Completed Lungs & Breathing Genetics & Molecular Biology

Large-scale genomic epidemiology approaches to study the natural history of lung function and COPD

In plain English

AI plain-English summary

A 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.

View original technical description
Whilst risk factors for COPD are known, the determinants of lung function, COPD susceptibility and progression of COPD are incompletely understood. More effective approaches to prevention and treatment are urgently needed. We discovered genomic variants at many independent loci associated with lung function and risk of COPD. We and others have developed genomic epidemiology resources of unprecedented size utilising genome-wide genotyping arrays. Combined with genome-wide imputation, new statistical genetic approaches and epidemiological studies with measured lung function and electronic medical records we will advance understanding of the associations known to date and generate novel discoveries. We will fine-map loci to inform functional studies and study pleiotropic effects of associated variants. Using risk scores of variants showing genome-wide association and also genome-wide polygenic risk scores, we will assess the potential for improved prediction of COPD. We will develop methods to make more complete use of electronic medical record data and apply these in UK Biobank to boost the power to study disease relevant phenotypes. We will harness UK Biobank and large consortia to facilitate subgroup analyses at scale to generate novel insights into clinical heterogeneity in the natural history of lung function, COPD susceptibility and progression of COPD.

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Researchers

Martin Tobin (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Discovery of genome-wide SNP associations for lung function
Applying a multidisciplinary approach to defining molecular pathways in lung function impairment
A program of research in respiratory and cardiovascular genetic epidemiology
Genetic variation, disease prediction and causation
Charactersisation of mechanisms of polygenic susceptibility in lung cancer

Original classification

Investigator Award in Science

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