Cross-scale genetic analysis prioritizes shared regulatory variation, cell-type contributions, co-expression programs, and exon-level patterns in atopic dermatitis and asthma.

Atopic dermatitis (AD) and asthma frequently co-occur, yet the regulatory mechanisms connecting cutaneous and airway inflammation remain unclear. We integrated European genome-wide association statistics for AD (22,474 cases; 774,187 controls) and asthma (56,167 cases; 352,255 controls) with expression and splicing quantitative trait loci (QTLs), immune single-cell expression QTLs, single-cell transcriptomes, and spatial transcriptomics. The AD dataset compared lesional skin with healthy controls, whereas the asthma dataset paired allergen and diluent challenges in four participants. Each was analyzed within its own design, and cross-disease comparison used independently derived annotations and gene sets. Regulatory QTL enrichment implicated skin, lung, fibroblast, and immune-related tissues. Cell-stratified Mendelian randomization identified multi-instrument associations in memory B cells (odds ratio = 1.35, 95% confidence interval 1.18-1.56; false discovery rate = 1.1 × 10⁻⁴) and immature/naïve B cells (1.26, 1.10-1.45); single-instrument estimates were exploratory regardless of false discovery rate, and no association has been independently replicated. T-cell co-expression analysis identified three cross-disease module overlaps-translational, metabolic-cytoskeletal, and cytotoxic effector-each significant after multiple-testing correction across 42 module comparisons. Airway transcripts in the asthma T-cell compartment were attributed predominantly to ambient RNA. Bayesian colocalization identified signals at 19 AD and 72 asthma loci and 112 shared genes. Integrated evidence prioritized SLC22A4, CTSW, IL1R1, RMI2, and IRF1; four ranked in the top five under all eight scoring schemes and IRF1 under seven, and all five retained top-ten ranking in ≥ 98.9% of 10,000 moderately concentrated randomized weightings. These results prioritize shared regulatory candidates for validation.