NOTE: End date changed to 10/1/2021 per Space Radiation (Ed., 8/2/21)

NOTE: End date changed to 9/30/2021 per L.Lewis/ARC HRP (Ed., 12/9/20)

NOTE: Extended to 5/31/2021 per L. Lewis/ARC HRP (Ed., 9/24/20)

NOTE: Extended to 5/31/2020 per PI (Ed., 11/15/19)

NOTE: Extended to 9/30/2019 per F. Hernandez/ARC (Ed., 2/18/19)

Crews on future exploration missions to Mars and other destinations in our solar system will be exposed to acute low doses (<100 mSv) and chronic low doses (<0.1 mSv/min) of high-LET (linear energy transfer) ionizing radiation from solar particle events (SPE) and galactic cosmic radiation (GCR). Predicting cancer risk associated with these radiation types is a mission-critical challenge for NASA radiation health scientists and mission planners. Epidemiological methods lack sensitivity and power to provide detailed risk estimates for cancer, mainly because the number of exposed individuals to date is relatively small, limited to several hundred individuals exposed to trapped radiation in low Earth orbit and fewer than two dozen Apollo astronauts exposed to GCR for several days at a time. Moreover, population-based studies do not take individual radiation sensitivity into account, are sensitive to the presence of other confounding environmental insults, and require long follow-up times.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at University of California (UC) Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE (high energy particles). Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model used in this work was a resource from the low dose program at DOE (Department of Energy) developed by the Lawrence Berkeley National Laboratory that has made it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.

Such work provides a new approach combining novel biomarkers with sophisticated mathematical analysis to better characterize individual sensitivity to space radiation. Once validated across mice and eventually a large cohort of humans, this approach could be generalized to establish individualized health risk management for astronauts and for the population at large being exposed to ionizing radiation.

We next analyzed human ex vivo immune cell sensitivity to multiple doses of high and low LET ionizing radiation in primary blood mononuclear cells isolated from 750+ healthy donors, followed by low coverage whole genome sequencing to identify the genes and pathways associated with initial DNA damage, persistent DNA damage, and baseline DNA damage. We have also analyzed the demographic associations with DNA damage and repair, and discovered an age-dependent increase in baseline DNA damage coupled with a reduction in ionizing radiation-induced DNA repair, as well as general negative association between baseline DNA damage and radiosensitivity.

The project has resulted in numerous conference presentations as well as 5 primary research manuscripts (Penninckx et al. Radiat Res 2019; Pariset et al. Radiat Res 2020; Pariset et al. Cell Rep 2020; Penninckx et al. Radiat Res 2021; Cekanaviciute et al. Life Sci Space Res 2023) and contributed to 3 reviews (Ray et al. Int J Part Ther 2018; Nikitaki et al. Cancers 2020; Penninckx et al. NAR Cancer 2021) to date, with a manuscript on human genomic associations with radiosensitivity in preparation. The final presentation of the project was given at the NASA Human Research Program (HRP) Investigators’ Workshop in January 2023. (Ed. Note: See Cumulative Bibliography for full citations).

NOTE: End date changed to 10/1/2021 per Space Radiation (Ed., 8/2/21)

NOTE: End date changed to 9/30/2021 per L.Lewis/ARC HRP (Ed., 12/9/20)

NOTE: Extended to 5/31/2021 per L. Lewis/ARC HRP (Ed., 9/24/20)

NOTE: Extended to 5/31/2020 per PI (Ed., 11/15/19)

NOTE: Extended to 9/30/2019 per F. Hernandez/ARC (Ed., 2/18/19)

Crews on future exploration missions to Mars and other destinations in our solar system will be exposed to acute low doses (<100 mSv) and chronic low doses (<0.1 mSv/min) of high-LET (linear energy transfer) ionizing radiation from solar particle events (SPE) and galactic cosmic radiation (GCR). Predicting cancer risk associated with these radiation types is a mission-critical challenge for NASA radiation health scientists and mission planners. Epidemiological methods lack sensitivity and power to provide detailed risk estimates for cancer, mainly because the number of exposed individuals to date is relatively small, limited to several hundred individuals exposed to trapped radiation in low Earth orbit and fewer than two dozen Apollo astronauts exposed to GCR for several days at a time. Moreover, population-based studies do not take individual radiation sensitivity into account, are sensitive to the presence of other confounding environmental insults, and require long follow-up times.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at University of California (UC) Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE (high energy particles). Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model used in this work was a resource from the low dose program at DOE (Department of Energy) developed by the Lawrence Berkeley National Laboratory that has made it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.

