Adductomic Screening of Hemoglobin Adducts and ... - ACS Publications

Article pubs.acs.org/crt

Adductomic Screening of Hemoglobin Adducts and Monitoring of Micronuclei in School-Age Children Henrik Carlsson,† Jenny Aasa,† Natalia Kotova,‡ Daniel Vare,‡ Pedro F. M. Sousa,† Per Rydberg,§ Lilianne Abramsson-Zetterberg,‡ and Margareta Törnqvist*,† †

Department of Environmental Science and Analytical Chemistry, Stockholm University, SE-106 91 Stockholm, Sweden Swedish National Food Agency, SE-751 26 Uppsala, Sweden § Department of Oncology-Pathology, Karolinska Institute, SE-171 77 Stockholm, Sweden ‡

S Supporting Information *

ABSTRACT: Electrophilic compounds/metabolites present in humans, originating from endogenous processes or exogenous exposure, pose a risk to health effects through their reactions with nucleophilic sites in proteins and DNA, forming adducts. Adductomic approaches are developed to screen for adducts to biomacromolecules in vivo by mass spectrometry (MS), with the aim to detect adducts corresponding to unknown exposures from electrophiles. In the present study, adductomic screening was performed using blood samples from healthy children about 12 years old (n = 51). The frequencies of micronuclei (MN) in erythrocytes in peripheral blood were monitored as a measure of genotoxic effect/genotoxic exposure. The applied adductomic approach has been reported earlier by us and is based on analysis of N-terminal valine adducts in hemoglobin (Hb) by liquid chromatography tandem mass spectrometry (LC-MS/MS). High resolution MS was introduced for refined screening of previously unknown N-terminal Hb adducts. Measured adduct levels were compared with MN frequencies using multivariate data analysis. In the 51 individuals, a total of 24 adducts (whereof 12 were previously identified) were observed and their levels quantified. Relatively large interindividual variations in adduct levels were observed. The data analysis (with partial least-squares regression) showed that as much as 60% of the MN variation could be explained by the adduct levels. This study, for the first time, applies the combination of these sensitive methods to measure the internal dose of potentially genotoxic chemicals and genotoxic effects, respectively. The results indicate that this is a valuable approach for the characterization of exposure to chemical risk factors for the genotoxic effects present in individuals of the general population.

■

INTRODUCTION

We have reported earlier on the development and application of an adductomic approach for the screening of adducts to Nterminal valine (Val) in hemoglobin (Hb) in human blood samples.7 The method is based on the FIRE procedure, a modified Edman procedure in which adducts to N-terminals in Hb are measured by liquid chromatography−tandem mass spectrometry (LC-MS/MS).8 In the screening of human blood, we detected 19 unknown adducts and 7 previously identified adducts.7 In subsequent studies, five of those unknown adducts were identified to correspond to the electrophilic precursors ethyl vinyl ketone,9 glyoxal, methylglyoxal, acrylic acid, and 1octen-3-one.10 The proposed sources of exposure to these electrophiles are food and/or endogenous formation.9,10 It is of particular importance to clarify the exposure to unwanted substances among children. Children are more vulnerable to adverse environmental exposure than adults, for instance, because of the risk of developing diseases at different developmental stages.4,11 Furthermore, the requirement of

Exposures from endogenous processes (e.g., oxidative stress and lipid peroxidation) and exogenous sources (e.g., food and air pollution) are indicated to contribute to a large fraction of cancer incidences and other chronic diseases in humans.1−3 With regard to exposure from chemicals, children are considered more susceptible than the adult population.4 One fraction of the chemical exposure consists of chemical compounds or metabolites which are electrophiles and which contribute to a risk of health effects through their reactions with biomacromolecules. The presence of such reactive compounds in vivo may be studied through their reaction products (adducts) with abundant proteins in blood or with DNA by methods based on mass spectrometric (MS) detection. In recent years, methods have been introduced for screening of unknown adducts, defined as adductomics.5,6 The aim of adductomics is to detect and identify adducts, to trace their precursors and exposure sources, and ultimately to disclose factors of importance for health, and also to find biomarkers of exposure. © 2017 American Chemical Society

Received: December 22, 2016 Published: April 11, 2017 1157

DOI: 10.1021/acs.chemrestox.6b00463 Chem. Res. Toxicol. 2017, 30, 1157−1167

Article

Chemical Research in Toxicology

Figure 1. Overview of the methodology for sample preparation and screening of adducts by LC-MS/MS.

Therefore, an association of quantified adducts with measured MN frequencies might indicate adducts which are interesting in this respect. The present study also aims to estimate the potential of the adductomic approach as such, and in combination with measurement of MN frequency, to reveal genotoxic exposure. The present study comprises a larger group of individuals, more homogeneous regarding age, than used before in screening of Hb adduct profiles. Since the results are based on the blood samples from randomly chosen healthy volunteers, we assume that the levels of biomarkers reflect the outcome of normal exposure and normal physiological conditions of the individuals.

energy and water per body weight is higher in children, which also would result in higher intake of toxicants, estimated to be up to several times higher from food and water in small children compared to that in adults.11 Hb adducts represent a sensitive biomarker of exposure which measure exposure to specific, potentially genotoxic, electrophilic compounds. The frequency of micronuclei (MN), measured in the very youngest erythrocytes, represents a sensitive biomarker of genotoxic effect12 and could also often be interpreted as a measure of the total genotoxic exposure. Therefore, it is of great value to be able to use these sensitive biomarkers for human biomonitoring in the same blood samples, in an effort to monitor and characterize the body burden of toxic chemical compounds or their metabolites, for instance, in children.13 The present investigation is part of a study in which food consumption and exposure in school-age children are studied, through questionnaires and analysis of biomarkers/metabolites. The present study concerns a subgroup from this cohort (n = 51), selected on the basis of measured frequencies of MN, as a biomarker for genotoxic effect.12 The blood samples from these individuals were then screened for internal exposure to electrophilic compounds/metabolites through measurement of adducts to N-terminals in Hb, using the FIRE procedure. As a first step, high resolution mass spectrometry (HRMS) was used for adductomic screening in a small number of samples (n = 6), to search for unknown Hb adducts, not observed in our earlier screening experiments. Then, targeted screening was used to determine the observed adducts in all of the blood samples. The aim was to characterize the exposure and to investigate possible associations between adduct levels and MN frequencies measured in the samples. Adductomics often aims to detect and identify adducts that could be associated with genotoxic damage and cancer.

