Genetic Associations and Architecture of Asthma-COPD Overlap

Catherine John, Anna L. Guyatt, Nick Shrine, Richard Packer, Thorunn A. Olafsdottir, Jiangyuan Liu, Lystra P. Hayden, Su H. Chu, Jukka T. Koskela, Jian'an Luan, Xingnan Li, Natalie Terzikhan, Hanfei Xu, Traci M. Bartz, Hans Petersen, Shuguang Leng, Steven A. Belinsky, Aivaras Cepelis, Ana I. Hernández Cordero, Ma'en ObeidatGudmar Thorleifsson, Deborah A. Meyers, Eugene R. Bleecker, Lori C. Sakoda, Carlos Iribarren, Yohannes Tesfaigzi, Sina A. Gharib, Josée Dupuis, Guy Brusselle, Lies Lahousse, Victor E. Ortega, Ingileif Jonsdottir, Don D. Sin, Yohan Bossé, Maarten van den Berge, David Nickle, Jennifer K. Quint, Ian Sayers, Ian P. Hall, Claudia Langenberg, Samuli Ripatti, Tarja Laitinen, Ann C. Wu, Jessica Lasky-Su, Per Bakke, Amund Gulsvik, Craig P. Hersh, Caroline Hayward, Arnulf Langhammer, Ben Brumpton, Kari Stefansson, Michael H. Cho, Louise V. Wain, Martin D. Tobin

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Background: Some people have characteristics of both asthma and COPD (asthma-COPD overlap), and evidence suggests they experience worse outcomes than those with either condition alone. Research Question: What is the genetic architecture of asthma-COPD overlap, and do the determinants of risk for asthma-COPD overlap differ from those for COPD or asthma? Study Design and Methods: We conducted a genome-wide association study in 8,068 asthma-COPD overlap case subjects and 40,360 control subjects without asthma or COPD of European ancestry in UK Biobank (stage 1). We followed up promising signals (P < 5 × 10–6) that remained associated in analyses comparing (1) asthma-COPD overlap vs asthma-only control subjects, and (2) asthma-COPD overlap vs COPD-only control subjects. These variants were analyzed in 12 independent cohorts (stage 2). Results: We selected 31 independent variants for further investigation in stage 2, and discovered eight novel signals (P < 5 × 10–8) for asthma-COPD overlap (meta-analysis of stage 1 and 2 studies). These signals suggest a spectrum of shared genetic influences, some predominantly influencing asthma (FAM105A, GLB1, PHB, TSLP), others predominantly influencing fixed airflow obstruction (IL17RD, C5orf56, HLA-DQB1). One intergenic signal on chromosome 5 had not been previously associated with asthma, COPD, or lung function. Subgroup analyses suggested that associations at these eight signals were not driven by smoking or age at asthma diagnosis, and in phenome-wide scans, eosinophil counts, atopy, and asthma traits were prominent. Interpretation: We identified eight signals for asthma-COPD overlap, which may represent loci that predispose to type 2 inflammation, and serious long-term consequences of asthma.

Original languageEnglish (US)
Pages (from-to)1155-1166
Number of pages12
Issue number5
StatePublished - May 2022


  • COPD
  • asthma
  • epidemiology
  • genome-wide association study
  • spirometry

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine
  • Cardiology and Cardiovascular Medicine


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