antioxidants Article Redox Status, Dose and Antioxidant Intake in Healthcare Workers Occupationally Exposed to Ionizing Radiation Natividad Sebastià 1,2 , Lorena Olivares-González 3,4 , Alegría Montoro 1,2 , Joan-Francesc Barquinero 5 , Antonio José Canyada-Martinez 6 , David Hervás 6 , Pilar Gras 1 , Juan Ignacio Villaescusa 1,2 , Luis Martí-Bonmatí 2,7 , Bianca Tabita Muresan 1 , José Miguel Soriano 8,9 , Juan Manuel Campayo 1 , Joaquin Andani 10 , Oscar Alonso 1 and Regina Rodrigo 3,4,9,11, * 1 Service of Radiological Protection, Clinical Area of Medical Image, Avda. Fernando Abril Martorell, 106, Hospital U. P. La Fe, 46026 Valencia, Spain; natividad.sebastia@uv.es (N.S.); almonpas@hotmail.com (A.M.); gras_pil@gva.es (P.G.); villaescusa_ign@gva.es (J.I.V.); bianca.muresan90@gmail.com (B.T.M.); juancampayo@gmail.com (J.M.C.); osalna@gmail.com (O.A.) 2 Biomedical Imaging Research Group GIBI230, Avda. Fernando Abril Martorell, 106, Health Research Institute Hospital La Fe (IISLaFe), 46026 Valencia, Spain; marti_lui@gva.es 3 Pathophysiology and Therapies for Visual Disorders, Eduardo Primo Yúfera, 3, Research Center Príncipe Felipe (CIPF), 46012 Valencia, Spain; lolivares@cipf.es 4 Center for Biomedical Network Research on Rare Diseases (CIBERER), Monforte de Lemos, 3-5. Pabellón 11, 28029 Madrid, Spain 5 Biological Anthropology Unit Animal Biology, Plant Biology and Ecology Department, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain; francesc.barquinero@uab.cat 6 Biostatistics Unit, Avda. Fernando Abril Martorell, 106, Health Research Institute Hospital La Fe (IISLaFe), 46026 Valencia, Spain; data_science@iislafe.es (A.J.C.-M.); bioestadistica@iislafe.es (D.H.) 7 Service of Radiology, Clinical Area of Medical Image, Avda. Fernando Abril Martorell, 106, Hospital U. P. La Fe, 46026 Valencia, Spain 8 Food & Health Lab, Institute of Materials Science, Parc Científic, Catedrático Agustín Escardino, Paterna (Valencia), University of Valencia, 46980 Valencia, Spain; jose.soriano@uv.es 9 Joint Research Unit on Endocrinology, Nutrition and Clinical Dietetics, University of Valencia, Avda. Fernando Abril Martorell, 106, Health Research Institute Hospital La Fe (IISLaFe), 46026 Valencia, Spain 10 Service of Occupational Risk Prevention, Avda. Fernando Abril Martorell, 106, Hospital U. P. La Fe, 46026 Valencia, Spain; andani_joa@gva.es 11 Joint Research Unit of Rare Diseases, CIPF-Health Research Institute La Fe, Eduardo Primo Yúfera, 3, 46012 Valencia, Spain * Correspondence: rrodrigo@cipf.es; Tel.: +34-96-328-9680  Received: 24 July 2020; Accepted: 18 August 2020; Published: 21 August 2020  Abstract: The purpose of this study was to evaluate the relationship between blood redox status, dose and antioxidant dietary intake of different hospital staff groups exposed to low doses of ionizing radiation (LDIR) (Interventional Radiology and Cardiology, Radiation Oncology, and Nuclear Medicine) and non-exposed. Personal dose equivalent (from last year and cumulative), plasma antioxidant markers (total antioxidant capacity, extracellular superoxide dismutase activity, and glutathione/oxidized glutathione ratio), oxidative stress markers (nitrites and nitrates, and lipid peroxidation) and dietary intake (antioxidant capacity using ORAC values) were collected and analyzed from 28 non-exposed healthcare workers and 42 healthcare workers exposed to LDIR. Hospital staff exposed to LDIR presented a redox imbalance in blood that seems to correlate with dose. Workers from the Nuclear Medicine Unit were the most affected group with the lowest value of plasma antioxidant response and the highest value of plasma thiobarbituric acid reactive substances, TBARS (indicator of lipid peroxidation) of all four groups. Cumulative personal dose equivalent positively correlated with nitrites and negatively correlated with total antioxidant capacity in blood. Antioxidants 2020, 9, 778; doi:10.3390/antiox9090778 www.mdpi.com/journal/antioxidants