A unified framework for systematic curation and evaluation of aging biomarkers

Kejun Ying; Seth Paulson; Alec Eames; Alexander Tyshkovskiy; Siyuan Li; Nir Eynon; Macsue Jacques; Robin Grolaux; Kirsten Seale; Erik Jacques; Ludger J. E. Goeminne; Andrea Cipriano; Martin Perez-Guevara; Mehrnoosh Emamifar; Maximiliano Casas Martínez; Dayoon Kwon; Anna Kosheleva; Michael Snyder; Dane Gobel; Chiara Herzog; Daniel L. McCartney; Riccardo E. Marioni; Jessica Lasky-Su; Jesse R. Poganik; Mahdi Moqri; Vadim N. Gladyshev

doi:10.1038/s43587-025-00987-y

A unified framework for systematic curation and evaluation of aging biomarkers

Kejun Ying, Seth Paulson, Alec Eames, Alexander Tyshkovskiy, Siyuan Li, Nir Eynon, Macsue Jacques, Robin Grolaux, Kirsten Seale, Erik Jacques, Ludger J. E. Goeminne, Andrea Cipriano, Martin Perez-Guevara, Mehrnoosh Emamifar, Maximiliano Casas Martínez, Dayoon Kwon, Anna Kosheleva, Michael Snyder, Dane Gobel, Chiara HerzogDaniel L. McCartney, Riccardo E. Marioni, Jessica Lasky-Su, Jesse R. Poganik, Mahdi Moqri^*, Vadim N. Gladyshev^*

^*Corresponding author for this work

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

Abstract

Aging biomarkers are essential tools for quantifying biological aging, but systematic validation has been hindered by methodological inconsistencies and fragmented datasets. Here we show that the ability of traditional aging clocks to predict chronological age does not correlate with mortality prediction capacity (R = 0.12, P = 0.67), suggesting that these metrics capture distinct biological processes. We developed Biolearn, an open-source framework enabling standardized evaluation of 39 biomarkers across over 20,000 individuals from diverse cohorts. The Horvath skin and blood clock achieved the highest chronological age accuracy (R ² = 0.88), while GrimAge2 demonstrated the strongest mortality association (hazard ratio = 2.57) and healthspan prediction (hazard ratio = 2.00). Our systematic evaluation reveals considerable heterogeneity in biomarker performance across different clinical outcomes, with optimal biomarkers varying according to specific application. Biolearn provides unified data processing pipelines with quality control and cell-type deconvolution capabilities, establishing a foundation for reproducible aging research and facilitating development of robust aging biomarkers.

Original language	English
Pages (from-to)	2323-2339
Journal	Nature Aging
Volume	5
Issue number	11
Early online date	4 Nov 2025
DOIs	https://doi.org/10.1038/s43587-025-00987-y
Publication status	Published - Nov 2025

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A Unified Framework for Systematic Curation and Evaluation of Aging BiomarkersAccepted author manuscript, 48.9 MB

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Cite this

Ying, K., Paulson, S., Eames, A., Tyshkovskiy, A., Li, S., Eynon, N., Jacques, M., Grolaux, R., Seale, K., Jacques, E., Goeminne, L. J. E., Cipriano, A., Perez-Guevara, M., Emamifar, M., Casas Martínez, M., Kwon, D., Kosheleva, A., Snyder, M., Gobel, D., ... Gladyshev, V. N. (2025). A unified framework for systematic curation and evaluation of aging biomarkers. Nature Aging, 5(11), 2323-2339. https://doi.org/10.1038/s43587-025-00987-y

@article{58215d1249c14c2ca07356b5ff3ec23e,

title = "A unified framework for systematic curation and evaluation of aging biomarkers",

abstract = "Aging biomarkers are essential tools for quantifying biological aging, but systematic validation has been hindered by methodological inconsistencies and fragmented datasets. Here we show that the ability of traditional aging clocks to predict chronological age does not correlate with mortality prediction capacity (R = 0.12, P = 0.67), suggesting that these metrics capture distinct biological processes. We developed Biolearn, an open-source framework enabling standardized evaluation of 39 biomarkers across over 20,000 individuals from diverse cohorts. The Horvath skin and blood clock achieved the highest chronological age accuracy (R 2 = 0.88), while GrimAge2 demonstrated the strongest mortality association (hazard ratio = 2.57) and healthspan prediction (hazard ratio = 2.00). Our systematic evaluation reveals considerable heterogeneity in biomarker performance across different clinical outcomes, with optimal biomarkers varying according to specific application. Biolearn provides unified data processing pipelines with quality control and cell-type deconvolution capabilities, establishing a foundation for reproducible aging research and facilitating development of robust aging biomarkers.",

