Effects of Radiation Contamination on Human Genome Stability and Health

Effects of Radiation Contamination on Human Genome Stability and Health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effects of Radiation Contamination on Human Genome Stability and Health Aitkhazha Bigaliev, Oksana Cherednichenko, Klara Shalabayeva, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7461846/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Environmental radiation exposure is a well-recognized risk factor for genomic instability and adverse health outcomes. Kazakhstan hosts multiple legacy radioactive waste disposal sites, including settlements in Western Kazakhstan located in close proximity to solid radioactive waste. While the health effects of the Semipalatinsk Nuclear Test Site have been studied extensively, the long-term cytogenetic and molecular genetic consequences of chronic low-dose exposure from radioactive waste storage remain poorly characterized. This study aimed to investigate the impact of chronic radiation exposure on genome stability and population health in residents of contaminated areas compared with non-exposed controls. Results: Peripheral blood samples were collected from residents living near a radioactive waste disposal site and from controls residing in non-contaminated regions. Cytogenetic analyses, including the micronucleus test and metaphase chromosome analysis, revealed significantly elevated frequencies of micronuclei and chromosomal aberrations among exposed individuals. Mutant allele distributions of DNA repair genes (XRCC1, XRCC3, and XPD) also differed between exposed and control groups. Correlation analysis demonstrated strong associations between chromosomal instability and increased prevalence of endocrine disorders, congenital anomalies, and nervous system diseases in the exposed population. These findings are consistent with international reports on chronic low-dose exposure and highlight the potential contribution of both genetic and environmental factors to population health risks. Conclusions: Residents living in close proximity to radioactive waste disposal sites in Western Kazakhstan exhibit measurable genomic instability and altered DNA repair gene profiles. These biological effects are associated with higher rates of specific health disorders, underscoring the urgent need for systematic medical-genetic monitoring, public health interventions, and environmental remediation. This study provides one of the first integrated analyses of chronic low-dose radiation exposure in Central Asia and contributes to global understanding of radiation-induced genomic instability. environment cytogenetics molecular genetics chromosomal abnormalities gene polymorphism human health Figures Figure 1 Figure 2 Introduction The stability of the human genome is constantly challenged by environmental stressors, and ionizing radiation remains one of the most potent and well-studied mutagenic factors. Radiation is a well-documented environmental mutagen capable of inducing a wide spectrum of biological effects, ranging from direct DNA double-strand breaks to oxidative damage mediated by reactive oxygen species (ROS) [1–3]. Persistent genomic instability, chromosomal aberrations, and gene mutations are recognized as hallmark outcomes of radiation exposure, leading to both stochastic effects (e.g., cancer) and hereditary consequences [4]. Modern radiobiology also emphasizes indirect mechanisms, such as radiation-induced bystander effects and genomic instability cascades, which can be triggered even by low and protracted doses [5,6]. These findings challenge the classical dose–response paradigm and underscore the need for sensitive molecular and cytogenetic biomarkers to detect early changes in exposed populations. Globally, territories affected by past nuclear testing, uranium mining, and radioactive waste disposal – such as Chernobyl (Ukraine), Fukushima (Japan), and the Marshall Islands—have demonstrated that radiological contamination can persist for decades, shaping both environmental quality and public health outcomes [7–9]. Kazakhstan holds a unique place in this context: in addition to the legacy of the Semipalatinsk Nuclear Test Site (SNTS), the country hosts multiple uranium production sites, missile-nuclear testing ranges, and localized solid radioactive waste repositories. While the health effects of SNTS exposure have been extensively investigated, the long-term genomic and ecological consequences of technogenic solid radioactive waste disposal sites in Western Kazakhstan remain poorly understood. These sites, often located in close proximity to residential settlements, represent a distinctive exposure model—characterized by chronic low-dose irradiation and a complex radionuclide composition—that has received little systematic research attention [10–12]. The regional specificity of Western Kazakhstan also includes environmental hazards related to rocket stage fall zones and industrial activities, potentially generating combined exposures with synergistic or additive biological effects [13]. In addition to direct health risks, these factors may influence reproductive outcomes, accelerate demographic decline in rural settlements, and contribute to the transgenerational transmission of genetic damage. This study addresses this knowledge gap by conducting a comprehensive ecological–genetic assessment of residents living near a solid radioactive waste disposal site. We hypothesized that chronic exposure in this setting is associated with increased genomic instability, higher frequencies of chromosomal aberrations, and altered distributions of DNA repair gene polymorphisms (XRCC1, XRCC3, XPD). To assess this hypothesis, we combined radiological characterization of the environment with cytogenetic (micronucleus assay, metaphase analysis) and molecular genetic (polymorphism detection) approaches, using a matched control group from a non-contaminated region. The results are expected to provide both scientific insights into the mechanisms of chronic low-dose radiation effects and practical recommendations for targeted public health interventions, aligning with the Sustainable Development Goals (SDG 3 “Good Health and Well-being” and SDG 15 “Life on Land”). Materials and Methods 2.1. Study Area and Population The study was conducted in settlements located at different distances from a solid radioactive waste disposal site in Western Kazakhstan. The surveyed population included permanent residents aged ≥10 years who had lived in the area for at least 10 years. Sampling was conducted in August 2023. Participants were selected by simple random sampling, meaning that every eligible individual had an equal probability of being included. The control group consisted of residents of the Almaty region, which has no documented history of radiation exposure according to the National Report under the IAEA Convention on Nuclear Safety [15]. Inclusion criteria: (1) age ≥10 years; (2) permanent residence in the settlement for ≥10 years; (3) absence of occupational exposure to ionizing radiation. Exclusion criteria: (1) relocation within the past 10 years; (2) diagnosed hematological malignancies at the time of sampling; (3) refusal to participate. All participants provided informed consent prior to biological sampling. The study was conducted in accordance with the Declaration of Helsinki (2013) [16]. Permission for laboratory analyses and publication of results was granted by the Research Institute of Genetics and Physiology. 2.2. 