Prospects for assessing the biological and immunological age of a person by blood factors

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Abstract

According to the WHO, by 2050 in developed countries, the population over 60 years old will double. This will lead to a further increase in the retirement age and an elevation of burden on the health care system. Therefore, there is an acute issue of maintaining health and prolonging active longevity, as well as the introduction of monitoring for prevention of premature aging and age-related disorders to avoid early disability. The review aims to discuss the aging process and identify critical blood factors affecting or indicating progress in biological aging. The connection of biological age, the regenerative and immune systems aging with the shift in circulating blood factors have been evaluated. The concepts of "health and longevity hygiene" and the concept of "immunological age" are debated. Perspective methods of rapid and multiplex analyzes of blood factors are discussed, as well as the prospects for preliminary analysis of biological and immunological age at home with subsequent processing in high-tech centers to identify risk groups and monitor healthy aging. Approaches to protecting health, slowing aging and rejuvenating the elderly, maintaining healthy aging, and prolonging active life have been defined.

About the authors

Nikita D. Kurgan

ITMO University

Email: mika97@list.ru

research engineer Faculty of Technological Managementand Innovations

Russian Federation, St. Petersburg

Evgeniya I. Panova

ITMO University

Email: evgeniyapanova1996@gmail.com

research engineer Faculty of Technological Management and Innovations

Russian Federation, St. Petersburg

Lyubov V. Silakova

ITMO University

Email: silakovalv@itmo.ru
ORCID iD: 0000-0003-2836-1281

PhD in Economics, Associate professor Faculty of Technological Management and Innovations

Russian Federation, St. Petersburg

Aleksandr M. Kaganskii

ITMO University; Far Eastern Federal University

Email: kagasha@yahoo.com
ORCID iD: 0000-0002-6219-6892

PhD in Biology, Associate professor, Faculty of Technological Management and Innovations; Director of the Center for genomic and regenerative medicine, School of Biomedicine

Russian Federation, St. Petersburg; Vladivostok

Stanislav A. Rybtsov

Center for Regenerative Medicine, Institute of Regeneration and Reparation,
University of Edinburgh

Author for correspondence.
Email: srybtsov@ed.ac.uk
ORCID iD: 0000-0001-7786-1878

PhD in Genetics, senior research fellow of the Centre for Regenerative Medicine, Institute of Regeneration and Repairation

