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Jargosch, M.

Publications and source records attributed to Jargosch, M..

2 recordsLinked to original sources

Low numbers of cytokine transcripts drive inflammatory skin diseases by initiating amplification cascades in localized epidermal clusters

Abundant polyclonal T cells infiltrate chronic inflammatory diseases and characterization of these cells is needed to distinguish disease-driving from bystander immune cells. Here, we investigated 52,000 human cutaneous transcriptomes of non-communicable inflammatory skin diseases (ncISD) using spatial transcriptomics. Despite the expected T cell infiltration, we observed only 1-10 pathogenic T cell cytokine per skin section. Cytokine expression was limited to lesional skin and presented in a disease-specific pattern. In fact, we identified responder signatures in direct proximity of cytokines, and showed that single cytokine transcripts initiate amplification cascades of thousands of specific responder transcripts forming localized epidermal clusters. Thus, within the abundant and polyclonal T cell infiltrates of ncISD, only a few T cells drive disease by initiating an inflammatory amplification cascade in their local microenvironment.

immunology↗

Identifying hidden drivers of heterogeneous inflammatory diseases

Chronic inflammatory diseases are characterized by complex interactions between genetic predisposition and tissue-specific immune responses. This heterogeneity complicates diagnoses and the ability to exploit omics approaches to improve disease management, develop more effective therapeutics, and apply precision medicine. Using skin inflammation as a model, we developed a method that integrates deep clinical phenotyping information (phenomics) with transcriptome data of lesional and non-lesional skin (564 samples) to identify clinically-relevant gene signatures. It led us to discover so-far unexplored factors, including CCAAT Enhancer-Binding Protein Beta (CEBPB) in neutrophil invasion, and Pituitary Tumor-Transforming 2 (PTTG2) in the pathogenic epithelial response to inflammation. These factors were validated using genetically-modified human skin equivalents, migration assays, and in situ imaging. Thus, by meaningful integration of deep clinical phenotyping and omics data we reveal hidden drivers of clinically-relevant biological processes.

immunology↗