<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">geroprob</journal-id><journal-title-group><journal-title xml:lang="ru">Проблемы геронауки</journal-title><trans-title-group xml:lang="en"><trans-title>Problems of Geroscience</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2949-4745</issn><issn pub-type="epub">2949-4753</issn><publisher><publisher-name>АНО «ОСО ИТЕМ»</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.37586/2949-4745-2-2025-60-66</article-id><article-id custom-type="elpub" pub-id-type="custom">geroprob-92</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Обзоры</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Reviews</subject></subj-group></article-categories><title-group><article-title>Использование калькуляторов биологического возраста в клинической практике</article-title><trans-title-group xml:lang="en"><trans-title>The use of biological age calculators in clinical practice</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3544-5347</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ильющенко</surname><given-names>А. К.</given-names></name><name name-style="western" xml:lang="en"><surname>Ilyushchenko</surname><given-names>A. K.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ильющенко Анна Константиновна</p><p>Москва</p></bio><bio xml:lang="en"><p>Ilyushchenko Anna Konstantinovna </p><p>Moscow </p></bio><email xlink:type="simple">ilyushchenko_ak@rgnkc.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0009-0858-2053</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мельницкая</surname><given-names>А. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Melnitskaya</surname><given-names>A. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow </p></bio><email xlink:type="simple">melnickaya_aa@rgnkc.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0009-0008-6926-2195</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Веряскина</surname><given-names>А. Е.</given-names></name><name name-style="western" xml:lang="en"><surname>Veriaskina</surname><given-names>A. E.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow </p></bio><email xlink:type="simple">arina.ver.15@mail.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2028-3939</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Мачехина</surname><given-names>Л. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Matchekhina</surname><given-names>L. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Москва</p></bio><bio xml:lang="en"><p>Moscow </p></bio><email xlink:type="simple">machehina_lv@rgnkc.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГАОУ ВО РНИМУ им. Н. И. Пирогова Минздрава России (Пироговский Университет),ОСП «Российский геронтологический научно-клинический центр»</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Russian Gerontology Research and Clinical Centre, Pirogov Russian National Research Medical University of the Ministry of Health of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2025</year></pub-date><pub-date pub-type="epub"><day>30</day><month>06</month><year>2025</year></pub-date><volume>0</volume><issue>2</issue><fpage>60</fpage><lpage>66</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Ильющенко А.К., Мельницкая А.А., Веряскина А.Е., Мачехина Л.В., 2025</copyright-statement><copyright-year>2025</copyright-year><copyright-holder xml:lang="ru">Ильющенко А.К., Мельницкая А.А., Веряскина А.Е., Мачехина Л.В.</copyright-holder><copyright-holder xml:lang="en">Ilyushchenko A.K., Melnitskaya A.A., Veriaskina A.E., Matchekhina L.V.