Zhe Yin; Yingnan Song; Junhui Zhang; Qiaoyun Dai; Xinyuan Zhang; Xueying Yang; Na Nie; Cuixia Chen; Zongfu Cao; Xu Ma; Zhe Yin; Yingnan Song; Junhui Zhang; Qiaoyun Dai; Xinyuan Zhang; Xueying Yang; Na Nie; Cuixia Chen; Zongfu Cao; Xu Ma

doi:10.46234/ccdcw2024.240

[1]

Hou YJ, Dan XL, Babbar M, Wei Y, Hasselbalch SG, Croteau DL, et al. Ageing as a risk factor for neurodegenerative disease. Nat Rev Neurol 2019;15(10):565 − 81. https://doi.org/10.1038/s41582-019-0244-7.

[2]

Popa-Wagner A, Petcu EB, Capitanescu B, Hermann DM, Radu E, Gresita A. Ageing as a risk factor for cerebral ischemia: Underlying mechanisms and therapy in animal models and in the clinic. Mech Ageing Dev 2020;190:111312. https://doi.org/10.1016/j.mad.2020.111312.

[3]

Smetana Jr K, Lacina L, Szabo P, Dvořánková B, Brož P, Šedo A. Ageing as an important risk factor for cancer. Anticancer Res 2016;36(10):5009 − 17. https://doi.org/10.21873/anticanres.11069.

[4]

Gloor AD, Berry GJ, Goronzy JJ, Weyand CM. Age as a risk factor in vasculitis. Semin Immunopathol 2022;44:281 − 301. https://doi.org/10.1007/s00281-022-00911-1.

[5]

Nie C, Li Y, Li R, Yan YZ, Zhang DT, Li T, et al. Distinct biological ages of organs and systems identified from a multi-omics study. Cell Rep 2022;38(10):110459. https://doi.org/10.1016/j.celrep.2022.110459.

[6]

Putin E, Mamoshina P, Aliper A, Korzinkin M, Moskalev A, Kolosov A, et al. Deep biomarkers of human aging: Application of deep neural networks to biomarker development. Aging (Albany NY) 2016;8(5):1021 − 33. https://doi.org/10.18632/aging.100968.

[7]

Zhong X, Lu YX, Gao Q, Nyunt SZ, Fulop T, Monterola CP, et al. Estimating biological age in the Singapore longitudinal aging study. J Gerontol A Biol Sci Med Sci 2020;75(10):1913 − 20. https://doi.org/10.1093/gerona/glz146.

[8]

An S, Ahn C, Moon S, Sim EJ, Park SK. Individualized biological age as a predictor of disease: Korean Genome and Epidemiology Study (KoGES) Cohort. J Pers Med 2022;12(3):505. https://doi.org/10.3390/jpm12030505.

[9]

Mamoshina P, Kochetov K, Putin E, Cortese F, Aliper A, Lee WS, et al. Population Specific Biomarkers of Human Aging: A Big Data Study Using South Korean, Canadian, and Eastern European Patient Populations. J Gerontol A Biol Sci Med Sci. 2018;73(11):1482−1490. http://dx.doi.org/10.1093/gerona/gly005.

[10]

Zhavoronkov A, Li R, Ma CDC, Mamoshina P. Deep biomarkers of aging and longevity: from research to applications. Aging (Albany NY) 2019;11(22):10771 − 80. https://doi.org/10.18632/aging.102475.

[11]

Manoj K, Senthamarai Kannan K. Comparison of methods for detecting outliers. Int J Sci Eng Res 2013;4(9):709-14. https://www.ijser.org/researchpaper/Comparison-of-methods-for-detecting-outliers.pdf.

[12]

Cao XQ, Yang GL, Jin XR, He L, Li XQ, Zheng ZT, et al. A machine learning-based aging measure among middle-aged and older Chinese adults: the China Health and Retirement Longitudinal Study. Front Med (Lausanne) 2021;8:698851. https://doi.org/10.3389/fmed.2021.698851.

[13]

Chen L, Zhang YQ, Yu CQ, Guo Y, Sun DJY, Pang YJ, et al. Modeling biological age using blood biomarkers and physical measurements in Chinese adults. eBioMedicine 2023;89:104458. https://doi.org/10.1016/j.ebiom.2023.104458.

[14]

Sebastiani P, Thyagarajan B, Sun FG, Honig LS, Schupf N, Cosentino S, et al. Age and sex distributions of age-related biomarker values in healthy older adults from the long life family study. J Am Geriatr Soc 2016;64(11):e189 − 94. https://doi.org/10.1111/jgs.14522.