Advertisement

Biochemistry (Moscow)

, Volume 83, Issue 12–13, pp 1517–1523 | Cite as

An Incipient Revolution in the Testing of Anti-aging Strategies

  • J. MitteldorfEmail author
Article
First Online:
  • 1 Downloads

Abstract

Recent advances in the technology of “aging clocks” based on DNA methylation suggest that it may soon be possible to measure changes in the rate of human aging over periods as short as a year or two. If this potential is realized, the testing of putative anti–aging interventions will become radically cheaper and faster. This should prompt a re–appraisal of the entire spectrum of methods for evaluating anti–aging technologies in humans and in model systems. In the body of this article, I will argue that (1) testing, not development, is the bottleneck in the flow of knowledge about human anti–aging; (2) single interventions are unlikely to afford major increments in life expectancy in humans; (3) interactions among combinations of known anti–aging interventions are the most important unknown in the field; (4) the daunting number of combinations may be tamed by enrolling large numbers of early adopters who are already using diverse combinations of strategies; (5) the newest methylation clock, called “DNAm PhenoAge” (Levine, M., et al. (2018) Aging (Albany), 10, 573–591) has the potential to tell us which of these people are best succeeding in their quest to slow the aging clock; (6) further optimization of this clock, specialized to the proposed application, is feasible; and (7) multivariate statistics can be used to efficiently identify the best combinations of known interventions that are already being deployed by members of the community which actively seeks to enhance their long–term health. The integration of these ideas leads to a proposal for a human trial crowd–funded largely by the subjects, organized around a web site, as well as standardization of individual record–keeping and an open–source database of methylation results before and after.

