A Physiology Clock for Human Aging

Abstract

Why people age at different rates is a fundamental unsolved problem in biology. We created a model that predicts an individual’s age, taking as input physiological traits that change with age in the large UK Biobank dataset, such as blood pressure, blood metabolites, strength, and stimulus-reaction time. The model’s Root Mean Square Error of age prediction (RMSE) is less than 5 years. We argue that the difference between calculated “biological” age and actual age (ΔAge) reflects an individual’s relative youthfulness and possibly their rate of aging. Validating this interpretation, people predicted to be physiologically young for their age have a lower subsequent mortality rate and a higher parental age at death, even though no mortality data were used to calculate ΔAge. A Genome-Wide Association Study (GWAS) of ΔAge, and analysis of environmental factors associated with ΔAge identified known as well as new factors that may influence human aging, including genes involved in synapse biology and a tendency to play computer games. We identify 12 readily-measured physiological traits that together assess a person’s biological age and may be used clinically to evaluate therapeutics designed to slow aging and extend healthy life.