Transitions from health to disease are characterized by dysregulation of biological networks under the influence of genetic and environmental factors, often over the course of years to decades before clinical symptoms appear. Understanding these dynamics has important implications for preventive medicine. However, progress has been hindered both by the difficulty of identifying individuals who will eventually go on to develop a particular disease and by the inaccessibility of most disease-relevant tissues in living individuals. Here we developed an alternative approach using polygenic risk scores (PRSs) based on genome-wide association studies (GWAS) for 54 diseases and complex traits coupled with multiomic profiling and found that these PRSs were associated with 766 detectable alterations in proteomic, metabolomic, and standard clinical laboratory measurements (clinical labs) from blood plasma across several thousand mostly healthy individuals. We recapitulated a variety of known relationships (e.g., glutamatergic neurotransmission and inflammation with depression, IL-33 with asthma) and found associations directly suggesting therapeutic strategies (e.g., Ω-6 supplementation and IL-13 inhibition for amyotrophic lateral sclerosis) and influences on longevity (leukemia inhibitory factor, ceramides). Analytes altered in high-genetic-risk individuals showed concordant changes in disease cases, supporting the notion that PRS-associated analytes represent presymptomatic disease alterations. Our results provide insights into the molecular pathophysiology of a range of traits and suggest avenues for the prevention of health-to-disease transitions.
Keywords: metabolomics; polygenic risk scores; presymptomatic disease; proteomics.