Research Paper Volume 8, Issue 2 pp 394—401
DNA methylation levels at individual age-associated CpG sites can be indicative for life expectancy
- 1 Helmholtz-Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH University Medical School, Aachen, Germany
- 2 Institute for Biomedical Technology – Cell Biology, RWTH University Medical School, Aachen, Germany
- 3 Interdisciplinary Centre for Clinical Research (IZKF), RWTH University Medical School, Aachen, Germany
- 4 Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- 5 Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK
- 6 Queensland Brain Institute, The University of Queensland, Brisbane 4072, QLD, Australia
- 7 Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
- 8 Department of Statistics, Centre for Natural and Exact Sciences, Federal University of Paraiba, CEP 58051-900, João Pessoa, Brazil
Received: December 4, 2015 Accepted: January 30, 2016 Published: February 25, 2016
https://doi.org/10.18632/aging.100908How to Cite
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.