2.2. Radiological Measurements Radiation monitoring was conducted in accordance with the sanitary standards “Sanitary and Epidemiological Requirements for Ensuring Radiation Safety” (Resolution No. KZ.07.00.00441-2005, Government of the Republic of Kazakhstan, 10 August 2013) [17]. Alpha and Beta Activity: Measured in environmental samples using an alpha–beta radiometer UMF-2000 (Ukraine) [18]. Radionuclide Composition: Determined in the hard tissues of extracted teeth by beta- and gamma-spectrometry at the Radiological Laboratory of the Scientific and Practical Center for Sanitary and Epidemiological Expertise and Monitoring (Almaty, Kazakhstan) using MKS 01A Multirad and Canberra CR-4018 gamma spectrometers. The limits of detection (LOD) were: 137 Cs – 1.0 Bq/kg; 40 K – 5.0 Bq/kg; 226 Ra – 0.5 Bq/kg. Radiation Dose: Measured via Electron Paramagnetic Resonance (EPR) spectroscopy of dental enamel. Calibration curves were established using gamma-irradiated reference samples (150, 350, 550, and 750 rad; 100 rad = 1 Gy). EPR parameters included a frequency of 9.5 GHz, modulation amplitude of 0.1 mT, and microwave power of 10 mW [19]. 2.3. Cytogenetic Analysis Peripheral capillary blood samples were collected from 95 residents of contaminated areas. Standard cytogenetic techniques were applied as described by Hungerford (1965) [20]. Micronucleus Test: Conducted on erythrocytes and buccal epithelial cells using MicroOptix (Austria, 2013) and Levenhuk MED D10T (2023) microscopes, following the protocol of Fenech (2000) [21]. A minimum of 2,000 cells per individual were scored. Metaphase Analysis: Cultures of peripheral blood lymphocytes were prepared, and chromosome preparations were stained with Giemsa (Merck, Germany) according to the ISCN 2020 guidelines [22]. A minimum of 100 metaphases per individual were analyzed for structural and numerical aberrations. 2.4. Molecular Genetic Analysis Native DNA was extracted from frozen blood samples using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s protocol [23]. DNA quality and concentration were evaluated using an Ultrospec 2000 spectrophotometer (Pharmacia Biotech) and 1.5% agarose gel electrophoresis, as described by Sambrook and Russell (2001) [24]. RAPD-PCR: Randomly Amplified Polymorphic DNA–PCR was performed with primers selected from the NCBI GenBank [25] and synthesized via the phosphoramidite method on an ASM-800 synthesizer. The method followed the protocol of Williams et al. (1990) [26]. PCR conditions included: initial denaturation at 94 °C for 5 min; 35 cycles of 94 °C for 30 s, 36 °C for 30 s, and 72 °C for 1 min; final extension at 72 °C for 10 min. DNA repair gene (Arg194Trp, Arg399Gln) mutations: XRCC1 (Arg194Trp, Arg399Gln) and XRCC3 (Thr241Met) mutations and polymorphisms were analyzed via PCR-based genotyping as described by Duell et al. (2000) [27] and Winsey et al. (2000) [28]. Amplified fragments were visualized on agarose gels, with genotype identification based on expected fragment sizes: XRCC1 Arg399Gln: 89 bp, 159 bp, 248 bp; XRCC3 Thr241Met: Thr/Thr, Thr/Met, Met/Met profiles. 2.5. Statistical Analysis Data was processed using Excel 2000 (Microsoft Corp., Redmond, WA, USA), Access 2000 (Microsoft Corp., Redmond, WA, USA), and SPSS Base 10.0 (IBM Corp., Armonk, NY, USA) [29]. Descriptive statistics were expressed as means ± standard error (SE). Group comparisons were performed using Student’s t-test [30] or Mann–Whitney U test [31], depending on data distribution. Frequencies were compared by χ² test [32]. Pearson’s correlation coefficients (r) [33] were calculated to assess associations between chromosomal aberration frequency and disease prevalence. A p-value <0.05 was considered statistically significant. Therefore, the purpose of this study is a lack of integrated studies linking environmental radiation monitoring, cytogenetic damage assessment, and molecular genetic profiling in these communities. These cytogenetic and molecular alterations correlate strongly with heightened prevalence of endocrine disorders, congenital anomalies, and nervous system diseases in the exposed population. An accurate description of all the processes of performing this study is given using genetic and environmental terminology and nonproprietary names of laboratory and statistical methods. Results The data obtained are presented by major groups of methods, including radiological measurements, cytogenetic assays, and molecular genetic analysis. 3.1. Radiological Measurements Radiation monitoring revealed that gamma dose rates along the perimeter of the landfill and in nearby settlements ranged from 0.06 to 0.14 μSv/h. In the Bokeyorda District, beta and gamma activity in dental enamel samples was below background levels (p ≥ 0.05), indicating radionuclide concentrations within natural limits. In contrast, in the Zhanibek District, radionuclide activity – particularly 40 K and 226 Ra – was significantly higher (p < 0.05) compared to Bokeyorda, with absorbed doses in some individuals exceeding 25–30 rad (Table 1, Table 2). Radionuclides Activity of the raw sample, Bq/kg The absolute value of activity, Bq/kg Error rate (P ≥; ≤ 0,95) 137 Сs < 32 12.0 ±32 ≥ 0,5 40 К < 6.6е +0.2 314.0 ±346 ≤ 0,5 226 Ra < 12 е +0.2 40.0 ±76 ≥ 0,5 Table 1. Activity of radionuclides in the hard tissues of teeth of residents of Bokeyorda district Table 2. Activity of radionuclides in the hard tissues of teeth of residents of the Zhanibek district Radionuclides Activity of the raw sample, Bq/kg The absolute value of activity, Bq/kg Error rate (P ≥; ≤ 0,95) 137 Сs < 32 12.0 ±32 ≥ 0,5 40 К < 6.6е +0.2 314.0 ±346 ≤ 0,5 226 Ra < 12 е +0.2 40.0 ±76 ≥ 0,5 Calibration curves derived from EPR spectroscopy demonstrated a linear relationship between absorbed dose and EPR signal amplitude (Figure 1). Relative dose values depending on the amplitude of the EPR signal from tooth enamel 3.2. Micronucleus Assay A total of 852,000 red blood cells were analyzed from residents of five settlements. The highest micronucleus (MN) frequency was observed in residents of Aktau’s industrial zone (0.764 ± 0.05%), followed by Akshukyr (1.070 ± 0.03%) and Mangystau-5 (0.771 ± 0.05%) (Table 3). Table 3. Distribution of chromosomal aberration types among exposed and control populations Names of settlements Total number of analyzed red blood cells (N) Cells with micronuclei abs. %+ Aktau 226260 2029 0.764±0.05 Baskudyk 118050 1087 0.469±0.03 Mangystau-5 136390 1245 0.771±0.05 Akshukyr 236830 2168 1.070±0.03 Mangystau-1 134430 1225 0.716±0.61 MN frequency varied by age group but did not show a consistent age-dependent trend. However, higher MN frequencies were associated with closer proximity to contamination sources (Figure 2). 3.3. Cytogenetic Analysis A total of 3,528 metaphases were analyzed in exposed populations. Chromosomal aberrations were detected in 2.4% of cells, with structural aberrations predominating (93.6%) over numerical ones (6.4%) (Table 4). Chromosome-type damage (67%) was more frequent than chromatid-type (33%), consistent with radiation-induced lesions. Number of metaphase spreads examined Total cells with cytogenetic abnormalities Structural aberrations Numerical aberrations Total Chromosome-type Chromatid-type abs. % abs. % abs % abs % abs. % 3528 94 2,4 88 93,6 59 67,04 29 32,9 6 6,4 Table 4. Distribution of chromosomal aberrations by type of structural and numerical abnormalities The frequency of aberrant metaphases was highest in high-risk zones (3.18 ± 0.43%), followed by moderate-risk (2.84 ± 0.26%) and low-risk (1.77 ± 0.15%) zones. In the control group, spontaneous aberrations were ≤1.7%. 3.4. Molecular Genetic Analysis Genotyping revealed the following mutant homozygote frequencies in the exposed group: XRCC1 Arg194Trp (1.7%), XRCC1 Arg399Gln (8.6%), XRCC3 Thr241Met (7.0%), XPD Lys751Gln (5.2%). Allele and genotype distributions for XRCC1 and XRCC3 conformed to Hardy–Weinberg equilibrium in both groups (p > 0.05). The exposed group had lower frequencies of wild-type genotypes compared to controls (Table 5). Settlement Radiation level (mSv/h) People Metaphases Total aberrant cells Selected disease groups Chromosomal abnormalities (%) Neoplasms (%) Blood and hematopoietic diseases (%) Endocrine diseases (%) Nervous system diseases (%) Respiratory diseases (%) Congenital anomalies (%) Akshukyr 0,3 38 3905 120 3,07 18,97 0,36 0,92 0,71 0,23 2,14 Baskudyk 3,8 188 19081 629 3,3 27,59 0,005 1,34 1,04 0,34 3,12 Atameken 0,87 31 2792 83 2,97 15,52 0,3 0,75 0,58 0,19 1,75 Mangystau 0,77 95 12134 278 2,3 41,3 0,8 2,01 1,56 0,51 4,68 Table 5. Correlation coefficients between environmental radiation exposure and prevalence of selected disease groups 3.5. Population Morbidity Analysis Analysis by age group showed that blood and hematopoietic system disorders were most prevalent among children <14 years (20.2% of all cases), followed by adolescents (11.6%) and adults (7.3%). Neoplasms occurred exclusively among adults (0.7%), while congenital anomalies were most common in children (1.8%). District-level analysis indicated that Munaily District had higher rates of adolescent blood disorders (19.1%) and congenital anomalies (1.6%) compared to Tupkaragan District. 