Paper THRESHOLD LIMITS FOR BIOLOGICAL INDICATION OF PROLONGED RADIATION EXPOSURE USING mFISH Sergey V. Osovets,* Natalia V. Sotnik,* Viktor Meineke,† Harry Scherthan,† Harald Dörr,† and Tamara V. Azizova*
Abstract—Chromosome aberration (translocation) yield was investigated by mFISH in peripheral blood lymphocytes of Mayak Production Association (PA) workers with prolonged occupational exposure to ionizing radiation (IR). A dose threshold for cytogenetic indication of a prolonged occupational radiation exposure was estimated for Mayak PA workers using functions of dose distributions. Two limits were estimated for the indication of IR exposure to workers with a prolonged external gamma-ray exposure: These are a background translocation yield of N0 = 0.812 ± 0.149% and a dose threshold of indication D0 estimated to be approximately 1 Gy. Health Phys. 106(6):677–681; 2014 Key words: biological indicators; chromosome aberration, gamma radiation, modeling, dose assessment
INTRODUCTION FROM THE worldwide experience with accidents involving exposure to ionizing radiation (IR), there are situations (e.g., Chernobyl nuclear power plant accident, exposure to the lost sources of ionizing radiation, etc.) when dose assessment by means of physical measurements is not feasible or verification of absorbed doses associated with past exposures is required. Hence, biological indication and/or biological dosimetry techniques become essential. The main objective of bioindication is to verify the fact of exposure to ionizing radiation and to estimate the radiation dose absorbed based on its biological parameters (characteristics). At present, many biodosimetry techniques have been developed based on various biomarkers (Swartz et al. 2010; Riecke et al. 2010; Simon et al. 2010; Decordier et al. 2010; Strimbu and Tavel 2010; Pernot et al. 2012). *Southern Urals Biophysics Institute (SUBI), 456780 Ozyorsk, Russian Federation; †Bundeswehr Institute of Radiobiology affiliated to the University of Ulm, Munich, GER. The authors declare no conflicts of interest. For correspondence contact: Sergey V. Osovets, Southern Urals Biophysics Institute (SUBI), Ozyorskoe Shosse 19, Ozyorsk, Chelyabinsk Region, 456780 Russian Federation, or email at [email protected]. (Manuscript accepted 15 October 2013) 0017-9078/14/0 Copyright © 2014 Health Physics Society DOI: 10.1097/HP.0000000000000057
According to the requirements for radiation biomarkers, these must be sensitive and specific to ionizing radiation (IR), they should possess temporal stability, the biomaterial for the analysis should be easily obtainable, and the laboratory screening assay should be simple, not time- and costconsuming (Pernot et al. 2012). Principles of cytogenetic biological dosimetry and indication were proved reasonably by a great number of national and international studies; these findings were the basis for the development of WHO, IAEA and UNSCEAR recommendations on the analysis of chromosomal aberrations in peripheral blood lymphocytes as a test system for a quantitative assessment of mutagenic radiation factors (IAEA, 2001, 2011; UNSCEAR, 2000). The cohort of Mayak Production Association (PA) workers exposed occupationally to prolonged external and/ or internal radiation at a wide dose range provides a unique opportunity to search for and validate biomarkers for the development of novel methods of biological indication and dosimetry of exposure to external gamma rays and internal alpha emitters due to incorporated plutonium, and this cohort is valuable for validation of existing methods as well. The objective of the present study was to establish threshold limits for biological indication of prolonged radiation exposure.
