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Context-specific genetic effects inform endotypes and treatment in asthma

Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Asthma has heterogeneous risk factors, subtypes, and treatments. It is often unclear how to stratify this heterogeneity in scientific studies and clinical care. Genetics could explain root causes of this clinical heterogeneity, called endotypes, but prior studies have used models that are not designed for complex diseases like asthma. OBJECTIVE: We aimed to find genetic effects that partly explain different asthma endotypes. METHODS: We used recent powerful and robust statistical models of context-specific genetic effects in complex traits. We identified genetic subtypes by clustering clinical asthma features in a case-control cohort, GALA II. We replicated the genetic endotypes in the UK Biobank with gene-context interaction tests. RESULTS: Asthma-associated single nucleotide polymorphisms, polygenic scores, and genome-wide heritability revealed subtype-specific genetic endotypes correlated with type 2 inflammation, allergy, and neuroticism. We validated the type 2 associations with molecular data including nasal RNA sequencing. In the UK Biobank, we replicated these endotypes and found they interact with several polygenic scores and drug-relevant genes. CONCLUSION: Our results show how context-specific genetic effects can unravel biomedically meaningful endotypes of complex disease and suggest novel precision treatment strategies.
DOI: 10.1016/j.jaci.2026.03.017
Authors: Andy Dahl, Satria Sajuthi, Nadav Rappaport, Joshua Galanter, Chris Gignoux, Esteban Burchard, Max Seibold, Noah Zaitlen
Institutions: University of Chicago, National Jewish Health, Ben-Gurion University of the Negev, Genentech, University of Colorado Anschutz, University of California, San Francisco, University of California, Los Angeles
Language: English
Subfield: Physiology
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $4,900
Awards: Characterizing individual- and subtype-specific risk factors and treatments in asthma, Improved methods for inference of genotype-specific response to environmental toxins, Genomic Approaches to Population Health in Multi-Ethnic Hospital Systems, Leveraging functional data to predict disease risk in multi-ethnic populations, Identifying and quantifying genetic effects on neurodevelopmental trajectories in adolescents, SINGLE-CELL MULTI-OMIC APPROACHES TO MECHANISTICALLY CHARACTERIZE PSYCHIATRIC DISORDER RISK LOCI IN THE HUMAN BRAIN, Novel statistical genetics methods to unravel polygenic interactions in complex traits, Leveraging genetic variation to dissect gene regulatory networks of reprogramming to pluripotency
OpenAlex ID: W7148917031
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