United Kingdom, Edinburgh

References

  1. Hamczyk MR, Nevado RM, Barettino A, et al. Biological Versus Chronological Aging, JACC Focus Seminar. J Am Coll Cardiol. 2020;75(8):919-930. doi: 10.1016/j.jacc.2019.11.062
  2. Bunning BJ, Contrepois K, Lee-McMullen B, et al. Global metabolic profiling to model biological processes of aging in twins. Aging Cell. 2020;19(1):e13073. doi: 10.1111/acel.13073
  3. Hertel J, Friedrich N, Wittfeld K, et al. Measuring Biological Age via Metabonomics: The Metabolic Age Score. J Proteome Res. 2016;15(2):400-410. doi: 10.1021/acs.jproteome.5b00561
  4. BelskyDW, Caspi A, Arseneault L, et al. Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. Elife. 2020;9. doi: 10.7554/eLife.54870
  5. Fang Y, Zhu L, An N, et al. Blood autophagy defect causes accelerated non-hematopoietic organ aging. Aging (Albany NY). 2019;11(14):4910-4922. doi: 10.18632/aging.102086
  6. Hansen M, Rubinsztein DC, Walker DW. Autophagy as a promoter of longevity: insights from model organisms. Nat Rev Mol Cell Biol. 2018;19(9):579-593. doi: 10.1038/s41580-018-0033-y
  7. Kiss T, Tarantini S, Csipo T, et al. Circulating anti-geronic factors from heterochonic parabionts promote vascular rejuvenation in aged mice: transcriptional footprint of mitochondrial protection, attenuation of oxidative stress, and rescue of endothelial function by young blood. Geroscience. 2020;42(2):727-748. doi: 10.1007/s11357-020-00180-6
  8. Dolgin E. Send in the senolytics. Nature Biotechnology. 2020;38(12):1371-1377. doi: 10.1038/s41587-020-00750-1
  9. Chin CD, Cheung YK, Laksanasopin T, et al. Mobile device for disease diagnosis and data tracking in resource-limited settings. Clin Chem. 2013; 59(4):629-640. doi: 10.1373/clinchem.2012.199596
  10. Hernández-Neuta I, Neumann F, Brightmeyer J, et al. Smartphone-based clinical diagnostics: towards democratization of evidence-based health care. J Intern Med. 2019;285(1):19-39. doi: 10.1111/joim.12820
  11. Castillo L, MacCallum DM. Cytokine measurement using cytometric bead arrays. Methods Mol Biol. 2012;845:425-434. doi: 10.1007/978-1-61779-539-8_29
  12. Subrahmanyam PB, Maecker HT. CyTOF Measurement of Immunocompetence Across Major Immune Cell Types. Curr Protoc Cytom. 2017;82:59.54.51-59.54.12. doi: 10.1002/cpcy.27
  13. Han G, Spitzer MH, Bendall SC, et al. Metal-isotope-tagged monoclonal antibodies for high-dimensional mass cytometry. Nat Protoc. 2018;13 (10):2121-2148. doi: 10.1038/s41596-018-0016-7
  14. Zannas AS, Jia M, Hafner K, et al. Epigenetic upregulation of FKBP5 by aging and stress contributes to NF-B-driven inflammation and cardiovascular risk. Proc Natl Acad Sci U S A. 2019;116(23):11370-11379. doi: 10.1073/pnas.1816847116
  15. Cheung P, Vallania F, Warsinske HC, et al. Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging. Cell. 2018;173 (6): 1385-1397, e1314. doi: 10.1016/j.cell.2018.03.079
  16. Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573-591. doi: 10.18632/aging.101414
  17. Silva-Palacios A, Ostolga-Chavarria M, Zazueta C, Konigsberg M. Nrf2: Molecular and epigenetic regulation during aging. Ageing Res Rev. 2018;47:31-40. doi: 10.1016/j.arr.2018.06.003
  18. Lu AT, Quach A, Wilson JG, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019;11(2): 303-327. doi: 10.18632/aging.101684
  19. Bialek S, Boundy E, Bowen V, et al. Severe Outcomes Among Patients with Coronavirus Disease 2019 (COVID-19) - United States, February 12-March 16, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(12):343-346. doi: 10.15585/mmwr.mm6912e2
  20. Lauc G, Sinclair D. Biomarkers of biological age as predictors of COVID-19 disease severity. Aging (Albany NY). 2020;12(8):6490-6491. doi: 10.18632/aging.103052
  21. Berezina TN, Rybtsov SA. The influence of quarantine on the indicators of biopsychological age in Russia (longitudinal study). Journal of Modern Foreign Psychology. 2021;10(1):57-69. (In Russ.). [Березина Т.Н., Рыбцов С.А. Влияние карантина на показатели биопсихологического возраста в России (лонгитюдное исследование). Современная зарубежная психология. 2021;10(1):57-69]. doi: 10.17759/jmfp.2021100106
  22. Atkins JL, Masoli JAH, Delgado J, et al. Preexisting Comorbidities Predicting COVID-19 and Mortality in the UK Biobank Community Cohort. J Gerontol A Biоl Sci Med Sci. 2020;75(11);2224-2230. doi: 10.1093/gerona/glaa183
