedural blanks, to the matrix-matched calibration curve. In cases where a matrix-matched calibration curve was unavailable (NA), as a result of unsatisfactory outcomes during the experimental phase, semi-quantification was performed using the calibration curve in the solvent. Given that suppression is generally observed in urine, semi-quantification based on the calibration curve in the solvent may result in an underestimation of the chemical concentration in urine samples. 2.5. Quality assurance and quality control To ensure the prevention of any contamination during sample treatments or instrumental analysis, rigorous quality assurance and quality control (QA/QC) measures were implemented. Glass materials were thoroughly cleaned with water and rinsed with distilled water, ethanol and acetone, prior to their utilization. Standards and internal standards were carefully stored in amber glass vials, Sara Catalina Darai Universidad de Valladolid 19 shielded from light, and maintained at a temperature of -80 °C. This storage condition was adopted to prevent degradation. Procedural blanks were carried out using the same protocol steps to account for any potential contamination that may arise during the process. To assess the repeatability of the signal, a calibration curve of the pooled urine was established, and a spiked pooled solution with a concentration of 10 µg L−1 was injected every 20 injections. Methanol injections were performed every 10 injections to monitor and control any possible carry-over issues. Clothianidin-d3, serving as surrogate, was employed to monitor the sample treatment performance. The rest of the IS were added just before the LC-MSMS analysis to monitor the instrument performance and correct any potential matrix effects. The signal of the IS was checked to see potential losses during sample treatment (surrogate signal) or during the LCMSMS analysis. 3. RESULTS AND DISCUSSION 3.1. Method validation The method used has been previously validated by Gutiérrez-Martín et al. [28], providing additional reassurance about its suitability and effectiveness in analyzing the target substances. Building upon this validation, we can be confident that our research is built on a validated method, ensuring the reliability and integrity of our findings. The objective of this validation is to assess the reliability, precision, and accuracy of the analytical procedure when applied for the analysis of the target analytes of this study before its application to real samples. Thus, out of the 36 initial compounds, 27 yielded successful results during the validation process, which corresponded to a 75% of the total compounds evaluated. Within this subset of 27 compounds, a distinction was made between those undergoing quantification, for which calibration curves in matrix and recovery were employed, and those for which semi-quantification was performed making use of a solvent-based calibration curve, assuming a 100% recovery rate. Sara Catalina Darai Universidad de Valladolid 20 It is crucial to recognize that the semi-quantification approach potentially introduced a bias of underestimation in concentration determination. This is due to the inherent complexity of real matrices, in this case, urine, where ionization suppression phenomena usually occur [31]. Ionization suppression affects the efficiency of analyte ionization in the analytical process, thereby influencing the accuracy of the obtained results. This phenomenon can lead to a significant reduction in signal intensity or even the absence of