Multi-omics and Multi-organ Aging Clocks Digitize Human Aging

Abstract

Multi-organ biological aging clocks derived from clinical phenotypes and neuroimaging have emerged as valuable tools for studying human aging and disease1,2,3,4. Plasma proteomics provides an additional molecular dimension to enrich these clocks5. Here, we used 2448 plasma proteins from 43,498 participants in the UK Biobank to develop 11 multi-organ proteome-based biological age gaps (ProtBAG). We compared them to 9 multi-organ phenotype-based biological age gaps (PhenoBAG1) regarding genetics, causal associations with 525 disease endpoints (DE) from FinnGen and PGC, and their clinical promise to predict 14 disease categories and mortality. We highlighted critical clinical and methodological considerations for generating ProtBAG, including the need for age bias correction6 and addressing protein organ specificity to enhance model performance and generalizability. Genetic analyses revealed overlap between ProtBAGs and PhenoBAGs, including shared loci, genetic correlations, and colocalization signals. A three-layer causal network linked ProtBAG, PhenoBAG, and DE, exemplified by the pathway of obesity[->]renal PhenoBAG[->]renal ProtBAG to holistically understand human aging and disease. Combining features across multiple organs improved predictions for disease categories and mortality. These findings provide a framework for integrating multi-omics and multi-organ biological aging clocks in biomedicine. All results are publicly disseminated at https://labs-laboratory.com/medicine/.