Perri Giorgia, French Chloe, Agostinis-Sobrinho César, Anand Atul, Antarianto Radiana Dhewayani, Arai Yasumichi, Baur Joseph A, Cauli Omar, Clivaz-Duc Morgane, Colloca Giuseppe, Demetriades Constantinos, de Lucia Chiara, Di Gessa Giorgio, Diniz Breno S, Dotchin Catherine L, Eaglestone Gillian, Elliott Bradley T, Espeland Mark A, Ferrucci Luigi, Fisher James, Grammatopoulos Dimitris K, Hardiany Novi S, Hassan-Smith Zaki, Hastings Waylon J, Jain Swati, Joshi Peter K, Katsila Theodora, Kemp Graham J, Khaiyat Omid A, Lamming Dudley W, Gallegos Jose Lara, Madeo Frank, Maier Andrea B, Martin-Ruiz Carmen, Martins Ian J, Mathers John C, Mattin Lewis R, Merchant Reshma A, Moskalev Alexey, Neytchev Ognian, Ni Lochlainn Mary, Owen Claire M, Phillips Stuart M, Pratt Jedd, Prokopidis Konstantinos, Rattray Nicholas J W, Rúa-Alonso María, Schomburg Lutz, Scott David, Shyam Sangeetha, Sillanpää Elina, Tan Michelle M C, Teh Ruth, Tobin Stephanie W, Vila-Chã Carolina J, Vorluni Luigi, Weber Daniela, Welch Ailsa, Wilson Daisy, Wilson Thomas, Zhao Tongbiao, Philippou Elena, Korolchuk Viktor I, Shannon Oliver M
Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.
School of Health Sciences, University of Manchester, Manchester, UK.
J Gerontol A Biol Sci Med Sci. 2025 Apr 7;80(5). doi: 10.1093/gerona/glae297.
Biomarkers of aging serve as important outcome measures in longevity-promoting interventions. However, there is limited consensus on which specific biomarkers are most appropriate for human intervention studies. This work aimed to address this need by establishing an expert consensus on biomarkers of aging for use in intervention studies via the Delphi method. A 3-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of aging. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of aging. Panel members could abstain from voting on biomarkers outside their expertise. Consensus was reached when there was ≥70% agreement on a statement/biomarker. Of the 460 international panel members invited to participate, 116 completed Round 1, 87 completed Round 2, and 60 completed Round 3. Across the 3 rounds, 14 biomarkers met consensus that spanned physiological (eg, insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (eg, high sensitivity C-reactive protein, interleukin-6), functional (eg, muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (eg, DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of aging which may be used as outcome measures in intervention studies. Future aging research should identify which combination of these biomarkers has the greatest utility.
衰老生物标志物是促进长寿干预措施中的重要结果指标。然而,对于哪些特定生物标志物最适合用于人体干预研究,目前尚无定论。这项工作旨在通过德尔菲法就用于干预研究的衰老生物标志物达成专家共识,以满足这一需求。使用在线平台进行了三轮德尔菲研究。在第一轮中,专家小组成员为衰老候选生物标志物提供了建议。在第二轮和第三轮中,他们就与20种衰老生物标志物相关的500条初始陈述(是/否)进行投票。小组成员可对其专业领域之外的生物标志物弃权投票。当对某一陈述/生物标志物的同意率≥70%时,即达成共识。在受邀参与的460名国际小组成员中,116人完成了第一轮,87人完成了第二轮,60人完成了第三轮。在这三轮中,有14种生物标志物达成了共识,涵盖生理(如胰岛素样生长因子1、生长分化因子-15)、炎症(如高敏C反应蛋白、白细胞介素-6)、功能(如肌肉量、肌肉力量、握力、定时起立行走测试、步速、站立平衡测试、衰弱指数、认知健康、血压)和表观遗传(如DNA甲基化/表观遗传时钟)领域。专家共识确定了14种潜在的衰老生物标志物,可作为干预研究的结果指标。未来的衰老研究应确定这些生物标志物的哪些组合具有最大效用。