  23. Franzen J, Nüchtern S, Tharmapalan V, et al. Epigenetic clocks are not accelerated in COVID-19 patients. International Journal of Molecular Sciences. 2021;22(17):9306. doi.org/10.3390/ijms22179306
  24. Rybtsova NN, Berezina TN, Kagansky AM, Rybtsov SA. Can blood-circulating factors unveil and delay your biological aging? Biomedicins. 2020;8(12):615. doi:https://doi.org/10.3390/biomedicines8120615
  25. Nehme J, Borghesan M, Mackedenski S, et al. Cellular senescence as a potential mediator of COVID-19 severity in the elderly. Aging Cell. 2020;19(10): e13237. doi: 10.1111/acel.13237
  26. Ovadya Y, Landsberger T, Leins H, et al. Impaired immune surveillance accelerates accumulation of senescent cells and aging. Nature Communications. 2018;9(1):5435. doi: 10.1038/s41467-018-07825-3
  27. Tsai, S, Clemente-Casares X, Zhou AC, et al. Insulin Receptor-Mediated Stimulation Boosts T Cell Immunity during Inflammation and Infection. Cell Metab. 2018;28(6):922-934.e924. doi: 10.1016/j.cmet.2018.08.003
  28. Berezina TN, Rybtsova NN, Rybtsov SA. Comparative Dynamics of Individual Ageing Among the Investigative Type of Professionals Living in Russia and Russian Migrants to the EU Countries. European Journal of Investigation in Health, Psychology and Education. 2020;10(3):749-762. doi:https://doi.org/10.3390/ejihpe10030055
  29. Berezina TN, Buzanov KE, Zinatullina AM, et al. The expectation of retirement as a psychological stress that affects the biological age in the person of the Russian Federation. Religación. Revista de Ciencias Sociales y Humanidades. 2019;4(18):192-198.
  30. Berezina TN, Stelmakh SA, Dergacheva EV. The effect of retirement stress on the biopsychological age in Russia and the Republic of Kazakhstan: a cross-cultural study. Psychologist. 2019;5. doi: 10.25136/2409-8701.2019.5.31159
  31. Voitenko VP, Tokar AV. The assessment of biological age and sex differences of human aging. Exp Aging Res. 1983;9(4):239-244. doi: 10.1080/03610738308258458
  32. Voitenko VP. Biological age. In: Physiological mechanisms of aging. Moscow, 1982:144-156.
  33. Pyrkov TV, Sokolov IS, Fedichev PO. Deep longitudinal phenotyping of wearable sensor data reveals independent markers of longevity, stress, and resilience. Aging (Albany NY). 2021;13(6):7900-7913. doi: 10.18632/aging.202816
  34. Kuo CL, Pilling LC, Atkins JC, et al. COVID-19 severity is predicted by earlier evidence of accelerated aging. MedRxiv, 2020. doi: 10.1101/2020.07.10.20147777
  35. Hewitt J, Carter B, Vilches-Moraga A, et al. The effect of frailty on survival in patients with COVID-19 (COPE): a multicentre, European, observational cohort study. Lancet Public Health. 2020;5(8): e444-e451. doi: 10.1016/s2468-2667(20)30146-8
  36. Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14(10): R115. doi: 10.1186/gb-2013-14-10-r115
  37. 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
  38. Chen BH, Marioni RE, Colicino E, et al. DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY). 2016;8(9):1844-1865. doi: 10.18632/aging.101020
  39. Marioni RE, Shah S, McRae AF, et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 2015;16(1):25. doi: 10.1186/s13059-015-0584-6
  40. Zhang Y, Wilson R, Heiss J, et al. DNA methylation signatures in peripheral blood strongly predict all-cause mortality. Nat Commun. 2017;8:14617. doi: 10.1038/ncomms14617
  41. Berezina T. Distribution of biomarkers of aging in people with different personality types. (In Russ.). E3S Web of Conferences 2020 (210). Article Number 17028. doi: 10.1051/e3sconf/202021017028
  42. Yegorov YE, Poznyak AV, Nikiforov NG, et al. The Link between Chronic Stress and Accelerated Aging. Biomedicines.2020;8(7). doi: 10.3390/biomedicines8070198
  43. Crosswell AD, Suresh M, Puterman E, et al. Advancing Research on Psychosocial Stress and Aging with the Health and Retirement Study: Looking Back to Launch the Field Forward. J Gerontol B Psychol Sci Soc Sci. 2020;75(5): 970-980. doi: 10.1093/geronb/gby106
  44. Madore C, Yin Z, Leibowitz J, Butovsky O. Microglia, Lifestyle Stress, and Neurodegeneration. Immunity. 2020;52(2);222-240. doi: 10.1016/j.immuni.2019.12.003
  45. Berezina TN. Differences in individual life path choices affecting life expectancy and health in Russia. E3s Web of Conferences, 2020;210(17032):10. doi:https://doi.org/10.1051/e3sconf/202021017032
  46. Berezina TN. Psychological factors in the development of cardiovascular diseases at different stages of life. Psychiatry, Psychotherapy and Clinical Psychology. 2020;11(1):75-84. doi: 10.34883/PI.2020.11.1.007
