Bioaccumulation of Polycyclic Aromatic Hydrocarbons for Forensic

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Bioaccumulation of polycyclic aromatic hydrocarbons for forensic assessment using gas chromatography-mass spectrometry Marta Pastor-Belda, Natalia Campillo, Natalia Arroyo-Manzanares, Carmen Torres, María Dolores Pérez-Cárceles, Manuel Hernandez-Cordoba, and Pilar Viñas Chem. Res. Toxicol., Just Accepted Manuscript • DOI: 10.1021/acs.chemrestox.9b00213 • Publication Date (Web): 15 Jul 2019 Downloaded from pubs.acs.org on July 19, 2019

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Chemical Research in Toxicology

Bioaccumulation of polycyclic aromatic hydrocarbons for forensic assessment using gas chromatography-mass spectrometry

Marta Pastor-Belda1, Natalia Campillo1, Natalia Arroyo-Manzanares1, Carmen Torres2, María Dolores Pérez-Cárceles2, Manuel Hernández-Córdoba1, Pilar Viñas1* 1

Department of Analytical Chemistry, Faculty of Chemistry, Regional Campus of International Excellence

"Campus Mare Nostrum", University of Murcia, E-30100 Murcia, Spain 2

Department of Legal and Forensic Medicine, Faculty of Medicine, Biomedical Research Institute (IMIB-

Arrixaca), University of Murcia, Spain

*Corresponding author: Prof. Pilar Viñas Department of Analytical Chemistry Faculty of Chemistry University of Murcia E-30100 Murcia SPAIN Tel.: +34 868887415 FAX: +34 868887682 e-mail: [email protected]

1 ACS Paragon Plus Environment

Chemical Research in Toxicology 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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ABSTRACT: Polycyclic aromatic hydrocarbons (PAHs) are considered xenobiotics of a potentially carcinogenic nature, being accumulated in the fatty tissue of the body. The objective of this work was the development and validation of a new analytical method to check the bioaccumulation of these toxic compounds in human organs obtained from autopsies. The contaminants were first isolated from the tissues by salt-assisted liquid-liquid extraction in acetonitrile. Due to the low concentrations of these compounds in the human body, a dispersive liquid-liquid microextraction procedure was included. The preconcentrated samples were analysed by gas chromatography-mass spectrometry to identify the compounds. Principal component analysis was applied to show the natural clustering of forensic samples and orthogonal partial least squares discriminant analysis to develop a multivariate regression method, which permitted the classification of samples. The quantification limits for the 13 PAHs (acenaphthylene, fluorene, phenanthrene, anthracene, pyrene, benzo(a)anthracene, chrysene,

benzo(b)fluoranthene,

benzo(k)fluoranthene,

benzo(a)pyrene,

dibenz(a,h)anthracene, benzo(g,h,i)perylene and indeno(1,2,3-cd)pyrene) analysed were in the 0.06-0.44 ng g-1 range, depending on the compound, while the mean intraday relative standard deviation of about 7% demonstrated the high precision of the method. Linearity was verified in the 0.5-200 ng g-1 range, and the enrichment factors were between 55 and 122. The results provided by the analysis of seven different human organs (brain, liver, kidney, lung, heart, spleen, and abdominal fat) from eight autopsies confirmed the PAHbioaccumulation capacity of human body, fat showing the highest degree of bioaccumulation. The present work is the first study on PAH contamination in different organs obtained from autopsies, being PAH detected in most human samples at values ranged from 0 to 19 ng g-1.

Keywords Forensic analysis • Polycyclic aromatic hydrocarbons • Human organs • Autopsies • GC-MS • Multivariate discriminant analysis

INTRODUCTION Studies concerning the source, transport, and fate of organic compounds in the environment are a major theme in the field of forensic research. Petroleum residues contain polycyclic aromatic hydrocarbons (PAHs) as a result of combustion and are mainly found in urbanized areas, where they are persistent in the environment, bioaccumulative and toxic. As a class of compounds with profiles that differ according to their source, they lend themselves to chemical forensic applications. 1, 2 PAHs reaching the aquatic environment can contaminate aquaculture sediments over a long period, and they may be deposited in the fatty tissues of aquatic animals, leading to health hazards for marine life and human


