Generating Detailed Intercellular Communication Patterns in Psoriasis at the Single-Cell Level Using Social Networking, Pattern Recognition, and Manifold Learning Methods to Optimize Treatment Strategies

This study on psoriasis used social network analysis, pattern recognition, and manifold learning to investigate single-cell communication patterns. It revealed that immune cells in psoriasis exhibit a synergistic interplay, with B-cells activation and Langerhans cells shifting to antigen presentation roles. Psoriasis cells were found to shut down many signaling pathways, affecting skin cell renewal and differentiation. The research identified numerous active cell type-specific regulons around hair follicles, highlighting new molecular features of the hair follicle cell-psoriasis axis. These insights offer innovative strategies for targeted drug treatments to improve psoriasis management.