What happened
Psoriasis is a chronic inflammatory skin disease characterized by immune dysregulation and complex cellular interactions involving keratinocytes (KCs), T cells, and endothelial cells. Single-cell studies have mapped the cellular diversity of psoriatic plaques, yet most analyses treat skin as either healthy or diseased and therefore overlook the graded changes that precede a visible lesion. We asked whether psoriasis instead progresses along a transcriptional continuum and whether clinically normal skin from patients already carries a measurable disease signature. Using single-cell RNA sequencing (scRNA-seq) of healthy skin (NS), clinically normal skin adjacent to lesions (PN), and lesional skin (PP), we combined two complementary designs: a complete set spanning all three states and a within-patient paired set of matched PN and PP skin biopsies that removes inter-individual variability. Trajectory analysis using a novel pseudotime approach reveals transcriptional changes within cell populations and dynamic cellular states underlying psoriatic pathology. To distinguish lesion-driven effects from disease-associated transcriptional changes, we applied a differential expression strategy comparing PP and PN psoriatic tissue with NS and integrating these contrasts. This approach enabled the identification of disease-specific gene signatures while minimizing lesion-specific bias. As a result, we identified a coherent, cell-type-resolved continuum of transcriptional states in which endothelial cells, IL20+ keratinocytes (KCs: IL20), and KGF+ keratinocytes (KCs: KGF) undergo trajectory-dependent state transitions. These trajectories converge on features including epidermal thickening, barrier dysfunction, and plaque maintenance. Endothelial cells transition from an inflamed, angiogenic state to a mature, barrier-stabilized phenotype, while KCs: IL20 and KCs: KGF shift from PN states toward hyperproliferative, stress-adapted lesional phenotypes. These findings reframe psoriasis as a dynamic, multicellular continuum and identify candidate temporal windows for early intervention.