Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2022 May 12;63(4):184–189. doi: 10.1002/em.22483

In vitro relationships of galactic cosmic radiation and epigenetic clocks in human bronchial epithelial cells

Jamaji C Nwanaji‐Enwerem 1,2,✉, Philippe Boileau 3, Jonathan M Galazka 4, Andres Cardenas 2
PMCID: PMC9233067  NIHMSID: NIHMS1801574  PMID: 35470505

Abstract

Ionizing radiation is a well‐appreciated health risk, precipitant of DNA damage, and contributor to DNA methylation variability. Nevertheless, relationships of ionizing radiation with DNA methylation‐based markers of biological age (i.e. epigenetic clocks) remain poorly understood. Using existing data from human bronchial epithelial cells, we examined in vitro relationships of three epigenetic clock measures (Horvath DNAmAge, MiAge, and epiTOC2) with galactic cosmic radiation (GCR), which is particularly hazardous due to its high linear energy transfer (LET) heavy‐ion components. High‐LET 56Fe was significantly associated with accelerations in epiTOC2 (β = 192 cell divisions, 95% CI: 71, 313, p‐value = .003). We also observed a significant, positive interaction of 56Fe ions and time‐in‐culture with epiTOC2 (95% CI: 42, 441, p‐value = .019). However, only the direct 56Fe ion association remained statistically significant after adjusting for multiple hypothesis testing. Epigenetic clocks were not significantly associated with high‐LET 28Si and low‐LET X‐rays. Our results demonstrate sensitivities of specific epigenetic clock measures to certain forms of GCR. These findings suggest that epigenetic clocks may have some utility for monitoring and better understanding the health impacts of GCR.

Keywords: DNA methylation, epigenetic age, Fe, mitotic clock, radiation, Si, X‐ray

Abbreviations

DNAmAge

Horvath DNA methylation age

EpiTOC2

epigenetic time to cancer‐2

GCR

galactic cosmic radiation

LET

linear energy transfer

MiAge

mitotic age

1. INTRODUCTION

Various forms of radiation are widely appreciated contributors to human cancer. For instance, ultraviolent solar radiation has been identified as the main causal factor in developing skin neoplasms (Narayanan et al., 2010). Meanwhile, ionizing radiation has been implicated in a host of solid and liquid cancers (Brenner et al., 2003). One of the main mechanisms by which radiation exerts its harmful effects is through DNA damage, including double‐stranded breaks (Sanders et al., 2020). Still, there is evidence that radiation may also alter phenotypes through DNA‐based epigenetic modifications, particularly DNA methylation alterations (Miousse et al., 2018). One 2018 in vitro study, used a human bronchial epithelial cell line to explore the relationships of high linear energy transfer (LET) galactic cosmic radiation (GCR) (56Fe and 28Si ions) as well as terrestrial low‐LET X‐rays on genome‐wide DNA methylation patterns (Kennedy et al., 2018). The authors were able to identify signature CpGs that were associated with each type of radiation and were able to use the 56Fe ion methylation signatures to identify tumor versus normal lung tissue. Despite this epigenome‐wide evidence, studies examining the relationships between radiation exposure and epigenetic clocks in humans have been more limited. Some of the existing evidence in this area comes from an analysis of childhood cancer survivors using a three CpG measure of biological aging. The study found that survivors who received total body irradiation and a hematopoietic stem cell transplant were biologically older than childhood cancer survivors who did not receive radiation (Daniel et al., 2018). Two studies of head/neck cancer and early‐stage breast cancer patients found significant acceleration in blood epigenetic clocks following patients' treatment with radiation therapies (Sehl et al., 2020; Xiao et al., 2021). However, when considering results beyond observational data, an earlier in vitro study interested in the relationship of epigenetic clocks and DNA damage‐related senescence found no significant relationships between Horvath DNAmAge and 10Gy X‐ray exposure even after 14 days of culture (Lowe et al., 2016).

