Aging
Navigate
Submit an Article
Research Paper|Volume 14, Issue 2|pp 623—659

A catalogue of omics biological ageing clocks reveals substantial commonality and associations with disease risk

Erin Macdonald-Dunlop1, Nele Taba2,3, Lucija Klarić4, Azra Frkatović5, Rosie Walker6, Caroline Hayward4, Tõnu Esko2,7, Chris Haley4, Krista Fischer2,8, James F. Wilson1,4, Peter K. Joshi1
  • 1Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh EH8 9AG, UK
  • 2Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu 51010, Estonia
  • 3Institute of Molecular and Cell Biology, University of Tartu, Tartu 51010, Estonia
  • 4MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, UK
  • 5Genos Glycoscience Research Laboratory, Zagreb 10000, Croatia
  • 6Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
  • 7Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
  • 8Institute of Mathematics and Statistics, University of Tartu, Tartu 51009, Estonia
* Equal contribution
Received: March 19, 2021Accepted: December 20, 2021Published: January 24, 2022
https://doi.org/10.18632/aging.203847

Copyright: © 2022 Macdonald-Dunlop et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Biological age (BA), a measure of functional capacity and prognostic of health outcomes that discriminates between individuals of the same chronological age (chronAge), has been estimated using a variety of biomarkers. Previous comparative studies have mainly used epigenetic models (clocks), we use ~1000 participants to compare fifteen omics ageing clocks, with correlations of 0.21-0.97 with chronAge, even with substantial sub-setting of biomarkers. These clocks track common aspects of ageing with 95% of the variance in chronAge being shared among clocks. The difference between BA and chronAge - omics clock age acceleration (OCAA) - often associates with health measures. One year’s OCAA typically has the same effect on risk factors/10-year disease incidence as 0.09/0.25 years of chronAge. Epigenetic and IgG glycomics clocks appeared to track generalised ageing while others capture specific risks. We conclude BA is measurable and prognostic and that future work should prioritise health outcomes over chronAge.