■

MATERIALS AND METHODS

Chemicals. The analytical standards corresponding to fluorescein thiohydantoin (FTH) derivatives of adducts from acrylamide (AA), glycidamide (GA), and ethylene oxide (EO) were previously synthesized from respective N-substituted valine/d7-valine and stored in acetonitrile (ACN)/H2O (1:1, v/v) at −20 °C until use.8 The following FTH standards were used: fluorescein-5-yl-[4-isopropyl-3(2-carbamoylethyl)-2-thioxo-imidazolidin-5-one] (AA-Val-FTH), fluorescein-5-yl-[4-d7-isopropyl-3-(2-carbamoyl-2-hydroxyethyl)-2-thioxoimidazolidin-5-one] (GA-d7-Val-FTH), fluorescein-5-yl-[4-d7-isopropyl-3-(2-carbamoylethyl)-2-thioxo-imidazolidin-5-one] (AA-d7-ValFTH), and fluorescein-5-yl-[4-d7-isopropyl-3-(2-hydroxyethyl)-2-thioxo-imidazolidin-5-one] (EO-d7-Val-FTH). Fluorescein-5-isothiocyanate (Isomer I, Reagent grade) was obtained from Karl Industries (Aurora, OH, USA). For the micronucleus test, magnetic beads (CELLection Pan Mouse IgG Kit) were purchased from Dynal (Oslo, Norway). The mouse antihuman CD71 antibody was purchased from DakoCytomation (Glostrup, Denmark). The fluorescent dye Hoechst 33342 was from Sigma-Aldrich (St. Louis, MO, USA) and Thiazole Orange from Molecular Probes (Eugene, OR, USA). All other chemicals and solvents were of analytical grade and obtained from Sigma-Aldrich. 1158


Article


Figure 2. Example of adduct selection from DIA data. Selected ion chromatograms (XICs) for FTH derivatives of three N-terminal Hb adducts observed in a single run; adducts from (A) methyl vinyl ketone, (B) acrylamide, and (C) acrylic acid. D−F show the XICs for the three diagnostic fragments used to qualify compounds as adducts. The methyl vinyl ketone adduct exhibits all three fragments (17.38 min), whereas the acrylamide (13.65 min) and acrylic acid (15.22 min) adducts only exhibit the m/z 445 and m/z 489 fragments. Note that the compound with a similar m/z value to that of the acrylamide adduct observed at 14.77 min does not correspond to an adduct derivative. Equipment and Material for Sample Preparation for Adduct Measurements. Solid phase extraction (SPE) cartridges Oasis Max (3 cc, 60 mg, 60 μm; mixed mode anion exchange) were obtained from Waters (Milford, MA, USA). The Hb analyzer (Hb 201+) was obtained from HemoCue (Ä ngelholm, Sweden). Bovine blood used for calibration samples was purchased from Håtunalab AB (Bro, Sweden). Study Population. The blood samples were from a study regarding food-related exposure in school-age children performed by the Swedish National Food Agency (with ethical permission from the Regional Ethical Review Board, Uppsala, Sweden; ref nr. 2013/354). The blood samples had been collected (at one occasion for each individual venous blood was collected in Vacutainer tubes) from 300 healthy, nonfasting, children (about 50% of each gender), about 12 years old. After collection, the sample tubes were rocked gently 5−10 times. Samples to be used for adduct measurement were centrifuged at 1500g for 10 min after 30 min at room temperature and red blood cells (RBCs) and serum were separated, followed by storage at −20 °C. From the cohort, the frequency of micronuclei (fMN) was measured in 150 randomly selected samples, and 51 of these were chosen for targeted screening of Hb adducts. The samples were selected without knowing any details of the participants. The choice of the 51 blood samples was made in order to obtain a wide range of fMN, resulting in samples from about 1/3 girls and 2/3 boys. Reference adult blood samples, used to check the repeatability of the adduct method and measurements, were obtained from Komponentlab at Karolinska University Hospital (Stockholm, Sweden). Micronucleus Assay. The applied sensitive assay to determine micronucleated erythrocytes in humans is performed on transferrin positive reticulocytes, Trf-Ret, according to previously described methods.12,14 Trf-Ret are the very youngest erythrocytes in the peripheral blood system, recently entered from the bone marrow. A volume of 1.5 mL of whole blood from each participant was used and mixed with 45 μL of magnetic beads (CELLection TM Pan Mouse IgG Kit) precoated with mouse antihuman CD71 antibody. Cells were stained with Hoechst 33342 and Thiazole Orange dissolved in PBS (37 °C, 1 h). A flow cytometer (FACSVantage SE from BD Immunocytometry systems, Sunnyvale, CA, USA), equipped with both an argon ion laser operating at 488 nm and an UV laser operating at 350 nm (Enterprise II, Coherent, Santa Clara, CA, USA), was used for the measurements at a rate of 500−1000 cells/s. A mean of 200 000 Trf-Ret was determined per sample. CellQuest software (BD BioSciences) was used for data acquisition.

Sample Preparation Prior to Adduct Measurement. The Hb adducts were measured according to the FIRE procedure (Figure 1).8,15,16 Prior to detachment and derivatization of adducts with fluorescein isothiocyanate (FITC), the Hb content was measured in the samples. The derivatization and workup procedure were performed as described previously, with minor adjustments.7 A volume of 250 μL of RBCs per sample was used. The final sample volume, prior to analysis, was 50 μL (40% ACN in H2O). All 51 samples were analyzed by LC-MS/MS using targeted screening. Six samples were randomly selected for untargeted adduct screening by high resolution MS (HRMS) prior to the targeted screening. To check the repeatability of the targeted approach, ten replicates of samples from two individuals (reference adult blood samples) were processed and analyzed according to the procedure. Liquid Chromatography Mass Spectrometry (LC-MS). Two mass spectrometers were used in this study: a high resolution MS (HRMS) instrument was used for untargeted screening of adducts and a triple quadrupole instrument was used for targeted analysis. Chromatography, i.e., choice of column, gradient, mobile phases, etc., was performed as described previously.7,9 Screening of Unknown Adducts Using LC-HRMS. The LCHRMS system used consisted of a Dionex UltiMate 3000 LC system interfaced to an Orbitrap Q Exactive HF mass spectrometer (Thermo Fisher Scientific, MA, USA). The MS instrument was used with the following tuning parameters: spray voltage, 4 kV; capillary temperature, 275 °C; sheath gas, 20 arbitrary units (au); auxiliary gas, 10 au; S-Lens RF level, 60%; probe heater temperature, 240 °C. The parameters were optimized manually for maximal signal intensity using infusion of a tuning solution containing three internal standards corresponding to adducts from acrylamide (AA), glycidamide (GA), and ethylene oxide (EO) (AA-d7-Val-FTH, GA-d7-Val-FTH, and EOd7-Val-FTH, respectively), at the same flow rate as that used in the LC method (0.12 mL/min). The screening was performed in the data independent acquisition (DIA) mode, with each sample injected repeatedly four times (10 μL) to cover the entire m/z range, ranging from 500−700 m/z (m/z, mass-to-charge ratio), and to get a sufficient number of data points per peak. In each injection, 50 m/z was covered, e.g., the m/z range of the first method used was 500−550 m/z, divided in 10 discrete m/z ranges in the inclusion list, e.g., covering 500−505, 505−510, etc. The resolution 3 × 104 and the inclusion window 6 m/z were used, in order to get a small overlap between the specified ranges in the inclusion list. The normalized collision energy (NCE) was 45. The 10 5 m/z ranges specified in the inclusion lists were looped, and before the next cycle of DIA measurements, a full-scan experiment was performed with resolution 12 × 104, scanning the range 450−700 m/z. 1159


