TY - JOUR
T1 - A computational solution for bolstering reliability of epigenetic clocks
T2 - Implications for clinical trials and longitudinal tracking
AU - Higgins-Chen, Albert T
AU - Thrush, Kyra L
AU - Wang, Yunzhang
AU - Minteer, Christopher J
AU - Kuo, Pei-Lun
AU - Wang, Meng
AU - Niimi, Peter
AU - Sturm, Gabriel
AU - Lin, Jue
AU - Moore, Ann Zenobia
AU - Bandinelli, Stefania
AU - Vinkers, Christiaan H
AU - Vermetten, Eric
AU - Rutten, Bart P F
AU - Geuze, Elbert
AU - Okhuijsen-Pfeifer, Cynthia
AU - van der Horst, Marte Z
AU - Schreiter, Stefanie
AU - Gutwinski, Stefan
AU - Luykx, Jurjen J
AU - Picard, Martin
AU - Ferrucci, Luigi
AU - Crimmins, Eileen M
AU - Boks, Marco P
AU - Hägg, Sara
AU - Hu-Seliger, Tina T
AU - Levine, Morgan E
N1 - Funding Information:
This work was supported by the National Institutes of Health (NIH, National Institute on Aging (NIA): 1R01AG068285-01, 1R01AG065403-01A1 and 1R01AG057912-01 to M.E.L.) and National Institute of Mental Health (2T32MH019961-21A1 to A.H.C.). It was also supported by the Thomas P. Detre Fellowship Award in Translational Neuroscience Research from Yale University (to A.H.C.) and the Medical Informatics Fellowship Program at the West Haven, CT Veterans Healthcare Administration (to A.H.C.). The InCHIANTI study baseline (1998–2000) was supported as a ‘targeted project’ (ICS110.1/RF97.71) by the Italian Ministry of Health and in part by the US NIA (contract nos. 263 MD 9164 and 263 MD 821336). The InCHIANTI follow-up 2 and 3 studies (2004–2010) were financed by the US NIA (contract nos. N01-AG-5-0002). InCHIANTI was supported in part by the Intramural Research Program of the NIA, NIH, Baltimore, Maryland, and this work utilized the computational resources of the NIH HPC Biowulf cluster ( https://hpc.nih.gov/ ). The HRS study was supported by NIA grants R01 AG060110 and U01 AG009740. The SATSA study was supported by NIH grants R01 (AG04563, AG10175 and AG028555), the MacArthur Foundation Research Network on Successful Aging, the European Union’s Horizon 2020 research and innovation programme (no. 634821), the Swedish Council for Working Life and Social Research (FAS/FORTE) (97:0147:1B, 2009-0795 and 2013-2292) and the Swedish Research Council (825-2007-7460, 825-2009-6141, 521-2013-8689 and 2015-03255). The recruitment and assessments in the PRISMO study were funded by the Dutch Ministry of Defence. The longitudinal clozapine study was funded by a personal Rudolf Magnus Talent Fellowship (H150) grant (to J.J.L.). The Cellular Lifespan Study was supported by NIA grant R01AG066828 (to M.P.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We also acknowledge S. Horvath, A. Lu, G. Hannum and the many other colleagues who developed the original epigenetic clocks analyzed in this study.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2022/7
Y1 - 2022/7
N2 - Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.
AB - Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data, but this data can be surprisingly unreliable. Here we show technical noise produces deviations up to 9 years between replicates for six prominent epigenetic clocks, limiting their utility. We present a computational solution to bolster reliability, calculating principal components from CpG-level data as input for biological age prediction. Our retrained principal-component versions of six clocks show agreement between most replicates within 1.5 years, improved detection of clock associations and intervention effects, and reliable longitudinal trajectories in vivo and in vitro. This method entails only one additional step compared to traditional clocks, requires no replicates or prior knowledge of CpG reliabilities for training, and can be applied to any existing or future epigenetic biomarker. The high reliability of principal component-based clocks is critical for applications to personalized medicine, longitudinal tracking, in vitro studies, and clinical trials of aging interventions.
U2 - 10.1038/s43587-022-00248-2
DO - 10.1038/s43587-022-00248-2
M3 - Article
C2 - 36277076
SN - 2662-8465
VL - 2
SP - 644
EP - 661
JO - Nature aging
JF - Nature aging
IS - 7
ER -