MATERIALS AND METHODS Identification of Mayak workers for the study was based on the “Clinic” medical-dosimetry database at Ozyorsk (Azizova et al. 2008). Three groups of former Mayak workers and a control group of Ozyorsk locals were formed to conduct the study (150 individuals in total): group 1 included 10 Mayak workers exposed to external gamma rays at total gamma dose 0.5–2.0 Gy; group 2 included eight Mayak workers exposed to external gamma rays at total gamma dose >2.0 Gy; group 3 included Mayak workers with combined exposure (total external gamma-ray dose >1.0 Gy with 239Pu body burden >0.8 kBq); group 4 included control residents of Ozyorsk (located near Mayak PA) never exposed occupationally, never involved in any
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cleanup operations following radiation accidents, and never living in contaminated areas. Individual doses from external gamma rays and internal alpha radiation due to incorporated 239Pu for Mayak workers were estimated based on the dosimetry system “Doses‐2005.” Measurement and calculation techniques were presented (Vasilenko et al. 2007) in an entire special issue of Health Physics (Volume 93, Issue 3, 2007). Each individual who gave his/her consent to participation in the study had to sign the “Informed Consent to Voluntary Participation in the Study” and the “Informed Consent to the Personal Data Treatment in accordance with Fundamental Principles of the Russian Federation Law on Health Protection dd 22.06.1993 No. 5487-1 and about Personal Data dd 27.07.2006 No. 152-FL,” which are required by “Legislation Principles on Health Protection of Citizens in the Russian Federation” as of 22.07.1993 and No. 152‐FL “About Personal Data” as of 27.07.2006. Individuals who signed the Informed Consent to voluntary participation in the study underwent the standard clinical and biophysical examination. Table 1 presents general characteristics of the groups. Peripheral blood lymphocyte cultivation and chromosome slide preparation were performed according to the standard protocol. mFISH hybridization of chromosome spreads was conducted using commercial 24XCyte mFISH probes according to 24XCyte lab manual protocol (MetaSystems, GmBH, Robert-Bosch-Str. 6, D-68804, Altlussheim, Germany). Metaphase spread image capturing and karyotyping were performed with an Axio Imager Z.2 (Carl Zeiss, Carl-Zeiss-Strasse 22, 73447 Oberkocken, Germany) fluorescent microscope with filter sets for DAPI, FITC, Texas Red, Spectrum Orange, DEAC, and Cy5 using ISIS 4 (MetaSystems) software. Between 100–150 metaphase spreads were analyzed for each individual. Aberration yield was scored per 100 analyzed metaphases. Mathematical processing of results was performed using standard methods in biostatistics and regression analysis
June 2014, Volume 106, Number 6
(Borovikov 2003; Dreiper and Smit 1987). Based on dose distribution functions as a specific technique, mathematical modeling was performed, and dose threshold for bioindication was calculated (Osovets et al. 2011).
RESULTS AND DISCUSSION In the current study, 15,488 metaphase spreads of 129 individuals were analyzed by mFISH. Due to the advanced age of some participants of the study, the proliferation capacity of peripheral blood lymphocytes was low; therefore, the number of metaphase spreads for these individuals was insufficient. It should be noted that the analysis of chromosome spreads in some Mayak PA workers and Ozyorsk residents registered chromosomal aberrations (CA) typical for malignancies (cell clones, increased CA yield, etc.). A detailed review of medical records and clinical examinations performed did reveal malignant neoplasms in a few individuals after the biosampling; thus these cases were excluded from the statistical analysis. Therefore, 113 individuals were included in the statistical analysis; among them there were 79 Mayak PA workers and 34 controls. Both stable (translocations, insertions, terminal deletions, and complex CAs) and unstable (dicentrics, rings, and acentric fragments) CAs were registered in groups of Mayak workers and controls. In the present study, complex chromosomal rearrangements are defined as aberrations involving three or more breaks in two or more chromosomes. The analysis of non-radiation confounding effects on CA yield demonstrated that CA yields in the study groups were not dependent on gender and age of individuals examined, and no association of stable CAs with social habits (smoking, alcohol consumption) was revealed. However, the authors observed a significantly higher stable CA yield in male Mayak PA workers with obesity (BMI in excess of 30) relative to individuals with a normal body weight.
Table 1. General characteristics of the main groups (1 – 3) and controls.
Characteristics 1 2 3 4 5 6
Males in the groups, % Mean age of workers as of the biosampling ± SD, y Mean total dose from external gamma rays for the entire employment period ± SD, Gy Mean 239Pu body burden ± SD, kBq Mean absorbed RBM dose from internal exposure to 239Pu ± SD, Gy Mean absorbed lung dose from internal exposure to 239Pu, Gy
Group 1 (N = 10)
Group 2 (N = 8)
Group 3 (N = 82)
Controls (N = 50)
80.00a 76.70 ± 4.55 1.12 ± 0.48
100.00a,b 81.13 ± 4.26 2.25 ± 0.50c
60.00a 79.29 ± 5.27 1.80 ± 0.68c
30.00 77.42 ± 5.85 —
— —
— —
1.85 ± 1.98 0.10 ± 0.12
— —
—
—
0.18 ± 0.25
—
Note: statistically significant values as compared to: a — controls; b — group 3; c — group 1; N — number of individuals in a group. www.health-physics.com
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Biological indication of prolonged radiation exposure c S. V. OSOVETS ET AL.