3.6. Correlation Analysis Pearson’s correlation analysis demonstrated strong positive correlations between chromosomal abnormalities and endocrine disorders (r = 0.85), congenital anomalies (r = 0.82), and nervous system diseases (r = 0.80). Moderate correlations were observed for respiratory diseases (r = 0.63). Weak or negative correlations were found for neoplasms (r = – 0.32) and blood disorders (r = – 0.41). Discussion 4.1. Key Findings This study demonstrates that residents living near a solid radioactive waste disposal site in Western Kazakhstan exhibit significantly elevated genomic instability – as evidenced by increased micronucleus (MN) frequencies, higher rates of chromosomal aberrations, and altered distributions of DNA repair gene mutation (XRCC1, XRCC3) and polymorphisms. These cytogenetic and molecular alterations correlate strongly with heightened prevalence of endocrine disorders, congenital anomalies, and nervous system diseases in the exposed population. 4.2. Comparison with International and Regional Literature Our findings align with global observations regarding chronic low-dose radiation exposure and its genomic consequences. For example, occupationally exposed interventional cardiology/radiology staff exhibit increased MN frequencies and cytogenetic damage, consistent with chronic low-dose exposure effects [34]. A human biodosimetry literature indicates low but measurable background levels of unstable chromosome aberrations in general populations and provides cut-offs for distinguishing background vs. exposure in dicentric assays; our observed elevations in exposed residents exceed these background expectations [35,36]. Studies in interventional radiologists/cardiologists have also documented genomic integrity impacts from occupational low-dose exposure, reinforcing that even low-level exposures can trigger detectable cytogenetic changes [34]. In contrast, some high-quality work on populations affected by the Chernobyl accident found no systematic increase in de novo germline mutation rates in children of exposed parents, while earlier minisatellite analyses reported elevated germline mutation rates after Chernobyl—highlighting heterogeneity across endpoints and study designs [37,38]. 4.3. Mechanistic Insights and Emerging Molecular Understanding Radiation-induced genomic instability likely arises via both direct and indirect mechanisms. Low-dose ionizing radiation can trigger oxidative DNA damage, double-strand breaks, and bystander effects where signals from irradiated cells impact neighboring cells – even at low doses [39,40]. Transcriptomic and epigenetic studies support dose-dependent modulation of cellular pathways and non-targeted responses at low doses; epigenetic alterations (e.g., DNA methylation, histone modifications) have been linked to reproductive dysfunction and may contribute to congenital outcomes observed in exposed communities [41–44]. 4.4. Regional Specificity — A Unique Exposure Model Unlike well-studied high-dose events like Chernobyl or Fukushima, this study centers on chronic low-dose exposure resulting from solid radioactive waste in close proximity to human habitation. Historical data around Chernobyl reported substantially increased minisatellite mutation rates in exposed families, suggesting potential intergenerational genomic effects, whereas newer sequencing-based analyses in humans report little or no increase in de novo germline SNV rates; together, these underscore how exposure pattern, biological endpoint, and latency shape observed outcomes [37,38]. 4.5. Strengths and Limitations Strengths: integrated environmental radiology, cytogenetics, molecular genotyping, and health outcomes; use of literature-based background expectations for unstable aberrations as an internal reference [35,36]. Limitations: modest sample sizes in molecular subgroups; cross-sectional design; incomplete control for co-exposures and lifestyle. 4.6. Public Health Implications and Future Directions The documented genomic effects and their correlation with adverse health outcomes underscore the need for targeted medical-genetic monitoring in affected communities. Regular cytogenetic screening, coupled with molecular assays, may facilitate early detection of vulnerable individuals. Policy directions include protective measures, remediation, and sustained surveillance aligned with SDG 3 and SDG 15 [45,46]. Future work should include longitudinal designs, dose reconstruction, and biodosimetry markers such as γ-H2AX for improved dose estimation under uncertainty, noting recent inter-laboratory and methodological advances [47–50]. Conclusion Residents living near a solid radioactive waste disposal site in Western Kazakhstan demonstrated elevated genomic instability, as indicated by increased micronucleus frequency, higher rates of structural chromosomal aberrations, and altered DNA repair gene polymorphism profiles. These biological changes correlated with higher prevalence of endocrine disorders, congenital anomalies, and nervous system diseases. The findings highlight the need for continuous medical–genetic monitoring, targeted public health interventions, and further research into the long-term and intergenerational effects of chronic low-dose radiation exposure Abbreviations EPR Electron Paramagnetic Resonance DNA Deoxyribonucleic Acid XRCC1, XRCC3 X-ray Repair Cross Complementing genes 1 and 3 NCBI National Center for Biotechnology Information MN Micronucleus ChMZ Chemical and Hydrometallurgical Plant SDG Sustainable Development Goals ROS Reactive Oxygen Species PCR Polymerase Chain Reaction RAPD-PCR Randomly Amplified Polymorphic DNA–PCR Declarations This study was approved by the Expert Committee (Chairman: Professor L.B. Dzhansugurova) at the Institute of Genetics and Physiology, Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty. Written informed consent was received from all blood donors prior to sample collection. Supplementary Materials: No supplementary materials are available. Author Contributions: Conceptualization, A.B. and A.K.; methodology, O.Ch.; software, A.M.; validation, A.B., K.Sh.; formal analysis, A.K.; investigation, O.Ch.; resources, O.Ch.; data curation, K.Sh.; writing — original draft preparation, A.M.; writing — review and editing, A.B.; visualization, A.K.; supervision, A.B.; project administration, A.K.; funding acquisition, A.B. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan, Grant No. AP19680351. Data Availability Statement: The data presented in this study are not publicly available due to privacy, ethical, and legal restrictions related to medical and genetic information of study participants. Acknowledgments: The authors express their sincere gratitude to Professor Bakhytzhan Bekmanov, Head of the Laboratory of the Research Institute of Genetics and Physiology, Ministry of Science and Higher Education of the Republic of Kazakhstan, for his ongoing advisory assistance in conducting laboratory studies. We also thank the staff of the Radiological Laboratory of the Scientific and Practical Center for Sanitary and Epidemiological Expertise and Monitoring (Almaty, Kazakhstan) for technical support in radionuclide measurements, and the local health authorities of Mangystau Region for assistance in organizing fieldwork. During the preparation of this manuscript, the authors used ChatGPT (GPT-5, OpenAI, 2025) for the purposes of language editing, improving academic style, and refining the structure of the introduction and methods sections. The authors have reviewed and edited the output and take full responsibility for the content of this publication. 