An expert consensus statement on biomarkers of ageing for use in intervention studies

Giorgia Perri; Chloe French; César Agostinis-Sobrinho; Atul Anand; Radiana Dhewayani Antarianto; Yasumichi Arai; Joseph A Baur; Omar Cauli; Morgane Clivaz-Duc; Giuseppe Colloca; Constantinos Demetriades; Chiara de Lucia; Giorgio Di Gessa; Breno S Diniz; Catherine L Dotchin; Gillian Eaglestone; Bradley T Elliott; Mark A Espeland; Luigi Ferrucci; James Fisher; Dimitris K Grammatopoulos; Novi S Hardiany; Zaki Hassan-Smith; Waylon J Hastings; Swati Jain; Peter K Joshi; Theodora Katsila; Graham J Kemp; Omid A Khaiyat; Dudley W Lamming; Jose Lara Gallegos; Frank Madeo; Andrea B Maier; Carmen Martin-Ruiz; Ian J Martins; John C Mathers; Lewis R Mattin; Reshma A Merchant; Alexey Moskalev; Ognian Neytchev; Mary Ni Lochlainn; Claire M Owen; Stuart M Phillips; Jedd Pratt; Konstantinos Prokopidis; Nicholas J W Rattray; María Rúa-Alonso; Lutz Schomburg; David Scott; Sangeetha Shyam; Elina Sillanpää; Michelle M C Tan; Ruth Teh; Stephanie W Tobin; Carolina J Vila-Chã; Luigi Vorluni; Daniela Weber; Ailsa Welch; Daisy Wilson; Thomas Wilson; Tongbiao Zhao; Elena Philippou; Viktor I Korolchuk; Oliver M Shannon

doi:10.1093/gerona/glae297

An expert consensus statement on biomarkers of ageing for use in intervention studies

Giorgia Perri, Chloe French, César Agostinis-Sobrinho, Atul Anand, Radiana Dhewayani Antarianto, Yasumichi Arai, Joseph A Baur, Omar Cauli, Morgane Clivaz-Duc, Giuseppe Colloca, Constantinos Demetriades, Chiara de Lucia, Giorgio Di Gessa, Breno S Diniz, Catherine L Dotchin, Gillian Eaglestone, Bradley T Elliott, Mark A Espeland, Luigi Ferrucci, James FisherDimitris K Grammatopoulos, Novi S Hardiany, Zaki Hassan-Smith, Waylon J Hastings, Swati Jain, Peter K Joshi, Theodora Katsila, Graham J Kemp, Omid A Khaiyat, Dudley W Lamming, Jose Lara Gallegos, Frank Madeo, Andrea B Maier, Carmen Martin-Ruiz, Ian J Martins, John C Mathers, Lewis R Mattin, Reshma A Merchant, Alexey Moskalev, Ognian Neytchev, Mary Ni Lochlainn, Claire M Owen, Stuart M Phillips, Jedd Pratt, Konstantinos Prokopidis, Nicholas J W Rattray, María Rúa-Alonso, Lutz Schomburg, David Scott, Sangeetha Shyam, Elina Sillanpää, Michelle M C Tan, Ruth Teh, Stephanie W Tobin, Carolina J Vila-Chã, Luigi Vorluni, Daniela Weber, Ailsa Welch, Daisy Wilson, Thomas Wilson, Tongbiao Zhao, Elena Philippou, Viktor I Korolchuk, Oliver M Shannon

Department of Life Sciences

Research output: Contribution to journal › Article › peer-review

Abstract

Biomarkers of ageing 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 ageing for use in intervention studies via the Delphi method. A three-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of ageing. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of ageing. 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 (e.g., insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (e.g., high sensitivity c-reactive protein, interleukin-6), functional (e.g., muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (e.g., DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of ageing which may be used as outcome measures in intervention studies. Future ageing research should identify which combination of these biomarkers has the greatest utility.

Original language	English
Journal	The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences
DOIs	https://doi.org/10.1093/gerona/glae297
Publication status	E-pub ahead of print - 21 Dec 2024

Keywords

delphi method
consensus
longevity

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1093/gerona/glae297

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Perri, G., French, C., Agostinis-Sobrinho, C., Anand, A., Antarianto, R. D., Arai, Y., Baur, J. A., Cauli, O., Clivaz-Duc, M., Colloca, G., Demetriades, C., de Lucia, C., Di Gessa, G., Diniz, B. S., Dotchin, C. L., Eaglestone, G., Elliott, B. T., Espeland, M. A., Ferrucci, L., ... Shannon, O. M. (2024). An expert consensus statement on biomarkers of ageing for use in intervention studies. The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. Advance online publication. https://doi.org/10.1093/gerona/glae297

