Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk
Andrew Zalesky, Ye Tian, Luigi Ferrucci, Keenan A. Walker, Wenjia Bai, Michael S. Rafii, Paul Aisen, Filippos Anagnostakis, Sarah Ko, Mehrshad Saadatinia, Jingyue Wang, Christos Davatzikos, Junhao Wen
Abstract
Multi-organ biological aging clocks across different organ systems have been shown to predict human disease and mortality. Here, we extend this multi-organ framework to plasma metabolomics, developing five organ-specific metabolome-based biological age gaps (MetBAGs) using 107 plasma non-derivatized metabolites from 274,247 UK Biobank participants. Our age prediction models achieve a mean absolute error of approximately 6 years (0.25<r < 0.42). Crucially, including composite metabolites (e.g. sums or ratios of raw metabolites) results in poor generalizability to independent test data due to multicollinearity. Genome-wide associations identify 405 MetBAG-locus pairs (P < 5 × 10−8/5). Using SBayesS, we estimate the SNP-based heritability (0.09< $${h}_{{SNP}}^{2}$$ < 0.18), negative selection signatures (−0.93 < S < −0.76), and polygenicity (0.001<Pi < 0.003) for the 5 MetBAGs. Genetic correlation and Mendelian randomization analyses reveal potential causal links between the 5 MetBAGs and cardiometabolic conditions (e.g., metabolic disorders and hypertension). Integrating multi-organ and multi-omics features improves disease category and mortality predictions. The 5 MetBAGs extend existing biological aging clocks to study human aging and disease across multiple biological scales. All results are publicly available at https://labs-laboratory.com/medicine/ . Aging affects multiple organs and tracking these changes could improve our understanding of disease risk. Here, the authors show that metabolomics-based organ-specific aging clocks can predict future risk of cardiometabolic disease and mortality.