Stable CA yield was found to be significantly increased ( p < 0.05) in Mayak PA workers occupationally exposed to prolonged external gamma- and/or internal alpha-radiation as compared to control individuals. Translocations were the prevailing stable CA type both in Mayak PA workers and in controls (78.4 % and 61.6 %, respectively). Translocation yield in Mayak PA workers exposed to prolonged occupational radiation was significantly higher than that in the group of controls. Data presented in Fig. 1 demonstrate that total stable aberration yield and specifically the level of translocations were significantly increased in the group of Mayak PA workers compared to controls. Correlation and subsequent multivariable analyses were conducted considering red bone marrow (RBM) doses from external gamma rays Dγ (Gy), RBM doses from internal alpha radiation Dα (Gy), and weighted total dose DW (Sv) as factors and their interactions. As a result, a statistically significant correlation was observed between translocation yield and RBM dose from external gamma rays, and a corresponding linear regression was estimated. Other factors or interactions of factors did not show statistically significant associations with translocation yield. Therefore, and according to available data in the literature (IAEA 2001, 2011; UNSCEAR, 2000; Bauchinger et al. 2001; Tucker 2008; Edwards et al. 2005, 2007), translocations were identified as biological markers of prolonged external gamma-ray exposure. A novel approach to quantitative bioindication was developed in the present study based on stable CA yield (translocation level) using the background aberration level. Stable CA (translocation) yield per 100 cells in the control group was assumed as background (N0 = 0.812 ± 0.149). Fig. 2 demonstrates that the background translocation yield (dashed line parallel to X-axis) divides the baseline data set (79 Mayak PA workers) into two groups: the main group (N2 = 68 workers) and the comparison group (N1 = 11 workers).
679
Fig. 2. Subdivision of the study group into the main group of indication (N2) and the comparison group (N1) using the background level of CA (dashed line with 95% confidence bounds) observed in non-exposed individuals.
The complete division of the baseline data set allows applying this simple equation to assess bioindication effectiveness:
η¼
N1
ðN1 þ N2 Þ
100% ;
where η is a bioindication effectiveness factor (expressed as a percentage). Here, the cytogenetic bioindication effectiveness factor [η = (68/79)100%] is obviously equal to 86%. Dose threshold for bioindication was further assessed using a Weibull model (IAEA 2005) for description of the probability of selection into the main group or the comparison group based on dose distribution functions (Osovets et al. 2011, 2012). Dose threshold for biological indication D0 is defined as a relative bound between the main group and the comparison group. It divides the original set of empirical points into two areas, one of which is characterized by the lower effectiveness (D < D0) and another one by the higher effectiveness of indication (D > D0). The Weibull model has the following form:
" P ¼ 1− exp − ln 2
Fig. 1. Chromosome aberration (translocations) yield in the study groups.
(1)
D D50
V # ;
(2)
where P is the probability of selection into the group [or the distribution function F(D) meaning the same], D is total absorbed dose from ionizing radiation, D50 is its median value, and V is the shape parameter.
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June 2014, Volume 106, Number 6
To calculate dose threshold D0, the following nonlinear equation was used: − ln 2ð
e
D V ð2Þ Þ ð2Þ 50
D
− ln 2ð
þe
D V ð 1Þ Þ ð1Þ D 50
−1¼ 0;
(3)
where index 1 points to the comparison group and index 2 to the main group. Calculation of D0 with the prescribed accuracy ε was performed using the Newton–Raphson iteration method (Bakhvalov et al. 1987). Two figures below (Figs. 3 and 4) demonstrate calculation results of the Weibull model for the main group and the comparison group. Both associations were estimated as nonlinear regressions based on the least square method using Statistica software (Borovikov 2003). Comparison between Figs. 3 and 4 shows that the Weibull model provided a good approximation of the empirical data both for the main group (Fig. 3) and for the comparison group (Fig. 4). The regression models derived were statistically significant both in terms of their parameters (according to Student’s t-test) and in general across the total association (according to Fisher’s F-test). Determination coefficients (R2) were significant as well and exceeded 0.9. The analytic form of the associations obtained was for the main group: " 2:9410:064 # D ; (4) P ¼ 1− exp − ln 2 1:343 0:007
Fig. 4. Probability of selection into the comparison group (♦ indicates empirical data).
The comparison between eqns (4) and (5) showed that the median dose estimate for the main group was ~ 1.34 Gy and ~ 0.88 Gy for the comparison group. The method of distribution functions (Osovets et al. 2011, 2012) allowed obtaining a dose threshold estimate for biological indication based on stable chromosomal aberration (translocation) yield scored after prolonged external gamma-ray exposure (D0 ≈ 1.04 Gy). The numerical estimate of the dose threshold D0 with the accuracy ε = 0.001 was calculated using a nonlinear eqn (3) by the Newton-Raphson method with parameter values ð1Þ
and for the comparison group: " 3:6920:254 # D : P ¼ 1− exp − ln 2 0:884 0:010
•
D50 ¼ 0:884; Vð1Þ ¼ 3:692;
(5)
Fig. 3. Probability of selection into the main group ( indicates empirical data).
