TY - JOUR
T1 - Genomic insights for personalised care in lung cancer and smoking cessation
T2 - motivating at-risk individuals toward evidence-based health practices
AU - Chen, Tony
AU - Pham, Giang
AU - Fox, Louis
AU - Adler, Nina
AU - Wang, Xiaoyu
AU - Zhang, Jingning
AU - Byun, Jinyoung
AU - Han, Younghun
AU - Saunders, Gretchen R.B.
AU - Liu, Dajiang
AU - Bray, Michael J.
AU - Ramsey, Alex T.
AU - McKay, James
AU - Bierut, Laura J.
AU - Amos, Christopher I.
AU - Hung, Rayjean J.
AU - Lin, Xihong
AU - Zhang, Haoyu
AU - Chen, Li Shiun
N1 - Publisher Copyright:
© 2024
PY - 2024/12
Y1 - 2024/12
N2 - 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. 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). 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. 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. Funding: National Institutes of Health, NIH Intramural Research Program, National Science Foundation.
AB - 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. 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). 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. 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. Funding: National Institutes of Health, NIH Intramural Research Program, National Science Foundation.
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U2 - 10.1016/j.ebiom.2024.105441
DO - 10.1016/j.ebiom.2024.105441
M3 - Article
C2 - 39520911
AN - SCOPUS:85208388937
SN - 2352-3964
VL - 110
JO - EBioMedicine
JF - EBioMedicine
M1 - 105441
ER -