Revealing polygenic pleiotropy using genetic risk scores for asthma

Matthew Dapas, Yu Lin Lee, William Wentworth-Sheilds, Hae Kyung Im, Carole Ober*, Nathan Schoettler*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In this study we examined how genetic risk for asthma associates with different features of the disease and with other medical conditions and traits. Using summary statistics from two multi-ancestry genome-wide association studies of asthma, we modeled polygenic risk scores (PRSs) and validated their predictive performance in the UK Biobank. We then performed phenome-wide association studies of the asthma PRSs with 371 heritable traits in the UK Biobank. We identified 228 total significant associations across a variety of organ systems, including associations that varied by PRS model, sex, age of asthma onset, ancestry, and human leukocyte antigen region alleles. Our results highlight pervasive pleiotropy between asthma and numerous other traits and conditions and elucidate pathways that contribute to asthma and its comorbidities.

Original languageEnglish (US)
Article number100233
JournalHuman Genetics and Genomics Advances
Volume4
Issue number4
DOIs
StatePublished - Oct 12 2023

Keywords

  • GBMI
  • Global Biobank Meta-analysis Initative
  • HLA
  • PRS
  • PheWAS
  • UK Biobank
  • UKB
  • asthma
  • phenome-wide association study
  • pleiotropy
  • polygenic risk score

ASJC Scopus subject areas

  • Genetics(clinical)
  • Molecular Medicine

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