analyte detection. Specifically, the results of the validation were: • Calibration Curves Matrix-matched calibration curves were satisfactory, with coefficient of determinations (R2) higher than 0.96 for 87% of the chemicals. This indicated a good correlation between the concentration of the substances and the analytical responses in such a complex matrix as urine. However, as expected, a comparison of slopes between the calibration curves in solvent and urine revealed noticeable differences, as shown in Figure 3. As indicated above, matrix effects often lead to a reduced ionization in urine samples, resulting in calibration curves with lower slopes compared to those observed in solvent. In our study, the presence of a suppression matrix effect was clearly observed in several compounds, including progesterone, carbamazepine, propranolol, metronidazole, ofloxacin, and levofloxacin. For these compounds, the matrix effect varied significantly, ranging from 11% to 92%. As a consequence of this phenomenon, the accuracy and reliability of measurements can be affected. This means that the calculated concentrations of these compounds in urine samples may be biased by the characteristics of the urine matrix, potentially leading to inaccurate results. Therefore, it becomes fundamental to quantify using a specific matrix-matched calibration curve in urine to account for this matrix effect. Sara Catalina Darai Universidad de Valladolid 21 Figure 3. Comparison of levofloxacin slopes in solvent vs. Matrix. However, in certain cases, specifically in 14, where calibration curves were not available for specific compounds in urine (Table 4) their concentrations can be estimated using the calibration curves built in the solvent. It should be noted that this estimation may lead to actual concentration underestimation due to the observed suppression effect in urine [28]. R² = 0.9957 R² = 0.986 0.00E+00 5.00E+07 1.00E+08 1.50E+08 2.00E+08 2.50E+08 3.00E+08 020 40 60 80 100 Concentration levofloxacin solvent levofloxoacin matrix In this case, matrix effect was 23%. Sara Catalina Darai Universidad de Valladolid 22 Chemical LOQ (ng/mL) iLOQ (ng/mL) LODs (ng/mL) iLODs (ng/mL) Precision (CV%) Levofloxacin 1 0.2 0.33 0.07 NA Sulfathiazole - 10 - 3.33 NA Tylosin - 2 - 0.67 NA Apramycin - 1 - 0.33 NA Trimethoprim 52 0.2 17.33 0.07 42% Progesterone 5 0.5 1.67 0.17 58% Carbamazepine 1 0.01 0.33 0.00 22% Propranolol 2 0.2 0.67 0.07 24% Metronidazole 0.05 0.05 0.02 0.02 NA Ofloxacion 1 2 0.33 0.67 71% Nalidixic acid NA 0.5 - 0.17 NA Atorvastatin 5 0.5 1.67 0.17 39% Atenolol - 2 - 0.67 NA Caffeine NA 0.2 - 0.07 NA DEET 1 0.01 0.33 0.00 47% Crotamiton 5 0.2 1.67 0.07 38% Estrone - 0.1 - 0.03 90% Alprazolam 10 0.01 3.33 0.00 48% Ibuprofen 5 1 1.67 0.33 57% Bisphenol A - 2 - 0.67 49% Nonylphenol - 5 - 1.67 NA Gembfibrozil 1 1 0.33 0.33 12% MEHP 0.01 0.01 0.00 0.00 19% BP AF - 5 - 1.67 NA Sara Catalina Darai Universidad de Valladolid 23 Chemical R2 solvent R2 matrix Matrix effect Recovery 10 ppb Recovery 50 ppb Levofloxacin 0.995 0.986 92% 130% 86% Sulfathiazole 0.990 NA NA NA NA Tylosin 0.994 NA NA NA NA Apramycin 0.981 NA NA NA NA Trimethoprim 0.991 0.983 13% NA 19% Progesterone 0.981 1.000 23% 98% 19% Carbamazepine 0.990 0.995 11% 117% 94% Propranolol 0.994 0.983 51% 149% 13% Metronidazole 1.000 1.000 26% NA 90% BP M - 5 - 1.67 NA BP Z - 5 - 1.67 NA BP P - 5 - 1.67 NA Tiamulin 52 0.2 17.33 0.07 93% B-Estradiol - 5 - 1.67 40% Codeine phosphate - 1 - 0.33 37% Dexamethasone - 5 - 1.67 NA Sulfapyridine 52 0.5 17.33 0.17 NA Norfloxacin 