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beings. In order to understand the exact distribution of PAHs in aquaculture ecosystems, it is necessary to assess their levels in aquaculture organisms3 since the consumption of polluted fish is an important health hazard to the human population in developed countries.4 Skin is also an entry route of PAHs due to its high permeation for protein-lipid, and they are accumulated in the fatty tissue of the body.5 Six PAHs, benzo(a)anthracene (BaA), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), dibenzo(a,h)anthracene (DBA) and indeno(1,2,3-cd)-pyrene (IND), have been classified as probable human carcinogens by the International Agency for Research on Cancer (IARC).6,7 For these reasons, the assessment of PAHs in the organs of patients with cancer or other diseases is important. Human health damage associated with PAHs has been evaluated by several authors, 8,9 and some have identified tobacco smoke as a major source of human exposure to PAHs.10 The extremely low concentrations of PAHs in biological samples as well as the complexity of the matrix make the determination of PAHs a challenging task. In this sense, the literature describes very different methodologies regarding both sample treatment and analysis methods. Liquid chromatography with fluorescence detection (LC-FLD) has been widely used,5,11-16 although diode array detection (DAD) is used for acenaphthylene (ACE) monitoring as this compound is not fluorescent.14-16 Forensic chemistry and toxicology sciences use gas chromatography-mass spectrometry (GC-MS) as the analytical method of choice for the elucidation of biomarker compounds or toxicants present in biological samples. Thus, GC-MS with simple quadrupole,17-21 triple quadrupole22-25 and quadrupole time-of-flight26,27 analyzers have also been applied for the determination of different PAHs in biological samples. Fish tissues are the biological matrices that have been most studied for their PAH content, because they readily accumulate these chemicals; however, the literature dealing with PAHs in other animal or human tissues is scarce,14,21,22,24 and no studies have been found dealing with PAH determination in human organs obtained from autopsies. The determination of PAHs for environmental forensic application requires analytical methods that are sensitive enough to meet the low detection limits needed for the protection of the environment and human health.28 Classical extraction methods such as Soxhlet extraction with nonpolar solvents have been used to isolate PAHs from fish,29 although saponification in basic alcoholic medium is probably the most widely applied sample treatment for seafood matrices.11,16,18, 23 Clean-up of the obtained extracts has been carried out by solvent extraction with NaOH/urea/thiourea11 and SPE with alumina and silica.18 The application of an auxiliary power in the isolation of the analytes from the respective solid matrices has proven to shorten this step, increasing the analyte recoveries. Thus, microwave-assisted extraction (MAE),15,16 pressurized liquid extraction (PLE),22 accelerated solvent extraction (ASE),14,30,31 ultrasound-assisted extraction (UAE)32 and supercritical fluid extraction (SFE)19 have demonstrated high efficiency for PAH isolation from different biological matrices. The environmental-friendly solvents known as deep eutectic solvents (DESs) have been used for the dissolution of microalgae and fish muscle prior to determining PAH content13. The QuEChERS methodology has also been used for the analysis of PAHs in animal tissues.5,26,33 On the other hand, microextraction techniques have not been widely employed in this type of matrices, and the literature only considers the use of in-tube solid-phase microextraction for human hair analysis12, stir bar sorptive extraction for seafood analysis23 and magnetic solid phase extraction, using three-dimensional ionic liquid-ferrite functionalized graphene oxide nanocomposite as sorbent, in human blood analysis.21 As far as we know, liquid phase microextraction (LPME) has not been applied for PAH determination in human organs from autopsies. Thus, a new procedure based on a salting out liquid-liquid extraction (SALLE) combined with dispersive liquid-liquid microextraction (DLLME) and GC-MS is proposed to determine thirteen PAHs in seven human organs (brain, liver, kidney, lung, heart, spleen, and abdominal fat) obtained from eight autopsies. The



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objective is not only the development and validation of a new analytical method, but also to check the bioaccumulation of these pollutants in the human body and to differentiate between the levels in these organs using multivariate discriminant analysis MATERIALS AND METHODS Reagents An EPA 525 PAH Mix B, which contains 500 µg mL-1 of acenaphthylene (ACE), fluorene (FLE), phenanthrene (PHN), anthracene (ANT), pyrene (PYR), benzo(a)anthracene (BaA), chrysene (CHR), benzo(b)fluoranthene (BbF), benzo(k)fluoranthene (BkF), benzo(a)pyrene (BaP), dibenz(a,h)anthracene (DBA), benzo(g,h,i)perylene (BgP) and indeno(1,2,3-cd)pyrene (IND) in acetone was provided by Sigma (St. Louis, MO, USA). Working standard solutions were prepared daily by diluting with methanol. Biphenyl (BPH), used as internal standard (IS), was purchased from Sigma-Aldrich. Chromatographic quality acetonitrile (ACN) was provided by ChemLab (Zedelgen, Belgium), carbon tetrachloride (CCl4), 1,2-dichloroethane (C2H4Cl2) were from Panreac (Barcelona, Spain). Chloroform (CHCl3), 1,1,2,2- tetrachloroethane (C2H2Cl4), dichloromethane (CH2Cl2) and NaCl from Sigma. The water used was previously purified in a Milli-Q system (Millipore, Bedford, MA, USA). Instrumentation Gas chromatographic analysis was carried out using an Agilent 6890N (Agilent, Waldbronn, Germany) gas chromatograph coupled to an Agilent 5973 quadrupole mass spectrometer. Mass spectrometer was equipped with an inert ion source and an HP-5MS (5% diphenyl–95% dimethylpolysiloxane, Agilent) capillary column (30 m × 0.25 mm I.D., 0.25 µm film thickness) was used. Carrier gas (helium) was maintained 1 mL min−1 (constant flow) and 1 µL was injected using pulsed splitless mode, with a pressure pulse value of 11 psi applied for 0.5 min. The programme of temperature was as follows: 75 ºC for 0.5 min, increase to 195 ºC at 15 ºC min−1 and hold for 3.5 min, increase to 230 ºC at 5 ºC min−1 and hold for 10 min, and finally increase to 305 ºC at 10 ºC min-1 and hold for 8.5 min. Under these conditions, the all analytes were eluted in less than 43 min. Temperatures of 230, 300 and 150 ºC were set at the ion source, transfer line and quadrupole, respectively and MS operated using electron-impact (EI) mode at 70 eV. In order to improve the limits of detection, compounds were quantified using selected ion monitoring (SIM) mode with one target and two qualifier ions. The retention times, and the target and qualifier ions for each compound are shown in Table 1. Identification was confirmed by the retention time of the target ion and the qualifier-to-target ion ratios for each compound. The compounds BaA and CHR were integrated and quantified together, as well as the BkF and BaP pair, because of the closeness of their chromatographic peaks. Data were acquired using MSD Chemstation Data Analysis application (Version G1701EA, revision E.02.02.SP29). The sample extracts were filtered using PVDF filters of 0.45 μm (Teknokroma, Barcelona, Spain). An EBA 20 (Hettich, Tuttlingen, Germany) centrifuge and a Perkin Elmer microwave digester model-3000 (Massachusetts, USA), with a maximum output of 1400 W provided by two 2455 MHz magnetrons, were also used for sample treatment. In order to isolate the PAHs from the solid samples, an UP 200H ultrasonic probe processor (Dr. Hielscher, Teltow, Germany) with an effective output of 200 W in liquid media equipped with a titanium sonotrode (7 mm I.D.) was used, and animal and human samples were crushed using a mixer IKA A11 basic (Wilmington, USA) mixer.


