| Title: | Genomic insights for personalised care in lung cancer and smoking cessation: motivating at-risk individuals toward evidence-based health practices |
| Journal: | EBioMedicine |
| Published: | 8 Nov 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39520911/ |
| DOI: | https://doi.org/10.1016/j.ebiom.2024.105441 |
Publication 14163
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Abstract
BACKGROUND: Lung cancer and tobacco use pose significant global health challenges, necessitating a comprehensive translational roadmap for improved prevention strategies such as cancer screening and tobacco treatment, which are currently under-utilised. Polygenic risk scores (PRSs) may further motivate health behaviour change in primary care for lung cancer in diverse populations. In this work, we introduce the GREAT care paradigm, which integrates PRSs within comprehensive patient risk profiles to motivate positive health behaviour changes.</p>
METHODS: We developed PRSs using large-scale multi-ancestry genome-wide association studies and standardised PRS distributions across all ancestries. We validated our PRSs in 561,776 individuals of diverse ancestry from the GISC Trial, UK Biobank (UKBB), and All of Us Research Program (AoU).</p>
FINDINGS: Significant odds ratios (ORs) for lung cancer and difficulty quitting smoking were observed in both UKBB and AoU. For lung cancer, the ORs for individuals in the highest risk group (top 20% versus bottom 20%) were 1.85 (95% CI: 1.58-2.18) in UKBB and 2.39 (95% CI: 1.93-2.97) in AoU. For difficulty quitting smoking, the ORs (top 33% versus bottom 33%) were 1.36 (95% CI: 1.32-1.41) in UKBB and 1.32 (95% CI: 1.28-1.36) in AoU.</p>
INTERPRETATION: Our PRS-based intervention model leverages large-scale genetic data for robust risk assessment across populations, which will be evaluated in two cluster-randomised clinical trials. This approach integrates genomic insights into primary care, promising improved outcomes in cancer prevention and tobacco treatment.</p>
FUNDING: National Institutes of Health, NIH Intramural Research Program, National Science Foundation.</p>
13 Keywords
- Evidence-Based Practice
- Female
- Genetic Predisposition to Disease
- Genome-Wide Association Study
- Genomics
- Humans
- Lung Neoplasms
- Male
- Middle Aged
- Multifactorial Inheritance
- Precision Medicine
- Risk Factors
- Smoking Cessation
19 Authors
- Tony Chen
- Giang Pham
- Louis Fox
- Nina Adler
- Xiaoyu Wang
- Jingning Zhang
- Jinyoung Byun
- Younghun Han
- Gretchen R.B. Saunders
- Dajiang Liu
- Michael J. Bray
- Alex T. Ramsey
- James McKay
- Laura J. Bierut
- Christopher I. Amos
- Rayjean J. Hung
- Xihong Lin
- Haoyu Zhang
- Li-Shiun Chen
1 Application
| Application ID | Title |
|---|---|
| 52008 | Development of statistical methods to discover novel genetic associations, explain underlying biological mechanisms, and develop risk prediction models across varied complex diseases. |
Enabling scientific discoveries that improve human health