100 5 33.33 1.67 200% Sulfadiazine - 0.02 - 0.01 NA Florfenicol - 0.1 - 0.03 173% Naproxen - 0.2 - 0.07 NA Sara Catalina Darai Universidad de Valladolid 24 Ofloxacion 1.000 0.990 76% 96% 64% Nalidixic acid 1.000 NA 26% NA 78% Atorvastatin 0.998 0.935 6% 59% 163% Atenolol 1.000 NA NA NA NA Caffeine 0.998 NA NA NA NA DEET 0.992 0.999 20% 186% 85% Crotamiton 0.994 0.996 21% 133% 102% Estrone 0.989 NA NA NA NA Alprazolam 1.000 0.828 7% 75% 99% Ibuprofen 0.996 0.971 32% 131% 168% Bisphenol A 0.968 NA NA NA NA Nonylphenol 1.000 NA NA NA NA Gembfibrozil 0.999 0.984 49% 99% 72% MEHP 0.990 0.963 37% 100% 62% BP AF 0.979 NA NA NA NA BP M 0.991 NA NA NA NA BP Z 0.935 NA NA NA NA BP P 0.989 NA NA NA NA Tiamulin 0.994 NA 84% NA 326% B-Estradiol 0.987 NA NA 188% 93% Sara Catalina Darai Universidad de Valladolid 25 Codeine phosphate 0.984 NA NA 127% 56% Dexamethasone 0.962 NA NA NA NA Sulfapyridine 1.000 NA NA NA 38% Norfloxacin 1.000 NA NA NA NA Sulfadiazine 0.991 NA 0% NA NA Florfenicol 0.997 NA NA NA NA Naproxen 0.998 NA 0% NA NA Table 4. Validation Table. (The compounds highlighted in dark blue are those that were quantified, the ones in light blue are those that were semi-quantified, and those left in white are those for which validation was not possible. NA, not available). Sara Catalina Darai Universidad de Valladolid 32 Chemical Urine-189 Urine-190 Urine-141 Urine-142 Urine-143 Urine-144 Urine-145 Urine-146 Urine-147 Urine-148 Levofloxacin ND ND ND ND ND ND ND ND ND ND Sulfathiazole ND ND ND ND ND ND ND ND ND ND Tylosin ND ND ND ND ND ND ND ND ND ND Apramycin ND ND ND ND ND ND ND ND ND ND Trimethoprim ND ND ND ND ND ND ND ND ND ND Progesterone ND 46.3 ND ND 19.3 ND ND ND ND ND Carbamazepine ND ND ND ND ND ND ND ND ND ND Propranolol ND ND ND ND ND ND ND ND ND ND Metronidazole ND ND ND ND ND ND ND ND ND ND Ofloxacion ND ND ND ND ND 5.9 ND ND ND ND Nalidixic acid ND ND ND 9.6 10.1 ND ND ND ND ND Atorvastatin ND ND ND ND ND ND ND ND ND ND Atenolol ND ND ND ND ND ND ND ND ND ND Caffeine ND ND ND 7.9 18.7 ND 53.7 2.4 ND ND DEET <LOQ ND ND ND ND <LOQ 1.1 ND ND ND Crotamiton ND ND ND ND ND ND ND ND ND 7.7 Estrone ND ND 73.8 ND ND ND ND 27.3 ND ND Alprazolam ND ND ND ND ND ND ND ND ND ND Ibuprofen 14.8 ND 61.1 ND ND ND 24.9 ND ND ND Bisphenol A ND ND ND 18.0 ND ND ND ND ND ND Nonylphenol ND ND ND ND ND ND ND ND ND ND Gembfibrozil ND ND ND ND ND ND ND ND ND ND MEHP ND ND ND ND ND 0.0 <LOQ ND 0.1 ND BP AF ND ND ND ND ND ND ND ND ND ND BP M ND ND ND ND ND ND ND ND ND ND BP Z ND ND ND ND ND ND ND ND ND ND Sara Catalina Darai Universidad de Valladolid 33 BP P ND ND ND ND ND ND ND ND ND ND Tiamulin ND ND ND ND ND ND ND ND ND ND B-Estradiol 772300 6097000 6016000 5933000 5367000 1261000 909900 2177000 1473000 1945000 Codeine phosphate 318700 139700 ND 351100 ND ND 80270.0 ND ND ND Dexamethasone ND ND ND ND ND ND ND ND ND ND Sulfapyridine ND ND ND ND ND ND ND ND ND ND Norfloxacin ND ND ND ND ND ND ND ND ND ND Sulfadiazine ND 590100 1464000 1148000 ND ND ND ND 469400 343800 Florfenicol ND 684100 1333000 ND 1167000 ND ND ND ND 457800 Naproxen ND ND ND ND ND ND ND ND ND ND Chemical Urine-149 Urine-150 Urine-151 Urine-152 Urine-153 Urine-154 Urine-155 Urine-156 Urine-157 Urine-158 Levofloxacin ND ND ND ND ND ND ND ND ND ND Sulfathiazole ND ND ND ND ND ND ND ND ND ND Tylosin ND ND ND ND ND ND ND ND ND ND Apramycin ND ND ND ND ND ND ND ND ND ND Trimethoprim ND ND ND ND ND ND ND ND 6.3 ND Progesterone ND ND ND ND ND ND ND ND ND ND Carbamazepine ND ND ND ND ND ND ND ND ND ND Propranolol ND ND ND ND ND ND ND ND ND ND Metronidazole