Abstract
The skin, the body's largest external organ, serves as the primary interface with the outside world. Psoriasis, a chronic skin condition, involves a complex interplay of immunological and environmental factors, initially affecting the skin but eventually leading to systemic immune dysregulation, rendering it a multifaceted systemic disease.
Over the past decade,
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the introduction of biologics has revolutionized psoriasis treatment by modulating the immune environment. However, it's important to recognize that not all psoriasis patients respond favorably to these biologics. This underscores the intricate and heterogeneous nature of psoriasis, which involves multiple immune pathways and genetic elements. Biologics targeting specific cytokines or cell types may not be universally effective in controlling the disease. Furthermore, the skin's immune response is intricately linked with the broader immune system, necessitating continuous interactions for immune regulation.
In Chapter 1, we explored the utility of omics technologies in the context of psoriasis, emphasizing the need for ongoing exploration of omics data to gain a comprehensive understanding of the intricate biological processes at play. Subsequent chapters (2-5) delved into the application of various omics techniques to investigate the transcriptomic, proteomic, and microbiomic aspects of both skin tissue and blood samples from patients with psoriasis and other autoimmune conditions like psoriatic arthritis, ankylosing spondylitis, and atopic dermatitis.
Chapter 2 employed a tree-based machine learning approach to uncover the gene regulatory networks underlying psoriasis, identifying key regulators that could serve as potential drug targets and disease severity markers. Notably, the interferon signaling pathway emerged as a central component of psoriatic inflammation.
In Chapter 3, we examined the associations between the transcriptome and microbiome in different skin samples, revealing significant differences in the transcriptome profiles between lesion and non-lesion skin. Functional annotation highlighted a strong emphasis on neutrophil activation. A core gene network emerged, intricately linked to inflammation and hyper-keratinization, with microbiome analysis shedding light on correlations with specific microbial species.
Chapter 4 focused on identifying psoriasis biomarkers through proteome profiling of patient serum and transcriptome sequencing of skin samples. Peptidase inhibitor 3 (PI3) emerged as a significant biomarker, correlating with local skin gene expression and disease severity. Single-cell analysis confirmed PI3's high expression in psoriatic keratinocytes, suggesting its utility as a psoriasis-specific biomarker.
In Chapter 5, single-cell RNA sequencing and T cell repertoire profiling were employed to understand the immune response in psoriasis, both in peripheral blood and skin samples. Immune signatures of various myeloid and lymphocyte subsets were revealed, highlighting significant alterations in immune cell subsets in psoriasis patients. Specific characteristics, such as the CD8+ TRM cells producing high levels of IFN-γ or IL-17, were identified as unique to psoriasis. These findings provide valuable insights into the pathophysiology of psoriasis.
Based on our findings, it is increasingly likely that environmental microbial triggers activate and recruit neutrophils and pDCs to the skin. This stimulation leads to the secretion of antimicrobial peptides like PI3 by keratinocytes, which can enter the circulation. Circulating monocytes and effector memory T cells may respond to these processes and migrate to the skin, forming monocyte-derived macrophages and resident memory T cells cells, thus contributing to the pro-inflammatory loop driving the development of psoriatic lesions. Finally, it is important to note that our observations might be the consequences of the transcriptional state rather than having been conclusively proven.
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