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Updated: Apr 30, 2026

Measuring Single-Cell Aging with an Imaging-based Biomarker of Chromatin and Epigenetic Aging
Published on: January 30, 2026
Face aging rate quantifies change in biological age to predict cancer outcomes
Fridolin Haugg1,2, Grace Lee1, John He1
1Department of Radiation Oncology, Mass General Brigham/Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Abstract:
Chronological age predicts cancer survival but does not capture differences in biological aging rates. We apply FaceAge, an artificial intelligence algorithm that predicts biological age from a facial photograph, to serial clinical facial photographs to calculate the Face Aging Rate (FAR; change in FaceAge divided by the time between photographs). We analyze data from 2276 cancer patients receiving radiation therapy, using photographs captured during routine care. Higher FAR is associated with worse overall survival in stratified analyses of cohorts with the following intervals between photographs: short 10-365 days (adjusted hazard ratio [aHR] and 95% confidence interval: 1.25 [1.03-1.51]), mid 366-730 days (aHR: 1.37 [1.00-1.86]), and long 731-1,460 days (aHR: 1.65 [1.22-2.22]) after adjustment for time between photographs, sex, race, and diagnosis. FAR provides additional prognostic information beyond single time-point measures of FaceAge. FAR is a non-invasive prognostic biomarker that captures dynamic changes in biological aging.
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