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://www.geronauka.com/jour/article/view/92">https://www.geronauka.com/jour/article/view/92</self-uri><abstract><p>Биологический возраст (БВ) является интегративным показателем, отражающим степень старения организма и биологический износ систем. В отличие от календарного возраста, БВ может быть изменяемым и использоваться в качестве маркера эффективности геропротективных вмешательств. Современные технологии позволяют рассчитывать БВ на основе различных источников: клинических и лабораторных данных, эпигенетических модификаций, иммунных профилей, микробиома и мультиомных панелей. В настоящей статье рассматриваются различные подходы к оценке БВ, включая эпигенетические часы (Horvath, GrimAge), фенотипические индексы (PhenoAge, индекс дефицитов), иммунологические модели (iAge), а также калькуляторы, основанные на анализе биохимических и гематологических параметров. Для подготовки обзора был проведен поиск литературы в базах данных PubMed и Scopus. Были отобраны оригинальные и обзорные статьи, опубликованные преимущественно с 2010 по 2024 год, содержащие информацию о методах оценки БВ, их прогностическом значении и применении в клинической практике. Авторы обсуждают потенциал внедрения оценки БВ в клиническую практику и персонализированную медицину, а также необходимость валидации существующих инструментов в разных популяциях.</p></abstract><trans-abstract xml:lang="en"><p>Biological age (BA) is defined as an integrative indicator reflecting the degree of organismal aging and biological wear of physiological systems. In contrast to chronological age, BA is a potentially modifiable variable and may serve as a biomarker of geroprotective intervention efficacy. Recent advances have enabled the development ofBA calculators based onclinical and laboratory data, epigenetic modifications, immune signatures, microbiome, and multi-omics profiles. This article reviews various approaches to BA assessment, including epigenetic clocks (Horvath, GrimAge), phenotypic indices (PhenoAge, frailty index), immune aging models (iAge), and calculators derived from standard blood tests. The present review was prepared by conducting a comprehensive literature search utilising the PubMed and Scopus databases. A comprehensive search was conducted of original and review papers published primarily between 2010 and 2024, the focus of which was the description of BA estimation methods, their predictive utility, and clinical applicability. The review discusses the potential for integrating BA assessment into clinical practice and personalised medicine, as well as the need for further validation and standardisation of these tools across populations.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>биологический возраст</kwd><kwd>эпигенетические часы</kwd><kwd>старение</kwd><kwd>калькуляторы старения</kwd><kwd>геронтология</kwd></kwd-group><kwd-group xml:lang="en"><kwd>biological age</kwd><kwd>epigenetic clocks</kwd><kwd>aging</kwd><kwd>aging calculators</kwd><kwd>gerontology</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">López-Otín C., Blasco MA, Partridge L., Serrano M., Kroemer G. Hallmarks of aging: An expanding universe. Cell. 2023; 186 (2): 243–278. DOI: 10.1016/j.cell.2022.11.001.</mixed-citation><mixed-citation xml:lang="en">López-Otín C., Blasco MA, Partridge L., Serrano M., Kroemer G. Hallmarks of aging: An expanding universe. Cell. 2023; 186 (2): 243–278. DOI: 10.1016/j.cell.2022.11.001.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Klemera P., Doubal S. A new approach to the concept and computation of biological age. Mech Ageing Dev. 2006; 127 (3): 240–248. DOI: 10.1016/j.mad.2005.10.004.</mixed-citation><mixed-citation xml:lang="en">Klemera P., Doubal S. A new approach to the concept and computation of biological age. Mech Ageing Dev. 2006; 127 (3): 240–248. DOI: 10.1016/j.mad.2005.10.004.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Cawthon R .M., Smith K. R., O'Brien E., Sivatchenko A., Kerber R. A. Association between telomere length in blood and mortality in people aged 60 years or older. Lancet. 2003; 361(9355): 393–395. DOI: 10.1016/S0140-6736(03)12384-7.</mixed-citation><mixed-citation xml:lang="en">Cawthon R .M., Smith K. R., O'Brien E., Sivatchenko A., Kerber R. A. Association between telomere length in blood and mortality in people aged 60 years or older. Lancet. 2003; 361(9355): 393–395. DOI: 10.1016/S0140-6736(03)12384-7.