Metabolomic and omic assessment of biological ageing across the life-course (METAGE)
Lead Research Organisation:
Imperial College London
Department Name: School of Public Health
Abstract
Both genetic and environmental factors affect the ageing process, leading to differences in ageing rates. Therefore, a person's "biological age", or overall physiological state, may differ from what is expected given their actual (chronological) age. Differences in biological aging rates mean some people die earlier and have more health problems in later life. In the first part of my project, I used metabolomics (whole sets of metabolites or small molecules) data from multiple population-based cohort studies in the UK, Europe, and the USA, to develop blood tests of biological age using advanced statistics. We found that the metabolomic-based biological age tests provided improved prediction, over chronological age itself, of age-related ill health and mortality. Furthermore, We found that that biological ageing was slower over two years among people who were supported to follow a healthier lifestyle, compared to those who did not receive this support in the FINGER study.
For the next part of my project, I will examine if the metabolomic-based biological age test can predict cognitive and physical aging among two cohort studies of older people (the CHARIOT PRO and TILDA studies). I will further refine the metabolomic-based biological age test, so it is less expensive and easier to measure in clinical laboratories. I will also test the use of proteins, another biologically important class of molecules, to develop biological age models in over 20,000 people in the EPIC and CHARIOT PRO studies. Since we know which organs in the body produce specific proteins, it is possible to test "organ-specific" ageing. This is useful as different biological systems in the body may age at different rates, and I will test organ-specific ageing against many types of disease. Furthermore, I will use genetic data and a technique called Medelian Randomization to test if proteins and metabolites that are correlated with age, may cause unhealthy ageing. I will use this information to further improve the biological age tests. Finally, I will analysis the pathways that connect proteins, metabolites and genetic factors involved in ageing to more deeply understand the biological processes that change with age.
For the next part of my project, I will examine if the metabolomic-based biological age test can predict cognitive and physical aging among two cohort studies of older people (the CHARIOT PRO and TILDA studies). I will further refine the metabolomic-based biological age test, so it is less expensive and easier to measure in clinical laboratories. I will also test the use of proteins, another biologically important class of molecules, to develop biological age models in over 20,000 people in the EPIC and CHARIOT PRO studies. Since we know which organs in the body produce specific proteins, it is possible to test "organ-specific" ageing. This is useful as different biological systems in the body may age at different rates, and I will test organ-specific ageing against many types of disease. Furthermore, I will use genetic data and a technique called Medelian Randomization to test if proteins and metabolites that are correlated with age, may cause unhealthy ageing. I will use this information to further improve the biological age tests. Finally, I will analysis the pathways that connect proteins, metabolites and genetic factors involved in ageing to more deeply understand the biological processes that change with age.
Publications
Ambroa-Conde A
(2024)
Inference of tobacco and alcohol consumption habits from DNA methylation analysis of blood
in Forensic Science International: Genetics
Fabbri L
(2025)
Childhood exposure to non-persistent endocrine disruptors, glucocorticosteroids, and attentional function: A cross-sectional study based on the parametric g-formula
in Environmental Research
Guimbaud JB
(2024)
Machine learning-based health environmental-clinical risk scores in European children.
in Communications medicine
Korologou-Linden R
(2024)
Novel Blood-Based Biomarkers and Disease Modifying Therapies for Alzheimer's Disease. Are We Ready for the New Era?
in The Journal of Prevention of Alzheimer's Disease
Korologou-Linden R
(2025)
Preparing the way for novel blood-based biomarkers and disease-modifying treatments for Alzheimer's disease in the NHS in the UK.
in Journal of the Royal Society of Medicine
Lau CE
(2024)
NMR metabolomic modeling of age and lifespan: A multicohort analysis.
in Aging cell
Llauradó-Pont J
(2025)
A meta-analysis of epigenome-wide association studies of ultra-processed food consumption with DNA methylation in European children.
in Clinical epigenetics
Robinson, O.
