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  5. Data from: Multi-ancestry genome-wide association study and meta-analysis of lung function decline

Data from: Multi-ancestry genome-wide association study and meta-analysis of lung function decline

File(s)
Patchen_GenomeWideAssociationStudy_README_2026.txt (2.57 KB)
Sumstats_ratio_crossancestry.txt.gz (164.7 MB)
Sumstats_ratio_EA.txt.gz (209.97 MB)
Sumstats_fev_AA.txt.gz (285.74 MB)
Sumstats_fev_EA.txt.gz (263.9 MB)
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Permanent Link(s)
https://hdl.handle.net/1813/127911
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Nutritional Sciences Publications, Manuscripts and Datasets
Author
Patchen, Bonnie
Jingwen Zhang
Dupuis, Josee
Cassano, Patricia A.
Hancock, Dana
Abstract

This item includes the summary statistics from the cross-ancestry and ancestry-specific meta-analyses for the manuscript "Multi-ancestry genome-wide association study and meta-analysis of lung function decline." Please see the full publication for additional details.

BACKGROUND: Despite evidence for a genetic component, few genetic associations with lung function decline have been identified. We aimed to evaluate genome-wide associations and putative downstream functionality of genetic variants for lung function decline. METHODS: We conducted genome-wide association study (GWAS) analyses of decline in FEV1, FVC, and FEV1/FVC in 52,056 White (N = 44,988), Black (N = 5,788), Hispanic (N = 550), and Chinese American (N = 730) participants across seven general population cohorts. GWAS analyses were stratified by cohort, ancestry, and sex. Results were combined in cross-ancestry and ancestry-specific meta-analyses. Significant variants available in two independent COPD-enriched cohorts were tested for replication. RESULTS: We identified 361 distinct genome-wide significant (p < 5E-08) variants for one or more of the FEV1, FVC, and FEV1/FVC decline phenotypes, which overlapped with previously reported genetic signals for pulmonary traits. Four variants, or 10.3% of variants available for replication testing, were nominally associated (p < 0.05) with at least one decline phenotype in COPD-enriched cohorts. Gene-level analysis of GWAS results implicated 38 genes, many with consistent associations across ancestries or decline phenotypes. Annotation class analysis revealed enrichment of regulatory processes for corticosteroid biosynthesis and metabolism. Drug repurposing analysis identified 43 approved compounds targeting eight implicated genes. CONCLUSIONS: Our 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 corticosteroids in the etiology of lung function decline, and identify drug targets meriting further study for potential repurposing to slow lung function decline and mitigate lung disease.

Description
Please cite as: Patchen, B.K., Zhang, J., Dupuis, J., Cassano, P.A., Hancock, D. (2026) Data from: Multi-ancestry genome-wide association study and meta-analysis of lung function decline. [data set] Cornell University Library eCommons Repository. https://hdl.handle.net/1813/127911.
Please also cite the published article if these data are used.
Sponsorship
This work was supported by NIH National Heart, Lung, and Blood Institute (NHLBI) award R01HL149352, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) award T32DK007158 and NIH award T32HL007427-43. The content is solely the responsibility of the authors and does not represent the official views of the NIH. Support for the individual cohorts contributing to this work are described in the footnotes section.
Date Issued
2026
Keywords
Chronic obstructive Pulmonary Disease
•
Genomics
•
Lung volume measurements
•
Spirometry
Related Publication(s)
Patchen, B.K., Zhang, J., Gaddis, N. et al. Multi-ancestry genome-wide association study and meta-analysis of lung function decline. Respir Res 27, 110 (2026). https://doi.org/10.1186/s12931-026-03565-x
Link(s) to Related Publication(s)
https://doi.org/10.1186/s12931-026-03565-x
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights URI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Type
dataset

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