A new research document was published in volume 17, number 8 of Aging August 8, 2025, entitled “LESET of tools led by IPF and aging research associated with pulmonary fibrosis with accelerated aging”.
In this study, researchers Fedor Galkin, Shan Chen, Alex Aliper, Alex Zhavoronkov and Feng Ren of Insilico Medicine used artificial intelligence (IA) to study the similarities between idiopathic pulmonary fibrosis (IPF), a serious pulmonary disease and the aging process. Their results show that IPF is not just accelerated aging, but a distinct biological condition shaped by age -related dysfunction. This idea can lead to a new approach in the way scientists and clinicians treat this complex disease.
The IPF mainly affects individuals over 60 years of age. It causes scars of pulmonary tissue, which makes it more difficult to breathe and often leading to respiratory failure. Current treatments can slow down the disease, but rarely stop or reverse its progression. The researchers used AI to identify the biological characteristics shared between aging and fibrosis, finding new potential targets for treatment.
The team has developed a “proteomic aging clock” on the basis of protein data of more than 55,000 participants in British biobank. This AI-focused tool precisely measured biological age and found that patients with severe COVID-19, who have an increased risk of pulmonary fibrosis, have also shown signs of accelerated aging. This suggests that fibrosis leaves a detectable biological trace, supporting the use of aging clocks in the study of age -related diseases.
“For training on the aging clock, we used the British Biobank collection of 55319 OLINK NPX proteomic profiles annotated with age and sex.”
They also developed a personalized AI model, IPF-P3GPT, to compare the activity of genes in aging lungs compared to those with IPF. Although some genes are active in both, many have shown opposite behavior. In fact, more than half of the shared genes have had opposite effects. This means that the IPF is not content to accelerate aging, but also to disturb the normal aging paths of the body.
The study has identified unique molecular signatures that distinguish the IPF from normal aging. Although the two involve inflammation and remodeling of the tissues, the IPF leads to more damaging changes in the pulmonary structure and repair systems. This difference could guide the development of drugs that specifically target fibrosis without affecting normal aging.
By combining AI with large -scale biological data, the study also introduces a power of powerful tools to examine other age -related conditions such as hepatic and renal fibrosis. These models can support personalized treatments and expand understanding of the relationships between aging and disease, opening up new directions for the development of therapy.
Source:
Journal reference:
Galkin, F., and al. (2025). The set of tools based on IPF and research on aging combine pulmonary fibrosis with accelerated aging. Aging. Doi.org/10.18632/agy.206295