In the present analysis, we use the aforementioned human bronchial epithelial cell dataset (Kennedy et al., 2018) to explore in vitro relationships of three types of radiation exposure (high‐LET 56Fe, high‐LET 28Si, and low‐LET X‐rays) with three epigenetic clocks (Horvath DNA methylation age [DNAmAge], Epigenetic Time to Cancer‐2 [epiTOC2], and Mitotic Age [MiAge]). These markers were selected given their strong relationships with cancer, which was of specific interest in the original study of Kennedy et al., 2018. The Horvath DNAmAge biomarker is a largely tissue‐independent predictor of chronological age and an estimate of biological aging calculated from 353 CpG sites (Horvath, 2013). In addition, accelerated DNAmAge is associated with adverse environmental exposures and increased cancer risk (Dhingra et al., 2018; Lau & Robinson, 2021). The epiTOC2 biomarker is calculated from 163 CpG sites and estimates the cumulative number of stem cell divisions (mitotic counts) in a tissue. Acceleration of the epiTOC2 biomarker has been associated with numerous cancers and pre‐invasive cancer lesions including lung adenocarcinoma and carcinoma in situ (Teschendorff, 2020). MiAge is calculated from 268 CpG sites and estimates the total number of lifetime cell divisions of a tissue. Prior research comparing tumors to normal adjacent tissues has shown that MiAge is universally accelerated in 13 cancer types (including lung squamous cell cancer) and is associated with worse cancer survival (Youn & Wang, 2018). We hypothesized that ionizing radiation exposure, particularly the hazardous high‐LET heavy‐ion components, would accelerate epigenetic clocks, thus, reflecting increased cancer and disease risk. Another important impetus for this study is that radiation can also be offered as a cancer therapeutic. Hence, building a more comprehensive understanding of radiation toxicity and potential biomarkers may be of immense public health benefit.

2. MATERIALS AND METHODS

2.1. Study data and radiation exposure

Our analyses used a publicly available NCBI GEO Methylation450K BeadChip human bronchial epithelial cell dataset (Series GSE108187 on “https://www.ncbi.nlm.nih.gov/geo”) also available in the NASA GeneLab repository (https://genelab-data.ndc.nasa.gov/genelab/accession/GLDS-317/). The dataset is comprised of 102 samples. Based on information in the original publication (Kennedy et al., 2018), the immortalized human bronchial epithelial cells (HBEC3‐KT) were grown in 5% CO2 at 37°C and passaged (1:4) twice a week for 3 months. From each passage, cell pellets were collected, flash‐frozen, and stored of −80°C for later DNA extraction. Three biological replicate cultures were independently irradiated. 56Fe doses were 0, 0.1, 0.3 or 1.0 Gy (Beam energy: 600 MeV/u; dose rate for the 0.1 Gy dose was 0.1 Gy/min, for the 0.3 Gy dose, 0.3 Gy/min, and for the 1.0 Gy dose, 1 Gy/min). 28Si doses were 0.0, 0.3, 1.0 Gy (Beam energy: 300 MeV/u; dose rate for the 0.3 Gy dose was 0.28 Gy/min, and for the 1.0 Gy dose, 0.63 Gy/min). X‐ray doses were 0 and 1.0 Gy (beam energy 320 kV; dose rate ~ 1 Gy/min). The 0.0 Gy mock irradiated samples were seeded at the same time as the experimental samples but were not placed in the radiation beam line. Immediately after irradiation, cultures were returned to their 37°C incubator for 48 h before pellets were collected. The remaining cells continued to be passaged for additional time points for a 3‐month period. Additional detail regarding cell handling, DNA extraction, and methylation processing can be found in the original publication (Kennedy et al., 2018). Final 102 samples include the following exposures: 56Fe ions (4 doses × 4‐time points × 3 replicates [4 removed in QC and not uploaded to NCBI] = 44 samples); 28Si ions (3 doses × 4‐time points × 3 replicates = 36 samples); X‐ray (2 doses × 4‐time points × 3 replicates [2 removed in QC and not uploaded to NCBI] = 22 samples).

