New research presented as an abstract at the European Congress of Psychiatry in Paris this week has revealed that the blood marker profile of people with a lifetime history of various mental illnesses, including depression, bipolar disorder, and anxiety disorders, suggests their bodies are "biologically older than their actual age".
Lead researcher Dr Julian Mutz, a postdoctoral research associate at King’s College London (KCL) explained: "It is now possible to predict people’s age from blood metabolites. We found that, on average, those who had a lifetime history of mental illness had a metabolite profile that implied they were older than their actual age. For example, people with bipolar disorder had blood markers indicating that they were around 2 years older than their chronological age."
Together with Cathryn Lewis, professor of genetic epidemiology & statistics at KCL, he examined information from up to 110,780 participants from the UK Biobank database who had complete data on all metabolomic measures, looking at tests on 168 different blood metabolites quantified using the Nightingale Health platform.
The researchers linked these data to information on individuals' history of mental illness. Their aim was to use machine-learning methods to predict biological age from nuclear magnetic resonance spectroscopy metabolomics data, and to identify psychiatric traits associated with accelerated biological ageing.
They noted that people with mental health disorders "tend to have poorer quality health" and "often people with poor mental health show an increased tendency to develop conditions such as heart disease and diabetes" – "and these conditions tend to worsen with age". For example, a 2019 study found that on average people with mental disorders had shorter life expectancy by around 10 years for men and 7 years for women compared with the general population.
"Accelerated biological ageing might contribute to the higher prevalence of age-related diseases and excess mortality amongst individuals with mental disorders," they explained. "Recent advances in machine learning and the collection of high-dimensional molecular 'omics' data allow for the quantification of biological age."
Estimates of the magnitude of this effect vary according to the mental health condition, they said. Based onmetabolomic age – the difference between predicted biological age and observed chronological age – they estimated group differences between individuals with and without mental disorders, and examined whether polygenic scores for mental disorders predicted metabolomic age.
They found that those with a mental illness had a metabolite profile older than would have been expected for their age compared with people without a mental illness. Polygenic scores for mental disorders were positively correlated with metabolomic age. "These findings suggest that individuals with a history of mental disorders, or with higher polygenic scores for mental disorders, were biologically older than their chronological age," they concluded.
"This may go some way to explaining why people with mental health problems tend to have shorter lifespans and more age-related diseases than the general population," the researchers said.
Dr Mutz said: "Our findings indicate that the bodies of people with mental health problems tend to be older than would be expected for an individual their age. This may not explain all the difference in health and life expectancy between those with mental health problems and the general population, but it does mean that accelerated biological ageing may be an important factor.
"If we can use these markers to track biological ageing, this may change how we monitor the physical health of people with mental illness and how we evaluate the effectiveness of interventions aimed at improving physical health."
Discussing the research with Medscape News UK, Dr Mutz said that, whilst the current study had not yet been published, publication was planned for "the next few months". He said that the study followed on from the team's previous work, also based on UK Biobank data, suggesting higher levels of frailty in individuals with mental disorders, and that all-cause mortality among individuals with mental disorders was linked with frailty scores.
For example, compared with non-frail people without mental disorders, the all-cause mortality hazard ratio was 3.65 (95% CI 2.40 to 5.54) among individuals with both bipolar disorder and frailty. Dr Mutz also told us that they had found a correlation between the frailty scores and blood markers. "I have found that people who have a blood metabolite profile older than expected for their age are also more likely to be physically frail and have higher frailty index scores," he said.
In terms of future research, he said that so far they have examined biological ageing in people with a history of depression, anxiety disorders or bipolar disorder – in future they plan to expand this work to other mental health diagnoses. Also, he added: "I am currently finalising a research project in which we have examined different machine learning algorithms to predict people's age from their blood metabolites." This work will be submitted for publication later this year.
Commenting on the abstract presentation, Dr Sara Poletti, from the Istituto Scientifico Universitario Ospedale San Raffaele in Milan, Italy, who was not involved in the research, said: "This is an important work as it gives a possible explanation for the higher prevalence of metabolic and age-related diseases in patients with mental illness. Understanding the mechanisms underlying accelerated biological ageing could be crucial for the development of prevention and tailored treatments to address the growing difficulty of an integrated management of these disorders."
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