@article{03f1bcb6c8534f83b45d9af00fd745cf,
title = "DNA methylation age of blood predicts all-cause mortality in later life",
abstract = "Background: DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Results: Here we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age ({increment}age) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between {increment}age and mortality. A 5-year higher {increment}age is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher {increment}age. A pedigree-based heritability analysis of {increment}age was conducted in a separate cohort. The heritability of {increment}age was 0.43. Conclusions: DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.",
author = "Marioni, {Riccardo E.} and Sonia Shah and McRae, {Allan F.} and Chen, {Brian H.} and Elena Colicino and Harris, {Sarah E.} and Jude Gibson and Henders, {Anjali K.} and Paul Redmond and Cox, {Simon R.} and Alison Pattie and Janie Corley and Lee Murphy and Martin, {Nicholas G.} and Montgomery, {Grant W.} and Feinberg, {Andrew P.} and Fallin, {M. Daniele} and Multhaup, {Michael L.} and Jaffe, {Andrew E.} and Roby Joehanes and Joel Schwartz and Just, {Allan C.} and Lunetta, {Kathryn L.} and Murabito, {Joanne M.} and Starr, {John M.} and Steve Horvath and Baccarelli, {Andrea A.} and Daniel Levy and Visscher, {Peter M.} and Wray, {Naomi R.} and Deary, {Ian J.}",
note = "Funding Information: We thank the cohort participants and team members who contributed to these studies. This work was supported by numerous funding bodies. Phenotype collection in the Lothian Birth Cohort 1921 was supported by the UK{\textquoteright}s Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Age UK (The Disconnected Mind project). Methylation typing was supported by the Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, The Wellcome Trust Institutional Strategic Support Fund, The University of Edinburgh, and The University of Queensland. REM, SEH, SRC, JMS, PMV, and IJD are members of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE). CCACE is supported by funding from the BBSRC, the Medical Research Council (MRC), and the University of Edinburgh as part of the cross-council Lifelong Health and Wellbeing initiative (MR/K026992/1). Research reported in this publication was supported by National Health and Medical Research Council (NHMRC) project grants 613608, APP496667, APP1010374, and APP1046880. NHMRC Fellowships to GWM, PMV, and NRW (613602) and Australia Research Council (ARC) Future Fellowship to NRW (FT0991360). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NHMRC or ARC. The Framingham Heart Study is funded by National Institutes of Health contract N01-HC-25195. The laboratory work for this investigation was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health. The analytical component of this project was funded by the Division of Intramural Research, National Heart, Lung, and Blood Institute, and the Center for Information Technology, National Institutes of Health, Bethesda, MD, USA. This study utilized the high-performance computational capabilities of the Biowulf Linux cluster (http://biowulf.nih.gov) and Helix Systems (http://helix.nih.gov) at the National Institutes of Health, Bethesda, MD, USA. JMM and KLL were supported by R01AG029451. The present work on the US Department of Veterans Affairs (VA) Normative Aging Study has been supported by funding from the U.S. National Institute of Environmental Health Sciences (NIEHS) (R01ES015172, R01ES021733). The VA Normative Aging Study is supported by the Cooperative Studies Program/ERIC, US Department of Veterans Affairs, and is a research component of the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC). Additional support to the VA Normative Aging Study was provided by the US Department of Agriculture, Agricultural Research Service (contract 53-K06-510). The views expressed in this paper are those of the authors and do not necessarily represent the views of the US Department of Veterans Affairs. We thank Stuart J Ritchie for his helpful comments and suggestions on the initial draft of the manuscript. Publisher Copyright: {\textcopyright} 2015 Marioni et al.; licensee BioMed Central.",
year = "2015",
month = jan,
day = "30",
doi = "10.1186/s13059-015-0584-6",
language = "English (US)",
volume = "16",
journal = "Genome biology",
issn = "1474-7596",
publisher = "BioMed Central",
number = "1",
}