- Title
- Genetic association and causal inference converge on hyperglycaemia as a modifiable factor to improve lung function
- Creator
- Reay, William R; El Shair, Sahar I El; Cairns, Murray J.; Geaghan, Michael P; Riveros, Carlos; Holliday, Elizabeth G; McEvoy, Mark A.; Hancock, Stephen; Peel, Roseanne; Scott, Rodney J; Attia, John R.
- Relation
- NHMRC.1147644 http://purl.org/au-research/grants/nhmrc/1147644
- Relation
- eLife Vol. 10, no. e63115
- Publisher Link
- http://dx.doi.org/10.7554/eLife.63115
- Publisher
- eLife Sciences Publications Ltd
- Resource Type
- journal article
- Date
- 2021
- Description
- Measures of lung function are heritable, and thus, we sought to utilise genetics to propose drug-repurposing candidates that could improve respiratory outcomes. Lung function measures were found to be genetically correlated with seven druggable biochemical traits, with further evidence of a causal relationship between increased fasting glucose and diminished lung function. Moreover, we developed polygenic scores for lung function specifically within pathways with known drug targets and investigated their relationship with pulmonary phenotypes and gene expression in independent cohorts to prioritise individuals who may benefit from particular drug-repurposing opportunities. A transcriptome-wide association study (TWAS) of lung function was then performed which identified several drug–gene interactions with predicted lung function increasing modes of action. Drugs that regulate blood glucose were uncovered through both polygenic scoring and TWAS methodologies. In summary, we provided genetic justification for a number of novel drug-repurposing opportunities that could improve lung function.
- Subject
- research article; genetics and genomics; GWAS; causal inference; TWAS; drug repurposing; lung function; polygenic scoring; SDG 3; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1465321
- Identifier
- uon:47250
- Identifier
- ISSN:2050-084X
- Rights
- © 2021, Reay et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
- Language
- eng
- Full Text
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