Insilico employs AI-driven tools to uncover the link between idiopathic pulmonary fibrosis (IPF) and accelerated aging
Peer-Reviewed Publication
Updates every hour. Last Updated: 8-Oct-2025 07:11 ET (8-Oct-2025 11:11 GMT/UTC)
Key Findings:
AI-powered Aging Clock: The new proteomic clock predicts biological age with high accuracy (R²=0.84, MAE=2.68 years) and captures accelerated aging signatures in severe lung disease cases—patients with severe COVID-19 (and likely fibrosis) exhibited biological ages nearly three years older than healthy controls.
Distinct Molecular Signatures: Analysis with the ipf-P3GPT generative model revealed both shared and unique gene expression patterns between aging lungs and fibrotic disease, highlighting that IPF is not just accelerated aging but entails unique pathological processes.
Pathway-Level Insights: The study identified four key pathways (TGF-ß signaling, oxidative stress, inflammation, ECM remodeling) as central to both IPF and aging, but involved differently at the gene level.
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