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Human tissue samples For optimization purposes, selected animal tissues were used in order to mimic as much as possible those of human origin. Lamb tissues (lung, kidney, liver, heart), pig brain and chicken fat were obtained from local supermarkets. Animal spleen was not found. Human tissue samples were obtained from cadavers selected from medical-legal autopsies carried out at the Institute of Legal Medicine of Murcia (Murcia, Spain), taking around 5 g of each tissue (brain, liver, kidney, lung, heart, spleen, and abdominal fat). The samples formed part of the usual complementary tests for the diagnosis of the cause of death, and samples were not specifically collected for this study. The present investigation was carried out in full compliance with ethical investigation and legal requirements mandatory for this type of study. The confidentiality of personal data and their automated processing was respected in accordance with current legislation concerning the protection of personal data. Supplemental Table S1 shows the representative data for each case. More information about diseases of the autopsies and/or more samples from autopsies from cancer diseases were impossible to obtain for this first study. However, the contact with the forensic researchers is maintained for doing future studies establishing the connection of PAHs levels and causes of death. Once the samples arrived at the laboratory, they were crushed to obtain a homogeneous mixture and stored at -20 ºC in the freezer. Before analysis, the samples were defrosted, and the optimized mass was weighed in a plastic centrifuge tube. Analytical procedure To a mass of 0.3 g tissue, 60 μL of BPH (0.1 μg mL-1) were added, followed by 3 mL of water and 3.5 mL of ACN and the mixture was manually shaken. The addition of 0.5 g NaCl permitted the separation of aqueous and organic phases by SALLE, which was enhanced by centrifuging the mixture for 5 min at 3000 rpm. The supernatant (2 mL ACN) was used as dispersant in the subsequent DLLME step. For this, 50 µL CCl4 were combined with the ACN recovered phase and the mixture was vigorously injected into 9 mL water containing 5% NaCl (w/v). Centrifugation for 3 min at 3000 rpm allowed sedimentation of the CCl4 drop at the bottom of the tube (volume recovered 35±5 μL), and 1 μL was injected into the gas chromatograph. For recovery studies, 0.3 g of animal tissue samples were spiked at two concentration levels (2.5 and 25 ng

g-1)

by duplicate and were homogenized for 5 min using a mixer and left in the freezer overnight, before

carrying out the analyses mentioned above. RESULTS AND DISCUSSION Optimization of PAHs extraction Different extraction methods were tested to isolate the PAHs from the matrix samples, using 0.1 g aliquots of lamb liver fortified at 50 ng g-1 with the PAHs. Preliminary experiments were carried out by applying saponification with 4 M KOH ethanolic solution, in which the samples were completely dissolved. Nevertheless, the high proteins content of the extracts makes hindered application of a subsequent LPME stage. Consequently, the saponification reaction was discarded. The effectiveness of MAE and UAE using 0.1 g sample mass and different compatible organic solvents like methanol, acetonitrile and ethanol (3 mL) were tested. Microwave energy was applied using a programme which increased the power from 0 to 200 W in 1 min before holding for 15 min, and ultrasounds energy through a probe directly immersed in the sample mixture for 3 min and applying 180 cycles of 0.8 s per cycle and 140