author = "Kejun Ying and Seth Paulson and Alec Eames and Alexander Tyshkovskiy and Siyuan Li and Nir Eynon and Macsue Jacques and Robin Grolaux and Kirsten Seale and Erik Jacques and Goeminne, \{Ludger J. E.\} and Andrea Cipriano and Martin Perez-Guevara and Mehrnoosh Emamifar and \{Casas Mart{\'i}nez\}, Maximiliano and Dayoon Kwon and Anna Kosheleva and Michael Snyder and Dane Gobel and Chiara Herzog and McCartney, \{Daniel L.\} and Marioni, \{Riccardo E.\} and Jessica Lasky-Su and Poganik, \{Jesse R.\} and Mahdi Moqri and Gladyshev, \{Vadim N.\}",

year = "2025",

month = nov,

doi = "10.1038/s43587-025-00987-y",

language = "English",

volume = "5",

pages = "2323--2339",

journal = "Nature Aging",

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Ying, K, Paulson, S, Eames, A, Tyshkovskiy, A, Li, S, Eynon, N, Jacques, M, Grolaux, R, Seale, K, Jacques, E, Goeminne, LJE, Cipriano, A, Perez-Guevara, M, Emamifar, M, Casas Martínez, M, Kwon, D, Kosheleva, A, Snyder, M, Gobel, D, Herzog, C, McCartney, DL, Marioni, RE, Lasky-Su, J, Poganik, JR, Moqri, M & Gladyshev, VN 2025, 'A unified framework for systematic curation and evaluation of aging biomarkers', Nature Aging, vol. 5, no. 11, pp. 2323-2339. https://doi.org/10.1038/s43587-025-00987-y

TY - JOUR

T1 - A unified framework for systematic curation and evaluation of aging biomarkers

AU - Ying, Kejun

AU - Paulson, Seth

AU - Eames, Alec

AU - Tyshkovskiy, Alexander

AU - Li, Siyuan

AU - Eynon, Nir

AU - Jacques, Macsue

AU - Grolaux, Robin

AU - Seale, Kirsten

AU - Jacques, Erik

AU - Goeminne, Ludger J. E.

AU - Cipriano, Andrea

AU - Perez-Guevara, Martin

AU - Emamifar, Mehrnoosh

AU - Casas Martínez, Maximiliano

AU - Kwon, Dayoon

AU - Kosheleva, Anna

AU - Snyder, Michael

AU - Gobel, Dane

AU - Herzog, Chiara

AU - McCartney, Daniel L.

AU - Marioni, Riccardo E.

AU - Lasky-Su, Jessica

AU - Poganik, Jesse R.

AU - Moqri, Mahdi

AU - Gladyshev, Vadim N.

PY - 2025/11

Y1 - 2025/11

N2 - Aging biomarkers are essential tools for quantifying biological aging, but systematic validation has been hindered by methodological inconsistencies and fragmented datasets. Here we show that the ability of traditional aging clocks to predict chronological age does not correlate with mortality prediction capacity (R = 0.12, P = 0.67), suggesting that these metrics capture distinct biological processes. We developed Biolearn, an open-source framework enabling standardized evaluation of 39 biomarkers across over 20,000 individuals from diverse cohorts. The Horvath skin and blood clock achieved the highest chronological age accuracy (R 2 = 0.88), while GrimAge2 demonstrated the strongest mortality association (hazard ratio = 2.57) and healthspan prediction (hazard ratio = 2.00). Our systematic evaluation reveals considerable heterogeneity in biomarker performance across different clinical outcomes, with optimal biomarkers varying according to specific application. Biolearn provides unified data processing pipelines with quality control and cell-type deconvolution capabilities, establishing a foundation for reproducible aging research and facilitating development of robust aging biomarkers.

AB - Aging biomarkers are essential tools for quantifying biological aging, but systematic validation has been hindered by methodological inconsistencies and fragmented datasets. Here we show that the ability of traditional aging clocks to predict chronological age does not correlate with mortality prediction capacity (R = 0.12, P = 0.67), suggesting that these metrics capture distinct biological processes. We developed Biolearn, an open-source framework enabling standardized evaluation of 39 biomarkers across over 20,000 individuals from diverse cohorts. The Horvath skin and blood clock achieved the highest chronological age accuracy (R 2 = 0.88), while GrimAge2 demonstrated the strongest mortality association (hazard ratio = 2.57) and healthspan prediction (hazard ratio = 2.00). Our systematic evaluation reveals considerable heterogeneity in biomarker performance across different clinical outcomes, with optimal biomarkers varying according to specific application. Biolearn provides unified data processing pipelines with quality control and cell-type deconvolution capabilities, establishing a foundation for reproducible aging research and facilitating development of robust aging biomarkers.

U2 - 10.1038/s43587-025-00987-y

DO - 10.1038/s43587-025-00987-y

M3 - Article

SN - 2662-8465

VL - 5

SP - 2323

EP - 2339

JO - Nature Aging

JF - Nature Aging

IS - 11

ER -

A unified framework for systematic curation and evaluation of aging biomarkers

Abstract

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Stratifying Resilience and Depression Longitudinally

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