  47. Prattichizzo F, Giuliani A, Mensa E, et al. Pleiotropic effects of metformin: Shaping the microbiome to manage type 2 diabetes and postpone ageing. Ageing Res Rev. 2018;48:87-98. doi: 10.1016/j.arr.2018.10.003
  48. Wang B, Kohli J, Demaria M. Senescent Cells in Cancer Therapy: Friends or Foes? Trends Cancer. 2020. doi: 10.1016/j.trecan.2020.05.004
  49. Franceschi C, Garagnani P, Morsiani C, et al. The Continuum of Aging and Age-Related Diseases: Common Mechanisms but Different Rates. Front Med (Lausanne). 2018;5:61. doi: 10.3389/fmed.2018.00061
  50. Zhavoronkov A. Geroprotective and senoremediative strategies to reduce the comorbidity, infection rates, severity, and lethality in gerophilic and gerolavic infections. Aging (Albany NY). 2020;12(8):6492-6510. doi: 10.18632/aging.102988
  51. Bhatt AS, DeVore AD, Hernandez AF, Mentz RJ. Can Vaccinations Improve Heart Failure Outcomes?: Contemporary Data and Future Directions. JACC Heart Fail. 2017;5(3):194-203. doi: 10.1016/j.jchf.2016.12.007
  52. Qato DM, Alexander GC, Conti RM, et al. Use of prescription and over-the-counter medications and dietary supplements among older adults in the United States. Jama. 2008;300 (24):2867-2878. doi: 10.1001/jama.2008.892
  53. Moskalev A. The challenges of estimating biological age. Elife. 2020;9. doi: 10.7554/eLife.54969
  54. Boerman EM, Segal SS. Depressed perivascular sensory innervation of mouse mesenteric arteries with advanced age. J Physiol. 2016;594 (8):2323-2338. doi: 10.1113/jp270710
  55. Gan KJ, Südhof TC. Specific factors in blood from young but not old mice directly promote synapse formation and NMDA-receptor recruitment. Proceedings of the National Academy of Sciences. 2019;116(25):12524. doi: 10.1073/pnas.1902672116
  56. Morgentaler A. Nerve growth factor as a new treatment for testosterone deficiency? EBioMedicine. 2018;36:10-11. doi: 10.1016/j.ebiom.2018.09.017
  57. Lou G, Zhang Q, Xiao F, et al. Intranasal TAT-haFGF Improves Cognition and Amyloid-β Pathology in an AβPP/PS1 Mouse Model of Alzheimer's Disease. J Alzheimers Dis. 2016;51(4):985-990. doi: 10.3233/jad-151121
  58. Luo J, Yang Y, Zhang T, et al. Nasal delivery of nerve growth factor rescue hypogonadism by up-regulating GnRH and testosterone in aging male mice. EBioMedicine. 2018;35:295-306. doi: 10.1016/j.ebiom.2018.08.021
  59. Moreno-García A, Kun A, Calero O, et al. An Overview of the Role of Lipofuscin in Age-Related Neurodegeneration. Front Neurosci. 2018;12:464. doi: 10.3389/fnins.2018.00464
  60. Feng FK, E LL, Kong XP, et al. Lipofuscin in saliva and plasma and its association with age in healthy adults. Aging Clin Exp Res. 2015;27(5):573-580. doi: 10.1007/s40520-015-0326-3
  61. Sinha M, Jang YC, Oh J, et al. Restoring systemic GDF11 levels reverses age-related dysfunction in mouse skeletal muscle. Science. 2014;344 (6184): 649-652. doi: 10.1126/science.1251152
  62. Katsimpardi L, Litterman NK, Schein PA, et al. Vascular and neurogenic rejuvenation of the aging mouse brain by young systemic factors. Science. 2014;344 (6184):630-634. doi: 10.1126/science.1251141
  63. Ozek C, Krolewski RC, Buchanan SM, Rubin LL. Growth Differentiation Factor 11 treatment leads to neuronal and vascular improvements in the hippocampus of aged mice. Sci Rep. 2018; 8(1):17293. doi: 10.1038/s41598-018-35716-6
  64. Roh JD, Hobson R, Chaudhari V, et al. Activin type II receptor signaling in cardiac aging and heart failure. Sci Transl Med. 2019;11(482):eaau8680. doi: 10.1126/scitranslmed.aau8680
  65. Latres E, Mastaitis J, Fury W, et al. Activin A more prominently regulates muscle mass in primates than does GDF8. Nat Commun. 2017;8:15153. doi: 10.1038/ncomms15153
  66. Suh J, Kim NK, Lee SH, et al. GDF11 promotes osteogenesis as opposed to MSTN, and follistatin, a MSTN/GDF11 inhibitor, increases muscle mass but weakens bone. Proc Natl Acad Sci U S A.2020;117(9):4910-4920. doi: 10.1073/pnas.1916034117
  67. Vinel C, Lukjanenko L, Batut A, et al. The exerkine apelin reverses age-associated sarcopenia. Nat Med. 2018;24 (9):1360-1371. doi: 10.1038/s41591-018-0131-6
  68. Jackson M, Fidanza A, Taylor AH, et al. Modulation of APLNR Signaling Is Required during the Development and Maintenance of the Hematopoietic System. Stem Cell Reports. 2021;16(4):727-740. doi: 10.1016/j.stemcr.2021.02.003
  69. Yu QC, Hirst CE, Costa M, et al. APELIN promotes hematopoiesis from human embryonic stem cells. Blood. 2012;119 (26): 6243-6254. doi: 10.1182/blood-2011-12-396093