ð2Þ
D50
¼1:343; Vð2Þ ¼2:941:
Thus, the dose threshold for indication D0 ≈ 1 Gy divides the original set of empirical points (see Fig. 2) into two areas: the D < 1 Gy area with the indication effectiveness η = 72%, and the D > 1 Gy area with the much higher indication effectiveness η = 93%. In other words, in the D < 1 Gy area, the proportion of individuals not identified using the cytogenetic technique (~28%) is four times that (~7%) in the D > 1 Gy area. Fig. 5 graphically interprets the devised method and the calculation results obtained. In addition to the estimate of a dose threshold for bioindication D0 = 1.04 Gy, Fig. 5 demonstrates that the intersection point of the complementary function (dashed line) and the dose distribution function for the main group (solid line on the right) fall into the ~25% quantile area. It is worth noting here that the complementary function is derived as 1−P, where P is a probability of selection into the comparison group (see eqn 5). Thus, the intersection point of the complementary function and the function of dose distribution for the main group is derived based on the condition that the probability of selection in the main group is equal to the probability of non-selection in the comparison group.
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Biological indication of prolonged radiation exposure c S. V. OSOVETS ET AL.
Fig. 5. Dose threshold for bioindication of prolonged external gammarays based on stable CA (translocation) yield (dashed line is complementary to a distribution function for the comparison group).
A standard relative uncertainty of dose threshold for bioindication may be estimated using nonlinear eqn (5) adjusting for errors in the included parameters. The preliminary crude estimate of the relative uncertainty of the dose threshold for bioindication was ~10%, calculated by the error propagation method (Novitskiy and Zograf 1991). CONCLUSION As a result of the present mFISH study of translocation yield in Mayak workers experiencing prolonged occupational exposure to external and internal IR, two limits were estimated for the indication of workers with prolonged external gamma-ray exposure. They are a background translocation yield of N0 = 0.812 ± 0.149% and a dose threshold of effective indication D0 ~ 1Gy. Acknowledgments—We are grateful to the Sanitätsamt of the Bundeswehr, Germany, for supporting this study through contract M/SAB X/ 9A001, “Biological indication and dosimetry of chronic exposure.”
REFERENCES Azizova TV, Day RD, Wald N, Muirhead CR, O’Hagan JA, Sumina MV, Belyaeva ZD, Druzhinina MB, Teplyakov II, Semenikhina NG, Stetsenko LA, Grigiryeva ES, Krupenina LN, Vlasenko EV. The “Clinic” medical-dosimetric database of Mayak production association workers: structure, characteristics and prospects of utilization. Health Phys 94:449–458; 2008. Bakhvalov NS, Zhidkov NP, Kobelkov GM. Numerical methods. Moscow: Science; 1987 (in Russian). Bauchinger M, Schmid E, Braselmann H. Time-course of translocation and dicentric frequencies in a radiation accident case. Int J Radiat Bio 77:553–557; 2001. Borovikov VP. STATISTICA: the art of computer data analysis: for professionals. St. Petersburg: Piter; 2003 (in Russian). Decordier I, Loock K, Kirsch-Volders M. Phenotyping for DNA repair capacity. Mutat Res 705:107–129; 2010.
