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An epigenetic predictor of death captures multi-modal measures of brain health

Robert F. Hillary, Anna J. Stevenson, Simon R. Cox, Daniel L. McCartney, Sarah E. Harris, Anne Seeboth, Jon Higham, Duncan Sproul, Adele M. Taylor, Paul Redmond, Janie Corley, Alison Pattie, Maria del. C Valdés Hernández, Susana Muñoz-Maniega, Mark E. Bastin, Joanna M. Wardlaw, Steve Horvath, Craig W. Ritchie, Tara L. Spires-Jones, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, Riccardo E. Marioni
doi: https://doi.org/10.1101/703504
Robert F. Hillary
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Anna J. Stevenson
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Simon R. Cox
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
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Daniel L. McCartney
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Sarah E. Harris
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
3Department of Psychology, University of Edinburgh, Edinburgh
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Anne Seeboth
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Jon Higham
4Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Duncan Sproul
4Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
5Edinburgh Cancer Research Centre, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Adele M. Taylor
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
3Department of Psychology, University of Edinburgh, Edinburgh
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Paul Redmond
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
3Department of Psychology, University of Edinburgh, Edinburgh
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Janie Corley
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
3Department of Psychology, University of Edinburgh, Edinburgh
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Alison Pattie
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
3Department of Psychology, University of Edinburgh, Edinburgh
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Maria del. C Valdés Hernández
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
6Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh
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Susana Muñoz-Maniega
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
6Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh
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Mark E. Bastin
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
6Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh
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Joanna M. Wardlaw
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
6Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh
10UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh
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Steve Horvath
7Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, USA
8Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, USA
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Craig W. Ritchie
9Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh
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Tara L. Spires-Jones
10UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh
11Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh
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Andrew M. McIntosh
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
12Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh
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Kathryn L. Evans
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
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Ian J. Deary
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
3Department of Psychology, University of Edinburgh, Edinburgh
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Riccardo E. Marioni
1Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh
2Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh
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  • For correspondence: riccardo.marioni@ed.ac.uk
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Abstract

Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm) – a commonly studied epigenetic mechanism. A novel epigenetic clock, termed ‘DNAm GrimAge’ has outperformed its predecessors in predicting the risk of mortality as well as a number of age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n=709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over twelve years of follow-up (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β=-0.11), lower age 73 general cognitive ability (β=-0.18), decreased brain volume (β=-0.25) and increased brain white matter hyperintensities (β=0.17). Sixty-eight of 137 health- and brain-related phenotypes tested were significantly associated with DNAm GrimAge. Adjusting all models for childhood cognitive ability attenuated to non-significance a small number of associations (12/68 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge cross-sectionally associates with lower cognitive ability and brain vascular lesions in older age, independently of early life cognitive ability. Thus, this epigenetic predictor of mortality is also associated with multiple different measures of brain health and may aid in the prediction of age-related cognitive decline.

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Posted July 16, 2019.
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An epigenetic predictor of death captures multi-modal measures of brain health
Robert F. Hillary, Anna J. Stevenson, Simon R. Cox, Daniel L. McCartney, Sarah E. Harris, Anne Seeboth, Jon Higham, Duncan Sproul, Adele M. Taylor, Paul Redmond, Janie Corley, Alison Pattie, Maria del. C Valdés Hernández, Susana Muñoz-Maniega, Mark E. Bastin, Joanna M. Wardlaw, Steve Horvath, Craig W. Ritchie, Tara L. Spires-Jones, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, Riccardo E. Marioni
bioRxiv 703504; doi: https://doi.org/10.1101/703504
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An epigenetic predictor of death captures multi-modal measures of brain health
Robert F. Hillary, Anna J. Stevenson, Simon R. Cox, Daniel L. McCartney, Sarah E. Harris, Anne Seeboth, Jon Higham, Duncan Sproul, Adele M. Taylor, Paul Redmond, Janie Corley, Alison Pattie, Maria del. C Valdés Hernández, Susana Muñoz-Maniega, Mark E. Bastin, Joanna M. Wardlaw, Steve Horvath, Craig W. Ritchie, Tara L. Spires-Jones, Andrew M. McIntosh, Kathryn L. Evans, Ian J. Deary, Riccardo E. Marioni
bioRxiv 703504; doi: https://doi.org/10.1101/703504

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