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Background: Atopic dermatitis (AD) is a frequent and heterogeneous inflammatory skin disease, for which personalized medicine remains a challenge. High‐throughput approaches have improved understanding of the complex pathophysiology of AD. However, a purely data‐driven AD classification is still lacking. Methods: To address this question, we applied an original unsupervised approach on the largest available transcriptome dataset of AD lesional (n = 82) and healthy (n = 213) skin biopsies. Results: Taking into account pathological and physiological state, a variance‐based filtering revealed 222 AD‐specific hyper‐variable genes that efficiently classified the AD samples into 4 clusters that turned out to be clinically and biologically distinct. Comparison of gene expressions between clusters identified 3 sets of upregulated genes used to derive metagenes (MGs): MG‐I (19 genes) was associated with IL‐1 family signaling (including IL‐36A and 36G) and skin remodeling, MG‐II (23 genes) with negative immune regulation (including IL‐34 and 37) and skin architecture, and MG‐III (17 genes) with B lymphocyte immunity. Sample clusters differed in terms of disease severity (p =.02) and S. aureus (SA) colonization (p =.02). Cluster 1 contained the most severe AD, highest SA colonization, and overexpressed MG‐I. Cluster 2 was characterized by less severe AD, low SA colonization, and high MG‐II expression. Cluster 3 included mild AD, mild SA colonization, and mild expression of all MGs. Cluster 4 had the same clinical features as cluster 3 but had hyper‐expression of MG‐III. Last, we successfully validated our method and results in an independent cohort. Conclusion: Our study revealed unrecognized AD endotypes with specific underlying biological pathways, highlighting novel pathophysiological mechanisms. These data could provide new insights into personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Loss-of-function mutations in the filaggrin (FLG) gene directly alter skin barrier function and critically influence atopic inflammation. While skin barrier dysfunction, Th2-associated inflammation and bacterial dysbiosis are well-known characteristics of atopic dermatitis (AD), the mechanisms interconnecting genotype, transcriptome and microbiome remain largely elusive. In-depth analysis of FLG genotype-associated skin gene expression alterations and host-microbe interactions in AD. Multi-omics characterization of a cohort of AD patients carrying heterozygous loss-of-function mutations in the FLG gene (AD Mut ) (n = 15), along with matched wild-type (AD Wt ) patients and healthy controls. Detailed clinical characterization, microarray gene expression and 16 S rRNA-based microbial marker gene data were generated and analyzed. In the context of filaggrin dysfunction, the transcriptome was characterized by dysregulation of barrier function and water homeostasis, while the lesional skin of AD Wt demonstrated the specific upregulation of pro-inflammatory cytokines and T-cell proliferation. S. aureus dominated the microbiome in both patient groups, however, shifting microbial communities could be observed when comparing healthy with non-lesional AD Wt or AD Mut skin, offering the opportunity to identify microbe-associated transcriptomic signatures. Moreover, an AD core signature with 28 genes, including CCL13, CCL18, BTC, SCIN, RAB31 and PCLO was identified. Our integrative approach provides molecular insights for the concept that FLG loss-of-function mutations are a genetic shortcut to atopic inflammation and unravels the complex interplay between genotype, transcriptome and microbiome in the human holobiont. • Eczema patients carrying filaggrin mutations present equal or moderately higher severity than matched wild-type patients. • More extensive dysregulation of gene expression is present in filaggrin Wt lesions than in filaggrin Mut • A lower threshold of onset in filaggrin Mut and a „longer route" required for the same manifestation in filaggrin Wt. [ABSTRACT FROM AUTHOR]