Estimating biological age by hematological blood parameters

  • Anatoly Pisaruk D.F. Chebotarev Institute of Gerontology NAMS of Ukraine
  • Ludmila Mekhova D.F. Chebotarev Institute of Gerontology NAMS of Ukraine
Keywords: biological age, hematological blood parameters, deep neural network

Abstract

Abstract. For the estimation of the biological age (BA) of people based on hematological parameters of the clinical blood test there were used MLR and Deep Neural Networks. In the archive of the Institute of Gerontology NAMS of Ukraine there were selected people aged from 20 up to 90 years (440 men and 504 women), who had all hematological parameters within normal limits. When using the MLR method, the multiple correlation coefficients (R) have low values for both men (0.37) and women (0.38). The use of Deep Neural Networks has given good results. The values of the correlation coefficients between BA and chronological age were 0.92 for men and 0.79 for women. The average absolute error in determining BA was 3.68 years for the men and 6.55 years for the women. The developed method for assessing hematological age can be used in clinical practice to identify people with the risk of developing hematological pathology, as well as in population researches.

Author Biographies

Anatoly Pisaruk, D.F. Chebotarev Institute of Gerontology NAMS of Ukraine

DSc (Medicine), Head of the Laboratory for Mathematical Modeling of Aging Processes

Ludmila Mekhova, D.F. Chebotarev Institute of Gerontology NAMS of Ukraine

PhD (Medicine), Senior Researcher of the Laboratory for Mathematical Modeling of Aging

References

Murabito, J. M.; Zhao, Q.; Larson, M. G.; Rong, J.; Lin, H. et al. Measures of biologic age in a community sample predict mortality and age-related disease: the framingham offspring study. J Gerontol Ser A Biol Sci Med Sci 2018, 73, 757–762. doi: 10.1093/gerona/glx144

Jia, L.; Zhang, W.; Chen, X. Common methods of biological age estimation. Clin Interv Aging 2017, 12, 759–772. doi: 10.2147/CIA.S134921.

Mamoshina, P.; Kochetov, K.; Putin, E.; Cortese, F.; Aliper, A.et al. Population specific biomarkers of human aging: a big data study using South Korean, Canadian and Eastern European patient populations. J Gerontol Ser A 2018, 1, 1–9. doi: 10.1093/gerona/gly005

Mamoshina, P.; Vieira, A.; Putin, E.; Zhavoronkov, A. Applications of deep learning in biomedicine. Mol Pharm 2016, 13, 1445–1454. doi: 10.1021/acs.molpharmaceut.5b00982

Sebastiani, P.; Thyagarajan, B.; Sun, F.; Schupf, N.; Newman et al. Biomarker signatures of aging. Aging Cell 2017, 16, 329–338. doi: 10.1111/acel.12557

Putin, E.; Mamoshina, P.; Aliper, A.; Korzinkin, M.; Moskalev, A. Deep biomarkers of human aging: application of deep neural networks to biomarker development. Aging (Albany NY) 2016, 8, 1021–1033. doi: 10.18632/aging.100968

Caballero, F.F.; Soulis, G.; Engchuan, W.; Sanchez-Niubo, A.; Arndt, H. et al. Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project. Sci Rep 2017, 7, 439-455. doi: 10.1038/srep43955.7

Ching, T.; Himmelstein, D. S.; Beaulieu-Jones, B. K.; Kalinin, A. A.; Do B. T. et al. Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface 2018, 15. doi: 10.1098/rsif.2017.0387

Cole, J. H.; Poudel, R. P. K.; Tsagkrasoulis, D.; Caan, M. W. A. et al. Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker. Neuroimage 2017, 163, 115–124. doi: 10.1016/j.neuroimage.2017.07.059

Korkushko, O. V.; Pisaruk, A. V.; Chyzhova,V. P. Estimation of human metabolic age using regression and neural network analysis. Zaporozhye medical journal 2021, 23, 60-64. doi:10.14739/2310-1210.2021.1.224883

Published
2021-10-07
How to Cite
Pisaruk, A., & Mekhova, L. (2021). Estimating biological age by hematological blood parameters. Ageing and Longevity, 2(3), 14-21. Retrieved from http://aging-longevity.org.ua/index.php/journal-description/article/view/34
Section
Статьи

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