2.2. Calculation of epigenetic clocks

We identified three cancer‐relevant epigenetic clocks that could be applied to a human bronchial epithelial cell line: DNAmAge (Horvath, 2013), EpiTOC2 (Teschendorff, 2020), and MiAge (Youn & Wang, 2018). DNAmAge was calculated by uploading the downloaded methylation Beta values to a publicly available online calculator (http://dnamage.genetics.ucla.edu). EpiTOC2 was calculated from the downloaded methylation Beta values using instructions and R code available at https://doi.org/10.5281/zenodo.2632938. MiAge was calculated from the downloaded methylation Beta values using instructions and R code available at http://www.columbia.edu/~sw2206/softwares.htm.

2.3. Statistical analysis

In our primary analysis, we used linear models and all available data points to model the relationships between doses of each of the three radiation exposures and each of the three epigenetic clocks. These models were also adjusted for time‐in‐culture. We next ran models that included an interaction term between radiation dose and time‐in‐culture. As a final assessment of modeling assumptions, we ran a sensitivity analysis testing the relationships between time‐in‐culture and the epigenetic clocks. Lastly, we looked for overlaps between epigenetic clock component CpGs and CpGs previously associated with radiation exposures (Kennedy et al., 2018). All statistical analyses were performed using R Version 4.1.0 (R Core Team, Vienna, Austria) and a p‐value <.05 was used as the threshold for statistical significance. We further adjusted for multiple testing using the Holm method to control for the family‐wise error rate (FWER) at .05.

3. RESULTS

3.1. Direct radiation dose and epigenetic clock relationships

Table 1 presents the results from the models examining relationships between radiation doses and epigenetic clocks. Increases in high‐LET 56Fe were significantly associated with increases in epiTOC2 (β = 192 cell divisions, 95% CI: 71, 313, p‐value = .003). This relationship remained statistically significant after adjusting for multiple hypothesis testing using the Holm method (adjusted p‐value = .047). High‐LET 56Fe was not significantly associated with DNAmAge or MiAge. Furthermore, there were no significant associations of high‐LET 28Si or low‐LET X‐rays with any of the epigenetic clocks.

TABLE 1.

Relationships of ionizing radiation with epigenetic clocks

Model Radiation Clock Difference in epigenetic clock p‐value 95% CI low 95% CI high Adj. p‐value (Holm)
No Interaction 56Fe DNAmAge −56.448 0.866 −730.107 617.210 1.000
No Interaction 56Fe MiAge 107.362 0.061 −4.987 219.711 0.969
No Interaction 56Fe epiTOC2 192.248 0.003 71.220 313.276 0.047
No Interaction 28Si DNAmAge 275.559 0.356 −323.171 874.288 1.000
No Interaction 28Si MiAge 30.022 0.454 −50.564 110.608 1.000
No Interaction 28Si epiTOC2 −16.205 0.839 −177.087 144.677 1.000
No Interaction X‐ray DNAmAge −72.308 0.860 −915.918 771.302 1.000
No Interaction X‐ray MiAge −18.266 0.681 −109.761 73.228 1.000
No Interaction X‐ray epiTOC2 66.392 0.162 −29.063 161.848 1.000
Interaction 56Fe DNAmAge −366.219 0.508 −1474.651 742.213 1.000
Interaction 56Fe MiAge 102.993 0.270 −83.032 289.018 1.000
Interaction 56Fe epiTOC2 241.427 0.019 42.011 440.843 0.321
Interaction 28Si DNAmAge −9.134 0.983 −894.332 876.063 1.000
Interaction 28Si MiAge 21.556 0.718 −98.990 142.101 1.000
Interaction 28Si epiTOC2 13.900 0.907 −226.448 254.247 1.000
Interaction X‐ray DNAmAge −516.243 0.392 −1753.600 721.114 1.000
Interaction X‐ray MiAge 50.864 0.422 −79.049 180.778 1.000
Interaction X‐ray epiTOC2 105.842 0.134 −35.745 247.430 1.000
Open in a new tab