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Horvath S. DNA methylation age of human tissues and cell types [published correction appears in Genome Biol. 2015 May 13; 16: 96. DOI: 10.1186/s13059-015-0649-6. Genome Biol. 2013; 14 (10): R115. DOI: 10.1186/gb-2013-14-10-r115.</mixed-citation><mixed-citation xml:lang="en">Horvath S. DNA methylation age of human tissues and cell types [published correction appears in Genome Biol. 2015 May 13; 16: 96. DOI: 10.1186/s13059-015-0649-6. Genome Biol. 2013; 14 (10): R115. DOI: 10.1186/gb-2013-14-10-r115.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Hannum G., Guinney J., Zhao L., et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013; 49 (2): 359–367. DOI: 10.1016/j.molcel.2012.10.016.</mixed-citation><mixed-citation xml:lang="en">Hannum G., Guinney J., Zhao L., et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013; 49 (2): 359–367. DOI: 10.1016/j.molcel.2012.10.016.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Belsky D. W., Caspi A., Corcoran D. L., et al. DunedinPACE, a DNA methylation biomarker of the pace of aging. Elife. 2022; 11: e73420. Published 2022 Jan 14. DOI: 10.7554/eLife.73420.</mixed-citation><mixed-citation xml:lang="en">Belsky D. W., Caspi A., Corcoran D. L., et al. DunedinPACE, a DNA methylation biomarker of the pace of aging. Elife. 2022; 11: e73420. Published 2022 Jan 14. DOI: 10.7554/eLife.73420.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Levine M. E. Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci. 2013; 68 (6): 667–674. DOI: 10.1093/gerona/gls233.</mixed-citation><mixed-citation xml:lang="en">Levine M. E. Modeling the rate of senescence: can estimated biological age predict mortality more accurately than chronological age? J Gerontol A Biol Sci Med Sci. 2013; 68 (6): 667–674. DOI: 10.1093/gerona/gls233.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Marioni R. E., Shah S., McRae A. F., et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015; 16 (1): 25. Published 2015 Jan 30. DOI: 10.1186/s13059-015-0584-6.</mixed-citation><mixed-citation xml:lang="en">Marioni R. E., Shah S., McRae A. F., et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015; 16 (1): 25. Published 2015 Jan 30. DOI: 10.1186/s13059-015-0584-6.</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Krištić J., Vučković F., Menni C., et al. Glycans are a novel biomarker of chronological and biological ages. J Gerontol A Biol Sci Med Sci. 2014; 69 (7): 779–789. DOI: 10.1093/gerona/glt190.</mixed-citation><mixed-citation xml:lang="en">Krištić J., Vučković F., Menni C., et al. Glycans are a novel biomarker of chronological and biological ages. J Gerontol A Biol Sci Med Sci. 2014; 69 (7): 779–789. DOI: 10.1093/gerona/glt190.</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Rode L., Nordestgaard B. G., Bojesen S. E. Peripheral blood leukocyte telomere length and mortality among 64, 637 individuals from the general population. J Natl Cancer Inst. 2015; 10 7(6): djv074. Published 2015 Apr 10. DOI: 10.1093/jnci/djv074.</mixed-citation><mixed-citation xml:lang="en">Rode L., Nordestgaard B. G., Bojesen S. E. Peripheral blood leukocyte telomere length and mortality among 64, 637 individuals from the general population. J Natl Cancer Inst. 2015; 10 7(6): djv074. Published 2015 Apr 10. DOI: 10.1093/jnci/djv074.</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Jylhävä J., Pedersen N. L., Hägg S. Biological Age Predictors. EBioMedicine. 2017; 21: 29–36. DOI: 10.1016/j.ebiom.2017.03.046.</mixed-citation><mixed-citation xml:lang="en">Jylhävä J., Pedersen N. L., Hägg S. Biological Age Predictors. EBioMedicine. 2017; 21: 29–36. DOI: 10.1016/j.ebiom.2017.03.046.</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Horvath S., Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet. 2018; 19 (6): 371–384. DOI: 10.1038/s41576-018-0004-3.</mixed-citation><mixed-citation xml:lang="en">Horvath S., Raj K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat Rev Genet. 