Definitions of Age

When modelling longevity, age is well-known to be a crucial risk factor. However it is also well-known that the life-expectancy upon attaining any specific age will differ between populations. A seventy-year-old life-long smoker from France may reasonably regard the future with less optimism than a non-smoking Okinawan of the same age (allowing, of course, for the occasional highly noteworthy exception). We sometimes describe such variations in life-expectancy between populations as differences in the rate of aging, although chronologically, we all (barring celebrities!) age at precisely the same rate. For this reason, there has long been a search for a biological measure of aging that could be used to explain these differences in outcomes. This area was recognised in Public Health Paper #37 issued by the World Health Organisation as early as 1970.

The concept of a biological age has always attracted opposition as well as advocacy. One real difficulty is inconsistency; even allowing for differences in judgement between research teams, the range and quality of biological measures will naturally evolve as science advances. This means one researcher's attempt to define the components of a biological age measure will rarely tally with another's. Despite this, the attraction of an objective measure derived from combinations of either measurable deficits (frailties) or biomarkers retains strong interest. Indeed a number of candidate methods have more recently been subject to benchmarking to determine which approach may be most predictive of mortality outcomes. Further, whilst approaches incorporating frailties seem naturally applicable later in life, recent efforts have shown the concept of biological age can successfully be applied to the young. This extends the reach of such a measure as a potential trigger for interventions from mid-life onwards.

In the last few years another "definition of age" has begun to garner attention, based around the concept of DNA Methylation. Methylation is a mechanism for epigenetic adjustment via chemical tagging of DNA sequences. It offers, among other interesting properties, an accurate life-long record of smoking behaviour. When Steve Horvath published his methylation-driven epigenetic clock, he made available software and tutorials to support the methodology, enabling rapid take-up of the technique. Further research has shown that the epigenetic clock is a predictor of all-cause mortality, and that various cancer tissues show either positive or negative epigenetic age acceleration. Recent work suggests the possibility of a minimally invasive biomarker for detecting cancer. Other genetic diagnostics now offer the promise of a reliable blood-based biomarker for Alzheimer's. We may find that what began as the search for accurate tissue-based measures of age ends with earlier detection of age-related disease and the potential to extend healthy lifespan.

References

Bourlière, F. (1970) The Assessment of Biological Age in Man. WHO Public Health Paper No. 37

Costa, P.T. Jr, McCrae R.R. (1988) Measures and markers of biological aging: 'a great clamoring ... of fleeting significance'. Arch Gerontol Geriatr. 1988 Sep;7(3):211-4.

Dean, W., Morgan, R.F. (1988) In defense of the concept of biological aging measurement--current status. Arch Gerontol Geriatr. 1988 Sep;7(3):191-210.

Mitnitski, A.B., Graham, J.E., Mogilner, A.J. , Rockwood, K. (2002) Frailty, fitness and late-life mortality in relation to chronological and biological age. BMC Geriatrics 20022:1 DOI: 10.1186/1471-2318-2-1

Jackson, S.H., Weale, M.R., Weale, R.A. (2003) Biological age--what is it and can it be measured? Arch Gerontol Geriatr. 2003 Mar-Apr;36(2):103-15.

Levine, M.E. (2013) Modeling the Rate of Senescence: Can Estimated Biological Age Predict Mortality More Accurately Than Chronological Age? J Gerontol A Biol Sci Med Sci. 2013 Jun; 68(6): 667674. doi: 10.1093/gerona/gls233

Belsky, D.W. et al. (2015) Quantification of biological aging in young adults. Proc. Natl Acad. Sci. USA 112, E4104E4110. doi: 10.1073/pnas.1506264112

Zeilinger, S. et al. (2013) Tobacco Smoking Leads to Extensive Genome-Wide Changes in DNA Methylation. PLOS One doi: 10.1371/journal.pone.0063812

Horvath, S. (2013) DNA methylation age of human tissues and cell types. Genome Biology 2013, 14:R115 doi:10.1186/gb-2013-14-10-r115

Marioni, R.E. et al. (2015) DNA methylation age of blood predicts all-cause mortality in later life. Genome Biology 2015 16:25 DOI: 10.1186/s13059-015-0584-6

Zheng, Y. et al. (2016) Blood Epigenetic Age may Predict Cancer Incidence and Mortality. EBioMedicine doi: 10.1016/j.ebiom.2016.02.008

Sood, S. et al. (2015) A novel multi-tissue RNA diagnostic of healthy ageing relates to cognitive health status. Genome Biology 2015 16:185 DOI: 10.1186/s13059-015-0750-x

 

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Gavin Ritchie
Gavin Ritchie is the IT Director of Longevitas