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EASTBIO - Defining lipidomic biomarkers of the interactions between Western diet and liver health using mass spectrometry imaging


Project Description

Lifestyle factors influence healthy ageing. Dietary choices modify susceptibility to many diseases. The low-fat Mediterranean diet is anti-oxidant and believed beneficial for health, whereas high-fat “Western diet” is associated with negative health outcomes. Body mass index is increasing worldwide, linked to increased risk of many diseases, including diabetes and non-alcoholic fatty liver disease, but individual risk is not uniform. When challenged with a fatty diet, the body responds by adjusting adipose depot volume and by storing fat “ectopically” e.g. in liver. This is a healthy, adaptive response that is initially not harmful. However, beyond a certain level and in some individuals, metabolic flexibility is exceeded and too much ectopic fat triggers progressive liver fibrosis, cirrhosis and potentially hepatocellular carcinoma. Biomarkers are needed define processes differentiating healthy vs unhealthy dietary adaptation in the liver to help improve the healthspan of at-risk individuals.
Metabolomics provides a fingerprint of personal biochemical status; lipidomics is a subfield, categorising endogenous bioactive lipids regulating metabolism and inflammation. Lipidomics is most commonly conducted in blood, easy to sample and useful for health screening. However, the circulating lipidome may not reflect tissue levels. When liver health declines, zonal changes occur with healthy and at-risk tissue co-existing side-by-side. Therefore, the hepatic lipidomic signature must be described spatially. This studentship will develop mass spectrometry imaging (MSI) to spatially profile lipids in liver and define how they respond to diet. In particular, excessive conversion of lysophosphatidyl cholines to their acidic metabolites by the enzyme autotaxin will be studied in detail.
Hypothesis
Diets varying in fat content differentially affect the hepatic lipidome. The lipidomic signature revealed by MSI will identify pathways to assess liver health and disease and identify markers amenable to therapeutic modification either by lifestyle or drugs.
Project Plan
Initially, the student will establish MSI to sample lipids from liver sections of mouse and human. LC-MS/MS will also be deployed to measure key lipids in plasma. The profile of lipids will be described and species identified through alignment with lipidomic databases e.g. Lipidmaps.
Next, we will study the hepatic lipidome of mouse models representative of healthy animals and study the effect of an obesogenic diet by varying the fat content. Image analysis methods for co-localising histological and lipidomic features will be developed, aiming to develop predictive models to identify regions at risk. The changes in the lipidome with the duration of diet will be compared and correlated with stages of disease (healthy versus steatotic/steatohepatitic/fibrotic liver disease) to stratify biomarkers.
Findings in mouse models will be translated to human liver samples from the NHS Lothian BioResource.
Training
The student will receive interdisciplinary training in a broad range of methods including: a) in vivo and in vitro studies using liver tissue from animal models and humans b) lipidomics by bioanalytical MS c) multi-variate statistical analysis of lipidomic datasets, involving interfacing with online databases (d) co-registration and image analysis of histological features. Studies will be conducted in well-funded laboratories within the Queen’s Medical Research Institute which are fully equipped for the proposed experiments.

Funding Notes

Download application and reference forms via: View Website

Applications: Completed application form along with your supporting documents should be sent to

References: Please send the reference request form to two referees. Completed forms for this project should be returned to [email protected],ac.uk ny the closing date: 5th January 2020.

It is your responsibility to ensure that references are provided by the specified deadline.

References

Khan, Andrew (2019) MSI of lipids, Current and emerging technologies in lipidomics, Royal Society of Chemistry, London, In Press.

Iredale, Pellicoro, Fallowfield (2017) Liver Fibrosis: Understanding the dynamics of bidirectional wound repair to inform the design of markers and therapies. Dig Dis 2017;35:310-313.

Cobice et al (2017) Quantification of 11β-HSD1 kinetics and pharmacodynamic effects of inhibitors in brain using MSI and stable-isotope tracers in mice. Biochem Pharm. 148:88-99.

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