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. 2023 Jan 19;26(3):106018.
doi: 10.1016/j.isci.2023.106018. eCollection 2023 Mar 17.

Association between biological aging and lung cancer risk: Cohort study and Mendelian randomization analysis

Zhimin Ma  1   2 , Chen Zhu  2   3   4 , Hui Wang  2 , Mengmeng Ji  1   2 , Yanqian Huang  2 , Xiaoxia Wei  2 , Jing Zhang  2 , Yuzhuo Wang  2   5 , Rong Yin  5 , Juncheng Dai  2   6 , Lin Xu  5 , Hongxia Ma  2   6   7 , Zhibin Hu  2   6 , Guangfu Jin  1   2   6 , Meng Zhu  2   6 , Hongbing Shen  1   2   3   7
Affiliations

Association between biological aging and lung cancer risk: Cohort study and Mendelian randomization analysis

Zhimin Ma et al. iScience. .

Abstract

Chronological age only represents the passage of time, whereas biological age reflects the physiology states and the susceptibility to morbidity and mortality. The association between biological age and lung cancer risk remains controversial. Hence, we conducted a prospective analysis in the UK Biobank study and two-sample Mendelian randomization analysis to investigate this association. Biological aging was evaluated by PhenoAgeAccel, derived from routine clinical biomarkers. Independent of chronological age, PhenoAgeAccel was positively associated with the risk of overall and histological subtypes of lung cancer. There was a joint effect of PhenoAgeAccel and genetics in lung cancer incidence. In Mendelian randomization analysis, the genetically predicted PhenoAgeAccel was associated with the increased risk of overall lung cancer, small cell, and squamous cell carcinoma. Our findings suggest PhenoAgeAccel is an independent risk factor for lung cancer, which could be incorporated with polygenic risk score to identify high-risk individuals for lung cancer.

Keywords: Cancer; Health sciences; Risk stratification.

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Conflict of interest statement

The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Distribution of PhenoAgeAccel and association between PhenoAgeAccel and lung cancer (A) The distribution of PhenoAgeAccel across non-lung cancer and lung cancer; (B) Individuals were split equally into ten groups based on PhenoAgeAccel, and the HR was estimated for each group in comparison with the first group (P trend<0.001); (C) (D)The standardized cumulative incidence of rate among participants with biologically older and younger, as well as individuals with low accelerated aging (the bottom quintile of PhenoAgeAccel), intermediate accelerated aging (quintiles 2–4), and high accelerated aging (the top quintile). Abbreviation: PhenoAgeAccel, Phenotypic age acceleration.
Figure 2
Figure 2
PhenoAgeAccel could provide additional information for lung cancer risk assessment (A) Absolute risk estimates of lung cancer by different PhenoAgeAccel; (B) Receiver operating characteristic (ROC) curve and corresponding area under the ROC curve (AUC). Abbreviation: PhenoAgeAccel, Phenotypic age acceleration; ROC, receiver operating characteristic.
Figure 3
Figure 3
Hazard risk and rate advancement period of incident lung cancer according to biological aging and genetic categories (A) The HR for lung cancer across each group was estimated via Cox regression model after adjusting for chronological age, sex, ethnicity, center, education, Townsend deprivation index, BMI, smoking status, family history of lung cancer, history of asthma, history of allergy and/or eczema, history of emphysema and/or bronchitis, the top 10 principal components of ancestry, and genotyping batch. (B) The dashed line is the RAP, assuming a constant disease rate during the follow-up period. The y axis is on the natural log scale. Compared with individuals at biologically younger and low genetic risk group, the RAP of lung cancer occurrence in the other groups. Abbreviation: PhenoAgeAccel, Phenotypic age acceleration; BMI, body mass index; RAP, rate advancement period; ROC, receiver operating characteristic.
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References

    1. Sung H., Ferlay J., Siegel R.L., Laversanne M., Soerjomataram I., Jemal A., Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA. Cancer J. Clin. 2021;71:209–249. doi: 10.3322/caac.21660. - DOI - PubMed
    1. Cho S.J., Stout-Delgado H.W. Aging and lung disease. Annu. Rev. Physiol. 2020;82:433–459. doi: 10.1146/annurev-physiol-021119-034610. - DOI - PMC - PubMed
    1. Kresovich J.K., Xu Z., O'Brien K.M., Weinberg C.R., Sandler D.P., Taylor J.A. Methylation-based biological age and breast cancer risk. J. Natl. Cancer Inst. 2019;111:1051–1058. doi: 10.1093/jnci/djz020. - DOI - PMC - PubMed
    1. Ahadi S., Zhou W., Schüssler-Fiorenza Rose S.M., Sailani M.R., Contrepois K., Avina M., Ashland M., Brunet A., Snyder M. Personal aging markers and ageotypes revealed by deep longitudinal profiling. Nat. Med. 2020;26:83–90. doi: 10.1038/s41591-019-0719-5. - DOI - PMC - PubMed
    1. Levine M.E., Lu A.T., Quach A., Chen B.H., Assimes T.L., Bandinelli S., Hou L., Baccarelli A.A., Stewart J.D., Li Y., et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging. 2018;10:573–591. doi: 10.18632/aging.101414. - DOI - PMC - PubMed

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