  70. Yang YR, Kabir MH, Park JH, et al. Plasma proteomic profiling of young and old mice reveals cadherin-13 prevents age-related bone loss. Aging (Albany NY). 2020;12(9):8652-8668. doi: 10.18632/aging.103184
  71. Zhang WB, Aleksic S, Gao T, et al. Insulin-like Growth Factor-1 and IGF Binding Proteins Predict All-Cause Mortality and Morbidity in Older Adults. Cells. 2020;9 (6):1368. doi: 10.3390/cells9061368
  72. Kong H, Chandel NS. To Claim Growth Turf, mTOR Says SOD Off. Mol Cell. 2018;70(3):383-384. doi: 10.1016/j.molcel.2018.04.015
  73. Mehdipour M, Etienne J, Chen CC, et al. Rejuvenation of brain, liver and muscle by simultaneous pharmacological modulation of two signaling determinants, that change in opposite directions with age. Aging (Albany NY). 2019;11(15):5628-5645. doi: 10.18632/aging.102148
  74. Elabd C, Cousin W, Upadhyayula P, et al. Oxytocin is an age-specific circulating hormone that is necessary for muscle maintenance and regeneration. Nat Commun. 2014;5:4082. doi: 10.1038/ncomms5082
  75. Nasi S, Ehirchiou D, Chatzianastasiou A, et al. The protective role of the 3-mercaptopyruvate sulfurtransferase (3-MST)-hydrogen sulfide (H2S) pathway against experimental osteoarthritis. Arthritis Research & Therapy. 2020;22(1):49. doi: 10.1186/s13075-020-02147-6
  76. Qabazard B, Sturzenbaum SR. H2S: A New Approach to Lifespan Enhancement and Healthy Ageing? Handb Exp Pharmacol. 2015;230:269-287. doi: 10.1007/978-3-319-18144-8_14
  77. Fujita Y, Taniguchi Y, Shinkai S, et al. Secreted growth differentiation factor 15 as a potential biomarker for mitochondrial dysfunctions in aging and age-related disorders. Geriatr Gerontol Int. 16 Suppl., 2016;1:17-29. doi: 10.1111/ggi.12724
  78. Mills KF, Yoshida S, Stein LR, et al. Long-Term Administration of Nicotinamide Mononucleotide Mitigates Age-Associated Physiological Decline in Mice. Cell Metab. 2016;24 (6):795-806. doi: 10.1016/j.cmet.2016.09.013
  79. Camacho-Pereira J, Tarragó MG, et al. CD38 Dictates Age-Related NAD Decline and Mitochondrial Dysfunction through an SIRT3-Dependent Mechanism. Cell Metab. 2016;23(6):1127-1139. doi: 10.1016/j.cmet.2016.05.006
  80. Yoshida M, Satoh A, Lin JB, et al. Extracellular Vesicle-Contained eNAMPT Delays Aging and Extends Lifespan in Mice. Cell Metab. 2019;30(2):329-342, e325. doi: 10.1016/j.cmet.2019.05.015
  81. Lewis-McDougall FC, Ruchaya PJ, Domenjo-Vila E, et al. Aged-senescent cells contribute to impaired heart regeneration. Aging Cell. 2019;18 (3):e12931. doi: 10.1111/acel.12931
  82. West MD, Sternberg H, Labat I, et al. Toward a unified theory of aging and regeneration. Regen Med. 2019;14 (9):867-886. doi: 10.2217/rme-2019-0062
  83. Kim DH, Bang E, Arulkumar R, et al. Senoinflammation: A major mediator underlying age-related metabolic dysregulation. Exp Gerontol. 2020;134:110891. doi: 10.1016/j.exger.2020.110891
  84. Zheng Z, Peng F, Xu B, et al. Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis. J Infect. 2020;81(2):e16-e25. doi: 10.1016/j.jinf.2020.04.021
  85. Willyard C. How anti-ageing drugs could boost COVID vaccines in older people. Nature. 2020;586(7829):352-354. doi: 10.1038/d41586-020-02856-7
  86. Santesmasses D, Castro JP, Zenin AA, et al. COVID-19 is an emergent disease of aging. Aging Cell. 2020;19(10):e13230. doi: 10.1111/acel.13230
  87. Rodewald HR. The thymus in the age of retirement. Nature. 1998;396(6712): 630-631. doi: 10.1038/25251
  88. Thomas R, Wang W, SuD M. Contributions of Age-Related Thymic Involution to Immunosenescence and Inflammaging. Immun Ageing. 2020;17:2. doi: 10.1186/s12979-020-0173-8
  89. Aw D, Hilliard L, Nishikawa Y, et al. Disorganization of the splenic microanatomy in ageing mice. Immunology. 2016;148(1): 92-101. doi: 10.1111/imm.12590
  90. Kale A, Sharma A, Stolzing A, et al. Role of immune cells in the removal of deleterious senescent cells. Immun Ageing. 2020;17:16. doi: 10.1186/s12979-020-00187-9
  91. Baz-Martínez M, Da Silva-Álvarez S, Rodríguez E, et al. Cell senescence is an antiviral defense mechanism. Sci Rep. 2016;6:37007. doi: 10.1038/srep37007
  92. Panneer Selvam S, Roth BM, Nganga R, et al. Balance between senescence and apoptosis is regulated by telomere damage–induced association between p16 and caspase-3. Journal of Biological Chemistry. 2018;293 (25):9784-9800. doi:https://doi.org/10.1074/jbc.RA118.003506
