Establishing a genomic radiation-age association for space exploration supplements lung disease differentiation

Abstract

PurposeOne possible way to quantify each individual's response or damage from ionizing radiation is to estimate their accelerated biological age following exposure. Since there is currently no definitive way to know if biological age estimations are accurate, we aim to establish a rad-age association using genomics as its foundation.MethodsTwo datasets were combined and used to empirically find the age cutoff between young and old patients. With age as both a categorical and continuous variable, two other datasets that included radiation exposure are used to test the interaction between radiation and age. The gene lists are oriented in preranked lists for both pathway and diseases analysis. Finally, these genes are used to evaluate another dataset on the clinical relevance in differentiating lung disease given ethnicity and sex using both pairwise t-tests and linear models.ResultsUsing 12 well-known genes associated with aging, a threshold of 29-years-old was found to be the difference between young and old patients. The two interaction tests yielded 234 unique genes such that pathway analysis flagged IL-1 signaling and PRPP biosynthesis as significant with high cell proliferation diseases and carcinomas being a common trend. LAPTM4B was the only gene with significant interaction among lung disease, ethnicity, and sex, with fold change greater than two.ConclusionThe results corroborate an initial association between radiation and age, given inflammation and metabolic pathways and multiple genes emphasizing mitochondrial function, oxidation, and histone modification. Being able to tie rad-age genes to lung disease supplements future work for risk assessment following radiation exposure.

A Review: Multi-Omics Approach to Studying the Association between Ionizing Radiation Effects on Biological Aging

“…Future developments in this field involve the assessment of radiation exposure risks during extended space missions and the development of effective shielding strategies. Recent studies have utilized computational models and experimental data from the International Space Station to evaluate the impact of space radiation on astronauts' health, as well as secondary analysis of the lab-controlled environment to better characterize effects of space-level radiation levels [144,145]. These findings are crucial for designing spacecraft and protective measures to ensure the wellbeing of space travelers.…”

Translating genetic findings to epigenetics: identifying the mechanisms associated with aging after high-radiation exposure on earth and in space

“…The genetics foundation that we carry over is noted as Data1, which is shown in red in Figure 1. Specifically, Data1-1 (n = 91) include dose analysis with sex and age as clinical factors while Data1-2 (n = 75) includes sex as a secondary clinical factor (21). GSE21240, GSE23515 (22), and GSE20173 (23) (collectively referred to as Data1-1) included a total of 163 originally collected samples (of which 91 are utilized in this analysis).…”