ND ND ND ND ND ND ND ND ND ND Ofloxacion ND ND ND ND ND 5.4 ND ND ND ND Nalidixic acid ND ND ND ND ND ND ND 5.4 5.3 ND Atorvastatin ND ND ND ND ND ND ND ND ND ND Atenolol ND ND ND ND ND ND ND ND ND ND Sara Catalina Darai Universidad de Valladolid 34 Caffeine ND ND ND 34.8 ND 41.9 81.8 ND ND ND DEET ND ND ND ND ND ND ND ND ND ND Crotamiton 6.7 ND ND ND 5.9 ND ND ND ND ND Estrone 22.2 ND ND ND 22.6 ND ND 25.5 21.6 ND Alprazolam ND ND ND ND ND ND ND ND ND ND Ibuprofen ND ND ND ND ND ND ND ND ND ND Bisphenol A ND ND ND ND ND 3.3 ND ND ND ND Nonylphenol ND ND ND ND ND ND ND ND ND ND Gembfibrozil ND ND ND ND ND ND ND ND ND ND MEHP ND ND 0.1 ND ND ND 0.1 0.1 ND 0.1 BP AF ND ND ND ND ND ND ND ND ND ND BP M ND ND ND ND ND ND ND ND ND ND BP Z ND ND ND ND ND 33.6 ND ND ND ND BP P ND ND ND ND ND ND ND ND ND ND Tiamulin ND ND ND ND ND ND ND ND ND ND B-Estradiol ND 2216000 1116000 1847000 5064000 626400 3326000 2492000 3452000 1859000 Codeine phosphate ND 125900 ND 198300 ND ND 151800 ND 185100 ND Dexamethasone ND ND ND ND ND ND ND ND ND ND Sulfapyridine ND ND ND ND ND ND ND ND ND ND Norfloxacin ND ND ND ND ND ND ND ND ND ND Sulfadiazine ND ND ND ND 418300 ND ND ND 646700 ND Florfenicol 785400 572300 ND ND ND ND ND ND ND 762100 Naproxen ND ND ND ND ND ND ND ND ND ND Table 5. Concentrations of different chemical compounds in urine samples (the compounds highlighted in dark blue are those that were quantified, the ones in light blue are those that were semi-quantified, and those left in white are those for which validation was not possible. ND, non-detectable). Sara Catalina Darai Universidad de Valladolid 35 Chemical DF Average (ng/mL) Median (ng/mL) Levofloxacin 0.03 0.03 0 Sulfathiazole 0 0 0 Tylosin 0 0 0 Apramycin 0 0 0 Trimethoprim 0 0 0 Progesterone 0.30 1336 3.13 Carbamazepine 0 0 0 Propranolol 0 0 0 Metronidazole 0.03 1.4E-05 0 Ofloxacion 0.10 1.2E+00 0 Nalidixic acid 0.18 1.5E+00 0 Atorvastatin 0 0 0 Atenolol 0 0 0 Caffeine 0.40 0 10.67 DEET 0.18 0 0.41 Crotamiton 0.13 0 0.96 Estrone 0.4 0 11.70 Alprazolam 0 0 0 Ibuprofen 0.3 0 16.34 Bisphenol A 0.13 0 2.86 Nonylphenol 0 0 0 Gembfibrozil 0 0 0 MEHP 0.28 0 0.015 BP AF 0 0 0 BP M 0 0 0 BP Z 0.03 0 0.84 BP P 0 0 0 Tabla 6. Summary table of concentrations. BP levels in urine ranged from non-detected (ND) to 284 ng/mL, with nearly 5% of the women having detectable concentrations of BPs (Table 5). In the present work, concentrations of BPA in urine samples ranged between 3.3 and 89.6 ng/mL, we can compare it with the data previously published in the literature, it was observed that the concentrations of BPA detected in urine samples range from 0.886 ng/mL in some studies in China [4] to 2070 ng/mL in a study in the United States [8], we can observe that the lower limit in the bibliography is similar to that in our study, while the upper limit we obtain is significantly lower than the bibliographic one. As for BP Z, it has been identified in only one sample with a value of 33.6 ng/mL, whereas in previous publications from the literature, it was Sara Catalina Darai Universidad de Valladolid 36 found to have a value of 0.06 ng/mL in a sample from Saudi Arabia [5]. No other bisphenols have been detected in the analyzed samples. Regarding phthalates, only the presence of mono-2-ethylhexyl phthalate has been detected in the analyzed samples. The levels ranged from non-detectable to 0.09 ng/mL, with nearly 9.5% of the women showing concentrations of phthalates above LOD (Table 5). The levels of concentration were quite low when compared to the bibliographic