Human aging phenome

Aging does not look the same in everyone. The human aging phenome is the full spectrum of measurable traits — molecular, physiological, cognitive and clinical — that change as people grow older, and that together describe how, and how fast, an individual is aging.

We integrate large-scale human datasets — electronic health records, biobanks, imaging, and multi-omics — to chart how thousands of age-related traits relate to one another and to underlying biological mechanisms. By linking these phenotypes back to the molecular pathways we study in the lab, we identify robust biomarkers of biological age and pinpoint which traits are most amenable to intervention.

A central tool is machine learning. We train "aging clocks" to read biological age from data such as cell-nucleus morphology, retinal and facial images, or routine clinical measurements — and to flag where a person's biological age diverges from their chronological age. The goal is a data-driven atlas of human aging that turns the diffuse experience of growing older into concrete, measurable targets for intervention.