A plasma proteomic and metabolomic map of diet and food preferences in UK Biobank volunteers

We will explore the proteomic and metabolomic biomarkers data gathered on UK Biobank volunteers and research their relationship to food preference and health.

Start date
1 October 2022
Duration
3 years
Application deadline
Funding source
University of Surrey
Funding information

UK student fees and stipend are covered. Stipend offered is £15,609.

About

UK Biobank has measured the concentration of hundreds of metabolites and thousands of proteins in the same UK Biobank participants’ samples. In many cases there is also data on food preferences as defined in responses to a UK Biobank questionnaire. Furthermore, at the time of taking blood samples from UK Biobank participants key features of their health status were recorded (e.g. inflammatory disease, type 2 diabetes, cardiovascular disease). This extremely rich dataset offers the opportunity for a unique analysis of blood plasma metabolite and proteome relationship to health status, diet and food preferences using cutting edge informatics and artificial intelligence approaches.

Peripheral blood offers major opportunities to identify and quantify biomarkers of wellness and disease. We and others have shown that the plasma proteome and metabolome changes with respect to diet (e.g. in response to bariatric surgery). UK Biobank has measured the concentration of hundreds of metabolites and thousands of proteins in the same UK Biobank participants’ samples. In many cases there is also data on food preferences as defined in responses to a UK Biobank questionnaire. Furthermore, at the time of taking blood samples from UK Biobank participants key features of their health status were recorded (e.g. inflammatory disease, type 2 diabetes, cardiovascular disease). This extremely rich dataset offers the opportunity for a unique analysis of blood plasma metabolite and proteome relationship to health status, diet and food preferences. There are over 140 food preference questionnaire answers, hundreds of metabolites measured and thousands of proteins measured. In this project we will use advanced data analysis and artificial intelligence approaches to identify relationships between concentrations of specific groups of metabolites and/or proteins and food preferences. We will further, using unsupervised machine learning, identify clusters or endophenotypes of food preferences, and correlate these with molecular biomarkers.

These signatures will then be further correlated with health outcomes and disease comorbidities. This will enable future studies on biomarkers for diseases and risk of diseases to take into account diet, nutrition and health on proteins and metabolites of potential value in clinical or wellness decisions.

The student will be taught advanced informatic, machine learning and artificial intelligence techniques in order to undertake the work described above.

Related links
Biobank online resources 'Redefining meaningful age groups in the context of disease' article 'The normal range: it is not normal and it is not a range' article
Additional notes

We will be using UK Biobank data that can be accessed remotely. The student will be based on the University of Surrey campus but can work remotely for much of their time. 

Eligibility criteria

This project would be suitable for students with an upper second class honours degree, for example in biological sciences or computer sciences, or the equivalent, which can include relevant work experience.

This studentship is available for UK and international students.

IELTS requirements: The standard requirement is for a score of 6.5 or above (or equivalent) with 6.0 in each individual category.

How to apply

If you think you are interested in the post and want an informal discussion then please submit a curriculum vitae and short letter to a.whetton@surrey.ac.uk.

Formal applications should be submitted via the Biosciences and Medicine PhD programme page on the "Apply" tab. Please clearly state the studentship title and supervisor on your application.


Application deadline

Contact details

Professor Anthony Whetton

Email: a.whetton@surrey.ac.uk

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