data. Nonetheless they varied from levels as low as 9.8 ng/mL in Germany [15], 6.2 ng/mL in Spain [19], 4.7 ng/mL in urban Egypt [20], 2.2 ng/mL in the United States [16] up to concentrations as high as 25 ng/mL in South Korea [18]. Regarding progesterone, it ranged from 6.3 ng/mL to 22881.46 ng/mL in the samples analyzed in the study, with detectable concentrations observed in 12 of the participants, we can compare these values with those found in the literature, where concentrations of progesterone in serum range from 0.08 to 1.57 ng/mL, with an average value of 0.24 ng/mL [31] Caffeine levels were found in a range from 2.0 ng/mL to 81.8 ng/mL, with 16 participants showing detectable concentrations [32]. We can compare with the values from the bibliography, caffeine and its metabolites were detectable in the urine of most individuals. Median concentrations ranged from 560 ng/mL to 58600 ng/mL [32]. We can observe that our experimental values are below the reference values. This could be attributed to the fact that caffeine concentration levels tend to be lower in the urine of pregnant women, as they are advised to limit their caffeine consumption during pregnancy. Similarly, nalidixic acid exhibited concentrations spanning from 3.5 ng/mL to 20.8 ng/L, detectable in 7 individuals. Again, this study entails the first time concentrations of this antibiotic is reported for urine. Then, as no previous data is available for urines, concentrations in urban wastewater were used as a reference. Hence, Ghosh et al. [30] reported an average concentration of 40 ng/mL for nalidixic acid in influent wastewater to urban wastewater treatment plants in Singapore. Sara Catalina Darai Universidad de Valladolid 37 DEET, on the other hand, displayed concentrations ranging from <LOQ to 1.1 ng/L, detected in 7 participants. We can compare with the values from the bibliography, where we found concentrations spanning from 0.0475 ng/mL to 2.57 ng/mL, with an average concentration of approximately 0.3439 ng/mL [33]. The analysis of crotamiton revealed concentrations varying from 5.9 ng/mL to 11.0 ng/mL, detectable in 5 participants out of the total 40 participants. The analysis of crotamiton in urine in this study was novel and no previous data is available for comparison. Crotamiton was reported to be present in wastewater samples collected from residential areas at concentrations extending from less than 0.0005 ng/mL to 0.387 ng/mL, with an average concentration of 0.0346 ng/mL [33]. Estrone levels spanned from 9.0 ng/mL to 73.8 ng/L, detectable in 16 individuals, we can compare these values with the literature, where urinary estrone levels, measured in nanograms per milligram of creatinine (ng/mg-Cr), range from 2.7 to 13.4 ng/mg-Cr, with an average value of 7.5 ng/mg-Cr [31], since we're studying urine from pregnant women, it's normal for our values to be higher. Finally, ibuprofen concentrations ranged from 14.8 ng/mL to 178.5 ng/L, with detectable levels observed in 12 participants. Ibuprofen has been found in urine before showing concentrations averaging 411000 ng/L [24]. Thus, levels of ibuprofen observed in the present study were clearly lower. However, this discrepancy can be explained as the bibliographic values were based on data from the general population, while our data was extracted from a specific group of pregnant women. In this context, it is understandable that the concentration of ibuprofen is lower, as this medication is generally not recommended during pregnancy due to safety concerns. Regarding levofloxacin, it