Article

Chemical Research in Toxicology The time for a full cycle, i.e., 10 DIA scans and a full-scan, was 1.2 s, thus giving 10 measurements over a 12 s wide peak (a peak width common for adducts at low levels). The analyses were performed in positive ion and profile scan modes. The results of the screening were evaluated using XCalibur software (Thermo Fisher Scientific). To select adduct candidates, the data were manually evaluated by monitoring compounds giving the fragments m/z 445.1, m/z 460.1, and m/z 489.1 (using accurate masses m/z 445.0489, m/z 460.0724, and m/z 489.1115, monitored with a 5 ppm mass tolerance) common for FTH derivatives of Val adducts (Figure 2).7 Each 5 m/z range in the inclusion lists was evaluated separately and the corresponding full-scan spectra were used for confirmation. Compounds exhibiting at least two of the specific fragments were considered to be possible adducts. These compounds were further studied using parallel reaction monitoring (PRM) methods to collect fragmentation patterns of the specific ions, with the resolution 3 × 104. The main difference between the DIA and PRM experiments is a more narrow isolation window when performing PRM. With PRM, only ions of specific m/z (unit resolution) are collected for fragmentation. Targeted Analysis Using Triple Quadrupole LC-MS. The LCMS system used for the targeted analysis consisted of an Acquity UPLC system coupled to a Xevo TQ-S micro mass spectrometer (Waters Corporation, MA, USA). The following settings were used for the MS analysis: capillary voltage, 3.5 kV; cone voltage 80 V; source temperature, 150 °C; desolvation temperature, 450 °C; cone gas flow, 10 L/h; desolvation gas flow, 500 L/h; collision energy, 38 eV. As for the LC-HRMS instrument described above, the tuning was performed using a mixture of internal standards corresponding to the analytes AA-d7-Val-FTH, GA-d7-Val-FTH, and EO-d7-Val-FTH. Multiplereaction monitoring (MRM) was used for the analysis, and for each analyte, two MRM transitions were used (for the adducts from compounds with available internal standards, i.e., AA, GA, EO, one transition was used for the adduct derivative and one for the internal standard). The transitions used corresponded to the adduct-specific fragments exhibiting the highest intensities for the different analytes.7 For the additional unknown adducts observed in the LC-HRMS screening (adducts observed for the first time in this study), a separate injection was done for each sample with three specific fragments monitored for each adduct to strengthen their detection. The MRM transitions used are given in the Supporting Information, Table S1. The dwell time of each transition was 20 ms, positive ionization was used, and data acquisition was performed in profile scan mode. The injection volume was 10 μL (total sample volume was 50 μL). Quantification/Calibration Curve. A semiquantitative approach, assuming that all FTH derivatives of Val adducts will give a similar response in the MS analysis,7 was used for the quantification of adduct levels in the targeted screening. Calibration samples were prepared by adding 0.15−20.0 pmol (n = 8) AA-Val-FTH, diluted in ACN/H2O 4:6, to 250 μL bovine blood (Hb 118 g/L, with a negligible background level of adducts from AA). The calibration standards were added together with the internal standard (AA-d7-Val-FTH) after FITC derivatization of the bovine blood samples during sample preparation. The calibration curve was established from the ratios between peak areas of AA-Val-FTH and AA-d7-Val-FTH, versus the added amount of AA-Val-FTH per sample. The amounts of AA-ValFTH in the calibration samples correspond to adduct levels 5−600 pmol/g Hb (linearity has previously been confirmed up to 10 000 pmol/g Hb).9 To check the repeatability of the method, 10 replicates of each of the two reference blood samples from two adults (a smoker and a nonsmoker) were prepared according to the FIRE procedure and analyzed using the targeted method. The evaluation of data was done using MassLynx software (Waters Corporation, MA, USA). The average peak areas of the monitored transitions were used for the quantification of each adduct, then using the calibration curve for acrylamide adducts and adjustment for the measured Hb concentrations in each blood sample.7 Statistical Evaluation. Partial least-squares (PLS) regression, was performed to compare the adduct levels with the determined MN frequencies. PLS regression, also known as projection on latent

structures, is considered the major regression technique for multivariate data.17 Unlike multilinear regression models, it may generate predictive models when there is a lack of information in the data. These predictions are essentially statistical. New abstract variables, designated as latent variables or factors, are determined taking the direction of the maximum covariance between the predictor variables and responses (adduct levels and fMN, respectively). This is performed sequentially, by deflating the data explained by each latent variable, until all covariance has been explained. However, modeling the data at 100% generally results in overfitting, i.e., the excess of latent variables result in a total modeling of the calibration data (adduct levels and fMN) but will produce poor predictions on other data that were not included in the model. To overcome this problem, crossvalidation is employed. This is done by calibrating with part of the data and predicting the other part of the data. The optimal number of latent variables in a model is determined when the cross-validation results begin to get worse, i.e., when overfitting of the data starts to occur. In the present study, a PLS regression model was employed on the 51 samples, taking into account the 24 measured adducts as variables and the fMN as the response using Unscrambler X v10.3 software (Camo Software, Oslo, Norway). Different data pretreatment methods were tested. The best results were obtained by standardizing, i.e., dividing the data by the standard deviation of their respective columns, and no mean centering. The cross-validation method used was “leaveone-out”, i.e., each response was predicted from the calibration of the rest of the samples.

■

RESULTS A Priori Unknown Adducts Observed with LC-HRMS. From the screening by HRMS of the six randomly selected samples, five probable adducts which were not detected in our previous adductomic screening were observed.7 The precursor ions ([M + H]+) of the five analytes are m/z 519.0865 (rt 12.3 min), m/z 519.0685 (rt 15.7 min), 651.1651 (rt 11.2 min), 659.2067 (rt 16.4 min), and 686.3256 (rt 11.2 min) (Figure S1). By subtracting the theoretical m/z corresponding to the fluorescein thiohydantoin (FTH) derivative of unmodified valine, m/z 489.1115, from the [M + H]+, the masses of the adducts were calculated (Table 1). The FTH derivatives Table 1. Unidentified Adducts Observed during Screening with Orbitrap MS in the m/z Range 500−700 observed m/z

rt (min)

adduct mass (Da)a theoretical log Pb

estimated

519.0865 519.0685 651.1651 659.2067 686.3256

12.3 15.7 11.2 16.4 11.2

29.9750 29.9570 162.0536 170.0952 197.2141

3.4 4.4 3.0 4.6 3.0

observed diagnostic fragments (m/z) 445, 445, 445, 445, 445,

460 460 460, 489 489 460, 489

a

Adduct mass was calculated by subtracting 489.1115 (theoretical m/z of fragment corresponding to FTH derivative of unmodified Val) from the m/z of the [M + H]+. bTheoretical log P estimated through comparisons of retention times and theoretical log P values of identified adducts.

corresponding to previously identified adducts (n = 12) were used as reference points, and their theoretical log P values (i.e., logarithmic partition coefficients, used as a measure of lipophilicity for chemical compounds; calculated by ChemBioDraw Ultra 12.0 from CambridgeSoft (Cambridge, MA, USA)) were plotted against their retention times (rt). The linear regression of the data (log P = 0.30rt − 0.34; R2 = 0.89) was then used to estimate the theoretical log P values of the five unknowns (Table 1). Theoretical log P values are an aid in the identification of unknown adducts when using reversed phase 1160


Article

Chemical Research in Toxicology Table 2. Estimated Mean and Range of Adduct Levels, Observed in Blood Samples from Children (n = 51) [M + H]+ m/z

identity/precursora

rt (min)

mean conc. ± SDb (pmol/g Hb)

range (pmol/g Hb)

detected out of 51 (n)

