TY - JOUR
T1 - An expert consensus statement on biomarkers of ageing for use in intervention studies
AU - Perri, Giorgia
AU - French, Chloe
AU - Agostinis-Sobrinho, César
AU - Anand, Atul
AU - Antarianto, Radiana Dhewayani
AU - Arai, Yasumichi
AU - Baur, Joseph A.
AU - Cauli, Omar
AU - Clivaz-Duc, Morgane
AU - Colloca, Giuseppe
AU - Demetriades, Constantinos
AU - de Lucia, Chiara
AU - Di Gessa, Giorgio
AU - Diniz, Breno S.
AU - Dotchin, Catherine L.
AU - Eaglestone, Gillian
AU - Elliott, Bradley T.
AU - Espeland, Mark A.
AU - Ferrucci, Luigi
AU - Fisher, James
AU - Grammatopoulos, Dimitris K.
AU - Hardiany, Novi S.
AU - Hassan-Smith, Zaki
AU - Hastings, Waylon J.
AU - Jain, Swati
AU - Joshi, Peter K.
AU - Katsila, Theodora
AU - Kemp, Graham J.
AU - Khaiyat, Omid A.
AU - Lamming, Dudley W.
AU - Gallegos, Jose Lara
AU - Madeo, Frank
AU - Maier, Andrea B.
AU - Martin-Ruiz, Carmen
AU - Martins, Ian J.
AU - Mathers, John C.
AU - Mattin, Lewis R.
AU - Merchant, Reshma A.
AU - Moskalev, Alexey
AU - Neytchev, Ognian
AU - Ni Lochlainn, Mary
AU - Owen, Claire M.
AU - Phillips, Stuart M.
AU - Pratt, Jedd
AU - Prokopidis, Konstantinos
AU - Rattray, Nicholas J. W.
AU - Rúa-Alonso, María
AU - Schomburg, Lutz
AU - Scott, David
AU - Shyam, Sangeetha
AU - Sillanpää, Elina
AU - Tan, Michelle M. C.
AU - Teh, Ruth
AU - Tobin, Stephanie W.
AU - Vila-Chã, Carolina J.
AU - Vorluni, Luigi
AU - Weber, Daniela
AU - Welch, Ailsa
AU - Wilson, Daisy
AU - Wilson, Thomas
AU - Zhao, Tongbiao
AU - Philippou, Elena
AU - Korolchuk, Viktor I.
AU - Shannon, Oliver M.
N1 - Data Availability Statement: The data can be made available upon request and any further inquiries can be directed to the corresponding author, Giorgia Perri.
Funding Information: This work was supported by the UK Research and Innovation (UKRI) funded AGEing and Nutrient Sensing (AGENTS) Network, UKRI’s Biotechnology and Biological Sciences Research Council (BBSRC), and the Medical Research Council (MRC). The study team (GP, CF, EP, VIK, OMS) was brought together to generate the study ideas by the meetings hosted by the same network.
PY - 2025/5
Y1 - 2025/5
N2 - 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.
AB - 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.
KW - Consensus
KW - Delphi method
KW - Longevity
UR - http://www.scopus.com/inward/record.url?scp=105003168957&partnerID=8YFLogxK
U2 - 10.1093/gerona/glae297
DO - 10.1093/gerona/glae297
M3 - Article
SN - 1079-5006
VL - 80
JO - The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences
JF - The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences
IS - 5
M1 - glae297
ER -