Antioxidants 2020, 9, 778 2 of 16 The diet of healthcare workers from Nuclear Medicine Unit had higher ORAC values than the diet of non-exposed. Therefore, occupational exposure to LDIR, especially for the Nuclear Medicine Unit, seems to produce an imbalanced redox status in blood that would correlate with cumulative personal dose equivalent. Keywords: antioxidant-oxidant status; ionizing radiation; occupational exposure; oxygen radical absorbance capacity (ORAC); personal dose equivalent 1. Introduction The evaluation of the health effects due to low doses of ionizing radiation (LDIR) in healthcare workers is a challenge. Ionizing radiation interacts with living cells, generating a wide range of highly reactive oxygen (ROS) and nitrogen (RNS) species which eventually damage macromolecules, such as DNA, proteins or lipids [1,2]. Affected cells counteract free radicals formation by antioxidant defense mechanisms allowing self-repairing, operating either normally or dysfunctionally, or dying [3,4]. Excessive and uncontrolled generation of free radicals leads to oxidative stress that contributes to the pathogenesis of several diseases, including neurodegenerative disorders, cancer, cardiovascular abnormalities, diabetes mellitus and liver damage. The free radical-mediated effect of ionizing radiation is suspected to have caused a majority of radiation-induced damage [5], and can trigger cell apoptosis or even genetic instability in living organisms [6]. Furthermore, inflammatory responses originated by ionizing radiation might further increase the risk of cancer development [7–9]. Therefore, the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) recommends to focusing on the evaluation of cancer and non-cancer diseases induced by exposure to LDIR [6,10]. Healthcare workers involved in diagnostic and/or treatment procedures with ionizing radiation represent a large collective exposed to long-term low or low radiation doses [11]. This collective includes physicians, medical physicists, nurses, and radiology technologists. There are some reports indicating that employees occupationally exposed to relatively low radiation doses at interventional radiology procedures suffer from a dis-regulated oxidative stress status [11,12], higher DNA breakage frequencies [13,14] and even an increase in cancer incidence, mainly leukemia [7]. Since exposure to very LDIR can lead to a broad range of consequences, it is worth exploring its health effects. The aims of this study are to assess whether healthcare workers occupationally exposed to low levels of ionizing radiation and to different conditions of the workplace present an altered redox status in blood compared to non-exposed workers and whether personal dose equivalent or antioxidant dietary intakes affect this blood redox status. 2. Materials and Methods 2.1. Selection and Description of Participants In the present study, we enrolled 42 healthcare workers exposed to LDIR belonging to three hospital services of the University and Polytechnic La Fe Hospital (Valencia, Spain) and 28 healthcare workers non-exposed to ionizing radiation from the same hospital. Main demographic features of all are shown in Table 1. Antioxidants 2020, 9, 778 3 of 16 Table 1. Characteristics of participants included in the study. Characteristics Control Group 1 Group 2 Group 3 18 10 14 6 nurses, 5 nurses 9 nurses, N of subjects 28 6 physicians,3 1 physician 4 physicians, physicists, 1 pharmacist 1 radiographer 3 radiographers 3 radiographers Males 10 3 8 1 Females 18 11 10 9 Age (yr) Mean (SEM) 43 (2) 48 (1) 50 (3) 48 (1) Smokers 3/28 4/14 4/18 5/10 (n smokers/group) High Cholesterol (n subjects with >220 6/28 1/14 0/18 1/10 mg/dL/group) Hypertension (n of subject with ≥140/90 mm 1/28 2/14 0/18 0/10 Hg/group) Vitamins/minerals supplements 1/28 1/14 0/18 0/10 (n of subject/group) ORAC (µmol TE/100 g) 12599 (1449) 17796 (2615) 17272 (3039) 23368 (3716) * Mean (SEM) 19074 (1822) (Groups 1–3) 0.22 (0.15) 0.05 (0.03) 0.45 (0.17) a,b —- Hp(10)12 (mSv) [0.0–1.9] [0.0–0.6] [0.0–1.4] Mean (SEM) 0.2 (0.07) [Range] [0.0–1.9] (Groups 1–3) 11.05 (5.66) 0.12 (0.08) c 3.14 (1.46) —- Hp(0.07)12 (mSv) [1.8–38.7] [0.0–0.5] [0.0–11.1] Mean (SEM) 4.7 (2.0) [Range] [0.0–38.7] (Groups 1–3) 5.16 (1.43) 5.56 (2.67) 9.8 (6.4) —- Cumulative Hp(10) (mSv) [0.0–13.7] [0.0–49.8] [0.0–65.3] Mean (SEM) 6.44 (1.95) [Range] [0.1–65.3] (Groups 1–3) Note: Hp(10)12 : Personal dose equivalent during 12 months; Hp(0.07)12 : Hand skin dose equivalent during 12 months; SEM: standard error of the mean; TE: Trolox equivalent; ORAC: Oxygen Radical Absorbance Capacity. * p < 0.05 group 3 vs. control; a p < 0.05 group 3 vs. group 1: b p < 0.01 group 3 vs. group 2; c p < 0.05 group 2 vs. group 1. ANOVA-one way and post hoc Tukey test for ORAC and Kruskal–Wallis and Dunn’s multiple comparisons test for Hp(10)12 and Hp(0.07)12 . Control: Non-exposed workers; Group 1: Interventional Radiology and Cardiology; Group 2: Radiation Oncology; Group 3: Nucleoracar Medicine. The healthcare workers exposed to LDIR enrolled in this study, were classified into three groups with different levels of “occupational exposure to ionizing radiation” (Royal Decree 783/2001 according to the characteristics of their workplace, the groups were: Group 1: workers from the Interventional Radiology and Interventional Cardiology Service; Group 2: workers from the Radiation Oncology Service; Group 3: workers from Nuclear Medicine Service. Personal whole-body and hand skin dose equivalent from last 12 months before to blood collection (Hp(10)12 and Hp(0.07)12 and cumulative personal dose equivalent (Hp(10)) were obtained from the personal dosimeters of these workers exposed to LDIR [15] (Table 1 and Table S1). The cumulative Hp(10) is computed by summing annual doses for the period during which the worker has been exposed to radiation. The mean ± standard error of the mean (SEM) of personal and hand skin dose equivalent for each group and individual data are presented in Table 1 and Table S1, respectively. Antioxidants 2020, 9, 778 4 of 16 Detection limit of the physical dosimetry is 0.1 mSv. Therefore a dose below this limit will be considered 0 mSv. All participants were in good health and were not presently taking medications. All of them underwent a clinical survey that included questions related to lifestyles and medical records (age, medications, smoking, drinking habits, cholesterol and blood pressure) (Table 1). Before peripheral blood collection, written informed consent was also obtained to participate in the study. The procedure complied with the Declaration of Helsinki and was approved by the Hospital Ethics Committee (Medicaments Research Ethics Committee-CEIm of the Health Research Institute Hospital La Fe (IIS La Fe)) (Reference 2012/0390). 2.2. Dietary Assessment and Dietary Antioxidant Capacity Estimation Antioxidant dietary intake was assessed using a 24 h recall questionnaire at three different days (three questionnaires each participant) [16]. This questionnaire provides detailed information about all foods, beverages, dietary supplements, tobacco and alcohol consumption during 24 h and at three different days. It also allows identifying the existence of fruits and vegetables in the diet, the presence or absence of unhealthy food and signs of an antioxidant deficiency diet. Total antioxidant capacity of diet was calculated using the Oxygen Radical Absorbance Capacity (ORAC) scores of previously analyzed foods [17]. The ORAC value for each food was utilized to develop individual indices for dietary antioxidant capacity. ORAC values were reported in µmol of Trolox equivalents per gram (µmol TroloxE/g). Dietary antioxidant capacity describes the ability of food antioxidants to scavenge free radicals [18]. 