Notes: Summary of tests assessing the associations between various radiation types and epigenetic clocks. Estimates and tests for the “No Interaction” models correspond to the slope coefficients of the radiation dose in the linear models with no interaction between radiation dose and time‐in‐culture. Estimates and tests for the “Interaction” models correspond to the slopes of the radiation dose and time‐in‐culture interactions in the interaction models. All nominal p‐values were adjusted at once using Holm's procedure; only one test was found to be significant at the 5% FWER level.

3.2. Radiation dose and time‐in‐culture interactions

Table 1 also presents relationships between radiation dose and time‐in‐culture interactions with each of the epigenetic clocks. We observed a significant, positive interaction of high‐LET 56Fe and time‐in‐culture with epiTOC2 (95% CI: 42, 441, p‐value = .019). However, this association was no longer statistically significant after Holm adjustment (adjusted p‐value = .321). High‐LET 56Fe and time‐in‐culture interactions were not significantly associated with DNAmAge or MiAge. There were no significant interactions of high‐LET 28Si or low‐LET X‐rays with any of the epigenetic clocks. In our sensitivity analysis, in the absence of radiation, time‐in‐culture had the strongest relationships with batch‐adjusted epiTOC2 (r = 0.89) and MiAge (r = 0.82) values (Figure 1). The relationship with batch‐adjusted DNAmAge was weaker (r = 0.25).

FIGURE 1.

FIGURE 1

Open in a new tab

Association of Time‐in‐Culture and Epigenetic Clocks in the absence of radiation. Presents the time‐in‐culture and batch‐adjusted epigenetic clock outputs' (DNAmAge, MiAge, and epiTOC2) correlation coefficients. Radiation‐type‐specific batch effects were mitigated by de‐meaning these groups' epigenetic clock outputs prior to estimating the correlation coefficients.

3.3. Overlapping CpG relationships

To help explain our results, we examined if there was any overlap between the CpGs that make up the epigenetic clocks and the CpGs previously associated with the three radiation types (high‐LET 56Fe, high‐LET 28Si, and low‐LET X‐rays) (Figure 2). There was no overlap between epiTOC2 component CpGs and CpGs associated with high‐LET 56Fe. The DNAmAge and epiTOC2 biomarkers share the component site cg10281002. MiAge and epiTOC2 shared the component site cg19761848. MiAge component site cg13389502 was associated with high‐LET 56Fe. Site cg19567866 was associated with both high‐LET 56Fe and high‐LET 28Si. Sites cg04444086 and cg09518151 were associated with both high‐LET 56Fe and low‐LET X‐rays. Finally, DNAmAge sites cg04452713 and cg21395782 were associated with high‐LET 56Fe.

FIGURE 2.

FIGURE 2

Open in a new tab

Overlap between epigenetic clock component CpGs and CpGs associated with radiation. Venn diagram demonstrating overlaps between CpGs associated with radiation types (high‐LET 56Fe, high‐LET 28Si, and low‐LET X‐rays) and epigenetic clock (DNAmAge, MiAge, and epiTOC2) component CpGs. One CpG is shared between epiTOC2 and DNAmAge (a), one CpG is shared between epiTOC2 and MiAge (B), one CpG is shared between 56Fe and MiAge (c), one CpG is shared between 56Fe and 28Si (d)], two CpGs are shared between 56Fe and X‐rays (e), and two CpGs are shared between 56Fe and DNAmAge (f)

4. DISCUSSION

In this experimental study of human bronchial epithelial cells, we examined relationships of high‐ and low‐LET radiation exposures with three epigenetic clocks (DNAmAge, epiTOC2, and MiAge). The interaction between time‐in‐culture and high‐LET 56Fe exposure along with high‐LET 56Fe exposure alone was significantly associated with increases in epiTOC2 estimated stem cell divisions. The direct high‐LET 56Fe and epiTOC2 association remained statistically significant following adjustments for multiple hypothesis testing. Neither high‐LET 28Si nor low‐LET X‐rays were associated with any of the epigenetic clocks tested. Furthermore, we found no overlap when comparing CpGs previously associated with 56Fe ion exposure (Kennedy et al., 2018) and component CpGs of epiTOC2.

