Millions of Reports and AI Detects Biological Ages Across Multiple Organs

Описание: "NotebookLM: "By analyzing over 33 million histological records from the Danish National Pathology Register, researchers constructed The Human Pathome, a comprehensive map of how different tissues age and affect mortality. This computational study utilizes natural language processing to identify distinct sexual dimorphism in aging, discovering that biological changes begin shortly after development in females but start later and accelerate faster in males. Beyond establishing these tissue-specific aging trajectories, the authors used machine learning to bridge clinical data with scientific literature, successfully identifying the drug nintedanib as a potential anti-aging intervention. Experimental validation confirmed that this compound reduces cellular senescence and increases the lifespan of fruit flies, demonstrating how population-level health data can accelerate the discovery of longevity-promoting therapies."

"...organ-specific proteomic aging clocks measure biological aging by analyzing thousands of proteins found in blood plasma. While traditional aging assessments often reflect a general systemic decline, these new models utilize organ-enriched proteins to quantify the unique aging trajectories of ten distinct physiological systems, such as the brain, heart, and kidneys. ... these clocks predict the risk of chronic diseases and mortality with greater precision than established clinical or genetic biomarkers. Notably, the researchers identified a parsimonious panel of proteins that maintains high accuracy, suggesting a practical path for clinical translation and personalized interventions."

https://doi.org/10.1038/s41514-025-00...
https://doi.org/10.1038/s43587-025-01...
   • 18th Landsteiner Lecture - Tony Wyss-Coray