503.1 517.1 519.1 519.1 533.1 547.1 559.1 560.1 561.1 561.1 563.1 573.1 576.1 577.1 593.1 595.1 595.1 615.1 617.1 625.1 631.1 651.1 659.1 686.1

methylation ethylation unknown unknown ethylene oxide carboxymethylation/glyoxal methyl vinyl ketone acrylamide acrylic acid/carboxyethylation methylglyoxal glycidol ethyl vinyl ketone glycidamide unknown unknown unknown unknown 1-octen-3-one unknown unknown unknown unknown unknown unknown

16.6 17.9 12.3 15.7 14.1 14.2 16.6 12.9 14.5 12.6 12.4 18.1 12.2 13 11.3 15.1 17 22.2 14.8 13.9 15.2 11.2 16.4 11.2

2100 ± 780 8±3 57 ± 54 26 ± 11 15 ± 9 1100 ± 520 130 ± 58 30 ± 15 120 ± 55 21 ± 14 8±2 59 ± 38 32 ± 19 130 ± 77 18 ± 10 21 ± 10 160 ± 120 110 ± 57 45 ± 24 100 ± 70 100 ± 62 830 ± 480 39 ± 24 69 ± 46

590−3800 n.d.c−13 n.d.c−290 5−55 n.d.c−41 210−2400 34−270 5−61 38−240 n.d.c−55 n.d.c−14 6−230 n.d.c−110 11−390 5−40 8−55 28−710 27−290 8−110 17−300 10−300 190−2300 n.d.c−110 8−190

51 34 48 51 35 51 51 51 51 44 10 51 48 51 51 51 51 51 51 51 51 51 47 51

a

The names of identified adducts or known/probable precursors are in bold. bMean conc. and SD calculated for the samples in which the adduct was detected. cn.d. = not detected. The limit of detection (LOD) for most of the analytes is ∼5 pmol/g Hb.

Results of Targeted Screening. The determined adduct levels of the 24 known and unidentified adducts observed in the analyzed blood samples (n = 51) are presented in Table 2. To illustrate the range of adduct levels, the lowest and highest levels of all adducts in all subjects are shown in an adductome map format in Figure 3. The variation in adduct levels shows a difference of a factor >10 between the highest and lowest levels in the 51 individuals for 17 out of the 24 adducts. A mean relative standard deviation (RSD) in adduct levels of about 20% for all adducts with mean levels above 10 pmol/g Hb (corresponding to the average limit of quantification) was observed in the analysis of 10 replicates of blood samples from two individuals (range of RSD: 14−25%). Micronuclei Frequencies and Statistical Evaluation. The measured MN frequencies, fMN, in the 51 samples ranged from 0.01−0.72%, with a mean of 0.1% and a standard deviation of ±0.13%. This mean fMN is about the same as that found in earlier studies of adults.12,14,18 A PLS regression model was employed for the 51 samples, using the 24 measured adducts as variables and the fMN as the response. Prior to the modeling, two different data pretreatment methods were performed, scaling (dividing the data by the standard deviation of the respective columns) with centering and scaling without centering of the data. A better model was achieved when not centering the data, with coefficients of determination for calibration and cross-validation for the first two latent variables of 61% and 45%, respectively (Supporting Information, Figure S3), while centering of the data resulted in the coefficients 39% and 12%, respectively. When modeling measurement data on both predictors and responses, there are often errors associated with both blocks, and mean centering may reduce the correlation between predictors and responses depending on the data. Additional

chromatography, as they may be matched with observed retention times and strengthen hypotheses on adduct structures. A strategy for identifying unknown Hb adducts involving the use of theoretical log P values was recently successfully applied in the identification of four previously unknown adducts detected through adductomic screening.10 High resolution MS data provide a good basis for the qualification and disqualification of adduct candidates in the screening of adducts. The analytes with [M + H]+ m/z 520, 550, 561 (several adduct derivatives have m/z 561 as the precursor ion, e.g., adducts corresponding to acrylic acid and methylglyoxal; this refers to a late-eluting species), 575, 580, and 608, previously considered adduct derivatives,7 were indicated less likely as true adducts according to the accurate mass spectra obtained from the Orbitrap experiments presented here. This is due to inconsistent fragmentation, exhibiting fragments that are close to the diagnostic fragments in m/z but not exhibiting the accurate masses (examples shown in Figure S2). These analytes are not included in the Results section. However, they should not be excluded from future considerations since there might be exceptions that FTH derivatives of certain adducts are not fragmenting as expected. One such example is the FTH derivative of the adduct from methylglyoxal, which only exhibits one of the diagnostic fragments (m/z 489).10 In addition to the adduct candidates disqualified according to what was mentioned above, the other identified and unidentified adducts that we have observed earlier7 were detected in the studied samples and their accurate masses recorded. One exception is the adduct corresponding to acrylonitrile, which is very low in nonsmokers and therefore not expected to be observed in samples from children. 1161


Article


relation to the adduct levels and fMN, but for neither of these two variables were any correlations observed.

■

DISCUSSION

Observed Adducts and Their Precursors. Targeted screening of previously observed identified and unidentified Nterminal Hb-Val adducts was performed in blood samples from 51 school-age children. A total number of 24 adducts was observed in the samples, and their levels were determined by a semiquantitative approach. The adduct levels of the measured adducts ranged from about 5 to 3800 pmol/g Hb. The adduct levels showed a large variation between individuals; a variation by a factor >10 was observed for most of the adducts when comparing the lowest and highest measured levels. What these variations mean in the context of differences in exposure, metabolism, etc. is not known. The intraindividual variation in adduct levels over time for some of the adducts studied earlier is indicated to be lower than the variation observed here.19 Structures for the FTH derivatives of the 12 identified adducts determined in the samples are shown in Figure 5. The identification of these adducts, through comparisons with references of their FTH derivatives, has previously been reported (for adducts from acrylamide, glycidamide, and ethylene oxide see ref 8; for adducts from methyl vinyl ketone, see ref 20; for adducts corresponding to ethylation and methylation, see ref 7; for the adduct from ethyl vinyl ketone, see ref 9; for adducts from acrylic acid, glyoxal, methylglyoxal, and 1-octen-3-one, see ref 10; for the adduct corresponding to glycidol, see ref 21). The adduct showing the highest level in all analyzed samples corresponds to the methylation of the N-terminal Val (cf. Table 2), in agreement with our previous adduct screening.7 The predominant background source of this adduct has previously been deduced to be the endogenous methylator S-adenosyl methionine.22,23 The adduct of the second highest level, also in agreement with previous observations, is the adduct corresponding to a carboxymethylation of the N-terminal Val.10 This adduct is an advanced glycation end product (AGE), primarily generated in the degradation of glycated Hb (HbA1c).24,25 The same adduct may also be formed from reactions with the precursor electrophile glyoxal.10 Increased levels of carboxymethylation AGEs are known to be associated with increased risks of complications of diabetes mellitus, aging, and oxidative stress.26

