The association between atopic dermatitis and rosacea: a comprehensive review from comorbidities to pathogenic mechanisms.

Objective: Atopic dermatitis (AD) and rosacea have traditionally been regarded as two distinct inflammatory skin disorders with divergent pathophysiology. However, emerging evidence has progressively revealed unexpected convergences between these conditions in clinical manifestations, comorbidity profiles and pathogenic mechanisms-raising the question of whether the apparent mechanistic overlaps represent true pathophysiological convergence-sharing common upstream drivers-or merely parallel, non- specific innate immune responses triggered by entirely distinct microbial and genetic factors? This distinction carries profound implications for the design of shared versus disease-specific therapeutic strategies. this review aims not simply to enumerate similarities but to critically evaluate whether the observed convergences represent true mechanistic overlap, or parallel but independent responses. Methods: Literature search strategy: A comprehensive literature search was conducted in PubMed, Embase and Scopus, the Cochrane Library between April, 2016 and April, 2026. The search strategy combined controlled vocabulary and free-text terms, including " rosacea", " atopic dermatitis", " mast cells", " comorbidity", " microbiome", " innate immunity", " adaptive immunity", and " neurovascular". Reference lists of relevant articles were also manually screened to identify additional eligible studies. Inclusion and exclusion criteria: Studies were included if they: (1) focused on atopic dermatitis and/or rosacea; (2) investigated relevant immunological mechanisms, comorbidities, or pathophysiological pathways; and (3) provided sufficient data to support qualitative synthesis. Both original research articles and high- quality reviews or meta-analyses were considered. Studies were excluded if they: (1) were duplicate publications; (2) lacked sufficient methodological detail or extractable data; or (3) were not directly relevant to the objectives of this review. Study selection and data extraction: Study selection and data extraction were performed independently by two reviewers. Titles and abstracts were initially screened, followed by full-text assessment for eligibility. Any discrepancies were resolved through discussion, and when necessary, a third reviewer was consulted to reach consensus. Study selection process: A total of 5381records were identified through database searching, with an additional 83 records identified through manual reference screening. After removal of duplicates, 3185records remained for title and abstract screening, of which 2864 were excluded due to irrelevance. A total of 321 full-text articles were assessed for eligibility, and 216 were further excluded for the following reasons: lack of relevance (n =117), insufficient data (n =53), or low methodological quality/non-original articles (n = 46). Ultimately, 105 studies were included in the qualitative synthesis. The study selection process is summarized in a PRISMA-style flow diagram ( Results: Critical appraisal of the evidence reveals that both diseases share an upstream innate immune activation platform' encompassing TLR2/TLR4 signaling, NLRP3 inflammasome activation, mast cell degranulation and neurovascular dysregulation via the CGRP/SP/VEGF/TRP axis. However, they diverge at the level of adaptive immune polarization: AD is dominated by Th2/ILC2 skewing with IgE sensitization and deficient antimicrobial peptide responses, while rosacea is characterized by Th 1/Th17 involvement with autonomous LL-37 overproduction as its primary amplification loop. Intriguingly, dupilumab-induced rosacea-like dermatitis suggests that these polarization states may not merely differ but actively compete, raising questions about the nature and limits of mechanistic overlap between the two conditions. This duality may challenge simplistic models of mechanistic overlap and has direct implications for differential clinical management. Future research should employ multi-omics approaches and prospective comorbidity cohorts to clarify causal pathways and translate mechanistic insights into optimized therapeutic strategies.