Transcriptomic Identification of Immune-Related Hubs as Candidate Predictor Biomarkers of Therapeutic Response in Psoriasis

Abstract

Psoriasis is a chronic inflammatory skin disease driven by genetic, environmental, and immune factors. While biologics like adalimumab (anti-TNFα) and risankizumab (anti-IL-23) have improved outcomes, patient response variability remains unclear. This study examined immune-related transcriptomic differences between lesional (L) and non-lesional (NL) psoriatic skin, focusing on immune-related hub genes, their plasma levels, and their correlations with severity and treatment response. Patients with moderate-to-severe psoriasis were enrolled before treatment with anti-TNFα (n = 16) or anti-IL-23 (n = 18). Plasma and paired L and NL skin biopsies were collected for RNA sequencing. Gene ontology enrichment analysis found four immune-related terms enriched in L skin: T-helper 17, granulocyte and lymphocyte chemotaxis, and antimicrobial humoral response. A protein–protein interaction network identified ten immune-related hub genes upregulated in L skin that correlated with clinical severity. Patients with prior treatments expressed distinctive gene profiles. Plasma levels of CCL20 strongly correlated with disease severity. Decision tree models identified CCL20 expression in skin and plasma levels of IL-6 and CXCL8 as candidate predictors for anti-TNFα response. Similarly, skin expression of CXCL8, IL-6, and CXCL10, alongside plasma levels of CCL20, IL-6, and CXCL8, may predict anti-IL-23 response. Ten immune-related hubs may serve as possible biomarkers for disease severity and therapeutic response in psoriasis.