Multi-ancestry genome-wide association study reveals novel genetic signals for lung function decline

  1. Bonnie K. Patchen
  2. Jingwen Zhang
  3. Nathan Gaddis
  4. Traci M. Bartz
  5. Jing Chen
  6. Catherine Debban
  7. Hampton Leonard
  8. Ngoc Quynh Nguyen
  9. Jungkun Seo
  10. Courtney Tern
  11. Richard Allen
  12. Dawn L. DeMeo
  13. Myriam Fornage
  14. Carl Melbourne
  15. Melyssa Minto
  16. Matthew Moll
  17. George O’Connor
  18. Tess Pottinger
  19. Bruce M. Psaty
  20. Stephen S. Rich
  21. Jerome I. Rotter
  22. Edwin K. Silverman
  23. Jeran Stratford
  24. R. Graham Barr
  25. Michael H. Cho
  26. Sina A. Gharib
  27. Ani Manichaikul
  28. Kari North
  29. Elizabeth C. Oelsner
  30. Eleanor M. Simonsick
  31. Martin D. Tobin
  32. Bing Yu
  33. Seung Hoan Choi
  34. Josee Dupuis
  35. Patricia A. Cassano
  36. Dana B. Hancock
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Abstract

Rationale

Accelerated decline in lung function contributes to the development of chronic respiratory disease. Despite evidence for a genetic component, few genetic associations with lung function decline have been identified.

Objectives

To evaluate genome-wide associations and putative downstream functionality of genetic variants with lung function decline in diverse general population cohorts.

Methods

We conducted genome-wide association study (GWAS) analyses of decline in the forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), and their ratio (FEV1/FVC) in participants across six cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. Genotypes were imputed to TOPMed (CHARGE cohorts) or Haplotype Reference Consortium (HRC) (UK Biobank) reference panels, and GWAS analyses used generalized estimating equation models with robust standard error. Models were stratified by cohort, ancestry, and sex, and adjusted for important lung function confounders and genotype principal components. Results were combined in cross-ancestry and ancestry-specific meta-analyses. Selected top variants were tested for replication in two independent COPD-enriched cohorts.

Measurements and Main Results

Our discovery analyses included 52,056 self-reported White (N=44,988), Black (N=5,788), Hispanic (N=550), and Chinese American (N=730) participants with a mean of 2.3 spirometry measurements and 8.6 years of follow-up. Functional mapping of GWAS meta-analysis results identified 361 distinct genome-wide significant (p<5E-08) variants in one or more of the FEV1, FVC, and FEV1/FVC decline phenotypes, which overlapped with previously reported genetic signals for several related pulmonary traits. Of these, 8 variants, or 20.5% of the variant set available for replication testing, were nominally associated (p<0.05) with at least one decline phenotype in COPD-enriched cohorts (White [N=4,778] and Black [N=1,118]). Using the GWAS results, gene-level analysis implicated 38 genes, including eight (XIRP2,GRIN2D,SATB1,MARCHF4,SIPA1L2,ANO5,H2BC10, andFAF2) with consistent associations across ancestries or decline phenotypes. Annotation class analysis revealed significant enrichment of several regulatory processes for corticosteroid biosynthesis and metabolism. Drug repurposing analysis identified 43 approved compounds targeting eight of the implicated 38 genes.

Conclusions

Our multi-ancestry GWAS meta-analyses identified numerous genetic loci associated with lung function decline. These findings contribute knowledge to the genetic architecture of lung function decline, provide evidence for a role of endogenous corticosteroids in the etiology of lung function decline, and identify drug targets that merit further study for potential repurposing to slow lung function decline and treat lung disease.

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