Longevity & Aging

Biolearn Benchmarks 39 Aging Clocks and Shows Age Accuracy Does Not Predict Mortality

Researchers built Biolearn, an open-source Python library that harmonizes 39 aging biomarkers (epigenetic, transcriptomic, and clinical) and the datasets used to test them. Benchmarking across many cohorts showed that how well a clock predicts chronological age is unrelated to how well it predicts mortality after adjusting for age and sex. The Horvath skin-and-blood clock was most accurate for age (R2 = 0.88), while GrimAge2 was the strongest mortality predictor in the largest cohort (HR = 2.57 per SD) and for healthspan (HR = 2.00). Performance varied by outcome: DunedinPACE led for stroke and dementia, and PhenoAge for metabolic disease. The framework also provides quality control, imputation, and blood cell-type deconvolution, supporting reproducible, community-driven biomarker validation.