Master regulators of infiltrate recruitment in autoimmune disease identified through network-based molecular deconvolution.

Network-based molecular modeling of physiological behaviors has proven invaluable in the study of complex diseases such as cancer, but these approaches remain largely untested in contexts involving interacting tissues such as autoimmunity. Here, using Alopecia Areata (AA) as a model, we have adapted regulatory network analysis to specifically isolate physiological behaviors in the skin that contribute to the recruitment of immune cells in autoimmune disease. We use context-specific regulatory networks to deconvolve and identify skin-specific regulatory modules with IKZF1 and DLX4 as master regulators (MRs). These MRs are sufficient to induce AA-like molecular states in three cultured cell lines, resulting in induced NKG2D-dependent cytotoxicity. This work demonstrates the feasibility of a network-based approach for compartmentalizing and targeting molecular behaviors contributing to interactions between tissues in autoimmune disease.