Figure 3. Adductome map illustrating the range of levels of the 24 measured adducts in the samples from 51 individuals. The estimated levels range from approximately 5−3700 pmol/g Hb, with the size of each circle corresponding to the relative level of the corresponding adduct (highest level in gray, lowest level in black). The 12 identified adducts or the corresponding precursors are labeled in the figure. The retention times (min) in the LC-MS analysis are shown on the x axis and the m/z of the adduct derivatives (precursor ions, [M + H]+) on the y axis.

latent variables result in better calibration coefficients of determination, but the present model overfits at the third latent variable (cf. Figure S3). From the interpretation of the loadings plot (Supporting Information, Figure S4) and coefficients (Figure 4), we observe that the adducts from ethylene oxide and glyoxal, and the unknown adducts with precursor ions ([M + H]+) m/z 519 and 577, have a positive association with the fMN. On the other hand, the adducts corresponding to ethyl and methylglyoxal and the unknown adducts with precursor ions ([M + H]+) m/z 625 and 631, have negative associations. Because of uncontrollable variables, i.e., variables influencing the fMN that were not accounted for, this model may be inconclusive. However, some trends were observed, and with the inclusion of more reliable variables, the impact of these adducts can be better estimated, with improved models, i.e., with better calibration and crossvalidation coefficients of determination. The body mass index (BMI) and sex of the 51 individuals were also investigated in

Figure 4. PLS regression coefficients for the first two latent variables. Positive coefficients represent a positive contribution of the variables (adducts) for the response (fMN). Negative coefficients represent negative contributions, i.e., individuals with high levels of those adducts have lower fMN. 1162


Article


Figure 5. Structures for the FTH derivatives of the 12 identified adducts determined in the samples. FL = fluorescein.

The adduct from ethylene oxide, a compound classified as a carcinogen,27 was the first “background” adduct to N-terminal valine in Hb which was carefully characterized. These studies showed that endogenous formation of ethene/ethylene oxide is the main source of this adduct.28−30 The adduct from acrylamide, as well as the adduct of its genotoxic metabolite glycidamide (both compounds shown to be carcinogenic in rodents),27,31,32 originates from the general exposure to acrylamide from food, as previously detected by Hb adducts.33−35 The 1,2-dihydroxypropyl-modification of Nterminal valine in Hb, observed in human blood samples, has been proposed to originate from the probable carcinogen glycidol,21,27 with food as a source.36,37 The recently identified adducts corresponding to vinyl ketones (ethyl vinyl ketone, methyl vinyl ketone, and 1-octen-3-one) and acrylic acid are assumed to be related to endogenous formation and/or food, even though their origins have so far not been studied in depth.9,10,20 Ethyl vinyl ketone is naturally present in a number of foods and beverages, e.g., orange juice;38 1-octen-3-one has been suggested to form in food from the oxidative degradation of arachidonic acid.39 Acrylic acid is a Maillard reaction product supposedly formed in food from, e.g., the degradation of aspartic acid during heating.40 Ethyl adducts have been suggested to originate from ethanol-metabolites,41 though not likely originating from exogenous exposure to ethanol in the studied population of children. It is well-known that the FIRE procedure and related methods using isothiocyanate reagents to detach and measure adducts require that the substituted N-terminal can be thiocarbamoylated by the used isothiocyanate reagent.

Substituents on the N-terminal nitrogen that inhibit this reaction are blocking agents such as acetylators,42 and alkylators that are bifunctional and could react with the N-terminal nitrogen to form ring-closed adducts, e.g., diepoxybutane and isoprene diepoxide.43,44 The applicability and limitations of modified Edman procedures for N-terminal adduct measurement have been discussed in more detail earlier.45,46 The FIRE procedure is currently the best option for simultaneous analysis of a large number of Hb adducts. To study the complete Nterminal Hb adductome, complementary procedures would be needed, e.g., analysis of tryptic peptides containing the modified N-terminal.47 Methods allowing the screening of adducts to other nucleophilic sites within Hb would be needed to uncover the full Hb adductome since some electrophiles may exhibit increased reactivity toward other sites compared to that of Nterminal Hb. One example is the β-Cys93 residue which is a known site for adduct formation from, e.g., aromatic amines.48,49 Adduct Levels and Micronuclei Frequencies. Many life style factors such as nutrition, physical exercise, smoking, and alcohol consumption, in addition to age and gender, have previously been found to influence MN formation.18,50,51 Here, we were able to link up to 60% of the observed fMN variation with the levels of 24 different adducts. The studied subcohort consists of only 51 individuals, though including the groups with highest and lowest fMN out of 150 individuals in the cohort. One issue to consider is the time windows of exposure covered by the biomarkers monitored. The measured fMN reflects the exposure a few days prior to sampling,52 levels of chemically stable Hb adducts reflect the last months of 1163


Article


high resolution MS (HRMS). The purpose was to screen for unknown adducts in an extended m/z range (500−700 m/z, compared to the previously applied range 503−638 m/z), as well as to confirm the presence of the earlier observed adducts with HRMS in this sample set. During the past few years, HRMS has gained much attention for various MS-based omics-type studies. Several HRMS methods for adductomic approaches, using Orbitrap instruments, have been reported.6,56−58 Elemental compositions of compounds may be suggested from accurate mass data, which could be an advantage for the identification of unknown adducts. The instrumentation also provides useful modes for MS scanning, which could potentially replace many of the MS/ MS modes used with triple quadrupole instruments. In this study, we have initiated our work with Orbitrap instrumentation for adductomic screening of N-terminal Hb adducts. The method previously applied by us for adductomic screening used triple quadrupole MS in the MRM mode.7 For screening with Orbitrap MS, analysis in the data independent acquisition (DIA) mode was considered the best suited option. The so far published adductomic approaches for Orbitrap MS are based on data-dependent acquisition, in which the most abundant ions are fragmented.6,56 When analyzing samples of high purity, such approaches are suitable, but for the analysis of blood samples treated according to the FIRE procedure, for which the concentrations of reagent byproducts are high, they are, however, not the optimal choice. In the DIA mode, all ions within a specified m/z range are fragmented, and collective fragmentation patterns for all ions within that range are recorded. To confirm possible adduct candidates observed in the DIA mode, subsequent measurements were performed in the PRM mode, in which ions of specific m/z (unit resolution) are fragmented. Porter and Bereman recently published a DIA method for the detection of cysteine modifications in tryptic peptides from human serum albumin and Hb, acknowledging the advantages of DIA over data-dependent acquisition for detection of low-level adducts.59 Five analytes corresponding to probable adducts, previously not observed, were detected during the screening with HRMS and later detected in the majority of the 51 samples during the targeted screening. The theoretical log P values were estimated for the detected adduct derivatives, and together with the calculated adduct masses, this will serve as a basis for identification of these unknowns (Table 1). We have earlier outlined a strategy for the identification of unknown adducts based on these parameters, which have been successfully applied for the identification of four unknown adducts.10 The accurate mass data obtained from the Orbitrap experiments may facilitate the formulation of hypotheses on identity. Accurate mass determinations of fragments may also facilitate qualification of adduct candidates, as shown in this study where six analytes previously considered adduct derivatives were deemed less likely as true adducts due to inconsistent fragmentation. Conclusions. To elucidate exposures to genotoxic compounds in children, this study used sensitive methods for analysis of biomarkers of exposure and effect in blood samples from a cohort of school-age children. Screening of adducts to N-terminal Val in Hb was used to characterize exposures to electrophiles. Measurement of MN frequency in erythrocytes in peripheral blood was used as a biomarker of genotoxic effect. Large individual differences were observed in the children for levels of both known and so far unidentified adducts

