Biomedical and environmental sciences : BES · 2026
Joint Effects of Metabolic Syndrome and Polygenic Risk Score on Lung Cancer Incidence and Mortality: A Prospective Cohort Study.
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Bu Qing Yin, Wang Qian, Zhang Gang, Wang Yi Fan, Sun Long Hu, Liang Shuang, Yang Fan, He Zha Zheng, Yi Hong Gang, Pu Zhe Ning, Dai Jun Cheng
Аннотация
OBJECTIVE: To investigate the effects of metabolic syndrome (MetS) and its interaction with genetic factors on lung cancer incidence and mortality.
METHODS: The cohort analysis included 355,344 participants from the UK Biobank. MetS was defined using the modified National Cholesterol Education Program Adult Treatment Panel III criteria. Cox proportional hazards models were used to evaluate the associations between MetS-related variables, their interactions with genetic factors, and lung cancer outcomes (incidence and mortality).
RESULTS: MetS was associated with increased risks of lung cancer incidence (hazard ratio [ HR]: 1.31, 95% confidence interval [ CI]: 1.22-1.42) and mortality ( HR: 1.35, 95% CI: 1.24-1.48). Risk increased proportionally to the number of metabolic abnormalities. Increased waist circumference, reduced high-density lipoprotein cholesterol, and elevated glycated hemoglobin were independently associated with both outcomes. Participants with both high genetic risk and MetS had the highest risk of lung cancer incidence ( HR: 2.07, 95% CI: 1.82-2.35) and mortality ( HR: 2.12, 95% CI: 1.83-2.45) compared with those with low genetic risk and no MetS. A significant positive additive interaction was observed between waist circumference and genetic risk.
CONCLUSION: Metabolic abnormalities are important modifiable risk factors for lung cancer. Integrating metabolic health assessment with genetic risk profiling may improve risk stratification and targeted prevention of lung cancer.
METHODS: The cohort analysis included 355,344 participants from the UK Biobank. MetS was defined using the modified National Cholesterol Education Program Adult Treatment Panel III criteria. Cox proportional hazards models were used to evaluate the associations between MetS-related variables, their interactions with genetic factors, and lung cancer outcomes (incidence and mortality).
RESULTS: MetS was associated with increased risks of lung cancer incidence (hazard ratio [ HR]: 1.31, 95% confidence interval [ CI]: 1.22-1.42) and mortality ( HR: 1.35, 95% CI: 1.24-1.48). Risk increased proportionally to the number of metabolic abnormalities. Increased waist circumference, reduced high-density lipoprotein cholesterol, and elevated glycated hemoglobin were independently associated with both outcomes. Participants with both high genetic risk and MetS had the highest risk of lung cancer incidence ( HR: 2.07, 95% CI: 1.82-2.35) and mortality ( HR: 2.12, 95% CI: 1.83-2.45) compared with those with low genetic risk and no MetS. A significant positive additive interaction was observed between waist circumference and genetic risk.
CONCLUSION: Metabolic abnormalities are important modifiable risk factors for lung cancer. Integrating metabolic health assessment with genetic risk profiling may improve risk stratification and targeted prevention of lung cancer.