Such work provides a new approach combining novel biomarkers with sophisticated mathematical analysis to better characterize individual sensitivity to space radiation. Once validated across mice and eventually a large cohort of humans, this approach could be generalized to establish individualized health risk management for astronauts and for the population at large being exposed to ionizing radiation.

We have irradiated the peripheral blood mononuclear cells (PBMCs) from all remaining subjects, including the repeats of previous BNL experiments that we were unable to analyze previously due to Covid restrictions. We have analyzed their DNA repair kinetics using immunostaining with fluorescently-tagged 53BP1 antibody followed by semi-automated high throughput microscopy, image processing, and quantification. Currently, we are collaborating with the lab of Dr. Christopher Mason at Weill Cornell Medicine to match the phenotypic outcomes of DNA repair with genotypes based on low coverage whole genome sequencing.

In summary, for this project we have collected DNA repair data from 750 subjects, whose PBMCs have been irradiated ex vivo with 3 types of particle radiation (350 MeV/n 28Si, 350 MeV/n 40Ar, 600 MeV/n 56Fe) as well as gamma rays, at 2 doses each (1.1 and 3 particle/100 micrometers2 fluence, which translates to 0.1 Gy and 0.3 Gy for 28Si, 0.18 Gy and 0.5 Gy for 40Ar, and 0.3 Gy and 0.82 Gy for 56Fe respectively; and 0.1 Gy and 1 Gy doses of gamma rays), and at 2 timepoints post irradiation: 4 and 24 hours; as well as at baseline that represents the time of collecting PBMCs. To our knowledge this is the largest such dataset of human ex vivo responses to simulated space radiation. We anticipate that our data, which we will publish open access on NASA GeneLab, will serve as a useful resource for multiple future investigations.

Furthermore, we have collected data on oxidative stress and cell death from a subset of ~400 subjects, analyzed additional responses to 5-ion simplified simulated GCRs (0.25 Gy and 0.5 Gy doses, 4 h and 24 h post irradiation) and 250 MeV/n 4He (0.15 Gy and 0.5 Gy doses, 4 h and 24 h post irradiation) as part of piggyback experiments at NASA Space Radiation Laboratory (NSRL), and collected supernatant for quantifying secreted factors from all our samples for follow-up studies that will be available for potential collaborations. Additional supernatant samples from 24 most variable subjects in response to 56Fe irradiation have also been collected for exosome quantification as part of a Human Research Program (HRP) Augmentation Award to our former postdoctoral scholar Eloise Pariset (awarded January 2021).

Finally, as part of a collaboration with the Mason lab, we have selected 96 subjects with maximal variability in DNA repair responses and collected their RNA for transcriptomic analysis after 56Fe and gamma irradiation (funded by the Mason lab) to validate whether genomic associations with radiosensitivity are reflected in changes in gene expression.

This year we have one review article on DNA damage markers in press (Penninckx et al., Quantification of radiation-induced DNA repair foci to evaluate and predict biological responses to ionizing radiation, NAR Cancer--ed. note: see Bibliography section) and one primary research article under revision (Cekanaviciute et al., Mouse Genomic Associations with Ex Vivo Sensitivity to Simulated Space Radiation). Our research was presented at the Human Research Program Investigators’ Workshop, the National Council on Radiation Protection (NCRP): Biomarkers & Countermeasures and Conclusions conference, the Radiation Research Society Annual Meeting, and the American Society for Gravitational and Space Research Annual Meeting (all Sylvain Costes, oral presentations) and will be presented at COSPAR 2022 (invited presentation, Sylvain Costes)).

Our main future directions for this project are reflected in two key collaborations that we have started this year, with the goals to use the data from this project to generate new results: a) applying AI/ML (artificial intelligence/machine learning) methods to analyze our data (with NASA GeneLab and Frontier Development Lab); and b) using network analysis to compare the effects of spaceflight stressors and terrestrial diseases and repurpose Food & Drug Administration (FDA)-approved therapeutics as countermeasures for space radiation (with the SPOKE project and Baranzini Lab at the University of California, San Francisco, on which we have published a pilot study: Nelson et al., Life 2021).

