Thanks to the interplay of their genes with environmental factors, some people age more robustly than others. Years lived is therefore not a reliable predictor of future health and longevity. Much more useful is “biological age”, derived from analysis of biological factors known as biomarkers. Research has identified a vast range of biomarkers that can help chart the accumulation of molecular and cellular damage that leads to age-dependent deterioration.^²

Future Horizons:

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5-yearhorizon

Beta testers and bigger data assist research

Datasets get bigger and more diverse. New sample analysis platforms make it possible to compare across cohorts for many different studies. More biomarkers are validated, and more companies use this information, making it available, initially, to private customers. Researchers begin to analyse molecular underpinnings of previously published clinical trials of successful ageing interventions, generating better models and driving deeper understanding.

10-yearhorizon

Biological age is normalised

Validated biomarkers enter the clinic more widely, approved either as companion diagnostics or independent predictors. Moderately invasive, inexpensive biomarkers of ageing, such as age-related molecular changes in blood, become part of standard clinical care and monitoring. Measurements from wearables collect non-invasive data that has been validated against epigenetic clocks, allowing more data to be collected. Large cohorts and established biobanks unlock genetic information that leads to better models of cognitive decline. Research pins down which diseases are primarily caused by biological ageing.

25-yearhorizon

Biomarkers directly improve healthspan

AI-led data analysis robustly correlates biomarkers of ageing with the underlying processes of ageing. Researchers gain a mechanistic understanding of how healthy and unhealthy ageing diverge. Age care based on personalised biomarkers becomes part of standard medical care, resulting in population-wide improvements in healthspan.

Epigenetic clocks — a type of biomarker that estimates biological age by analysing DNA methylation patterns — can estimate accelerated biological ageing in cells, tissues or organs.^³ This is a means of identifying problematic biochemical trends before diseases manifest. More recent advances integrate statistics from multiple epigenetic biomarkers to predict mortality.^⁴

Validating these biomarkers so that they are reliable and consistent is the key to making biological age a useful tool. Because biomarkers are statistical tools whose power lies in the amount of data that they can draw on, the more population data that is available against which to benchmark individuals, the more accurately the tools will be able to identify patterns and make predictions. One promising model, the Global Neurodegeneration Proteomics Consortium,^⁵ combines the data of 40,000 individuals and solves data-privacy issues via federation of access and cloud analysis. Mining this and future large datasets, including the UK Biobank, will refine biomarkers of ageing.

Biomarkers of ageing - Anticipation Scores

The Anticipation Potential of a research field is determined by the capacity for impactful action in the present, considering possible future transformative breakthroughs in a field over a 25-year outlook. A field with a high Anticipation Potential, therefore, combines the potential range of future transformative possibilities engendered by a research area with a wide field of opportunities for action in the present. We asked researchers in the field to anticipate:

The uncertainty related to future science breakthroughs in the field
The transformative effect anticipated breakthroughs may have on research and society
The scope for action in the present in relation to anticipated breakthroughs.

This chart represents a summary of their responses to each of these elements, which when combined, provide the Anticipation Potential for the topic. See methodology for more information.