2018/12/01 by J. Mitteldorf, Josh Mitteldorf
Biochemistry, Genetics and Molecular Biology · Medicine · Psychology · #Bottleneck #Business #Computer science #Data science #Epigenetics and DNA Methylation #Genetics, Aging, and Longevity in Model Organisms #Gerontology #Life expectancy #Medicine #Psychological intervention #Psychology #Risk analysis (engineering) #Successful aging
paper · doi:10.1134/s000629791812009x
crossref issued 2018/12/01 · crossref published 2018/12/01 · crossref published-print 2018/12/01 · openalex publication_date 2018/12/01 · crossref published-online 2019/02/08 · crossref created 2019/02/08 · openalex created_date 2025/10/10 · crossref deposited 2026/03/16 · crossref indexed 2026/07/29 · openalex updated_date 2026/08/01
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.