Meet the team

Paul Elliott

"We aim to acquire new knowledge of environmental, lifestyle, genetic and metabolic risk factors related to development of dementias so that we can identify and recommend effective and practical clinical and lifestyle interventions and preventive measures that will ultimately lead to an improvement in diagnosis, quality of life and life expectancy." Paul Elliott
UK DRI Group Leader

A world-leader in epidemiology and public health, Prof Paul Elliott brings a wealth of knowledge and expertise to the UK DRI. After training as a doctor, Paul specialised in epidemiology, studying at the London School of Hygiene & Tropical Medicine where he remained until 1995, rising to Head of the Environmental Epidemiology Unit. Moving to Imperial College London, he is now Chair in Epidemiology and Public Health Medicine in the School of Public Health, an honorary consultant in public health medicine at Imperial College Healthcare NHS Trust, and academic lead for the Informatics & Biobanking research theme (Imperial NIHR Biomedical Research Centre). As a Group Leader at UK DRI at Imperial, Paul will lead an exciting research programme using advanced methods in genetic, epidemiology and metabolic phenotyping to improve scientific understanding of the development of dementias.

1. At a glance

Developing an overall picture of the risk factors for dementia 

Although the causes of different types of dementia are not well understood, we know that each involves a complex mix of genetic, environmental and lifestyle factors. For instance, several ‘risk’ genes have now been identified that can influence a person’s chances of developing Alzheimer’s disease but don’t guarantee it. Developing a better knowledge of how different risk factors interact together to tip the balance from health to disease will be key to tackling different dementias. 

Prof Paul Elliott is using powerful technologies that can measure hundreds of thousands of small molecules at a time, such as in blood or urine, to give an extraordinarily detailed snapshot of what’s going on inside a person’s body. By carrying out sophisticated data analyses of the molecular signatures from people taking part in large population studies looking into the risk factors for dementia, he hopes to identify subtle shifts that associate with different types of the disease and link these with specific genetic, dietary or lifestyle factors. He hopes that this approach will build valuable insights into the molecular pathways involved in the development of different dementias, offering the potential for lifestyle and preventive measures, and new treatments that can delay or mitigate the occurrence of disease. 

2. Scientific goals

Alzheimer’s disease (AD) is characterised by a prolonged pre-clinical phase involving Aβ deposition but without the typical symptoms of cognitive impairment and dementia until relatively late on in the disease process. Although there is a well described genetic predisposition to AD, known genetic factors to date explain only a small proportion of the variance in AD occurrence. Little is known about the environmental, lifestyle and metabolic factors which, interacting with genetic background, determine who ultimately will go on to manifest clinical disease. Gaining knowledge of these risk factors is key to tackling the growing burden of AD, vascular and other dementias, as it offers the potential for lifestyle and preventive measures, and novel treatments, to delay or offset occurrence of clinical disease.

The ‘exposome’ concept captures the totality of internal and external exposures and their biological imprints, from a variety of sources including chemical and biological agents, gut microbial and dietary/lifestyle/psychosocial factors. These interact at a cellular and systems level to generate molecular signatures characteristic of health or disease that can be assessed through ‘omic technologies and biomarkers. Specifically, metabolomics, the metabolic profiling of small molecule metabolites, for example in blood or urine, is a powerful and innovative approach that captures in extraordinarily high-resolution direct signatures of the end-products of a wide range of physiological and pathophysiological processes. These signatures tend to be more closely associated with phenotypic expression than genes and proteins, whose function is subject to epigenetic regulation and post-translational modifications.

Main objectives and research goals:

The overall objective is to gain new knowledge on metabolic phenotypes and related metabolic pathways associated with cognitive decline or mild cognitive change (MCI), AD, vascular and other dementias, as well as cardio-metabolic, lifestyle and other putative risk factors. Specific aims are:

1. To provide novel functional data and reveal metabolic pathways influenced by genetic signals for AD and other dementias. By investigating genome-wide association study findings in relation to the blood and urinary metabolome.

2. To identify discriminatory metabolite signatures associated with cognitive change; sleep disturbance/shift work; incident MCI, AD and vascular dementia – and identify the dietary, social and lifestyle correlating factors. Through the statistical analysis of large patient cohort data.

3. To structurally identify discriminatory metabolites. Using a range of chemometric, bioinformatic as well as analytic chemistry methods.

4. To identify both common and specific pathways that underlie cognitive change, incident MCI, AD, vascular and other dementias. By placing the discovered metabolites into metabolic pathways using various statistical, chemometric and bioinformatic approaches.

5. To identify underlying pathways and investigate the extent that the metabolic signals/pathways found in peripheral blood/urine also pertain in the brain. By measuring discovered and pathway-associated metabolites in CSF of people with MCI, AD and controls.

3. Team members

Dr Abbas Dehghan (Reader in Epidemiology)
Dr Ioanna Tzoulaki (Reader in Epidemiology)
Dr Antonio Berlanga (Postdoctoral Researcher)
Dr Rui Pinto (Postdoctoral Researcher)
Dr Ibrahim Karaman (Postdoctoral Researcher)
Dr Jian Huang (Postdoctoral Researcher)
Parisa Mottaghi (PhD Student)

4. Collaborations

Within UK DRI:

  • Prof Elaine Holmes, UK DRI at Imperial
  • Dr Gaynor Smith, UK DRI at Cardiff
  • Dr Owen Peters, UK DRI at Cardiff

Beyond UK DRI

  • Prof Timothy Hughes, Centre for Healthy Aging and Alzheimer's Prevention, Wake Forest University, USA
  • Dr Katie Meyer, Department of Nutrition and UNC Nutrition Research Institute, University of North Carolina at Chapel Hill, USA

5. Topics

Metabolomics, exposome, biomarkers, dementia risk factors, molecular epidemiology

6. Techniques

Proton nuclear magnetic resonance (1H NMR) spectrometry, ultra-performance liquid chromatography (UPLC)-mass spectrometry (MS)

7. Key publications

Suzuki H, Gao H, Bai W, Evangelou E, Glocker B, O'Regan DP, Elliott P, Matthews PM. Abnormal brain white matter microstructure is associated with both pre-hypertension and hypertension. PLoS One. 2017; 12(11):e0187600

Evangelou E, Warren HR, Mosen-Ansorena D, et al, Wain LV, Elliott P, Caulfield MJ. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nat Genet. 2018; 50(10):1412-1425

Tzoulaki I, Iliou A, Mikros E, Elliott P. An Overview of Metabolic Phenotyping in Blood Pressure Research. Curr Hypertens Rep. 2018; 20(9):78

Climaco Pinto R, Karaman I, Fussel J, Evangelou E, Kelly F, Elliott P, Tzoulaki I. Applications of Metabolic Phenotyping in Epidemiology. The Handbook of Metabolic Phenotyping. Edited by John C Lindon, JK Nicholson & E Holmes. Elsevier, USA, 2018. 

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