NOTE: End date changed to 9/30/2021 per L.Lewis/ARC HRP (Ed., 12/9/20)

NOTE: Extended to 5/31/2021 per L. Lewis/ARC HRP (Ed., 9/24/20)

NOTE: Extended to 5/31/2020 per PI (Ed., 11/15/19)

NOTE: Extended to 9/30/2019 per F. Hernandez/ARC (Ed., 2/18/19)

Crews on future exploration missions to Mars and other destinations in our solar system will be exposed to acute low doses (<100 mSv) and chronic low doses (<0.1 mSv/min) of high-LET (linear energy transfer) ionizing radiation from solar particle events (SPE) and galactic cosmic radiation (GCR). Predicting cancer risk associated with these radiation types is a mission-critical challenge for NASA radiation health scientists and mission planners. Epidemiological methods lack sensitivity and power to provide detailed risk estimates for cancer, mainly because the number of exposed individuals to date is relatively small, limited to several hundred individuals exposed to trapped radiation in low Earth orbit and fewer than two dozen Apollo astronauts exposed to GCR for several days at a time. Moreover, population-based studies do not take individual radiation sensitivity into account, are sensitive to the presence of other confounding environmental insults, and require long follow-up times.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at University of California (UC) Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE (high energy particles). Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model used in this work was a resource from the low dose program at DOE (Department of Energy) developed by the Lawrence Berkeley National Laboratory that has made it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.

Such work provides a new approach combining novel biomarkers with sophisticated mathematical analysis to better characterize individual sensitivity to space radiation. Once validated across mice and eventually a large cohort of humans, this approach could be generalized to establish individualized health risk management for astronauts and for the population at large being exposed to ionizing radiation.

We have published 6 peer-reviewed articles based on mouse and human data analysis, with more articles in preparation. We have presented our work in talks and posters in the NASA Human Research Program (HRP) Investigators’ Workshop (presentations: Sylvain Costes, Eloise Pariset) and the Radiation Research Society Annual Meeting (presentation: Sylvain Costes, posters: Eloise Pariset, Egle Cekanaviciute) and have been accepted to present it again at COSPAR (Committee on Space Research) 2021 (invited presentation: Sylvain Costes).

Furthermore, we have been awarded a NASA HRP Tissue Sharing grant (“Mapping peripheral immune signatures of mouse and human responses to space radiation for biomarker identification,” PI: Costes, Co-I/Science PI: Cekanaviciute, Co-I: Pariset) to follow up on this work. We will utilize the samples from this project together with samples collected by Dr. Susanna Rosi’s group on her HRP-funded project on mouse neuroimmune responses to combined exposures to ionizing radiation and simulated microgravity, in order to identify a shared signature of immune responses to spaceflight that could be utilized for biomarker and countermeasure development.

NOTE: Extended to 5/31/2020 per PI (Ed., 11/15/19)

NOTE: Extended to 9/30/2019 per F. Hernandez/ARC (Ed., 2/18/19)

Crews on future exploration missions to Mars and other destinations in our solar system will be exposed to acute low doses (<100 mSv) and chronic low doses (<0.1 mSv/min) of high-LET (linear energy transfer) ionizing radiation from solar particle events (SPE) and galactic cosmic radiation (GCR). Predicting cancer risk associated with these radiation types is a mission-critical challenge for NASA radiation health scientists and mission planners. Epidemiological methods lack sensitivity and power to provide detailed risk estimates for cancer, mainly because the number of exposed individuals to date is relatively small, limited to several hundred individuals exposed to trapped radiation in low Earth orbit and fewer than two dozen Apollo astronauts exposed to GCR for several days at a time. Moreover, population-based studies do not take individual radiation sensitivity into account, are sensitive to the presence of other confounding environmental insults, and require long follow-up times.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at University of California (UC) Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE (high energy particles). Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model used in this work was a resource from the low dose program at DOE (Department of Energy) developed by the Lawrence Berkeley National Laboratory that has made it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.

Such work provides a new approach combining novel biomarkers with sophisticated mathematical analysis to better characterize individual sensitivity to space radiation. Once validated across mice and eventually a large cohort of humans, this approach could be generalized to establish individualized health risk management for astronauts and for the population at large being exposed to ionizing radiation.

