Program in Quantitative Genomics
The Program in Quantitative Genomics (PQG) develops and applies quantitative methods to help handle massive genetic, genomic, and health data. Based in the Harvard Chan School and Longwood Medical Area, its goal is to improve health through the interdisciplinary study of genetics, behavior, environment, and health.
255 Huntington Ave
Building 2, 4th floor
Boston, MA 02115
Proteomic Signatures Capture Environmental Exposures Across Diverse Populations
Environmental exposures shape disease risk, but the generalizability of circulating protein-based readouts of exposures across diverse populations remains unknown. Using plasma proteomic profiles of 5,416 proteins in 10,043 participants from the All of Us Research Program, we evaluated associations with and composite scores of 100+ exposures, spanning adiposity, air pollution, ambient temperature, and substance use. We find that proteomic exposure signatures are largely consistent across populations and socioeconomic strata, with <1% of proteins showing significant cross-population heterogeneity, which included BMI as an exception, with leptin being the most heterogeneous association. Population-specific leptin trajectories adiposity, together with residual leptin-type 2 diabetes associations after BMI adjustment, revealed sex-specific metabolic risk not captured by BMI alone. Aggregated protein scores were largely exposure-specific, but substance-use scores showed cross-prediction and SES scores were broadly associated. PM2.5 protein scores captured within-region exposure variation and outperformed geographic and socioeconomic correlates, but spatial confounders remain embedded within protein-environment associations. Scores trained in UK Biobank transferred to All of Us for biologically proximal exposures, supporting cross-biobank portability. These findings establish plasma proteomics as a scalable framework for exposure measurement across diverse populations, while underscoring that responsible applications require careful consideration of biological context, social patterning, and cohort structure.