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bioRxiv · 10.1101/2025.01.09.632065

AI-Driven Toolset for IPF and Aging Research Associates Lung Fibrosis with Accelerated Aging

Galkin, F.·Chen, S.·Aliper, A.·Zhavoronkov, A.·Ren, F.
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Abstract

Idiopathic pulmonary fibrosis (IPF) is a condition predominantly affecting the elderly and leading to a decline in lung function. Our study investigates the aging-related mechanisms in IPF using artificial intelligence (AI) approaches. We developed a pathway-aware proteomic aging clock using UK Biobank data and applied it alongside a specialized version of Precious3GPT (ipf-P3GPT) to demonstrate an AI-driven mode of IPF research. The aging clock shows great performance in cross-validation (R2=0.84) and its utility is validated in an independent dataset to show that severe cases of COVID-19 are associated with an increased aging rate. Computational analysis using ipf-P3GPT revealed distinct but overlapping molecular signatures between aging and IPF, suggesting that IPF represents a dysregulation rather than mere acceleration of normal aging processes. Our findings establish novel connections between aging biology and IPF pathogenesis while demonstrating the potential of AI-guided approaches in therapeutic development for age-related diseases.

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Galkin, F., Chen, S., Aliper, A., Zhavoronkov, A., Ren, F.. 2025-01-13. AI-Driven Toolset for IPF and Aging Research Associates Lung Fibrosis with Accelerated Aging. https://doi.org/10.1101/2025.01.09.632065

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