Activation-dependent genetic regulation in CD4⁺ T cells prioritizes druggable targets for asthma

Asthma is a genetically complex immune-mediated disease, yet most functional genomic studies rely on steady-state expression quantitative trait locus (eQTL) resources that may not fully capture activation-dependent regulatory effects. We investigated whether genetically supported asthma-associated regulatory signals differ across CD4⁺ T-cell activation states. We integrated activation-resolved CD4⁺ T-cell eQTL data spanning multiple activation stages with two-sample Mendelian randomization (MR) and colocalization analyses using asthma genome-wide association study summary statistics. Results were compared with four static eQTL resources (OneK1K, DICE, GTEx, and eQTLGen). We further assessed CD4⁺ T-cell subset specificity, cross-stage heterogeneity, activation-stage regulatory patterns, independent validation in the Global Biobank Meta-analysis Initiative (GBMI), and translational relevance using drug–target and clinical evidence. Across 7,295 genes and 34,266 MR tests, 316 genes showed significant MR associations with asthma risk, of which 278 were further supported by colocalization. Genetically supported signals were more frequently detected at intermediate and late activation stages, and most were restricted to a single activation state. GBMI validation supported 477 of 787 primary MR-supported cell-state–gene pairs (60.6%), of which 97.1% showed concordant effect directions. Among the 278 genes, 163 (58.6%) were identified only in the activation-resolved analysis under the applied criteria. Overall, these MR- and colocalization-supported genes were enriched in activated and effector CD4⁺ T-cell subsets, particularly CD4_STIM, TH2, TFH, and TH17. Cross-stage analyses identified sustained and direction-switch profiles as the predominant regulatory patterns. Higher CD4⁺ T-cell specificity was associated with increased odds of activation-stage-specific signals (OR = 1.18, 95% CI: 1.11–1.25, P = 1.4 × 10⁻⁷, FDR = 1.6 × 10⁻⁶). Translational prioritization yielded a structured set of 47 candidate genes, including seven linked to asthma-related clinical trials and others with possible repurposing relevance. Asthma-associated regulatory signals vary across CD4⁺ T-cell activation contexts. Activation-resolved eQTL analysis provides complementary information to steady-state resources and reveals heterogeneity across activation stages and CD4⁺ T-cell lineages. These patterns reflect differences in genetically supported associations across activation states rather than direct evidence of temporal changes in causal effects. Because the underlying genetic resources were derived predominantly from individuals of European ancestry, generalizability to other populations requires further evaluation.