This paper integrates contemporary multi-omics research in psoriasis—proteomics, single-cell RNA sequencing, and spatial transcriptomics—with the Universal Resonance Model (URM) as a framework for understanding disease as a dynamic process rather than a static state. Psoriasis is described through established biological pathways (IL-23/IL-17 axis), cellular states, tissue niches, and circulating biomarker signatures. URM is introduced not as a philosophical overlay but as a biological model of instability, transition, and timing, explaining why identical molecular pathways can produce different clinical trajectories. A central contribution is the formulation of URM as a biological modifier of molecular signatures, allowing social and environmental context to be modeled inside biological trajectories through measurable changes in baseline inflammation, biomarker variability, and recovery dynamics. The paper critiques static biomarker logic, proposes falsifiable predictions based on temporal variability and system stability, and positions precision medicine as incomplete without a theory of timing, buffering, and transition. This work bridges immunology, multi-omics, systems biology, and clinical dynamics, offering a testable framework for understanding psoriasis as a path rather than a point.
Anita Domargård (Tue,) studied this question.