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Dreiper N, Smit G. Applied regression analysis. V. 2. Moscow: Financy and Statistica; 1987(in Russian). Edwards A, Lindholm C, Darroudi F, Stephan G, Romm H, Barquinero J, Barrios L, Caballin MR, Roy L, Whitehouse CA, Tawn EJ, Moquet J, Lloyd DC, Voisin P. Review of translocations detected by FISH for retrospective biological dosimetry application. Radiat Protect Dosim 113:396–402; 2005. Edwards A, Szіuinska M, Lloyd DC. Reconstruction of doses from ionizing radiation using fluorescence in situ hybridization techniques. Brit J Radiol 80:63–67; 2007. Health Physics. 93(3); 2007. International Atomic Energy Agency. Cytogenetic analysis for radiation dose assessment. Vienna: IAEA; Technical Report Series No. 405; 2001. International Atomic Energy Agency. Development of an extended framework for emergency response criteria. IAEATECDOC‐1432. Vienna: IAEA; 2005. International Atomic Energy Agency. Cytogenetic dosimetry: applications in preparedness for and response to radiation emergencies. EPR-biodosimetry. Vienna: IAEA; 2011. Novitskiy PV, Zograf IA. Assessment of inaccuracy of measurement results. Leningrad: Energoatomizdat; 1991 (in Russian). Osovets SV, Azizova TV, Day RD, Wald N, Druzhinina MB. Assessment of risks and close thresholds for some effects of acute exposure. Health Phys 100:176–184; 2011. Osovets SV, Azizova TV, Day RD, Wald N, Moseeva MB. Direct and indirect tasks on assessment of close and time distributions and thresholds of acute radiation exposure. Health Phys 102:189–195; 2012. Pernot E, Hall J, Baatout S, Benotmane MA, Blanchardon E, Bouffler S, El Saghire H, Gomolka M, Guertler A, HarmsRingdahl M, Jeggo P, Kreuzer M, Laurier D, Lindholm C, Mkacher R, Quintens R, Rothkamm K, Sabatier L, Tapio S, de Vathairem F, Cardis E. Ionizing radiation biomarkers for potential use in epidemiological studies. Mut Res 751: 258–286; 2012. Riecke A, Ruf CG, Meineke V. Assessment of radiation damage— the need for a multi-parametric and integrative approach with the help of both clinical and biological dosimetry. Health Phys 98:160–167; 2010. Russian Federation Law No. 5487‐1, Legislation Principles on Health Protection of Citizens in the Russian Federation, as of 22.07. 1993. Russian Federation Law No. 152‐FL, About Personal Data, as of 27.07.2006. Simon SL, Bouville A, Kleinerman R. Current use and future needs of biodosimetry in studies of long-term health risk following radiation exposure. Health Phys 98:109–117; 2010. Strimbu K, Tavel J. What are biomarkers? Curr Opin HIV AIDS 5:463–466; 2010. Swartz M, Flood A, Gougelet R, Rea M, Nicolalde R, Williams B. A critical assessment of biodosimetry methods for largescale incident. Health Phys 98:95–108; 2010. Tucker JD. Low-dose ionizing radiation and chromosome translocations: a review of the major considerations for human biological dosimetry. Mutat Res 659:211–220; 2008. UNSCEAR 2000 report to the General Assembly. Exposures and effects of the Chernobyl accident. Int J Radiat Med Special Issue 2‐4:3–109; 2000. Vasilenko EK, Khokhryakov VF, Miller SC. Mayak worker dosimetry study: an overview. Health Phys 93:187–258; 2007.
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■■
Abstract—Chromosome aberration (translocation) yield was investigated by mFISH in peripheral blood lymphocytes of Mayak Production Association (PA) workers with prolonged occupational exposure to ionizing radiation (IR). A dose threshold for cytogenetic indication of a prolonged occupational radiation exposure was estimated for Mayak PA workers using functions of dose distributions. Two limits were estimated for the indication of IR exposure to workers with a prolonged external gamma-ray exposure: These are a background translocation yield of N0 = 0.812 ± 0.149% and a dose threshold of indication D0 estimated to be approximately 1 Gy. Health Phys. 106(6):677–681; 2014 Key words: biological indicators; chromosome aberration, gamma radiation, modeling, dose assessment
INTRODUCTION FROM THE worldwide experience with accidents involving exposure to ionizing radiation (IR), there are situations (e.g., Chernobyl nuclear power plant accident, exposure to the lost sources of ionizing radiation, etc.) when dose assessment by means of physical measurements is not feasible or verification of absorbed doses associated with past exposures is required. Hence, biological indication and/or biological dosimetry techniques become essential. The main objective of bioindication is to verify the fact of exposure to ionizing radiation and to estimate the radiation dose absorbed based on its biological parameters (characteristics). At present, many biodosimetry techniques have been developed based on various biomarkers (Swartz et al. 2010; Riecke et al. 2010; Simon et al. 2010; Decordier et al. 2010; Strimbu and Tavel 2010; Pernot et al. 2012). *Southern Urals Biophysics Institute (SUBI), 456780 Ozyorsk, Russian Federation; †Bundeswehr Institute of Radiobiology affiliated to the University of Ulm, Munich, GER. The authors declare no conflicts of interest. For correspondence contact: Sergey V. Osovets, Southern Urals Biophysics Institute (SUBI), Ozyorskoe Shosse 19, Ozyorsk, Chelyabinsk Region, 456780 Russian Federation, or email at [email protected]. (Manuscript accepted 15 October 2013) 0017-9078/14/0 Copyright © 2014 Health Physics Society DOI: 10.1097/HP.0000000000000057
According to the requirements for radiation biomarkers, these must be sensitive and specific to ionizing radiation (IR), they should possess temporal stability, the biomaterial for the analysis should be easily obtainable, and the laboratory screening assay should be simple, not time- and costconsuming (Pernot et al. 2012). Principles of cytogenetic biological dosimetry and indication were proved reasonably by a great number of national and international studies; these findings were the basis for the development of WHO, IAEA and UNSCEAR recommendations on the analysis of chromosomal aberrations in peripheral blood lymphocytes as a test system for a quantitative assessment of mutagenic radiation factors (IAEA, 2001, 2011; UNSCEAR, 2000). The cohort of Mayak Production Association (PA) workers exposed occupationally to prolonged external and/ or internal radiation at a wide dose range provides a unique opportunity to search for and validate biomarkers for the development of novel methods of biological indication and dosimetry of exposure to external gamma rays and internal alpha emitters due to incorporated plutonium, and this cohort is valuable for validation of existing methods as well. The objective of the present study was to establish threshold limits for biological indication of prolonged radiation exposure.
