ArticleArchives of medical science : AMS2026
Identification of potential drug target genes for atopic dermatitis leveraging Mendelian randomization, single-cell transcriptomics, and spatial transcriptomics.
Article in Archives of medical science : AMS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Atopic dermatitis (AD), the most common chronic inflammatory dermatosis, currently lacks definitive curative treatments. This study aimed to identify potential drug targets for AD through an integrative genomic approach. Material and methods: Cis-expression quantitative trait loci (cis-eQTL) from the eQTLGen consortium were used as genetic instruments for druggable genes. Summary-level AD statistics were obtained from the largest available GWAS dataset (cases = 22,474; controls = 774,187) with replication in an independent cohort (cases = 10,788; controls = 30,047). Mendelian randomization (MR) was employed to explore the causal relationship between druggable genes and AD risk, augmented by colocalization analysis to identify shared causal variants. A pQTL dataset was thereafter used for further validation. Furthermore, the potential association between the identified genes and five other inflammatory skin diseases was also assessed. Finally, we specifically investigated expression patterns of identified genes through analysis of single-cell RNA sequencing and spatial transcriptomics data from GEO datasets via Seurat. Results: Three druggable genes, Conclusions: These findings suggest that IL2RA inhibitors could be promising therapeutic agents for the treatment of AD.
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