Tissue gene expression profiles and communication networks inform candidate blood biomarker identification in psoriasis and atopic dermatitis

Abstract

Overlapping clinical and pathomechanistic features can complicate the diagnosis and treatment of inflammatory skin diseases, including psoriasis and atopic dermatitis (AD). Spatial transcriptomics allows the identification of disease- and cell-specific molecular signatures that may advance biomarker development and future treatments. This study identified transcriptional signatures in keratinocytes and sub-basal CD4⁺ and CD8⁺ T lymphocytes from patients with psoriasis and AD. In silico prediction of ligand:receptor interactions delivered key signalling pathways (interferon, effector T cells, stroma cell and matrix biology, neuronal development, etc.). Targeted validation of selected transcripts, including CCL22, RELB, and JUND, in peripheral blood T cells suggests the chosen approach as a promising tool also in other inflammatory diseases. Psoriasis and AD are characterized by transcriptional dysregulation in T cells and keratinocytes that may be targeted therapeutically. Spatial transcriptomics is a valuable tool in the search for molecular signatures that can be used as biomarkers and/or therapeutic targets.

Keywords: Atopic dermatitis; Bioinformatic; Biomarker; Inflammation; Psoriasis; Spatial transcriptomics; Treatment.