Keywords

methylation epigenetic clock anti–aging testing 
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Barzilai, N., Crandall, J. P., Kritchevsky, S. B., and Espeland, M. A. (2016) Metformin as a tool to target aging, Cell Metab., 23, 1060–1065.CrossRefGoogle Scholar
  2. 2.
    Knowler, W. C., Barrett–Connor, E., Fowler, S. E., Hamman, R. F., Lachin, J. M., Walker, E. A., Nathan, D. M., and Diabetes Prevention Program Research Group (2002) Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin, N. Engl. J. Med., 346, 393–403.CrossRefGoogle Scholar
  3. 3.
    Aronson, M. K., Ooi, W. L., Geva, D. L., Masur, D., Blau, A., and Frishman, W. (1991) Dementia: age–dependent incidence, prevalence, and mortality in the old old, Arch. Intern. Med., 151, 989–992.Google Scholar
  4. 4.
    Mattison, J. A., Roth, G. S., Beasley, T. M., Tilmont, E. M., Handy, A. M., Herbert, R. L., Longo, D. L., Allison, D. B., Young, J. E., Bryant, M., Barnard, D., Ward, W. F., Qi, W., Ingram, D. K., and de Cabo, R. (2012) Impact of caloric restriction on health and survival in rhesus monkeys from the NIA study, Nature, 489, 318–321.CrossRefGoogle Scholar
  5. 5.
    Colman, R. J., Beasleu, T. M., Kemnitz, J. W., Johnson, S. C., Weindruch, R., and Anderson, R. M. (2014) Caloric restriction reduces age–related and all–cause mortality in rhesus monkeys, Nat. Commun., 5, 3557.CrossRefGoogle Scholar
  6. 6.
    Antithrombotic Trialists’ Collaboration (2002) Collabo–rative meta–analysis of randomised trials of antiplatelet therapy for prevention of death, myocardial infarction, and stroke in high risk patients, BMJ, 324, 71–86.Google Scholar
  7. 7.
    Bannister, C. A., Holden, S. E., Jenkins–Jones, S., Morgan, C. L., Halsox, J. P., Schernthaner, G., Mukherjea, J., and Currie, C. J. (2014) Can people with type 2 diabetes live longer than those without? A comparison of mortality in people initiated with metformin or sulphonylurea monotherapy and matched, non–diabetic controls, Diabetes Obes. Metab., 16, 1165–1173.CrossRefGoogle Scholar
  8. 8.
    Schork, N. J. (2015) Personalized medicine: time for one–person trials, Nature, 520, 609–611.CrossRefGoogle Scholar
  9. 9.
    Levine, M. E., Lu, A. T., Quach, A., Chen, B. H., Assimer, T. L., Bandinelli, S., Hou, L., Baccarelli, A. A., Stewart, J. D., Li, J., Whitsel, E. A., Wilson, J. G., Reiner, A. P., Aviv, A., Lohman, K., Liu, Y., Ferrucci, L., and Horvath, S. (2018) An epigenetic biomarker of aging for lifespan and healthspan, Aging (Albany NY), 10, 573–591.CrossRefGoogle Scholar
  10. 10.
    Horvath, S. (2013) DNA methylation age of human tissues and cell types, Genome Biol., 14, R115.CrossRefGoogle Scholar
  11. 11.
    Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J. B., Gao, Y., Deconde, R., Chen, M., Rajapakse, I., Friend, S., Ideker, T., and Zhang, K. (2013) Genome–wide methylation profiles reveal quantitative views of human aging rates, Mol. Cell, 49, 359–367.CrossRefGoogle Scholar
  12. 12.
    Moskalev, A., Chernyagina, E., de Magalhaes, J. P., Barardo, D., Thoppil, H., Shaposhnikov, M., Budovsky, A., Fraifeld, V. E., Garazha, A., Tsvetkov, V., Bronovitsky, E., Bogomolov, V., Scerbacov, A., Kuryan, O., Gurinovich, R., Jellen, L. C., Kennedy, B., Mamoshina, P., Dobrovolskaya, E., Aliper, A., Kaminsky, D., and Zhavoronkov, A. (2015) Geroprotectors.org: a new, structured and curated database of current therapeutic interventions in aging and age–related disease, Aging (Albany NY), 7, 616–628.Google Scholar
  13. 13.
    Anisimov, V. N. (2008) Pineal gland, biorhythms and aging of an organism, Usp. Fiziol. Nauk, 39, 40–65.Google Scholar
  14. 14.
    Anisimov, V. N., and Khavinson, V. K. (2010) Peptide bioregulation of aging: results and prospects, Biogerontology, 11, 139–149.CrossRefGoogle Scholar
  15. 15.
    Singh, A. K., Garg, G., Singh, S., and Rizvi, S. I. (2017) Synergistic effect of rapamycin and metformin against age–dependent oxidative stress in rat erythrocyte, Rejuvenation Res., 20, 420–429.CrossRefGoogle Scholar
  16. 16.
    Blagosklonny, M. V. (2017) From rapalogs to anti–aging formula, Oncotarget, 8, 35492–35507.CrossRefGoogle Scholar
  17. 17.
    Teschendorff, A. E., Menon, U., Gentry–Maharaj, A., Ramus, S. J., Weisenberger, D. J., Shen, H., Campan, M., Noushmehr, H., Bell, C. G., Maxwell, A. P., Savage, D. A., Mueller–Holzner, E., Marth, C., Kocjan, G., Gayther, S. A., Jones, A., Beck, S., Wagner, W., Laird, P. W., Jacobs, I. J., and Widschwendter, M. (2010) Age–dependent DNA methylation of genes that are suppressed in stem cells is a hallmark of cancer, Genome Res., 20, 440–446.CrossRefGoogle Scholar
  18. 18.
    Pidsley, R., Zotenko, E., Peters, T. J., Lawrence, M. G., Risbridger, G. P., Molloy, P., Van Djik, S., Muhlhausler, B., Stirzaker, C., and Clark, S. J. (2016) Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole–genome DNA methylation profiling, Genome Biol., 17,208.CrossRefGoogle Scholar
  19. 19.
