Population attributable fraction of lung cancer due to genetic variants, modifiable risk factors, and their interactions: a nationwide prospective cohort study

被引:12
|
作者
Wang, Xiaojie [1 ]
Qian, Zhengmin [2 ]
Zhang, Zilong [1 ]
Cai, Miao [1 ]
Chen, Lan [1 ]
Wu, Yinglin [1 ]
Li, Haitao [3 ]
Liu, Echu [4 ]
McMillin, Stephen Edward [5 ]
Lin, Hualiang [1 ,6 ]
机构
[1] Sun Yat Sen Univ, Sch Publ Hlth, Dept Epidemiol, Guangzhou, Peoples R China
[2] St Louis Univ, Coll Publ Hlth & Social Justice, Dept Epidemiol & Biostat, St Louis, MI USA
[3] Shenzhen Univ, Dept Social Med & Hlth Serv Management, Gen Hosp, Shenzhen, Peoples R China
[4] St Louis Univ, Coll Publ Hlth & Social Justice, Dept Hlth Management & Policy, St Louis, MI USA
[5] St Louis Univ, Coll Publ Hlth & Social Justice, Sch Social Work, St Louis, MI USA
[6] 74 Zhongshan 2nd Rd, Guangzhou 510030, Peoples R China
基金
中国国家自然科学基金;
关键词
Lung cancer; Genetic susceptibility; Additive interaction; Population attributable fractions; Modifiable risk factors; PARTICULATE MATTER; UK; ASSOCIATION; EXPOSURE; SMOKING; SUSCEPTIBILITY; POLYMORPHISMS; MORTALITY; SAMPLE; DIET;
D O I
10.1016/j.chemosphere.2022.134773
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background: Genetic variants and modifiable risk factors (including environmental exposure and lifestyle) greatly contribute to the development of lung cancer. The population attributable fraction (PAF) of these risk factors, especially their interactive effects, has not been well quantified. Methods: A total of 398,577 participants were included in this analysis. There were 2504 incident lung cancer cases identified over an average 10.4-year follow-up. We applied Cox proportional hazards models to examine the associations between risk factors and incident lung cancer. We further developed a polygenic risk score and evaluated whether environmental factors modified the effect of genetic risk on incident lung cancer. Furthermore, we calculated the PAF for each risk factor, as well as their gene-environment additive interaction, and then combined them to create a weighted PAF that takes into consideration participants with overlapping risk factors. Results: Our analysis showed that smoking was the leading risk factor for lung cancer with a PAF of 63.73%. We observed additive interactions between smoking, PM2.5, NOx, and genetic risk, with PAFs of 17.85% (smoking high genetic risk interaction), 10.79% (smoking-intermediate genetic risk interaction), 5.30% (NOx-high genetic risk interaction), 6.55% (PM2.5-high genetic risk interaction), and 4.99% (PM2.5-intermediate genetic riskinteraction). We estimated that 73.46% of lung cancer cases could be attributable to potentially modifiable risk factors after adjusting for the correlation between them. Conclusion: High genetic risk and several modifiable factors may increase the risk of incident lung cancer. Participants with a high genetic risk may be more vulnerable to developing lung cancer if exposed to smoking and/ or high air pollution. Our findings provide evidence that the majority of incident lung cancer cases could be prevented by eliminating modifiable risk factors.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Population Attributable Fraction of Established Modifiable Risk Factors on Colorectal Cancer in Korea
    Cho, Sooyoung
    Shin, Aesun
    CANCER RESEARCH AND TREATMENT, 2021, 53 (02): : 480 - 486
  • [2] Population attributable fraction of modifiable risk factors for dementia in Chile
    Vergara, Rodrigo C. C.
    Zitko, Pedro
    Slachevsky, Andrea
    San Martin, Consuelo
    Delgado, Carolina
    ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING, 2022, 14 (01)
  • [3] The fraction of cancer attributable to modifiable risk factors in Turkey in 2018
    Tozduman, Busra
    Ergor, Gul
    INTERNATIONAL JOURNAL OF CANCER, 2024,
  • [4] Population attributable fraction of modifiable risk factors of severe maternal morbidity
    Freese, Kyle
    Bodnar, Lisa M.
    Brooks, Maria M.
    Himes, Katherine P.
    AMERICAN JOURNAL OF OBSTETRICS AND GYNECOLOGY, 2018, 218 (01) : S452 - S452
  • [5] Prevalence of hyperuricemia and the population attributable fraction of modifiable risk factors: Evidence from a general population cohort in China
    He, Huijing
    Guo, Pei
    He, Jiangshan
    Zhang, Jingbo
    Niu, Yujie
    Chen, Shuo
    Guo, Fenghua
    Liu, Feng
    Zhang, Rong
    Li, Qiang
    Ma, Shitao
    Zhang, Binbin
    Pan, Li
    Shan, Guangliang
    Zhang, Minying
    FRONTIERS IN PUBLIC HEALTH, 2022, 10
  • [6] Modifiable risk factors and incidence of gout: Estimation of population attributable fraction in the US
    Liu, Ke
    Yao, Yewen
    Chen, Weiwei
    Mao, Yingying
    Ye, Ding
    Wen, Chengping
    SEMINARS IN ARTHRITIS AND RHEUMATISM, 2022, 55
  • [7] Prevalence of modifiable risk factors of tuberculosis and their population attributable fraction in Iran: A cross-sectional study
    Sadeghi, Kamal
    Poorolajal, Jalal
    Doosti-Irani, Amin
    PLOS ONE, 2022, 17 (08):
  • [8] Population attributable fraction of dietary risk factors for cancer mortality with a focus on gastrointestinal cancers in a population based cohort study
    Isfahani, Marjan Moallemian
    Dalvand, Sahar
    Dehaghi, Nahid Raei
    Sharafkhah, Maryam
    Sepanlou, Sadaf G.
    Hashemian, Maryam
    Poustchi, Hossein
    Sadjadi, Alireza
    Roshandel, Gholamreza
    Khoshnia, Masoud
    Delavari, Alireza
    Rezaei, Negar
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [9] Population attributable fraction of total stroke associated with modifiable risk factors in the United States
    Lee, Mark
    Lakshminarayan, Kamakshi
    Sedaghat, Sanaz
    Sabayan, Behnam
    Chen, Lin Yee
    Johansen, Michelle C.
    Gottesman, Rebecca F.
    Heckbert, Susan R.
    Misialek, Jeffrey R.
    Szklo, Moyses
    Lutsey, Pamela L.
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2024, 193 (12) : 1712 - 1719
  • [10] Population Attributable Fractions of Modifiable Risk Factors for Nonsyndromic Orofacial Clefts: A Prospective Cohort Study From the Japan Environment and Children's Study
    Sato, Yukihiro
    Yoshioka, Eiji
    Saijo, Yasuaki
    Miyamoto, Toshinobu
    Sengoku, Kazuo
    Azuma, Hiroshi
    Tanahashi, Yusuke
    Ito, Yoshiya
    Kobayashi, Sumitaka
    Minatoya, Machiko
    Bamai, Yu Ait
    Yamazaki, Keiko
    Itoh, Sachiko
    Miyashita, Chihiro
    Araki, Atsuko
    Kishi, Reiko
    JOURNAL OF EPIDEMIOLOGY, 2021, 31 (04) : 272 - 279