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January 22, 20260 citationsOpen Access

Psoriasis in the Era of Multi-omics: Integrating Biomarkers, Cell States, and URM as a Biological Modifier

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ADAnita Domargård

Key Points

  • The research aims to integrate multi-omics in psoriasis with the Universal Resonance Model to better understand the disease's dynamics.
  • Utilized proteomics, single-cell RNA sequencing, and spatial transcriptomics in the analysis of psoriasis.
  • Formulated the Universal Resonance Model (URM) to explain biological instability and transition in disease.
  • Critiqued static biomarker logic by proposing a model that incorporates temporal variability.
  • Inspected how identical molecular pathways can lead to divergent clinical outcomes in psoriasis.
  • Identified that changes in baseline inflammation and biomarker variability are critical to understanding disease progression.
  • Established a framework for precision medicine that integrates timing and environmental factors into treatment approaches.

Abstract

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.

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Cite This Study

Anita Domargård (2026) studied this question.

synapsesocial.com/papers/6971be10642b1836717e2bf5https://doi.org/10.5281/zenodo.18315820
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