was not detected in any of the examined samples. Similarly, sulfathiazole, tylosin, apramycin, trimethoprim, carbamazepine, propranolol, atorvastatin, atenolol, alprazolam, nonylphenol, gemfibrozil, tiamulin, B-Estradiol, codeine phosphate, dexamethasone, sulfapyridine, norfloxacin, sulfadiazine, florfenicol and naproxen were not detected either. The lack of detection of these compounds in the urine samples of pregnant women could be attributed to the fact that these substances are generally avoided by Sara Catalina Darai Universidad de Valladolid 38 expectant mothers on medical advice due to the potential adverse effects they could have on embryonic and fetal development. The chemical compounds bisphenol AF, bisphenol P, bisphenol B, bisphenol M and bisphenol Z have also not been detected, which is in accordance with what it was observed in the study conducted by Ye et al [8]. 4. CONCLUSIONS This study has provided an enriching insight into the presence of emerging contaminants in human urine samples, emphasizing the importance of understanding their relevance and the potential health risks they pose. Emerging contaminants have become a subject of growing concern due to their ubiquity in consumer products and their ability to negatively impact human health, even at very low concentrations. It is worth noting that, although 36 compounds were analyzed, satisfactory results were obtained for only 27 of them. This highlights the complexity of analyzing urine samples due to the matrix and the need to use semi-quantification in some cases. Despite the inherent challenges posed by the urine matrix, a 76% success rate was achieved in method validation, demonstrating the robustness of the applied methodology. The significance of this study lies in its impact on public health. The findings provide valuable information about the population's exposure to these emerging contaminants through urine biomonitoring. Such studies can influence future regulations aimed at mitigating the risks associated with these contaminants and protecting public health and the environment. Ultimately, this work underscores the need for ongoing research and the optimization of analytical methods to improve the accuracy of emerging contaminant detection and to assess potential health risks more precisely. This study significantly contributes to the understanding of emerging contaminants and their impact on the human environment. Sara Catalina Darai Universidad de Valladolid 39 5. SUPLEMENTARY INFORMATION Supplementary information is available at the end of this document. 6. ACKNOWLEDGMENTS Authors acknowledge the Regional Government of Castilla y León and the EUFEDER (CL-EI-2021-07, 587 UIC 320, UIC 338). IDAEA-CSIC author acknowledge the Spanish Ministry of Science and Innovation through the support received as “Centro de Excelencia Severo Ochoa 2019–2023″. We thank the effort put in the collection and distribution of samples from the INSULIN cohort (TECSPR19-1-0022) to researchers from Rovira i Virgili University and the Joan XXIII Hospital. 7. BIBLIOGRAPHY [1] J. R. Rochester, “Bisphenol A and human health: A review of the literature,” Reproductive Toxicology, vol. 42. 2013. doi: 10.1016/j.reprotox.2013.08.008. [2] D. 