{"title":"First-generation versus next-generation epigenetic aging clocks: Differences in performance and utility.","authors":"Adiv A Johnson, Maxim N Shokhirev","doi":"10.1007/s10522-025-10265-4","DOIUrl":null,"url":null,"abstract":"<p><p>Aging biomarkers that predict age given methylomic data are referred to as epigenetic aging clocks. While the earliest, first-generation clocks were exclusively trained to predict chronological age, more recent next-generation models have been explicitly trained to associate with health, lifestyle, and/or age-related outcomes. Although these next-generation models have been trained using distinct approaches and techniques, existing evidence indicates that they associate with a greater number of health and disease signals than first-generation clocks. Moreover, they are often more predictive of age-related outcomes and appear more responsive to interventions. In this work, we provide definitions for first- versus next-generation clocks and discuss the potential merits of further dividing next-generation clocks into sub-categories. In addition, we summarize existing next-generation epigenetic aging clocks, including how they were trained and how they can be accessed. Given the relative value of interventional data over observational data, we comprehensively tabulate existing literature documenting the ability of an intervention to influence at least one epigenetic aging clock. While we acknowledge that the decision to a use a specific clock is ultimately dependent on the research application and goal, current evidence suggests that next-generation models should be generally prioritized for health-oriented association and interventional studies.</p>","PeriodicalId":8909,"journal":{"name":"Biogerontology","volume":"26 4","pages":"121"},"PeriodicalIF":4.4000,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biogerontology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10522-025-10265-4","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GERIATRICS & GERONTOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Aging biomarkers that predict age given methylomic data are referred to as epigenetic aging clocks. While the earliest, first-generation clocks were exclusively trained to predict chronological age, more recent next-generation models have been explicitly trained to associate with health, lifestyle, and/or age-related outcomes. Although these next-generation models have been trained using distinct approaches and techniques, existing evidence indicates that they associate with a greater number of health and disease signals than first-generation clocks. Moreover, they are often more predictive of age-related outcomes and appear more responsive to interventions. In this work, we provide definitions for first- versus next-generation clocks and discuss the potential merits of further dividing next-generation clocks into sub-categories. In addition, we summarize existing next-generation epigenetic aging clocks, including how they were trained and how they can be accessed. Given the relative value of interventional data over observational data, we comprehensively tabulate existing literature documenting the ability of an intervention to influence at least one epigenetic aging clock. While we acknowledge that the decision to a use a specific clock is ultimately dependent on the research application and goal, current evidence suggests that next-generation models should be generally prioritized for health-oriented association and interventional studies.
期刊介绍:
The journal Biogerontology offers a platform for research which aims primarily at achieving healthy old age accompanied by improved longevity. The focus is on efforts to understand, prevent, cure or minimize age-related impairments.
Biogerontology provides a peer-reviewed forum for publishing original research data, new ideas and discussions on modulating the aging process by physical, chemical and biological means, including transgenic and knockout organisms; cell culture systems to develop new approaches and health care products for maintaining or recovering the lost biochemical functions; immunology, autoimmunity and infection in aging; vertebrates, invertebrates, micro-organisms and plants for experimental studies on genetic determinants of aging and longevity; biodemography and theoretical models linking aging and survival kinetics.