A Circulating Proteomic Signature of Allostatic Load Predicts Multisystem Disease and Mortality

Chronic stress contributes to the development of cardiometabolic, malignant, and other chronic diseases through cumulative multisystem physiological dysregulation, conceptualized as allostatic load (AL). However, traditional AL relies on heterogeneous clinical biomarkers that limit reproducibility and translational utility. Here, we develop and validate ProAL50, a proteomics-based measure of AL derived from 50 circulating proteins. Using high-dimensional plasma proteomic data from the UK Biobank, we constructed ProAL50 via penalized regression and stability selection and externally validated it in the Coronary Artery Risk Development in Young Adults (CARDIA) Study. ProAL50 closely mirrored traditional AL in its associations with sociodemographic characteristics, lifestyle behaviors, physical and mental health, inflammation, and biological aging, supporting strong construct validity. Beyond replication, ProAL50 consistently demonstrated stronger associations with incident chronic diseases, including all cancers, type 2 diabetes, ischemic heart disease, chronic lung disease, and chronic kidney disease, and with all-cause and cause-specific mortality. Functional enrichment analyses revealed that ProAL50 proteins cluster within lipid metabolic and immune-inflammatory pathways. These findings establish ProAL50 as a scalable, biologically grounded measure of cumulative stress that not only replaces traditional AL but surpasses it in predicting disease risk and mortality, offering a novel tool for population health and translational research.