Stanford cell-type aging clock predicts seven diseases years before diagnosis
A Nature Medicine study applied machine learning to single-cell RNA sequencing across 40+ cell types in approximately 60,000 individuals. The models predicted ALS more than three years before diagnosis, along with Alzheimer's, lung cancer, lymphoma, type 2 diabetes, COPD, and stroke. Only 35% of participants showed no extreme aging gaps across any cell type.