MATERIALS AND METHODS Identification of Mayak workers for the study was based on the “Clinic” medical-dosimetry database at Ozyorsk (Azizova et al. 2008). Three groups of former Mayak workers and a control group of Ozyorsk locals were formed to conduct the study (150 individuals in total): group 1 included 10 Mayak workers exposed to external gamma rays at total gamma dose 0.5–2.0 Gy; group 2 included eight Mayak workers exposed to external gamma rays at total gamma dose >2.0 Gy; group 3 included Mayak workers with combined exposure (total external gamma-ray dose >1.0 Gy with 239Pu body burden >0.8 kBq); group 4 included control residents of Ozyorsk (located near Mayak PA) never exposed occupationally, never involved in any
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Copyright © 2014 Health Physics Society. Unauthorized reproduction of this article is prohibited.
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cleanup operations following radiation accidents, and never living in contaminated areas. Individual doses from external gamma rays and internal alpha radiation due to incorporated 239Pu for Mayak workers were estimated based on the dosimetry system “Doses‐2005.” Measurement and calculation techniques were presented (Vasilenko et al. 2007) in an entire special issue of Health Physics (Volume 93, Issue 3, 2007). Each individual who gave his/her consent to participation in the study had to sign the “Informed Consent to Voluntary Participation in the Study” and the “Informed Consent to the Personal Data Treatment in accordance with Fundamental Principles of the Russian Federation Law on Health Protection dd 22.06.1993 No. 5487-1 and about Personal Data dd 27.07.2006 No. 152-FL,” which are required by “Legislation Principles on Health Protection of Citizens in the Russian Federation” as of 22.07.1993 and No. 152‐FL “About Personal Data” as of 27.07.2006. Individuals who signed the Informed Consent to voluntary participation in the study underwent the standard clinical and biophysical examination. Table 1 presents general characteristics of the groups. Peripheral blood lymphocyte cultivation and chromosome slide preparation were performed according to the standard protocol. mFISH hybridization of chromosome spreads was conducted using commercial 24XCyte mFISH probes according to 24XCyte lab manual protocol (MetaSystems, GmBH, Robert-Bosch-Str. 6, D-68804, Altlussheim, Germany). Metaphase spread image capturing and karyotyping were performed with an Axio Imager Z.2 (Carl Zeiss, Carl-Zeiss-Strasse 22, 73447 Oberkocken, Germany) fluorescent microscope with filter sets for DAPI, FITC, Texas Red, Spectrum Orange, DEAC, and Cy5 using ISIS 4 (MetaSystems) software. Between 100–150 metaphase spreads were analyzed for each individual. Aberration yield was scored per 100 analyzed metaphases. Mathematical processing of results was performed using standard methods in biostatistics and regression analysis
June 2014, Volume 106, Number 6
(Borovikov 2003; Dreiper and Smit 1987). Based on dose distribution functions as a specific technique, mathematical modeling was performed, and dose threshold for bioindication was calculated (Osovets et al. 2011).
RESULTS AND DISCUSSION In the current study, 15,488 metaphase spreads of 129 individuals were analyzed by mFISH. Due to the advanced age of some participants of the study, the proliferation capacity of peripheral blood lymphocytes was low; therefore, the number of metaphase spreads for these individuals was insufficient. It should be noted that the analysis of chromosome spreads in some Mayak PA workers and Ozyorsk residents registered chromosomal aberrations (CA) typical for malignancies (cell clones, increased CA yield, etc.). A detailed review of medical records and clinical examinations performed did reveal malignant neoplasms in a few individuals after the biosampling; thus these cases were excluded from the statistical analysis. Therefore, 113 individuals were included in the statistical analysis; among them there were 79 Mayak PA workers and 34 controls. Both stable (translocations, insertions, terminal deletions, and complex CAs) and unstable (dicentrics, rings, and acentric fragments) CAs were registered in groups of Mayak workers and controls. In the present study, complex chromosomal rearrangements are defined as aberrations involving three or more breaks in two or more chromosomes. The analysis of non-radiation confounding effects on CA yield demonstrated that CA yields in the study groups were not dependent on gender and age of individuals examined, and no association of stable CAs with social habits (smoking, alcohol consumption) was revealed. However, the authors observed a significantly higher stable CA yield in male Mayak PA workers with obesity (BMI in excess of 30) relative to individuals with a normal body weight.