  93. Orzalli MH, Kagan JC. Apoptosis and Necroptosis as Host Defense Strategies to Prevent Viral Infection. Trends Cell Biol. 2017;27(11):800-809. doi: 10.1016/j.tcb.2017.05.007
  94. Zheng Y, Liu X, Le W, et al. A human circulating immune cell landscape in aging and COVID-19. Protein Cell. 2020;11(10):740-770. doi: 10.1007/s13238-020-00762-2
  95. Ruan Q, Yang K, Wang W, et al. Correction to: Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46(6):1294-1297. doi: 10.1007/s00134-020-06028-z
  96. Sargiacomo C, Sotgia F, Lisanti MP. COVID-19 and chronological aging: senolytics and other anti-aging drugs for the treatment or prevention of corona virus infection? Aging (Albany NY). 2020;12 (8):6511-6517. doi: 10.18632/aging.103001
  97. Tay MZ, Poh CM, Rénia L, et al. The trinity of COVID-19: immunity, inflammation and intervention. Nature Reviews Immunology. 2020;20 (6):363-374. doi: 10.1038/s41577-020-0311-8
  98. Piber D, Olmstead R, Cho JHJ, et al. Inflammaging: Age and Systemic, Cellular, and Nuclear Inflammatory Biology in Older Adults. Journals of Gerontology – Series A Biological Sciences and Medical Sciences. 2019;74 (11):1716-1724. doi: 10.1093/gerona/glz130
  99. Biver E, Berenbaum F, Valdes AM, et al. Gut microbiota and osteoarthritis management: an expert consensus of the European Society for Clinical and Economic Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO). Ageing Res Rev. 2019:100946. doi: 10.1016/j.arr.2019.100946
  100. Willis SA, Sargeant JA, Yates T, et al. Acute Hyperenergetic, High-Fat Feeding Increases Circulating FGF21, LECT2, and Fetuin-A in Healthy Men. J Nutr. 2020;150(5):1076-1085. doi: 10.1093/jn/nxz333
  101. Moeller M, Pink C, Endlich N, et al. Mortality is associated with inflammation, anemia, specific diseases and treatments, and molecular markers. PLoS One. 2017;12 (4):e0175909. doi: 10.1371/journal.pone.0175909
  102. Hojyo S, Uchida M, Tanaka K, et al. How COVID-19 induces cytokine storm with high mortality. Inflamm Regen. 2020;40:37. doi: 10.1186/s41232-020-00146-3
  103. Villeda SA, Plambeck KE, Middeldorp J, et al. Young blood reverses age-related impairments in cognitive function and synaptic plasticity in mice. Nat Med. 2014;20(6):659-663. doi: 10.1038/nm.3569
  104. Zhao J, Legge K, Perlman S. Age-related increases in PGD(2) expression impair respiratory DC migration, resulting in diminished T cell responses upon respiratory virus infection in mice. J Clin Invest. 2011;121(12):4921-4930. doi: 10.1172/jci59777
  105. Gschwandtner M, Derler R, Midwood KS. More Than Just Attractive: How CCL2 Influences Myeloid Cell Behavior Beyond Chemotaxis. Front Immunol. 2019;10, 2759. doi: 10.3389/fimmu.2019.02759
  106. Mulholland BS, Forwood MR, Morrison NA. Monocyte Chemoattractant Protein-1 (MCP-1/CCL2) Drives Activation of Bone Remodelling and Skeletal Metastasis. Curr Osteoporos Rep. 2019;17 (6):538-547. doi: 10.1007/s11914-019-00545-7
  107. Joly-Amado A, Hunter J, Quadri Z, et al. CCL2 Overexpression in the Brain Promotes Glial Activation and Accelerates Tau Pathology in a Mouse Model of Tauopathy. Front Immunol. 2020;11:997. doi: 10.3389/fimmu.2020.00997
  108. Yousefzadeh MJ, Schafer MJ, Noren Hooten N, et al. Circulating levels of monocyte chemoattractant protein-1 as a potential measure of biological age in mice and frailty in humans. Aging Cell. 2018;17(2):e12706. doi: 10.1111/acel.12706
  109. Kawamoto D, Amado PPL, Albuquerque-Souza E, et al. Chemokines and cytokines profile in whole saliva of patients with periodontitis. Cytokine. 2020;135:155197. doi: 10.1016/j.cyto.2020.155197
  110. Wang F, Ye Y, Luo ZY, et al. Diverse expression of TNF-α and CCL27 in serum and blister of Stevens – Johnson syndrome/toxic epidermal necrolysis. Clinical and Translational Allergy. 2018;8(1):12. doi: 10.1186/s13601-018-0199-6
  111. Riis JL, Johansen C, Vestergaard C, et al. Kinetics and differential expression of the skin-related chemokines CCL27 and CCL17 in psoriasis, atopic dermatitis and allergic contact dermatitis. Exp Dermatol. 2011;20(10):789-794. doi: 10.1111/j.1600-0625.2011.01323.x
  112. Wang WT, Lee SS, Wang YC, et al. Impaired cutaneous T-cell attracting chemokine elevation and adipose-derived stromal cell migration in a high-glucose environment cause poor diabetic wound healing, The Kaohsiung Journal of Medical Sciences. 2018;34(10):539-546. doi: https://doi.org/10.1016/j.kjms.2018.05.002
