BACKGROUND: Humans are subjected to various environmental stressors (bacteria, viruses, pollution) throughout life. As such, an inherent relationship exists between the effect of these exposures with age. The impact of these environmental stressors can manifest through DNA methylation (DNAm). However, whether these epigenetic effects selectively target genes, pathways, and biological regulatory mechanisms remains unclear. Due to the frequency of human rhinovirus (HRV) infections throughout life (particularly in early development), we propose the use of HRV under controlled conditions can model the effect of multiple exposures to environmental stressors. METHODS: We generated a prediction model by combining transcriptome and DNAm datasets from human epithelial cells after repeated HRV infections. We applied a novel experimental statistical design and method to systematically explore the multifaceted experimental space (number of infections, multiplicity of infections and duration). Our model included 35 samples, each characterized by the three parameters defining their infection status. RESULTS: Trainable genes were defined by a consistent linear directionality in DNAm and gene expression changes with successive infections. We identified 77 trainable genes which could be further explored in future studies. The identified methylation sites were tracked within a pediatric cohort to determine the relative changes in candidate-trained sites with disease status and age. CONCLUSIONS: Repeated viral infections induce an immune training response in bronchial epithelial cells. Training-sensitive DNAm sites indicate alternate divergent associations in asthma compared to healthy individuals. Our novel model presents a robust tool for identifying trainable genes, providing a foundation for future studies.
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