Table 1. General characteristics of the main groups (1 – 3) and controls.
Characteristics 1 2 3 4 5 6
Males in the groups, % Mean age of workers as of the biosampling ± SD, y Mean total dose from external gamma rays for the entire employment period ± SD, Gy Mean 239Pu body burden ± SD, kBq Mean absorbed RBM dose from internal exposure to 239Pu ± SD, Gy Mean absorbed lung dose from internal exposure to 239Pu, Gy
Group 1 (N = 10)
Group 2 (N = 8)
Group 3 (N = 82)
Controls (N = 50)
80.00a 76.70 ± 4.55 1.12 ± 0.48
100.00a,b 81.13 ± 4.26 2.25 ± 0.50c
60.00a 79.29 ± 5.27 1.80 ± 0.68c
30.00 77.42 ± 5.85 —
— —
— —
1.85 ± 1.98 0.10 ± 0.12
— —
—
—
0.18 ± 0.25
—
Note: statistically significant values as compared to: a — controls; b — group 3; c — group 1; N — number of individuals in a group. www.health-physics.com
Copyright © 2014 Health Physics Society. Unauthorized reproduction of this article is prohibited.
Biological indication of prolonged radiation exposure c S. V. OSOVETS ET AL.
Stable CA yield was found to be significantly increased ( p < 0.05) in Mayak PA workers occupationally exposed to prolonged external gamma- and/or internal alpha-radiation as compared to control individuals. Translocations were the prevailing stable CA type both in Mayak PA workers and in controls (78.4 % and 61.6 %, respectively). Translocation yield in Mayak PA workers exposed to prolonged occupational radiation was significantly higher than that in the group of controls. Data presented in Fig. 1 demonstrate that total stable aberration yield and specifically the level of translocations were significantly increased in the group of Mayak PA workers compared to controls. Correlation and subsequent multivariable analyses were conducted considering red bone marrow (RBM) doses from external gamma rays Dγ (Gy), RBM doses from internal alpha radiation Dα (Gy), and weighted total dose DW (Sv) as factors and their interactions. As a result, a statistically significant correlation was observed between translocation yield and RBM dose from external gamma rays, and a corresponding linear regression was estimated. Other factors or interactions of factors did not show statistically significant associations with translocation yield. Therefore, and according to available data in the literature (IAEA 2001, 2011; UNSCEAR, 2000; Bauchinger et al. 2001; Tucker 2008; Edwards et al. 2005, 2007), translocations were identified as biological markers of prolonged external gamma-ray exposure. A novel approach to quantitative bioindication was developed in the present study based on stable CA yield (translocation level) using the background aberration level. Stable CA (translocation) yield per 100 cells in the control group was assumed as background (N0 = 0.812 ± 0.149). Fig. 2 demonstrates that the background translocation yield (dashed line parallel to X-axis) divides the baseline data set (79 Mayak PA workers) into two groups: the main group (N2 = 68 workers) and the comparison group (N1 = 11 workers).
679
Fig. 2. Subdivision of the study group into the main group of indication (N2) and the comparison group (N1) using the background level of CA (dashed line with 95% confidence bounds) observed in non-exposed individuals.
The complete division of the baseline data set allows applying this simple equation to assess bioindication effectiveness:
η¼
N1
ðN1 þ N2 Þ
100% ;
where η is a bioindication effectiveness factor (expressed as a percentage). Here, the cytogenetic bioindication effectiveness factor [η = (68/79)100%] is obviously equal to 86%. Dose threshold for bioindication was further assessed using a Weibull model (IAEA 2005) for description of the probability of selection into the main group or the comparison group based on dose distribution functions (Osovets et al. 2011, 2012). Dose threshold for biological indication D0 is defined as a relative bound between the main group and the comparison group. It divides the original set of empirical points into two areas, one of which is characterized by the lower effectiveness (D < D0) and another one by the higher effectiveness of indication (D > D0). The Weibull model has the following form:
" P ¼ 1− exp − ln 2
Fig. 1. Chromosome aberration (translocations) yield in the study groups.
