The mucosal barrier, as a critical interface of the body's defense system, is central to the pathogenesis of allergic diseases, with its structural integrity (epithelial cells, tight junctions, mucus layer, basement membrane) and functional homeostasis being key factors. This paper systematically elucidates the dynamic regulatory network constituted by five major signaling pathways: Wnt/β-catenin, TGF-β/Smad, RhoA/ROCK, MAPK, and JAK-STAT. These pathways interact through cross-talk (for example, Smad7 inhibits TGF-βRI to enhance Wnt signaling, and the β-catenin/Smad4 complex synergistically activates EMT genes), forming synergistic/antagonistic effects that jointly regulate epithelial repair, the expression of tight junction proteins (ZO-1/Claudin/Occludin), mucus secretion (MUC2/MUC5AC), and basement membrane remodeling. In allergic diseases, this network exhibits organ-specific imbalances: respiratory barrier damage is primarily characterized by RhoA/ROCK-mediated abnormal mucus secretion (asthma) and JAK-STAT-driven Th2 inflammation (rhinitis), whereas the intestinal barrier relies more on the epithelial regenerative capacity of the Wnt pathway.We innovatively propose a "phased-organ-targeting strategy": during the acute inflammatory phase (0-72 hours), JAK inhibitors (such as CYT387 nasal spray) are utilized to block STAT6 phosphorylation and control the immune storm; in the repair phase (72 hours to 2 weeks), Wnt agonists (WNT2b-pH microspheres) are employed to promote epithelial regeneration, or RhoA regulators (fasudil inhalation) are used to reconstruct the mucus layer; in the chronic remodeling phase, a temporally regulated dual-pathway therapy (such as JAK-STAT inhibition combined with Wnt activation hydrogels) is applied. The current challenges lie in overcoming pathway redundancy, tissue delivery efficiency, and individual differences in microbial flora. Future efforts should focus on achieving precise interventions through local delivery using nanocarriers, temporally coordinated dosing regimens, and predictive models of microbiota-host interactions.
Zhang et al. (Tue,) studied this question.