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Low-dose radiation can cause epigenetic alterations associated with impairments in both male and female reproductive cells. Front. Genet. 2021, 12 , 710143. https://doi.org/10.3389/fgene.2021.710143. Leung, C.T.; Yang, Y.; Yu, K.N.; Tam, N.; Chan, T.F.; Lin, X.; Kong, R.Y.C.; Chiu, J.M.Y.; Wong, A.S.T.; Lui, W.Y.; Yuen, K.W.Y.; Lai, K.P.; Wu, R.S.S. Low-dose radiation can cause epigenetic alterations associated with impairments in both male and female reproductive cells. Front. Genet. 2021, 12 , 710143. https://doi.org/10.3389/fgene.2021.710143. Raavi, V.; Perumal, V.; Paul, S.F.D. Potential application of γ-H2AX as a biodosimetry tool for radiation triage. Mutat. Res. Rev. Mutat. Res. 2021, 787 , 108350. https://doi.org/10.1016/j.mrrev.2020.108350. Moquet, J.; Ainsbury, E.; Balázs, K.; Barnard, S.; Hristova, R.; Lumniczky, K.; Port, M.; Roessler, U.; Scherthan, H.; Staynova, A.; Szatmári, T.; Wojewodzka, M.; Abend, M. RENEB Inter-Laboratory Comparison 2021: The γ-H2AX foci assay. Radiat. Res. 2023, 199 , 661–671. https://doi.org/10.1667/RADE-22-00205.1. Jose, S.R.; Timothy, P.B.; Suganthy, J.; Backianathan, S.; Amirtham, S.M.; Rani, S.; Singh, R. Determination of dose-response calibration curves for gamma radiation using γ-H2AX immunofluorescence-based biodosimetry. Rep. Pract. Oncol. Radiother. 2024, 29 (2), 164–175. https://doi.org/10.5603/rpor.99678. Wakeford, R. The risk of childhood leukaemia following exposure to ionising radiation—a review. J. Radiol. Prot. 2013, 33 (1), 1–25. https://doi.org/10.1088/0952-4746/33/1/1. Degenhardt, Ä.L.; Sreetharan, S.; Amrenova, A.; Adam-Guillermin, C.; Dekkers, F.; Dumit, S.; Frelon, S.; Horemans, N.; Laurier, D.; Liutsko, L.; Salomaa, S.; Schneider, T.; Hande, M.P.; Wakeford, R.; Applegate, K.E. The ICRP, MELODI, and ALLIANCE workshop on effects of ionizing radiation exposure in offspring and next generations: a summary of discussions. Int. J. Radiat. Biol. 2024 , 100 (9), 1382–1392. https://doi.org/10.1080/09553002.2024.2306335. Brand, F.; Klinkhammer, H.; Knaus, A.; Holtgrewe, M.; Weinhold, L.; Beule, D.; Ludwig, K.; Kothiyal, P.; Maxwell, G.; Noethen, M.; Schmid, M.; Sperling, K.; Krawitz, P. Evidence for a transgenerational mutational signature from ionizing radiation exposure in humans. Sci. Rep. 2025 , 15 , 20262. https://doi.org/10.1038/s41598-025-07030-5. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7461846","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":511784488,"identity":"341b81be-ec02-4b7b-b63a-8d719754afb2","order_by":0,"name":"Aitkhazha Bigaliev","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYDACZgZmZiCVwMDeAKQMLIjRwgzVwnMApEWCKGugWiQSQDwitPC38x82Lqipy+Of+fzqhh8FEkCR7gS8WiQOMzMnzzjGVixxO6fsZg/QYRJnzm7Abw1Qy2EeNp7Ehts5aTd4gFoMJHLxa5EHa/knkTj/5pm0m3+I0WIAchhvm0Hihhvsx24TZYvhYWZjY96+hMSNZ3LYbssYSPAQ9Ivc+YOPpXm+1SXOO3782c03f2zk+Nt7CXgfAXgMwCSxykGA/QEpqkfBKBgFo2AEAQBxA0P0dSUABQAAAABJRU5ErkJggg==","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":true,"prefix":"","firstName":"Aitkhazha","middleName":"","lastName":"Bigaliev","suffix":""},{"id":511784489,"identity":"1f3fe396-bf15-4add-aab2-ff67976eb37e","order_by":1,"name":"Oksana Cherednichenko","email":"","orcid":"","institution":"Research Institute of Genetics and Physiology","correspondingAuthor":false,"prefix":"","firstName":"Oksana","middleName":"","lastName":"Cherednichenko","suffix":""},{"id":511784490,"identity":"a6846837-6668-4eb8-b162-7640a8e8565e","order_by":2,"name":"Klara Shalabayeva","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Klara","middleName":"","lastName":"Shalabayeva","suffix":""},{"id":511784491,"identity":"67464d61-1ac1-4666-8e2a-37edadbec067","order_by":3,"name":"Aizada Kozhakhmetova","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Aizada","middleName":"","lastName":"Kozhakhmetova","suffix":""},{"id":511784492,"identity":"8a94d788-4843-41b9-a54e-9ac09822e5f0","order_by":4,"name":"Ayaulym Myrzatay","email":"","orcid":"","institution":"Al-Farabi Kazakh National University","correspondingAuthor":false,"prefix":"","firstName":"Ayaulym","middleName":"","lastName":"Myrzatay","suffix":""}],"badges":[],"createdAt":"2025-08-26 10:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7461846/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7461846/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91096876,"identity":"4685aca4-2664-4605-ad14-68ca870e4f85","added_by":"auto","created_at":"2025-09-11 14:10:35","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94554,"visible":true,"origin":"","legend":"\u003cp\u003eCurve 1 — Bokeyorda District, Curve 2 — Zhanibek District\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7461846/v1/2307fd8cf4c17bfaa9bd6e3d.jpg"},{"id":91096877,"identity":"f4d5eb65-33fa-45c1-b97b-528dfa935be4","added_by":"auto","created_at":"2025-09-11 14:10:35","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60414,"visible":true,"origin":"","legend":"\u003cp\u003eMicrophotographs of human somatic cells with micronuclei: (a) erythrocytes; (b) buccal epithelial cells.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7461846/v1/360f91d14635dd3dbcb8e7f9.jpg"},{"id":91097475,"identity":"4ed346d8-9d21-4e0f-862f-f6b48cf24793","added_by":"auto","created_at":"2025-09-11 14:18:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":786759,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7461846/v1/ca2b26d4-50a2-46e8-a179-e3db427927a0.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of Radiation Contamination on Human Genome Stability and Health","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe stability of the human genome is constantly challenged by environmental stressors, and ionizing radiation remains one of the most potent and well-studied mutagenic factors. Radiation is a well-documented environmental mutagen capable of inducing a wide spectrum of biological effects, ranging from direct DNA double-strand breaks to oxidative damage mediated by reactive oxygen species (ROS) [1–3]. Persistent genomic instability, chromosomal aberrations, and gene mutations are recognized as hallmark outcomes of radiation exposure, leading to both stochastic effects (e.g., cancer) and hereditary consequences [4]. Modern radiobiology also emphasizes indirect mechanisms, such as radiation-induced bystander effects and genomic instability cascades, which can be triggered even by low and protracted doses [5,6]. These findings challenge the classical dose–response paradigm and underscore the need for sensitive molecular and cytogenetic biomarkers to detect early changes in exposed populations.\u003c/p\u003e\n\u003cp\u003eGlobally, territories affected by past nuclear testing, uranium mining, and radioactive waste disposal – such as Chernobyl (Ukraine), Fukushima (Japan), and the Marshall Islands—have demonstrated that radiological contamination can persist for decades, shaping both environmental quality and public health outcomes [7–9]. Kazakhstan holds a unique place in this context: in addition to the legacy of the Semipalatinsk Nuclear Test Site (SNTS), the country hosts multiple uranium production sites, missile-nuclear testing ranges, and localized solid radioactive waste repositories. While the health effects of SNTS exposure have been extensively investigated, the long-term genomic and ecological consequences of technogenic solid radioactive waste disposal sites in Western Kazakhstan remain poorly understood. These sites, often located in close proximity to residential settlements, represent a distinctive exposure model—characterized by chronic low-dose irradiation and a complex radionuclide composition—that has received little systematic research attention [10–12].\u003c/p\u003e\n\u003cp\u003eThe regional specificity of Western Kazakhstan also includes environmental hazards related to rocket stage fall zones and industrial activities, potentially generating combined exposures with synergistic or additive biological effects [13]. In addition to direct health risks, these factors may influence reproductive outcomes, accelerate demographic decline in rural settlements, and contribute to the transgenerational transmission of genetic damage.