Multi-Ancestry Genome-wide Association Analyses Identify Shared and Specific Genetic Architecture in Mild and Moderate-to-Severe Asthma

Moderate-to-severe asthma affects 15-30% of asthma patients but accounts for more than 50% of healthcare costs and disproportionate morbidity, yet the genetic mechanisms distinguishing it from mild asthma have remained poorly understood.

The study performed separate pooled multi-ancestry GWAS of mild asthma (N = 14,372) and moderate-to-severe asthma (N = 7,096) versus non-asthma controls (N = 28,816) among adult participants in the NIH All of Us Research Program (version 8). European, African, and Latino/admixed ancestry-specific GWAS were combined using fixed-effect meta-analysis, and lung expression quantitative trait loci (eQTL) and pathway analyses were used to identify candidate genes and biological pathways across the phenotypes.

Mild and moderate-to-severe asthma shared susceptibility loci at IL1RL1, IKZF3, and the GTF3AP1-IL33, GTF3AP1-RANBP6, LINC02757-EMSY and HLA-DRB1-HLA-DQA1 regions; shared lung eQTLs implicated IL18R1, IL18RAP, HLA genes, IL33, LRRC32, GRB7, MIEN1 and GSDMB. Beyond this overlap, the phenotypes showed distinct genetic architectures: mild asthma was characterized by broader HLA class II signals and associations at SMAD3 and GSDMB, with enrichment of antigen presentation, T-helper cell differentiation, and TGF-β regulation, consistent with adaptive immune mechanisms. Moderate-to-severe asthma was characterized by WDR36 and PTCH1, with lung eQTLs implicating TSLP, CAMK4, and FANCC, and pathway analysis showing enrichment of IL-13, IL-6, and IL-10 production, myeloid leukocyte differentiation, and oxidative stress responses — consistent with innate inflammation and pathways implicated in steroid resistance. The IL33 signals showed a severity-gradient effect, with stronger associations in moderate-to-severe asthma.

The authors conclude that mild and moderate-to-severe asthma exhibit shared and distinct genetic architectures that support existing biologic targets and suggest novel therapeutic candidates.