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μm amplitude. In both cases, ethanol and ACN provided the highest extraction efficiencies. The best results in the shortest times were obtained with UAE. Nevertheless, the extracts thus obtained were dirty and no sedimented drop appeared when DLLME was applied. For this reason, SALLE with ACN was tested, by adding 2 mL of water to 0.1 g sample, followed by 2.5 mL ACN and 0.5 g NaCl. After centrifugation, the water-soluble sample components remained in the aqueous phase, giving a cleaner ACN extract. In addition, this procedure provided a higher extraction efficiency for all the studied PAHs than MAE and UAE, as shown in Fig. 1. Different solvents (methanol, ethanol, ACN and acetone) were checked, but only ACN led to good separation from the aqueous phase in the presence of salt. Moreover, because ACN provided the higher recoveries, it was selected. The volume of ACN was studied as described below for its further use as dispersant solvent in the DLLME step. Optimization of DLLME procedure Preliminary experiments were carried out using 0.1 g of lamb liver fortified at 50 ng g-1, which, when submitted to SALLE, provided an ACN extract volume of 1.5 mL. Several DLLME extractant solvent (100 µL) were investigated, all of them denser than water CCl4, CHCl3, C2H4Cl2, C2H2Cl4, CH2Cl2. These were mixed with 1.5 mL of ACN extract recovered from the SALLE step, and the mixture was rapidly injected into 10 mL of aqueous phase. As previously reported,34 the highest extraction efficiency for all PAHs was obtained using CCl4, which was therefore selected. The microextraction efficiency can be affected by four closely related variables, such as the extractant volume, the aqueous phase volume, the salt concentration in the aqueous phase and the volume of dispersant solvent. For this reason, these variables were optimized using the Taguchi method, by means of an orthogonal array design (OAD) (each factor at three levels, in duplicate). Since equilibrium is rapidly reached, extraction time, temperature, and centrifugation speed were not considered during the optimization. The centrifugation speed was fixed at 3000 rpm for 3 min. The extraction efficiency was maximal with 30 µL of carbon tetrachloride, the decrease at higher volumes probably being due to dilution effects. However, a 50 µL of CCl4 volume was finally selected with the aim of obtaining a cleaner drop. As regards the dispersant volume, dispersion of the extractant phase improved as the ACN volume increased, so a volume of 3.5 mL in SALLE (corresponding to 2 mL of dispersant for the DLLME step) was chosen. Increasing the aqueous phase volume up to 9 mL led to higher peak areas, thus this volume was selected. Maximum signals were obtained using a 5% w/v salt content in the aqueous phase. The influence of the sample mass submitted to SALLE-DLLME was studied between 0.1 and 1 g, using a lamb liver sample fortified with 250 ng of each compound. Masses higher than 0.3 g did not provide clean drops after DLLME step, with the consequence of dirty chromatograms and instrumental problems in the GCMS system. Therefore, a 0.3 g sample mass was selected. . Method performance According to international guidelines,35 the method was characterized and linearity, limits of detection (LODs) and quantification (LOQs), selectivity, accuracy, robustness and recovery were evaluated. Biphenyl was used as internal standard (20 ng g-1) after checking that all samples were free of this compound. This appeared to be suitable for the purpose because it had similar chromatographic and DLLME preconcentration behaviour to the analyzed PAHs.


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Calibration curves were stablished using six concentration levels in duplicate, by plotting peak area ratios of each analyte with respect to the IS peak area vs analyte concentration. The slopes of the aqueous standard calibration graphs were compared with the corresponding values obtained for the standard additions to different human tissue samples. No significant differences (95% of confidence level) were observed, as confirmed by the ANOVA test, because the “p” values obtained were higher than 0.05 for all the compounds. Consequently, the absence of a matrix effect was confirmed, and the simpler calibration method with internal standard was applied for quantification purposes. The linearity of the method was established in the 0.5-200 ng g-1 range and regression coefficient values higher than 0.99 were obtained. LODs and LOQs, calculated for a signal-to-noise ratio of 3 and 10, respectively, are summarized in Table 1. Intraday repeatability and interday reproducibility of the method were calculated using the relative standard deviation (RSD) from a series of eight consecutive analyses of a sample spiked with all the compounds at 25 ng g-1. RSD values lower than 13% were obtained for both intra- and interday precision studies. The enrichment factors (EFs), calculated as the ratio of the slope of the calibration graph for the DLLME method and the slope obtained without preconcentration, were between 55 and 122, depending on the compound (Table 1). The PAHs were identified by comparing the retention times, identifying the target (T) and qualifier ions and qualifier-to-target ratios of the peaks in the samples, standard solutions and fortified samples. Method accuracy was evaluated by means of recovery assays. Two samples (brain and liver) were spiked at two concentration levels, 2.5 and 25 ng g-1, corresponding to a low and an intermediate concentration of the linear range. The recoveries ranged between 89 and 110% (n=44) at the lowest level and between 92 and 108% (n=44) for the highest level. The comparison of the proposed method with previous reported methods is shown in Table 3.

