Dynamic CD4⁺ T-Cell eQTLs Reveal Gene Regulatory Networks Associated with Atopic Dermatitis
- 1Department of Dermatology
Abstract
Jian Chen,1,2 Bingxue Bai11Department of Dermatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China; 2Department of Dermatology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People’s Hospital), Dongguan, 523059, People’s Republic of ChinaCorrespondence: Bingxue Bai, Department of Dermatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China, Tel +86 15114517408, Email [email protected] and Objective: Atopic dermatitis (AD) is a complex immune-mediated disorder in which aberrant activation of CD4⁺ T cells plays a critical pathogenic role. We integrated dynamic CD4⁺ T cell expression quantitative trait loci (eQTL) data with Mendelian randomization (MR) to dissect the causal effect of transcriptional changes on AD risk.Methods: This study integrated dynamic CD4⁺ T-cell eQTL analysis, two-sample MR, colocalization analysis, single-cell transcriptomic, pseudotime, cell–cell communication and protein–protein interaction (PPI) analyses, with virtual single-cell knockout further used to evaluate gene regulatory effects in AD. We systematically analyzed gene expression and genetic variation in CD4⁺ T cells from 119 individuals of European ancestry across multiple activation time points (0 h, 16 h, 40 h, and 5 days).Results: We performed two-sample Mendelian randomization (MR) integrating dynamic CD4⁺ T-cell eQTL, OneK1K, eQTLGen, and FinnGen R12 AD cohort data. The analysis identified 298 genes significantly associated with AD (FDR < 0.05), including key regulators such as FADS1, IRF5, and IL1RN, showing distinct causal effects between resting and activated states. Colocalization confirmed 11 core genes (eg, KDELR2, FADS1) underlying AD risk loci. Single-cell transcriptomic and pseudotime analyses revealed dynamic CD4⁺ T-cell regulatory trajectories, while cell–cell communication and protein interaction networks linked several candidates (IRF5, CTSS, PTGER4) to therapeutic pathways of existing AD drugs. Virtual single-cell knockouts of AHI1, CTSS, PTGER4, and PPP5C showed gene-specific regulatory patterns in skin barrier and immune-related pathways.Conclusion: We demonstrate that understanding the dynamic characteristics of CD4⁺ T cells is crucial for AD, and prioritize genes for future research into its pathogenesis.Keywords: atopic dermatitis, dynamic eQTL, single-cell analysis, Mendelian randomization analysis, virtual knockout
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BibTeX
@article{chen2026dynamic,
title = {{Dynamic CD4⁺ T-Cell eQTLs Reveal Gene Regulatory Networks Associated with Atopic Dermatitis}},
author = {Chen J and Bai B},
journal = {Clinical, Cosmetic and Investigational Dermatology},
year = {2026},
month = nov,
url = {https://www.dovepress.com/dynamic-cd4-t-cell-eqtls-reveal-gene-regulatory-networks-associated-wi-peer-reviewed-fulltext-article-CCID},
note = {CC BY},
}
RIS
TY - JOUR
TI - Dynamic CD4⁺ T-Cell eQTLs Reveal Gene Regulatory Networks Associated with Atopic Dermatitis
AU - Chen J
AU - Bai B
PY - 2026
DA - 2026/11/05
JO - Clinical, Cosmetic and Investigational Dermatology
UR - https://www.dovepress.com/dynamic-cd4-t-cell-eqtls-reveal-gene-regulatory-networks-associated-wi-peer-reviewed-fulltext-article-CCID
AB - Jian Chen,1,2 Bingxue Bai11Department of Dermatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China; 2Department of Dermatology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People’s Hospital), Dongguan, 523059, People’s Republic of ChinaCorrespondence: Bingxue Bai, Department of Dermatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, People’s Republic of China, Tel +86 15114517408, Email [email protected] and Objective: Atopic dermatitis (AD) is a complex immune-mediated disorder in which aberrant activation of CD4⁺ T cells plays a critical pathogenic role. We integrated dynamic CD4⁺ T cell expression quantitative trait loci (eQTL) data with Mendelian randomization (MR) to dissect the causal effect of transcriptional changes on AD risk.Methods: This study integrated dynamic CD4⁺ T-cell eQTL analysis, two-sample MR, colocalization analysis, single-cell transcriptomic, pseudotime, cell–cell communication and protein–protein interaction (PPI) analyses, with virtual single-cell knockout further used to evaluate gene regulatory effects in AD. We systematically analyzed gene expression and genetic variation in CD4⁺ T cells from 119 individuals of European ancestry across multiple activation time points (0 h, 16 h, 40 h, and 5 days).Results: We performed two-sample Mendelian randomization (MR) integrating dynamic CD4⁺ T-cell eQTL, OneK1K, eQTLGen, and FinnGen R12 AD cohort data. The analysis identified 298 genes significantly associated with AD (FDR < 0.05), including key regulators such as FADS1, IRF5, and IL1RN, showing distinct causal effects between resting and activated states. Colocalization confirmed 11 core genes (eg, KDELR2, FADS1) underlying AD risk loci. Single-cell transcriptomic and pseudotime analyses revealed dynamic CD4⁺ T-cell regulatory trajectories, while cell–cell communication and protein interaction networks linked several candidates (IRF5, CTSS, PTGER4) to therapeutic pathways of existing AD drugs. Virtual single-cell knockouts of AHI1, CTSS, PTGER4, and PPP5C showed gene-specific regulatory patterns in skin barrier and immune-related pathways.Conclusion: We demonstrate that understanding the dynamic characteristics of CD4⁺ T cells is crucial for AD, and prioritize genes for future research into its pathogenesis.Keywords: atopic dermatitis, dynamic eQTL, single-cell analysis, Mendelian randomization analysis, virtual knockout
SN - 1178-7015
ER -