Molecular ageing clocks – making the links between mental illness and shorter lifespans

A young person and old person's faces side by side with close up of their eyes

Dr Julian Mutz is a post-doctoral research associate at the Social, Genetic and Developmental Psychiatry (SGDP) Centre at the Institute of Psychiatry, Psychology & Neuroscience. Cathryn Lewis is Professor of Genetic Epidemiology & Statistics at King’s College London and NIHR Maudsley BRC’s deputy theme lead for Trials, Genomics and Prediction.

In this blog, they discuss their research on biological ageing in individuals with mental health conditions and highlight how their epidemiological studies may inform clinical research and practice.

Mental illness is linked to poor physical health and shorter lifespan

People with mental health conditions such as depression or bipolar disorder suffer from worse physical health and have more age-related diseases than the general population, including cardiovascular disease and diabetes.

They also have a lower average life expectancy than people without a mental illness. For example, a recent meta-analysis, a statistical technique that combines data from multiple studies, found that individuals with bipolar disorder had a life expectancy of 67 years, which was nearly five years lower than the global average of 73 years (in 2019).

Research into the relationship between mental health and lifespan has shown that there are many different factors that contribute to this difference in life expectancy, for example higher rates of suicide and fatal accidents and higher smoking rates amongst individuals with mental health conditions.

Another important factor may be accelerated biological ageing. This concept explains why there is a variation in how fast people age biologically even though the amount of time that has passed from birth to a given date, our “chronological age”, advances at the same pace in everyone. This means that a person who is chronologically younger than another could in fact be biologically older.

Our research on ageing and mental illness in the UK Biobank

To deepen our understanding of biological ageing in individuals with mental health conditions and inform how we can help people who experience both physical and mental health problems, we conducted several epidemiological analyses in the UK Biobank, a large biomedical research study of more than half a million people in the UK.

In a series of three studies of depression, bipolar disorder and anxiety disorder, we explored 15 physiological measures that are known to change with age, such as cardiovascular or lung function, bone mineral density and body composition. We observed modest average differences between individuals with and without a mental illness for several of these measures. For example, individuals with a mental illness had a lower grip strength and a higher body fat percentage, on average, highlighting that mental illness is associated with changes across the body, and not just the central nervous system or the brain.

In a subsequent study, we found that individuals with mood or anxiety disorders had higher rates of frailty, which is a condition characterised by a lower capacity to respond well to stressors and being more vulnerable to experience adverse health outcomes. We found that individuals with both bipolar disorder and physical frailty had a three-fold higher mortality risk than people without a mental illness and frailty, highlighting that this group have a high unmet therapeutic need.

Finally, moving to the level of cells, we found that telomeres, a hallmark of cellular ageing, were shorter in individuals with depression or bipolar disorder, indicating that these people were biologically older. Shorter telomeres were also found in people who had a higher polygenic risk score for depression, which is an estimate of a person’s genetic risk for depression.

Molecular ageing clocks and mental illness

Using a different approach to examine biological ageing in people with mental health conditions we recently developed a molecular ageing clock using data from the UK Biobank. The basic concept of an ageing clock involves using machine learning to identify relationships between biological data and (usually) chronological age. The machine learning model is then used to predict a person’s age, and the difference between their predicted and chronological age represents a measure of biological ageing.

We developed a metabolomic ageing clock from data on 168 markers in the blood called “metabolites”, small molecules that result from cellular processes, for example when food is broken down into energy. Using this clock, we found that people with mood or anxiety disorders were biologically older than their chronological age.

Julian recently presented this work at the European Congress of Psychiatry in Paris, France, and our research received widespread coverage in national and international media. This included, The Daily Telegraph, TIME and Fortune, indicating that there is strong public interest in research on biological ageing and health.

We are currently expanding this work to include other mental health conditions and hope to submit our study for publication in the next few months.

Impact on clinical research and practice

Our research provides important scientific insight into biological ageing and physical health in individuals with mental health conditions. To help more people live healthier for longer, further research is needed to identify modifiable factors that may impact health and biological ageing. For example, to what extent do loneliness, lifestyle behaviours and weight management impact biological ageing in individuals with a mental illness? With this insight we can then develop ways of mitigating the risk associated with these factors, which could help protect against their adverse impact on biological ageing.

While epidemiological studies do not always have an immediate impact on health policy or clinical practice, their findings often inform the design and implementation of clinical research studies. For clinical research and care, molecular ageing clocks have the potential to provide new and accessible ways of tracking biological ageing.

Molecular ageing clocks may also change how we monitor the physical health of people with mental health conditions. These technologies may also be useful in assessing the effectiveness of interventions aimed at improving physical health outcomes and are probably more readily interpretable by patients compared to individual biological markers.


Media coverage


Pictured: Professor Cathryn Lewis and Dr Julian Mutz

Cathryn LewisJulian Mutz


Tags: Geonomics and Prediction - Biomarkers & genomics -

By NIHR Maudsley BRC at 4 May 2023, 13:56 PM

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