Large-scale genomic epidemiology approaches to study the natural history of lung function and COPD
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AI plain-English summaryA single DNA test could one day predict a person’s risk of developing chronic obstructive pulmonary disease (COPD) decades before symptoms appear. COPD is a progressive lung condition that makes breathing difficult, yet doctors cannot reliably predict who will get it or how fast it will worsen. Known risk factors like smoking explain only part of the picture. This project aims to fill that gap by using massive genetic datasets—including UK Biobank and international consortia—to identify the specific DNA variants that control lung function and COPD susceptibility. The team will combine genome-wide scans, statistical methods, and electronic medical records to pinpoint causal variants and build polygenic risk scores. If successful, these risk scores could allow clinicians to identify high-risk individuals early, target prevention efforts, and tailor treatments based on a person’s genetic profile. The research may also reveal why COPD progresses differently in different patients, enabling more precise clinical trials. While the work is fundamentally about understanding the genetic architecture of lung function, its immediate practical payoff would be better prediction tools—not a cure, but a way to intervene sooner.
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