Transcriptional profiling of irritant contact dermatitis (ICD) in a mouse model identifies specific patterns of gene expression and immune-regulation

Unique molecular signatures typify skin inflammation induced by chemical allergens and irritants

BACKGROUND

Skin exposure to chemicals may induce an inflammatory disease known as contact dermatitis (CD). Distinguishing the allergic and irritant forms of CD often proves challenging in the clinic.

METHODS

To characterize the molecular signatures of chemical-induced skin inflammation, we conducted a comprehensive transcriptomic analysis on the skin lesions of 47 patients with positive patch tests to reference contact allergens and nonallergenic irritants.

RESULTS

A clear segregation was observed between allergen- and irritant-induced gene profiles. Distinct modules pertaining to the epidermal compartment, metabolism, and proliferation were induced by both contact allergens and irritants; whereas only contact allergens prompted strong activation of adaptive immunity, notably of cytotoxic T-cell responses. Our results also confirmed that: (a) unique pathways characterize allergen- and irritant-induced dermatitis; (b) the intensity of the clinical reaction correlates with the magnitude of immune activation. Finally, using a machine-learning approach, we identified and validated several minimal combinations of biomarkers to distinguish contact allergy from irritation.

CONCLUSION

These results highlight the value of molecular profiling of chemical-induced skin inflammation for improving the diagnosis of allergic versus irritant contact dermatitis.

Loss of Interleukin-6 Influences Transcriptional Immune Signatures and Alters Bacterial Colonization in the Skin

The skin functions as a protective barrier to inhibit the entry of foreign pathogens, all the while hosting a diverse milieu of microorganisms. Over time, skin cells, immune cells, cytokines, and microbes interact to integrate the processes of maintaining the skin's physical and immune barrier. In the present study, the basal expression of two immunologically divergent mouse strains C57BL/6 and BALB/c, as well as a strain on the C57 background lacking IL-6, was characterized. Additionally, cutaneous antimicrobial gene expression profiles and skin bacterial microbiome were assessed between strains. Total RNA sequencing was performed on untreated C57BL/6 (control), BALB/c, and IL-6-deficient skin samples and found over 3,400 genes differentially modulated between strains. It was found that each strain modulated its own transcriptional "profile" associated with skin homeostasis and also influenced the overall bacterial colonization as indicated by the differential phyla present on each strain. Together, these data not only provide a comprehensive view of the transcriptional changes in homeostatic skin of different mouse strains but also highlight the possible influence of the strain differences (e.g., Th1/Th2 balance) as well as a role for IL-6 in overall skin immunity and resident microbial populations.

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.