The world’s population is ageing. In 2018, for the first time in history, people aged 65 or above outnumbered children under five worldwide. As the number of ageing individuals continues to rise, so does the prevalence of age-related disease and disabilities, and so does the global pressure on healthcare systems and economies.
A key aim of the healthcare community is to be able to predict (and ideally extend) an individual’s heathy lifespan, also known as an individual’s longevity. As a result, it is becoming ever more important to find ways that we can monitor and maintain health, as well as to develop therapies that directly address ageing processes so that we can delay or prevent the onset of age-related diseases. One way to address these needs is to identify key measures of biological ageing, i.e. ageing biomarkers.
The identification of such biomarkers continues to present a challenge. Our chronological age, i.e. our age in years, is strongly associated with ageing-related functional deterioration but it has limited use as a measure of ageing because there is considerable variation between people: everyone ages differently and at different rates.
Four genetic and molecular biomarkers, or sets of biomarkers, have been discovered recently that may allow us to realise the goals above. There is increasing evidence that the slower the rate of telomere shortening, the longer that individual is likely to live. An increased level of gene methylation has been correlated with shortened longevity. A genetic study in 2018 reported to be able to identify “the 10 percent of people with the most protective genes, who will live an average of five years longer than the least protected 10 percent”. Finally, a group of 14 blood-based metabolic biomarkers was described in 2019 which can be combined into a score that might be able to predict a high risk of mortality within 10 years.
However, whilst these molecular markers may be useful, they have limitations when used individually. Some need further validation and they do not provide an overall picture of how someone is ageing, nor where preventative efforts should be focused. It is likely that we need to take a wider look that examines multiple biomarkers, as well as incorporating the more traditional markers of ageing such as physical capability, physiological function, and cognitive ability.
A shift to a broader approach is illustrated by the emergence of collaborations that bring together traditional molecular sciences and AI in the longevity field. For example, the recently-established Longevity AI Consortium at King’s College London aims to use deep learning techniques to identify novel longevity and healthy ageing biomarkers, accelerate diagnosis of age-related health decline, and promote effective healthy lifestyles for longevity. The hope is that the Consortium, among others, can bring together doctors, clinics, data providers, AI companies and corporate partners for efficient biomarker commercialisation and clinical implementation.
We are still some way off from reaching the point where it is scientifically valid to use biomarkers to predict longevity, and probably even further from having the preventative or therapeutic measures in place to provide an effective response if such markers are detected. Considerations around the use of data will also come into play. Insurance companies, pension funds, and government bodies are likely to be interested in predicting healthy lifespans, and there are concerns about companies offering end-of-life predictions in terms of consent and the possible psychological effects on consumers.
That said, extending the functional lifespan of humans by just one year may improve the quality of life for billions of people. Research into ageing and longevity is attracting more and more support from investors and industry, which should help us to realise the potential of biomarkers for ageing.
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