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A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking

Albert T. Higgins-Chen, Kyra L. Thrush, Yunzhang Wang, Pei-Lun Kuo, Meng Wang, Christopher J. Minteer, Ann Zenobia Moore, Stefania Bandinelli, Christiaan H. Vinkers, Eric Vermetten, Bart P.F. Rutten, Elbert Geuze, Cynthia Okhuijsen-Pfeifer, Marte Z. van der Horst, Stefanie Schreiter, Stefan Gutwinski, Jurjen J. Luykx, Luigi Ferrucci, Eileen M. Crimmins, Marco P. Boks, Sara Hägg, Tina T. Hu-Seliger, Morgan E. Levine
doi: https://doi.org/10.1101/2021.04.16.440205
Albert T. Higgins-Chen
1Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
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  • For correspondence: a.higginschen@yale.edu
Kyra L. Thrush
2Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
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Yunzhang Wang
3Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Pei-Lun Kuo
4Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
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Meng Wang
2Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
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Christopher J. Minteer
5Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
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Ann Zenobia Moore
4Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
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Stefania Bandinelli
6Geriatric Unit, Azienda Sanitaria Toscana Centro, Florence, Italy
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Christiaan H. Vinkers
7Department of Psychiatry, Amsterdam University Medical Center, Amsterdam, The Netherlands
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Eric Vermetten
8Department Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
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Bart P.F. Rutten
9School for Mental Health and Neuroscience, Department of Psychiatry and Neuropsychology, Maastricht University Medical Centre, Maastricht, The Netherlands
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Elbert Geuze
10Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, The Netherlands
11Brain Research & Innovation Centre, Ministry of Defence, Utrecht, the Netherlands
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Cynthia Okhuijsen-Pfeifer
10Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, The Netherlands
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Marte Z. van der Horst
10Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, The Netherlands
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Stefanie Schreiter
12Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Stefan Gutwinski
12Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
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Jurjen J. Luykx
10Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, The Netherlands
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Luigi Ferrucci
4Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA
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Eileen M. Crimmins
13Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
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Marco P. Boks
10Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, The Netherlands
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Sara Hägg
3Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
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Tina T. Hu-Seliger
14Elysium Health, Inc, New York, NY, USA
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Morgan E. Levine
5Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
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  • For correspondence: a.higginschen@yale.edu
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Abstract

Epigenetic clocks are widely used aging biomarkers calculated from DNA methylation data. Unfortunately, measurements for individual CpGs can be surprisingly unreliable due to technical noise, and this may limit the utility of epigenetic clocks. We report that noise produces deviations up to 3 to 9 years between technical replicates for six major epigenetic clocks. The elimination of low-reliability CpGs does not ameliorate this issue. Here, we present a novel computational multi-step solution to address this noise, involving performing principal component analysis on the CpG-level data followed by biological age prediction using principal components as input. This method extracts shared systematic variation in DNAm while minimizing random noise from individual CpGs. Our novel principal-component versions of six clocks show agreement between most technical replicates within 0 to 1.5 years, equivalent or improved prediction of outcomes, and more stable trajectories in longitudinal studies and cell culture. This method entails only one additional step compared to traditional clocks, does not require prior knowledge of CpG reliabilities, and can improve the reliability of any existing or future epigenetic biomarker. The high reliability of principal component-based epigenetic clocks will make them particularly useful for applications in personalized medicine and clinical trials evaluating novel aging interventions.

Competing Interest Statement

The methodology described in this manuscript is the subject of a pending patent application for which MEL and AHC are named as inventors and Yale University is named as owner. MEL is a Scientific Advisor for, and receives consulting fees from, Elysium Health. MEL also holds licenses for epigenetic clocks that she has developed. All other authors report no biomedical financial interests or potential conflicts of interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted April 19, 2021.
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A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking
Albert T. Higgins-Chen, Kyra L. Thrush, Yunzhang Wang, Pei-Lun Kuo, Meng Wang, Christopher J. Minteer, Ann Zenobia Moore, Stefania Bandinelli, Christiaan H. Vinkers, Eric Vermetten, Bart P.F. Rutten, Elbert Geuze, Cynthia Okhuijsen-Pfeifer, Marte Z. van der Horst, Stefanie Schreiter, Stefan Gutwinski, Jurjen J. Luykx, Luigi Ferrucci, Eileen M. Crimmins, Marco P. Boks, Sara Hägg, Tina T. Hu-Seliger, Morgan E. Levine
bioRxiv 2021.04.16.440205; doi: https://doi.org/10.1101/2021.04.16.440205
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A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking
Albert T. Higgins-Chen, Kyra L. Thrush, Yunzhang Wang, Pei-Lun Kuo, Meng Wang, Christopher J. Minteer, Ann Zenobia Moore, Stefania Bandinelli, Christiaan H. Vinkers, Eric Vermetten, Bart P.F. Rutten, Elbert Geuze, Cynthia Okhuijsen-Pfeifer, Marte Z. van der Horst, Stefanie Schreiter, Stefan Gutwinski, Jurjen J. Luykx, Luigi Ferrucci, Eileen M. Crimmins, Marco P. Boks, Sara Hägg, Tina T. Hu-Seliger, Morgan E. Levine
bioRxiv 2021.04.16.440205; doi: https://doi.org/10.1101/2021.04.16.440205

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