We used publicly available data to build upon the work of Kennedy et al., 2018. The authors were interested in building a better understanding of the biological health risks of galactic cosmic radiation (GCR) to better inform human space travel. Thus, they examined the impact of high linear energy transfer GCR (56Fe and 28Si ions) as well as terrestrial low linear energy transfer X‐rays on genome‐wide DNA methylation patterns in human bronchial epithelial cells in culture. Their experiments demonstrated that 56Fe ions primarily induced hypermethylation, X‐rays primarily induced hypomethylation, and 28Si had mixed effects. They identified 935 CpG sites that were associated with 56Fe ions, 300 CpGs associated with 28Si ions, and 1150 CpGs associated with X‐rays. To determine the relevance of the methylation changes to human lung cancer, the authors then used the significant CpGs to build signatures to distinguish primary lung tumor for normal tissues available in the Cancer Genome Atlas Project. Only the 56Fe ion sites reasonably distinguished between tumor and normal specimens in human adenocarcinoma and squamous cell carcinoma of the lung (Kennedy et al., 2018).

To meaningfully add to these results, our analyses focused on epigenetic clocks, which have been demonstrated to have robust associations with cancer but whose relationships with radiation exposure remain understudied (Lau & Robinson, 2021). Given the adverse nature of radiation exposure, we hypothesized that radiation exposures, primarily the high‐LET ions, would be associated with the acceleration of the epigenetic clocks. In line with findings from Kennedy et al., 2018, our most robust associations were with 56Fe ions. In our study, 56Fe ions were the only radiation type associated with an epigenetic clock. In line with our hypothesis, increases in the dose of 56Fe ion exposure were associated with increases in epiTOC2, suggesting increased cancer risk from this exposure. We observed no associations with 28Si ions or X‐rays. Given that the cells were cultured for ~3 months, Kennedy et al., 2018 were also able to explore radiation‐induced DNA methylation changes over time. They found that radiation‐induced methylation changes occurred early but did not change over time. This finding is also in line with our observed statistically significant direct 56Fe association, but the time‐in‐culture and 56Fe ion interaction no longer being statistically significant after adjusting for multiple hypothesis testing. Our findings together with the inability of 28Si or X‐ray associated CpGs to delineate between tumor and normal tissues suggest that DNA methylation and epigenetic clocks are more sensitive to 56Fe ions and their cancer‐related risks. We found no overlap between CpGs previously associated with 56Fe exposure (Kennedy et al., 2018) and component CpGs of epiTOC2 to help explain this differential sensitivity.

We explicitly considered why epiTOC2, and not DNAmAge or MiAge, was sensitive to 56Fe ions. Especially, since CpGs associated with 56Fe ions are also MiAge (cg13389502 [HIC1]) and DNAmAge (cg04452713 [DST], cg21395782 [NDUFA13]) component CpGs. The HIC1 gene is a tumor repressor and growth regulatory gene (Pinte et al., 2004) while DST and NDUFA13 encode a cytoskeletal linker protein (Brown et al., 1995) and a subunit of the mitochondrial membrane respiratory chain NADH dehydrogenase (Angebault et al., 2015), respectively. It seems unlikely that it is due to correlations given that epiTOC2 was only marginally better correlated with time‐in‐culture than MiAge. These differences in exposure sensitivity are more likely due to robust differences in component CpGs. For example, epiTOC2 only shares one CpG with DNAmAge (cg10281002 [TBX5]) and MiAge (cg19761848 [GBX2]), respectively. TBX5 and GBX2 encode transcription factors involved in development (Lin et al., 1996; McDermott et al., 2005).