2.3. Blood Collection Blood samples (10 mL) were collected in heparinized tubes and processed to obtain plasma by centrifugation at 800× g for 10 min. Plasma was stored in several aliquots at −80 ◦ C until biochemical determinations as soon as possible (2–3 months). Freeze-thaw cycles were avoided. 2.4. Determination of Antioxidant and Oxidant Markers Plasma antioxidant-oxidant (redox) status was evaluated by measuring total antioxidant capacity (TAC), lipid peroxidation (TBARS), extracellular SOD (EC-SOD) activity, nitrites and nitrates (NOX) levels, glutathione (GSH) and oxidized glutathione (GSSG) as previously described [19,20]. To avoid technical variations samples from non-exposed and exposed workers were always included for each determination. Specifically, TAC was measured by the ABTS ((2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) method with a commercial kit (Cayman Chemical, Ann Arbor, MI, USA). Lipid peroxidation was evaluated by measuring the formation of thiobarbituric acid reactive substances (TBARS, including malondialdehyde (MDA) which are formed as a byproduct of lipid peroxidation (Cayman Chemical, Ann Arbor, MI, USA). Determination of EC-SOD activity was based on the dismutation of superoxide oxygen and hydrogen peroxide with a commercial kit (Cayman Chemical, Ann Arbor, MI, USA) Nitrites (stable end-product of NO) and nitrate (NOX) levels were measured by nitrate reductase and Griess reaction [21]. GSH and GSSG were measured by the liquid chromatography tandem mass spectrometry (LC-MS/MS) system [20]. 2.5. Statistics Statistical analyses were performed using R software (version 3.4.2) (foundation for statistical computing, Vienna, Austria). Normal distribution of data was analyzed by Shapiro–Wilk and Kolmogorov–Smirnov tests. Comparisons between non-exposed and exposed workers were performed using the Mann–Whitney U test (nonparametric analysis). Comparisons between non-exposed and different groups of exposed workers were performed using Kruskal–Wallis and Dunn’s multiple comparisons test or ANOVA-one way and post hoc Tukey depending on data distribution. Spearman’s rank correlation coefficient was used for non-parametric data. Ordinal regression models, which are a Antioxidants 2020, 9, 778 5 of 16 multivariable generalization of the Wilcoxon–Mann–Whitney test, were used to assess associations between the different groups and oxidative stress status, controlling for age, gender, ORAC, presence of high cholesterol and smoking habit by including them in the models as potential confounding factors. A fuzzy clustering algorithm was used to globally group the different individuals according to their oxidative stress status [22,23]. The probability of the workers to belong to a group with high (1, high TBARS/NOX and low TAC/EC-SOD values) or low (0, low TBARS/NOX and high TAC/EC-SOD values) oxidative stress was modeled. These values of 0 or 1 were regarded as their global oxidative stress level. Then, beta regression was used to assess differences in the fuzzy clustering results among the different groups. or beta regression, smoking habit, gender, age, ORAC and cumulative Hp(10) were included as confounding factors. p values < 0.05 were considered statistically significant. 3. Results 3.1. High Values of Personal Dose Equivalent and Dietary Antioxidant Capacity among Workers from Nuclear Medicine Table 1 showed main characteristics of the participants. We analyzed whether values of personal and hand skin equivalent dose were different between healthcare workers exposed to LDIR belonging to different services. Kruskal–Wallis and Dunn’s multiple comparisons test revealed that healthcare workers from Nuclear Medicine Service (Group 3) showed higher values of Hp(10)12 than those from the Interventional Radiology and Interventional Cardiology Service (Group 1, p < 0.05) or from the Radiation Oncology Service (Group 2, p < 0.01) (Table 1). We also analyzed whether ORAC values were different between healthcare workers non-exposed and exposed to LDIR. Values observed for workers of the Nuclear Medicine Service (Group 3) were significantly higher than those values from non-exposed (p < 0.05, ANOVA-one way and post hoc Tukey). For Groups 1 and 2 although ORAC values tended to be higher than in non-exposed workers, this difference was not statistically significant (p = 0.43 and p = 0.42, respectively, ANOVA-one way and post hoc Tukey) (Table 1). 