Bioinformatics and experimental approach identify DNMT3A as a diagnostic marker associated with regulated cell death patterns in psoriasis.

Regulated cell death (RCD) is crucial for the advancement of psoriasis, and providing opportunities as diagnostic indicators and drug sensitivity markers for psoriasis. Nevertheless, there is a lack of exploration regarding a thorough evaluation of RCD and psoriasis. 10 transcriptome datasets from psoriasis patients were retrieved, and then RCD mRNA profile was generated consensus cluster. Subsequently, RCD.score was conducted through machine-learning. Two psoriasis subclasses were identified., each exhibiting distinctive molecular patterns and immunologic landscape. Specifically, patients in molecular cluster B exhibited an immunosuppressive microenvironment, suggesting a non-inflamed immune infiltration phenotype. Then, an RCD.score was conducted, and RCD.score demonstrated promising diagnostic capabilities across 10 datasets. High RCD.score category exhibited a more active immune microenvironment, suggesting an inflamed immune infiltration phenotype. Additionally, scRNA-seq revealed an association between cell types and RCD.score, and RCD.score was higher in the T cells and psoriasis patients. Furthermore, Mendelian randomization screening revealed five genes (CDH6, MTHFR, DNMT3A, SETD1A, and RGS14) as feature genes for psoriasis, and validated in psoriasis patients. Recognizing RCD.score serves as an essential resource for prediction of psoriasis diagnostic, carrying wide-ranging implications for clinical practice.