Importantly, there was also very little overlap between radiation exposure associated CpGs suggesting that the exposures themselves generated very different DNA methylation changes. Only one CpG was shared between 56Fe and 28Si ion exposures (cg19567866 [SPOCK1]). The SPOCK1 gene encodes a protein thought to regulate epithelial to mesenchymal transitions in cancer cells (Sun et al., 2020). Two CpGs were shared between 56Fe and X‐ray exposures (cg04444086 [SSTR5‐AS1], cg09518151 [LYG1]). SSTR5‐AS1 is an antisense RNA gene associated with cancer (Wang et al., 2019) while LYG1 is involved in lysozyme activity (Liu et al., 2021).

Despite our novel findings, this study has some important limitations. First this is an experimental study based on cell culture data and physiological relationships may differ in in vivo contexts or with primary tissues. Second, cells were exposed to radiation at 0, 0.1, 0.3, and 1.0 Gy. These exposures are likely to differ in real‐life contexts. For instance, a single chest X‐ray has an approximate radiation dose of 0.1 mSv (0.0001 Gy) or 10 days of natural background radiation exposure (Diederich & Lenzen, 2000). Some may argue that our study then speaks to more chronic radiation exposure but this is relevant for long space missions. Nevertheless, additional studies will be necessary to test that assertion and test if the observed associations persist at lower acute radiation exposures.

In conclusion, our study uses epigenetic clocks to provide novel evidence that DNA methylation may be a sensitive biomarker of high‐LET 56Fe ion exposure. This finding adds to the body of literature suggesting that epigenetic clocks may be useful in monitoring the health of humans exposed to radiation including those whose exposures happen during spaceflight (Nwanaji‐Enwerem et al., 2020). Still, future studies will be important for further characterizing these relationships and improving our understanding of epigenetic clock and radiation relationships.

AUTHOR CONTRIBUTIONS

Jamaji C. Nwanaji‐Enwerem performed data analysis, visualization, developed analytical methodology, original writing, review & editing of final manuscript. Philippe Boileau performed data curation, data analysis, visualization, developed analytical methodology, original writing, review & editing of final manuscript. Andres Cardenas conceived the original study, supervised and reviewed statistical analyses, and contributed to writing/editing of the manuscript. Jonathan M. Galazka supervised and reviewed statistical analyses, and contributed to writing/editing of the manuscript.

CONFLICT OF INTEREST

The authors declare no conflict of interests.

FUNDING

Jamaji C. Nwanaji‐Enwerem and Andres Cardenas are supported by the National Institutes of Health grants R03AG067064 and R01ES031259. Philippe Boileau gratefully acknowledges the support of the Fonds de recherche du Québec—Nature et technologies and the Natural Sciences and Engineering Research Council of Canada.

ACKNOWLEDGMENTS

The authors acknowledge and thank Kennedy, E.M., Powell, D.R., Li, Z., Bell, J.S.K., Barwick, B.G., Feng, H., McCrary, M.R., Dwivedi, B., Kowalski, J., Dynan, W.S. and Conneely, K.N. for making their dataset publicly available.