\u003c/p\u003e\n\u003cp\u003eThis study addresses this knowledge gap by conducting a comprehensive ecological–genetic assessment of residents living near a solid radioactive waste disposal site. We hypothesized that chronic exposure in this setting is associated with increased genomic instability, higher frequencies of chromosomal aberrations, and altered distributions of DNA repair gene polymorphisms (XRCC1, XRCC3, XPD). To assess this hypothesis, we combined radiological characterization of the environment with cytogenetic (micronucleus assay, metaphase analysis) and molecular genetic (polymorphism detection) approaches, using a matched control group from a non-contaminated region. The results are expected to provide both scientific insights into the mechanisms of chronic low-dose radiation effects and practical recommendations for targeted public health interventions, aligning with the Sustainable Development Goals (SDG 3 “Good Health and Well-being” and SDG 15 “Life on Land”).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cem\u003e2.1. Study Area and Population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in settlements located at different distances from a solid radioactive waste disposal site in Western Kazakhstan. The surveyed population included permanent residents aged ≥10 years who had lived in the area for at least 10 years. Sampling was conducted in August 2023.\u003c/p\u003e\n\u003cp\u003eParticipants were selected by simple random sampling, meaning that every eligible individual had an equal probability of being included. The control group consisted of residents of the Almaty region, which has no documented history of radiation exposure according to the National Report under the IAEA Convention on Nuclear Safety [15].\u003c/p\u003e\n\u003cp\u003eInclusion criteria: (1) age ≥10 years; (2) permanent residence in the settlement for ≥10 years; (3) absence of occupational exposure to ionizing radiation. Exclusion criteria: (1) relocation within the past 10 years; (2) diagnosed hematological malignancies at the time of sampling; (3) refusal to participate.\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent prior to biological sampling. The study was conducted in accordance with the Declaration of Helsinki (2013) [16]. Permission for laboratory analyses and publication of results was granted by the Research Institute of Genetics and Physiology.\u003cem\u003e2.2.\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.2. Radiological Measurements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRadiation monitoring was conducted in accordance with the sanitary standards “Sanitary and Epidemiological Requirements for Ensuring Radiation Safety” (Resolution No. KZ.07.00.00441-2005, Government of the Republic of Kazakhstan, 10 August 2013) [17].\u003c/p\u003e\n\u003cp\u003eAlpha and Beta Activity: Measured in environmental samples using an alpha–beta radiometer UMF-2000 (Ukraine) [18].\u003c/p\u003e\n\u003cp\u003eRadionuclide Composition: Determined in the hard tissues of extracted teeth by beta- and gamma-spectrometry at the Radiological Laboratory of the Scientific and Practical Center for Sanitary and Epidemiological Expertise and Monitoring (Almaty, Kazakhstan) using MKS 01A Multirad and Canberra CR-4018 gamma spectrometers. The limits of detection (LOD) were: \u003csup\u003e137\u003c/sup\u003eCs – 1.0 Bq/kg; \u003csup\u003e40\u003c/sup\u003eK – 5.0 Bq/kg; \u003csup\u003e226\u003c/sup\u003eRa – 0.5 Bq/kg.\u003c/p\u003e\n\u003cp\u003eRadiation Dose: Measured via Electron Paramagnetic Resonance (EPR) spectroscopy of dental enamel. Calibration curves were established using gamma-irradiated reference samples (150, 350, 550, and 750 rad; 100 rad = 1 Gy). EPR parameters included a frequency of 9.5 GHz, modulation amplitude of 0.1 mT, and microwave power of 10 mW [19].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.3. Cytogenetic Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral capillary blood samples were collected from 95 residents of contaminated areas. Standard cytogenetic techniques were applied as described by Hungerford (1965) [20].\u003c/p\u003e\n\u003cp\u003eMicronucleus Test: Conducted on erythrocytes and buccal epithelial cells using MicroOptix (Austria, 2013) and Levenhuk MED D10T (2023) microscopes, following the protocol of Fenech (2000) [21]. A minimum of 2,000 cells per individual were scored.\u003c/p\u003e\n\u003cp\u003eMetaphase Analysis: Cultures of peripheral blood lymphocytes were prepared, and chromosome preparations were stained with Giemsa (Merck, Germany) according to the ISCN 2020 guidelines [22]. A minimum of 100 metaphases per individual were analyzed for structural and numerical aberrations.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.4. Molecular Genetic Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNative DNA was extracted from frozen blood samples using the QIAamp DNA Mini Kit (Qiagen, Hilden, Germany) following the manufacturer’s protocol [23]. DNA quality and concentration were evaluated using an Ultrospec 2000 spectrophotometer (Pharmacia Biotech) and 1.5% agarose gel electrophoresis, as described by Sambrook and Russell (2001) [24].\u003c/p\u003e\n\u003cp\u003eRAPD-PCR: Randomly Amplified Polymorphic DNA–PCR was performed with primers selected from the NCBI GenBank [25] and synthesized via the phosphoramidite method on an ASM-800 synthesizer. The method followed the protocol of Williams et al. (1990) [26]. PCR conditions included: initial denaturation at 94 °C for 5 min; 35 cycles of 94 °C for 30 s, 36 °C for 30 s, and 72 °C for 1 min; final extension at 72 °C for 10 min.\u003c/p\u003e\n\u003cp\u003eDNA repair gene (Arg194Trp, Arg399Gln) mutations: XRCC1 (Arg194Trp, Arg399Gln) and XRCC3 (Thr241Met) mutations and polymorphisms were analyzed via PCR-based genotyping as described by Duell et al. (2000) [27] and Winsey et al. (2000) [28]. Amplified fragments were visualized on agarose gels, with genotype identification based on expected fragment sizes: \u003cem\u003eXRCC1\u003c/em\u003e Arg399Gln: 89 bp, 159 bp, 248 bp; XRCC3 Thr241Met: Thr/Thr, Thr/Met, Met/Met profiles.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2.5. Statistical Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eData was processed using Excel 2000 (Microsoft Corp., Redmond, WA, USA), Access 2000 (Microsoft Corp., Redmond, WA, USA), and SPSS Base 10.0 (IBM Corp., Armonk, NY, USA) [29]. Descriptive statistics were expressed as means ± standard error (SE). Group comparisons were performed using Student’s t-test [30] or Mann–Whitney U test [31], depending on data distribution. Frequencies were compared by χ² test [32]. Pearson’s correlation coefficients (r) [33] were calculated to assess associations between chromosomal aberration frequency and disease prevalence. A p-value \u0026lt;0.05 was considered statistically significant. Therefore, the purpose of this study is a lack of integrated studies linking environmental radiation monitoring, cytogenetic damage assessment, and molecular genetic profiling in these communities. These cytogenetic and molecular alterations correlate strongly with heightened prevalence of endocrine disorders, congenital anomalies, and nervous system diseases in the exposed population. An accurate description of all the processes of performing this study is given using genetic and environmental terminology and nonproprietary names of laboratory and statistical methods.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe data obtained are presented by major groups of methods, including radiological measurements, cytogenetic assays, and molecular genetic analysis.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.1. Radiological Measurements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRadiation monitoring revealed that gamma dose rates along the perimeter of the landfill and in nearby settlements ranged from 0.06 to 0.14 \u0026mu;Sv/h. In the Bokeyorda District, beta and gamma activity in dental enamel samples was below background levels (p \u0026ge; 0.05), indicating radionuclide concentrations within natural limits.