exposure. Not all Hb adducts are chemically stable; for instance, we have previously found that the adduct from ethyl vinyl ketone has an unusual short half-life of less than a day.9 It is probable that some measured adducts formed through the same mechanism as ethyl vinyl ketone are not stable over the lifetime of the erythrocytes (approximately 4 months) and thus reflect shorter periods of exposure. The preliminary assumption is though that the monitored biomarkers, despite different halflives, reflect the normal exposure and physiological conditions of each individual. The first application of the combination of these sensitive methods to measure genotoxic effect and internal dose of electrophiles, respectively, is indicated to be useful for further characterization of risk factors for genotoxic effects in humans. From samples with relatively high fMN, unknown adducts associated with genotoxic damage may be pinpointed and chosen for in-depth studies. The high sensitivity of the applied method to measure fMN is obtained through enrichment of the very youngest erythrocytes combined with flow cytometric detection using two lasers. The high sensitivity of the applied method to measure MN as a biomarker of genotoxic effect/genotoxic exposure due to dietary habits was shown earlier in a human intervention study.53 In that study, the increased intake (and internal dose) of acrylamide from heat-processed food over a few days showed a high correlation with increased MN frequencies.53 In this case, it could though be quantitatively estimated that the acrylamide intake could only give a minor contribution to the observed genotoxic effect, which thus had to be due to other factors associated with the intake of acrylamide-rich food. Of the identified Hb adducts observed in the present study, a few correspond to exposures from known genotoxic carcinogens. These are the epoxides glycidamide and ethylene oxide, and glycidol which is the probable source to 1,2-dihydroxypropyl adducts, which all form adducts via SN2 reactions. Of those, glycidamide is indicated to have the highest genotoxic potency.54,55 Several of the electrophilic precursors to the measured adducts form adducts via Michael addition (such as acrylamide, ethyl vinyl ketone, acrylic acid, and 1-octen-3-one) or via Schiff base formation (glyoxal and methylglyoxal). Such compounds might not be expected to have high genotoxic potency and lower than the above-mentioned epoxides. They may, however, reflect exposures of importance for other health conditions. One example is the adducts formed from glyoxal and methylglyoxal, thought to reflect the status for diabetes mellitus, aging, and oxidative stress.26 When studying adducts in samples from the general population, individual adducts will probably have a low influence on MN frequencies. However, when considered collectively, as done here, an association between adduct levels and MN frequencies might be observed. The sources and toxicological significance of many of the monitored adducts are not presently known and may reflect a number of different processes and conditions. For a more profound study and better modeling, considering that there may exist innumerous interindividual sources of variation in adduct levels and fMN, a much larger number of samples, including replicates, may be required. If data representing other factors known to affect fMN, for instance food consumption, could be included, better predictive models would most likely be generated. HRMS for the Detection and Qualification of Unknown Adducts. Prior to the targeted analysis of adducts in the present work, adductomic screening was performed using 1164


Article


Environmental & Heritable Factors in the Causation of Cancer. N. Engl. J. Med. 343, 78−85. (2) American Institute for Cancer Research (2007) Food, Nutrition, Physical Activity, and the Prevention of Cancer: a Global Perspective, World Cancer Research Fund/American Institute for Cancer Research, Washington, DC. (3) Rappaport, S. M. (2016) Genetic factors are not the major causes of chronic diseases. PLoS One (Scott, R. J., Ed.) 11, e0154387. (4) World Health Organization (2006) Environmental Health Criteria 237: Principles for Evaluating Health Risks in Children Associated with Exposure to Chemicals, World Health Organization, Geneva, Switzerland. (5) Rappaport, S. M., Li, H., Grigoryan, H., Funk, W. E., and Williams, E. R. (2012) Adductomics: characterizing exposures to reactive electrophiles. Toxicol. Lett. 213, 83−90. (6) Balbo, S., Turesky, R. J., and Villalta, P. W. (2014) DNA adductomics. Chem. Res. Toxicol. 27, 356−366. (7) Carlsson, H., von Stedingk, H., Nilsson, U. L., and Törnqvist, M. Å. (2014) LC−MS/MS screening strategy for unknown adducts to Nterminal valine in hemoglobin applied to smokers and nonsmokers. Chem. Res. Toxicol. 27, 2062−2070. (8) von Stedingk, H., Rydberg, P., and Törnqvist, M. (2010) A new modified Edman procedure for analysis of N-terminal valine adducts in hemoglobin by LC-MS/MS. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 878, 2483−2490. (9) Carlsson, H., Motwani, H. V., Osterman Golkar, S., and Törnqvist, M. (2015) Characterization of a Hemoglobin Adduct from Ethyl Vinyl Ketone Detected in Human Blood Samples. Chem. Res. Toxicol. 28, 2120−2129. (10) Carlsson, H., and Törnqvist, M. (2016) Strategy for identifying unknown hemoglobin adducts using adductome LC-MS/MS data: Identification of adducts corresponding to acrylic acid, glyoxal, methylglyoxal, and 1-octen-3-one. Food Chem. Toxicol. 92, 94−103. (11) Sly, P. D., and Flack, F. (2008) Susceptibility of children to environmental pollutants. Ann. N. Y. Acad. Sci. 1140, 163−183. (12) Abramsson-Zetterberg, L., Zetterberg, G., Bergqvist, M., and Grawé, J. (2000) Human cytogenetic biomonitoring using flowcytometric analysis of micronuclei in transferrin-positive immature peripheral blood reticulocytes. Environ. Mol. Mutagen. 36, 22−31. (13) Lagerqvist, A., Birgisdóttir, B. E., Halldorsson, T. I., Thomsen, C., Darnerud, P. O., and Kotova, N. (2015) Human Biomonitoring and Policy Making: Human Biomonitoring as a Tool in Policy Making towards Consumer Safety. TemaNord, 2015:571, Nordiska Ministerrådet, Copenhagen, Denmark. (14) Abramsson-Zetterberg, L., Durling, L. J. K., Yang-Wallentin, F., Rytter, E., and Vessby, B. (2006) The impact of folate status and folic acid supplementation on the micronucleus frequency in human erythrocytes. Mutat. Res., Genet. Toxicol. Environ. Mutagen. 603, 33−40. (15) Rydberg, P., von Stedingk, H., Magnér, J., and Björklund, J. (2009) LC/MS/MS Analysis of N-Terminal Protein Adducts with Improved Sensitivity: A Comparison of Selected Edman Isothiocyanate Reagents. Int. J. Anal. Chem. 2009, 153472. (16) Rydberg, P. (2005) Patent: Method for Analyzing N-terminal Protein Adducts Using Isothiocyanate Reagents. International Publication Number: WO 2005/101020 A1. (17) Brereton, R. G. (2003) Chemometrics: Data Analysis for the Laboratory and Chemical Plant, Ch. 5, Calibration, pp 271−338, John Wiley & Sons, Ltd, Chichester, UK. (18) Kotova, N., Frostne, C., Abramsson-Zetterberg, L., Tareke, E., Bergman, R., Haghdoost, S., Paulsson, B., Törnqvist, M., Segerbäck, D., Jenssen, D., and Grawé, J. (2015) Differences in micronucleus frequency and acrylamide adduct levels with hemoglobin between vegetarians and non-vegetarians. Eur. J. Nutr. 54, 1181−1190. (19) Carlsson, H. (2016) Development of an Adductomic Approach to Identify Electrophiles in Vivo through Their Hemoglobin Adducts, Ph.D. Thesis, Department of Environmental Science and Analytical Chemistry, Stockholm University, Sweden. (20) von Stedingk, H., Davies, R., Rydberg, P., and Törnqvist, M. (2010) Methyl vinyl ketone-Identification and quantification of

