A systems analysis of biomarkers of aging for definition of biological age

Authors

Krut'ko V. N. Dontsov V.

Annotation

Biological age (BA) is a quantitative measure of aging that reflects the decline in the body's vitality with age. The viability of the whole (organism) consists of the viability of parts (organs and systems of the body), which corresponds to their functional resource. Indicators of such resource - biomarkers (BM) of aging. BM of aging are any indicators that decrease significantly with age and have little variation between individuals. To BM of aging, quantitatively characterizing the BA, can be imposed a number of quality requirements. Optimal is the set of 6-15 "orthogonal" - minimally cross-correlated BM, characterizing the state of various vital body systems (especially cardiovascular and respiratory), in particular reflecting: age physiology, features of aging the most important organs and systems, physical and mental performance, limits of adaptation and functional reserves, age-related chronic pathology, self-reported health conditions. The most important requirements for BM are: accuracy; information content; low individual variability and resistance to external influences, diseases and training; not too high complexity and cost; availability of equipment; taking into account specific tasks and capabilities of the researcher. Taking into account these requirements, perspective biomarkers of aging of which various diagnostic panels for BA assessment for the different purposes and tasks of users can be formed are selected.

External links

DOI: 10.14357/20790279180404

Download the article (PDF) from the Proceedings of the Instittute for Systems Analysis website (in Russian): http://www.isa.ru/proceedings/images/documents/2018-68-4/32-41.pdf

Download the article (PDF) from eLibrary (in Russian, registration required): https://www.elibrary.ru/item.asp?id=36654646 

Reference link

V. I. Dontsov, V. N. Krut`ko. A systems analysis of biomarkers of aging for definition of biological age // Proceedings of the Instittute for Systems Analysis of the Russian Academy of Sciences. 2018. Issue 68. № 4. Pp. 32–41.