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DERMATOLOGY / CLINICAL RESEARCH
Identification of potential drug target genes for atopic dermatitis leveraging Mendelian randomization, single-cell transcriptomics, and spatial transcriptomics
1
Department of Dermatology, The Calmette Affiliated Hospital of Kunming Medical University, Kunming, China
2
Department of Dermatology, Kunming City Maternal and Child Health Hospital, Wuhua District, Kunming, China
3
Department of Dermatology, Guiyang Second People’s Hospital, Guanshanhu District, Guiyang, China
These authors had equal contribution to this work
Submission date: 2025-04-15
Final revision date: 2025-07-24
Acceptance date: 2025-07-31
Online publication date: 2025-10-05
Corresponding author
Qi Li
Department of Dermatology The Calmette Affiliated Hospital of Kunming Medical University Kunming, China Phone: +86-13698760791
Department of Dermatology The Calmette Affiliated Hospital of Kunming Medical University Kunming, China Phone: +86-13698760791
KEYWORDS
atopic dermatitisdrug targetMendelian randomizationsingle-cell RNA sequencingspatial transcriptomics
TOPICS
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, HSP90AA1, IL2RA, and MANBA, were positively associated with an increased risk of AD. Colocalization analysis identified rs61839660 as a shared variant between IL2RA and AD, with pQTL data confirming IL2RA protein-level effects. Increased IL2RA gene expression was observed in natural killer cells within leukocyte infiltration regions. Moreover, MR analysis indicated that IL2RA gene expression also increases the risk of psoriasis and eczema, though without colocalization evidence.
Conclusions:
These findings suggest that IL2RA inhibitors could be promising therapeutic agents for the treatment of AD.
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, HSP90AA1, IL2RA, and MANBA, were positively associated with an increased risk of AD. Colocalization analysis identified rs61839660 as a shared variant between IL2RA and AD, with pQTL data confirming IL2RA protein-level effects. Increased IL2RA gene expression was observed in natural killer cells within leukocyte infiltration regions. Moreover, MR analysis indicated that IL2RA gene expression also increases the risk of psoriasis and eczema, though without colocalization evidence.
Conclusions:
These findings suggest that IL2RA inhibitors could be promising therapeutic agents for the treatment of AD.
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| eISSN: | 1896-9151 |
| ISSN: | 1734-1922 |
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