    Chen, B. H., Marioni, R. E., Colicino, E., Peters, M. J., Ward–Caviness, C. K., Tsai, P. C., Roetker, N. S., Just, A. C., Demerath, E. W., Guan, W., Bressler, J., Fornage, M., Studenski, S., Vandiver, A. R., Moore, A. Z., Tanaka, T., Kiel, D. P., Liang, L., Vokonas, P., Schwartz, J., Lunetta, K. L., Murabito, J. M., Bandinelli, S., Hernandez, D. G., Melzer, D., Nalls, M., Pilling, L. C., Price, T. R., Singleton, A. B., Gieger, C., Holle, R., Kretschmer, A., Kronenberg, F., Kunze, S., Linseisen, J., Meisinger, C., Rathmann, W., Waldenberger, M., Visscher, P. M., Shah, S., Wray, N. R., McRae, A. F., Franco, O. H., Hofman, A., Uitterlinden, A. G., Absher, D., Assimes, T., Levine, M. E., Lu, A. T., Tsao, P. S., Hou, L., Manson, J. E., Carty, C. L., LaCroix, A. Z., Reiner, A. P., Spector, T. D., Feinberg, A. P., Levy, D., Baccarelli, A., van Meurs, J., Bell, J. T., Peters, A., Deary, I. J., Pankow, J. S., Ferrucci, L., and Horvath, S. (2016) DNA methylation–based measures of biological age: meta–analysis predicting time to death, Aging (Albany NY), 8, 1844–1859.CrossRefGoogle Scholar
  20. 20.
    Horvath, S., and Raj, K. (2018) DNA methylation–based biomarkers and the epigenetic clock theory of ageing, Nat. Rev. Genet., 19, 371–384.CrossRefGoogle Scholar
  21. 21.
    Horvath, S., and Ritz, B. R. (2015) Increased epigenetic age and granulocyte counts in the blood of Parkinson’s disease patients, Aging (Albany NY), 7, 1130–1142.CrossRefGoogle Scholar
  22. 22.
    Stolzel, F., Brosch, M., Horvath, S., Kramer, M., Thiede, C., von Bonin, M., Ammerpohl, O., Middeke, M., Schetelig, J., Ehninger, G., Hampe, J., and Bornhauser, M. (2017) Dynamics of epigenetic age following hematopoietic stem cell transplantation, Haematologica, 102, e321–e323.CrossRefGoogle Scholar
  23. 23.
    Goldberg, A. D., Allis, C. D., and Bernstein, E. (2007) Epigenetics: a landscape takes shape, Cell, 128, 635–638.CrossRefGoogle Scholar
  24. 24.
    Murgatroyd, C., and Spengler, D. (2011) Epigenetics of early child development, Front. Psychiatry, 2, doi: 10.3389/fpsyt.2011.00016.Google Scholar
  25. 25.
    De Magalhaes, J. P. (2012) Programmatic features of aging originating in development: aging mechanisms beyond molecular damage? FASEB J., 26, 4821–4826.CrossRefGoogle Scholar
  26. 26.
    Rando, T. A., and Chang, H. Y. (2012) Aging, rejuvenation, and epigenetic reprogramming: resetting the aging clock, Cell, 148, 46–57.Google Scholar
  27. 27.
    Blagosklonny, M. V. (2006) Aging and immortality: quasi-programmed senescence and its pharmacologic inhibition, Cell Cycle, 5, 2087–2102.CrossRefGoogle Scholar
  28. 28.
    Johnson, A. A., Akman, K., Calimport, S. R., Wuttke, D., Stolzing, A., and de Magalhaes, J. P. (2012) The role of DNA methylation in aging, rejuvenation, and age–related disease, Rejuvenation Res., 15, 483–494.CrossRefGoogle Scholar
  29. 29.
    Mitteldorf, J. (2013) How does the body know how old it is? Introducing the epigenetic clock hypothesis, Biochemistry (Moscow), 78, 1048–1053.CrossRefGoogle Scholar
  30. 30.
    Smith, Z. D., and Meissner, A. (2013) DNA methylation: roles in mammalian development, Nat. Rev. Genet., 14, 204–220.CrossRefGoogle Scholar
  31. 31.
    Mitteldorf, J. (2016) An epigenetic clock controls aging, Biogerontology, 17, 257–265.CrossRefGoogle Scholar
  32. 32.
    Blagosklonny, M. V., and Hall, M. N. (2009) Growth and aging: a common molecular mechanism, Aging (Albany NY), 1, 357–362.CrossRefGoogle Scholar
  33. 33.
    Katcher, H. L. (2013) Studies that shed new light on aging, Biochemistry (Moscow), 78, 1061–1070.CrossRefGoogle Scholar
  34. 34.
    Conboy, M. J., Conboy, I. M., and Rando, T. A. (2013) Heterochronic parabiosis: historical perspective and methodological considerations for studies of aging and longevity, Aging Cell, 12, 525–530.CrossRefGoogle Scholar
  35. 35.
    Rebo, J., Mehdipour, M., Gathwala, R., Causey, K., Liu, Y., Conboy, M. J., and Conboy, I. M. (2016) A single hete–rochronic blood exchange reveals rapid inhibition of multiple tissues by old blood, Nat. Commun., 7, 13363.CrossRefGoogle Scholar
  36. 36.
    Mendelsohn, A. R., and Larrick, J. W. (2017) Epigenetic drift is a determinant of mammalian lifespan, Rejuvenation Res., 20, 430–436.CrossRefGoogle Scholar
  37. 37.
    Horvath, S., Erhart, W., Brosch, M., Ammerpohl, O., von Schonfels, W., Ahrens, M., Heits, N., Bell, J. T., Tsai, P. C., Spector, T. D., Deloukas, P., Siebert, R., Sipos, B., Becker, T., Rocken, C., Schafmayer, C., and Hampe, J. (2014) Obesity accelerates epigenetic aging of human liver, Proc. Natl. Acad. Sci. USA, 111, 15538–15543.CrossRefGoogle Scholar
  38. 38.
    Petkovich, D. A., Podolskiy, D. I., Lobanov, A. V., Lee, S. G., Miller, R. A., and Gladyshev, V. N. (2017) Using DNA methylation profiling to evaluate biological age and longevity interventions, 25, 954–960.Google Scholar

Copyright information

© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  1. 1.School of MedicineWashington University of St. LouisSt. LouisUSA
  2. 2.National Institute of Biological SciencesBeijingChina

Personalised recommendations

Cite article

Buy options