(altogether 24 adducts), as well as for MN frequencies. The monitored exposure originates both from exogenous sources, for instance, food consumption, as well as from endogenous sources, such as metabolic processes. Thus, this study shows that these two sensitive methods are applicable in human biomonitoring, for instance, in children, as tools to characterize the exposome, that is the body burden of toxic chemical compounds/metabolites. The study design, using the combination of these two sensitive methods for human biomonitoring, is indicated to strengthen the prospect for detection and characterization of exposure to genotoxic compounds contributing to risk in the general population.

■

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.chemrestox.6b00463. Full list of the MRM transitions used in the targeted screening, mass spectra of the five unidentified adducts observed during screening with Orbitrap MS, mass spectra of two example compounds previously considered as FTH derivatives of unknown adducts considered less likely to correspond to true adducts following experiments with Orbitrap MS, PLS response explained variance for the first three latent variables, and PLS loadings plot for the first two latent variables (PDF)

■

AUTHOR INFORMATION

Corresponding Author

*Tel: +46 8 16 3769. E-mail: [email protected]. ORCID

Margareta Törnqvist: 0000-0002-5626-1125 Funding

The research was funded by the Swedish Research Council (VR, 621-2012-4187), the Swedish Civil Contingencies Agency, Swedish National Food Agency, and Stockholm University. Notes

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS We are grateful to Farshid Mashayekhy Rad, M.Sc., and Merle Plassmann, Ph.D., Department of Environmental Science and Analytical Chemistry, Stockholm University, for technical assistance with the MS instruments used in this study.

■

ABBREVIATIONS ACN, acetonitrile; AGE, advanced glycation end product; DIA, data independent acquisition; FITC, fluorescein isothiocyanate; FTH, fluorescein thiohydantoin; fMN, frequency of micronuclei; Hb, hemoglobin; HRMS, high resolution mass spectrometry; IS, internal standard; LC/MS, liquid chromatography/mass spectrometry; LOD, limit of detection; MN, micronucleus; MS, mass spectrometry; MRM, multiple reaction monitoring; PLS, partial least-squares; PRM, parallel reaction monitoring; RBC, red blood cells; Rt, retention time; SPE, solid-phase extraction; Val, valine

■

REFERENCES

(1) Lichtenstein, P., Holm, N. V., Verkasalo, P. K., Iliadou, A., Kaprio, J., Koskenvuo, M., Pukkala, E., Skytthe, A., and Hemminki, K. (2000) 1165


Article

Chemical Research in Toxicology adducts to N-terminal valine in human hemoglobin. J. Chromatogr. B: Anal. Technol. Biomed. Life Sci. 878, 2491−2496. (21) Aasa, J., Abramsson-Zetterberg, L., Carlsson, H., and Törnqvist, M. (2017) The genotoxic potency of glycidol established from micronucleus frequency and hemoglobin adduct levels in mice. Food Chem. Toxicol. 100, 168−174. (22) Törnqvist, M., Osterman-Golkar, S., Kautiainen, A., Näslund, M., Calleman, C. J., and Ehrenberg, L. (1988) Methylations in human hemoglobin. Mutat. Res., Genet. Toxicol. Test. 204, 521−529. (23) Törnqvist, M., Svartengren, M., and Ericsson, C. H. (1992) Methylations in hemoglobin from monozygotic twins discordant for cigarette smoking: Hereditary and tobacco-related factors. Chem.-Biol. Interact. 82, 91−98. (24) Shimada, S., Tanaka, Y., Ohmura, C., Tamura, Y., Shimizu, T., Uchino, H., Watada, H., Hirose, T., Nakaniwa, T., Miwa, S., and Kawamori, R. (2005) N-(carboxymethyl)valine residues in hemoglobin (CMV-Hb) reflect accumulation of oxidative stress in diabetic patients. Diabetes Res. Clin. Pract. 69, 272−278. (25) Uchimura, T., Nakano, K., Hashiguchi, T., Iwamoto, H., Miura, K., Yoshimura, Y., Hanyu, N., Hirata, K., Imakuma, M., Motomiya, Y., and Maruyama, I. (2001) Elevation of N-(carboxymethyl)valine residue in hemoglobin of diabetic patients - Its role in the development of diabetic nephropathy. Diabetes Care 24, 891−896. (26) Poulsen, M. W., Hedegaard, R. V., Andersen, J. M., de Courten, B., Bügel, S., Nielsen, J., Skibsted, L. H., and Dragsted, L. O. (2013) Advanced glycation endproducts in food and their effects on health. Food Chem. Toxicol. 60, 10−37. (27) International Agency for Research on Cancer (IARC) (2016) Agents Classified by the IARC Monographs, Volumes 1−116. http:// monographs.iarc.fr/ENG/Classification/index.php. (28) Törnqvist, M., Gustafsson, B., Kautiainen, A., Harms-Ringdahl, M., Granath, F., and Ehrenberg, L. (1989) Unsaturated lipids and intestinal bacteria as sources of endogenous production of ethene and ethylene oxide. Carcinogenesis 10, 39−41. (29) Filser, J. G., Denk, B., Törnqvist, M., Kessler, W., and Ehrenberg, L. (1992) Pharmacokinetics of ethylene in man; body burden with ethylene oxide and hydroxyethylation of hemoglobin due to endogenous and environmental ethylene. Arch. Toxicol. 66, 157− 163. (30) Törnqvist, M., Osterman-Golkar, S., Kautiainen, A., Jensen, S., Farmer, P. B., and Ehrenberg, L. (1986) Tissue doses of ethylene oxide in cigarette smokers determined from adduct levels in hemoglobin. Carcinogenesis 7, 1519−1521. (31) Beland, F. A., Mellick, P. W., Olson, G. R., Mendoza, M. C. B., Marques, M. M., and Doerge, D. R. (2013) Carcinogenicity of acrylamide in B6C3F1 mice and F344/N rats from a 2-year drinking water exposure. Food Chem. Toxicol. 51, 149−159. (32) Beland, F. A., Olson, G. R., Mendoza, M. C. B., Marques, M. M., and Doerge, D. R. (2015) Carcinogenicity of glycidamide in B6C3F 1 mice and F344/N rats from a two-year drinking water exposure. Food Chem. Toxicol. 86, 104−115. (33) Tareke, E., Rydberg, P., Karlsson, P., Eriksson, S., and Törnqvist, M. (2000) Acrylamide: A cooking carcinogen? Chem. Res. Toxicol. 13, 517−522. (34) Tareke, E., Rydberg, P., Karlsson, P., Eriksson, S., and Törnqvist, M. (2002) Analysis of acrylamide, a carcinogen formed in heated foodstuffs. J. Agric. Food Chem. 50, 4998−5006. (35) Vikström, A., Abramsson-Zetterberg, L., Naruszewicz, M., Athanassiadis, I., Granath, F., and Törnqvist, M. (2011) In vivo doses of acrylamide and glycidamide in humans after intake of acrylamide-rich food. Toxicol. Sci. 119, 41−49. (36) Hindsø Landin, H., Tareke, E., Rydberg, P., Olsson, U., and Törnqvist, M. (2000) Heating of food and haemoglobin adducts from carcinogens: possible precursor role of glycidol. Food Chem. Toxicol. 38, 963−969. (37) Honda, H., Törnqvist, M., Nishiyama, N., and Kasamatsu, T. (2014) Characterization of glycidol-hemoglobin adducts as biomarkers of exposure and in vivo dose. Toxicol. Appl. Pharmacol. 275, 213−220.