  113. Stout-Delgado HW, Du W, Shirali AC, et al. Aging promotes neutrophil-induced mortality by augmenting IL-17 production during viral infection. Cell Host Microbe. 2009;6(5):446-456. doi: 10.1016/j.chom.2009.09.011
  114. Li Q, Ding S, Wang YM, et al. Age-associated alteration in Th17 cell response is related to endothelial cell senescence and atherosclerotic cerebral infarction. Am J Transl Res. 2017;9(11):5160-5168.
  115. Blauvelt A, Chiricozzi A. The Immunologic Role of IL-17 in Psoriasis and Psoriatic Arthritis Pathogenesis. Clin Rev Allergy Immunol. 2018;55(3):379-390. doi: 10.1007/s12016-018-8702-3
  116. Cătană CS, Berindan Neagoe I, Cozma V, et al. Contribution of the IL-17/IL-23 axis to the pathogenesis of inflammatory bowel disease. World J Gastroenterol. 2015;21(19):5823-5830. doi: 10.3748/wjg.v21.i19.5823
  117. Abdel-Moneim A, Bakery HH, Allam G. The potential pathogenic role of IL-17/Th17 cells in both type 1 and type 2 diabetes mellitus. Biomed Pharmacother. 2018;101:287-292. doi: 10.1016/j.biopha.2018.02.103
  118. Rybtsov SA, Lagarkova MA. Development of Hematopoietic Stem Cells in the Early Mammalian Embryo. Biochemistry (Mosc.). 2019;84(3):190-204. doi: 10.1134/s0006297919030027
  119. Peshkova IO, Aghayev T, Fatkhullina AR, et al. IL-27 receptor-regulated stress myelopoiesis drives abdominal aortic aneurysm development. Nat Commun. 2019;10(1):5046. doi: 10.1038/s41467-019-13017-4
  120. He H, Xu P, Zhang X, et al. Aging-induced IL27Ra Signaling Impairs Hematopoietic Stem Cells. Blood. 2020; 9;136(2):183-198. doi: 10.1182/blood.2019003910
  121. Miura K, Saita E, Suzuki-Sugihara N, et al. Plasma interleukin-27 levels in patients with coronary artery disease. Medicine (Baltimore). 2017;96 (43), e8260. doi: 10.1097/md.0000000000008260
  122. Yousef H, Czupalla CJ, Lee D, et al. Aged blood impairs hippocampal neural precursor activity and activates microglia via brain endothelial cell VCAM1. Nat Med. 2019;25(6):988-1000. doi: 10.1038/s41591-019-0440-4
  123. Lee WJ, Chen LK, Liang CK, et al. Soluble ICAM-1, Independent of IL-6, Is Associated with Prevalent Frailty in Community-Dwelling Elderly Taiwanese People. PLoS One. 2016;11(6):e0157877. doi: 10.1371/journal.pone.0157877
  124. Gragnano F, Sperlongano S, Golia E, et al. The Role of von Willebrand Factor in Vascular Inflammation: From Pathogenesis to Targeted Therapy. Mediators Inflamm. 2017:5620314. doi: 10.1155/2017/5620314
  125. Wu MD, Atkinson TM, Lindner JR. Platelets and von Willebrand factor in atherogenesis. Blood. 2017;129 (11):1415-1419. doi: 10.1182/blood-2016-07-692673
  126. Prata L, Ovsyannikova IG, Tchkonia T, Kirkland JL. Senescent cell clearance by the immune system: Emerging therapeutic opportunities. Semin Immunol. 2018;40:101275. doi: 10.1016/j.smim.2019.04.003
  127. Chirco KR, Potempa LA. C-Reactive Protein As a Mediator of Complement Activation and Inflammatory Signaling in Age-Related Macular Degeneration. Front Immunol. 2018;9:539. doi: 10.3389/fimmu.2018.00539
  128. Lee S, Choe JW, Kim HK, Sung J. High-sensitivity C-reactive protein and cancer. J Epidemiol. 2011;21(3):161-168. doi: 10.2188/jea.je20100128
  129. Liao C, Gao W, Cao W, et al. Associations of Metabolic/Obesity Phenotypes with Insulin Resistance and C-Reactive Protein: Results from the CNTR. Study. Diabetes Metab Syndr Obes. 2021;14:1141-1151. doi: 10.2147/dmso.s298499
  130. Cui C, Sun J, Pawitan Y, et al. Creatinine and C-reactive protein in amyotrophic lateral sclerosis, multiple sclerosis and Parkinson's disease. Brain Commun. 2020;2 (2):fcaa152. doi: 10.1093/braincomms/fcaa152
  131. Foster MC, Inker LA, Levey AS, et al. Novel filtration markers as predictors of all-cause and cardiovascular mortality in US adults. Am J Kidney Dis. 2013;62(1):42-51. doi: 10.1053/j.ajkd.2013.01.016
  132. Liu ZY, Shen YY, Ji LJ, et al. Association between serum β2-microglobulin levels and frailty in an elderly Chinese population: results from RuLAS. Clin Interv Aging. 2017;12:1725-1729. doi: 10.2147/cia.s142507
  133. Rebo J, Mehdipour M, Gathwala R, et al. A single heterochronic blood exchange reveals rapid inhibition of multiple tissues by old blood. Nat Commun. 2016;7:13363. doi: 10.1038/ncomms13363
  134. Spencer ME, Jain A, Matteini A, et al. Serum levels of the immune activation marker neopterin change with age and gender and are modified by race, BMI, and percentage of body fat.J Gerontol A Biol Sci Med Sci. 2010;65(8): 858-865. doi: 10.1093/gerona/glq066