Analysis of human organs The proposed method was applied to the determination of the PAH content in seven types of human tissue (brain, lung, liver, kidney, heart, spleen, and abdominal fat) obtained from eight different autopsies. The elution profiles obtained demonstrated the absence of interfering compounds eluting at the retention times of the studied PAHs, as shown in Fig. 2 for both a standard solution mixture (A) and a fortified kidney sample (B). The comparison of the retention times for the analytes in the standard mixture and the fortified samples and, especially, the MS spectra, allowed identification of the PAHs. Table 2 shows the mean content, range of values found and occurrence for each analyte in the seven types of human tissue. The least ubiquitous PAHs were BgP, ACE, DBA and IND. BgP was not detected in five samples, ACE in four samples, DBA in two samples and IND in two samples. Contamination by PAHs was higher for the abdominal fat because the PAHs are liposoluble compounds showing a great tendency to be accumulated in fat tissues, and also in brain and liver samples. Table S2 shows the percentage of contaminated samples which contained one or more PAHs and the mean concentration of total PAHs found in each organ. All samples contained one or more PAHs. The mean concentration ranged between 0.163 (spleen) and 0.540 (fat) ng g-1. Table S2 also shows the percentage of individuals in which the PAHs were detected, regardless of the type of organ, as well as the mean concentration of each PAH in the organs analyzed. As can be seen, the organs showing higher PAHs accumulation were abdominal fat and brain, while similar accumulation was observed in lung, kidney and heart. Higher levels of FLE, PHN, ANT and BbF were observed, thus corresponding to the low-molecular weight PAHs, which were more easily bioaccumulated.



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Statistical study of PAHs bioaccumulation One-way ANOVA statistical tests were applied to check the presence of significant differences between the concentrations of both total and individual PAHs in each organ and tissues. When the total content of PAHs in the different organs was compared, no significant differences were found (F-ratio=1.37; p-value=0.2440). Nevertheless, the highest content of total PAHs was observed in fat, reflecting its high PAHs bioaccumulation capacity. In addition, significant statistical differences were found for ACE (p-value=0.0097) and BbF (pvalue=0.0431), observing the greatest accumulation in liver and brain, respectively. For the other compounds, no significant differences were found (p-value>0.05). However, some PAHs showed higher levels in specific organs: thus PHN (p-value=0.0864), ANT (p-value=0.3014), IND (pvalue=0.2336) and FLE (p-value=0.3686) were more likely to bioaccumulate in fat; IND and FLE showed higher concentrations in heart; PYR (p-value=0.8338), DBA (p-value=0.4470) and BgP (p-value=0.5417) were bioaccumulated to the greatest extent in brain; finally, a clear tendency for BgP to accumulate in spleen was observed. A one-way ANOVA statistical test was applied to establish which compounds showed a greater tendency to bioaccumulation in the body, independently of the organ. All the compounds behaved differently, FLE, PHN, ANT and BbF being the most likely to be bioaccumulated (F-ratio=5.78; p-value=0.000). Significant differences were observed for the accumulation of PAHs in brain (p-value=0.0007), where BbF showed the greatest accumulation, and also a high occurrence, since it appeared in 100% of the brain samples; FLE also showed 100% occurrence, but its concentration was similar in all the organs or tissues. Significant differences were also obtained for liver samples (F-ratio=5.57; p-value=0.000), probably due to the different behaviour of LMW-PAHs (ACE, FLE and PHN), which showed a greater tendency to accumulate in this organ, while the rest of HMW-PAHs showed a lower trend; BaA, CHR and BbF showed an intermediate behaviour between both groups. Lung, kidney, heart, and spleen samples also presented significant differences in terms of PAH behaviour (p-value=0.0000), BbF, FLE and PHN being most likely to bioaccumulate. The concentrations of these contaminants were also variable. Fat was the most contaminated tissue with PAHs, but no significant differences (p-value=0.2288) between the compounds were obtained, although ANT presented higher concentrations than the rest of contaminants. The reasons why certain PAHs were detected in higher or lower levels in according organs may be explained because their chemical properties, as PAHs are hydrophobic, having high sorption capacity in oils, thus abdominal fat is the tissue having a higher bioaccumulation, followed by brain and liver, which are the tissues having more lipid contents. Furthermore, ACE, FLE, ANT and PHN, having less than four aromatic rings, were the dominant are more bioaccumulated compounds. These results agree with those found by other authors. Zhang et al.21 determined 16 PAHs in human whole blood and found that the dominant PAHs were LMW-PAHs (2–4 rings), including naphthalene, acenaphtene, ACE, FLE, PHN, ANT, fluoranthene and PYR, while HMW-PAHs were found at lower concentrations. A similar tendency was found by Yamamoto et al.12 in hair, ANT, naphthalene and BaA showing considerably higher concentrations in smokers. High concentrations of both carcinogenic and non-carcinogenic PAHs were found in lung tissues from 31 patients diagnosed with lung cancer by Cioroiu et al..14 The presence of PAHs in placenta indicated the extent to which neonates are exposed to PAHs.22 Hernández et al.27 found naphthalene, PHN, fluoranthene and pyrene in human breast adipose tissues.