(38) National Toxicology Program (1992) Ethyl Vinyl Ketone, NTP Nomination History and Review, NCI Summary of Data for Chemical Selection. http://ntp.niehs.nih.gov/ntp/htdocs/chem_background/ exsumpdf/ethylvinylketone_508.pdf. (39) Kihara, H., Tanaka, M., Yamato, K. T., Horibata, A., Yamada, A., Kita, S., Ishizaki, K., Kajikawa, M., Fukuzawa, H., Kohchi, T., Akakabe, Y., and Matsui, K. (2014) Arachidonic acid-dependent carbon-eight volatile synthesis from wounded liverwort (Marchantia polymorpha). Phytochemistry 107, 42−49. (40) Stadler, R. H., Verzegnassi, L., Varga, N., Grigorov, M., Studer, A., Riediker, S., and Schilter, B. (2003) Formation of Vinylogous Compounds in Model Maillard Reaction Systems. Chem. Res. Toxicol. 16, 1242−1250. (41) Matsuda, T., Yabushita, H., Kanaly, R. A., Shibutani, S., and Yokoyama, A. (2006) Increased DNA damage in ALDH2-deficient alcoholics. Chem. Res. Toxicol. 19, 1374−1378. (42) Driessen, H. P. C., De Jong, W. W., Tesser, G. I., and Bloemendal, H. (1985) The Mechanism of N-Terminal Acetylation of Protein. Crit. Rev. Biochem 18, 281−325. (43) Fred, C., Cantillana, T., Henderson, A. P., Golding, B. T., and Törnqvist, M. (2004) Adducts of N-terminal valines in hemoglobin with isoprene diepoxide, a metabolite of isoprene. Rapid Commun. Mass Spectrom. 18, 2177−2184. (44) Kautiainen, A., Fred, C., Rydberg, P., and Törnqvist, M. (2000) A liquid chromatography tandem mass spectrometric method for in vivo dose monitoring of diepoxybutane, a metabolite of butadiene. Rapid Commun. Mass Spectrom. 14, 1848−1853. (45) Rydberg, P., Lüning, B., Wachtmeister, C. A., Eriksson, L., and Törnqvist, M. (2002) Applicability of a modified Edman procedure for measurement of protein adducts: mechanisms of formation and degradation of phenylthiohydantoins. Chem. Res. Toxicol. 15, 570−581. (46) Rydberg, P. (2000) The N-alkyl Edman Method: Mechanisms and Application for Identification of Mutagens in the General Environment, Ph.D. Thesis, Department of Environmental Chemistry, Stockholm University, Sweden. (47) Goel, S., Evans-Johnson, J. A., Georgieva, N. I., and Boysen, G. (2013) Exposure profiling of reactive compounds in complex mixtures. Toxicology 313, 145−150. (48) Pathak, K. V., Chiu, T. L., Amin, E. A., and Turesky, R. J. (2016) Methemoglobin Formation and Characterization of Hemoglobin Adducts of Carcinogenic Aromatic Amines and Heterocyclic Aromatic Amines. Chem. Res. Toxicol. 29, 255−269. (49) Sabbioni, G., and Jones, C. R. (2002) Biomonitoring of arylamines and nitroarenes. Biomarkers 7, 347−421. (50) Fenech, M., and Bonassi, S. (2011) The effect of age, gender, diet and lifestyle on DNA damage measured using micronucleus frequency in human peripheral blood lymphocytes. Mutagenesis 26, 43−49. (51) Wu, C., Lu, Y., and Morimoto, K. (2010) Effect of gene polymorphisms and ethanol consumption on micronucleus frequency in human reticulocytes: A preliminary study. Environ. Health Prev. Med. 15, 188−193. (52) Grawé, J., Biko, J., Lorenz, R., Reiners, C., Stopper, H., Vershenya, S., Vukicevic, V., and Hempel, K. (2005) Evaluation of the reticulocyte micronucleus assay in patients treated with radioiodine for thyroid cancer. Mutat. Res., Genet. Toxicol. Environ. Mutagen. 583, 12− 25. (53) Abramsson-Zetterberg, L., Vikström, A. C., Törnqvist, M., and Hellenäs, K. E. (2008) Differences in the frequency of micronucleated erythrocytes in humans in relation to consumption of fried carbohydrate-rich food. Mutat. Res., Genet. Toxicol. Environ. Mutagen. 653, 50−56. (54) Silvari, V., Haglund, J., Jenssen, D., Golding, B. T., Ehrenberg, L., and Tö rnqvist, M. (2005) Reaction-kinetic parameters of glycidamide as determinants of mutagenic potency. Mutat. Res., Genet. Toxicol. Environ. Mutagen. 580, 91−101. (55) Aasa, J., Vare, D., Motwani, H. V., Jenssen, D., and Törnqvist, M. (2016) Quantification of the mutagenic potency and repair of 1166


Article

Chemical Research in Toxicology glycidol-induced DNA lesions. Mutat. Res., Genet. Toxicol. Environ. Mutagen. 805, 38−45. (56) Chung, M. K., Grigoryan, H., Iavarone, A. T., and Rappaport, S. M. (2014) Antibody enrichment and mass spectrometry of albuminCys34 adducts. Chem. Res. Toxicol. 27, 400−407. (57) Hemeryck, L. Y., Decloedt, A. I., Vanden Bussche, J., Geboes, K. P., and Vanhaecke, L. (2015) High resolution mass spectrometry based profiling of diet-related deoxyribonucleic acid adducts. Anal. Chim. Acta 892, 123−131. (58) Grigoryan, H., Edmands, W. M. B., Lu, S. S., Yano, Y., Regazzoni, L., Iavarone, A. T., Williams, E. R., and Rappaport, S. M. (2016) An adductomics pipeline for untargeted analysis of modifications to Cys34 of human serum albumin. Anal. Chem. 88, 10504−10512. (59) Porter, C. J., and Bereman, M. S. (2015) Data-independentacquisition mass spectrometry for identification of targeted-peptide site-specific modifications. Anal. Bioanal. Chem. 407, 6627−6635.

1167


Adductomic Screening of Hemoglobin Adducts and ... - ACS Publications

Recommend Documents