Background: Allergic rhinitis is common and clinically heterogeneous, but the genes whose genetically regulated immune-state expression influences susceptibility remain incompletely resolved. Methods: We integrated dynamic CD4+ T cell eQTL data (46 activation-state profiles) with allergic rhinitis GWAS summary statistics, applying transcriptome-wide Mendelian randomization (MR), colocalization, SMR/HEIDI, metabolite screening, paired single-cell RNA-seq and TCR analysis, and computational follow-up. Colocalization support was prespecified as conditional ratio PP.H4/(PP.H3 + PP.H4) > 0.7; HEIDI at p > 0.05. Results: After MHC-region exclusion, 50,654 gene-profile pairs were tested and 129 MR-significant genes were identified. Colocalization supported 418 pairs (111 genes); 70 genes passed both SMR and HEIDI; and cross-database comparison yielded a nine-gene overlap set. In GSE200107, baseline good-versus-poor responder differences were larger than treatment-induced transcriptional change; patient-level reanalysis found no pair surviving multiple-testing correction (n = 4 vs. 3); these findings are hypothesis-generating. Paired TCR analysis suggested greater clonotype renewal in good responders (descriptive). Structure-guided screening prioritized unvalidated binder candidates for SLC25A46 and TLR1 (TLR1 TIR docking −5.86 kcal/mol; MD RMSD 0.20 nm). Conclusions: An exploratory metabolite screen yielded nominally significant indirect-effect signals, but the candidate metabolite did not colocalize with the disease locus. This framework prioritizes candidate therapeutic targets for allergic rhinitis.
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Gu et al. (2026) studied this question.
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