The primarily alternative to epigenetic clocks and other omics clocks to assess biological age is the use of aging clocks constructed from clinical chemistry, physical, and other simple measures, such as result from the Klemera-Doubal Method or Phenotypic Age. Examples of suitable measures include specific metabolite levels in serum, blood count data, morphometry based on waist circumference, blood pressure, grip strength, and so forth. The construction of a clock proceeds in much the same way regardless; data is assembled from a large study population of different ages, and machine learning approaches are employed to discover algorithmic combinations of data that predict chronological age. Where the predicted clock age is higher than chronological age, it is said that this person exhibits accelerated aging. The advantage of simple measure clocks versus omics clocks is that the data used is easier to theorize on; if one sees that an individual has a higher predicted age because their blood pressure increased, for example, one can form a hypothesis quite quickly and easily. When the cause is a different prevalence of DNA methylation on seven CpG sites on the genome, well, that is largely inscrutable.
That said, given the way in the which a clock is produced, a great deal of work is required in order to understand how it actually behaves, and whether it actually reflects biological age in any useful way. This is the case regardless of the type of underlying clock data. For early clocks, the discovery process has been underway for quite some time now, and it remains an interesting open question as to the degree that we should trust or can make good use of clock data in assessing interventions thought to affect aging. The uncertainty runs the other way as well, in that perhaps some of the results produced by clocks might cause us to question how we define biological age or what we might think a priori is a useful intervention. Most clocks have quirks that are distinct from these points, such as the relative insensitivity to physical fitness exhibited by first generation epigenetic clocks. In today's open access paper, researchers note that a short change of diet can move the biological age predicted by the Klemera-Doubal Method clock by a couple of years. Is this meaningful? A limited quirk? Something that should cause us to question the clock more broadly? These sorts of questions remain hard to resolve.
Short-Term Dietary Intervention Alters Physiological Profiles Relevant to Ageing
Ageing is a complex process influenced by modifiable factors such as diet, which may accelerate or decelerate physiological decline. While chronological age increases uniformly, biological ageing varies between individuals, reflecting differences in health status and the resilience of biological systems. The Klemera-Doubal Method (KDM), a composite biomarker-based index often used as an estimate of biological age, has been associated with morbidity and mortality in large cohorts. This study examined whether dietary manipulation of protein source and macronutrient composition affects KDM estimates in older adults.
We analysed data from the Nutrition for Healthy Living study, a dietary intervention trial involving 104 participants aged 65-75 years. Participants were randomised to one of four diets: omnivorous/high-fat (OHF), omnivorous/high-carbohydrate (OHC), semi-vegetarian/high-fat (VHF) or semi-vegetarian/high-carbohydrate (VHC). KDM-derived δAge (the difference between KDM-age and chronological-age) was calculated before and after a 4-week intervention.
The OHF group, most like participants' baseline diets, showed no meaningful change in δAge. Compared to OHF, participants in the OHC group showed a significant reduction in δAge. The VHF and VHC groups showed similar reductions in δAge, relative to OHF, though not all reached statistical significance. KDM-derived δAge appears responsive to dietary change within 4 weeks and may offer a useful proxy for evaluating shifts in physiological status. Caution is warranted in interpreting such changes as evidence of biological age reversal as observed shifts may reflect acute physiological responsiveness to dietary inputs rather than altered ageing trajectories. Longer-term treatment would be needed to assess changes in age-related disease risks.
View the full article at FightAging
