A Framework for Skin Microbiome–Immune Interactions in Dermatitis

Thesis Abstract

There is growing recognition that perturbations in the skin microbiome and dysregulated immune responses jointly drive the pathogenesis and clinical heterogeneity of dermatitis, yet an integrative framework linking microbial signals to host immune pathways remains underdeveloped. This study aims to construct and validate a comprehensive framework for Skin Microbiome–Immune Interactions in Dermatitis that explains how microbial communities modulate local and systemic immune responses to influence disease severity, progression, and treatment outcomes. Specific objectives are to (i) characterize baseline skin microbiome composition and community structure in patients with atopic dermatitis (AD) and contact dermatitis (CD) compared with healthy controls; (ii) quantify skin and systemic immune mediators, including cytokines, chemokines, and T-cell profiles, and examine their associations with microbial features; (iii) identify microbial taxa and metabolic pathways linked to pro- and anti-inflammatory immune signatures; (iv) develop a conceptual and statistical model outlining bidirectional interactions between microbiome dynamics and immune responses; and (v) evaluate the model’s predictive performance for flare timing, treatment response, and disease trajectory. The study adopts an explanatory sequential mixed-methods design conducted across three dermatology clinics with a total population of approximately 320 participants 120 AD patients, 100 CD patients, and 100 age- and sex-matched healthy controls. For quantitative analysis, skin swab and tape-strip samples will be collected from lesional and non-lesional sites, with longitudinal follow-up at 3 and 6 months. High-throughput 16S rRNA gene sequencing and shallow-shotgun metagenomics will characterize bacterial community composition and functional potential. Parallel immunophenotyping will quantify serum and skin tissue cytokines (e.g., IL-4, IL-13, IL-17, IFN-?, TSLP) via multiplex immunoassays, alongside flow cytometric profiling of circulating and skin-resident T cell subsets. Data will be integrated using multivariate regression, structural equation modeling, and machine-learning approaches including random forest for feature selection and generalized additive models for nonlinear relationships. Qualitative interviews with a subset of patients (n=30) will explore perceived symptomatology, treatment adherence, and lifestyle factors, with thematic analysis to contextualize quantitative findings and inform framework construction. Key expected findings include (i) distinct microbiome-enterotype patterns associated with AD and CD, characterized by differential abundance of Staphylococcus aureus, Cutibacterium species, and Corynebacterium species, and corresponding shifts in microbial metabolic pathways such as bile acid and short-chain fatty acid production; (ii) robust associations between specific taxa and immune mediators, notably elevated Th2 cytokines correlating with S. aureus–dominated dysbiosis and reduced regulatory T cell signatures; (iii) identification of a bidirectional interaction model in which microbial-derived metabolites modulate epithelial barrier integrity and dendritic cell activation, which in turn shapes T helper cell differentiation and cytokine milieus; (iv) a predictive framework with AUCs exceeding 0.80 for flare risk and treatment response when combining microbial, immunological, and clinical variables. The study contributes to knowledge by operationalizing a mechanistic, integrative framework that bridges microbiology and immunology in dermatitis, offering transferable components for other inflammatory skin conditions. It advances methodological integration by coupling multi-omic microbiome data with immunophenotyping in a longitudinal design and by incorporating qualitative insights to enhance model relevance to patient experiences. The anticipated conclusions emphasize the centrality of microbiome-immune crosstalk in disease expression and response to therapy, with recommendations for personalized interventions that target microbial communities (e.g., microbiome-modulating therapies) in conjunction with immune-directed treatments. Practical implications include the potential for microbiome-informed biomarkers to guide precision dermatology, the design of adjunctive therapies aimed at restoring barrier function and immune balance, and the incorporation of lifestyle and environmental factors into comprehensive management plans.