Frontiers in Public Health · 7 authors, 2 centres
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This study used a bioinformatics approach on multiple human datasets to establish a genomic association between ionizing radiation exposure and a chronological age threshold. The analysis identified 234 genes linked to radiation-age interaction, with functional pathways involving inflammation and metabolism, and found one gene, *LAPTM4B*, as significant for differentiating lung diseases based on ethnicity and sex.
The study employed a secondary analysis of multiple public human datasets to investigate a genomic association between radiation and age. First, using datasets of healthy individuals, an empirical chronological age cutoff of 29 years was established to categorize 'young' versus 'old' patients. Datasets including radiation exposure data were then used to test the interaction between radiation and age, yielding 234 unique genes. Pathway analysis of these genes flagged significant involvement of IL-1 signaling and PRPP biosynthesis pathways. The genes were subsequently evaluated in a dataset of lung disease patients, revealing that *LAPTM4B* was the only gene with a significant interaction among lung disease, ethnicity, and sex. Limitations include the reliance on chronological age as a proxy for biological age, the use of small, diverse datasets, and the inability to adjust for all clinical factors.
