Single-Cell Regulatory Network Analysis Identifies Adjunctive Drug Candidates in Early Risankizumab-Treated Psoriasis

Risankizumab has demonstrated remarkable efficacy in the treatment of psoriasis; however, its long-term use faces multiple challenges, including high costs, reduced efficacy over time, and potential safety concerns, such as infections and malignancies. Therefore, identifying potential alternative or adjunctive therapies to risankizumab has significant clinical importance.

We analyzed single-cell RNA sequencing data from mature dendritic cells (mDCs) and CD4⁺ T cells collected before risankizumab treatment and at days 3 and 14 post-treatment. Differential expression, cell communication analysis, pseudotime trajectory analysis, and transcription factor regulatory network analysis were performed. Small-molecule drug prediction was performed using the DsigDB database, and molecular docking was used to evaluate binding interactions between candidate drugs and their targets.

We identified 15 key transcription factors (MAFB, IRF3, NFIC, SREBF1, ELF3, DLX5, MEF2A, MXD3, MAFF, MECP2, ERF, KLF9, RARA, KLF5, ZBTB2) that were significantly altered in CD4⁺ T cells during the early phase of risankizumab treatment in psoriasis, along with their downstream differentially expressed genes (including KRT14, S100A9, S100A8, S100A7, KRT6A, GJB2, CALML3, and KRT6B). Based on these core factors, five candidate small-molecule drugs with potential therapeutic value for psoriasis were predicted: alitretinoin, simvastatin, MS-275 (entinostat), colchicine, and (+)-chelidonine.

This study characterized transcriptional regulation of CD4⁺ T cells and mDCs during early risankizumab treatment in psoriasis, predicting potential therapeutic targets and candidate small-molecule drugs from single-cell regulatory networks. Although promising, these results need further validation in larger cohorts and experimental models.

These findings offer preliminary clues for future risankizumab-based combination strategies in psoriasis.