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title = "An expert consensus statement on biomarkers of ageing for use in intervention studies",

abstract = "Biomarkers of ageing 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 ageing for use in intervention studies via the Delphi method. A three-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of ageing. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of ageing. 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 (e.g., insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (e.g., high sensitivity c-reactive protein, interleukin-6), functional (e.g., muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (e.g., DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of ageing which may be used as outcome measures in intervention studies. Future ageing research should identify which combination of these biomarkers has the greatest utility.",

keywords = "delphi method, consensus, longevity",

author = "Giorgia Perri and Chloe French and C{\'e}sar Agostinis-Sobrinho and Atul Anand and Antarianto, {Radiana Dhewayani} and Yasumichi Arai and Baur, {Joseph A} and Omar Cauli and Morgane Clivaz-Duc and Giuseppe Colloca and Constantinos Demetriades and {de Lucia}, Chiara and {Di Gessa}, Giorgio and Diniz, {Breno S} and Dotchin, {Catherine L} and Gillian Eaglestone and Elliott, {Bradley T} and Espeland, {Mark A} and Luigi Ferrucci and James Fisher and Grammatopoulos, {Dimitris K} and Hardiany, {Novi S} and Zaki Hassan-Smith and Hastings, {Waylon J} and Swati Jain and Joshi, {Peter K} and Theodora Katsila and Kemp, {Graham J} and Khaiyat, {Omid A} and Lamming, {Dudley W} and Gallegos, {Jose Lara} and Frank Madeo and Maier, {Andrea B} and Carmen Martin-Ruiz and Martins, {Ian J} and Mathers, {John C} and Mattin, {Lewis R} and Merchant, {Reshma A} and Alexey Moskalev and Ognian Neytchev and {Ni Lochlainn}, Mary and Owen, {Claire M} and Phillips, {Stuart M} and Jedd Pratt and Konstantinos Prokopidis and Rattray, {Nicholas J W} and Mar{\'i}a R{\'u}a-Alonso and Lutz Schomburg and David Scott and Sangeetha Shyam and Elina Sillanp{\"a}{\"a} and Tan, {Michelle M C} and Ruth Teh and Tobin, {Stephanie W} and Vila-Ch{\~a}, {Carolina J} and Luigi Vorluni and Daniela Weber and Ailsa Welch and Daisy Wilson and Thomas Wilson and Tongbiao Zhao and Elena Philippou and Korolchuk, {Viktor I} and Shannon, {Oliver M}",

year = "2024",

month = dec,

day = "21",

doi = "10.1093/gerona/glae297",

language = "English",

journal = "The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences",

issn = "1079-5006",

publisher = "Oxford University Press",

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Perri, G, French, C, Agostinis-Sobrinho, C, Anand, A, Antarianto, RD, Arai, Y, Baur, JA, Cauli, O, Clivaz-Duc, M, Colloca, G, Demetriades, C, de Lucia, C, Di Gessa, G, Diniz, BS, Dotchin, CL, Eaglestone, G, Elliott, BT, Espeland, MA, Ferrucci, L, Fisher, J, Grammatopoulos, DK, Hardiany, NS, Hassan-Smith, Z, Hastings, WJ, Jain, S, Joshi, PK, Katsila, T, Kemp, GJ, Khaiyat, OA, Lamming, DW, Gallegos, JL, Madeo, F, Maier, AB, Martin-Ruiz, C, Martins, IJ, Mathers, JC, Mattin, LR, Merchant, RA, Moskalev, A, Neytchev, O, Ni Lochlainn, M, Owen, CM, Phillips, SM, Pratt, J, Prokopidis, K, Rattray, NJW, Rúa-Alonso, M, Schomburg, L, Scott, D, Shyam, S, Sillanpää, E, Tan, MMC, Teh, R, Tobin, SW, Vila-Chã, CJ, Vorluni, L, Weber, D, Welch, A, Wilson, D, Wilson, T, Zhao, T, Philippou, E, Korolchuk, VI & Shannon, OM 2024, 'An expert consensus statement on biomarkers of ageing for use in intervention studies', The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences. https://doi.org/10.1093/gerona/glae297

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

PY - 2024/12/21

Y1 - 2024/12/21

N2 - Biomarkers of ageing 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 ageing for use in intervention studies via the Delphi method. A three-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of ageing. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of ageing. 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 (e.g., insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (e.g., high sensitivity c-reactive protein, interleukin-6), functional (e.g., muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (e.g., DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of ageing which may be used as outcome measures in intervention studies. Future ageing research should identify which combination of these biomarkers has the greatest utility.

AB - Biomarkers of ageing 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 ageing for use in intervention studies via the Delphi method. A three-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of ageing. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of ageing. 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 (e.g., insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (e.g., high sensitivity c-reactive protein, interleukin-6), functional (e.g., muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (e.g., DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of ageing which may be used as outcome measures in intervention studies. Future ageing research should identify which combination of these biomarkers has the greatest utility.

KW - delphi method

KW - consensus

KW - longevity

U2 - 10.1093/gerona/glae297

DO - 10.1093/gerona/glae297

M3 - Article

C2 - 39708300

SN - 1079-5006

JO - The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences

JF - The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences

ER -

An expert consensus statement on biomarkers of ageing for use in intervention studies

Abstract

Keywords

UN SDGs

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