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Cho et al., “Relationship between environmental phthalate exposure and the intelligence of school-age children,” Environ Health Perspect, vol. 118, no. 7, 2010, doi: 10.1289/ehp.0901376. [19] L. Casas et al., “Urinary concentrations of phthalates and phenols in a population of Spanish pregnant women and children,” Environ Int, vol. 37, no. 5, 2011, doi: 10.1016/j.envint.2011.02.012. [20] J. A. Colacino et al., “Exposure to phthalates among premenstrual girls from rural and urban Gharbiah, Egypt: A pilot exposure assessment study,” Environ Health, vol. 10, no. 1, 2011, doi: 10.1186/1476-069X-10-40. Sara Catalina Darai Universidad de Valladolid 41 [21] H. M. Koch and A. M. Calafat, “Human body burdens of chemicals used in plastic manufacture,” Philosophical Transactions of the Royal Society B: Biological Sciences, vol. 364, no. 1526. 2009. doi: 10.1098/rstb.2008.0208. [22] F. Carlstedt, B. A. G. Jönsson, and C. G. 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Khaskheli et al., “Estimation of ibuprofen in urine and tablet formulations by transmission Fourier Transform Infrared spectroscopy by partial least square,” Spectrochim Acta A Mol Biomol Spectrosc, vol. 102, 2013, doi: 10.1016/j.saa.2012.10.021. [27] H. A. Mashayekhi, P. Abroomand-Azar, M. Saber-Tehrani, and S. W. Husain, “Rapid determination of carbamazepine in human urine, plasma samples and water using DLLME followed by RP-LC,” Chromatographia, vol. 71, no. 5–6, 2010, doi: 10.1365/s10337-009-1456-6. [28] D. S.-R. E. R.-M. E. G. O. L.-S. R. A. R. T. N. M. M. G.-F. P. G.-S. R. Gutiérrez-Martín, “Comprehensive profiling and semi-quantification of exogenous chemicals in human urine using HRMS-based strategies,” Under review in Analytical and Bioanalytical Chemistry, 2023. [29] M. Boonsaner and D. W. Hawker, “Evaluation of food chain transfer of the antibiotic oxytetracycline and human risk assessment,” Chemosphere, vol. 93, no. 6, 2013, doi: 10.1016/j.chemosphere.2013.05.070. [30] N. Magon and P. Kumar, “Hormones in pregnancy,” Nigerian Medical Journal, vol. 53, no. 4, 2012, doi: 10.4103/0300-1652.107549. [31] M. Newman, S. M. Pratt, D. A. Curran, and F. Z. Stanczyk, “Evaluating urinary estrogen and progesterone metabolites using dried filter paper samples and gas chromatography with tandem mass spectrometry (GC-MS/MS),” BMC Chem, vol. 13, no. 3, 2019, doi: 10.1186/s13065-019-0539-1. [32] M. E. Rybak, M. R. Sternberg, C. I. Pao, N. Ahluwalia, and C. M. Pfeiffer, “Urine excretion of caffeine and select caffeine metabolites is common in the US population and associated with caffeine intake,” Journal of Nutrition, vol. 145, no. 4, 2015, doi: 10.3945/jn.114.205476. Sara Catalina Darai Universidad de Valladolid 48 Progesterone Hormone - C21 H30 O2 57-83-0 3.827 - Estrone (E1) Hormone - C18 H22 O2 53-16-7 3.624 10.25 DEET Insect repellents - C12 H17 NO 134-623 2.419 ֊1.37 (MB) 4-Nonylphenol Surfactants - C15 H24 O 104-405 6.142 10.15 (MA) Sara Catalina Darai Universidad de Valladolid 49 Bisphenol A Industrial chemicals (plastic additives…) - C15 H16 O2 80-05-7 3.641 10.29 (MA) Bisphenol Z Industrial chemicals (plastic additives…) Bisphenol C18H20O2 9117467-3 - - Bisphenol AF Industrial chemicals (plastic additives…) Bisphenol C16 H14 F4 O2 147861-1 9.5 - Sara Catalina Darai Universidad de Valladolid 50 Bisphenol P Industrial chemicals (plastic additives…) Bisphenol C24 H26 O2 1359525-0 - - Bisphenol M Industrial chemicals (plastic additives…) Bisphenol C24 H26 O2 216751-3 - - Caffeine Stimulant xanthines C8 H10 N4 O2 58-082. ֊0.628 0.52 (MB) Crotamiton Anti-itching drugs - C13 H17 N O 483-633 2.464 1.14 Sara Catalina Darai Universidad de Valladolid 51 Alprazolam Anxiolytic Benzodiazepines. C17 H13 Cl N4 2898197-7 2.12 - MEHP Phthalat - C16 H22 O4 103-093 5.3310. - Metronidazole Antimicrobial - C6 