ArticleAnnals of dermatology2026
From Genetic Variants to Immune Dysregulation: Multi-Omics Mendelian Randomization Decodes Molecular Networks in Rosacea.
Article in Annals of dermatology, 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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8 authors.
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Abstract
backgroundRosacea is a chronic inflammatory skin disease with incompletely understood pathogenesis.
objectiveThis study aimed to identify key genes and regulatory mechanisms using multi-omics Mendelian randomization (MR) and machine learning, and to validate the findings in animal experiments.
methodsBidirectional MR analysis using eQTL, pQTL, and mQTL datasets (GWAS ID: GCST90476178) identified rosacea-associated genes. LASSO regression and random forest were used to screen key genes. Immune infiltration, GSEA/GSVA, non-coding RNA network analysis, and molecular docking were used to explore gene functions and drug targets. Real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot validated findings in a rosacea mouse model.
resultsFive key genes (
conclusionThis study reveals five key genes and immune-related mechanisms in rosacea, offering novel targets for diagnosis and therapy.
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