Translating cellular aging clocks into disease risk prediction.

Journal: Cell reports. Medicine
Published Date:

Abstract

Ding et al. mapped over 7,000 plasma proteins to more than 40 cell types and developed machine learning aging clocks across 60,000 individuals, demonstrating that cell-type-specific biological aging is heterogeneous, measurable from blood alone, and powerfully predictive of neurodegenerative disease, cancer, and mortality up to 15 years before clinical onset.1.

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