Nwanaji‐Enwerem, J.C. , Boileau, P. , Galazka, J.M. & Cardenas, A. (2022) In vitro relationships of galactic cosmic radiation and epigenetic clocks in human bronchial epithelial cells. Environmental and Molecular Mutagenesis, 63(4), 184–189. Available from: 10.1002/em.22483

Accepted by: S. Gaddameedhi

Funding information Fonds de recherche du Québec ‐ Nature et technologies and the Natural Sciences and Engineering Research Council of Canada; National Institutes of Health, Grant/Award Numbers: R01ES031259, R03AG067064

REFERENCES

  1. Angebault, C. , Charif, M. , Guegen, N. , Piro‐Megy, C. , Mousson, B. , de Camaret, V. et al. (2015) Mutation in NDUFA13/GRIM19 leads to early onset Hypotonia, dyskinesia and sensorial deficiencies, and mitochondrial complex I instability. Human Molecular Genetics, 24(14), 3948–3955. 10.1093/hmg/ddv133 [DOI] [PubMed] [Google Scholar]
  2. Brenner, D.J. , Doll, R. , Goodhead, D.T. , Hall, E.J. , Land, C.E. , Little, J.B. et al. (2003) Cancer risks attributable to low doses of ionizing radiation: assessing what we really know. Proceedings of the National Academy of Sciences, 100(24), 13761–13766. 10.1073/pnas.2235592100 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Brown, A. , Dalpé, G. , Mathieu, M. & Kothary, R. (1995) Cloning and characterization of the neural isoforms of human Dystonin. Genomics, 29(3), 777–780. 10.1006/geno.1995.9936 [DOI] [PubMed] [Google Scholar]
  4. Daniel, S. , Nylander, V. , Ingerslev, L.R. , Zhong, L. , Fabre, O. , Clifford, B. et al. (2018) T cell epigenetic remodeling and accelerated epigenetic aging are linked to long‐term immune alterations in childhood cancer survivors. Clinical Epigenetics, 10(November), 138. 10.1186/s13148-018-0561-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Dhingra, R. , Nwanaji‐Enwerem, J.C. , Samet, M. & Ward‐Caviness, C.K. (2018) DNA methylation age‐environmental influences, health impacts, and its role in environmental epidemiology. Current Environmental Health Reports, 5(3), 317–327. 10.1007/s40572-018-0203-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Diederich, S. & Lenzen, H. (2000) Radiation exposure associated with imaging of the chest. Cancer, 89(S11), 2457–2460. [DOI] [PubMed] [Google Scholar]
  7. Horvath, S. (2013) DNA methylation age of human tissues and cell types. Genome Biology, 14(10), R115. 10.1186/gb-2013-14-10-r115 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Kennedy, E.M. , Powell, D.R. , Li, Z. , Bell, J.S.K. , Barwick, B.G. , Feng, H. et al. (2018) Galactic cosmic radiation induces persistent Epigenome alterations relevant to human lung cancer. Scientific Reports, 8(1), 6709. 10.1038/s41598-018-24755-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Lau, C.‐H.E. & Robinson, O. (2021) DNA methylation age as a biomarker for cancer. International Journal of Cancer, 148(11), 2652–2663. 10.1002/ijc.33451 [DOI] [PubMed] [Google Scholar]
  10. Lin, X. , Swaroop, A. , Vaccarino, F.M. , Murtha, M.T. , Haas, M. , Ji, X. et al. (1996) Characterization and sequence analysis of the human Homeobox‐containing gene GBX2. Genomics, 31(3), 335–342. 10.1006/geno.1996.0056 [DOI] [PubMed] [Google Scholar]
  11. Liu, H. , Zhengyu, Y. , Tang, B. , Miao, S. , Qin, C. , Li, Y. et al. (2021) LYG1 deficiency attenuates the severity of acute graft‐versus‐host disease via skewing allogeneic T cells polarization towards Treg cells. Frontiers in Immunology, 12, 647894. 10.3389/fimmu.2021.647894 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Lowe, D. , Horvath, S. & Raj, K. (2016) Epigenetic clock analyses of cellular senescence and ageing. Oncotarget, 7(8), 8524–8531. 10.18632/oncotarget.7383 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. McDermott, D.A. , Bressan, M.C. , He, J. , Lee, J.S. , Aftimos, S. , Brueckner, M. et al. (2005) TBX5 genetic testing validates strict clinical criteria for Holt‐Oram syndrome. Pediatric Research, 58(5), 981–986. 10.1203/01.PDR.0000182593.95441.64 [DOI] [PubMed] [Google Scholar]