\u003c/p\u003e\n\u003cp\u003eIn contrast, in the Zhanibek District, radionuclide activity \u0026ndash; particularly \u003csup\u003e40\u003c/sup\u003eK and \u003csup\u003e226\u003c/sup\u003eRa \u0026ndash; was significantly higher (p \u0026lt; 0.05) compared to Bokeyorda, with absorbed doses in some individuals exceeding 25\u0026ndash;30 rad (Table 1, Table 2).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRadionuclides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eActivity of the raw sample, Bq/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eThe absolute value of activity, Bq/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError rate (P \u0026ge;; \u0026le; 0,95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e137 Сs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.0 \u0026plusmn;32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 К\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 6.6е +0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e314.0 \u0026plusmn;346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e226 Ra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 12 е +0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.0 \u0026plusmn;76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Activity of radionuclides in the hard tissues of teeth of residents of Bokeyorda district\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Activity of radionuclides in the hard tissues of teeth of residents of the Zhanibek district\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"594\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRadionuclides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eActivity of the raw sample, Bq/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eThe absolute value of activity, Bq/kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eError rate (P \u0026ge;; \u0026le; 0,95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e137 Сs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.0 \u0026plusmn;32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 К\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 6.6е +0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e314.0 \u0026plusmn;346\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026le; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e226 Ra\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt; 12 е +0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.0 \u0026plusmn;76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026ge; 0,5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCalibration curves derived from EPR spectroscopy demonstrated a linear relationship between absorbed dose and EPR signal amplitude (Figure 1).\u003c/p\u003e\n\u003cp\u003eRelative dose values depending on the amplitude of the EPR signal from tooth enamel\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.2. Micronucleus Assay\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 852,000 red blood cells were analyzed from residents of five settlements. The highest micronucleus (MN) frequency was observed in residents of Aktau\u0026rsquo;s industrial zone (0.764 \u0026plusmn; 0.05%), followed by Akshukyr (1.070 \u0026plusmn; 0.03%) and Mangystau-5 (0.771 \u0026plusmn; 0.05%) (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eDistribution of chromosomal aberration types among exposed and control populations\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"501\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eNames of settlements\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003eTotal number of analyzed red blood cells (N)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eCells with micronuclei\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eabs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e%+\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAktau\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e226260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.764\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBaskudyk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e118050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1087\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.469\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMangystau-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e136390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.771\u0026plusmn;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAkshukyr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e236830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.070\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMangystau-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e134430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.716\u0026plusmn;0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMN frequency varied by age group but did not show a consistent age-dependent trend. However, higher MN frequencies were associated with closer proximity to contamination sources (Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.3. Cytogenetic Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA total of 3,528 metaphases were analyzed in exposed populations. Chromosomal aberrations were detected in 2.4% of cells, with structural aberrations predominating (93.6%) over numerical ones (6.4%) (Table 4). Chromosome-type damage (67%) was more frequent than chromatid-type (33%), consistent with radiation-induced lesions.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"567\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eNumber of metaphase spreads examined\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal cells with cytogenetic abnormalities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003eStructural aberrations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eNumerical aberrations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eChromosome-type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eChromatid-type\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eabs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eabs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eabs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eabs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eabs.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e93,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Distribution of chromosomal aberrations by type of structural and numerical abnormalities\u003c/p\u003e\n\u003cp\u003eThe frequency of aberrant metaphases was highest in high-risk zones (3.18 \u0026plusmn; 0.43%), followed by moderate-risk (2.84 \u0026plusmn; 0.26%) and low-risk (1.77 \u0026plusmn; 0.15%) zones. In the control group, spontaneous aberrations were \u0026le;1.7%.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.4. Molecular Genetic Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGenotyping revealed the following mutant homozygote frequencies in the exposed group: XRCC1 Arg194Trp (1.7%), XRCC1 Arg399Gln (8.6%), XRCC3 Thr241Met (7.0%), XPD Lys751Gln (5.2%).\u003c/p\u003e\n\u003cp\u003eAllele and genotype distributions for XRCC1 and XRCC3 conformed to Hardy\u0026ndash;Weinberg equilibrium in both groups (p \u0026gt; 0.05). The exposed group had lower frequencies of wild-type genotypes compared to controls (Table 5).