Abstract
Expression profiling of skin biopsy specimens has established molecular features of the skin in patients with atopic dermatitis (AD). The invasiveness of biopsies has prevented their use in defining individual-level AD pathobiological mechanisms (endotypes) in large research studies. We sought to determine whether minimally invasive skin tape strip transcriptome analysis identifies gene expression dysregulation in AD and molecular disease endotypes. We sampled nonlesional and lesional skin tape strips and biopsy specimens from white adult patients with AD (18 male and 12 female patients; age [mean±SE], 36.3±2.2years) and healthy control subjects (9 male and 16 female subjects; age [mean±SE], 34.8±2.2years). AmpliSeq whole-transcriptome sequencing was performed on extracted RNA. Differential expression, clustering/pathway analyses, immunostaining of skin biopsy specimens, and clinical trait correlations were performed. Skin tape expression profiles were distinct from skin biopsy profiles and better sampled epidermal differentiation complex genes. Skin tape expression of 29 immune and epidermis-related genes (false discovery rate<5%) separated patients with AD from healthy subjects. Agnostic gene set analyses and clustering revealed 50% of patients with AD exhibited a type 2 inflammatory signature (type 2-high endotype) characterized by differential expression of 656 genes, including overexpression of IL13, IL4R, CCL22, CCR4 (log2 fold change=5.5, 2.0, 4.0, and 4.1, respectively) and at a pathway level by TH2/dendritic cell activation. Both expression and immunostaining of skin biopsy specimens indicated this type 2-high group was enriched for inflammatory, type 2-skewed dendritic cells expressing FcεRI. The type 2-high endotype group exhibited more severe disease by using both the Eczema Area and Severity Index score and body surface area covered by lesions. Minimally invasive expression profiling of nonlesional skin reveals stratification in AD molecular pathology by type 2 inflammation that correlates with disease severity.
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