2018; 19 (6): 371–384. DOI: 10.1038/s41576-018-0004-3.</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Yamada H. Epigenetic Clocks and EpiScore for Preventive Medicine: Risk Stratification and Intervention Models for Age-Related Diseases. J Clin Med. 2025; 14 (10): 3604. Published 2025 May 21. DOI: 10.3390/jcm14103604.</mixed-citation><mixed-citation xml:lang="en">Yamada H. Epigenetic Clocks and EpiScore for Preventive Medicine: Risk Stratification and Intervention Models for Age-Related Diseases. J Clin Med. 2025; 14 (10): 3604. Published 2025 May 21. DOI: 10.3390/jcm14103604.</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Sayed N., Huang Y., Nguyen K., et al. An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging [published correction appears in Nat Aging. 2021 Aug; 1 (8): 748. DOI: 10.1038/s43587-021-00102-x. Nat Aging. 2021; 1: 598–615. DOI: 10.1038/s43587-021-00082-y.</mixed-citation><mixed-citation xml:lang="en">Sayed N., Huang Y., Nguyen K., et al. An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging [published correction appears in Nat Aging. 2021 Aug; 1 (8): 748. DOI: 10.1038/s43587-021-00102-x. Nat Aging. 2021; 1: 598–615. DOI: 10.1038/s43587-021-00082-y.</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Galkin F., Mamoshina P., Aliper A., et al. Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning. iScience. 2020; 23 (6): 101199. DOI: 10.1016/j.isci.2020.101199.</mixed-citation><mixed-citation xml:lang="en">Galkin F., Mamoshina P., Aliper A., et al. Human Gut Microbiome Aging Clock Based on Taxonomic Profiling and Deep Learning. iScience. 2020; 23 (6): 101199. DOI: 10.1016/j.isci.2020.101199.</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Tanaka T., Biancotto A., Moaddel R., et al. Plasma proteomic signature of age in healthy humans. Aging Cell. 2018; 17 (5): e12799. DOI: 10.1111/acel.12799.</mixed-citation><mixed-citation xml:lang="en">Tanaka T., Biancotto A., Moaddel R., et al. Plasma proteomic signature of age in healthy humans. Aging Cell. 2018; 17 (5): e12799. DOI: 10.1111/acel.12799.</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Huh J. Y., Ross G. W., Chen R., et al. Total and differential white blood cell counts in late life predict 8-year incident stroke: the Honolulu Heart Program. J Am Geriatr Soc. 2015; 63 (3): 439–446. DOI: 10.1111/jgs.13298.</mixed-citation><mixed-citation xml:lang="en">Huh J. Y., Ross G. W., Chen R., et al. Total and differential white blood cell counts in late life predict 8-year incident stroke: the Honolulu Heart Program. J Am Geriatr Soc. 2015; 63 (3): 439–446. DOI: 10.1111/jgs.13298.</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Wang Q., Zhan Y., Pedersen N. L., Fang F., Hägg S. Telomere Length and All-Cause Mortality: A Meta-analysis. Ageing Res Rev. 2018; 48: 11–20. DOI: 10.1016/j.arr.2018.09.002.</mixed-citation><mixed-citation xml:lang="en">Wang Q., Zhan Y., Pedersen N. L., Fang F., Hägg S. Telomere Length and All-Cause Mortality: A Meta-analysis. Ageing Res Rev. 2018; 48: 11–20. DOI: 10.1016/j.arr.2018.09.002.</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Vetter V. M., Meyer A., Karbasiyan M., Steinhagen-Thiessen E., Hopfenmüller W., Demuth I. Epigenetic Clock and Relative Telomere Length Represent Largely Different Aspects of Aging in the Berlin Aging Study II (BASE-II). J Gerontol A Biol Sci Med Sci. 2019; 74 (1): 27–32. DOI: 10.1093/gerona/gly184.</mixed-citation><mixed-citation xml:lang="en">Vetter V. M., Meyer A., Karbasiyan M., Steinhagen-Thiessen E., Hopfenmüller W., Demuth I. Epigenetic Clock and Relative Telomere Length Represent Largely Different Aspects of Aging in the Berlin Aging Study II (BASE-II). J Gerontol A Biol Sci Med Sci. 2019; 74 (1): 27–32. DOI: 10.1093/gerona/gly184.</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Lu A. T., Quach A., Wilson J. G., et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019; 11 (2): 303–327. DOI: 10.18632/aging.101684.