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"705\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSettlement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eRadiation level (mSv/h)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePeople\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMetaphases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eTotal aberrant cells\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"7\" valign=\"top\"\u003e\n \u003cp\u003eSelected disease groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChromosomal abnormalities (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeoplasms (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBlood and hematopoietic diseases (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEndocrine diseases (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNervous system diseases (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRespiratory diseases (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCongenital anomalies (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAkshukyr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBaskudyk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27,59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3,12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAtameken\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2792\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15,52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMangystau\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2,01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0,51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4,68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Correlation coefficients between environmental radiation exposure and prevalence of selected disease groups\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.5. Population Morbidity Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis by age group showed that blood and hematopoietic system disorders were most prevalent among children \u0026lt;14 years (20.2% of all cases), followed by adolescents (11.6%) and adults (7.3%).\u003c/p\u003e\n\u003cp\u003eNeoplasms occurred exclusively among adults (0.7%), while congenital anomalies were most common in children (1.8%). District-level analysis indicated that Munaily District had higher rates of adolescent blood disorders (19.1%) and congenital anomalies (1.6%) compared to Tupkaragan District.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.6. Correlation Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePearson\u0026rsquo;s correlation analysis demonstrated strong positive correlations between chromosomal abnormalities and endocrine disorders (r = 0.85), congenital anomalies (r = 0.82), and nervous system diseases (r = 0.80). Moderate correlations were observed for respiratory diseases (r = 0.63). Weak or negative correlations were found for neoplasms (r = \u0026ndash; 0.32) and blood disorders (r = \u0026ndash; 0.41).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003e4.1. Key Findings\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study demonstrates that residents living near a solid radioactive waste disposal site in Western Kazakhstan exhibit significantly elevated genomic instability \u0026ndash; as evidenced by increased micronucleus (MN) frequencies, higher rates of chromosomal aberrations, and altered distributions of DNA repair gene mutation (XRCC1, XRCC3) and polymorphisms. These cytogenetic and molecular alterations correlate strongly with heightened prevalence of endocrine disorders, congenital anomalies, and nervous system diseases in the exposed population.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.2. Comparison with International and Regional Literature\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eOur findings align with global observations regarding chronic low-dose radiation exposure and its genomic consequences. For example, occupationally exposed interventional cardiology/radiology staff exhibit increased MN frequencies and cytogenetic damage, consistent with chronic low-dose exposure effects\u0026nbsp;[34].\u003c/p\u003e\n\u003cp\u003eA human biodosimetry literature indicates low but measurable background levels of unstable chromosome aberrations in general populations and provides cut-offs for distinguishing background vs. exposure in dicentric assays; our observed elevations in exposed residents exceed these background expectations [35,36].\u003c/p\u003e\n\u003cp\u003eStudies in interventional radiologists/cardiologists have also documented genomic integrity impacts from occupational low-dose exposure, reinforcing that even low-level exposures can trigger detectable cytogenetic changes [34].\u003c/p\u003e\n\u003cp\u003eIn contrast, some high-quality work on populations affected by the Chernobyl accident found no systematic increase in de novo germline mutation rates in children of exposed parents, while earlier minisatellite analyses reported elevated germline mutation rates after Chernobyl\u0026mdash;highlighting heterogeneity across endpoints and study designs [37,38].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.3. Mechanistic Insights and Emerging Molecular Understanding\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eRadiation-induced genomic instability likely arises via both direct and indirect mechanisms. Low-dose ionizing radiation can trigger oxidative DNA damage, double-strand breaks, and bystander effects where signals from irradiated cells impact neighboring cells \u0026ndash; even at low doses [39,40].\u003c/p\u003e\n\u003cp\u003eTranscriptomic and epigenetic studies support dose-dependent modulation of cellular pathways and non-targeted responses at low doses; epigenetic alterations (e.g., DNA methylation, histone modifications) have been linked to reproductive dysfunction and may contribute to congenital outcomes observed in exposed communities [41\u0026ndash;44].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.4. Regional Specificity \u0026mdash; A Unique Exposure Model\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eUnlike well-studied high-dose events like Chernobyl or Fukushima, this study centers on chronic low-dose exposure resulting from solid radioactive waste in close proximity to human habitation. Historical data around Chernobyl reported substantially increased minisatellite mutation rates in exposed families, suggesting potential intergenerational genomic effects, whereas newer sequencing-based analyses in humans report little or no increase in de novo germline SNV rates; together, these underscore how exposure pattern, biological endpoint, and latency shape observed outcomes [37,38].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.5. Strengths and Limitations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStrengths: integrated environmental radiology, cytogenetics, molecular genotyping, and health outcomes; use of literature-based background expectations for unstable aberrations as an internal reference [35,36].\u003c/p\u003e\n\u003cp\u003eLimitations: modest sample sizes in molecular subgroups; cross-sectional design; incomplete control for co-exposures and lifestyle.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4.6. Public Health Implications and Future Directions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe documented genomic effects and their correlation with adverse health outcomes underscore the need for targeted medical-genetic monitoring in affected communities. Regular cytogenetic screening, coupled with molecular assays, may facilitate early detection of vulnerable individuals. Policy directions include protective measures, remediation, and sustained surveillance aligned with SDG 3 and SDG 15 [45,46].\u003c/p\u003e\n\u003cp\u003eFuture work should include longitudinal designs, dose reconstruction, and biodosimetry markers such as \u0026gamma;-H2AX for improved dose estimation under uncertainty, noting recent inter-laboratory and methodological advances [47\u0026ndash;50].