3.2. Putative Correlation between Impaired Redox Status and Personal Dose Equivalent Firstly, we analyzed raw data to discern whether values of each variable (TAC, EC-SOD, NOX, TBARS and GSH/GSSG ratio) were different between non-exposed and all the healthcare workers exposed to LDIR. As shown in Figure 1, workers exposed to LDIR had lower TAC values and higher NOX values than non-exposed workers (in both cases, p < 0.0001 and p < 0.001, respectively, Mann–Whitney test). Besides, the Spearman rank correlation test suggested correlations between the doses, TAC and NOX values (Figure 2). TAC negatively correlated with cumulative Hp(10), NOX positively correlated with cumulative Hp(10) and NOX and TAC showed a negative association. In addition, we found that high ORAC values negatively correlated with TAC. Due to the unexpected negative correlation between TAC and ORAC values for all healthcare workers, we analyzed this association among non-exposed and among exposed workers. We found that the negative correlation occurred only among exposed workers (p = 0.09), but not among non-exposed (p = 0.68). Antioxidants 2020, 9, x FOR PEER REVIEW 6 of 16 Antioxidants 2020, 9,2020, Antioxidants 778 9, x FOR PEER REVIEW 6 of 16 6 of 16 2.0 20 1.5 15 2.0 *** * 20 TAC (mM) ** Ec-SODEc-SOD * (U/mL) (U/mL) 1.0 10 1.5 15 *** * TAC (mM) * ** 0.5 5 1.0 10 0.0 0 0.5 5 C G1,2,3 G1 G2 G3 C G1,2,3 G1 G2 G3 0.0 0 C G1,2,3 G1 G2 G3 C G1,2,3 G1 G2 G3 20 30 15 *** 20 ** NOX (M) 30 20 TBARS TBARS (M) (M) ** 10 15 *** ** NOX (M) 20 10 ** 5 10 10 0 0 5 C G1,2,3 G1 G2 G3 C G1,2,3 G1 G2 G3 0 0 C G1,2,3 G1 G2 G3 C G1,2,3 G1 G2 G3 50 * 40 ratio ratio 50 30 * GSH/GSSG * 40 20 30 * GSH/GSSG 10 20 0 10 C G1,2,3 G1 G2 G3 0 C G1,2,3 G1 G2 G3 Figure 1. Plasma antioxidant-oxidant markers from healthcare workers occupationally exposed to Figure 1. Plasma antioxidant-oxidant markers from healthcare workers occupationally exposed low doses of ionizing radiation. Total antioxidant capacity (TAC), extracellular superoxide dismutase to lowFigure doses1. of Plasma antioxidant-oxidant ionizing radiation. Total markers from healthcare antioxidant workers capacity (TAC), occupationally extracellularexposed to superoxide (EC-SOD) activity, thiobarbituric acid reactive substances (TBARS), nitrites (NOX) content and low doses of ionizing radiation. Total antioxidant capacity (TAC), extracellular superoxide dismutase (EC-SOD) activity, thiobarbituric acid reactive substances (TBARS), nitrites (NOX) content dismutase glutathione/oxidized glutathione ratio (GSH/GSSG) were determined from plasma as described in (EC-SOD) activity, thiobarbituric and glutathione/oxidized glutathione acid (GSH/GSSG) reactive substances (TBARS), nitrites (NOX) content and in Material and Methods. C: Workersratio non-exposed were radiation; to ionizing determinedG1:from plasma asRadiology Interventional described glutathione/oxidized glutathione ratio (GSH/GSSG) were determined from plasma as described in Material andand Methods. Cardiology; G2:C: WorkersOncology; Radiation non-exposed to ionizing G3: Nuclear radiation; Medicine. G1:analysis Statistical Interventional Radiology was carried out Material and Methods. C: Workers non-exposed to ionizing radiation; G1: Interventional Radiology and Cardiology; G2: Radiation Oncology; G3: Nuclear Medicine. Statistical analysis as described in Material and Methods. Ordinal regression models considering several variables was carried and Cardiology; G2: Radiation Oncology; G3: Nuclear Medicine. Statistical analysis was carried out out assimultaneously described in Material were usedand (* p Methods. < 0.05; ** p