  135. Zhang B, Gems D. Gross ways to live long: Parasitic worms as an anti-inflammaging therapy? Elife. 2021;10. doi: 10.7554/eLife.65180
  136. Castellano JM, Mosher KI, Abbey RJ, et al. Human umbilical cord plasma proteins revitalize hippocampal function in aged mice. Nature. 2017;544(7651):488-492. doi: 10.1038/nature22067
  137. Luo H, Xiang Y, Qu X, et al. Apelin-13 Suppresses Neuroinflammation Against Cognitive Deficit in a Streptozotocin-Induced Rat Model of Alzheimer's Disease Through Activation of BDNF-TrkB Signaling Pathway. Front Pharmacol. 2019;10:395. doi: 10.3389/fphar.2019.00395
  138. Zhou H, Yang R, Wang W, et al. Fc-apelin fusion protein attenuates lipopolysaccharide-induced liver injury in mice. Scientific Reports. 2018;8(1):11428. doi: 10.1038/s41598-018-29491-7
  139. Guo Y, Li P, Gao L, et al. Kallistatin reduces vascular senescence and aging by regulating microRNA-34a-SIRT1 pathway. Aging Cell. 2017;16(4):837-846. doi: 10.1111/acel.12615
  140. Biran A, Zada L, Abou Karam P, et al. Quantitative identification of senescent cells in aging and disease. Aging Cell. 2017;16(4):661-671. doi: 10.1111/acel.12592
  141. Rasmussen LJH, Caspi A, Ambler A, et al. Association Between Elevated suPAR, a New Biomarker of Inflammation, and Accelerated Aging. J Gerontol A Biol Sci Med Sci. 2021;18;76(2):318-327. doi: 10.1093/gerona/glaa178
  142. Leng SX, McElhaney JE, Walston JD. ELISA and multiplex technologies for cytokine measurement in inflammation and aging research. J Gerontol A Biol Sci Med Sci. 2008;63(8): 879-884. doi: 10.1093/gerona/63.8.879
  143. Zhang S, Hu B, Xia X, et al. Highly Sensitive Detection of PCV2 Based on Tyramide Signals and GNPL Amplification. Molecules (Basel, Switzerland). 2019;24(23):4364. doi: 10.3390/molecules24234364
  144. Wang JY, Chen MH, Sheng ZC. Development of colloidal gold immunochromatographic signal-amplifying system for ultrasensitive detection of Escherichia coli O157:H7 in milk. RSC Advances. 2015;5(76):62300-62305. doi: 10.1039/c5ra13279g
  145. Sun W, Hu X, Liu J, et al. A novel multi-walled carbon nanotube-based antibody conjugate for quantitative and semi-quantitative lateral flow assays. Biosci Biotechnol Biochem. 2017;81(10): 1874-1882. doi: 10.1080/09168451.2017.1365590
  146. Ohmuro-Matsuyama Y, Ueda H. Homogeneous Noncompetitive Luminescent Immunodetection of Small Molecules by Ternary Protein Fragment Complementation. Anal Chem. 2018;90(5):3001-3004. doi: 10.1021/acs.analchem.7b05140
  147. Baraket A, Lee M, Zine N, et al. A fully integrated electrochemical biosensor platform fabrication process for cytokines detection. Biosens Bioelectron. 2017;93;170-175. doi: 10.1016/j.bios.2016.09.023
  148. Platchek M, Lu Q, Tran H, Xie W. Comparative Analysis of Multiple Immunoassays for Cytokine Profiling in Drug Discovery. SLAS Discov. 2020;25(10):1197-1213. doi: 10.1177/2472555220954389
  149. Lombardelli L, Logiodice F, Kullolli O, Piccinni M P. Evaluation of Secreted Cytokines by Multiplex Bead-Based Assay (X MAP Technology, Luminex). Methods Mol Biol. 2021;2285:121-130. doi: 10.1007/978-1-0716-1311-5_10
  150. Severins I, Szczepaniak M, Joo C. Multiplex Single-Molecule DNA Barcoding Using an Oligonucleotide Ligation Assay. Biophys J. 2018;115(6):957-967. doi: 10.1016/j.bpj.2018.08.013
  151. Zhang Y, Lai BS, Juhas M. Recent Advances in Aptamer Discovery and Applications. Molecules. 2019;24(5):941. doi: 10.3390/molecules24050941

Supplementary files

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2. Figure 1. The processes of the immune system aging. On the left – the young immune system, on the right – the immune system of the elderly.

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3. Figure 2. Conventional analytic methods of concentration and structure of proteins and/or metabolites. A. Enzyme immunoassay. B. Immunochromatic-graphical analysis. C. The method of bioluminescent protein-fragment complementation assay.

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4. Figure 3. Multiplex analysis of concentration and structure of proteins and/or metabolites.

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5. Figure 4. An example of the use of isotopes and fluorescent markers in the multiplex analysis of secreted interleukins by T helper cells.

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Copyright (c) 2021 Kurgan N.D., Panova E.I., Silakova L.V., Kaganskii A.M., Rybtsov S.A.

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