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eResidents living near a solid radioactive waste disposal site in Western Kazakhstan demonstrated elevated genomic instability, as indicated by increased micronucleus frequency, higher rates of structural chromosomal aberrations, and altered DNA repair gene polymorphism profiles. These biological changes correlated with higher prevalence of endocrine disorders, congenital anomalies, and nervous system diseases. The findings highlight the need for continuous medical\u0026ndash;genetic monitoring, targeted public health interventions, and further research into the long-term and intergenerational effects of chronic low-dose radiation exposure\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEPR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eElectron Paramagnetic Resonance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eDeoxyribonucleic Acid\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eXRCC1, XRCC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eX-ray Repair Cross Complementing genes 1 and 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNCBI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNational Center for Biotechnology Information\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMicronucleus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eChMZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eChemical and Hydrometallurgical Plant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSDG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSustainable Development Goals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eROS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eReactive Oxygen Species\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePolymerase Chain Reaction\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRAPD-PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRandomly Amplified Polymorphic DNA–PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003eThis study was approved by the Expert Committee (Chairman: Professor L.B. Dzhansugurova) at the Institute of Genetics and Physiology, Ministry of Science and Higher Education of the Republic of Kazakhstan, Almaty. Written informed consent was received from all blood donors prior to sample collection.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSupplementary Materials:\u0026nbsp;\u003c/strong\u003eNo supplementary materials are available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, A.B. and A.K.; methodology, O.Ch.; software, A.M.; validation, A.B., K.Sh.; formal analysis, A.K.; investigation, O.Ch.; resources, O.Ch.; data curation, K.Sh.; writing — original draft preparation, A.M.; writing — review and editing, A.B.; visualization, A.K.; supervision, A.B.; project administration, A.K.; funding acquisition, A.B. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was funded by the Ministry of Science and Higher Education of the Republic of Kazakhstan, Grant No. AP19680351.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data presented in this study are not publicly available due to privacy, ethical, and legal restrictions related to medical and genetic information of study participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their sincere gratitude to Professor Bakhytzhan Bekmanov, Head of the Laboratory of the Research Institute of Genetics and Physiology, Ministry of Science and Higher Education of the Republic of Kazakhstan, for his ongoing advisory assistance in conducting laboratory studies. We also thank the staff of the Radiological Laboratory of the Scientific and Practical Center for Sanitary and Epidemiological Expertise and Monitoring (Almaty, Kazakhstan) for technical support in radionuclide measurements, and the local health authorities of Mangystau Region for assistance in organizing fieldwork.\u003c/p\u003e\n\u003cp\u003eDuring the preparation of this manuscript, the authors used ChatGPT (GPT-5, OpenAI, 2025) for the purposes of language editing, improving academic style, and refining the structure of the introduction and methods sections. The authors have reviewed and edited the output and take full responsibility for the content of this publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMa, L.; Zhang, Y.; Xu, J.; Yu, Y.; Zhou, P.; Liu, X.; Guan, H. Effects of Ionizing Radiation on DNA Methylation Patterns and Their Potential as Biomarkers. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cstrong\u003e2025\u003c/strong\u003e, \u003cem\u003e26\u003c/em\u003e, 3342. https://doi.org/10.3390/ijms26073342.\u003c/li\u003e\n\u003cli\u003eSiama, Z.; et al. Chronic Low Dose Exposure of Hospital Workers to Ionizing Radiation Leads to Increased Micronuclei Frequency and Reduced Antioxidants in Their Peripheral Blood Lymphocytes. \u003cem\u003eInt. J. Radiat. Biol.\u003c/em\u003e \u003cstrong\u003e2019\u003c/strong\u003e, \u003cem\u003e95\u003c/em\u003e, 697–709. https://doi.org/10.1080/09553002.2019.1571255.\u003c/li\u003e\n\u003cli\u003eLusiyanti, Y.; Tetriana, D.; Suvifan, V.A.; Kisnanto, T.; Yusuf, D.; Budiantari, C.T.; Surniyantoro, H.N.E.; Hasan Basri, I.K.; Purnami, S. Preliminary Study of Spontaneous Micronuclei and Hematology Profile of Workers Exposed to Low-Dose Radiation. \u003cem\u003eAsian Pac. J. 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Rep.\u003c/em\u003e \u003cstrong\u003e2025\u003c/strong\u003e, \u003cem\u003e15\u003c/em\u003e, 20262. https://doi.org/10.1038/s41598-025-07030-5.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"environment, cytogenetics, molecular genetics, chromosomal abnormalities, gene polymorphism, human health","lastPublishedDoi":"10.21203/rs.3.rs-7461846/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7461846/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Environmental radiation exposure is a well-recognized risk factor for genomic instability and adverse health outcomes. Kazakhstan hosts multiple legacy radioactive waste disposal sites, including settlements in Western Kazakhstan located in close proximity to solid radioactive waste. While the health effects of the Semipalatinsk Nuclear Test Site have been studied extensively, the long-term cytogenetic and molecular genetic consequences of chronic low-dose exposure from radioactive waste storage remain poorly characterized. This study aimed to investigate the impact of chronic radiation exposure on genome stability and population health in residents of contaminated areas compared with non-exposed controls.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Peripheral blood samples were collected from residents living near a radioactive waste disposal site and from controls residing in non-contaminated regions. Cytogenetic analyses, including the micronucleus test and metaphase chromosome analysis, revealed significantly elevated frequencies of micronuclei and chromosomal aberrations among exposed individuals. Mutant allele distributions of DNA repair genes (XRCC1, XRCC3, and XPD) also differed between exposed and control groups. Correlation analysis demonstrated strong associations between chromosomal instability and increased prevalence of endocrine disorders, congenital anomalies, and nervous system diseases in the exposed population. These findings are consistent with international reports on chronic low-dose exposure and highlight the potential contribution of both genetic and environmental factors to population health risks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions: Residents living in close proximity to radioactive waste disposal sites in Western Kazakhstan exhibit measurable genomic instability and altered DNA repair gene profiles. These biological effects are associated with higher rates of specific health disorders, underscoring the urgent need for systematic medical-genetic monitoring, public health interventions, and environmental remediation. This study provides one of the first integrated analyses of chronic low-dose radiation exposure in Central Asia and contributes to global understanding of radiation-induced genomic instability.\u003c/p\u003e","manuscriptTitle":"Effects of Radiation Contamination on Human Genome Stability and Health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-11 14:10:30","doi":"10.21203/rs.3.rs-7461846/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ecc64d07-16b8-4004-8e60-645e58fb04de","owner":[],"postedDate":"September 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-11T14:10:30+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-11 14:10:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7461846","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7461846","identity":"rs-7461846","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}