Longevity Briefs: Research Still Disagrees About How To Measure Ageing

Longevity briefs provides a short summary of novel research in biology, medicine, or biotechnology that caught the attention of our researchers in Oxford, due to its potential to improve our health, wellbeing, and longevity.

Why is this research important: A biomarker of ageing is a measurable factor that correlates well with age and can therefore be used to estimate whether someone is biologically older or younger than expected. Levels of inflammatory markers in the blood are an example of a biomarker of ageing, but something like gait speed could also qualify. Of course, some biomarkers are more accurate and consistent than others.

In an ideal world, a doctor would prick your finger and give you a single number that told you whether you were ageing faster or slower than the norm. The reality is that different cells and organ systems may age at different rates – the brain of an athlete with dementia is likely to be biologically older than their heart or muscle tissue. Similarly, ageing is a disease with many different components that can progress at different rates in different people – you could have the mitochondria of a 45 year-old but the telomeres of a 50 year-old. To make matters worse, studies don’t always agree on how a biomarker correlates with age, or whether a given biomarker is even a marker of ageing at all. Today’s study is one such example.

What did the researchers do: In this study, 169 people were recruited and divided into three age groups: under-35s, 35 to 50 year-olds, and over-50s. They then measured various biomarkers of ageing in the blood to see how well they correlated with the participants’ age. They excluded certain participants in whom biomarkers of ageing could be affected for one reason or another, such as pregnancy and recent surgery or infection.

Key takeaway(s) from this research:

• Some known biomarkers of ageing were found to correlate with age only up to age 50
• Telomerase, DNA/RNA damage, NAD+ and klotho didn’t correlate with age
• The extent to which biomarkers correlate with ageing depends on many factors including age and sex

Some of the study’s results aligned with previous findings. For example, NLRP3 (an inflammatory biomarker), advanced glycation end-products (AGEs, proteins and lipids that have become damaged by sugar) and GDF15 (a marker of faulty mitochondria) all increased with age. Interestingly, however, many of these correlations were only significant up to age 50, and no longer correlated past that age. In the case of AGEs, participants aged 35-50 actually had the highest levels on average.

The negative findings of the study were more surprising. Firstly, the activity of telomerase (the protein that repairs the protective caps of the chromosomes known as telomeres) did not significantly change with age. Note that this doesn’t imply that telomere shortening doesn’t contribute to ageing – participants’ telomeres still got shorter with increasing age. It also doesn’t contradict evidence that telomere shortening accelerates in old age – just that this may not have anything to do with telomerase deficiency.

Other biomarkers that did not change significantly between age groups included oxidative damage to DNA and RNA, levels of NAD+ (a molecule thought to be essential for DNA repair among many other functions) and klotho (a molecule of recent interest that seems to be involved in ageing). These latter two molecules also varied greatly between individuals, with levels in some people being hundreds of times higher than in others.

Why does this research matter:

This study is not the first to contradict what some consider to be ‘conventional wisdom’ when it comes to biomarkers of ageing. Most of the findings presented here have both supportive and contradictory pre-existing research and require further investigation. However, these results do highlight how a biomarker can correlate well with ageing on average throughout a population, but may still not be very useful for assessing an individual person’s rate of ageing. A biomarker may only correlate well with ageing within a certain age band, sex, ethnicity, or may simply have too much variation within the population to be of use (as this paper suggests might be the case for NAD+ and klotho). To account for this, we either need to identify more consistent biomarkers or develop a better understanding of in what context a biomarker is useful and when it isn’t.