Research Paper Advance Articles

AI-driven toolset for IPF and aging research associates lung fibrosis with accelerated aging

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Figure 2. Comparison of biological age predictions between healthy controls and cases of severe COVID-19 infection. (A) Proteomic aging clock shows R2=0.84 in the task of age prediction in CV within the UK Biobank dataset (N = 55,319). (B) Proteomic aging clock’s error depends on the age group and is skewed toward the mean of the total sample. (C) Biological age acceleration (difference between predicted and chronological age) across severity groups. compared to healthy controls. Error bars represent standard error of the mean. (D) Linear regression analysis reveals that patients with severe cases, which are likely to develop lung fibrosis, showed significantly higher biological age predictions (+2.77 years, p=0.026).