H9 N3 O3 443-481 ֊0.135 2.58 / 14.44 Nalidixic acid Antibiotic Quinolone C12 H22 N2 O3 389-082 0.025 3.45 / 6.12 Sara Catalina Darai Universidad de Valladolid 52 Tiamulin Antibiotic Pleuromutilin C28 H47 N O4 S 5529796-6 4,38 E +00 14,65 / 9,74 Codeine Phosphate Opioids Narcotic analgesic C18 H21 N O3 •H3PO4 52-28-8 - 8.22 Dexametasone Analgesic/Antiinflammatory Corticosteroid C22 H29 F O5 50-02-2 2.033 12.13 17-betaestradiol (E2) Hormone - C20 H24 O2 50-28-2 4.106 10.24 Sara Catalina Darai Universidad de Valladolid 53 Sulfapyridine Precusor of compounds - C11 H11 N3 O2 S 144-832 0.469 2.13 / 8.54 Norfloxacin Antibiotic Quinolone C16 H18 F N3 O3 7045896-7 1.744 0.16 / 8.68 Naproxen Analgesic/Antiinflammatory - C14 H14 O3 2220453-1 2.867 4.84 Florfenicol Antibiotic - C12 H14 Cl2 F N O4 S 7323134-2 1.175 10,73 / - 1,79 Data for log P at 25°C and pKa at 25°C were sourced from pubchem. Sara Catalina Darai Universidad de Valladolid 54 Table S2. Chromatographic parameters Time (min) Flow (mL min−1) Mobile pase A (%) 0 o.5 95 2.00 o.5 5 5.00 o.5 5 5.10 o.5 95 12.00 o.5 95 Table S3. List of SRMs and mass spectrometry instrumental conditions for A) the target analytes and B) the internal standards A) RT (min) Analyte Q1 (m/z) Q3 (m/z) DP (V) CE (V) CXP (V) 0.64 Atenolol 1 267.1 145.1 11 33 24 Atenolol 2 190.3 11 29 4 0.80 Metronidazole 1 172.0 128.4 41 21 6 Metronidazole 2 82.1 41 35 14 1.15 Sulfadiazine 1 251.0 155.9 71 23 20 Sulfadiazine 2 108.2 71 31 12 1.50 Sulfathiazole 1 255.9 155.9 96 21 8 Sulfathiazole 2 108.1 96 33 12 Sara Catalina Darai Universidad de Valladolid 55 1.84 Sulfapyridine 1 250.1 156.1 61 23 10 Sulfapyridine 2 108.1 61 35 12 1.93 Trimethoprim 1 291.0 230.1 51 33 18 Trimethoprim 2 261.1 51 35 16 3.30 Apramycin 1 271.0 156.1 50 20 19 Apramycin 2 180.0 50 40 19 3.64 Caffeine 1 195.0 137.9 71 27 18 Caffeine 2 110.6 71 31 16 3.76 Ofloxacin 1 362.0 318.3 86 29 26 Ofloxacin 2 261.1 86 37 14 3.82 Norfloxacin 1 320.1 276.2 96 27 18 Norfloxacin 2 233.1 96 37 16 4.18 Florfenicol 1 357.8 339.9 66 13 24 Florfenicol 2 241.3 66 25 14 4.42 Bisphenol A 1 227.0 227.1 -60 -14 -15 Bisphenol A 2 211.1 -60 -26 -13 4.46 Propranolol 1 260.1 183.1 66 25 12 Propranolol 2 116.1 66 25 8 Sara Catalina Darai Universidad de Valladolid 56 4.52 Tiamulin 1 494.1 192.2 51 29 10 Tiamulin 2 119.7 51 59 12 4.72 Tylosin 1 916.2 772.3 156 43 36 Tylosin 2 174.1 156 51 10 4.79 Nalidixic acid 1 233.1 187.1 21 37 18 Nalidixic acid 2 159.9 21 45 18 4.86 Carbomazepine 1 237.0 194.2 66 29 12 Carbomazepine 2 193.3 66 47 6 4.98 DEET 1 192.0 119.3 56 23 10 DEET 2 90.3 56 41 10 5.03 Dexamethasone 1 392.9 355.1 41 19 20 Dexamethasone 2 147.3 41 39 10 5.06 4-nonylphenol 1 219.1 132.9 -65 -42 -7 4-nonylphenol 2 117.0 -65 -80 -13 5.13 Naproxen 1 231.1 185.1 56 21 12 Naproxen 2 170.5 56 37 10 5.14 Atorvastatin 1 559.2 440.2 26 33 38 Atorvastatin 2 250.1 26 59 18 Sara Catalina Darai Universidad de Valladolid 57 5.32 Ibuprofen 1 205.0 159.1 -35 -10 -15 Ibuprofen 2 160.9 -35 -12 -21 5.37 Progesterone 1 315.1 109.2 141 31 10 Progesterone 2 297.2 141 23 28 5.39 Estrone (E1) 1 271.1 253.3 101 19 10 Estrone (E1) 2 133.1 101 35 12 5.50 β-Estradiol (E2) 1 273.0 255.0 46 17 14 β-Estradiol (E2) 2 107.8 61 41 14 5.55 Crotamiton 1 204.1 69.4 61 35 12 Crotamiton 2 136.1 61 27 14 5.56 Gemfibrozil 1 248.9 121.0 -5 -30 -7 Gemfibrozil 2 127.5 -85 -14 -5 5,28 Bisphenol P 1 345 329 -15 -36 -23 Bisphenol P 2 315 -15 -48 -17 5.26 Bisphenol M 1 345 329 -115 -40 -17 Bisphenol M 2 250 -115 -38 -15 5.01 Bisphenol Z 1 267 173 -65 -36 -9 Bisphenol Z 2 145 -65 -48 -9