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Massively parallel analysis of genotype-dependent enhancer activity among atopic dermatitis genetic risk variants

2025/08/21 by Molly Shook, Xiaoming Lu, Xiaoting Chen +16 · 1 voice
Immunology and Microbiology · Medicine · #Dermatology and Skin Diseases #Hair Growth and Disorders #Psoriasis: Treatment and Pathogenesis

paper · doi:10.1016/j.jaci.2025.07.032

openalex publication_date 2025/08/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Abstract

BACKGROUND: Atopic dermatitis (AD) is an inflammatory, pruritic disease of the skin with a complex etiology involving environmental and genetic factors. Numerous genetic risk loci for AD have been nominated through genome-wide association studies, with most associated variants residing in noncoding regions. Further work is needed to understand how genetic variation contributes to disease-related alterations to gene expression. OBJECTIVE: We sought to use massively parallel reporter assays to identify genetic risk variants with genotype-dependent regulatory activity within a set of 2,381 variants distributed among 49 independent AD risk loci. METHODS: We used our massively parallel reporter assay library in HaCaT skin keratinocytes, TE-7 esophageal epithelial cells, and Jurkat T cells, enabling the identification of shared and cell-type-specific variants with genotype-dependent enhancer activity. Stimulation of HaCaT and TE-7 cells with the cytokine IL-13 revealed 14 variants with stimulation-dependent allelic expression patterns. RESULTS: Our approach discovered 96 allelic enhancer variants among all investigated cellular contexts, representing 32 independent AD risk loci. We discover a possible mechanistic role for activator protein 1 family transcription factors, as revealed by motif enrichment, genotype-dependent binding, and enhanced chromatin immunoprecipitation sequencing signal at AD risk variants with allelic enhancer activity compared with variants with nonallelic enhancer activity. We assign allelic enhancer variants to probable target genes, including previously identified risk genes such as KIF3A and FLG. CONCLUSIONS: Our systematic, genome-scale approach implicates causal genotype-dependent gene regulatory mechanisms for most AD risk loci, providing a unique resource for the discovery of the genetic mechanisms underlying this disease.

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