So close, and yet so far away: The dichotomy of the specific immune response and inflammation in psoriasis and atopic dermatitis (Review).

Abundant heterogeneous immune cells infiltrate lesions in chronic inflammatory diseases and characterization of these cells is needed to distinguish disease-promoting from bystander immune cells. Here, we investigate the landscape of non-communicable inflammatory skin diseases (ncISD) by spatial transcriptomics resulting in a large repository of 62,000 spatially defined human cutaneous transcriptomes from 31 patients. Despite the expected immune cell infiltration, we observe rather low numbers of pathogenic disease promoting cytokine transcripts (IFNG, IL13 and IL17A), i.e. >125 times less compared to the mean expression of all other genes over lesional skin sections. Nevertheless, cytokine expression is limited to lesional skin and presented in a disease-specific pattern. Leveraging a density-based spatial clustering method, we identify specific responder gene signatures in direct proximity of cytokines, and confirm that detected cytokine transcripts initiate amplification cascades of up to thousands of specific responder transcripts forming localized epidermal clusters. Thus, within the abundant and heterogeneous infiltrates of ncISD, only a low number of cytokine transcripts and their translated proteins promote disease by initiating an inflammatory amplification cascade in their local microenvironment.

Chronic inflammatory diseases of the cardiovascular system, brain, gut, joints, skin and lung are characterized by complex interactions between genetic predisposition and tissuespecific 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 bio-computational approach that assigns deep clinical phenotyping information to transcriptome data of lesional and non-lesional skin (564 samples) to identify biologically-relevant gene signatures. This identified previously unknown key 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 were validated using genetically-modified human skin equivalents, migration assays, and in situ imaging. Thus, by combining deep clinical phenotyping and omics data with sophisticated bio-computational algorithms we present a methodological advance to identify hidden drivers of clinically-relevant biological processes within omics datasets.One Sentence SummaryDeciphering the pathogenesis of chronic inflammatory diseases by assigning transcriptome profiles to deep clinical phenotyping.

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