During year 3, the Radiation Biophysics Lab at NASA Ames has finished the mouse research component and significantly moved forward with the human research component of this proposal. Human blood sample collection to investigate genomic associations with radiation sensitivity began in February 2018, and by December 2018 we have collected, isolated, and stored peripheral blood mononuclear cells (PBMCs) from 602 healthy subjects, 18-75 years old, 50/50 male/female, of Northern European origin. We have irradiated primary immune cells from the first 192 subjects at Brookhaven National Laboratory (BNL) in the summer 18B run using 350 MeV/n 28Si, 350 MeV/n 38Ar, and 600 MeV/n 56Fe ions and gamma rays, immunostained them with DNA damage marker anti-53BP1, performed high-throughput imaging and quantification of DNA damage foci, and are in the process of analyzing the results. In addition, we have designed a flow cytometry-based analysis of oxidative stress and cell death and used it to quantify the cellular responses to particle and gamma radiation from the first 192 BNL samples. We have also started collecting the supernatants from irradiated cells for potential future analysis of secreted biomarkers of human radiation sensitivity.

Crews on future exploration missions to Mars and other destinations in our solar system will be exposed to acute low doses (<100 mSv) and chronic low doses (<0.1 mSv/min) of high-LET (linear energy transfer) ionizing radiation from solar particle events (SPE) and galactic cosmic radiation (GCR). Predicting cancer risk associated with these radiation types is a mission-critical challenge for NASA radiation health scientists and mission planners. Epidemiological methods lack sensitivity and power to provide detailed risk estimates for cancer, mainly because the number of exposed individuals to date is relatively small, limited to several hundred individuals exposed to trapped radiation in low Earth orbit and fewer than two dozen Apollo astronauts exposed to GCR for several days at a time. Moreover, population-based studies do not take individual radiation sensitivity into account, are sensitive to the presence of other confounding environmental insults, and require long follow-up times.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at University of California (UC) Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE (high energy particles). Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model is an SFA resource that will make it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.

Such work provides a new approach combining novel biomarkers with sophisticated mathematical analysis to better characterize individual sensitivity to space radiation. Once validated across mice and eventually a large cohort of humans, this approach could be generalized to establish individualized health risk management for astronauts and for the population at large being exposed to ionizing radiation.

We identified seven significant associations on chromosomes 2, 3, 7, 10, 11, and 19 corresponding to 350 Mev/n Ar, three significant associations on chromosomes 10 and 13, corresponding to 600 MeV/n Fe, and two significant loci at chromosome 2 and 6, corresponding to 350 MeV/n Si. For both the high LET radiations, Ar and Fe, a common locus on chromosome 10 was identified, with peak SNP as UNC18214722 (p value = 7.22 x 10-7) along with fourteen genes affiliated with chromatin modification, DNA replication, transcription, and double stranded break repair. For 350 Mev/n Ar, additionally, two other peak SNPs were identified on chromosome 10 (JAX00021248, p = 4.24 x 10-6) and on chromosome 11 (UNC20271233, p = 4.03 x 10-6) with five DNA damage response genes. For low LET Si, out of 21 genes in the LD, one repair-associated gene at peak SNP JAX00629117 on chromosome 6 (p = 1.2 x 10-6) was identified. Pathway analysis using DAVID identified DNA repair response as the most enriched pathway.

The second part of our study applies a similar approach to humans and aims to characterize the genomic risk factors associated with sensitivity to ionizing radiation in a large human cohort. We are in the process of collecting peripheral blood mononuclear cells (PBMCs) from a large cohort of at least 500 and up to 700 healthy human volunteers, combining samples from Institut Pasteur in France, Oklahoma Blood Institute, and NASA Ames. We have optimized all relevant protocols to isolate, freeze, thaw, and culture human PBMCs, and in order to measure DNA repair responses, we have developed an experimental setup for high-throughput immunocytochemistry for DNA repair markers 53-bp1 and gamma-H2AX on human PBMCs as well as automated image acquisition and analysis. We will also quantify primary human immune cell death and differentiation into pro- or anti-inflammatory phenotypes.