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As a conclusion, the results obtained in this study for the bioaccumulation of PAHs in forensic samples obtained from autopsies are very close to those of other studies using different human organs, confirming a higher frequency for LMW-PAHs. Classification of the cases according to age using multivariate discriminant analysis An attempt was made to select the cases with a similar distribution between the ages and sex, thus 4 cases of ages below 50 and 4 cases of ages over 50 were achieved. However, a similar distribution for sex was difficult, and more samples from autopsies were impossible to obtain for this first study. An ANOVA test was applied to compare the total PAH concentration between the autopsies of individuals with ages below 50 (4 cases) and over 50 years (4 cases). There were no significant differences at the 95% confidence level (F-ratio=0.630; pvalue=0.4587) between the groups. A principal component analysis (PCA) was applied to show the natural clustering of samples between both age groups using the individual concentration of each PAH. The score plot led to a similar conclusion, as no separation between both age groups was observed. Therefore, data was used to carried out an orthogonal partial least squares discriminant analysis (OPLSDA) that allows the classification of each kind of sample. OPLS-DA models showed two well differentiated groups (Fig. 3). Then, contribution plots were obtained in order to see the most influential variables in the classification. As shown in Supplemental Fig. S1, FLE and BgP were detected at higher concentrations in autopsies of persons aged above 50 years, while the rest of compounds predominated in autopsies of persons under 50 years.

Classification of the cases according to sex In this case, the data were not homogeneous because the number of persons in each group differed: 6 men and only 2 women. However, simply for an approximate idea, the same tests (ANOVA, PCA and OPLS-DA) as those used in the previous classification, were applied. The ANOVA test was applied by comparing the total PAH concentration between the groups of autopsies of persons with different sex. There were no significant differences at the 95% confidence level (F-ratio=0.00; p-value=0.9473) between the groups. However, the directed analysis OPLS-DA found differences between the groups and therefore provided a classification (Fig. 4). Contribution graphs were again constructed in order to know how the OPLS-DA test established the classification. As shown in Supplemental Fig. S2, ACE, PHN, BbF and BgP were detected in higher concentrations in autopsies of women that in autopsies of men, a conclusion that needs to be confirmed using a greater number of samples. CONCLUSIONS

The GC–MS technique in combination with SALLE and DLLME techniques is a valuable tool to discriminate a range of PAH toxicants of interest in environmental forensic studies. The present work is the first study on PAH contamination in different organs obtained from autopsies. Fat showed the highest PAH bioaccumulation capacity, while ACE tended to accumulate in liver and BbF in brain. The bioaccumulation of PAHs in forensic samples obtained from autopsies confirmed the higher frequency of low molecular weight PAHs. The application of OPLS-DA tests to the data permitted the classification into two groups of cases well differentiated by age and sex. However, more cases should be studied to stablish more rigorous conclusions.



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Acknowledgements The authors acknowledge the financial support of the Comunidad Autónoma de la Región de Murcia (CARM, Fundación Séneca, Project 19888/GERM/15), the Spanish Ministry of Science, Innovation and Universities (Project PGC2018-098363-B-I00) and the European Commission (FEDER/ERDF). M. Pastor-Belda acknowledges a fellowship from Fundación Séneca, CARM.

Compliance with ethical guidelines Conflict of Interest The authors declare that they have no conflict of interest. Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee (the consent for autopsies to use organs obtained from cadavers for this study has been approved by the Research Ethical Committee of the University of Murcia, Favourable Inform ID: 1841/2018) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. REFERENCES (1) Medeiros, P.M., Simoneit, B.R.T. (2007) Gas chromatography coupled to mass spectrometry for analyses of organic compounds and biomarkers as tracers for geological, environmental, and forensic research. J. Sep. Sci. 30, 1516–1536. (2) O'Reilly, K.T., Pietari, J., Boehm, P.D. (2013) Parsing pyrogenic polycyclic aromatic hydrocarbons, forensic chemistry, receptor models, and source control policy. Integr. Environ. Assess. Manage 1, 279–285. (3) Retnam, A., Zakaria, M.P., Juahir, H., Aris, A.Z., Zali, M.A., Kasim, M.F. (2013) Chemometric techniques in distribution, characterisation and source apportionment of polycyclic aromatic hydrocarbons (PAHS) in aquaculture sediments in Malaysia. Marine Pollution Bull. 69, 55–66. (4) Mahboob, S., Sultana, S., AlGhanim, K.A., Al-Misned, F., Sultana, T., Hussain, B., Ahmed, Z. (2017) Distribution and accumulation of polychlorinated biphenyls (PCB), polycyclic aromatic hydrocarbons (PAHs) and organo-chlorine residues in the muscle tissue of Labeo rohita. Int. J. Agric. Biol. 19, 701–706. (5) Kielbasa, A., Buszewski, B. (2017) PAHs in animal tissues ? the analytics of PAHs in new reference materials and their homogeneity. Anal. Methods 9, 76–83. (6) International Agency for Research on Cancer (IARC), 2008. List of IARC Evaluations. International Agency for Research on Cancer, Lyon, France. . (7) International Agency for Research on Cancer (IARC), 1986. Monographs on the Evaluation of the Carcinogenic Risk of Chemicals to Humans, vol. 38. Lyon, France, pp. 389–394 (Appendix 2).


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spectrofluorimetric determination. Talanta 66, 683–690. (33) Cloutier, P.L., Fortin, F., Groleau, P.E., Brousseau, P., Fournier, M., Desrosiers, M. (2017) QuEChERS extraction for multi-residue analysis of PCBs, PAHs, PBDEs and PCDD/Fs in biological samples. Talanta 165, 332–338. (34) Cacho, J.I., Campillo, N., Viñas, P., Hernández-Córdoba, M. (2016) Evaluation of the contamination of spirits by polycyclic aromatic hydrocarbons using ultrasound-assisted emulsification microextraction coupled to gas chromatography–mass spectrometry. Food Chem. 190, 324–330. (35) Commission decision of 12 August 2002 implementing Council Directive 96/23/EC concerning the performance of analytical methods and the interpretation of results, Off. J. Eur. Communities L221 (2002) 8-36.