(2025)
A Life Course Approach to the Epidemiology of Chronic Diseases and Ageing
| Description | Demonstration of utility of age modelling approach and improved understanding of relationship of biological age to health and developmental outcomes |
| Exploitation Route | Key pathways identified in ageing and disease may be targeted for therapeutical intervention. Age models may be used for patient stratification in clinical trials and as endpoints in epidemiological research |
| Sectors | Healthcare |
| Description | AD-Riddle |
| Amount | £644,000 (GBP) |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2024 |
| End | 01/2028 |
| Description | Chariot Pro Longitudinal Study |
| Amount | £4,220,000 (GBP) |
| Organisation | Bill and Melinda Gates Foundation |
| Sector | Charity/Non Profit |
| Country | United States |
| Start | 03/2024 |
| End | 07/2027 |
| Description | Understanding how endocrine disruptors and chemical mixtures of concern target the immune system to trigger or perpetuate disease (ENDOMIX) |
| Amount | £390,274 (GBP) |
| Funding ID | 10106479 |
| Organisation | Innovate UK |
| Sector | Public |
| Country | United Kingdom |
| Start | 01/2024 |
| End | 01/2028 |
| Title | DNAm metabolomic age assessment |
| Description | Model applicable to DNA methylation microarray data |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2025 |
| Provided To Others? | Yes |
| Impact | Published here: https://onlinelibrary.wiley.com/doi/full/10.1111/acel.14484?msockid=0b746f4c54426ef414ee7a5e55896f2b Other researchers are already using this |
| URL | https://github.com/Kexin-xu-01/DNAm-metabolic-age/ |
| Description | AIRWAVE study |
| Organisation | Imperial College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Analysis of data provided by AIRWAVE cohort. We are re-processing and performing additional annotation experiments to enrich the existing metabolomic database |
| Collaborator Contribution | Provision of data collected in the AIRWAVE cohort. Intellectual contribution to research design and interpretation. |
| Impact | Untargeted metabolomics study database doi: 10.1111/acel.13149 |
| Start Year | 2020 |
| Description | Global Neurodegeneration Proteomics Consortium (GNPC) |
| Organisation | Janssen Research & Development |
| Country | Global |
| Sector | Private |
| PI Contribution | Data from Chariot Pro study. Members of steering and analysis comittees |
| Collaborator Contribution | Provision of proteomics analysis. Consortium infrastructure for data sharing |
| Impact | No outputs yet -Further cohorts being invited to join consortium |
| Start Year | 2022 |
| Description | Global Neurodegeneration Proteomics Consortium (GNPC) |
| Organisation | University College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Data from Chariot Pro study. Members of steering and analysis comittees |
| Collaborator Contribution | Provision of proteomics analysis. Consortium infrastructure for data sharing |
| Impact | No outputs yet -Further cohorts being invited to join consortium |
| Start Year | 2022 |
| Description | HELIX/Athlete exposome study |
| Organisation | Barcelona Institute for Global Health |
| Country | Spain |
| Sector | Multiple |
| PI Contribution | The research team are analysing data collected in EU HELIX Exposome study of European children. In addition we are performing a glucocorticoid steroid profiling assay (in collaboration with our laboratory research partners) of hair and urine samples from the study. Additionally we contribute intellectually to the working group on biological aging in this study. |
| Collaborator Contribution | The partners are providing data and biological samples to meet our project aims. Intellectual contribution to research design and interpretation |
| Impact | Child study database |
| Start Year | 2020 |
| Description | TILDA |
| Organisation | Trinity College Dublin |
| Department | The Irish Longitudinal Study on Ageing |
| Country | Ireland |
| Sector | Academic/University |
| PI Contribution | We are analyzing 1,700 blood samples provided by the TILDA using four liquid-chromatography mass-spectrometry platforms |
| Collaborator Contribution | They are providing samples and covariate data and intellectual contribution to downstream data analysis |
| Impact | Laboratory analysis underway so not outputs to report yet |
| Start Year | 2021 |
| Description | Exhibition Road Festival |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | Regularly host stall at the Great exhibition Festival where my team and myself talked to members of the public and did interactive activities to talk about our work on environmental effects on biological age. The event was very popular with about 500 participants over the course of the weekend |
| Year(s) Of Engagement Activity | 2023,2024,2025 |
| URL | https://www.greatexhibitionroadfestival.co.uk/ |
| Description | In2Med School hackthon |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Schools |
| Results and Impact | This event was organized by a nationwide In2MedSchool aiming to widen applications to Medical school. I gave a presentation and judged the student project where they aimed to design a public health intervention. |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.in2medschool.com/ |
| Description | Lifelong Ageing Fair |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | The Lifelong ageing fair, organized by The Sciences of Ageing and The Culture of Youth at King's college London was held in Lambeth town hall and including stands and talks by experts in Ageing. I gave two talks attending by around 30 elderly members of the public. We also had an interactive stand hosted by members of my team where we discussed our work |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.kcl.ac.uk/research/saacy |
| Description | Royal Institute event: For your Inspiration Earth Extremes |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Around 200 people (mainly younger adults and children) attended this event sand enjoyed interacting at out stall: (MRC Centre in Environment and Health) How old am I really? How molecules can reveal your biological age |
| Year(s) Of Engagement Activity | 2024 |
| URL | https://www.rigb.org/whats-on/your-inspiration-earth-extremes |
