Transcriptome profiling identifies disease- and therapy-associated signatures in atopic dermatitis

Atopic dermatitis (AD) is the most common chronic inflammatory skin disease and has a substantially detrimental impact on patients and caregivers. The disease is characterised by eczematous lesions, persistent itch, and a relapsing and remitting pattern, and a high heterogeneity with currently unpredictable disease courses and clinical outcomes. AD potentially comprises a variety of endotypes, which share common clinical characteristics, but arise from distinct molecular and cellular mechanisms. Although omics analyses have promoted the understanding of disease mechanisms and the development of innovative targeted therapies, many questions regarding the pathophysiology, disease heterogeneity, and patient-stratified therapeutic approaches remain unresolved. So far, most of the transcriptome studies, i.e. studies investigating the gene expression, on AD relied on microarray data, were conducted in the context of clinical trials, examined one timepoint only, and rarely included healthy control subjects as reference. Further, most of the previous transcriptome studies in AD were focused exclusively on the skin, while blood was not covered, although there is robust evidence for systemic immune abnormalities in AD. Within the scope of this work, I analysed transcriptome data generated from longitudinal skin and blood samples of deeply characterised AD patients from the TREATgermany registry as well as of healthy controls using sensitive and unbiased mRNA sequencing. In a first study, I was able to identify a stable core transcriptome signature in both lesional and nonlesional skin differentiating patients from healthy individuals and reflecting epidermal barrier dysfunction, innate immune activation and heightened itch signalling as key disease mechanism. A second dynamic signature reflects a progressive activation of immune responses with heightened inflammation in lesions. A large proportion of transcriptomic dysregulation is reverted with clinically successful systemic treatment with, however, a considerable residual genomic profile with treatment-specific differences indicating insufficient disease control on the molecular level that might give rise to flares and recurrences. In a second study, I characterised skin transcriptomic signatures attributable to natural killer (NK) cells, which recently have been suggested to be involved in the pathophysiology of AD. The analysis showed that NK cells and related killer cells accumulate in AD lesions, and that there is a disturbed composition of resting and activated NK cells. After successful remission through systemic treatment I observed qualitative albeit not quantitative shifts of NK cell signatures. In a third work, I analysed whole-blood transcriptome data of patients with AD and healthy controls. In a cluster analysis, I identified two potential endotypes, one of which showed a high degree of systemic transcriptomic dysregulation and an eosinophilic profile, and another showing a low degree of dysregulation and a non-eosinophilic profile. Association of eosinophil expression profiles with disease activity suggest that these endotypes might have clinical implications. Detected signatures related to NK cells indicate a reduced abundance and dysfunction of certain NK cells subsets also in the peripheral blood, underpinning the importance of this cell type for the pathophysiology of AD.

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