Discovering metabolite quantitative trait loci in asthma using an isolated population

Randi K. Johnson, Tonya Brunetti, Kevin Quinn, Katrina Doenges, Monica Campbell, Christopher Arehart, Margaret A. Taub, Rasika A. Mathias, Nichole Reisdorph, Kathleen C. Barnes, Michelle Daya

Research output: Contribution to journalArticlepeer-review


Background: Integration of metabolomics with genetics may advance understanding of disease pathogenesis but has been underused in asthma genetic studies. Objective: We sought to discover new genetic effects in asthma and to characterize the molecular consequences of asthma genetic risk through integration with the metabolome in a homogeneous population. Methods: From fasting serum samples collected on 348 Tangier Island residents, we quantified 2612 compounds using untargeted metabolomics. Genotyping was performed using Illumina's MEGA array imputed to the TOPMed reference panel. To prioritize metabolites for genome-wide association analysis, we performed a metabolome-wide association study with asthma, selecting asthma-associated metabolites with heritability q value less than 0.01 for genome-wide association analysis. We also tested the association between all metabolites and 8451 candidate asthma single nucleotide polymorphisms previously associated with asthma in the UK Biobank. We followed up significant associations by characterizing shared genetic signal for metabolites and asthma using colocalization analysis. For detailed Methods, please see this article's Online Repository at Results: A total of 60 metabolites were associated with asthma (P <.01), including 40 heritable metabolites tested in genome-wide association analysis. We observed a strong association peak for the endocannabinoid linoleoyl ethanolamide on chromosome 6 in VNN1 (P < 2.7 × 10−9). We found strong evidence (colocalization posterior probability >75%) for a shared causal variant between 3 metabolites and asthma, including the polyamine acisoga and variants in LPP, and derivative leukotriene B4 and intergenic variants in chr10p14. Conclusions: We identified novel metabolite quantitative trait loci with asthma associations. Identification and characterization of these genetically driven metabolites may provide insight into the functional consequences of genetic risk factors for asthma.

Original languageEnglish (US)
Pages (from-to)1807-1811.e16
JournalJournal of Allergy and Clinical Immunology
Issue number5
StatePublished - May 2022


  • Metabolomics
  • asthma
  • genome-wide association
  • heritability
  • quantitative trait

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology


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