Table 1 GC-MS characteristics of PAHs and method performance Table 2 Summary of the occurrence of the studied PAHs: percentage of positive samples, mean concentration and range of found concentrations Table 3 Comparison of method performance

Figure Legends

Fig. 1 Comparison of different extraction methods for PAHs using ACN Fig. 2 Chromatogram for both a standard solution mixture (A) and a fortified kidney sample (B). The concentration of PAHs are 25 ng g-1 Fig. 3 OPLS-DA model for age discrimination Fig. 4 OPLS-DA model for sex discrimination

Electronic supplementary material

Supplemental Table S1 Autopsies details Supplemental Table S2 PAHs concentration in the organs analyzed Supplemental Fig. S1 Contribution graphs for ages under and over 50 years Supplemental Fig. S2 Contribution graphs for sex variable


Chemical Research in Toxicology 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46

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Table 1 GC-MS characteristics of PAHs and method performance tR (min)

Target ion (m/z)

Confirmation ions Q1 , Q2 (m/z)

Slope, (g ng1)

Linearity range (ng g-1)

LODa (LOQ)b (ng g-1)

Enrichment Factor

Intraday RSDc (%)

Interday RSDc (%)

Biphenyl (BPH, IS)

7.94

154

153, 152

--

--

--

--

--

--

Acenaphthylene, ACE

8.69

152

151, 150

0.0328

0.5-200

0.054 (0.18)

64

4.7

8.3

Fluorene, FLE

10.02

166

165, 83

0.0429

0.5-200

0.041 (0.14)

122

3.8

7.5

Phenanthrene, PHN

13.15

178

176, 179

0.0529

0.5-200

0.033 (0.11)

119

5.2

10.2

Anthracene, ANT

13.40

178

176, 179

0.0358

0.5-200

0.050 (0.16)

111

7.3

12.7

Pyrene, PYR

19.28

202

101, 200

0.0557

0.5-200

0.032 (0.11)

102

6.1

11.8

Benz(a)anthracene, BaA

28.15

228

114, 226

0.0838

28.45

228

114, 226

0.5-200

0.021 (0.071)

111

Chrysene, CHR

8.2

13.2

Benzo(k)fluoranthene, BkF

35.48

252

126, 250

89

7.2

12.7

35.48

252

126, 250

0.5-200

0.019 (0.066)

Benzo(a)pyrene, BaP Benzo(b)fluoranthene, BbF

36.55

252

126, 250

0.0135

0.5-200

0.13 (0.44)

55

7.7

12.8

Benzo(g,h,i)perylene, BgP

41.11

276

138, 277

0.0596

0.5-200

0.030 (0.099)

90

8.1

12.3

Dibenz(a,h)anthracene, DBA

41.32

278

139, 279

0.0557

0.5-200

0.032 (0.11)

99

7.0

11.3

Indeno(1,2,3-cd)pyrene, IND

42.25

276

138, 277

0.0455

0.5-200

0.039 (0.13)

80

7.6

10.2

Compound

a S/N=3; b

S/N=10;

0.0893

c n=8


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Table 2 Summary of the occurrence of the studied PAHs: percentage of positive samples, mean concentration and range of found concentrations ACE

Range (ng g-1)

---

FLE 0.851  0.26 0.426-1.373

Incidence (%)

0.0 0.745  0.83 0-2.066

100.0 0.735  0.36 0-1.215

87.5 0.698  0.39 0-1.473

87.5 0.145  0.19 0-0.597

25.0

---

12.5 0.195  0.35 0-1.016

Range (ng g-1)

50.0 0.202  0.53 0-1.616

88.0 0.663  0.28 0-0.966

88.0 0.784  0.51 0-1.958

62.5 0.214  0.17 0-0.469

0.0 0.017  0.03 0-0.080

25.0 0.063  0.17 0-0.502

62.5 0.084  0.07 0-0.188

75.0 0.614  0.53 0-1.716

Incidence (%)

12.5

g-1)

ND

100.0 0.489  0.22 0.121-0.817

75.0 0.152  0.17 0-0.491

25.0 0.004  0.01 0-0.030

12.5 0.076  0.14 0.076-0.381

75.0 0.059  0.04 0-0.133

75.0 0.896  0.49 0-2.029

g-1)

Mean (ng Brain

Mean (ng g-1) Liver

Range (ng g-1) Incidence (%) Mean (ng g-1)

Lung

Fat

BaA+CHR 0.074  0.19 0-0.593

BkF+ BaP 0.165  0.21 0-0.630

BbF 1.351  1.10 0.482-4.166

BgP 0.028  0.07 0-0.221

DBA 0.689  1.71 0-5.224

IND

87.5 0.159  0.31 0-0.960

100.0 0.579  0.45 0-1.421

12.5

37.5

0.0

ND

ND

ND

---

---

---

0.0

0.0 0.123  0.23 0-0.730

0.0 0.085  0.22 0-0.677

---

37.5 0.075  0.10 0-0.263

12.5 0.203  0.34 0-0.965

0.0

37.5

ND

ND

ND

ND ---

---

Incidence (%)

