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Research Report

This study utilizes an extensive dataset of 33 million histological samples to extract thousands of age- and mortality-associated features, compiling them into a platform named The Human Pathome. We have discovered broad patterns of when pathological aging begins, noting a distinct sexual dimorphism where females age earlier but slower, while males age later but faster. Using machine learning, specifically unsupervised topic modeling, we identified predictive terms and themes for age and mortality. In a proof of principle, we applied these terms to a PubMed search and identified nintedanib as a potential intervention for aging. Experimental results showed nintedanib reduced cellular senescence markers, suppressed pro-fibrotic gene pathways in senescent cells, and extended the lifespan of fruit flies. This work opens the door for future exploitation of population datasets towards the discovery of novel aging interventions.

Supplementary materials for "The human pathome shows sex specific
aging patterns post- development"

Contains:
• Figure legends for Extended Data Figures 1-3.
• Extended Data Figures 1-3.

The human pathome shows sex specific aging patterns post- development