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Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex.

Shireby, Gemma L and Davies, Jonathan P and Francis, Paul T and Burrage, Joe and Walker, Emma M and Neilson, Grant WA and Dahir, Aisha and Thomas, Alan J and Love, Seth and Smith, Rebecca G and Lunnon, Katie and Kumari, Meena and Schalkwyk, Leonard C and Morgan, Kevin and Brookes, Keeley and Hannon, Eilis and Mill, Jonathan (2020) 'Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex.' Brain: a journal of neurology, 143 (12). 3763 - 3775. ISSN 0006-8950

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Abstract

Human DNA methylation data have been used to develop biomarkers of ageing, referred to as 'epigenetic clocks', which have been widely used to identify differences between chronological age and biological age in health and disease including neurodegeneration, dementia and other brain phenotypes. Existing DNA methylation clocks have been shown to be highly accurate in blood but are less precise when used in older samples or in tissue types not included in training the model, including brain. We aimed to develop a novel epigenetic clock that performs optimally in human cortex tissue and has the potential to identify phenotypes associated with biological ageing in the brain. We generated an extensive dataset of human cortex DNA methylation data spanning the life course (n = 1397, ages = 1 to 108 years). This dataset was split into 'training' and 'testing' samples (training: n = 1047; testing: n = 350). DNA methylation age estimators were derived using a transformed version of chronological age on DNA methylation at specific sites using elastic net regression, a supervised machine learning method. The cortical clock was subsequently validated in a novel independent human cortex dataset (n = 1221, ages = 41 to 104 years) and tested for specificity in a large whole blood dataset (n = 1175, ages = 28 to 98 years). We identified a set of 347 DNA methylation sites that, in combination, optimally predict age in the human cortex. The sum of DNA methylation levels at these sites weighted by their regression coefficients provide the cortical DNA methylation clock age estimate. The novel clock dramatically outperformed previously reported clocks in additional cortical datasets. Our findings suggest that previous associations between predicted DNA methylation age and neurodegenerative phenotypes might represent false positives resulting from clocks not robustly calibrated to the tissue being tested and for phenotypes that become manifest in older ages. The age distribution and tissue type of samples included in training datasets need to be considered when building and applying epigenetic clock algorithms to human epidemiological or disease cohorts.

Item Type: Article
Uncontrolled Keywords: DNA methylation, age, cortex, brain, clock
Divisions: Faculty of Science and Health > Life Sciences, School of
Faculty of Social Sciences > Institute for Social and Economic Research
Depositing User: Elements
Date Deposited: 26 Feb 2021 13:25
Last Modified: 26 Feb 2021 13:25
URI: http://repository.essex.ac.uk/id/eprint/29954

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