The integration of large-scale public data and network analysis uncovers molecular characteristics of psoriasis

Integrative network analysis suggests prioritised drugs for atopic dermatitis

BACKGROUND

Atopic dermatitis (AD) is a prevalent chronic inflammatory skin disease whose pathophysiology involves the interplay between genetic and environmental factors, ultimately leading to dysfunction of the epidermis. While several treatments are effective in symptom management, many existing therapies offer only temporary relief and often come with side effects. For this reason, the formulation of an effective therapeutic plan is challenging and there is a need for more effective and targeted treatments that address the root causes of the condition. Here, we hypothesise that modelling the complexity of the molecular buildup of the atopic dermatitis can be a concrete means to drive drug discovery.

METHODS

We preprocessed, harmonised and integrated publicly available transcriptomics datasets of lesional and non-lesional skin from AD patients. We inferred co-expression network models of both AD lesional and non-lesional skin and exploited their interactional properties by integrating them with a priori knowledge in order to extrapolate a robust AD disease module. Pharmacophore-based virtual screening was then utilised to build a tailored library of compounds potentially active for AD.

RESULTS

In this study, we identified a core disease module for AD, pinpointing known and unknown molecular determinants underlying the skin lesions. We identified skin- and immune-cell type signatures expressed by the disease module, and characterised the impaired cellular functions underlying the complex phenotype of atopic dermatitis. Therefore, by investigating the connectivity of genes belonging to the AD module, we prioritised novel putative biomarkers of the disease. Finally, we defined a tailored compound library by characterising the therapeutic potential of drugs targeting genes within the disease module to facilitate and tailor future drug discovery efforts towards novel pharmacological strategies for AD.

CONCLUSIONS

Overall, our study reveals a core disease module providing unprecedented information about genetic, transcriptional and pharmacological relationships that foster drug discovery in atopic dermatitis.

Architecture of skin inflammation in psoriasis revealed by spatial transcriptomics

Psoriasis is a chronic inflammatory skin disease, thought to be predominantly mediated by TH17 cells. Significance of other inflammatory pathways and the innate immune system is not well understood and the spatial heterogeneity of inflammation in the skin has largely been overlooked. Our aim was to create a comprehensive map of skin inflammation in psoriasis, exploring the tissue patterning of inflammation. In situ whole transcriptome sequencing (spatial sequencing) was performed on lesional psoriatic skin in four patients with moderate-to-severe disease to quantify all expressed genes within a tissue section. Transcriptional analysis revealed three major inflammatory niches in psoriasis skin, each with distinct cytokine circuits and chemokines: the hyperplastic epidermis, upper (papillary) dermis, and reticular dermis. Interestingly, key cytokines such as IL-23, IL-17 s, and TNFα were not notably present in the skin's transcriptomic signature. Unexpectedly, IL-32 showed strong expression in the dermis. Our findings underscore the complexity of psoriatic inflammation, highlighting its architectural heterogeneity and the roles of innate cytokines. Both IL-32 and IL-1 family cytokines appear to play critical roles in the dermal and epidermal inflammation, respectively, and may provide pharmacological targets to improve the control of the inflammatory process.

Multi-Omics Research Strategies for Psoriasis and Atopic Dermatitis

Psoriasis and atopic dermatitis (AD) are multifactorial and heterogeneous inflammatory skin diseases, while years of research have yielded no cure, and the costs associated with caring for people suffering from psoriasis and AD are a huge burden on society. Integrating several omics datasets will enable coordinate-based simultaneous analysis of hundreds of genes, RNAs, chromatins, proteins, and metabolites in particular cells, revealing networks of links between various molecular levels. In this review, we discuss the latest developments in the fields of genomes, transcriptomics, proteomics, and metabolomics and discuss how they were used to identify biomarkers and understand the main pathogenic mechanisms underlying these diseases. Finally, we outline strategies for achieving multi-omics integration and how integrative omics and systems biology can advance our knowledge of, and ability to treat, psoriasis and AD.