</mixed-citation><mixed-citation xml:lang="en">Lu A. T., Quach A., Wilson J. G., et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019; 11 (2): 303–327. DOI: 10.18632/aging.101684.</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Lu A. T., Binder A. M., Zhang J., et al. DNA methylation GrimAge version 2. Aging (Albany NY). 2022; 14 (23): 9484–9549. DOI: 10.18632/aging.204434.</mixed-citation><mixed-citation xml:lang="en">Lu A. T., Binder A. M., Zhang J., et al. DNA methylation GrimAge version 2. Aging (Albany NY). 2022; 14 (23): 9484–9549. DOI: 10.18632/aging.204434.</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Lehallier B., Gate D., Schaum N., et al. Undulating changes in human plasma proteome profiles across the lifespan. Nat Med. 2019; 25 (12): 1843–1850. DOI: 10.1038/s41591-019-0673-2.</mixed-citation><mixed-citation xml:lang="en">Lehallier B., Gate D., Schaum N., et al. Undulating changes in human plasma proteome profiles across the lifespan. Nat Med. 2019; 25 (12): 1843–1850. DOI: 10.1038/s41591-019-0673-2.</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Gialluisi A., Santoro A., Tirozzi A., et al. Epidemiological and genetic overlap among biological aging clocks: New challenges in biogerontology. Ageing Res Rev. 2021; 72: 101502. DOI: 10.1016/j.arr.2021.101502.</mixed-citation><mixed-citation xml:lang="en">Gialluisi A., Santoro A., Tirozzi A., et al. Epidemiological and genetic overlap among biological aging clocks: New challenges in biogerontology. Ageing Res Rev. 2021; 72: 101502. DOI: 10.1016/j.arr.2021.101502.</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Fahy G. M., Brooke R. T., Watson J. P., et al. Reversal of epigenetic aging and immunosenescent trends in humans. Aging Cell. 2019; 18 (6): e13028. DOI: 10.1111/acel.13028.</mixed-citation><mixed-citation xml:lang="en">Fahy G. M., Brooke R. T., Watson J. P., et al. Reversal of epigenetic aging and immunosenescent trends in humans. Aging Cell. 2019; 18 (6): e13028. DOI: 10.1111/acel.13028.</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Zhavoronkov A., Mamoshina P. Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity. Trends Pharmacol Sci. 2019; 40 (8): 546–549. DOI: 10.1016/j.tips.2019.05.004.</mixed-citation><mixed-citation xml:lang="en">Zhavoronkov A., Mamoshina P. Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity. Trends Pharmacol Sci. 2019; 40 (8): 546–549. DOI: 10.1016/j.tips.2019.05.004.</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Prattichizzo F., Frigé C., Pellegrini V., et al. Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine. Ageing Res Rev. 2024; 96: 102253. DOI: 10.1016/j.arr.2024.102253.</mixed-citation><mixed-citation xml:lang="en">Prattichizzo F., Frigé C., Pellegrini V., et al. Organ-specific biological clocks: Ageotyping for personalized anti-aging medicine. Ageing Res Rev. 2024; 96: 102253. DOI: 10.1016/j.arr.2024.102253.</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Forrester S. N., Baek J., Hou L., Roger V., Kiefe C. I. A Comparison of 5 Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study. J Am Heart Assoc. 2024; 13 (8): e032847. DOI: 10.1161/JAHA.123.032847.</mixed-citation><mixed-citation xml:lang="en">Forrester S. N., Baek J., Hou L., Roger V., Kiefe C. I. A Comparison of 5 Measures of Accelerated Biological Aging and Their Association With Incident Cardiovascular Disease: The CARDIA Study. J Am Heart Assoc. 2024; 13 (8): e032847. DOI: 10.1161/JAHA.123.032847.</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Furrer R., Handschin C. Biomarkers of aging: from molecules and surrogates to physiology and function. Physiol Rev. 2025; 105 (3): 1609–1694. DOI: 10.1152/physrev.00045.2024.</mixed-citation><mixed-citation xml:lang="en">Furrer R., Handschin C. Biomarkers of aging: from molecules and surrogates to physiology and function. Physiol Rev. 2025; 105 (3): 1609–1694. DOI: 10.1152/physrev.00045.2024.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
