Research Paper|Volume 8, Issue 2|pp 394—401

DNA methylation levels at individual age-associated CpG sites can be indicative for life expectancy

Qiong Lin^1,², Carola I. Weidner^1,², Ivan G. Costa^2,³, Riccardo E. Marioni^4,^5,⁶, Marcelo R. P. Ferreira^2,^3,⁸, Ian J. Deary^4,⁷, Wolfgang Wagner^1,²

¹Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH University Medical School, Aachen, Germany
²Institute for Biomedical Technology – Cell Biology, RWTH University Medical School, Aachen, Germany
³Interdisciplinary Centre for Clinical Research (IZKF), RWTH University Medical School, Aachen, Germany
⁴Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
⁵Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
⁶Queensland Brain Institute, The University of Queensland, Brisbane 4072, QLD, Australia
⁷Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
⁸Department of Statistics, Centre for Natural and Exact Sciences, Federal University of Paraiba, CEP 58051-900, João Pessoa, Brazil

Received: December 4, 2015Accepted: January 30, 2016Published: February 25, 2016

https://doi.org/10.18632/aging.100908

Copyright: © 2016 Lin et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

DNA-methylation (DNAm) levels at age-associated CpG sites can be combined into epigenetic aging signatures to estimate donor age. It has been demonstrated that the difference between such epigenetic age-predictions and chronological age is indicative for of all-cause mortality in later life. In this study, we tested alternative epigenetic signatures and followed the hypothesis that even individual age-associated CpG sites might be indicative for life-expectancy. Using a 99-CpG aging model, a five-year higher age-prediction was associated with 11% greater mortality risk in DNAm profiles of the Lothian Birth Cohort 1921 study. However, models based on three CpGs, or even individual CpGs, generally revealed very high offsets in age-predictions if applied to independent microarray datasets. On the other hand, we demonstrate that DNAm levels at several individual age-associated CpGs seem to be associated with life expectancy – e.g., at CpGs associated with the genes PDE4C and CLCN6. Our results support the notion that small aging signatures should rather be analysed by more quantitative methods, such as site-specific pyrosequencing, as the precision of age-predictions is rather low on independent microarray datasets. Nevertheless, the results hold the perspective that simple epigenetic biomarkers, based on few or individual age-associated CpGs, could assist the estimation of biological age.