0.0 0.149  0.39 0-1.195

100.0 1.001  0.49 0.364-1.912

100.0 0.757  0.17 0.533-1.21

62.5 0.178  0.12 0-0.332

12.5 0.031  0.08 0-0.235

25.0 0.056  0.11 0-0.322

87.5 0.029  0.04 0-0.128

100.0 0.466  0.59 0-1.737

Incidence (%)

12.5

Mean (ng g-1)

ND ---

100.0 1.056  0.77 0-2.420

75.0 2.774  6.18 0-19.093

25.0 0.032  0.08 0-0.252

25.0 0.220  0.58 0-1.763

50.0 0.116  0.08 0-0.227

50.0 0.349  0.45 0-1.329

ND

Range (ng g-1)

100.0 1.023  0.71 0-2.639

Incidence (%)

0.0

Mean (ng g-1)

ND

88.0 0.367  0.17 0.146-0.653

62.5 0.069  0.06 0-0.176

12.5 0.025  0.06 0-0.197

12.5 0.085  0.22 0-0.682

87.5 0.117  0.09 0-0.236

100.0

62.5

12.5

12.5

87.5

Range (ng

g-1)

Range (ng g-1)

---

88.0 0.548  0.12 0.356-0.724

Incidence (%) ND means No Detected

0.0

100.0

Spleen

PYR 0.047  0.10 0-0.313

Range (ng g-1) Mean (ng g-1)

Heart

ANT 0.256  0.16 0-0.601

88.0 0.748  0.53 0.045-1.874

Mean (ng Kidney

ND

PHN 0.685  0.29 0-0.988

0.0 ND

ND ---

---

---

37.5 0.278  0.39 0-1.008

0.0

---

0.0 0.035  0.09 0-0.281

37.5 0.341  0.48 0-1.345

50.0 0.391  0.31 0-0.931

0.0 0.041  0.11 0-0.324

12.5 0.045  0.12 0-0.360

37.5 0.104  0.27 0-0.834

75.0

12.5

12.5

12.5


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Page 16 of 20

Table 3. Comparison of method performance PAHs analyzed

Sample

Sample preparation (time)

Detection system

Sensitivity

Precision (%)

Accuracy (%)

Ref.

6

Animal and fish tissues

QuEChERS (35 min)

GC-MS

0.24-0.30 ng g-1

0.13-0.88

91-123

[5]

17

Human hair

UAE and SPME (105 min)

HPLC-FLD

0.5–20 pg mL-1

0.3-13.7

70.1–113.3

[12]

16

Human lung tissues

ASE and SPE

HPLC-DAD and HPLC-FLD

0.25- 23.23 pg µL-1

2.34-8.52

62-120

[14]

16

Mussels

Digestion, LLE and clean up (6 h)

GC-MS

-

2.1-27.45

71.7-113.6

[18]

10

Crab tissue

SFE (25 min)

GC-MS

93-103

[19]

16

Human blood

PT-SPE (8 min)

GC–MS

0.002-0.04 µg L-1

2.27-9.89

85.0-115

[21]

9

Human placenta

PLE and SPE (50 min)

GC–MS/MS

0.0025-0.24 ng g-1

4-11

69-94

[22]

15

Human adipose tissue

LLE and GPC (75 min)

GC–MS/MS

0.10-5.30 µg kg-1

8.48-0.1

82-129

[24]

24

Feeds and fish tissues

QuEChERS and clean up (3 h)

GC-QTOF-MS

0.005-0.05 mg kg-1

-

-

[26]

4

Human breast tissues

SPE (30 min)

GC-TOF-MS

-

-

-

[27]

13

Trout liver

Soxhlet extraction and clean up (20 h)

GC-MS

-

-

-

[29]

Mussel and salmon QuEChERS, GPC and SPE GC-MS 0.05-0.25 µg k-1 4-7 52-114 tissues (45 min) Human organs and SALLE-DLLME 13 GC-MS 0.030-0.131 ng g-1 3.8-13.7 89-110 tissues (15 min) PT-SPE: On pipette-tip solid phase extraction; ASE: Automatic solvent extraction; SFE: Supercritical fluids extraction; GPC: Gel permeation chromatography 10

[32] This work


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Fig. 1 Comparison of different extraction methods for PAHs using ACN 547x311mm (96 x 96 DPI)

ACS Paragon Plus Environment


Figure 2. Chromatogram for both a standard solution mixture (A) and a fortified kidney sample (B). The concentration of PAHs are 25 ng g-1 192x116mm (96 x 96 DPI)


Page 18 of 20

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Fig. 3 OPLS-DA model for age discrimination 132x67mm (96 x 96 DPI)



Fig. 4 OPLS-DA model for sex discrimination 147x74mm (96 x 96 DPI)


Page 20 of 20

Bioaccumulation of Polycyclic Aromatic Hydrocarbons for Forensic

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