Identification of Key Genetic Markers for Drug Pseudoallergy via Experimental Transcriptomics and GWAS-Based Causal Inference

Drug-induced pseudoallergic reactions are rapid in onset and complex in mechanism, with current clinical safety assessments lacking precise molecular underpinnings. Cells were treated with pseudoallergen-positive compounds. Cell degranulation was verified by neutral red staining and ELISA, followed by high-throughput RNA sequencing. Key signaling pathways were elucidated through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. A pseudoallergic characteristic gene network was identified and constructed using WGCNA. Finally, two-sample MR analysis was performed utilizing GWAS data to evaluate the causal relationship between candidate genes and drug pseudoallergy, thereby identifying key genetic risk markers. The pseudoallergen-positive compounds significantly induced cell degranulation and extensive transcriptional regulation. Enrichment analyses indicated that MAPK, JAK-STAT, TNF, and PI3K-Akt signaling pathways play central roles in pseudoallergic reactions. WGCNA identified a pseudoallergic characteristic gene signature. Subsequent MR analysis identified EMP1 and KIF26A might be the key genetic risk markers associated with drug pseudoallergy. These two genes potentially increase the causal risk of drug-induced pseudoallergy by modulating membrane coating, vesicle formation, and related cellular transport processes. This study successfully established a mast cell characteristic gene signature for pseudoallergic reactions, elucidated the core transcriptional network, and identified key risk markers that may have a causal association with drug pseudoallergy.

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Journal
Current Issues in Molecular Biology
Published
2026-09-29
DOI
https://doi.org/10.3390/cimb48101000
Primary Topic
Drug-Induced Adverse Reactions
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article
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article

Identification of Key Genetic Markers for Drug Pseudoallergy via Experimental Transcriptomics and GWAS-Based Causal Inference

Lihui Zhang, Feng Wei, Fangliang He, Xianlong Cheng et al.
Current Issues in Molecular Biology
Drug-Induced Adverse Reactions
article

Identification of Key Genetic Markers for Drug Pseudoallergy via Experimental Transcriptomics and GWAS-Based Causal Inference

Lihui Zhang, Feng Wei, Fangliang He, Xianlong Cheng, Yifan Guo, Lizhi Wan, Jiating Zhang, Yuechen Zhao, Yongqiang Lin, Jia Chen
article en

Abstract

Drug-induced pseudoallergic reactions are rapid in onset and complex in mechanism, with current clinical safety assessments lacking precise molecular underpinnings. Cells were treated with pseudoallergen-positive compounds. Cell degranulation was verified by neutral red staining and ELISA, followed by high-throughput RNA sequencing. Key signaling pathways were elucidated through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses. A pseudoallergic characteristic gene network was identified and constructed using WGCNA. Finally, two-sample MR analysis was performed utilizing GWAS data to evaluate the causal relationship between candidate genes and drug pseudoallergy, thereby identifying key genetic risk markers. The pseudoallergen-positive compounds significantly induced cell degranulation and extensive transcriptional regulation. Enrichment analyses indicated that MAPK, JAK-STAT, TNF, and PI3K-Akt signaling pathways play central roles in pseudoallergic reactions. WGCNA identified a pseudoallergic characteristic gene signature. Subsequent MR analysis identified EMP1 and KIF26A might be the key genetic risk markers associated with drug pseudoallergy. These two genes potentially increase the causal risk of drug-induced pseudoallergy by modulating membrane coating, vesicle formation, and related cellular transport processes. This study successfully established a mast cell characteristic gene signature for pseudoallergic reactions, elucidated the core transcriptional network, and identified key risk markers that may have a causal association with drug pseudoallergy.

Current Issues in Molecular BiologyVol. 48(10)
Shenyang Pharmaceutical University (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), National Institutes for Food and Drug Control (CN)
Good health and well-being
Openalex Percentile: Top 13%
Drug-Induced Adverse Reactions
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