Genome-wide association study of preserved ratio impaired spirometry (PRISm)

Daniel H. Higbee, Alvin Lirio, Fergus Hamilton, Raquel Granell, Annah B. Wyss, Stephanie J. London, Traci M. Bartz, Sina A. Gharib, Michael H. Cho, Emily Wan, Edwin Silverman, James D. Crapo, Jesus V.T. Lominchar, Torben Hansen, Niels Grarup, Thomas Dantoft, Line Kårhus, Allan Linneberg, George T. O’Connor, Josée DupuisHanfie Xu, Maaike M. De Vries, Xiaowei Hu, Stephen S. Rich, R. Graham Barr, Ani Manichaikul, Sara R.A. Wijnant, Guy G. Brusselle, Lies Lahousse, Xuan Li, Ana I. Hernández Cordero, Maen Obeidat, Don D. Sin, Sarah E. Harris, Paul Redmond, Adele M. Taylor, Simon R. Cox, Alexander T. Williams, Nick Shrine, Catherine John, Anna L. Guyatt, Ian P. Hall, George Davey Smith, Martin D. Tobin, James W. Dodd*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

1 Citation (Scopus)


Background Preserved ratio impaired spirometry (PRISm) is defined as a forced expiratory volume in 1 s (FEV1) <80% predicted and FEV1/forced vital capacity ≤0.70. PRISm is associated with respiratory symptoms and comorbidities. Our objective was to discover novel genetic signals for PRISm and see if they provide insight into the pathogenesis of PRISm and associated comorbidities. Methods We undertook a genome-wide association study (GWAS) of PRISm in UK Biobank participants (Stage 1), and selected single nucleotide polymorphisms (SNPs) reaching genome-wide significance for replication in 13 cohorts (Stage 2). A combined meta-analysis of Stage 1 and Stage 2 was done to determine top SNPs. We used cross-trait linkage disequilibrium score regression to estimate genome-wide genetic correlation between PRISm and pulmonary and extrapulmonary traits. Phenome-wide association studies of top SNPs were performed. Results 22 signals reached significance in the joint meta-analysis, including four signals novel for lung function. A strong genome-wide genetic correlation (rg) between PRISm and spirometric COPD (rg=0.62, p<0.001) was observed, and genetic correlation with type 2 diabetes (rg=0.12, p=0.007). Phenome-wide association studies showed that 18 of 22 signals were associated with diabetic traits and seven with blood pressure traits. Conclusion This is the first GWAS to successfully identify SNPs associated with PRISm. Four of the signals, rs7652391 (nearest gene MECOM), rs9431040 (HLX), rs62018863 (TMEM114) and rs185937162 (HLA-B), have not been described in association with lung function before, demonstrating the utility of using different lung function phenotypes in GWAS. Genetic factors associated with PRISm are strongly correlated with risk of both other lung diseases and extrapulmonary comorbidity.

Original languageEnglish
Article number2300337
JournalEuropean Respiratory Journal
Issue number1
Publication statusPublished - 10 Jan 2024

Bibliographical note

Publisher Copyright:
©ERS 2024.

Structured keywords

  • Bristol Population Health Science Institute


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