Profiling of remote skeletal muscle gene changes resulting from stimulation of atopic dermatitis disease in NC/Nga mouse model

Darier's disease exhibits a unique cutaneous microbial dysbiosis associated with inflammation and body malodour

BACKGROUND

Darier's disease (DD) is a genodermatosis caused by mutations of the ATP2A2 gene leading to disrupted keratinocyte adhesion. Recurrent episodes of skin inflammation and infections with a typical malodour in DD indicate a role for microbial dysbiosis. Here, for the first time, we investigated the DD skin microbiome using a metabarcoding approach of 115 skin swabs from 14 patients and 14 healthy volunteers. Furthermore, we analyzed its changes in the context of DD malodour and the cutaneous DD transcriptome.

RESULTS

We identified a disease-specific cutaneous microbiome with a loss of microbial diversity and of potentially beneficial commensals. Expansion of inflammation-associated microbes such as Staphylococcus aureus and Staphylococcus warneri strongly correlated with disease severity. DD dysbiosis was further characterized by abundant species belonging to Corynebacteria, Staphylococci and Streptococci groups displaying strong associations with malodour intensity. Transcriptome analyses showed marked upregulation of epidermal repair, inflammatory and immune defence pathways reflecting epithelial and immune response mechanisms to DD dysbiotic microbiome. In contrast, barrier genes including claudin-4 and cadherin-4 were downregulated.

CONCLUSIONS

These findings allow a better understanding of Darier exacerbations, highlighting the role of cutaneous dysbiosis in DD inflammation and associated malodour. Our data also suggest potential biomarkers and targets of intervention for DD. Video Abstract.

Review-Current Concepts in Inflammatory Skin Diseases Evolved by Transcriptome Analysis: In-Depth Analysis of Atopic Dermatitis and Psoriasis

During the last decades, high-throughput assessment of gene expression in patient tissues using microarray technology or RNA-Seq took center stage in clinical research. Insights into the diversity and frequency of transcripts in healthy and diseased conditions provide valuable information on the cellular status in the respective tissues. Growing with the technique, the bioinformatic analysis toolkit reveals biologically relevant pathways which assist in understanding basic pathophysiological mechanisms. Conventional classification systems of inflammatory skin diseases rely on descriptive assessments by pathologists. In contrast to this, molecular profiling may uncover previously unknown disease classifying features. Thereby, treatments and prognostics of patients may be improved. Furthermore, disease models in basic research in comparison to the human disease can be directly validated. The aim of this article is not only to provide the reader with information on the opportunities of these techniques, but to outline potential pitfalls and technical limitations as well. Major published findings are briefly discussed to provide a broad overview on the current findings in transcriptomics in inflammatory skin diseases.