This paper interprets large-scale pan-disease blood proteomics through the Universal Resonance Model (URM), reframing so-called “non-specific” biomarkers as indicators of global system states rather than failures of disease specificity. Using evidence from pan-disease and longitudinal proteomic atlases, it argues that many circulating proteins reflect resonance, coupling, and instability across immune, metabolic, and structural subsystems. The work shows how longitudinal proteomics enables detection of early-warning signals, phase shifts, and reset windows—features that remain invisible in static biomarker models. By integrating proteomics with URM, the paper proposes a dynamical language for precision medicine in which biomarkers function as phase indicators and clinical decisions are guided by timing and system stability rather than isolated measurements. This approach positions pan-disease proteomics not as a limitation of precision medicine, but as its next stage: a map of systemic resonance that supports prediction, prevention, and timing-sensitive intervention.
Anita Domargård (Tue,) studied this question.