(1)
D D50
V # ;
(2)
where P is the probability of selection into the group [or the distribution function F(D) meaning the same], D is total absorbed dose from ionizing radiation, D50 is its median value, and V is the shape parameter.
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680
Health Physics
June 2014, Volume 106, Number 6
To calculate dose threshold D0, the following nonlinear equation was used: − ln 2ð
e
D V ð2Þ Þ ð2Þ 50
D
− ln 2ð
þe
D V ð 1Þ Þ ð1Þ D 50
−1¼ 0;
(3)
where index 1 points to the comparison group and index 2 to the main group. Calculation of D0 with the prescribed accuracy ε was performed using the Newton–Raphson iteration method (Bakhvalov et al. 1987). Two figures below (Figs. 3 and 4) demonstrate calculation results of the Weibull model for the main group and the comparison group. Both associations were estimated as nonlinear regressions based on the least square method using Statistica software (Borovikov 2003). Comparison between Figs. 3 and 4 shows that the Weibull model provided a good approximation of the empirical data both for the main group (Fig. 3) and for the comparison group (Fig. 4). The regression models derived were statistically significant both in terms of their parameters (according to Student’s t-test) and in general across the total association (according to Fisher’s F-test). Determination coefficients (R2) were significant as well and exceeded 0.9. The analytic form of the associations obtained was for the main group: " 2:9410:064 # D ; (4) P ¼ 1− exp − ln 2 1:343 0:007
Fig. 4. Probability of selection into the comparison group (♦ indicates empirical data).
The comparison between eqns (4) and (5) showed that the median dose estimate for the main group was ~ 1.34 Gy and ~ 0.88 Gy for the comparison group. The method of distribution functions (Osovets et al. 2011, 2012) allowed obtaining a dose threshold estimate for biological indication based on stable chromosomal aberration (translocation) yield scored after prolonged external gamma-ray exposure (D0 ≈ 1.04 Gy). The numerical estimate of the dose threshold D0 with the accuracy ε = 0.001 was calculated using a nonlinear eqn (3) by the Newton-Raphson method with parameter values ð1Þ
and for the comparison group: " 3:6920:254 # D : P ¼ 1− exp − ln 2 0:884 0:010
•
D50 ¼ 0:884; Vð1Þ ¼ 3:692;
(5)
Fig. 3. Probability of selection into the main group ( indicates empirical data).
ð2Þ
D50
¼1:343; Vð2Þ ¼2:941:
Thus, the dose threshold for indication D0 ≈ 1 Gy divides the original set of empirical points (see Fig. 2) into two areas: the D < 1 Gy area with the indication effectiveness η = 72%, and the D > 1 Gy area with the much higher indication effectiveness η = 93%. In other words, in the D < 1 Gy area, the proportion of individuals not identified using the cytogenetic technique (~28%) is four times that (~7%) in the D > 1 Gy area. Fig. 5 graphically interprets the devised method and the calculation results obtained. In addition to the estimate of a dose threshold for bioindication D0 = 1.04 Gy, Fig. 5 demonstrates that the intersection point of the complementary function (dashed line) and the dose distribution function for the main group (solid line on the right) fall into the ~25% quantile area. It is worth noting here that the complementary function is derived as 1−P, where P is a probability of selection into the comparison group (see eqn 5). Thus, the intersection point of the complementary function and the function of dose distribution for the main group is derived based on the condition that the probability of selection in the main group is equal to the probability of non-selection in the comparison group.
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Biological indication of prolonged radiation exposure c S. V. OSOVETS ET AL.
Fig. 5. Dose threshold for bioindication of prolonged external gammarays based on stable CA (translocation) yield (dashed line is complementary to a distribution function for the comparison group).
A standard relative uncertainty of dose threshold for bioindication may be estimated using nonlinear eqn (5) adjusting for errors in the included parameters. The preliminary crude estimate of the relative uncertainty of the dose threshold for bioindication was ~10%, calculated by the error propagation method (Novitskiy and Zograf 1991). CONCLUSION As a result of the present mFISH study of translocation yield in Mayak workers experiencing prolonged occupational exposure to external and internal IR, two limits were estimated for the indication of workers with prolonged external gamma-ray exposure. They are a background translocation yield of N0 = 0.812 ± 0.149% and a dose threshold of effective indication D0 ~ 1Gy. Acknowledgments—We are grateful to the Sanitätsamt of the Bundeswehr, Germany, for supporting this study through contract M/SAB X/ 9A001, “Biological indication and dosimetry of chronic exposure.”
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