We will participate in the BNL (Brookhaven National Laboratory) summer and fall 2018 runs where we will expose these human PBMCs to high-LET radiation. Specifically, in summer 2018 we will expose PBMCs from 100 subjects (50 of the most susceptible and 50 of the least susceptible to low-LET radiation) to 2 fluences (1.1 and 3 particles/100um^2) of 14Si, 18Ar, and 26Fe ions and isolate them at 4 h, 24 h, and 48 h after irradiation to measure the time course of DNA repair and cellular responses. In fall 2018, we will repeat this experiment with PBMCs from 300 subjects, focusing specifically on responses to Fe irradiation. In this way, we have expanded our original experimental plan to include more subjects, which will allow us to achieve more conclusive results on modeling responses to high-LET radiation-induced DNA damage and repair.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at University of California (UC) Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE (high energy particles). Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model is an SFA resource that will make it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.

Such work provides a new approach combining novel biomarkers with sophisticated mathematical analysis to better characterize individual sensitivity to space radiation. Once validated across mice and eventually a large cohort of humans, this approach could be generalized to establish individualized health risk management for astronauts and for the population at large being exposed to ionizing radiation.

Overall, our results suggest that repair kinetic found in skin is a surrogate marker for in vivo radiation sensitivity in other tissue, such as blood cells and such response is modulated by genetic. On the other hand, different genes seem to be involved for low dose of low-LET sensitivity versus high dose low-LET or high-LET sensitivity. This work also validates our hypothesis showing that DNA repair kinetic following high doses of X-ray is an accurate predictor for radiation sensitivity to high-LET when evaluated on cell culture.

Single-nucleotide polymorphism arrays are currently being used to identify potential pools of genes responsible for radiation sensitivity to low-LET and/or high-LET. To the best of our knowledge, this work is one of the most extensive studies done on such a large animal genetic diversity regarding both low dose radiation and high-LET.

NOTE: The lab moved from Lawrence Berkeley National Lab (LBNL) to NASA Ames Research Center in 2017, where it was established as the Radiation Biophysics Lab in Space Biosciences Division. Dr. Costes will continue collaborating with LBNL and some funding will be left at LBNL to cover more plate processing in collaboration with Dr. Weil (CSU) and for support from CoI Dr. Snijders for the writing of the animal data.

In collaboration with the radiation Biodosimetry Laboratory and the modeling group at NASA Johnson Space Center and with the International Computer Science Institute (ICSI) at UC Berkeley, our team will bring unique inter-disciplinary expertise to integrate the large array of cancer data generated over the past 25 years and archived by NASA under the various Human Research Program (HRP) funded projects. The main goal of this proposal is to identify factors influencing radiation-induced carcinogenesis and integrate them into a multi-scale model already started at the Berkeley Lab that encompasses DNA damage response and inter-cellular signaling to predict cancer risk for any types of HZE. Because experimental data are dispersed across many different cancer models, radiation qualities, and measurement types, this project will also generate a complete set of experimental data designed to fully inform and validate the model. In this project, the model will impose the types of measurements being made, with a strong emphasis on well-established blood biomarkers. In our approach we hypothesize that genetic factors strongly influence risk of cancer from space radiation and that biomarkers reflecting DNA damage and inflammatory processes in the blood are great tools to predict risk and monitor potential health effects post-flight. By using blood as a surrogate organ, the proposed work will allow extrapolation of cancer risk from mice to humans. A cohort of 6 different strains of mice (collaborative cross-mouse) with expected sensitivity to ionizing radiation will be monitored for biomarkers and cancer after exposure to 0.3 Gy of 1 GeV/amu Fe particle and compared to 1 Gy exposure of gamma ray control. Because we favor larger number of animals per radiation condition, we selected only one dose and the most carcinogenic particle to prove the principle of our approach while validating our model on a complete set of ex-vivo data and in-vivo longitudinal data. The collaborative cross-mouse model is an SFA resource that will make it possible for our team to examine the impact of genetic diversity in an animal model in a systematic and reproducible manner. In parallel, we propose to fully characterize the DNA damage response and cell death from ionizing radiation administered ex-vivo to 30 genetically different strains of mice and to 1000 human’s blood donors, matching the age and gender distribution of the astronaut population. Taken together, an array of ex-vivo phenotypic features will be associated to genetic traits across mice and humans as a function of age and gender. At the end of this proposal, our team will provide NASA with a model to estimate individualized risk for an astronaut before a flight as well as estimating the risk during the flight. Information generated in this proposal will also be useful to generate guidelines and suggest the best biomarkers to monitor the healthy recovery of astronauts post-flight.