Tissue structure, the organization of cells, vasculature and extracellular matrix, determines organ function. Yet how tissue structure changes with aging remains largely unknown. Current aging research primarily focuses on molecular changes, missing this structural dimension. Here, we present PathStAR, Pathology based Structural Aging Rate, the first computational framework that captures when and how tissue structure changes during aging from histopathology images. We applied it to 25,306 postmortem tissues covering 40 tissue types from individuals aged 21 - 70, connecting structural aging to molecular data, health records and genotype data. Without any training on chronological age, PathStAR captured non-linear functional decline of ovary, undetectable by bulk-molecular profiling. Applying it across 40 tissues, it revealed that structural aging occurs through discrete phases of rapid change (accelerated periods), with tissue-specific trajectories following three patterns: Early Aging Tissues (vascular system with major changes during the 30s), Late Aging Tissues (uterus and vagina with major changes during menopause (50s)) and Biphasic Aging Tissues (digestive, male reproductive tissues, and ovary with two periods of major changes). During these accelerated phases, most tissues exhibited shared aging hallmarks of inflammation and energy production decline, coupled with disruption of pathways governing their specialized functions. Cross-organ analysis revealed coordinated aging within organ systems and an unexpected link between digestive and male reproductive tissues. We next identified 123 germline variants associated with organ-specific accelerated structural aging, including SIRT6 variants linked to accelerated vascular decline. Finally, individuals with systemic autoimmune disease, as well as tissues with classical aging pathologies (atrophy, calcification, fibrosis), showed elevated structural aging scores. We demonstrate that structural aging is measurable from histology scans and provide the first systematic framework for studying it, revealing organ-specific aging processes.
Yadav et al. (Wed,) studied this question.