Deconstruction of immune-mediated skin diseases defines six inflammatory subtypes

解构(建筑) 免疫系统 免疫学 医学 生物 生态学
作者
Yanhong Shou,Ronghui Zhu,Zhaoyuan Wang,Mei‐Jie Zhang,Xiao‐Yong Man
出处
期刊:QJM: An International Journal of Medicine [Oxford University Press]
标识
DOI:10.1093/qjmed/hcaf233
摘要

Abstract Background Most chronic skin diseases are classified as immune-mediated disorders, and targeted treatments, such as those blocking the cytokines IL-17, IL-23, IL-4/13, and the JAK–STAT pathway, have revolutionized therapy. However, a substantial proportion of patients fail to achieve remission and remain refractory to these therapies. Methods We meta-analyzed heterogeneous cell clusters in different immune-mediated skin diseases to understand the cell states and molecular pathways contributing to pathogenic heterogeneity. Results Therefore, we re-analyzed single-cell RNA-sequencing of 166 skin tissues, including 605,030 cells, to build a single-cell atlas of immune-mediated skin diseases. The results were validated using an independent patient cohort and in vitro fibroblast experiments. Samples were categorized into six groups, termed inflammatory phenotypes (IPs), each characterized by distinct variations in inflammatory pathways. These IPs offered new insights into inflammatory abnormalities and shared characteristics across different skin conditions. Disease-relevant cell states, cytokines, and genes were systematically mapped to individual IPs. Furthermore, cell-type abundance, cytokine infiltration, and metabolic heterogeneity were found to modulate shifts among Th1, Th2, and Th17/Th22 pathways. IPs were dynamic in individuals and could predict treatment response. Among our cohort, patients with unfavorable therapeutic outcomes exhibited distinct inflammatory patterns, characterized by elevated Th2 in psoriasis and elevated Th17/Th22 in atopic dermatitis. Conclusions This comprehensive atlas and molecular-based stratification of immune-mediated skin diseases provide new insights into the “pan-inflammation” features of cell states, which could help guide the development of targeted therapies.
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