Machine learning-derived R-loop-related diagnostic signature for psoriasis: a multi-cohort and single-cell validation study

Background

Psoriasis is a chronic inflammatory skin disease characterized by dysregulated immune responses and keratinocyte (KC) hyperproliferation. Although therapeutic strategies have advanced considerably, achieving durable long-term remission remains challenging. R-loops are three-stranded nucleic acid structures involved in genomic stability and inflammatory regulation in multiple diseases; however, their role in psoriasis remains poorly understood.

Objective

To investigate the involvement of R-loops in psoriasis, develop an R-loop-related diagnostic signature, and identify key molecular drivers of disease pathogenesis.

Methods