  14. Miousse, I.R. , Ewing, L.E. , Kutanzi, K.R. , Griffin, R.J. & Koturbash, I. (2018) DNA methylation in radiation‐induced carcinogenesis: experimental evidence and clinical perspectives. Critical Reviews™ in Oncogenesis, 23(1–2), 1–11. 10.1615/CritRevOncog.2018025687 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Narayanan, D.L. , Saladi, R.N. & Fox, J.L. (2010) Ultraviolet radiation and skin cancer. International Journal of Dermatology, 49(9), 978–986. 10.1111/j.1365-4632.2010.04474.x [DOI] [PubMed] [Google Scholar]
  16. Nwanaji‐Enwerem, J.C. , Nwanaji‐Enwerem, U. , Van Der Laan, L. , Galazka, J.M. , Redeker, N.S. & Cardenas, A. (2020) A longitudinal epigenetic aging and leukocyte analysis of simulated space travel: the Mars‐500 Mission. Cell Reports, 33(10), 108406. 10.1016/j.celrep.2020.108406 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Pinte, S. , Stankovic‐Valentin, N. , Deltour, S. , Rood, B.R. , Guérardel, C. & Leprince, D. (2004) The tumor suppressor gene HIC1 (Hypermethylated in cancer 1) is a sequence‐specific transcriptional repressor: definition of its consensus binding sequence and analysis of its DNA binding and repressive properties. The Journal of Biological Chemistry, 279(37), 38313–38324. 10.1074/jbc.M401610200 [DOI] [PubMed] [Google Scholar]
  18. Sanders, J.T. , Freeman, T.F. , Yang, X. , Golloshi, R. , Stallard, M.A. , Hill, A.M. et al. (2020) Radiation‐induced DNA damage and repair effects on 3D genome organization. Nature Communications, 11(1), 6178. 10.1038/s41467-020-20047-w [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Sehl, M.E. , Carroll, J.E. , Horvath, S. & Bower, J.E. (2020) The acute effects of adjuvant radiation and chemotherapy on peripheral blood epigenetic age in early stage breast cancer patients. NPJ Breast Cancer, 6, 23. 10.1038/s41523-020-0161-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Sun, L.‐R. , Li, S.‐Y. , Guo, Q.‐S. , Zhou, W. & Zhang, H.‐M. (2020) SPOCK1 involvement in epithelial‐to‐mesenchymal transition: a new target in cancer therapy? Cancer Management and Research, 12, 3561–3569. 10.2147/CMAR.S249754 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Teschendorff, A.E. (2020) A comparison of epigenetic mitotic‐like clocks for cancer risk prediction. Genome Medicine, 12(1), 56. 10.1186/s13073-020-00752-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Wang, B. , Zhao, L. , Chi, W. , Cao, H. , Cui, W. & Meng, W. (2019) Aberrant methylation‐mediated downregulation of LncRNA SSTR5‐AS1 promotes progression and metastasis of laryngeal squamous cell carcinoma. Epigenetics & Chromatin, 12(1), 35. 10.1186/s13072-019-0283-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Xiao, C. , Beitler, J.J. , Peng, G. , Levine, M.E. , Conneely, K.N. , Zhao, H. et al. (2021) Epigenetic age acceleration, fatigue, and inflammation in patients undergoing radiation therapy for head and neck cancer: a longitudinal study. Cancer, 127(18), 3361–3371. 10.1002/cncr.33641 [DOI] [PubMed] [Google Scholar]
  24. Youn, A. & Wang, S. (2018) The MiAge calculator: a DNA methylation‐based mitotic age calculator of human tissue types. Epigenetics, 13(2), 192–206. 10.1080/15592294.2017.1389361 [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Environmental and Molecular Mutagenesis are provided here courtesy of Wiley

RESOURCES